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Reviewer #1

This is an interesting and thorough study characterising human iPSC with hetero or homozygous mutation in pi3k pathway that lead to its hyper-activation. They prove that the increased stemness results from enhanced autocrine responsiveness to TGF signalling pathway. The main conclusions are well supported by the presented data. Cutting edge tools and bioinformatic analysis are adequately applied. I have only one important point:

1) Western blot based validation of TGF pathway activation in wt and mutant iPSCs will be helpful to strengthen the results based on bioinformatic data.

AUTHORS’ RESPONSE__:__ We thank the Reviewer for the positive evaluation of our work.

Functional validation of the signalling hypothesis is indeed important, and we did in fact already present supportive data. Current evidence suggests that SMAD2 is the main transcription factor mediating actions of the TGFb/NODAL pathway in an early developmental context [1,2], and we have shown increased phosphorylation of SMAD2 (S465/S467) in PIK3CAH1047R/H1047R iPSCs using RPPA in the two datasets shown in Fig.2.

We have attempted to demonstrate increased NODAL protein directly in PIK3CAH1047R/H1047R cells, but have been unsuccessful due to poor signal on immunoblotting. We thus opted for functional testing of our hypothesis using the experiment presented in Fig. 5, wherein TGFb (a surrogate for NODAL) is removed from the culture medium. Human iPSCs depend strictly on TGFb/NODAL for maintenance of NANOG expression and thus pluripotency [3,4]. Upon exclusion of TGFb/NODAL from the culture medium of normal human iPSCs, the early responses (prior to overt differentiation) are expected to be: (A) decreased NODAL expression, due to well-established autoregulation [2], then (B) a decrease in NANOG and ultimately POU5F1 (OCT3/4) mRNA levels (see also Introduction, lines 80-90). The evidence in Fig. 5 that PIK3CAH1047R/H1047R fail to exhibit these responses upon exogenous TGFb/NODAL removal supports the notion that these cells autonomously sustain TGFb/NODAL signalling.

For improved clarity, we have also added the following information to the revised manuscript:

lines 202-205: “This is consistent with strong NODAL mRNA upregulation and increased pSMAD2 (S465/S467) in PIK3CAH1047R/H1047R iPSCs in the current study (Dataset S2 and RPPA data in Fig. 2, respectively), and with prior evidence of activation of the NODAL/TGFb pathway in homozygous PIK3CAH1047R iPSCs.”

Reviewer #2

In this manuscript, Madsen et al have investigated the role of heterozygous versus homozygous PIK3CAH1047R gain-of-function mutation at maintaining stemness of induced pluripotent stem cells (iPSCs). The authors have performed high-depth RNAseq, proteomic, and RPPA analyses to show that biallelic PIK3CA alterations induce stronger activation of the PI3K signaling axis, compared to monoallelic mutations. The authors claim that a higher PI3K signaling dose activates the NODAL/TGF-b pathway, which in turn supports stemness in an autocrine fashion. These are important findings, however, the manuscript and its conclusions can be improved.

AUTHORS’ RESPONSE__:__ We thank the Reviewer for acknowledging the importance of the work and for their constructive suggestions for improvements.

The authors have described the role of PIK3CAH-1047R gain-of-function mutation in cancer and overgrowth syndromes. However, cancer associated somatic mutations in PIK3CA are mostly heterozygous. Similarly, PIK3CA related overgrowth syndromes (PROS) are caused by post-zygotic mosaic PIK3CA activating mutation. As such, the relevance of homozygous PIK3CA alterations to these pathological conditions is unclear. The authors should elaborate on the biological implications of their findings.

AUTHORS’ RESPONSE__:__ We disagree with the Reviewer’s comment which implies that homozygous PIK3CA mutations are not relevant to many cancers. In our previous work [5], we provided evidence that many human cancers harbour multiple PIK3CA mutant alleles. Specifically, among cancers with a unique PIK3CA mutation, approximately 50% exhibit multiple copies according to allele copy number analysis. We further demonstrated that a substantial proportion of cancers have multiple different PIK3CA variants or additional oncogenic ‘hits’ within the pathway. These findings have been supported by other recent high-profile papers [6–8]. Such multiple alterations increase activity of the PI3K pathway beyond the level seen with heterozygosity alone [5,6]. This substantial body of literature renders our PIK3CAH1047R iPSC model system highly relevant for studying disease-relevant, dose-dependent oncogenic PIK3CA activation.

The Reviewer is correct, however, that PROS is caused by postzygotic heterozygous PIK3CA mutations almost exclusively. Observations in homozygous cells are therefore not directly relevant to the pathogenesis of PROS. On the other hand, the heterozygous cells are closely relevant, being human, carefully matched with isogenic controls, and unperturbed by further manipulations such as artificial immortalisation. Our prior studies demonstrated no clear phenotypes in heterozygous cells in the iPSC differentiation paradigm, despite the rock solid causal nature of heterozygous mutations in PROS. This negative finding, surprising given the dramatic PROS phenotypes, is very important in understanding how best to create disease-relevant PROS models. One intent of the current study was to increase the sensitivity of our transcriptomic analysis, and to combine this with proteomic studies to determine if heterozygous cells really do not exhibit a phenotype. We now show that there are indeed faint echoes in heterozygous cells of the dramatic changes in homozygous cells. We believe that the human growth phenotype is a summative consequence of such small differences in growth behaviours sustained over months and years, highlighting how subtle difference in signalling can lead to dramatic human growth consequences across the lifecourse. Similar observations were also recently made following systematic analyses of oncogenic RAS mutations [9]. The new information we present about heterozygous PIK3CAH1047R cells, while much less “showy” than the cancer-relevant behavious of homozygous cells, we thus contend is very important for understanding of the PROS phenotype and its experimental modelling. To emphasise this point, we have added the following statements to the abstract and discussion, respectively.

• lines 56-57: “This work illustrates the importance of allele dosage and expression when artificial systems are used to model human genetic disease caused by activating PIK3CA mutations.”
• lines 104-106: “We discuss the implications of our findings for understanding and modelling developmental disorders and cancers driven by genetic PI3K activation.”
• lines 333-340: “Finally, our observations are important for future studies seeking to model human PIK3CA-related diseases. The modest changes observed in heterozygous PIK3CAH1047R cells, in sharp contrast to the radical transcriptional alterations in homozygous cells, emphasise the importance of careful allele dose titration when artificial overexpression systems are used to model disorders caused by genetic PIK3CA activation. Our findings in heterozygous cells are also a reminder that very small effect sizes in cellular systems may summate and result in major human phenotypes over a life course. That such minor changes are found in a cellular study of a rare and severe disorder emphasises the challenges of modelling much more subtle disease susceptibility conferred by GWAS-detected genetic associations, where cellular effect sizes are likely to be smaller still.”

  The role of biallelic PIK3CA mutation is reminiscent of compound mutations in PIK3CA which have also been shown to increase PI3K signaling output. However, double PIK3CA mutations confer enhanced sensitivity to PI3K inhibition (Toska et al. Science 2019). Could the authors kindly speculate on this discrepancy.

AUTHORS’ RESPONSE: We emphasise first that PIK3CAH1047R/H1047R cells do respond to BYL719 at the signalling level, as demonstrated previously [5] and in the manuscript (revised Figure S5; see also additional Western blot below). Our point is that the cells have undergone a switch to self-sustained stemness. That is, while PIK3CA activation was the driver of the initial change in cell state, the induced stemness phenotype is no longer reversed by removal of that trigger, with our data suggesting that this is now driven by self-sustained TGFb/NODAL signalling. This is in line with the role of this pathway in the maintenance of the pluripotent state. We speculate that this may be important in a cancer context where surviving stem cells may permit cancer persistence after toxic therapies, even if short term growth of tumours is reduced by agents such as PI3K inhibitors.

Our data are not directly comparable to prior cellular data, for example in Vasan et al. [6], due to: (a) use of different cell model system and (b) assessment of different functional responses. We would also sound some methodological notes of caution re some of the prior studies alluded to, as potentially confounding differences in growth rate in the cells studied was not corrected for. It is well-established that IC50 and Emax values depend on cell division rates, and failure to correct for this can result in artefactual correlations between genotype and drug sensitivity (see, e.g., Hafner et al. Nature Methods 2016: “Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs” [10]**).

Similarly, the p110 alpha specific inhibitor, alpelisib, is highly effective against PIK3CA-mutant ER+ breast cancer and PROS. As such, the clinical relevance of the insensitivity of homozygous PIK3CA mutation to PI3K inhibitors is unclear.

AUTHORS’ RESPONSE__:__ Efficacy of Alpelisib in PROS is currently supported only by unregistered observational studies, but is nevertheless striking. It is not relevant to our findings in homozygous cells, as the Reviewer has previously observed, however.

As for cancer, in a randomised phase 3 trial that compared Alpelisib/BYL719 with fulvestrant to fulvestrant alone, the overall response (irrespective of PIK3CA mutant status) was indeed greater with the combination treatment (26.6 % vs 12.8 %), with a hazard ratio of 0.65 (95% CI, 0.5 to 0.85) in patients with PIK3CA-mutant caners versus a hazard ratio of 0.85 (95% CI, 0.58 to 1.25) in those without a PIK3CA mutation [11]. This trial demonstrated the utility of additional PIK3CA mutant-centric stratification, but a substantial proportion of patients with PIK3CA-mutant tumours (>50%) did not benefit from the BYL719 and fulvestrant combination [11]. However, these observations are not directly relevant to this manuscript and are instead included in a separate manuscript focused on PI3K signalling and stemness in human breast cancers (preprint [12]**).

Figure 2: The authors have performed RPPA analysis in the presence of 100 nM BYL719. Alpelisib is commonly used at 1 uM concentration for in-vitro experiments, and has a cMax of ~5 uM. We suggest the authors perform western blot analysis to confirm the results of RPPA.

AUTHORS’ RESPONSE__:__ We carefully chose the optimal concentration of BYL719 to preserve inhibitor selectivity, and to avoid undue toxicity and confounding off-target effects, rather than copying the dose “commonly used”. The Cmax is not relevant to our use of BYL719 in the current study as a precise tool compound. We refer the Reviewer to the known pharmacological characteristics of this compound [13,14]. According to available evidence, it is only a selective PI3Kα inhibitor at concentrations 250 nM (Table below adapted from Ref. **[13]; for formatted version, please see PDF version: https://osf.io/ecmhr/)

Enzyme

In vitro IC50 for NVP-BYL719 (nM)

PI3Kα

4.6 +/- 0.4

PI3Kα-H1047R

4.8 +/- 0.4

PI3K**b

1156 +/- 77

PI3K**d

290 +/- 180

PI3K**g

250 +/- 140

PI4K**b

571 +/- 42

We have previously demonstrated (Fig. 2C in Ref. [5]) that 100 nM BYL719 is sufficient to restore pAKT (S473) levels in both heterozygous and homozygous PIK3CAH1047R to levels observed in WT cells. This is consistent with the RPPA data reported in the current work (Fig. 2B). Of note, while 500 nM BYL719 completely ablates pAKT irrespective of genotype, we previously noted substantial toxicity [5], precluding use of this or higher doses of BYL719 in our model system. This is in line with a recent Nature Cell Biology study by Yilmaz et al. ([15]) which demonstrated the essential growth-promoting role of the PI3K pathway in human pluripotent stem cells; Yilmaz et al. also demonstrate that compared to somatic cells (fibroblasts), human pluripotent stem cells suffer dramatic effects on growth/survival in response to Torin1/rapamycin [15], overall suggesting that this cell type is exquisitely sensitive to inhibition of the PI3K/AKT/mTOR pathway.

In the present study we have also confirmed that 250 nM BYL719, used for Fig. 5 experiments, has worked as expected at the level of pAKT (S473) as shown in the below Western blot (see also revised Fig. S5; please access PDF version to view Western blot: https://osf.io/ecmhr/)

Figures 3 and 4: The authors should expand their RNAseq analysis to demonstrate enrichment of stemness and TGFb signaling in homozygous mutant cells compared to heterozygous cells.

AUTHORS’ RESPONSE__:__ We thank the Reviewer for this suggestion. The unsupervised MDS plot (Fig. 1A) clearly demonstrates the overlap between wild-type and heterozygous cells, strongly suggesting functional concordance and consistent differences to homozygous counterparts. Indeed, the below count table illustrates that the majority of differentially expressed genes in homozygous versus wild-type cells are also differentially expressed in homozygous versus heterozygous cells, including the direction of the change (please access the PDF version for formatted table: https://osf.io/ecmhr/)

Comparison

Differentially expressed gene count

HOMvsWT

5644

HOMvsHET

5764

HOMvsWT AND HOMvsHET

4825 (2300 upregulated; 2525 downregulated; 1 discordant)

We have now performed additional fast gene set enrichment analyses (fgsea; shown below - please access PDF version to view figure: https://osf.io/ecmhr/) using the R package fgsea ([16]) and 14 of the Broad Institute’s 50 Hallmark Gene Set Collection [17], including manual addition of the PLURINET signature [18]. The 14 gene sets were chosen based on their relevance to answering the Reviewer’s question as well as their connection to PI3K signalling. Fold changes for all expressed genes were included in the analyses, without further thresholding in order to minimise bias.

The results for homozygous vs wild-type comparisons are concordant with our upstream regulator analyses using IPA; as expected, TGFb signalling and PI3K signalling are among the top positively enriched (NES > 1) in comparison between homozygous and heterozygous cells. Unsurprisingly, however, the strength of the enrichments are lower when comparing the two PIK3CAH1047R genotypes.

We are not convinced that including these surplus data will add value to the manuscript and its main message, however we will leave this decision to the discretion of the Editor (please also refer to our response to the subsequent question from Reviewer 2). Moreover, these data will remain visible in the publicly available rebuttal document.

The authors should confirm the results of pathway analysis in vitro to show that homozygous PIK3CA mutation confers increased stemness compared to heterozygous mutation.

AUTHORS’ RESPONSE__:__ This was a key finding in our previous publication [5]. The aim of the current study was to interrogate this phenomenon further through high-depth transcriptomic/signalling analyses.

Figure 5: Kindly provide direct evidence demonstrating that increased PIK3CA signaling output induces NODAL expression in this experimental setting.

AUTHORS’ RESPONSE__:__ We have consistently demonstrated increased NODAL mRNA expression (RNAseq data, Fig. S4 and Ref. [5]). Unfortunately, we have been unsuccessful in attempts to obtain good quality immunoblots for NODAL protein in PIK3CAH1047R/H1047R cells (as noted in response to Reviewer 1). We note, in fact, that such documentation of NODAL protein levels, while not unprecedented, is fairly rare.

Also, please normalize gene expression data to WT cells so it is easy to visualize the changes in NODAL and NANOG expression in homozygous and heterozygous mutants compared to WT iPSCs.

AUTHORS’ RESPONSE__:__ It is arithmetically more precise to normalise to the highest expression (i.e. that of PIK3CAH1047R/H1047R cells) – thereby avoiding artificial inflation of fold-changes when normalising to very low levels of expression. Ultimately, the relative levels calculated – and the increased expression of NODAL in PIK3CAH1047R/H1047R cells – are identical visually. Only the entirely arbitrary units change. Thus we do not deem normalisation to WT to be necessary or to add value to the analysis.

Kindly quantify Fig. S5.

AUTHORS’ RESPONSE__:__ These brightfield micrographs were taken as part of routine practice to monitor cell health during maintenance and experimentation, and are suboptimal for direct quantitation due to uneven illumination background and lack of whole-well imaging. Nevertheless, we have now undertaken quantification as the Reviewer suggests, using individual images taken during independent experimental replicates. The results have been added to Fig. S5 and support our assertion that 250 nM BYL719 had a growth inhibitory effect in homozygous PIK3CAH1047R iPSCs. All raw images and associated data have been uploaded to the Open Science Framework (https://osf.io/hbf7x/). The following short method section detailing the image analysis algorithm has also been included in the revised supplementary material:

“Colony size quantitation from light micrographs

Routine cell culture light micrographs were acquired on an EVOS FL digital inverted microscope (AMF4300, Thermo Fisher Scientific) using the 4X or 10X objective (final magnification 40X and 100X, respectively). For quantitation, 4X images were used for colony segmentation with Definiens Developer XD software. Background was detected using a contrast threshold; for this each pixel was compared to those in the surrounding 24 pixels (i.e. a 5x5 pixel box), and pixels with low contrast (between -50 and +50) were classified as background. Remaining pixels were classified as colonies, and any holes (pixels that were not initially classified as being part of the colony due to low contrast) were filled. Edges of the resulting colonies were smoothened by shrinking and then growing the colonies by 2 pixels. Finally, colonies less than 2000 pixels in size were reclassified as background. The area of the resulting colonies could then be measured and averaged over each field of view.”

Reviewer #3

In this manuscript by Madsen et al., a comparison of the transcriptome and proteome in heterozygous and homozygous PIK3CAH1047R human pluripotent stem cells mutants is presented. The authors demonstrate marked alterations in expression at both the protein and RNA level of homozygous mutants compared to wildtype, while heterozygous lines exhibit only minor changes. Multiple analytical approaches are employed to investigate network alterations, leading the authors to suggest a TGFβ-mediated rewiring of key pluripotent genes to induce a state of sustained stemness. Madsen et al. conclude with a set of experiments to functionally implicate NODAL/TGFβ autocrine signalling in PIK3CAH1047R dose-dependent stemness. The key conclusions are not convincing. While the unbiased omics approach sets up this study well, the study suffers from a lack of convincing functional assays (cell biological assays) to test their model and tease apart a phenotype for the het cells. More robust functional experiments are required to support the finding the NODAL/TGFβ signalling mediates the self-sustained stemness, particularly because this is the major novel finding distinguished from the authors previous work.

AUTHORS’ RESPONSE__:__ We thank the Reviewer for their detailed critique. Our perspective on the robustness and novelty of our findings diverges from that of the Reviewer, however, as we elaborate on in more detail below.

While the authors present a comprehensive omics investigation into alterations between wild type, homozygous, and heterozygous mutants, the critical functional experiments are lacking. In Figure 5, the authors seek to support the role of TGFβ in mediated stemness in the homozygous mutants, however, are not able to directly deplete TGFβ due to technical limitations of the culture conditions. Consequentially, the experiments are primarily built on the use of NODAL withdrawal and stimulation. The data presented thus implicate NODAL in the stemness phenotype, but it's not obvious TGFβ is substantially involved, particularly considering the inhibitor subsequently employed also inhibits NODAL type 1 receptors.

AUTHORS’ RESPONSE__:__ NODAL and TGFb activate shared signalling pathways downstream from their respective receptors, and indeed they (as well as Activin) can be used interchangeably in stem cell culture, which is common practice [19–21]. Commercially available Essential 8/TeSR-E8 is supplemented with TGFb not NODAL; therefore the factor we have removed is TGFb, prior to any controlled introduction of NODAL (based on strong upregulation of its mRNA in PIK3CAH1047R/H1047R). Any residual TGFb-like ligands will be contributed by Matrigel as outlined in the text (lines 247-251). It is well-established that “NODAL/TGFb signalling” denotes signalling through SMAD2/3/4 (as opposed to BMP signalling through SMAD1/5/8), and this is how we use the term throughout the manuscript. Accordingly, it is functional activation of the “NODAL/TGFb signalling pathway” that we investigate (see also response to Reviewer 1, p.1).

In summary, we seek not to make a distinct point about TGFb, but rather refer to NODAL/TGFb signalling as a matter of biochemical correctness. For clarity, we now replace mentions of “TGFb signalling” with “NODAL/TGFb signalling” throughout the revised manuscript. We have also revised the legend for Figure 3 to make this clearer.

Furthermore, there is a paucity of readouts for stemness. For example, a more convincing narrative would include additional expression markers of the core pluripotency network (e.g. OCT4, SOX2, etc.) as well as functional readouts (e.g. NODAL withdrawal and assessment of differentiation) after NODAL stimulation/depletion and comparing across genotypes. Overall, the primary conclusions of this work are not well-evidence by the presented data and the authors should consider additional functional experiments or reframing the narrative.

AUTHORS’ RESPONSE__:__ We chose the current strategy because we wanted to capture the earliest changes after depletion of NODAL/TGFb/ signalling, prior to any signalling rewiring triggered by differentiation. In fact, we believe that a strength of this study is our observation of differences in critical stemness markers in spite of the short time course. To aid non-expert readers we offered a primer on stemness genes and rationale for the markers chosen in the existing introduction (lines 80-90).

We have further assessed additional stemness and differentiation marker genes in two independent homozygous PIK3CAH1047R cell lines using a high-throughput pluripotent stem cell scorecard (Fig. S4). This replicates the effect on cell marker genes documented by RT-qPCR in Fig.5, while also showing additional reductions in genes that were upregulated in homozygous PIK3CAH1047R cells (MYC, GDF3, FGF4) and which have previously been shown to be highly expressed in pluripotent stem cells (we have now added this additional clarification to the legend of Fig. S4) [22]. Despite the short term treatment, these data also show that no other treatment but SB431542 is capable of triggering expression of early neuroectoderm markers (CDH9, MAP2 and PAPLN) [23], prior to overt morphological changes in the cultures (Fig. S5; higher resolution images are also available via The Open Science Framework: https://osf.io/hbf7x/). Neuroectodermal gene expression is expected upon inhibition of TGFb signalling in human pluripotent stem cells [24,25].

A key conclusion of this study is there is a dose-dependent stemness phenotype. As this is not explicitly defined, to this reader, it would imply a graded response between wild type, heterozygotes, and homozygotes in the phenotypic and molecular characteristics. However, as is noted particularly in the omics components of the manuscript, there is in fact "near-binary" alteration in the assayed characteristics. Again, this should be qualified more explicitly, but it is more consistent with the data, which suggests the heterozygotes behave very similarly to the wild types, while homozygotes have substantial alterations. I would suggest the authors consider renaming their descriptions, removing "near-binary" and "dose-dependent" to something like "dose-threshold." This suggests after X threshold of oncogenic PI3K signalling, substantial alterations occur; under this threshold (e.g. hets), changes are marginal. In the event however that there may be a more "dose-dependent" effect, I would expect the transcriptomic and proteomic changes observed in the heterozygous cell lines should be seen in the homozygous cell lines (of which they are likely in greater in magnitude in addition to other changes).

AUTHORS’ RESPONSE__:__ This appears to us to be largely a matter of semantics. In talking of “dose dependency” we were certainly not implying a graded affect (as the Reviewer points out, our are findings are far from this, suggesting a sharp threshold of dose which triggers widespread changes), and indeed nothing in these words strictly suggests this interpretation. Nevertheless we are sensitive to the fact of the Reviewer’s interpretation of the term, and mindful that this might be shared by other readers. On the other hand talking of a “near-binary” effect seems to us to be an accurate description of our findings. We have edited the manuscript to minimise ambiguity with the following changes:

• line 49 “dose” replaced with “strength”: “We demonstrate signalling rewiring as a function of oncogenic PI3K signalling strength, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFb”
• line 102: “This work provides in-depth characterisation of the near-binary PI3K signalling effects seen in hPSCs ….”
• lines 195, 198, 317: inserted “allele dose-dependent” We would also like to take issue with the case that the Reviewer seems to be making that a more graded change in gene expression across heterozygotes and homozygotes is to be expected. As mentioned in the manuscript (lines 206-210), there is evidence for NODAL/TGFb pathway activation in heterozygous cells. Nevertheless given the known temporal, context- and dose-dependent effects of this pathway [1,2,26,27] and, importantly, the widely described biological properties of developmental systems (featuring positive feedback loops, bistability and hysteresis; see Ref. [28,29]), we have no reason to expect that transcriptomic and proteomic changes observed in homozygous cell lines will be reproduced in heterozygous cell lines.

The manuscript would benefit from more direct comparisons between the heterozygotes and homozygotes.

AUTHORS’ RESPONSE__:__ Please refer to the additional data provided in response to a similar question by Reviewer 2.

Further to the above point, as the marginal phenotype observed in heterozygotes is a critical point in this paper, the authors would benefit from including heterozygote lines in the functional experiments presented in Fig 5. Inclusion of the hets in these experiments would instill confidence in this reader that the marginal molecular alterations characterized at the proteomic and transcriptomic level is reflected in the lack of functional stemness-sustaining behaviour.

AUTHORS’ RESPONSE__:__ The lack of stemness-sustaining behaviour in the heterozygous clones was demonstrated across multiple different experiments in our previous work, and further functional studies of early differentiation in these cells seemed a poor use of resource and very unlikely to give useful insights. Given the major disease phenotype associated with the same genetic change (PROS), the relative lack of phenotype in heterozygous cells was surprising and holds obvious implications for disease modelling (see also response to Reviewer 2, pp.2-3), and for how model systems are “calibrated” against human developmental disease. The aim of the current work was to:

1. • Determine whether increasing the depth of signalling and transcriptomic analyses would unmask small but important changes in heterozygous mutants that might have been missed in prior studies (i.e. we actively aimed to increase the power of the study for identification of subtle changes) and *
2. • To characterise in greater depth the signalling and transcriptional changes underpinning the robust threshold effect observed for self-sustained stemness driven by PIK3CAH1047R/H1047R. We would further observe that PROS does not feature obvious qualititative errors in tissue specification, but rather excessive growth of more or less normally differentiated tissues. We conceptualise this as reflecting a small incremental growth advantage in normally differented tissues of certain lineages that summates to create a major disease phenotype over months and years.*

Thus, without the functional and mechanistic experiments alluded to above, the claims/ conclusions are speculative. In particular, the cancer narrative is irrelevant to the study. Considering both the lack of conclusive differentiation experiments or relevant breast cancer experiments, the discussion on differentiation therapy for breast cancer should be removed.

AUTHORS’ RESPONSE__:__ The reference to cancer links to a computational study of human breast cancers where we specifically looked at the relationship between strength of PI3K signalling and ‘stemness’ [12], both measured using established transcriptional indices. We have included the bioRxiv reference in our revised manuscript (see l.337). While there is an element of speculation in this cancer observation, we do feel it is important and grounded in this and the BioRXiv study, and would prefer to maintain it. However, if editors take a different view it can be removed.

Reproducibility is a concern for this study. The authors should perform more replicates on their experiments (focusing on technical replicates of the lines employed to discern technical vs biological variability). A challenge in reading this manuscript is understanding which replicates were used for which experiments, and whether they are technical or biological (i.e. different lines). While some of the figure legends note this information, it would be helpful to provide clarity throughout the text. In addition, it should be noted that some experiments (e.g. the RPPA analysis in Fig 2B and Fig S3B) show substantial variability between replicates, but because it appears only a single technical replicate from two different cell lines was used, it is impossible to distinguish whether the variability is of a biological or technical nature. The authors would do well to focus on collecting more technical replicates of fewer biological replicates, and then expand to include more biological replicates if initial biological variation is observed.

AUTHORS’ RESPONSE__:__ We strenuously disagree with the Reviewer on this point. Throughout this manuscript, we have been transparent and thorough in reporting how experiments were performed, including the number of both biological and technical replicates. Representative examples include:

Legend to Figure 2A (RPPA dataset in growth-replete conditions): “The data are based on 10 wild-type cultures (3 clones), 5 PIK3CAWT/H1047R cultures (3 clones) and 7 PIK3CAH1047R/H1047R cultures (2 clones) as indicated.”

Legend to Figure 5: “The data are from two independent experiments, with each treatment applied to triplicate cultures of three wild-type and two homozygous iPSC clones.”

Specifically to address the RPPA studies, and as is clear from the Figure 2 legend, we initially performed RPPA analyses in growth factor-replete conditions with extensive technical and biological replication, arguing against the Reviewer’s point. To aid interpretation, we opted for summarising this large dataset in Venn diagrams (following extensive limma-based statistical analysis, including correction for multiple comparisons and sample interdependence as advised in Ref. [30]). If the Reviewer deems it valuable, we could include a heatmap overview as shown below:

[To view figure, please access PDF version of this rebuttal on https://osf.io/ecmhr/]

We took the view that the above representation, while comprehensive, is not particularly informative to the reader. All individual data points for both total and phosphoproteins – with and without normalisation – are plotted as part of separate barplots in the accompanying RNotebook (https://osf.io/d9tca/). These clearly demonstrate that the technical and biological variability in canonical PI3K signalling responses at the level of AKT and immediately downstream of AKT is very low. The same applies to the increased phosphorylation of SMAD2 (S465/S467) in PIK3CAH1047R iPSCs. We include two examples below, and would be happy to include the link to the above RNotebook in the respective Figure legend if the Reviewer deems this helpful.

[To view figure, please access PDF version of this rebuttal on https://osf.io/ecmhr/]

The interpretation of the second RPPA experiment (Fig. 2B) in growth factor-depleted conditions is focused entirely on these responses due to their consistency across both datasets (further supported by low-throughput signalling analyses in the previous PNAS publication).

We had made all raw data and guided analysis scripts for the above RPPA dataset publicly available, and the same is true for all original data as highlighted in the Materials & Methods section. Thus we strongly believe that readers have the opportunity to assess our work and reproduce our analyses/conclusions fully should they wish to do so.

• Finally, we noted in the initial PNAS paper describing these models that we derived and worked with up to 10 independent homozygous PIK3CAH1047R clones, as well as with 3 and 4 independent heterozygous and wild-type clones, respectively. This exceeds the common use of 2 clones (if at all mentioned) in many similar studies in the stem cell literature (e.g. Ref. [31–34]). In our view, derivation of more than two independent clones is crucial for reproducibility in gene editing studies given substantial variability arising from genetic drift [35,36]. We have consistently shown the phenotypic robustness of our mutant clones across the two studies; note, for example, the low technical and biological variability in both heterozygous and homozygous mutants in the transcriptomic data in Fig. 1A. As noted in the manuscript, the high-depth RNAseq data analysis was performed in different clones and independently of the RNAseq reported in Ref. [5], yet yields highly similar results and confirms transcriptional rewiring of PIK3CAH1047R/H1047R iPSCs.*

Throughout the text, the authors frequently reference their previous study in PNAS and often the lines of what is novel in this paper vs. reproduction of previous findings is blurred. The authors would benefit from reducing the frequency of referencing their previous study and focusing on emphasizing the novelty of the present findings.

AUTHORS’ RESPONSE__:__ We have carefully reviewed all instances of citation of our previous study in the manuscript and have reduced their numbers to improve focus on the current findings as suggested. As noted above, however, the current study builds closely upon the findings of the previous work, and referring to these to put the current work in context is important. Indeed, this is reflected in some of the reviewers’ collective comments and questions which are answered by the prior study. We have carefully reviewed the places in which we have cited our previous study and note that except for 2 citations in the Introduction and 3 more in the Discussion, all remaining citations are in the context of linking new and old data, which we believe is important for clarity as suggested by the reviewers. However, if editors take a different view we can minimise this and reduce the number of citations.

Without functional assays to complement and test their models, this manuscript is not a significant advance.

AUTHORS’ RESPONSE__:__ While we take the Reviewer’s point that further studies could have strengthened robustness of the evidence supporting a mediating role of NODAL/TGFb signalling in PI3K-driven stemness, we think this assertion is far too sweeping, and neglects numerous facets of the study of use and interest to several fields (as agreed by the other reviewers). To recapitulate some key points of interest/use of this study:

• Using a carefully derived PIK3CAH1047R iPSC model system and pharmacologically relevant doses of a recently approved PI3Ka-selective inhibitor, we demonstrate that the efficacy of the latter can depend on the strength of PI3K pathway activation and phenotype under investigation – despite expected downregulation of PI3K signalling by Alpelisib, the stemness phenotype is not reversed.
• We link this to self-sustained TGFb signalling in cells with strong PI3K activation by homozygous PIK3CAH1047R The link between the two pathways and the underlying rewiring are likely to be relevant in other contexts, as observed recently in a breast epithelial model system [37]. Given similarity between human pluripotent stem cells and cancer cells, our findings are of wider relevance.
• Aberrant PI3K activation has been associated with numerous pathologies, so it is important for the field to have well-characterised model systems with endogenous expression of one of the most common PIK3CA mutations. Our thorough characterisation of PIK3CAH1047R iPSCs validates one such model.
• To our knowledge, this is the first study to provide a comprehensive and integrated characterisation of isoform-specific PI3K signalling and transcriptomic changes in human pluripotent stem cells. This is important because current knowledge of PI3K signalling in human PSCs is largely based on extrapolation of findings from mouse embryonic stem cells, with many previous studies relying on high concentrations of the non-specific pan-PI3K inhibitor LY294002 (the use of which has been discouraged by the PI3K signalling community [38]).

  I believe the narrative was written for pluripotent stem cell biologists but without robust functional and quantitative cell biological assays to test their models, I don't anticipate stem cell biologists will be very interested.

AUTHORS’ RESPONSE__:__ The Reviewer is incorrect in his/her assertion about the target audience. PI3K signalling plays a key role in numerous disease and physiological processes as well as in development, and is of broad interest to cancer biologists, genetecists, rare disease biologists, biochemists, cell signallers, and endocrinologists among many others. Indeed we started with a primary focus on disease modelling (cancer, PROS) rather than stem cell biology, but because our findings are significant for the role of PI3K in stem cell biology as well as for these diseases, we aimed to make findings accessible across many of these readers. We refer the Reviewer to our previous response with regards to the significance of this work.

**Minor Comments:**

Consider adding gridlines to the MDS plots for clarity of read

AUTHORS’ RESPONSE__:__ This is a matter of taste, and as we honestly can not see how it would enhance appreciation of the very clear clustering, we have decided to leave the plot in its current form.

In Fig S2, some of the in-figure labelling is incorrect

AUTHORS’ RESPONSE__:__ We thank the Reviewer for spotting this. We believe the labelling error to be corrected now and we have further tried to streamline the plot headings, but please do let us know if there is something else which we may have missed.

In Fig S1C, the authors note poor correlation in the heterozygotes between this and a previous study. It would be helpful to qualify this discrepancy, as it is potentially concerning.

AUTHORS’ RESPONSE__: The sensitivity to detect differential gene expression is high for large fold changes (as seen in PIK3CAH1047R/H1047R mutants) in transcriptomic studies, but declines rapidly for fold changes in expression lines 126-131: “The magnitudes of gene expression changes in PIK3CAH1047R/H1047R cells correlated strongly with our previous findings (Spearman’s rho = 0.74, p WT/H1047R iPSCs (Fig. S1C), as expected given the smaller number and lower magnitude of observed gene expression changes in heterozygous cells, and the lower depth of previous transcriptomic studies__.”*

Line 208, the authors state that the small p-value for the homozygotes is suggestive of a dose-dependent effect. This is not the case; it simply suggests a greater probability of the effect being non-random.

AUTHORS’ RESPONSE__:__ The Reviewer is formally correct, and we apologise for the imprecision of our language. Nevertheless biological effect size is pertinent to the p value determined, and so our statement, while requiring an inductive leap from the reader, is not wholly invalid. To tidy this up and improve precision we have reworded as follows:

lines 215-217: “This is in keeping with the much lower effect size in heterozygous cells, and consistent with a critical role for the TGFbeta pathway in mediating the allele dose-dependent effect of PIK3CAH1047R in human iPSCs.”

