eLife Assessment

This important paper uses elegant models, including genetic knock outs, to demonstrate that FABP4 contributes to lipid accumulation in tumor-associated macrophages, which seems to increase breast cancer migration. While the work is of high interest, the strength of the evidence relating to some of the conclusions is incomplete and the paper would benefit from some refinement. The work will be of interest to those researchers trying to link metabolism, the immune system, and cancer.

Reviewer #1 (Public review):

Summary:

In the manuscript "FABP4-mediated lipid accumulation and lipolysis in tumor-associated macrophages promote breast cancer metastasis", Yorek, et al. provide a novel mechanism explaining how unsaturated fatty acids induce macrophages to accumulate lipid droplets, which when contained in tumor-associated macrophages (TAMs) are associated with increased metastasis in breast cancer. The authors conclude that unsaturated fatty acids are transported into macrophages by the chaperone FABP4 where they induce C/EBPalpha expression and transcriptional activity resulting in upregulation of enzymes involved in triacylglycerol and lipid droplet biosynthesis. The resulting accumulation of lipid droplets in macrophages creates a store of fatty acids that can subsequently be released through FABP4-dependent lipolysis and thereby stimulate the migration of nearby breast cancer cells. While generally well-written and developed, there are a few concerns about the rigor of experimental evidence that supports some conclusions, including the existence of a FABP4-C/EBPalpha pathway. Overall, the mechanism identified is a valuable contribution to our understanding of how tumor-associated macrophages may influenced by available metabolites to promote the aggressiveness of certain cancers. FABP4 has the potential to be used as a novel biomarker of macrophage-induced cancer aggressiveness and/or a therapeutic target to prevent metastasis.

Strengths:

(1) The study is logically organized and provides extensive evidence in support of the overall model proposed.

(2) Multiple complementary techniques are used to identify and quantify lipid droplets.

(3) Primary macrophages and macrophage cell lines are used and provide consistent data.

(4) Knock-down and knock-out cells are used to assess the contributions of FABP4 and C/EBPalpha to gene expression.

(5) Public gene expression data (GEO, TCGA) is used effectively throughout.

Weaknesses:

(1) After Figure 1, a single saturated (palmitic acid; PA) and a single unsaturated (linoleic acid; LA) fatty acid are used for the remaining studies, bringing into question whether effects are in fact the result of a difference in saturation vs. other potential differences.

(2) While primary macrophages are used in several mechanistic studies, tumor-associated macrophages (TAMs) are not used. Rather, correlative evidence is provided to connect mechanistic studies in macrophage cell lines and primary macrophages to TAMs.

(3) C/EBPalpha and FABP4 clearly regulate LA-induced changes in gene expression. However, whether these two key proteins act in parallel or as a pathway is not resolved by presented data.

(4) It is very interesting that FABP4 regulates both lipid droplet formation and lipolysis, yet is unclear if the regulation of lipolysis is direct or if the accumulation of lipid droplets - likely plus some other signal(s) - induces upregulation of lipolysis genes.

(5) In several places increased expression of genes coding for enzymes with known functions in lipid biology is conflated with an increase in the lipid biology process the enzymes mediate. Additional evidence would be needed to show these processes are in fact increased in a manner dependent on increased enzyme expression.

Reviewer #2 (Public review):

The manuscript by Yorek et al explores the role of fatty acids, particularly unsaturated fatty acids, in lipid droplet accumulation and lipolysis in tumor-associated macrophages (TAMs). Using flow cytometry, immunofluorescent imaging, and TEM, the authors observed that unsaturated fatty acids, such as linoleic acids (LA), tend to induce lipid droplet accumulation in the ER of macrophages, but not in the lysosomes. This phenomenon led them to examine the key enzymes involved in lipid droplet/TAG biosynthesis, where they found incubation of LA upregulates GPAT/DGAT and C/EBPα. In vitro studies, data from public databases, single-cell RNA sequencing of splenic macrophages, and more show that FABP4 emerges as an important mediator for C/EBPα activation. This is further confirmed by FABP4-knockout macrophages, where lipid accumulation and utilization of unsaturated fatty acids were compromised in macrophages through inhibition of LA-induced lipolysis. Using the co-culture system and immunohistochemical analysis, they found that the high FABP4 expression in TAMs, which are observed in metastatic breast cancer tissue, promotes breast cancer cell migration in vitro.

This study is important since the impact of tumor microenvironment is crucial for the development of breast cancer. The individual experiments are well-designed and structured. However, the logic connecting to the next step is a bit difficult to follow, especially when combined with incomplete statistical analysis in some figures, making the conclusion less convincing. For instance, the comparison of macrophage FABP4 expression between breast cancer patients with or without metastasis illustrates the importance of FABP4 expression in metastasis, yet there is no examination of the expression of other key enzymes in the lipolysis or lipid biosynthesis pathway nor there is any correlation with parameters that would reflect patients' consumption of fatty acids. Similarly, an in vivo study comparing FABP4 knockout mice with or without unsaturated fatty acids would yield more compelling evidence. The statistical analysis was largely focused on the sets of unsaturated fatty acids when data from both types of fatty acids were present. In some cases, significant changes are observed in the sets of saturated fat, but there is no explanation of why only the data from unsaturated fats are important for investigation.

Overall, there is solid evidence for the importance of FABP4 expression in TAMs on metastatic breast cancer as well as lipid accumulation by LA in the ER of macrophages. A stronger rationale for the exclusive contribution of unsaturated fatty acids to the utilization of TAMs in breast cancer and a more detailed description and statistical analysis of data will strengthen the findings and resulting claims.

Reviewer #3 (Public review):

Summary:

Regulated metabolism has only recently been recognized as a key component of cancer biology, and even more recently recognized as a significant modulator of the tumor microenvironment (TME). TAMs in the TME play a major role in supporting cancer cell survival and growth/spread, as well as generating an immunosuppressive ME to suppress anti-tumor immunity. Specific regulation of lipid metabolism in this context, in particular how lipids are stored and subsequently mobilized for metabolism, is largely unexplored - especially in the immunological components of the TME.

In this manuscript, the authors build on their previous observations that the fatty acid-binding protein FABP4 plays an important role in macrophage function and that FABP4 expression in tumor associated macrophages (TAM) promotes breast cancer progression. They demonstrate:

(1) Unlike saturated fatty acids (FA), unsaturated FA promotes lipid droplet (LD) accumulation in murine macrophages. LD is the primary intracellular storage depot for FA.

(2) Unsaturated FA activates the FABP4-C/EBPalpha axis to upregulate transcription of the enzymes involved in the synthesis of neutral triacylglycerol (TAG) is an essential step in the formation of the neutral lipid core of LD. It should be noted that the authors speculate that UFA-activated FABP4 translocates to the nucleus to activate PPARgamma, which is known to induce C/EBPalpha expression, but do not directly test the involvement of PPARgamma in this axis.

(3) FABP4 deficiency compromises unsaturated FA-mediated lipid accumulation and utilization in murine macrophages.

(4) FABP4-mediated lipid metabolism in macrophages (TAMS) contributes to breast cancer metastasis, in in-vitro of tumor migration induced by murine macrophages and in correlative studies from human patient breast cancer biopsies.

From these studies, the manuscript concludes that FABP4 plays a pivotal role in mediating lipid droplet formation and lipolysis in TAM, which provides lipids to breast cancer cells that contribute to their growth and metastasis.

These are significant findings, as they provide new insight into the mechanistic regulation of TAM biology via regulation of lipid metabolism, as well as define new biomarkers and potential novel therapeutic targets.

The findings are strong in the studies that mechanistically define the role of FAB4 in lipid accumulation and utilization in murine macrophages. However, evidence is less compelling regarding TAM biology and human breast cancer in 3 main areas:

First, while there is clear in vitro evidence that co-cultured murine macrophages genetically deficient in FABP4 (or their conditioned media) do not enhance breast cancer cell motility and invasion, these macrophages are not bonafide TAM - which may have different biology. The use of actual TAM in these experiments would be more compelling. Perhaps more importantly, there is no in vivo data in tumor-bearing mice that macrophage deficiency of FABP4 affects tumor growth or metastasis - which are doable experiments given the availability of the FABP4 KO mice.

Second, no data is presented that the mechanisms/biology that are elegantly demonstrated in the murine macrophages also occur in human macrophages - which would be foundational to translating these findings into human breast cancer. It seems like straightforward in vitro studies in human monocytes/macrophages could be done to recapitulate the main characteristics seen in the murine macrophages.

Third, while the data from the human breast cancer specimens is very intriguing, it is difficult to ascertain how accurate IHC is in determining that the CD163+ cells (TAM) are in fact the same cells expressing FABP4 - which is the central premise of these studies. Demonstrating that IHC has the resolution to do this would be important. Additionally, the in vitro characterization of FABP4 expression in human macrophages would also add strength to these findings.

In summary, the strengths of this manuscript are the significance of metabolic regulation of the immune tumor microenvironment (TME), and the careful mechanistic delineation of FABP4 involvement in mediating lipid droplet formation and lipolysis in murine macrophages. The weaknesses of the work are the lack of direct experimental evidence that human macrophages behave in the same way as murine macrophages, the incomplete characterization of the role of FABP4 expression in TAM in modulating tumor growth in vivo (in murine models), and whether it can be definitively determined that FABP4 is being primarily expressed in the CD163+ macrophages in human breast cancer samples.

Strengths:

(1) Regulated metabolism has only recently been recognized as a key component of cancer biology, and even more recently recognized as a significant modulator of the tumor microenvironment (TME). TAMs in the TME play a major role in supporting cancer cell survival and growth/spread, as well as generating an immunosuppressive ME to suppress anti-tumor immunity.

(2) Regulation of lipid metabolism in this context is largely unexplored, especially in the immunological components of the TME.

(3) The work builds on the authors' previous work on the role of FABP4 plays an important role in macrophage function including FABP4 expression in TAM promotes breast cancer progression (Hao et al, Cancer Res 2018). This paper identified FABP4-expressing macrophages as being pro-tumorigenic via upregulation of IL-6STAT3 signaling.

(4) The careful and thorough mechanistic delineation of FABP4 involvement in mediating lipid droplet formation and lipolysis in murine macrophages.

(5) The intriguing observations that FABP4-mediated lipid metabolism in macrophages contributes to breast cancer metastasis, in in vitro of tumor migration induced by murine macrophages and in correlative studies from human patient breast cancer biopsies that CD163+ cell numbers (putatively TAM) and FABP4 expression was associated with increased metastatic disease and poor overall survival.

(6) Identification of FABP4 both a prognostic biomarker and a potential therapeutic target to modulate the pro-tumor immune TME.

Weaknesses:

(1) While the authors speculate that UFA-activated FABP4 translocates to the nucleus to activate PPARgamma, which is known to induce C/EBPalpha expression, they do not directly test involvement of PPARgamma in this axis.

(2) While there is clear in vitro evidence that co-cultured murine macrophages genetically deficient in FABP4 (or their conditioned media) do not enhance breast cancer cell motility and invasion, these macrophages are not bonafide TAM - which may have different biology. Use of actual TAM in these experiments would be more compelling. Perhaps more importantly, there is no in vivo data in tumor bearing mice that macrophage-deficiency of FABP4 affects tumor growth or metastasis.

(3) Related to this, the authors find FABP4 in the media and propose that macrophage secreted FABP4 is mediating the tumor migration - but don't do antibody neutralizing experiments to directly demonstrate this.

(4) No data is presented that the mechanisms/biology that are elegantly demonstrated in the murine macrophages also occurs in human macrophages - which would be foundational to translating these findings into human breast cancer.

(5) While the data from the human breast cancer specimens is very intriguing, it is difficult to ascertain how accurate IHC is in determining that the CD163+ cells (TAM) are in fact the same cells expressing FABP4 - which is central premise of these studies. Demonstration that IHC has the resolution to do this would be important. Additionally, the in vitro characterization of FABP4 expression in human macrophages would also add strength to these findings.

Author response:

Reviewer #1:

(1) After Figure 1, a single saturated (palmitic acid; PA) and a single unsaturated (linoleic acid; LA) fatty acid are used for the remaining studies, bringing into question whether effects are in fact the result of a difference in saturation vs. other potential differences.

PA, SA, OA and LA are the most common FA species in humans (Figure 1A in manuscript). Among them, PA predominantly represents saturated FAs while LA is the main unsaturated FAs, respectively. Of note, although both SA and OA were included in our studies, their effects were comparable to those of PA and LA, respectively. Due to space constraints, the data of SA and OA are not presented in the figures.  

(2) While primary macrophages are used in several mechanistic studies, tumor-associated macrophages (TAMs) are not used. Rather, correlative evidence is provided to connect mechanistic studies in macrophage cell lines and primary macrophages to TAMs.

The roe of FABP4 in TAMs has been demonstrated in our previous studies using in vivo animal models1. Therefore, we did not include TAM-specific data in the current study.

(3) CEBPA and FABP4 clearly regulate LA-induced changes in gene expression. However, whether these two key proteins act in parallel or as a pathway is not resolved by presented data.

Multiple lines of evidence in our studies suggest that FABP4 and CEBPA act as a pathway in LA-induced changes: 1) FABP4-negative macrophages exhibit reduced expression of CEBPA in single cell sequencing data; 2) FABP4 KO macrophages exhibited reduced CEBPA expression; 3) LA-induced CEBPA expression in macrophages was compromised when FABP4 was absent.

(4) It is very interesting that FABP4 regulates both lipid droplet formation and lipolysis, yet is unclear if the regulation of lipolysis is direct or if the accumulation of lipid droplets - likely plus some other signal(s) - induces upregulation of lipolysis genes.

Yes, it is likely that tumor cells induce lipolysis signals. Multiple studies have shown that various tumor types stimulate lipolysis to support their growth and progression2-4.  In this process, lipid-loaded macrophages have emerged as a promising therapeutic target in cancer5, 6. Consistent with findings that lipolysis is essential for tumor-promoting M2 alternative macrophage activation7, our data using FABP4 WT and KO macrophages demonstrate that FABP4 plays a critical role in LA-induced lipid accumulation and lipolysis for tumor metastasis. 

(5) In several places increased expression of genes coding for enzymes with known functions in lipid biology is conflated with an increase in the lipid biology process the enzymes mediate. Additional evidence would be needed to show these processes are in fact increased in a manner dependent on increased enzyme expression.

We fully agree with the reviewer that increased gene expression does not necessarily equate to increased activity. The key finding of this study is that FABP4 plays a pivotal role in linoleic acid (LA)-mediated lipid accumulation and lipolysis in macrophages that promote tumor metastasis. Numerous lipid metabolism-related genes, including FABP4, CEBPA, GPATs, DGATs, and HSL, are involved in this process. While it was not feasible to verify the activity of all these genes, we confirmed the functional roles of key genes like FABP4 and CEBPA through various functional assays, such as gene silencing, knockout cell lines, lipid droplet formation, and tumor migration assays. Supported by established lipid metabolism pathways, our data provide compelling evidence that FABP4 functions as a crucial lipid messenger, facilitating unsaturated fatty acid-driven lipid accumulation and lipolysis in tumor-associated macrophages (TAMs), thus promoting breast cancer metastasis.   

Reviewer #2:

Overall, there is solid evidence for the importance of FABP4 expression in TAMs on metastatic breast cancer as well as lipid accumulation by LA in the ER of macrophages. A stronger rationale for the exclusive contribution of unsaturated fatty acids to the utilization of TAMs in breast cancer and a more detailed description and statistical analysis of data will strengthen the findings and resulting claims.

We greatly appreciated the positive comments from Reviewer #2. In our study, we evaluated the effects of both saturated and unsaturated fatty acids (FA) on lipid metabolism in macrophages.  Our results showed that unsaturated FAs exhibited a preference for lipid accumulation in macrophages compared to saturated FAs. Further analysis revealed that unsaturated LA, but not saturated PA, induced FABP4 nuclear translocation and CEBPA activation, driving the TAG synthesis pathway. For in vitro experiments, statistical analyses were performed using a two-tailed, unpaired student t-test, two-way ANOVA followed by Bonferroni’s multiple comparison test, with GraphPad Prism 9. For experiments analyzing associations of FABP4, TAMs and other factors in breast cancer patients, the Kruskal-Wallis test was applied to compare differences across levels of categorical predictor variable. Additionally, multiple linear regression models were used to examine the association between the predictor variables and outcomes, with log transformation and Box Cox transformation applied to meet the normality assumptions of the model. It is worth noting that in some experiments, only significant differences were observed in groups treated with unsaturated fatty acids. Non-significant results from groups treated with saturated fatty acids were not included in the figures.

Reviewer #3

(1) While the authors speculate that UFA-activated FABP4 translocates to the nucleus to activate PPARgamma, which is known to induce C/EBPalpha expression, they do not directly test involvement of PPARgamma in this axis.

Yes, LA induced FABP4 nuclear translocation and activation of PPARgamma in macrophages (see Figure below). Since these findings have been reported in multiple other studies 8, 9, we did not include the data in the current manuscript.

Author response image 1.

LA induced PPARg expression in macrophages. Bone-marrow derived macrophages were treated with 400μM saturated FA (SFA), unsaturated FA (UFA) or BSA control for 6 hours. PPARg expression was measured by qPCR (***p<0.001).

(2) While there is clear in vitro evidence that co-cultured murine macrophages genetically deficient in FABP4 (or their conditioned media) do not enhance breast cancer cell motility and invasion, these macrophages are not bonafide TAM - which may have different biology. Use of actual TAM in these experiments would be more compelling. Perhaps more importantly, there is no in vivo data in tumor bearing mice that macrophage-deficiency of FABP4 affects tumor growth or metastasis.

In our previous studies, we have shown that macrophage-deficiency of FABP4 reduced tumor growth and metastasis in vivo in mouse models1.

(3) Related to this, the authors find FABP4 in the media and propose that macrophage secreted FABP4 is mediating the tumor migration - but don't do antibody neutralizing experiments to directly demonstrate this.

Yes, we have recently published a paper of developing anti-FABP4 antibody for treatment of breast cancer in moue models10.

(4) No data is presented that the mechanisms/biology that are elegantly demonstrated in the murine macrophages also occurs in human macrophages - which would be foundational to translating these findings into human breast cancer.

Thanks for the excellent suggestions. Since this manuscript primarily focuses on mechanistic studies using mouse models, we plan to apply these findings in our future human studies. 

(5) While the data from the human breast cancer specimens is very intriguing, it is difficult to ascertain how accurate IHC is in determining that the CD163+ cells (TAM) are in fact the same cells expressing FABP4 - which is central premise of these studies. Demonstration that IHC has the resolution to do this would be important. Additionally, the in vitro characterization of FABP4 expression in human macrophages would also add strength to these findings.

The expression of FABP4 in CD163+ TAM observed through IHC is consistent with our previous findings, where we confirmed FABP4 expression in CD163+ TAMs using confocal microscopy. Emerging evidence further supports the pro-tumor role of FABP4 expression in human macrophages across various types of obesity-associated cancers11-13. 

References

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(4) Balaban S, Shearer RF, Lee LS, van Geldermalsen M, Schreuder M, Shtein HC, Cairns R, Thomas KC, Fazakerley DJ, Grewal T, Holst J, Saunders DN, Hoy AJ. Adipocyte lipolysis links obesity to breast cancer growth: adipocyte-derived fatty acids drive breast cancer cell proliferation and migration. Cancer Metab. 2017;5:1. Epub 20170113. doi: 10.1186/s40170-016-0163-7. PubMed PMID: 28101337; PMCID: PMC5237166.

(5) Masetti M, Carriero R, Portale F, Marelli G, Morina N, Pandini M, Iovino M, Partini B, Erreni M, Ponzetta A, Magrini E, Colombo P, Elefante G, Colombo FS, den Haan JMM, Peano C, Cibella J, Termanini A, Kunderfranco P, Brummelman J, Chung MWH, Lazzeri M, Hurle R, Casale P, Lugli E, DePinho RA, Mukhopadhyay S, Gordon S, Di Mitri D. Lipid-loaded tumor-associated macrophages sustain tumor growth and invasiveness in prostate cancer. J Exp Med. 2022;219(2). Epub 20211217. doi: 10.1084/jem.20210564. PubMed PMID: 34919143; PMCID: PMC8932635.

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eLife Assessment

This manuscript describes a valuable study of a new lipid-mediated regulation mechanism of adenylyl cyclases. The biochemical evidence provided is convincing, but more evidence for regulation by lipids under natural cellular processes would be interesting. This manuscript will be of interest to all scientists working on lipid regulation and adenylyl cyclases.

Reviewer #1 (Public review):

Summary:

The authors show that the Gαs-stimulated activity of human membrane adenylyl cyclases (mAC) can be enhanced or inhibited by certain unsaturated fatty acids (FA) in an isoform-specific fashion. Thus, with IC50s in the 10-20 micromolar range, oleic acid affects 3-fold stimulation of membrane-preparations of mAC isoform 3 (mAC3) but it does not act on mAC5. Enhanced Gαs-stimulated activities of isoforms 2, 7, and 9, while mAC1 was slightly attenuated, but isoforms 4, 5, 6, and 8 were unaffected. Certain other unsaturated octadecanoic FAs act similarly. FA effects were not observed in AC catalytic domain constructs in which TM domains are not present. Oleic acid also enhances the AC activity of isoproterenol-stimulated HEK293 cells stably transfected with mAC3, although with lower efficacy but much higher potency. Gαs-stimulated mAC1 and 4 cyclase activity were significantly attenuated in the 20-40 micromolar by arachidonic acid, with similar effects in transfected HEK cells, again with higher potency but lower efficacy. While activity mAC5 was not affected by unsaturated FAs, neutral anandamide attenuated Gαs-stimulation of mAC5 and 6 by about 50%. In HEK cells, inhibition by anandamide is low in potency and efficacy. To demonstrate isoform specificity, the authors were able to show that membrane preparations of a domain-swapped AC bearing the catalytic domains of mAC3 and the TM regions of mAC5 are unaffected by oleic acid but inhibited by anandamide. To verify in vivo activity, in mouse brain cortical membranes 20 μM oleic acid enhanced Gαs-stimulated cAMP formation 1.5-fold with an EC50 in the low micromolar range.

Strengths:

(1) A convincing demonstration that certain unsaturated FAs are capable of regulating membrane adenylyl cyclases in an isoform-specific manner, and the demonstration that these act at the AC transmembrane domains.

(2) Confirmation of activity in HEK293 cell models and towards endogenous AC activity in mouse cortical membranes.

(3) Opens up a new direction of research to investigate the physiological significance of FA regulation of mACs and investigate their mechanisms as tonic or regulated enhancers or inhibitors of catalytic activity.

(4) Suggests a novel scheme for the classification of mAC isoforms.

Weaknesses:

(1) Important methodological details regarding the treatment of mAC membrane preps with fatty acids are missing.

(2) It is not evident that fatty acid regulators can be considered as "signaling molecules" since it is not clear (at least to this reviewer) how concentrations of free fatty acids in plasma or endocytic membranes are hormonally or otherwise regulated.

Reviewer #2 (Public review):

Summary:

The authors extend their earlier findings with bacterial adenylyl cyclases to mammalian enzymes. They show that certain aliphatic lipids activate adenylyl cyclases in the absence of stimulatory G proteins and that lipids can modulate activation by G proteins. Adding lipids to cells expressing specific isoforms of adenylyl cyclases could regulate cAMP production, suggesting that adenylyl cyclases could serve as 'receptors'.

Strengths:

This is the first report of lipids regulating mammalian adenylyl cyclases directly. The evidence is based on biochemical assays with purified proteins, or in cells expressing specific isoforms of adenylyl cyclases.

Weaknesses:

It is not clear if the concentrations of lipids used in assays are physiologically relevant. Nor is there evidence to show that the specific lipids that activate or inhibit adenylyl cyclases are present at the concentrations required in cell membranes. Nor is there any evidence to indicate that this method of regulation is seen in cells under relevant stimuli.

Reviewer #3 (Public review):

Summary:

Landau et al. have submitted a manuscript describing for the first time that mammalian adenylyl cyclases can serve as membrane receptors. They have also identified the respective endogenouse ligands which act via AC membrane linkers to modify and control Gs-stimulated AC activity either towards enhancement or inhibition of ACs which is family and ligand-specific. Overall, they have used classical assays such as adenylyl cyclase and cAMP accumulation assays combined with molecular cloning and mutagenesis to provide exceptionally strong biochemical evidence for the mechanism of the involved pathway regulation.

Strengths:

The authors have gone the whole long classical way from having a hypothesis that ACs could be receptors to a series of MS studies aimed at ligand indentification, to functional studies of how these candidate substances affect the activity of various AC families in intact cells. They have used a large array of techniques with a paper having clear conceptual story and several strong lines of evidence.

Weaknesses:

(1) At the beginning of the results section, the authors say "We have expected lipids as ligands". It is not quite clear why these could not have been other substances. It is because they were expected to bind in the lipophilic membrane anchors? Various lipophilic and hydrophilic ligands are known for GPCR which also have transmembrane domains. Maybe 1-2 additional sentences could be helpful here.

(2) In stably transfected HEK cells expressing mAC3 or mAC5, they have used only one dose of isoproterenol (2.5 uM) for submaximal AC activation. The reference 28 provided here (PMID: 33208818) did not specifically look at Iso and endogenous beta2 adrenergic receptors expressed in HEK cells. As far as I remember from the old pharmacological literature, this concentration is indeed submaximal in receptor binding assays but regarding AC activity and cAMP generation (which happen after signal amplification with a so-called receptor reserve), lower Iso amounts would be submaximal. When we measure cAMP, these are rather 10 to 100 nM but no more than 1 uM at which concentration response dependencies usually saturate. Have the authors tried lower Iso concentrations to prestimulate intracellular cAMP formation? I am asking this because, with lower Iso prestimulation, the subsequent stimulatory effects of AC ligands could be even greater.

(3) The authors refer to HEK cell models as "in vivo". I agree that these are intact cells and an important model to start with. It would be very nice to see the effects of the new ligands in other physiologically relevant types of cells, and how they modulate cAMP production under even more physiological conditions. Probably, this is a topic for follow-up studies.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

The authors have achieved their aims to a very high degree, their results do nicely support their conclusions. There is only one point (various classical GPCR concentrations, please see above) that would be beneficial to address.

Without any doubt, this is a groundbreaking study that will have profound implications in the field for the next years/decades. Since it is now clear that mammalian adenylyl cyclases are receptors for aliphatic fatty acids and anandamide, this will change our view on the whole signaling pathway and initiate many new studies looking at the biological function and pathophysiological implications of this mechanism. The manuscript is outstanding.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors show that the Gαs-stimulated activity of human membrane adenylyl cyclases (mAC) can be enhanced or inhibited by certain unsaturated fatty acids (FA) in an isoform-specific fashion. Thus, with IC50s in the 10-20 micromolar range, oleic acid affects 3-fold stimulation of membrane-preparations of mAC isoform 3 (mAC3) but it does not act on mAC5. Enhanced Gαs-stimulated activities of isoforms 2, 7, and 9, while mAC1 was slightly attenuated, but isoforms 4, 5, 6, and 8 were unaffected. Certain other unsaturated octadecanoic FAs act similarly. FA effects were not observed in AC catalytic domain constructs in which TM domains are not present. Oleic acid also enhances the AC activity of isoproterenol-stimulated HEK293 cells stably transfected with mAC3, although with lower efficacy but much higher potency. Gαs-stimulated mAC1 and 4 cyclase activity were significantly attenuated in the 20-40 micromolar by arachidonic acid, with similar effects in transfected HEK cells, again with higher potency but lower efficacy. While activity mAC5 was not affected by unsaturated FAs, neutral anandamide attenuated Gαs-stimulation of mAC5 and 6 by about 50%. In HEK cells, inhibition by anandamide is low in potency and efficacy. To demonstrate isoform specificity, the authors were able to show that membrane preparations of a domain-swapped AC bearing the catalytic domains of mAC3 and the TM regions of mAC5 are unaffected by oleic acid but inhibited by anandamide. To verify in vivo activity, in mouse brain cortical membranes 20 μM oleic acid enhanced Gαs-stimulated cAMP formation 1.5-fold with an EC50 in the low micromolar range.

Strengths:

(1) A convincing demonstration that certain unsaturated FAs are capable of regulating membrane adenylyl cyclases in an isoform-specific manner, and the demonstration that these act at the AC transmembrane domains.

(2) Confirmation of activity in HEK293 cell models and towards endogenous AC activity in mouse cortical membranes.

(3) Opens up a new direction of research to investigate the physiological significance of FA regulation of mACs and investigate their mechanisms as tonic or regulated enhancers or inhibitors of catalytic activity.

(4) Suggests a novel scheme for the classification of mAC isoforms.

Weaknesses:

(1) Important methodological details regarding the treatment of mAC membrane preps with fatty acids are missing.

We will address this issue in more detail.

(2) It is not evident that fatty acid regulators can be considered as "signaling molecules" since it is not clear (at least to this reviewer) how concentrations of free fatty acids in plasma or endocytic membranes are hormonally or otherwise regulated.

Although this question is not the subject of this ms., we will address this question in more detail in the discussion of the revision.

Reviewer #2 (Public review):

Summary:

The authors extend their earlier findings with bacterial adenylyl cyclases to mammalian enzymes. They show that certain aliphatic lipids activate adenylyl cyclases in the absence of stimulatory G proteins and that lipids can modulate activation by G proteins. Adding lipids to cells expressing specific isoforms of adenylyl cyclases could regulate cAMP production, suggesting that adenylyl cyclases could serve as 'receptors'.

Strengths:

This is the first report of lipids regulating mammalian adenylyl cyclases directly. The evidence is based on biochemical assays with purified proteins, or in cells expressing specific isoforms of adenylyl cyclases.

Weaknesses:

It is not clear if the concentrations of lipids used in assays are physiologically relevant. Nor is there evidence to show that the specific lipids that activate or inhibit adenylyl cyclases are present at the concentrations required in cell membranes. Nor is there any evidence to indicate that this method of regulation is seen in cells under relevant stimuli.

Although this question is not the subject of this manuscript, we will address this question in more detail in the discussion of the revision.

Reviewer #3 (Public review):

Summary:

Landau et al. have submitted a manuscript describing for the first time that mammalian adenylyl cyclases can serve as membrane receptors. They have also identified the respective endogenouse ligands which act via AC membrane linkers to modify and control Gs-stimulated AC activity either towards enhancement or inhibition of ACs which is family and ligand-specific. Overall, they have used classical assays such as adenylyl cyclase and cAMP accumulation assays combined with molecular cloning and mutagenesis to provide exceptionally strong biochemical evidence for the mechanism of the involved pathway regulation.

Strengths:

The authors have gone the whole long classical way from having a hypothesis that ACs could be receptors to a series of MS studies aimed at ligand indentification, to functional studies of how these candidate substances affect the activity of various AC families in intact cells. They have used a large array of techniques with a paper having clear conceptual story and several strong lines of evidence.

Weaknesses:

(1) At the beginning of the results section, the authors say "We have expected lipids as ligands". It is not quite clear why these could not have been other substances. It is because they were expected to bind in the lipophilic membrane anchors? Various lipophilic and hydrophilic ligands are known for GPCR which also have transmembrane domains. Maybe 1-2 additional sentences could be helpful here.

Will be done as suggested.

(2) In stably transfected HEK cells expressing mAC3 or mAC5, they have used only one dose of isoproterenol (2.5 uM) for submaximal AC activation. The reference 28 provided here (PMID: 33208818) did not specifically look at Iso and endogenous beta2 adrenergic receptors expressed in HEK cells. As far as I remember from the old pharmacological literature, this concentration is indeed submaximal in receptor binding assays but regarding AC activity and cAMP generation (which happen after signal amplification with a so-called receptor reserve), lower Iso amounts would be submaximal. When we measure cAMP, these are rather 10 to 100 nM but no more than 1 uM at which concentration response dependencies usually saturate. Have the authors tried lower Iso concentrations to prestimulate intracellular cAMP formation? I am asking this because, with lower Iso prestimulation, the subsequent stimulatory effects of AC ligands could be even greater.

The best way to address this issue is to establish a concentration-response curve for Iso-stimulated cAMP formation using the permanently transfected cells. We note that in the past isoproterenol concentrations used in biochemical or electrophysiological experiments differed substantially.

(3) The authors refer to HEK cell models as "in vivo". I agree that these are intact cells and an important model to start with. It would be very nice to see the effects of the new ligands in other physiologically relevant types of cells, and how they modulate cAMP production under even more physiological conditions. Probably, this is a topic for follow-up studies.

The last sentence is correct.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

The authors have achieved their aims to a very high degree, their results do nicely support their conclusions. There is only one point (various classical GPCR concentrations, please see above) that would be beneficial to address.

Without any doubt, this is a groundbreaking study that will have profound implications in the field for the next years/decades. Since it is now clear that mammalian adenylyl cyclases are receptors for aliphatic fatty acids and anandamide, this will change our view on the whole signaling pathway and initiate many new studies looking at the biological function and pathophysiological implications of this mechanism. The manuscript is outstanding.

eLife Assessment

This important study reports the transcriptomic and proteomic landscape of the oviducts at four different preimplantation periods during natural fertilization, pseudopregnancy, and superovulation. The data presented convincingly supported the conclusion in general, although more analyses would strengthen the conclusions drawn. This work will interest reproductive biologists and clinicians practicing reproductive medicine.

Reviewer #1 (Public review):

Summary:

The paper demonstrated through a comprehensive multi-omics study of the oviduct that the transcriptomic and proteomic landscape of the oviduct at 4 different preimplantation periods was dynamic during natural fertilization, pseudopregnancy, and superovulation using three independent cell/tissue isolation and analytical techniques. This work is very important for understanding oviductal biology and physiology. In addition, the authors have made all the results available in a web search format, which will maximize the public's access and foster and accelerate research in the field.

Strengths:

(1) The manuscript addresses an important and interesting question in the field of reproduction: how does the oviduct at different regions adapt to the sperm and embryos for facilitating fertilization and preimplantation embryo development and transport?

(2) Authors used cutting-edge techniques: Integrated multi-modal datasets followed by in vivo confirmation and machine learning prediction.

(3) RNA-seq, scRNA-seq, and proteomic results are immediately available to the scientific community in a web search format.

(4) Substantiated results indicate the source of inflammatory responses was the secretory cell population in the IU region when compared to other cell types; sperm modulate inflammatory responses in the oviduct; the oviduct displays immuno-dynamism.

Weaknesses:

(1) The rationale for using the superovulation model is not clear. The oviductal response to sperm and embryos can be studied by comparing mating with normal and vasectomized mice and comparing pregnancy vs pseudopregnancy (induced by mating with vasectomized males). Superovulation causes supraphysiological hormone levels and other confounding conditions.

(2) This study involves a very complex dataset with three different models at four time points. If possible, it would be very informative to generate a graphic abstract/summary of their major findings in oviductal responses in different models and time points

(3) The resolution of Figures 3A-3C in the submitted file was not high enough to assess the authors' conclusion.

(4) The authors need to double-check influential transcription factors identified by machine learning. Apparently, some of them (such as Anxa2, Ift88, Ccdc40) are not transcription factors at all.

Reviewer #2 (Public review):

The manuscript investigates oviductal responses to the presence of gametes and embryos using a multi-omics and machine learning-based approach. By applying RNA sequencing (RNA-seq), single-cell RNA sequencing (sc-RNA-seq), and proteomics, the authors identified distinct molecular signatures in different regions of the oviduct, proximal versus distal. The study revealed that sperm presence triggers an inflammatory response in the proximal oviduct, while embryo presence activates metabolic genes essential for providing nutrients to the developing embryos. Overall, this study offers valuable insights and is likely to be of great interest to reproductive biologists and researchers in the field of oviduct biology. However, further investigation into the impact of sperm on the immune cell population in the oviduct is necessary to strengthen the overall findings.

Author response:

eLife Assessment

This important study reports the transcriptomic and proteomic landscape of the oviducts at four different preimplantation periods during natural fertilization, pseudopregnancy, and superovulation. The data presented convincingly supported the conclusion in general, although more analyses would strengthen the conclusions drawn. This work will interest reproductive biologists and clinicians practicing reproductive medicine. 

We appreciate the concise summary and agree that additional experiments can reinforce the fidelity of predictions made by our robust bioinformatic characterization of the oviduct. Our robust bioinformatic model appears reproducible as similar pathway trends have been produced in all three datasets, lending confidence for future researchers to establish testable hypotheses more effectively.  

Reviewer #1 (Public review):

The paper demonstrated through a comprehensive multi-omics study of the oviduct that the transcriptomic and proteomic landscape of the oviduct at 4 different preimplantation periods was dynamic during natural fertilization, pseudopregnancy, and superovulation using three independent cell/tissue isolation and analytical techniques. This work is very important for understanding oviductal biology and physiology. In addition, the authors have made all the results available in a web search format, which will maximize the public's access and foster and accelerate research in the field.

Strengths:

(1) The manuscript addresses an important and interesting question in the field of reproduction:

how does the oviduct at different regions adapt to the sperm and embryos for facilitating fertilization and preimplantation embryo development and transport?

(2) Authors used cutting-edge techniques: Integrated multi-modal datasets followed by in vivo confirmation and machine learning prediction.

(3) RNA-seq, scRNA-seq, and proteomic results are immediately available to the scientific community in a web search format.

(4) Substantiated results indicate the source of inflammatory responses was the secretory cell population in the IU region when compared to other cell types; sperm modulate inflammatory responses in the oviduct; the oviduct displays immuno-dynamism.

We sincerely thank you for your thorough and insightful review of our manuscript. Your comprehensive summary accurately captures the essence of our multi-omics study on oviductal biology, highlighting its importance in understanding reproductive physiology. We are particularly grateful for your recognition of our study's strengths. In the revised manuscript, we

plan to add another searchable scRNA-seq data on our public website; https://genesearch.org/winuthayanon/Oviduct_pregnancy/. We will also address the weaknesses in the response below in our revised manuscript.  

Weaknesses:  

(1) The rationale for using the superovulation model is not clear. The oviductal response to sperm and embryos can be studied by comparing mating with normal and vasectomized mice and comparing pregnancy vs pseudopregnancy (induced by mating with vasectomized males). Superovulation causes supraphysiological hormone levels and other confounding conditions.

We agree with this assessment that superovulation changes the hormonal levels and could have a confounding impact on the oviduct function. As such, for all experiments involving pseudopregnant datasets, pseudopregnancy was induced by mating females with vasectomized males without superovulation. In our oviductal luminal protein content analysis, oviductal fluid was collected from pregnant females with and without superovulation. This allowed us to directly compare the impact of superovulation on protein abundance and profile. In the revised manuscript, we will provide clarifying statements on using superovulation in our experimental design. 

One exception for using superovulation in the absence of a “natural mating” group for comparison is the scRNA-seq dataset. As single-cell libraries should be performed in a single run to avoid batch effects, we need to ensure that the sufficient number of females were pregnant for single-cell isolation (we used ~4 mice/timepoint). Therefore, superovulation was used to synchronize and ensure that the females were receptive to mating. At the time of our sample collection, single nuclei isolation methods (freeze tissue now, isolate nuclei later) have not been reliable or standardized. We have tried to synchronize females using the male bedding without having to superovulate. However, we would still need to set up at least 12-15 females per pregnancy timepoint to mate with male mice, which totals to ~48-60 mice each night. Due to budget and vivarium space limitations, we were not able to do so. We will include a similar statement to explain and clarify these limitations in the revised manuscript.

(2) This study involves a very complex dataset with three different models at four time points. If possible, it would be very informative to generate a graphic abstract/summary of their major findings in oviductal responses in different models and time points

Thank you for this suggestion. We will include the graphical abstract to accompany our final version of the manuscript.

(3) The resolution of Figures 3A-3C in the submitted file was not high enough to assess the authors' conclusion.

We plan to provide a higher magnification of images in Figures 3A-C in the revised version.

(4) The authors need to double-check influential transcription factors identified by machine learning. Apparently, some of them (such as Anxa2, Ift88, Ccdc40) are not transcription factors at all.

We appreciate the recognition of this oversight. We will clearly state the distinction between ‘influential TFs’ and ‘significant proteins’ in the revised manuscript. We will ensure that all TFs are stated correctly. 

Reviewer #2 (Public review):

The manuscript investigates oviductal responses to the presence of gametes and embryos using a multi-omics and machine learning-based approach. By applying RNA sequencing (RNAseq), single-cell RNA sequencing (sc-RNA-seq), and proteomics, the authors identified distinct molecular signatures in different regions of the oviduct, proximal versus distal. The study revealed that sperm presence triggers an inflammatory response in the proximal oviduct, while embryo presence activates metabolic genes essential for providing nutrients to the developing embryos. Overall, this study offers valuable insights and is likely to be of great interest to reproductive biologists and researchers in the field of oviduct biology. However, further investigation into the impact of sperm on the immune cell population in the oviduct is necessary to strengthen the overall findings.

We appreciate the concise summary, strengths, and weakness highlighted. We plan to address comments made by the reviewer concerning superovulation, figure recommendations, and additional analysis in our revised manuscript. We plan to include the comparison of findings from scRNA-seq analysis from fallopian tube tissues collected from hydrosalpinx patients by Ulrich et al. (PMID: 35320732) with our data. The evaluation of this data by Ulrich et al. will help distinguish between different inflammatory pathways stimulated by sperm vs. general inflammation. We will follow up on a detailed description of immune cell types present at 0.5 dpc using FACS analysis in future studies. This is mainly due to a lack of expertise and technical limitations in our lab on immune cell investigation. Nevertheless, we have made collaborative efforts and recruited two immunologists to facilitate our future immune cell studies. We will also provide a clear justification for using superovulation, especially in the scRNA-seq analysis in the revised manuscript (please see response to Reviewer 1 above).

eLife Assessment

The authors follow up on a prior paper in which they showed that beta1 adrenergic receptors contributed to the pathogenesis of cavernous malformations. In the prior work, they used morpholinos and drugs to show this. In this new advance, they now extend this using a genetic knockout of the receptor. While both reviewers agree that this is important for the CV field, there are concerns about the labeling of figures and sample sizes used to make their claims, so the evidence is currently incomplete.

Reviewer #1 (Public review):

Summary:

This work seeks to provide genetic evidence for a role for beta-adrenergic receptors that regulate heart rate and blood flow on cavernous malformation development using a zebrafish model, and to extend information regarding beta-adrenergic drug blockade in cavernous malformation development, with the idea that these drugs may be useful therapeutically.

Strengths:

The work shows that genetic loss of a specific beta-adrenergic receptor in zebrafish, adrb1, prevents embryonic venous malformations and CCM in adult zebrafish brains. Two drugs, propranolol and metoprolol, also blunt CCM in the adult fish brain. These findings are predicted to potentially impact the treatment of human CCM, and they increase understanding of the factors leading to CCM.

Weaknesses:

There are minor weaknesses that detract slightly from enthusiasm, including poor annotation of the Figure panels and lack of a baseline control for the study of Klf2 expression (Figure 4).

Reviewer #2 (Public review):

Summary:

Previously, the authors developed a zebrafish model for cerebral cavernous malformations (CCMs) via CRISPR/Cas9-based mosaic inactivation of the ccm2 gene. This model yields CCM-like lesions in the caudal venous plexus of 2 days post-fertilization embryos and classical CNS cavernomas in 8-week fish that depend, like the mouse model, on the upregulation of the KLF2 transcription factor. Remarkably, the morpholino-based knockdown of the gene encoding the Beta1 adrenergic receptor or B1AR (adrb1; a hemodynamic regulator) in fish and treatment with the anti-adrenergic S enantiomer of propranolol in both fish and mice reduce the frequency and size of CMM lesions.

In the present study, the authors aim to test the model that adrb1 is required for CCM lesion development using adrb1 mutant fish (rather than morpholino-mediated knockdown and pharmacological treatments with the anti-adrenergic S enantiomer of propranolol or a racemic mix of metoprolol (a selective B1AR antagonist).

Strengths:

The goal of the work is important, and the findings are potentially highly relevant to cardiovascular medicine.

Weaknesses:

(1) The following figures do not report sample sizes, making it difficult to assess the validity of the findings: Figures 1B and D (the number of scored embryos is missing), Figures 2G and 3B (should report both the number of fish and lesions scored, with color-coding to label the lesions corresponding to individual fish in which they where found).

(2) Figure 4 has a few caveats. First, the use of adrb1 morphants (rather than morphants) is at odds with the authors' goal of using genetic validation to test the involvement of adrb1 in CCM2-induced lesion development.

Second, the authors should clarify if they have validated that the tnnt (tnnt2a) morpholino phenocopies tnnt2a mutants in the context in which they are using it (this reviewer found that the tnnt2a morpholino blocks the heartbeat just like the mutant, but induces additional phenotypes not observed in the mutants).

Third, the data in Figure 4E is from just two embryos per treatment, a tiny sample size. Furthermore, judging from the number of points in the graph, only a few endothelial PCV cells appear to have been sampled per embryo. Also, judging from the photos and white arrowheads and arrows (Figure 4A-D), only the cells at the ventral side of the vessel were scored (if so, the rationale behind this choice requires clarification).

Fourth, it is unclear whether and how the Tg(kdrl:mcherry)is5 endothelial reporter was used to mask the signals from the klf2a reporter. The reviewer knows by experience that accuracy suffers if a cytosolic or cell membrane signal is used to mask a nuclear green signal.

Finally, the text and legend related to Figure 4 could be more explicit. What do the authors mean by a mosaic pattern of endothelial nuclear EGFP intensity, and how is that observation reflected in graph 4E? When I look at the graph, I understand that klf2a is decreased in C-D compared to A-B. Are some controls missing? Suppose the point is to show mosaicism of Klf2a levels upon ccm2 CRISPR. Don't you need embryos without ccm2 CRISPR to show that Klf2a levels in those backgrounds have average levels that vary within a defined range and that in the presence of ccm2 mosaicism, some cells have values significantly outside that range? Also, in 4A-D, what are the white arrowheads and arrows? The legend does not mention them.

Given the practical relevance of the findings to cardiovascular medicine, increasing the strength of the evidence would greatly enhance the value of this work.

Author response:

Thank you for your thoughtful and constructive feedback on our manuscript. We greatly appreciate your recognition of the strengths in our work, particularly regarding the genetic evidence demonstrating the role of beta-adrenergic receptors in cavernous malformation (CCM) development and the therapeutic potential of beta-blocker drugs.

We acknowledge your concerns and have addressing them to improve the clarity and rigor of our study. Specifically:

For Reviewer 1:

(1) Figure Annotation: We will enhance the annotation of the figure panels to provide clearer and more detailed descriptions, ensuring that each panel is easily interpretable and contributes effectively to the overall narrative of the study.

(2) Baseline Control for Klf2 Expression: We will include this control (klf2 expression in control Morpholino-injected embryos) in our revised figures and text to provide a more complete context for the changes in klf2 expression observed in response to genetic loss of adrb1 in ccm2 morphants and ccm2-CRISPR embryos.

For Reviewer 2:

(3) Sample Sizes in Figures 1, 2, and 3: We agree that reporting sample sizes is crucial for the transparency and reproducibility of our findings. For Figures 1B and D, as well as Figures 2G and 3B, we will update the figure legends to include the number of embryos and adult fish in which lesions were scored.

(4) Figure 4 Concerns: Use of adrb1 Morphants: We will note that the adrb1 morphant shows similar hemodynamic changes to the adrb1 mutant and that the morphants did not prevent the mosaic klf2 expression in ccm2 CRISPR embryos. Thus supporting our conclusion that protection from CVP cavernomas in the adrb1 mutant are not due to altered hemodynamics blocking mosaic klf2 expression.

eLife Assessment

In this important study, the authors used a zebrafish model and scRNAseq analysis to show that a subset of keratinocytes within melanoma microenvironment highly up-regulate Twist and undergo Epithelial-Mesenchymal Transition (EMT). Surprisingly, when overexpressing Twist in keratinocytes, the resulting alteration in keratinocytes is inhibitory for melanoma invasion in both zebrafish and human cell culture models. The results are supported by overall convincing experimental data that provide new insights into the interactions between melanoma cells and their environment.

Reviewer #1 (Public review):

Summary:

Ma et al. show that melanoma cells induce an EMT-like state in nearby keratinocytes and that when this state is induced experimentally by Twist-overexpression the resulting alteration in keratinocytes is inhibitory for melanoma invasion. These conclusions are based on experiments in vivo with zebrafish and, in vitro, with human cells. The work is carefully done and provides new insights into the interactions between melanoma cells and their environment.

Strengths:

The use of both zebrafish and human cells adds confidence that findings are relevant to human melanomas while also further demonstrating the utility of the zebrafish system for discovering important new features of melanoma biology that could ultimately have clinical impacts. The work also combines a nice suite of approaches including different models for induced melanomagenesis in zebrafish, single-cell RNA-sequencing, and more. Some of the final observations are intriguing as well, especially the possibility of EMT-induced melanocyte-keratinocyte interactions via Jam3 expression; it will be interesting to see if this is indeed a mechanism for restraining melanoma invasion. The paper is clearly written and the inferences are appropriate for the results obtained. Overall the work makes a solid contribution to our understanding of important, but too often neglected, roles of the tumor microenvironment in promoting or inhibiting tumor progression and outcome.

Weaknesses:

No critical weaknesses were noted.

Reviewer #2 (Public review):

Summary:

The manuscript by Ma et. al. utilizes a zebrafish melanoma model, single-cell RNA sequencing (scRNA-seq), a mammalian in vitro co-culture system, and quantitative PCR (Q-PCR) gene expression analysis to investigate the role keratinocytes might play within the melanoma microenvironment. Convincing evidence is presented from scRNA-seq analysis showing that a small cluster of melanoma-associated keratinocytes upregulates the master EMT regulator, transcription factor, Twist1a. To investigate how Twist-expressing keratinocytes might influence melanoma development, the authors use an in vivo zebrafish model to induce melanoma initiation while overexpressing Twist in keratinocytes through somatic transgene expression. This approach reveals that Twist overexpression in keratinocytes suppresses invasive melanoma growth. Using a complementary in vitro human cell line co-culture model, the authors demonstrate reduced migration of melanoma cells into the keratinocyte monolayer when keratinocytes overexpress Twist. Further scRNA-seq analysis of zebrafish melanoma tissues reveals that in the presence of Twist-expressing keratinocytes, subpopulations of melanoma cells show altered gene expression, with one unique melanoma cell cluster appearing more terminally differentiated. Finally, the authors use computational methods to predict putative receptor-ligand pairs that might mediate the interaction between Twist-expressing keratinocytes and melanoma cells.

Strengths:

The scRNA-seq approach reveals a small proportion of keratinocytes undergoing EMT within melanoma tissue. The use of a zebrafish somatic transgenic model to study melanoma initiation and progression provides an opportunity to manipulate host cells within the melanoma microenvironment and evaluate their impact on tumour progression. Solid data demonstrate that Twist-expressing keratinocytes can constrain melanoma invasive development in vivo and reduce melanoma cell migration in vitro, establishing that Twist-overexpressing keratinocytes can suppress at least one aspect of tumour progression.

Weaknesses:

While the scRNA-seq analysis of melanoma tissue and RT-PCR analysis of EMT gene expression in isolated keratinocytes provide evidence that a subpopulation of host keratinocytes upregulates Twist and other EMT marker genes and potentially undergoes EMT, the in vivo evidence for keratinocyte EMT within the melanoma microenvironment is based on cell morphology in a single image without detailed characterization and quantification. No EMT marker gene expression was examined in melanoma tissue sections to determine the proportion and localization of Twist+ve keratinocytes within the melanoma microenvironment.

The scRNA-seq UMAP suggests the proportion of EMT keratinocytes within the melanoma microenvironment is very small, raising questions about their precise location and significance within the tumour microenvironment. Although both in vivo and in vitro evidence demonstrates that Twist-expressing keratinocytes can suppress melanoma progression, the conditions modelled by the authors involve over-expression of Twist in all keratinocytes, which do not naturally occur within the melanoma microenvironment and, therefore, might not be relevant to naturally occurring melanoma progression. The author did not test whether blocking EMT through down-regulation of Twist in keratinocytes may influence melanoma development, which would establish the role of Twist expression keratinocytes in the melanoma microenvironment.

To address the potential mechanism by which Twist-expressing keratinocytes suppress melanoma progression, a second scRNA-seq analysis was conducted. However, this analysis is not adequately presented to provide strong evidence for proposed mechanisms for how Twist-expressing keratinocytes suppress melanoma cell invasion. CellChat analysis was used to attempt to identify receptor-ligand pairs that might mediate keratinocyte-melanoma cell interaction, but the interactions between tumour-associated keratinocytes (TAK) and melanoma cells were not included in the analysis. Furthermore, although genetic reporters were used to label both keratinocytes and melanoma cells, no images showing the detailed distribution and positional information of these cells within melanoma tissue are presented in the report. None of the gene expression changes detected through Q-PCR or scRNA-seq were validated using immunostaining or in situ hybridization.

Overall, the data presented in this report draw attention to a less-studied host cell type within the tumour microenvironment, the keratinocytes, which, similar to well-studied immune cells and fibroblasts, could play important roles in either promoting or constraining melanoma development.

Counterintuitively, the authors show that Twist-expressing EMT keratinocytes can constrain melanoma progression. While the detailed mechanisms remain to be uncovered, this is an interesting observation.

Reviewer #3 (Public review):

Summary:

In this study the authors use the zebrafish model and in vitro co-cultures with human cell lines, to study how keratinocytes modulate the early stages of melanoma development/migration. The authors demonstrate that keratinocytes undergo an EMT-like transformation in the presence of melanoma cells which leads to a reduction in melanoma cell migration. This EMT transformation occurs via Twist; and resulted in an improvement in OS in zebrafish melanoma models. Authors suggest that the limitation of melanoma cell migration by Twist-overexpressing keratinocytes was through altered cell-cell interactions (Jam3b) that caused a physical blockage of melanoma cell migration.

Strengths:

The authors describe a new cross-talk between melanoma and its major initial microenvironment: the keratinocytes and how instructed by melanoma cells keratinocytes undergo an EMT transformation, which then controls melanoma migration.

Overall, the paper is very well written, and the results are clearly organized and presented.

Weaknesses:

(1) To really show their last point it would be important to CRISPR KO Jam3b in melanoma with twist OE keratinocytes, in vivo or in vitro.

(2) The use of patient biopsies from early-stage melanomas vs healthy tissue to assess if there is a similar alteration of morphology of adjacent keratinocytes and an increase in vimentin in human samples would strengthen the author's findings.

(3) The cell-cell junctions and borders between cells (melanoma/ keratinocytes) should be characterized better, with cellular and sub-cellular resolution. Since melanocytes can "touch" with their dendrites ~40 keratinocytes - can authors expand and explain better their model? Can this explain that in some images we cannot observe a direct interface between the cells?

eLife Assessment

This study corroborates recent findings from another group and provides valuable insights into the structure of the autophagy initiation complex, which includes ULK1, ATG13, and FIP200. The authors present solid evidence that supports their claims and addresses one of the key questions in autophagy initiation.

Reviewer #1 (Public review):

In this study, Hama et al. explored the molecular regulatory mechanisms underlying the formation of the ULK1 complex. By employing the AlphaFold structural prediction tool, they showed notable differences in the complex formation mechanisms between ULK1 in mammalian cells and Atg1 in yeast cells. Their findings revealed that in mammalian cells, ULK1, ATG13, and FIP200 form a complex with a stoichiometry of 1:1:2. These predicted interaction regions were validated through both in vivo and in vitro assays, enhancing our understanding of the molecular mechanisms governing ULK1 complex formation in mammalian cells. Importantly, they identified a direct interaction between ULK1 and FIP200, which is crucial for autophagy. However, some aspects of this manuscript require further clarification, validation, and correction by the authors.

Reviewer #2 (Public review):

Summary:

This is important work that helps to uncover how the process of autophagy is initiated - via structural analyses of the initiating ULK1 complex. High-resolution structural details and a mechanistic insight of this complex have been lacking and understanding how it assembles and functions is a major goal of a field that impacts many aspects of cell and disease biology. While we know components of the ULK1 complex are essential for autophagy, how they physically interact is far from clear. The work presented makes use of AlphaFold2 to structurally predict interaction sites between the different subunits of the ULK1 complex (namely ULK1, ATG13, and FIP200). Importantly, the authors go on to experimentally validate that these predicted sites are critical for complex formation by using site-directed mutagenesis and then go on to show that the three-way interaction between these components is necessary to induce autophagy in cells.

Strengths:

The data are very clear. Each binding interface of ATG13 (ATG13 with FIP300/ATG13 with ULK1) is confirmed biochemically with ITC and IP experiments from cells. Likewise, IP experiments with ULK1 and FIP200 also validate interaction domains. A real strength of the work in in their analyses of the consequences of disrupting ATG13's interactions in cells. The authors make CRISPR KI mutations of the binding interface point mutants. This is not a trivial task and is the best approach as everything is monitored under endogenous conditions. Using these cells the authors show that ATG13's ability to interact with both ULK1 and FIP200 is essential for a full autophagy response.

Weaknesses:

I think a main weakness here is the failure to acknowledge and compare results with an earlier preprint that shows essentially the same thing (https://doi.org/10.1101/2023.06.01.543278). Arguably this earlier work is much stronger from a structural point of view as it relies not only on AlphaFold2 but also actual experimental structural determinations (and takes the mechanisms of autophagy activation further by providing evidence for a super complex between the ULK1 and VPS34 complexes). That is not to say that this work is not important, as in the least it independently helps to build a consensus for ULK1 complex structure. Another weakness is that the downstream "functional" consequences of disrupting the ULK1 complex are only minimally addressed. The authors perform a Halotag-LC3 autophagy assay, which essentially monitors the endpoint of the process. There are a lot of steps in between, knowledge of which could help with mechanistic understanding. Not in the least is the kinase activity of ULK1 - how is this altered by disrupting its interactions with ATG13 and/or FIP200?

Reviewer #3 (Public review):

In this study, the authors employed the protein complex structure prediction tool AlphaFold-Multimer to obtain a predicted structure of the protein complex composed of ULK1-ATG13-FIP200 and validated the structure using mutational analysis. This complex plays a central role in the initiation of autophagy in mammals. Previous attempts at resolving its structure have failed to obtain high-resolution structures that can reveal atomic details of the interactions within the complex. The results obtained in this study reveal extensive binary interactions between ULK1 and ATG13, between ULK1 and FIP200, and between ATG13 and FIP200, and pinpoint the critical residues at each interaction interface. Mutating these critical residues led to the loss of binary interactions. Interestingly, the authors showed that the ATG13-ULK1 interaction and the ATG13-FIP200 interaction are partially redundant for maintaining the complex.

The experimental data presented by the authors are of high quality and convincing. However, given the core importance of the AlphaFold-Multimer prediction for this study, I recommend the authors improve the presentation and documentation related to the prediction, including the following:

(1) I suggest the authors consider depositing the predicted structure to a database (e.g. ModelArchive) so that it can be accessed by the readers.

(2) I suggest the authors provide more details on the prediction, including explaining why they chose to use the 1:1:2 stoichiometry for ULK1-ATG13-FIP200 and whether they have tried other stoichiometries, and explaining why they chose to use the specific fragments of the three proteins and whether they have used other fragments.

(3) I suggest the authors present the PAE plot generated by AlphaFold-Multimer in Figure S1. The PAE plot provides valuable information on the prediction.

eLife Assessment

This work attempts to demonstrate an ATP-independent non-canonical role of proteasomal component PA28y in the promotion of oral squamous cell carcinoma growth, migration, and invasion. The evidence around the following two areas remains incomplete and would benefit from further experimental work: 1) the stabilisation of the complement C1q binding protein (C1QBp) by PA28y, and 2) the impact of the PA28y-C1QBp interaction on mitochondrial function.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors have tried to dissect the functions of Proteasome activator 28γ (PA28γ) which is known to activate proteasomal function in an ATP-independent manner. Although there are multiple works that have highlighted the role of this protein in tumours, this study specifically tried to develop a correlation with Complement C1q binding protein (C1QBp) that is associated with immune response and energy homeostasis.

Strengths:

The observations of the authors hint that beyond PA28y's association with the proteasome, it might also stabilize certain proteins such as C1QBP which influences energy metabolism.

Weaknesses:

The strength of the work also becomes its main drawback. That is, how PA28y stabilizes C1QBP or how C1QBP elicits its pro-tumourigenic role under PA28y OE.<br /> In most of the experiments, the authors have been dependent on the parallel changes in the expression of both the proteins to justify their stabilizing interaction. However, this approach is indirect at best and does not confirm the direct stabilizing effect of this interaction. IP experiments do not indicate direct interaction and have some quality issues. The upregulation of C1QBP might be indirect at best. It is quite possible that PA28y might be degrading some secondary protein/complex that is responsible for C1QBP expression. Since the core idea of the work is PA28y direct interaction with C1QBP stabilizing it, the same should be demonstrated in a more convincing manner.

In all of the assays, C1QBP has been detected as doublet. However, the expression pattern of the two bands varies depending on the experiment. In some cases, the upper band is intensely stained and in some the lower bands. Do C1QBP isoforms exist and are they differentially regulated depending on experiment conditions/tissue types?

Problems with the background of the work: Line 76. This statement is far-fetched. There are presently a number of works of literature that have dealt with the metabolic programming of OSCC including identification of specific metabolites. Moreover, beyond the estimation of OCR, the authors have not conducted any experiments related to metabolism. In the Introduction, the significance of this study and how it will extend our understanding of OSCC needs to be elaborated.

Reviewer #2 (Public review):

Summary:

The authors tried to determine how PA28g functions in oral squamous cell carcinoma (OSCC) cells. They hypothesized it may act through metabolic reprogramming in the mitochondria.

Strengths:

They found that the genes of PA28g and C1QBP are in an overlapping interaction network after an analysis of a genome database. They also found that the two proteins interact in coimmunoprecipitation and pull-down assays using the lysate from OSCC cells with or without expression of the exogenous genes. They used truncated C1QBP proteins to map the interaction site to the N-terminal 167 residues of C1QBP protein. They observed the levels of the two proteins are positively correlated in the cells. They provided evidence for the colocalization of the two proteins in the mitochondria, the effect on mitochondrial form and function in vitro and in vivo OSCC models, and the correlation of the protein expression with the prognosis of cancer patients.

Weaknesses:

Many data sets are shown in figures that cannot be understood without more descriptions, either in the text or the legend, e.g., Figure 1A. Similarly, many abbreviations are not defined.

Some of the pull-down and coimmunoprecipitation data do not support the conclusion about the PA28g-C1QBP interaction. For example, in Appendix Figure 1B the Flag-C1QBP was detected in the Myc beads pull-down when the protein was expressed in the 293T cells without the Myc-PA28g, suggesting that the pull-down was not due to the interaction of the C1QBP and PA28g proteins. In Appendix Figure 1C, assume the SFB stands for a biotin tag, then the SFB-PA28g should be detected in the cells expressing this protein after pull-down by streptavidin; however, it was not. The Western blot data in Figure 1E and many other figures must be quantified before any conclusions about the levels of proteins can be drawn.

The immunoprecipitation method is flawed as it is described. The antigen (PA28g or C1QBP) should bind to the respective antibody that in turn should binds to Protein G beads. The resulting immunocomplex should end up in the pellet fraction after centrifugation and be analyzed further by Western blot for coprecipitates. However, the method in the Appendix states that the supernatant was used for the Western blot.

To conclude that PA28g stabilizes C1QBP through their physical interaction in the cells, one must show whether a protease inhibitor can substitute PA28q and prevent C1QBP degradation, and also show whether a mutation that disrupts the PA28g-C1QBP interaction can reduce the stability of C1QBP. In Figure 1F, all cells expressed Myc-PA28g. Therefore, the conclusion that PA28g prevented C1QBP degradation cannot be reached. Instead, since more Myc-PA28g was detected in the cells expressing Flag-C1QBP compared to the cells not expressing this protein, a conclusion would be that the C1QBP stabilized the PA28g. Figure 1G is a quantification of Western blot data that should be shown.

The binding site for PA28g in C1QBP was mapped to the N-terminal 167 residues using truncated proteins. One caveat would be that some truncated proteins did not fold correctly in the absence of the sequence that was removed. Thus, the C-terminal region of the C1QBP with residues 168-283 may still bind to the PA29g in the context of full-length protein. In Figure 1I, more Flag-C1QBP 1-167 was pulled down by Myc-PA28g than the full-length protein or the Flag-C1QBP 1-213. Why?

The interaction site in PA28g for C1QBP was not mapped, which prevents further analysis of the interaction. Also, if the interaction domain can be determined, structural modeling of the complex would be feasible using AlphaFold2 or other programs. Then, it is possible to test point mutations that may disrupt the interaction and if so, the functional effect

eLife Assessment

This useful study by Gao et al identifies Hspa2 as a heterogeneous transcript in the early embryo and proposes a plausible mechanism showing interactions with Carm1. The authors propose that variability in HSPA2 levels among blastomeres at the 4-cell stage skews their relative contribution to the embryonic lineage. Given only 4 other heterogeneous transcripts/non-coding RNA have been proposed to act similarly at or before the 4-cell stage, this would be a key addition to our understanding of how the first cell fate decision is made. Whilst this is a solid study, in order to support its conclusions image analyses and quantifications would need to be better described, and the overexpression studies should be validated.

Reviewer #1 (Public review):

Summary:

The authors investigate the role of HSPA2 during mouse preimplantation development. Knocking down HSPA2 in zygotes, the authors describe lower chances of developing into blastocysts, which show a reduced number of inner cell mass cells. They find that HSPA2 mRNA and protein levels show some heterogeneity among blastomeres at the 4-cell stage and propose that HSPA2 could contribute to skewing their relative contribution to embryonic lineages. To test this, the authors try to reduce HSPA2 expression in one of the 2-cell stage blastomere and propose that it biases their contribution to towards extra-embryonic lineages. To explain this, the authors propose that HSPA2 would interact with CARM1, which controls chromatin accessibility around genes regulating differentiation into embryonic lineage.

Strengths:

(1) The study offers simple and straightforward experiments with large sample sizes.

(2) Unlike most studies in the field, this research often relies on both mRNA and protein levels to analyse gene expression and differentiation.

Weaknesses:

(1) Image and statistical analyses are not well described.

(2) The functionality of the overexpression construct is not validated.

(3) Tracking of KD cells in embryos injected at the 2-cell stage with GFP is unclear.

(4) A key rationale of the study relies on measuring small differences in the levels of mRNA and proteins using semi-quantitative methods to compare blastomeres. As such, it is not possible to know whether those subtle differences are biologically meaningful. For example, the lowest HSPA2 level of the embryo with the highest level is much higher than the top cell from the embryo with the lowest level. What does this level mean then? Does this mean that some blastomeres grafted from strong embryos would systematically outcompete all other blastomeres from weaker embryos? That would be very surprising. I think the authors should be more careful and consider the lack of quantitative power of their approach before reaching firm conclusions. Although to be fair, the authors only follow a long trend of studies with the same intrinsic flaw of this approach.

(5) Some of the analyses on immunostaining do not take into account that this technique only allows for semi-quantitative measurements and comparisons.<br /> a) Some of the microscopy images are shown with an incorrect look-up table.<br /> b) Some of the schematics are incorrect and misleading.

Reviewer #2 (Public review):

Summary:

In this study, Gao et al. use RNA-seq to identify Hspa2 as one of the earliest transcripts heterogeneously distributed between blastomeres. Functional studies are performed using siRNA knockdown showing Hspa2 may bias cells toward the ICM lineage via interaction with the known methyltransferase CARM1.

Strengths:

This study tackles an important question regarding the origins of the first cell fate decision in the preimplantation embryo. It provides novelty in its identification of Hspa2 as a heterogeneous transcript in the early embryo and proposes a plausible mechanism showing interactions with Carm1. Multiple approaches are used to validate their functional studies (FISH, WB, development rates, proteomics). Given only 4 other transcripts/RNA have been identified at or before the 4-cell stage (LincGET, CARM1, PRDM14, HMGA1), this would be an important addition to our understanding of how TE vs ICM fate is established.

Weaknesses:

The RNA-seq results leading the authors to focus on Hspa2 are not included in the manuscript. This dataset would serve as an important resource but is neither included nor discussed. Nor is it mentioned whether Hspa2 was identified in prior RNA-seq embryos studies (for example Deng Science 2014).

In addition, the functional studies are centered on Hspa2 knockdown at the zygote (1-cell) stage, which would largely target maternal transcript. Given the proposed mechanism relies on Hspa2 heterogeneity post-ZGA (late 2-cell stage), the knockdown studies don't necessarily test this and thus don't provide direct support to the authors' conclusions. The relevance of the study would be improved if the authors could show that zygotic knockdown leads to symmetric Hspa2 levels at the late 2-cell and/or 4-cell stage. It may be possible that zygotic knockdown leads to lower global Hspa2 levels, but that asymmetry is still generated at the 4-cell stage.

Furthermore, the authors show that Hspa2 knockdown at the 1-cell stage lowers total Carm1 levels at the 4-cell stage. However, it is unclear how total abundance within the embryo alters lineage specification within blastomeres. The authors go on to propose a plausible mechanism involving Hspa2 and Carm1 interaction, but do not discuss how expression levels may be involved.

eLife Assessment

This important study investigates the function of a critical regulator of human early cardiac development. The convincing examination of GATA6 function is thorough and well-executed. The study will be of interest to scientists working on how the human heart acquires its identity.

Reviewer #1 (Public review):

Summary:

This is a comprehensive study that clearly and deeply investigates the function of GATA6 in human early cardiac development.

Strengths:

This study combines hESC engineering, differentiation, detailed gene expression, genome occupancy, and pathway modulation to elucidate the role of GATA6 in early cardiac differentiation. The work is carefully executed and the results support the conclusions. The use of publicly available data is well integrated throughout the manuscript. The RIME experiments are excellent.

Weaknesses:

Much has been known about GATA6 in mesendoderm development, and this is acknowledged by the authors.

Reviewer #2 (Public review):

Summary:

This manuscript by Bisson et al describes the role of GATA6 to regulate cardiac progenitor cell (CPC) specification and cardiomyocyte (CM) generation using human embryonic stem cells (hESCs). The authors found that GATA6 loss-of-function hESC exhibits early defects in mesendoderm and lateral mesoderm patterning stages. Using RNA-seq and CUT&RUN assays the genes of the Wnt and BMP programs were found to be affected by the loss of GATA6 expression. Modulating Wnt and BMP during early cardiac differentiation can partially rescue CPC and CM defects in GATA6 hetero- and homozygous mutant hESCs.

Strengths:

The studies performed were rigorous and the rationale for the experimental design was logical. The results obtained were clear and supported the conclusions that the authors made regarding the role of GATA6 on Wnt and BMP pathway gene expression.

Weaknesses:

Given the wealth of studies that have been performed in this research area previously, the amount of new information provided in this study is relatively modest. Nevertheless, the results and quite clear and should make a strong contribution to the field.

Reviewer #3 (Public review):

In this study, Bison et al. analyzed the role of the GATA6 transcription factor in patterning the early mesoderm and generating cardiomyocytes, using human embryonic stem cell differentiation assays and patient-derived hiPSCs with heart defects associated with mutations in the GATA6 gene. They identified a novel role for GATA6 in regulating genes involved in the WNT and BMP pathways -findings not previously noted in earlier analyses of GATA6 mutant hiPSCs during early cardiac mesoderm specification (Sharma et al., 2020). Modulation of the WNT and BMP pathways may partially rescue early cardiac mesoderm defects in GATA6 mutant hESCs. These results provide significant insights into how GATA6 loss-of-function and heterozygous mutations contribute to heart defects.

I have the following comments:

(1) Throughout the manuscript, Bison et al. alternate between different protocols to generate cardiomyocytes, which creates some confusion (e.g., Figure 1 vs. Supplemental Figure 2A). The authors should provide a clear justification for using alternative protocols.

(2) The authors should characterise the mesodermal identity and cardiomyocyte subtypes generated with the activin/BMP-induction protocol thoroughly and clarify whether defects in the expression of BMP and WNT-related gene affect the formation of specific cardiomyocyte subtypes in a chamber-specific manner. This analysis is important, as Sharma et al. suggested a role for GATA6 in orchestrating outflow tract formation, and Bison et al. similarly identified decreased expression of NRP1, a gene involved in outflow tract septation, in their GATA6 mutant cells.

(3) The authors developed an iPSC line derived from a congenital heart disease (CHD) patient with an atrial septal defect and observed that these cells generate cTnnT+ cells less efficiently. However, it remains unclear whether atrial cardiomyocytes (or those localised specifically at the septum) are being generated using the activin/BMP-induction protocol and the patient-derived iPSC line.

(4) The authors should also justify the necessity of using the patient-derived line to further analyse GATA6 function.

(5) Figure 3 suggests an enrichment of paraxial mesoderm genes in the context of GATA6 loss-of-function, which is intriguing given the well-established role of GATA6 in specifying cardiac versus pharyngeal mesoderm lineages in model organisms. Could the authors expand their analysis beyond GO term enrichment to explore which alternative fates GATA6 mutant cells may acquire? Additionally, how does the potential enrichment of paraxial mesoderm, rather than pharyngeal mesoderm, relate to the initial mesodermal induction from their differentiation protocol? Could the authors also rule out the possibility of increased neuronal cell fates?

eLife Assessment

This study presents useful quantitative insights into the prevalence of functionally clustered synaptic inputs on neuronal dendrites. The simple analytical calculations and computer simulations provide solid support for the main arguments. With improvements to the presentation and more realistic simulations (e.g. including the interaction between calcium and electric signals) the findings can lead to a more detailed understanding of how dendrites contribute to the computation of neuronal networks.

Reviewer #1 (Public Review):

In the current manuscript, the authors use theoretical and analytical tools to examine the possibility of neural projections to engage ensembles of synaptic clusters in active dendrites. The analysis is divided into multiple models that differ in the connectivity parameters, speed of interactions, and identity of the signal (electric vs. second messenger). They first show that random connectivity almost ensures the representation of presynaptic ensembles. As expected, this convergence is much more likely for small group sizes and slow processes, such as calcium dynamics. Conversely, fast signals (spikes and postsynaptic potentials) and large groups are much less likely to recruit spatially clustered inputs. Dendritic nonlinearity in the postsynaptic cells was found to play a highly important role in distinguishing these clustered activation patterns, both when activated simultaneously and in sequence. The authors tackled the difficult issue of noise, showing a beneficiary effect when noise 'happens' to fill in gaps in a sequential pattern but degraded performance at higher background activity levels. Last, the authors simulated selectivity to chemical and electrical signals. While they find that longer sequences are less perturbed by noise, in more realistic activation conditions, the signals are not well resolved in the soma.

While I think the premise of the manuscript is worth exploring, I have a number of reservations regarding the results.

(1) In the analysis, the authors made a simplifying assumption that the chemical and electrical processes are independent. However, this is not the case; excitatory inputs to spines often trigger depolarization combined with pronounced calcium influx; this mixed signaling could have dramatic implications on the analysis, particularly if the dendrites are nonlinear (see below)

(2) Sequence detection in active dendrites is often simplified to investigating activation in a part of or the entirety of individual branches. However, the authors did not do that for most of their analysis. Instead, they treat the entire dendritic tree as one long branch and count how many inputs form clusters. I fail to see why simplification is required and suspect it can lead to wrong results. For example, two inputs that are mapped to different dendrites in the 'original' morphology but then happen to fall next to each other when the branches are staggered to form the long dendrites would be counted as neighbors.

(3) The simulations were poorly executed. Figures 5 and 6 show examples but no summary statistics. The authors emphasize the importance of nonlinear dendritic interactions, but they do not include them in their analysis of the ectopic signals! I find it to be wholly expected that the effects of dendritic ensembles are not pronounced when the dendrites are linear.

To provide a comprehensive analysis of dendritic integration, the authors could simulate more realistic synaptic conductances and voltage-gated channels. They would find much more complicated interactions between inputs on a single site, a sliding temporal and spatial window of nonlinear integration that depends on dendritic morphology, active and passive parameters, and synaptic properties. At different activation levels, the rules of synaptic integration shift to cooperativity between different dendrites and cellular compartments, further complicated by nonlinear interactions between somatic spikes and dendritic events.

While it is tempting to extend back-of-the-napkin calculations of how many inputs can recruit nonlinear integration in active dendrites, the biological implementation is very different from this hypothetical. It is important to consider these questions, but I am not convinced that this manuscript adequately addressed the questions it set out to probe, nor does it provide information that was unknown beforehand.

Reviewer #2 (Public Review):

Summary:

If synaptic input is functionally clustered on dendrites, nonlinear integration could increase the computational power of neural networks. But this requires the right synapses to be located in the right places. This paper aims to address the question of whether such synaptic arrangements could arise by chance (i.e. without special rules for axon guidance or structural plasticity), and could therefore be exploited even in randomly connected networks. This is important, particularly for the dendrites and biological computation communities, where there is a pressing need to integrate decades of work at the single-neuron level with contemporary ideas about network function.

Using an abstract model where ensembles of neurons project randomly to a postsynaptic population, back-of-envelope calculations are presented that predict the probability of finding clustered synapses and spatiotemporal sequences. Using data-constrained parameters, the authors conclude that clustering and sequences are indeed likely to occur by chance (for large enough ensembles), but require strong dendritic nonlinearities and low background noise to be useful.

Strengths:

(1) The back-of-envelope reasoning presented can provide fast and valuable intuition. The authors have also made the effort to connect the model parameters with measured values. Even an approximate understanding of cluster probability can direct theory and experiments towards promising directions, or away from lost causes.

(2) I found the general approach to be refreshingly transparent and objective. Assumptions are stated clearly about the model and statistics of different circuits. Along with some positive results, many of the computed cluster probabilities are vanishingly small, and noise is found to be quite detrimental in several cases. This is important to know, and I was happy to see the authors take a balanced look at conditions that help/hinder clustering, rather than to just focus on a particular regime that works.

(3) This paper is also a timely reminder that synaptic clusters and sequences can exist on multiple spatial and temporal scales. The authors present results pertaining to the standard `electrical' regime (~50-100 µm, <50 ms), as well as two modes of chemical signaling (~10 µm, 100-1000 ms). The senior author is indeed an authority on the latter, and the simulations in Figure 5, extending those from Bhalla (2017), are unique in this area. In my view, the role of chemical signaling in neural computation is understudied theoretically, but research will be increasingly important as experimental technologies continue to develop.

Weaknesses:

(1) The paper is mostly let down by the presentation. In the current form, some patience is needed to grasp the main questions and results, and it is hard to keep track of the many abbreviations and definitions. A paper like this can be impactful, but the writing needs to be crisp, and the logic of the derivation accessible to non-experts. See, for instance, Stepanyants, Hof & Chklovskii (2002) for a relevant example.

It would be good to see a restructure that communicates the main points clearly and concisely, perhaps leaving other observations to an optional appendix. For the interested but time-pressed reader, I recommend starting with the last paragraph of the introduction, working through the main derivation on page 7, and writing out the full expression with key parameters exposed. Next, look at Table 1 and Figure 2J to see where different circuits and mechanisms fit in this scheme. Beyond this, the sequence derivation on page 15 and biophysical simulations in Figures 5 and 6 are also highlights.

(2) I wonder if the authors are being overly conservative at times. The result highlighted in the abstract is that 10/100000 postsynaptic neurons are expected to exhibit synaptic clustering. This seems like a very small number, especially if circuits are to rely on such a mechanism. However, this figure assumes the convergence of 3-5 distinct ensembles. Convergence of inputs from just 2 ensembles would be much more prevalent, but still advantageous computationally. There has been excitement in the field about experiments showing the clustering of synapses encoding even a single feature.

(3) The analysis supporting the claim that strong nonlinearities are needed for cluster/sequence detection is unconvincing. In the analysis, different synapse distributions on a single long dendrite are convolved with a sigmoid function and then the sum is taken to reflect the somatic response. In reality, dendritic nonlinearities influence the soma in a complex and dynamic manner. It may be that the abstract approach the authors use captures some of this, but it needs to be validated with simulations to be trusted (in line with previous work, e.g. Poirazi, Brannon & Mel, (2003)).

(4) It is unclear whether some of the conclusions would hold in the presence of learning. In the signal-to-noise analysis, all synaptic strengths are assumed equal. But if synapses involved in salient clusters or sequences were potentiated, presumably detection would become easier? Similarly, if presynaptic tuning and/or timing were reorganized through learning, the conditions for synaptic arrangements to be useful could be relaxed. Answering these questions is beyond the scope of the study, but there is a caveat there nonetheless.

eLife Assessment

This manuscript reports fundamental discoveries on how necrotic cells contribute to organ regeneration through apoptotic signaling. These findings would be of broad interest to those who study wound repair and tissue regeneration. The strength of the evidence is solid, but would be stronger with additional quantifications and controls.

Reviewer #1 (Public review):

Summary:

In previous work, the authors described necrosis-induced apoptosis (NiA) as a consequence of induced necrosis. Specifically, experimentally induced necrosis in the distal pouch of larval wing imaginal discs triggers NiA in the lateral pouch. In this manuscript, the authors confirmed this observation and found that while necrosis can kill all areas of the disc, NiA is limited to the pouch and to some extent to the notum, but is excluded from the hinge region. Interestingly and unexpectedly, signaling by the Jak/Stat and Wg pathways inhibits NiA. Further characterization of NiA by the authors reveals that NiA also triggers regenerative proliferation which can last up to 64 hours following necrosis induction. This regenerative response to necrosis is significantly stronger compared to discs ablated by apoptosis. Furthermore, the regenerative proliferation induced by necrosis is dependent on the apoptotic pathway because RNAi targeting the RHG genes is sufficient to block proliferation. However, NiA does not promote proliferation through the previously described apoptosis-induced proliferation (AiP) pathway, although cells at the wound edge undergo AiP. Further examination of the caspase levels in NiA cells allowed the authors to group these cells into two clusters: some cells (NiA) undergo apoptosis and are removed, while others referred to as Necrosis-induced Caspase Positive (NiCP) cells survive despite caspase activity. It is the NiCP cells that repair cellular damage including DNA damage and that promote regenerative proliferation. Caspase sensors demonstrate that both groups of cells have initiator caspase activity, while only the NiA cells contain effector caspase activity. Under certain conditions, the authors were also able to visualize effector caspase activity in NiCP cells, but the level was low, likely below the threshold for apoptosis. Finally, the authors found that loss of the initiator caspase Dronc blocks regenerative proliferation, while inhibiting effector caspases by expression of p35 does not, suggesting that Dronc can induce regenerative proliferation following necrosis in a non-apoptotic manner. This last finding is very interesting as it implies that Dronc can induce proliferation in at least two ways in addition to its requirement in AiP.

Strengths:

This is a very interesting manuscript. The authors demonstrate that epithelial tissue that contains a significant number of necrotic cells is able to regenerate. This regenerative response is dependent on the apoptotic pathway which is induced at a distance from the necrotic cells. Although regenerative proliferation following necrosis requires the initiator caspase Dronc, Dronc does not induce a classical AiP response for this type of regenerative response. In future work, it will be very interesting to dissect this regenerative response pathway genetically.

Weaknesses:<br /> No weaknesses were identified.

Reviewer #2 (Public review):

Summary / Strengths:

In this manuscript, Klemm et al., build on past published findings (Klemm et al., 2021) to characterize caspase activation in distal cells following necrotic tissue damage within the Drosophila wing imaginal disc. Previously in Klemm et al., 2021, the authors describe necrosis-induced-apoptosis (NiA) following the development of a genetic system to study necrosis that is caused by the expression of a constitutive active GluR1 (Glutamate/Ca2+ channel), and they discovered that the appearance of NiA cells were important for promoting regeneration.

In this manuscript, the authors aim to investigate how tissues regenerate following necrotic cell death. They find that:<br /> (1) the cells of the wing pouch are more likely to have non-autonomous caspase activation than other regions within the wing imaginal disc (hinge and notum),<br /> (2) two signaling pathways that are known to be upregulated during regeneration, Wnt (wingless) and JAK/Stat signaling, act to prevent additional NiA in pouch cells, and may explain the region specificity,<br /> (3) the presence of NiA cells promotes regenerative proliferation in late stages of regeneration,<br /> (4) not all caspase-positive cells are cleared from the epithelium (these cells are then referred to as Necrosis-induced Caspase Positive (NiCP) cells), these NiCP cells continue to live and promote proliferation in adjacent cells,<br /> (5) the caspase Dronc is important for creating NiA/NiCP cells and for these cells to promote proliferation. Animals heterozygous for a Dronc null allele show a decrease in regeneration following necrotic tissue damage.

The study has the potential to be broadly interesting due to the insights into how tissues differentially respond to necrosis as compared to apoptosis to promote regeneration.

Weaknesses:

However, here are some of my current concerns for the manuscript in its current version:

(1) The presence of cells with activated caspase that don't die (NiCP cells) is an interesting biological phenomenon but is not described until Figure 5. How does the existence of NiCP cells impact the earlier findings presented? Is late proliferation due to NiA, NiCP, or both? Does Wg and JAK/STAT signaling act to prevent the formation of both NiA and NiCP cells or only NiA cells? Moreover, the authors are able to specifically manipulate the wound edge (WE) and lateral pouch cells (LP), but don't show how these manipulations within these distinct populations impact regeneration. The authors provide evidence that driving UAS-mir(RHG) throughout the pouch, in the LP or the WE all decrease the amount of NiA/NiCP in Figure 3G-O, but no data on final regenerative outcomes for these manipulations is presented (such as those presented for Dronc-/+ in Fig 7M). The manuscript would be greatly enhanced by quantification of more of the findings, especially in describing if the specific manipulations that impacted NiA /NiCP cells disrupt end-point regeneration phenotypes.

(2) How fast does apoptosis take within the wing disc epithelium? How many of the caspase(+) cells are present for the whole 48 hours of regeneration? Are new cells also induced to activate caspase during this time window? The author presented a number of interesting experiments characterizing the NiCP cells. For the caspase sensor GC3Ai experiments in Figure 5, is there a way to differentiate between cells that have maintained fluorescent CG3Ai from cells that have newly activated caspase? What is the timeline for when NiA and NiCP are specified? In addition, what fraction of NiCP cells contribute to the regenerated epithelium? Additional information about the temporal dynamics of NiA and NiCP specification/commitment would be greatly appreciated.

(3) The notum also does not express developmental JAK/STAT, yet little NiA was observed within the notum. Do the authors have any additional insights into the differential response between the pouch and notum? What makes the pouch unique? Are NiA/NiCP cells created within other imaginal discs and other tissues? Are they similarly important for regenerative responses in other contexts?

Reviewer #3 (Public review):

The manuscript "Regeneration following tissue necrosis is mediated by non-apoptotic caspase activity" by Klemm et al. is an exploration of what happens to a group of cells that experience caspase activation after necrosis occurs some distance away from the cells of interest. These experiments have been conducted in the Drosophila wing imaginal disc, which has been used extensively to study the response of a developing epithelium to damage and stress. The authors revise and refine their earlier discovery of apoptosis initiated by necrosis, here showing that many of those presumed apoptotic cells do not complete apoptosis. Thus, the most interesting aspect of the paper is the characterization of a group of cells that experience mild caspase activation in response to an unknown signal, followed by some effector caspase activation and DNA damage, but that then recover from the DNA damage, avoid apoptosis, and proliferate instead. Many questions remain unanswered, including the signal that stimulates the mild caspase activation, and the mechanism through which this activation stimulates enhanced proliferation.

The authors should consider answering additional questions, clarifying some points, and making some minor corrections:

Major concerns affecting the interpretation of experimental results:

Expression of STAT92E RNAi had no apparent effect on the ability of hinge cells to undergo NiA, leading the authors to conclude that other protective signals must exist. However, the authors have not shown that this STAT92E RNAi is capable of eliminating JAK/STAT signaling in the hinge under these experimental conditions. Using a reporter for JAK/STAT signaling, such as the STAT-GFP, as a readout would confirm the reduction or elimination of signaling. This confirmation would be necessary to support the negative result as presented.

Similarly, the authors should confirm that the Zfh2 RNAi is reducing or eliminating Zfh2 levels in the hinge under these experimental conditions, before concluding that Zfh2 does not play a role in stopping hinge cells from undergoing NiA.

EdU incorporation was quantified by measuring the fluorescence intensity of the pouch and normalizing it to the fluorescence intensity of the whole disc. However, the images show that EdU fluorescence intensity of other regions of the disc, especially the notum, varied substantially when comparing the different genetic backgrounds (for example, note the substantially reduced EdU in the notum of Figure 3 B' and B'). Indeed, it has been shown that tissue damage can lead to suppression of proliferation in the notum and elsewhere in the disc, unless the signaling that induces the suppression is altered. Therefore, the normalization may be skewing the results because the notum EdU is not consistent across samples, possibly because the damage-induced suppression of proliferation in the notum is different across the different genetic backgrounds.

The authors expressed p35 to attempt to generate "undead cells". They take an absence of mitogen secretion or increased proliferation as evidence that undead cells were not generated. However, there could be undead cells that do not stimulate proliferation non-autonomously, which could be detected by the persistence of caspase activity in cells that do not complete apoptosis. Indeed, expressing p35 and observing sustained effector caspase activation could help answer the later question of what percentage of this cell population would otherwise complete apoptosis (NiA, rescued by p35) vs reverse course and proliferate (NiCP, unaffected by p35).

It is unclear if the authors' model is that the NiCP cells lead to autonomous or non-autonomous cell proliferation, or both. Could the lineage-tracing experiments and/or the experiments marking mitosis relative to caspase activity answer this question?

Many of the conclusions rely on single images. Quantification of many samples should be included wherever possible.

Why does the reduction of Dronc appear to affect regenerative growth in females but not males?

Author response:

Reviewer #1 (Public Review):

Summary:

In previous work, the authors described necrosis-induced apoptosis (NiA) as a consequence of induced necrosis. Specifically, experimentally induced necrosis in the distal pouch of larval wing imaginal discs triggers NiA in the lateral pouch. In this manuscript, the authors confirmed this observation and found that while necrosis can kill all areas of the disc, NiA is limited to the pouch and to some extent to the notum, but is excluded from the hinge region. Interestingly and unexpectedly, signaling by the Jak/Stat and Wg pathways inhibits NiA. Further characterization of NiA by the authors reveals that NiA also triggers regenerative proliferation which can last up to 64 hours following necrosis induction. This regenerative response to necrosis is significantly stronger compared to discs ablated by apoptosis. Furthermore, the regenerative proliferation induced by necrosis is dependent on the apoptotic pathway because RNAi targeting the RHG genes is sufficient to block proliferation. However, NiA does not promote proliferation through the previously described apoptosis-induced proliferation (AiP) pathway, although cells at the wound edge undergo AiP. Further examination of the caspase levels in NiA cells allowed the authors to group these cells into two clusters: some cells (NiA) undergo apoptosis and are removed, while others referred to as Necrosis-induced Caspase Positive (NiCP) cells survive despite caspase activity. It is the NiCP cells that repair cellular damage including DNA damage and that promote regenerative proliferation. Caspase sensors demonstrate that both groups of cells have initiator caspase activity, while only the NiA cells contain effector caspase activity. Under certain conditions, the authors were also able to visualize effector caspase activity in NiCP cells, but the level was low, likely below the threshold for apoptosis. Finally, the authors found that loss of the initiator caspase Dronc blocks regenerative proliferation, while inhibiting effector caspases by expression of p35 does not, suggesting that Dronc can induce regenerative proliferation following necrosis in a non- apoptotic manner. This last finding is very interesting as it implies that Dronc can induce proliferation in at least two ways in addition to its requirement in AiP.

Strengths:

This is a very interesting manuscript. The authors demonstrate that epithelial tissue that contains a significant number of necrotic cells is able to regenerate. This regenerative response is dependent on the apoptotic pathway which is induced at a distance from the necrotic cells. Although regenerative proliferation following necrosis requires the initiator caspase Dronc, Dronc does not induce a classical AiP response for this type of regenerative response. In future work, it will be very interesting to dissect this regenerative response pathway genetically.

Weaknesses:

No weaknesses were identified.

We thank the reviewer for their positive evaluation and kind words.

Reviewer #2 (Public Review):

Summary / Strengths:

In this manuscript, Klemm et al., build on past published findings (Klemm et al., 2021) to characterize caspase activation in distal cells following necrotic tissue damage within the Drosophila wing imaginal disc. Previously in Klemm et al., 2021, the authors describe necrosis-induced-apoptosis (NiA) following the development of a genetic system to study necrosis that is caused by the expression of a constitutive active GluR1 (Glutamate/Ca2+ channel), and they discovered that the appearance of NiA cells were important for promoting regeneration.

In this manuscript, the authors aim to investigate how tissues regenerate following necrotic cell death. They find that the cells of the wing pouch are more likely to have non-autonomous caspase activation than other regions within the wing imaginal disc (hinge and notum),two signaling pathways that are known to be upregulated during regeneration, Wnt (wingless) and JAK/Stat signaling, act to prevent additional NiA in pouch cells, and may explain the region specificity, the presence of NiA cells promotes regenerative proliferation in late stages of regeneration, not all caspase-positive cells are cleared from the epithelium (these cells are then referred to as Necrosis-induced Caspase Positive (NiCP) cells), these NiCP cells continue to live and promote proliferation in adjacent cells, the caspase Dronc is important for creating NiA/NiCP cells and for these cells to promote proliferation. Animals heterozygous for a Dronc null allele show a decrease in regeneration following necrotic tissue damage.

The study has the potential to be broadly interesting due to the insights into how tissues differentially respond to necrosis as compared to apoptosis to promote regeneration.

Weaknesses:

However, here are some of my current concerns for the manuscript in its current version:

The presence of cells with activated caspase that don't die (NiCP cells) is an interesting biological phenomenon but is not described until Figure 5. How does the existence of NiCP cells impact the earlier findings presented? Is late proliferation due to NiA, NiCP, or both? Does Wg and JAK/STAT signaling act to prevent the formation of both NiA and NiCP cells or only NiA cells? Moreover, the authors are able to specifically manipulate the wound edge (WE) and lateral pouch cells (LP), but don't show how these manipulations within these distinct populations impact regeneration. The authors provide evidence that driving UAS-mir(RHG) throughout the pouch, in the LP or the WE all decrease the amount of NiA/NiCP in Figure 3G-O, but no data on final regenerative outcomes for these manipulations is presented (such as those presented for Dronc-/+ in Fig 7M). The manuscript would be greatly enhanced by quantification of more of the findings, especially in describing if the specific manipulations that impacted NiA /NiCP cells disrupt end-point regeneration phenotypes.

We thank the reviewer for their assessment and helpful suggestions to improve the manuscript. Regarding the presence of NiA and NiCP cells, and the proportion of each within a regenerating wing disc, unfortunately we are currently limited in our ability to distinguish each type of cell using available tools. This applies to both visualizing these cells via anti-cDcp-1 staining or the activity of GC3Ai, DBS-GFP and CasExpress, and detecting their function via their influence on proliferation. As such, although the identification of NiCP does not change any of the conclusions prior to Figure 5 in which NiCP are described, we are currently unable to comment on the contribution of NiA versus NiCP to late proliferation, or whether they are differently affected by Wg and JAK/STAT signaling. This issue is touched on in the discussion, but we will expand upon our commentary to better highlight these issues.

With respect to the reviewer’s suggestion to include evidence on whether blocking NiA/NiCP influences final regenerative outcomes, these data were published in our first paper on this work (Klemm et al., 2021, PMID: 34740246), which we will gladly reiterate in this work.

Finally, we agree that further quantification of our findings will strengthen the work, which is also suggested by Reviewer 3, and plan to add it where possible in a revised manuscript.

How fast does apoptosis take within the wing disc epithelium? How many of the caspase(+) cells are present for the whole 48 hours of regeneration? Are new cells also induced to activate caspase during this time window? The author presented a number of interesting experiments characterizing the NiCP cells. For the caspase sensor GC3Ai experiments in Figure 5, is there a way to differentiate between cells that have maintained fluorescent CG3Ai from cells that have newly activated caspase? What is the timeline for when NiA and NiCP are specified? In addition, what fraction of NiCP cells contribute to the regenerated epithelium? Additional information about the temporal dynamics of NiA and NiCP specification/commitment would be greatly appreciated.

Regarding the timing of apoptosis, Schott et al., 2017 (PMID:28870988) demonstrated that apoptotic GC3Ai-labeled cells in imaginal discs are extruded within 1 hr of labeling, the kinetics of which agree with previously published work on the temporal dynamics of apoptotic cell extrusion by Monier et al., 2015 (PMID:25607361). This is much faster than the continued labeling that we observe up to 64 hr post necrosis. We will include this information alongside a quantification of the percent of the wing pouch with GC3Ai-positive cells over time to better address whether the GC3Ai signal is maintained over time or if newly activated caspases account for the signal in late regenerating discs. We plan to include PH3 staining to distinguish between cells that have activated GC3Ai and are proliferating versus new caspase activity. Additionally, we plan to include new experimental evidence to evaluate the timing of GC3Ai-labelled apoptotic cell loss in our system.

The question of when NiA/NiCP are specified is difficult to address due to the issue of not being able to easily distinguish between these cell types. We previously attempted to answer this particular question, and also to determine what fraction of these cells contribute to the regenerated epithelium, using caspase-based lineage tracing with CasExpress. However, as shown in the paper, we are unable to label NiA/NiCP with CasExpress, either due to the lack of caspase activity level or subcellular localization. We are currently attempting to combine other caspase reporters with lineage tracing tools and examine late-stage wing discs to address these questions.

The notum also does not express developmental JAK/STAT, yet little NiA was observed within the notum. Do the authors have any additional insights into the differential response between the pouch and notum? What makes the pouch unique? Are NiA/NiCP cells created within other imaginal discs and other tissues? Are they similarly important for regenerative responses in other contexts?

As noted by Martin et al., 2017 (PMID:28935711), Martin & Morata, 2018 (PMID:29938762), and our own observations in Harris et al., 2016 (PMID:26840050), the notum does not respond to damage in a way that leads to regeneration, while the pouch does. As NiA/NiCP are a pro-regenerative response, we speculate that this intrinsic difference in regenerative capacity that is potentially caused by a different proliferative and genetic response to injury may account for the disparity in NiA/NiCP occurrence in the pouch vs the notum. A difference in the presence of the (currently unidentified) DAMPs or PRRs in notum vs pouch cells may also be responsible. Alternatively, since the hinge tissue is also refractory to NiA/NiCP due to the presence of genetic factors such as Wg and JAK/STAT, there may be an analogous pathway present in notum cells that acts to protect against the induction of pro-apoptotic factors. Indeed, caspase 3 activation does not seem to occur upon ablation of the notum (Bergantinos et al. 2010, PMID:20215351). We plan to add these points to the discussion.

Regarding the existence of NiA/NiCP in other contexts, we have additional data stemming from our clonal patch experiments (Figure S1) that demonstrates this phenomenon occurs in other imaginal discs, which we plan to include in the revised manuscript.

Reviewer #3 (Public Review):

The manuscript "Regeneration following tissue necrosis is mediated by non- apoptotic caspase activity" by Klemm et al. is an exploration of what happens to a group of cells that experience caspase activation after necrosis occurs some distance away from the cells of interest. These experiments have been conducted in the Drosophila wing imaginal disc, which has been used extensively to study the response of a developing epithelium to damage and stress. The authors revise and refine their earlier discovery of apoptosis initiated by necrosis, here showing that many of those presumed apoptotic cells do not complete apoptosis. Thus, the most interesting aspect of the paper is the characterization of a group of cells that experience mild caspase activation in response to an unknown signal, followed by some effector caspase activation and DNA damage, but that then recover from the DNA damage, avoid apoptosis, and proliferate instead. Many questions remain unanswered, including the signal that stimulates the mild caspase activation, and the mechanism through which this activation stimulates enhanced proliferation.

The authors should consider answering additional questions, clarifying some points, and making some minor corrections:

Major concerns affecting the interpretation of experimental results:

Expression of STAT92E RNAi had no apparent effect on the ability of hinge cells to undergo NiA, leading the authors to conclude that other protective signals must exist. However, the authors have not shown that this STAT92E RNAi is capable of eliminating JAK/STAT signaling in the hinge under these experimental conditions. Using a reporter for JAK/STAT signaling, such as the STAT-GFP, as a readout would confirm the reduction or elimination of signaling. This confirmation would be necessary to support the negative result as presented.

We thank the reviewer for their assessment and helpful suggestions to improve the manuscript. Although the knockdown of Stat92E using this RNAi line has been shown to produce phenotypes associated with loss of JAK/STAT signaling in previous papers (Monahan and Starz-Gaiano, 2014, 2016 PMID:26277564, 26993259), we agree it would be useful to demonstrate this in our hands and therefore plan to include these data.

Similarly, the authors should confirm that the Zfh2 RNAi is reducing or eliminating Zfh2 levels in the hinge under these experimental conditions, before concluding that Zfh2 does not play a role in stopping hinge cells from undergoing NiA.

We attempted to demonstrate the loss of Zfh2 using this RNAi line, but as noted by the reviewer the antibody staining appears mostly unchanged. A reduction in Zfh2 protein levels by this RNAi has previously been demonstrated in cells of the gut (Rojas Villa et al., 2019, PMID: 31841513), suggesting that the persistent Zfh2 staining we see could be due to perdurance of the Zfh2 protein, high levels of expression or high sensitivity of the Zfh2 antibody (or a combination of these factors). We plan to repeat the experiment using a longer knockdown duration prior to ablation to show a change in Zfh2, and/or test alternative RNAi lines. In the absence of these data, we will alter our conclusions to state that Zfh2 cannot be ruled out as playing a role in preventing NiA/NiCP formation in the hinge.

EdU incorporation was quantified by measuring the fluorescence intensity of the pouch and normalizing it to the fluorescence intensity of the whole disc. However, the images show that EdU fluorescence intensity of other regions of the disc, especially the notum, varied substantially when comparing the different genetic backgrounds (for example, note the substantially reduced EdU in the notum of Figure 3 B' and B'). Indeed, it has been shown that tissue damage can lead to suppression of proliferation in the notum and elsewhere in the disc, unless the signaling that induces the suppression is altered. Therefore, the normalization may be skewing the results because the notum EdU is not consistent across samples, possibly because the damage-induced suppression of proliferation in the notum is different across the different genetic backgrounds.

We agree with the reviewer that the use of EdU cannot distinguish between an increase in proliferation in the pouch versus a decrease in proliferation of the notum (or a combination of the two), since EdU incorporation by its nature is a relative rather than absolute measure of proliferation. However, we believe that the important finding is that a localized change in proliferation is observed late in necrosis, which is dependent on NiA/NiCP since blocking the formation of these cells prevents this change. While it is possible that this observed change is caused by a reduction in proliferation of the notum, with little or even no alteration in the pouch, this would imply that NiA/NiCP act to non-autonomously limit the proliferation of cells far from where they appear in the pouch, rather than causing localized proliferation in the immediately surrounding tissue that is representative of a blastema. Although we cannot rule this possibility out, our use of a different marker for proliferation in this work (fluorescent E2F) and a more objective proliferation marker, PH3, (Klemm et al., 2021, PMID: 34740246) agree with our observations made using EdU and suggest the formation of a localized blastema in the pouch. To attempt to address this issue, due to the variability of EdU staining between samples, we aim to quantify changes in EdU that are normalized to undamaged discs stained and mounted in the same sample, thus allowing a more objective background level of proliferation to be used for comparison.

The authors expressed p35 to attempt to generate "undead cells". They take an absence of mitogen secretion or increased proliferation as evidence that undead cells were not generated. However, there could be undead cells that do not stimulate proliferation non-autonomously, which could be detected by the persistence of caspase activity in cells that do not complete apoptosis. Indeed, expressing p35 and observing sustained effector caspase activation could help answer the later question of what percentage of this cell population would otherwise complete apoptosis (NiA, rescued by p35) vs reverse course and proliferate (NiCP, unaffected by p35).

While it is very possible that expression of P35 in NiA/NiCP could induce a previously uncharacterized type of undead cell that persists but does not secrete known AiP-related factors, the way in which P35 blocks activity of effector caspases (Drice and Dcp-1) precludes our ability to reliably detect and assay NiA/NiCP over time: P35 inactivates caspases by binding to their catalytic site, which causes cDcp-1 labeling to become weak and diffuse (Klemm et al 2021, PMID: 34740246), likely because the detectable epitope is in the catalytic site (Florentin & Arama, 2012. PMID: 22351928). Similarly, the GC3Ai reporter acts as a substrate for caspases and must be cleaved for fluorescence to occur (Zhang et al., 2013 PMID: 23857461). Thus, co-expressing P35 with GC3Ai actually reduces the number of NiA/NiCP cells labeled by GC3Ai and weakens cDcp-1 staining, preventing us from assaying their persistence or association with proliferative markers.

It is unclear if the authors' model is that the NiCP cells lead to autonomous or non-autonomous cell proliferation, or both. Could the lineage-tracing experiments and/or the experiments marking mitosis relative to caspase activity answer this question?

While we see GC3Ai-labeled NiA/NiCP in the same area of the pouch with high levels of proliferation (PH3), we observe a mixture of GC3Ai cells that overlapped the PH3 cells and GC3Ai cells that were adjacent to PH3(+) cells. Thus, we are unable to conclusively say whether proliferation is induced autonomously or non-autonomously. We have attempted to answer this question with lineage tracing, however NiA/NiCP are not labeled by the CasExpress tool, and we were unable to define a relationship between NiA/NiCP and proliferation through lineage tracing. However, we add further explanation of our findings to better clarify the proposed model of NiA/NiCP-induced proliferation.

Many of the conclusions rely on single images. Quantification of many samples should be included wherever possible.

As suggested by Reviewers 2 and 3 we plan to strengthen our findings by adding quantification of phenotypes where possible, in particular in Figure 2 as mentioned in the “Recommendations for the authors”.

Why does the reduction of Dronc appear to affect regenerative growth in females but not males?

We note that the effect on regenerative growth does appear to be present in males, but that the effect is not significant. We suspect that the lower n for this experiment is the cause, and are addressing this by repeating the experiment to increase the n.

eLife Assessment

This important study develops a high throughput version of expansion microscopy that can be performed in 96-well plates. The engineered technology is convincing and compatible with standard microplates and automated microscopes and thus will be of broad interest. The application to hiPCS-derived cardiomyocytes treated with doxorubicin provides a solid proof-of-concept demonstrating the potential for high-throughput analysis.

Reviewer #1 (Public review):

Summary

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

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

Strengths

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

Weaknesses

(1) It is still unclear to me whether or not cells that do not expand remain in the well given the response to point 1. The authors say the cells are digested and washed away but then say that there is a remaining signal from the unexpanded DNA in some cases. I believe this is still a concern that potential users of the protocol should be aware of.

(2) Regarding the response to point 9, I think this information should be included in the manuscript, possibly in the methods. It is important for others to have a sense of how long imaging may take if they were to adopt this method.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Addition upon revision:

The authors addressed this reviewer's suggestions.

Reviewer #3 (Public review):

Summary:

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

Addition upon revision:

Overall, the authors have adequately addressed most of the concerns raised. There are a few minor issues that require attention.

Minor comments:

Figure S10: There appears to be a discrepancy in the panel labeling. The current labels are E-H, but it is unclear whether panels A-D exist. Also, this reviewer thought that panels G and H would benefit from statistical testing to strengthen the conclusions. As a general rule for scientific graph presentation, the y-axis of all graphs should start at zero unless there is a compelling reason not to do so.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

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

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

Strengths: 

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

Weaknesses: 

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

The hydrogel footprint covers approximately 5% of the surface within an individual well and only cells within this area are embedded in the polymerized hydrogel for subsequent processing steps. Cells that are outside of this footprint are not incorporated into the gel because these cells are digested by Proteinase K and washed away by the excess water exchange in the gel swelling step. Note that different cell types may require higher or lower concentrations of Proteinase K to adequately digest cells for expansion while maintaining fluorescence signal. Given the compatibility of HiExM with 96-well plates, this titration can be performed rapidly in a single experiment. Although cells outside of the hydrogel footprint are removed prior to imaging, we do occasionally observe Hoechst signal that appears to be underneath the gels. We believe this signal is likely from excess DNA from digested cells that was not fully washed out in the gel swelling step. This signal is both spatially and morphologically distinct from the nuclear signal of intact cells and it does not affect image acquisition, analysis, or data interpretation. 

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

The variability in expansion factor across plates can likely be attributed to the small volume of gel solution (~250 nL) required for expansion within 96 well plates. Small variations in gel volume could impact gel polymerization compared to standard ExM gels. For example, gels in HiExM are more sensitive to evaporation because of the ~1000x reduced volume compared to standard expansion gel preparations, resulting in an increased air-liquid-interface. Evaporation in HiExM gels would increase monomer and cross linker concentrations, leading to variation in expansion factor across plates. We note that expansion factor is robust within well plates and that variance is slightly increased between plates. These considerations are discussed in the revised manuscript.

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

We did not show data using Alexa dyes because these fluorophores are highly sensitive to photobleaching using Irgacure and thus we could not obtain images. In contrast, some CF dyes are more robust to bleaching in HiExM including CF488A, CF568, and CF633 dyes.  We have recently adapted our protocol to PhotoExM chemistry which is compatible with a wider range of fluorophores as described by Günay et al. (2023) and as shown in Fig. S16.

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

We revised the legend for revised Fig. S11 (now Fig. S16) as follows: Example of a cell expanded in HiExM using Photo-ExM gel chemistry. Photo-ExM does not require an anoxic environment for gel deposition and polymerization, improving ease of use of HiExM. Mitochondria were stained with an Alexa 647 conjugated secondary antibody, demonstrating that HiExM is compatible with additional fluorophores when combined with Photo-ExM.

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

We imaged plates on the Opera Phenix using the PreciScan Acquisition Software in Harmony. In brief, each well is imaged at 5x magnification in the Hoechst channel to capture the full well at low resolution. Hoechst is used for this step given its signal brightness, ubiquity across established staining protocols, and spectral independence from most fluorophores commonly conjugated to secondary antibodies. Using this information, the microscope detects regions of interest (nuclei) based on criteria including size, brightness, circularity, etc. Finally, the positional information for each region is stored, and the microscope automatically images those regions at 63x magnification. The working distance for the objective used in this study is 600 µm which is sufficient to capture the entirety of expanded cells in the Z direction. This strategy minimizes offtarget imaging and allows robust image acquisition even in cultures with lower seeding density. A detailed description of the automated imaging strategy is included in the methods section of the revised manuscript.

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

Pre-expansion imaging is performed after staining is complete, but prior to the application of AcX, which is the first step of the HiExM protocol. Following staining and imaging, plates can be sealed with parafilm and stored at 4˚C for up to a week prior to starting the expansion protocol. We typically image 61 fields of view at the center of the well plate (where the gel will be deposited) to obtain sufficient pre-expansion images as shown in Figure 2b (left). After preexpansion imaging, we perform the HiExM protocol followed by image acquisition. We then tile all the images, as shown in Figure 2b, and compare tiled images from the same well pre- and post-expansion to manually identify the same cells. Comparisons of the pre- and postexpansion images of the same cell are used to calculate expansion factor and isotropy measurements as described. A detailed description of this process is included in the revised manuscript.

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

We performed the doxorubicin titration assay across four different well plates (n=4). For each condition, the total number of expanded nuclei measured was 118, 111, 110, 113, and 77 for DMSO, 1nM, 10nM, 100nM, and 1µM, respectively. For SEM calculations, we included the number of independent experiments to avoid underestimating error. We revised the Fig. 3 legend to include these experimental details.

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

For this analysis, the result is heavily dependent on the angle at which the edge of the nucleus intersects the image plane in the orthogonal view. For this reason, we opted to only use the optimal image plane for each nucleus. We repeated our analysis on an image using multiple optical sections to demonstrate this point. These new data are included as Fig. S11 of the revised manuscript.

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

The parameters that dictate imaging speed in HiExM include exposure time, z-stack height, and number of fluorophore channels. Depending on the signal intensity for a given channel, exposure times vary from 200ms to 1000ms. For z-stack height, we found that imaging 65 sections with 1µm spacing allowed for robust identification of each region of interest in the 5x pre-scan. As an example, collecting images for a full well plate (e.g., 20 images per well with 4 channels) requires approximately 24 hours of autonomous image acquisition using the Opera Phenix. Depending on cell size, this process yields imaging data for 1200 cells (1 cell per field of view) to 6000 cells (5 cells per field of view). Different autonomous imagers as well as improving staining techniques that increase signal:noise can be expected to significantly decrease the exposure time as it will reduce the number of z-stacks needed for each region.

Reviewer #2 (Public Review): 

Summary: 

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

Strengths: 

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

Weaknesses: 

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

We believe the data provide an example of the utility of HiExM that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.) by enabling easier sample processing and autonomous acquisition of thousands of nanoscale images in parallel. The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this work is to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of HiExM.

Reviewer #3 (Public Review):

Summary: 

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

Strengths: 

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

Weaknesses: 

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

The application we chose was intended as a methods proof-of-concept that could enable future deep biological investigations using HiExM. We believe the data provide an example of the utility of HiExM for collecting thousands of nanoscale images that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.). The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this experiment was to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of HiExM. 

The variability in expansion factor across plates can likely be attributed to the small volume (~250 nL) deposited by the device posts. Small variations in gel volume could impact gel polymerization compared to standard ExM gels. For example, HiExM gels are more sensitive to evaporation due to an increased air-liquid-interface because they are ~1000x smaller than standard expansion gel preparations. Evaporation in HiExM gels likely increases monomer and cross linker concentrations, leading to variation in expansion factor across plates. We note that expansion factor is robust within well plates and that the expansion factor can be more variable between plates, likely due to differences in gel volumes and evaporation. Future iterations of the platform are expected to control for these environmental conditions. These differences are discussed in the revised manuscript.

Recommendations for the authors:.

Reviewer #1 (Recommendations For The Authors):

(1) Please include a scale bar in Figure 3a.

A scale bar has been added to Figure 3a.

(2) Please show the data related to nuclear volume after dox treatment.

We have added a supplementary figure (Fig. S10) showing nuclear volume and sphericity for post-expansion nuclei as well as nuclear area and circularity for pre-expansion nuclei.

(3) I think it would be extremely helpful for the method as a whole if analysis code and files for device fabrication were made publicly available rather than upon request.

The analysis code has been included in the supplementary files as CM_Hoechst_Analysis_for publication.ipynb. Device design files are also available at the supplementary files link as hiExM_device.SLDPRT (96-well plate device) and MultiExM_24_July28_2022.SLDPRT (24-well plate device).

(4) Some details are missing from the methods, such as the concentration of AcX used for HiExM, the concentration of antibodies, etc. Related, how long does the photopolymerization take? Just the 60 seconds that the UVA light is on?

Additional protocol details are included in the methods section of the revised manuscript. The photopolymerization does only take 60 seconds.

Reviewer #2 (Recommendations For The Authors):

(1) The first three references are chosen a little strangely here. I suggest citing STED, SIM, and PALM/STORM from the original manuscripts here. Also, EM is technically not a super-resolution technique as it is within the resolution of electron beams. This reviewer would stay with light microscopy methods when discussing "super-resolution".

We removed the reference to EM and added citations to the original publications for SIM, STED, and STORM.

(2) The sentence after citation 4 is a little off in its meaning.

We have edited the sentence to improve clarity.

(3) It is highly useful and great that the authors include the observations on the effect of photopolymerization with Irgacure 2959 on dyes.

(4) In the discussion, the authors could mention new high NA silicone oil objectives that may further optimise the resolution in their scheme.

We added a sentence in the discussion to reflect this important point.

(5) The files for the manufacture of the HiExM devices must be in the supplementary data rather than available on request.

The Solidworks designs for the 96 and 24 well plate devices are included in the supplementary files as hiExM_device.SLDPRT and MultiExM_24_July28_2022.SLDPRT, respectively.

(6) It would be useful if the authors could discuss their thoughts on the high throughput processing of expansion factors in the data analysis routine.

We added details to the methods section describing how images are processed and analyzed.

Reviewer #3 (Recommendations For The Authors):

Major:

(1) In the experiments depicted in Figure 3, the authors attempted cellular phenotyping using hiPCS-derived cardiomyocytes treated with doxorubicin (dox). They addressed that the relative intensity of Hoechst at the nuclear periphery increased solely in post-expansion images, although this trend is not clearly evidenced in the provided data (e.g., DMSO control vs. 1 nM dox, Figure 3b). Moreover, this observed phenomenon lacks clear biological significance and may not be suitable as a demonstration for proof-of-concept (POC) acquisition. It is crucial to delineate the biological processes linked with the specific enhancement of DNA binding dye signals in the nuclear periphery and how to rule out the possibility of heterogeneous redistribution of nuclear components rather than enhancing resolution. For instance, if this change can be associated with a biological process such as DNA damage, quantitative detection of the accumulated proteins related to DNA repair, or the specific histone marks, may be more suitable and less susceptible to heterogeneous expansion factors. Additionally, the authors noted the absence of significant changes in nuclear volume, yet the corresponding data was not presented. Moreover, the application insufficiently demonstrated the HiExM's scalable feature employing various well plates. If only acquiring images of dozens of nuclei (Figure 3 legend, p15), a single well per condition would suffice. Therefore, it is necessary to elucidate why this application necessitates a 96-well format for demonstration purposes. The potential experimental design should also incorporate the requirement for well-to-well replication and the acquisition of features at the individual well level, rather than at the single-cell level. Also, related to Figure S10, whether outer gradient slope, but not inner gradient slope, is linked to apoptosis (Page 8, Line 2-4) remains unclear in the H2O2-treated cells.

We believe the data provide an example of the utility of HiExM that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.) by enabling easier sample processing and autonomous acquisition of thousands of nanoscale images in parallel. The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this work is to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of the HiExM method. As discussed in the manuscript, dox treatment is associated with DNA damage, cellular stress, and apoptosis, and commonly observed at high dox concentrations (>200 nM) in in vitro studies using conventional microscopy. Our data suggest that cardiomyocytes exhibit sensitivity to lower concentrations of dox than previously anticipated. Although direct evidence specifically linking dox to increased DNA condensation at the nuclear periphery is limited, the known proapoptotic effects of dox strongly suggest that our observations correlate with these changes. We have now included the data analysis on nuclear morphology in revised Fig. S10. We agree that deeper biological interpretation of the observed changes in Hoechst signal upon dox treatment (or other cellular stressors such as H2O2) using HiExM and whether these changes are correlated with DNA damage or other cellular alterations remains an exciting future direction to develop a more sensitive platform for assessing drug responses.

For expanded samples, we performed the doxorubicin titration assay across four different well plates (n=4). For each condition, the total number of nuclei measured was 118, 111, 110, 113, and 77 for DMSO, 1nM, 10nM, 100nM, and 1µM, respectively. We apologize for the confusion with respect to the number of replicates and cells analyzed. For SEM calculations, we used the number of independent experiments to avoid underestimating error. 

(2) In Figure 2b, do the orange arrows indicate the same cell with a unique shape in both the pre- and post-expansion images? Additionally, in Figure 3b, why do the pre- and post-expansion nuclei exhibit such different global shapes? Considering that the gel may freely rotate within the well during expansion, it raises doubts about whether one can identify cells with consistent shapes in both the pre- and post-expansion images. Furthermore, this reviewer observed a similar issue regarding reproducibility among different well plates, as shown in Figure 2h. The panel illustrates that different plates yielded distinct populations of gel sizes. The expansion factors provided in the figure legend (page 13) ranged from 3.5x to 5.1x across gels, indicating a relatively large variation in expansion size. What is the reason behind these variations, and how can they be minimized? These variations could become critical when considering large-scale screening across multiple plates.

The orange arrow is intended to indicate the same cell with a unique shape in both the pre- and post-expansion images, albeit at a different orientation given that the gel is not fixed within the well. We agree that improved methods to identify the same cells pre- and post-expansion could facilitate error measurements. We have referenced recent methods that could be combined with HiExM to automate and improve error and distortion detection to the discussion of the revised manuscript. 

Fig. 2 illustrates the ability of HiExM to achieve reproducible gel formation with minimal error within gels, wells, and across plates, measurements consistent with proExM. While uniform within gels, the expansion factor is somewhat variable between gels and plates. We attribute these differences primarily to the small size of the gels, making them vulnerable to the effects of evaporation between experiments. We note this variability should be taken into consideration for studies where absolute length measurements between plates are important for biological interpretation. Future iterations of the platform that allow precise delivery of gel volumes and that minimizes environmental exposure are expected to improve the expansion factor reproducibility across plates to further enable the use of HiExM as a tool for high-throughput nanoscale imaging.

Minor:

(1) Considering the signal loss due to photobleaching and fluorophore dilution during expansion, protein imaging may occasionally lack the sensitivity required to detect subtle morphological changes in cellular machinery. This potential limitation should be addressed or discussed in the text.

A sentence reflecting this point has been added to the manuscript.

(2) On page 15, the figure legend for panel d states, "Heatmaps of nuclei in b showing..." However, it appears that the panel referred to in this sentence corresponds to panel c.

The typo has been fixed.

(3) The type of glass 96-well plate utilized in this study should be specified, as the quality of the product could impact the expansion results.

The supplier and product number of the well plate used in our study has been added to the methods section.

(4) In Figure S3, the raw pixel values of CF305 dye are exceptionally low. Is there a specific reason for the very low signals observed when using this dye?

CF® 350 (305 was a typo) does not excite well at 405 nm, which is the excitation wavelength for the channel we used.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

In their manuscript, Gan and colleagues identified a functional critical residue, Tyr404, which when mutated to W or A results in GOF and LOF of TRPML1 activity, respectively. In addition, the authors provide a high-resolution structure of TRPML1 with PI(4,5)P2 inhibitor. This high-resolution structure also revealed a bound phospholipid likely sphingomyelin at the agonist/antagonist site, providing a plausible explanation for sphingomyelin inhibition of TRPML1.

This is an interesting study, revealing valuable additional information on TRPML1 gating mechanisms including effects on endogenous phospholipids on channel activity. The provided data are convincing. Some major open questions remain. The work will be of interest to a wide audience including industry researchers occupied with TRPML1 exploration as a drug target.

We appreciate reviewer #1’s positive comments and the specific points raised by this reviewer are addressed in our response to Recommendations For The Authors

Reviewer #2 (Public Review):

The transient receptor potential mucolipin 1 (TRPML1) functions as a lysosomal organelle ion channel whose variants are associated with lysosomal storage disorder mucolipidosis type IV. Understanding sites that allosterically control the TRPML1 channel function may provide new molecular moieties to target with prototypic drugs.

Gan et al provide the first high-resolution cryo-EM structures of the TRPML1 channel (Y404W) in the open state without any activating ligands. This new structure demonstrates how a mutation at a site some distance away from the pore can influence the channel's conducting state. However, the authors do not provide a structural analysis of the Y404W pore which would validate their open-state claims. Nonetheless, Gan et al provide compelling electrophysiology evidence which supports the proposed Y404W gain of function effect. The authors propose an allosteric mechanism with the following molecular details- the Y404 to W sidechain substitution provides extra van der Waals contacts within the pocket surrounded by helices of the VSD-like domain and causes S4 bending which in turn opens to the pore through the S4-S5 linker. Conversely, the author functionally demonstrates that an alanine mutation at this site causes a loss of function. Although the authors do not provide a structure of the Y404A mutation, they propose that the alanine substitution disrupts the sidechain packing and likely destabilizes the open conformation. TRPM1 channels are regulated by PIP2 species, which is related to their cell function. In the membrane of lysosomes, PI(3,5)P2 activates the channel, whereas PI(4,5)P2 found in the plasma membrane has inhibitory effects. To understand its lipid regulation, the authors solved a cryo-EM structure of TRPM1 bound to PI(4,5)P2 in its presumed closed state. Again, while the provided functional evidence suggests that PI(4,5)P2 occupancy inhibits TRPML1 current, the authors do not provide analysis of the pore which would support their closed state assertion. Within this same structure, the authors observe a density that may be attributed to sphingomyelin (or possibly phosphocholine). Using electrophysiology of WT and the Y404W channels, the authors report sphingomyelins antagonist effect on TRPML1 currents under low luminal (external) pH. Taken together, the results described in Gan et al provide compelling evidence for a gating (open, closed) mechanism of the TRPML1 pore which can be allosterically regulated by altered packing and lipid interactions within the VSDL.

We appreciate reviewer #2’s positive comments and constructive suggestions. We functionally demonstrated that the Y404A mutant is more stable in the closed state. We did not pursue the structure of this mutant as we expect its structure will be the same as the apo closed TRPML1. To verify the open conformation of the Y404W mutant and the closed conformation of PI(4,5)P2 –bound TRPML1, we analyzed the pore radii of our structures in the revision as suggested by the reviewer and compared them with open and closed pores from previously determined TRPML1. Some specific points raised by this reviewer are addressed in our response to Recommendations For The Authors

Reviewer #1 (Recommendations For The Authors):

(1) Mutations in TRPML1 cause Mucolipidosis type IV. One patient mutation reported earlier (Chen et al., 2014 https://pubmed.ncbi.nlm.nih.gov/25119295/) to be a LOF mutation is R403C. This mutation resides just next to the here-identified Y404 position which can be converted in either LOF or GOF. Another patient mutation, F408del (also reported previously: (Chen et al., 2014 https://pubmed.ncbi.nlm.nih.gov/25119295/)) results in a mild activity reduction, in particular of the PI(3,5)P2 effect. Can the authors please discuss their findings in the context of the reported literature on these patient mutations and provide explanations as to why this part of the TRPML1 protein seemingly is such a hotspot for mutations affecting channel activity and how they explain this based on their structural evidence? What characteristics would be required for a small molecule agonist of TRPML1 in order to elicit larger activation in these patient LOF mutations if possible?

We thank the reviewer for highlighting these mutations identified in human patients. R403 appears to play two key roles. Firstly, its side chain participates in stabilizing Y404 in the open state. Secondly, as demonstrated in our previous study on TRPML1 (PMID: 35131932), the R403 side chain points towards the PI(3,5)P2 binding pocket, where it forms a critical salt bridge with the C3 phosphate group in the open state. Therefore, R403C mutation likely abolishes PI(3,5)P2 activation and also destabilizes the open state, resulting in the loss of function of the channel. We have expanded our discussion on this mutation in the revision. F408 is positioned at the junction between S4 and the S4-S5 linker. Its deletion mutation could change the stability or the folding of the protein. It is difficult to speculate the exact cause of the F408Δ LOF based on the TRPML1 structure. We don’t feel the effect of this mutation is relevant to the findings of this study.

(2) The authors used ML-SA1 only as a basis for their claims. Could they possibly provide some key data also on alternative small molecule agonists such as SF-51 and/or MK6-83?

We thank the reviewer for this suggestion. The TRPML1 agonists such as  ML-SA1 (derived from SF-51) and  MK6-83 have been well characterized in previous studies. In our study of sphingomyelin effect on TRPML1 activity, we used SF-51 to activate the channel (Figure 4b). The goal of our study is to demonstrate that agonist and antagonist can still allosterically regulate the LOF Y404A and GOF Y404W mutant channels, respectively, and their competition with sphingomyelin. We chose ML-SA1 in our experiment simply because it has been a commonly used TRPML1 agonist and its binding has been structurally defined, allowing us to compare various TRPML1 structures with different ligands. We don’t feel the use of other agonists would add extra information to our findings.  

(3) Sphingomyelin effects on TRPML1 have been confirmed by other groups as well (see e.g. Prat Castro et al., 2022 https://pubmed.ncbi.nlm.nih.gov/36139381/ Fig.3. Interestingly TPC2 seems unaffected by sphingomyelin albeit it is also activated by PI(3,5)P2. Can the authors provide possibly some modeling and/or cryoEM data on TPC2 with sphingomyelin to potentially explain why TPC2 is seemingly unaffected by sphingomyelin?

We appreciate the reviewer for providing additional evidence of sphingomyelin's effects on TRPML1 and have included the reference in revision. The binding site and activation mechanism of PI(3,5)P2 are different between TPC2 and TRPML1. It is beyond the scope of this study and also too speculative to model sphingomyelin binding (if any) in TPC2 to explain its lack of effect on TPC2 activity.

Reviewer #2 (Recommendations For The Authors):

The findings from Gan et al provide structural insights into the allosteric regulation of TRPML1 channel gating. The authors have provided compelling and hard-won cryo-EM structural evidence of the channel regulation by PI4,5P2 and at sites that pack the gating pore of the VSDL (S4). However, as noted in the public review, the analysis of the cryo-EM structures that would support claims of open and closed channel states is woefully lacking. Additional information related to the functional results is required to evaluate the activation and inhibition kinetic effect of lipids and pharmacological agents used to support their allosteric mechanism of TRPML1 gating.

Major concerns:

(a) At the very least, the pore domains of the new channels (PDB 9CBZ and 9CC2) should be analyzed using the HOLE (or other) programs to estimate the distances along the ion-conducting pathway - are the structures wide enough to support the passage of hydrated or partially hydrated cations? Additional figure panels should provide this comparative analysis.

We thank the reviewer for this valuable suggestion. We have added a figure (Figure Supplement 3b) of pore domain radius analysis using the HOLE program in the revision and have also included the radius comparison with previous determined open and closed TRPML1 structures.  

(b) At the very least, all current traces (Figures 1C, 1D, 1E, 4B, 4C) should be accompanied by time course plots of current amplitudes. It is impossible to evaluate the authors' claims of lipid and drug effects on TRPML1 channels without this information.

The corresponding time course plots of current amplitudes have now been included in the revision as Figure Supplement 1 and 7.

(c) Regarding the gain of function Y404W mutation structure, the authors' allosteric mechanistic hypothesis centers on side chain packing details within the VSD-like domain S4 (which in turn opens the pore through the S4-S5 linker). However, the local resolution within the structures at this site is not described. To assess the veracity of these claims, at the very least, authors should provide electron density maps of this region, either in Figure 2 or in Figure Supplement 4.

We have included the electron density map and local resolution information surrounding the W404 residue from the Y404W GOF mutant structure in the revision as  Figure Supplement 3c.

Minor concerns:

(d) Additional evidence related to the identity of the pore domain-associated lipid density (PC or sphingomyelin), and its channel regulation would improve the manuscript. The authors examine sphingomyelin, but what is the functional impact of PC on TRPML1 currents? While this is suggested, it is at the authors' discretion whether or not to carry out this analysis.

We thank the reviewer for raising this question. Adding extra PC has no effect on TRPML1 activity. This is expected since PC is the major lipid component of the membrane.

(e) The manuscript is well written. However, a few errors were noted while reviewing this draft.

i. Line 138, (Figure F&G).

ii. Line 66, "signaling transduction".

These errors have now been corrected.

eLife Assessment

Transient receptor potential mucolipin 1 (TRPML1) functions as a lysosomal ion channel whose variants are associated with lysosomal storage disorder mucolipidosis type IV. This important report describes local and global structural changes driven by binding of regulatory phospholipids and by mutations that allosterically cause gain or loss of channel function. Most of the claims related to the allosteric regulation of TRPML1 are convincingly supported by two new cryo-EM structures which are evaluated within the context of previously reported TRPML1 structures, and a proposed allosteric gating mechanism is partially supported by functional electrophysiology results.

Joint Public Review:

TRPML1 functions as a lysosomal ion channel whose variants are associated with lysosomal storage disorder mucolipidosis type IV. Understanding the structure and function of sites involved in the allosteric control TRPML1 may provide new molecular moieties to target with prototypic drugs.

Gan et al provide the first high resolution cryo-EM structure of a mutant (Y404W) TRPML1 channel in the open state without any activating ligands. This new structure demonstrates how a mutation at a site some distance away from the pore can influence channel gating. The authors provide compelling electrophysiology evidence which supports the proposed Y404W gain of function effect.