What does the height in Fig 4B correspond to? It would perhaps be of value to scale nodes based on the significance value.

AUTHORS’ RESPONSE__:__ 4B illustrates hierarchical clustering of the module eigengenes - the height corresponds to similarity of gene expression. We clarify this in the revised manuscript.

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This is very interesting!

Great observations

Author Response

We thank the Editor of eLife f or kindly considering our manuscript for publication and for soliciting three peer reviews. We note that the reviews were positive for the most part. We sincerely believe that the key criticisms arise regrettably from a seeming misunderstanding of the motivation and context of our work – one that we hoped was a candid presentation of available data for tarantulas and the methods used. We provide detailed responses to the reviewers’ concerns below. We further note that our manuscript has since been published with minimal changes (Foley et al. 2020 Proceedings of the Royal Society B 287: 20201688, doi:10.1098/rspb.2020.1688).

Tarantulas belong to an enigmatic and charismatic group with a nearly cosmopolitan distribution and intriguingly show vivid coloration despite being mostly nocturnal/ crepuscular. Using a robust phylogeny based on a comprehensive transcriptomic dataset that includes nearly all theraphosid subfamilies (except Selenogyrinae), we performed both discrete and continuous ancestral state reconstructions of blue and green coloration in tarantulas using modern phylogenetic methods. Using phylogenetic correlation tests, we evaluated various possible functions for blue and green coloration, for instance aposematism and crypsis. Our results suggest green coloration is likely used in crypsis, while blue (and green) coloration show no correlation with urtication, stridulation or arboreality. Our findings also support a single ancestral origin of blue in tarantulas with losses being more frequent than gains, while green color has evolved multiple independent times but never lost. We comparatively assessed opsin expression from the transcriptomic data across tarantulas to understand the functional significance of blue and green coloration. Our opsin homolog network shows that tarantulas possess a rather diverse suite of regular arthropod opsins than previously appreciated.

While color vision in (jumping) spiders is relatively well studied, to the best of our knowledge, this is the first study to comparatively consider the identity of opsin expression across tarantulas, and in relation to the evolution of coloration. Our study challenges current belief (e.g., Morehouse et al. 2017 doi: 10.1086/693977 and references therein; Hsiung et al. 2015 doi: 10.1126/sciadv.1500709) that tarantulas are incapable of perceiving colors, at least from a molecular perspective and suggests a role for sexual selection in their evolution. This also adds to the growing body of knowledge on the complexity of arthropod visual systems (e.g., see Futahashi et al. 2015 doi:10.1073/pnas.1424670112, Hill et al. 2002 doi:10.1126/science.1076196).

In short, we believe our results are timely and pertinent broadly to sensory biologists, behavioural ecologists and evolutionary biologists as it is an exhortation for sorely needed behavioural and sensory experiments to understand proximate use of vivid coloration in this enigmatic group.

Summary:

This study offers some interesting data and ideas on colour evolution in tarantulas, building upon previous work on this topic. However, the reviewers judged that the insights are too taxon-specific and that several key conclusions are too speculative. There were also concerns about the methodology for trait scoring from photographs that the authors might consider going forward.

Reviewer #1:

This study investigates the evolution of blue and green setae colouration in tarantulas using phylogenetic analyses and trait values calculated from photographs. It argues that (i) green colouration has evolved in association with arboreality, and thus crypsis, and (ii) blue colouration is an ancestral trait lost and gained several times in tarantula evolution, possibly under sexual selection. It also uses transcriptome data to identify opsin homologs, as indirect evidence that tarantulas may have colour vision.

Otherwise, a few comments:

1) Given that data is limited for the family (only 25% of genera could be included in this study), it seemed a shame not to discuss further the variation in colour and habit within genera. Based on Figure 1 and supplementary tables, the majority of "blue" genera contain a mix of blue and not-blue (and not-photographed) species. Does this mean that blue has been lost many more times in recent evolutionary history? And how often are "losses" on your tree likely to be the result of insufficient sampling for the genus (i.e. you happen not to have sampled the blue species)?

First, the taxa in our robust and well-resolved phylogeny are representative of the major lineages within Theraphosidae, i.e., we have sampled nearly all theraphosid subfamilies (except Selenogyrinae). Our ideal is also to work with a more complete genus-level molecular phylogeny and corresponding color dataset for theraphosidae. However, this group is generally not well represented in museum collections (let alone in digitized collections), while the pet trade is focussed on only a select number of taxa. While we appreciate the reviewer’s concern that adding more taxa and corresponding data could potentially change the results, we believe that with a strong backbone phylogeny recovering the major branches, the results should not change all that much (For instance, cf. Hackett et al. 2008 10.1126/science.1157704 vs. Prum et al. 2016 10.1038/nature19417, where the initial Hackett et al. backbone is robust to increased sampling). Although the way trait losses are concentrated towards the tip suggests that using a genus-level phylogeny would perhaps show a few more recent trait losses, but unlikely to contradict an ancient origin of blue coloration at the base of this group, especially given the way the outgroups are polarized (i.e., outgroups also exhibit blue).

2) A key conclusion of the study is that sexual selection should not be discarded as a possible explanation for spider colour. However, there is very little detail given in the discussion to build this case. Do these spiders have mating displays that might plausibly include visual signals? How common are sexually-selected colours in spiders generally? Where on the body is the blue coloration (in cases where it is not whole body)? I also missed whether the images used are of males or females or both, or how many species show sexual dimorphism in colouration (mentioned briefly in the Discussion, but not summarised for species or genera).

We agree with the reviewer that we should have provided more information regarding sexual dichromatism in tarantulas, and on the images we used in the study (whether male/female). However, the location of blue coloration varies wildly with species – some species have blue chelicerae, blue abdomens, or blue carapaces while others are entirely blue. We also know very little about mating (and selection, if any) strategies in tarantulas, let alone the sensory ecology of this group. However, there is intriguing anecdotal information from one species (Aphonopelma) that they can be active as early as 4pm (Shillington 2002 Canadian J. Zoology, 80: 251-259, doi: 10.1139/z01-227), while some species show an intensification of color upon maturation, often a hallmark of sexual selection. Indeed, we believe that our work will incite broad interest on these intriguing questions.

3) A quick scroll through the amazing images on Rick West's site suggests that oranges and red/pinks are not rare in tarantulas. Perhaps the data is just not available, but it would be good to mention somewhere the rationale behind the blue/green focus, rather than examining all colours.

We agree. However, in the present study, we focused on blue and green colors because the data is readily available and we wanted to build upon the previous work by Hsiung et al 2015. Given that violet/blue and likely also some green coloration are structural in origin (Saranathan et al. 2015 Nano Letters, doi: 10.1021/acs.nanolett.5b0020; Hsiung et al. 2015), these hues are unlikely to fade or vary between individuals unlike diet acquired pigmentary coloration. Hence, these colors perhaps better lend themselves to analyses using digital photographs.

I suggest defining stridulating / urticating setae for non-specialist readers. I had to look these up to understand that they were involved in defence.

We thank the reviewer for this suggestion.

I notice the Rick West website says species IDs should not be made from photos alone. Is there a risk of misidentification for any photos?

We understand the reviewer’s concern. However, Rick West is an experienced arachnologist and quite knowledgeable in tarantula systematics and taxonomy (see https://www.tarantupedia.com/researchers/rick-c-west), which is why we endeavoured to use his website as extensively as possible without resorting to photos from hobbyists. We further validated the IDs with field guides, when in doubt.

The Results section would benefit from some more clear statements of key results. For example, phrases like "AIC values to assess the relationships between greenness and arboreality are reported in Table 3" could be replaced instead with a summary statement indicating what this table shows.

We agree and thank the reviewer for this suggestion.

In the Figure 1 caption I think there is a typo: 'the proportions of species with images that possess blue colouration (grey = no available images)" but should this say "grey = not blue"?

We apologize for the confusion. This is not a typo – this is in relation to Trichopelma, for which no images of described species were available, and so we cannot conclude that none of the taxa are blue/green.

142 - the lengthy discussion here of whether there is one or more mechanisms by which blue is produced in tarantulas, and the detailed criticism of Hsuing SEMs, seems a bit out of place given that the current study does not investigate the proximate mechanism of blue colouration but merely its presence.

We respectfully disagree. The core support for Hsiung et al.’s (2015) argument against sexual selection as a driver of color evolution in tarantulas comes from their structural diagnoses of the nanostructures responsible for the violet/blue structural coloration and their subsequent argument that a diversity of divergent nanostructures rather than convergence argues against sexual selection. While it is true that we did not investigate the proximate mechanism of blue coloration here, one of us (Saranathan et al. 2015) has already done so elsewhere. It appears that in insects and spiders, the bulk of the nanostructural diversity is across families and not within.

Table S6 - It is not clear to me how the values for predicted N orthologs were calculated.

This is mentioned in line 354 of our methods – “Per the ‘moderate’ criteria from the Alliance of Genome Resources (55), hits may be considered orthologous if three or more of the twelve tools in their suite converge upon that result”.

The Table S7 caption states: "A * indicates currently undescribed species with blue or green colour that can be confidently attributed to corresponding genus. However, as the described species exhibit no blue or green colour, we conservatively scored these as 0." Is this a conservative approach though? If they have been confidently assigned to genus, I don't understand why they would not be included.

This refers to the cases where a hitherto undescribed species possesses the blue or green color. However, even though the species has not formally been described, its placement in the genus is not in question. We have not included such undescribed species in our tabulated number of species per genus, as it is difficult to express any such undescribed species as a fraction of the total number of species in that genus.

Reviewer #2:

This paper presents a broad-ranging overview of tarantula visual pigments in relationship with the color of the spiders. The paper is interesting, well-written and presented, and will inspire further study into the visual and spectral characteristics of the genus.

We thank the reviewer for her/his/their kind words.

First a minor remark, Terakita and many others distinguish between opsin, being the protein part of the visual pigment molecule and intact light-sensing, so-called opsin-based pigment, often generalized as a rhodopsin. The statement of line 65, 'convert light photons to electrochemical signals through a signalling cascade' is according to that view strictly not correct. Furthermore, the presence of opsins in transcriptomes may be telling, but it is not at all sure that they are expressed in the eyes, if at all. As the authors well know, in many animal species some of the opsins are expressed elsewhere. It may be informative to mention that.

We thank the reviewer for this clarification. As for the regions of opsin expression, we very much agree – were it not for constraints of sample availability, we would also have preferred to sequence only the eyes and brain of various tarantulas that were all exposed to similar lighting conditions. However, we encouragingly see that our “leg only” transcriptomes have far fewer (often no) opsins as compared to the whole-body data.

The blueness or greenness feature prominently in the paper, but the criteria used for determining to which class a spider belongs are not at all sure. The Color Survey and Supplementary Table S2 refer to Birdspiders.com, but that requires a donation; not very welcoming. The other used sources are also not readily giving the insight or overview which material was sampled. I therefore think that the paper would considerably gain in palatability by adding a few exemplary photographs as well as measured spectra. Of course, I am inclined to trust the authors, but I would not immediately take color photographs from the web as the best material for assessing color data with 4-digit accuracy. Furthermore, the accessible photographs do not always show nice, uniform colors, so it might be sensible to mention which body part was used to score the animals. And finally, using CIE metric might infer to many readers that the spiders are presumably trichromatic, like us. Any further evidence?

We refer to the detailed description of our method for scoring blue or green coloration in tarantulas (l. 277-303). Briefly, we calculated ΔE (CIE 1976) difference values using between the images of each taxa against a suitable reference (average of green leaves, or Haplopelma lividum, the bluest taxa in our survey based on the b value of its images). We use the ΔE Lab values to perform quantitative ancestral state reconstruction, while we use ΔE b (for blue) and ΔE a (for green) to discretize the data for understanding trait gains and losses.

BirdSpiders.com only requires one to enter names of genera as search terms in order to see photos that we used. However, we agree could have provided some photos of exemplars. We do realise that using pictures is not ideal, as opposed to reflectance spectrophotometry (our ideal as well), which is why we limited ourselves to a single reputable source (BirdSpiders.com) for consistent images, whenever possible. However, acquiring sample material and reflectance of tarantulas is challenging. This group is generally not well represented in museum collections (let along in digitized collections), while the pet trade is focussed on only a select number of taxa and doing field work to collect specimens is fraught with moral and ethical issues (e.g., see https://www.nytimes.com/2019/04/01/science/poaching-wildlife-scientists.html). This study nevertheless represents a substantial improvement upon a recent high-profile work that used the OSX “color picker” function (Hsiung et al. 2015).

Indeed, available evidence on tarantula vision (including our opsin sequences) suggests tarantulas are likely trichromats (Dahl and Granda 1989 J. Arachnol., Morehouse et al. 2017) similar to jumping spiders (e.g., Zurek et al. 2015, doi: 10.1016/j.cub.2015.03.033), so we consider CIE as an appropriate color space for a putative tristimulus system in tarantulas (see also our response to Reviewer 3). Again, this underscores the need for future studies on the sensory biology and psychophysics of this enigmatic group.

Reviewer #3:

This neat paper continues the story of structural colour evolution in a group that is rarely appreciated for their ornamentation. The study uses colour & ecological data to model their evolution in a comparative framework, and also synthesises transcriptomic data to estimate the presence and diversity of opsins in the group. The main findings are that the tarantulas are ancestrally 'blue' and that green colouration has arisen repeatedly and seems to follow transitions to arboreality, along with evidence of perhaps underappreciated opsin diversity in the group. It's well-written and engaging, and a useful addition to our understanding of this developing story. I just have a few concerns around methods and the interpretation of results, however, which I feel need some further consideration.

We thank the reviewer for his/her/their kind words.

As the authors discuss in detail, this work in many ways parallels that of Hsiung et al. (2015). The two studies seem to agree in the broad-brush conclusions, which is interesting (and promising, for our understanding of the question), though their results conflict in significant ways too. Differences in methodology are an obvious cause, and they are particularly important in studies such as this in which the starting conditions (e.g. the assumed phylogeny or decisions around mapping of traits) so significantly shape outcomes. The current study uses a more recent and robust phylogeny, which is great, and the authors also emphasise their use of quantitative methods to assign colour traits (blue/green), unlike Hsiung et al.

We thank the reviewer for his/her/their appreciation.

1) This latter point is my main area of methodological concern, and I am not currently convinced that it is as useful or objective as is suggested. One issue is that the photographs are unstandardised in several dimensions, which will render the extracted values quite unreliable. I know the authors have considered this (as discussed in their supplement), but ultimately I don't believe you can reliably compare colour estimates from such diverse sources. Issues include non-standardised lighting conditions, alternate white-balancing algorithms, artefacts introduced through image compression, differences in the spectral sensitivities of camera models, no compensation for non-linear scaling of sensor outputs (which would again differ with camera models and even lenses), and so on (the works of Martin Stevens, Jolyon Troscianko, Jair Garcia, Adrian Dyer offer good discussion of these and related challenges). Some effort is made to minimise adverse effects, such as excluding the L dimension when calculating some colour distances, but even then the consequences are overstated since the outputs of camera sensors scale non-linearly with intensity, and so non-standardised lighting will still affect chromatic channels (a & b values). So with these factors at play, it becomes very difficult to know whether identified colour differences are a consequence of genuine differences in colouration, or simply differences in white balancing or some other feature of the photographs themselves.

We thank the reviewer for his/her/their carefully considered thoughts and for drawing our attention to the work of Martin Stevens, Jolyon Troscianko, Jair Garcia, and Adrian Dyer in this regard (e.g. Stevens et al. 2007 Biol. J. Linn. Soc. Lond., doi: 10.1111/j.1095-8312.2007.00725.x). These are fair points raised by the reviewer. We are indeed aware that there are clear drawbacks in working solely with photographs from online sources as opposed to optical reflectance data (our ideal), but we are sure that the reviewer appreciates how challenging it is to source specimens of tarantulas. It is for this reason that we restricted ourselves to photographs from mostly only 1 reputable source (BirdSpiders.com). Furthermore, this is why we chose a perceptual model that permits device independent color representation, one that lets us separate chromatic variables from brightness, keeping in mind the underlying assumptions. However, some recent research suggests that CIELab space can perform reasonably well as compared to the latest algorithms for illuminant-invariant color spaces (Chong et al. 2008 ACM Transactions on Graphics, doi: 10.1145/1360612.1360660). Please also see our response below (to point #2) and also to Reviewer #2 above.

Given the dearth of tarantula specimens and in the absence of spectrometry, future work will have to try and acquire uncompressed original images (with EXIF data) and could perform image processing such as homomorphic filtering and adaptive histogram equalization (Pizer et al. 1987 Computer Vision, Graphics, and Image Processing; Gonzalez and Woods 2018 Digital Image Processing, Pearson) in order to further mitigate artefacts such as those arising from differences in illumination, especially if using images from a diversity of sources.

2) The justification for some related decisions are also unclear to me. The CIE-76 colour distance is used, and is described as 'conservative'. But it is not so much conservative as it is an inaccurate model of human colour sensation. It fails to account for perceptual non-uniformity and actually overestimates colour differences between highly chromatic colours (like saturated blues). The authors note they preferred this to CIE-2000, which is a much better measure in terms of accuracy, because the latter was too permissive (line 300). I understand the problem, and appreciate their honesty, but this decision seems very arbitrary. If the goal is to quantitatively estimate colour differences according to human viewers, then the metric which best estimates our perceptual abilities would strike me as most appropriate. Also, the fact that all species would be classified as 'blue' using the CIE-2000, when some of them are obviously not blue by simply looking at them, is consistent with the kinds of image-processing issues noted above. I only focus on this general point because it is offered as a key advance on previous work (L 40-41), but I don't think that is clearly the case (though I agree that the scoring methods of Hsiung et al. are quite vague). I'm generally in favour of this sort of quantitative approach, but here I wonder if it wouldn't be simpler and more defensible to just ask some humans to classify images of spiders as either 'blue' or 'green', since that seems to be the end-goal anyway.

We agree that CIE 1976 is an inaccurate model of “human color sensation,” but at the same time the degree of their applicability or lack thereof to non-human tristimulus visual systems is not clear. In any case, the digital photographs do not preserve UV information anyway. We hasten to add CIE 1976 is still widely used in color science and engineering research for its simplicity and perceptual uniformity, as a simple Google Scholar search would attest. We believe that the reviewer is perhaps mistaken as to our motivation for choosing the CIE 1976 and the exact nature of the shortcomings of the CIE 1976 model, which it turns out to be an unintended advantage. Our goal was not, as the reviewer suggests, to just “quantitatively estimate color differences according to human viewers,” but to do so in a device independent fashion given the constraints of working with already available digital images, and for a putative trichromat visual system. Given there are technically no limits for a and b values in the CIE 76 space, color patches with high values of chroma are computed to have too strong a difference than in actual fact (Hill et al. 1997 ACM Transactions on Graphics, 16, 109-154). This is precisely the kind of situation that we do not face here, as we are essentially comparing shades of blue rather than for instance, chromatic contrasts between saturated blue vs. green or blue vs. red. Moreover, we only use the rectilinear rather than the polar coordinate representation of the colors (in other words, we do not compute the psychometric correlates, chroma Cab, or the hue angle hab). Contrary to the reviewer’s assertion that the CIE 1976 “overestimates color differences between highly chromatic colors (like saturated blues),” a quick perusal of Table S3 affirms that a comparison of highly saturated blues such as between our “standard” H. lividum and Poecilotheria metallica reveals they are quite close in terms of chromatic contrasts (i.e., small E values). Moreover, CIE 1994 and subsequent revisions rely on a von Kries-type transformation to account for non-uniformity of the perceptual space, but as the reviewer is well aware, without an accurate idea of the illumination conditions, use of CIE 2000 is not justified.

Lastly, we are sure the reviewer appreciates that asking humans to manually score the colors of images (e.g. Hsiung et al. 2015) is neither reproducible nor enables quantitative analyses of trait evolution.

3) L26-27, 53-56, 171-176: This is a more minor point than the above, but some of the discussion and logic around hypothesised functions could be elaborated upon, given it's presented as a motivating aim of the text (52-56). The challenge with a group like this, as the authors clearly know, is that essentially none of the ecological and behavioural work necessary to identify function(s) hasn't been done yet, so there are serious limitations on what might be inferred from purely comparative analyses at this stage. The (very interesting!) link between green colouration and arboreality is hypothesised and interpreted as evidence for crypsis, for example, but the link is not so straightforward. Light in a dense forest understory is quite often greenish (e.g. see Endler's work on terrestrial light environments) including at night which, when striking a specular, structurally-coloured green could make for a highly conspicuous colour pattern - especially achromatically (which is what nocturnal visual predators would often be relying on). This is particularly true if the substrate is brown rotten leaves or dirt, in which case they could shine like a beacon. Conversely, if the blue is sufficiently saturated and spectrally offset from the substrate it could be quite achromatically cryptic at dusk or night. To really answer these questions demands information on the viewers, viewing conditions, visual environment etc. The point being that it is a bit too simplistic to observe that, to a human, spiders are green and leaves on the forest floor may be green, and so suggest crypsis as the likely function (abstract L 22-23). So inferences around visual function(s) could either be toned down in places given the evidence at hand or shored up with further detail (though I'm not sure how much is available).

We agree. Indeed, we are limited by the absence of rigorous behavioural studies. With this in mind, we have already made every effort to tone down and emphasize that our results might point towards a given function, but we do not claim it outright. It is our fervent hope that these findings will form the basis for future behavioural studies by giving researchers a starting point to test their hypotheses.

We would like to point out that the association we uncovered is actually between arboreal taxa and the presence of green coloration and not as the reviewer says “spiders are green and leaves on forest floor may be green.” These taxa live in natural crevices on trees, shrubs and essentially spend their lives arboreally. Also, green coloration in tarantulas need not be structural in origin (see e.g., Saranathan et al. 2015) and this is why to test for crypsis against foliage, we used (pigmentary) leaves as the representative model for comparison to tarantula green colors. Although, certain lycaenid butterflies (Saranathan et al. 2010 10.1073/pnas.0909616107; Michielsen et al. 2010 10.1098/rsif.2009.0352), for instance, use structural coloration to better aid in crypsis against foliage.

Minor comments:

• I'm not familiar enough with with methods for creating homolog networks to comment in detail, but the use of BLASTing existing opsin sequences against transcriptomes seems straightforward enough. As do the methods for phylogenetic reconstruction.

We agree this is straightforward.

• L48: What constitutes a 'representative' species? And how reasonable is it to assign a value for such a labile trait to an entire genus? I understand we can only do our best of course and simplifications need to be made, but I can imagine many cases among insects (e.g. among butterflies and flies) where genus-level assignments would be meaningless due to the immense diversity of structural colouration among species (including in terms of simple presence/absence).

Please see our response to Reviewer 2 above.

• Line 168: Wouldn't this speak against a sexual function? Only in a tentative way of course, but the presence of conspicuous structural colouration in juveniles, which is absent in adults, would suggest a non-sexual origin to me.

The reviewer’s inference is incorrect. We do not suggest that blue coloration is present in juveniles but absent in adults, but only that such conspicuous colors already appear in the penultimate moult right before the male creates a sperm web and is ready for mating.

Reviewer #3:

This neat paper continues the story of structural colour evolution in a group that is rarely appreciated for their ornamentation. The study uses colour & ecological data to model their evolution in a comparative framework, and also synthesises transcriptomic data to estimate the presence and diversity of opsins in the group. The main findings are that the tarantulas are ancestrally 'blue' and that green colouration has arisen repeatedly and seems to follow transitions to arboreality, along with evidence of perhaps underappreciated opsin diversity in the group. It's well-written and engaging, and a useful addition to our understanding of this developing story. I just have a few concerns around methods and the interpretation of results, however, which I feel need some further consideration.

As the authors discuss in detail, this work in many ways parallels that of Hsiung et al. (2015). The two studies seem to agree in the broad-brush conclusions, which is interesting (and promising, for our understanding of the question), though their results conflict in significant ways too. Differences in methodology are an obvious cause, and they are particularly important in studies such as this in which the starting conditions (e.g. the assumed phylogeny or decisions around mapping of traits) so significantly shape outcomes. The current study uses a more recent and robust phylogeny, which is great, and the authors also emphasise their use of quantitative methods to assign colour traits (blue/green), unlike Hsiung et al.

1) This latter point is my main area of methodological concern, and I am not currently convinced that it is as useful or objective as is suggested. One issue is that the photographs are unstandardised in several dimensions, which will render the extracted values quite unreliable. I know the authors have considered this (as discussed in their supplement), but ultimately I don't believe you can reliably compare colour estimates from such diverse sources. Issues include non-standardised lighting conditions, alternate white-balancing algorithms, artefacts introduced through image compression, differences in the spectral sensitivities of camera models, no compensation for non-linear scaling of sensor outputs (which would again differ with camera models and even lenses), and so on (the works of Martin Stevens, Jolyon Troscianko, Jair Garcia, Adrian Dyer offer good discussion of these and related challenges). Some effort is made to minimise adverse effects, such as excluding the L dimension when calculating some colour distances, but even then the consequences are overstated since the outputs of camera sensors scale non-linearly with intensity, and so non-standardised lighting will still affect chromatic channels (a & b values). So with these factors at play, it becomes very difficult to know whether identified colour differences are a consequence of genuine differences in colouration, or simply differences in white balancing or some other feature of the photographs themselves.

2) The justification for some related decisions are also unclear to me. The CIE-76 colour distance is used, and is described as 'conservative'. But it is not so much conservative as it is an inaccurate model of human colour sensation. It fails to account for perceptual non-uniformity and actually overestimates colour differences between highly chromatic colours (like saturated blues). The authors note they preferred this to CIE-2000, which is a much better measure in terms of accuracy, because the latter was too permissive (line 300). I understand the problem, and appreciate their honesty, but this decision seems very arbitrary. If the goal is to quantitatively estimate colour differences according to human viewers, then the metric which best estimates our perceptual abilities would strike me as most appropriate. Also, the fact that all species would be classified as 'blue' using the CIE-2000, when some of them are obviously not blue by simply looking at them, is consistent with the kinds of image-processing issues noted above. I only focus on this general point because it is offered as a key advance on previous work (L 40-41), but I don't think that is clearly the case (though I agree that the scoring methods of Hsiung et al. are quite vague). I'm generally in favour of this sort of quantitative approach, but here I wonder if it wouldn't be simpler and more defensible to just ask some humans to classify images of spiders as either 'blue' or 'green', since that seems to be the end-goal anyway.

3) L26-27, 53-56, 171-176: This is a more minor point than the above, but some of the discussion and logic around hypothesised functions could be elaborated upon, given it's presented as a motivating aim of the text (52-56). The challenge with a group like this, as the authors clearly know, is that essentially none of the ecological and behavioural work necessary to identify function(s) hasn't been done yet, so there are serious limitations on what might be inferred from purely comparative analyses at this stage. The (very interesting!) link between green colouration and arboreality is hypothesised and interpreted as evidence for crypsis, for example, but the link is not so straightforward. Light in a dense forest understory is quite often greenish (e.g. see Endler's work on terrestrial light environments) including at night which, when striking a specular, structurally-coloured green could make for a highly conspicuous colour pattern - especially achromatically (which is what nocturnal visual predators would often be relying on). This is particularly true if the substrate is brown rotten leaves or dirt, in which case they could shine like a beacon. Conversely, if the blue is sufficiently saturated and spectrally offset from the substrate it could be quite achromatically cryptic at dusk or night. To really answer these questions demands information on the viewers, viewing conditions, visual environment etc. The point being that it is a bit too simplistic to observe that, to a human, spiders are green and leaves on the forest floor may be green, and so suggest crypsis as the likely function (abstract L 22-23). So inferences around visual function(s) could either be toned down in places given the evidence at hand or shored up with further detail (though I'm not sure how much is available).

Minor comments:

-I'm not familiar enough with with methods for creating homolog networks to comment in detail, but the use of BLASTing existing opsin sequences against transcriptomes seems straightforward enough. As do the methods for phylogenetic reconstruction.

-L48: What constitutes a 'representative' species? And how reasonable is it to assign a value for such a labile trait to an entire genus? I understand we can only do our best of course and simplifications need to be made, but I can imagine many cases among insects (e.g. among butterflies and flies) where genus-level assignments would be meaningless due to the immense diversity of structural colouration among species (including in terms of simple presence/absence).

-Line 168: Wouldn't this speak against a sexual function? Only in a tentative way of course, but the presence of conspicuous structural colouration in juveniles, which is absent in adults, would suggest a non-sexual origin to me.

Reviewer #1:

This study investigates the evolution of blue and green setae colouration in tarantulas using phylogenetic analyses and trait values calculated from photographs. It argues that (i) green colouration has evolved in association with arboreality, and thus crypsis, and (ii) blue colouration is an ancestral trait lost and gained several times in tarantula evolution, possibly under sexual selection. It also uses transcriptome data to identify opsin homologs, as indirect evidence that tarantulas may have colour vision.

Otherwise, a few comments:

1) Given that data is limited for the family (only 25% of genera could be included in this study), it seemed a shame not to discuss further the variation in colour and habit within genera. Based on Figure 1 and supplementary tables, the majority of "blue" genera contain a mix of blue and not-blue (and not-photographed) species. Does this mean that blue has been lost many more times in recent evolutionary history? And how often are "losses" on your tree likely to be the result of insufficient sampling for the genus (i.e. you happen not to have sampled the blue species)?

2) A key conclusion of the study is that sexual selection should not be discarded as a possible explanation for spider colour. However, there is very little detail given in the discussion to build this case. Do these spiders have mating displays that might plausibly include visual signals? How common are sexually-selected colours in spiders generally? Where on the body is the blue coloration (in cases where it is not whole body)? I also missed whether the images used are of males or females or both, or how many species show sexual dimorphism in colouration (mentioned briefly in the Discussion, but not summarised for species or genera).

3) A quick scroll through the amazing images on Rick West's site suggests that oranges and red/pinks are not rare in tarantulas. Perhaps the data is just not available, but it would be good to mention somewhere the rationale behind the blue/green focus, rather than examining all colours.

Minor comments:

I suggest defining stridulating / urticating setae for non-specialist readers. I had to look these up to understand that they were involved in defence.

I notice the Rick West website says species IDs should not be made from photos alone. Is there a risk of misidentification for any photos?

The Results section would benefit from some more clear statements of key results. For example, phrases like "AIC values to assess the relationships between greenness and arboreality are reported in Table 3" could be replaced instead with a summary statement indicating what this table shows.

In the Figure 1 caption I think there is a typo: 'the proportions of species with images that possess blue colouration (grey = no available images)" but should this say "grey = not blue"?

142 - the lengthy discussion here of whether there is one or more mechanisms by which blue is produced in tarantulas, and the detailed criticism of Hsuing SEMs, seems a bit out of place given that the current study does not investigate the proximate mechanism of blue colouration but merely its presence.

The Table S7 caption states: "A * indicates currently undescribed species with blue or green colour that can be confidently attributed to corresponding genus. However, as the described species exhibit no blue or green colour, we conservatively scored these as 0." Is this a conservative approach though? If they have been confidently assigned to genus, I don't understand why they would not be included.

Table S6 - It is not clear to me how the values for predicted N orthologs were calculated.

An example of a divide between the social standards for men and women. Helena talks about how women cannot "fight for love" which illustrates them not being able to peruse the ones they truly love, but I also think this comparison works to demonstrate the quite literal fight for "love" that Theseus peruses through taking Hippolyta in the midst of a battle. This quote describes a passive love that women are supposed to partake in, just allowing things to happen, while men are the ones who chose who and how they love. The words "scandal on my sex" demonstrates how not abiding by these terms is in no way acceptable and is a social disgrace.

Lysander's referral to Hermia as an Ethiope is meant to be an insult regarding her darker complexion. We have talked about this sort of thing a lot, but again, we see how darker complexions were seen as negative qualities and could be used as an insult. Like in Othello, we see how these racial systems were already in place where white people thought less of black people. However, I think it may be of importance to note that Lysander, before the magic juice, was in love with Hermia despite this "negative" quality. I do not think this was intended, but the fact that Lysander only says this when he is in this trance makes me read it as a comment about how racial insults/hate/discrimination is the not the result of logical or empathetic thinking, but of animalistic, basic, and disgust driven thought processes. Again though, this is modern view of what I want this play to be saying, I do not think given the time period Shakespeare was arguing that racial biases are fickle and driven only by hate/ignorance.

The best social studies teacher I had was as good as he was, not just because he showed a lot of devotion and energy in his teaching, but also because he understood and used the tools that we used every day

This abstract is a great place to find topics that you may be interested in as you look for your 3 letters from the main website. Think about what topics were of interest to students. Also, how did this assignment give students, "choice and voice"? How does this type of assignment contrast to a typical assignment the could've been given on this topic but without student voice? Take note and find correlations that may be relevant and/or helpful to you as you write your final paper for this week.

Very insightful

This is a very interesting account of how you related to ideas in the chapter.

Author Response

1) There were concerns about the normality tests and reanalysis to avoid pseudo-replication that must be addressed.

We have now checked the data by two tests for normal distribution (Shapiro-Wilk and Kolmogorov_Smirnoff) and found that flight data do not follow a normal distribution. Therefore statistical analysis of flight data have now been performed using non-parametric tests. We have used the Kruskal-Wallace test followed by Dunn’s multiple comparison test for multiple comparisons and Mann-Whitney U-Test for pair wise comparisons. This information has been included in the statistical tests section in methods. Regarding pseudo-replication, as suggested imaging data have been replotted and calculated now to include just one cell, or one lobe per brain. In addition we have included individual brain traces for every experiment as supplemental data (Figure 5 - supplement F2, Figure 6 – supplement F1, F3 and F4).

2) Discussion should be made clearer and expanded to encompass more of the literature. Specifically, the authors should expand upon the final section of the discussion to discuss more about 1) the potential context for cholinergic modulation of the PPL1-y2alpha'1 DANs (For example, consider where the acetylcholine signal onto DANs might come from. DANs may not be entirely presynaptic to Kenyon cells but might also receive input from Kenyon cells.), 2) the proposed role of these DANs (which have been studied in several contexts) and 3) modulation of innate behavior in general. The paper begins with the importance of modulating innate behavior, but the discussion on this topic is spare and focused almost entirely on research on the mushroom bodies of Drosophila. The discussion section leans heavily on summarizing the results, rather than making connections to work in other systems or networks.

As suggested we have now addressed each of these points in greater detail in the last section of the discussion which has been expanded to two paragraphs. The possibility of cholinergic inputs from KC cells to DANs stimulating the IP3R have been included in the discussion and in the final model in Figure 7. Several other references that mention the role of PPL1-y2alpha'1 DANs in modulation of behaviour are now included – see last para of the discussion. We have expanded the last section of the discussion to include possible roles for other regions of the brain in modulating flight and references to other insect brains, where relevant.

3) One common point raised by all reviewers was the need for expression of the itprDN during pupation which could have been due to either the perdurance of endogenous itpr vs. a developmental effect caused by the itprDN (the authors fully acknowledge the issue). This section raised many questions that aren't within the scope of this study, nor are easily resolved. Nevertheless, the authors must expand upon the implications of these results and suggest future studies will needed to resolve the issue.