The authors propose an allosteric mechanism whereby the engineered W404 sidechain provides extra van der Waals contacts within a pocket surrounded by helices of the voltage sensor-like domain (VSLD) and causes S4 bending which in turn opens the pore through the S4-S5 linker. Conversely, the authors functionally demonstrate that an alanine mutation at this site causes a loss of function. Although the authors do not provide a structure of the Y404A mutant, they propose that the alanine substitution disrupts the sidechain packing and likely destabilizes the open conformation.

TRPML1 channels are regulated by PIP2 species in the cell. In the lysosomal membrane, PI(3,5)P2 activates the channel, whereas in the plasma membrane PI(4,5)P2 inhibits it. Towards understanding its lipid regulation, the authors solve a cryo-EM structure of TRPML1 bound to PI(4,5)P2 in the closed state and provide functional evidence that PI(4,5)P2 occupancy inhibits TRPML1 currents.

Within this same structure, the authors observe a density which may be attributed to sphingomyelin (or possibly phosphocholine). Using electrophysiology on WT and Y404W channels, the authors report an antagonist effect of sphingomyelin on TRPML1 currents.

Taken together, the study provides convincing evidence for a gating (opening/closing) mechanism of the TRPML1 pore which can be allosterically regulated by altered side-chain packing and by lipid interactions within the VSLD.

eLife Assessment

This valuable study describes an apparatus, workflow, and proof-of-concept data for a system to study social cooperation in marmosets, an increasingly popular primate model for neuroscience. The apparatus and methodology have clear and convincing advantages over conventional methods based on manual approaches. However, claims of faster social learning or of finer-grained behavioural analysis in this setup will require further corroboration.

Reviewer #1 (Public Review):

Summary:

This manuscript by Meissner and colleagues described a novel take on a classic social cognition paradigm developed for marmosets. The classic pull task is a powerful paradigm that has been used for many years across numerous species, but its analog approach has several key limitations. As such, it has not been feasible to adopt the task for neuroscience experiments. Here the authors capture the spirit of the classic task but provide several fundamental innovations that modernize the paradigm - technically and conceptually. By developing the paradigm for marmosets, the authors leverage the many advantages of this primate model for studies of social brain functions and their particular amenability to freely-moving naturalistic approaches.

Strengths:

The current manuscript describes one of the most exciting paradigms in primate social cognition to be developed in many years. By allowing for freely-moving marmosets to engage in high numbers of trials, while precisely quantifying their visual behavior (e.g. gaze) and recording neural activity this paradigm has the potential to usher in a new wave of research on the cognitive and neural mechanisms underlying primate social cognition and decision-making. This paradigm is an elegant illustration of how naturalistic questions can be adapted to more rigorous experimental paradigms. Overall, I thought the manuscript was well written and provided sufficient details for others to adopt this paradigm.

Reviewer #2 (Public Review):

Summary:

This important work by Meisner et al., developed an automated apparatus (MarmoAPP) to collect a wide array of behavioral data (lever pulling, gaze direction, vocalizations) in marmoset monkeys, with the goal of modernizing collection of behavioral data to coincide with the investigation of neurological mechanisms governing behavioral decision making in an important primate neuroscience model. The authors show a variety of "proof-of-principle" concepts that this apparatus can collect a wide range of behavioral data, with higher behavioral resolution than traditional methods. For example, the authors highlight that typical behavioral experiments on primate cooperation provide around 10 trials per session, while using their approach the authors were able to collect over 100 trials per 20-minute session with the MarmoAAP.

Overall the authors argue that this approach has a few notable advantages:

(1) It enhances behavioral output which is important for measuring small or nuanced effects/changes in behavior;

(2) Allows for more advanced analyses given the higher number of trials per session;

(3) Significantly reduces the human labor of manually coding behavioral outcomes and experimenter interventions such as reloading apparatuses for food or position;

(4) Allows for more flexibility and experimental rigor in measuring behavior and neural activity simultaneously.

Strengths:

The paper is well-written and the MarmoAPP appears to be highly successful at integrating behavioral data across many important contexts (cooperation, gaze, vocalizations), with the ability to measure significantly many more behavioral contexts (many of which the authors make suggestions for).

The authors provide substantive information about the design of the apparatus, how the apparatus can be obtained via a long list of information Apparatus parts and information, and provide data outcomes from a wide number of behavioral and neurological outcomes. The significance of the findings is important for the field of social neuroscience and the strength of evidence is solid in terms of the ability of the apparatus to perform as described, at least in marmoset monkeys. The advantage of collecting neural and freely-behaving behavioral data concurrently is a significant advantage.

Reviewer #3 (Public Review):

Summary:

The authors set out to devise a system for the neural and behavioral study of socially cooperative behaviors in nonhuman primates (common marmosets). They describe instrumentation to allow for a "cooperative pulling" paradigm, the training process, and how both behavioral and neural data can be collected and analyzed. This is a valuable approach to an important topic, as the marmoset stands as a great platform to study primate social cognition. Given that the goals of such a methods paper are to (a) describe the approach and instrumentation, (b) show the feasibility of use, and (c) quantitatively compare to related approaches, the work is easily able to meet those criteria. My specific feedback on both strengths and weaknesses is therefore relatively limited in scope and depth.

Strengths:

The device is well-described, and the authors should be commended for their efforts in both designing this system but also in "writing it up" so that others can benefit from their R&D.

The device appears to generate more repetitions of key behavior than other approaches used in prior work (with other species).

The device allows for quantitative control and adjustment to control behaviour.

The approach also supports the integration of markerless behavioral analysis as well as neurophysiological data.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Summary:

This manuscript by Meissner and colleagues described a novel take on a classic social cognition paradigm developed for marmosets. The classic pull task is a powerful paradigm that has been used for many years across numerous species, but its analog approach has several key limitations. As such, it has not been feasible to adopt the task for neuroscience experiments. Here the authors capture the spirit of the classic task but provide several fundamental innovations that modernize the paradigm - technically and conceptually. By developing the paradigm for marmosets, the authors leverage the many advantages of this primate model for studies of social brain functions and their particular amenability to freely-moving naturalistic approaches.

Strengths:

The current manuscript describes one of the most exciting paradigms in primate social cognition to be developed in many years. By allowing for freely-moving marmosets to engage in high numbers of trials, while precisely quantifying their visual behavior (e.g. gaze) and recording neural activity this paradigm has the potential to usher in a new wave of research on the cognitive and neural mechanisms underlying primate social cognition and decision-making. This paradigm is an elegant illustration of how naturalistic questions can be adapted to more rigorous experimental paradigms. Overall, I thought the manuscript was well written and provided sufficient details for others to adopt this paradigm. I did have a handful of questions and requests about topics and information that could help to further accelerate its adoption across the field.

Weaknesses:

LN 107 - Otters have also been successful at the classic pull task (https://link.springer.com/article/10.1007/s10071-017-1126-2)

We have added this reference to the manuscript.

LN 151 - Can you provide a more precise quantification of timing accuracy than the 'sub-second level'. This helps determine synchronization with other devices.

We have included more precise timing details, noting that data is stored at the millisecond level.

Using this paradigm, the marmosets achieved more trials than in the conventional task (146 vs 10). While this is impressive, given that only ~50 are successful Mutual Cooperation trials it does present some challenges for potential neurophysiology experiments and particular cognitive questions. The marmosets are only performing the task for 20 minutes, presumably because they become sated and are no longer motivated. This seems a limitation of the task and is something worth discussing in the manuscript. Did the authors try other food rewards, reduce the amount of reward, food/water restrict the animals for more than the stated 1-3 hours? How might this paradigm be incorporated into in-cage approaches that have been successful in marmosets? Any details on this would help guide others seeking to extend the number of trials performed each day.

We have added a discussion addressing the use of liquid rewards, minimal food and water restriction, and the potential for further optimization to increase task engagement and trial numbers. This is now reflected in the revised manuscript.

Can you provide more details on the DLC/Anipose procedure? How were the cameras synchronized? What percentage of trials needed to be annotated before the model could be generalized? Did each monkey require its own model, or was a single one applied to all animals?

We have added more detailed information on the DLC and Anipose tracking which can be found in the Multi-animal 3D tracking section under Materials & Methods.

Will the schematics and more instructions on building this system be made publicly available? A number of the components listed in Table 1 are custom-designed. Although it is stated that CAD files will be made available upon request, sharing a link to these files in an accessible folder would significantly add to the potential impact of this paradigm by making it easier for others to adopt.

We have made the SolidWorks CAD files publicly available. They can now be found in the Github repository alongside the apparatus and task code.

In the Discussion, it would be helpful to have some discussion of how this paradigm might be used more broadly. The classic pulling paradigm typically allows one to ask a specific question about social cognition, but this task has the potential to be more widely applied to other social decision-making questions. For example, how might this task be adopted to ask some of the game-theory-type approaches common in this literature? Given the authors' expertise in this area, this discussion could serve to provide a roadmap for the broader field to adopt.

Although this paradigm was developed specifically for marmosets, it seems to me that it could readily be adopted in other species with some modifications. Could the authors speak to this and their thoughts on what may need to be changed to be used in other species? This is particularly important because one of the advantages of the classic paradigm is that it has been used in so many species, providing the opportunity to compare how different species approach the same challenge. For example, though both chimps and bonobos are successful, their differences are notably illuminating about the nuances of their respective social cognitive faculties.

We have expanded the discussion for the broader applications of this apparatus both for other decision-making research questions as well as its adaptability for use in other species.

Reviewer #2 (Public Review):

Summary:

This important work by Meisner et al., developed an automated apparatus (MarmoAPP) to collect a wide array of behavioral data (lever pulling, gaze direction, vocalizations) in marmoset monkeys, with the goal of modernizing collection of behavioral data to coincide with the investigation of neurological mechanisms governing behavioral decision making in an important primate neuroscience model. The authors show a variety of "proof-of-principle" concepts that this apparatus can collect a wide range of behavioral data, with higher behavioral resolution than traditional methods. For example, the authors highlight that typical behavioral experiments on primate cooperation provide around 10 trials per session, while using their approach the authors were able to collect over 100 trials per 20-minute session with the MarmoAAP.

Overall the authors argue that this approach has a few notable advantages:<br /> (1) it enhances behavioral output which is important for measuring small or nuanced effects/changes in behavior;<br /> (2) allows for more advanced analyses given the higher number of trials per session;<br /> (3) significantly reduces the human labor of manually coding behavioral outcomes and experimenter interventions such as reloading apparatuses for food or position;<br /> (4) allows for more flexibility and experimental rigor in measuring behavior and neural activity simultaneously.

Strengths:

The paper is well-written and the MarmoAPP appears to be highly successful at integrating behavioral data across many important contexts (cooperation, gaze, vocalizations), with the ability to measure significantly many more behavioral contexts (many of which the authors make suggestions for).

The authors provide substantive information about the design of the apparatus, how the apparatus can be obtained via a long list of information Apparatus parts and information, and provide data outcomes from a wide number of behavioral and neurological outcomes. The significance of the findings is important for the field of social neuroscience and the strength of evidence is solid in terms of the ability of the apparatus to perform as described, at least in marmoset monkeys. The advantage of collecting neural and freely-behaving behavioral data concurrently is a significant advantage.

Weaknesses:

While this paper has many significant strengths, there are a few notable weaknesses in that many of the advantages are not explicitly demonstrated within the evidence presented in the paper. There are data reported (as shown in Figures 2 and 3), but in many cases, it is unclear if the data is referenced in other published work, as the data analysis is not described and/or self-contained within the manuscript, which it should be for readers to understand the nature of the data shown in Figures 2 and 3.

(1) There is no data in the paper or reference demonstrating training performance in the marmosets. For example, how many sessions are required to reach a pre-determined criterion of acceptable demonstration of task competence? The authors reference reliably performing the self-reward task, but this was not objectively stated in terms of what level of reliability was used. Moreover, in the Mutual Cooperation paradigm, while there is data reported on performance between self-reward vs mutual cooperation tasks, it is unclear how the authors measured individual understanding of mutual cooperation in this paradigm (cooperation performance in the mutual cooperation paradigm in the presence or absence of a partner; and how, if at all, this performance varied across social context). What positive or negative control is used to discern gained advantages between deliberate cooperation vs two individuals succeeding at self-reward simultaneously?

Thank you for your comment. This Tools & Resources paper is focused solely on the development of the apparatus and methods. Future publications will provide more details on training performance, learning behaviors, and include appropriate controls to distinguish deliberate cooperation from simultaneous success in self-reward tasks.

(2) One of the notable strengths of this approach argued by the authors is the improved ability to utilize trials for data analysis, but this is not presented or supported in the manuscript. For example, the paper would be improved by explicitly showing a significant improvement in the analytical outcome associated with a comparison of cooperation performance in the context of ~150 trials using MarmoAAP vs 10-12 trials using conventional behavioral approaches beyond the general principle of sample size. The authors highlight the dissection of intricacies of behavioral dynamics, but more could be demonstrated to specifically show these intricacies compared to conventional approaches. Given the cost and expertise required to build and operate the MarmoAAP, it is critical to provide an important advantage gained on this front. The addition of data analysis and explicit description(s) of other analytical advantages would likely strengthen this paper and the advantages of MarmoAAP over other behavioral techniques.

Thank you for the suggestion. While this manuscript focuses on the apparatus and methods, the increase in trial numbers itself provides clear advantages, including greater statistical power and more robust analyses of behavioral dynamics. Future publications will offer more in-depth analyses comparing the performance and cooperation behavior observed with MarmoAAP, further demonstrating these analytical benefits.

Reviewer #3 (Public Review):

Summary:

The authors set out to devise a system for the neural and behavioral study of socially cooperative behaviors in nonhuman primates (common marmosets). They describe instrumentation to allow for a "cooperative pulling" paradigm, the training process, and how both behavioral and neural data can be collected and analyzed. This is a valuable approach to an important topic, as the marmoset stands as a great platform to study primate social cognition. Given that the goals of such a methods paper are to (a) describe the approach and instrumentation, (b) show the feasibility of use, and (c) quantitatively compare to related approaches, the work is easily able to meet those criteria. My specific feedback on both strengths and weaknesses is therefore relatively limited in scope and depth.

Strengths:

The device is well-described, and the authors should be commended for their efforts in both designing this system but also in "writing it up" so that others can benefit from their R&D.

The device appears to generate more repetitions of key behavior than other approaches used in prior work (with other species).

The device allows for quantitative control and adjustment to control behavior.

The approach also supports the integration of markerless behavioral analysis as well as neurophysiological data.

Weaknesses:

A few ambiguities in the descriptions are flagged below in the "Recommendations for authors".

The system is well-suited to marmosets, but it is less clear whether it could be generalized for use in other species (in which similar behaviors have been studied with far less elegant approaches). If the system could impact work in other species, the scope of impact would be significantly increased, and would also allow for more direct cross-species comparisons. Regardless, the future work that this system will allow in the marmoset will itself be novel, unique, and likely to support major insights into primate social cognition.

Thank you for this feedback. We have expanded the discussion to include how the apparatus could be adapted for use in other species, highlighting the potential modifications required, such as adjusting the size and strength of the servo motor and components. These changes would enable broader applications and facilitate cross-species comparisons.

eLife Assessment

This study introduces a useful extension to a recently proposed model of neural assembly activity. The extension was to add recurrent connections to the hidden units of the Restricted Boltzmann Machine. The authors show solid evidence that the new model outperforms their earlier model on both a simulated dataset and on whole-brain neural activity from zebrafish.

Reviewer #1 (Public review):

Summary:

Understanding large-scale neural activity remains a formidable challenge in neuroscience. While several methods have been proposed to discover the assemblies from such large-scale recordings, most of previous studies do not explicit modeling the temporal dynamics. This study is an attempt to uncover the temporal dynamics of assemblies using a tool that have been establish in other domains.

The authors previously introduced the compositional Restricted Boltzmann Machine (cRBM) to identify neuron assemblies in zebrafish brain activity. Building upon this, they now employ the Recurrent Temporal Restricted Boltzmann Machine (RTRBM) to elucidate the temporal dynamics within these assemblies. By introducing recurrent connections between hidden units, RTRBM could retrieve neural assemblies and their temporal dynamics from simulated and zebrafish brain data.

Strengths:

The RTRBM has been previously used in other domains. Training the model has been already established. This study is an application of such model to neuroscience. Overall, the paper is well-structured and the methodology is robust, the analysis is solid to support the authors claim.

Weaknesses:

The overall degree of advance is very limited. The performance improvement by RTRBM compared to their cRBM is marginal, and insights into assembly dynamics are limited.

(1) The biological insights from this method are constrained. Though the aim is to unravel neural ensemble dynamics, the paper lacks in-depth discussion on how this method enhances our understanding of zebrafish neural dynamics. For example, the dynamics of assemblies can be analyzed using various tools such as dimensionality reduction methods once we have identified them using cRBM. What information can we gain by knowing the effective recurrent connection between them? It would be more convincing to show this in real data.

(2) Including predicted and measured neural activity traces could aid readers in evaluating model efficacy. The current version only contains comparison of the statistics, such as mean and covariance.

Reviewer #2 (Public review):

Summary:

In this work, the authors propose an extension to some of the last author's previous work, where a compositional restricted Boltzmann machine was considered as a generative model of neuron-assembly interaction. They augment this model by recurrent connections between the Boltzmann machine's hidden units, which allow them to explicitly account for temporal dynamics of the assembly activity. Since their model formulation does not allow the training towards a compositional phase (as in the previous model), they employ a transfer learning approach according to which they initialise their model with a weight matrix that was pre-trained using the earlier model so as to essentially start the actually training in a compositional phase. Finally, they test this model on synthetic and actual data of whole-brain light-sheet-microscopy recordings of spontaneous activity from the brain of larval zebrafish.

Strengths:

This work introduces a new model for neural assembly activity. Importantly, being able to capture temporal assembly dynamics is an interesting feature that goes beyond many existing models. While this work clearly focuses on the method (or the model) itself, it opens up an avenue for experimental research where it will be interesting to see if one can obtain any biologically meaningful insights considering these temporal dynamics when one is able to, for instance, relate them to development or behaviour.

Weaknesses:

For most of the work, the authors present their RTRBM model as an improvement over the earlier cRBM model. Yet, when considering synthetic data, they actually seem to compare with a "standard" RBM model. This seems odd considering the overall narrative and that when considering whole-brain zebrafish data, the comparisons were made between RTRBM and cRBM models. For that, the RTRBM model was initialised with the cRBM weight matrix to overcome the fact that RTRBM alone does not seem to converge to a compositional phase, so to cite the latter as reason does not really make sense.

Furthermore, whether the clusters shown in Figure 3E can indeed be described as "spatially localized" is debatable. Especially in view of clusters 3 and 4, this seems a stretch. If receptive fields are described as "spatially localized", arguably, one would expect that they are contained in some small (compared to the overall size of the brain) or specific anatomical brain region. However, this is clearly not the case here.

In addition, the performance comparison for the temporal dynamics of the hidden units actually suggests that the RTRBM (significantly) underperforms where the text says (Line 235f) it outperforms the cRBM model.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Summary:

Understanding large-scale neural activity remains a formidable challenge in neuroscience. While several methods have been proposed to discover the assemblies from such large-scale recordings, most previous studies do not explicitly model the temporal dynamics. This study is an attempt to uncover the temporal dynamics of assemblies using a tool that has been established in other domains.

The authors previously introduced the compositional Restricted Boltzmann Machine (cRBM) to identify neuron assemblies in zebrafish brain activity. Building upon this, they now employ the Recurrent Temporal Restricted Boltzmann Machine (RTRBM) to elucidate the temporal dynamics within these assemblies. By introducing recurrent connections between hidden units, RTRBM could retrieve neural assemblies and their temporal dynamics from simulated and zebrafish brain data.

Strengths:

The RTRBM has been previously used in other domains. Training in the model has been already established. This study is an application of such a model to neuroscience. Overall, the paper is well-structured and the methodology is robust, the analysis is solid to support the authors' claim.

Weaknesses:

The overall degree of advance is very limited. The performance improvement by RTRBM compared to their cRBM is marginal, and insights into assembly dynamics are limited.

(1) The biological insights from this method are constrained. Though the aim is to unravel neural ensemble dynamics, the paper lacks in-depth discussion on how this method enhances our understanding of zebrafish neural dynamics. For example, the dynamics of assemblies can be analyzed using various tools such as dimensionality reduction methods once we have identified them using cRBM. What information can we gain by knowing the effective recurrent connection between them? It would be more convincing to show this in real data.

See below in the recommendations section.

(2) Despite the increased complexity of RTRBM over cRBM, performance improvement is minimal. Accuracy enhancements, less than 1% in synthetic and zebrafish data, are underwhelming (Figure 2G and Figure 4B). Predictive performance evaluation on real neural activity would enhance model assessment. Including predicted and measured neural activity traces could aid readers in evaluating model efficacy.

See below in the recommendations section.

Recommendations:

(1) The biological insights from this method are constrained. Though the aim is to unravel neural ensemble dynamics, the paper lacks in-depth discussion on how this method enhances our understanding of zebrafish neural dynamics. For example, the dynamics of assemblies can be analyzed using various tools such as dimensionality reduction methods once we have identified them using cRBM. What information can we gain by knowing the effective recurrent connection between them? It would be more convincing to show this in real data.

We agree with the reviewer that our analysis does not explore the data far enough to reach the level of new biological insights. For practical reasons unrelated to the science, we cannot further explore the data in this direction at this point, however, funding permitting, we will pick up this question at a later stage. The only change we have made to the corresponding figure at the current stage was to adapt the thresholds, which better emphasizes the locality of the resulting clusters.

(2) Despite the increased complexity of RTRBM over cRBM, performance improvement is minimal. Accuracy enhancements, less than 1% in synthetic and zebrafish data, are underwhelming (Figure 2G and Figure 4B). Predictive performance evaluation on real neural activity would enhance model assessment. Including predicted and measured neural activity traces could aid readers in evaluating model efficacy.

We thank the reviewer kindly for the comments on the performance comparison between the two models. We would like to highlight that the small range of accuracy values for the predictive performance is due to both the sparsity and stochasticity of the simulated data, and is not reflective of the actual percentage in performance improvement. To this end, we have opted to use a rescaled metric that we call the normalised Mean Squared Error (nMSE), where the MSE is equal to 1 minus the accuracy, as the visible units take on binary values. This metric is also more in line with the normalised Log-Likelihood (nLLH) metric used in the cRBM paper in terms of interpretability. The figure shows that the RTRBM can significantly predict the state of the visible units in subsequent time-steps, whereas the cRBM captures the correct time-independent statistics but has no predictive power over time.

We also thank the reviewer for pointing out that there is no predictive performance evaluation on the neural data. This has been chosen to be omitted for two reasons. First, it is clear from Fig. 2 that the (c)RBM has no temporal dependencies, meaning that the predictive performance is determined mostly by the average activity of the visible units. If this corresponds well with the actual mean activity per neuron, the nMSE will be around 0. This correspondence is already evaluated in the first panel of 3F. Second, as this is real data, we can not make an estimate of a lower bound on the MSE that is due to neural noise. Because of this, the scale of the predictive performance score will be arbitrary, making it difficult to quantitatively assess the difference in performance between both models.

(3) The interpretation of the hidden real variable $r_t$ lacks clarity. Initially interpreted as the expectation of $\mathbf{h}_t$, its interpretation in Eq (8) appears different. Clarification on this link is warranted.

We thank the reviewer kindly for the suggested clarification. However, we think the link between both values should already be sufficiently clear from the text in lines 469-470:

“Importantly, instead of using binary hidden unit states 𝐡[𝑡−1], sampled from the expected real valued hidden states 𝐫[𝑡−1], the RTRBM propagates these real-valued hidden unit states directly.”

In other words, both indeed are the same, one could sample a binary-valued 𝐡[𝑡-1] from the real-valued 𝐫[𝑡-1] through e.g. a Bernoulli distribution, where 𝐫[𝑡-1] would thus indeed act as an expectation over 𝐡[𝑡−1]. However, the RTRBM formulation keeps the real-valued 𝐫[𝑡-1] to propagate the hidden-unit states to the next time-step. The motivation for this choice is further discussed in the original RTRBM paper (Sutskever et al. 2008).

(4) In Figure 3 panel F, the discrepancy in x-axis scales between upper and lower panels requires clarification. Explanation regarding the difference and interpretation guidelines would enhance understanding.

Thank you for pointing out the discrepancy in x-axis scales between the upper and lower panels of Figure 3F. The reason why these scales are different is that the activation functions in the two models differ in their range, and showing them on the same scale would not do justice to this difference. But we agree that this could be unclear for readers. Therefore we added an additional clarification for this discrepancy in line 215:

“While a direct comparison of the hidden unit activations between the cRBM and the RTRBM is hindered by the inherent discrepancy in their activation functions (unbounded and bounded, respectively), the analysis of time-shifted moments reveals a stronger correlation for the RTRBM hidden units ($r_s = 0.92$, $p<\epsilon$) compared to the cRBM ($r_s = 0.88$, $p<\epsilon$)”

(5) Assessing model performance at various down-sampling rates in zebrafish data analysis would provide insights into model robustness.

We agree that we would have liked to assess this point in real data, to verify that this holds as well in the case of the zebrafish whole-brain data. The main reason why we did not choose to do this in this case is that we would only be able to further downsample the data. Current whole brain data sets are collected at a few Hz (here 4 Hz, only 2 Hz in other datasets), which we consider to be likely slower than the actual interaction speed in neural systems, which is on the order of milliseconds between neurons, and on the order of ~100 ms (~10 Hz) between assemblies. Therefore reducing the rate further, we expect to only see a reduction in quality, which we considered less interesting than finding an optimum. Higher rates of imaging in light-sheet imaging are only achievable currently by imaging only single planes (which defies the goal of whole brain recordings), but may be possible in the future when the limiting factors (focal plane stepping and imaging) are addressed. For completeness, we have now performed the downstepping for the experimental data, which showed the expected decrease in performance. The results have been integrated into Figure 4.

Reviewer #2 (Public Review):

Summary:

In this work, the authors propose an extension to some of the last author's previous work, where a compositional restricted Boltzmann machine was considered as a generative model of neuron-assembly interaction. They augment this model by recurrent connections between the Boltzmann machine's hidden units, which allow them to explicitly account for temporal dynamics of the assembly activity. Since their model formulation does not allow the training towards a compositional phase (as in the previous model), they employ a transfer learning approach according to which they initialise their model with a weight matrix that was pre-trained using the earlier model so as to essentially start the actually training in a compositional phase. Finally, they test this model on synthetic and actual data of whole-brain light-sheet-microscopy recordings of spontaneous activity from the brain of larval zebrafish.

Strengths:

This work introduces a new model for neural assembly activity. Importantly, being able to capture temporal assembly dynamics is an interesting feature that goes beyond many existing models. While this work clearly focuses on the method (or the model) itself, it opens up an avenue for experimental research where it will be interesting to see if one can obtain any biologically meaningful insights considering these temporal dynamics when one is able to, for instance, relate them to development or behaviour.

Weaknesses:

For most of the work, the authors present their RTRBM model as an improvement over the earlier cRBM model. Yet, when considering synthetic data, they actually seem to compare with a "standard" RBM model. This seems odd considering the overall narrative, and it is not clear why they chose to do that. Also, in that case, was the RTRBM model initialised with the cRBM weight matrix?

Thank you for raising the important point regarding the RTRBM comparison in the synthetic data section. Initially, we aimed to compare the performance of the cRBM with the cRTRBM. However, we encountered significant challenges in getting the RTRBM to reach the compositional phase. To ensure a fair and robust comparison, we opted to compare the RBM with the RTRBM.

A few claims made throughout the work are slightly too enthusiastic and not really supported by the data shown. For instance, when the authors refer to the clusters shown in Figure 3D as "spatially localized", this seems like a stretch, specifically in view of clusters 1, 3, and 4.

Thanks for pointing out this inaccuracy. When going back to the data/analyses to address the question about locality, we stumbled upon a minor bug in the implementation of the proportional thresholding, causing the threshold to be too low and therefore too many neurons to be considered.

Fixing this bug reduces the number of neurons, thereby better showing the local structure of the clusters. Furthermore, if one would lower the threshold within the hierarchical clustering, smaller, and more localized, clusters would appear. We deliberately chose to keep this threshold high to not overwhelm the reader with the number of identified clusters. We hope the reviewer agrees with these changes and that the spatial structure in the clusters presented are indeed rather localized.

Moreover, when they describe the predictive performance of their model as "close to optimal" when the down-sampling factor coincided with the interaction time scale, it seems a bit exaggerated given that it was more or less as close to the upper bound as it was to the lower bound.

We thank the reviewer for catching this error. Indeed, the best performing model does not lay very close to the estimated performance of an optimal model. The text has been updated to reflect this.

When discussing the data statistics, the authors quote correlation values in the main text. However, these do not match the correlation values in the figure to which they seem to belong. Now, it seems that in the main text, they consider the Pearson correlation, whereas in the corresponding figure, it is the Spearman correlation. This is very confusing, and it is not really clear as to why the authors chose to do so.

Thank you for identifying the discrepancy between the correlation values mentioned in the text and those presented in the figure. We updated the manuscript to match the correlation coefficient values in the figure with the correct values denoted in the text.

Finally, when discussing the fact that the RTRBM model outperforms the cRBM model, the authors state it does so for different moments and in different numbers of cases (fish). It would be very interesting to know whether these are the same fish or always different fish.

Thank you for pointing this out. Keeping track of the same fish across the different metrics makes sense. We updated the figure to include a color code for each individual fish. As it turns out each time the same fish are significantly better performing.

Recommendations:

Figure 1: While the schematic in A and D only shows 11 visible units ("neurons"), the weight matrices and the activity rasters in B and C and E and F suggest that there should be, in fact, 12 visible units. While not essential, I think it would be nice if these numbers would match up.

Thank you for pointing out the inconsistency in the number of visible units depicted in Figure 1. We agree that this could have been confusing for readers. The figure has been updated accordingly. As you suggested, the schematic representation now accurately reflects the presence of 12 visible units in both the RBM and RTRBM models.

Figure 3: Panel G is not referenced in the main text. Yet, I believe it should be somewhere in lines 225ff.

Thank you for mentioning this. We added in line 233 a reference to figure 3 panel G to refer to the performance of the cRBM and RTRBM on the different fish.

Line 637ff: The authors consider moments <v\_i h\_μ> and <v\_i h\_j>, and from the context, it seems they are not the same. However, it is not clear as to why because, judging from the notation, they should be the same.

The second-order statistic <v\_i h\_j> on line 639 was indeed already mentioned and denoted as <v\_i h\_μ> on line 638. It has now been removed accordingly in the updated manuscript.

I found the usage of U^ and U throughout the manuscript a bit confusing. As far as I understand, U^ is a learned representation of U. However, maybe the authors could make the distinction clearer.

We understand the usage of Û and U throughout the text may be confusing for the reader. However, we would like to notify the reviewer that the distinction between these two variables is explained in line 142: “in addition to providing a close estimate (̂Û) to the true assembly connectivity matrix U”. However, for added clarification to the reader, we added additional mentions of the estimated nature of Û throughout the text in the updated manuscript.

Equation 3: It would be great if the authors could provide some more explanation of how they arrived at the identities.

These identities have previously been widely described in literature. For this reason, we decided not to include their derivation in our manuscript. However, for completeness, we kindly refer to:

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Chapter 20: Deep generative models [In Deep Learning]. MIT Press. https://www.deeplearningbook.org/contents/generative_models.html

Typos:

-  L. 196: "connectiivty" -> "connectivity"

-  L. 197: Does it mean to say "very strong stronger"?

-  L. 339: The reference to Dunn et al. (2016) should appear in parentheses.

-  L. 504f: The colon should probably be followed by a full sentence.

-  Eq. 2: In the first line, the potential V still appears, which should probably be changed to show the concrete form (-b * h) as in the second line.

-  L. 351: Is there maybe a comma missing after "cRBM"?

-  L. 271: Instead of "correlation", shouldn't it rather be "similarity"? - L. 218: "Figure 3D" -> "Figure 3F"

We thank the reviewer for pointing out these typos, which have all (except one) been fixed in the text. We do emphasize the potential V to show that there are alternative hidden unit potentials that can be chosen. For instance, the cRBM utilizes dReLu hidden unit potentials.

Reviewer #3 (Public Review):

With ever-growing datasets, it becomes more challenging to extract useful information from such a large amount of data. For that, developing better dimensionality reduction/clustering methods can be very important to make sense of analyzed data. This is especially true for neuroscience where new experimental advances allow the recording of an unprecedented number of neurons. Here the authors make a step to help with neuronal analyses by proposing a new method to identify groups of neurons with similar activity dynamics. I did not notice any obvious problems with data analyses here, however, the presented manuscript has a few weaknesses:

(1) Because this manuscript is written as an extension of previous work by the same authors (van der Plas et al., eLife, 2023), thus to fully understand this paper it is required to read first the previous paper, as authors often refer to their previous work for details. Similarly, to understand the functional significance of identified here neuronal assemblies, it is needed to go to look at the previous paper.

We agree that the present Research Advance has been written in a way that builds on our previous publication. It was our impression that this was the intention of the Research Advance format, as spelled out in its announcement "eLife has introduced an innovative new type of article – the Research Advance – that invites the authors of any eLife paper to present significant additions to their original research". In the previous formatting guidelines from eLife this was more evident with a strong limitation on the number of figures and words, however, also for the present, more liberal guidelines, place an emphasis on the relation to the previous article. We have nonetheless tried in several places to fill in details that might simplify the reading experience.

(2) The problem of discovering clusters in data with temporal dynamics is not unique to neuroscience. Therefore, the authors should also discuss other previously proposed methods and how they compare to the presented here RTRBM method. Similarly, there are other methods using neural networks for discovering clusters (assemblies) (e.g. t-SNE: van der Maaten & Hinton 2008, Hippocluster: Chalmers et al. 2023, etc), which should be discussed to give better background information for the readers.

The clustering methods suggested by the reviewer do not include modeling any time dependence, which is the crucial advance presented here by the introduction of the RTRBM, in extending the (c)RBM. In our previous publication on the cRBM (an der Plas et al., eLife, 2023), this comparison was part of the discussion, although it focussed on a different set of methods. While clustering methods like t-SNE, UMAP and others certainly have their value in scientific analysis, we think it might be misleading the reader to think that they achieve the same task as an RTRBM, which adds the crucial dimension of temporal dependence.

(3) The above point to better describe other methods is especially important because the performance of the presented here method is not that much better than previous work. For example, RTRBM outperforms the cRBM only on ~4 out of 8 fish datasets. Moreover, as the authors nicely described in the Limitations section this method currently can only work on a single time scale and clusters have to be estimated first with the previous cRBM method. Thus, having an overview of other methods which could be used for similar analyses would be helpful.

We think that the perception that the RTRBM performs only slightly better is based on a misinterpretation of the performance measure, which we have tried to address (see comments above) in this rebuttal and the manuscript. In addition we would like to emphasize that the structural estimation (which is still modified by the RTRBM, only seeded by the cRBMs output), as shown in the simulated data, makes improved structural estimates, which is important, even in cases where the performance is comparable (which can be the case if the RBM absorbs temporal dependencies of assemblies into modified structure of assemblies). We have clarified this now in the discussion.

Recommendations:

(1) Line 181: it is not explained how a reconstruction error is defined.

Dear reviewer, thanks for pointing this out. A definition of the (mean square) reconstruction error is added in this line.

(2) How was the number of hidden neurons chosen and how does it affect performance?

Thank you for pointing this out. Due to the fact that we use transfer learning, the number of hidden units used for the RTRBM is given by the number of hidden units used for training the cRBM. In further research, when the RTRBM operates in the compositional phase, we can exploit a grid search over a set of hyper parameters to determine the optimal set of hidden units and other parameters.

Author response:

The following is the authors’ response to the previous reviews.

Reviewing Editor (Recommendations For The Authors):

The revised manuscripts and rebuttal sufficiently answered all the questions raised by three Reviewers. Overall, the manuscript is well written and the results are clear based on a straightforward experiment in a pursuit of comparing dimeric PTH analog to 1-34 PTH analog, which has established clinical efficacy. The study's results are valuable as it utilized large animal models, specifically examined the local bone integration effects, and demonstrated the comparable therapeutic efficacy of the new PTH analog to 1-34 PTH. However, the data did not convincingly show how the dimeric PTH analog overcomes the limitations of 1-34 PTH. I suggest that the discussion should focus more on the differences between the two analogs.

We sincerely appreciate your thorough review and valuable feedback. We have carefully considered your comments and would like to address them as follows:

“Regarding the results on the effect of dimeric R25CPTH(1-34) in the OVX mouse model (Noh et al., 2024), bone formation markers were increased in the dimeric R25CPTH(1-34) group compared to the rhPTH (1-34) group. Additionally, bone resorption markers were decreased in the rhPTH (1-34) group compared to the control group. However, no significant differences were observed in the dimeric R25CPTH(1-34) group. This suggests that the mechanism of action of the dimeric peptide differs from that of the wildtype peptide. Furthermore, based on unpublished data comparing mRNA expression in bone and kidney tissues between the dimeric R25CPTH(1-34) and rhPTH (1-34) treated groups, we strongly believe that dimeric R25CPTH(1-34) exhibits distinct biological activity from rhPTH (1-34). These differences may arise from variations in PTH receptor binding, involvement of different G protein subtypes, or downstream intracellular signaling pathways.

The distinct effects of dimeric R25CPTH(1-34) and rhPTH (1-34) on osteoblasts and osteoclasts could indicate that while remodeling-based osteogenesis has a limited clinical use period, the dimeric form might promote sustained bone formation and increased bone density over a longer duration. Given that patients with this mutation, who have been exposed to the mutant dimer throughout their lives, exhibit high bone density, this suggests significant potential for dimeric R25CPTH(1-34) as a novel therapeutic option alongside wildtype PTH.” (Discussion section 2nd paragraph)

A few minor points I 'd like to point out. This line number is based on a Word file.

Line 146-148 - However, both were insufficient compared to the control group and did not illustrate any bone filling. The measured bone-implant contact ratio was 18.32 {plus minus} 16.19% for the control group, 48.13 {plus minus} 29.81% for the group, and 39.53 {plus minus} 26.17% (P < 0.05).

- Does it mean that bone generation of both treatment group is inferior to the control group? please specify which groups the values are belong to and between which groups P-value compare.

Thank you very much for your suggestion to improve the manuscript. We have recognized the previous omission and have revised the sentence clearly as follows.

"The measured bone–implant contact ratio was 18.32 ± 16.19% for the control group, 48.13 ± 29.81% for the rhPTH(1-34) group, and 39.53 ± 26.17% for the dimeric R25CPTH(1-34) group, illustrating the significant improvement in osseointegration. (P < 0.05 for the control group compared to both PTH groups; however, the difference between the PTH groups was not significant.)"

Line 157 - incompleteness over the same period. The rhPTH(1-34) group exhibited a mature trabecularcfghnc

- Please correct misspellings.

As the reviewer mentioned, I have corrected "trabecularcfghnc" to "trabecular." Thank you.

Line 165-168 and Figure 4 M-N - Both the rhPTH(1-34) and dimeric R25CPTH(1-34) groups showed a significantly higher number of TRAP+ cells at both bone defects, with and without a xenograft, compared to the control group (Figure 4M,N). (P < 0.05) In addition, the number of TRAP+ cells in the dimeric R25CPTH(1-34)group was significantly higher than in the vehicle, yet lower than in the rhPTH(1-34) group (Figure 4M,N).)

- I believe the heading of figure 4M-N should be changed to with or without xenograft. And maybe you want to explain the significant difference of TRAP positive cells between two groups (with vs. without xenograft). Minor point: was - were

We totally agree with reviewer’s comment. We changed figure 4. Also, based on the revised figure, the figure legends for figure 4 were also revised as follows. “The number of TRAP-positive cells in the mandible with and without xenograft in the rhPTH(1-34) and dimeric R25CPTH(1-34)-treated beagle groups.” Following the reviewer's comments, the be verb in the sentences in the results section was changed from ‘was’ to ‘were’. “The capability of rhPTH(1-34) and dimeric R25CPTH(1-34) in bone remodeling were evaluated by tartrate-resistant acid phosphatase (TRAP) immunohistochemical staining.”

Line 182-186 - This study investigated the therapeutic effects of rhPTH(1-34) and dimeric R25CPTH(1-34) on bone regeneration and osseointegration in a large animal model with postmenopausal osteoporosis. rhPTH(1-34) and dimeric R25CPTH(1-34) have shown significant clinical efficacy, and although there have been a few studies investigating their effects on bone regeneration in rodents (Garcia et al., 2013), the authors in this study aimed to investigate the effects using a large animal model that more accurately mimics osteoporotic humans (Cortet, 2011).

- Please split the sentences for better clarity. In last sentence, I'm unsure what Cortet 2011 citation here is for. The statement should be written in the first person not the third person.

We appreciate your attention to detail, which has helped improve the clarity and accuracy of this manuscript. As per the reviewer's suggestion, I have reordered and changed the references to fit the content and revised the sentences to the first person.

“rhPTH(1-34) and dimeric R25CPTH(1-34) have shown significant clinical efficacy. Although there have been a few studies investigating their effects on bone regeneration in rodents (Garcia et al., 2013), we aimed to investigate these effects using a large animal model. We chose this model because it more accurately mimics osteoporotic humans (Jee and Yao, 2001).”

Line 196-197 - Furthermore, by demonstrating that dimeric R25CPTH(1-34) exhibits a distinct pharmacological profile different from rhPTH(1-34) but still provides a clear anabolic effect in the localized jaw region, the authors have shown that it may possess different potential therapeutic indications from rhPTH(1-34).

- This study does not include any pharmacological data. (Please cite reference). Again, I would suggest writing it in the first person. It sounds like you are reviewing someone else's work

Thank you for your insightful comments. We acknowledge that our study did not include pharmacological data. We have changed the sentence to clarify that the pharmacological profile information is derived from previous studies. A suitable citation was included to substantiate this assertion. As suggested, we have revised the statement in the first person to more accurately represent our own research and discoveries.

“Furthermore, we have shown that dimeric R25CPTH(1-34) has a distinct anabolic effect in the localized mandible region, which is comparable to that of rhPTH(1-34). Our findings indicate that dimeric R25CPTH(1-34) may have distinct potential therapeutic indications, as demonstrated by prior pharmacological studies  (Bae et al., 2016), which demonstrated that it possesses a distinct pharmacological profile from rhPTH(1-34).”

Line 201 - One of the potential clinical advantages of dimeric R25CPTH(1-34) is its partial agonistic effect in pharmacodynamics.

- it needs reference

Thank you for your insightful advice. As reviewer’s suggestion, we have included references as follows.

“Additionally, the potency of cAMP production in cells was lower for dimeric R25CPTH compared to monomeric R25CPTH, consistent with its lower PTH1R-binding affinity (Noh et al., 2024).”

Line 206-207 - Also, the effects of dimer were prominent, as we mentioned better bone formation than the control group

- But not compared with monomeric 1-34 PTH

We have revised the statement to more accurately reflect our findings.

“Also, the impact of dimeric R25CPTH(1-34) was notable, as we observed a noticeable improvement in bone formation when compared to the control group. However, these effects were not as strong as those of rhPTH(1-34). Both PTH analogs demonstrated enhanced anabolic effects around the titanium implants, promoting bone regeneration and remodeling.”

Line 224 - The authors have attributed this phenomenon to the unique anatomical characteristics observed in the jawbone.

- I would suggest writing it in the first person

We totally understood the reviewer’s comment. We have corrected the sentences as follows.

“The anabolic effects of both PTH analogs in this specific region may have been enhanced by the unique anatomical characteristics of the mandible, which we attribute to these improvements.”

Line 236 - The authors have attributed this phenomenon to the unique anatomical characteristics observed in the jawbone.

- This is outdated as the label of two year limit of Forteo use was lifted by FDA in 2021

Thank you for your valuable comments regarding the FDA’s decision to lift the two-year limit on Forteo (teriparatide) use in 2021. We have revised sentences to reflect this recent information in FDA guidelines as follows.

“Despite the FDA's decision to remove the two-year treatment limit in 2021, which opens possibilities for broader clinical applications, there are still numerous challenges that need to be addressed. There are ongoing concerns about the potential long-term effects of extended use, including accelerated bone remodeling, possible hypercalcemic conditions, and heightened bone resorption”

Line 380-382 - bone volume (TV; mm3), trabecular number (Tb.N; 1/mm), trabecular thickness (Tb. Th; um), trabecular separation (Tb.sp; µm).

- minor points- please superscript mm3, and change u -> µ

We appreciate reviewer’s detailed comments. We have corrected the part about unit display in figure legend.

Line 405-406 - following treatment with dimeric dimeric R25CPTH(1-34)

- please remove redundancy.

We removed dimeric duplication in the figure legend for figure 5 as follows.

“Figure 5. Measurement of biochemical Marker Dynamics in serum. The serum levels of calcium, phosphorus, P1NP, and CTX across three time points (T0, T1, T2) following treatment with dimeric R25CPTH(1-34), rhPTH(1-34) and control.”

Line 409-410 - CTX levels, associated with bone resorption, show no significant differences between groups.

- there is a missing figure identification. please specify relevant figure - I guess (E)

We appreciate the reviewer's insightful comment regarding the missing figure identification in the sentence about CTX levels. After reviewing Figure 5, we have specified the relevant figure panel as follows:

“Figure 5. (A) The study timeline. (B-C) Calcium and phosphorus levels show an upward trend in response to both PTH treatments compared to control, indicating enhanced bone mineralization. (D) P1NP levels, indicative of bone formation, remain relatively stable across time and treatments. (E) CTX levels, associated with bone resorption, show no significant differences between groups.”

eLife Assessment

Using a large animal model, this study demonstrated valuable findings that R25CPTH(1-34), based on a mutation associated with isolated familial hypoparathyroidism, generated an anabolic osteointegration effect comparable to that of native PTH1-34. The translational aspect of this human-to-animal work, aimed at animal-to-human translation for therapeutic purposes, should be highlighted. The study design is simple and straightforward, and the methods used are solid. The authors have addressed all the questions in their revision.

Reviewer #1 (Public Review):

Summary:

This study provides valuable insights into the therapeutic effects of two parathyroid hormone (PTH) analogs on bone regeneration and osseointegration. The research is methodologically sound, employing a robust animal model and a comprehensive array of analytical techniques, including micro-CT, histological/histomorphometric analyses, and serum biochemical analysis.

Strengths:

The use of a large animal model, which closely mimics postmenopausal osteoporosis in humans, enhances the study's relevance to clinical applications. The study is well-structured, with clear objectives, detailed methods, and a logical flow from introduction to conclusion. The findings are significant, demonstrating the potential of rhPTH(1-34) and dimeric R25CPTH(1-34) in enhancing bone regeneration, particularly in the context of osteoporosis.

Weaknesses:

There are no major weaknesses.

Reviewer #2 (Public Review):

Summary:

This article explores the regenerative effects of recombinant PTH analogues on osteogenesis.

Strengths:

Although PTH has known to induce the activity of osteoclasts, accelerating bone resorption, paradoxically its intermittent use has become a common treat for osteoporosis. Previous studies successfully demonstrated this phenomenon in vivo, but most of them used rodent animal models, inevitably having a limitation. In this article, the authors tried to address this, using a beagle model, and assessed the osseointegrative effect of recombinant PTH analogues. As a result, the authors clearly observed the regenerative effects of PTH analogues, and compared the efficacy, using histologic, biochemical, and radiologic measurement for surgical-endocrinal combined large animal models. The data seem to be solid, and has potential clinical implications.

Weaknesses:

All the issues that I raised have been resolved in the revision process.

Overall, this paper is well-written and has clarity and consistency for a broader readership.

Reviewer #3 (Public Review):

Summary:

The work submitted by Dr. Jeong-Oh Shin and co-workers aims to investigate the therapeutic efficacy of rhPTH(1-34) and R25CPTH(1-34) on bone regeneration and osseointegration of titanium implants using a postmenopausal osteoporosis animal model.

In my opinion the findings presented are not strongly supported by the provided data since the methods utilized do not allow to significantly support the primary claims.

Strengths:

Strengths include certain good technologies utilized to perform histological sections (i.e. the EXAKT system).

Weaknesses:

Certain weaknesses continue to significantly lower the enthusiasm for this work. Most important: the limited number of samples/group. In fact, as presented, the work has an n=4 for each treatment group. This limited number of samples/group significantly impairs the statistical power of the study. In addition, the implants were surgically inserted following a "conventional implant surgery", implying that no precise/guided insertion was utilized. This weakness is, in my opinion, particularly significant since the amount of bone osteointegration may greatly depend on the bucco-lingual positioning of each implant at the time of the surgical insertion (which should, therefore, be precisely standardized across all animals and for all surgical procedures).

eLife Assessment

This valuable study is a detailed investigation of how chromatin structure influences replication origin function in yeast ribosomal DNA, with a focus on the role of the histone deacetylase Sir2 and the chromatin remodeler Fun30. Convincing evidence shows that Sir2 does not affect origin licensing but rather affects local transcription and nucleosome positioning which correlates with increased origin firing. Overall, the evidence is solid and the model plausible. However, the methods employed do not rigorously establish a key aspect of the mechanism where initiation precisely occurs or rigorously exclude alternative models and the effect of Sir2 on transcription is not re-examined in the fun30 context.

Reviewer #1 (Public review):

Summary:

This paper presents a mechanistic study of rDNA origin regulation in yeast by SIR2. Each of the ~180 tandemly repeated rDNA gene copies contains a potential replication origin. Early-efficient initiation of these origins is suppressed by Sir2, reducing competition with origins distributed throughout the genome for rate-limiting initiation factors. Previous studies by these authors showed that SIR2 deletion advances replication timing of rDNA origins by a complex mechanism of transcriptional de-repression of a local PolII promoter causing licensed origin proteins (MCMcomplexes) to re-localize (slide along the DNA) to a different (and altered) chromatin environment. In this study, they identify a chromatin remodeler, FUN30, that suppresses the sir2∆ effect, and remarkably, results in a contraction of the rDNA to about one-quarter it's normal length/number of repeats, implicating replication defects of the rDNA. Through examination of replication timing, MCM occupancy and nucleosome occupancy on the chromatin in sir2, fun30, and double mutants, they propose a model where nucleosome position relative to the licensed origin (MCM complexes) intrinsically determines origin timing/efficiency. While their interpretations of the data are largely reasonable and can be interpreted to support their model, a key weakness is the connection between Mcm ChEC signal disappearance and origin firing. While the cyclical chromatin association-dissociation of MCM proteins with potential origin sequences may be generally interpreted as licensing followed by firing, dissociation may also result from passive replication and as shown here, displacement by transcription and/or chromatin remodeling. Moreover, linking its disappearance from chromatin in the ChEC method with such precise resolution needs to be validated against an independent method to determine the initiation site(s). Differences in rDNA copy number and relative transcription levels also are not directly accounted for, obscuring a clearer interpretation of the results. Nevertheless, this paper makes a valuable advance with the finding of Fun30 involvement, which substantially reduces rDNA repeat number in sir2∆ background. The model they develop is compelling and I am inclined to agree, but I think the evidence on this specific point is purely correlative and a better method is needed to address the initiation site question. The authors deserve credit for their efforts to elucidate our obscure understanding of the intricacies of chromatin regulation. At a minimum, I suggest their conclusions on these points of concern should be softened and caveats discussed. Statistical analysis is lacking for some claims.

Strengths are the identification of FUN30 as suppressor, examination of specific mutants of FUN30 to distinguish likely functional involvement. Use of multiple methods to analyze replication and protein occupancies on chromatin. Development of a coherent model.

Weaknesses are failure to address copy number as a variable; insufficient validation of ChEC method relationship to exact initiation locus; lack of statistical analysis in some cases.

Review of revised version and response letter:

In the response, the authors make some improvements by better quantifying 2D gels, adding some missing statistical analyses, analyzing the effect of fun30 on rDNA replication in strains with reduced rDNA copy number, and using ChIP-seq of MCMs to support the ChEC-seq data. However, these additions do not address the main issue that is at the heart of their model: where initiation precisely occurs and whether the location is altered in the mutant(s). Thus, mechanistic insight is limited.

Under the section "Addressing Alternative Explanations", the authors claim that processes like transcription and passive replication cannot affect the displaced complex specifically. Why? They are not on same DNA (as mentioned in the Fig 1 legend).

The model in Fig 7 implies that initiation sites are different in WT versus the mutants and this determines their timing/efficiency. But they also suggest that the same site might be used with different efficiencies in this response. I agree that both are possibilities and are not resolved.

Supporting their model requires better resolution to determine the actual replication initiation site. While this may be challenging, it should be feasible with methods to map nascent strands like DNAscent, or Okazaki fragment mapping.

The 2D gel analysis of strains with reduced rDNA copy numbers adequately addresses the copy number variable with regard to the replication effect.

Overall, the paper is improved by providing additional data and improved analysis. The paper nicely characterizes the effect of Fun30. The model is reasonable but remains lacking in precise details of mechanism.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors follow up on their previous work showing that in the absence of the Sir2 deacetylase the MCM replicative helicase at the rDNA spacer region is repositioned to a region of low nucleosome occupancy. Here they show that the repositioned displaced MCMs have increased firing propensity relative to non-displaced MCMs. In addition, they show that activation of the repositioned MCMs and low nucleosome occupancy in the adjacent region depend on the chromatin remodeling activity of Fun30.

Strengths:

The paper provides new information on the role of a conserved chromatin remodeling protein in regulation of origin firing and in addition provides evidence that not all loaded MCMs fire and that origin firing is regulated at a step downstream of MCM loading.

Weaknesses:

The relationship between the authors results and prior work on the role of Sir2 (and Fob1) in regulation of rDNA recombination and copy number maintenance is not explored, making it difficult to place the results in a broader context. Sir2 has previously been shown to be recruited by Fob1, which is also required for DSB formation and recombination-mediated changes in rDNA copy number. Are the changes that the authors observe specifically in fun30 sir2 cells related to this pathway? Is Fob1 required for the reduced rDNA copy number in fun30 sir2 double mutant cells?

Reviewer #3 (Public review):

Summary:

Heterochromatin is characterized by low transcription activity and late replication timing, both dependent on the NAD-dependent protein deacetylase Sir2, the founding member of the sirtuins. This manuscript addresses the mechanism by which Sir2 delays replication timing at the rDNA in budding yeast. Previous work from the same laboratory (Foss et al. PLoS Genetics 15, e1008138) showed that Sir2 represses transcription-dependent displacement of the Mcm helicase in the rDNA. In this manuscript, the authors show convincingly that the repositioned Mcms fire earlier and that this early firing partly depends on the ATPase activity of the nucleosome remodeler Fun30. Using read-depth analysis of sorted G1/S cells, fun30 was the only chromatin remodeler mutant that somewhat delayed replication timing in sir2 mutants, while nhp10, chd1, isw1, htl1, swr1, isw2, and irc5 had no effect. The conclusion was corroborated with orthogonal assays including two-dimensional gel electrophoresis and analysis of EdU incorporation at early origins. Using an insightful analysis with an Mcm-MNase fusion (Mcm-ChEC), the authors show that the repositioned Mcms in sir2 mutants fire earlier than the Mcm at the normal position in wild type. This early firing at the repositioned Mcms is partially suppressed by Fun30. In addition, the authors show Fun30 affects nucleosome occupancy at the sites of the repositioned Mcm, providing a plausible mechanism for the effect of Fun30 on Mcm firing at that position. However, the results from the MNAse-seq and ChEC-seq assays are not fully congruent for the fun30 single mutant. Overall, the results support the conclusions providing a much better mechanistic understanding how Sir2 affects replication timing at rDNA,

Strengths

(1) The data clearly show that the repositioned Mcm helicase fires earlier than the Mcm in the wild type position.<br /> (2) The study identifies a specific role for Fun30 in replication timing and an effect on nucleosome occupancy around the newly positioned Mcm helicase in sir2 cells.

Weaknesses

(1) It is unclear which strains were used in each experiment.<br /> (2) The relevance of the fun30 phospho-site mutant (S20AS28A) is unclear.<br /> (3) For some experiments (Figs. 3, 4, 6) it is unclear whether the data are reproducible and the differences significant. Information about the number of independent experiments and quantitation is lacking. This affects the interpretation, as fun30 seems to affect the +3 nucleosome much more than let on in the description.

Author response:

The following is the authors’ response to the original reviews.

eLife Assessment 

This study is a detailed investigation of how chromatin structure influences replication origin function in yeast ribosomal DNA, with focus on the role of the histone deacetylase Sir2 and the chromatin remodeler Fun30. Convincing evidence shows that Sir2 does not affect origin licensing but rather affects local transcription and nucleosome positioning which correlates with increased origin firing. However, the evidence remains incomplete as the methods employed do not rigorously establish a key aspect of the mechanism, fully address some alternative models, or sufficiently relate to prior results. Overall, this is a valuable advance for the field that could be improved to establish a more robust paradigm. 

We have added extensive new results to the manuscript that, we believe, address all three criticisms above, namely that the methods employed do not (1) rigorously establish a key aspect of the mechanism; (2) fully address some alternative models; or (3) sufficiently relate to prior results.

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

This paper presents a mechanistic study of rDNA origin regulation in yeast by SIR2. Each of the ~180 tandemly repeated rDNA gene copies contains a potential replication origin. Earlyefficient initiation of these origins is suppressed by Sir2, reducing competition with origins distributed throughout the genome for rate-limiting initiation factors. Previous studies by these authors showed that SIR2 deletion advances replication timing of rDNA origins by a complex mechanism of transcriptional de-repression of a local PolII promoter causing licensed origin proteins (MCMcomplexes) to re-localize (slide along the DNA) to a different (and altered) chromatin environment. In this study, they identify a chromatin remodeler, FUN30, that suppresses the sir2∆ effect, and remarkably, results in a contraction of the rDNA to about onequarter it's normal length/number of repeats, implicating replication defects of the rDNA. Through examination of replication timing, MCM occupancy and nucleosome occupancy on the chromatin in sir2, fun30, and double mutants, they propose a model where nucleosome position relative to the licensed origin (MCM complexes) intrinsically determines origin timing/efficiency. While their interpretations of the data are largely reasonable and can be interpreted to support their model, a key weakness is the connection between Mcm ChEC signal disappearance and origin firing.  

Criticism: The reviewer expressed concern about the connection between Mcm ChEC signal disappearance and origin firing.

To further support our claim that the disappearance of the MCM signal in our ChEC datasets reflects origin firing, we now present additional data using the well-established method of MCM Chromatin IP (ChIP).

(1) New Supporting Evidence:  ChIP at genome-wide origins. In Figure 5 figure supplement 2, we demonstrate that the Mcm2 ChIP signal in cells released into hydroxyurea (HU) is significantly reduced at early origins compared to late origins, which mirrors the pattern observed with the MCM2 ChEC signal. This reduction in the ChIP signal at early origins supports the interpretation that the MCM signal disappearance is associated with origin firing.

(2) New supporting based evidence:  ChIP at rDNA Origins. Our ChIP analysis also shows that the disappearance of the MCM signal at rDNA origins in sir2Δ cells released into HU is accompanied by signal accumulation at the replication fork barrier (RFB), indicative of stalled replication forks at this location (Figure 5 figure supplement 3). This pattern is consistent with the initiation of replication at these origins and fork stalling at the RFB.

(3) New supporting evidence:  2D gels with quantification. Furthermore, additional 2D gel electrophoresis results provide ample independent evidence of rDNA origin firing in HU in sir2Δ mutants and suppression of origin firing in sir2 fun30 cells. These new data include 1) quantification of 2D gels in Figure 4D and 2) new 2D gels presented in Figure 4C as described below in greater detail. Collectively, these results demonstrate that rDNA origins fire prematurely in HU in sir2 cells and that firing is suppressed by FUN30 deletion. These additional data reinforce our model and support the association between MCM signal disappearance and replication initiation.

While the cyclical chromatin association-dissociation of MCM proteins with potential origin sequences may be generally interpreted as licensing followed by firing, dissociation may also result from passive replication and as shown here, displacement by transcription and/or chromatin remodeling.

The reviewer raised a concern that the cyclical chromatin association-dissociation of MCM proteins could be interpreted as licensing followed by firing, but might also result from passive replication or displacement by transcription and chromatin remodeling.

Addressing Alternative Explanations:

(1) Selective Disappearance of MCM Complexes: While transcription and passive replication can indeed cause the MCM-ChEC signal to disappear, these processes cannot selectively cause the disappearance of the displaced MCM complex without also affecting the non-displaced MCM complex. Specifically, RNA polymerase transcribing C-pro would first need to dislodge the normally positioned MCM complex before reaching the displaced complex, which is not observed in our data.

(2) Role of FUN30 Deletion:  FUN30 deletion results in increased C-pro transcription and reduced disappearance of the displaced MCM complex. This observation supports our model, as transcription alone would not selectively affect the displaced MCM complex while leaving the normally positioned MCM complex unaffected.

(3) Licensing Restrictions: It is crucial to note that continuous replenishment of displaced MCMs with newly loaded MCMs is not possible in our experimental conditions, as the cells are in S phase and licensing is restricted to G1. This temporal restriction further supports our interpretation that the disappearance of the MCM signal reflects origin firing rather than alternative processes.

In summary, while alternative explanations such as transcription and passive replication could potentially account for MCM signal disappearance, our data indicate that these processes cannot selectively affect the displaced MCM complex without impacting the non-displaced complex. The selective disappearance observed in our experiments, along with the effects of FUN30 deletion and the temporal constraints on MCM loading, strongly support our interpretation that the disappearance of the MCM signal reflects origin firing.

Moreover, linking its disappearance from chromatin in the ChEC method with such precise resolution needs to be validated against an independent method to determine the initiation site(s). Differences in rDNA copy number and relative transcription levels also are not directly accounted for, obscuring a clearer interpretation of the results. 

The reviewer raised concerns about the need to validate the disappearance of MCM from chromatin observed using the ChEC method against an independent method to determine initiation sites. Additionally, they pointed out that differences in rDNA copy number and relative transcription levels are not directly accounted for, which may obscure the interpretation of the results.

(1) Reduced rDNA Copy Number promotes Early Replication: Copy number reduction of the magnitude caused by deletion of both SIR2 and FUN30 is not expected to suppress early rDNA replication in sir2, but rather to exacerbate it. Specifically, deletion of SIR2 and FUN30 causes the rDNA to shrink to approximately 35 copies. Kwan et al., 2023 (PMID: 36842087) have shown that a reduction in rDNA copy number to 35 copies results in a dramatic acceleration of rDNA replication in a SIR2+ strain. Therefore, the effect of rDNA size on replication timing reinforces our conclusion that deletion of FUN30 suppresses rDNA replication.

(2) New 2D Gels in sir2 and sir2 fun30 strains with equal number of rDNA repeats: To directly address the concern regarding differences in the number of rDNA repeats, we have included new 2D gel analyses in the revised manuscript. By using a fob1

background, we were able to equalize the repeat number between the sir2 and sir2 fun30 strains (Figure 4E). The 2D gels conclusively show that the suppression of rDNA origin firing upon FUN30 deletion is independent of both rDNA size and FOB1.

Nevertheless, this paper makes a valuable advance with the finding of Fun30 involvement, which substantially reduces rDNA repeat number in sir2∆ background. The model they develop is compelling and I am inclined to agree, but I think the evidence on this specific point is purely correlative and a better method is needed to address the initiation site question. The authors deserve credit for their efforts to elucidate our obscure understanding of the intricacies of chromatin regulation. At a minimum, I suggest their conclusions on these points of concern should be softened and caveats discussed. Statistical analysis is lacking for some claims. 

Strengths are the identification of FUN30 as suppressor, examination of specific mutants of FUN30 to distinguish likely functional involvement. Use of multiple methods to analyze replication and protein occupancies on chromatin. Development of a coherent model. 

Weaknesses are failure to address copy number as a variable; insufficient validation of ChEC method relationship to exact initiation locus; lack of statistical analysis in some cases. 

With regard to "insufficient validation of ChEC method relationship to exact initiation locus":  The two potential initiation sites that one would monitor (non-displaced and displaced) are separated by less than 150 base pairs, and other techniques simply do not have the resolution necessary to distinguish such differences. Indeed, our new ChIP results presented in Figure 5 figure supplement 3 clearly demonstrate that while the resolution of ChIP is adequate to detect the reduction of MCM signal at the replication initiation site and its relocation to the RFB ( ~2 kb away), it lacks the resolution required to differentiate closely spaced MCM complexes.

Furthermore, as we suggest in the manuscript, our results are consistent with a model in which it is only the displaced MCM complex that is activated, whether in sir2 or WT.  If no genotypedependent difference in initiation sites is even expected, it would be hard to interpret even the most precise replication-based assays.  

We appreciate the reviewer pointing out that some statistical analyses were lacking: we have added statistical analysis for 2D gels (Figures 4D and 4E),  EdU incorporation experiments in Figure 4F and disappearance of MCM ChEC and ChIP signal upon release of cells into HU (Figure 5 supplement 1 and Supplement 2).  

Additional background and discussion for public review: 

This paper broadly addresses the mechanism(s) that regulate replication origin firing in different chromatin contexts. The rDNA origin is present in each of ~180 tandem repeats of the rDNA sequence, representing a high potential origin density per length of DNA (9.1kb repeat unit). However, the average origin efficiency of rDNA origins is relatively low (~20% in wild-type cells), which reduces the replication load on the overall genome by reducing competition with origins throughout the genome for limiting replication initiation factors. Deletion of histone deacetylase SIR2, which silences PolII transcription within the rDNA, results in increased early activation or the rDNA origins (and reduced rate of overall genome replication). Previous work by the authors showed that MCM complexes loaded onto the rDNA origins (origin licensing) were laterally displaced (sliding) along the rDNA, away from a well-positioned nucleosome on one side. The authors' major hypothesis throughout this work is that the new MCM location(s) are intrinsically more efficient configurations for origin firing. The authors identify a chromatin remodeling enzyme, FUN30, whose deletion appears to suppress the earlier activation of rDNA origins in sir2∆ cells. Indeed, it appears that the reduction of rDNA origin activity in sir2∆ fun30∆ cells is severe enough to results in a substantial reduction in the rDNA array repeat length (number of repeats); the reduced rDNA length presumably facilitates it's more stable replication and maintenance. 