We are indeed unable to state equivocally if adult behavioural phenotypes, arising from expression of the IP3R^DN, are only pupal or both pupal and adult. We have expanded on the implications of these results both in the results (Page 9-10) and in the discussion (page 11). One way of addressing this is to express a tagged IP3R^DN specifically in late pupae and then follow it’s perdurance in adults. This experiment has now been suggested as a way to resolve this issue in the second paragraph of the discussion.

Reviewer #1:

The authors report experiments on Drosophila to show that the proper function of an IP3 receptor in a small subset of dopaminergic neurons is required for flight behavior. Most interesting is the fact that the requirement is restricted to a time point during pupal development. Technically, the authors report a novel dominant-negative mutant for of the IP3 receptor to interfere with its function. Physiologically, the IP3 receptor-dependent impairment in the function of the dopaminergic neurons affects both synaptic vesicle release and excitability, Also, muscarinic acetylcholine receptors are required for proper development of the flight-modulating circuit during development.

The role of dopamine in the brain of Drosophila (as a model for general dopamine and brain function) is in the center of current research, and is studied by a large number of laboratories. More and more types of behavior are discovered that are modulated by dopaminergic neurons, and in particular those innervating the mushroom body. Therefore, the study is of very high interest for researchers working on Drosophila, but also to a broader readership.

The experiments are well designed. with appropriate controls at place. The conclusions drawn are highly interesting and novel (dopaminergic modulation of flight behavior, perhaps in the context of food seeking behavior, molecular mechanisms of circuit maturation).

Minor comments:

1) A test for normal distribution of data is required to determine whether parametric statistical tests are actually appropriate.

Done – please see response above.

2) It is not clear to me why the authors conclude an acute requirement of IP3R during the adult state although the phenotype can arise through a genetic intervention during earlier time points in development (Page 9, lines 297ff). This has to be outlined much clearer. My interpretation of the data is: During a certain time window after pupal formation IP3 signaling is required for a proper formation of the neuronal circuit. This is likely to be not only a cell-intrinsic (i.e., cell autonomous) effect because the mAchR is also required during this time window. This provides an excellent example (there are actually only very few!) of circuit development that requires synaptic interactions between neurons. If one keeps in mind that dopaminergic neurons have reciprocal synapses with Kenyon cells (e.g. Cervantes-Sandova, elife 2017; should be included in schematic illustration!)), and these release acetylcholine onto dopaminergic neurons, a potential circuit maturation based on the concerted activity is most interesting. I suggest that the authors point out more precisely how they think the actual phenotype comes about, of course, with all due caution.

The primary reason that we suggest an adult requirement for the IP3R in the DANs is that we see a Ca2+ response to carbachol in adult PPL1-y2alpha'1 DANs (Figure 5 – supplement 1). We put together this finding with the observation that carbachol stimulates dopamine release from PPL1-y2alpha'1 DANs (Figure 5) and that blocking vesicle release acutely in adults reduce durations of flight bouts (Figure 4) to suggest that there is likely to be an adult requirement. However, we agree that this is not conclusive and certainly does not negate a pupal requirement. As mentioned above we have addressed the pupal vs pupal+adult issue in greater detail in the results (page 9, 10) and discussion (page 11). We agree that there may be acetylcholine release from Kenyon cells at the MB synapse. This possibility has been included in the discussion and in Figure 7.

3) Statistical tests should be done across independent brains, not across different cells in the same brains.

We have done this. Thank you for pointing this out.

Additional data files and statistical comments:

A test for normal distribution of data is required to determine whether parametric statistical tests are actually appropriate.

Done.

Figure legend 5 C should be 5B. The scaling of the y-axis is not optimal.

Done.

Statistical tests should be done across independent brains, not across different cells in the same brains. This would cause a mixture of dependent and independent data. This is of importance!

Done.

Reviewer #2:

The results of the individual experiments reported by the authors are convincing. The approach is rigorous and they take full advantage of the many powerful molecular genetic tools available in Drosophila. The identification of a mechanism by which a small subset of dopaminergic cells may control behavior is significant. My concerns about the manuscript are relatively minor.

Minor comments:

I have reviewed "Modulation of flight and feeding behaviours requires presynaptic IP3Rs in dopaminergic Neurons" by Sharma and Hasan. The authors first translated to Drosophila a dominant negative (DN) strategy first tested in mammalian cells to block the function of the fly IP3 receptor. Controls using westerns to test the expression in vivo and calcium imaging to assess inhibitory activity in an ex vivo prep were generally convincing. They then show that the DNA, RNAi and a wt transgene disrupts flight as they have shown previously using both genetic mutants and RNAi. They use genetic rescue to further show that alterations in the function of itpr in dopaminergic cells are likely to mediate at least some aspects of the flight deficit. The restricted distribution of the THD' driver was used to narrow down the identity of DA cell clusters responsible for this effect to PPL1 and/or PPL3. Additional split GAL4 lines identified a deficit when the DN was expressed in the PPL1-γ2α′1 subset of DA cells that project to the mushroom bodies. This is a key finding of the paper since it localizes the requirement of the IP3R to cells that have been implicated in other behaviors. Developmental tests using TARGET/GAL80 indicate a requirement for itpr during late development. Disruption of itpr only in the adult did not have a significant effect. This seems likely to be due to perdurance of itpr as suggested by the authors. However, these data make it difficult to determine which aspects of the phenotype are due to broad developmental deficits versus disruption of IP3R in the adult (see below). The authors next test the effects of mAhR with the idea that mAChR is likely to signal through IP3R. While it was known that developmental expression of mAcHR expression is required for adult flight, the current data more specifically that the PPL1-γ2α′1 DANs are required, enhancing the impact of the paper.

To tie these results to vesicle recycling and release the authors use the shibere[ts] transgene in PPL1-γ2α′1. Flight bouts were disrupted via exposure to the non-permissive temperature both during late pupal development and the adult. The adult phenotype has been demonstrated previously but the developmental defect is novel. The demonstration of an effect in adults is important since it suggests loss of itpr during adulthood might also have an effect in adults even though this can't be tested due to perdurance. Expression of shibire[ts] in PPL1-γ2α′1 also disrupts feeding, and the authors next phenotype these effects with the itpr DN, indicating that IP3R expression in PPL1-γ2α′1 is required for both feeding and flight. However, here as with the flight experiments, it is not possible to directly demonstrate an effect in adults due to perdurance. They show that knockdown of mAChR also reduces feeding similar to its effects on flight and suggest that the deficits are due to disruption of the mAchR ->(Gq) ->IPR3 pathway. The suggestion of connections between mAchR and IPR3 within PPL1-γ2α′1 and the idea that PPL1-γ2α′1 controls two distinct behaviors are a significant finding and one of main contributions of the paper.

To help link the shibire[ts] data set with and the results of perturbing mAchR and IPR3, the authors show that carbochol induced DA release is reduced, making excellent use of the relatively new GRAB-DA lines. As a control, they show that synapse density of PPL1-γ2α′1 in the γ2α′1 MB lobes are not altered. The demonstration that DA release is altered elevates the technical strength of the paper. Moreover, although further experiments might be needed to prove their model, these data support the argument that mAchR ->(Gq) ->IPR3 pathway is disrupted in the adult. The final set of experiments in Fig 6 indicate that excitability of the PPL1-γ2α′1 DANs is also disrupted by knock down or IP3R. Is it possible that this deficit contributes to the decrease in DA release by the mAchR ->(Gq) ->IPR3 and the authors nicely explain a possible mechanism and cite relevant references in the Discussion.

The results of the individual experiments reported by the authors are convincing. The approach is rigorous and they take full advantage of the many powerful molecular genetic tools available in Drosophila. The generation of the DN transgene is a nice idea and in combination with other tools helped them to identify specific subsets of DA neurons important for the behaviors they test. However, they have previously demonstrated similar effects with mutants and RNAi, and again use them to help map the relevant cells. Since the use of the DN construct did not really go beyond the experiments using RNAi or genetic rescue, the emphasis on the importance of this reagent might be reduced in the abstract and introduction.

Flight deficits have also been seen in other experiments on these the DANs identified by the authors. Thus, the major novel finding of this section is the demonstration that itpr is required in these cells for regulating flight. While it was previously shown that feeding behavior is also required by DAN projections to the MB, the idea that overlapping cells might control both flight and feeding is interesting. Although the idea that these two phenotypes are specifically related to each other seems somewhat speculative, one major strength of the paper lies in tying together prior observations on itpr and the DANs with their current experiments. They do this again at the cellular level using GRAB to show that carbachol induced release of DA (but not synapse density) is reduced by itpr knock-down, thus tying together data on shibere, AcHR and itpr.

These connections make for an exciting story, and they have been cleverly woven together by the authors. On the other hand, they also represent a possible concern about the manuscript as a whole, since causal relationships between the deficits between the effects of blocking the effects of IP3R, mAcHR, neuronal excitability and vesicle release are not yet proven. It is therefore possible that all of these are relatively non-specific effects of disrupting the function of PPL1-γ2α′1 neurons. This modestly reduces the strength of the paper but is also a relatively minor concern. A second potential concern is that despite the interesting connections made by the authors as well as some exciting new data, some of the findings replicate previous data.

It is indeed likely that loss of the IP3R in PPL1-y2alpha'1 DANs leads to both specific (acetylcholine signaling followed by neurotransmitter release) and non-specific changes (such as loss of excitability). Both are likely to have an effect on the behavioural phenotypes modulated by PPL1-y2alpha'1 DANs. We have previously shown a role for both mAchR and the IP3R in flight. However, in this work we have addressed cell specificity and mechanism, neither of which was known earlier.

A third concern is the relationship between the effects of disrupting PPL1-γ2α′1 during development versus the adult. As the authors suggest, perdurance (of protein expression) and/or "perdurance" of previously formed tetramers could easily account for the failure of itpr and mAChR knock down in the adult to cause behavioral deficits. By the same token, it is difficult to parse out the contribution of developmental defects in the DA cells versus problems with signaling in the adult and the following issues should be addressed: the observation that synaptic bouton density is not disrupted is a good way to eliminate gross disruption of connectivity during development but does not rule out other more subtle developmental defects in neuronal function. The fact that shibire[ts] can cause effects in the adult is appreciated but does not really help us to understand what IP3R and perhaps mAcHR are doing during development.

We agree and have tried to further address this issue in the text (see above).

Additional Minor Concerns.

To validate the decrease in the overall response to carbachol in Fig 1D and E, the authors show a statistically significant difference for area under the curve. A parallel metric and statistical test might be used to support the statement that the response is delayed in 1D but not 1E.

Thank you for this suggestion. We performed the test and in fact found that both cellular and mitochondrial responses are delayed. In presence of IP3RDN. This part of the text has been modified (page 4).

"Interestingly, the mitochondrial response did not exhibit a delay in reaching peak values." Why is that? A brief explanation might be useful.

This is no longer the case. The sentence has been removed.

The second explanation of how shibire[ts] works might be shortened.

Done.

Reviewer #3:

General Assessment:

This study demonstrates that IP3R signaling (triggered by muscarinic receptor activation) affects excitability and quantal content of a subset of dopaminergic neurons to modulate flight duration and food search. I had no technical concerns and am generally supportive. My only major concern was that the narrative was fragmented. I believe this is because the perspective shifted between the IP3Rs and the dopamine neurons themselves, and was too focused. I think that streamlining the narrative and providing a broader perspective for the results will remedy this issue.

Major Comments:

-I would like the authors to expand upon their final section of the discussion to discuss more about 1) the potential context for cholinergic modulation of the PPL1-y2alpha'1 DANs, 2) the proposed role of these DANs (which have been studied in several contexts) and 3) modulation of innate behavior in general. The paper begins with the importance of modulating innate behavior, but the discussion on this topic is spare and focused almost entirely on research on the mushroom bodies of Drosophila. The discussion section leans heavily on summarizing the results, rather than making connections to work in other systems or networks.

We have expanded the last section of the discussion to include these suggestions (see above under consolidated review points).

-The developmental section seemed somewhat tangential as the authors cannot distinguish between a developmental role for the IP3R from a need to express the ItprDN transgene prior to adulthood to overcome a potential slow turnover of endogenous IP3R. In essence, it was unclear how these results contributed to the overall narrative of state modulation of behavior. Is this section informative to the development of the mushroom bodies or rigorous validation of the novel transgene?

The manuscript addresses how IP3R function impacts behaviour. In that context pupal (developmental) and adult contributions are both relevant.

Reviewer #1:

In this manuscript, Bosco et al. propose that DHX30 coordinates cytoplasmic translation and mitochondrial function to impact on cancer cell survival. They deplete DHX30 and report that this causes an enhancement of translation including those of mRNAs encoding for cytoplasmic ribosomal proteins, while paradoxically reducing the translation of mitoribosome protein mRNAs. There are cytoplasmic and mitochondrial isoforms of DHX30 and the authors assess the long-term consequences of knockdown of the cytoplasmic versus mitochondrial + cytoplasmic proteins. Some of the novelty of this paper has been preempted by a previous publication by Antonicka and Shoubridge showing that loss of DHX30 results in impaired mitochondrial ribosome assembly, impaired mitochondria OXPHOS assembly, impaired mitochondrial mRNA precursor processing, and a very severe decrease in mitochondrial translation. I think the work, while interesting, is preliminary and should aim to provide mechanistic insight for the phenotype associated with DHX30 knockdown.

As far as I can see, none of the targets obtained from the polysome profiling are validated in this study. This is concerning since polysome profiling was previously reported in a Cell Report 2020 publication by the authors (GSE 95024; available at the GEO database), but the origin of the RNA-seq data in the current paper is not clear (GSE 154065; not available at the GEO database). We do not know if the RNA-seq data was generated from the same samples as the polysome profiling samples previously reported or completely independent of these (this information is lacking). Regardless, validation of any putative translation responsive genes predicted from polysome profiling data would appear to be a reasonable expectation these days.

The authors claim that depletion of DHX30 leads to increased global translation (Figs 1f, g). They also provide evidence that translation of mRNAs encoding cytoplasmic ribosomal proteins is increased, while the translation of mRNAs encoding mitoribosome ribosomal proteins is decreased (Fig 1b). DHX30 is associated with ribosomal subunits, 80S monosone and low-molecular weight polysomes, and it also interacts with a CG-rich motif for p53-dependent death (CGPD) in 3' UTRs of mRNAs. What is lacking is a mechanism to explain these observations (if the data validates)? To this reviewer the lack of mechanistic insight is a serious shortcoming of the current submission. What is responsible for the general translational increase (including cytoplasmic rps encoding mRNAs), yet mitochondrial rp mRNA translation decrease, upon DHX30 knockdown? Many rp mRNAs have TOP motifs at their 5' ends, is this pathway affected?

The authors previously identified DHX30 as a CGPD-motif interactor. They published this as a specific DHX30 binding motif, yet this motif is not enriched in the new data set established by the authors. I don't understand the statement put forth by the authors on line 286 that " While we cannot exclude that the CGPD motif can be implicated, only a subset of RP transcripts harbors instances of it". Either it is significantly enriched or it is not. In any event, there appears to be an inconsistency with previously published data.

The ENCODE eCLIP data suggests that DHX30 can bind to 67 cytoplasmic ribosomal and 23 mitochondrial protein transcripts. Yet in their eCLIP validation experiments using RIP, the authors probe for the potential of DHX30 to bind to only MRPL11 and MRPS22 (Fig 2a). They write "These findings suggest that DHX30 directly promotes the stability and/or translation of mitoribosome transcripts." What about the cytoplasmic ribosome protein mRNAs, which according to the ENCODE data can also bind DHX30, yet their response to DHX30 depletion is the opposite of that of the mitoribosome protein mRNAs. I think it may be premature to correlate DHX30 with mitoribosome protein regulation.

The comparison of the efficiency of knockdown using siRNAs targeting the cytoplasmic form versus the mitochondrial + cytoplasmic forms versus shRNA knockdown efficiency is confusing and, in my humble opinion doesn't add insight into mechanism of action. "Transient silencing of DHX30" (ie, using siRNAs) achieves ~50% mRNA reduction in HCT and U2OS cells 48-96s following transfection. On the other hand, silencing of DHX30 mRNA using shRNA achieved better levels of reduction (60-75% decrease) in U2OS and MCF7 cells (Fig S2e). The authors use these differences in knockdown efficiencies to correlate differences in expression response of several mitochondrial encoded genes. The authors need to show the extent to which DHX30 protein levels are reduced in the siRNA treated cells (only changes in mRNA levels are presented). As well, there should be a genetic rescue experiment to show that siRNA or shRNA resistant DHX30 cDNA can overcome this effect. Lane 3 of Fig 2h appears underloaded as assessed by the actin intensity. MRPL11 protein levels appear greater in lane 2 (siDHX30-C) compared to lane 1, why is that?

Please provide details on the siRNA and shRNAs used. It appears that only one shDHX30 was used to target cytoplasmic DHX30 and one shRNA to target cytoplasmic + mito DHX30. I couldn't find information on this.

If mutations in DHX30 are known to trigger stress granules formation, does knockdown of DHX30 do the same. Is eIF2 alpha phosphorylated upon HDX30 knockdown?

There appears to be several DHX30 mRNAs made through alternative splicing (see https://www.ncbi.nlm.nih.gov/gene/22907). In this study, when the authors refer to cytoplasmic DHX30, is the equivalent function being attributed to these different potential isoforms?

The pictures in Figs 1e, 2d, and S3g are quite difficult to appreciate and should be provided at higher magnification.

Fig 2f. Why is there so much tubulin in the mitochondrial protein extract lane?

Suppression of DHX30 mRNA leads to lowered proliferation rates in HCT116 cells. This however was not due to significant alterations in the cell cycle (Fig 4e). Apoptotic rates do not appear to be affected (compare HCT_shNT to HCT_shDHX30 in the DMSO samples of Fig 4g). Can the authors please provide an understanding into what is leading to the lowered proliferation rates if cell cycle progression and cell death are unaffected. Confusingly, "transient" silencing of DHX30 mRNA (protein levels were not assessed) in U2OS cells did not impact proliferation while in MCF7 cells it did. Although the authors attribute this difference in response to better depletion of DHX30 mRNA in MCF7 cells, they do not actually measure DHX30 protein levels and the use of different cell lines complicates the interpretation.

Line 267 "none of the DHX30 closer homologs showed strong evidence of such localized translation". What homologs are being referred to here?

Line 269. "Although our experiments did not enable us to confirm this in HCT116, a previous report also showed evidence for DHX30 interaction with mitochondrial transcripts in human fibroblasts by RIP-seq (Antonicka and Shoubridge, 2015). Our data instead point to a direct interaction with mitoribosome transcripts and their positive modulation as another means by which DHX30 can indirectly affect mitochondrial translation." DHX30 thus interacts with many different mRNAs and in my view it becomes difficult to ascribe a particular biological response to DHX30 to a particular set of transcripts based on interaction data.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

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Reply to the reviewers

Response to the reviewers’ comments:

We thank both the reviewer for their critical evaluation and excellent suggestion to improve the manuscript. We are making all the changes suggested by both the reviewers and performing the experiments to address all the concerns specifically from the reviewer #1. Please find below our response to the reviewers’ comments:

Reviewer #1:

This is an interesting study from the Rahaman group that identifies cardiolipin (CL) as a potential binding target for Drp6 recruitment to the nuclear membrane in Tetrahymena (that has a unique nuclear remodeling program). In addition, they identify a residue, I553 in the DTD region, which they claim is a key residue involved in specific CL interactions. While the experiments themselves are technically sound, and are well performed and controlled, I don't find the major conclusion that I553 is involved in direct CL interactions justified or well rationalized. By their own admission (in the discussion), the conservative mutation I553M may perturb local folding and may indirectly affect CL interactions. There is no test of DTD folding with and without the I553M mutation, nor are there other mutations (e.g. I553A and in the vicinity) tested. CD experiments in the absence and presence of CL-containing membranes will likely yield information on the impact of the I553 mutations, while DLS experiments would inform on the hydrodynamic properties (overall 3D fold) of the DTD and the impact of these mutations. CL interactions generally involve a combination of electrostatic and hydrophobic forces. Where do the electrostatic interactions come from? Why would an Isoleucine to Methionine mutation affect the hydrophobic component, even if I553 is the key hydrophobic residue?

Response:

We thank the reviewer for the comments that the experiments are sound, well performed with appropriate controls. While we agree that the exact mechanism of how I553 provides specificity to cardiolipin binding is not addressed in the present manuscript, our study clearly demonstrates that the isoleucine at 553 plays important role in determining cardiolipin specificity and nuclear recruitment. As pointed out by the reviewer, it is possible that changing isoleucine to methionine may affect the local conformation. However, there is no major conformational change in the DTD due to this mutation. This conclusion is based on clear loss of nuclear localization and cardiolipin interaction for the mutant without affecting other properties. The in vitro floatation assay clearly stablish that the effect is directly by inhibiting interaction specifically with cardiolipin containing membrane. It should be further noted that the same domain DTD interacts with other two lipids (PS and PA) and mutant retains interaction with them arguing that conformation of this domain is not significantly changed due to I to M mutation. Consistent with these results I553M mutant could be targeted to the nuclear membrane as a complex with wildtype Drp6 further confirming that I553 could form correct self-assembled structure with wildtype protein required for association with nuclear membrane. This is further substantiated by comparing all the known biochemical properties including GTPase activity, membrane binding via other two lipids, formation of helical spirals and ring structures. Hence it is clear that I553 provides specificity to bind cardiolipin and recruitment to the nuclear membrane. We will further confirm if there is any local conformation change due to the mutation I to M by fluorescence quenching experiments and will be incorporated in the revised manuscript.

Regarding overall folding of the mutant, this is an excellent suggestion by the reviewer. We are planning to perform CD experiments of the I553M mutant and wildtype proteins to compare if there is any change in overall folding due to mutation. This result would be incorporated in the revised manuscript.

Reviewer is right to point out that both electrostatic and hydrophobic interactions are important for interaction with cardiolipin. Electrostatic interaction is important for all the phospholipids while interacting with protein and is expected to come from other amino acid residues which are positively charged. Electrostatic interaction may contribute to the affinity of the interaction by providing additional binding energy. But considering its universal nature of interaction with all the phospholipids, it cannot give specificity for a specific lipid and hence would not discriminate among different phospholipids.

Regarding affecting hydrophobic component, the reviewer is correct that both are strong hydrophobic amino acids and loss of I553M interaction with cardiolipin may not be due to change in hydrophobicity

To address that the loss of cardiolipin interaction is not specific to methionine and is due to absence of isoleucine, the suggestion from the reviewer to replace I553 with A (alanine) is an excellent one. We are doing the experiments and we anticipate to incorporate these results in our revised manuscript.

Reviewer #1 (Significance (Required)):

The addressed phenomenon is restricted to Tetrahymena and may not have far reaching implications. Regardless, the identification of CL as a binding target for Drp6 at the nuclear membrane of this organism is in itself significant. The conclusion that I553 is the key CL binding residue is however not warranted. Additional experiments are needed to dissect how this residue impacts CL interactions and examine whether the observed effect is direct or indirect.

Response:

We thank the reviewer for appreciating the significance of this work. We agree that our data is Tetrahymena specific. However, we believe that the study is relevant for all the proteins whose association with target membranes depend on cardiolipin including many cardiolipin interacting DRPs (such as DRPs involved in biogenesis and maintenance of mitochondria).

We really appreciate the reviewer for the excellent suggestions. Based on this we are performing the following experiments.

1. CD experiments to assess overall folding of I553M and Wildtype protein
2. Fluorescence quenching of Tryptophan (at amino acid position 548) residue in the vicinity of I553 to compare conformation of the mutant with that of wildtype protein.
3. Evaluation of I553A in nuclear localization and cardiolipin binding. We anticipate these results to further confirm if I553 is the key CL binding residue and if the effect is direct.

The writing is not clear in some parts and may require a round of language editing. There are no issues with reproducibility.

Response

We thank the reviewer for pointing out the language editing. We will edit the language wherever we find it appropriate. We would highly appreciate if reviewer can indicate the portions that need special attention.

Reviewr #2:

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Dynamin is a GTPase superfamily protein involved in membrane fusion and division. This paper focused on Drp6, one of the eight dynamin superfamily proteins of Tetrahymena, and analyzed its nuclear envelope localization mechanism by a combination of in vivo cytogenetical analysis and in vitro biochemical analysis for the various mutant Drp6 proteins. Results showed that a specific amino acid residue (isoleucine at the 553rd) in the membrane binding domain of Drp6 was required for its nuclear membrane localization, but this residue is not required for ER/endosome localization and GTPase activity. Furthermore, in vitro floating analysis using centrifugation indicated that Drp6 specifically bound to the cardiolipin at the 553rd isoleucine residue and this binding was required for Drp6's nuclear membrane localization. Finally, removal of cardiolipin from the conjugating cells using inhibitor treatment showed that cardiolipin was required for the new macronucleus formation (including the expansion of macronuclear envelope) through the function of Drp6. Based on these results, authors concluded that cardiolipin targets Drp6 to the nuclear membrane in Tetrahymena.

\*Major comments:***

The experimental data presented in this paper are reasonable and the results are solid, and therefore I think the deduced conclusions are convincing. However, to improve this paper, I have several minor comments to be revised before publication.

\*Minor comments:***

1. In the previous paper, it has been shown that GFP-Drp6 is localized in the inner nuclear membrane of both macronucleus and micronucleus. In this paper, however, this point is not clearly stated and is not shown in the figures --- I could not understand such localization pattern of GFP-Drp6 in Fig. 1C and Fig. 3b and the statements in the text. I suggest adding such statements somewhere in Introduction or Result section. Also, add adequate references to the corresponding statements in the text.
2. • Related to the comment 1, I suggest replacing Fig. 1C (images of fixed cells) with Fig. S1B (images of live cells) because nuclear localization of GFP-Drp6 are much clearer in Fig. S1B (live cell) than Fig. 1C (fixed cell), and because fixation may cause artificial redistribution of the proteins. Please add arrows in those figures to point out the position of micronucleus in those figures if necessary.*
3. • Similarly, I suggest replacing images of Fig. 5B (fixed cells) with those of Fig. S3 (live cells).*
4. • page 7, line 224: GFP-Nup3 is used as a marker protein of the nuclear pore complex (NPC). However, there is no description of how GFP-Nup3 is obtained or made. Add description how this DNA plasmid was obtained or generated.*
5. • Related to the comment 4, "Nup3" is first discovered in Malone et al., Eukaryotic Cells, 2009, but also soon after discovered as the name of "MicNup98B" in Iwamoto et al., Curr Biol, 2009 and used in several papers including Iwamoto et al., Genes Cells, 2010; JCS, 2015; JCS 2017; and more. Because Nup3 is the Tetrahymena paralogs of human Nup98 and the name of "Nup98" is well established to call these homologs in various eukaryotes, I suggest adding the name of "MacNup98B" after the word of "Nup3" for reader's better understanding. I also suggest adding appropriate references to refer to this protein as follows: Add Malone et al. 2009 for "Nup3" and Iwamoto et al., 2009 for "MacNup98B."*
6. • page 9, line 295: I wonder if "Fig. 3b" may be a mistake of "Fig. 5C." If so, please correct this.*
7. • page 10, the second paragraph (lines 311-322): This paragraph discussed the possible involvement of Drp6 in the nuclear envelope expansion of the post-zygotic nucleus. It may be interesting to point out that large-scale nuclear envelope reorganization including the formation of the redundant nuclear envelope and the type-switching of the NPC (from the MIC-type NPC to the MAC-type one) has been reported at this developmental stage (Iwamoto et al., JCS 2015). For example, the peculiar shaped nuclear envelope with the redundant/overlapping nuclear envelope structure can be seen and the MAC-type NPCs rapidly assembles to the expanding nuclear envelope. It may be interesting to point out that cardiolipin and Drp6 may be involved in these phenomena. But it is too speculative and therefore consider adding such a discussion as an option.*
8. • page 13, line 412: Is the word "GFP-drp6-I553M" written in italics intended for the gene for the GFP-drp6-I553M protein? If so, protein may be acceptable here. Make sure there are no problems with italicized characters. Also, check if the lowercase letter "d" in "drp6" is OK because large letters are used in other cases.*
9. • page 20, figure 1: I recommend switching the positions of HDyn1 and Drp6 in Figure 1a to keep the order in Figure 1b.*
10. • page 21, line 671: Add the word "Tetrahymena" before "Drp 6" to pair with the word "human dynamin 1".*
11. • page 23, line 729: Remove "and."*
12. • page 23, lines 729 and 731: Unify the expression of "cardiolipin" and "Cardiolipin"*
13. • page 23, line 732: Add "or" before "10% Phosphatidylserin."*
14. • page 24, Figure 3a: Please mark the position of I553M in the figure if possible. Alternatively, indicate the range of amino acid residues after the words "red" and "green" in the figure legend.* Response:

We thank the reviewer for the excellent comments that “the experimental data presented in this paper are reasonable and the results are solid, and therefore I think the deduced conclusions are convincing.” We also thank the reviewer for the minor comments which are thorough and very insightful. it will improve the manuscript substantially. We would incorporate all the changes in the revised manuscript.

Reviewer #2 (Significance (Required)):

The corresponding author and his colleagues have reported that Tetrahymena Drp6 is localized to the outer nuclear membrane of both macronucleus and micronucleus of Tetrahymena (Elde et al., 2005) and that Drp6 is required for the formation of new macronuclei during nuclear differentiation (Rahaman et al., 2008). Therefore, these parts are not novel.

The novelty of this study is as follows:

(1) The discovery of a specific amino acid residue (isoleucine at the 553rd) of Drp6 that is required for its nuclear membrane localization.

(2) the discovery of a lipid molecule, cardiolipin, as a critical partner for Drp6's nuclear membrane targeting.

(3) Discovery of involvement of cardiolipin in the new macronucleus formation (the expansion of macronuclear envelope) through the function of Drp6.

*

I think their findings are highly novel and will provide new insight into a field of cell biology. Especially, their findings will contribute to understanding how specific proteins targeted to the specific intracellular membranes. In addition, their methods (such as floatation assay) for analyzing the interaction between the protein of interest and lipid/liposomes will become an important tool.*

Response:

We are very happy to note that the reviewer has pointed out the significance of the present study. We fully agree with reviewer and appreciate thorough analysis and excellent conclusion from the reviewer.

FOX NEWS SUCKS

SO TRUE-- "just because someone consistently believes something doesn't mean that it's likely to be true"... "even if a large number of people consistently believe something, its credibility may be negligible" 1.

1) Theodore Schick Jr., Lewis Vaughn, How to Think About Weird Things: Critical Thinking for a New Age, (New York: McGraw-Hill Education, 2019), 84, e-book.

Reviewer #2:

The authors describe the dependence of the p-value on sample size (which is true by definition) and offer a solution, using simulated data and an applied example.

I'm not sure that the introduction successfully motivates the paper. It is unclear whether this is due to misunderstandings by the authors of some key points, or rather is a matter of awkward communication, such that the authors' intentions are accurately conveyed.

The authors note the link between the p-value and sample size. In particular, the authors suggest that statistical significance can be achieved by using a sufficiently large sample size, and they call this 'p-hacking'. I certainly don't recognise use of a large sample size as an example of p-hacking. Instead, this term refers to analytical behaviours which cause the p-value to lose its advertised properties (advertised type 1 error rate). Examples would include taking repeated looks at data without making any appropriate adjustment, trying tests on different groupings of data (and selecting results on the basis of significance), or trying different definitions of an outcome measure. The key point is that, when these actions are performed, reported p-values are no longer valid p-values - they do not behave as they are supposed to. So straight away the authors' argument becomes confusing. Are they criticising the behaviour of the valid p-value? Or are they trying to criticise behaviours that cause the p-value to lose its stated properties? This point remains very unclear. I believe the authors are attempting the former, but wrongly describe this as an example of p-hacking.

But other statements in the introduction invite further confusion. The authors say " even when comparing the mean value of two groups with identical distribution, statistically significant differences among the groups can always be found as long as a sufficiently large number of observations is available using any of the conventional statistical tests (i.e., Mann Whitney U-test (Mann and Whitney, 1947), Rank Sum test (Wilcoxon, 1945), Student's ttest (Student, 1908)) (Bruns and Ioannidis, 2016)." Again, it is unclear what the authors are trying to say here, and the statement is clearly false under the most obvious interpretation. If the authors are saying that significance will always be found when the null is true and model assumptions are correct provided that the sample size is large, then this is clearly false. In this case, the test will reject the null 5% of the time, using a significance threshold of 5%. The authors can easily confirm this for themselves with a simple simulation. Are the authors trying to make the point that the error rate is conditional not only on the null, but also on the test assumptions (and so when they are violated the test may reject erroneously?) They certainly do not state this, and the fact that they refer to 'identical distribution' suggests otherwise. Another way the test assumptions could be violated is if actual p-hacking (see examples above) were present, such that the reported p-values were no longer valid. Again, the authors do not tell us that this is what they mean, if they in fact do, and this would be a criticism of p-hacking behaviours rather than of the p-value.

When they write "big data can make insignificance seemingly significant by means of the classical p-value" they might be thinking of confusion between statistical and practical significance, which is a common misinterpretation made in the presence of large data size, but again, if this is what the authors are thinking of they should say it. The discussion by Greenland (Valid P-Values Behave Exactly as They Should: Some Misleading Criticisms of P-Values and Their Resolution With S-Values, especially section 4.3) seems to address the concerns raised by the authors fairly decisively. For a given parameter size, increasing sample size should produce stronger evidence against the null. The p-value does not tell you about the size of the parameter directly - it measures the discrepancy between the data and the null - interpreted correctly, there is no problem.

So, with apologies to the authors, I don't think they are successful in convincing the reader that there is a problem to be solved, and the manner of presentation (which may just be an issue of communicating the authors' intentions) is such that it causes doubt about the authors' handling of the relevant concepts. Throughout the text, there are other confusing presentations around fundamental concepts. E.g. the authors write things like "Hence, we claim that whenever there exist real statistically significant differences between two samples..." I know what a real difference is, but what is a real statistically significant difference? There are no statistically significant differences in nature. Are the authors trying to refer to instances where the null is false and is rejected? Or, are they trying to say that a 'real significant difference' is where the difference exceeds some magnitude?

For example - the authors write things such as "When 𝑁(0,1) is compared with 𝑁(0,1), 𝑁(0.01,1) and 𝑁(0.1,1), 𝜃 is null; so those distributions are assumed to be equal. In the remaining comparisons though, 𝜃 = 1, thus there exist differences between 𝑁(0,1) and 𝑁(𝜇,1) for 𝜇 ∈ [0.25,3]", highlighting the fact that perhaps the authors really want to address the practical significance vs statistical significance issue (although again, this is not explicitly stated). If the authors are interested in size of effect/ difference, then it is not clear that this proposal offers any advantage in that regard over the p-value (which, as noted, does not tell us about the size of a parameter). If interest is in size, then it is unclear why the authors do not direct the reader to consider the estimate and confidence interval, so that they may consider this explicitly in terms of magnitude and precision.

With apologies to the authors, who have clearly spent a large amount of time on this - I would think that the best way forward here would be to post this as a preprint and to try to invite as much feedback as possible. The authors have lofty ambitions with this work. Maybe there is a good underlying idea here, obscured by the presentation? Unfortunately, it is difficult to assess this at present.

Reviewer #1:

The paper sets out to confront p-hacking and addressing the dependence of the p-value on the sample size. The paper sets out the motivation behind the problem and then proposes a solution using three examples.

I have a major problem with this work in that I do not understand the motivation and hence cannot judge the value of the proposed solution.

The authors need to set out some definitions which might help them framing the context. I outline below what I understand as the context and hence why I do not understand how their proposal will address the problem.

Firstly 'p-hacking' is the term usually reserved for when researchers do not follow a pre-specified protocol on how a research question will be answered through the statistical analysis of a resource, single study or experiment, but instead analyse the data in many ways. Maybe they use slightly different assumptions, adjust the definition of an outlier or who is eligible for inclusion or adjust to a different outcome variable. In this manner they select to report the analysis that gives the smallest p-value. (Ioannidis referred to some of this as vibration effects) This is a major problem in science but it is not only the problem of the size of the data available. Although the bigger the dataset, the more subgroups that can be analysed. The main problem here is that we do not know how many ways the data have been analysed, we only know what researchers have selected to report. The manuscript does not address this problem at all.

The p-value is defined as the probability of observing a result as or more extreme when the null hypothesis is true. In most settings the 'null' is that there are no differences between two or more groups, for example that all the means are the same or equal. Often this translates into the statement that we expect the distribution of p-values under the null to be uniformly distributed [0,1]. This can be demonstrated or checked by simulation. In the hypothesis testing framework we usually power our studies so we will be able to detect a (true) difference between two groups with some high probability. The specific difference we are interested in would be called the alternative hypothesis. Hence the p-value is used to reject the null, but under the alternative hypothesis the p-value will not be uniform [0,1]. It is well known that the larger your sample size the more precise estimates you will obtain and the smaller differences you will be able to detect. Sample size calculations require a specific alternative to be stated (e.g. a difference in means of 0.5 of a standard deviation) then a sample size that guarantees as specific power for the specific type 1 error can be calculated.

This manuscript is confusing properties of the p-value when there are no differences and minimal differences between the two groups. I think the authors are trying to make the point that a statistically significant result is not necessarily a clinically or biologically meaningful result. They have done some simulations to show the distribution of the p-value when the true difference between the two means is 0.01. This is an example of an 'unimportant' difference, but it is not the null. This problem is best addressed by reporting effect sizes and 95% confidence intervals for quantities of interest rather than trying to adjust p-values in some way. Obviously when we have access to large datasets we may have a much larger sample than we needed to detect a meaningful effect though we may find small p-values. Adjusting the p-values will not really help as it is the effect sizes that are of interest.

I feel the manuscript needs to be redrafted to be more clear about the problem they are trying to fix.

This is the only useful idea in the text. Whatever we read has the context in which it was written and the context in whcih it is being read. Is this a hermeneutic circle as described earlier? Don't think so.

Author Response

We thank the editors and reviewers for taking the time to assess our paper. We note that the reviewers seemed generally supportive of the paper, including noting that the paper addressed important questions. For context, we reiterate here our main findings:

• a prefrontal cortex population encodes the past and the present in its joint activity, but solves the interference problem by encoding all features on independent axes for their past and their present.
• This encoding would in principle allow upstream regions to independently access representations of the past and present in mPfC populations. We go on to show this happens: we show that only the encoding of the present, and not the past, is reactivated in sleep after training.

In this context, the main editorial objection that we “did not control for potential confounding of behavioral variables” is not explained in the reviews; we also note that there were no “concerns about the analytical methods used” that were pertinent to our main findings. We are thus unclear about the basis for rejection.

We respond below to the main points of each reviewer; their suggestions on terminology and of separating literature citations on rodent and primate PfC are being given due consideration.

Reviewer #1:

Maggi and Humphries examined how the coding of the present and past choices in the medial prefrontal cortex (mPFC) of the rats during a Y-maze task overlaps and whether they can be reliably distinguished. They found that the neural signals related to the animal's choice in the present and past are distinct and as a result they can be recalled separately, for example, during post-training sleep. Although these are very important questions and an interesting set of analyses have been applied, the results in this report are not entirely convincing, because the analyses did not successfully exclude some alternative hypotheses.

1) The authors analyzed the signals related to the choice, light cue, and outcome separately, and this is possible because the relationship between the animal's choices and cues were decoupled by testing the animals under at least two different rules. There were a total of 4 alternative rules and different sessions included different subsets of these rules. It is possible that at least some results reported in this paper might vary depending on which of these results were tested. For example, rules might affect how the animals learned the task. Therefore, the authors should provide more detailed information about how often different rules were used to collect the neural data reported in this paper, and whether any of the results change according to the rules used in a given session.

In the paper we did examine mPfC encoding in the trials under the two qualitatively distinct types of rule (direction-based i.e. egocentric, and cue-based i.e. allocentric), and showed that encoding of the direction, light, and outcome occurred in both rule types (figure 1e). We gave the number of sessions for those rules in the legend for Figure 1e. (We could equally decode all 3 features in direction-based and cue-based rule sessions in the inter-trial interval as well, see Maggi et al 2018, Figure 9). Thus we compared the decoding vectors across all rule-types.

Only 8 sessions contained more than 1 rule, in the sessions in which the rule was switched. In the full analysis underlying this paper, we had also separately examined the decoding in these 8 rule-switch sessions, and found equally good decoding of direction, choice, and cue. As the paper was already dense - see e.g. Reviewer 3’s comments - we elected to not show this null result in the current version of the manuscript - it is available in version 1 of this preprint - but it can be restored if desired.

2) The authors claim that the neural coding identified in this study does not depend on the signals in individual neurons by showing comparable results after removing the neurons with significant modulations. This logic is flawed, because the neurons without "significant" modulations might still include meaningful signals due to type II errors. Furthermore, if individual neurons carry absolutely no signals, how can a population of neurons still encode any signals? This might suggest some kind of joint coding, and the authors should not merely implicate such a possibility without more thorough tests.

The joint coding of information by a population of neurons is the basis for the whole paper, and is tested extensively: for example, Figure 1 is about establishing that joint coding exists in mPfC. Our point on lines 91-95 was simply to show that the decoding could not be trivially explained by one or two neurons that reliably and strongly differed in the firing rates between different labels (e.g. between left or right choice of direction). To do so, we found sessions in which there were neurons with significantly detectable tuning to the task feature, omitted those sessions, and then looked at the performance of the feature decoding in the remaining sessions - and found it was just as good. Indeed, our point is precisely that it is possible for individual neurons to carry no signals detectable by classic significance testing (potentially due to Type II errors), yet for the population to be able to perfectly encode the information.

The explanation is simply that most, and sometimes all, individual neurons do not consistently covary their firing with the changes in a feature (e.g. choose left and choose right trials) across every trial of a session. In other words, no neuron need consistently participate in encoding information. But so long as when a neuron does change its firing it does consistently vary with the feature, then across a population there are enough intermittently participating neurons on a given trial to always decode the information.

3) The authors analyzed the activity divided into 5 different epochs, where the position #3 corresponds to a choice point and #5 corresponds to the reward site. Therefore, it is surprising that the reliable outcome signals begin to emerge from the position #3 (i.e., choice point). Is this a false positive?

No, this replicated a common finding of outcome-predictive signals in prefrontal cortex; e.g. Daw, N. D., O’Doherty, J. P., Dayan, P., Seymour, B. & Dolan, R. J. Cortical substrates for exploratory decisions in humans. Nature 441, 876–879 (2006).

Fellows, L. K. Advances in understanding ventromedial prefrontal function: the accountant joins the executive. Neurology 68, 991–995 (2007).

Sul, J. H., Kim, H., Huh, N., Lee, D. & Jung, M. W. Distinct roles of rodent orbitofrontal and medial prefrontal cortex in decision making. Neuron 66, 449–460 (2010).

Kaplan, R. et al. The neural representation of prospective choice during spatial planning and decisions. PLoS Biol. 15, e1002588 (2017).

We will add these references to the next version of the manuscript.

4) The authors report that there is retrospective coding, i.e., no coding of the choice in the previous. By contrast, during the intertrial interval (while the animal's returning to the start position), the signals related to the "past" choice were still present but different from how this information was coding earlier during the trial. This is not surprising since during the intertrial interval, the animal's movement direction is opposite compared to that during the trial, so this coding change could reflect the animal's sensory environment. Whether the brain encodes the past and previous events using different coding schemes or not cannot be tested with such confounding.

We note that the reviewer’s objection here only relates to the choice of arm direction, whereas we showed independent encoding of all three features: direction, outcome, and cue position. We can thus test how the past and present are differently encoded because we showed they are both encoded in the same set of neurons. We showed at length both here (Figure 2a&c, Supplementary Figure 5a) and in Maggi et al 2018 (Figs 5-6 and accompanying supplementary figures) that we could decode the past events from the population activity during the inter-trial interval. The information of the trial and the inter-trial interval can be decoded from the same neurons, so the question is: how can the same neurons encode both the present and the past?

One interpretation of the reviewer’s comments is that they are concerned about the possible confounding of movement direction between the trial and the following inter-trial interval. Namely, that the turn directions are guaranteed to be opposite: e.g a left turn into the left-hand arm on the trial would mean a right-hand turn on the return journey of the inter-trial interval. However, that would mean the feature labels would be exactly complementary e.g. trial =[L L R L R] and ITI = [R R L R L]. So if the population was encoding the direction choice the same way in both the trial and ITI, then using the trial’s decoder of direction to decode direction choice in the ITI should result in a performance of 1-[proportion of correctly classified trials], meaning the classifier would be significantly below chance (and vice-versa for using the inter-trial interval’s decoder for the trials). However, we find the cross-decoding performs at chance (Fig 2).

5) The authors tested whether the coding of present and past events is consistent using a transfer (cross-decoding) analysis. However, this is based on simply correlation, and does not exclude the possibility that neurons changing their activity similarly according to (for example) the animal's choice might also change their baseline activity between the two periods (as revealed by the analysis of "population activity" in Figure 3) or might additionally encode different variables. In this case, decoding based on simple correlation might not reveal consistent coding that might be present.

It is unclear what the referee means by the cross-decoding analysis being “based on simple correlation”. The decoder is trained on vectors of firing rates (cf Figure 1b). The decoder assigns high weights to neurons whose activity differs most strongly between the two labels (e.g. left and right choice of direction). So a change in “baseline”, presumably meaning the average firing rate of a neuron across all trials or all ITIs, would not alter the decoder outcome. In addition to the two cross-decoding tests, we also showed the independent encoding by: (a) The angles formed by the decoding vectors trained solely on the trials and solely on the ITIs (Fig 2d-f) (b) The independence of the population rate vectors between trials and ITIs (Fig 3). Indeed, the change in population rates between trials and ITIs shown in Figure 3 is exactly those predicted by the cross-decoding results, as explained on pg 7.

Reviewer #2:

The study by Maggi and Humphries re-examines data by Peyrache et al. (2009), which the authors have themselves analysed previously (Maggi et al., 2018), recorded , in rat prelimbic/infralimbic cortex (see comment below on terminology). In particular, they look at the relationship between decoding of task events during performance of a trial, and during the subsequent intertrial interval. (n.b. in this study, unlike in many studies, the ITI is considerably longer than the trial period). They find that although task-relevant information can be decoded during these two periods, the information is encoded in orthogonal subspaces during trials ('the present') and ITIs ('the past'). They build on this to examine how information is encoded during sleep following training (vs a pre-training control period). They find that only the trial subspaces are reactivated during sleep, not the ITI subspaces, and more so if the rat received a higher rate of average reward.

On the whole, I found this an interesting paper with a clear set of findings, and well-analysed data. Although the advance in some ways an incremental one on previous studies of sleep/replay, and on the authors' previous analyses of this dataset, the study will undoubtedly be of interest to researchers who are interested in consolidation of past experience during sleep. In particular, the study benefits from being able to look for two different types of information ('past' and 'present' decoders) in the same sleep recording sessions. There were a few things that I felt the authors could address:

1) For the cross-decoding analysis in figure 2 b, it is not entirely clear from the main text which part of the trial and ITI coding is being used here. It seems to me like a more useful way of showing the cross-decoding analysis would be to show the 10x10 matrix of cross decoding accuracy for each of the 5 maze positions in both trials and ITIs. This is, I think, different from what the analysis in figure 3g is trying to show (which plots the classification error after dimensionality reduction to a 2D space).

As we strived to explain in the text, for the cross-decoding analysis we used the decoder trained on the firing rates across the entire trial and separately across the entire ITI, in order to arrive at the most stable decoding vectors. We did not show the cross-decoding for the full 5x5 matrix of positions, as the results would be quite noisy. Nevertheless, this is a constructive suggestion, and we will add this analysis. (And indeed the analysis in Figure 3 already shows that the population activity is separable in 1 or 2 dimensions between the trials and ITIs at each maze position, so we would expect the decoder weight vectors to also be independent).

2) It was surprising to me that the authors do not mention the finding in figure 4e anywhere in the abstract or introduction. It makes the reactivation story far more compelling if it can be linked to a change in behaviour during the preceding trials. I think this finding would benefit from not being buried deep in the results section.

We are happy to make this result clearer. Our main finding is of the independent coding, and this result in Fig 4e does not speak directly to the independent coding results, but rather is a lovely little result to support the hypothesis that there really is reactivation of the population vectors in sleep. Because it did not speak to the main thrust of the paper, it was omitted from the abstract given the constraints on the number of words (150).

3) The finding in figure 5 seems slightly extra-ordinary. It suggests that reactivation decoding during sleep is reliable even if very long bins of activity are used to calculate the firing rate (e.g. up to 10s). Does this relationship ever break down? Presumably with the sleep data, it would be possible to extend bins up to 1 minute, 5 minutes, etc. If there is still more reactivation at these extremely long time-bin lengths, does this mean that these neurons are essentially more persistently active? One possible way to test for this might be to project the data recorded during sleep through the classifier weights, and then calculate the autocorrelation function of this projected data (e.g. Murray et al., Nat Neuro 2014) - if this activity becomes more persistent, the shape of the ACF may change post-training.

An excellent question. Rather than persistent activity, we interpreted the consistency of reactivation across orders of magnitude time-scales as showing that the correlations between the neurons were roughly consistent; and thus when active tended to be active in roughly the same relative order. Support for this comes from the findings in Appendix Fig A4e - the correlation matrix between neurons in the trial was more consistently found in post than pre-session sleep.

Reviewer #3:

This article asks the question if within trial (present) and ITI (past) task parameters are encoded in mPFC, and how encoding during these two trial epochs are encoded. They claim that firing in mPFC reflects past and present, but population encoding of past and present are independent. Further they show that the present is reactivated during sleep, not the past.

On the face of it, this seems like an interesting paper. It is novel in that ITI encoding would be highly related to what was going on in the trial. The sleep finding is also interesting but I don't quite get the distinction between present and past for sleep. That could use some clarification.

1) I'm not an expert in regards to this type of analysis, but throughout I was left with the feeling that I would prefer at least some single neuron data and firing rate analysis to complement the highly computational analysis, which frankly, was difficult to understand or critique by somebody who is not an expert.

The goal of the paper is to assess the population coding in PfC of the same events in the past and the present. Indeed, as reported in the paper, we found 25-39 sessions which had no single neuron tuning at all to a given event in a trial (such as the choice of maze arm).

2) I would have liked to see more analysis of firing correlations with behavior. It seems to me if animals were doing different things during the trial and the ITI, then it might not be a surprise that there is independent encoding.

3) I also wonder if the finding is solely dependent on the task (which is poorly described). It seems like there should be independent coding of past and present in this circumstance because they do not feed into each other, and behavior during one is independent of behavior in the other.

4) Relatedly, the authors suggest that independent encoding can explain how the brain resolves interference between past and present, but in this task there was no interference between past and present, and the authors do not show that when there is more or less dependent encoding that there is more or less interference. Without it is unclear how to know how important this finding is as it relates to performance and general mPFC function.

We deal with these points together, as they are all on the behaviour in the trial and inter-trial interval in the task. Yes, the behaviour in the trial is independent of that in the inter-trial interval, so there is no “interference” of behaviour. But that is not of relevance to what is encoded in the PfC. The Introduction and Discussion both point out that the problem is interference of the encoding itself: the encoding of the past and present exists, as we show at length, so the question is: how can it co-exist in the same neurons? We indeed ask if there is no “interference” in the encoding simply because activity in the inter-trial interval is just a memory trace of activity in the trial, and rule that out.

We cannot address when there is “more or less dependent” encoding, because the results are what they are: there is independent encoding of the same events (Figure 2).

The task is described in detail in the Methods (pgs 20-21).

5) Could activity reflect what the animal predicts will happen on the next trial, or what they are planning to do? It wasn't clear if that was examined.

Whether activity in the inter-trial interval predicted what will happen in the next trial was examined in detail in Maggi et al 2018 (Fig 6), and shown here in Figure 2g. We found no encoding of the following trial’s choices, except for a very niche occurrence: an above chance decoding of the next trial’s direction choice when the rat had returned to the start position, during a learning session, and for a direction rule. In other words, as it turned to start the next trial, so there was decoding of the upcoming choice of arm.

I also agree with this statement because it should be only under the law that has been established by the people that someone who seems to have committed a crime be deemed guilty. Until that point in time when the jury decides on a guilty verdict, the person should be treated as though they are innocent for individuals can not be arbitrators of justice. Doing so may lead to false accusations and wrongful imprisonment, which we see far too often today. So although I agree with the statement, I do not think that it is applied as it should be in the modern society.

"Advocating invading countries with mass forms of slow-motion toxicity, however, requires rethinking our accepted assumptions of violence to include slow violence." Because it's not what we typically think when we think of violence, its prioritization may be delayed in the news and our perception and response may not be as emergent as it should be.

Also the valences of publishing in these different areas has markedly changed over my parent's lifetime...

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Reply to the reviewers

This is a fascinating and beautifully written article about the possible evolutionary relationship between two major protein superfamilies - the P-loop NTPases and the Rossmans. Both are ancient and highly diverse superfamilies, containing a significant proportion of all extant domain sequences and were probably amongst the earliest enzyme superfamilies to emerge in evolution. No major evolutionary classification of proteins, such as SCOP, reports evolutionary relationships between them.

Both share the same structural architecture of a beta-alpha-beta 3-layer sandwich and have an intriguing number of other shared structural features including the location of the binding site for phospho-ligands. However, whilst both bind phosphorylated ribonucleosides, the mode of binding differs and also the manner in which these compounds are exploited. Furthermore, there are differences in the topologies of the folds possibly suggesting distinct evolutionary trajectories. The Rossmanns appear to be more structurally conserved, whilst the P-Loops vary more in their topologies and possibly represent less stable arrangements of beta-sheets and alpha-helices. The authors have brought together several strands of evidence to explore possibly evolutionary relationships. Detailed structural analyses allow the authors to explicitly detail the significant shared structural features. For example, similarities in the mode of binding the phosphate moiety in the ligand. The structural features are well described and there are appropriate illustrations visualising key differences and similarities. The shared features of the phosphate binding site likely emerged and were favoured early in evolution, as supported by other analyses reported by Longo et al. However, as the authors point out there are other compelling similarities including the equivalent location of this site in the first beta-loop-alpha element in both superfamilies, which is not a necessary constraint of phosphate binding and the authors support this by giving examples of phosphate binding at the tip of alpha-4. In addition, they provide evidence supporting the common involvement of beta-2 which contains the conserved Asp in the Rossmanns common ancestor. The Walker-B Asp in the P-loops is also at the tip of the beta-strand adjacent to beta-1, as in the Rossmanns - although this is an inserted strand relative to the Rossmann topology. The authors propose feasible evolutionary scenarios for how the P-Loops and Rossmans may have diverged to acquire additional secondary structure elements extending the common beta-PBL-alpha-beta-Asp feature present in both superfamilies. Further compelling evidence is given by detection of a bridging protein - Tubulin - linking the two superfamilies. This has the distinct Rossmann topology but binds GTP in the P-loop NTPase mode. Furthermore, the GTP is hydrolysed by water activated by a ligated metal dication. Final support is given by reporting common sequence themes between the P-loop enzyme HPr kinase/phosphatase and some Rossmann proteins. The authors present further interesting and detailed analyses of similarities between the proteins sharing this unusual theme. The evidence provided by the authors for the shared beta-PBL-alpha-beta-Asp fragment seems very strong to me and has been presented in an interesting and informative way. Of course, it is not possible to know the subsequent evolutionary trajectories but the scenarios presented seem plausible.

We thank the reviewer for their encouraging remarks on our manuscript.

**I only have minor comments** 1) SCOP2 provides information on links between superfamilies based on rare sequence or structural features. Have the authors checked this resource for any details on beta-PBL-alpha-beta-ASP fragment? Or perhaps consulted with Alexey Murzin about this feature?

The classification of Rossmann and P-Loop proteins in SCOP2 is consistent with the ECOD classification scheme. For further confirmation, we wrote Alexey Murzin and he replied that Rosmanns and P-Loops are annotated as two separate evolutionary lineages, termed “hyperfamilies” in SCOP2. He found our new evidence compelling, but that given the current criteria for shared ancestry, P-loops and Rossmanns are separate lineages.

2) I was rather confused by the way in which EC annotations were collected for the two superfamilies ie via Pfam – wouldn’t it be better to use SUPERFAMILY as the domain structures would map directly to these sequence relatives. I’m also surprised that they only took the common EC from a Pfam family since the aim of this analysis was to identify how many different enzyme functions the two superfamilies supported. Pfam does not classify by function and so inevitably groups functionally diverse relatives. However, to get the full range of enzyme functions supported by these superfamilies I would have thought all non-redundant EC functions across these constituent Pfam families should be counted. Perhaps I have misunderstood.

We have updated the analysis to make use of the SUPERFAMILY database and, as per your suggestion, we now count all non-redundant EC numbers. Although the EC number counts have somewhat changed, the major point – that these are exceptionally diverse evolutionary lineages – has not.

3) The authors refer to a set of previously curated ‘themes’ and allude to a methodology that will be reported in a forthcoming manuscript. The idea of identifying rare themes and then using them to locate very distant homologues is appealing. However, I think some details should be provided here. For example, some brief details on the technology for detecting the themes and thresholds on significance. How rare are they and how conserved do these fragments need to be between superfamilies to join their curated list? Furthermore, how many of these curated themes are similar to the one reported in their article and do they get crosslinks to other superfamilies based on closely related themes? ie how unique is this theme to the P-loop and Rossmanns and are there closely related themes linking these two superfamilies to other superfamilies? I would imagine it is quite a distinct theme but I would have liked to see a few more details on this to reassure that there are no closely related themes.

We have updated the manuscript to include a more detailed description of the methods used to detect bridging themes shared between the Rossmann and P-Loop evolutionary lineages. In addition, we now include a supplemental table (Table S2) with all of the initial hits from the theme analysis.

4) The authors have built model structures to allow them to estimate ligand location in proteins with no structural characterisation. It would be helpful if they reported the degree of sequence similarity between the query and template proteins and also the model quality.

We have updated this section to include more details. In addition, we have identified a structure from the same T-group to serve as our ligand donor. The updated ligand donor is more closely related to 1ko7 than the previous ligand donor, though the positioning of the ligand is effectively unchanged. We note that the global sequence identity to both the previous and new ligand donor is low (less than 30% sequence identity). However, the phosphate binding loops align well in both sequence and structure, as is detailed in the revised Methods section.

The study by Longo et al. was devoted to evolutionary history of P-loop NTPases and Rossmann fold proteins. Although not related in sequence, the two protein families share some structural features that imply that they could be diverged from a common ancestor. Using bioinformatic analyses, the study under review identified some bridge proteins (of tubulin family) that share themes of both P-loops and Rossmanns, offering a possible support for the common ancestry. A minimum ancestral peptide structure is proposed based on the analysis and its possible diversification trajectory is hypothesized. Even though the divergence scenario is clearly outlined, the authors do not over-interpret the observations and admit that convergence could still explain the scenario. The methodology and results are sufficiently described and conclusions are explained in detail. Although it would be really interesting to design an experimental study to support the conclusion (and I suppose that the authors will do that), that is clearly outside the scope of this bioinformatic study.

Obtaining experimental evidence for our hypothesis is far from trivial. Modern proteins, including the bridging ones identified here, may not be amenable to exchange due to differing contexts (epistasis). Still, we agree that highlighting experimental directions is a good idea. We have updated the sections From an ancestral seed to intact domains and Conclusion to include a brief discussion of experiments that may help test our hypotheses about the evolution of these protein lineages.

I would not propose any major changes to the manuscript as I think that the message is very clear. **Minor comments:** (1)In the results section, the text is very clear but tends to be repetitive in places. I think the manuscript would be more easily readable if more to the point at some sections.

We have edited the manuscript to remove cases of unnecessary repetition in the results section and throughout.

(2)There is probably a few typos or unclear sentences, e.g. pg 5, mid-page, "The core, most common topology...); pg 12, three lines from the bottom "(where this element in canonical", probably should be "is canonical"; pg 11, mid page "the mode of binding of the catalytic dication of tubuling (often Ca2+)" - all the structures listed in Table S1 list Mg2+, so "often" is a bit misleading.

We have corrected the unclear sentences and typos noted above, as well as a few others.

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Two-Byte Characters

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Strings which contain two-byte characters: can cause rendering issues or character-length issues

田中さんにあげて下さい パーティーへ行かないか 和製漢語 部落格 사회과학원 어학연구소 찦차를 타고 온 펲시맨과 쑛다리 똠방각하 社會科學院語學研究所 울란바토르 𠜎𠜱𠝹𠱓𠱸𠲖𠳏

Strings which contain two-byte letters: can cause issues with naïve UTF-16 capitalizers which think that 16 bits == 1 character

𐐜 𐐔𐐇𐐝𐐀𐐡𐐇𐐓 𐐙𐐊𐐡𐐝𐐓/𐐝𐐇𐐗𐐊𐐤𐐔 𐐒𐐋𐐗 𐐒𐐌 𐐜 𐐡𐐀𐐖𐐇𐐤𐐓𐐝 𐐱𐑂 𐑄 𐐔𐐇𐐝𐐀𐐡𐐇𐐓 𐐏𐐆𐐅𐐤𐐆𐐚𐐊𐐡𐐝𐐆𐐓𐐆

Special Unicode Characters Union

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A super string recommended by VMware Inc. Globalization Team: can effectively cause rendering issues or character-length issues to validate product globalization readiness.

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表 CJK_UNIFIED_IDEOGRAPHS (U+8868)

ポ KATAKANA LETTER PO (U+30DD)

あ HIRAGANA LETTER A (U+3042)

A LATIN CAPITAL LETTER A (U+0041)

鷗 CJK_UNIFIED_IDEOGRAPHS (U+9DD7)

ΠLATIN SMALL LIGATURE OE (U+0153)

é LATIN SMALL LETTER E WITH ACUTE (U+00E9)

Ｂ FULLWIDTH LATIN CAPITAL LETTER B (U+FF22)

逍 CJK_UNIFIED_IDEOGRAPHS (U+900D)

Ü LATIN SMALL LETTER U WITH DIAERESIS (U+00FC)

ß LATIN SMALL LETTER SHARP S (U+00DF)

ª FEMININE ORDINAL INDICATOR (U+00AA)

ą LATIN SMALL LETTER A WITH OGONEK (U+0105)

ñ LATIN SMALL LETTER N WITH TILDE (U+00F1)

丂 CJK_UNIFIED_IDEOGRAPHS (U+4E02)

㐀 CJK Ideograph Extension A, First (U+3400)

𠀀 CJK Ideograph Extension B, First (U+20000)

表ポあA鷗ŒéＢ逍Üߪąñ丂㐀𠀀

Changing length when lowercased

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Characters which increase in length (2 to 3 bytes) when lowercased

Credit: https://twitter.com/jifa/status/625776454479970304

Ⱥ Ⱦ

Japanese Emoticons

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Strings which consists of Japanese-style emoticons which are popular on the web

ヽ༼ຈل͜ຈ༽ﾉ ヽ༼ຈل͜ຈ༽ﾉ (｡◕ ∀ ◕｡) ｀ｨ(´∀｀∩ _ﾛ(,,) ・(￣∀￣)・:: ﾟ･✿ヾ╲(｡◕‿◕｡)╱✿･ﾟ ,。・::・゜’( ☻ ω ☻ )。・::・゜’ (╯°□°）╯︵ ┻━┻) (ﾉಥ益ಥ）ﾉ ┻━┻ ┬─┬ノ( º ºノ) ( ͡° ͜ʖ ͡°) ¯\(ツ)_/¯

Emoji

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Strings which contain Emoji; should be the same behavior as two-byte characters, but not always

😍 👩🏽 👨‍🦰 👨🏿‍🦰 👨‍🦱 👨🏿‍🦱 🦹🏿‍♂️ 👾 🙇 💁 🙅 🙆 🙋 🙎 🙍 🐵 🙈 🙉 🙊 ❤️ 💔 💌 💕 💞 💓 💗 💖 💘 💝 💟 💜 💛 💚 💙 ✋🏿 💪🏿 👐🏿 🙌🏿 👏🏿 🙏🏿 👨‍👩‍👦 👨‍👩‍👧‍👦 👨‍👨‍👦 👩‍👩‍👧 👨‍👦 👨‍👧‍👦 👩‍👦 👩‍👧‍👦 🚾 🆒 🆓 🆕 🆖 🆗 🆙 🏧 0️⃣ 1️⃣ 2️⃣ 3️⃣ 4️⃣ 5️⃣ 6️⃣ 7️⃣ 8️⃣ 9️⃣ 🔟

Regional Indicator Symbols

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Regional Indicator Symbols can be displayed differently across

fonts, and have a number of special behaviors

🇺🇸🇷🇺🇸 🇦🇫🇦🇲🇸 🇺🇸🇷🇺🇸🇦🇫🇦🇲 🇺🇸🇷🇺🇸🇦

Unicode Numbers

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Strings which contain unicode numbers; if the code is localized, it should see the input as numeric

１２３ ١٢٣

Right-To-Left Strings

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Strings which contain text that should be rendered RTL if possible (e.g. Arabic, Hebrew)

ثم نفس سقطت وبالتحديد،, جزيرتي باستخدام أن دنو. إذ هنا؟ الستار وتنصيب كان. أهّل ايطاليا، بريطانيا-فرنسا قد أخذ. سليمان، إتفاقية بين ما, يذكر الحدود أي بعد, معاملة بولندا، الإطلاق عل إيو. בְּרֵאשִׁית, בָּרָא אֱלֹהִים, אֵת הַשָּׁמַיִם, וְאֵת הָאָרֶץ הָיְתָהtestالصفحات التّحول ﷽ ﷺ مُنَاقَشَةُ سُبُلِ اِسْتِخْدَامِ اللُّغَةِ فِي النُّظُمِ الْقَائِمَةِ وَفِيم يَخُصَّ التَّطْبِيقَاتُ الْحاسُوبِيَّةُ، الكل في المجمو عة (5)

Ogham Text

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The only unicode alphabet to use a space which isn't empty but should still act like a space.