Analysis of replication by 2D gels is marginally convincing, using 2D gels for this purpose is very challenging and tricky to quantify. 

We address this criticism by carefuly quantifying 2 D gel results using single rARS signal for normalizing bubble arc as discussed below.

The more quantitative analysis by EdU incorporation is more convincing of the suppression of the earlier replication caused by SIR2 deletion. 

We have also added quantification of EdU results to strengthen our arguments.  

To address the mechanism of suppression, they analyze MCM positioning using ChEC, which in G1 cells shows partial displacement of MCM from normal position A to positions B and C in sir2∆ cells and similar but more complete displacement away from A to positions B and C in sir2fun30 cells. During S-phase in the presence of hydroxyurea, which slows replication progression considerably (and blocks later origin firing) MCM signals redistribute, which is interpreted to represent origin firing and bidirectional movement of MCMs (only one direction is shown), some of which accumulate near the replication fork barrier, consistent with their interpretation. They observe that MCMs displaced (in G1) to sites B or C in sir2∆ cells, disappear more rapidly during S-phase, whereas the similar dynamic is not observed in sir2∆fun30∆. This is the main basis for their conclusion that the B and C sites are more permissive than A. While this may be the simplest interpretation, there are limitations with this assay that undermine a rigorous conclusion (additional points below). The main problem is that we know the MCM complexes are mobile so disappearance may reflect displacement by other means including transcription which is high is the sir2∆ background. Indeed, the double mutant has greater level of transcription per repeat unit which might explain more displaced from A in G1. Thus, displacement might not always represent origin firing. Because the sir2 background profoundly changes transcription, and the double mutant has a much smaller array length associated with higher transcription, how can we rule out greater accessibility at site A, for example in sir2∆, leading to more firing, which is suppressed in sir2 fun30 due to greater MCM displacement away from A? 

I think the critical missing data to solidly support their conclusions is a definitive determination of the site(s) of initiation using a more direct method, such as strand specific sequencing of EdU or nascent strand analysis. More direct comparisons of the strains with lower copy number to rule out this facet. As discussed in detail below, copy number reduction is known to suppress at least part of the sir2∆ effect so this looms over the interpretations. I think they are probably correct in their overall model based on the simplest interpretation of the data but I think it remains to be rigorously established. I think they should soften their conclusions in this respect. 

Please see discussion below about these issues.

Reviewer #2 (Public Review): 

Summary: 

In this manuscript, the authors follow up on their previous work showing that in the absence of the Sir2 deacetylase the MCM replicative helicase at the rDNA spacer region is repositioned to a region of low nucleosome occupancy. Here they show that the repositioned displaced MCMs have increased firing propensity relative to non-displaced MCMs. In addition, they show that activation of the repositioned MCMs and low nucleosome occupancy in the adjacent region depend on the chromatin remodeling activity of Fun30. 

Strengths: 

The paper provides new information on the role of a conserved chromatin remodeling protein in the regulation of origin firing and in addition provides evidence that not all loaded MCMs fire and that origin firing is regulated at a step downstream of MCM loading. 

Weaknesses: 

The relationship between the author's results and prior work on the role of Sir2 (and Fob1) in regulation of rDNA recombination and copy number maintenance is not explored, making it difficult to place the results in a broader context. Sir2 has previously been shown to be recruited by Fob1, which is also required for DSB formation and recombination-mediated changes in rDNA copy number. Are the changes that the authors observe specifically in fun30 sir2 cells related to this pathway? Is Fob1 required for the reduced rDNA copy number in fun30 sir2 double mutant cells? 

We have conducted additional studies in the fob1 background to address how FOB1 and the replication fork barrier (RFB) influence the kinetics of rDNA size reduction upon FUN30 deletion (Figure 2 - figure supplement 2), rDNA replication timing (Figure 2 - figure supplement 3), and rDNA origin firing using 2D gels (Figure 4C).

Strains lacking SIR2 exhibit unstable rDNA size, and FOB1 deletion stabilizes rDNA size in a sir2 background (and otherwise). Similarly, we found that FOB1 deletion influences the kinetics of rDNA size reduction in sir2 fun30 cells. Specifically, we were able to generate a fob1 sir2 fun30 strain with more than 150 copies. Nonetheless, and consistent with our model, this strain still exhibited delayed rDNA replication timing (Figure 2 - figure supplement 3), and its rDNA still shrank upon continuous culture (Figure 2 figure supplement 2). These results demonstrate that, although FOB1 affects the kinetics of rDNA size reduction in sir2 fun30 strains, the reduced rDNA array size or delayed replication timing upon FUN30 deletion size does not depend on FOB1.

The use of the fob1 background allowed us to compare the activation of rDNA origins in sir2 and sir2 fun30 strains with equally short rDNA sizes. 2D gels demonstrate robust and reproducible suppression of rDNA origin activity upon deletion of FUN30 in sir2 fob1 strains with 35 rDNA copies (Figure 4C). These results indicate that the main effect we are interested in—FUN30-induced reduction in origin firing—is independent of both FOB1 and rDNA size.

Our additional studies conclusively show that the FUN30-induced reduction in rDNA origin firing is independent of both FOB1 and rDNA size. These findings provide important insights into the mechanisms regulating rDNA copy number maintenance, placing our results within the broader context of existing knowledge on Sir2 and Fob1 functions.

Reviewer #3 (Public Review): 

Summary: 

Heterochromatin is characterized by low transcription activity and late replication timing, both dependent on the NAD-dependent protein deacetylase Sir2, the founding member of the sirtuins. This manuscript addresses the mechanism by which Sir2 delays replication timing at the rDNA in budding yeast. Previous work from the same laboratory (Foss et al. PLoS Genetics 15, e1008138) showed that Sir2 represses transcription-dependent displacement of the Mcm helicase in the rDNA. In this manuscript, the authors show convincingly that the repositioned Mcms fire earlier and that this early firing partly depends on the ATPase activity of the nucleosome remodeler Fun30. Using read-depth analysis of sorted G1/S cells, fun30 was the only chromatin remodeler mutant that somewhat delayed replication timing in sir2 mutants, while nhp10, chd1, isw1, htl1, swr1, isw2, and irc3 had not effect. The conclusion was corroborated with orthogonal assays including two-dimensional gel electrophoresis and analysis of EdU incorporation at early origins. Using an insightful analysis with an Mcm-MNase fusion (Mcm-ChEC), the authors show that the repositioned Mcms in sir2 mutants fire earlier than the Mcm at the normal position in wild type. This early firing at the repositioned Mcms is partially suppressed by Fun30. In addition, the authors show Fun30 affects nucleosome occupancy at the sites of the repositioned Mcm, providing a plausible mechanism for the effect of Fun30 on Mcm firing at that position. However, the results from the MNAse-seq and ChEC-seq assays are not fully congruent for the fun30 single mutant. Overall, the results support the conclusions providing a much better mechanistic understanding how Sir2 affects replication timing at rDNA, 

The observation that the MNase-seq plot in fun30 mutant shows a large signal at the +3 nucleosome and somewhat smaller at position +2, while the ChEC-seq plot exhibits negligible signals, is indeed an important point of consideration. This discrepancy arises because most of the MCM in fun30 mutant remains at its original site where it abuts +1 nucleosome. As a result, the MCM-MNase fusion protein fails to reach and “light up” the +3 nucleosome, which is, nonetheless, well-visualized with exogenous MNase.  The paucity of displaced MCMs, which is responsible for cutting +2 nucleosome, explains the discrepancy in the +2 nucleosome signal between exogenous MNase and CheC datasets in the fun30 mutant.  

Despite this apparent discrepancy, the overall results support our conclusions and provide a much better mechanistic understanding of how Sir2 affects replication timing at rDNA. The MNaseseq data reflect nucleosome positioning and chromatin structure, while the ChEC-seq data specifically highlights the locations where MCM is bound and active.  

Strengths 

(1) The data clearly show that the repositioned Mcm helicase fires earlier than the Mcm in the wild type position. 

(2) The study identifies a specific role for Fun30 in replication timing and an effect on nucleosome occupancy around the newly positioned Mcm helicase in sir2 cells. 

Weaknesses 

(1) It is unclear which strains were used in each experiment. 

(2) The relevance of the fun30 phospho-site mutant (S20AS28A) is unclear. 

We appreciate the reviewer pointing out places in which our manuscript omitted key pieces of information (items 1 and 3), we have included the strain numbers in our revision.  With regard to point 2, we had written:  

Fun30 is also known to play a role in the DNA damage response; specifically, phosphorylation of Fun30 on S20 and S28 by CDK1 targets Fun30 to sites of DNA damage, where it promotes DNA resection (Chen et al. 2016; Bantele et al. 2017). To determine whether the replication phenotype that we observed might be a consequence of Fun30's role in the DNA damage response, we tested non-phosphorylatable mutants for the ability to suppress early replication of the rDNA in sir2; these mutations had no effect on the replication phenotype (Figure 2B), arguing against a primary role for Fun30 in DNA damage repair that somehow manifests itself in replication. 

(3) For some experiments (Figs. 3, 4, 6) it is unclear whether the data are reproducible and the differences significant. Information about the number of independent experiments and quantitation is lacking. This affects the interpretation, as fun30 seems to affect the +3 nucleosome much more than let on in the description. 

We have provided replicas and quantitation for the results in these figures.

(Replica ChEC Southern blot with quantification (Figure 3 figure supplement 1), quantification and replicas for 2D gels in Figure 4 and replicas for nucleosome occupancy (Figure 6 supplement 1).

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors): 

Fig. 3-Examination of MCM occupancy at the rDNA ARS region using a variation of ChEC.

Presumably these are these G1-arrested cells but does not seem to be stated. Please confirm. 

The 2D gels results are not very convincing of their conclusions. We are asked to compare bubble to fork arcs at 30 minutes, but this is not feasible. It is the author's job to quantify the data from multiple replicates, but none is given. After much careful examination, comparing the relative intensities of ascending bubble and Y-arcs, I think I can accept that 4A shows highest early efficiency for sir2 over WT and fun30, which are similar to each other, and lowest for sir2 fun30, at 60 and 90 min. 

In the revision we provide a careful quantification of the 2D gels in Figure 4. For assessing rDNA origin activity, we normalized the bubble arc during the HU time course to a single rARS signal, that appears as large 24.4kb Nhe1I fragment originating from the  rightmost rDNA repeat (see Figures 4A and 4B). The description of the quantification in the text is provided below. 

“Prior to separation on 2D gels, DNA was digested with NheI, which releases a 4.7 kb rARScontaining linear DNA fragment at the internal rDNA repeats (1N) and a much larger, 24.5 kb single-rARS-containing fragment originating from the rightmost repeat. In 2D gels, active origins generate replication bubble arc signals, whereas passive replication of an origin appears as a y-arc. Having a signal emanating from a single ARS-containing fragment simplifies the comparison of rDNA origin activity in strains with different numbers of rDNA repeats, such as in sir2 vs sir2 fun30 mutants. Origin activity is expressed as a ratio of the bubble to the single-ARS signal, effectively measuring the number of active rDNA origins per cell at a given time point. 

As seen previously (Foss et al. 2019), deletion of SIR2 increased the number of activated rDNA origins, while deletion of FUN30 suppressed this effect. When analyzed in aggregate at 20, 30, 60 and 90 minutes following release into HU, the average number of activated rDNA origin activity in sir2 mutant was increased 6.3-fold compared to those in WT (5.0±2.3 in sir2 vs 0.8±0.4 in wt, p<0.05 by 2 tailed t-test), and the increased number was reduced upon FUN30 deletion (1.3±0.7 in sir2 fun30, p<0.05 by 2 tailed t-test vs sir2, NS for comparison to WT).”

However, for part 4B, they state (p. 11) that deletion of FUN30 in a SIR2 background had no perceptible effect (on ARS305) but I think the data appear otherwise: the FUN30 cells show more Y-arc than WT.

We now provide the assessment of ARS305 activity in HU cells as a ratio of bubble-arc to 1N signal. The reviewer is right that FUN30 has a more robust bubble arc signal compared to WT.

However, after normalization to 1N this difference did not appear significant (3.7 vs 5.1). Overall the analysis of activity or ARS305 origins demonstrates a reciprocity with the activity of rDNA origins in each of the four genotypes.  Furthermore, this observation is confirmed in our EdU-based analysis of 111 genomic origins, with statistical analysis showing a very high level of significance (see below).  

Ultimately, analysis of unsynchronized cells would give unambiguous results about origin efficiency. In this regard I note that analysis of rDNA origin firing by 2D gels with HU versus asynchronous gives different results in WT versus sir2∆, with no difference in unsynchronized cells (He et al. 2022). It would be interesting to test the strains here unsynchronized, though copy number size would still be a variable to address.

Origin activity in log cultures is typically assessed by comparing replication initiation within an origin, presenting as a bubble arc, to passively replicated DNA (Y-arc). However, such an analysis at tandemly arrayed origins, such as rDNA, is not feasible, as both active and passive replication are the result of activation of the same origins. This explains the lack of difference between WT and sir2 cells previously reported (He et al. 2022), which we have also observed. Differences in activation of rDNA origins in WT vs sir2 cells is clearly reflected in HU experiments, as was the case in the earlier report (He et al. 2022). 

To address the issue of differences in copy number between sir2 and sir2 fun30 cells we have now done experiments in a fob1 background where we can equalize the copy number among the two genotypes. These 2D gels are presented in Figure 4C. We address this issue in the revised manuscript as follows:

“The overall impact of FUN30 deletion on rDNA origin activity in a sir2 background is expected to be a composite of two opposing effects: a suppression of rDNA origin activation and increased rDNA origin activation due to reduced rDNA size (Kwan et al. 2023). To evaluate the effect FUN30 on rDNA origin activation independently of rDNA size, we generated an isogenic set of strains in a fob1 background, all of which contain 35 copies of the rDNA repeat.  (Deletion of FOB1 is necessary to stabilize rDNA copy number.)  Comparing rDNA origin activity in sir2 versus sir2 fun30 genotypes, we observed a robust and reproducible reduction in rDNA origin activity upon FUN30 deletion. This finding confirms that the FUN30 suppresses rDNA origin firing in sir2 background independently of both rDNA size and FOB1 status.”

-EdU analysis is more convincing regarding relative effects on genome versus rDNA, however, again, the effect of reduced rDNA array size in the sir2 fun30 cells may also be the proximal cause of the reduced effect on genome (early origins) replication rather than a direct effect on origin efficiency. No statistic provided to support that fun30 suppresses sir2 for rDNA activity. 

This comment raises three distinct, but related, issues: 

First, the reviewer is asking whether the reduced rDNA size, of the magnitude we observed in sir2 fun30 cells, could by itself be responsible for increased origin activity elsewhere in the genome, just because there is less rDNA that needs to be replicated. As noted earlier (Kwan et al. 2023), Kwan et al. examined the effect of rDNA size reduction and observed: 1) marked increased in rDNA origin activity and 2) reciprocal reduction in origin activity elsewhere in the genome. This counterintuitive finding suggests that a smaller rDNA size exerts more competition for limited replication resources compared to a larger rDNA size. In light of this, our findings with FUN30 deletion become even more compelling. The suppression of rDNA firing upon FUN30 deletion is so significant that it overrides the expected effects of rDNA size reduction.

Second, the reviewer points out our lack of statistical analysis to support our contention that fun30 suppresses sir2 with regard to rDNA origin activity. We have now addressed this issue as well, by quantifying 2D gel signals, as described above in the text that begins with "Prior to separation on 2D gels, DNA was digested with NheI ...". 

Third, we have now provided a statistical analysis to support our conclusion that EdU-based analysis of activity of 111 early origins shows suppression upon deletion of SIR2 that is largely reversed by additional deletion of FUN30. 

"Deletion of FUN30 in a sir2 background partially restored EdU incorporation at early origins, concomitant with reduced EdU incorporation at rDNA origins. In particular, the median value of log10 of read depths at 111 early origins, as the data are shown in Figure 4F, dropped from 6.5 for wild type to 6.2 for sir2 but then returned almost to wild type levels (6.4) in sir2 fun30.  The p value obtained by Student's t test, comparing the drop in 111 origins from wild type to sir2 with that from wild type to sir2 fun30 was highly significant (<< 10-16)  In contrast, FUN30 deletion in the WT background did not reduce EdU incorporation at genomic origins (median 6.6). These findings highlight that FUN30 deletion-induced suppression of rDNA origins in sir2 is accompanied by the activation of genomic origins."

Use loss of Mcm-ChEC signal as proxy for origin firing. Reasonably convincing that decrease correlates with origin firing on a one-to-one basis (Fig. 5B), though no statistic given. 

We provide the statistical analysis in Figure 5-figure supplement 1.

However, there is no demonstration of ability to observe this correlation with fine resolution as needed for the claims here. It seems equally possible that sir2 deletion causes more firing by repositioning MCMs to a better location or that the prior location, which still contains substantial MCM, becomes more permissive. The MCM signal appears to be mobile, so perhaps the role of FUN30 is to prevent to mobility of MCM away from the original site in WT cells; note that significantly less Mcm signal is at the original position in sir2 fun30. No accumulation of MCM occurs near the RFB in WT (and fun30) cells. I understand that origin firing is lower in WT but raises concerns about sensitivity and dynamic range of this assay and that MCM positions may reflect transcription versus replication. 

Please see the section above labeled "Addressing Alternative Explanations".  

Is Fig 6A Y-axis correctly labeled? I understand this figure to represent MNase-seq reads; is there any Mcm2-ChEC-seq in part A? 

We have corrected the labeling. 6A represent MNase-seq reads. Thank you for pointing this out.

I understand part B to represent nucleosome-sized fragments released by Mcm2-ChEC interpreted to be nucleosomes. But could they be large fragments potentially containing adjacent MCM-double hexamers?  

Our representation of ChEC-seq data in Figure 1 supplement 1, where we can see the entire spectrum of fragment sizes, demonstrates two distinct populations of fragments: nucleosome size and MCM-size fragments.

Reviewer #2 (Recommendations For The Authors): 

Suggestions for the authors to consider: 

(1) The authors make a good case for the importance of replication balance between rDNA and euchromatin in ensuring that the genome is replicated in a timely fashion. This seems to be clearly regulated by Sir2. However, Sir2 also affects rDNA copy number and suppresses unequal cross over events, which are stimulates by Fob1. Does Fun30 suppress Fob1-dependent recombination events in sir2D cells? 

It is unclear why FUN30 only affects rDNA repeat copy number in sir2 cells. Why doesn't Fun30 reduce copy number in wild-type cells? 

Deletion of SIR2 causes rightward repositioning of MCMs to a position where they are more prone to fire, as shown by our HU ChEC datasets in which we show that the repositioned MCMs are more prone to activation than the non-repositioned ones. FUN30 deletion suppresses activation of these, activation-prone repositioned MCMs, as shown by HU ChEC. This suppression of rDNA origin activation in sir2 cells causes rDNA to shrink. In fun30 single mutants, due to the paucity of non-repositioned MCMs, we do not observe significant suppression of rDNA origin firing, and consequently, there is no reduction in rDNA size in fun30 cells.

(2) The authors use Mcm-MNase to map the location of the MCM helicase. Can these results be confirmed using the more standard and direct ChIP assay to examine changes in MCM localization

We carried out suggested MCM ChIP experiments and present these results in Figure 5 supplement 2 and supplement 3. These ChIP data demonstrate that: 

(1) MCM signal disappears preferentially at early origins compared to late origins, as seen in our ChEC results.

(2) The disappearance of ChEC signal at rDNA origins in sir2 mutant is accompanied by the signal accumulation at the RFB, consistent with fork stalling at the RFB mirroring the results we obtained by ChEC. While these results indicate that that ChIP has adequate resolution to detect MCM repositioning at 2 kb, scale, its resolution was insufficient for fine scale discrimination of repositioned and non-repositioned MCMs.

In this regard, the specific role of Fun30 in regulation of MCM firing at rDNA is interesting. 

Does Fun30 localize to the ARS region of rDNA? How is Fun30 specifically recruited to rDNA?  

We carried out ChIP for Fun30 and observed, similarly to previous reports (Durand-Dubief et al. 2012), a wide distribution of Fun30 throughout the genome and at rDNA. We have elected not to include these results in the current manuscript.

(3) The 2D gels in Figure 4 are difficult to interpret. The bubble to arc ratios in fun30D seem different from both wild-type and sir2D. It may be helpful to the reader to quantify the bubble to arc ratios. fun30D also seems to be affecting ARS305 by itself.

We provide quantification of 2 D gels in Figure 4.

(4) Figure 5. 

(4.1) For examining origin firing based on the disappearance of the Mcm-MNase reads, is HU arrest necessary? HU may be causing indirect effects due to replication fork stalling. In principle, the authors should be able to perform this analysis without HU, since their cells are released from synchronized arrest in G1 (and at least for the first cell cycle should proceed synchronously on to S phase). In addition, validation of Mcm-ChEC results using ChIP for one of the subunits of the MCM complex would increase confidence in the results. 

The HU arrest allows us to examine early events in DNA replication at much finer spatial and temporal resolution than it would be possible without it.

We have now used Mcm2 ChIP to confirm that the signal disappears at the MCM loading site in HU in sir2 cells as discussed above (Figure 5 figure supplement 3). However, the resolution is inadequate to discriminate non-repositioned vs repositioned MCMs.

(4.2) The non-displaced Mcm-ChEC signal in sir2D seems like it's decreasing more than in wildtype cells. Explain. It would be helpful to quantify these results by integrating the area under each peek (or based on read numbers). It looks like one of the displaced Mcm signals (the one more distal from the non-displaced) is changing at a similar rate to the non-displaced.  

Integrating the area under each Mcm-ChEC peak or using read numbers is superfluous for the following reasons:  (1) The rectangular appearance of the peaks in Figure 5 clearly reflects signal intensity, making additional numerical integration redundant. (2) The visual differences between wild-type and sir2D cells are distinct and sufficient for drawing conclusions without further quantification.  (3) Keeping the analysis straightforward avoids unnecessary complexity and maintains clarity.

(4.3) Can the authors explain why fun30D seems to be suppressing only one of the 2 displaced Mcms from firing? 

We speculate that the local environment is more conductive for firing one of two displaced MCMs, but we do not understand why.

(5) Figure 6. Why would the deletion of SIR2, a silencing factor, results in increased nucleosome occupancy at rDNA? 

If we understand correctly, the reviewer is referring to a small increase in +2 and +3 signal in sir2 compared to the WT. In WT G1 cells, there is a single MCM between +1 and +3 nucleosome. This space cannot accommodate a +2 nucleosome in G1 cells because MCM is loaded at that position in most cells (in G2 cells however, this space is occupied by a nucleosome (Foss et al., 2019). MCM repositioning in sir2 mutant would displace MCM from this location making it possible for this space to be now occupied by a nucleosome.

The changes in nuc density seem modest. Also, nucleosome density is similarly increased in sir2D and fun30D cells, but sir2 has a dramatic effect on origin firing but fun30D does not. Explain. 

We believe that the FUN30 status makes most of the difference for firing of displaced MCMs.

Since there are few displaced MCMs in SIR2 cells, there is not large impact on origin firing. Furthermore, the rDNA already fires late in WT cells, so our ability to detect further delay upon  FUN30 deletion could be more difficult.

(6) Discussion. At rDNA Sir2 may simply act by deacetylating nucleosomes and decreasing their mobility. This is unrelated to compaction which is usually only invoked regarding the activities of the full SIR complex (Sir2/3/4) at telomeres and the mating type locus. The arguments regarding polymerase size, compaction etc may not be relevant to the main point since although the budding yeast Sir2 participates in heterochromatin formation at the mating type loci and telomeres, at rDNA it may act locally near its recruitment site at the RFB. 

This is a valid point. We have added this sentence in the discussion to highlight the differences between silencing at rDNA and those at the silent mating loci and telomeres that SIR-complex dependent.

“Steric arguments such as these are even less compelling when made for rDNA than for the silent mating type loci and telomeres, because chromatin compaction has been studied mostly in the context of the complete Sir complex (Sir1-4). In contrast, Sir1, 3, and 4 are not present at the rDNA.”

Minor 

It would be interesting to see if deletion of any histone acetyltranferases acts in a similar way to Fun30 to reduce rDNA copy number in sir2D cells. 

Thank you for this suggestion.

Reviewer #3 (Recommendations For The Authors): 

(1) The design of Figure 3 could be improved. A scheme could help understand the assay without flipping back to Figure 1. The numbers below the gel bands need definition. 

We have included the scheme describing the restriction and MCM-MNase cut sites and the location of the probe for the Southern blot.

(2) The design of Figure 4 could be improved by adding a scheme to help interpret the 2d gel picture. The figure also lacks quantitation. Are the results reproducible and the differences significant? 

We have added the scheme, quantification and statistics in Figure 4.

(3) Please list in each figure legend the exact strains from Table S1 which were used. 

We have included the strain numbers in the Figure legend.

Durand-Dubief M, Will WR, Petrini E, Theodorou D, Harris RR, Crawford MR, Paszkiewicz K, Krueger F, Correra RM, Vetter AT et al. 2012. SWI/SNF-like chromatin remodeling factor Fun30 supports point centromere function in S. cerevisiae. PLoS Genet 8: e1002974.

Foss EJ, Gatbonton-Schwager T, Thiesen AH, Taylor E, Soriano R, Lao U, MacAlpine DM, Bedalov A. 2019. Sir2 suppresses transcription-mediated displacement of Mcm2-7 replicative helicases at the ribosomal DNA repeats. PLoS Genet 15: e1008138.

He Y, Petrie MV, Zhang H, Peace JM, Aparicio OM. 2022. Rpd3 regulates single-copy origins independently of the rDNA array by opposing Fkh1-mediated origin stimulation. Proc Natl Acad Sci U S A 119: e2212134119.

Kwan EX, Alvino GM, Lynch KL, Levan PF, Amemiya HM, Wang XS, Johnson SA, Sanchez JC, Miller MA, Croy M et al. 2023. Ribosomal DNA replication time coordinates completion of genome replication and anaphase in yeast. Cell Rep 42: 112161.

eLife Assessment

This important study shows that soluble uric acid is an endogenous inhibitor of CD38, a regulator of inflammatory responses. The convincing evidence draws both on biochemical analyses and in vivo models. This work provides insights into NAD+ metabolism, with significant implications for inflammation and potential roles in metabolic diseases and aging.

Reviewer #1 (Public review):

This manuscript describes soluble Uric Acid (sUA) as an endogenous inhibitor of CD38, affecting CD38 activity and NAD+ levels both in vitro and in vivo. Importantly, the inhibition constants calculated supports the claim that sUA inhibits CD38 under physiological conditions. These findings are of extreme importance to understand the regulation of an enzyme that has been shown to be the main NAD+/NMN-degrading enzyme in mammals, which impacts several metabolic processes and has major implications to understanding aging diseases. The manuscript is well written, the figures are self explanatory, and in the experiments presented, the data is very solid. The authors discuss the main limitations of the study, especially in regard to the in vivo results. As a whole, I believe that this is a very interesting manuscript that will be appreciated by the scientific community and that opens a lot of new questions in the field of metabolism and aging.

During the revision process, the authors have performed new experiments to respond to relevant questions raised by the reviewers. In other cases, they have made changes in the text to improve the manuscript.

I believe that this manuscript in its current form is a mature and relevant set of findings that deserve attention and future developments.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

The authors investigate macrophages as the cells affected by sUA in promoting immunoregulation, proposing that sUA's inhibition of CD38 and the resulting increase in NAD+ promotes inflammasome inhibition through a previously established mechanism of NLRP3 regulation by NAD+-dependent sirtuins. However, they were unable to validate their in vivo findings using murine bone marrow-derived macrophages, a standard model for assessing inflammasome activation, due to the low uptake of sUA in these cells. Pharmacological blockage in THP-1 cells provides mechanistic evidence that sUA inhibits NLRP3-mediated secretion of IL-1β through CD38, but genetic evidence and direct assessment of the activation of inflammasome components would be necessary to fully validate the model.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Comment on revised version:

The authors have responded the majority of my criticism.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

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

We greatly appreciate the reviewer’s thoughtful comments and favorable review of our work.

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

Yes, we agreed with the reviewer. Two representative papers regarding the pioneering findings [Ref 1, 2] of pharmacological inhibition of CD38 were cited in the discussion of current manuscript.

(1) Tarragó, M. G., et al. (2018). A Potent and Specific CD38 Inhibitor Ameliorates Age-Related Metabolic Dysfunction by Reversing Tissue NAD+ Decline. Cell Metab 27(5): 1081-1095.e1010.

(2) Escande, C., et al. (2013). Flavonoid apigenin is an inhibitor of the NAD+ ase CD38: implications for cellular NAD+ metabolism, protein acetylation, and treatment of metabolic syndrome. Diabetes 62(4): 1084-1093.

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

Currently, there are several kinds of CD38 inhibitors, including NAD+/NMN analogs, flavonoids, 4-quinolines, etc. [Ref 1], but they do not have 1,3-dihydroimidazol-2-one or similar groups. We also noticed that sUA and its analogs have no remarkable structural similarity with these inhibitors. We have ever tried to identify the binding sites of sUA on CD38 by NMR. Since our NMR method required a large sample size, we had to prepare recombinant human CD38 using a cell-free protein synthesis system. However, the obtained CD38 protein showed a lower Vmax than commercial recombinant CD38 expressed in HEK293 cells, raising a concern of spatial conformation deference in the synthesized CD38. Thus, we were unable to get convinced data to confirm if sUA has different binding sites. Given the difference in structural feature and inhibition type, we did not use the PDB data regarding 78c-CD38 interaction for analysis in this study.

(1) Chini, E. N., et al. (2018). The Pharmacology of CD38/NADase: An Emerging Target in Cancer and Diseases of Aging. Trends Pharmacol Sci 39(4): 424-436.

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

We appreciate the reviewer’s kind suggestions. Yes, CD38 expression in young mice is relatively low and we used young mice in this study; thus, aged mice would be promising to furthest evaluate the interaction between CD38 and sUA. Regarding the changes in sUA levels during aging, previous reports indicate that sUA levels seem to increase with age in mice and humans [Ref 1, 2]. We speculate that this increase is a physiologically compensatory response to aging in organisms. Accordingly, we added more details in the discussion (second paragraph).

(1) Iwama, M., et al. (2012). Uric acid levels in tissues and plasma of mice during aging. Biol Pharm Bull 35(8): 1367-1370.

(2) Kuzuya, M., et al. (2002). Effect of aging on serum uric acid levels: longitudinal changes in a large Japanese population group. J Gerontol A Biol Sci Med Sci 57(10): M660-664.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

We deeply thank the reviewer for the thoughtful comments and appreciation of our findings.

Weaknesses:

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

We deeply thank the reviewer for pointing out this weakness in our work. In fact, we tried to prepare stable CD38 KD/KO THP-1 cells in the middle of 2021; however, we faced some technical problems due to the limitations of instruments. Thus, we used CD38 KO mice to prepare CD38 KO BMDMs, as shown in the first version of manuscript, we failed to replicate the results in BMDMs because of the low uptake of sUA. To address the reviewer’s concern regarding the lack of an in vitro link between CD38 and sUA immunosuppression, we used 78c, a highly specific and potent inhibitor of CD38, to block CD38 in primed THP-1 cells. Then we evaluated the effect of sUA pre-incubation on MSU crystal-induced IL-1β release in primed THP-1 cells (vehicle and CD38 blockade). The added results in Figure 4-figure supplement 2B and 2C indicated that CD38 blockade largely impaired the immunosuppressive effect of sUA without reducing sUA uptake. In addition, we found that sUA at physiological levels boosted NAD+ levels in THP-1 cells (Figure 3-figure supplement 1B) without affecting the activities of other key enzymes involved in NAD+ synthesis and degradation, including NAMPT and PARP (Figure 3-figure supplement 2). All these results supported that CD38 is a key mediator for sUA at physiological levels to regulate inflammasome activation in vitro.

Reviewer #3 (Public Review):

Summary:

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

Strengths:

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

We greatly appreciate the reviewer for the thoughtful comments and valuable suggestions.

Weaknesses:

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

Yes, it is necessary to confirm if sUA affects other NAD+-consuming and synthesizing enzymes. To address the concern and to provide additional validation, we tested the direct effects of sUA and other purine derivates on the activities of another two key enzymes involved in the metabolic network of NAD+, including PARP (NAD+-consuming enzyme) and NAMPT (NAD+-synthesizing enzyme). The added results in Figure 3-figure supplement 2 showed that sUA has no effect on PARP and NAMPT activity, suggesting that CD38 is a main target for sUA in regulating NAD+ availability. In addition, we also confirmed both PARP and NAMPT were not affected by purine metabolism under physiological conditions. Although hypoxanthine and xanthine, at 500 μM (supraphysiological levels), slightly inhibited PARP activity, it has no physiological significance due to their low physiological concentrations (generally below 20 μM). Further evaluation of these inhibitory effects under pathological conditions would be of interest but were beyond the focus of this study.

Given that tissue sUA uptake is saturated under physiological conditions (tissue sUA did not increase in our models, Figure 3-figure supplement 5A and 5B), CD38 and other potential targets in tissues may be not affected by sUA in our models. We used CD38 KO mice to confirm if sUA interacts with other targets to regulate NAD+ degradation and inflammatory responses. A previous study [Ref 1] revealed that inhibition of other enzymes involved in NAD+ metabolism, such as PARP, resulted in a significant increase of NAD+ availability in CD38 KO mice, which indicates that CD38 KO mice can be used to exclude the potential interaction between sUA and other targets. In fact, we did not observe significant effects of sUA in CD38 KO mice. More importantly, we added the additional validation regarding PARP and NAMPT activity according to the reviewer’s kind suggestion, which further confirmed that CD38 is the main target for sUA in our models.

(1) Tarragó, M. G., et al. (2018). A Potent and Specific CD38 Inhibitor Ameliorates Age-Related Metabolic Dysfunction by Reversing Tissue NAD+ Decline. Cell Metab 27(5): 1081-1095.e1010.

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

We thank the reviewer’s insightful suggestions. Yes, sUA depletion model is ideal for further validation, as we discussed in the limitations of this study. Given that introduction of exogenous recombinant uricase (immunometabolism may be affected) to deplete sUA is not ideal for the evaluation under physiological conditions, uricase-transgenic mice would be a promising model. However, now we have no uricase-transgenic mice, and we are unable to prepare CD38 KO/uricase-transgenic mice for additional validation within a reasonable time. In the first version of manuscript, therefore, we used an sUA-release model in sUA-supplementation mice as a further validation in Figure 3E.

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

Answer: We highly appreciate the reviewer’s suggestion regarding metabolic flux analysis. Yes, flux analysis using specifically designed isotope-labeled NAD+ is an ideal validation in mice, as it can track any sUA-induced changes in NAD+ metabolism. However, we are unable to synthesize or obtain suitable isotope-labeled substrates for in vivo validation due to the technical limitations and financial burdens.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

The manuscript is very solid and very well-presented and discussed. In my opinion, the only weakness in the writing is that the message about finding an endogenous regulator of CD38 activity and NAD levels gets blurred by the temptation of jumping into the potential of developing new pharmacological CD38 inhibitors based on sUA structure. My recommendation would be to focus on delivering a clear message about sUA as a physiological inhibitor of CD38, and the possible implications for understanding the onset and evolution of metabolic diseases and aging. Maybe leave the potential of developing novel sUA-based CD38 inhibitors for a final comment. I understand this last point is very attractive, but there are very potent pharmacological CD38 inhibitors already available with promising results.

We greatly appreciate the reviewer’s valuable suggestions. Yes, there are some promising CD38 inhibitors with nanomolar Ki such as 78c. To clearly focus on sUA as a physiological inhibitor of CD38, we simplified the description in the manuscript and just keep the discussion of functional group. Since the data regarding the development of CD38 inhibitors in our manuscript remain limited, we did not put it in a separate part. We believe the simplified information is still sufficient for medicinal chemists who are interested in the development of CD38 inhibitors.

Reviewer #2 (Recommendations For The Authors):

Major comments:

(1) The authors present several pieces of data to explain why there is no impact of sUA in inflammasome-mediated cytokine secretion, which is convincing and supports that BMDM will not be a model of choice to establish macrophages as the target of sUA. However, their data with THP-1 cells is compelling and could be further explored using shRNA, or CRISPR approaches to deplete CD38, thus establishing a mechanistic link in vitro.

We greatly appreciate the reviewer’s thoughtful comments. We added more results as mentioned before (please see our response to public review).

(2) There is a severe lack of linearity in how the figures are presented in the main text, making it difficult to read through the manuscript. The figures should be presented in the order they appear in the panels.

We thank the reviewer for pointing out this issue. We improved the figure assembly according to eLife guidelines.

Minor comments:

(1) The authors do not appropriately address the finding that CD38 impacts the secretion of IL-1b in BMDM (Figure S6B) and in vivo (Figure 4), possibly independently of sUA.

Yes, the regulatory effect of CD38 on cytokine release seems independent of sUA. In fact, we used CD38 KO BMDMs to validate the role of CD38 in the inflammasome activation. We showed that sUA levels are comparable between WT and KO mice, suggesting that CD38 KO does not affect the baselines and boosted levels of sUA in our models. In this situation, we were able to evaluate the immunosuppressive effects of sUA at the same physiological levels in WT and CD38 KO mice, thus providing evidence to support that sUA at physiological levels limits excessive inflammation via CD38.

(2) Figure 3F: the legend on the x-axis lacks the indication of which groups were treated with recombinant hCD38.

We appreciate the reviewer’s comments. We improved Figure 3 by adding more information.

(3) While the results on panels 3 and 4 provide robust evidence that sUA is anti-inflammatory through CD38, the title of the figures extrapolates their findings (i.e., no data shows CD38-sUA, either in vitro or in vivo).

We appreciate the reviewer’s kind suggestion. We provided data to support the direct interaction between CD38 and sUA in Figure 3F; we admitted that we did not show the data regarding the direct interaction in mice in Figure 4. To help readers easily track the results, however, we used a conclusion-like title.

(4) The introduction could briefly mention NMN and CD38 activity as an ecto-enzyme to facilitate the understanding of their findings by a general audience, especially the dosing of NMN and their data on BMDM.

We added more description regarding CD38 and NMN in the introduction part. Once again, we deeply thank the reviewer for the valuable suggestions.

Reviewer #3 (Recommendations For The Authors):

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

We greatly appreciate the reviewer’s valuable suggestions. We added more results to validate CD38 as the main target of sUA in our models. Please see our response to public review.

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

We greatly appreciate the reviewer’s valuable suggestions. Please see our response to public review.

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

We greatly appreciate the reviewer’s valuable suggestions. Please see our response to public review.

eLife Assessment

This paper, on the role of calcium and integrin-binding protein 2 and 3 in the hair-cell in the mechano-electrical transduction (MET) apparatus, is a mix of confirmatory studies with new and potentially important data. Some parts, such as zebrafish studies, the modelling and simulations, are regarded as necessary and convincing. Other parts of the paper do not have the same novelty. Both Liang et al. (2021) and Wang et al. (2023) had previously demonstrated a role for CIB2/CIB3 in auditory and vestibular cells in mice. Moreover, there are also data in Riazuddin et al. (2012) paper that demonstrates the importance of CIB2 in zebrafish and Drosophila. Breaking the manuscript up to focus on specific aspects of the problem might alleviate the limitations of this multi-faceted study.

eLife Assessment

This valuable study reports an extensive analysis of the way a humoral immune response to parasitoid wasp is expressed and regulated, building on previous work from the authors on an anti-parasitoid effector lectin. The solid evidence uses two complementary approaches to show which innate immune pathways are involved in the regulation of the anti-parasitoid response. The evidence would be stronger if some analytical and related concerns can be addressed. The work will be of relevance to the community of investigators studying insect immune cells as well as researchers interested in host defense against parasitism.

Reviewer #1 (Public review):

Summary:

The signaling pathways regulating the immune response to bacteria and fungi have been well characterized in Drosophila. Using the recently identified anti-parasitoid effector Lectin24A as a read-out, this article describes the signaling pathways regulating the humoral response against parasites.

Strengths:

This study reveals a role of JAK-STAT, Toll, and GATA in the fat body in the regulation of Lectin24A. They also observe an enrichment of binding sites for NF-kB, STAT, and GATA factors upstream of ORFs of genes induced upon encapsulation. Based on this observation, they generalize their findings on the involvement of JAK-STAT, Toll, and Gata in the humoral response to encapsulation. Although roles for the Toll and JAK-STAT pathways in capsule formation have previously been identified, the merit of this article is in analyzing the roles of these pathways in the humoral response using a new gene readout that will be a precious tool in the community.

Weaknesses:

The data are mostly convincing, but not always analyzed with sufficient detail; their conclusions should be reinforced by monitoring Lectin24A gene expression by RT-qPCR, by adding additional time points and by using alternative genetic tools. Using read-outs of the Toll and Imd pathways as comparisons is also important. Thus, this paper is interesting and important in advancing our understanding of Drosophila immunity but not yet enough solid to reach definitive conclusions on the proposed claims.

Reviewer #2 (Public review):

Summary:

In a previous study, the investigators had identified through genetic analysis of lines derived from natural populations that lectin-24A was an important gene required for protection against the parasitoid wasp Leptopilina boulardii, albeit only in a specific genetic context depending on an unidentified locus on the third chromosome (Arunkumar, et al., PNAS, 2023). They had documented that the gene is induced upon wasp infection and that the corresponding Lectin-24A binds to the wasp egg prior to hemocyte, mediating a faster encapsulating cellular response. They had identified a polymorphism in susceptible lines that correlated with a 21 nt deficiency in the lectin-24A promoter that removed a proximal NF-kappaB binding site. Here, they follow up this work by first performing a transgenic dissection of this promoter, including the mutations of putative transcription factor binding sites (TFBS) of the JAK-STAT, the Toll pathway, and the GATA family transcription factors. Secondly, they directly affect the expression of genes of the JAK-STAT pathway, of the DIF or Dorsal NF-kappaB transcription factors (and also Relish), and of pannier, the one induced gene of five GATA family members. Of note, the lectin is preferentially expressed in the posterior part of the fat body.

Strengths:

The combination of the analysis of the expression of the lectin-24A gene in cis through mutations in putative TFBS for three families of transcription factors and the analysis in trans of either the genetic pathway (JAK-STAT) or the STAT/DIF/Dorsal/Pannier transcription factors provides a fine-grained description of the regulation of the expression of a humoral effector gene that is induced by parasitoid wasp infestation. Thus, this work goes much beyond the bioinformatics analysis by using a rather thorough experimental approach. The finding of an induction of lectin-24A in the posterior rather than the anterior fat body is interesting yet puzzling. Is it known whether this species of parasitoid wasps deposits its eggs preferentially in the posterior part of the larva?

Weaknesses:

There are some discrepancies between the "cis" and "trans" approaches as regards their effects on basal or induced expression of lectin-24A:

JAK-STAT:<br /> Figure 4D shows that mutating three of six predicted STAT TFBS in the 314 bp promoter leads to a reduction of both basal and induced lectin-24A expression levels, with the gene still being inducible. In contrast, knocking down or out the Drosophila JAK and STAT genes abolished the inducibility of the lectin-24A reporter down or close to basal levels. Conversely, the overactivation of the JAK-STAT pathway led to basal levels that increased to those of induced ones.

Toll pathway:<br /> Figure 4D shows that mutating the proximal Dif-Dorsal TFBS reduces both basal and induced levels of the reporter gene to a common level that is below that of the wild-type basal activity. These data suggest that NF-kappaB signaling is required for both basal and induced expression of Lectin-24A. Affecting either Dif or dorsal gene expression led to opposite changes essentially in the basal expression level of the lectin-24A reporter. Conversely, dorsal overexpression in the fat body and other tissues (hemocytes) led to an enhanced basal expression of the lectin gene.

GATA:<br /> The mutation of the single GATA TFBS in the promoter led to a reduced expression phenotype very similar to that of JAK-STAT TFBS mutations. In contrast, ubiquitous somatic KO mutations of pannier did not affect the basal or induced lectin-24A expression levels. The overactivation of pannier using an allele that cannot be negatively regulated leads to a higher induction of Lectin-24A gene expression, strikingly with basal expression going up to induced levels.

Reviewer #3 (Public review):

Summary:

In this very thorough manuscript, the authors provide further evidence that the lectin-24A gene in Drosophila melanogaster is directly involved in the anti-parasitoid wasp humoral immune reaction.

Strengths:

In this study in particular they use a fluorescent reporter and promoter-bashing to determine how this gene is regulated. They find that JAK/STAT, Pannier, and NF-κB signaling are integral to the regulation of lectin-24A and to the humoral anti-parasitoid immune response. These claims are well supported by the experimental design, results, and analysis.

Weaknesses:

A bit of clarity is needed regarding Figure 4a as well as on the rationale for the lengths of the promoter intervals used.

eLife Assessment

This manuscript introduces a new low-cost and accessible method for assembling combinatorially complete microbial consortia using basic laboratory equipment, which is a valuable contribution to the field of microbial ecology and biotechnology. The evidence presented is convincing, demonstrating the method's effectiveness through empirical testing on both synthetic colorants and Pseudomonas aeruginosa strains.

Reviewer #1 (Public review):

Summary:

This work develops a simple, rapid, low-cost methodology for assembling combinatorially complete microbial consortia using basic laboratory equipment. The motivation behind this work is to make the study of microbial community interactions more accessible to laboratories that lack specialized equipment such as robotic liquid handlers or microfluidic devices. The method was tested on a library of Pseudomonas aeruginosa strains to demonstrate its practicality and effectiveness. It provided a means to explore the complex functional interactions within microbial communities and identify optimal consortia for specific functions, such as biomass production.

Strengths:

The primary strength of this manuscript lies in its accessibility and practicality. The method proposed by the authors allows any laboratory with standard equipment, such as multichannel pipettes and 96-well plates, to readily construct all possible combinations of microbial consortia from a given set of species. This greatly enhances access to full factorial designs, which were previously limited to labs with advanced technology.

Another strength of the manuscript is the measurement and analysis of the biomass of all possible combinations of 8 strains of P. aeruginosa. This analysis provides a concrete example of how the authors' new methodology can be used to identify the best-performing communities and map pairwise and higher-order functional interactions.

Notably, the authors do exceptionally well in providing a thorough description of the methodology, including detailed protocols and an R script for customizing the method to different experimental needs. This enhances the reproducibility and adaptability of the methodology, making it a valuable resource for researchers wishing to adopt this methodology.

Weaknesses:

While the methodology is robust and well-presented, there are some limitations that should be acknowledged more thoroughly. First, the method's scalability is an important factor. The authors indicate that it should be effective for up to 10-12 species, but there is no discussion of what sets this scale: time, amount of labor, consumables, the likelihood of error, sample volume, etc. Second, this methodology is tailored to construct communities where the abundance of each strain is identical in each combination. Therefore, combinations with a different number of strains also differ in the total initial amount of microbial cells. Second, variations in the initial proportions of the same set of strains cannot be readily explored. Third, the manuscript only discusses how to construct the combinations, and not how to assay them afterward (e.g. for community function, interspecific interactions, etc'). While details on how to achieve these goals are clearly outside the scope of this work, the use of biomass as an example function may obfuscate this caveat, which should be stated more explicitly.

Reviewer #2 (Public review):

Summary:

A simple and effective method for combinatorial assembly of microbes in synthetic communities of <12 species.

Strengths:

Overall this manuscript is a useful contribution. The efficiency of the method and clarity of the presentation is a strength. It is well-written and easy to follow. The figures are great, the pedagogical narrative is crisp. I can imagine the method being used in lots of other contexts too.

Weaknesses:

The authors could better clarify what HOIs mean. They could address challenges with assaying community function. However, neither of these "weaknesses" affects the primary goal of the paper which is methodological.

Reviewer #3 (Public review):

The authors developed a useful methodology for generating all combinations of multiple reagents using standard lab equipment. This methodology has clear uses for studying microbial ecology as they demonstrated. The methodology will likely be useful for other types of experiments that require exhaustive testing of all possible combinations of a given set of reagents (e.g., drug-drug antagonism and synergy).

The authors provided a useful R script that generates a detailed experimental protocol for building the desired combination from any number of reagents. The produced document is useful and has clear instructions. The output of the computer script will be strengthened if graphical output is also provided (similar to the one provided in Figure 1C).

The authors show that the error rate of the method doesn't go up with the number of combinations using dyes (Figure 2).

The authors demonstrate the value of their methodology for studying interactions within microbial consortia by assembling all possible combinations of eight strains of Pseudomonas aeruginosa. The value of their methodology for this application is well-founded. However, it is also unclear why specific experimental choices were made for this application. It is unclear why authors continue to show the absorbance measurements of strain assemblies over the entire wavelength spectrum and not just for ABS 600 nm (Figures 3 and 4). It is also unclear why the authors provided information on the "sum of the three spectra" as this reference line is meaningless and not a reasonable null model for estimating how well specific strain combinations will grow together.

Figure 5 illustrates the various analysis types that can be performed on the data collected from growing combinations of eight Pseudomonas aeruginosa strains. It is a very informative figure since it provides a "roadmap" on the various ways in which the dataset produced can be explored. The information in Figures 5 and S6 will likely be very useful for a wide audience.

eLife Assessment

This study provides important new insight into chemosensation by showing that odors activate taste sensory neurons in Drosophila to promote feeding behaviors. Using a convincing methodology, combining behavior analysis, electrophysiology, and calcium imaging, Kazama and colleagues have deepened our understanding of how this phenomenon modulates the feeding behavior, although in some cases additional controls would strengthen the conclusions. Here, the authors articulate a clear instance of a novel neural and behavioral mechanism for gustatory receptors in an olfactory response making this work relevant to researchers studying chemosensation, sensory biology, and insect behavior.

Reviewer #1 (Public review):

Summary:

Odor- and taste-sensing are mediated by two different systems, the olfactory and gustatory systems, and have different behavioral roles. In this study, Wei et al. challenge this dichotomy by showing that odors can activate gustatory receptor neurons (GRNs) in Drosophila to promote feeding responses, including the proboscis extension response (PER) that was previously thought to be driven only by taste. While previous studies suggested that odors can promote PER to appetitive tastants, Wei et al. go further to show that odors alone cause PER, this effect is mediated through sweet-sensing GRNs, and sugar receptors are required. The study also shows that odor detection by bitter-sensing GRNs suppresses PER. The authors' conclusions are supported by behavioral assays, calcium imaging, electrophysiological recordings, and genetic manipulations. The observation that both attractive and aversive odors promote PER leaves an open question as to why this effect is adaptive. Overall, the study sheds new light on chemosensation and multimodal integration by showing that odor and taste detection converge at the level of sensory neurons, a finding that is interesting and surprising while also being supported by another recent study (Dweck & Carlson, Sci Advances 2023).

Strengths:

(1) The main finding that odors alone can promote PER by activating sweet-sensing GRNs is interesting and novel.

(2) The study uses video tracking of the proboscis to quantify PER rather than manual scoring, which is typically used in the field. The tracking method is less subjective and provides a higher-resolution readout of the behavior.

(3) The study uses calcium imaging and electrophysiology to show that odors activate GRNs. These represent complementary techniques that measure activity at different parts of the GRN (axons versus dendrites, respectively) and strengthen the evidence for this conclusion.

(4) Genetic manipulations show that odor-evoked PER is primarily driven by sugar GRNs and sugar receptors rather than olfactory neurons. This is a major finding that distinguishes this work from previous studies of odor effects on PER and feeding (e.g., Reisenman & Scott, 2019; Shiraiwa, 2008) that assumed or demonstrated that odors were acting through olfactory neurons.

Weaknesses/Limitations:

1) The authors may want to discuss why PER to odors alone has not been previously reported, especially as they argue that this is a broad effect evoked by many different odors. Previous studies testing the effect of odors on PER only observed odor enhancement of PER to sugar (Oh et al., 2021; Reisenman & Scott, 2019; Shiraiwa, 2008) and some of these studies explicitly show no effect of odor alone or odor with low sugar concentration; regardless, the authors likely would have noticed if PER to odor alone had occurred. Readers of this paper may also be aware of unpublished studies failing to observe an effect of PER on odor alone (including studies performed by this reviewer and unrelated work by other colleagues in the field), which of course the authors are not expected to directly address but may further motivate the authors to provide possible explanations.

(2) Many of the odor effects on behavior or neuronal responses were only observed at very high concentrations. Most effects seemed to require concentrations of at least 10-2 (0.01 v/v), which is at the high end of the concentration range used in olfactory studies (e.g., Hallem et al., 2004), and most experiments in the paper used a far higher concentration of 0.5 v/v. It is unclear whether these are concentrations that would be naturally encountered by flies.

(3) The calcium imaging data showing that sugar GRNs respond to a broad set of odors contrasts with results from Dweck & Carlson (Sci Adv, 2023) who recorded sugar neurons with electrophysiology and observed responses to organic acids, but not other odors. This discrepancy is not discussed.

(4) Related to point #1, it would be useful to see a quantification of the percent of flies or trials showing PER for the key experiments in the paper, as this is the standard metric used in most studies and would help readers compare PER in this study to other studies. This is especially important for cases where the authors are claiming that odor-evoked PER is modulated in the same way as previously shown for sugar (e.g., the effect of starvation in Figure S4).

(5) Given the novelty of the finding that odors activate sugar GRNs, it would be useful to show more examples of GCaMP traces (or overlaid traces for all flies/trials) in Figure 3. Only one example trace is shown, and the boxplots do not give us a sense of the reliability or time course of the response. A related issue is that the GRNs appear to be persistently activated long after the odor is removed, which does not occur with tastes. Why should that occur? Does the time course of GRN activation align with the time course of PER, and do different odors show differences in the latency of GRN activation that correspond with differences in the latency of PER (Figure S1A)?

(6) Several controls are missing, and in some cases, experimental and control groups are not directly compared. In general, Gal4/UAS experiments should include comparisons to both the Gal4/+ and UAS/+ controls, at least in cases where control responses vary substantially, which appears to be the case for this study. These controls are often missing, e.g. the Gal4/+ controls are not shown in Figure 2C-G and the UAS/+ controls are not shown in Figure 2J-L (also, the legend for the latter panels should be revised to clarify what the "control" flies are). For the experiments in Figure S5, the data are not directly compared to any control group. For several other experiments, the control and experimental groups are plotted in separate graphs (e.g., Figure 2C-G), and they would be easier to visually compare if they were together. In addition, for each experiment, the authors should denote which comparisons are statistically significant rather than just reporting an overall p-value in the legend (e.g., Figure 2H-L).

(7) Additional controls would be useful in supporting the conclusions. For the Kir experiments, how do we know that Kir is effective, especially in cases where odor-evoked PER was not impaired (e.g., Orco/Kir)? The authors could perform controls testing odor aversion, for example. For the Gr5a mutant, few details are provided on the nature of the control line used and whether it is in the same genetic background as the mutant. Regardless, it would be important to verify that the Gr5a mutant retains a normal sense of smell and shows normal levels of PER to stimuli other than sugar, ruling out more general deficits. Finally, as the method of using DeepLabCut tracking to quantify PER was newly developed, it is important to show the accuracy and specificity of detecting PER events compared to manual scoring.

(8) The authors' explanation of why both attractive and aversive odors promote PER (lines 249-259) did not seem convincing. The explanation discusses the different roles of smell and taste but does not address the core question of why it would be adaptive for an aversive odor, which flies naturally avoid, to promote feeding behavior.

Reviewer #2 (Public review):

Summary:

A gustatory receptor and neuron enhances an olfactory behavioral response, proboscis extension.

This manuscript clearly establishes a novel mechanism by which a gustatory receptor and neuron evokes an olfactory-driven behavioral response. The study expands recent observations by Dweck and Carlson (2023) that suggest new and remarkable properties among GRNs in Drosophila. Here, the authors articulate a clear instance of a novel neural and behavioral mechanism for gustatory receptors in an olfactory response.

Strengths:

The systematic and logical use of genetic manipulation, imaging and physiology, and behavioral analysis makes a clear case that gustatory neurons are bona fide olfactory neurons with respect to proboscis extension behavior.

Weaknesses:

No weaknesses were identified by this reviewer.

Reviewer #3 (Public review):

Summary:

Using flies, Kazama et al. combined behavioral analysis, electrophysiological recordings, and calcium imaging experiments to elucidate how odors activate gustatory receptor neurons (GRNs) and elicit a proboscis extension response, which is interpreted as a feeding response.

The authors used DeepLabCut v2.0 to estimate the extension of the proboscis, which represents an unbiased and more precise method for describing this behavior compared to manual scoring.

They demonstrated that the probability of eliciting a proboscis extension increases with higher odor concentrations. The most robust response occurs at a 0.5 v/v concentration, which, despite being diluted in the air stream, remains a relatively high concentration. Although the probability of response is not particularly high it is higher than control stimuli. Notably, flies respond with a proboscis extension to both odors that are considered positive and those regarded as negative.

The authors used various transgenic lines to show that the response is mediated by GRNs. Specifically, inhibiting Gr5a reduces the response, while inhibiting Gr66a increases it in fed flies. Additionally, they find that odors induce a strong positive response in both types of GRNs, which is abolished when the labella of the proboscis are covered. This response was also confirmed through electrophysiological tip recordings.

Finally, the authors demonstrated that the response increases when two stimuli of different modalities, such as sucrose and odors, are presented together, suggesting clear multimodal integration.

Strengths:

The integration of various techniques, that collectively support the robustness of the results.

The assessment of electrophysiological recordings in intact animals, preserving natural physiological conditions.

Weaknesses:

The behavioral response is observed in only a small proportion of animals.

eLife Assessment

This work by Hill and colleagues offers valuable insights into the development of learning abilities involved in action control from toddlerhood to adulthood. Data across 4 experiments provide solid evidence that in a task involving noisy but continuous action, the ability to learn reward probability develops gradually and may be limited by spatial processing and probabilistic reward reasoning. Questions remain about whether the task truly measures motor learning or more generic cognitive capacities, and whether a proposed model of reinforcement-based motor learning adequately captures the data.

Reviewer #1 (Public review):

Summary:

Here the authors address how reinforcement-based sensorimotor adaptation changes throughout development. To address this question, they collected many participants in ages that ranged from small children (3 years old) to adulthood (18+ years old). The authors used four experiments to manipulate whether binary and positive reinforcement was provided probabilistically (e.g., 30 or 50%) versus deterministically (e.g.,100%), and continuous (infinite possible locations) versus discrete (binned possible locations) when the probability of reinforcement varied along the span of a large redundant target. The authors found that both movement variability and the extent of adaptation changed with age.

Strengths:

The major strength of the paper is the number of participants collected (n = 385). The authors also answer their primary question, that reinforcement-based sensorimotor adaptation changes throughout development, which was shown by utilizing established experimental designs and computational modelling.

Weaknesses:

Potential concerns involve inconsistent findings with secondary analyses, current assumptions that impact both interpretation and computational modelling, and a lack of clearly stated hypotheses.

(1) Multiple regression and Mediation Analyses.

The challenge with these secondary analyses is that:<br /> (a) The results are inconsistent between Experiments 1 and 2, and the analysis was not performed for Experiments 3 and 4,<br /> (b) The authors used a two-stage procedure of using multiple regression to determine what variables to use for the mediation analysis, and<br /> (c) The authors already have a trial-by-trial model that is arguably more insightful.

Given this, some suggested changes are to:<br /> (a) Perform the mediation analysis with all the possible variables (i.e., not informed by multiple regression) to see if the results are consistent.<br /> (b) Move the regression/mediation analysis to Supplementary, since it is slightly distracting given current inconsistencies and that the trial-by-trial model is arguably more insightful.

(2) Variability for different phases and model assumptions:

A nice feature of the experimental design is the use of success and failure clamps. These clamped phases, along with baseline, are useful because they can provide insights into the partitioning of motor and exploratory noise. Based on the assumptions of the model, the success clamp would only reflect variability due to motor noise (excludes variability due to exploratory noise and any variability due to updates in reach aim). Thus, it is reasonable to expect that the success clamps would have lower variability than the failure clamps (which it obviously does in Figure 6), and presumably baseline (which provides success and failure feedback, thus would contain motor noise and likely some exploratory noise).

However, in Figure 6, one visually observes greater variability during the success clamp (where it is assumed variability only comes from motor noise) compared to baseline (where variability would come from:<br /> (a) Motor noise.<br /> (b) Likely some exploratory noise since there were some failures.<br /> (c) Updates in reach aim.

Given the comment above, can the authors please:<br /> (a) Statistically compare movement variability between the baseline, success clamp, and failure clamp phases.<br /> (b) The authors have examined how their model predicts variability during success clamps and failure clamps, but can they also please show predictions for baseline (similar to that of Cashaback et al., 2019; Supplementary B, which alternatively used a no feedback baseline)?<br /> (c) Can the authors show whether participants updated their aim towards their last successful reach during the success clamp? This would be a particularly insightful analysis of model assumptions.<br /> (d) Different sources of movement variability have been proposed in the literature, as have different related models. One possibility is that the nervous system has knowledge of 'planned (noise)' movement variability that is always present, irrespective of success (van Beers, R. J. (2009). Motor learning is optimally tuned to the properties of motor noise. Neuron, 63(3), 406-417). The authors have used slightly different variations of their model in the past. Roth et al (2023) directly compared several different plausible models with various combinations of motor, planned, and exploratory noise (Roth A, 2023, "Reinforcement-based processes actively regulate motor exploration along redundant solution manifolds." Proceedings of the Royal Society B 290: 20231475: see Supplemental). Their best-fit model seems similar to the one the authors propose here, but the current paper has the added benefit of the success and failure clamps to tease the different potential models apart. In light of the results of a), b), and c), the authors are encouraged to provide a paragraph on how their model relates to the various sources of movement variability and other models proposed in the literature.<br /> (e) line 155. Why would the success clamp be composed of both motor and exploratory noise? Please clarify in the text

(3) Hypotheses:

The introduction did not have any hypotheses of development and reinforcement, despite the discussion above setting up potential hypotheses. Did the authors have any hypotheses related to why they might expect age to change motor noise, exploratory noise, and learning rates? If so, what would the experimental behaviour look like to confirm these hypotheses? Currently, the manuscript reads more as an exploratory study, which is certainly fine if true, it should just be explicitly stated in the introduction. Note: on line 144, this is a prediction, not a hypothesis. Line 225: this idea could be sharpened. I believe the authors are speaking to the idea of having more explicit knowledge of action-target pairings changing behaviour.

Reviewer #2 (Public review):

Summary:

In this study, Hill and colleagues use a novel reinforcement-based motor learning task ("RML"), asking how aspects of RML change over the course of development from toddler years through adolescence. Multiple versions of the RML task were used in different samples, which varied on two dimensions: whether the reward probability of a given hand movement direction was deterministic or probabilistic, and whether the solution space had continuous reach targets or discrete reach targets. Using analyses of both raw behavioral data and model fits, the authors report four main results: First, developmental improvements reflected 3 clear changes, including increases in exploration, an increase in the RL learning rate, and a reduction of intrinsic motor noise. Second, changes to the task that made it discrete and/or deterministic both rescued performance in the youngest age groups, suggesting that observed deficits could be linked to continuous/probabilistic learning settings. Overall, the results shed light on how RML changes throughout human development, and the modeling characterizes the specific learning deficits seen in the youngest ages.

Strengths:

(1) This impressive work addresses an understudied subfield of motor control/psychology - the developmental trajectory of motor learning. It is thus timely and will interest many researchers.

(2) The task, analysis, and modeling methods are very strong. The empirical findings are rather clear and compelling, and the analysis approaches are convincing. Thus, at the empirical level, this study has very few weaknesses.

(3) The large sample sizes and in-lab replications further reflect the laudable rigor of the study.

(4) The main and supplemental figures are clear and concise.

Weaknesses:

(1) Framing.<br /> One weakness of the current paper is the framing, namely w/r/t what can be considered "cognitive" versus "non-cognitive" ("procedural?") here. In the Intro, for example, it is stated that there are specific features of RML tasks that deviate from cognitive tasks. This is of course true in terms of having a continuous choice space and motor noise, but spatially correlated reward functions are not a unique feature of motor learning (see e.g. Giron et al., 2023, NHB). Given the result here that simplifying the spatial memory demands of the task greatly improved learning for the youngest cohort, it is hard to say whether the task is truly getting at a motor learning process or more generic cognitive capacities for spatial learning, working memory, and hypothesis testing. This is not a logical problem with the design, as spatial reasoning and working memory are intrinsically tied to motor learning. However, I think the framing of the study could be revised to focus in on what the authors truly think is motor about the task versus more general psychological mechanisms. Indeed, it may be the case that deficits in motor learning in young children are mostly about cognitive factors, which is still an interesting result!

(2) Links to other scholarship.<br /> If I'm not mistaken a common observation in studies of the development of reinforcement learning is a decrease in exploration over-development (e.g., Nussenbaum and Hartley, 2019; Giron et al., 2023; Schulz et al., 2019); this contrasts with the current results which instead show an increase. It would be nice to see a more direct discussion of previous findings showing decreases in exploration over development, and why the current study deviates from that. It could also be useful for the authors to bring in concepts of different types of exploration (e.g. "directed" vs "random"), in their interpretations and potentially in their modeling.

(3) Modeling.<br /> First, I may have missed something, but it is unclear to me if the model is actually accounting for the gradient of rewards (e.g., if I get a probabilistic reward moving at 45˚, but then don't get one at 40˚, I should be more likely to try 50˚ next then 35˚). I couldn't tell from the current equations if this was the case, or if exploration was essentially "unsigned," nor if the multiple-trials-back regression analysis would truly capture signed behavior. If the model is sensitive to the gradient, it would be nice if this was more clear in the Methods. If not, it would be interesting to have a model that does "function approximation" of the task space, and see if that improves the fit or explains developmental changes. Second, I am curious if the current modeling approach could incorporate a kind of "action hysteresis" (aka perseveration), such that regardless of previous outcomes, the same action is biased to be repeated (or, based on parameter settings, avoided).