᚛ᚄᚓᚐᚋᚒᚄ ᚑᚄᚂᚑᚏᚅ᚜ ᚛                 ᚜

Trick Unicode

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Strings which contain unicode with unusual properties (e.g. Right-to-left override) (c.f. http://www.unicode.org/charts/PDF/U2000.pdf)

‪‪test‪ ‫test‫ 
test
 test⁠test‫ ⁦test⁧

Zalgo Text

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Strings which contain "corrupted" text. The corruption will not appear in non-HTML text, however. (via http://www.eeemo.net)

Ṱ̺̺̕o͞ ̷i̲̬͇̪͙n̝̗͕v̟̜̘̦͟o̶̙̰̠kè͚̮̺̪̹̱̤ ̖t̝͕̳̣̻̪͞h̼͓̲̦̳̘̲e͇̣̰̦̬͎ ̢̼̻̱̘h͚͎͙̜̣̲ͅi̦̲̣̰̤v̻͍e̺̭̳̪̰-m̢iͅn̖̺̞̲̯̰d̵̼̟͙̩̼̘̳ ̞̥̱̳̭r̛̗̘e͙p͠r̼̞̻̭̗e̺̠̣͟s̘͇̳͍̝͉e͉̥̯̞̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ͏͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣ ̡͓̞ͅI̗̘̦͝n͇͇͙v̮̫ok̲̫̙͈i̖͙̭̹̠̞n̡̻̮̣̺g̲͈͙̭͙̬͎ ̰t͔̦h̞̲e̢̤ ͍̬̲͖f̴̘͕̣è͖ẹ̥̩l͖͔͚i͓͚̦͠n͖͍̗͓̳̮g͍ ̨o͚̪͡f̘̣̬ ̖̘͖̟͙̮c҉͔̫͖͓͇͖ͅh̵̤̣͚͔á̗̼͕ͅo̼̣̥s̱͈̺̖̦̻͢.̛̖̞̠̫̰ ̗̺͖̹̯͓Ṯ̤͍̥͇͈h̲́e͏͓̼̗̙̼̣͔ ͇̜̱̠͓͍ͅN͕͠e̗̱z̘̝̜̺͙p̤̺̹͍̯͚e̠̻̠͜r̨̤͍̺̖͔̖̖d̠̟̭̬̝͟i̦͖̩͓͔̤a̠̗̬͉̙n͚͜ ̻̞̰͚ͅh̵͉i̳̞v̢͇ḙ͎͟-҉̭̩̼͔m̤̭̫i͕͇̝̦n̗͙ḍ̟ ̯̲͕͞ǫ̟̯̰̲͙̻̝f ̪̰̰̗̖̭̘͘c̦͍̲̞͍̩̙ḥ͚a̮͎̟̙͜ơ̩̹͎s̤.̝̝ ҉Z̡̖̜͖̰̣͉̜a͖̰͙̬͡l̲̫̳͍̩g̡̟̼̱͚̞̬ͅo̗͜.̟ ̦H̬̤̗̤͝e͜ ̜̥̝̻͍̟́w̕h̖̯͓o̝͙̖͎̱̮ ҉̺̙̞̟͈W̷̼̭a̺̪͍į͈͕̭͙̯̜t̶̼̮s̘͙͖̕ ̠̫̠B̻͍͙͉̳ͅe̵h̵̬͇̫͙i̹͓̳̳̮͎̫̕n͟d̴̪̜̖ ̰͉̩͇͙̲͞ͅT͖̼͓̪͢h͏͓̮̻e̬̝̟ͅ ̤̹̝W͙̞̝͔͇͝ͅa͏͓͔̹̼̣l̴͔̰̤̟͔ḽ̫.͕ Z̮̞̠͙͔ͅḀ̗̞͈̻̗Ḷ͙͎̯̹̞͓G̻O̭̗̮

Unicode Upsidedown

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Strings which contain unicode with an "upsidedown" effect (via http://www.upsidedowntext.com)

˙ɐnbᴉlɐ ɐuƃɐɯ ǝɹolop ʇǝ ǝɹoqɐl ʇn ʇunpᴉpᴉɔuᴉ ɹodɯǝʇ poɯsnᴉǝ op pǝs 'ʇᴉlǝ ƃuᴉɔsᴉdᴉpɐ ɹnʇǝʇɔǝsuoɔ 'ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥ 00˙Ɩ$-

Unicode font

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Strings which contain bold/italic/etc. versions of normal characters

Ｔｈｅ ｑｕｉｃｋ ｂｒｏｗｎ ｆｏｘ ｊｕｍｐｓ ｏｖｅｒ ｔｈｅ ｌａｚｙ ｄｏｇ 𝐓𝐡𝐞 𝐪𝐮𝐢𝐜𝐤 𝐛𝐫𝐨𝐰𝐧 𝐟𝐨𝐱 𝐣𝐮𝐦𝐩𝐬 𝐨𝐯𝐞𝐫 𝐭𝐡𝐞 𝐥𝐚𝐳𝐲 𝐝𝐨𝐠 𝕿𝖍𝖊 𝖖𝖚𝖎𝖈𝖐 𝖇𝖗𝖔𝖜𝖓 𝖋𝖔𝖝 𝖏𝖚𝖒𝖕𝖘 𝖔𝖛𝖊𝖗 𝖙𝖍𝖊 𝖑𝖆𝖟𝖞 𝖉𝖔𝖌 𝑻𝒉𝒆 𝒒𝒖𝒊𝒄𝒌 𝒃𝒓𝒐𝒘𝒏 𝒇𝒐𝒙 𝒋𝒖𝒎𝒑𝒔 𝒐𝒗𝒆𝒓 𝒕𝒉𝒆 𝒍𝒂𝒛𝒚 𝒅𝒐𝒈 𝓣𝓱𝓮 𝓺𝓾𝓲𝓬𝓴 𝓫𝓻𝓸𝔀𝓷 𝓯𝓸𝔁 𝓳𝓾𝓶𝓹𝓼 𝓸𝓿𝓮𝓻 𝓽𝓱𝓮 𝓵𝓪𝔃𝔂 𝓭𝓸𝓰 𝕋𝕙𝕖 𝕢𝕦𝕚𝕔𝕜 𝕓𝕣𝕠𝕨𝕟 𝕗𝕠𝕩 𝕛𝕦𝕞𝕡𝕤 𝕠𝕧𝕖𝕣 𝕥𝕙𝕖 𝕝𝕒𝕫𝕪 𝕕𝕠𝕘 𝚃𝚑𝚎 𝚚𝚞𝚒𝚌𝚔 𝚋𝚛𝚘𝚠𝚗 𝚏𝚘𝚡 𝚓𝚞𝚖𝚙𝚜 𝚘𝚟𝚎𝚛 𝚝𝚑𝚎 𝚕𝚊𝚣𝚢 𝚍𝚘𝚐 ⒯⒣⒠ ⒬⒰⒤⒞⒦ ⒝⒭⒪⒲⒩ ⒡⒪⒳ ⒥⒰⒨⒫⒮ ⒪⒱⒠⒭ ⒯⒣⒠ ⒧⒜⒵⒴ ⒟⒪⒢

Script Injection

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Strings which attempt to invoke a benign script injection; shows vulnerability to XSS

SQL Injection

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Strings which can cause a SQL injection if inputs are not sanitized

1;DROP TABLE users 1'; DROP TABLE users-- 1 ' OR 1=1 -- 1 ' OR '1'='1 '; EXEC sp_MSForEachTable 'DROP TABLE ?'; --

% _

Server Code Injection

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Strings which can cause user to run code on server as a privileged user (c.f. https://news.ycombinator.com/item?id=7665153)

-

--version --help $USER /dev/null; touch /tmp/blns.fail ; echo touch /tmp/blns.fail $(touch /tmp/blns.fail) @{[system "touch /tmp/blns.fail"]}

Command Injection (Ruby)

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Strings which can call system commands within Ruby/Rails applications

eval("puts 'hello world'") System("ls -al /") ls -al / Kernel.exec("ls -al /") Kernel.exit(1) %x('ls -al /')

XXE Injection (XML)

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String which can reveal system files when parsed by a badly configured XML parser

<?xml version="1.0" encoding="ISO-8859-1"?><!DOCTYPE foo [ <!ELEMENT foo ANY ><!ENTITY xxe SYSTEM "file:///etc/passwd" >]><foo>&xx;;</foo>

Unwanted Interpolation

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Strings which can be accidentally expanded into different strings if evaluated in the wrong context, e.g. used as a printf format string or via Perl or shell eval. Might expose sensitive data from the program doing the interpolation, or might just represent the wrong string.

$HOME $ENV{'HOME'} %d %s%s%s%s%s {0} %.s %@ %n File:///

File Inclusion

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Strings which can cause user to pull in files that should not be a part of a web server

../../../../../../../../../../../etc/passwd%00 ../../../../../../../../../../../etc/hosts

Known CVEs and Vulnerabilities

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Strings that test for known vulnerabilities

() { 0; }; touch /tmp/blns.shellshock1.fail; () { ; } >[$($())] { touch /tmp/blns.shellshock2.fail; } <<< %s(un='%s') = %u +++ATH0

MSDOS/Windows Special Filenames

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Strings which are reserved characters in MSDOS/Windows

CON PRN AUX CLOCK$ NUL A: ZZ: COM1 LPT1 LPT2 LPT3 COM2 COM3 COM4

IRC specific strings

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Strings that may occur on IRC clients that make security products freak out

DCC SEND STARTKEYLOGGER 0 0 0

Scunthorpe Problem

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Innocuous strings which may be blocked by profanity filters (https://en.wikipedia.org/wiki/Scunthorpe_problem)

Scunthorpe General Hospital Penistone Community Church Lightwater Country Park Jimmy Clitheroe Horniman Museum shitake mushrooms RomansInSussex.co.uk http://www.cum.qc.ca/ Craig Cockburn, Software Specialist Linda Callahan Dr. Herman I. Libshitz magna cum laude Super Bowl XXX medieval erection of parapets evaluate mocha expression Arsenal canal classic Tyson Gay Dick Van Dyke basement

Human injection

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Strings which may cause human to reinterpret worldview

If you're reading this, you've been in a coma for almost 20 years now. We're trying a new technique. We don't know where this message will end up in your dream, but we hope it works. Please wake up, we miss you.

Terminal escape codes

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Strings which punish the fools who use cat/type on this file

Roses are ?[0;31mred?[0m, violets are ?[0;34mblue. Hope you enjoy terminal hue But now...?[20Cfor my greatest trick...?[8m The quic??????k brown fo???????????x... [Beeeep]

iOS Vulnerabilities

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Strings which crashed iMessage in various versions of iOS

Powerلُلُصّبُلُلصّبُررً ॣ ॣh ॣ ॣ冗 🏳0🌈️ జ్ఞ‌ా

Persian special characters

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This is a four characters string which includes Persian special characters (گچپژ)

گچپژ

jinja2 injection

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first one is supposed to raise "MemoryError" exception

second, obviously, prints contents of /etc/passwd

{% print 'x' 64 1024**3 %} {{ "".class.mro[2].subclasses()40.read() }}

question 7. Another perspective to take into account is that they were locked down below the ships main surface and one of the crew members noticed Olaudahs curiosity of looking out the ship so he allowed him to. Makes me begin to think this may not of been to be nice, but to remind him of how little freedom he has. How his only time to experience this is while being enslaved looking out, and not being able to experience this in the way that the crew members could.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

RESPONSE TO REVIEWER #1

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

In this manuscript, Ishihara et al. investigate and compare microtubule polymerization/depolymerization dynamics inside vs. at the periphery of microtubule asters in a cell-free Xenopus egg extract system. By tracking EB comets, which localize to growing microtubule ends, they find that the microtubule growth rates and EB comet lifetimes (interpreted as an indicator of microtubule catastrophe rates) are similar between the two spatially-distinct microtubule populations. However, using a tubulin-intensity-difference image analysis, the authors are also able to measure local microtubule depolymerization rates, and they find a significant difference in depolymerization rates of the two populations. Specifically, the authors report that the microtubule depolymerization rates measured within asters are faster than those measured at the periphery.

\*Specific comments:***

Figure 2.

In the text, the authors report: "The depolymerization rate was 36.3 {plus minus} 7.9 μm/min (mean, std) in the aster interior, compared to 29.2 {plus minus} 8.9 μm/min (mean, std) at the aster periphery." This difference is certainly not two-fold (as stated in the abstract). It would also be useful to mark the mean rates on the graph in 2B.

We removed the words ‘almost two-fold’ in the abstract. In the revision, we will mark the mean rates on Fig. 2B (using vertical lines).

The bimodal shape of the depolymerization rate distributions in 2B is very interesting. This definitely warrants further investigation. At the minimum, the depolymerization rates should be determined at 50 um- intervals, as done for other parameters in Figure 1. Could it be that there are two coexisting populations of microtubules at the same location? Or is there a clear spatial compartmentalization of the two that is not obvious here because of the too large of a distance interval used for the measurements. This is a very important distinction for the claims of the paper.

We understand the reviewer’s concern. There are some technical limitations that make the depolymerization measurement more challenging. While we use widefield imaging of EB1-GFP comets to obtain polymerization rates from a field of view spanning 500 microns, we may only use TIRF imaging for depolymerization measurements. In this method, we are limited to observing microtubules very close to the cover slip in a small field of view of 80x80 microns at 500 ms time intervals (movies span 1-2 minutes). One would need to move the TIRF field every 1-2 minutes at 50 micron intervals, but the aster periphery would be changing during this time, so the exact location of the measurement is hard to define. Thus, we opted to image the two spatial extremes: interior (close to the MTOCs) and the very periphery (where MT density is still sparse.)

Perhaps, the largest limitation of this approach is the choice of peripheral regions based on the apparent sparsity of MTs in the TIRF field of view. Indeed, when we examine the depolymerization rate distributions for individual movies separately (see figure below, periphery #1-3 are three individual movies), we observe that some movies have rates as low as 20 µm/min, while others have higher values with a center around 36 µm/min. The depolymerization rates for the interior also vary from the mean values of 34.8-43.2 µm/min (interior #1-3 are three individual movies). In general, the spread of depolymerization rate within a field of view as well as across different fields of view is much larger than for polymerization. It is possible that this is partly explained by the lack of precise definition of interior vs. periphery in this TIRF-based measurement approach.

Our data still supports the spatial regulation of depolymerization rate. However, there is no clear evidence for a bimodal distribution of depolymerization rate in any given field of view (80x80 micron square region). To clarify this point, we have removed the language “bimodal” in the main text. In the revisions, we will provide this figure as a supplement.

We thank the critical feedback from reviewer #1 and #2 that allowed us to clarify this issue of apparent bimodality of the depolymerization rates.

The authors make a point here that the distribution of measured polymerization rates is fairly narrow. This appears to be in contrast with Figure 1B, where polymerization rates take on a wide range of values. How do the two distributions of polymerization rates obtained by these two methods compare?

To address this point, we directly compare the standard deviation of the polymerization rate measurements. For Fig. 1B EB1 tracking measurements, std ranges from 7.7-10.5 µm/min for a given spatial bin (as stated in Fig. 1B legend), while for Fig. 2A TIRF measurements std is 4.0 (periphery) and 4.5 µm/min (interior) as stated in the main text. Given that the mean values of polymerization rates are similar, this suggests that the TIRF measurements are less noisy. This further highlights the relative pros and cons of the two measurement methods. To discuss these issues, we have added a new paragraph in the discussion section.

Figure 3.

The laser ablation figure and movies are beautiful, but don't seem to add support to the story. Importantly, the authors do not confirm any spatial variability in depolymerization rate with these experiment. As a matter of fact, although the laser ablation experiments are only performed in the aster interior, the measured depolymerization rates appear to be just as consistent with the periphery rates in Figure 2. as they are with the interior rates in Figure 2. (They span quite a large range of values with the average right in the middle between what was measured for the two areas in Figure 2).

Indeed, the values obtained with laser ablation are quite variable, even compared to the physiological depolymerization rate measured via TIRF microscopy. This perhaps reflects the variability of biology as well as the nature of the laser ablation which measures depolymerization rate at the level of microtubule populations. We hope our paper will increase interest in this rarely measured parameter, and perhaps invention of new probes to measure it more accurately and conveniently.

Given the variability of our measurements, we conclude that the results between the TIRF based approach vs. laser ablation based approach of depolymerization rates are indistinguishable. We agree with the reviewer that the data does NOT argue that laser ablation results are more consistent with the interior TIRF measurements than peripheral TIRF measurements.

To clarify this point, we remove the following clause “, which was comparable to the modal value of the depolymerization rates in the aster interior (Fig. 2).”

We change the concluding sentence of our laser ablation paragraph from

“Overall, these observations suggest that depolymerization dynamics are similar for plus ends following a natural catastrophe vs. ablation in the aster interior.”

to

“Overall, these observations confirm that depolymerization rates are variable, and we find no statistical distinction of rates between plus ends following a natural catastrophe vs. ablation.”

Although the authors report they don't see any correlation between the distance and depolymerization rate, they should still plot the rate as a function of initial cut positions (Figures 3D, 3E).

To address this concern, we plan to provide a supplemental figure in the revision. Please see the preliminary figure below. Due to technical limitations with the laser ablation system (field of view for 60x magnification), we only have measurements that span 15-100 microns from the center..

From the single decaying inward wave the authors conclude that microtubules depolymerize fully to their minus ends which are distributed throughout the aster. Can the possibility that depolymerization is stopped by microtubule lattice defects/islands be excluded by these observations?

The existence of microtubule lattice/defects is a recent development in the field and much is not known. If we assume that defects are structurally unstable, we predict that the episode of depolymerization will continue even when reaching a defect. If defects are stable and lead to instantaneous rescue of plus ends, we cannot distinguish the defects from minus ends. In this latter scenario, the interpretation of the decaying inward wave requires caution.

What are the effects of the local increase in tubulin concentration due to the subunit release by depolymerization? What about the release of other lattice-binding MAPs (stabilizers)?

We are interested in these questions as well. Soluble GDP-bound tubulin, released by depolymerization, is thought to exchange its nucleotide to GTP without need of a GEF, and no GEF is known. The dissociation rate of GDP is ~0.1 [1/sec], for a half-life of ~5 sec (Brylawski and Caplow, 1983, J. of Biol. Chem.), so we believe the tubulin subunits are recycled relatively quickly. It is not entirely obvious whether this necessarily results in a significant increase in ‘soluble’ tubulin concentration given tubulin diffusive transport. We hypothesize the main effect of stabilizing MAPs is on the depolymerization rate as discussed in our model in Fig. 5.

Figure 4.

Is the local depletion of tubulin/EB1 thought to be only within the narrow annulus at ~100 um distance, or is it not measurable on the inside due to the polymer signal? Can the two be separated? Such a sharp transition within a discrete annular region doesn't speak to the relative effects on the inside vs. the outside of the aster?!

Yes, we also believe the soluble tubulin levels are even lower in the more inner regions of the aster. However, polymerized tubulin accounts for a large part of the fluorescence intensity in these inner regions, and our method does not faithfully reflect the soluble fraction. It will be important for future studies to employ specific methods that may unequivocally distinguish polymer vs. soluble tubulin concentrations (see below).

More importantly, the local depletion of either tubulin or EB1 is not a good representation of a depletion of a MAP component that associates with the microtubule lattice. Both tubulin and EB1 bind preferably to microtubule ends, not lattice. Thus showing a profile of slight local tubulin and/or EB depletion does not seem to be relevant for the proposed model. Rather, overall microtubule polymer mass/density as a function of distance may be more relevant?

Reviewer #1 makes a valid point that tubulin and EB1 are specifically incorporated to plus ends and not to the entire lattice as we assume for the MAPs in our theoretical model. To address this issue, we analyzed the fluorescence intensity of images obtained for a MAP that associates with the MT lattice, Tau-mCherry (Mooney et al. 2017). This quantification shows a depletion pattern similar to tubulin and EB1. Thus, we believe the local depletion is a general feature. For the revision, we plan to incorporate this Tau-mCherry data in Fig. 4.

Figure 5.

The toy model is intuitive and clear, but not sufficient without any experimental investigation. An attempt to quantify the actual distributions of at least one or a few selected proposed MAPs is needed. Is the depletion strongest where microtubule density is highest? What is the ratio of a MAP intensity to microtubule polymer density as a function of distance? How does that relate to local depolymerization rates? What are other testable model predictions that can show support for the proposed mechanism?

We understand that our proposal is rather speculative, and the goal of this manuscript was to propose a hypothesis that may inspire others working on assembly on intracellular organelles. Although Tau is not an endogenous component of the egg extract system, we believe that our new quantification of Tau-mCherry depletion adds more credibility to our general proposal.

Microtubule density is roughly uniform within the interior of the aster according to our current understanding (Ishihara et al. 2016 eLife). So the MAP:MT ratio is relatively uniform throughout the aster except at the very periphery where there are very few MTs assembled (i.e. “depletion is weakest where MT density is lowest.”)

In the future, we may perform (1) FCS measurements of candidate MAPs to directly measure the concentration profile of the candidate MAP in soluble form and (2) depletion/addback to show which MAP most affects depolymerization rate. Although these experiments are appealing, this requires generation of new molecular reagents as well as calibration of a highly specialized optical method. Therefore, we decided to limit this paper to focus on the unusual observation of the variation of depolymerization rate and speculate the underlying mechanism.

Also, the table is insufficiently described. Are any or all of these MAPs known to be specific regulators of microtubule depolymerization rates, but not other dynamics parameters?

There are a large number of MAPs in Xenopus eggs, as there are in all cells, and the degree to which their effects on microtubules has been characterized is variable. To address this comment we include in the revised ms a list of known MAPs that are present in Xenopus egg extract, along with their estimated concentration from a published proteomic study. We annotate each MAP as to whether it increases or decreases microtubule stability, acknowledging that these data are very incomplete, in some cases there is disagreement in literature, and that we are combining pure protein and whole cell analysis. This table illustrates the challenge of associating dynamics regulation with any one MAP, since the behavior of microtubules is regulated by all these factors operating in parallel. That said, certain MAPs jump out as candidate depolymerization regulators that have been little studied for effects on dynamics, for example, MAP7.

In the revision, we suggest to add this expanded table as a supplementary Table in addition to Table 1.

Protein Description

Gene Symbol

Est. Conc. (nM)

MT polymerization/nucleation/rescue?

MT depolymerization/catastrophe?

Lead reference

Microtubule-associated protein RP/EB family member 1

MAPRE1

1800

Increase

Decrease

PMID: 18364701

Stathmin

STMN1

1600

Decrease

Increase

PMID: 11792540

MAP4

MAP4

960

Increase

Decrease

PMID: 7962090

Echinoderm microtubule-associated protein-like 2

EML2

580

Decrease

Increase

PMID: 11694528

EML4 protein

EML4

500

Increase

Decrease

PMID: 17196341

Disks large-associated protein 5

DLGAP5

380

Increase

Decrease

PMID: 16631580

Cytoskeleton-associated protein 5

CKAP5

300

Increase

Increase

PMID: 23666085

Kinesin-like protein KIF2C

KIF2C

200

Decrease

Increase

PMID: 12620232

CAP-Gly domain-containing linker protein 1

CLIP1

190

na

na

Cytoskeleton-associated protein 4

CKAP4

160

Increase

Decrease

PMID: 9799226

Echinoderm microtubule-associated protein-like 1

EML1

140

na

na

Ensconsin

MAP7

91

na

Decrease

PMID: 31391261

Targeting protein for Xklp2

TPX2

91

Increase

Decrease

PMID: 26414402

Microtubule-associated protein 1B

MAP1B

85

Increase

Decrease

PMID: 7664878

MAP1S

MAP1S

66

Decrease

Decrease

PMID: 25300793

Hyaluronan mediated motility receptor

HMMR

61

na

na

MAP7 domain-containing protein 1

MAP7D1

47

na

na

Cytoskeleton-associated protein 2

CKAP2

46

Increase

Decrease

PMID: 15504249

Microtubule-associated tumor suppressor 1

MTUS1

43

na

na

Kinesin-like protein KIF2A

KIF2A

37

Decrease

Increase

PMID: 29980677

CLIP-associating protein 1

CLASP1

30

Decrease

Decrease

PMID: 29937387

Microtubule-associated protein RP/EB family member 3

MAPRE3

21

Increase

Decrease

PMID: 20850319

MAP7 domain containing 2 protein variant 2 (Fragment)

MAP7D2

8

na

na

CAP-Gly domain-containing linker protein 4

CLIP4

2

na

na

\*Minor comments:***

Figure 1.

typo in the figure legend: "interior (distance>300 μm) vs. periphery (50 μmThere appears to be a clear dip in EB1 density at 100 um (Figure 1C). What could be the cause of that?*

Thank you for catching the typo. We corrected this to “periphery (distance>300 µm) vs. interior (50 µmFigure 2.

Note that the distances used in Figure 2. to define 'interior' and 'periphery' are completely different than those in Figure 1. (Interior in Figure 1 is defined to be between 50 and 280 um from the MTOC, and exterior larger than 300 um. However, in Figure 2. interior is defined as less than 100 um, and exterior as larger than 200 um.) Given that the asters are actively growing, it would be good to clearly explain how these intervals were defined in each case.

For both experiments, we had clearly stated the definitions of interior and periphery, either in the figure legends or in the methods section. We have added a new paragraph explaining why we could not choose exactly the same quantitative definitions for these two methods (please also see our reply to Reviewer #2 comment 1).

In the periphery movie, there are several notable examples of apparent minus-end depolymerization and treadmilling. The authors state these are very rare - perhaps a quantification would be useful here?

Thank you for pointing this out. We modified the sentence to reflect the outward depolymerization events in the periphery. “We observed few outward-moving depolymerization events (Reviewer #1 (Significance (Required)):

The observation of distinct depolymerization rates within vs. at the periphery of microtubule asters is novel and interesting. However, the manuscript in its current form is rather preliminary. The observation can be significantly strengthened by additional experiments/analysis that would characterize the effect in more detail. Even more importantly, the authors propose a highly speculative (although compelling) mechanism, but make no attempt to test it in any way. This is a major deficiency of the current manuscript that should be addressed prior to publication.

REFEREES CROSS COMMENTING

I agree with Reviewer #2 that our comments are both overlapping and complementary. I also find Reviewer #2's comments fair and reasonable and see no need for further adjustments.

RESPONSE TO REVIEWER #2

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

\*SUMMARY ***

This paper reports measurements of microtubule dynamics in interphase asters nucleated in Xenopus egg extracts. Dynamics are measured using two methods. First tracking of GFP tagged EB1 protein forming comets at the tips of growing microtubules, as used in other studies, which can only measure growth rates. Second using a recently developed automated tracking based on subtractive difference images of fluorescently labelled microtubules, which can measure both growth and shrinkage rates. The main and novel observation of this paper, using difference image tracking, is that the MT shrinkage rate is ~2 fold faster in the interior of the aster compared with the periphery of the aster, whilst rates of MT polymerisation and catastrophe vary only slightly, if at all. The authors speculate that this might be due to a reduced MAP concentration and occupancy in the aster interior. They also discuss the role of a depletion-dependent increased shrinkage rate as a feedback mechanism to maintain a low MT polymer density in the aster interior.

\*MAJOR COMMENTS***

The movies are startling in their beauty and clarity and the key conclusion that the shrinkage rate is significantly faster in the interior compared to the periphery of the aster is convincing.

The observation that the rate of net MT plus end growth rate is ~10% faster at the periphery compared to interior of the aster is only supported by EB1 tip tracking method. The difference imaging method shows no significant difference in rates. The authors need to discuss this discrepancy between the established and new methods of analysis. It is insufficient to state that the growth rates obtained by the two methods are "consistent".

This comment prompts the comparison of the two methods (EB1 vs. TIRF difference imaging). On one hand, EB1 tracking is more sensitive in detecting plus ends, and allows large N observations so it is likely to show statistical significance. On the other hand, EB1 tracking method is noisier (higher standard deviation) than the TIRF based measurements (see our response to Reviewer #1). In the TIRF difference imaging, the exact location of the periphery (relative to the center as well as the overall microtubule density profile) is hard to evaluate.

What is consistent between the two methods is the approximate mean value of polymerization rates. The 10% faster polymerization velocity is only suggested by the EB1 tracking method, calling for caution/further investigation. However, the potential relatively small difference in polymerization rate is not the main point of this paper.

We deleted the sentence in the results section for the TIRF method: “These values of polymerization rates are consistent with EB1 comet tracking (Fig. 1). ” We have added a new paragraph discussing the discrepancies between the methods in reporting polymerization rate.

The discussion proposing MAP depletion-dependent increased shrinkage rate as a feedback mechanism to limit MT polymer density is reasonable.

The model and discussion of the role of MAPs might be criticised as highly speculative and unsupported by any experimental data. The authors do acknowledge this. Whether the ratio of data to speculative interpretation is appropriate will be an editorial decision for whichever journal ultimately hosts this.

Thank you. This is exactly the kind of comments that we wanted to hear from an initiative like Review Commons. This helps us gauge how our work is received and decide which journal to submit our work.

In particular since the aster forms by growth from the nucleating bead, early in its formation the final interior MTs must have first formed the peripheral MTs and could therefore enter fresh media and bind MAPs. The authors show by calculation that as the aster expands, these MTs and MAPs become isolated from mixing with the external media. This isolation would then suggest that any MAPS released by dissociation or MT depolymerisation must remain in the interior, and are therefore available to rebind to newly formed MTs. So, it is unclear why the MAPs should be depleted in the interior compared to the periphery, unless expansion of the Aster is slowed in which case additional MAPs could diffuse into the stationary periphery from the surrounding media. The kinetics of MT growth, MAP binding and aster expansion would then also be expected to have an effect on the outcome beyond a simple "depletion" of the internal MAP concentration.

We use the term “depletion” to mean a significant decrease of MAP from the cytoplasm. As outlined in our toy model, more MTs lead to more MAP binding and depletion of soluble MAPs. Note that the total local abundance of MAP is constant unless there is significant diffusive transport of MAP from one region to another. We argue this transport is ineffective for the large length scale of interphase asters.

It is also not clear how the authors preferred model would account for the suggestion of bimodal shrinkage rates. It is not clear if this is a simplification (binning things in to external and internal) applied for the purposes of discussion.

Please see our comment to Reviewer #1. We now believe there is no evidence for bimodality of depolymerization rates. The spread of the data reflects the variability of depolymerization rates in a given a field of view as well as the variability across multiple fields of view.

\*MINOR COMMENTS***

Line 71

Authors reference Gardner et al 2011, when discussing depolymerisation as a zero order process, as showing a free tubulin dimer concentration effect on shrinkage rates. However, the results in Gardner refer to the off rate during MT polymerisation, and measurements of rapid small scale events during overall growth phases and would be applicable to GTP-heterodimers, whereas the extended shrinkage events measured in this paper would presumably apply to post-catastrophe GDP-heterodimer dissociation and may not be comparable. The reference should be omitted or a further explanation given.

Thanks, good point. We wanted to cite Gardner et al (2011) to make the point that classic assembly models may not always hold, but the reviewer is correct, that paper only looked at concentration dependence of depolymerization at growing ends. The text was changed to:

“This assumption has been questioned for growing ends (Gardner 2011)​, but not for shrinking ends to our knowledge.”

Line 89

States "density of plus ends is approximately homogenous within interphase asters"

However, in results section it is stated Line 111 that "the plus end density is lower at the periphery compared to the aster center".

Please clarify

The plus end density is approximately homogenous from the center to the periphery of the aster. However, only at the most peripheral region, where there are few microtubules, the density drops.

Line 135

The distances given for the interior and periphery appear to be mixed up.

Thank you, we corrected this.

Line277

"approximately consistent with our Peclet number estimate". 50µm gives a Pe value of 2.8. The Peclat number "significance" is earlier given in terms of "Pe>>1" (Line255). Please clarify what range of experimental values is required for the argument to hold.

Our statement was unclear. We modified the sentence in the following way to clarify our point: “The half-width of the depleted zone extended ~50 microns beyond the growing aster periphery, which is smaller than the typical aster radius. This analysis indicated that soluble protein levels may vary between subregions of growing asters due to subunit consumption.”

Line 404

needs details of the GFP-EB1 and fluorescent tubulin used in this experiment.

The detailed concentrations are described for each method in the subsequent sections. To avoid confusion, we removed the sentence in line 404, which omitted details.

The tubulin depletion measurements detect a 4% reduction in tubulin concentration in the interior versus the exterior, and the same for eGFP-EB1 (Fig.4B). This observation provides important support for the depletion proposal. But the experiments apparently lack a control for potential reduction of fluorescence excitation intensity with depth in these deep specimens (equivalent to the inner filter effect in spectroscopy). Is there a component whose apparent concentration (fluorescence emission intensity) does not decrease by 4% in the interior of the aster?

Indeed, fluorescent intensity measurements require special attention. Our samples are made by squashing 4 ul of extract under a 18 mm x 18 mm coverslip and the resulting thickness is 10 micron, which we believe is a distance that is too small to result in an inner filter effect.

In response to Reviewer #2’s request for an example of a component whose fluorescence intensity is uniform, we provide the intensity profile of the inert 10kDa Dextran labeled with Alexa568. This serves as a control for the reviewer’s specific concern with our method. We will incorporate this as a supplementary figure in the revision.

There is no direct discussion of the relative lifetime of MTs in the interior compared to the exterior of the aster. Catastrophe rates and growth rates are essentially invariant, I think this implies that MT lifetimes are essentially the same in the interior versus the exterior? Please confirm and estimate the lifetime. This could exclude a maturation process whereby one set of MAPs got replaced by another over time?

Indeed, MT lifetime is a function of four rates: polymerization, depolymerization, catastrophe, and rescue. The figure below shows the MT lifetime as a function of depolymerization rate, assuming other parameters are fixed at what we found in our previous report Ishihara et al. 2016. In regions of fast depolymerization rate 40 µm/min, the microtubule lifetime is 0.98 min. As the depolymerization rate decreases to 30 and 25 µm/min, the lifetime increases to 1.5 and 2.4 min. This implies that the microtubules at the aster periphery are longer lived than those in the interior.

Association and dissociation rate constants have not been measured for most MAPs, but in general we expect them to be fast compared to the timescale of MT lifetime of ~1 minute. Most MAPs bind in the low micromolar or high nM regime, which implies dissociation rates of seconds or less. MAP4 and MAP7 were both shown to bind and dissociate rapidly in living cells (PMID: 16714020, PMID: 11719555)

Reviewer #2 (Significance (Required)):

This paper is significant as it is the first observation of spatial variation in MT shrinkage rates in an aster. It proposes the broad shape of an underlying mechanism (depletion of stabilising MAPS in the aster interior) and presents sound quantitative arguments, but the experiments do not directly test this mechanism. Aster formation in Xenopus egg extracts is widely used as a model system, and if indeed the spatial variation turns out to be due to spatial depletion of components then this will become a landmark paper. The paper may promote wider use of this method of automated analysis and encourage study of shrinkage rate mechanisms in other systems.

REFEREES CROSS COMMENTING

In my opinion the comments of reviewer #1 are fair and reasonable and overlap with and complement my own. In my opinion there is zero conflict requiring adjustment.

Contextualize

Human civilization is heavily dependent on nature, and for a long time, humans have not realized that. Humans, everything nature, have they can control and rule it for their own needs. However, is it like that? The answer is no. The river has played a significant role in human civilization. It is almost impossible to have it developed without a river. Cunha state that in the reading, "All this is to say that rivers are taken to be constituents of the earth and not products of human enterprise" (pp.4). Many civilizations are developed next to the river. For example, the Egyptians developed their civilization next to the Nile River. Without it, this civilization may not be existing at all. In "Ancient Egyptian civilization," the author states, "This annual flooding was vital to agriculture because it deposited a new layer of nutrient-rich soil each year. In years when the Nile did not flood, the nutrient level in the soil was seriously depleted, and the chance of food shortages increased greatly. Food supplies had political effects, as well, and periods of drought probably contributed to the decline of Egyptian political unity at the ends of both the Old and Middle Kingdoms". Agriculture is one of the essential elements for human civilization to be continued, and the river is the crucial element for it to happen. At some point time, I think humans have underestimated the power of the river. Like Cunha, the river is not the human enterprise's product, but it is the earth's constituents.

Cunha, D. D. (2019). Ocean of Rain. In The invention of rivers: Alexander’s eye and Ganga’s descent (pp.1-19). Philadelphia: University of Pennsylvania Press.

Ancient Egyptian civilization (article). (n.d.). Retrieved October 15, 2020, from https://www.khanacademy.org/humanities/world-history/world-history-beginnings/ancient-egypt-hittites/a/egypt-article

Relate

There has always been this argument: the river constructed by man or it was naturally existing. Many conservationists believe that river was naturally living, and human civilization has been highly dependent on it. We have been underestimating the power of the river. Many other people believe that humans are the one that brought in value to the river. Without human constructions, the river will be a river.

However, there is a balance between these two extremes believes. It is not only about the physical phenomenon but also about how we use or act it. We cannot underestimate the value and power of the river, but we also have to do the right construction to maximize the value. Gain useful knowledge of the river before we take in human action is the right way to do.

I don't think there is a solution to the white public space problem until society acknowledges the fact that everyone has their own kind of dialect. In America, there is a large amount of diversity, but we live under the impression that we have to speak a certain way to get opportunities. People of the Hispanic culture often get let down because of the fact that they speak Spanish in public. Some white people in our country feel that they are inferior to minorities because of the privilege they are given. This causes them to look down on those who may not be in the same situation that they are in. In order to create a solution for this problem. as citizens living in America, we have to accept the fact that people represent their cultures differently. We can't discriminate against those who don't "act white" or follow those professional values.

This is TEA structure. It starts off with listing negative emotions and the topic sentence is saying that in the case of negative emotions, trust them/ yourself. The second sentence is telling us why this could be a thing. It could also be an example. Then it gives us an example of feelings that we could have and how we can deal with them. I think that counts as an example.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

We would like to express our appreciation for both the Editors’ and Reviewers’ efforts as essential contributions to the peer review process. We highly value the Reviewers’ constructive critique of our manuscript#RC-2020_00434R entitled “A drug repurposing screen identifies hepatitis C antivirals as inhibitors of the SARS-CoV2 main protease.__” __

We appreciate the Reviewers’ thoughtful consideration of our work and feel their critiques and recommendations have significantly improved our manuscript. Taken together, we believe the additional data, clarification of data presentation, and revised discussion address the heart of the Reviewers’ previous concerns. Thus we feel the work is ready for reconsideration and will be an impactful addition to the literature appropriate for publication. Below we provide a breakdown and a point by point response to previous review critiques.

Thank you for your attention. We look forward to your response.