(4) Psychological mechanisms.<br /> There is a line of work that shows that when children and adults perform RL tasks they use a combination of working memory and trial-by-trial incremental learning processes (e.g., Master et al., 2020; Collins and Frank 2012). Thus, the observed increase in the learning rate over development could in theory reflect improvements in instrumental learning, working memory, or both. Could it be that older participants are better at remembering their recent movements in short-term memory (Hadjiosif et al., 2023; Hillman et al., 2024)?

Reviewer #3 (Public review):

Summary:

The study investigates reinforcement learning across the lifespan with a large sample of participants recruited for an online game. It finds that children gradually develop their abilities to learn reward probability, possibly hindered by their immature spatial processing and probabilistic reasoning abilities. Motor noise, reinforcement learning rate, and exploration after a failure all contribute to children's subpar performance.

Strengths:

(1) The paradigm is novel because it requires continuous movement to indicate people's choices, as opposed to discrete actions in previous studies.

(2) A large sample of participants were recruited.

(3) The model-based analysis provides further insights into the development of reinforcement learning ability.

Weaknesses:

(1) The adequacy of model-based analysis is questionable, given the current presentation and some inconsistency in the results.

(2) The task should not be labeled as reinforcement motor learning, as it is not about learning a motor skill or adapting to sensorimotor perturbations. It is a classical reinforcement learning paradigm.

eLife Assessment

This study presents TopOMetry, an important novel dimensionality reduction method that addresses a signficant challenge in the analysis of single-cell RNA sequencing data. The authors provide convincing evidence of the method's utility across various tasks, including estimating intrinsic dimensionalities and identifying cell types. The work would benefit from more rigorous validation and a reorganization of the text.

Reviewer #1 (Public review):

Summary:

Sidarta-Oliveira et al. present TopOMetry, a novel dimensionality reduction method based on the eigendecomposition of approximated Laplace-Beltrami Operator. Shortly, TopOMetry is an iterative version of the existing spectral methods (e.g., Laplacian Eigenmap or Diffusion map). It approximates the Laplacian operators twice, once in a "phenotypic space" and then once again in the eigenbases space. By doing this the approximated operator will contain more information of the manifold, which allows for more robust and accurate downstream analyses.

Strengths:

(1) The approach was rigorously tested based on synthetic and real single-cell RNA-seq datasets.

(2) The package is well-made and easily scalable to millions of cells.

(3) The comprehensive documentation helps the end-users to run desired analyses.

Weaknesses:

(1) The method is an extension of the current state-of-art methods, not a fundamentally new one.

(2) Considering the target readers, the paper contains a lot of jargon.

Reviewer #2 (Public review):

Summary:

This work introduces a novel framework to systematically learn the latent dimensions of single-cell data, grounded in the theory of the Riemannian manifold. The authors demonstrate how this framework can be applied to various important tasks, such as estimating intrinsic dimensionalities, annotating cell types, etc. They did a great job of tackling an important but not yet established problem in the field and approaching it with a theoretically sound and novel approach. I think after a more rigorous and comprehensive validation, this work could be impactful.

Strengths:

(1) Dimensionality reduction is a routine step in analyzing many high-dimensional data, such as molecular data. While the downstream analysis results depend heavily on this step, existing methods rely on strong assumptions and are sometimes heuristic. The authors present a novel, theoretically grounded approach to address this important problem.

(2) The authors demonstrated its usability in downstream analysis in a comprehensive manner. In particular, they show evidence suggesting novel T-cell subpopulations.

(3) I commend the authors for releasing and maintaining their software well with comprehensive documentation. This significantly increases the usability and accessibility of the method.

Weaknesses:

(1) To encourage the single-cell community to adopt this method, the authors should more clearly demonstrate its advantages over existing methods. There are many single cell analysis algorithms that are proposed in each task and some of them are widely used by biologists. However, the comparison in this work is somewhat limited. For example, Even methods mentioned in the relevant work paragraph (2nd paragraph) on page 2 are not all compared, or the reason why they are not included is not discussed. Also, I am curious how PC dimensions are determined. The choice of 300 PCs on page 11 seems arbitrary. Furthermore, the usefulness of dimension-reduced data also depends a lot on the preceding processing steps, such as highly variable gene selection. I understand it is hard to control all those factors, but I think there is room for improvement.

(2) The paper lacks experiments that validate the results. It would be beneficial to see additional evaluation settings with better-established ground truths to more strongly demonstrate the method's effectiveness.

(3) The effect of various parameters, such as those involved in k-nearest neighbors (KNN) or choosing the appropriate Laplacian operator, is not comprehensively explored. How can we ensure the analysis is not overly sensitive to these parameters?

(4) Batch effects are prevalent in single-cell data. The paper does not adequately address how the proposed method handles this issue.

eLife Assessment

This important study provides convincing evidence that emotional information in biological motion can induce different patterns of pupil responses, which could serve as a behavioral marker of an autistic trait. These results broaden our understanding of how emotional biological motion can automatically trigger physiological changes and reveal the potential of using emotional-modulated pupil response to facilitate the diagnosis of social cognitive disorders. The work will be of broad interest to cognitive neuroscience, psychology, affective neuroscience, and vision science.

Reviewer #1 (Public review):

Summary:

Tian et al. investigated the effects of emotional signals in biological motion on pupil responses. In this study, subjects were presented with point-light biological motion stimuli with happy, neutral, and sad emotions. Their pupil responses were recorded with an eye tracker. Throughout the study, emotion type (i.e., happy/sad/neutral) and BM stimulus type (intact/inverted/non-BM/local) were systematically manipulated. For intact BM stimuli, happy BM induced a larger pupil diameter than neutral BM, and neutral BM also induced a larger pupil diameter than sad BM. Importantly, the diameter difference between happy and sad BM correlated with the autistic trait of individuals. These effects disappeared for the inverted BM and non-BM stimuli. Interestingly, both happy and sad emotions show superiority in pupil diameter.

Strengths:

(1) The experimental conditions and results are very easy to understand.<br /> (2) The writing and data presentation are clear.<br /> (3) The methods are sound. I have no problems with the experimental design and results.

Reviewer #2 (Public review):

Summary:

Through a serial of four experiments, Yuan, Wang and Jiang examined pupil size responses to emotion signals in point-light motion stimuli. Experiment 1 examined upright happy, sad and neutral point-light biological motion (BM) walkers. The happy BM induced a significantly larger pupil response than the neutral, whereas the sad BM evoked a significantly smaller pupil size than the neutral BM. Experiment 2 examined inverted BM walkers. Experiment 3 examined BM stimuli with acceleration removed. No significant effects of emotion were found in neither Experiment 2 nor Experiment 3. Experiment 4 examined scrambled BM stimuli, in which local motion features were preserved while the global configuration was disrupted. Interestingly, the scrambled happy and sad BM led to significant greater pupil size than the scrambled neutral BM at a relatively early time, while no significant difference between the scrambled happy and sad BM was found. Thus, the authors argue that these results suggest multi-level processing of emotions in life motion signals.

Strengths:

The experiments were carefully designed and well-executed, with point-light stimuli that eliminate many potential confounding effects of low-level visual features such as luminance, contrast, and spatial frequency.

Overall, I think this is a well-written paper with solid experimental results that support the claim of the authors, i.e., the human visual system may process emotional information in biological motion at multiple levels. Given the key role of emotion processing in normal social cognition, the results will be of interest not only to basic scientists who study visual perception, but also to clinical researchers who work with patients of social cognitive disorders. In addition, this paper suggests that examining pupil size responses could be a very useful methodological tool to study brain mechanisms underlying emotion processing.

Reviewer #3 (Public review):

Summary:<br /> The overarching goal of the authors was to understand whether emotional information conveyed through point-light biological motion can trigger automatic physiological responses, as reflected in pupil size.

Strengths:<br /> This manuscript has several noticeable strengths: it addresses an intriguing research question that fills that gap in existing literature, presents a clear and accurate presentation of the current literature, and conducts a series of experiments and control experiments with adequete sample size. Yet, it also entails several noticeable limitations - especially in the study design and statistical analyses.

Assessment of the revision:

The authors have done a thorough job revising the manuscript, effectively addressing all of my previous concerns.

Author response:

The following is the authors’ response to the original reviews.

eLife assessment:

This study presents an important finding on the implicit and automatic emotion perception from biological motion (BM). The evidence supporting the claims of the authors is solid, although inclusion of a larger number of samples and more evidence for the discrepancy between Intact and local emotional BMs would have strengthened the study. The work will be of broad interest to perceptual and cognitive neuroscience.

We express our sincere gratitude for the positive and constructive evaluation of our manuscript. We have now included more participants and conducted a replication experiment to strengthen our results.

Reviewer #1 (Public Review):

Summary:

Tian et al. investigated the effects of emotional signals in biological motion on pupil responses. In this study, subjects were presented with point-light biological motion stimuli with happy, neutral, and sad emotions. Their pupil responses were recorded with an eye tracker. Throughout the study, emotion type (i.e., happy/sad/neutral) and BM stimulus type (intact/inverted/non-BM/local) were systematically manipulated. For intact BM stimuli, happy BM induced a larger pupil diameter than neutral BM, and neutral BM also induced a larger pupil diameter than sad BM. Importantly, the diameter difference between happy and sad BM correlated with the autistic trait of individuals. These effects disappeared for the inverted BM and non-BM stimuli. Interestingly, both happy and sad emotions show superiority in pupil diameter.

Strengths:

(1) The experimental conditions and results are very easy to understand.

(2) The writing and data presentation are clear.

(3) The methods are sound. I have no problems with the experimental design and results.

Weaknesses:

(1) My main concern is the interpretation of the intact and local condition results. The processing advantage of happy emotion is not surprising given a number of existing studies. However, the only difference here seems to be the smaller (or larger) pupil diameter for sad compared to neutral in the intact (or local, respectively) condition. The current form only reports this effect but lacks in-depth discussions and explanations as to why this is the case.

Thanks for pointing this out, our apology for not making this point clear. It has long been documented that pupil size reflects the degree of cognitive effort and attention input (Joshi & Gold, 2019; van der Wel & van Steenbergen, 2018), and indexes the noradrenalin activity in emotion processing structures like amygdala (Dal Monte et al., 2015; Harrison et al., 2006; Liddell et al., 2005). Accordingly, we proposed that the smaller pupil response observed under the sad condition as compared to the neutral condition is because the sad biological motion (BM) could be less efficient in attracting visual attention and evoking emotional arousal. In line with this, it has been found that infants looked more at the neutral point-light walker when displayed in pair with the sad walker (Ogren et al., 2019), suggesting that the sad BM is less effective in capturing visual attention than the neutral BM. Besides, neural studies have revealed that, compared with other emotions (anger, happiness, disgust, and fear), the processing of sad emotion failed to evoke heightened activities in any emotionally relevant brain regions including the amygdala, the extrastriate body area (EBA) and the fusiform body area (FBA) (Peelen et al., 2007)(Peelen et al., 2007). The current study echoed with these previous findings by demonstrating a disadvantage for intact sad BM in evoking pupil responses. Notably, different from the intact sad BM, the local sad BM would instead induce stronger pupil responses than the neutral local BM. This distinctive pupil modulation effect observed in intact and local sad BM could be explained as a multi-level emotion processing model of BM. Specifically, even though both the intact and local BM conveyed important life information (Chang & Troje, 2008, 2009; Simion et al., 2008), the latter is deprived of the global form feature. Hence, the processing of emotions in local BM may occur at a more basic and preliminary level, responding to the general affective salient emotion information (happy and sad) without detailed analysis. In fact, similar dissociated emotion processing phenomenon has been observed in another important type of emotional signal with analogous function (i.e., facial expression). For example, happy and fearful faces elicited differential amygdala activations when perceived consciously. However, they elicited comparable amygdala activations when suppressed (Williams et al., 2004). Moreover, it has been proposed that there exist two parallel routes for facial expression processing: a quick but coarse subcortical route that detects affective salient information without detailed analysis, and a fine-grained but slow cortical route that discriminates the exact emotion type. Similarly, the dissociated emotion processing in local and intact BM may function in the same manner, with the former serving as a primary emotion detection mechanism and the latter serving as a detailed emotion discrimination mechanism. Still, future studies adopting more diverse experimental paradigms and neuroimaging techniques were needed to further investigate this issue. We have added these points and more thoroughly discussed the potential mechanism in the revised text (see lines 329-339, 405-415, 418-420).

References:

Chang, D. H. F., & Troje, N. F. (2008). Perception of animacy and direction from local biological motion signals. Journal of Vision, 8(5), 3. https://doi.org/10.1167/8.5.3

Chang, D. H. F., & Troje, N. F. (2009). Characterizing global and local mechanisms in biological motion perception. Journal of Vision, 9(5), 8–8. https://doi.org/10.1167/9.5.8

Dal Monte, O., Costa, V. D., Noble, P. L., Murray, E. A., & Averbeck, B. B. (2015). Amygdala lesions in rhesus macaques decrease attention to threat. Nature Communications, 6(1). https://doi.org/10.1038/ncomms10161

Harrison, N. A., Singer, T., Rotshtein, P., Dolan, R. J., & Critchley, H. D. (2006). Pupillary contagion: central mechanisms engaged in sadness processing. Social Cognitive and Affective Neuroscience, 1(1), 5–17. https://doi.org/10.1093/scan/nsl006

Joshi, S., & Gold, J. I. (2019). Pupil size as a window on neural substrates of cognition. Trends in Cognitive Sciences, 24(6), 466–480. https://doi.org/10.31234/osf.io/dvsme

Liddell, B. J., Brown, K. J., Kemp, A. H., Barton, M. J., Das, P., Peduto, A., Gordon, E., & Williams, L. M. (2005). A direct brainstem–amygdala–cortical ‘alarm’ system for subliminal signals of fear. NeuroImage, 24(1), 235–243.

Ogren, M., Kaplan, B., Peng, Y., Johnson, K. L., & Johnson, S. P. (2019). Motion or emotion: infants discriminate emotional biological motion based on low-level visual information. Infant Behavior and Development, 57, 101324. https://doi.org/10.1016/j.infbeh.2019.04.006

Peelen, M. V., Atkinson, A. P., Andersson, F., & Vuilleumier, P. (2007). Emotional modulation of body-selective visual areas. Social Cognitive and Affective Neuroscience, 2(4), 274–283. https://doi.org/10.1093/scan/nsm023

Simion, F., Regolin, L., & Bulf, H. (2008). A predisposition for biological motion in the newborn baby. Proceedings of the National Academy of Sciences, 105(2), 809–813. https://doi.org/10.1073/pnas.0707021105

van der Wel, P., & van Steenbergen, H. (2018). Pupil dilation as an index of effort in cognitive control tasks: a review. Psychonomic Bulletin & Review, 25(6), 2005–2015. https://doi.org/10.3758/s13423-018-1432-y

Williams, M. A., Morris, A. P., McGlone, F., Abbott, D. F., & Mattingley, J. B. (2004). Amygdala responses to fearful and happy facial expressions under conditions of binocular suppression. Journal of Neuroscience, 24(12), 2898-2904.

(2) I also found no systematic discussion and theoretical contributions regarding the correlation with the autistic traits. If the main point of this paper is to highlight an implicit and objective behavioral marker of the autistic trait, more interpretation and discussion of the links between the results and existing findings in ASD are needed.

We thank the reviewer for this insightful suggestion. The perception of biological motion (BM) has long been considered an important hallmark of social cognition. Abundant studies reported that individuals with social cognitive deficits (e.g., ASD) were impaired in BM perception (Blake et al., 2003; Freitag et al., 2008; Klin et al., 2009; Nackaerts et al., 2012). More recently, it has been pointed out that the extraction of more complex social information (e.g., emotions, intentions) from BM, as compared to basic BM recognitions, could be more effective in detecting ASDs (Federici et al., 2020; Koldewyn et al., 2009; Parron et al., 2008; Todorova et al., 2019). Specifically, a meta-analysis found that the effect size expanded nearly twice when the task required emotion recognition as compared to simple perception/detection (Todorova et al., 2019). However, for the high-functioning ASD individuals, it has been reported that they showed comparable performance with the control group in explicitly labelling BM emotions, while their responses were rather delayed (Mazzoni et al., 2021). This suggested that ASD individuals could adopt compensatory strategies to complete the explicit BM labelling task, while their automatic behavioural responses remained impaired. This highlights the importance of using more objective measures that do not rely on active reports to investigate the intrinsic perception of emotions from BM and its relationship with ASD-related social deficits. The current study thus introduced the pupil size measurement to this field, and we combined it with the passive viewing task to investigate the more automatic aspect of BM emotion processing. More importantly, in addition to diagnostic ASDs, the non-clinical general population also manifested autistic tendencies that followed normal distribution and demonstrated substantial heritability (Hoekstra et al., 2007). Here, we focused on the autistic tendencies in the general population, and our results showed that pupil modulations by BM emotions were indicative of individual autistic traits. Specifically, passively viewing the happy BMs evoked larger pupil responses than the sad BMs, while such emotional modulation diminished with the increase of autistic tendencies. More detailed test-retest examination further illustrated such a correlation was driven by the general diminishment in pupil modulation effects by emotional BM (happy or sad) for individuals with high autistic tendencies. This finding demonstrated that the automatic emotion processing of BM stimuli was impaired in individuals with high autistic tendencies, lending support to previous studies (Hubert et al., 2006; Nackaerts et al., 2012; Parron et al., 2008). This indicated the utility of emotional BM stimuli and pupil measurement in identifying ASD-related tendencies in both clinical and non-clinical populations. We have added these points to the revised text (see lines 347-375).

References:

Blake, R., Turner, L. M., Smoski, M. J., Pozdol, S. L., & Stone, W. L. (2003). Visual recognition of biological motion is impaired in children with autism. Psychological Science, 14(2), 151–157. https://doi.org/10.1111/1467-9280.01434

Federici, A., Parma, V., Vicovaro, M., Radassao, L., Casartelli, L., & Ronconi, L. (2020). Anomalous perception of biological motion in autism: a conceptual review and meta-analysis. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-61252-3

Freitag, C. M., Konrad, C., Häberlen, M., Kleser, C., von Gontard, A., Reith, W., Troje, N. F., & Krick, C. (2008). Perception of biological motion in autism spectrum disorders. Neuropsychologia, 46(5), 1480–1494. https://doi.org/10.1016/j.neuropsychologia.2007.12.025

Hoekstra, R. A., Bartels, M., Verweij, C. J. H., & Boomsma, D. I. (2007). Heritability of autistic traits in the general population. Archives of Pediatrics & Adolescent Medicine, 161(4), 372. https://doi.org/10.1001/archpedi.161.4.372

Hubert, B., Wicker, B., Moore, D. G., Monfardini, E., Duverger, H., Fonséca, D. D., & Deruelle, C. (2006). Brief report: recognition of emotional and non-emotional biological motion in individuals with autistic spectrum disorders. Journal of Autism and Developmental Disorders, 37(7), 1386–1392. https://doi.org/10.1007/s10803-006-0275-y

Klin, A., Lin, D. J., Gorrindo, P., Ramsay, G., & Jones, W. (2009). Two-year-olds with autism orient to non-social contingencies rather than biological motion. Nature, 459(7244), 257–261. https://doi.org/10.1038/nature07868

Koldewyn, K., Whitney, D., & Rivera, S. M. (2009). The psychophysics of visual motion and global form processing in autism. Brain, 133(2), 599–610. https://doi.org/10.1093/brain/awp272

Mazzoni, N., Ricciardelli, P., Actis-Grosso, R., & Venuti, P. (2021). Difficulties in recognising dynamic but not static emotional body movements in autism spectrum disorder. Journal of Autism and Developmental Disorders, 52(3), 1092–1105. https://doi.org/10.1007/s10803-021-05015-7

Nackaerts, E., Wagemans, J., Helsen, W., Swinnen, S. P., Wenderoth, N., & Alaerts, K. (2012). Recognizing biological motion and emotions from point-light displays in autism spectrum disorders. PLoS ONE, 7(9), e44473. https://doi.org/10.1371/journal.pone.0044473

Parron, C., Da Fonseca, D., Santos, A., Moore, D. G., Monfardini, E., & Deruelle, C. (2008). Recognition of biological motion in children with autistic spectrum disorders. Autism, 12(3), 261–274. https://doi.org/10.1177/1362361307089520

Todorova, G. K., Hatton, R. E. M., & Pollick, F. E. (2019). Biological motion perception in autism spectrum disorder: a meta-analysis. Molecular Autism, 10(1). https://doi.org/10.1186/s13229-019-0299-8

Reviewer #2 (Public Review):

Summary:

Through a series of four experiments, Yuan, Wang and Jiang examined pupil size responses to emotion signals in point-light motion stimuli. Experiment 1 examined upright happy, sad and neutral point-light biological motion (BM) walkers. The happy BM induced a significantly larger pupil response than the neutral, whereas the sad BM evoked a significantly smaller pupil size than the neutral BM. Experiment 2 examined inverted BM walkers. Experiment 3 examined BM stimuli with acceleration removed. No significant effects of emotion were found in neither Experiment 2 nor Experiment 3. Experiment 4 examined scrambled BM stimuli, in which local motion features were preserved while the global configuration was disrupted. Interestingly, the scrambled happy and sad BM led to significantly greater pupil size than the scrambled neutral BM at a relatively early time, while no significant difference between the scrambled happy and sad BM was found. Thus, the authors argue that these results suggest multi-level processing of emotions in life motion signals.

Strengths:

The experiments were carefully designed and well-executed, with point-light stimuli that eliminate many potential confounding effects of low-level visual features such as luminance, contrast, and spatial frequency.

Weaknesses:

Correlation results with limited sample size should be interpreted with extra caution.

Thanks for pointing this out. To strengthen the correlation results, we have conducted a replication experiment (Exp.1b) and added a test-retest examination to further assess the reliability of our measurements. Specifically, a new group of 24 participants (16 females, 8 males) were recruited to perform the identical experiment procedure as in Experiment 1. Then, after at least seven days, they were asked to return to the lab for a retest. The results successfully replicated the previously reported main effect of emotional condition in both the first test (F(2, 46) = 12.0, p < .001, ηp2 = 0.34, Author response image 1A) and the second test (F(2, 46) = 14.8, p < .001, ηp2 = 0.39, Author response image 1B). The happy BM induced a significantly larger pupil response than the neutral BM (First Test: t(23) = 2.60, p = .022, Cohen’s d = 0.53, 95% CI for the mean difference = [0.02, 0.14], Holm-corrected, p = .048 after Bonferroni correction, Author response image 1A; Second Test: t(23) = 3.36, p = .005, Cohen’s d = 0.68, 95% CI for the mean difference = [0.06, 0.24], Holm-corrected, p = .008 after Bonferroni correction, Author response image 1B). On the contrary, the sad BM induced a significantly smaller pupil response than the neutral BM (First Test: t(23) = -2.77, p = .022, Cohen’s d = 0.57, 95% CI for the mean difference = [-0.19, -0.03], Holm-corrected, p = .033 after Bonferroni correction; Second Test: t(23) = -3.19, p = .005, Cohen’s d = 0.65, 95% CI for the mean difference = [-0.24, -0.05], Holm-corrected, p = .012 after Bonferroni correction, Author response image 1B). Besides, the happy BM induced significantly larger pupil response than the sad BM (first test: t(23) = 4.23, p < .001, Cohen’s d = 0.86, 95% CI for the mean difference = [0.10, 0.28], Holm-corrected, p < .001 after Bonferroni correction, Author response image 1A; second test: t(23) = 4.26, p < .001, Cohen’s d = 0.87, 95% CI for the mean difference = [0.15, 0.44], Holm-corrected, p < .001 after Bonferroni correction, Author response image 1B). The results of the cluster-based permutation analysis were also similar (see Supplementary Material for more details).

Author response image 1.

Normalized mean pupil responses in the replication experiment (Experiment 1b) of Experiment 1a and its retest, using the neutral condition as baseline, plotted against happy and sad conditions. (A) In the first test, the group average pupil response to happy intact BM is significantly larger than that to sad and neutral BM, while the pupil response induced by sad BM is significantly smaller than that evoked by neutral BM, replicating the results of Experiment 1a. (B) Moreover, such results were similarly found in the second test.

Notably, we successfully replicated the negative correlation between the happy over sad dilation effect and individual autistic traits in the first test (r(23) = -0.46, p = .023, 95% CI for the mean difference = [-0.73, -0.07], Author response image 2A). No other significant correlations were found (see Author response image 2B-C). Moreover, in the second test, such a correlation was similarly found and was even stronger (r(23) = -0.61, p = .002, 95% CI for the mean difference = [-0.81, -0.27], Author response image 2D). We‘ve also performed a test-retest reliability analysis on the happy over sad pupil dilation effect and the AQ score. The results showed robust correlations. See Author response table 1 for more details.

Author response table 1.

Reliability of pupil size and AQ indices.

Importantly, in the second test, we’ve also observed a significant negative correlation between AQ and the happy minus neutral pupil dilation effect (r(23) = -0.44, p = .032, 95% CI for the mean difference = [-0.72, -0.04], Author response image 2E), and a significant positive correlation between the sad minus neutral pupil size and AQ (r(23) = 0.50, p = .014, 95% CI for the mean difference = [0.12, 0.75], Author response image 2F). This indicated that the overall correlation between happy over sad dilation effect and AQ was driven both by the diminished happy dilation effect as well as the sad constriction effect. Overall, our replication experiment consistently found a significant negative correlation between AQ and happy over sad dilation effect both in the test and the retest. Moreover, it revealed that such an effect was contributed by both a negative correlation between AQ and happy-neutral pupil response and a positive correlation between AQ and sad-neutral pupil response, demonstrating a general impairment in BM emotion perception (happy or sad) for individuals with high autistic tendencies. This also indicated the utility of adopting a test-retest pupil examination to more precisely detect individual autistic tendencies. We have added these points in the revised text (see lines 135-173, lines 178-180).

Author response image 2.

Correlation results for pupil modulation effects and AQ scores in the replication experiment (Experiment 1b) of Experiment 1a and its retest. (A) We replicated the negative correlation between the happy over sad pupil dilation effect and AQ in the first test. (B-C) No other significant correlations were found. (D) In the second test, the negative correlation between the happy over sad pupil dilation effect and AQ was similarly observed and even stronger. (E-F) Moreover, the happy vs. neutral pupil dilation effect and the sad vs. neutral pupil constriction effect respectively correlate with AQ in the second test.

It would be helpful to add discussions as a context to compare the current results with pupil size reactions to emotion signals in picture stimuli.

Thanks for this this thoughtful comment. The modulation of emotional information on pupil responses has been mostly investigated using picture stimuli. Bradley et al. (2008) first demonstrated that humans showed larger pupil responses towards emotional images as compared to neutral images, while no difference was observed between the positive and negative images. This was regarded as the result of increased sympathetic activity induced by emotional arousal that is independent of the emotional valence. Similar results have been replicated with different presentation durations, repetition settings, and tasks (Bradley & Lang, 2015; Snowden et al., 2016). However, the emotional stimuli adopted in these studies were mostly complicated scene images that conveyed rather general emotional information. When it comes to the specific emotion cues (e.g., fear, anger, happy, sad) delivered by our conspecifics through biologically salient signals (e.g., faces, gestures, voices), the results became intermixed. Some studies demonstrated that fearful, disgusted, and angry static faces induced larger pupil sizes than the neutral face, while sad and happy faces failed to induce such pupil dilatory effects (Burley et al., 2017). In contrast, other studies observed larger pupil responses for happy faces as compared to sad and fearful faces (Aktar et al., 2018; Burley & Daughters, 2020; Jessen et al., 2016). These conflicting results could be due to the low-level confounds of emotional faces (e.g., eye size) (Carsten et al., 2019; Harrison et al., 2006). Similar to faces, BM also conveyed salient clues concerning the emotional states of our interactive partners. However, they were highly simplified, deprived of various irrelevant visual confounders (e.g., body shape). Here, we reported that the happy BM induced a stronger pupil response than the neutral and sad BM, lending support to the happy dilation effect observed with faces (Burley & Daughters, 2020; Prunty et al., 2021). Moreover, it helps ameliorate the concern regarding the low-level confounding factors by identifying similar pupil modulations in another type of social signal with distinctive perceptual features. We have added these points to the revised text (see lines 301-321).

References:

Aktar, E., Mandell, D. J., de Vente, W., Majdandžić, M., Oort, F. J., van Renswoude, D. R., Raijmakers, M. E. J., & Bögels, S. M. (2018). Parental negative emotions are related to behavioral and pupillary correlates of infants’ attention to facial expressions of emotion. Infant Behavior and Development, 53, 101–111. https://doi.org/10.1016/j.infbeh.2018.07.004

Bradley, M. M., & Lang, P. J. (2015). Memory, emotion, and pupil diameter: repetition of natural scenes. Psychophysiology, 52(9), 1186–1193. https://doi.org/10.1111/psyp.12442

Bradley, M. M., Miccoli, L., Escrig, M. A., & Lang, P. J. (2008). The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology, 45(4), 602–607. https://doi.org/10.1111/j.1469-8986.2008.00654.x

Burley, D. T., & Daughters, K. (2020). The effect of oxytocin on pupil response to naturalistic dynamic facial expressions. Hormones and Behavior, 125, 104837. https://doi.org/10.1016/j.yhbeh.2020.104837

Burley, D. T., Gray, N. S., & Snowden, R. J. (2017). As far as the eye can see: relationship between psychopathic traits and pupil response to affective stimuli. PLOS ONE, 12(1), e0167436. https://doi.org/10.1371/journal.pone.0167436

Carsten, T., Desmet, C., Krebs, R. M., & Brass, M. (2019). Pupillary contagion is independent of the emotional expression of the face. Emotion, 19(8), 1343–1352. https://doi.org/10.1037/emo0000503

Harrison, N. A., Singer, T., Rotshtein, P., Dolan, R. J., & Critchley, H. D. (2006). Pupillary contagion: central mechanisms engaged in sadness processing. Social Cognitive and Affective Neuroscience, 1(1), 5–17. https://doi.org/10.1093/scan/nsl006

Jessen, S., Altvater-Mackensen, N., & Grossmann, T. (2016). Pupillary responses reveal infants’ discrimination of facial emotions independent of conscious perception. Cognition, 150, 163–169. https://doi.org/10.1016/j.cognition.2016.02.010

Prunty, J. E., Keemink, J. R., & Kelly, D. J. (2021). Infants show pupil dilatory responses to happy and angry facial expressions. Developmental Science, 25(2). https://doi.org/10.11<br /> 11/desc.13182

Snowden, R. J., O’Farrell, K. R., Burley, D., Erichsen, J. T., Newton, N. V., & Gray, N. S. (2016). The pupil’s response to affective pictures: role of image duration, habituation, and viewing mode. Psychophysiology, 53(8), 1217–1223. https://doi.org/10.1111/psyp.12668

Overall, I think this is a well-written paper with solid experimental results that support the claim of the authors, i.e., the human visual system may process emotional information in biological motion at multiple levels. Given the key role of emotion processing in normal social cognition, the results will be of interest not only to basic scientists who study visual perception, but also to clinical researchers who work with patients of social cognitive disorders. In addition, this paper suggests that examining pupil size responses could be a very useful methodological tool to study brain mechanisms underlying emotion processing.

Reviewer #3 (Public Review):

Summary:

The overarching goal of the authors was to understand whether emotional information conveyed through point-light biological motion can trigger automatic physiological responses, as reflected in pupil size.

Strengths:

This manuscript has several noticeable strengths: it addresses an intriguing research question that fills that gap in existing literature, presents a clear and accurate presentation of the current literature, and conducts a series of experiments and control experiments with adequate sample size. Yet, it also entails several noticeable limitations - especially in the study design and statistical analyses.

Weaknesses:

(1) Study design:

(1.1) Dependent variable:

Emotional attention is known to modulate both microsaccades and pupil size. Given the existing pupillometry data that the authors have collected, it would be both possible and valuable to determine whether the rate of microsaccades is also influenced by emotional biological motion.

We thank the reviewer for this advice. Microsaccades functioned as a mechanism to maintain visibility by continuously shifting the retinal image to overcome visual adaptation (Martinez-Conde et al., 2006). Moreover, it was found to be sensitive to attention processes (Baumeler et al., 2020; Engbert & Kliegl, 2003b; Meyberg et al., 2017), and could reflect the activity of superior colliculus (SC) and other related brain areas (Martinez-Conde et al., 2009, 2013). Previous studies have found that, compared with neutral and pleasant images, unpleasant images significantly inhibit early microsaccade rates (Kashihara, 2020; Kashihara et al., 2013). This is regarded as the result of retaining previous crucial information at the sacrifice of updating new visual input. We agree with the reviewer that it would be valuable to investigate whether emotional information conveyed by BM could modulate microsaccades. However, it should be noted that our data collection and experimental design are not optimized for this purpose. This is because we have only recorded the left eye’s data, while abundant methodological studies have doubted the reliability of using only one eye’s data to analyze microsaccades (Fang et al., 2018; Hauperich et al., 2020; Nyström et al., 2017) and suggested that the microsaccades should be defined by spontaneous binocular eye movement (Engbert & Kliegl, 2003a, 2003b). Besides, according to Kashihara et al. (2013), participants showed differential microsaccade rates after the stimuli disappeared so as to maintain the previously observed different emotional information. However, in the current study, we discarded the data after the stimuli disappeared, making it impossible to analyze the microsaccade data after the stimuli disappeared. Despite these disadvantages, we have attempted to analyze the microsaccade rate during the stimuli presentation using only the left eye’s data. Specifically, we applied the algorithm developed by Otero-Millan et al. (2014) (minimum duration =6 ms, maximum amplitude = 1.5 degrees, maximum velocity = 150 degrees/sec) to the left eye’s data from 100 ms before to 4000 ms after stimulus onset. Subsequently, we calculated the microsaccade rates using a moving window of 100 ms (stepped in 1 ms) (Engbert & Kliegl, 2003b; Kashihara et al., 2013). The microsaccade rate displayed a typical curve, with suppression shortly after stimulus appearance (inhibition phase), followed by an increased rate of microsaccade occurrence (rebound phase). The cluster-based permutation analysis was then applied to explore the modulation of BM emotions on microsaccade rates. However, no significant differences among different emotional conditions (happy, sad, neutral) were found for the four experiments.

Author response image 3.

Time-series change in the microsaccade rates to happy, sad, and neutral BM in Experiments 1-4. Solid lines represent microsaccade rates under each emotional condition as a function of time (happy: red; sad: blue; neutral: gray); shaded areas represent the SEM between participants. No significant differences were found after cluster-based permutation correction for the four experiments.

It is important to note that the microsaccade rate analysis was conducted on only the left eye’s data and that the experiment design is not optimized for this analysis, thus, extra caution should be exercised in interpreting the results. Still, we found it very innovative and important to combine the microsaccade index with the pupil size to holistically investigate the processing of emotional information in BM, and future studies are highly needed to adopt more suitable recording techniques and experiment designs to further probe this issue. We have discussed this issue in the revised text (see lines 339-344).

References:

Baumeler, D., Schönhammer, J. G., & Born, S. (2020). Microsaccade dynamics in the attentional repulsion effect. Vision Research, 170, 46–52. https://doi.org/10.1016/j.visres.2020.03.009

Engbert, R., & Kliegl, R. (2003a). Binocular coordination in microsaccades. In The Mind’s Eye (pp. 103–117). Elsevier. https://doi.org/10.1016/b978-044451020-4/50007-4

Engbert, R., & Kliegl, R. (2003b). Microsaccades uncover the orientation of covert attention. Vision Research, 43(9), 1035–1045. https://doi.org/10.1016/s0042-6989(03)00084-1

Fang, Y., Gill, C., Poletti, M., & Rucci, M. (2018). Monocular microsaccades: do they really occur? Journal of Vision, 18(3), 18. https://doi.org/10.1167/18.3.18

Hauperich, A.-K., Young, L. K., & Smithson, H. E. (2020). What makes a microsaccade? a review of 70 years research prompts a new detection method. Journal of Eye Movement Research, 12(6). https://doi.org/10.16910/jemr.12.6.13

Kashihara, K. (2020). Microsaccadic modulation evoked by emotional events. Journal of Physiological Anthropology, 39(1). https://doi.org/10.1186/s40101-020-00238-6

Kashihara, K., Okanoya, K., & Kawai, N. (2013). Emotional attention modulates microsaccadic rate and direction. Psychological Research, 78(2), 166–179. https://doi.org/10.1007/s00426-013-0490-z

Martinez-Conde, S., Macknik, S. L., Troncoso, X. G., & Dyar, T. A. (2006). Microsaccades counteract visual fading during fixation. Neuron, 49(2), 297–305. https://doi.org/10.1016/j.neuron.2005.11.033

Martinez-Conde, S., Macknik, S. L., Troncoso, X. G., & Hubel, D. H. (2009). Microsaccades: a neurophysiological analysis. Trends in Neurosciences, 32(9), 463–475. https://doi.org/10.1016/j.tins.2009.05.006

Martinez-Conde, S., Otero-Millan, J., & Macknik, S. L. (2013). The impact of microsaccades on vision: towards a unified theory of saccadic function. Nature Reviews Neuroscience, 14(2), 83–96. https://doi.org/10.1038/nrn3405

Meyberg, S., Sinn, P., Engbert, R., & Sommer, W. (2017). Revising the link between microsaccades and the spatial cueing of voluntary attention. Vision Research, 133, 47–60. https://doi.org/10.1016/j.visres.2017.01.001

Nyström, M., Andersson, R., Niehorster, D. C., & Hooge, I. (2017). Searching for monocular microsaccades – a red hering of modern eye trackers? Vision Research, 140, 44–54. https://doi.org/10.1016/j.visres.2017.07.012

Otero-Millan, J., Castro, J. L. A., Macknik, S. L., & Martinez-Conde, S. (2014). Unsupervised clustering method to detect microsaccades. Journal of Vision, 14(2), 18–18. https://doi.org/10.1167/14.2.18

(1.2) Stimuli:

It appears that the speed of the emotional biological motion stimuli mimics the natural pace of the emotional walker. What is the average velocity of the biological motion stimuli for each condition?

Thanks for pointing out this issue. The neutral and emotional (sad or happy) BM stimuli are equal in walking speed (one step for one second, 1Hz). We have also computed their physical velocity by calculating the Euclidean distance in pixel space of each key point between adjacent frames (Poyo Solanas et al., 2020). The velocity was 5.76 pixels/frame for the happy BM, 4.14 pixels/frame for the neutral BM, and 3.21 pixels/frame for the sad BM. This difference in velocity profile was considered an important signature for conveying emotional information, as the happy walker was characterized by a larger step pace and longer arm swing and the sad walker would instead exhibit a slouching gait with short slow strides and smaller arm movement (Barliya et al., 2012; Chouchourelou et al., 2006; Halovic & Kroos, 2018; Roether et al., 2009). More importantly, our current results could not be explained by the differences in velocities. This is because the inverted emotional BM with identical velocity characteristics failed to induce any modulations on pupil responses. Furthermore, the local sad and happy BM differed the most in velocity feature, while they induced similar modulations on pupil sizes. We have added these points in the revised text (see lines 254-257, 484-491).

References:

Barliya, A., Omlor, L., Giese, M. A., Berthoz, A., & Flash, T. (2012). Expression of emotion in the kinematics of locomotion. Experimental Brain Research, 225(2), 159–176. https://doi.org/10.1007/s00221-012-3357-4

Chouchourelou, A., Matsuka, T., Harber, K., & Shiffrar, M. (2006). The visual analysis of emotional actions. Social Neuroscience, 1(1), 63–74. https://doi.org/10.1080/17470910600630599

Halovic, S., & Kroos, C. (2018). Not all is noticed: kinematic cues of emotion-specific gait. Human Movement Science, 57, 478–488. https://doi.org/10.1016/j.humov.2017.11.008

Poyo Solanas, M., Vaessen, M. J., & de Gelder, B. (2020). The role of computational and subjective features in emotional body expressions. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-63125-1

Roether, C. L., Omlor, L., Christensen, A., & Giese, M. A. (2009). Critical features for the perception of emotion from gait. Journal of Vision, 9(6), 15–15. https://doi.org/10.1167/9.6.15

When the authors used inverted biological motion stimuli, they didn't observe any modulation in pupil size. Could there be a difference in microsaccades when comparing inverted emotional biological motion stimuli?

Thanks for this consideration. Both microsaccades and pupil size can provide valuable insights into the underlying neural dynamics of attention and cognitive control (Baumeler et al., 2020; Engbert & Kliegl, 2003; Meyberg et al., 2017). Notably, previous studies have shown that the microsaccades and pupil sizes could be similar and highly correlated in reflecting various cognitive processes, such as multisensory integration, inhibitory control, and cognitive load (Krejtz et al., 2018; Wang et al., 2017; Wang & Munoz, 2021). Moreover, the generation of both microsaccades and pupil responses would involve shared neural circuits, including the midbrain structure superior colliculus (SC) and the noradrenergic system (Hafed et al., 2009; Hafed & Krauzlis, 2012; Wang et al., 2012). However, the pupil size could be more sensitive than microsaccade rates in contexts such as affective priming (Krejtz et al., 2020) and decision formation (Strauch et al., 2018). Moreover, abundant former studies have all shown that inversion would significantly disrupt the perception of emotions from BM (Atkinson et al., 2007; Dittrich et al., 1996; Spencer et al., 2016; Yuan et al., 2022, 2023). Overall, it is unlikely for the microsaccade rates to show significant differences when comparing inverted emotional biological motion stimuli. Besides, we have attempted to analyze the microsaccade rate in the inverted BM situation, while our results showed no significant differences (see also Point 1.1, Author response image 3). Still, it is needed for future studies to combine the microsaccade index and pupil size to provide a thorough understanding of BM emotion processing. We have discussed this issue in the revised text (see lines 339-344).

References:

Atkinson, A. P., Tunstall, M. L., & Dittrich, W. H. (2007). Evidence for distinct contributions of form and motion information to the recognition of emotions from body gestures. Cognition, 104(1), 59–72. https://doi.org/10.1016/j.cognition.2006.05.005

Baumeler, D., Schönhammer, J. G., & Born, S. (2020). Microsaccade dynamics in the attentional repulsion effect. Vision Research, 170, 46–52. https://doi.org/10.1016/j.visres.2020.03.009

Dittrich, W., Troscianko, T., Lea, S., & Morgan, D. (1996). Perception of emotion from dynamic point-light displays represented in dance. Perception, 25(6), 727–738. https://doi.org/10.1068/p250727

Engbert, R., & Kliegl, R. (2003). Microsaccades uncover the orientation of covert attention. Vision Research, 43(9), 1035–1045. https://doi.org/10.1016/s0042-6989(03)00084-1

Hafed, Z. M., Goffart, L., & Krauzlis, R. J. (2009). A neural mechanism for microsaccade generation in the primate superior colliculus. Science, 323(5916), 940–943. https://doi.org/10.1126/science.1166112

Hafed, Z. M., & Krauzlis, R. J. (2012). Similarity of superior colliculus involvement in microsaccade and saccade generation. Journal of neurophysiology, 107(7), 1904-1916.

Krejtz, K., Duchowski, A. T., Niedzielska, A., Biele, C., & Krejtz, I. (2018). Eye tracking cognitive load using pupil diameter and microsaccades with fixed gaze. Plos One, 13(9), e0203629. https://doi.org/10.1371/journal.pone.0203629

Krejtz, K., Żurawska, J., Duchowski, A., & Wichary, S. (2020). Pupillary and microsaccadic responses to cognitive effort and emotional arousal during complex decision making. Journal of Eye Movement Research, 13(5). https://doi.org/10.16910/jemr.13.5.2

Meyberg, S., Sinn, P., Engbert, R., & Sommer, W. (2017). Revising the link between microsaccades and the spatial cueing of voluntary attention. Vision Research, 133, 47–60. https://doi.org/10.1016/j.visres.2017.01.001

Spencer, J. M. Y., Sekuler, A. B., Bennett, P. J., Giese, M. A., & Pilz, K. S. (2016). Effects of aging on identifying emotions conveyed by point-light walkers. Psychology and Aging, 31(1), 126–138. https://doi.org/10.1037/a0040009

Strauch, C., Greiter, L., & Huckauf, A. (2018). Pupil dilation but not microsaccade rate robustly reveals decision formation. Scientific Reports, 8(1). https://doi.org/10.1038/s41598-018-31551-x

Wang, C.-A., Blohm, G., Huang, J., Boehnke, S. E., & Munoz, D. P. (2017). Multisensory integration in orienting behavior: pupil size, microsaccades, and saccades. Biological Psychology, 129, 36–44. https://doi.org/10.1016/j.biopsycho.2017.07.024

Wang, C.-A., Boehnke, S. E., White, B. J., & Munoz, D. P. (2012). Microstimulation of the monkey superior colliculus induces pupil dilation without evoking saccades. Journal of Neuroscience, 32(11), 3629–3636. https://doi.org/10.1523/jneurosci.5512-11.2012

Wang, C.-A., & Munoz, D. P. (2021). Differentiating global luminance, arousal and cognitive signals on pupil size and microsaccades. European Journal of Neuroscience, 54(10), 7560–7574. https://doi.org/10.1111/ejn.15508

Yuan, T., Ji, H., Wang, L., & Jiang, Y. (2022). Happy is stronger than sad: emotional information modulates social attention. Emotion. https://doi.org/10.1037/emo0001145

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(2) Statistical analyses

(2.1) Multiple comparisons:

There are many posthoc comparisons throughout the manuscript. The authors should consider correction for multiple comparisons. Take Experiment 1 for example, it is important to note that the happy over neutral BM effect and the sad over neutral BM effect are no longer significant after Bonferroni correction, which is worth noting.

Thanks for this suggestion. In our original analysis, we applied the Holm post-hoc corrections for multiple comparisons. The Holm correction is a step-down correction method and is more powerful but less conservative than the Bonferroni correction. We have now conducted the stricter Bonferroni post-hoc correction. In Experiment 1, the happy over neutral, and happy over sad BM effect is still significant after the Bonferroni post-hoc correction (happy vs. neutral: p = .036; happy vs. sad: p = .009), and the sad over neutral comparison remains marginally significant after the Bonferroni post-hoc correction (p = .071). Importantly, the test-retest replication experiment also yielded significant results for the comparisons between happy and neutral (First Test: p = .022, Holm-corrected, p = .048, Bonferroni-corrected; Second Test: p = .005,  Holm-corrected, p = .008, Bonferroni-corrected), sad and neutral (First Test: p = .022, Holm-corrected, p = .033, Bonferroni-corrected; Second Test: p = .005, Holm-corrected, p = .012, Bonferroni-corrected, Author response image 1B), and happy and sad BM  (First test: p < .001, Holm-corrected, p < .001, Bonferroni-corrected; Second test: p < .001, Holm-corrected, p < .001, Bonferroni-corrected). These results provided support for the replicability and consistency of the reported significant contrasts. See also Point 2.3.

In Experiment 4, the significance levels of all comparisons remained the same after Bonferroni post-hoc correction (happy vs. neutral: p = .011; sad vs. neutral: p = .007; happy vs. sad: p = 1.000). We have now added these results in the main text (See lines 119, 122, 124, 143, 145, 148, 150, 153, 155, 248, 251, 254).

(2.2) The authors present the correlation between happy over sad dilation effect and the autistic traits in Experiment 1, but do not report such correlations in Experiments 2-4. Did the authors collect the Autistic Quotient measure in Experiments 2-4? It would be informative if the authors could demonstrate the reproducibility (or lack thereof) of this happy-sad index in Experiments 2-4.

We apologize for not making it clear. We have collected the AQ scores in Experiments 2-4. However, it should be pointed out that the happy over sad pupil dilation effect was only observed in Experiment 1. Moreover, we’ve again identified such happy over sad pupil dilation effect in the replication experiment (Experiment 1b) as well as its correlation with AQ. Instead, no significant correlations between AQ and the happy-sad pupil index were found in Experiments 2-4, see Author response image 4 for more details. We have reported these correlations in the main text (see lines 157-173, 190-194, 212-216, 257-262).

Author response image 4.

Correlations between the happy over sad pupil dilation effect and AQ scores. (A)  The happy over sad pupil dilation effect correlated negatively with individual autistic scores. (B-C) Such correlation was similarly observed in the test and retest of the replication experiment. (D-F) No such correlations were found for the inverted, nonbiological, and local BM stimuli.

(2.3) The observed correlation between happy over sad dilation effect and the autistic traits in Experiment 1 seems rather weak. It could be attributed to the poor reliability of the Autistic Quotient measure or the author-constructed happy-sad index. Did the authors examine the test-retest reliability of their tasks or the Autistic Quotient measure?

Thanks for this suggestion. We have now conducted a test-retest replication study to further confirm the observed significant correlations. Specifically, we recruited a new group of 24 participants (16 females, 8 males) to perform the identical procedure as in Experiment 1, and they were asked to return to the lab for a retest after at least seven days. We’ve replicated the significant main effect of emotional conditions in both the first test (F(2, 46) = 12.0, p < .001, ηp2 = 0.34) and the second test (F(2, 46) = 14.8, p < .001, ηp2 = 0.39). Besides, we also replicated the happy minus neutral pupil dilation effect (First Test: t(23) = 2.60, p = .022, Cohen’s d = 0.53, 95% CI for the mean difference = [0.02, 0.14], Holm-corrected, p = .048 after Bonferroni correction; Second Test: t(23) = 3.36, p = .005, Cohen’s d = 0.68, 95% CI for the mean difference = [0.06, 0.24], Holm-corrected, p = .008 after Bonferroni correction), and the sad minus neutral pupil constriction effect (First Test: t(23) = -2.77, p = .022, Cohen’s d = 0.57, 95% CI for the mean difference = [-0.19, -0.03], Holm-corrected, p = .033 after Bonferroni correction; Second Test: t(23) = -3.19, p = .005, Cohen’s d = 0.65, 95% CI for the mean difference = [-0.24, -0.05], Holm-corrected, p = .012 after Bonferroni correction). Additionally, the happy BM still induced a significantly larger pupil response than the sad BM (first test: t(23) = 4.23, p < .001, Cohen’s d = 0.86, 95% CI for the mean difference = [0.10, 0.28], Holm-corrected, p < .001 after Bonferroni correction; second test: t(23) = 4.26, p < .001, Cohen’s d = 0.87, 95% CI for the mean difference = [0.15, 0.44], Holm-corrected, p < .001 after Bonferroni correction).

Notably, we’ve successfully replicated the negative correlation between the happy over sad dilation effect and individual autistic traits (r(23) = -0.46, p = .023, 95% CI for the mean difference = [-0.73, -0.07]). Such a correlation was similarly found and was even stronger in the retest (r(23) = -0.61, p = .002, 95% CI for the mean difference = [-0.81, -0.27]). A test-retest reliability analysis was conducted on the happy over sad pupil dilation effect and the AQ score. The results showed robust correlations (r(happy-sad pupil size)= 0.56; r(AQ)= 0.90) and strong test-retest reliabilities (α(happy-sad pupil size)= 0.60; α(AQ)= 0.82). We have added these results to the main text (see lines 135-173). See also Response to Reviewer #2 Response 1 for more details.

(2.4) Relatedly, the happy over sad dilation effect is essentially a subtraction index. Without separately presenting the pipul size correlation with happy and sad BM in supplemental figures, it becomes challenging to understand what's primarily driving the observed correlation.

Thanks for pointing this out. We have now presented the separate correlations between AQ and the pupil response towards happy and sad BM in Experiment 1 (see Author response image 5A), and the test-retest replication experiment of Experiment 1 (see Author response image 5B-C). No significant correlations were found. This is potentially because the raw pupil response is a mixed result of BM perception and emotion perception, while the variations in pupil sizes across emotional conditions could more faithfully reflect individual sensitivities to emotions in BM (Burley et al., 2017; Pomè et al., 2020; Turi et al., 2018).  

Author response image 5.

No significant correlations between AQ and pupil response towards happy and sad intact BM were found in Experiment 1a and the test-retest replication experiment (Experiment 1b).

To probe what's primarily driving the observed correlation between happy-sad pupil size and AQ, we instead used the neutral as the baseline and separately correlated AQ with the happy-neutral and the sad-neutral pupil modulation effects. No significant correlation was found in Experiment 1a (Author response image 6A-B) and the first test of the replication experiment (Experiment 1b) (Author response image 6C-D). Importantly, in the second test of the replication experiment, we found a significant negative correlation between AQ and the happy-neutral pupil size (r(23) = -0.44, p = .032, 95% CI for the mean difference = [-0.72, -0.04], Author response image 6E), and a significant positive correlation between AQ and the sad-neutral pupil size (r(23) = 0.50, p = .014, 95% CI for the mean difference = [0.12, 0.75], Author response image 6F). This suggested that the overall correlation between AQ and the happy over sad dilation effect was driven by diminished pupil modulations towards both the happy and sad BM for high AQ individuals, demonstrating a general deficiency in BM emotion perception (happy or sad) among individuals with high autistic tendencies. It further revealed the potential of adopting a test-retest pupil examination to more precisely detect individual autistic tendencies. We have reported these results in the main text (see lines 166-173).

Author response image 6.

Correlation results for pupil modulations and AQ scores. (A-B) In Experiment 1a, no significant correlation was observed between AQ and the happy pupil modulation effect, as well as between AQ and the sad pupil modulation effect. (C-D) Similarly, no significant correlations were found in the first test of the replication experiment (Experiment 1b). (E-F) Importantly, in the second test of Experiment 1b, the happy vs. neutral pupil dilation effect was positively correlated with AQ, and the sad vs. neutral pupil constriction effect was positively correlated with AQ.

References:

Burley, D. T., Gray, N. S., & Snowden, R. J. (2017). As Far as the Eye Can See: Relationship between Psychopathic Traits and Pupil Response to Affective Stimuli. PLOS ONE, 12(1), e0167436. https://doi.org/10.1371/journal.pone.0167436

Pomè, A., Binda, P., Cicchini, G. M., & Burr, D. C. (2020). Pupillometry correlates of visual priming, and their dependency on autistic traits. Journal of vision, 20(3), 3-3.

Turi, M., Burr, D. C., & Binda, P. (2018). Pupillometry reveals perceptual differences that are tightly linked to autistic traits in typical adults. eLife, 7. https://doi.org/10.7554/elife.32399

(2.5) For the sake of transparency, it is important to report all findings, not just the positive results, throughout the paper.

Thanks for this suggestion. We have now reported all the correlations results between AQ and pupil modulation effects (happy-sad, happy-neutral, sad-neutral) in the main text (see lines 130-131, 157-162, 166-170, 190-194, 212-216, 257-262). Given that no significant correlations were observed between AQ and the raw pupil responses across four experiments, we reported their correlations with AQ in the supplementary material. We have stated this point in the main text (see lines 132-134).

(3) Structure

(3.1) The Results section immediately proceeds to the one-way repeated measures ANOVA. This section could be more reader-friendly by including a brief overview of the task procedures and variables, e.g., shifting Fig. 3 to this section.

Thanks for this advice. We have now added a brief overview of the task procedures and variables and we have also shifted the figure position (see lines 101-103).

Reviewer #1 (Recommendations For The Authors):

(1) I suggest that the authors first explain the task (i.e., Fig. 3) at the beginning of the results. And it seems more appropriate to show the time course figures (Fig. 2) and before the bar plots (Fig. 1). If I understand correctly, the bar plots reflect the averaged data from the time course plots. Also, please clearly state the time window used to average the data. The results of the correlation analysis can be displayed in the last step.

Thanks for this suggestion. We have now added a concise explanation of the task at the beginning of the results (see lines 101-103). We have also adjusted the figure positions and adjusted the order of our results according to the reviewer’s suggestion. The time window we used to average the data was from the onset of the stimuli until the end of the stimuli presentation. We have now clearly stated these issues in the revised text (see lines 111-112).

(2) According to the above, I think a more reasonable arrangement should be Fig. 3, 2, and 1.

Thanks for this suggestion. We have adjusted the figure positions accordingly.

(3) Please include each subject's data points in the bar plots in Fig. 1.

We have now presented each subject’s individual data point in the bar plot.

(4) Lines 158-160 and 199-202 report interaction effects of the two-way ANOVA. This is good, but the direction of interaction effect should also be reported.

We thank the reviewer for this suggestion. We have now reported the direction of the interaction effect. The significant interaction observed across Experiment 1 and Experiment 2 was mainly due to the diminishment of emotional modulation in inverted BM. The significant interaction crossing Experiment 1 and Experiment 3 was similarly caused by the lack of emotional modulation in nonbiological stimuli. With regard to the significant interaction across Experiment 1 and Experiment 4, it could be primarily attributed to the vanishment of pupil modulation effect between happy and sad local BM. We have specified these points in the revised text, see lines 198-199, 219-220, 267-269.

Reviewer #3 (Recommendations For The Authors):

(1) Number of experiments:

As stated in the Methods section, this study seems to consist of five experiments (120/24=5) according to the description below. However, the current manuscript only reports findings from four of these experiments. Can the authors clarify on this matter?

"A total of 120 participants (44 males, 76 females) ranging from 18 to 29 years old (M ± SD = 23.1 ± 2.5) were recruited, with 24 in each experiment."

We apologize for not making it clear. This referred to a pure behavior explicit emotion classification experiment (N=24) that served as a prior test to confirm that the local BM stimuli conveyed recognizable emotional information. We have now more carefully stated this issue in the revised text, see lines 456-458.

(2) Emotion processing mechanism of BM

"Mechanism" is a very strong word, suggesting a causal relationship. In the setting of a passive viewing task that lacks any behavioral report, it is possible that the observed changes in pupil size could be epiphenomenal, rather than serving as the underlying mechanism.

Thanks for this suggestion. We have now either changed “mechanism” into “phenomenon” or deleted it. We have also carefully discussed the potential implications for future studies to incorporate variant behavioral, physiological and neural indexes to yield more robust causal evidence to unveil the potential mechanism serving the observed multi-level BM emotion processing phenomenon.

(3) Data sharing

The authors could improve their efforts in promoting data transparency to ensure a comprehensive view of the results. This implies sharing deidentified raw data instead of summary data in an Excel spreadsheet.

Thanks for this suggestion. We have now uploaded the deidentified raw data. (https://doi.org/10.57760/sciencedb.psych.00125).

eLife Assessment

This important study identifies a short amino acid sequence that, when fused in multimeric form to the amino termini of luminal ER proteins, initiates proteasomal degradation via the Hrd1 ER quality control ubiquitin ligase complex. The authors provide solid evidence that this sequence functions as a "degron" for ER proteins. Future work is required to obtain a more detailed view of the properties of this degron, the mechanisms underlying its recognition by ER-resident and cytoplasmic factors, and the in vivo relevance of the findings.

Reviewer #1 (Public Review):

The authors use a previously established reporter comprising a slow- and a fast-folding fluorescent protein fused to a randomly-generated library of penta-peptides at its amino-terminus and a signal sequence for import into the endoplasmic reticulum (ER). They then determine the stability of these constructs in a high throughput FACS-sorting procedure and identify a set of peptides that route the construct to proteasomal degradation. Increasing the copy number of one of these peptides further decreases the stability of the construct. This polypeptide resembles a "degron" for ER proteins, because it also targets other ER proteins with different topological and folding properties for degradation. It only works when placed at the amino-terminus of a protein and utilizes components of the Hrd1 ubiquitin ligase complex, a well-established quality control ubiquitin ligase in the ER membrane. Importantly, the degron also targets ER-proteins in mammalian cells.

The authors convincingly show that fusion of their newly identified degron to the amino terminus of ER-resident proteins with different topology suffices to target them for proteasomal degradation. The data for this are well-founded and contain appropriate controls. While technically sound, the study does only give superficial information on general properties of the degron and its recognition by cellular factors. Further simple experiments would have addressed a number of important points. The authors only provide data about the composition of the identified amino acid sections from the high-throughput approach and the statistical preference for certain amino acids at individual positions. They do not study degron composition experimentally by substituting individual amino acids with other residues and analyzing protein stability. Increasing the numbers of the initially identified degron pentamer increases substrate turnover, but the basis for this remains unclear. Each copy may be actively involved in better recognition, elongation of the degron may facilitate accessibility by recognition factors or multiplying the short amino acid stretch may generate new signatures at the amino-terminus that are more readily recognized by a quality control machinery. Consequently, this study does not allow conclusions to be drawn about general properties of degron composition and/or structure. The degron also functions with cytoplasmic proteins, suggesting that similar characteristics of a polypeptide attract the attention of quality control systems also in other cellular compartments. However, the authors did not pursue this finding further, e.g. by identifying factors for degron recognition in the cytoplasm. It would have been particularly interesting to test whether the degron would initiate degradation when placed at cytoplasmically-exposed amino termini of membrane-bound ER proteins. Information on degron properties is required to better understand principles of substrate recognition by protein quality control pathways and to design constructs for targeting endogenous proteins via proteolysis targeting chimeras (PROTACs).

Reviewer #2 (Public review):

Summary:

Sharninghausen et al use a generic screening platform to search for short (5 amino acid) degrons that function in the lumen of the endoplasmic reticulum (ER) of budding yeast. The screen did indeed identify a number of sequences which increased the rate of degradation of their test proteins. Although the effect of the single degron was rather modest the authors could show that by mutimerising the sequence (4x) they obtained degrons that functioned fairly efficiently. Further characterisation indicated that the degrons only functioned when placed at the N-terminus of the target protein and, were dependent on both the proteasome and the segregase Cdc48 (p97) for degradation. The authors also demonstrated that degradation was via the ERAD pathway.

Strengths:

In general, the data presented is supportive of the conclusions drawn and the authors have thus identified a sequence that can be appended onto other ER targeted proteins to mediate their degradation within the lumen of the ER. How useful this will be to the community remains to be seen.

Weaknesses:

While the observation that such mutimerised sequences can act as degrons is an interesting curiosity, it is not clear that such sequences function in vivo. In fact the DegV1 sequence used throughout the paper is not present in any yeast or fungal proteins and the fact that it has to be located at the N-terminus of the protein to induce degradation is at odds with the idea that proteins to be degraded need to be unfolded. Thus, the role of such sequences in vivo is questionable.

Comments on revised manuscript:

Although the role of such degron sequences remains to be determined in vivo, it is clear that the authors have developed a tool that could be useful to the scientific community. The specific points raised were appropriately addressed by the authors.

Author response:

The following is the authors’ response to the original reviews.

We would like to thank the reviewers for their constructive feedback and overall positive response to our manuscript. Reviewer #1 had no specific recommendations, so below we address Reviewer #2’s comments.

Reviewer #2 (Recommendations For The Authors):

Specific points

(1) In Fig. 1H peptides selected are much more stable than the positive control KHN-FT, but they appear to be less stable than randomly selected 5 amino acid sequences. Are the differences

between the randomly selected sequences and the selected sequences statistically significant.

Thank you for the feedback. Yes, the differences are statistically significant by one-way ANOVA and the Tukey’s multiple comparisons tests, we’ve updated the figure legend to indicate this fact.

(2) In Fig. 1I the FACS profile of 4x looks like that of KHN, but it is very difficult to see in the figure. Looking at the quantitation in Fig. 1J it is impossible to compare KHN with 4x as the KHN is on the baseline. Could this be improved by using a log scale to present the data.

Thank you for pointing this out. We’ve improved the figure so the KHN is easier to see. In addition, we’ve attempted different way to display these results, but settled on scaling the data between 1 and 0 as our comparison points. We’ve updated the main figure to more clearly show this result so the KHN is easier to compare.

(3) In Fig. 2G and Fig. 2F don't really match up. It looks from Fig. 2G like there is still some degradation in the hrd1 deletion strain, but this is not reflected in the quantitation (Fig. 2H).

To our eyes, the degradation in a hrd1null appears to be quite small, which seems to be reflected in the quantification (~20% decrease over 90 minutes). We included the figure in Author response image 1 for quick comparison.

Author response image 1.

(4) Throughout the paper the authors claim that the proteins are degraded by a cytosolic proteasome. I agree that the proteins are degraded via the proteasome, but I don't see any evidence that it is cytosolic.

Thank you for pointing this out. We’ve adjusted the text to reflect the fact that the proteasomal degradation is not necessarily in the cytosol.

eLife Assessment

Brain inflammation is a hallmark of multiple sclerosis. Using novel spatial transcriptomics methods, the authors provide solid evidence for a gradient of immune genes and inflammatory markers from the meninges toward the adjacent brain parenchyma in a mouse model. This important study advances our understanding of the mechanisms of brain damage in this autoimmune disease.

Reviewer 1 (Public Review):

Multiple sclerosis (MS) is a debilitating autoimmune disease that causes loss of myelin in neurons of the central nervous system. MS is characterized by the presence of inflammatory immune cells in several brain regions as well as the brain barriers (meninges). This study aims to understand the local immune hallmarks in regions of the brain parenchyma that are adjacent to the leptomeninges in a mouse model of MS. The leptomeninges are known to be a foci of inflammation in MS and perhaps "bleed" inflammatory cells and molecules to adjacent brain parenchyma regions. To do so, they use novel technology called spatial transcriptomics so that the spatial relationships between the two regions remain intact. The study identifies canonical inflammatory genes and gene sets such as complement and B cells enriched in the parenchyma in close proximity to the leptomeninges in the mouse model of MS but not control. The manuscript is very well written and easy to follow. The results will become a useful resource to others working in the field and can be followed by time series experiments where the same technology can be applied to the different stages of the disease.

Reviewer 2 (Public Review):

Accumulating data suggests that the presence of immune cell infiltrates in the meninges of the multiple sclerosis brain contributes to the tissue damage in the underlying cortical grey matter by the release of inflammatory and cytotoxic factors that diffuse into the brain parenchyma. However, little is known about the identity and direct and indirect effects of these mediators at a molecular level. This study addresses the vital link between an adaptive immune response in the CSF space and the molecular mechanisms of tissue damage that drive clinical progression. In this short report the authors use a spatial transcriptomics approach using Visium Gene Expression technology from 10x Genomics, to identify gene expression signatures in the meninges and the underlying brain parenchyma, and their interrelationship, in the PLP-induced EAE model of MS in the SJL mouse. MRI imaging using a high field strength (11.7T) scanner was used to identify areas of meningeal infiltration for further study. They report, as might be expected, the upregulation of genes associated with the complement cascade, immune cell infiltration, antigen presentation, and astrocyte activation. Pathway analysis revealed the presence of TNF, JAK-STAT and NFkB signaling, amongst others, close to sites of meningeal inflammation in the EAE animals, although the spatial resolution is insufficient to indicate whether this is in the meninges, grey matter, or both.

UMAP clustering illuminated a major distinct cluster of upregulated genes in the meninges and smaller clusters associated with the grey matter parenchyma underlying the infiltrates. The meningeal cluster contained genes associated with immune cell functions and interactions, cytokine production, and action. The parenchymal clusters included genes and pathways related to glial activation, but also adaptive/B-cell mediated immunity and antigen presentation. This again suggests a technical inability to resolve fully between the compartments as immune cells do not penetrate the pial surface in this model or in MS. Finally, a trajectory analysis based on distance from the meningeal gene cluster successfully demonstrated descending and ascending gradients of gene expression, in particular a decline in pathway enrichment for immune processes with distance from the meninges.

Author response:

The following is the authors’ response to the previous reviews

Reviewer 1 (Public Review):

Multiple sclerosis (MS) is a debilitating autoimmune disease that causes loss of myelin in neurons of the central nervous system. MS is characterized by the presence of inflammatory immune cells in several brain regions as well as the brain barriers (meninges). This study aims to understand the local immune hallmarks in regions of the brain parenchyma that are adjacent to the leptomeninges in a mouse model of MS. The leptomeninges are known to be a foci of inflammation in MS and perhaps "bleed" inflammatory cells and molecules to adjacent brain parenchyma regions. To do so, they use novel technology called spatial transcriptomics so that the spatial relationships between the two regions remain intact. The study identifies canonical inflammatory genes and gene sets such as complement and B cells enriched in the parenchyma in close proximity to the leptomeninges in the mouse model of MS but not control. The manuscript is very well written and easy to follow. The results will become a useful resource to others working in the field and can be followed by time series experiments where the same technology can be applied to the diAerent stages of the disease.

Comments on revised version:

I agree that the authors successfully addressed most of my comments/critiques. However, the fact that the control mice were not injected with CFA and pertussis toxin is somewhat concerning, because it will be hard to interpret the cause of the transcriptomic readouts described in this study. Some of the described eAects might be due to CFA or pertussis (which was used in the EAE but not the "naive" group), and not necessarily to the relapsing-remitting EAE immune features recapitulated in this mouse model. Moreover, this caveat associated with the "naive" control group is not being clearly stated throughout the manuscript and might go unnoticed to readers.

The authors should clearly state, in the methods section (in the section "Induction of SJL EAE"), that the naive control group was not injected with CFA or pertussis toxin.

Additionally, this potential confounder, of not using a control group injected with the same CFA and pertussis toxin regimen of the EAE group, should be mentioned in paragraph two of the discussion alongside the other limitations of the study already highlighted by the authors (or in another section of the discussion).

We thank the reviewer for highlighting this point. Our choice of healthy/naïve, rather than CFA only, controls was intentional, given our desire to sensitively measure genes changing during neuroinflammation. Ultimately, however, we believe the choice of control group had little effect on our conclusions. We would like to note that SJL-EAE does not require pertussis toxin, so the only difference between naïve and CFA only groups is a single injection of CFA 11 weeks prior to experiment endpoint. We have performed additional IHC imaging of naïve and CFA only groups, finding no difference in glial reactivity by MFI measurement of GFAP, IBA1, or CD68 (updated Supplementary Figure 1C–E).

We have also added sections to the Results and Discussion section to clearly address this point. In the Results: “Since naïve animals were used as controls, we confirmed that CFA alone does not produce lasting glial reactivity or LMI formation. Groups of animals were given CFA only or left naïve. Neither group developed neurologic signs, and after 11 weeks the brains were processed for IHC analysis. There was no evidence of LMI development, and no difference in glial reactivity as measured by GFAP, IBA1, or CD68 intensity (Supplemental Figure 1C–E).” In the Discussion: “Another important consideration in these experiments is our choice of naïve, rather than CFA only, controls. While often used as the control in EAE studies focused on mechanisms of autoimmunity, CFA only can independently induce systemic inflammation. Since this study seeks to describe transcriptomic changes in neuroinflammation more broadly, we chose to use a healthy comparison group to maximize our ability to find genes enriched in neuroinflammation. Ultimately, however, the choice of naïve or CFA only controls is unlikely to have affected our conclusions. SJL-EAE, unlike the more common C57Bl6-EAE, does not require pertussis toxin during the induction. The only difference between naïve and CFA only controls is the subcutaneous CFA delivered at time of immunization (11 weeks prior to experiment endpoint). Indeed, when we compared CFA only and healthy animals at 11 weeks there was no difference in glial reactivity by GFAP, IBA1, or CD68 MFI. There was also no evidence of neurologic symptoms or LMI development in CFA only controls.”

Reviewer 2 (Public Review):

Accumulating data suggests that the presence of immune cell infiltrates in the meninges of the multiple sclerosis brain contributes to the tissue damage in the underlying cortical grey matter by the release of inflammatory and cytotoxic factors that diAuse into the brain parenchyma. However, little is known about the identity and direct and indirect eAects of these mediators at a molecular level. This study addresses the vital link between an adaptive immune response in the CSF space and the molecular mechanisms of tissue damage that drive clinical progression. In this short report the authors use a spatial transcriptomics approach using Visium Gene Expression technology from 10x Genomics, to identify gene expression signatures in the meninges and the underlying brain parenchyma, and their interrelationship, in the PLP-induced EAE model of MS in the SJL mouse. MRI imaging using a high field strength (11.7T) scanner was used to identify areas of meningeal infiltration for further study. They report, as might be expected, the upregulation of genes associated with the complement cascade, immune cell infiltration, antigen presentation, and astrocyte activation. Pathway analysis revealed the presence of TNF, JAK-STAT and NFkB signaling, amongst others, close to sites of meningeal inflammation in the EAE animals, although the spatial resolution is insuAicient to indicate whether this is in the meninges, grey matter, or both.

UMAP clustering illuminated a major distinct cluster of upregulated genes in the meninges and smaller clusters associated with the grey matter parenchyma underlying the infiltrates. The meningeal cluster contained genes associated with immune cell functions and interactions, cytokine production, and action. The parenchymal clusters included genes and pathways related to glial activation, but also adaptive/B-cell mediated immunity and antigen presentation. This again suggests a technical inability to resolve fully between the compartments as immune cells do not penetrate the pial surface in this model or in MS. Finally, a trajectory analysis based on distance from the meningeal gene cluster successfully demonstrated descending and ascending gradients of gene expression, in particular a decline in pathway enrichment for immune processes with distance from the meninges.

Comments on revised version:

The authors have addressed all of my comments regarding the lack of spatial resolution between the grey matter and the overlying meninges and also concerning the diAiculties in extrapolating from this mouse model to MS itself.

I am however very concerned about the lack of the correct control group. Immunization of rodents with complete freunds adjuvant and pertussis alone gives rise to widespread microglial activation, some immune cell infiltration and also structural changes to axons, particularly at nodes of Ranvier (https://doi.org/10.1097/NEN.0b013e3181f3a5b1). This will inevitably make it diAicult to interpret the transcriptomics results, depending on whether these changes are reversible or not and the time frame of the reversal. In the C57Bl6 EAE models adjuvant induced microglial activation becomes chronic, whereas the axonal changes do reverse by 10 weeks. Whether this is the same in SJL EAE model is not clear.

We thank the reviewer for bringing up this concern regarding control group, which we discussed above in point 1.1. To specifically address reviewer 2’s point regarding microglial activation, we performed IHC analysis comparing naïve and CFA only groups of SJL animals. We found no substantial diAerence in astrocyte or microglial activation in these animals after 11 weeks, as measured by GFAP, IBA1, and CD68. This new data appears in updated Supplementary Figure 1C–D.

Recommendations for the authors:

Both reviewers agree that the revised version has improved and some of their major concerns were adequately addressed. However, both reviewers also agree that critical experimental controls are missing, including the FCA and pertussis toxin injected mice which likely show some degree of inflammation in their brain and are needed to compare your experimental MS group and interpret the transcriptomics data.

We appreciate both reviewers’ important comments on the control group used in this study. In this revised manuscript we have described our rationale for choosing naïve controls, rather than CFA only, and believe they are the most appropriate comparison group. Additionally, we believe that both CFA only and naïve will have similar degrees of baseline neuroinflammation at the 11- week time point. We apologize for not clarifying before, but pertussis toxin is not used in the SJL-EAE, and therefore the “CFA only” control is much milder in SJL-EAE compared to C57Bl6-EAE. Given that many signs of inflammation resolve by 10 weeks in CFA only with pertussis controls (https://academic.oup.com/jnen/article/69/10/1017/2917071; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10902151/),) CFA only without pertussis controls are unlikely to have any substantial remaining neuroinflammation at 11 weeks. To test this, we performed an additional experiment directly comparing naïve and CFA only without pertussis.

These groups showed similar degrees of glial reactivity.

Given the costs of repeating a spatial transcriptomic experiment and inevitable batch effects should we add a group at this point, we have chosen to not as a CFA only control condition to our transcriptomics analysis. However, we believe our added text clarifying the rationale behind control choice and added immunofluorescence data gives readers the appropriate context to accurately interpret our results.

eLife Assessment

Genetic analysis of complex traits in Drosophila provides a resource for exploring the relationship between genetic and phenotypic variation. The web tool DGRPool presented in this paper makes data and results from the Drosophila Genetic Reference Panel accessible that will enable downstream analyses of genetic association. The findings of this paper are considered to be important, with practical implications beyond a single subfield, supported by convincing evidence using appropriate and validated methodology in line with current state of the art.

Reviewer #1 (Public Review):

This is a technically sound paper focused on a useful resource around the DRGP phenotypes which the authors have curated, pooled, and provided a user-friendly website. This is aimed to be a crowd-sourced resource for this in the future. The authors should make sure they coordinate as well as possible with the NC datasets and community and broader fly community.

Reviewer #2 (Public Review):

In the present study, Gardeux et al provide a web-based tool for curated association mapping results from DRP studies. The tool lets users view association results for phenotypes and compare mean phenotype ~ phenotype correlations between studies. In the manuscript, the authors provide several example utilities associated with this new resource, including pan-study summary statistics for sex, traits, and loci. They highlight cross-trait correlations by comparing studies focused on longevity with phenotypes such as oxphos and activity. Strengths: -Considerable efforts were dedicated toward curating the many DRG studies provided. -Available tools to query large DRP studies are sparse and so new tools present appeal Weaknesses: The creation of a tool to query these studies for a more detailed understanding of physiologic outcomes seems underdeveloped. These could be improved by enabling usages such as more comprehensive queries of meta-analyses, molecular information to investigate given genes or pathways, and links to other information such as in mouse rat or human associations.

Author response:

The following is the authors’ response to the original reviews.

We would like to thank the reviewers for their positive and constructive comments on the manuscript.

We committed in our original rebuttal letter to implement the following revisions to both DGRPool and the corresponding manuscript to address the reviewers’ comments:

(1) We agree with reviewer #1 that normalizing the data could potentially improve the GWAS results. Thus, for computing the GWAS results, we are now using these two additional options in PLINK2: “--quantile-normalize --variance-standardize”. We assessed the impact of these options on the overall results, which revealed only minor improvements of the results, globally being a bit more stringent. In this direction, we also now filter the top results with a nominal p-value of 0.001 instead of 0.01, also because it provided better results for the new gene set enrichment step.

(2) We added a KRUSKAL test next to the ANOVA test for assessing the links between the phenotypes and the 6 known covariates, as well as a Shapiro-Wilk test of normality.

(3) We agree with both reviewers that gene expression information is of interest. As mentioned before, adding gene expression data to the portal would have required extensive work, beyond the current scope of this paper, which primarily focuses on phenotypes and genotype-phenotype associations. Nonetheless, we included more gene-level outlinks to Flybase. Additionally, we now link variants and genes to Flybase's online genome browser, JBrowse. By following the reviewers' suggestions, we aim to guide DGRPool users to potentially informative genes.

(4) Consistent with the latter point, and in agreement with reviewer #2, we acknowledge that additional tools could enhance DGRPool's functionality and facilitate meta- analyses for users. Therefore, we developed a gene-centric tool that now allows users to query the database based on gene names. Moreover, we integrated ortholog databases into the GWAS results. This feature will enable users to extend Drosophila gene associations to other species if necessary.

(5) We amended the manuscript to describe all the new tools and features that were developed and implemented. In short, the new features include a new gene-centric page with diverse links (Phenotypes, Genome Browser JBrowse, Orthologs …), a variant-centric page (variant details, and PheWAS), an API for programmatic access to the database, and other statistical outputs and filtering options.

We will detail these advances in the point-by-point response below and in the revised manuscript.

Reviewer #1 (Public Review):

This is a technically sound paper focused on a useful resource around the DRGP phenotypes which the authors have curated, pooled, and provided a user-friendly website. This is aimed to be a crowd-sourced resource for this in the future.

The authors should make sure they coordinate as well as possible with the NC datasets and community and broader fly community. It looks reasonable to me but I am not from that community.

We thank the reviewer for the positive comments. We will leverage our connections to the fly and DGRP communities to make the resource as valuable as possible. DGRPool in fact already reflects the input of many potential users and was also inspired by key tools on the DGRP2 website. Furthermore, it also rationalizes why we are bridging our results with other resources, such as linking out to Flybase, which is the main resource for the Drosophila community at large.

I have only one major concern which in a more traditional review setting I would be flagging to the editor to insist the authors did on resubmission. I also have some scene setting and coordination suggestions and some minor textual / analysis considerations.

The major concern is that the authors do not comment on the distribution of the phenotypes; it is assumed it is a continuous metric and well-behaved - broad gaussian. This is likely to be more true of means and medians per line than individual measurements, but not guaranteed, and there could easily be categorical data in the future. The application of ANOVA tests (of the "covariates") is for example fragile for this.

The simplest recommendation is in the interface to ensure there is an inverse normalisation (rank and then project on a gaussian) function, and also to comment on this for the existing phenotypes in the analysis (presumably the authors are happy). An alternative is to offer a kruskal test (almost the same thing) on covariates, but note PLINK will also work most robustly on a normalised dataset.

We thank the reviewer for raising this interesting point. Indeed, we did not comment on the distribution of individual phenotypes due to the underlying variability from one phenotype to another, as suggested by the reviewer. Some distributions appear normal, while others are clearly not normally distributed. This information is 'visible' to users by clicking on any phenotype; DGRPool automatically displays its global distribution if the values are continuous/quantitative. Now, we also provide a Shapiro-Wilk test to assess the normality of the distribution.

We acknowledge the reviewer's concerns regarding the use of ANOVA tests. However, we want to point out that the ANOVA test is solely conducted to assess whether any of the well- established inversions or symbiont infection status (that, for simplification, we call “covariates” or “known covariates”) are associated with the phenotype of interest. This is merely informational, to help the user understand if their phenotype of interest is associated with a known covariate. But all of these known covariates are put in the model in any case, so PLINK2 will automatically correct for them, whatever is the output of the ANOVA test.

Still, we amended the manuscript to better explain this, and we added a Kruskal-Wallis test (in addition to the ANOVA test) in the results, so the users can have a better overview of potentially associated known covariates. We added this text on p. 10 of the revised manuscript:

“The tool further runs a gene set enrichment analysis of the results filtered at p<0.001 to enrich the associated genes to gene ontology terms, and Flybase phenotypes. We also provide an ANOVA and a Kruskal-Wallis test between the phenotype and the six known covariates to uncover potential confounder effects (prior correction), which is displayed as a “warning” table to inform the user about potential associations of the phenotype and any of the six known covariates. It is important to note that these ANOVA and Kruskal tests are conducted for informational purposes only, to assess potential associations between well-established inversions or symbiont infection status and the phenotype of interest. However, all known covariates are included in the model regardless, and PLINK2 will automatically correct for them, irrespective of the results from the ANOVA or Kruskal tests. “

We also acknowledge in the manuscript (Methods section) that the Kruskal-Wallis test is used for a single factor (independent variables) at a time. This is unlike the ANOVA test that we initially performed, which was handling multiple factors simultaneously (given that it was performed in a multifactorial design). For a more direct comparison with our ANOVA model, we ran separate Kruskal-Wallis tests for each factor, but then we acknowledged its potential limitations compared to our multifactorial ANOVA, since each of these tests treats the factor in question as the only source of variation, not considering other factors. But since the test is not intended for interactions or combined effects of these factors, we deem it to be sufficient.

Nevertheless, we concur with the reviewer that normalizing the data could potentially enhance GWAS results. Consequently, we have rerun the GWAS analyses using the PLINK2 --quantile- normalize and --variance-standardize options. We have updated all results on the website and also updated the plots in the manuscript, accordingly.

Minor points:

On the introduction, I think the authors would find the extensive set of human GWAS/PheWAS resources useful; widespread examples include the GWAS Catalog, Open Targets PheWAS, MR-base, and the FinnGen portal. The GWAS Catalog also has summary statistics submission guidelines, and I think where possible meta-data harmonisation should be similar (not a big thing). Of course, DRGP has a very different structure (line and individuals) and of course, raw data can be freely shown, so this is not a one-to-one mapping.

Thank you for the suggestion. We cited these resources in the Introduction.

“This aligns with the harmonization effort undertaken by other human GWAS/PheWAS resources, such as the GWAS Catalog, Open Targets PheWAS, MR-base, and the FinnGen portal, which provide extensive examples of effective data use and accessibility. Although the structure of DGRPool differs from these human databases, we acknowledge the importance of similar meta-data harmonization guidelines. Inspired by the GWAS Catalog's summary statistics submission guidelines, we propose submission guidelines for DGRP phenotyping data in this paper. “

For some authors coming from a human genetics background, they will be interpreting correlations of phenotypes more in the genetic variant space (eg LD score regression), rather than a more straightforward correlation between DRGP lines of different individuals. I would encourage explaining this difference somewhere.

We understand that this is a potential issue and we made the distinction clearer in the manuscript to avoid any confusion. We added this text on p.7, at the beginning of the correlation results section:

“Of note, by “phenotype correlations”, we mean direct phenotype-phenotype correlations, i.e. a straightforward Spearman’s correlation of two phenotypes between common DRGP lines, and we repeated this process for each pair of phenotypes. “

This leads to an interesting point that the inbred nature of the DRGP allows for both traditional genetic approaches and leveraging the inbred replication; there is something about looking at phenotype correlations through both these lenses, but this is for another paper I suspect that this harmonised pool of data can help.

We agree with the reviewer and hope that more meta-analyses will be made possible by leveraging the harmonized data that are made available through DGRPool.

I was surprised the authors did not crunch the number of transcript/gene expression phenotypes and have them in. Is this because this was better done in other datasets? Or too big and annoying on normalisation? I'd explain the rationale to leave these out.

This is a very good point and is in fact something that we initially wanted to do. However, to render the analysis fair and robust, it would require processing all datasets in the same way. This implies cataloging all existing datasets and processing them through the same pipeline. In addition, it would require adding a “cell type” or “tissue” layer, because gene expression data from whole flies is obviously not directly comparable to gene expression data from specific tissues or even specific conditions. This would be key information as phenotypes are often tissue-dependent. Consequently, and as implied by the reviewer, we deemed this too big of a challenge beyond the scope of the current paper. Nevertheless, we plan to continue investigating this avenue in a potential follow-up paper.

We still added a gene-centric tool to be able to query the GWAS results by gene. We also added orthologs and Flybase gene-phenotype information, both in this new gene-centric tool and also in all GWAS results.

I think 25% FDR is dangerously close to "random chance of being wrong". I'd just redo this section at a higher FDR, even if it makes the results less 'exciting'. This is not the point of the paper anyway.

We agree with the reviewer that this threshold implies a higher risk of false positive results. However, this is not an uncommonly used threshold (Li et al., PLoS biology, 2008; Bevers et al., Nature Metabolism, 2019; Hwangbo et al, Elife, 2023), and one that seems robust enough in our analysis since similar phenotypes are significant in different studies at different FDR thresholds.

Nevertheless, we revisited these results with a stronger threshold of 5% FDR in the main Figure 3C. Most of the conclusions were maintained, except for the relation between longevity and “food intake”, as well as “sleep duration”. We modified the manuscript accordingly, notably removing these points from the abstract, and tuning down the results section. We kept the 25% FDR results as supplemental information.

I didn't buy the extreme line piece as being informative. Something has to be on the top and bottom of the ranks; the phenotypes are an opportunity for collection and probably have known (as you show) and cryptic correlations. I think you don't need this section at all for the paper and worry it gives an idea of "super normals" or "true wild types" which ... I just don't think is helpful.

We appreciate the reviewer’s feedback on the section regarding extreme DGRP lines and understand the concern about potential implications of “super normals” or “true wild types.” This section aimed to explore whether specific DGRP lines consistently rank in the extremes of phenotypic measures, particularly those tied to viability-related traits. Our hypothesis was that if particular lines consistently appear at the top or bottom, this might suggest some inherent bias or inbreeding-related weakness that could influence genetic association studies.

However, as per the analyses presented, we did not discover support for this phenomenon. Importantly, the observed mild correlation in extremeness across sexes, while not profound, further suggested that this phenomenon is not a consistent population-wide feature.

Nevertheless, we consider that this message is still important to convey. In response to the reviewer's feedback, we have provided a clearer conclusion of this paper section by adding the following paragraph:

“In conclusion, this analysis showed that while certain lines exhibit lower longevity or outlier behavior for specific traits, we found no evidence of a general pattern of extremeness across all traits. Therefore, the data do not support the idea of 'super normals' or any other inherently biased lines that could significantly affect genetic studies. “

I'd say "well-established inversion genotypes and symbiot levels" rather than generic covariates. Covariates could mean anything. You have specific "covariates" which might actually be the causal thing.

We thank the author for the suggestion. We agree and modified the manuscript accordingly.

I wouldn't use the adjective tedious about curation. It's a bit of a value judgement and probably places the role of curation in the wrong way. Time-consuming due to lack of standards and best practice?

We thank the author for the suggestion. We agree and modified the manuscript accordingly, replacing the occurrences by “thorough” and “rigorous” which correspond better to the initial intended meaning.

Reviewer #2 (Public Review):

Summary:

In the present study, Gardeux et al provide a web-based tool for curated association mapping results from DRP studies. The tool lets users view association results for phenotypes and compare mean phenotype ~ phenotype correlations between studies. In the manuscript, the authors provide several example utilities associated with this new resource, including pan-study summary statistics for sex, traits, and loci. They highlight cross-trait correlations by comparing studies focused on longevity with phenotypes such as oxphos and activity.

Strengths:

-Considerable efforts were dedicated toward curating the many DRG studies provided.

-Available tools to query large DRP studies are sparse and so new tools present appeal

Weaknesses:

The creation of a tool to query these studies for a more detailed understanding of physiologic outcomes seems underdeveloped. These could be improved by enabling usages such as more comprehensive queries of meta-analyses, molecular information to investigate given genes or pathways, and links to other information such as in mouse rat or human associations.

We appreciate the reviewer's kind comments.

Regarding the tools, we concur with the reviewer that incorporating additional tools could enhance DGRPool and facilitate users in conducting meta-analyses. Therefore, we developed two new tools: a gene-centric tool that enables users to query the database based on gene names, and a variant-centric tool mostly for studying the impact of specific genomic loci on phenotypes. Additionally, in all GWAS results, we added links to ortholog databases, thereby allowing users to extend fly gene associations to other species, if required.

Furthermore, we added links to the Flybase database, for variants, phenotypes, and genes that are already present in Flybase. We also link out to a 'genome browser-like' view (Flybase’s JBrowse tool) of the GWAS results centered around the affected variants/genes.

Finally, we now also perform a gene-set enrichment analysis for each GWAS result, both in the Flybase gene-phenotype database and the Gene Ontology (GO) database.

Reviewer #2 (Recommendations For The Authors):

(1) The authors discuss how current available DRG databases are basically data-dump sites and there is a need for integrative queries. Clearly, they spent (and are spending) considerable efforts into curating associations from available studies so the current resource seems to contain several areas of missed opportunities. The most clear addition would be to integrate gene-level queries. For example which genes underlie associations to given traits, what other traits map to a specific gene, or multiple genes which map to traits. This absence of integration is somewhat surprising given the lab's previous analyses of eQTL data in DRPs (https://doi.org/10.1371/journal.pgen.1003055 ) and readily available additional data (ex. 10.1101/gr.257592.119 ,flybase) simple intersections between these at the locus level would provide much deeper molecular support for searching this database.

The point raised by the reviewer concerning eQTL / transcriptomic data is in fact similar to the one raised by reviewer #1. We strongly agree with both reviewers that incorporating eQTL results in the tool would be very valuable, and this is in fact something that we initially wanted to do. However, to render the analysis fair and robust, it would require re-processing multiple public datasets in the same way. This would imply cataloging all existing datasets and processing them through the same pipeline. In addition, it would require adding a “cell type” or “tissue” layer, because gene expression data from whole flies is obviously not directly comparable to gene expression data from specific tissues or even specific conditions. This would be key information as phenotypes are often tissue-dependent. Consequently, we deemed implementing all these layers too big of a challenge beyond the scope of the current paper, but we plan to continue investigating this avenue in a potential follow-up paper.

As mentioned before, we still integrated gene-level queries in a new tool, querying genes in the context of GWAS results. We acknowledge that this is not directly related to gene expression, and thus not implicating eQTL datasets (at least for now), but we think that it is for now a good alternative, reinforcing the interpretation of the GWAS results.

Since this point was raised by both reviewers, we added a discussion about this in the manuscript.

“We recognize certain limitations of the current web tool, particularly the lack of eQTL or gene expression data integration. Properly integrating DGRP GWAS results with gene expression data in a fair and robust manner would require uniform processing of multiple public datasets, necessitating the cataloging and standardization of all available datasets through a consistent pipeline. Moreover, incorporating a “cell type” or “tissue” layer would be essential, as gene expression data from whole flies is not directly comparable to data from specific tissues or even specific conditions. Since phenotypes are often tissue-dependent, this information is vital. However, implementing these layers presented too big of a challenge and was beyond the scope of this paper. “

(2) Another area that would help to improve is to provide either a subset or the ability to perform a meta-analysis of the studies proposed to see where phenotype intersections occur, as opposed to examining their correlation structure. For any given trait the PLINK data or association results seem already generated so running together and making them available seems fairly straightforward. This can be done in several ways to highlight the utility (for example w/wo specific covariates from Huang et al., 2014 and/or comparing associations that occur similarly or differently between sexes).

We are not 100% sure what the reviewer refers to when mentioning “phenotype intersection”, but we interpreted it as a “PheWAS capability”. Currently, in DGRPool, for every variant, there is a PheWAS option, which scans all phenotypes across all studies to see if several phenotypes are impacted by this same variant.

We tried to make this tool more visible, both in the GWAS section of the website, but also in the “Check your phenotype” tool, when users are uploading their own data to perform a GWAS. We have also created a “Variants” page, accessible from the top menu, where users can view particular variants and explore the list of phenotypes they are significantly associated with.

From both result pages, users can download the data table as .tsv files.

(3) As pointed out by the authors, an advantage of DRGs is the ease of testing on homozygous backgrounds. For each phenotype queried (or groups of related phenotypes would be of interest too), I imagine that subsetting strains by the response would help to prioritize lines used for follow-up studies. For example, resistant or sensitive lines to a given trait. This is already done in Fig 4C and 4E but should be an available analysis for all traits.

For all quantitative phenotypes, we show the global distribution by sex, followed by the sorted distribution by DGRP line. Since the data can be directly downloaded from the corresponding plots, resistant and sensitive lines can then be readily identified for all phenotypes.

(4) To researchers beyond the DRP community, one feature to consider would be seeing which other associations are conserved across species. While doing this at the phenotype level might be tricky to rename, assigning gene-level associations would make this streamlined. For example, a user could query longevity, subset by candidate gene associations then examine outputs  for  what  is  associated  with  orthologue  genes  in  humans (ex. https://www.ebi.ac.uk/gwas/docs/file-downloads) or other reference panels such as mice and rats.

In all GWAS results, and in the gene-centric tool, we have added links to ortholog databases. In short, when clicking on a variant, users can see which gene is potentially impacted by this variant (gene-level variant annotation). When clicking on these genes, the user can then open the corresponding, detailed gene page.

To address the reviewer’s comment, in the gene page, we have added two orthologous databases (Flybase and OrthoDB), which enables cross-species association analyses.

(5) Related to enabling a meta-data analysis, it would be helpful to let users download all PLINK or DGRP tables in one query. This would help others to query all data simultaneously.

We would like to kindly point out that all phenotyping data can already be downloaded from the front page, which includes the phenotypes, the DGRP lines and the studies’ data and metadata. However, we did not provide the global GWAS results through a single file, because the data is too large. Instead, we provide each GWAS dataset via a unique file, available per phenotype, on the corresponding GWAS result page of this phenotype. This file is filtered for p<0.001, and contains GWAS results (PLINK beta, p and FDR) as well as gene and regulatory annotations.

(6) Following analysis of association data an interesting feature would be to enable users to subset strains for putative LOF variants at a given significant locus. This is commonly done for mouse strains (ex. via MGI).

The GWAS result table available for each phenotype can be filtered for any variant of interest. We added the capability to filter by variant impact; LOF variants being usually referred to as HIGH impact variants.

(7) Viewing the locus underlying annotation can also provide helpful information. For example, several nice fly track views are shown in 10.1534/g3.115.018929, which would help users to interpret molecular mechanisms.

We now link the GWAS results out to Flybase’s JBrowse genome browser.

eLife Assessment

This important study shows that a splice variant of the kainate receptor Glu1-1a that inserts 15 amino acids in the extracellular N-terminal region substantially changes the channel's desensitization properties, the sensitivity to glutamate and kainate, and the effects of modulatory Neto proteins. In the revised paper the authors have clarified several points raised by reviewers but the structural portion of the study has not been improved and consequently, more data are needed to determine the molecular mechanism by which the insert changes the functional profile of the channel. Even so, these solid findings advance our understanding of splice variants among glutamate receptors and will be of interest to neuro- and cell-biologists and biophysicists in the field.

Reviewer #1 (Public Review):

Kainate receptors play various important roles in synaptic transmission. The receptors can be divided into low affinity kainate receptors (GluK1-3) and high affinity kainate receptos (GluK4-5). The receptors can assemble as homomers (GluK1-3) or low-high affinity heteromers (GluK4-5). The functional diversity is further increased by RNA splicing. Previous studies have investigated C-terminal splice variants of GluK1, but GluK1 N-terminal (exon 9) insertions have not been previously characterized. In this study Dhingra et al investigate the functional implications of a GluK1 splice variant that inserts a 15 amino acid segment into the extracellular N-terminal region of the protein using whole-cell and excised outside-out electrophysiology.

The authors convincingly show that the insertion profoundly impacts the function of GluK1-1a - the channels that have the insertion are slower to desensitize. The data also shows that the insertion changes the modulatory effects of Neto proteins, resulting in altered rates of desensitization and recovery from desensitization. To determine the mechanism by which the insertion exerts these functional effects, the authors perform pull-down assays of Neto proteins, and extensive mutagenesis on the insert.<br /> The electrophysiological part of the study is very rigorous and meticulous.

The biggest weakness of the manuscript is the structural work. Due to issues with preferred orientation (a common problem in cryo-EM), the 3D reconstructions are at a low resolution (in the 5-8 Å range) and cannot offer much mechanistic insight into the effects of the insertion. The authors have opted to keep this data unchanged in the revised manuscript.

Despite this, the study is a valuable contribution to the field because it characterizes a GluK1 variant that has not been studied before and highlights the functional diversity that exists within the kainate receptor family.

Author response:

The following is the authors’ response to the previous reviews.

We are grateful to all three reviewers and editors for their critical comments and suggestions.

Reviewer #2 (Recommendations For The Authors):

The authors responded satisfactorily to all my comments and suggestions.

We thank the reviewer for his time and feedback.

Reviewer #3 (Recommendations For The Authors):

Comments for authors:

The authors have addressed most of the reviewer's concerns. Although no additional data were included to strengthen the manuscript, they have clarified some relevant points, and the manuscript has been updated accordingly. In my view, the current manuscript is well-written and mostly straightforward.

We thank the reviewer for his time and suggestions. Addressing them have improved the quality of our manuscript.

After a second revision, I just have a few minor comments (mostly editorial) that should be easy to address.

(1) Page 16: "The dominant presence of the GRIK1-1 gene was also reported in retinal Off bipolar cells..." Please include reference(s).

We have now cited the following reference:

Lindstrom, S.H., Ryan, D.G., Shi, J., DeVries, S.H., 2014. Kainate receptor subunit diversity underlying response diversity in retinal Off bipolar cells. J. Physiol. 592, 1457–1477. https://doi.org/10.1113/jphysiol.2013.265033

(2) Page 18: "Based on our functional assays, the splice seems to affect the interaction between the receptor and auxiliary proteins". Please remove or tone down this statement; the current data do not support this claim.

We have revised the sentence as following: “Based on our functional assays, the splice may possibly affect the interaction between the receptor and auxiliary proteins.”

(3) Page 24: "cultures ... at 0.5 µg/mL were transfected". In the current context, it is not clear what you mean with 0.5 µg/mL. Please check and correct.

Thanks for pointing out this error. We have corrected it.

(4) Page 30. He et al. reference is repeated.

Thanks. We have fixed it now.

(5) Figure 3, Panel C: Please incorporate the EC50 value for the red trace into the figure; it appears to be a different data set and, consequently, a different fitting compared with Figure 2C.

The GluK1-1a data set (red trace) is identical to that in Figure 2c, though it may appear different due to the scale of the X and Y axis. As suggested, we have now included the EC50 value for this data set in Figure 3, panel C.

(6) Figure legend 4: Please check two minor issues here:

(a) "Bar graphs... with or without Neto1 protein..." This statement is apparently wrong; Figure 4 does not show the effect of Neto1.

(b) "The wild type GluK1 splice variant data is the same as from Figure 1.." I think the authors mean Figure 2A instead of Fig. 1. Please check.

Thanks for pointing out the error. We have fixed the same in the revised manuscript.

(7) Please check and correct spelling/wording issues in the text. Here are some examples:

(a) Page 9 " Figure 3G - I, Table2.." (There is no Panel I). 

Fixed.

(b) Page 16 "... and is involved in various pathophysiology..." 

We have revised the sentence as “… and is involved in various pathophysiological conditions”

(c) Page 19 "The constructs used for this study were HEK293 WT mammalian cells were seeded on..." 

Fixed. Thanks.

(d) Page 23 "The immunoblots were probed..." Please check the whole paragraph and correct the issues.

Fixed. Thanks.

(e) Page 27 "initially, 1,97,908 particles were picked". Check the value; the same issue occurs in Fig.6 table supplement 1. 

Thanks. We have now modified the sentence to clarify that for  GluK1-1aEM ND-SYM, initially, 1,97,908 particles were picked and subjected to multiple rounds of clean-up using 2D and 3D classification. Finally,  24,531 particles were used for the final 3D reconstruction and refinement.

(f) Legend Figure 2: Remove "(F)" from the legend. 

Thanks. Fixed.

(g) Legend Figure 2-Sup.1: Check/correct spelling issues. 

Thanks. Fixed.

(h) Figure 5-figure supplement 1: There is a mistake in panel B: "GFP" label is shown for Gluk1 and Neto2, but the authors mention that the pull-down was done with Anti-His antibodies. Please correct.

Thanks. The pull-down experiments were done with anti-His for both the blots presented in panels A and B as mentioned in both the figures (right side panels of both A and B). However, for the GluK1 and Neto2 pull downs (panel B), the blots were probed with anti-GFP antibody which would detect both the receptor (as the receptor has both GFP-His8) and Neto2-GFP at their respective sizes. This has been indicated in the figure panel B.

(8) Related to the point-by-point document:

Major concern 2: Interpreting the effect of mutants on the regulation by Neto proteins requires knowing how the mutant is affecting the channel properties without Neto. In my view, if the data showing the K368/375/379/382H376-E mutant without Neto is missing (in this case due to low current amplitude), then, the pink bars in Fig. 5 should be removed from the figure. 

We thank the reviewer for raising this interesting point and agree that it would be valuable to characterize the channel properties of all the mutants individually. However, as mentioned earlier, the functions of some mutant receptors are only rescued, or reliable, measurable currents are detected, when they are co-expressed with Neto proteins. We still believe that comparing wild-type and mutant receptors co-expressed with Neto proteins provides important insights, and therefore, we would like to retain the K368/375/379/382H376-E mutant data in the figure.

Major concern 4: Figure 6-figure Supplement 8 is not mentioned in the manuscript. It would help to include a proper description in the Results section similar to the answer included in the point-by-point document.

Figure6-figure Supplement 8 has already been cited on page 15. We have also cited Figure6-figure Supplement 9 on the same page and have added following sentences in the text:

“A superimposition of GluK1-1aEM (detergent-solubilized or reconstituted in nanodiscs) and GluK1-2a (PDB:7LVT) showed an overall conservation of the structures in the desensitized state. No significant movements were observed at both the ATD and LBD layers of GluK1-1a with respect to GluK1-2a (Figure 6; Figure 6-figure supplement 9).”

Major concern 5: The ramp/recovery protocol was not included properly in the manuscript; please include the time of the ramp pulse and the time used for the recovery period.

Elaborated ramp and recovery protocols are included in the methods section. The time used for the recovery period was variable and was tuned as per the recovery kinetics. All the figures were representative traces are shown include the scale bar showing the time period of agonist application.

Minor concern 1: The proposed change was not included in the manuscript; check page 7.

Thanks for highlighting this error. We have now changed it in the revised manuscript.

Minor concern 10: The manuscript was not corrected as indicated. Please check.

Thanks. We have now modified the sentence as following: “…..a reduction was observed for K375/379/382H376-E receptors (1.17 ± 0.28 P=0.3733) compared to wild-type although differences do not reach statistical significance”

Minor concern 14: The figure was not corrected as indicated. Please check.

Thanks for highlighting this error. We have now changed it in the revised manuscript.

Minor concern 19: I suggest including this briefly in the Discussion section.

Thanks for the suggestion. We have included the following sentence in the discussion:

“The differences in observations could be due to variations in experimental conditions, such as the constructs and recording conditions used.”

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Weaknesses:

Given that all mutants tested showed the same degree of activation by PEG400, it seemed possible that PEG400 might be an allosteric activator of WNK1/3 through direct binding interactions. Perhaps PEG400 eliminates CWN1/2 waters by inducing conformational changes so that water loss is an effect not a cause of activation. To address this it would be helpful to comment on whether new electron densities appeared in the X-ray structure of WNK1/SA/PEG400 that might reflect PEG400 interactions with chains A or B.

We re-evaluated the WNK1/SA/PEG400 electron density looking for non-protein densities larger than water. No new densities were found. However, we do observe a PEG400-destabilizing effect using differential scanning fluorimetry, and have included this data into Figure 2. We conclude that the effects on the water structure and destabilization are due to demands on solvent.

We have included in the second paragraph of the introduction references to primary literature that advance similar arguments to explain osmolyte induced effects on activity.

Specifically, Colombo MF, Rau DC, Parsegian VA (1992) Protein solvation in allosteric regulation: a water effect on hemoglobin. Science 256: 655-659 and LiCata VJ, Allewell NM (1997) Functionally linked hydration changes in Escherichia coli aspartate transcarbamylase and its catalytic subunit. Biochemistry 36: 10161—10167. 

It would also be helpful to discuss any experiments that might have been done in previous work to examine the direct binding of glycerol and other osmolytes to WNKs.

We did not observe PEG400 in WNK1/SA/PEG400 despite effects on the space group and subunit packing. On the other hand, glycerol was observed in WNK1/SA, which was cryoprotected in glycerol (PDB file 6CN9). We have highlighted these differences in the second section of the results. A thorough analysis on the effects of various osmolytes on WNK structure, stability, and activity is a potential future direction.

The study would benefit from a deeper discussion about how to reconcile the different effects of mutations. For example, wouldn't most or all of the mutations be expected to disrupt the water network, and relieve the proposed autoinhibition? This seemed especially true for some of the residues, like Y420(Y346), D353(D279), and K310(K236), which based on Fig 3 appeared to interact with waters that were removed by PEG400.

The manuscript has been updated with new data and better discussion of this point. Given the inconsistencies on the effects of mutation in static light scattering (SLS), we addressed the possibility that the reducing agent was not constant across experiments. In a repeated study, including reducing agent (1 mM TCEP), we obtained results on mutant mass more similar to wild-type than in the original experiment. An exception was that two of the mutants were much more monomeric than wild-type. It follows that the network CWN1 stabilizes the inactive dimer. The reduced activity of some of the mutants probably reflects the position of CWN1 and the AL-CL Cluster in the active site, such that mutants can affect substrate binding or catalysis. This is now better discussed both in the data and discussion sections.

Mutants have a tendency to have complex effects on activity and structure. It was satisfying to find any activating mutants. We point out that we have been careful to present all of our data including mutants that are not easily explained by our models.

Alternatively, perhaps the waters in CWN2 are more important for maintaining the autoinhibited structure. This possibility would be useful to discuss, and perhaps comment on what may be known about the energetic contributions of bound water towards stabilizing dimers.

This research focused on the most salient unique feature of WNK1- CWN1. We also identified CWN2. Mutational analysis of CWN2 can’t be done without disrupting the dimer interface, greatly complicating data interpretation.

It would also be useful to comment on why aggregation of E319Q/A (E314) shouldn't inhibit kinase activity instead of activating it.

On recollection of the SLS data in the presence of reducing agent, we saw reduced aggregation. WNK3/D279N and WNK3/E314Q were more monomeric, especially at the higher protein concentration used. WNK3/E314Q is one of the more active mutants.

The X-ray work was done entirely with WNK1 while the mutational work was done entirely with WNK3. Therefore, a simple explanation for the disconnect between structure and mutations might be that WNK1 and WNK3 differ enough that predictions from the structure of one are not applicable to mutations of the other. It would be helpful to describe past work comparing the structure and regulation of WNK1 and WNK3 that support the assumption of their interchangeability.

We have responded directly to this concern. We introduced our most interesting amino acid replacement WNK3/E314A into WNK1, making WNK1/E388A. Similar trends in chloride inhibition and mutational activation were observed in WNK1 as in WNK3. This supports the assumption of interchangeability of WNK1 and WNK3 we invoked for practical reasons.  As expected, the overall activity of WNK1 is lower than WNK3. Overall, the lower activity limited data collection. However, the lower activity did allow us to fit the chloride inhibition data to a kinetic model for WNK1.  Panels on WNK1 activity, mutation, and chloride inhibition were added to Figure 5 and to Supplemental data (Table S6).

Reviewer #2 (Public Review):

Strengths:

The most interesting result presented here is that P1 crystals of WNK1 convert to P21 in the presence of PEG400 and still diffract (rather than being destroyed as the crystal contacts change, as one would expect). All of the assays for activity and osmolyte sensing are carried out well.

Thank you. We have emphasized this point in the Results section with the word “remarkably”

Weaknesses:

The rationale for using WNK3 for the mutagenesis study is that it is more sensitive to osmotic pressure than WNK1. I think that WNK1 would have been a better platform because of the direct correlation to the structural work leading to the hypothesis being tested. All of the crystallographic work is WNK1; it is not logical to jump to WNK3 without other practical considerations.

This point is addressed in the last comment to Reviewer 1. We added autophosphorylation assay data on our most interesting mutant (WNK3/E314A) in WNK1 (WNK1/E388A). Conversely, we have crystallographic data on uWNK3 (on uWNK3/E314A collected to 3.3Å). These new data justify the assumption of interchangeability of results obtained for uWNK1 and uWNK3.

Osmolyte sensing was tested by measuring ATP consumption as a function of PEG400 (Figure 6). Data for the subset of mutants analyzed by this assay showed increasing activity. It is not clear why the same collection of mutant proteins analyzed in the experiments of Figure 5 was not also measured for osmolyte sensing in Figure 6.

These data are now more complete, having been now collected for all of the WNK3 mutants (now Figure 7).

The last set of data presented uses light scattering to test whether the WNK3 mutant proteins exhibit quaternary structural changes consistent with the monomer/dimer hypothesis. If they did, one would expect a higher degree of monomer for those that are activated by mutation, and a lower amount of monomer (like wt) for those that are not. Instead, one of the mutant proteins that showed the most chloride inhibition (Y346F) had a quaternary structure similar to the wt protein, and others have similar monomer/dimer mixtures but distinct chloride inhibition profiles (K307A and M301A). I don't see how the light scattering data contribute to this story other than to refute the hypothesis by showing a lack of correlation between quaternary structure, water binding, and activity. This is another reason why the disconnect between WNK1 and WNK3 could be a problem. All of the detailed structural work with WNK1 must be assumed with WNK3; perhaps the light scattering data are contradicting this assumption?

As noted above, on recollection of the SLS data in the presence of reducing agent, we saw reduced aggregation and more consistency with our model. Thus, we now feel it is a useful contribution to the manuscript. The table in Supplemental data has been updated.

Reviewer #1 (Recommendations For The Authors):

Fig 3D in the PDF manuscript seemed distorted - waters were cut off. Also Fig 2D would benefit from showing the whole molecule, instead of cutting off the top and bottom of the kinase domain.<br /> We suspect this is a data transfer problem, since we don’t see these truncations.

Both Figure 2 and 3 have been changed, addressing these concerns and adding new differential scanning fluorimetry data as discussed in reply to Reviewer 1. Figure 2 was simplified by eliminating Figures 2A-2C, and replacing them with a new Figure 2B, the superposition of WNK1/SA/PEG400 (PDB 9D3F), WNK1/SA (PDB 6CN9).  

In Figure 3, we added a panel highlighting the volume change around CWN1 in presence of PEG400 (Figure 3C). Hopefully, inappropriate cropping has been eliminated.

Line 162: Y314F should be Y346F.

This has been corrected. Thank you.

Lines 211-213 - these two sentences do not seem to logically go together: "Two hyper-active mutants were discovered, WNK3/E314A, and WNK3/E314Q. These mutants are straightforward to interpret based on our model: the mutated residues support and stabilize inactive dimeric WNK."

An extensive rewrite has been conducted to address the difference in activity between the higher activity mutants versus less active mutants, now discussed in two paragraphs, and two Figures, Figure 5 and 6. The SLS data, recollected with more reducing agent, has given more consistent results (Supplemental), making the discussion more straightforward (discussed above).

Reviewer #2 (Recommendations For The Authors)

I think WNK1 would be a better platform for mutagenesis than WNK3. Or minimally the authors should better justify the switch to WNK3 from WNK1. Analyze the same set of mutants in Figure 5 into Figure 6.

Again, we have added assay data on uWNK1/E388A, and structural data on uWNK3/E314A.

I would analyze the same set of mutants in Figures 5 and 6.

We have analyzed all of the WNK3 mutants in the ADP-Glo assays (Figure 7).

Will the P21 crystal form grow independently in PEG400?

Attempts to crystallize WNK1/SA or WNK3/SA or other constructs in PEG400 have been unsuccessful.

I would also add some context about the role of water in allosteric mechanisms. I know there is a long history in hemoglobin in which specific waters have been associated with the T and R states such as that by Marcio Colombo. There is a relatively recent article in J. Phys Chem. that would provide good context. Leitner et al., J. Chem. Phys. 152, 240901 (2020)

Thank you. Good call.

eLife Assessment

This study presents an important investigation of water coordination in a specific kinase family with a focus on the regulation of osmosensing protein kinases. X-ray crystallographic approaches combined with functional assays are used to address the hypothesis that bound water participates in the osmosensing mechanism as an allosteric kinase inhibitor. The evidence for changes in kinase conformation and space group of the crystal as a function of added low molecular weight polyethylene glycol is solid. The work will be of considerable interest to the kinase field as well as colleagues studying allosteric regulation of protein function.

Reviewer #1 (Public Review):

This manuscript addresses the regulation of the osmosensing protein kinases, WNK1 and WNK3. Prior work by the authors has shown that these enzymes are activated by PEG400 or ethylene glycol and inhibited by chloride ion, and that activation is associated with a conformational transition from dimer to monomer. In X-ray structures of the WNK1/SA inactive dimer, a water-mediated hydrogen bond network was observed between the catalytic loop (CL) and the activation loop (AL), named CWN1. This led to the proposal that bound water may be part of the osmosensing mechanism.

The current study carries this work further, by applying PEG400 to Xtals of dimeric WNK1/SA. This results in a change in kinase conformation and space group, along with 4-9 fewer waters in CWN1 and the complete disappearance of another water cluster (CWN2) located at the dimer interface. Six conserved residues lining the CWN1 pocket in WNK3 are mutated to determine effects on activity and inhibition by chloride ion (measured by AL autophosphorylation) and monomer-dimer interconversion (light scattering).

The results show that two mutants (E314Q/A in WNK3) at a site central to the water cluster result in increased kinase activity (autophosphorylation), and increased SLS, interpreted as aggregation. Three sites (D279A, Y346F, M301A) inhibit kinase activity with varying effects on oligomerization - Y346A and M301A retain monomer-dimer ratios similar to WT while D279N promotes aggregation. K236A and K307A show activity and monomer:dimer ratios similar to WT. Selected mutants (E314Q, D279N, Y346F) and WT appear to retain osmosensitivity with comparable activation by PEG400.

The study concludes that osmolytes may activate the kinase by removing waters from the CWN1 and CWN2 clusters, suggesting that waters might be considered allosteric ligands that promote the inactive structure of WNKs. The differing effects of mutations may be ascribed to disruption of the water networks as well as inhibitory perturbations at the active site.

Comments on latest version:

The revised manuscript incorporated new experiments that satisfactorily addressed my concerns.

Reviewer #2 (Public Review):

This work tests the hypothesis that water coordination in WNK kinases is linked to allosteric control of activity. It is proposed that dimeric WNK is inactive and bound to some conserved water molecules, and that monomerization/activation involves departure of these waters. New data here include a crystal structure of monomeric WNK1 which shows missing waters compared to the dimeric structure, in support of the hypothesis. Mutant proteins of a different isozyme (WNK3) designed to disrupt water coordination were produced, and activity and quaternary structure were measured.

Comments on latest version:

The authors have largely addressed my concerns by making sure collection of mutants analyzed for autophosphorylation in Figure 6 are consistent with the measurement of osmotic sensitivity in Figure 7. The other changes in response to reviews have made a stronger manuscript in my opinion.

eLife Assessment

This fundamental study uses a creative experimental system to directly test Ohno's hypothesis, which describes how and why new genes might evolve by duplication of existing ones. In agreement with existing criticism of Ohno's original idea, the authors present compelling evidence that having two gene copies does not speed up the evolution of a new function as posited by Ohno, but instead leads to the rapid inactivation of one of the copies through the accumulation of mostly deleterious mutations. These findings will be of broad interest to evolutionary biologists and geneticists.

Reviewer #1 (Public review):

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

Comments on revised version:

The authors have addressed my prior concerns, and I have no further comments on the manuscript.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

In the revised version of the paper, the authors now discuss one potential weakness of their study, which is tied to its biggest strength (as often in experimental biology there is a trade-off between 'resolution' and 'realism').<br /> The experimental set-up leaves out an important component of the evolutionary process in order to disentangle dosage effects from other effects that carrying two copies might have on their evolution. Specifically, by employing a recombination-deficient strain and constructing their duplicates as inverted repeats their experimental design completely abolishes recombination between the two copies. This was pointed out in my first review to be problematic for two reasons:

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

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

In their revised version, the authors now address this point and with much clarity explain why their experimental system is so powerful to study the fate of a gene duplicate, not despite lacking recombination, but *because* it lacks recombination.

Author response:

The following is the authors’ response to the original reviews.

eLife assessment

This fundamental study uses a creative experimental system to directly test Ohno's hypothesis, which describes how and why new genes might evolve by duplication of existing ones. In agreement with existing criticism of Ohno's original idea, the authors present compelling evidence that having two gene copies does not speed up the evolution of a new function as posited by Ohno, but instead leads to the rapid inactivation of one of the copies through the accumulation of mostly deleterious mutations. These findings will be of broad interest to evolutionary biologists and geneticists.

We thank the editors and the reviewers for their positive feedback concerning our experimental system and for the constructive feedback on how to further improve the manuscript. We have now addressed the reviewer’s comments in a revised version.

Reviewer #1 (Public Review):

Overview:

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

Major comments:

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

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

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

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

We fully agree with the reviewer that trade-offs might play an important role in the evolution of single copy and of duplicated genes, depending on the gene and on the selection regime. And while trade-offs are not likely to play a big role in the selection regime we discuss in detail in the main text (evolution towards more green), they probably are important for at least one our selection regimes. In fact, we so state in the following passage of the discussion. In addition, we have now added a sentence that acknowledges the importance of trade-offs for evolution in the absence of gene duplication:

“A single gene encoding such a protein suffers from an adaptive conflict between the two activities. Gene duplication may provide an escape from this adaptive conflict, because each duplicate may specialize on one activity14, 15. For coGFP, a trade-off likely exists for fluorescence in these two colors, because improvement of green fluorescence entails a loss of blue fluorescence during evolution (Figure S8 and Figure S16). We therefore expected that during selection for both green and blue fluorescence, one cogfp copy in double-copy populations would “specialize” on green fluorescence whereas the other copy would specialize on blue fluorescence. However, when we analyzed individual population members with two active gene copies we could not find any such specialization (Figure S21). Moreover, the identified key mutations at positions 147 and 162 have a very low frequency (<1%) in these populations (Figure S15). Future experiments with different selection strategies might reveal the reasons for this observation and the conditions under which such a specialization can occur.“

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

The reviewer is correct. To be able to follow the evolutionary trajectories of the different constructs, the populations were treated separately. The gates were adjusted for each library separately to select for the top 60, 1 or 0.01% of cells and the gates for the double-copy populations were set to slightly higher fluorescence, reflected in the higher fluorescence of these populations in Figure 3A. Indeed, if individuals in these populations were to compete against each other, the double-copy populations would have a benefit due to the dosage advantage. However, as we already pointed out in the manuscript, we did not see any additional advantage beyond the increased gene dosage provided by the second copy (Figure 3B). To discuss this issue in more detail, we have now added the following text to the discussion:

“It is worth noting that we evolved each of our single- and double-copy populations separately and in parallel to follow their individual evolutionary trajectories. In a natural population, individuals with one or two copies might occur in the same population and compete against each other. In this situation any dosage advantage of a duplicate gene would itself entail selective benefit. Our approach allowed us to find out if gene duplication facilitates phenotypic evolution beyond any such gene dosage effect. At least for the specific genes, selection pressures, and mutation rates we used, the data suggest that it does not.”

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

Figure S15 shows that some mutations are indeed still increasing in frequency during late evolutionary rounds, in particular S2L, V141L and V205L. We have measured the emission spectra of these mutants (Figure S16), and these mutations increase fluorescence both in green and blue. It is therefore likely that these mutations, similar to L98M, increase protein expression, solubility, or thermal stability, as suggested by the reviewer. We now clarify this matter in a new passage of the results:

“Like L98M, the additional mutations S2I, V141I and V25L also occurred in all selection regimes, but they reached lower frequencies than L98M during the 5 generations of the experiment. We hypothesized that mutations observed in all selection regimes do not derive their benefit from increasing the intensity of any one fluorescent color. Instead, they may increase protein expression, solubility, or thermal stability.”

Reviewer #2 (Public Review):

Summary:

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

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

Strengths:

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

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

Weaknesses:

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

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

This is problematic for two reasons:

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

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

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

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

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

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

We understand the reviewer’s position and fully agree that we needed to clarify better what our experiments aimed to achieve. To this end, we rewrote the beginning of the discussion to read:

“Our aim was to study whether gene duplication can affect mutational robustness and phenotypic evolution beyond any effect of increased gene dosage provided by multiple gene copies. To this end, we needed to maintain a constant and stable copy number of duplicated genes during experimental evolution.”

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

On this point, we respectfully disagree. To ask questions like ours, laboratory experiments that are highly controlled albeit possibly “unnatural” can be essential. And we would argue that our experiments do not merely aim to “recapitulate” an influential idea but to validate it and potentially refute it, as we did for our study system. Validating theory is an essential aspect of experimental science. Textbooks in biology and beyond are rife with examples.

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

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

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

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

Your points are well taken. To clarify the insights from previous experiments and the aims of our experiments we rewrote this passage in question as follows.

“These studies underline the importance of gene duplication in providing fast adaptation under changing environmental conditions. In some studies one copy was lost6, 25, while in others, additional copies were gained8, 26, 27. Together these studies highlight that gene dosage and selection for dosage can play an important role during the evolution of duplicated genes6, 8, 25-28.

These studies also raise the question whether gene duplication can provide an advantage beyond its effects on gene dosage. To find out it is necessary to study the evolution of gene duplicates while keeping the copy number of the duplicated gene exactly at two. This is challenging because gene duplication causes recombinational instability and high variability in copy number. No previous experimental studies were designed to control copy number. Here, we present an experimental system that allowed us to keep the copy number fixed at one or two genes, and to follow the evolution of each gene copy in the absence of any dosage increase.”

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

We agree and in response rewrote the paragraph in question to read:

“The challenge that a duplicated gene copy must remain free of frequent deleterious mutations long enough to acquire beneficial mutations that provide a new selectable phenotype is known as Ohno’s dilemma13. Our experiments confirm that this challenge is highly relevant for post-duplication evolution. Other models such as the innovation-amplification-divergence (IAD) model8, 13 postulate that this dilemma can be resolved through an increase in gene dosage that allows latent pre-duplication phenotypes to come under the influence of selection. To distinguish between the effects of gene dosage and other benefits of gene duplication, we prevented recombination and gene amplification to prevent copy number increases beyond two copies. We are aware that our experimental design does not reflect how evolution may occur in the wild. However, this design allowed us to study evolutionary forces separately that are otherwise difficult to disentangle. “

Finally, we also made two changes in the abstract (highlighted in red) to take your feedback into account.

Reviewer #2 (Recommendations For The Authors):

The paper is very well written, with a lot of emphasis put on explaining every step and every finding. It was a joy to read.

Thanks!

Full stop missing in line 5 of abstract.

Corrected.

eLife Assessment

In this valuable study, the authors investigate how inflammatory priming and exposure to irradiated Mycobacterium tuberculosis or the bacterial endotoxin LPS impact the metabolism of primary human airway macrophages and monocyte-derived macrophages. The work shows that metabolic plasticity is greater in monocyte-derived macrophages than alveolar macrophages, with solid experimental methods and overall evidence. The findings are relevant to the field of immunometabolism.

Reviewer #3 (Public review):

Summary:

In this manuscript the authors explore the contribution of metabolism to the response of two subpopulations of macrophages to bacterial pathogens commonly encountered in the human lung, as well as the influence of priming signals typically produced at a site of inflammation. The two subpopulations are resident airway macrophages (AM) isolated via bronchoalveolar lavage and monocyte-derived macrophages (MDM) isolated from human blood and differentiated using human serum. The two cell types were primed using IFNγ and Il-4, which are produced at sites of inflammation as part of initiation and resolution of inflammation respectively, followed by stimulation with either heat-killed tuberculosis (Mtb) or LPS to simulate interaction with a bacterial pathogen that is either gram-negative in the case of Mtb or gram-positive in the case of LPS. The authors use human cells for this work, which makes use of widely reported and thoroughly described priming signals, as well as model antigens. This makes the observations on the functional response of these two subpopulations relevant to human health and disease to a greater extent that the mouse models typically used to interrogate these interactions. To examine the relationship between metabolism and functional response, the authors measure rates of oxidative phosphorylation and glycolysis under baseline conditions, primed using IFNγ or IL-4, and primed and stimulated with Mtb or LPS.

Overall, this study reveals how inflammatory and anti-inflammatory cytokine priming contributes to the metabolic reprogramming of AM and MDM populations. Their conclusions regarding the relationship between cytokine secretion and inflammatory molecule expression in response to bacterial stimuli are supported by the data. The involvement of metabolism in innate immune cell function is relevant when devising treatment strategies that target the innate immune response during infection. The data presented in this paper further our understanding of that relationship and advance the field of innate immune cell biology.

Author response:

The following is the authors’ response to the previous reviews.

Reviewer #2 (Recommendations for the authors):

Comments to the authors:

R1. The authors show a similar reduction in ECAR as a measure of glycolytic inhibition upon treating H37Rv-infected unprimed MDMs with 5 mM 2-DG at 1 h and 24 h. However, the data pertaining to the extent of glycolytic inhibition upon 2-DG treatment in IFN-γ or IL-4 primed AMs or MDMs is not included.

We acknowledge that we have not checked the ECAR of every dataset herein treated with 2DG. However, we have provided evidence that 2DG reduced ECAR in the control datasets, and moreover, 2DG is functionally affecting the cells (e.g. the presence of 2DG altered cytokine production in both AM and MDM, even in the presence of IFN-γ or IL-4).

R2. The authors have replotted the same data as percent change and fold difference with different normalizing samples. While they have corrected one of the highlighted discrepancies in the data plotting of Fig. 1A and 1C, similar discrepancies are still evident in many other instances. Based on my understanding of the data and normalization methodology stated by the authors in response to comment (#5) by reviewer 1, the authors are plotting fold changes across all samples with respect to unstimulated and unprimed macrophages, whereas percent changes are plotted for stimulated (LPS or dead H37Rv) samples with respect to baseline measurements for each unstimulated sample under differently primed macrophages. I believe the slope of lines connecting unstimulated and LPS stimulates/H37Rv infected upon percent increase or decrease (from the baseline of unstimulated samples) will still maintain their trend in fold changes (relative to unstimulated and unprimed macrophages) irrespective of changes in absolute values. For instance, in Fig. 1F, there are at least 3 samples that show an increase in fold change in OCR upon H37Rv infection in IFN-γ primed MDMs. However, Fig. 1H, plotted from the same data, shows a decrease in OCR across all IFN-γ primed MDMs upon H37Rv infection. The authors have also highlighted that this decrease in OCR upon H37Rv infection in IFN- γ primed MDMs is highly significant (P < 0.01). The same data is again plotted as a bar plot in Fig. 1J as fold change relative to unstimulated and unprimed macrophages (mislabeled as percent change to unstimulated), showing no difference upon H37Rv infection of IFN-γ primed MDMs.

We have amended the axis in Figure 1 and Supplemental Figure 1 to more accurately describe the two different forms of analysis. We have fixed the errors outlined. We have also amended the methods in the text to clarify the two analyses carried out on the metabolic data. Lines 113-122 as follows:

“Fold change in ECAR and OCR was calculated compared to unstimulated unprimed controls at 150 minutes, where unstimulated unprimed macrophages were set to 1. This allows for analysis of the effects of both priming and subsequent stimulation for and accounts for the variation in the raw ECAR and OCR reading between runs thereby making each donor its own control.

Percent change in ECAR and OCR was also calculated to equalise groups to the same point prior to stimulation. Each condition was compared to its own respective primed or unprimed baseline at 30 minutes and this was set to 100%, prior to stimulation, this was carried to examine the capacity of cells to increase metabolic parameters in response to stimulation. Post stimulation percent change data was then extracted and analysed at 150 minutes. This controls for the priming effect and enables the analysis of metabolic capacity in each dataset.”

For figure 1J, the data is replotted from fold change datasets (not percentage change where the decrease in OCR is significant). The axis label has been revised for accuracy.

eLife Assessment

This study investigates the role of Caspar (Casp), an orthologue of human Fas-associated factor-1, in regulating the number of primordial germ cells that form during Drosophila embryogenesis. The findings are important in that they reveal an additional pathway that contributes to germ cell specification and maintenance. The evidence supporting the conclusions is solid, as the authors identify Casp and its binding partner Transitional endoplasmic reticulum 94 (TER94) as factors that influence germ cell numbers.

Reviewer #1 (Public review):

Summary:

The authors were seeking to define the roles of the Drosophila caspar gene in embryonic development and primordial germ cell (PGC) formation. They demonstrate that PGC number, and the distribution of the germ cell determinant Oskar, change as a result of changes in caspar expression; reduction of caspar reduces PGC number and the domain of Oskar protein expression, while overexpression of caspar does the reverse. They also observe defects in syncytial nuclear divisions in embryos produced from caspar mutant mothers. Previous work from the same group demonstrated that Caspar protein interacts with two partners, TER94 and Vap33. In this paper, they show that maternal knockdown of TER94 results in embryonic lethality and some overlap of phenotypes with reduction of caspar, supporting the idea may work together in their developmental roles. The authors propose models for how Caspar might carry out its developmental functions. The most specific of these is that Caspar and its partners might regulate oskar mRNA stability by recruiting ubiquitin to the translational regulator Smaug.

Strengths:

The work identifies a new factor that is involved in PGC specification and points toward an additional pathway that may be involved in establishing and maintaining an appropriate distribution of Oskar at the posterior pole of the embryo. It also ties together earlier observations about the presence of TER94 in the pole plasm that have not heretofore been linked to a function.

Weaknesses:

(1) A PiggyBac insertion allele casp[c04227] is used throughout the paper and referred to as a loss-of-function allele (casp[lof]). While the authors avoid the terms 'null' or 'amorph' and on one occasion refer to the allele as a 'strong hypomorph', nevertheless terming it a 'loss-of-function' allele is misleading. This is because the phenotype of the allele when homozygous is different from the phenotype produced when heterozygous over a deficiency.