Best Wishes,

Brian Kraemer, PhD ▪ Associate Director for Research Geriatric Research Education and Clinical Center ▪ Veterans Affairs Puget Sound Health Care System ▪ Research Professor ▪ Departments of Medicine, Psychiatry and Behavioral Sciences, and Pathology ▪ University of Washington ▪ 1660 South Columbian Way ▪ Seattle, WA 98108 ▪ Phone 206-277-1071 ▪ www.kraemerlab.uw.edu

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

In this manuscript, Baker et al. report the screening of a collection of ~6,070 drugs for their inhibitory activity against the enzymatic activity of the SARS-SoV-2 Mpro protein in vitro using two peptide substrates. 50 compounds with activity against Mpro were identified and tested for their dose-dependent effect in the same assay. Several hits were identified, among which are approved drugs that target the HCV protease.

Indeed, there is an urgent need for effective drugs for SARS-CoV-2 infection, and high throughput screenings can discover novel candidates. However, the novelty of this work is quite limited, as former screens have been published with the same target using the same substrates. Moreover, as discussed below the translational impact of the hits discussed is also quite limited, particularly in the absence of antiviral data. Lastly, there are several overstatements in the write up and it will require major editing.

**Major comments:**

1. Were there any positive controls previously shown to potently inhibit the SARS-CoV-2 Mpro included in the screen (e.g. ebselen)? How did these perform in this assay? When first designing our protease assay, we did use ebselen as the initial control. Ebselen showed low potency in all our in our assays and was not considered as a positive control subsequently. It should be noted that Ebselen failed to work against multiple substrates. It is possible that our buffer conditions prevented Ebselen activity. See data plotted below. After identifying boceprevir as a potent inhibitor, it was used in all subsequent assays as a positive control.

It will be helpful if the authors would provide info re the 50 hits from prior screens conducted with this library of compounds - how promiscuous are they across screens? How toxic in cell based assays?

We have updated the table to provide additional useful information as well as a footnote explaining statuses. The compounds in the Broad repurposing library are generally non-toxic and information about them can be found here: https://clue.io/repurposing

The translational potential of the findings appears to be limited. The calculated IC50s for these drugs in the Mpro assay are very high (10-1000 fold higher) relative to their IC50 in an enzymatic assay involving the HCV protease (Boceprevir: IC50 = 0.95 μM vs. 0.084 μM in HCV), Ciluprevir (IC50 = 20.77 μM vs. 0.0087 in HCV), Telaprevir (IC50 = 15.25 μM vs.0.050 μM in HCV) (https://aac.asm.org/content/aac/57/12/6236.full.pdf ). In the absence of antiviral data, the main statement of the manuscript that "the work presented here supports the rapid evaluation of previous HCV NS3/4A inhibitors for repurposing as a COVID-19 therapy." is thus an overstatement. Even is there is some activity, since likely to be limited, as with the HIV protease inhibitors, its chances to elicit a meaningful clinical effect is low. Moreover, when used in monotherapy, some of these protease inhibitors have a very low genetic barrier to resistance.

We have reworked the discussion to incorporate these concerns and limitations of our results.

There are additional inaccurate or overstatements - e.g. line 61 "Probably the most successful approved antivirals are protease inhibitors such as atazanavir for HIV-1 and simeprevir for hepatitis C. [reviewed in 10 and 11]."

We have reworded this statement: (Page 4, Lines 61-62)

“There is precedence for targeting the protease, as this approach has been successful in treating both HIV-1 and hepatitis C (10,11).”

The manuscript requires editing - e.g. structure of sentences, commas, spacing (including in the abstract) etc.

The manuscript has been re-proofed throughout (see tracked changes version of manuscript)

What is the take home message? The statement "Taken together this work suggests previous large-scale commercial drug development initiatives targeting hepatitis C NS3/4A viral protease should be revisited because some previous lead compounds may be more potent against SARS-CoV-2 Mpro than Boceprevir and suitable for rapid repurposing." is unclear.

The take home message of the manuscript is that HCV-targeting protease inhibitors have potential in blocking the SARS-Cov2 protease and a more thorough analysis of the space is needed. As the reviewer pointed out, the identified hits boceprevir and narlaprevir are less potent when targeting the SARS-Cov2 protease as compared to the HCV protease. However, we believe this work does show the potential for screening HCV-targeting protease inhibitors that may not have made it to the clinic. For instance, Boceprevir or Narlaprevir analogs may be even more potent against Mrpo. Further, we believe that these compounds would benefit from further optimization through medicinal chemistry.

We have expanded the discussion to incorporate issues brought up here and in point 3.

Reviewer #1 (Significance (Required)):

Limited. As discussed above

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

SARS-CoV-2 pandemic causing serious health crisis globally. There are no specific medicine or vaccines to contain this virus currently. To address this issue, the authors developed one efficient fluorescent Mpro assay system and screened ~6070 previous used drugs in this article. Several compounds with activity against SARS-CoV-2 Mpro in vitro were founded. Most hits are hepatitis C NS3/4A protease inhibitors with fair IC50 value. Besides, the authors found that most identified compounds in in silico screen lack activity against Mpro in kinetic protease assays.

These research results are well proved and reproducible. But there are two minor questions I present below:

1. In your Mpro assay optimization process you said substrate MCA-AVLQSGFR-K(Dnp)- K-NH2 had drastically lower rates of Mpro catalyzed hydrolysis and were not considered further in your assay development. And in your Fig.1 I saw extremely low RFU changes. But several nice inhibitors were screened using this substrate that was reported in April. Can you explain this result? The substrates used in our assay appear to be much more efficiently cleaved at least with our buffer conditions and Mpro concentrations tested. Variables including recombinant Mpro purity and activity, differences in assay buffer, reader sensitivity may all play a role, but our best guess is that the substrate identified by Marcin Drag’s group (https://doi.org/10.1101/2020.04.29.068890), is more readily cleaved by Mpro. Although screening with other reported substrates is feasible given previous results, we believe the Ac-Abu-Tle-Leu-Gln-AFC to be superior for use in high throughput screening because of its superior cleavage kinetics yielding an improved signal to background ratio for HTS.

To exclude inhibitors possibly acting as aggregators, a detergent-based control should do at the same time when you do IC50 value measurement.

Compound aggregation is a concern, and our assays were all run with detergent in the buffer. Our buffer composition was 20mM Tris pH 7.8, 150mM NaCl, 1mM EDTA, 1mM DTT, 0.05% Triton X-100.

Reviewer #2 (Significance (Required)):

Nice work but the significance of this article is losing now. Most screened hits are reported in the last serval months. Some inhibitor complex structures have been published or released on Protein Data Bank. The novelty is missing. I suggest the authors add more results and resubmit it again.

**Referees Cross-commenting**

I agree with the other two reviewers' comments. The significance of this work is losing but still has something interest. I think it can be published in the lower-impact journal if they complete our suggestions

We concur with both reviewers that demonstration of antiviral activity would strengthen the impact of the manuscript. However, this work remains outside of the scope of feasibility at our institution. We believe that our screen and hit identification can stand on their own until further translational work can be completed.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

In this report, Baker et al. show that four inhibitors of hepatitis C virus (HCV) NS3/4 protease (ciluprevir, boceprevir, narlaprevir and telaprevir) are also effective inhibitors of the SARS-CoV-2 main protease (Mpro) in enzymatic assays, with lower IC50 values for narlaprevir and boceprevir (around 1 µM in their assay conditions). HCV NS3/4 inhibitors were identified after screening a library of >6,000 compounds of the Broad Institute, including approved drugs. Screening was done with fluorometric proteolytic assays.

Experiments have been apparently well-done and results are sound. The manuscript needs editing.

Reviewer #3 (Significance (Required)):

Experiments have been apparently well-done and results are sound. However, this is a limited study since there are no data obtained in cell culture and a comparison of IC50 values of the selected drugs against HCV and SARS-CoV-2 proteases is missing. It is difficult to infer whether the drugs would be equally effective against SARS-CoV-2 than against HCV, and otherwise, how much should the doses increase in order to have a therapeutic effect.

The manuscript needs editing (see below) and the Discussion is poor. The results reported by authors are not new, and a discussion of the effects of HCV inhibitors on SARS-CoV-2 replication, based on previous publications is necessary to provide the appropriate context for the study.

Here are some references on Covid-19 and HCV inhibitors, that in my opinion should be considered for discussion and proper citation. As correctly pointed out by Baker and co- workers, docking studies should be considered with caution, though.

We appreciate the feedback and have now reworked and expanded the discussion to incorporate reviewer #1 and #3 comments and suggestions.

1: Ghahremanpour MM, Tirado-Rives J, Deshmukh M, Ippolito JA, Zhang CH, de Vaca IC, Liosi ME, Anderson KS, Jorgensen WL. Identification of 14 Known Drugs as Inhibitors of the Main Protease of SARS-CoV-2. bioRxiv [Preprint]. 2020 Aug 28:2020.08.28.271957. doi: 10.1101/2020.08.28.271957. PMID: 32869018; PMCID: PMC7457600.

2: Sacco MD, Ma C, Lagarias P, Gao A, Townsend JA, Meng X, Dube P, Zhang X, Hu Y, Kitamura N, Hurst B, Tarbet B, Marty MT, Kolocouris A, Xiang Y, Chen Y, Wang J. Structure and inhibition of the SARS-CoV-2 main protease reveals strategy for developing dual inhibitors against Mpro and cathepsin L. bioRxiv [Preprint]. 2020 Jul 27:2020.07.27.223727. doi: 10.1101/2020.07.27.223727. PMID: 32766590; PMCID: PMC7402059.

3: Ma C, Sacco MD, Hurst B, Townsend JA, Hu Y, Szeto T, Zhang X, Tarbet B, Marty MT, Chen Y, Wang J. Boceprevir, GC-376, and calpain inhibitors II, XII inhibit SARS-CoV-2viral replication by targeting the viral main protease. Cell Res. 2020 Aug;30(8):678-692. doi: 10.1038/s41422-020-0356-z. Epub 2020 Jun 15. PMID: 32541865; PMCID: PMC7294525.

4: Ke YY, Peng TT, Yeh TK, Huang WZ, Chang SE, Wu SH, Hung HC, Hsu TA, Lee SJ, Song JS, Lin WH, Chiang TJ, Lin JH, Sytwu HK, Chen CT. Artificial intelligence approach fighting COVID-19 with repurposing drugs. Biomed J. 2020 May 15:S2319- 4170(20)30049-4. doi: 10.1016/j.bj.2020.05.001. Epub ahead of print. PMID: 32426387; PMCID: PMC7227517.

5: Elzupir AO. Inhibition of SARS-CoV-2 main protease 3CLpro by means of α-ketoamide and pyridone-containing pharmaceuticals using in silico molecular docking. J Mol Struct. 2020 Dec 15;1222:128878. doi: 10.1016/j.molstruc.2020.128878. Epub 2020 Jul 10.

PMID: 32834113; PMCID: PMC7347502.

Additional computational studies:

1: Hosseini FS, Amanlou M. Anti-HCV and anti-malaria agent, potential candidates to repurpose for coronavirus infection: Virtual screening, molecular docking, and molecular dynamics simulation study. Life Sci. 2020 Aug 8;258:118205. doi:10.1016/j.lfs.2020.118205. Epub ahead of print. PMID: 32777300; PMCID:PMC7413873.

2: Hakmi M, Bouricha EM, Kandoussi I, Harti JE, Ibrahimi A. Repurposing of known anti- virals as potential inhibitors for SARS-CoV-2 main protease using molecular docking analysis. Bioinformation. 2020 Apr 30;16(4):301-306. doi:10.6026/97320630016301.

PMID: 32773989; PMCID: PMC7392094.

3: Chtita S, Belhassan A, Aouidate A, Belaidi S, Bouachrine M, Lakhlifi T. Discovery of Potent SARS-CoV-2 Inhibitors from Approved Antiviral Drugs via Docking Screening. Comb Chem High Throughput Screen. 2020 Jul 30. doi:10.2174/1386207323999200730205447. Epub ahead of print. PMID: 32748740.

4: Alamri MA, Tahir Ul Qamar M, Mirza MU, Bhadane R, Alqahtani SM, Muneer I, Froeyen M, Salo-Ahen OMH. Pharmacoinformatics and molecular dynamics simulation studies reveal potential covalent and FDA-approved inhibitors of SARS-CoV-2 main protease 3CLpro. J Biomol Struct Dyn. 2020 Jun 24:1-13. doi:10.1080/07391102.2020.1782768. Epub ahead of print. PMID: 32579061; PMCID:PMC7332866.

5: Bafna K, Krug RM, Montelione GT. Structural Similarity of SARS-CoV2 Mpro and HCV NS3/4A Proteases Suggests New Approaches for Identifying Existing Drugs Useful as COVID-19 Therapeutics. ChemRxiv [Preprint]. 2020 Apr 21. doi: 10.26434/chemrxiv.12153615. PMID: 32511291; PMCID: PMC7263768.

6: Eleftheriou P, Amanatidou D, Petrou A, Geronikaki A. In Silico Evaluation of the Effectivity of Approved Protease Inhibitors against the Main Protease of the Novel SARS- CoV-2 Virus. Molecules. 2020 May 29;25(11):2529. doi:10.3390/molecules25112529.

PMID: 32485894; PMCID: PMC7321236.

7: Wang J. Fast Identification of Possible Drug Treatment of Coronavirus Disease-19 (COVID-19) through Computational Drug Repurposing Study. J Chem Inf Model. 2020 Jun 22;60(6):3277-3286. doi: 10.1021/acs.jcim.0c00179. Epub 2020 May 4. PMID: 32315171; PMCID: PMC7197972.

8: Chen YW, Yiu CB, Wong KY. Prediction of the SARS-CoV-2 (2019-nCoV) 3C-like protease (3CL pro) structure: virtual screening reveals velpatasvir, ledipasvir, and other drug repurposing candidates. F1000Res. 2020 Feb 21;9:129. doi: 10.12688/f1000research.22457.2. PMID: 32194944; PMCID: PMC7062204.

Minor comments:

We appreciate the time that the reviewer has taken to address grammatical changes and have addressed each throughout the manuscript with tracked changes.

p.2, line 26: > appears as an attractive

Manuscript edited

p.2, line 27: > we show that the existing

Manuscript edited

p.2, line 33: > separate numbers and units, eg. 1.10 µM (this is a persisting error that should be corrected throughout the whole ms)

Manuscript edited

p.4, line 44: SARS virus should be referred as to SARS-CoV-1 throughout the whole manuscript. MERS-CoV is the name of the virus causing MERS

Manuscript edited

p.4, lines 61-62: > the selection of the specific compounds seems to be arbitrary... why atazanavir and not darunavir or other? The sentence should be rewritten.

Rewritten as: “There is precedence for targeting the protease, as this approach has been successful in treating both HIV-1 and hepatitis C.”

p.6, line 100: Citing Fig. 2B before completing the description of Fig. 1 is distracting. Authors should think of a better way to describe their results.

This was a mistake and should have cited Fig 1B. Thank you for catching this.

p.7, line 116: It is not clear what "10m-20,810" means

This has been clarified to state: “ΔRFU at 10 minutes = 20,810 relative fluorescence units”

p.7, lines 125-126: These sentences belong to an introduction, not appropriate in results section.

We have removed these sentences.

Figure 2. Part A is not necessary in results (ok for introduction). Black and purple dots in part B is not a good choice since they are difficult to distinguish, maybe orange and black is better.

We have removed panel A, expanded the size of panel B and changed the color.

Table 1: Status should be explained in a footnote (i.e the distinction between launched, P2/P3, phase 2, preclinical is not clear).

The one compound indicated in P2/P3 development is now Phase 3 and the table has been updated. We have added a footnote:

*Launched = compound approved for humans, though may only be approved for veterinary use in some countries

Discussion. I think that subheadings are not necessary.

Subheadings have been removed from the discussion.

**Referees cross-commenting** I agree with reviewer no. 1 on the limited interest of the study. However, it could be published in a specialized lower-impact journal after addressing issues raised by reviewers 2 and 3 (likely to be completed in less than a month)

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Referee #3

Evidence, reproducibility and clarity

In this report, Baker et al. show that four inhibitors of hepatitis C virus (HCV) NS3/4 protease (ciluprevir, boceprevir, narlaprevir and telaprevir) are also effective inhibitors of the SARS-CoV-2 main protease (Mpro) in enzymatic assays, with lower IC50 values for narlaprevir and boceprevir (around 1 µM in their assay conditions). HCV NS3/4 inhibitors were identified after screening a library of >6,000 compounds of the Broad Institute, including approved drugs. Screening was done with fluorometric proteolytic assays.

Experiments have been apparently well-done and results are sound. The manuscript needs editing.

Significance

Experiments have been apparently well-done and results are sound. However, this is a limited study since there are no data obtained in cell culture and a comparison of IC50 values of the selected drugs against HCV and SARS-CoV-2 proteases is missing. It is difficult to infer whether the drugs would be equally effective against SARS-CoV-2 than against HCV, and otherwise, how much should the doses increase in order to have a therapeutic effect. The manuscript needs editing (see below) and the Discussion is poor. The results reported by authors are not new, and a discussion of the effects of HCV inhibitors on SARS-CoV-2 replication, based on previous publications is necessary to provide the appropriate context for the study. Here are some references on Covid-19 and HCV inhibitors, that in my opinion should be considered for discussion and proper citation. As correctly pointed out by Baker and co-workers, docking studies should be considered with caution, though.

1: Ghahremanpour MM, Tirado-Rives J, Deshmukh M, Ippolito JA, Zhang CH, de Vaca IC, Liosi ME, Anderson KS, Jorgensen WL. Identification of 14 Known Drugs as Inhibitors of the Main Protease of SARS-CoV-2. bioRxiv [Preprint]. 2020 Aug 28:2020.08.28.271957. doi: 10.1101/2020.08.28.271957. PMID: 32869018; PMCID: PMC7457600.

2: Sacco MD, Ma C, Lagarias P, Gao A, Townsend JA, Meng X, Dube P, Zhang X, Hu Y, Kitamura N, Hurst B, Tarbet B, Marty MT, Kolocouris A, Xiang Y, Chen Y, Wang J. Structure and inhibition of the SARS-CoV-2 main protease reveals strategy for developing dual inhibitors against M^pro and cathepsin L. bioRxiv [Preprint]. 2020 Jul 27:2020.07.27.223727. doi: 10.1101/2020.07.27.223727. PMID: 32766590; PMCID: PMC7402059.

3: Ma C, Sacco MD, Hurst B, Townsend JA, Hu Y, Szeto T, Zhang X, Tarbet B, Marty MT, Chen Y, Wang J. Boceprevir, GC-376, and calpain inhibitors II, XII inhibit SARS-CoV-2 viral replication by targeting the viral main protease. Cell Res. 2020 Aug;30(8):678-692. doi: 10.1038/s41422-020-0356-z. Epub 2020 Jun 15. PMID: 32541865; PMCID: PMC7294525.

4: Ke YY, Peng TT, Yeh TK, Huang WZ, Chang SE, Wu SH, Hung HC, Hsu TA, Lee SJ, Song JS, Lin WH, Chiang TJ, Lin JH, Sytwu HK, Chen CT. Artificial intelligence approach fighting COVID-19 with repurposing drugs. Biomed J. 2020 May 15:S2319-4170(20)30049-4. doi: 10.1016/j.bj.2020.05.001. Epub ahead of print. PMID: 32426387; PMCID: PMC7227517.

5: Elzupir AO. Inhibition of SARS-CoV-2 main protease 3CLpro by means of α-ketoamide and pyridone-containing pharmaceuticals using in silico molecular docking. J Mol Struct. 2020 Dec 15;1222:128878. doi: 10.1016/j.molstruc.2020.128878. Epub 2020 Jul 10. PMID: 32834113; PMCID: PMC7347502.

Additional computational studies:

1: Hosseini FS, Amanlou M. Anti-HCV and anti-malaria agent, potential candidates to repurpose for coronavirus infection: Virtual screening, molecular docking, and molecular dynamics simulation study. Life Sci. 2020 Aug 8;258:118205. doi:10.1016/j.lfs.2020.118205. Epub ahead of print. PMID: 32777300; PMCID:PMC7413873.

2: Hakmi M, Bouricha EM, Kandoussi I, Harti JE, Ibrahimi A. Repurposing of known anti-virals as potential inhibitors for SARS-CoV-2 main protease using molecular docking analysis. Bioinformation. 2020 Apr 30;16(4):301-306. doi:10.6026/97320630016301. PMID: 32773989; PMCID: PMC7392094.

3: Chtita S, Belhassan A, Aouidate A, Belaidi S, Bouachrine M, Lakhlifi T. Discovery of Potent SARS-CoV-2 Inhibitors from Approved Antiviral Drugs via Docking Screening. Comb Chem High Throughput Screen. 2020 Jul 30. doi:10.2174/1386207323999200730205447. Epub ahead of print. PMID: 32748740.

4: Alamri MA, Tahir Ul Qamar M, Mirza MU, Bhadane R, Alqahtani SM, Muneer I, Froeyen M, Salo-Ahen OMH. Pharmacoinformatics and molecular dynamics simulation studies reveal potential covalent and FDA-approved inhibitors of SARS-CoV-2 main protease 3CL^pro. J Biomol Struct Dyn. 2020 Jun 24:1-13. doi:10.1080/07391102.2020.1782768. Epub ahead of print. PMID: 32579061; PMCID:PMC7332866.

5: Bafna K, Krug RM, Montelione GT. Structural Similarity of SARS-CoV2 M^pro and HCV NS3/4A Proteases Suggests New Approaches for Identifying Existing Drugs Useful as COVID-19 Therapeutics. ChemRxiv [Preprint]. 2020 Apr 21. doi: 10.26434/chemrxiv.12153615. PMID: 32511291; PMCID: PMC7263768.

6: Eleftheriou P, Amanatidou D, Petrou A, Geronikaki A. In Silico Evaluation of the Effectivity of Approved Protease Inhibitors against the Main Protease of the Novel SARS-CoV-2 Virus. Molecules. 2020 May 29;25(11):2529. doi:10.3390/molecules25112529. PMID: 32485894; PMCID: PMC7321236.

7: Wang J. Fast Identification of Possible Drug Treatment of Coronavirus Disease-19 (COVID-19) through Computational Drug Repurposing Study. J Chem Inf Model. 2020 Jun 22;60(6):3277-3286. doi: 10.1021/acs.jcim.0c00179. Epub 2020 May 4. PMID: 32315171; PMCID: PMC7197972.

8: Chen YW, Yiu CB, Wong KY. Prediction of the SARS-CoV-2 (2019-nCoV) 3C-like protease (3CL ^pro) structure: virtual screening reveals velpatasvir, ledipasvir, and other drug repurposing candidates. F1000Res. 2020 Feb 21;9:129. doi: 10.12688/f1000research.22457.2. PMID: 32194944; PMCID: PMC7062204.

Minor comments:

p.2, line 26: > appears as an attractive

p.2, line 27: > we show that the existing

p.2, line 33: > separate numbers and units, eg. 1.10 µM (this is a persisting error that should be corrected throughout the whole ms)

p.4, line 44: SARS virus should be referred as to SARS-CoV-1 throughout the whole manuscript. MERS-CoV is the name of the virus causing MERS

p.4, lines 61-62: > the selection of the specific compounds seems to be arbitrary... why atazanavir and not darunavir or other? The sentence should be rewritten.

p.6, line 100: Citing Fig. 2B before completing the description of Fig. 1 is distracting. Authors should think of a better way to describe their results.

p.7, line 116: It is not clear what "10m-20,810" means

p.7, lines 125-126: These sentences belong to an introduction, not appropriate in results section.

Figure 2. Part A is not necessary in results (ok for introduction). Black and purple dots in part B is not a good choice since they are difficult to distinguish, maybe orange and black is better.

Table 1: Status should be explained in a footnote (i.e the distinction between launched, P2/P3, phase 2, preclinical is not clear).

Discussion. I think that subheadings are not necessary.

Referees cross-commenting

I agree with reviewer no. 1 on the limited interest of the study. However, it could be published in a specialized lower-impact journal after addressing issues raised by reviewers 2 and 3 (likely to be completed in less than a month)

I think this is referring to our ecological footprint that we as humans leave on the Earth. The connotation of these few stanzas is very bleak and cold, suggesting the grim fate of the human race in the future.

I think this paragraph is very important since it's almost or if not the introduction paragraph where he speaks freely and as I am reading this it's not perfect English, it's his English, and we all have different English.

I think that Pollan did an amazing job in this piece here. He showed signs of reading with the grain while alos arguing against the animal topic by preaching his own beleifs.

Who's to say that our standard of living as we take care of animals is better for them. it may be more humane but i dont think humans can judge happiness for animals. they would probably rather be left alone. its in there nature to survive and they don't need humans until humans make it impossible for them to live without the help of us.

This is the basis of why this topic is so controversial. After looking at the details and hearing from experts on environmental issues, it's clear that The Green New Deal is not as far-reaching as some may originally think. However, the true controversy comes in when we look at the values held by democrats and republicans. Because many republicans have been known to deny climate change, such an aggressive plan to change how the United States runs is likely to cause an uproar by the far-right.

The metaphor that I see when Rich refers to the wreck and not the myth of the drowned ship is it being compared to the universe or the world. You/Rich did not come looking for the myth, you came looking for the wreck. I interpreted this as you did not come here for people to tell you how the world is. You simply came to experience the world. Now, when Rich speaks about the mermaid and the merman, where "I am she: I am he", I believe that Rich understands that fundamentally, we are all the same. Humans have created classifications for things. Gender, sexual orientation, race, religion, age. As we live in this era, these classifications are incredibly useful, however, many of our world's problems stem from the differences between these demographics. As Rich was an advocate for not only women's rights, but also lesbian's issues, I think she had a very good grasp on how to explain and get others to understand perspectives that aren't theirs. While to some people, this message may be cryptic, the fact of its existence proves that this is a valid interpretation. Before I am a straight, male, Bengali adolescent, I am a human. As we all are, and understanding that allows you to see through all of the classifications we have for ourselves. It allows people to more easily sympathize with those who are different from them. While Rich may not have reached everyone, she has certainly been influential to many.

Contextualize

When I read, “In South Asia, where the history of scientific forestry has perhaps been most fully documented, the forest department quickly became a reviled arm of the colonial state”. It reminds me that “Ecological Imperialism” from previous reading. The majority of those Asian countries that colonized by Europeans are following their way of environmentalism. However, is this the right way to apply one method to all the occupied lands? In “Ecological Imperialism,” Crosby states that “The human invaders and their descendants have consulted their egos, rather than ecologists, for explanations of their triumphs. But the human victims, the aborigines of the Lands of the Demographic Takeover, knew better, knew they were only one of many species being displaced and replaced; knew they were victims of something more irresistible and awesome than the spread of capitalism or Christianity”. Human has always been arrogant concerning nature. Humans did not realize the importance of nature for a long time and how we cannot live without nature. We must have enough knowledge of the landscape we are about to take action before doing our work. The experience we have can limit the negative impacts that we may do on the environment surrounding.

Crosby, A. W. (1988). Ecological Imperialism: The Overseas Migration of Western Europeans as a Biological Phenomenon. In The ends of the earth: Perspectives on modern environmental history (pp. 103-117). Cambridge: Cambridge University Press.

Relate

There are many examples of humans taking advantage of nature in the colonized period and modern times due to the anthropocentric. That results in most of the natural ecosystem was damages during those human actions. For example, the Longleaf Pine ecosystem was once widely covered the southeastern region in the United States. Due to the fire burning and the timber industry's needs, the whole Longleaf Pine ecosystem was sharp decreasing in very short. Therefore, one of the most covered ecosystems became the most endangered ecosystem in the United States.

Ecology imperialism is apropos to describe the relation human and nature has, even though today many people have cared about nature's sustainability. However, humans have not found the right balance between us and nature, and it is imperative to figure that out. We are not the only living species existing on the earth. We are sharing it with thousands of other species. It is also essential to think the future generations, think it sustainably, what are we giving them if we take actions into nature with no control.

I find it somewhat interesting to note that with 246 public annotations on this page using Hypothes.is, that from what I can tell as of 4/2/2019 only one of them is a simple highlight. All the rest are highlights with an annotation or response of some sort.

It makes me curious to know what the percentage distribution these two types have on the platform. Is it the case that in classroom settings, which many of these annotations appear to have been made, that much of the use of the platform dictates more annotations (versus simple highlights) due to the performative nature of the process?

Is it possible that there are a significant number of highlights which are simply hidden because the platform automatically defaults these to private? Is the friction of making highlights so high that people don't bother?

I know that Amazon will indicate heavily highlighted passages in e-books as a feature to draw attention to the interest relating to those passages. Perhaps it would be useful/nice if Hypothes.is would do something similar, but make the author of the highlights anonymous? (From a privacy perspective, this may not work well on articles with a small number of annotators as the presumption could be that the "private" highlights would most likely be directly attributed to those who also made public annotations.

Perhaps the better solution is to default highlights to public and provide friction-free UI to make them private?

A heavily highlighted section by a broad community can be a valuable thing, but surfacing it can be a difficult thing to do.

I would push back on this. I have a feeling the effect may seem different because the network is so small. Making specific choices as we scale up may help to mitigate the effect, but eventually we will assuredly see some of the same problems because while the technology will help to mitigate some of the underlying problems with society, culture, and our media, it is not going to cure them.

A case in point is the small network on Micro.blog, which, while generally warm and welcoming, is more monolithic towards the tech space, the Apple space, and has a high proportion of white, cis-gender males. This "founder effect" is likely going to heavily influence this community for a long time. Most times I spend time there, I'm subtly surrounded by the spectacle of Apple.

Push back, sure, but where? Where would we find this push back? The comments section only has a few tidbits. Perhaps the rest is on Twitter, Facebook, or some other social silo where the conversation is fraught-fully fragmented. Your own social capital is thus spread out and not easily compiled or compounded. As a result I wonder who may or may not have read this piece...

Great points!

Reviewer #3:

The manuscript by Hutchings et al. describes several previously uncharacterised molecular interactions in the coats of COP-II vesicles by using a reconstituted coats of yeast COPI-II. They have improved the resolution of the inner coat to 4.7A by tomography and subtomogram averaging, revealing detailed interactions, including those made by the so-called L-loop not observed before. Analysis of the outer layer also led to new interesting discoveries. The sec 31 CTD was assigned in the map by comparing the WT and deletion mutant STA-generated density maps. It seems to stabilise the COP-II coats and further evidence from yeast deletion mutants and microsome budding reconstitution experiments suggests that this stabilisation is required in vitro. Furthermore, COP-II rods that cover the membrane tubules in right-handed manner revealed sometimes an extra rod, which is not part of the canonical lattice, bound to them. The binding mode of these extra rods (which I refer to here a Y-shape) is different from the canonical two-fold symmetric vertex (X-shape). When the same binding mode is utilized on both sides of the extra rod (Y-Y) the rod seems to simply insert in the canonical lattice. However, when the Y-binding mode is utilized on one side of the rod and the X-binding mode on the other side, this leads to bridging different lattices together. This potentially contributes to increased flexibility in the outer coat, which may be required to adopt different membrane curvatures and shapes with different cargos. These observations build a picture where stabilising elements in both COP-II layers contribute to functional cargo transport. The paper makes significant novel findings that are described well. Technically the paper is excellent and the figures nicely support the text. I have minor suggestions that I think would improve the text and figures.

L 108: "We collected .... tomograms". While the meaning is clear to a specialist, this may sound somewhat odd to a generic reader. Perhaps you could say "We acquired cryo-EM data of COP-II induced tubules as tilt series that were subsequently used to reconstruct 3D tomograms of the tubules."

L 114: "we developed an unbiased, localisation-based approach". What is the part that was developed here? It seems that the inner layer particle coordinates where simply shifted to get starting points in the outer layer. Developing an approach sounds more substantial than this. Also, it's unclear what is unbiased about this approach. The whole point is that it's biased to certain regions (which is a good thing as it incorporates prior knowledge on the location of the structures).

L 124: "The outer coat vertex was refined to a resolution of approximately ~12 A, revealing unprecedented detail of the molecular interactions between Sec31 molecules (Supplementary Fig 2A)". The map alone does not reveal molecular interactions; the main understanding comes from fitting of X-ray structures to the low-resolution map. Also "unprecedented detail" itself is somewhat problematic as the map of Noble et al (2013) of the Sec31 vertex is also at nominal resolution of 12 A. Furthermore, Supplementary Fig 2A does not reveal this "unprecedented detail", it shows the resolution estimation by FSC. To clarify, these points you could say: "Fitting of the Sec31 atomic model to our reconstruction vertex at 12-A resolution (Supplementary Fig 2A) revealed the molecular interactions between different copies of Sec31 in the membrane-assembled coat.

L 150: Can the authors exclude the possibility that the difference is due to differences in data processing? E.g. how the maps’ amplitudes have been adjusted?

L 172: "that wrap tubules either in a left- or right-handed manner". Don't they always do both on each tubule? Now this sentence could be interpreted to mean that some tubules have a left-handed coat and some a right-handed coat.

L276: "The difference map" hasn't been introduced earlier but is referred to here as if it has been.

L299: Can "Secondary structure predictions" denote a protein region "highly prone to protein binding"?

L316: It's true that the detail in the map of the inner coat is unprecedented and the model presented in Figure 7 is partially based on that. But here "unprecedented resolution" sounds strange as this sentence refers to a schematic model and not a map.

L325: "have 'compacted' during evolution" -> remove. It's enough to say it's more compact in humans and less compact in yeast as there could have been different adaptations in different organisms at this interface.

L327: What's exactly meant by "sequence diversity or variability at this density".

L606-607: The description of this custom data processing approach is difficult to follow. Why is in-plane flip needed and how is it used here?

L627: "Z" here refers to the coordinate system of aligned particles not that of the original tomogram. Perhaps just say "shifted 8 pixels further away from the membrane"

L642-643: How can the "left-handed" and "right-handed" rods be separated here? These terms refer to the long-range organisation of the rods in the lattice; it's not clear how they were separated in the early alignments.

Figure 2B. It's difficult to see the difference between dark and light pink colours.

Figure 3C. These panels report the relative frequency of neighbouring vertices at each position; "intensity" does not seem to be the right measure for this. You could say that the colour bar indicates the "relative frequency of neighbouring vertices at each position" and add detail how the values were scaled between 0 and 1. The same applies to SFigure 1E.

Figure 4. The COP-II rods themselves are relatively straight, and they are not left-handed or right-handed. Here, more accurate would be "architecture of COPII rods organised in a left-handed manner". (In the text the authors may of course define and then use this shorter expression if they so wish.) Panel 4B top panel could have the title "left-handed" and the lower panel should have the title "right-handed" (for consistency and clarity).

This is important to me because we often think to ourselves that this is basic knowledge, however, there are those who may not be exposed to it, are uneducated, or simply deny the reality of our systems. As we get older we experience more and for those who haven't been as exposed to it realizing the importance of evidence about inequality is essential to education. (Gerrymandering, institutionalized racism, voter oppression, higher rates of hate crimes and violence against people of color, outdated policing systems and education)

This is an interesting concept, especially as someone from this generation. Our generation has been one of the most open minded to date, however, we live in the United States, a country that is notorious for leaning toward conservative views. Some of us may not have a concept of what politics in other places are and we may not be as open minded as we think.