(2) The peptide counts in the mass spectrometry experiment aimed at finding protein partners for Casp are extremely low, except for Casp itself and TER94. Peptide counts of 1-2 seem to me to be of questionable significance.

(3) The pole bud phenotypes from TER94 knockdown and casp mutant shown in Fig 5 appear to be quite different. These differences are unexplained and seem inconsistent with the model proposed that the two proteins work in a common pathway. Whole embryos should also be shown, as the TER94 KD phenotype could result from a more general dysmorphism.

(4) Fig 6 is not quantitative, lacking even a second control staining to check for intensity variation artifacts. Therefore it shows that the distribution of Oskar protein changes in the various genotypes, but not convincingly that the level of Oskar changes as the paper claims.

(5) The error bars are huge in the graphs in Fig 7H, I, and J, and in fact these changes are not statistically significant. Therefore the conclusion that 'Reduction in Casp activity specifically affects Smaug degradation during the MZT' is not supported by the data in this figure.

Reviewer #2 (Public review):

Summary:

This study investigated the role of the Caspar (Casp) gene, a Drosophila homolog of human Fas-associated factor-1. It revealed that maternal loss of Casp led to centrosomal and cytoskeletal abnormalities during nuclear cycles in Drosophila early embryogenesis, resulting in defective gastrulation. Moreover, Casp regulates PGC numbers, likely by regulating the levels of Smaug and then Oskar. They demonstrate that Casp protein levels are linearly correlated to the PGC number. The partner protein TER94, an ER protein, shows similar but slightly distinct phenotypes. Based on the deletion mutant analysis, TER94 seems functionally relevant for the observed Casp phenotype. Additionally, it is likely involved in regulating protein degradation during PGC specification.

Strengths:

This paper uncovers a new function of the Casper (Casp) gene, previously known for its role in immune response regulation and NF-kB signaling inhibition. This new function includes nuclear division and PGC formation in early fly embryos. The findings provide crucial insights into how this pathway contributes to the proper establishment of both somatic cells and the germline, particularly in the context of early embryogenesis. This research is therefore of significant interest to cell and developmental biologists.

Future Research:

While this study has made significant strides in understanding the role of the Casp gene in early embryogenesis, the functional relationships among molecules shown here (Casp, TER94, Osk) and other genes previously known to regulate these processes remain unclear. This underscores the need for future studies to delve deeper into these relationships and their implications.

Reviewer #3 (Public review):

Summary:

Das et al. discovered a maternal role for Caspar (Casp), the Drosophila orthologue of human Fas-associated factor-1 (FAF1), in embryonic development and germ cell formation. They find that Casp interacts with Transitional endoplasmic reticulum 94 (TER94). Loss of Casp or TER94 leads to partial embryonic lethality, correlated with aberrant centrosome behavior and cytoskeletal abnormalities. This suggests that Casp, along with TER94, promotes embryonic development through a still unidentified mechanism. They also find that Casp regulates germ cell number by controlling a key determinant of germ cell formation, Oskar, through its negative regulator, Smaug.

Strengths:

Overall, the experiments are well-conducted, and the conclusions of this paper are mostly well-supported by data.

Weaknesses:

Some additional controls could be included, and the language could be clarified for accuracy.

Author response:

The following is the authors’ response to the original reviews.

This study investigates the role of Caspar (Casp), an orthologue of human Fas- associated factor-1, in regulating the number of primordial germ cells that form during Drosophila embryogenesis. The findings are important in that they reveal an additional pathway involved in germ cell specification and maintenance. The evidence supporting the conclusions is solid, as the authors identify Casp and its binding partner Transitional endoplasmic reticulum 94 (TER94) as factors that influence germ cell numbers. Minor changes to the title, text, and experimental design are recommended.

We thank the Editors and Reviewers for their overall positive and thoughtful feedback. Based on these comments, we have revised our manuscript. The changes in the manuscript have been highlighted in ‘blue’ font for easy visualisation.

Reviewer #1 (Public Review):

Summary:

The authors were seeking to define the roles of the Drosophila caspar gene in embryonic development and primordial germ cell (PGC) formation. They demonstrate that PGC number, and the distribution of the germ cell determinant Oskar, change as a result of changes in caspar expression; reduction of caspar reduces PGC number and the domain of Oskar protein expression, while overexpression of caspar does the reverse. They also observe defects in syncytial nuclear divisions in embryos produced from caspar mutant mothers. Previous work from the same group demonstrated that Caspar protein interacts with two partners, TER94 and Vap33. In this paper, they show that maternal knockdown of TER94 results in embryonic lethality and some overlap of phenotypes with reduction of caspar, supporting the idea may work together in their developmental roles. The authors propose models for how Caspar might carry out its developmental functions. The most specific of these is that Caspar and its partners might regulate oskar mRNA stability by recruiting ubiquitin to the translational regulator Smaug.

Strengths:

The work identifies a new factor that is involved in PGC specification and points toward an additional pathway that may be involved in establishing and maintaining an appropriate distribution of Oskar at the posterior pole of the embryo. It also ties together earlier observations about the presence of TER94 in the pole plasm that have not heretofore been linked to a function.

Weaknesses:

(1)  A PiggyBac insertion allele casp[c04227] is used throughout the paper and referred to as a loss-of-function allele (casp[lof]). However, this allele does not appear to act strictly as a loss-of-function. Figure 1E shows that some residual Casp protein is present in early embryos produced by casp[lof]/Df females, and this protein is presumably functional as the PiggyBac insertion does not affect the coding region. Also, Figures 1B and 1C show that the phenotypes of casp[lof] homozygotes and casp[lof]/Df are not the same; surprisingly, the homozygous phenotypes are more severe. These observations are unexplained and inconsistent with the insertion being simply a loss-of-function allele. Might there be a second-site mutation in casp[c04227]?

The term loss-of-function (lof) is used rather than null or amorph. casplof is a strong hypomorph, with residual (and functional) protein estimated in the range 5-10% when compared to the wild type. The caspc04227 was procured from BDSC, and based on the decrease in lethality of the casplof/casp(Df) compared to casplof, we assume that second site hits in the casplof line are the reason for the enhanced lethality. For this very reason, we have used casplof/ casp(Df) for all subsequent experiments. We also conducted rescue experiments wherever possible to confirm the specificity with caspWT and various deletion variants of casp.

(2)  TER94 knockdown phenotypes have been previously published (Zhang et al 2018 PMID 30012668), and their effects on embryonic viability and syncytial mitotic divisions were described there. This paper is inappropriately not cited, and the data in Figure 4 should be presented in the context of what has been published before.

We apologize for the oversight. Indeed, Zhang et al. (2018) highlighted TER94 as one of the loci uncovered in their screen and some of the relevant phenotypes are described there. We have referred to their findings at the appropriate junctures as suggested (pg 11, pg13, pg 15).

(3)  The peptide counts in the mass spectrometry experiment aimed at finding protein partners for Casp are extremely low, except for Casp itself and TER94. Peptide counts of 1-2 seem to me to be of questionable significance.

Peptide counts are indeed low, but the fact that they are enriched at all, in comparison to controls, considering that we are using whole embryo lysates rather than isolated PGC lysates, suggests interaction with Casp could be biologically/ functionally meaningful. The data is restricted to the supplementary material and is not analyzed in isolation; we have combined data from multiple mass spectrometry experiments by other researchers to link Casp to pole plasm components.

(4)  The pole bud phenotypes from TER94 knockdown and casp mutant shown in Fig 5 appear to be quite different. These differences are unexplained and seem inconsistent with the model proposed that the two proteins work in a common pathway. Whole embryos should also be shown, as the TER94 KD phenotype could result from a more general dysmorphism.

We agree that TER94 KD is a stronger phenotype, with TER94 having essential cell division and patterning roles. In fact, the TER94 RNAi embryos, unlike casplof, stall in terms of their developmental program before Stage 4. This has been noted in the earlier study (Zhang et al., 2018). As a result, we focused on pole bud stage embryos that were rare - but present in the collections. We report that PGC from very early TER94 RNAi embryos have fewer pole buds.

The rationale behind the presumption that these two proteins may work in a common pathway is clear-cut. We have validated the physical interaction using protein lysates from two developmental time points. Satisfyingly, an affinity purification using antibodies against TER94 or Casp invariably enriches the other protein as the primary interacting partner. Our model integrates data from mammalian and fly systems to support the idea that there must be an overlap between TER94/Casp function, with these two proteins working together to engineer the degradation of ubiquitinated Smaug. Future experiments are necessary to confirm and extend this claim.

(5)  Figure 6 is not quantitative, lacking even a second control staining to check for intensity variation artifacts. Therefore, it shows that the distribution of Oskar protein changes in the various genotypes, but not convincingly that the level of Oskar changes as the paper claims.

We appreciate that oskar RNA localization is also somewhat altered due to change in casp levels. We have acknowledged the variability in the various phenotypes, and as such, it is unsurprising that it has also reflected in the Oskar levels. However, it is evident that a statistically significant number of mutant embryos show a decrease in Oskar levels.

(6)  The error bars are huge in the graphs in Figure 7H, I, and J, leading me to question whether these changes are statistically significant. Calculations of statistical significance are missing from these graphs and need to be added.

The data in the Western blots represents the whole embryo, as the lysates used are from embryos 0-1, 1-2, 2-3 hrs. We have averaged and plotted data from 5 Western blots. The changes are not statistically significant. Even without the statistical significance, the data for Fig. 7I led us to examine Smaug in the pole cells, rather than in the whole embryo. The pole cell data (Fig8-D3) is striking and led to the conclusion – that Smaug protein perdures in the pole cells during the stages of syncytial/cellular blastoderm.

(7)  There are many instances of fuzzy and confusing language when describing casp phenotypes. For example, on lines 211-212, it is stated that 'casp[lof] adults are only partially homozygous viable as ~70% embryos laid by the homozygous mutant females failed to hatch into larvae'. Isn't this more accurately described as 'casp[c04227] is a maternal-effect lethal allele with incomplete penetrance'? Another example is on line 1165, what exactly is a 'semi-vital function'?

We thank the reviewer for reading the manuscript in detail. We have tried to pay attention to reduce the ambiguity and fixed the text accordingly (pg 7, line 214; pg 33, line 1169, word semi-vital is deleted).

Reviewer #2 (Public Review):

Summary:

This study investigated the role of the Caspar (Casp) gene, a Drosophila homolog of human Fas-associated factor-1. It revealed that maternal loss of Casp led to centrosomal and cytoskeletal abnormalities during nuclear cycles in Drosophila early embryogenesis, resulting in defective gastrulation. Moreover, Casp regulates PGC numbers, likely by regulating the levels of Smaug and then Oskar. They demonstrate that Casp protein levels are linearly correlated to the PGC number. The partner protein TER94, an ER protein, shows similar but slightly distinct phenotypes. Based on the deletion mutant analysis, TER94 seems functionally relevant for the observed Casp phenotype. Additionally, it is likely involved in regulating protein degradation during PGC specification.

Strengths:

The paper reveals an unexpected function of the maternally produced Casp gene, previously implicated in immune response regulation and NF-kB signaling inhibition, in nuclear division and PGC formation in early fly embryos. Experiments are properly conducted and strongly support the conclusion. The rescue experiment using deletion mutant form is particularly informative as it suggests the requirement of each domain function.

Weaknesses:

Functional relationships among molecules shown here (and other genes known to regulate these processes) are still unclear.

We completely agree with this assessment. In our view this is an interesting albeit initial report. We also appreciate that understanding the mechanistic underpinnings of these results will be critical. We have ensured that our present claims are backed up by data, however, are fully sensitive to the fact that newer observations will refine or even alter these claims. We are continuing to work on the problem and will hopefully make further inroads in mechanism in the coming years.

Reviewer #3 (Public Review):

Summary:

Das et al. discovered a maternal role for Caspar (Casp), the Drosophila orthologue of human Fas-associated factor-1 (FAF1), in embryonic development and germ cell formation. They find that Casp interacts with Transitional endoplasmic reticulum 94 (TER94). Loss of Casp or TER94 leads to partial embryonic lethality, correlated with aberrant centrosome behavior and cytoskeletal abnormalities. This suggests that Casp, along with TER94, promotes embryonic development through a still unidentified mechanism. They also find that Casp regulates germ cell number by controlling a key determinant of germ cell formation, Oskar, through its negative regulator, Smaug.

Strengths:

Overall, the experiments are well-conducted, and the conclusions of this paper are mostly well-supported by data.

Weaknesses:

Some additional controls could be included, and the language could be clarified for accuracy.

Reviewer #1 (Recommendations For The Authors):

(1)  The paper is inconsistent in using standard Drosophila nomenclature. Often the name of the mammalian counterpart is used instead. This needs to be cleaned up as it is very confusing to the reader.

The names of the mammalian counterpart are explicitly used, when we intended, to underscore the parallels between mammalian vs Drosophila function, specifically in the context of the major players in this study, TER94 vs VCP; Caspar vs FAF1. Since we do not have direct biochemical data indicating that TER94/Casp degrades Smaug, we use published mammalian literature to draw parallels. At no point have we swapped terminology casually.

(2)  The Discussion is far too long and in my view extends too far beyond the experimental data in the paper. As a start for editing, its first two paragraphs (lines 1138-1164) include mostly general statements and could be greatly reduced or eliminated.

Our aim was to emphasize the repurposing of factors between early development and later/adult stages for different functional contexts. Our laboratory (Ratnaparkhi) works on Casp in terms of its roles in NF-kappa B signalling. We serendipitously stumbled on the embryonic lethality while characterizing the casplof allele, which, later, led us to examine the function of Casp during embryonic germ cell development.

(3)  The Introduction is weak in its description of the developmental function of Toll and Dorsal. This could be summarized in a sentence or two.

As suggested, a few sentences that highlight the developmental function of Toll/Dorsal signalling have been added to the text (pg 3, line 90-92).

(4)  Even if correctly cited, it is not appropriate to simply reproduce an image from a public database, as was done in Figure S1C. This should be removed.

Figure S1C has been deleted.

(5)  The Materials and Methods section should be moved to after the Discussion so it does not interrupt the flow of the Results.

The Section has been moved as suggested.

Reviewer #2 (Recommendations For The Authors):

For general readers, more detailed information about the PGC specification will be helpful in the Introduction or Results section.

PGC specification is introduced in the text as the story transits from global embryonic effects of casp knockdown to specific effects on PGCs. A few additional sentences have been added to bolster the text (pg 11, first paragraph).

The Methods section talks about live imaging, but I could not find the experiments in the figures. Are the data available for asynchronous nuclear divisions in the live imaging?

The live imaging relates to DIC movies that are part of Suppl. Fig 2A. The movies are embedded in an MS PowerPoint slide, which has been uploaded as a PowerPoint (and not a PDF).

To ensure that the mutant changes the Osk translation rate, showing the Osk RNA level may be helpful.

oskar RNA localization is quite distinct as compared to Oskar and Vasa protein. It has been shown that oskar RNA is localized to the founder granules and is, in fact, excluded from the germ granules that contain Vasa, Oskar and nos RNA etc. Gavis lab recently reported (Eichler et al., 2020) that ectopic localization of osk RNA in the germ granules is toxic to pole cells. Thus, it will be of interest to analyze whether and how oskar RNA is localized in casp embryos.

More discussion about the difference between Casp and ter94 phenotypes and potential reasons would be informative.

TER94 appears to be an essential maternal gene. Hypomorphic knockdown of TER94 using RNAi is sufficient to induce early embryonic lethality. In fact, Zhang et. al., 2018 et al., using stronger/earlier maternal drivers highlighted the lethality and somatic cell division defects caused due to the severe loss of TER94. The UBX domain is present in multiple proteins, in addition to Casp. TER94 possible plays a vital role in protein degradation of critical cell cycle proteins, such as cyclins that need to be degraded for efficient genomic duplications in the 10’ nuclear division cycles that predominate the first few hours of embryogenesis.

N=3 (Fig1 legend) and N =15 (Fig2). What are those numbers?

N=3 indicated the number of repeats of the western blot. This reference has been deleted. N=15, represents the number of embryos imaged for data in panels G and H.

Reviewer #3 (Recommendations For The Authors):

Major Suggestion:

(1)  Oskar (Osk) mRNA Localization: Does Osk mRNA localization change upon overexpression or LOF of Casp? Since TER94 has been implicated in Osk mRNA localization (Ruden et al., 2000), this would be a good control to include.

As mentioned earlier, in the response to editors, data presented in our manuscript indicates that Caspar is unique in its ability to regulate both Oskar levels and centrosome dynamics. As the reviewer pointed out, we are in the process of analysing the possible localization defects in oskar mRNA in the embryos. Since the preliminary data are promising, we are pursuing this carefully to better understand the involvement of Caspar. We are focusing on the ability of Caspar to regulate early nuclear divisions prior to pole cell formation. It is possible that in casp mutant embryos the nuclei/centrosomes that enter the pole plasm are already defective and thus can influence release of the pole plasm components. This needs to be examined carefully, and we are conducting these experiments.

(2)  Western Blot for Osk Protein: It would also be beneficial to perform a western blot for Osk protein to demonstrate that it is indeed increased upon Casp overexpression.

This is a good suggestion. However, Oskar antibodies are not readily available, and we have a very limited supply which have been used for embryo staining experiments. We considered these more useful as in addition to the absolute levels, staining experiment can reveal localization pattern. It was thus possible to correlate Oskar function with the pole cell counts in respective genetic backgrounds.

(3)  Title Clarification: The title states, "Caspar determines primordial germ cell identity in Drosophila melanogaster." The current experiments do not show that Casp determines germ cell identity. It would be more accurate to conclude that Casp regulates germ cell numbers.

Please refer to the introductory paragraphs where we explain our views in this regard. We have modified our title to “Caspar specifies primordial germ cell count and identity in Drosophila melanogaster."

Minor Suggestions:

(1)  Line 69: Delete the use of "recent" for papers published in 2001 and 2007. These papers are around 20 years old.

The word has been deleted.

(2)  Paragraph from Line 110: Consider splitting this paragraph into two for better readability and clarity.

Paragraph has been split into two; this has improved readability.

(3)  Line 266: Check and correct the formatting issues in this line.

Edited, based on suggestion. A line break was added after the title.

(4)  Line 328: Adding references to earlier studies here will be useful for providing context and supporting information.

References that introduce Centrosomes and their roles as organizing centres have been added in line 336.

(5)  Line 564: It is best to avoid using the word "master." Please consider using other terms such as "key" or "principal."

Edited, based on suggestion.

(6)  Citations: The authors should also cite Cinalli et al., 2013 for the Gcl reference to ensure comprehensive citation of relevant literature.

Thank you for the suggestion. The reference has been added on pages 16 and 29.

(7)  Overall Length: The paper is quite long. If it can be shortened, it will be easier to read. Consider condensing sections where possible without losing essential information.

The paper is indeed longer than average, but the choice of eLife as the home for this study was, in part, determined by the platform's flexibility regarding length/ word count. It seemed worthwhile to elaborate the text in places to accentuate the novelty of the findings.

These additions and adjustments would help to further substantiate the claims and improve the clarity of the paper.

We hope that the claims made in our manuscript are substantiated by the data that are presented. Wherever possible, we have tried to modify the text suitably to improve clarity.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Summary:

The manuscript studies nutrient intake rates for stationary and motile microorganisms to assess the effectiveness of swim vs. stay strategies. This work provides valuable insights on how the different strategies perform in the context of a simplified mathematical model that couples hydrodynamics to nutrient advection and diffusion. The swim and stay strategies are shown to yield similar nutrient flux under a range of conditions.

Strengths:

Strengths of the work include (i) the model prediction in Fig. 3 of nutrient flux applied to a range of microorganisms including an entire clade that are known to use different feeding strategies and (ii) a study of the interaction between cilia and absorption coverage showing the robustness of their predictions provided these regions have sufficient overlap.

We thank the referee for their thorough review of our manuscript and for their constructive feedback.

Weaknesses: To improve the work, the authors should further expand their discussion of the following points:

(1) The authors comment that a number of species alternate between sessile and motile behavior. It would be helpful to discuss what is known about what causes switching between these modes and whether this provides insights regarding the advantages of the different behaviors.

The transition between sessile and motile states is often influenced by external environmental conditions, such as prey availability and predator presence, which determine the most advantageous state at any given time. For instance, members of the genus Stentor are known to detach from their colonies and exhibit solitary swimming behavior in response to low prey abundance (Tartar, 2013) or when avoiding predators (Dexter et al. 2019). Similarly, the transition in Vorticella is influenced by chemical cues, such as pH (Baufer et al., 1999) or algae concentration (Langlois, 1975).

References:

Dexter, J. P., Prabakaran, S., & Gunawardena, J. (2019). A complex hierarchy of avoidance behaviors in a single-cell eukaryote. Current biology, 29(24), 4323-4329.

Tartar, V. (2013). The biology of stentor: International series of monographs on pure and applied biology: Zoology. Elsevier.

BAUFER, P. J. D., Amin, A. A., Pak, S. C., & BUHSE JR, H. E. (1999). A method for the synchronous induction of large numbers of telotrochs in Vorticella convallaria by monocalcium phosphate at low pH. Journal of Eukaryotic Microbiology, 46(1), 12-16.

LANGLOIS, G. A. (1975). Effect of algal exudates on substratum selection by motile telotrochs of the marine peritrich ciliate Vorticella marina. The Journal of Protozoology, 22(1), 115-123.

(2) An encounter zone of R=1.1a appears be used throughout the manuscript, but I could not find a biological justification for this particular value. This results appear to be quite sensitive to this choice, as shown in Supplement Fig. 3(B). In the Discussion, it is mentioned that using a much larger exclusion zone leads to significantly different nutrient flux, and it is implied that such a large exclusion zone is not biologically plausible, but this was not explained sufficiently.

Thank you for pointing this out. We chose the value of the encounter zone based on a rough calculation of cilia length relative to body length. Cilia are typically of the order of 10 microns in length, and the cell body of a ciliate is typically of the order of 100-1000 microns. 

For example, in the work of Jiang, H., & Buskey, E. J., 2024, I&II, the nutrient encounter is reported at the leading edge of the ciliary band in Strombidium and Amphorides. Here, cilia appear to be about 20% of the body length and the particles are absorbed quite close to the cell surface. A similar encounter near the cell surface is reported in Gilmour, 1978 and Thomazo et al., 2020.

In the theoretical model of Andersen and Kiørboe (2020), a much larger encounter zone, extending 10 times the body length (that is, an encounter zone that is 1000% larger than the body length). This is obviously not biologically justifiable. 

We edited the manuscript to better justify our choices and provide supporting references. 

References:

Andersen, A., & Kiørboe, T. (2020). The effect of tethering on the clearance rate of suspension-feeding plankton. Proceedings of the National Academy of Sciences, 117(48), 30101-30103.

Jiang, H., & Buskey, E. J. (2024). Relating ciliary propulsion morphology and flow to particle acquisition in marine planktonic ciliates II: the oligotrich ciliate Strombidium capitatum. Journal of Plankton Research, fbae011.

Jiang, H., & Buskey, E. J. (2024). Relating ciliary propulsion morphology and flow to particle acquisition in marine planktonic ciliates I: the tintinnid ciliate Amphorides quadrilineata. Journal of Plankton Research, fbae012.

Gilmour, T. H. J. (1978). Ciliation and function of the food-collecting and waste-rejecting organs of lophophorates. Canadian Journal of Zoology, 56(10), 2142-2155.

Thomazo, J. B., Le Révérend, B., Pontani, L. L., Prevost, A. M., & Wandersman, E. (2021). A bending fluctuation-based mechanism for particle detection by ciliated structures. Proceedings of the National Academy of Sciences, 118(31), e2020402118.

(3) In schematic of the in Fig. 2(B) it was unclear if the encounter zone in the envelope model is defined analogously to the Stokeslet model or if a different formulation is used.

Yes, we defined the encounter zone the same in both models. In fact, we used two metrics for evaluating nutrient uptake: one considers only the fluid flow rate through an encounter zone, another considers the mass transport within the fluid and absorption at the entire ciliary surface. For the first metric, the clearance rate Q, evaluated by calculating the flow rate past an annular disk, it is consistent applied to all models, depicted in Figure 2(B). The second metric, the nutrient uptake rate, which we define as the dimensionless integration of mass flux over the entire spherical surface, is also consistently applied to all models to evaluate Sh number. Both metrics are evaluated on the Stokeslet and envelope models.

We edited the main text to further clarify these two metrics in the revision.

(4) The force balance argument should be clarified. Equation (3) of the supplement gives the force-velocity relation in the motile case. Since equation (4), which the authors state is the net force in the sessile case, seems to involve the same expression, would it not follow from U=0 in the sessile case that one would simply obtain quiescent flow with Fcilia = 0?

The force balance equations for the model organism differ between the motile and sessile modes. In the submitted version, SI Eq.(3) and SI Eq.(4) are derived from different force balance equations, where the velocity U does not appear in the sessile Stokeslet model.

Author response image 1.

For the Stokeslet model, the force generated by the flagella acting on the fluid is modeled as a point force

Motile Stokeslet model:

The force balance on the sphere is given by:

Where  is the thrust force generated by the flagella in the direction of swimming, is the drag force due to a moving sphere in fluid with speed U, and K is the hydrodynamic force acting on the sphere by the flow generated by the point force F. For a given strength of the Stokeslet, , the swimming speed U can be calculated by the force balance.

Sessile Stokeslet model:

The force balance on the sphere is given by:

Where , T= -F, and K are defined as above. Similarly, for a given point force F, the required force provided by a stalk to fix the sphere can be calculated by the force balance.

Therefore, SI Eq.(3) and (4), are not directly applicable across both the Stokeslet and envelope models. While the expressions appear similar due to the presence of the forces F and K, separate calculations are needed depending on the force model.

We edited the SI document and SI Figure 3 to clarify this.

Reference:

Andersen, A., & Kiørboe, T. (2020). The effect of tethering on the clearance rate of suspension-feeding plankton. Proceedings of the National Academy of Sciences, 117(48), 30101-30103.

Reviewer #2 (Public Review):

Summary:

The authors have collected a significant amount of data from the literature on the flow regimes associated with microorganisms whose propulsion is achieved through the action of cilia or flagella, with particular interest in the competition between sessile and motile lifestyles. They then use several distinct hydrodynamic models for the cilia-driven flows to quantify the nutrient uptake and clearance rate, reported as a function of the Peclet number. Among the interesting conclusions the authors draw concerns the question of whether, for certain ciliates, there is a clear difference in nutrient uptake rates in the sessile versus motile forms. The authors show that this is not the case, thereby suggesting that the evolutionary pressure associated with such a difference is not present. The analysis also includes numerical calculations of the uptake rate for spherical swimmers in the regime of large Peclet numbers, where the authors note an enhancement due to advection-generated thinning of the solutal boundary layer around the organism.

Strengths:

In addressing the whole range of organism sizes and Peclet numbers the authors have achieved an important broad perspective on the problem of nutrient uptake of ciliates, with implications for understanding evolutionary driving forces toward particular lifestyles (e.g. sessile versus motile).

We thank the referee for their thorough review of our manuscript and for their feedback regarding the inclusion of more relevant references.

Weaknesses:

The authors appear to be unaware of rather similar calculations that were done some years ago in the context of Volvox, in which the issue of the boundary layer size and nutrient uptake enhancement were clearly recognized [M.B. Short, et al., Flows Driven by Flagella of Multicellular Organisms Enhance Long-Range Molecular Transport, PNAS 103, 8315-8319 (2006)]. This reference also introduced the model of a fixed shear stress at the surface of the sphere as a representation of the action of the cilia, which may be more realistic than the squirmer-type boundary condition, although the two lead to similar large-Pe scalings.

We apologize for having missed to include this reference in the submitted version of the manuscript. We read this work thoroughly, it is indeed highly relevant to the present study.

The findings reported in Figure 4, that the uptake rate is robust to variations in cilia coverage and absorption fraction, are similar in spirit to an observation made recently in the context of the somatic cell neighbourhood areas in Vovox [Day, et al., eLife 11, e72707 (2022)]. There, it was found that while there is a broad distribution of those areas, and hence of the coarse-grained tangential flagellar force acting on the fluid, the propulsion speed is rather insensitive to those variations.

Thank you for pointing us to the work of Day, et al., eLife 11, e72707 (2022). We did not know about this study and have not read it before. The work is broadly relevant to our study, and we added a reference to this work in the discussion.

eLife Assessment

This important paper addresses the role of fluid flows in nutrient uptake by microorganisms propelled by the action of cilia or flagella. Using a range of mathematical models for the flows created by such appendages, the authors provide convincing evidence that the two strategies of swimming and sessile motion can be competitive. These results will have significant implications for our understanding of the evolution of multicellularity in its various forms.

Reviewer #1 (Public review):

Summary:

The manuscript studies nutrient intake rates for stationary and motile microorganisms to assess the effectiveness of swim vs. stay strategies. This work provides valuable insights on how the different strategies perform in the context of a simplified mathematical model that couples hydrodynamics to nutrient advection and diffusion. The swim and stay strategies are shown to yield similar nutrient flux under a range of conditions.

Strengths:

Strengths of the work include (i) the model prediction in Fig. 3 of nutrient flux applied to a range of microorganisms including an entire clade that are known to use different feeding strategies and (ii) a study of the interaction between cilia and absorption coverage showing the robustness of their predictions provided these regions have sufficient overlap.

Weaknesses:

In the revision, the authors have adequately addressed the weaknesses I raised in the first round of review.

Reviewer #2 (Public review):

Summary:

The authors have collected a significant amount of data from the literature on the flow regimes associated with microorganisms whose propulsion is achieved through the action of cilia or flagella, with particular interest in the competition between sessile and motile lifestyles. They then use several distinct hydrodynamic models for the cilia-driven flows to quantify the nutrient uptake and clearance rate, reported as a function of the Peclet number. Among the interesting conclusions the authors draw concerns the question of whether, for certain ciliates, there is a clear difference in nutrient uptake rates in the sessile versus motile forms. The authors show that this is not the case, thereby suggesting that the evolutionary pressure associated with such a difference is not present. The analysis also includes numerical calculations of the uptake rate for spherical swimmers in the regime of large Peclet numbers, where the authors note an enhancement due to advection-generated thinning of the solutal boundary layer around the organism.

Strengths:

In addressing the whole range of organism sizes and Peclet numbers the authors have achieved an important broad perspective on the problem of nutrient uptake of ciliates, with implications for understanding evolutionary driving forces toward particular lifestyles (e.g. sessile versus motile).

Author response:

The following is the authors’ response to the original reviews.

Reviewer 1 (Public Review):

Summary: Wilmes and colleagues present a computational model of a cortical circuit for predictive processing which tackles the issue of how to learn predictions when different levels of uncertainty are present for the predicted sensory stimulus. When a predicted sensory outcome is highly variable, deviations from the average expected stimulus should evoke prediction errors that have less impact on updating the prediction of the mean stimulus. In the presented model, layer 2/3 pyramidal neurons represent either positive or negative prediction errors, SST neurons mediate the subtractive comparison between prediction and sensory input, and PV neurons represent the expected variance of sensory outcomes. PVs therefore can control the learning rate by divisively inhibiting prediction error neurons such that they are activated less, and exert less influence on updating predictions, under conditions of high uncertainty.

Strengths: The presented model is a very nice solution to altering the learning rate in a modality and context-specific way according to expected uncertainty and, importantly, the model makes clear, experimentally testable predictions for interneuron and pyramidal neuron activity. This is therefore an important piece of modelling work for those working on cortical and/or predictive processing and learning. The model is largely well-grounded in what we know of the cortical circuit.

Weaknesses: Currently, the model has not been challenged with experimental data, presumably because data from an ad- equate paradigm is not yet available. I therefore only have minor comments regarding the biological plausibility of the model:

Beyond the fact that some papers show SSTs mediate subtractive inhibition and PVs mediate divisive inhibition, the selection of interneuron types for the different roles could be argued further, given existing knowledge of their properties. For instance, is a high PV baseline firing rate, or broad sensory tuning that is often interpreted as a ’pooling’ of pyramidal inputs, compatible with or predicted by the model?

Thank you for this nice suggestion. We added a section to the discussion expanding on this: “The model predicts that the divisive interneuron type, which we here suggest to be the PVs, receive a representation of the stimulus as an input. PVs could be pooling the inputs from stimulus-responsive layer 2/3 neurons to estimate uncertainty. The more the stimulus varies, the larger the variability of the pyramidal neuron responses and, hence, the variability of the PV activity. The broader sensory tuning of PVs (Cottam et al. 2013) is in line with the model insofar as uncertainty modulation could be more general than the specific feature, which is more likely for low-level features processed in primary sensory cortices. PVs were shown to connect more to pyramidal cells with similar feature-tuning (Znamenskyiy et al. 2024); this would be in line with the model, as uncertainty modulation should be feature-related. In our model, some SSTs deliver the prediction to the positive prediction error neurons. SSTs are already known to be involved in spatial prediction, as they underlie the effect of surround suppression (Adesnik et al. 2012), in which SSTs suppress the local activity dependent on a predictive surround.”

On a related note, SSTs are thought to primarily target the apical dendrite, while PVs mediate perisomatic inhibition, so the different roles of the interneurons in the model make sense, particularly for negative PE neurons, where a top-down excitatory predicted mean is first subtractively compared with the sensory input, s, prior to division by the variance. However, sensory input is typically thought of as arising ’bottom-up’, via layer 4, so the model may match the circuit anatomy less in the case of positive PE neurons, where the diagram shows ’s’ arising in a top-down manner. Do the authors have a justification for this choice?

We agree that ‘s’ is a bottom-up input and should have been more clear about that we do not consider ‘s’ to be a top-down input like the prediction. We hence adjusted the figure correspondingly and added a few clarifying sentences to the manuscript. The reviewer, however, raises an important point, which is not talked about enough. Namely, that if the bottom-up input ‘s’ comes from L4, how can it be compared in a subtractive manner with the top-down prediction arriving in the superficial layers? In Attinger et al. it was shown that the visual stimulus had subtractive effects on SST neurons. The axonal fibers delivering the stimulus information are hence likely to arrive in the vicinity of the apical dendrites, where SSTs target pyramidal cells. Hence, those axons delivering stimulus information could also target the apical dendrites of pyramidal cells. As the reviewer probably had in mind, L4 input tends to arrive in the somatic layer. However, there are also stimulus-responsive cells in layer 2/3, such that the stimulus information does not need to come directly from L4, it could be relayed via those stimulus-responsive layer 2/3 cells. It has been shown that L2/3→L3 axons are mostly located in the upper basal dendrites and the apical oblique dendrites, above the input from L4 (Petreanu et al. The subcellular organization of neocortical excitatory connections). Hence, stimulus information could arrive on the apical dendrites, and be subtractively modulated by SSTs. We would also like to note that the model does not take into account the precise dendritic location of the inputs. The model only assumes that the difference between stimulus and prediction is calculated before the divisive modulation by the variance.

In cortical circuits, assuming a 2:8 ratio of inhibitory to excitatory neurons, there are at least 10 pyramidal neurons to each SST and PV neuron. Pyramidal neurons are also typically much more selective about the type of sensory stimuli they respond to compared to these interneuron classes (e.g., Kerlin et al., 2012, Neuron). A nice feature of the proposed model is that the same interneurons can provide predictions of the mean and variance of the stimulus in a predictor-dependent manner. However, in a scenario where you have two types of sensory stimulus to predict (e.g., two different whiskers stimulated), with pyramidal neurons selective for prediction errors in one or the other, what does the model predict? Would you need specific SST and PV circuits for each type of predicted stimulus?

If we understand correctly, this would be a scenario in which the same context (e.g., sound) is predicting two types of sensory stimulus. In that case, one may need specific SST and PV circuits for the different error neurons selective for prediction errors in these stimuli, depending on how different the predictions are for the two stimuli as we elaborate in the following. The reviewer is raising an important point here and that is why we added a section to the discussion elaborating on it.

We think that there is a reason why interneurons are less selective than pyramidal cells and that this is also a feature in prediction error circuits. Similarly-tuned cells are more connected to each other, because they tend to be activated together as the stimuli they encode tend to be present in the environment together. Also, error neurons selective to nearby whiskers are more likely to receive similar stimulus information, and hence similar predictions. Hence, because nearby whiskers are more likely to be deflected similarly, a circuit structure may have developed during development such that neurons selective for prediction errors of nearby whiskers, may receive inputs from the same inhibitory interneurons. In that case, the same SST and PV cells could innervate those different neurons. If, however, the sensory stimuli to be predicted are very different, such that their representations are likely to be located far away from each other, then it also makes sense that the predictions for those stimuli are more diverse, and hence the error neurons selective to these are unlikely to be innervated by the same interneurons.

We added a shorter version of this to the discussion: “The lower selectivity of interneurons in comparison to pyramidal cells could be a feature in prediction error circuits. Error neurons selective to similar stimuli are more likely to receive similar stimulus information, and hence similar predictions. Therefore, a circuit structure may have developed such that prediction error neurons with similar selectivity may receive inputs from the same inhibitory interneurons.”

Reviewer 2 (Public Review):

Summary: This computational modeling study addresses the observation that variable observations are interpreted differently depending on how much uncertainty an agent expects from its environment. That is, the same mismatch between a stimulus and an expected stimulus would be less significant, and specifically would represent a smaller prediction error, in an environment with a high degree of variability than in one where observations have historically been similar to each other. The authors show that if two different classes of inhibitory interneurons, the PV and SST cells, (1) encode different aspects of a stimulus distribution and (2) act in different (divisive vs. subtractive) ways, and if (3) synaptic weights evolve in a way that causes the impact of certain inputs to balance the firing rates of the targets of those inputs, then pyramidal neurons in layer 2/3 of canonical cortical circuits can indeed encode uncertainty-modulated prediction errors. To achieve this result, SST neurons learn to represent the mean of a stimulus distribution and PV neurons its variance.

The impact of uncertainty on prediction errors is an understudied topic, and this study provides an intriguing and elegant new framework for how this impact could be achieved and what effects it could produce. The ideas here differ from past proposals about how neuronal firing represents uncertainty. The developed theory is accompanied by several predictions for future experimental testing, including the existence of different forms of coding by different subclasses of PV interneurons, which target different sets of SST interneurons (as well as pyramidal cells). The authors are able to point to some experimental observations that are at least consistent with their computational results. The simulations shown demonstrate that if we accept its assumptions, then the authors’ theory works very well: SSTs learn to represent the mean of a stimulus distribution, PVs learn to estimate its variance, firing rates of other model neurons scale as they should, and the level of un- certainty automatically tunes the learning rate, so that variable observations are less impactful in a high uncertainty setting.

Strengths: The ideas in this work are novel and elegant, and they are instantiated in a progression of simulations that demonstrate the behavior of the circuit. The framework used by the authors is biologically plausible and matches some known biological data. The results attained, as well as the assumptions that go into the theory, provide several predictions for future experimental testing.

Weaknesses: Overall, I found this manuscript to be frustrating to read and to try to understand in detail, especially the Results section from the UPE/Figure 4 part to the end and parts of the Methods section. I don’t think the main ideas are so complicated, and it should be possible to provide a much clearer presentation.

For me, one source of confusion is the comparison across Figure 1EF, Figure 2A, Figure 3A, Figure 4AB, and Figure 5A. All of these are meant to be schematics of the same circuit (although with an extra neuron in Figure 5), yet other than Figures 1EF and 4AB, no two are the same! There should be a clear, consistent schematic used, with identical labeling of input sources, neuron types, etc. across all of these panels.

We changed all figures to make them more consistent and pointed out that we consider subparts of the circuit.

The flow of the Results section overall is clear until the “Calculation of the UPE in Layer 2/3 error neurons” and Figure 4, where I find that things become significantly more confusing. The mention of NMDA and calcium spikes comes out of the blue, and it’s not clear to me how this fits into the authors’ theory. Moreover: Why would this property of pyramidal cells cause the PV firing rate to increase as stated? The authors refer to one set of weights (from SSTs to UPE) needing to match two targets (weights from s to UPE and weights from mean representation to UPE); how can one set of weights match two targets? Why do the authors mention “out-of-distribution detection’ here when that property is not explored later in the paper? (see also below for other comments on Figure 4)

We agree that the introduction of NMDA and calcium spikes was too short and understand that it was confusing. We therefore modified and expanded the section. To answer the two specific questions: First, Why would this property of pyramidal cells cause the PV firing rate to increase as stated? This property of pyramidal cells does not cause the PV firing rate to increase. When for example in positive error neurons, the mean input increases, then the PVs receive higher stimulus input on average, which is not compensated by the inhibitory prediction (which is still at the old mean), such that the PV firing rate increases. Due to the nonlinear integration in PVs, the firing rate can increase a lot and inhibit the error neurons strongly. If the error neurons integrate the difference nonlinearly, they compensate for the increased inhibition by PVs. In Figure 5, we show that a circuit in which error neurons exhibit a dendritic nonlinearity matches an idealised circuit in which the PVs perfectly represent the variance. We modified the text to clarify this.

Second, how can one set of weights match two targets? In our model, one set of weights does not need to match two targets. We apologise that this was written in such a confusing way. In positive error neurons, the inhibitory weights from the SSTs need to match the excitatory weights from the stimulus, and in negative error neurons, the inhibitory weights from the SSTs need to match the excitatory weights from the prediction. The weights in positive and negative circuits do not need to be the same. So, on a particular error neuron, the inhibition needs to match the excitation to maintain EI balance. Given experimental evidence for EI balance and heterosynaptic plasticity, we think that this constraint is biologically achievable. The inhibitory and excitatory synapses that need to match are targeting the same postsynaptic neuron and could hence have access to their postsynaptic effect. We modified the text to be more clear. Finally, we omitted the mentioning of out-of-distribution detection, see our reply below.

Coming back to one of the points in the previous paragraph: How realistic is this exact matching of weights, as well as the weight matching that the theory requires in terms of the weights from the SSTs to the PVs and the weights from the stimuli to the PVs? This point should receive significant elaboration in the discussion, with biological evidence provided. I would not advocate for the authors’ uncertainty prediction theory, despite its elegant aspects, without some evidence that this weight matching occurs in the brain. Also, the authors point out on page 3 that unlike their theory, “...SSTs can also have divisive effects, and PVs can have subtractive effects, dependent on circuit and postsynaptic properties”. This should be revisited in the Discussion, and the authors should explain why these effects are not problematic for their theory. In a similar vein, this work assumes the existence of two different populations of SST neurons with distinct UPE (pyramidal) targets. The Discussion doesn’t say much about any evidence for this assumption, which should be more thoroughly discussed and justified.

These are very important points, we agree that the biological plausibility of the model’s predictions should be discussed and hence expanded the discussion with three new paragraphs:

To enable the comparison between predictions and sensory information via subtractive inhibition, we pointed out that the weights of those inputs on the postsynaptic neuron need to match. This essentially means that there needs to be a balance of excitatory and inhibitory inputs. Such an EI balance has been observed experimentally (Tan and Wehr, 2009). And it has previously been suggested that error responses are the result of breaking this EI balance (Hertäg und Sprekeler, 2020, Barry and Gerstner, 2024). Heterosynaptic plasticity is a possible mechanism to achieve EI balance (Field et al. 2020). For example, spike pairing in pre- and postsynaptic neurons induces long-term potentiation at co-activated excitatory and inhibitory synapses with the degree of inhibitory potentiation depending on the evoked excitation (D’amour and Froemke, 2015), which can normalise EI balance (Field et al. 2020).

In the model we propose, SSTs should be subtractive and PVs divisive. However, SSTs can also be divisive, and PVs subtractive dependent on circuit and postsynaptic properties (Seybold et al. 2015, Lee et al. 2012, Dorsett et al. 2021). This does not necessarily contradict our model, as circuits in which SSTs are divisive and PVs subtractive could implement a different function, as not all pyramidal cells are error neurons. Hence, our model suggests that error neurons which can calculate UPEs should have similar physiological properties to the layer 2/3 cells observed in the study by Wilson et al. 2012.

Our model further posits the existence of two distinct subtypes of SSTs in positive and negative error circuits. Indeed, there are many different subtypes of SSTs. SST is expressed by a large population of interneurons, which can be further subdivided. There is e.g. a type called SST44, which was shown to specifically respond when the animal corrects a movement (Green et al. 2023). Our proposal is hence aligned with the observation of functionally specialised subtypes of SSTs.

Finally, I think this is a paper that would have been clearer if the equations had been interspersed within the results. Within the given format, I think the authors should include many more references to the Methods section, with specific equation numbers, where they are relevant throughout the Results section. The lack of clarity is certainly made worse by the current state of the Methods section, where there is far too much repetition and poor ordering of material throughout.

We implemented the reviewer’s detailed and helpful suggestions on how to improve the ordering and other aspects of the methods section and now either intersperse the equations within the results or refer to the relevant equation number from the Methods section within the Results section.

Reviewer 3 (Public Review):

Summary: The authors proposed a normative principle for how the brain’s internal estimate of an observed sensory variable should be updated during each individual observation. In particular, they propose that the update size should be inversely proportional to the variance of the variable. They then proposed a microcircuit model of how such an update can be implemented, in particularly incorporating two types of interneurons and their subtractive and divisive inhibition onto pyramidal neurons. One type should represent the estimated mean while another represents the estimated variance. The authors used simulations to show that the model works as expected.

Strengths: The paper addresses two important issues: how uncertainty is represented and used in the brain, and the role of inhibitory neurons in neural computation. The proposed circuit and learning rules are simple enough to be plausible. They also work well for the designated purposes. The paper is also well-written and easy to follow.

Weaknesses: I have concerns with two aspects of this work.

(1) The optimality analysis leading to Eq (1) appears simplistic. The learning setting the authors describe (estimating the mean of a stationary Gaussian variable from a stream of observations) is a very basic problem in online learning/streaming algorithm literature. In this setting, the real “optimal” estimate is simply the arithmetic average of all samples seen so far. This can be implemented in an online manner with µˆt = µˆt−1 +(st −µˆt−1)/t. This is optimal in the sense that the estimator is always the maximum likelihood estimator given the samples seen up to time t. On the other hand, doing gradient descent only converges towards the MLE estimator after a large number of updates. Another critique is that while Eq (1) assumes an estimator of the mean (mˆu), it assumes that the variance is already known. However, in the actual model, the variance also needs to be estimated, and a more sophisticated analysis thus needs to take into account the uncertainty of the variance estimate and so on. Finally, the idea that the update should be inverse to the variance is connected to the well-established idea in neuroscience that more evidence should be integrated over when uncertainty is high. For example, in models of two-alternative forced choices it is known to be optimal to have a longer reaction time when the evidence is noisier.

We agree with the reviewer that the simple example we gave was not ideal, as it could have been solved much more elegantly without gradient descent. And the reviewer correctly pointed out that our solution was not even optimal. We now present a better example in Figure 7, where the mean of the Gaussian variable is not stationary. Indeed, we did not intend to assume that the Gaussian variable is stationary, as we had in mind that the environment can change and hence also the Gaussian variable. If the mean is constant over time, it is indeed optimal to use the arithmetic mean. However, if the mean changes after many samples, then the maximum likelihood estimator model would be very slow to adapt to the new mean, because t is large and each new stimulus only has a small impact on the estimate. If the mean changes, uncertainty modulation may be useful: if the variance was small before, and the mean changes, then the resulting big error will influence the change in the estimate much more, such that we can more quickly learn the new mean. A combination of the two mechanisms would probably be ideal. We use gradient descent here, because not all optimisation problems the brain needs to solve are that simple. The problem with converging only after a large number of updates is a general problem of the algorithm. Here, we propose how the brain could estimate uncertainty to achieve the uncertainty-modulation observed in inference and learning tasks observed in behavioural studies. To give a more complex example, we present in a new Figure 8 how a hierarchy of UPE circuits can be used for uncertainty-based integration of prior and sensory information, similar to Bayes-optimal integration.

Yes, indeed, there is well-known behavioural evidence, we would like to thank the reviewer for pointing out this connection to two-alternative forced choice tasks. We now cite this work. Our contribution is not on the already established computational or algorithmic level, but the proposal of a neural implementation of how uncertainty could modulate learning. The variance indeed needs to be estimated for optimal mean updating. That means that in the beginning, there will be non-optimal updating until the variance is learned. However, once the variance is learned, mean-updating can use the learned variance. There may be few variance contexts but many means to be learned, such that variance contexts can be reused. In any case, this is a problem on the algorithmic level, and not so much on the implementational level we are concerned with.

(2) While the incorporation of different inhibitory cell types into the model is appreciated, it appears to me that the computation performed by the circuit is not novel. Essentially the model implements a running average of the mean and a running average of the variance, and gates updates to the mean with the inverse variance estimate. I am not sure about how much new insight the proposed model adds to our understanding of cortical microcircuits.

We here suggest an implementation for how uncertainty could modulate learning via influencing prediction error com- putation. Our model can explain how humans could estimate uncertainty and weight prior versus sensory information accordingly. The focus of our work was not to design a better algorithm for mean and variance estimation, but rather to investigate how specialised prediction error circuits in the brain can implement these operations to provide new experimental hypotheses and predictions.

Reviewer 1 (Recommendations For The Authors):

Clarity and conciseness are a strength of this manuscript, but a more comprehensive explanation could improve the reader’s understanding in some instances. This includes the NMDA-based nonlinearity of pyramidal neuron activation - I am a little unclear exactly what problem this solves and how (alongside the significance of 5D and E).

We agree that the introduction of the NMDA-based nonlinearity was too short and understand that it was confusing. We therefore modified and expanded the section, where we introduce the dendritic nonlinearity of the error neurons.

Page 5: I think there is a ’positive’ and ’negative’ missing from the following sentence: ’the weights from the SSTs to the UPE neurons need to match the weights from the stimulus s to the UPE neuron and from the mean representation to the UPE neuron, respectively.’

Thanks for pointing that out! We changed the sentence to be more clear to the following: “To ensure a comparison between the stimulus and the prediction, the inhibition from the SSTs needs to match the excitation it is compared to in the UPE neurons: In the positive PE circuit, the weights from the SSTs representing the prediction to the UPE neurons need to match the weights from the stimulus s to the UPE neurons. In the negative PE circuit, the weights from SSTs representing the stimulus to the negative UPE neurons need to match the weights from the mean representation to the UPE neurons, respectively.”

Reviewer 2 (Recommendations For The Authors):

Related to the first point above: I don’t feel that the authors adequately explained what the “s” and “a” information (e.g., in Figures 2A, 3A) represent, where they are coming from, what neurons they impact and in what way (and I believe Fig. 3A is missing one “a” label). I think they should elaborate more fully on these key, foundational details for their theory. To me, the idea of starting from the PV, SST, and pyramidal circuit, and then suddenly introducing the extra R neuron in Figure 5, just adds confusion. If the R neuron is meant to be the source, in practice, of certain inputs to some of the other cell types, then I think that should be included in the circuit from the start. Perhaps a good idea would be to start with two schematics, one in the form of Figure 5A (but with additional labeling for PV, SST) and one like Figure 1EF (but with auditory inputs as well), with a clear indication that the latter is meant to represent a preliminary, reduced form of the former that will be used in some initial tests of the performance of the PV, SST, UPE part of the circuit. Related to the Methods, I also can give a list of some specific complaints (in latex):

(1) φ, φP V are used in equations (10), (11), so they should be defined there, not many equations later.

Thank you, we changed that.

(2) β, 1 − β appear without justification or explanation in (11). That is finally defined and derived several pages later.

Thank you, we now define it right at the beginning.

(3) Equations (10)-(12) should be immediately followed by information about plasticity, rather than deferring that.

That’s a great idea. We changed it. Now the synaptic dynamics are explained together with the firing rate dynamics.

(4) After the rate equations (10)-(12) and weight change equations (23)-(25) are presented, the same equations are simply repeated in the “Explanation of the synaptic dynamics” subsection.

We agree that this was suboptimal. We moved the explanation of the synaptic dynamics up and removed the repetition.

(5) In the circuit model (13)-(19), it’s not clear why rR shows up in the SST+ and PV− equations vs. rs in PV+ and SST−. Moreover, rs is not even defined! Also, I don’t see why wP V +,R shows up in the equation for rP V − .

We added more explanation to the Methods section as to why the neurons receive these inputs and renamed rs to s, which is defined. The “+” in wP V +,R was a typo. Thank you for spotting that.

(6) The authors should only number those equations that they will reference by number. Even more importantly, there are many numbers such as (20), (26), (32), (39) that are just floating there without referring to an equation at all.

Thank you for spotting that. We corrected this.

(7) The authors fail to specify what is ra in Figure 8. Moreover, it seems strange to me that wP V,a approaches σ rather than wP V,ara approaching σ, since φP V is a function of wP V,ara.

You are right, wP V,ara should approach σ, but since ra is either 1 or 0 to indicate the presence of absence of the cue, and only wP V,a is plastic and changing„ wP V,a approaches σ.

(8) I don’t understand the rationale for the authors to introduce equation. (30) when they already had plasticity equations earlier. What is the relation of (30), (31) to (24)?

It is the same equation. In 30 we introduce simpler symbols for a better overview of the equations. 31 is equal to 30, with rP V replaced by it’s steady state.

(9) η is omitted from (33) - it won’t affect the final result but should be there.

We fixed this.

I have many additional specific comments and suggestions, some related to errors that really should have been caught before manuscript submission. I will present these based on the order in which they arise in the manuscript.

(1) In the abstract, the mention of layer 2/3 comes out of nowhere. Why this layer specifically? Is this meant to be an abstract/general cortical circuit model or to relate to a specific brain area? (Also watch for several minor grammatical issues in the abstract and later.)

Thank you for pointing this out. We now mention that the observed error neurons can be found in layer 2/3 of diverse brain areas. It is meant to be a general cortical circuit model independent of brain area.

(2) In par. 2 of the introduction, I find sentences 3-4 to be confusing and vague. Please rewrite what is meant more directly and clearly.

We tried to improve those sentences.

(3) Results subtitle 1: “suggests” → “suggest”

Thank you.

(4) Be careful to use math font whenever variables, such as a and N, are referenced (e.g., use of a instead of a bottom pg. 2).

We agree and checked the entire manuscript.

(5) Ref. to Fig. 1B bottom pg. 2 should be Fig. 1CD. The panel order in the figure should then be changed to match how it is referenced.

We fixed it and matched the ordering of the text with the ordering of the figure.

(6) Fig. 2C and 3E captions mention std but this is not shown in the figures - should be added.

It is there, it is just very small.

(7) Please clarify the relation of Figure 2C to 2F, and Figure 3F to 3H.

We colour-coded the points in 2F that correspond to the bars in 2C. We did the same for 3F and 3H.

(8) Figures 3E,3F appear to be identical except for the y-axis label and inclusion of std in 3F. Either more explanation is needed of how these relate or one should be cut.

The difference is that 3E shows the activity of PVs based on only the sound cue in the absence of a whisker stimulus. And 3F shows the activity of PVs based on both the sound cue and whisker stimuli. We state this more clearly now.

(9) Bottom of pg. 4: clarify that a quadratic φP V is a model assumption, not derived from results in the figure.

We added that we assume this.

(10) When k is referenced in the caption of Figure 4, the reader has no idea what it is. More substantially, most panels of Figure 4 are not referenced in the paper. I don’t understand what point the authors are trying to make here with much of this figure. Indeed, since the claim is that the uncertainy prediction should be based on division by σ2, why aren’t the numerical values for UPE rates much larger, since σ gets so small? The authors also fail to give enough details about the simulations done to obtain these plots; presumably these are after some sort of (unspecified) convergence, and in response to some sort of (unspecified) stimulus? Coming back to k, I don’t understand why k > 2 is used in addition to k = 2. The text mentions – even italicizes – “out-of-distribution dectection’, but this is never mentioned elsewhere in the paper and seems to be outside the true scope of the work (and not demonstrated in Figure 4). Sticking with k = 2 would also allow authors to simply use (·)k below (10), rather than the awkward positive part function that they have used now.

We now introduce the equation for the error neurons in Eq. 3 within the text, such that k is introduced before the caption. It also explains why the numerical values do not become much larger. Divisive inhibition, unlike mathematical division, cannot lead to multiplication in neurons. To ensure this, we add 1 to the denominator.

We show the error neuron responses to stimuli deviating from the learned mean after learning the mean and variance. The deviation is indicated either on the x-axis or in the legend depending on the plot. We now more explicitly state that these plots are obtained after learning the mean and the variance.

We removed the mentioning of the “out-of-distribution detection” as a detailed treatment would indeed be outside of the scope.

(11) Page 5, please clarify what is meant by “weights from the sound...”. You have introduced mathematical notation - use it so that you can be precise.

We added the mathematical notation, thank you!

(12) Figure 5D: legend has 5 entries but the figure panel only plots 4 quantities.

The SST firing rate was below the R firing rate. We hence omitted the SST firing rate and its legend.

(13) Figure 5: I don’t understand what point is being made about NMDA spikes. The text for Figure 5 refers to NMDA spikes in Figure 4, but nothing was said about NMDA spikes in the text for Figure 4 nor shown in Figure 4 itself.

We were referring to the nonlinearity in the activation function of UPEs in Figure 4. We changed the text to clarify this point.

(14) Figure 6: It is too difficult to distinguish the black and purple curves even on a large monitor. Also, the authors fail to define what they mean by “MM” and also do not define the quantities Y+ and Y− that they show. Another confusing aspect is that the model has PV+ and PV− neurons, so why doesn’t the figure?

Thank you for the comment. We changed the colour for better visibility, replaced the Upsilons with UPE (we changed the notation at some point and forgot to change it in the figure), and defined MM, which is the mismatch stimulus that causes error activity. We did not distinguish between PV+ and PV− in the plot as their activity is the same on average. We plotted the activity of the PV+. We now mention that we show the activity of PV+ as the representative.

(15) Also Figure 6: The authors do not make it clear in the text whether these are simulation results or cartoons. If the latter, please replace this with actual simulation results.

They are actual simulation results. We clarified this in the text.

(16) This work assumes the existence of two different populations of SST neurons with distinct UPE (pyramidal) targets. The Discussion doesn’t say much about any evidence for this assumption, which should be more thoroughly discussed and justified.

We now discuss this in more detail in the discussion as mentioned in our response to the public review.

(17) Par. 2 of the discussion refers to “Bayesian” and “Bayes-optimal” several times. Nothing was said earlier in the paper about a Bayesian framework for these results and it’s not clear what the authors mean by referring to Bayes here. This paragraph needs editing so that it clearly relates to the material of the results section and its implications.

We added an additional results section (the last section with Figure 8) on integrating prior and sensory information based on their uncertainties, which is also the case for Bayes-optimal integration, and show that our model can reproduce the central tendency effect, which is a hallmark of Bayes-optimal behaviour.

Reviewer 3 (Recommendations For The Authors):

See public review. I think the gradient-descent type of update the authors do in Equation (1) could be more useful in a more complicated learning scenario where the MLE has no closed form and has to be computed with gradient-based algorithms.

We responded in detail to your points in our point-by-point response to the public review.

eLife Assessment

This important study introduces a new cortical circuit model for predictive processing. Simulations effectively illustrate that, with appropriate synaptic plasticity, a canonical layer 2/3 cortical circuit - comprising two classes of interneurons providing subtractive and divisive inhibition - can generate uncertainty-modulated prediction errors by pyramidal neurons. The model is compelling; although it relies on many assumptions and has not yet been compared directly to data, the model does align with empirical observations and yields a range of testable predictions. The study is expected to be of great interest to those involved in cortical and predictive processing research.

Reviewer #2 (Public review):

Summary:

This computational modeling study addresses the observation that variable observations are interpreted differently depending on how much uncertainty an agent expects from its environment. That is, the same mismatch between a stimulus and an expected stimulus would be less significant, and specifically would represent a smaller prediction error, in an environment with a high degree of variability than in one where observations have historically been similar to each other. The authors show that if two different classes of inhibitory interneurons, the PV and SST cells, (1) encode different aspects of a stimulus distribution and (2) act in different (divisive vs. subtractive) ways, and if (3) synaptic weights evolve in a way that causes the impact of certain inputs to balance the firing rates of the targets of those inputs, then pyramidal neurons in layer 2/3 of canonical cortical circuits can indeed encode uncertainty-modulated prediction errors. To achieve this result, SST neurons learn to represent the mean of a stimulus distribution and PV neurons its variance.

The impact of uncertainty on prediction errors in an understudied topic, and this study provides an intriguing and elegant new framework for how this impact could be achieved and what effects it could produce. The ideas here differ from past proposals about how neuronal firing represents uncertainty. The developed theory is accompanied by several predictions for future experimental testing, including the existence of different forms of coding by different subclasses of PV interneurons, which target different sets of SST interneurons (as well as pyramidal cells). The authors are able to point to some experimental observations that are at least consistent with their computational results. The simulations shown demonstrate that if we accept its assumptions, then the authors' theory works very well: SSTs learn to represent the mean of a stimulus distribution, PVs learn to estimate its variance, firing rates of other model neurons scale as they should, and the level of uncertainty automatically tunes the learning rate, so that variable observations are less impactful in a high uncertainty setting.

Strengths:

The ideas in this work are novel and elegant, and they are instantiated in a progression of simulations that demonstrate the behavior of the circuit. The framework used by the authors is biologically plausible and matches some known biological data. The results attained, as well as the assumptions that go into the theory, provide several predictions for future experimental testing. The authors have taken into account earlier review comments to revise their paper in ways that enhance its clarity.

Weaknesses:

One weakness could be that the proposed theory does rely on a fairly large number of assumptions. However, there is at least some biological support for these. Importantly, the authors do lay out and discuss their key assumptions in the Discussion section, so readers can assess their validity and implications for themselves.

Reviewer #4 (Public review):

Summary:

Wilmes and colleagues develop a model for the computation of uncertainty modulated prediction errors based on an experimentally inspired cortical circuit model for predictive processing. Predictive processing is a promising theory of cortical function. An essential aspect of the model is the idea of precision weighting of prediction errors. There is ample experimental evidence for prediction error responses in cortex. However, a central prediction of the theory is that these prediction error responses are regulated by the uncertainty of the input. Testing this idea experimentally has been difficult due to a lack of concrete models. This work provides one such model and makes experimentally testable predictions.

Strengths:

The model proposed is novel and well-implemented. It has sufficient biological accuracy to make useful and testable predictions.

Weaknesses:

One key idea the model hinges on is that stimulus uncertainty is encoded in the firing rate of parvalbumin positive interneurons. This assumption, however, is rather speculative and there is no direct evidence for this.

eLife Assessment

Treatment of pseudomonas aeruginosa (PA) is challenging because of intrinsic and acquired antibiotic resistance to most antibiotic drug classes. Therefore, by using donor B cells in subjects with cystic fibrosis who undergo intermittent or chronic airway PA infections, the authors tried to isolate BCRs against PA virulence factors and examine their biological activities. The data are solid and isolated protective antibodies could be useful for protection against PA.

Joint Public Review:

Summary:

This study presents a strategy to efficiently isolate PcrV-specific BCRs from human donors with cystic fibrosis who have/had Pseudomonas aeruginosa (PA) infection. Isolation of mAbs that provide protection against PA may be a key to developing a new strategy to treat PA infection as the PA has intrinsic and acquired resistance to most antibiotic drug classes. Hale et al. developed fluorescently labeled antigen-hook and isolated mAbs with anti-PA activity. Overall, the authors' conclusion is supported by solid data analysis presented in the paper. Four of five recombinantly expressed PcrV-specific mAbs exhibited anti-PA activity in a murine pneumonia challenge model as potent as the V2L2MD mAb (equivalent to gremubamab). However, therapeutic potency for these isolated mAbs is uncertain as the gremubamab has failed in Phase 2 trials. Clarification of this point would greatly benefit this paper.

Strengths:

(1) High efficiency of isolating antigen-specific BCRs using an antigenic hook.

(2) The authors' conclusion is supported by data.

Weaknesses:

Although the authors state that the goal of this study was to generate novel protective mAbs for therapeutic use (P12; Para. 2), it is unclear whether PcrV-specific mAbs isolated in this study have therapeutic potential better than the gremubamab, which has failed in Phase 2 trials. Four of five PcrV-specific mAbs isolated in this study reduced bacterial burdens in mice as potent as, but not superior to, gremubamab-equivalent mAb. Clarification of this concern by revising the text or providing experimental results that show better potential than gremubamab would greatly benefit this paper.

Author response:

Joint Public Review:

Summary:

This study presents a strategy to efficiently isolate PcrV-specific BCRs from human donors with cystic fibrosis who have/had Pseudomonas aeruginosa (PA) infection. Isolation of mAbs that provide protection against PA may be a key to developing a new strategy to treat PA infection as the PA has intrinsic and acquired resistance to most antibiotic drug classes. Hale et al. developed fluorescently labeled antigen-hook and isolated mAbs with anti-PA activity. Overall, the authors' conclusion is supported by solid data analysis presented in the paper. Four of five recombinantly expressed PcrV-specific mAbs exhibited anti-PA activity in a murine pneumonia challenge model as potent as the V2L2MD mAb (equivalent to gremubamab). However, therapeutic potency for these isolated mAbs is uncertain as the gremubamab has failed in Phase 2 trials. Clarification of this point would greatly benefit this paper.

Strengths:

(1) High efficiency of isolating antigen-specific BCRs using an antigenic hook.

(2) The authors' conclusion is supported by data.

Weaknesses:

Although the authors state that the goal of this study was to generate novel protective mAbs for therapeutic use (P12; Para. 2), it is unclear whether PcrV-specific mAbs isolated in this study have therapeutic potential better than the gremubamab, which has failed in Phase 2 trials. Four of five PcrV-specific mAbs isolated in this study reduced bacterial burdens in mice as potent as, but not superior to, gremubamab-equivalent mAb. Clarification of this concern by revising the text or providing experimental results that show better potential than gremubamab would greatly benefit this paper.

The authors thank the reviewer for their thoughtful positive assessment. As noted by the reviewer, the studies described here, which were performed in mice, show that our MBC-derived mAbs are as effective as V2L2MD, a mAb that is one component of the gremubamab bi-specific. However, key theoretical strengths of MBC-derived mAbs (reduced immunogenicity, full participation in effector functions) are not easily tested in mice. We have clarified and expanded our discussion of these points in our revised manuscript, particularly in the Discussion paragraph 4.

eLife Assessment

This valuable study addresses one way in which animals identify predator-associated cues and respond in a manner that reflects the imminence of the potential threat. The report shows that, in mice, fresh saliva from a natural predator (cat) elicits a greater defensive response compared to old cat saliva and implicates the vomeronasal organ and ventromedial hypothalamus as part of a circuit that underlies this process. The evidence supporting the main conclusions is solid. This study will be of interest to those interested in aversive behavior, its processes, and mechanisms.

Reviewer #1 (Public review):

Summary:

Animals in natural environments need to identify predator-associated cues and respond with the appropriate behavioral response to survive. In rodents, some chemical cues produced by predators (e.g., cat saliva) are detected by chemosensory neurons in the vomeronasal organ (VNO). The VNO transmits predator-associated information to the accessory olfactory bulb, which in turn projects to the medial amygdala and the bed nucleus of the stria terminalis, two regions implicated in the initiation of antipredator defensive behaviors. A downstream area to these two regions is the ventromedial hypothalamus (VMH), which has been shown to control both active (i.e., flight) and passive (i.e, freezing) antipredator defensive responses via distinct efferent projections to the anterior hypothalamic nucleus or the periaqueductal gray, respectively. However, whether differences in predator-associated sensory information initially processed in the VNO and further conveyed to the VMH can trigger different types of behavioral responses remained unexplored. To address this question, here the authors investigated the behavioral responses of mice exposed to either fresh or old cat saliva, and further compared the underlying neural circuits that are activated by cat saliva with different freshness.

The scientific question of the study is valid, the experiments were well-performed, and the statistical analyses are appropriate. However, there are some concerns that may directly affect the main interpretation of the results.

In this revised version of the manuscript, the authors have made important modifications in the text, inserted new experiments and performed additional data analyses, as recommended. These modifications have significantly improved the quality of the manuscript and addressed all the major concerns detected during the prior submission.

Reviewer #2 (Public review):

In this study, Nguyen et al. showed that cat saliva can robustly induce freezing behavior in mice. This effect is mediated through accessory olfactory system as it requires physical contact and is abolished in Trp2 KO mice. The authors further showed that V2R-A4 cluster is responsive to cat saliva. Lastly, they demonstrated c-Fos induction in AOB and VMHdm/c by the cat saliva. The c-Fos level in the VMHdm/c is correlated with freezing response.

Strength:

The study opens an interesting direction. It reveals the potential neural circuit for detecting cat saliva and driving defense behavior in mice. The behavior results and the critical role of accessory olfactory system in detecting cat saliva are clear and convincing.

Weakness:

The findings are relatively preliminary. The identities of the receptor and the ligand in the cat saliva that induces the behavior remain unclear. The identity of VMH cells that are activated by the cat saliva remains unclear. There is a lack of targeted functional manipulation to demonstrate the role of V2R-A4 or VMH cells in the behavioral response to the cat saliva.

Here are some specific comments:

(1) This result suggests that V2R-A4 may be the dominant VR for mice to detect cat saliva. Future studies should determine the identity of the receptor and the ligand in the cat saliva. Additionally, the functional importance of V2R-A4 remains unclear. It is important to knockout the receptor and test changes in cat saliva-induced freezing.

(2) AOB does not project to VMH directly. Other known important nodes for the predator defense circuit includes MeApv, BNST, PMd, AHN and PAG. It will be helpful to provide c-Fos data in those regions (especially MEA and BNST as they are between AOB and VMH) to provide a complete picture regarding how the brain process cat saliva to induce the behavior change.

(3) It is interesting that activation level difference in the VNO by old and fresh cat saliva does not transfer to AOB. It could be informative to examine correlation between VNO and AOB p6/c-Fos cell number and AOB and VMH c-Fos cell number across animals to understand whether the activation level across those regions are related. If they are not correlated, it could be helpful to add a discussion regarding potential reasons, e.g. neuromodulatory inputs to the AOB.

(4) Please indicate n in all figure plots and specify what individual dots means. In Figure 4h, there are 7 dots in old saliva group, presumably indicating 7 animals. In Figure 6b, there appear to be more than 7 dots for old cat saliva group. Are there more than 7 animals? If so, why are they not included in Figure 4h? If not, what does each dot mean? Note that each dot should represent independent sample. One animal should not contribute more than one dot.

(5) The identification of a cluster of VMHdm cells uniquely activated by fresh cat saliva urine is interesting. It will be important to identify the molecular handle of the cells to facilitate further investigation. This could be achieved using either activity dependent RNAseq or double in situ of saliva-induced c-Fos and candidate genes (candidate gene may be identified based on the known gene expression pattern).

Reviewer #3 (Public review):

Summary:

Nguyen et al show data indicating that the vomeronasal organ (VNO) and ventromedial hypothalamus (VMH) are part of a circuit that elicits defensive responses induced by predator odors. They also suggest that using fresh or old predator saliva may be a method to change the perceived imminence of predation. The authors also identify a family of VNO receptors that are activated by cat saliva. Next, the authors show how different components of this defensive circuit are activated by saliva, as measured by fos expression. The work also shows that different VMH populations are activated by fresh and old saliva, demonstrating that these stimuli create qualitatively different neural activity profiles. However, the exact components that differ between fresh and old saliva remain unknown and may be identified in future studies.

Strengths:

(1) Predator saliva is a stimulus of high ethological relevance<br /> (2) The authors performed a careful quantification of fos induction across the anterior-posterior axis<br /> (3) Authors show that different VMH populations are activated by fresh and old saliva

Weaknesses:

(1) There is a lack of standard circuit dissection methods, such as characterizing the behavioral effects of increasing and decreasing neural activity of relevant cell bodies and axonal projections

(2) Some of the findings are disconnected from the story. For example, the authors show V2R-A4-expressing cells are activated by predator odors, but the causal role of these cells in generating defensive actions is not shown

Author response:

The following is the authors’ response to the previous reviews

We greatly appreciate all the reviewers’ constructive comments on our previously revised manuscript. In the current revision, we added several experimental data for answering the reviewers’ comments. Below we describe our point-by-point responses to their comments:

Reviewer #1 (Public Review):

Unaddressed and additional concerns (re-submission)

In this revised version of the manuscript, the authors have made important modifications in the text, inserted new references, and incorporated additional quantifications of cFos immunolabeling in three brain regions, as recommended by the reviewers. While these modifications have significantly improved the quality of the manuscript, other critical concerns raised during the initial submission of the

manuscript (Major concerns 1, 2, and 4; some of them also raised by the other reviewers) were not properly addressed by the authors. On several occasions, the authors recognize the importance of clarifying the points for the correct interpretation of the results but opt for leaving the open questions to be addressed during future studies. Therefore, the authors might consider adding a new section at the end of the manuscript to include all the caveats and future directions.

In the current revision, in order to answer the reviewer #1’s original concerns 1, 2, and 4, we added several experimental data.

Original major concerns 1) and 2): Regarding whether mice are detecting qualitative or quantitative differences between fresh and old cat saliva.

To address these concerns, as shown in new Figure 1I and J, we measured volumes of saliva contained in in individual swabs and total protein concentrations at the time of behavior tests: Fresh (15 minutes after collection) and Old (4 hours after collection). The saliva volumes at the time of behavioral testing were indistinguishable between fresh and old samples (Figure 1I). In addition, the concentrations of total proteins in both fresh and old saliva were also indiscernible (Figure 1J). Furthermore, we also examined the difference of the amount of Fel d 4 protein, one of the most abundant proteins in cat saliva, between fresh and old saliva by conducting western blotting analyses. As shown in new Supplemental Figure 2, the amount of Fel d 4 was nearly equivalent between fresh and old saliva. Indeed, our analyses using recombinant Fel d 4 protein showed that Fel d 4 does not induce freezing behavior (Supplemental Figure 5). Based on these findings, we believe that the difference between fresh and old cat saliva lies in specific components rather than the total or major saliva content. One possible explanation for this difference is the time-dependent reduction of specific freezing-inducing components in old saliva.

To investigate such a possibility, we also examined mouse behavior directed toward swabs containing diluted fresh cat saliva. Indeed, exposure to diluted fresh saliva resulted in a shorter duration of freezing behavior. Fresh saliva diluted to 70% induced freezing behavior for a duration equivalent to that of undiluted fresh saliva, while freezing behavior in response to 50% and 30% fresh saliva was significantly reduced to the same duration as that observed with old saliva (Figure 1K). The duration of direct interaction with swabs containing 70% and 50–30% fresh saliva also exhibited a similar trend to that observed with fresh and old saliva swabs, respectively (Figure 1L).

These new results provide compelling evidence that the differential freezing response of mice to fresh versus old cat saliva is not attributed to quantitative differences, such as total volume, total protein concentration, or the amount of major proteins like Fel d 4. However, when fresh saliva was diluted, we observed a corresponding reduction in freezing behavior, suggesting that specific components within the saliva—those responsible for inducing freezing—may decrease over time.

Our findings indicate that while the overall content of saliva remains consistent over time, specific freezing-inducing components seem to degrade or reduce at a different rate than other components, which alters the composition of saliva over time. The speed of reduction of these freezing-inducing components appears to be different from more stable proteins such as Fel d 4. As a result, the composition of saliva changes over time, leading to a qualitative difference between fresh and old saliva that mice can detect. This ability to discern such subtle chemical changes likely reflects an adaptive sensory mechanism, allowing mice to respond to predator cues to induce optimal defensive behavior in a certain context. Identifying the specific freezing-inducing components through traditional purification processes, such as high-performance liquid chromatography followed by behavioral examination (Haga-Yamanaka et al., 2014; Kimoto et al., 2005), is crucial for a deeper understanding of the mechanisms underlying the observed behavior. Our research team is actively working to isolate these molecules, and we hope to report our findings in future studies.

(4) The interpretation that fresh and old saliva activates different subpopulations of neurons in the VMH based on the observation that cFos positively correlates with freezing responses only with the fresh saliva lacks empirical evidence. To address this question, the authors should use two neuronal activity markers to track the response of the same population of VHM cells within the same animals during exposure to fresh vs. old saliva.

To address this issue, as shown in the new Figure 7, we performed a double exposure experiment using Fos2A-iCreERT2; Ai9 (TRAP2) mice (Allen et al., 2017; DeNardo et al., 2019). In this experiment, mice were exposed to the first stimulus under the treatment of 4-hydroxytamoxifen (4-OHT). One week after the initial exposure, the same mice were subjected to a second stimulus exposure for one hour. Through this paradigm, neurons activated by the first stimulus were visualized by tdTomato, while ones activated by the second stimulus were detected as cFos-IR (Figure 7A). Quantification of tdTomato and cFos-IR double-positive cells among tdTomato-labeled cells revealed that 43% (mean per animal: 61 / 143) of cells activated by fresh saliva during the first exposure were also activated by fresh saliva during the second exposure, whereas only 16% (17 / 106) of cells activated by old saliva during the first exposure were activated by fresh saliva during the second exposure (p = 7.5e-6, Chi-squared test). The difference in the fraction of overlapping cells between fresh and old saliva exposures was found significant when we compared the two groups of animals (Figure 7D, p = 0.0035, permutation test). Additionally, quantification of tdTomato and cFos-IR double-positive cells among cFos-IR cells indicated that over 27% (61 / 226) of cells activated by fresh saliva during the second exposure were previously activated by fresh saliva, whereas only 15% (17 / 112) of cells activated by fresh saliva during the second exposure were previously activated by old saliva (p = 0.015, Chi-squared test). The difference in the fraction of overlapping cells between fresh and old saliva exposures was also significant in this analysis (Figure 7E,p = 0.0060, permutation test). Together, these results demonstrate that fresh and old cat saliva activate largely different populations of neurons within the VMH. These new results were described on page 11 line 18 – page 12 line 8.

In addition to these unaddressed concerns, some new issues have emerged in the new version of the manuscript. For example, the following paragraph introduced in the discussion section is not supported by the experimental findings.

"We assume that such differential activations of the mitral cells between fresh and old saliva result in the differential activation of targeting neural substrates, possibly MeApv, which results in differential activation of VMH neurons (Figure 7)."

Although the authors did not observe statistical differences in cFos expression in the pvMeA among groups, they claim that the differences in cFos expression in the VMH between fresh vs. old saliva are mediated by differential activation of upstream neurons in the MeApv. The lack of statistical differences may be caused by the reduced number of subjects in each group, as recognized in the text by the

authors.

We appreciate the reviewer's thoughtful comment. We agree that the paragraph in the comment, which presented a working hypothesis regarding differential activations of mitral cells and the MeApv between fresh and old saliva exposures, was speculative and not fully supported by our experimental findings. To address this, we have removed the assumptions related to the differential responses of mitral cells and the MeApv from the discussion and have updated the figure accordingly (now presented as new Figure 8).

Moreover, the authors propose that in addition to fel d 4, multiple molecules present in the cat saliva can be inducing distinct defensive responses in the animals, but they do not provide any reference to support their claim.

We thank the reviewer for highlighting this point. Our claim regarding the presence of other molecules in cat saliva inducing freezing defensive responses is based on our observation, as shown in the new Supplemental Figure 5, that recombinant Fel d 4 protein alone does not induce freezing behavior. This suggests the existence of other unidentified components in cat saliva that may contribute to freezing behavior. As we agree that identifying these specific freezing-inducing components is important for a more comprehensive understanding of the underlying mechanisms, our research team is actively working to isolate these molecules, and we hope to report our findings in future studies.

Reviewer #2 (Public Review):

The findings are relatively preliminary. The identities of the receptor and the ligand in the cat saliva that induces the behavior remain unclear. The identity of VMH cells that are activated by the cat saliva remains unclear. There is a lack of targeted functional manipulation to demonstrate the role of V2R-A4 or VMH cells in the behavioral response to the cat saliva.

We thank the reviewer’s important insight on the need for further investigation into the molecular and neural mechanisms underlying the behavioral response to cat saliva. We recognize the importance of conducting studies involving V2R-A4 receptor knockouts and targeted functional manipulations within the VMH using neural circuit perturbation approaches.

However, the V2R-A4 subfamily consists of 25 Vmn2r genes, most of which are closely grouped together, forming a V2R-A4 gene cluster within a 2.5-megabase chromosomal region. As we described in our recent review article (Rocha et al., 2024), the Vmn2r genes within the V2R-A4 subfamily display a high degree of homology, with nucleotide and amino acid identities among the several Vmn2rs surpassing 97-99%, suggesting possible redundancy among these receptor genes. This is in stark contrast to the diversity typically observed within other V2R subfamilies. Consequently, knockout strategies targeting a single receptor gene, which have been successful for other vomeronasal receptors, may not be effective for V2R-A4 receptor genes. The most appropriate strategy for examining the necessity of V2R-A4 receptors would be knocking out the entire V2R-A4 gene cluster, spanning a 2.5-megabase chromosomal region. Due to the technical challenges involved, addressing this issue is not feasible in the foreseeable future. Moreover, in our current study, we aimed to establish the foundational relationship between predator cues in cat saliva and defensive behaviors. We view our findings as an important first step that sets the stage for these more targeted and mechanistic studies involving the neural circuit perturbation experiments, such as optogenetics and Designer Receptors Exclusively Activated by Designer Drugs (DREADDs), in the next step.

Reviewer #3 (Public Review):

Weaknesses:

(1)  It is unclear if fresh and old saliva indeed alter the perceived imminence of predation, as claimed by the authors. Prior work indicates that lower imminence induces anxiety-related actions, such as re- organization of meal patterns and avoidance of open spaces, while slightly higher imminence produces freezing. Here, the authors show that fresh and old predator saliva only provoke different amounts of freezing, rather than changing the topography of defensive behaviors, as explained above. Another prediction of predatory imminence theory would be that lower imminence induced by old saliva should produce stronger cortical activation, while fresh saliva would activate amygdala, if these stimuli indeed correspond to significantly different levels of predation imminence.

We appreciate the reviewer’s insightful comments regarding the perceived imminence of predation and the behavioral responses to fresh and old saliva. Our study specifically focused on comparing the defensive behaviors of mice in response to 15-minute-old and 4-hour-old cat saliva, particularly within the context of freezing behavior in their home cages. We chose these specific time points to capture the potential variation in behavioral intensity rather than the full spectrum of defensive behaviors. While a more comprehensive analysis—including varying time points, different types of defensive behaviors, and broader neural activation patterns (e.g., cortical versus amygdala activation)—might provide further insights into predation imminence theory, these aspects were beyond the scope of our current study. Future research could certainly address these points by examining behavioral and neural responses across additional saliva aging intervals and in varied behavioral contexts. Such studies would complement and extend the findings presented here, further elucidating the relationship between predator cue characteristics and defensive behaviors.

(2)  It is known that predator odors activate and require AOB, VNO and VMH, thus replications of these findings are not novel, decreasing the impact of this work.

As the reviewer mentioned, the activation of the AOB, VNO, and VMH by predator odors has been established in prior studies. However, our study provides new insights by demonstrating that defensive freezing behavior in response to predator odors is mediated through the vomeronasal organ (VNO) sensory circuit, which has not been previously shown. The novelty of our work lies in two key findings: 1) the introduction of a new behavioral paradigm that assesses freezing responses to predator cues based on the freshness of chemosensory signals in cat saliva, and 2) the demonstration that the vomeronasal sensory circuit mediates defensive freezing behavior in response to cat saliva.

Additionally, our results show that cat saliva of different freshness levels differentially activates VNO sensory neurons that express the same subfamily of sensory receptors. This differential activation subsequently modulates the downstream neural circuits, leading to varied freezing behavioral outcomes. We believe these findings provide a novel conceptual advance over previous studies by elucidating a more detailed mechanism of how predator-derived cues influence defensive behaviors through the accessory olfactory system.

(3)  There is a lack of standard circuit dissection methods, such as characterizing the behavioral effects of increasing and decreasing neural activity of relevant cell bodies and axonal projections, significantly decreasing the mechanistic insights generated by this work

We thank the reviewer for this valuable comment. Investigating the behavioral effects of manipulating specific cell types and axonal projections, as well as characterizing circuit connectivity, is essential for a more comprehensive understanding of the underlying neural circuits. These approaches, such as modulating neural activity in defined cell populations and dissecting circuit pathways, using optogenetics, DREADD, etc., would provide deeper mechanistic insights. In our current study, however, we aimed to establish the foundational relationship between predator cues in cat saliva and defensive behaviors. We view our findings as an important first step that sets the stage for these more targeted and mechanistic studies in the future.

(4)  The correlation shown in Figure 5c may be spurious. It appears that the correlation is primarily driven by a single point (the green square point near the bottom left corner). All correlations should be calculated using Spearman correlation, which is non-parametric and less likely to show a large correlation due to a small number of outliers. Regardless of the correlation method used, there are too few points in Figure 5c to establish a reliable correlation. Please add more points to 5c.

We appreciate the reviewer’s suggestion regarding the correlation analysis in Figure 5E. We assessed the normality of our data using both the Shapiro-Wilk and Kolmogorov-Smirnov tests, which confirmed that the dataset is parametric, justifying the use of a parametric correlation method in this context. However, we acknowledge the concern about the limited number of data points and the influence of potential outliers on the observed correlation. Increasing the sample size might provide a more robust assessment of correlation patterns and reduce the potential impact of any single data point. While this would be an important direction for future research, such as with larger sample sizes, it is beyond the scope of the current study.

(5)  Please cite recent relevant papers showing VMH activity induced by predators, such as https://pubmed.ncbi.nlm.nih.gov/33115925/ and https://pubmed.ncbi.nlm.nih.gov/36788059/

We thank the reviewer’s suggestion to cite these important papers. https://pubmed.ncbi.nlm.nih.gov/33115925/ (Esteban Masferrer et al., 2020) and https://pubmed.ncbi.nlm.nih.gov/36788059/ (Tobias et al., 2023) are now cited at page 16 line 10 in Discussion under “Differential activation of VMH neurons potentially underlying distinct intensities of freezing behavior.”

(6)  Add complete statistical information in the figure legends of all figures, which should include n, name of test used and exact p values.

We included statistical analysis results in figure legends; for Figure 6B, we provided statistical analysis results in Supplemental Table 1.

(7)  Some of the findings are disconnected from the story. For example, the authors show V2R-A4- expressing cells are activated by predator odors. Are these cells more likely to be connected to the rest of the predatory defense circuit than other VNO cells?

Yes, our hypothesis posits that V2R-A4-expressing VNO sensory neurons serve as receptor neurons for predator cues present in cat saliva. Additionally, we assume that these specific sensory neurons have stronger anatomical connections with the defensive circuit compared to VNO sensory neurons expressing other receptor subfamilies. In our modified Discussion section, we discussed this point under “V2R-A4 subfamily as the receptor for predator cues in cat saliva.”

(8)  Please paste all figure legends directly below their corresponding figure to make the manuscript easier to read

We have added figure legends directly below their corresponding figures.

(9)  Were there other behavioral differences induced by fresh compared to old saliva? Do they provoke differences in stretch-attend risk evaluation postures, number of approaches, average distance to odor stimulus, velocity of movements towards and away the odor stimulus, etc?

We appreciate the reviewer's valuable comments. We have now incorporated an analysis of stretch-sniff risk assessment behavior, presented in new Figure 1F (graph) and Supplemental Figure 1B (raster plot). Mice exhibited stretch-sniff risk assessment behavior, which remained consistent across control, fresh saliva, and old saliva swabs. Additionally, we have also included a raster plot for direct investigation, previously noted as ‘interaction’ in the original manuscript (Supplemental Figure 1C). Mice exposed to a swab containing either fresh or old saliva significantly avoided directly investigating the swab. In contrast, mice exposed to a clean control swab spent a significant amount of time directly investigating the swab, engaging in behaviors such as sniffing and chewing (Figure 1G). A comparison of temporal behavioral patterns revealed a slightly higher frequency of direct investigation behavior toward old saliva compared to fresh saliva at the beginning of the exposure period (Supplemental Figure 1C).

Reviewer #3 (Recommendations For The Authors):

The authors have partially addressed several important points raised in the prior review, increasing the strength of the manuscript. However, 2 key questions already raised previously, were not addressed:

(1)  Is old saliva qualitatively different from new saliva, or is it the same as a smaller amount of new saliva? As Reviewer 1 wrote: "An important point that the authors should clarify in this study is whether mice are detecting qualitative or quantitative differences between fresh and old cat saliva."

Since one of the author's main points is that fresh and old saliva elicit different perceived threat imminences, it is crucial to show that these two stimuli are somehow qualitatively different.

One way to investigate this could be to show that animals perform different behaviors when exposed to smaller among of new saliva vs old saliva, or that the cfos activation patterns are different in these two conditions.

The answers to these concerns are provided in the Public review Comment from Reviewer #1.

(2)  The other key question is if different VMH populations are activated by new vs old saliva.

The answer to this concern is provided in the Public Review comment from Reviewer #1.

Lastly, although the new analysis and text changes improved the manuscript, many issues raised were addressed with some variation of 'future studies will be done', or 'we concur with the Reviewer'. However, the extra experiments required to answer these questions were not done. For this reason, even though the authors have numerous exciting pieces of data, overall the work is still incomplete. I highlight below some examples in which the authors agree with the Reviewer, but do not answer the question with the new work that would be required, or propose to do the work in future studies.

In this revised manuscript, we have conducted several additional experiments to address key concerns raised by the reviewers that are directly relevant to our claims. Specifically, we have examined: 1) whether qualitative or quantitative differences between fresh and old cat saliva are detected by mice to modulate behavior (NEW Figure 1I, J, K, and L, and NEW Supplemental Figure 2); 2) the involvement of Fel d 4 in freezing behavior (NEW Supplemental Figure 5); and 3) whether different VMH populations are activated by fresh versus old saliva (NEW Figure 7). However, some concerns raised by the reviewers fall outside the scope of the current manuscript. These include: 1) identifying the specific components that induce freezing, 2) examining the necessity of V2R-A4 receptors, 3) conducting neural circuit perturbations, and 4) performing a comprehensive analysis—including varying time points, different types of defensive behaviors, and broader neural activation patterns (e.g., cortical versus amygdala activation)—of the mouse’s defensive response to different levels of predator threat imminence. As these aspects are beyond the focus of our current manuscript, we have noted in the Public Review comments.

References:

Allen WE, DeNardo LA, Chen MZ, Liu CD, Loh KM, Fenno LE, Ramakrishnan C, Deisseroth K, Luo L. 2017. Thirst-associated preoptic neurons encode an aversive motivational drive. Science 357:1149– 1155.

DeNardo LA, Liu CD, Allen WE, Adams EL, Friedmann D, Fu L, Guenthner CJ, Tessier-Lavigne M, Luo L. 2019. Temporal evolution of cortical ensembles promoting remote memory retrieval. Nat Neurosci 22:460–469.

Haga-Yamanaka S, Ma L, He J, Qiu Q, Lavis LD, Looger LL, Yu CR. 2014. Integrated action of pheromone signals in promoting courtship behavior in male mice. Elife 3:e03025.

Kimoto H, Haga S, Sato K, Touhara K. 2005. Sex-specific peptides from exocrine glands stimulate mouse vomeronasal sensory neurons. Nature 437:898–901.

Rocha A, Nguyen QAT, Haga-Yamanaka S. 2024. Type 2 vomeronasal receptor-A4 subfamily: Potential predator sensors in mice. Genesis 62:e23597.

eLife Assessment

This important work shows how a simple geophysical setting of gas flow over a narrow channel of water can create a physical environment that leads to the isothermal replication of nucleic acids. The work presents convincing evidence for an isothermal polymerase chain reaction in careful experiments involving evaporation and convective flows, complimented with fluid dynamics simulations. This work will be of interest to scientists working on the origin of life and more broadly, on nucleic acids and diagnostic applications.

Reviewer #1 (Public review):

This manuscript from Schwintek and coworkers describes a system in which gas flow across a small channel (10^-4-10^-3 m scale) enables the accumulation of reactants and convective flow. The authors go on to show that this can be used to perform PCR as a model of prebiotic replication.

Strengths:

The manuscript nicely extends the authors' prior work in thermophoresis and convection to gas flows. The demonstration of nucleic acid replication is an exciting one, and an enzyme-catalyzed proof-of-concept is a great first step towards a novel geochemical scenario for prebiotic replication reactions and other prebiotic chemistry.

The manuscript nicely combines theory and experiment, which generally agree well with one another, and it convincingly shows that accumulation can be achieved with gas flows and that it can also be utilized in the same system for what one hopes is a precursor to a model prebiotic reaction. This continues efforts from Braun and Mast over the last 10-15 years extending a phenomenon that was appreciated by physicists and perhaps underappreciated in prebiotic chemistry to increasingly chemically relevant systems and, here, a pilot experiment with a simple biochemical system as a prebiotic model.

I think this is exciting work and will be of broad interest to the prebiotic chemistry community.

Weaknesses:

The manuscript states: "The micro scale gas-water evaporation interface consisted of a 1.5 mm wide and 250 µm thick channel that carried an upward pure water flow of 4 nl/s ≈ 10 µm/s perpendicular to an air flow of about 250 ml/min ≈ 10 m/s." This was a bit confusing on first read because Figure 2 appears to show a larger channel - based on the scale bar, it appears to be about 2 mm across on the short axis and 5 mm across on the long axis. From reading the methods, one understands the thickness is associated with the Teflon, but the 1.5 mm dimension is still a bit confusing (and what is the dimension in the long axis?) It is a little hard to tell which portion (perhaps all?) of the image is the channel. This is because discontinuities are present on the left and right sides of the experimental panels (consistent with the image showing material beyond the channel), but not the simulated panels. Based on the authors' description of the apparatus (sapphire/CNC machined Teflon/sapphire) it sounds like the geometry is well-known to them. Clarifying what is going on here (and perhaps supplying the source images for the machined Teflon) would be helpful.

The data shown in Figure 2d nicely shows nonrandom residuals (for experimental values vs. simulated) that are most pronounced at t~12 m and t~40-60m. It seems like this is (1) because some symmetry-breaking occurs that isn't accounted for by the model, and perhaps (2) because of the fact that these data are n=1. I think discussing what's going on with (1) would greatly improve the paper, and performing additional replicates to address (2) would be very informative and enhance the paper. Perhaps the negative and positive residuals would change sign in some, but not all, additional replicates?

The authors will most likely be familiar with the work of Victor Ugaz and colleagues, in which they demonstrated Rayleigh-Bénard-driven PCR in convection cells (10.1126/science.298.5594.793, 10.1002/anie.200700306). Not including some discussion of this work is an unfortunate oversight, and addressing it would significantly improve the manuscript and provide some valuable context to readers. Something of particular interest would be their observation that wide circular cells gave chaotic temperature profiles relative to narrow ones and that these improved PCR amplification (10.1002/anie.201004217). I think contextualizing the results shown here in light of this paper would be helpful. Again, it appears n=1 is shown for Figure 4a-c - the source of the title claim of the paper - and showing some replicates and perhaps discussing them in the context of prior work would enhance the manuscript.

I think some caution is warranted in interpreting the PCR results because a primer-dimer would be of essentially the same length as the product. It appears as though the experiment has worked as described, but it's very difficult to be certain of this given this limitation. Doing the PCR with a significantly longer amplicon would be ideal, or alternately discussing this possible limitation would be helpful to the readers in managing expectations.

Reviewer #2 (Public review):

Schwintek et al. investigated whether a geological setting of a rock pore with water inflow on one end and gas passing over the opening of the pore on the other end could create a non-equilibrium system that sustains nucleic acid reactions under mild conditions. The evaporation of water as the gas passes over it concentrates the solutes at the boundary of evaporation, while the gas flux induces momentum transfer that creates currents in the water that push the concentrated molecules back into the bulk solution. This leads to the creation of steady-state regions of differential salt and macromolecule concentrations that can be used to manipulate nucleic acids. First, the authors showed that fluorescent bead behavior in this system closely matched their fluid dynamic simulations. With that validation in hand, the authors next showed that fluorescently labeled DNA behaved according to their theory as well. Using these insights, the authors performed a FRET experiment that clearly demonstrated the hybridization of two DNA strands as they passed through the high Mg++ concentration zone, and, conversely, the dissociation of the strands as they passed through the low Mg++ concentration zone. This isothermal hybridization and dissociation of DNA strands allowed the authors to perform an isothermal DNA amplification using a DNA polymerase enzyme. Crucially, the isothermal DNA amplification required the presence of the gas flux and could not be recapitulated using a system that was at equilibrium. These experiments advance our understanding of the geological settings that could support nucleic acid reactions that were key to the origin of life.

The presented data compellingly supports the conclusions made by the authors. To increase the relevance of the work for the origin of life field, the following experiments are suggested:

(1) While the central premise of this work is that RNA degradation presents a risk for strand separation strategies relying on elevated temperatures, all of the work is performed using DNA as the nucleic acid model. I understand the convenience of using DNA, especially in the latter replication experiment, but I think that at least the FRET experiments could be performed using RNA instead of DNA.

(2) Additionally, showing that RNA does not degrade under the conditions employed by the authors (I am particularly worried about the high Mg++ zones created by the flux) would further strengthen the already very strong and compelling work.

(3) Finally, I am curious whether the authors have considered designing a simulation or experiment that uses the imidazole- or 2′,3′-cyclic phosphate-activated ribonucleotides. For instance, a fully paired RNA duplex and a fluorescently-labeled primer could be incubated in the presence of activated ribonucleotides +/- flux and subsequently analyzed by gel electrophoresis to determine how much primer extension has occurred. The reason for this suggestion is that, due to the slow kinetics of chemical primer extension, the reannealing of the fully complementary strands as they pass through the high Mg++ zone, which is required for primer extension, may outcompete the primer extension reaction. In the case of the DNA polymerase, the enzymatic catalysis likely outcompetes the reannealing, but this may not recapitulate the uncatalyzed chemical reaction.

Author response:

Reviewer #1 (Public review):

This manuscript from Schwintek and coworkers describes a system in which gas flow across a small channel (10^-4-10^-3 m scale) enables the accumulation of reactants and convective flow. The authors go on to show that this can be used to perform PCR as a model of prebiotic replication.

Strengths:

The manuscript nicely extends the authors' prior work in thermophoresis and convection to gas flows. The demonstration of nucleic acid replication is an exciting one, and an enzyme-catalyzed proof-of-concept is a great first step towards a novel geochemical scenario for prebiotic replication reactions and other prebiotic chemistry.

The manuscript nicely combines theory and experiment, which generally agree well with one another, and it convincingly shows that accumulation can be achieved with gas flows and that it can also be utilized in the same system for what one hopes is a precursor to a model prebiotic reaction. This continues efforts from Braun and Mast over the last 10-15 years extending a phenomenon that was appreciated by physicists and perhaps underappreciated in prebiotic chemistry to increasingly chemically relevant systems and, here, a pilot experiment with a simple biochemical system as a prebiotic model.

I think this is exciting work and will be of broad interest to the prebiotic chemistry community.

Weaknesses:

The manuscript states: "The micro scale gas-water evaporation interface consisted of a 1.5 mm wide and 250 µm thick channel that carried an upward pure water flow of 4 nl/s ≈ 10 µm/s perpendicular to an air flow of about 250 ml/min ≈ 10 m/s." This was a bit confusing on first read because Figure 2 appears to show a larger channel - based on the scale bar, it appears to be about 2 mm across on the short axis and 5 mm across on the long axis. From reading the methods, one understands the thickness is associated with the Teflon, but the 1.5 mm dimension is still a bit confusing (and what is the dimension in the long axis?) It is a little hard to tell which portion (perhaps all?) of the image is the channel. This is because discontinuities are present on the left and right sides of the experimental panels (consistent with the image showing material beyond the channel), but not the simulated panels. Based on the authors' description of the apparatus (sapphire/CNC machined Teflon/sapphire) it sounds like the geometry is well-known to them. Clarifying what is going on here (and perhaps supplying the source images for the machined Teflon) would be helpful.

We understand. We will update the figures to better show dimensions of the experimental chamber. We will also add a more complete Figure in the supplementary information. Part of the complexity of the chamber however stems from the fact that the same chamber design has also been used to create defined temperature gradients which are not necessary and thus the chamber is much more complex than necessary.

The data shown in Figure 2d nicely shows nonrandom residuals (for experimental values vs. simulated) that are most pronounced at t~12 m and t~40-60m. It seems like this is (1) because some symmetry-breaking occurs that isn't accounted for by the model, and perhaps (2) because of the fact that these data are n=1. I think discussing what's going on with (1) would greatly improve the paper, and performing additional replicates to address (2) would be very informative and enhance the paper. Perhaps the negative and positive residuals would change sign in some, but not all, additional replicates?

To address this, we will show two more replicates of the experiment and include them in Figure 2.

We are seeing two effects when we compare fluorescence measurements of the experiments.

Firstly, degassing of water causes the formation of air-bubbles, which are then transported upwards to the interface, disrupting fluorescence measurements. This, however, mostly occurs in experiments with elevated temperatures for PCR reactions, such as displayed in Figure 4.

Secondly, due to the high surface tension of water, the interface is quite flexible. As the inflow and evaporation work to balance each other, the shape of the interface adjusts, leading to alterations in the circular flow fields below.

Thus the conditions, while overall being in steady state, show some fluctuations. The strong dependence on interface shape is also seen in the simulation. However, modeling a dynamic interface shape is not so easy to accomplish, so we had to stick to one geometry setting. Again here, the added movies of two more experiments should clarify this issue.

The authors will most likely be familiar with the work of Victor Ugaz and colleagues, in which they demonstrated Rayleigh-Bénard-driven PCR in convection cells (10.1126/science.298.5594.793, 10.1002/anie.200700306). Not including some discussion of this work is an unfortunate oversight, and addressing it would significantly improve the manuscript and provide some valuable context to readers. Something of particular interest would be their observation that wide circular cells gave chaotic temperature profiles relative to narrow ones and that these improved PCR amplification (10.1002/anie.201004217). I think contextualizing the results shown here in light of this paper would be helpful.

Thanks for pointing this out and reminding us. We apologize. We agree that the chaotic trajectories within Rayleigh-Bénard convection cells lead to temperature oscillations similar to the salt variations in our gas-flux system. Although the convection-driven PCR in Rayleigh-Bénard is not isothermal like our system, it provides a useful point of comparison and context for understanding environments that can support full replication cycles. We will add a section comparing approaches and giving some comparison into the history of convective PCR and how these relate to the new isothermal implementation.

Again, it appears n=1 is shown for Figure 4a-c - the source of the title claim of the paper - and showing some replicates and perhaps discussing them in the context of prior work would enhance the manuscript.

We appreciate the reviewer for bringing this to our attention. We will now include the two additional repeats for the data shown in Figure 4c, while the repeats of the PAGE measurements are already displayed in Supplementary Fig. IX.2. Initially, we chose not to show the repeats in Figure 4c due to the dynamic and variable nature of the system. These variations are primarily caused by differences at the water-air interface, attributed to the high surface tension of water. Additionally, the stochastic formation of air bubbles in the inflow—despite our best efforts to avoid them—led to fluctuations in the fluorescence measurements across experiments. These bubbles cause a significant drop in fluorescence in a region of interest (ROI) until the area is refilled with the sample.

Unlike our RNA-focused experiments, PCR requires high temperatures and degassing a PCR master mix effectively is challenging in this context. While we believe our chamber design is sufficiently gas-tight to prevent air from diffusing in, the high surface-to-volume ratio in microfluidics makes degassing highly effective, particularly at elevated temperatures. We anticipate that switching to RNA experiments at lower temperatures will mitigate this issue, which is also relevant in a prebiotic context.

The reviewer’s comments are valid and prompt us to fully display these aspects of the system. We will now include these repeats in Figure 4c to give readers a deeper understanding of the experiment's dynamics. Additionally, we will provide videos of all three repeats, allowing readers to better grasp the nature of the fluctuations in SYBR Green fluorescence depicted in Figure 4c.

I think some caution is warranted in interpreting the PCR results because a primer-dimer would be of essentially the same length as the product. It appears as though the experiment has worked as described, but it's very difficult to be certain of this given this limitation. Doing the PCR with a significantly longer amplicon would be ideal, or alternately discussing this possible limitation would be helpful to the readers in managing expectations.

This is a good point and should be discussed more in the manuscript. Our gel electrophoresis is capable of distinguishing between replicate and primer dimers. We know this since we were optimizing the primers and template sequences to minimize primer dimers, making it distinguishable from the desired 61mer product. That said, all of the experiments performed without a template strand added did not show any band in the vicinity of the product band after 4h of reaction, in contrast to the experiments with template, presenting a strong argument against the presence of primer dimers.

Reviewer #2 (Public review):

Schwintek et al. investigated whether a geological setting of a rock pore with water inflow on one end and gas passing over the opening of the pore on the other end could create a non-equilibrium system that sustains nucleic acid reactions under mild conditions. The evaporation of water as the gas passes over it concentrates the solutes at the boundary of evaporation, while the gas flux induces momentum transfer that creates currents in the water that push the concentrated molecules back into the bulk solution. This leads to the creation of steady-state regions of differential salt and macromolecule concentrations that can be used to manipulate nucleic acids. First, the authors showed that fluorescent bead behavior in this system closely matched their fluid dynamic simulations. With that validation in hand, the authors next showed that fluorescently labeled DNA behaved according to their theory as well. Using these insights, the authors performed a FRET experiment that clearly demonstrated the hybridization of two DNA strands as they passed through the high Mg++ concentration zone, and, conversely, the dissociation of the strands as they passed through the low Mg++ concentration zone. This isothermal hybridization and dissociation of DNA strands allowed the authors to perform an isothermal DNA amplification using a DNA polymerase enzyme. Crucially, the isothermal DNA amplification required the presence of the gas flux and could not be recapitulated using a system that was at equilibrium. These experiments advance our understanding of the geological settings that could support nucleic acid reactions that were key to the origin of life.

The presented data compellingly supports the conclusions made by the authors. To increase the relevance of the work for the origin of life field, the following experiments are suggested:

(1) While the central premise of this work is that RNA degradation presents a risk for strand separation strategies relying on elevated temperatures, all of the work is performed using DNA as the nucleic acid model. I understand the convenience of using DNA, especially in the latter replication experiment, but I think that at least the FRET experiments could be performed using RNA instead of DNA.

We understand the request only partially. The modification brought about by the two dye molecules in the FRET probe to be able to probe salt concentrations by melting is of course much larger than the change of the backbone from RNA to DNA. This was the reason why we rather used the much more stable DNA construct which is also manufactured at a lower cost and in much higher purity also with the modifications. But we think the melting temperature characteristics of RNA and DNA in this range is enough known that we can use DNA instead of RNA for probing the salt concentration in our flow cycling.

Only at extreme conditions of pH and salt, RNA degradation through transesterification, especially under alkaline conditions is at least several orders of magnitude faster than spontaneous degradative mechanisms acting upon DNA [Li, Y., & Breaker, R. R. (1999). Kinetics of RNA degradation by specific base catalysis of transesterification involving the 2 ‘-hydroxyl group. Journal of the American Chemical Society, 121(23), 5364-5372.]. The work presented in this article is however focussed on hybridization dynamics of nucleic acids. Here, RNA and DNA share similar properties regarding the formation of double strands and their respective melting temperatures. While RNA has been shown to form more stable duplex structures exhibiting higher melting temperatures compared to DNA [Dimitrov, R. A., & Zuker, M. (2004). Prediction of hybridization and melting for double-stranded nucleic acids. Biophysical Journal, 87(1), 215-226.], the general impact of changes in salt, temperature and pH [Mariani, A., Bonfio, C., Johnson, C. M., & Sutherland, J. D. (2018). pH-Driven RNA strand separation under prebiotically plausible conditions. Biochemistry, 57(45), 6382-6386.] on respective melting temperatures follows the same trend for both nucleic acid types. Also the diffusive properties of RNA and DNA are very similar [Baaske, P., Weinert, F. M., Duhr, S., Lemke, K. H., Russell, M. J., & Braun, D. (2007). Extreme accumulation of nucleotides in simulated hydrothermal pore systems. Proceedings of the National Academy of Sciences, 104(22), 9346-9351.].

Since this work is a proof of principle for the discussed environment being able to host nucleic acid replication, we aimed to avoid second order effects such as degradation by hydrolysis by using DNA as a proxy polymer. This enabled us to focus on the physical effects of the environment on local salt and nucleic acid concentration. The experiments performed with FRET are used to visualize local salt concentration changes and their impact on the melting temperature of dissolved nucleic acids.  While performing these experiments with RNA would without doubt cover a broader application within the field of origin of life, we aimed at a step-by-step / proof of principle approach, especially since the environmental phenomena studied here have not been previously investigated in the OOL context. Incorporating RNA-related complexity into this system should however be addressed in future studies. This will likely require modifications to the experimental boundary conditions, such as adjusting pH, temperature, and salt concentration, to account for the greater duplex stability of RNA. For instance, lowering the pH would reduce the RNA melting temperature [Ianeselli, A., Atienza, M., Kudella, P. W., Gerland, U., Mast, C. B., & Braun, D. (2022). Water cycles in a Hadean CO2 atmosphere drive the evolution of long DNA. Nature Physics, 18(5), 579-585.].

(2) Additionally, showing that RNA does not degrade under the conditions employed by the authors (I am particularly worried about the high Mg++ zones created by the flux) would further strengthen the already very strong and compelling work.

Based on literature values for hydrolysis rates of RNA [Li, Y., & Breaker, R. R. (1999). Kinetics of RNA degradation by specific base catalysis of transesterification involving the 2 ‘-hydroxyl group. Journal of the American Chemical Society, 121(23), 5364-5372.], we estimate RNA to have a halflife of multiple months under the deployed conditions in the FRET experiment (High concentration zones contain <1mM of Mg2+). Additionally, dsRNA is multiple orders of magnitude more stable than ssRNA with regards to degradation through hydrolysis [Zhang, K., Hodge, J., Chatterjee, A., Moon, T. S., & Parker, K. M. (2021). Duplex structure of double-stranded RNA provides stability against hydrolysis relative to single-stranded RNA. Environmental Science & Technology, 55(12), 8045-8053.], improving RNA stability especially in zones of high FRET signal. Furthermore, at the neutral pH deployed in this work, RNA does not readily degrade. In previous work from our lab [Salditt, A., Karr, L., Salibi, E., Le Vay, K., Braun, D., & Mutschler, H. (2023). Ribozyme-mediated RNA synthesis and replication in a model Hadean microenvironment. Nature Communications, 14(1), 1495.], we showed that the lifetime of RNA under conditions reaching 40mM Mg2+ at the air-water interface at 45°C was sufficient to support ribozymatically mediated ligation reactions in experiments lasting multiple hours.

With that in mind, gaining insight into the median Mg2+ concentration across multiple averaged nucleic acid trajectories in our system (see Fig. 3c&d) and numerically convoluting this with hydrolysis dynamics from literature would be highly valuable. We anticipate that longer residence times in trajectories distant from the interface will improve RNA stability compared to a system with uniformly high Mg2+ concentrations.

(3) Finally, I am curious whether the authors have considered designing a simulation or experiment that uses the imidazole- or 2′,3′-cyclic phosphate-activated ribonucleotides. For instance, a fully paired RNA duplex and a fluorescently-labeled primer could be incubated in the presence of activated ribonucleotides +/- flux and subsequently analyzed by gel electrophoresis to determine how much primer extension has occurred. The reason for this suggestion is that, due to the slow kinetics of chemical primer extension, the reannealing of the fully complementary strands as they pass through the high Mg++ zone, which is required for primer extension, may outcompete the primer extension reaction. In the case of the DNA polymerase, the enzymatic catalysis likely outcompetes the reannealing, but this may not recapitulate the uncatalyzed chemical reaction.

This is certainly on our to-do list. Our current focus is on templated ligation rather than templated polymerization and we are working hard to implement RNA-only enzyme-free ligation chain reaction, based on more optimized parameters for the templated ligation from 2’3’-cyclic phosphate activation that was just published [High-Fidelity RNA Copying via 2′,3′-Cyclic Phosphate Ligation, Adriana C. Serrão, Sreekar Wunnava, Avinash V. Dass, Lennard Ufer, Philipp Schwintek, Christof B. Mast, and Dieter Braun, JACS doi.org/10.1021/jacs.3c10813 (2024)]. But we first would try this at an air-water interface which was shown to work with RNA in a temperature gradient [Ribozyme-mediated RNA synthesis and replication in a model Hadean microenvironment, Annalena Salditt, Leonie Karr, Elia Salibi, Kristian Le Vay, Dieter Braun & Hannes Mutschler, Nature Communications doi.org/10.1038/s41467-023-37206-4 (2023)] before making the jump to the isothermal setting we describe here. So we can understand the question, but it was good practice also in the past to first get to know the setting with PCR, then jump to RNA.

Reviewer #2 (Recommendations for the authors):

(1) Could the authors comment on the likelihood of the geological environments where the water inflow velocity equals the evaporation velocity?

This is an important point to mention in the manuscript, thank you for pointing that out. To produce a defined experiment, we were pushing the water out with a syringe pump, but regulated in a way that the evaporation was matching our flow rate. We imagine that a real system will self-regulate the inflow of the water column on the one hand side by a more complex geometry of the gas flow, matching the evaporation with the reflow of water automatically. The interface would either recede or move closer to the gas flux, depending on whether the inflow exceeds or falls short of the evaporation rate. As the interface moves closer, evaporation speeds up, while moving away slows it down. This dynamic process stabilizes the system, with surface tension ultimately fixing the interface in place.

We have seen a bit of this dynamic already in the experiments, could however so far not yet find a good geometry within our 2-dimensional constant thickness geometry to make it work for a longer time. Very likely having a 3-dimensional reservoir of water with less frictional forces would be able to do this, but this would require a full redesign of a multi-thickness microfluidics. The more we think about it, the more we envisage to make the next implementation of the experiment with a real porous volcanic rock inside a humidity chamber that simulates a full 6h prebiotic day. But then we would lose the whole reproducibility of the experiment, but likely gain a way that recondensation of water by dew in a cold morning is refilling the water reservoirs in the rocks again. Sorry that I am regressing towards experiments in the future.

(2) Could the authors speculate on using gases other than ambient air to provide the flux and possibly even chemical energy? For example, using carbonyl sulfide or vaporized methyl isocyanide could drive amino acid and nucleotide activation, respectively, at the gas-water interface.

This is an interesting prospect for future work with this system. We thought also about introducing ammonia for pH control and possible reactions. We were amazed in the past that having CO2 instead of air had a profound impact on the replication and the strand separation [Water cycles in a Hadean CO2 atmosphere drive the evolution of long DNA, Alan Ianeselli, Miguel Atienza, Patrick Kudella, Ulrich Gerland, Christof Mast & Dieter Braun, Nature Physics doi.org/10.1038/s41567-022-01516-z (2022)]. So going more in this direction absolutely makes sense and as it acts mostly on the length-selectively accumulated molecules at the interface, only the selected molecules will be affected, which adds to the selection pressure of early evolutionary scenarios.

Of course, in the manuscript, we use ambient air as a proxy for any gas, focusing primarily on the energy introduced through momentum transfer and evaporation. We speculate that soluble gasses could establish chemical gradients, such as pH or redox potential, from the bulk solution to the interface, similar to the Mg2+ accumulation shown in Figure 3c. The nature of these gradients would depend on each gas's solubility and diffusivity. We have already observed such effects in thermal gradients [Keil, L. M., Möller, F. M., Kieß, M., Kudella, P. W., & Mast, C. B. (2017). Proton gradients and pH oscillations emerge from heat flow at the microscale. Nature communications, 8(1), 1897.] and finding similar behavior in an isothermal environment would be a significant discovery.

(3) Line 162: Instead of "risk," I suggest using "rate".

Oh well - thanks for pointing this out! Will be changed.

(4) Using FRET of a DNA duplex as an indicator of salt concentration is a decent proxy, but a more direct measurement of salt concentration would provide further merit to the explicit statement that it is the salt concentration that is changing in the system and not another hidden parameter.

Directly observing salt concentration using microscopy is a difficult task. While there are dyes that change their fluorescence depending on the local Na+ or Mg2+ concentration, they are not operating differentially, i.e. by making a ratio between two color channels. Only then we are not running into artifacts from the dye molecules being accumulated by the non-equilibrium settings. We were able to do this for pH in the past, but did not find comparable optical salt sensors. This is the reason we ended up with a FRET pair, with the advantage that we actually probe the strand separation that we are interested in anyhow. Using such a dye in future work would however without a doubt enhance the understanding of not only this system, but also our thermal gradient environments.

(5) Figure 3a: Could the authors add information on "Dried DNA" to the caption? I am assuming this is the DNA that dried off on the sides of the vessel but cannot be sure.

Thanks to the reviewer for pointing this out. This is correct and we will describe this better in the revised manuscript.

(6) Figure 4b and c: How reproducible is this data? Have the authors performed this reaction multiple independent times? If so, this data should be added to the manuscript.

The data from the gel electrophoresis was performed in triplicates and is shown in full in supplementary information. The data in c is hard to reproduce, as the interface is not static and thus ROI measurements are difficult to perform as an average of repeats. Including the data from the independent repeats will however give the reader insight into some of the experimental difficulties, such as air bubbles, which form from degassing as the liquid heats up, that travel upwards to the interface, disrupting the ongoing fluorescence measurements.

(7) Line 256: "shielding from harmful UV" statement only applies to RNA oligomers as UV light may actually be beneficial for earlier steps during ribonucleoside synthesis. I suggest rephrasing to "shielding nucleic acid oligomers from UV damage.".

Will be adjusted as mentioned.

(8) The final paragraph in the Results and Discussion section would flow better if placed in the Conclusion section.

This is a good point and we will merge results and discussion closer together.

(9) Line 262, "...of early Life" is slightly overstating the conclusions of the study. I suggest rephrasing to "...of nucleic acids that could have supported early life."

This is a fair comment. We thank the reviewer for his detailed analysis of the manuscript!

(10) In references, some of the journal names are in sentence case while others are in title case (see references 23 and 26 for example).

Thanks - this will be fixed.

eLife assessment

This important study demonstrates a mechanism underlying the sex-dependent regulation of the susceptibility to gut colonization by Methicillin-resistant Staphylococcus aureus (MRSA). The evidence supporting the conclusion is solid, but additional experiments would strengthen the findings. The work will interest biologists who are working on intestinal infection and immunity.

Reviewer #1 (Public review):

Summary:

Lejeune et al. demonstrated sex-dependent differences in the susceptibility to MRSA infection. The authors demonstrated the role of the microbiota and sex hormones as potential determinants of susceptibility. Moreover, the authors showed that Th17 cells and neutrophils contribute to sex hormone-dependent protection in female mice.

Strengths:

The role of microbiota was examined in various models (gnotobiotic, co-housing, microbiota transplantation). The identification of responsible immune cells was achieved using several genetic knockouts and cell-specific depletion models. The involvement of sex hormones was clarified using ovariectomy and the FCG model.

Weaknesses:

The mechanisms by which specific microbiota confer female-specific protection remain unclear.

Reviewer #2 (Public review):

The current study by Lejeune et al. investigates factors that allow for persistent MRSA infection in the GI tract. They developed an intriguing model of intestinal MRSA infection that does not use the traditional antibiotic approach, thereby allowing for a more natural infection that includes the normal intestinal microbiota. This model is more akin to what might be expected to be observed in a healthy human host. They find that biological sex plays a clear role in bacterial persistence during infection but only in mice bred at an NYU Facility and not those acquired from Jackson Labs. This clearly indicates a role for the intestinal microbiome in affecting female bacterial persistence but not male persistence which was unaffected by the origin of the mice and thus the microbiome. Through a series of clever microbiome-specific transfer experiments, they determine that the NYU-specific microbiome plays a role in this sexual dimorphism but is not solely responsible. Additional experiments indicate that Th17 cells, estrogen, and neutrophils also participate in the resistance to persistent infection. Notably, they assess the role of sex chromosomes (X/Y) using the established four core genotype model and find that these chromosomes appear to play little role in bacterial persistence.

Overall, the paper nicely adds to the growing body of literature investigating how biological sex impacts the immune system and the burden of infectious disease. The conclusions are mostly supported by the data although there are some aspects of the data that could be better addressed and clarified.

(1) There is something of a disconnect between the initial microbiome data and the later data that analyzes sex hormones and chromosomes. While there are clearly differences in microbial species across the two sites (NYU and JAX) how these bacterial species might directly interact with immune cells to induce female-specific responses is left unexplored. At the very least it would help to try and link these two distinct pieces of data to try and inform the reader how the microbiome is regulating the sex-specific response. Indeed, the reader is left with no clear exploration of the microbiota's role in the persistence of the infection and thus is left wanting.

(2) While the authors make a reasonable case that Th17 T cells are important for controlling infection (using RORgt knockout mice that cannot produce Th17 cells), it is not clear how these cells even arise during infection since the authors make most of the observations 2 days post-infection which is longer before a normal adaptive immune response would be expected to arise. The authors acknowledge this, but their explanation is incomplete. The increase in Th17 cells they observe is predicated on mitogenic stimulation, so they are not specific (at least in this study) for MRSA. It would be helpful to see a specific restimulation of these cells with MRSA antigens to determine if there are pre-existing, cross-reactive Th17 cells specific for MRSA and microbiota species which could then link these two as mentioned above.

(3) The ovariectomy experiment demonstrates a role for ovarian hormones; however, it lacks a control of adding back ovarian hormones (or at least estrogen) so it is not entirely obvious what is causing the persistence in this experiment. This is especially important considering the experiments demonstrating no role for sex chromosomes thus demonstrating that hormonal effects are highly important. Here it leaves the reader without a conclusive outcome as to the exact hormonal mechanism.

(4) The discussion is underdeveloped and is mostly a rehash of the results. It would greatly enhance the manuscript if the authors would more carefully place the results in the context of the current state of the field including a more enhanced discussion of the role of estrogen, microbiome, and T cells and how the field might predict these all interact and how they might be interacting in the current study as well.

Reviewer #3 (Public review):

Summary:

Using a mouse model of Staphylococcus aureus gut colonization, Lejeune et al. demonstrate that the microbiome, immune system, and sex are important contributing factors for whether this important human pathogen persists in the gut. The work begins by describing differential gut clearance of S. aureus in female B6 mice bred at NYU compared to those from Jackson Laboratories (JAX). NYU female mice cleared S. aureus from the gut but NYU male mice and mice of both sexes from JAX exhibited persistent gut colonization. Further experimentation demonstrated that differences between staphylococcal gut clearance in NYU and JAX female mice were attributed to the microbiome. However, NYU male and female mice harbor similar microbiomes, supporting the conclusion that the microbiome cannot account for the observed sex-dependent clearance of S. aureus gut colonization. To identify factors responsible for female clearance of S. aureus, the authors performed RNAseq on intestinal epithelial cells and cells enriched within the lamina propria. This analysis revealed sex-dependent transcriptional responses in both tissues. Genes associated with immune cell function and migration were distinctly expressed between the sexes. To determine which immune cell types contribute to S. aureus clearance Lejeune et al employed genetic and antibody-mediated immune cell depletion. This experiment demonstrated that CD4+ IL17+ cells and neutrophils promote the elimination of S. aureus from the gut. Subsequent experiments, including the use of the 'four core genotype model' were conducted to discern between the roles of sex chromosomes and sex hormones. This work demonstrated that sex-chromosome-linked genes are not responsible for clearance, increasing the likelihood that hormones play a dominant role in controlling S. aureus gut colonization.

Strengths:

A strength of the work is the rigorous experimental design. Appropriate controls were executed and, in most cases, multiple approaches were conducted to strengthen the authors' conclusions. The conclusions are supported by the data.

The following suggestions are offered to improve an already strong piece of scholarship.

Weaknesses:

The correlation between female sex hormones and the elimination of S. aureus from the gut could be further validated by quantifying sex hormones produced in the four core genotype mice in response to colonization. Additionally, and this may not be feasible, but according to the proposed model administering female sex hormones to male mice should decrease colonization. Finally, knowing whether the quantity of IL-17a CD4+ cells change in the OVX mice has the potential to discern whether abundance/migration of the cells or their activation is promoted by female sex hormones.

In the Discussion, the authors highlight previous work establishing a link between immune cells and sex hormone receptors, but whether the estrogen (and progesterone) receptor is differentially expressed in response to S. aureus colonization could be assessed in the RNAseq dataset. Differential expression of known X and Y chromosome-linked genes were discussed but specific sex hormones or sex hormone receptors, like the estrogen receptor, were not. This potential result could be highlighted.

Author response:

Reviewer #1 (Public review):

Summary:

Lejeune et al. demonstrated sex-dependent differences in the susceptibility to MRSA infection. The authors demonstrated the role of the microbiota and sex hormones as potential determinants of susceptibility. Moreover, the authors showed that Th17 cells and neutrophils contribute to sex hormone-dependent protection in female mice.

Strengths:

The role of microbiota was examined in various models (gnotobiotic, co-housing, microbiota transplantation). The identification of responsible immune cells was achieved using several genetic knockouts and cell-specific depletion models. The involvement of sex hormones was clarified using ovariectomy and the FCG model.

Weaknesses:

The mechanisms by which specific microbiota confer female-specific protection remain unclear.

We thank the reviewer for highlighting the strength of the manuscript including the models and techniques we employ. We agree that the relationship between the microbiota and sex-dependent protection is less developed compared with other aspects of the study. In preparation of a revised manuscript, we intend on performing a more thorough comparison of male vs. female microbiota, along with quantification of sex hormones and downstream Th17 function (neutrophil recruitment and activation).

Reviewer #2 (Public review):

Overall, the paper nicely adds to the growing body of literature investigating how biological sex impacts the immune system and the burden of infectious disease. The conclusions are mostly supported by the data although there are some aspects of the data that could be better addressed and clarified.

We thank the reviewer for appreciating our contribution. We intend on performing experiments to fill-in gaps and text revisions to increase clarity and acknowledge limitations.

(1) There is something of a disconnect between the initial microbiome data and the later data that analyzes sex hormones and chromosomes. While there are clearly differences in microbial species across the two sites (NYU and JAX) how these bacterial species might directly interact with immune cells to induce female-specific responses is left unexplored. At the very least it would help to try and link these two distinct pieces of data to try and inform the reader how the microbiome is regulating the sex-specific response. Indeed, the reader is left with no clear exploration of the microbiota's role in the persistence of the infection and thus is left wanting.

We agree. This comment is similar to Reviewer #1’s feedback. As mentioned above, we anticipate clarifying the association between sex differences and the microbiota. We will attempt to investigate specific bacteria, although some aspects of microbiota characterization may be outside the timeframe of the revision.

(2) While the authors make a reasonable case that Th17 T cells are important for controlling infection (using RORgt knockout mice that cannot produce Th17 cells), it is not clear how these cells even arise during infection since the authors make most of the observations 2 days post-infection which is longer before a normal adaptive immune response would be expected to arise. The authors acknowledge this, but their explanation is incomplete. The increase in Th17 cells they observe is predicated on mitogenic stimulation, so they are not specific (at least in this study) for MRSA. It would be helpful to see a specific restimulation of these cells with MRSA antigens to determine if there are pre-existing, cross-reactive Th17 cells specific for MRSA and microbiota species which could then link these two as mentioned above.

We acknowledge that this is a major limitation of our study. Although an experiment demonstrating pre-existing, cross-reactive T cells would help support our conclusion, aspects of MRSA biology may make the results of this experiment difficult to interpret. We have consulted with an expert on MRSA virulence factors, co-lead author Dr. Victor Torres, about the feasibility of this experiment. MRSA possess superantigens, such as Staphylococcal enterotoxin B, which bind directly to specific Vβ regions of T-cell receptors (TCR) and major histocompatibility complex (MHC) class II on antigen-presenting cells, resulting in hyperactivation of T lymphocytes and monocytes/macrophages. Additionally, other MRSA virulence factors, such as α-hemolysin and LukED, can induce cell death of lymphocytes. MRSA’s enterotoxins are heat stable, so heat-inactivation of the bacterium may not help in this matter.  For these reasons, restimulation of lymphocytes with MRSA antigens may be difficult to interpret. We humbly suggest that addressing this aspect of the mechanism is outside the scope of this manuscript.

A study by Shao et al. provides an example of a host commensal species inducing Th17 cells with cross-reactivity against MRSA. Upon intestinal colonization, the intestinal fungus Candida albicans influences T cell polarization towards a Th17 phenotype in the spleen and peripheral lymph nodes which provided protection to the host against systemic candidemia. Interestingly, this induction of protective Th17 cells, increased IL-17 and responsiveness in circulating Ly6G+ neutrophils also protected mice from intravenous infection with MRSA, indicating that T cell activation and polarization by intestinal C. albicans leads to non-specific protective responses against extracellular pathogens.

Shao TY, Ang WXG, Jiang TT, Huang FS, Andersen H, Kinder JM, Pham G, Burg AR, Ruff B, Gonzalez T, Khurana Hershey GK, Haslam DB, Way SS. Commensal Candida albicans Positively Calibrates Systemic Th17 Immunological Responses. Cell Host & Microbe. 2019 Mar 13;25(3):404-417.e6. doi: 10.1016/j.chom.2019.02.004. PMID: 30870622; PMCID: PMC6419754.

Reviewer #3 (Public review):

Strengths:

A strength of the work is the rigorous experimental design. Appropriate controls were executed and, in most cases, multiple approaches were conducted to strengthen the authors' conclusions. The conclusions are supported by the data.

The following suggestions are offered to improve an already strong piece of scholarship.

Weaknesses:

The correlation between female sex hormones and the elimination of S. aureus from the gut could be further validated by quantifying sex hormones produced in the four core genotype mice in response to colonization. Additionally, and this may not be feasible, but according to the proposed model administering female sex hormones to male mice should decrease colonization. Finally, knowing whether the quantity of IL-17a CD4+ cells change in the OVX mice has the potential to discern whether abundance/migration of the cells or their activation is promoted by female sex hormones.

In the Discussion, the authors highlight previous work establishing a link between immune cells and sex hormone receptors, but whether the estrogen (and progesterone) receptor is differentially expressed in response to S. aureus colonization could be assessed in the RNAseq dataset. Differential expression of known X and Y chromosome-linked genes were discussed but specific sex hormones or sex hormone receptors, like the estrogen receptor, were not. This potential result could be highlighted.

We appreciate the comment on the scholarship and thank the Reviewer for the insightful suggestions to improve this manuscript. We intend on measuring hormone levels and performing the recommended (or similar) experiments based on availability of reagents and mice during the revision period. We also apologize for not including references that address some of the Reviewer’s questions. Other research groups have compared the levels of hormones between XX and XY males and females in the four core genotypes model and have found similar levels of circulating testosterone in adult XX and XY males. No difference was found in circulating estradiol levels in XX vs XY- females when tested at 4-6 or 7-9 months of age.

Karen M. Palaszynski, Deborah L. Smith, Shana Kamrava, Paul S. Burgoyne, Arthur P. Arnold, Rhonda R. Voskuhl, A Yin-Yang Effect between Sex Chromosome Complement and Sex Hormones on the Immune Response. Endocrinology, Volume 146, Issue 8, 1 August 2005, Pages 3280–3285, https://doi.org/10.1210/en.2005-0284

Sasidhar MV, Itoh N, Gold SM, Lawson GW, Voskuhl RR. The XX sex chromosome complement in mice is associated with increased spontaneous lupus compared with XY. Ann Rheum Dis. 2012 Aug;71(8):1418-22. doi: 10.1136/annrheumdis-2011-201246. Epub 2012 May 12. PMID: 22580585; PMCID: PMC4452281.

Examination of the levels of estrogen, progesterone, and androgen receptors in our cecal-colonic lamina propria RNA-seq dataset is an excellent idea. We will add these analyses to the revised manuscript. We are planning additional experiments to better understand the contributions of hormones or their receptors and anticipate including such data in either a response letter or revised manuscript.