As human beings we ruled ourselves without any goverments or governers. Humans doesn't need these things at all,a governer can only provide unfair punishments to us.The idea that Anarchy lead us to chaos is only for corrupted minds. Our nature is not available for a governor to rule us.Since the Homo Sapiens are te only mankinds on this earth we know we never had it in our nature.That's why anarchy maybe good for our routine.So thats the way I think about that part

This paragraph basically states the fact that physiology is completely different from psychology in the fact that it focuses on strictly physical things. This reiterates the fact that psychology is it's own individual science. That we have made psychology unique and formed it and branched it off of other sciences and theories

Most of us as humans grow up being taught to respect personal space. Gideon Kahn says that he doesn't think that he's ever used the word consent when teaching young children. I think it's important to start using that word and teaching children at younger age. It may be hard for some of the kids to understand but it still needs to be a conversation. We should all start learning at a younger age so we can realize the full extent of consent before reaching the age where kids start to develop a sex drive. Without this understanding, you may unintentionally hurt somebody by not respecting their space.

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Reply to the reviewers

Response to Reviewers and Revision Plan

We thank all three reviewers for their time and their comments on our manuscript.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Here Ryan et al. have used localization analysis following induced rapid relocalization of endogenous proteins to investigate the composition and recruitment hierarchy of a clathrin-TACC3-based spindle complex that is important for microtubule organization and stability.

The authors generate different HeLa cell lines, each with one of four complex members (TACC3, CLTA, chTOG and GTSE1) endogenously tagged with FKBP-GFP via Cas9-mediated editing. This tag allows rapid recruitment to the mitochondria upon rapamycin addition ("knocksideways"). They ultimately quantify each of the 4 components' localization to the spindle following knocksideways of each component using fluorescently-tagged transfected constructs. The authors' interpretation of the results of this analysis are summarized in the last model figure, in which a core MT-binding complex of clathrin and TACC3 recruit the ancillary components GTSE1 and chTOG. In addition, the authors investigate the contribution of individual clathrin-binding LIDL motifs in GTSE1 to the recruitment of clathrin and GTSE1 to spindles. Their findings here largely agree with and confirm a recent report regarding the contribution of these motifs to GTSE1 recruitment to the spindle. They further analyzed GTSE1 fragments for interphase and mitotic microtubule localization, and identified a second region of GTSE1 required (but not sufficient) for spindle localization. Finally, the authors report that PIK3C2A is not part of this complex, contradicting (correcting) a previously published study.

**Major comments:**

1.The chTOG-FKBP-GFP cell line the authors generate has only a small fraction of chTOG tagged, and thus should not be used for any conclusions about protein localization dependency on chTOG. Because they were unable to construct a HeLa cell line with all copies tagged, the authors expect that the homozygous knock-in of chTOG-FKBP-GFP is lethal, and thus their experience is appropriate to report. However, the authors should not use this cell line alone to make statements about chTOG dependency. They would have to use similar localization analysis, but after another method to disrupt chTOG (as a second-best approach), such as RNAi. In fact, they have reported this in a previous publication (Booth et al 2011). However, the result was different. There, loss of chTOG resulted in reduced clathrin on spindles, suggesting it may stabilize or help recruit the complex. Alternatively, they could remove their chTOG data, but this would compromise the "comprehensive" nature of the work.

The referee is correct. The point here is to show the results we had using this approach for all four proteins under study. For this reason, we do not want to remove this data and prefer to show our results “warts-and-all”. We feel that the shortcomings of our approach are honestly presented and discussed in the manuscript. While only a fraction of chTOG was tagged, we should expect some co-removal after its induced mislocalization. Since we saw no change, we concluded that chTOG is auxiliary.

The “second best” approach suggested (RNAi of chTOG) is problematic for two reasons. First, chTOG RNAi results in gross changes to spindle structure (multipolar spindles) and it is difficult to pick apart differences in protein partner localization that result from loss of chTOG from those resulting from changes in spindle structure. Second, the paper is about induced mislocalization as a method for determining protein complexes once a normal spindle has formed. So, removing chTOG prior to mitosis is not comparable. If we get the same or different result, does it confirm or conflict with the data we have? Nonetheless, given the discrepancy with our earlier work, we should investigate this further.

To address this concern, we will stain endogenous clathrin, TACC3 and GTSE1 following chTOG RNAi and measure their relative levels at the spindle.

Making the chTOG-FKBP-GFP cell line was difficult. As described in the paper, we only recovered heterozygous clones despite repeated attempts. Since submission, we have been made aware of a HCT116 chTOG-FKBP-GFP cell line that is reported to be homozygously tagged (Cherry et al. 2019 doi: 10.1002/glia.23628).

A note about this cell line has been added to the paper (Results section, final sentence of 1st paragraph).

2.The authors initially analyze complex member localization after knocksideways experiments by antibody staining, which has the advantage of analyzing endogenous proteins (versus the later transfected fluorescent constructs). Setting aside potential artefacts from fixation, this would seem to be a better method for controlled analysis to take advantage of their setup (short of generating stable cell lines with second proteins endogenously tagged in a second color - a huge undertaking). The authors conclude that antibody specificity problems confounded their analysis and explained unusual results. However, I think is worth investing a little more effort to sort this out, rather than bringing doubt to the whole data set. Verifying and then using another antibody for chTOG localization would be informative. Of course, the negative control should not be their chTOG-FKBP-GFP line, as it does not relocalize most of chTOG.

In the case of GTSE1, an alternative explanation to antibody specificity issues would be that the GTSE1-FKBP-GFP cell line is not in fact homozygously tagged. Given the low expression levels on the western provided, and the detection of GTSE1 on the spindle in the induced GTSE1-FKBP-GFP cell line (but not TACC3-FKBP-GFP), it seems plausible that an untagged copy remains. If there are multiple copies of GTSE1 in Hela cells, one untagged copy could represent a small fraction of total GTSE1. This should thus be ruled out. GTSE1 clones should be analyzed with more protein extracts loaded - dilutions of the extracts can determine the sensitivity of the blot to lower protein levels. In addition, sequencing of genomic DNA can reveal a small percentage with different reads.

We used a two-pronged approach for assessing relocalization of protein partners (staining vs transfected constructs). The staining approach is superior since endogenous proteins are examined, but it is limited by antibody specificity. The transfection approach overcomes this limitation but is in turn limited by effects of overexpression and tagging. Together the two approaches allow us, and anyone employing this method, to get a picture of protein complexes. We didn’t want to create the impression that one or other approach is confounded, but the referee is correct that this analysis would benefit from further work.

Specifically, to address these concerns:

• We will verify and use alternative chTOG antibodies to try to improve this dataset.
• We will test the possibility that an untagged allele of GTSE1 remains. We will use western blotting and a summary of our genomic analysis will be added to the paper.

  3.There is a lot of data contained in the small graphs summarizing quantification of localization in Figs 3 and 4. They would be more accessible to the reader if they were larger and/or an "example" of the chart with labels was present explaining it (essentially what is in the figure legends). Furthermore, there is no statistical test applied to this data that I see. This is needed. How do authors determine whether there is an "effect"?

Our aim was to compress a lot of information into a small space, while still showing some example primary data. All reviewers raised the same concern which tells us that we went too far towards “data visualization”.

To address this point, we will rework these figures.

**Minor issues:**

1.The GTSE1 constructs used for mutation and localization analysis are 720 amino acids long. A recent study analyzing similar mutations uses a 739 amino acid construct (Rondelet et al 2020). The latter is the predominant transcript in NCBI and Ensembl databases. It appears the construct used by the authors omits the first 19 a.a.. I do not think using the truncated transcript affects conclusions of the manuscript, but it could generate confusion when identifying residues based on a.a.#s of mutant constructs (Fig 6). This should be somehow clarified.

We were aware of the longer transcript but were using the 720 residue form since it is the canonical sequence in Uniprot (https://www.uniprot.org/uniprot/Q9NYZ3). We did not know that the 739 form is the predominant transcript. We agree this is unlikely to affect our work but that the numbering may cause confusion.

We have added a note to the Methods (Molecular Biology section) to accurately describe what we and Rondelet et al. have used.

2.The labeling of constructs in Fig 6C/D is confusing, and appears shifted by eye at places. Please relabel this more clearly.

Apologies for the error.

We have relabeled Figure 6C,D and also made a similar alteration to Figure 5C.

The recommended new experimental data (Analysis complex member levels on spindles after full perturbation of spindle chTOG; new chTOG antibody stainings in the FKBP lines; reanalysis of GTSE1 DNA/protein in GTSE1-FKBP line) should only require a new antibody/siRNA, plus a few weeks time to repeat the analyses already in the paper with new reagents.

Reviewer #1 (Significance (Required)):

While multiple individual components of this complex have been previously characterized, the structure and nature of the complex formation and its recruitment to microtubules/spindles remains a complex problem that has yet to be solved.

Overall this study represents a comprehensive localization-dependency analysis of the Clathrin-TACC3 based spindle complex using a consistent methodology. Although several of the conclusions of the findings echo previous reports, some of the previous literature is contradictory within itself as well as with the conclusions here. Analyzing all components with a single, rapid-perturbation technique thus has great value to present a clear data set, given that the experimental setup conditions and analysis are solid (a goal to which the majority of comments refer).

Beyond the complex localization/recruitment analysis, two novel findings of this study that emerge are:

a)GTSE1 contains a second, separate protein region, distinct from the clathrin-binding motifs that is required for its localization to the spindle, and most likely a microtubule-interaction site. This suggests that GTSE1 recruitment to the spindle is more complex than previously reported.

b)PI3KC2A, which has been reported previously to be a stabilizing member of this complex, is in fact not a member, nor localizes to spindles, nor displays a mitotic defect after loss. This is important conclusion to be made as it would correct the literature, and avoid future confusion.

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Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this paper, the authors investigate the nature of interactions between members of the TACC3-chTOG-clathrin-GTSE1 complex on the mitotic spindle. By using a series of HeLa cell lines that they have created by CRISPR/Cas9 editing to enable spatial manipulation (knocksideways) of either TACC3, chTOG, clathrin and GTSE1, they show that on spindle microtubules TACC3 and clathrin represent core complex members whereas chTOG and GTSE1 bind to them respectively but not to each other. Additionally, the authors find that the protein PIK3C2A, which has been implicated in this complex previously is in fact not a component of this complex in mitotic cells. The main advance of the paper in my opinion is the endogenous tagging of the proteins for knocksideways experiments since former experiments depended on RNAi silencing and expression of tagged proteins from plasmids, which introduced issues of protein silencing efficiency and plasmid overexpression problems. This approach seems to alleviate these problems, except in the case of chTOG which seems to be lethal in its homozygous variant.

**Major comments:**

I find the key conclusions regarding the localization of the components of the complex convincing. There are some issues regarding the specificity of antibodies in immunostaining experiments (Fig 3.) and the influence of mCherry-TACC3 expression on distorted localization of the complex prior to knocksideways. However, I think the general conclusion about which complex components (clathrin and TACC3) influence the localization of the other proteins in the complex (chTOG and GTSE1) stands. One thing that I miss from the paper is the data on the consequences on the spindle shape and morphology after knocksideways. I have noticed on images in both Figure 3 and Figure 4 that in some cases distribution of the signal seems to influence quite a bit the spindle morphology. Also, In Figure 3 I have noticed what seems to me a quite big variation in spindle size in tubulin signal in both untreated and rapamycin cells. Since authors have many of these images already, I believe it would be realistic, not costly and of additional value for the paper to provide more data on the consequences of the knocksideways experiments. Change of spindle size, tubulin intensity and DNA/kinetochore misalignment upon knocksideways would be helpful to appreciate more the findings of the paper. More so since the authors on more than one occasion find their motivation in the field of cancer research and spindle stability relation to it. Some data connection to this motivation would be of value. Experiments seem reproducible.

The focus of the paper is on using the knocksideways methodology to understand a protein complex during mitosis, rather than looking at its function. We are not keen to do new experiments that are not part of the central message of the paper. However, the Reviewer is correct that we do already have a dataset that can be mined in the manner described.

To address this point, we will analyze spindle size parameters and also the intensity of tubulin. Our analysis will be limited to the short timeframe of our experiments, but it should reveal or refute any changes in spindle structure that may result from loss of complex members.

**Minor comments:**

I have some problems with the clarity of Figure 3 and 4. For Figure 3. In Figure 3 plots on the right are a bit small and not easy to read. Some reorganization of the figure might be beneficial. In Figure 4 plots to the right are also too small to be clear. Also, I miss the number of cells (n) I can't see the number of individual arrows because of the size of graphs.

Our aim was to compress a lot of information into a small space, while still showing some example primary data. All reviewers raised the same concern which tells us that we went too far towards “data visualization”.

To address this point, we will rework these figures.

Reviewer #2 (Significance (Required)):

I find that the biggest significance of the paper is in the creation of new tools (cell lines) to study the localization of proteins TACC3, chTOG, clathrin and GTSE1. Cell lines where endogenous proteins can be delocalized rapidly will be of value for scientist working not only in mitosis but such as in the case of clathrin research, vesicle formation and trafficking or p53-dependent apoptosis in the case of GTSE1. In the field of mitosis it will surely help and speed up the research concerning the role of these proteins in spindle assembly and stability.

Field of expertise: mitotic spindle

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Reviewer #3 (Evidence, reproducibility and clarity (Required)):

**Summary:**

This papers analyses the chTog/TACC3/clathrin/GTSE1 complex that crosslinks and stabilises microtubule bundles in the mitotic spindle. The authors have developed an elegant knock sideways approach to specifically analyse the effects of removing individual components of the complex from the spindle and study the effect this has on the other interactors. They report, based on these assays that the core of the complex is formed by TACC3 and Clathrin while GTSE1 and chTog are auxiliary interactors. They also refute previous evidence that this complex also incorporates PIK3C2A. Overall, this is an interesting study that distinguishes itself predominantly by its methodology. However, some of the reported results need more thorough analysis to allow convincing conclusions.

**Major comments:**

1)The knockside way method is the main highlight if this paper. Unlike previous studies by the PI, this time endogenous genes are tagged which is a key advance and allows much better interpretation of the results. I am not sure why the authors have chosen HeLa cells as their model here, given the messed up genome of these cells. A non-transformed cell line would have been preferable, but as a proof of principle study, I think HeLa are acceptable, and I wouldn't expect the authors to repeat all the experiment in another system.

Figure 1,2 and S1 are describing and validating this approach in some detail, but this will require some more work.

The authors state that gene targeting was validated using a combination of PCR, sequencing, Western blotting, but show only the results for westerns. PCR analysis that demonstrates homozygous or heterozygous gene targeting should be shown here.

Another issue is the penetrance of the phenotypes induced by Rapamycin. The authors show nice data of the system working in individual cells but do not give us an idea if this happens in all cells. The localisation of the individual tagged genes should be quantified (ideally with line plots) in 50 randomly chosen mitotic cells with 3 repeats before and after rapamycin treatment. Moreover, the analysis of mitotic duration (Figure S1D) should be extended to include a plus Rapamycin cohort and this should be moved in the main Figure.

If the system works only in a small proportion of cells, this should be clearly stated. I don't think this would prevent publication, but it is an important piece of information that is missing.

The Reviewer raises two issues here.

• PCR analysis should be shown. This issue was also partly raised by Reviewer 1. A summary of our PCR analysis was actually included in Table 1, since the analysis we did is pretty unwieldy. We agree though that presenting our evidence for homozygosity of the cell lines would be useful. To address this point, we will add more detail of the PCR and sequencing work done to validate these cell lines.
• Does knocksideways happen in all cells? The answer to this depends on the transient expression of MitoTrap and sufficient application of rapamycin. We agree that this will be a useful piece of information to add to the manuscript. A related issue is whether knocksideways of complex members affects mitotic progression. We have established through other experiments that rapamycin application to wild-type cells alters mitotic progression, although application of Rapalog does not have this effect. Our plan to address these points is 1) to analyze the efficacy of knocksideways that readers can expect to achieve using these, or similar cells, and 2) analyze mitotic duration in rapalog-treated cells expressing a rapalog sensitive MitoTrap.

  2)Apart from a simple quantification of mitotic duration, I believe a more detailed mitotic phenotype analysis for each knock-side way gene, especially the homozygous targeted clones, should be included. This can involve more high-resolution live cell imaging of mitotic progression with SiR-DNA and GFP-tubulin, using the dark mitotrap.

We don’t agree that such an analysis should be included. The focus of this paper is on using the knocksideways methodology to understand a protein complex during mitosis, and not looking at its function. There are several papers on the mitotic phenotypes of these genes probed using RNAi in different cellular systems (examples for chTOG: 10.1101/gad.245603; TACC3/clathrin: 10.1038/emboj.2011.15, 10.1242/jcs.075911, 10.1083/jcb.200911091, 10.1083/jcb.200911120; GTSE1: 10.1083/jcb.201606081). Moreover, our 2013 paper used knocksideways (with RNAi and overexpression) and has a detailed analysis of mitotic progression, microtubule stability, checkpoint activity and kinetochore motions (Cheeseman et al., 2013 doi: 10.1242/jcs.124834).

New experiments that are not part of the central message of the paper and are unlikely to give new insight are not the best use of our revision efforts for this paper (especially during the pandemic). Having said this, Reviewer 2’s suggestion to use our existing dataset to investigate mitotic phenotypes, will largely answer Reviewer 3’s request.

We will analyze spindle size parameters and also the intensity of tubulin. Our analysis will be limited to the short timeframe of our experiments, but it should reveal or refute any changes in spindle structure that result from the loss of complex members.

3)Overall, the quantitative analysis in Figure 3 ,4 and 7 is not good enough and sometimes doesn't fully support the conclusions. In Figure 3,4 a convoluted way of demonstrating the change in localisation is shown and this panel is so small that is almost impossible to read. Also, there is no statistical analysis, and the sample size seems very small . At least 25 cells should be analysed here in 3 repeats. I would suggest to unify the quantification in the MS and use the line plots shown in Figure 5 and 6 and compare each protein before and after rapamycin addition. This is much easier to read and more convincing. The images of the cells panels can be moved to a supplement as they contain very little information. This would generate space to expand the size and depth of the quantitative analysis. Instead of Anova tests, I would recommend using a simple t-test comparing each condition to its relevant control since this is the only relevant comparison in the experiment. Statistical significance should be calculated for each experiment with sufficient sample size. It would also be better to show the individual data points from the three repeats in different colours so that the reproducibility between repeat can be judged.

This type of statistical analysis should be uniformly done throughout the MS and also extended to Figure 7.

The referee raises several issues here with our data presentation and statistical analysis.

• Our aim in Figures 3 and 4 was to compress a lot of information into a small space, while still showing some example primary data. All reviewers raised the same concern about these figures which tells us that we went too far towards “data visualization”. To address this point, we will rework Figures 3 and 4 to provide more clear data presentation.
• The Reviewer’s comments about statistical analysis however are not sound. First, it is incorrect to state that simple t-tests can be applied (this is a form of p-hacking). Correction for multiple testing must be done on these datasets. Second, the reviewer arbitrarily states numbers for cells and experimental repeats without considering the effect size or it seems, understanding the structure of the data that we have collected. Sample sizes are small but they are taken from many independent replicates. Third, and related to the previous point, the fixed and live cell data are structured differently which means that a uniform data presentation is not possible. The live data has a paired design and each cell is an independent replicate (with replicates done over several trials). The fixed data is unpaired and we have taken measures from several experiments (independent replicates). The point about applying statistical tests to the data is also made by Reviewer 1 and we will use appropriate tests (NHST or estimation statistics) as we re-work the figures.

  Reviewer #3 (Significance (Required)):

In my opinion, the most interesting aspect of the MS is the methodology. Based on this, publication is justified and will be of interest to a wider audience. That is why a more detailed analysis of the penetrance of this manipulation across the cell population will be critical.

The application of this method to analyse the composition of the TACC3/Clathrin complex on the spindle is the main biological advance, and the novel information is rather limited but not unimportant.

Overall, if these results can be properly quantified I would recommend publication.

I think this is a crucial note; however, I think the central focus of this is warped deeply by the reality of social distancing. I wonder how we may be able to find "hidden lessons" within the (no pun intended) small wiggle room we have physically/spatially in the classroom as of now.

I think the author is referring to how even though it may seem there is movement towards equality, the damage and trauma done under apartheid and colonialism cannot be forgotten among South Africans, which is seen in South African literature. The author's discussion about power dynamics reminded me of a previous reading we discussed about minor literatures. One of the struggles they may be dealing with is being a minor literature in their own country - even though they are technically the majority, they are fighting for their rights and freedoms.

This sermon is truly eye opening to those who have never read it before. I have never seen such bold, outright wording in a religious setting and am somewhat shocked by the abrasiveness of the pastor. Edwards warns the audience that they will go to hell if they don't repent for their sins and find their way back to God. The audience is obviously church-goers yet Edwards is fervent in his accusations that they are not righteous people. The message was well-received due to the impact it left and may have been well-intended. However, the pastor could have shown more care in his more outrageous accusations. Religion is very important to some people but it is not something that should consume ones whole life. God is meant to be fair and loving therefore presenting him as a being that is dangling people and waiting for them to drop into hell is quite shocking and somewhat dramatic. God would not abandon one of his creations because they don't worship the same way as someone else.

Edwards here makes the strongest connection to his audience in the document as he specifically points out people who may have not been getting his message. In pointing out people who may be listening but change nothing or simply choose to not believe him are the most likely to simply put themselves in a position where God will not allow them to escape. I feel that at the time this sermon was given there were defiantly people listening to his sermon that just though about how all he was saying were lies and to stick to the old ways of thinking, but I wonder how these people were effected when this truly blew up with the great awakening and if they themselves had to come to terms with accepting this new way of thinking or being push away. It is an interesting point because many people were effected by the sermon some fainting others crying but what about the ones who thought it was all some big hoax?

Reviewer #1

The authors propose two related (though distinct) methods for the improvement of pharmacological screening analysis and related biomarker analyses. The first is a Gaussian process (GP) approach to dose-response curve fitting for the estimation of IC50, AUC, and related quantities. The goal of this method is to improve point and uncertainty estimates of these quantities through more flexible functional specification and outlier-robust error modeling. The second method is a hierarchical Bayesian approach to biomarker association analysis. This incorporates uncertainty estimates produced by the GP modeling with the aim of providing more sensitive association analyses with fewer false positives.

The combination of methods presented has some potential. Flexible modeling of dose-response relationships and better estimation of uncertainty are interesting axes to wring more information out of large-scale screening datasets. There are a few areas to shore up in the paper to increase confidence in the empirical results and generalizability of the methods.

1) There are a number of fixed parameters in the proposed methods, and the calibration procedure used to set these is unclear to me. For the GP models, there are a set of noise parameters for Beta mixture and the length scales and variance parameter for the kernel. I'm not sure how one would generalize the GP methods to other screening datasets as a result of this ambiguity (e.g., how would one determine appropriate noise parameters?). For the hierarchical Bayesian biomarker association model, we have prior scale parameters related to both the effect size and variance parameters. The number of researcher degrees of freedom introduced by these tuned parameters also raises some concerns about the sensitivity of empirical results (e.g., 24 clinically established biomarkers and 6 novel) to these choices. It's not clear if we're seeing a corner case or a robust result. I think the work would benefit from both sensitivity analyses with respect to tuned parameters and guidance on or methods for their estimation. The latter is particularly important if other researchers hope to employ these methods in a different context.

2) The proposed hierarchical Bayesian approach to biomarker association analysis is a reasonable start, but it was unclear to me whether changes in performance stemmed from correcting misspecification in original ANOVA or the use of uncertainty estimates. I suggest comparing results to a heteroskedasticity-robust estimator (e.g., HC3, see Long and Ervin, 2000), which would be valid under the stated model without the requirement for explicit uncertainty estimates or priors. The transformations and tuning applied to uncertainty estimates in this context also make generalization of the approach challenging. The need for the c (power) parameter suggests a potential misspecification or miscalibration at some point in the modeling chain. It would be useful to understand this misspecification better, particularly for researchers hoping to extend or reuse these methods.

3) The GP method provides reasonable estimates of uncertainty, but it would be useful to see them compared to those from the sigmoid model (e.g., from the delta method). It wasn't clear to me how much of the difference in results is coming from incorporation of uncertainty estimates as opposed to changes in the point estimates.

4) The handling of cases with IC50 beyond the maximum observed dose (extrapolating to 10x the maximum concentration) provided a reasonable starting point, but a few subtleties in the handling of corner cases remain unaddressed (e.g., GPs allow positive slope at right edge of range). It would be useful to provide a more general, systematic procedure to address these. Imposing monotonicity may not be the best path, but additional guidance for researchers applying these methods in other contexts would help.

Preprint Review

This preprint was reviewed using eLife’s Preprint Review service, which provides public peer reviews of manuscripts posted on bioRxiv for the benefit of the authors, readers, potential readers, and others interested in our assessment of the work. This review applies only to version 3 of the manuscript.

Summary

In this manuscript the authors propose the identification of a novel protein involved in outer membrane remodelling, named BdpA (BAR domain-like protein A). According to the proposed model BdpA has a conserved role in membrane curvature control during formation of outer membrane vesicle (OMV) and of outer membrane extension (OMEs) in Shewanella oneidensis. The authors also provide evidence that heterologous expression of BdpA promotes formation of OMEs in other bacteria (namely in E. coli), and that BdpA is sufficient to induce OME-like structures when expressed in conditions where OMEs are normally not formed. In eukaryotes proteins containing BAR domains are important for shaping membrane curvature. Given the homology of BdpA to eukaryotic BAR-domain proteins, the authors suggest that BdpA and its homologs define the first prokaryotic family of BAR proteins or pBARs, with eukaryotic-like roles in membrane curvature modulation.

Overall, the reviewers think that this is a very interesting study, and provided that further support is obtained to substantiate the proposed model the reviewers agree that the findings described here tackle a number of significant questions of broad interest. However, the reviewers also think that the evidence provided in this manuscript still does not fully support the conclusion that BdpA protein is involved in membrane curvature control as the eukaryotic proteins containing the BAR domains.

We have compiled a list of comments that we hope will help the authors address the concerns of the reviewers to obtain stronger support for the function of BdpA.

1) The reviewers are concerned that some of the conclusions are based on qualitative observations of microscopy analysis of OMVs and OMEs, and quantitative analyses are lacking to validate qualitative observations. As specified in with examples in the list of minor points below the reviewers propose that the data should be re-analyzed to obtain quantitative results. Specifically, a size distribution analysis could be applied to some microscopy data. Also note that the microscopy methods are poorly described, and as the calculation methods used are not fully available it is difficult to understand if the appropriate methods were used. Please specify how many cells were examined microscopically and how many biological replicates (cultures) were used in each experiment.

2) Statistical analyses were not always the most accurate. In figure 2 unpaired t-test was used for samples that have high variance, this approach may inflate the statistical difference between the strains. For figure 2 a histogram of size distribution analyses could be shown for each strain.

3) The reviewers are concerned that the proteomic data is not clear enough to conclude that the BdpA protein is localized to or enriched in OMV/OME. Could the results be complemented with some other method to confirm BdpA localization? The reviewers are particularly concerned by the fact that a large number of proteins were identified in the OMV fraction. Could it be that some of the OMV/OME fractions were contaminated? What controls were used to ensure that the purification procedure was working effectively? Could the data be strengthened by some quality control analyses to determine how many of those proteins are actually predicted to localize to the outer membrane and periplasm? From the methods it seems that the culture conditions used to prepare the OM versus OMV were different, is this so? If yes, why were the culture conditions different? This could affect protein expression? Please include the detailed growth conditions in the method section.

4) The conclusion that BdpA is a BAR-domain protein is largely based on homology. The supplementary information file includes homology models that show striking similarity with eukaryotic BAR proteins. However, as the authors state, BdpA barely meets the cutoff for a BAR-domain protein. The results with the phenotype of the BdpA mutant, complementations and sufficiency data provide good support to the functional role of BdpA in membrane remodelling. However, the effect of BdpA on membrane stability could be indirect or the result of binding to outer membrane features in a manner distinct from other BAR proteins. Could these results be strengthened with some biochemical corroboration of its activity on membranes or structural data to confirm its relationship to eukaryotic Bar domain proteins? Or structural data to confirm its relationship to eukaryotic BAR domain proteins?

5) The reviewers propose that the paper would be strengthened with the addition of topological studies in OMVs and OMEs. The reviewers had problems in reconciling the presence of a galactose-binding domain in BdpA and LPS sugar binding. The authors hypothesize that the putative Galactose-binding domain of BdpA mediates binding to LPS. However, it is also possible that it binds to peptidoglycan components. This would suggest that the proteins interact with the periplasmic side of the outer membrane rather than coat the OMV to promote OMV formation and release (which one could assume based on the role of some eukaryotic BARs). The addition of topological studies (or some biochemical approach) could make these models less speculative, strengthening the conclusions.

6) Heterologous expression of BdpA in other bacteria provides important compelling arguments for its central role in producing OMEs. However, the imaging data provided do not provide the clearest evidence for induction of OMEs in M. atlanticus and E. coli. This is especially the case with the E. coli images. The extended web of staining in 4c does not resemble the tubules seen in S. oneidensis. It would be great to have some electron microscopy data and/or higher resolution fluorescence images of these bacteria as corroborating evidence. Additionally, only a few cells are shown and quantification of the proportion of cells with OMEs is needed. Thus, as already discussed in point 1, quantitative analyses could improve this important point.

This is quite important to Development Theory, as it presents ideas about different ways of thinking. It shows that people, including scientists think differently about this topic even when evidence may be presented for a different side. There is also evidence for that other side as well, which may bring up we do not know exact origins of species, especially back then.

I don't think that Darwin's theory of evolution was proposed in order to track origins of the universe. It was developed as an explanation for the changes in species we see on earth and even if it were to be considered a theory of cosmogony, it would have many advantages over the other theory of cosmogony which was stated.

This is just slight changes to tests that Cattel now uses to conduct research. Mostly changes in apparatus to provide a slightly more accurate measurement.

Relate:

When talking about turf in the landscape I think there are a lot of levels to the idea of using it in the landscape. It is a complicated subject because it has become so ingrained into our culture. If it is using over 70 million tons of pesticides to manage it then how do, we reduce that and change the culture of these huge lawns. I don’t think that all lawns should be disposed of, but we could reduce the amount that is in the landscape. When I was working for a landscaping company there would be these huge hillsides of perfectly manicured turf that provided no recreation or real purpose to the design. I think if we reduces the amount of these areas , but also stopped trying to put turf in the wrong environments then they may not have as many problems with pests, or we could just reduce the amount of turf used. I also think the idea of not using turf in all areas should be advertised as something unique and prideful the same way turf was advertised.

I think this is important to note. Though the teachers are trying to find those moments of "knots" through observations, the receptiveness of the children may not be what the teacher is hoping to see as a "sticking point".

The facts show that America has it all wrong in putting to much emphasis on national "data-driven" competition. These approaches take away from the unique aspects of each child.

I think the parrot here is symbolizing El General himself. Parrot is not spring which brings joy and happiness. El General is a bad person, however, he is pretending to bring his people joy and justice from his palace.

We can also think of the parrot at the cage as a symbol for the Haitian people who were considered slaves. Even though the parrot is not free and is caged, it is still imitating spring, by the same token, in spite of the oppression and injustice, the Haitian people are not only pretending that everything is ok, but rather that they are happy! Because being miserable may actually upset El General.

This makes me think of our role as educators and evolving beliefs that we have of children. Do we see children as passive or active contributors? What thing I know is that the image of the child I have today may change tomorrow as I believe it gets reshaped with time, experience, and reflection.

I think the author's first sentence has a strong personal point of view that allows the reader to know what she is thinking directly. Personally, I would be curious to know what she would say next, and what discoveries would lead her to such an opinion and conclusion.According to the author's verse, the Truth About many things is not always what it seems. What we see, hear or feel may have different meanings. There are many times when human beings may be wrong about something

As a student, I think we can all agree that this gives us a sense of relief and some breathing room as we are living in one of the most chaotic eras of our life. This is greatly appreciated.

Author Response

We would like to thank eLife editors and the reviewers for their time and effort in reviewing our manuscript, entitled: “Partial prion cross-seeding between fungal and mammalian amyloid signaling motifs” by Bardin et al. We considered carefully their comments and modified our preprint accordingly (new version posted here) and address the remarks and criticism of the reviewers in the response provided below.

The editors’ summary of the review read as follows:

Summary

Bardin and colleagues identify and characterize a third prion system in P. anserina based on a cognate innate immunity signalosome comprised of PNT1/HELLP. The authors demonstrate that the three prion pathways operate orthogonally without cross-seeding; however, the newly identified PNT1/HELLP prion can be cross-seeded by the putatively homologous human necroptosis pathway when it is reconstituted in P. anserina, which further supports an evolutionary relationship between them. The review has identified substantive concerns, which limit the novelty of the work and would require significant new studies to address the mechanistic gaps. These concerns include prior work revealing several major tenets including prion activity for PNT1/HELLP in C. globosum and evolutionary conservation to the mammalian necroptosis pathway and the absence for robust experimental support for cross-seeding, or the absence thereof, membrane disruption as the cause of incompatibility, and for the relationship among toxicity, growth, protein state, and protein interaction. Concerns were also raised about the data presented, or absent, in terms of replicates, frequency of observations, and variability.

It is our understanding that the editors and reviewers raise two types of concerns. One relates to the novelty of the work. The second type directly questions the experimental soundness of some of the presented results. We will briefly respond to the criticism regarding novelty and in detail to the methodological critique. We show the existence of a third PFD-based cell-death inducing system in Podospora, that human RHIM-motifs form prions in Podospora and that RHIM-prions partially cross-seed with PP-fungal prions. These results are nonetheless novel and do shed light on the biology of Podospora and the relation of fungal and mammalian amyloid signaling motifs. Regarding the second group of concerns, we think that by clarifying certain approaches and by giving experimental results in full detail, we are able to wave many of the criticisms. For the remaining points (essentially the question of the HELLP membrane interaction), we amend our preprint to point at the delineation of experimental results and interpretation explicitly. We gratefully acknowledge the editors and reviewers input as a mean to improve the quality of the preprint and realize in light of some of these comments that the manuscript lacked in clarity at place and that detailed results tables (that were summarized in the original preprint for the sake of conciseness) should indeed be included. But having said that, it is our intention to stand our ground regarding the central claims of the paper (as they appeared in the abstract of the preprint).

Reviewer #1

Bardin and colleagues identify and characterize a third prion system in P. anserina based on the PNT1/HELLP NLR-based signalosome based on the amyloid signaling motif PP from Chaetomium globosum. The C-terminal domain of HELLP is shown to exist in either soluble or aggregated states based on fluorescence microscopy of tagged protein in vivo, termed the [pi] state, and to form amyloid in vitro. These distinct states can be propagated independently and induce conversion of full-length HELLP upon cytoplasmic mixing, which leads to cell death. The PNT1 N-terminal domain also forms foci in vivo and can seed conversion of HELLP, also leading to cell death. The C-terminal domain of C. globosum HELLP and the RHIM regions of mammalian RIP1 and RIP3, which both contain PP motifs, can cross-seed HELLP conversion to the aggregated state but the other known P. anserina prions [Het-s] and [phi] are unable to do so.

Support for the model proposed is generally qualitative in nature, with multiple instances of data described but not presented, including the timing of conversion to the aggregated state, revision of the aggregated state in meiotic progeny, the frequencies of conversion and co-localization, and the correlations between growth and prion phenotype. For the data presented, replicates, frequency of observations, and variability are not reported.

It is unclear to us what is meant by “the model proposed”. It is not our understanding that we are proposing “a model” in this paper. The results that we claim are:

-There is a third NLR/HELL protein pair involving amyloid signaling in Podospora

-There is no cross-seeding between HELLP PFD and the two other Podospora PFDs (HET-s, HELLF)

-RHIM can form a prion in Podospora

-There is a partial prion cross-seeding between PP PFDs and mammalian RHIM in vivo in Podospora

These are the statements made in the abstract of the preprint. It is our opinion that these central claims stand in face of the reviewers criticism. We shall attempt to provide whenever possible quantitative details regarding the points raised.

Specifically:

the timing of conversion to the aggregated state

There are two types of experimental situations here. In certain sets of experiments, spontaneous conversion to the prion state is measured at different subculture durations (5, 11, 19 days of subculture) (as appears in Table 1). When induced conversion (cross-seeding) is assayed, the conversion process is measured at a single time point. Details of the timing of assay of the conversion are given in the material and methods section (and now given in Table 1).

revision of the aggregated state in meiotic progeny

Details of the progeny of a specific cross involving curing of the [π] prion are now given. Among 20 meiotic progeny containing the GFP-HELLP(214-271), 3 were cured.

the frequencies of conversion

Possibly the statement that the results are “generally qualitative” comes from the fact that several conversion experiments or barrage interaction results were presented in tables with a binary output (+ or -) in the original preprint. This presentation was chosen because the replicates of these experiments yielded only monotonous all-or-none results. All tested strains were either converted (+) or not (-). In all tables, the number of tested strains and the number of replicates per strain are now given (Table S1 to S6). This presentation results in quite boring tables but we think that this should eliminate this ambiguity.

and co-localization

For all co-localization experiments, in addition to representative micrographs, counts of independent observations for each phenotypes and of co-localizing dots are given in Tables S7 and S8.

the correlations between growth and prion phenotype.

As there is no toxic effect of prion itself in absence of HELL or HeLo containing proteins (published results for [Het-s] and [φ], and verified here for [π] and [Rhim]), this last remark appear to apply to RHIM/HELLP co-expression that results in growth defects. We observe that strains co-expressing RHIM and HELLP are affected in their growth when there are infected with [Rhim] prions. These results are presented in Table 2. We based the conclusion that the growth defect relates to acquisition of the prion phenotype because the growth defect occurs after contact with a prion infected strain. This increase in the number of strains with a growth defect requires presence of the corresponding PFD in the recipient strain. Finally, the same table presents as positive control a similar experiment with homotypic [π]/HELLP interactions.

In addition, a mechanism is proposed to explain the toxicity associated with HELLP conversion to the aggregated state - membrane localization - but this model is not supported by robust data such as a marker for the membrane in the fluorescence images or a biochemical fractionation. Moreover, the absence of functional data, such as mutations that disrupt amyloid formation, leave the model with correlative observations to support it.

We agree that we do not prove membrane association for HELLP. Considering the precedent of HET-S, it is however a plausible explanation for the documented cell-death inducing activity. We acknowledge that we do not provide experimental evidence based on biochemical fractionation or dual labeling that HELLP relocates to the membrane (this would probably require confocal microscopy). What we due claim however is that in this regard HELLP behaves analogously to HET-S, CgHELLP and HELLF. We have modified the text of the preprint to specifically make the statement that proof of membrane localization would require other approaches (in particular biochemical fractionation).

The reviewer calls for mutations that disrupt amyloid formation and that should accordingly abolish HELLP toxicity. While this type of experiment is not lacking interest (this exact type of study has been made in the case of HET-S), we feel that at the present stage the fact that toxicity of HELLP is conditional and occurs specifically in interaction with [π] (not [π*] or other Podospora prions) is a sufficient support to legitimate the suggestion that HELLP functions analogously to HET-S, HELLF and CgHELLP by activation through amyloid templating.

Finally, observations on the C. globosum system decrease the novelty of the observations.

We address this comment below (response to substantive concern 1 of the reviewer #2).

Reviewer #2

This work reports the discovery of an amyloid-based cell death signaling pathway in the filamentous fungus, Podospora anserina. This makes the third such pathway in this fungus. As for the others, the amyloid in this case has prion-like activity, is selectively nucleated by a cognate innate immunity sensor protein, and results in activation of the membrane-disrupting activity of the protein. They show that all three pathways operate orthogonally - that is without cross-seeding. In contrast, cross-seeding did occur between this pathway and the putatively homologous human necroptosis pathway when it is reconstituted in P. anserina, which further supports an evolutionary relationship between them.

Substantive concerns:

1) The novelty of this finding is somewhat dampened by this group's prior demonstration of several of the major points of interest in previous papers. They had previously discovered and characterized the homologous pathway in a different fungus, and suggested an evolutionary link between fungal amyloid signalosomes and mammalian necroptosis using strong bioinformatic and structural evidence. In addition, they had shown that the two previously known amyloid signaling pathways in P. anserina operated orthogonally. Hence the major point of novelty, as reflected in the title, is the demonstration that this particular amyloid pathway can cross-seed the human necroptosis amyloids.

We are honestly puzzled by this comment, shared indeed also by reviewer 1. At no place in the preprint do we claim that the discovery of the PP-motif is new, we build on preceding work on CgHELLP and claim novelty on distinct aspects. While argumenting on the significance of one’s work is somewhat of a vain enterprise, we shall nonetheless point the specific interest we see in these results. As part of our longstanding attention on Podospora as a model to study fungal PCD, we consider it of interest to document that this species contains three amyloid-activated HeLo/HELL-domain cell-death execution pathways. Bioinformatic surveys suggest the co-occurrence of several amyloid motifs in different fungal genomes, it is of interest we think to document this redundancy at a more functional level at least in one system. The present study is superior to the previous one on CgHELLP in the aspect that activity of the PP-motif proteins is being studied in their native context (not in a heterologous host that diverged from C. globosum tens of millions of years ago). Then, to our knowledge, RHIM-motifs have never been shown to behave as prions. There is a non-trivial relation of the concepts of amyloids and prions. The reviewer writes in a later paragraph that amyloids are inherently self-perpetuating but this does imply that all amyloids are prions (or vice versa for that matter). Showing that RHIM forms (like PP-motifs) a prion when expressed in Podospora, stresses we feel the functional similarity between the fungal and animal signaling motifs. The formation of the [Rhim] prions and their propagation in a fungal environment was not a foregone conclusion. It is our experience that not any amyloid sequence will form a prion in Podospora (Aβ, α-syn, etc..) and the reviewer is surely more than aware of the rich literature dealing with the amyloid/prion-relation in yeast models. The Podospora in vivo system might also be of use to others to study RHIM-assembly, for instance to screen for inhibitors of RHIM-assembly. As stated by the reviewer the major novelty is the demonstration of cross-seeding between fungal and human necroptosis pathways which has so far only been suggested on the basis of a sequence similarity on a minute motif of 5-10 amino acids in length. We feel that documenting cross-seeding does strengthen the hypothesis that these motifs are evolutionary related.

2) Implications of "cross-seeding". The interspecific cross-seeding observed was modest; much lower than that for intraspecific templating between proteins of the same pathway. Specifically, it failed to induce a barrage, the puncta formed at different times, and colocalization was incomplete. More importantly, cross-seeding does not imply functional or evolutionary conservation. Consider the wide range of amyloid proteins that have been reported to cross-seed each other despite in some cases very different sequences, structures, and functions - for example the type-II diabetes peptide IAPP with the Alzheimer's peptide Aβ; the yeast prion protein Rnq1 with human Huntingtin; and the yeast prion Sup35 with human transthyretin. Although a direct comparison with the present data are not possible, these cross-seeding interactions appear comparably robust. The present demonstration of limited cross-seeding therefore seems not to add much additional support for an evolutionary relationship between necroptosis and fungal amyloid cell-death pathways.

Cross-seeding is partial and not as efficient as in homotypic or intra-kingdom interactions. This is precisely our conclusion (see for instance line 470 to 473 of the original preprint). We point at this partial effect and state that it suggests both some level of structural similarity but also the existence of functionally important structural differences between RHIM and PP-amyloids. These results are in line with the fact that the consensus RHIM and PP-motifs while sharing some common position also markedly differ on others. The specificity of the cross interaction between [π] and [Rhim] prions is also supported by the absence of cross-reaction between [π] and the other Podospora prions (or between [Rhim] and [Het-s]). The same is true for the partial co-localization. These results serve as a functional context that will allow future structural data on the fold of the PP-motif to be meaningfully compared to the RHIM-structure. To insist on the partial nature of this cross-seeding underlying both relation and differences between PP and RHIM, we propose to modify the title of the manuscript to “Partial prion cross-seeding between fungal and mammalian amyloid signaling motifs”.

The reviewer states : “More importantly, cross-seeding does not imply functional or evolutionary conservation”. Absolutely so. But when two amyloid forming regions show sequence similarity (not just composition bias) and both work as functional amyloid signaling motifs leading to necroptotic cell-death then cross-seeding is a further support (not proof) of evolutionary and functional conservation.

3) Rigor of the fusion experiments. In all cases, despite having generated and validated the use of RFP- and GFP-labeled proteins, all fusion experiments to examine cell death microscopically (using Evans Blue staining) were between two GFP-expressing strains. This is frustrating because it makes it impossible to know from the images alone which of the two proteins is expressed in which cells, and in which cases of mycelia crossing paths is fusion occurring. I must therefore rely entirely on the labels provided, but they sometimes appear implausible. For example, the lower fusion event demarcated in Fig. 3C left panel would have been expected to allow GFP levels to equilibrate across the point of contact; instead there remains a sharp transition in GFP intensity between the two mycelia (third panel) indicating the cytoplasm is not being shared at the time of the image. In Fig. S8 top row, there is no apparent relationship between cell death and HELLP-GFP; moreover, cell death is seen occurring in mycelia containing either punctate or diffuse GFP-RIP3. While I appreciate that Evans Blue fluorescence may overlap with that of RFP (which should be stated) and preclude its visualization without multispectral imaging capabilities that may not be available to the authors, alternative viability stains and fluorescent proteins could in principle have been used to avoid this problem.

Evans blue shows fluorescence that does indeed overlap with RFP fluorescence, which is the reason why we used GFP labeled proteins which is indeed less convenient to distinguish strains. But Evans blue staining allow clear and rapid identification of dead cells. Even with both strain labelled with GFP, strains can be identified based on diffuse versus dot-like fluorescence. Moreover, the fusion are observed in contact zone between the two strains under the microscope where the proportion of dead cells (stained cells) is drastically increased compared to the rest of the mycelium, the relative orientation and position of the filaments allows for strain identification. As for the concerns regarding equilibration levels of GFP or HELLP presence in heterokaryotic cells, it could be explained by the fact that necroptotic cell-death due to HELLP toxic effect, as for the others HeLo or HELL domain containing proteins (Seuring et al. 2012, Mathur et al. 2012, Daskalov et al. 2016, Daskalov et al. 2020), is associated with blocking of the septa to limit the spreading of cell-death through the entire mycelium. Fungal incompatibility is associated both with cell death and compartmentation of the mycelium.

We thank the reviewer to bring to our attention the issues that may be encountered to clearly identify heterokaryotic cells on these images. Therefore, cell death imaging is presented in the new preprint using methylene blue allowing the use of RFP and GFP labeled proteins to identify unequivocally heterokaryotic cells.

Minor Comments:

1) The significance of these proteins forming "prions", as opposed to (merely) amyloids, should be articulated. This is important because prion-formation per se is irrelevant to the cell-level functions of the proteins, as nucleation of the amyloid state causes cell death and hence precludes their persistent/heritable propagation. Amyloid by nature is self-perpetuating at the molecular level and hence would seem to explain the properties of the protein. The discussion about possible exaptation of these pathways for allorecognition could be expanded or clarified in this regard.

These are interesting points. Prion and amyloids are terms with different field of application. The term prion is only meaningful in vivo. We use it preferentially here, because for the most part we document prion propagation and only indirectly amyloid formation. We feel however that it might be premature to conclude that the prion-behaviour is totally irrelevant to the function of these proteins as signaling devices. This all depends (as for other prions) on the actual balance between toxicity and infectivity. It might well be that HELLP propagates part of the amyloid signal before it actually leads to cell death. Please note that even full length HET-S can be observed in certain growth condition in the form of dots and may thus partition between a toxic and an infectious fraction.

2) Colocalization between two proteins does not imply that one has templated the other to form amyloid, even when both are capable of forming amyloid independently (see https://doi.org/10.1073/pnas.0611158104 ).

We fully agree. We have corrected the labelling of the figures that document co-localization that were previously labelled as cross-seeding experiments.

3) Statements of partial cross-seeding are supported by quantitation (Fig. 8). In contrast, the authors appear to use qualitative observations to support rather definitive statements about the "total absence of" (line 344) of cross-seeding between other pathways.

Quantitative data are now given regarding the experiment presented line 344. It is true that the statement “total absence of” relates to the absence of detectable cross-seeding in the experimental setting that was use. Here in this specific case, no prion formation of [Het-s] was detected in a total of 18x2x3 infection attempts with [Rhim] prion donor strains (18 transformants for each [Rhim]-type in triplicate).

4) Fig. S9. "Note that induction of [Rhim] in transformants leads to growth alteration to varying extent ranging from sublethal phenotype to more or less stunted growth." Can the authors suggest an explanation for this heterogeneity? From my limited perspective, it suggests the existence of amyloid polymorphisms (i.e. a prion strain phenomenon), which is quite unexpected given the lack of polymorphism among known functional amyloids in contrast to rampant polymorphism among pathological amyloids. Hence the phenomenon could be interpreted as suggesting that amyloid is not an evolved/functional state for the PP motif. In any case the phenomenon is interesting and merits further discussion.

Phenotypic variability in this experiment can be explained by variation of expression levels of the transgene and prion curing. Transformation occurs through ectopic integration in these experiments (there are no autonomous plasmids available for Podospora). As a consequence in any given experiment, the transformants will display different copy number and integration sites of the transgene and hence variability in expression level. An additional cause of variety is “escape” a due to counter-selection when strain show self-incompatibility, fungal articles in which the transgene causing incompatibility is mutated or deleted will escape cell-death and resume growth. This is very typical of self-incompatible strains and has been largely documented and used as an experimental tool for mutant selection in Podospora and other filamentous fungi. This phenomenon typically leads to sector formation. Then in the specific case of experiments involving prion proteins in addition to these mechanisms leading to genetic variability, “escape” can also occur through prion curing. If a prion causes self-incompatibility, growth recovery occurs through prion curing (this has been largely studied in the case of the [Het-s]/HET-S interaction). We do not formally exclude the possibility that part of the variability may reflect prion strain formation but other explanations should probably be considered more likely, as indeed we have no evidence for strain formation for any of the wild –type functional prion motifs we have characterized so far in fungi.

Reviewer #3

Three distinct amyloid-based cell-death pathways in fungi have been reported. The authors of the current manuscript extend their previous work of the HELLP/SBP/PNT1 pathway in Chaetomium globosum and describe a similar system in P. anserina. It is shown that the amyloid signaling domain of PTN1 can form a prion in cells deleted of HELLP, which is otherwise activated by the prion to cause cell death. Using this artificial system, the authors test whether the related RHIM motif of the human RIP1 and RIP3 protein can also form a prion in P. anserina and whether RHIM amyloids as well as other fungal amyloid-forming motifs can cross-seed PTN1.

The experiments are well executed and explained but I have a few suggestions:

1) Amyloid cross seeding is usually assayed in vitro using purified protein fragments. The artificial genetic system used here is certainly clever but the expression level of different proteins needs to be measured for better comparison of cross-seeding efficiencies.

We feel that the in vivo system presented here has important advantages, in particular is it less “artificial” than in vitro seeding in the sense that at least HELLP is in its native cellular context. Note also that the cross-seeding experiments are done with several distinct transformants which as explained above represent different expression levels of the transgene.

2) Page 16, line 333-334 and Fig 8: How were recipient strains sampled? How random was it? How many samples?

We thank the reviewer to bring this to our attention and to address these shortcomings, we added precisions on samples selection and numbers in results and in methods section.

3) Jargons/abbreviations. Page 19, line 405; Page 20, line 429: What are PAMPs, MAMPs, and PCD?

These abbreviations have been spelled out.

While Mr. Turners ideas were of honorable intentions, ( so we think) , one could point out the mental status of this persons actions. I also would like to know who taught him the christian ways and who was apart of his upbringing and what their ideals were. As we know many christian's do not spare the rod; to include his enslavement, lack of social interactions, and a huge contributor may have been lack of proper nutrition with can lead to many aliments alone. Now whether his reasons for commiting the mass murders was indeed the voice of a spirit or just a story to cover his tracks , knowing that many at the time were very strong in their christian beliefs and the word of God, this does not excuse the fact that what his did was on his own terms. This story brings light to many current events and how we can study history to prevent future incidents. Thank you for the lesson and thought provoking reading material, Professor.

Being able to adapt, add meetings / remove meetings, or even change process as needed (ie: tiger team for critical fixes) is important.

Once close to release - we added a "bug triage meeting" just to see if things were actually bugs or not, it served a purpose for a few weeks - then we killed it once it was no longer needed.

I try to consider "what is the value I am getting out of X" - and how we get there may change over time.

At Rangle, there was a "Rangle Flow" ---- I don't think any project every fully hit it, but it was a bit of an ideal that we strove for.

The fact that every project wasn't run exactly the same really bothered some people, but it was something that I enjoyed.

Different teams have different dynamics - and if something is working really well for one team, doesn't mean the same thing will work for another.

this example further helps me understand how powerful our associations can be as a society when thinking or naming things. we gave meaning to the colors red and green in the sense that they mean stop and go, because we associated those colors to colors of importance. it's a given now for everyone to think of those signals because we gave it importance, even though colors don't have definite purposes or definitions in itself.

I found this statement very interesting because when we think of Zeus people often associate him as a person who has little to no weakness. Society views him as as someone who cannot be defied. This example of greek mythology shows how he is not as powerful as he may usually be portrayed.

This alone is a statement each of us should have on our teaching desks. Sometimes we need this, especially when our students need structure in order to pass an exam or begin/jumpstart their writing for school (especially when we get them as high schoolers who have been trained not to write); BUT, a 5 paragraph essay isn't writing nor is it the teaching of writing. We have to think rhetorically and do better by our student writers.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

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Reply to the reviewers

Point-by-point response to reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)): **

The authors constructed a virtually complete fitness landscape of the P1 extension region (4-base-paired helix) in the group I intron from Tetrahymena thermophila, using a kanamycin resistance reporter to evaluate the fold-change in fitness, which is related to self-splicing activity. This was a clever choice of system because it was known from earlier work that the P1 extension adopts two different conformations during self-splicing. The fitness of each variant was determined from the number of reads acquired from the sequencing data sets and analyzed through an extensive computational pipeline. The strength of the paper is that this machine learning approach can be used to calculate how individual variants contribute to the fitness landscape and assess the directions of epistasis across a large number of identified genotypes.

We thank the reviewer for highlighting one of the key strengths of our manuscript, the fact that our analytical approach, using SHAP values, enables contributions of individual variants to be assessed in a genotype-specific manner. This approach provides for a sound, robust, and principled way of describing and understanding the fitness impact of one mutation in the context of (potentially many) others.

The authors argue that machine learning more successfully models subtle effects that arise from interactions between RNA residues, and that the power to analyze deep mutational sequencing experiments can better rationalize fitness constraints arising from multiple conformational states.

We do indeed argue that machine learning is likely to play an increasing role in making sense of deep mutational scanning data. These scans provide high-resolution information on how fitness maps onto genotype, but the molecular underpinnings of this relationship often remain obscure. It is these “hidden” underpinnings, including the effects of specific mutations on RNA/protein folding, structures, and dynamics, that machine learning approaches can help elucidate.

The results are mostly consistent with previous studies even though the authors collected the data in a more advanced and complicated way. They are also able to rationalize complex phenotypes - for example, the observed fitness defects are more prevalent under an unfavorable growth condition (30ºC), because the lower temperature hinders conformational exchange. Although such cold sensitive effects are well known in RNA, it is gratifying that this can be captured in the fitness landscape.

Finding temperature-related fitness effects that are consistent with impaired conformational exchange was also gratifying for us and we thank the reviewer for highlighting this finding.

The results would be more convincing if the authors directly measure the self-splicing activity of a few key variants, such as the C2C21 mutant, to determine whether these mutations alter the self-splicing mechanism of the Tte-119(C20A) master sequence in the way that they infer from their model. In interpreting their results, they may want to consider misfolding of the intron core (coupled to base pairing of P1) and reverse self-splicing. Reversibility in the hairpin ribozyme, for example, turned out to be the key for understanding the effects of certain mutations.

We appreciate that measurements of splicing activity for individual genotypes would complement and further strengthen our study. We will therefore aim to construct strains for a few key genotypes and assay self-splicing activity using RT-qPCR – an approach we previously used successfully to monitor splicing kinetics of self-splicing introns in yeast mitochondria (see Rudan et al. 2018 eLife 7:e35330). Specifically, we will quantify the fraction of spliced and unspliced transcripts using primers that span the exon-exon and the 3’ exon-intron junction, respectively (the 5’ intron-exon junction is genotypically diverse and would require genotype-specific primers). This will be done under non-selective (-kan) conditions, where the relative fraction of spliced and unspliced transcripts is a function of intrinsic splicing ability and not confounded by selection. We aim to include the master sequence, C2C21, G3C20 and its mirror genotype C3G20, U3 (which restores perfect complementarity in the master sequence), and G5 (inferred from the high-throughput experiment to make a strong negative contribution to fitness).

In interpreting our results, we will consider different mechanisms of splicing failure, such as kinetic problems (slow dissociation of P1ex), misfolding of the intron core, reverse self-splicing, and the use of cryptic splice sites, which has previously been documented (see e.g. Woodson & Cech 1991 Biochemistry 30:2042-2050). We note, however that a precise mechanistic dissection of the splicing defects of individual variants is not the purpose of this manuscript and we therefore do not aim to establish genotype-specific defects in great molecular detail.

Related to the point above, interesting conclusions regarding the relationships between base identity and epistasis that arise from metastability should be strengthened with additional examples. For example, the authors can explain why a reverse base-pairing variant (C3G20) exhibits negative epistasis but is not similar to that of the G3C20 construct. This would ideally use the data from the screen but also be validated by checking the self-splicing activity of a few individuals at low and high temperature.

In measuring splicing activity and its link to fitness for a subset of key variants (see point #4), we will include at least one mirror example such as C3G20/G3C20. In addition, we will highlight additional examples of this mirror asymmetry based on the results from our high-throughput screen.

They should validate the screen by showing that kanamycin resistance does indeed correlate strictly with self-splicing activity, and not some other feature such as RNA turnover. (It would also not be a bad idea to check this in the cell, which can be done by primer extension or Northern blotting.)

This question (i.e. whether altered RNA stability rather than splicing efficiency explains differential KNT production and ultimately fitness) has previously been addressed by Guo & Cech (2002) when introducing the knt+intron reporter system. These authors found no difference in mRNA stability in constructs that displayed differential kanamycin resistance. To shore up this conclusion further, we will measure fitness (via colony counts, growth rate or more directly through competitive fitness assays) of the key variants for which we determine splicing activity (see point #4) and then correlate splicing and fitness.

The benefit of the machine learning model is that it can extract signals that may be hard to detect otherwise. The downside is that it doesn't produce a physical model, as far as I am aware. The parameters are themselves not meaningful - except to the degree that trends in the fitness estimates can be explained after the fact. This is something that should ideally be explained more directly in the manuscript.

The reviewer raises an interesting point, that indeed deserves further discussion/explanation. The reviewer is right that, at first sight, high-resolution fitness landscapes like ours do not directly produce a physical (structural) model of the molecule under investigation. They connect genotype and fitness, but the molecular intermediate – a biophysical structure – is not explicit. However, over the last few years, it has become apparent that deep mutational scanning experiments can – both in principle and in practice – yield information that can be leveraged to infer such a physical model. In short, covariation in fitness between residues in a protein or bases in an RNA can be used as inputs for constraint-based modelling of physical interactions. Notably, Schmiedel & Lehner (2019, Nature Genetics 51: 1177-1186) recently demonstrated that deep mutational scanning data can be used in this manner to reconstruct secondary and tertiary protein structure with high accuracy. In principle, the same approach can be used to reconstruct RNA structures. This will require more extensive, molecule-wide fitness data, but our study points towards just this future, even for data collected from structural ensembles.

When we stated in the original manuscript that deconvolution of the fitness landscape might help to reverse engineer structures, this ability to interpolate between genotype and fitness to reveal hidden biophysical/structural relationships is what we refer to. We will revise the manuscript to make this connection more explicit.

The authors claim that by evaluating a large number of sequences at two conditions, they can capture variants with intermediate phenotypes (Fig. 1). This is not necessarily true. If the original screen allows only the most active variants to survive on kan+ medium, then the signature of intermediate phenotypes may not be encoded in the original data, and thus not retrievable even with sophisticated algorithms, which may also be prone to overfitting. At what limit of stringency will the screen fail to yield information about intermediate fitness? How deeply must one sequence to recover this information, especially if noisy or degraded? Some discussion of these effects would be helpful.

The capacity of any high-throughput sequencing-based DMS experiment to resolve intermediate phenotypes does indeed depend on a number of things. The reviewer highlights two of these: First, in screens where the phenotype is not binary (dead/alive) but fitness can be measured on a continuous scale, can we – and do we – capture phenotypes with intermediate fitness? What if only the fittest/most active variants survive? This is, ultimately, an empirical question, and one we can answer quite definitively: we do observe a large range of intermediate phenotypes, which – in our study – correspond to intermediate fold-change values. For each genotype, we can provide confidence limits and assess statistical significance. Table S1 provides this information. Our capacity to resolve these intermediate phenotypes is mainly based on three things. One is adequate sequencing depth, as highlighted by the reviewer. The second is the number of biological replicates (N=6) we analyse, which allows us to differentiate biological variability from noise for a large number of genotypes. This is an important aspect of DMS experiments that has often been overlooked (i.e. there are many other studies where only a single replicate is analysed and biological heterogeneity is not taken into account). With six replicates in hand, we can directly estimate variability (as done e.g. in our DESeq2 analysis) and quantify uncertainty so as to guard against overfitting. In our view, this is arguably more important than sequencing depth in deriving appropriate fitness estimates. Finally, we can resolve intermediate phenotypes because we keep the time lag between initial exposure to kanamycin and assaying genotype frequencies relatively short (overnight growth, see Methods). Our experiment is effectively a multi-genotype competition experiment, and we provide a snapshot across the genotype pool at a given time. If we had measured after several days of culture, genotypes with greater relative fitness would have spread further through the population, at the cost of less fit genotypes, many of which would likely have been eliminated. We kept measurement lag relatively short on purpose so that we could see a clear differential response to kanamycin while still being able to catch more than just a handful of the very fittest genotypes.

In light of the above, it will be apparent that there are no simple answers to the reviewer’s questions about required sequencing depth, levels of stringency, etc. The ability to assign differential fitness across a large population of genotypes hinges on multiple interrelated considerations (sequencing depth, complexity of the final & starting pool, number of replicates). In revising the manuscript, we will highlight some of the key considerations just discussed, bearing in mind that the manuscript cannot possibly discuss all possible pitfalls and requirements of deep mutational scanning experiments in great detail.

Lastly, the evolvability of RNA is fascinating and there is much to learn. However, the authors don't discuss the implications of their findings for molecular evolution although they throw the term around. It would be exciting if there is a trend in the fitness landscape that could help explain the trajectory of RNA evolution in nature.

We agree with the reviewer that it would be exciting to link deep mutational scanning results more closely with observable patterns of RNA evolution. This is true both in relation to evolution of P1ex/group I introns specifically and evolution of dynamic RNA structures more generally. Regarding the latter, we note that selection against excess stability has previously been inferred for 5’ UTRs (see e.g. Gu et al. 2010 PLoS Comp Biol 6: e1000664), although our case is slightly different in that a helix still needs to form but be sufficiently unstable to enable swift dissociation. We also note that riboswitches might make for an excellent subject to study asymmetric constraint and selection against excess stability as they involve formation of competing helices (including participation of some but not all nucleotides in more than one helix), their structure/function is well understood, and many examples are known, providing opportunities for evolutionary analysis. We consider this outside the scope of the current study. We will, however, seek to analyse patterns of evolution in P1ex to establish whether they correspond in a meaningful way to the fitness trends we observe in the laboratory. To do so, we will analyse the distribution and evolutionary history of variants across orthologous introns in different Tetrahymena species/strains, with a focus on P1ex, P10 and the surrounding sequence. Fortunately for us, the 23S ribosomal RNA gene in which the intron is embedded has been used as a phylogenetic marker so that intron/exon sequence information is available for a reasonable number of species/strains (see Doerder 2018 J Eukaryot Microbiol 66:182-208). We will generate an alignment of these sequences and ask, for example, whether N2-N5 are subject to different constraints than N18-N21 mirroring our experimental findings. We have previously successfully quantified patterns of variation surrounding self-splicing introns in yeast mitochondria (Repar & Warnecke 2017 Genetics 205:1641-1648). Note here that extending this analysis beyond Tetrahymena is problematic. Specifically, the intron is absent from close relatives of Tetrahymena (Doerder 2018 J Eukaryot Microbiol 66:182-208) and P1-proximal structures of distant relatives are quite variable. In addition, we are looking at intronic regions that are not only adjacent to but also directly interact with exonic sequence. The exonic context in which the intron is embedded therefore matters but will be quite different for more distant group I introns. We therefore think that aligning and comparing distant orthologs has limited merit.

The authors use the abbreviation DMS for deep mutational scanning; the RNA structure field uses the reagent dimethylsulfate that is also abbreviated DMS. They may want to choose a different acronym or just avoid an acronym altogether.

We appreciate this point about false-friend acronyms. We will either find a different acronym or avoid it altogether.

Reviewer #1 (Significance (Required)):

As the importance of RNA structure for gene expression becomes more widely appreciated, interest in understanding the evolution of RNA structures is also increasing. Compared with the molecular evolution of proteins, evolution and fitness in RNA is far less understood, although the authors appropriately point to a number of recent studies on this topic. The main advance here is to use machine learning methods to analyze the results of a large genotypic screen, with the goal of more accurately capturing the fitness effects of sequences at varied distances from the parental sequence. The specific conclusions reached here such as the importance of metastability or the prominence of cold sensitive effects are not revolutionary, but the authors illustrate how such phenomena can be investigated more systematically and in more depth.

We thank the reviewer for highlighting that our analytical approach showcases how deep mutational scanning data can be analysed in an unbiased and systematic manner to better understand the relationship between genotype, molecular phenotype (e.g. structure), and fitness. The reviewer also rightly points to specific results we obtain regarding temperature-related effects and metastability of P1ex/P10. However, we believe that the most important contribution of this work is a more general one, namely our proof-of-principle demonstration that deep mutational scanning data can capture multiple conformational states simultaneously, and that these states can be deconvoluted from a single fitness landscape to attribute the fitness impact of individual mutations to specific RNA conformations. To our knowledge this had not been explicitly demonstrated before and our work provides an important cornerstone for future studies looking to interpret mutational effects in either RNAs or proteins in the light of dynamic structures.

In light of comments by reviewer #2 below, it is worth reiterating the proof-of-principle nature of this study. Many of the specific results we obtain (e.g. importance of avoiding excess stability in P1ex) are not revolutionary. Indeed, we would be worried if they were. We chose to investigate P1ex because substantial prior work exists that has furnished us with solid positive controls. This independent prior validation allows us to both have great confidence in the data we generate and demonstrate cogently that the two conformational states at the beginning and end of the splicing reaction are captured in the data.

Finally, we believe our work, in covering a virtually complete genotype space, using multiple replicates to quantify uncertainty in fitness estimates, and using SHAP scores to interpret variant effects in genotype-specific context, sets a new high bar for this type of study and will provide valuable reference data and analytical recipes for future analyses. **

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The manuscript by Soo et al probes the effect of mutations on the fitness of the Tetrahymena Group I self-splicing intron. They used high-throughput sequencing to simultaneously identify the effect of every possible sequence in a 4-bp helix. The approach is sound and the conclusions are generally supported. However, the analysis seems overly complicated given the dataset. Both the analysis and the accompanying writing make it difficult to understand what seems to be a fairly clear conclusion - that the relative stabilities of two alternative RNA helices are important for splicing.

We thank the reviewer for testifying to the validity of our approach and the soundness of our conclusions. Regarding the complexity of the analysis, the reviewer is right in that – for the conclusion that the relative stabilities of two alternative helices are important for fitness – a simpler analysis would have sufficed. However, as elaborated in response to point #11 above, our objective here is not merely to draw specific conclusions about the relative stabilities of P1ex and P10, but more general: a) to demonstrate that a single fitness landscape can be deconvoluted to implicate multiple conformations in fitness defects and b) to provide a basic but powerful recipe for doing so in an unbiased, systematic manner using machine learning.

We will strive to make the writing clearer so that readers can follow this reasoning and appreciate our analytical choices.

• **Major Comments** *

The authors state that this method can identify the impact of transient conformational states. However, the two conformational states in this study are not transient - in fact they are associated with two distinct chemical steps of splicing and are quite stable. It may be that the effect of important transient states would be observed, but this study does not demonstrate that.

We used the word “transient” to describe two alternative RNA structures formed during the life cycle of the intron. Both states (characterized by P1ex and P10 formation) are transient in as much as they disappear as splicing proceeds. In retrospect, we agree with the reviewer that this usage is too loose (given how the term is generally used in the literature) and might evoke the wrong connotations. We will therefore revise the manuscript to eliminate references to P1ex and P10 as transient states, but rather describe them as alternative conformations. Of course, the general point remains true: that deep mutational scanning data should in principle capture all fitness-relevant structural states even if these are transient (in the strict sense of the word).

"Fitness" ends up being on an arbitrary scale, which impairs some analysis. A similar high-throughput sequencing pipeline could have been used to directly monitor splicing of every mutant, though at this point that is outside the scope of this study. Even with the arbitrary units, it would be clearer if more time were spent comparing fitness to base-pair stability on an individual basis, rather than the broad analyses. (See minor comments for details.)

The reviewer is right in saying that a high-throughput pipeline could have been designed to monitor splicing of each genotype directly (rather than assaying fitness of the cell population that represents a particular genotype).We chose not to do so. One reason for this is that monitoring splicing directly would have necessitated design of a more complicated assay. This is because, to monitor splicing efficiency, one would have to monitor both pre-mRNA and mRNA for different genotypes. The former is straightforward (using primers that span the exon-intron junction) but the latter is not: successful splicing removes the genotype-specific information from the mRNA (that information being solely encoded in the intron). This a solvable problem in principle. One might, for example, introduce barcodes of sufficient complexity in the mRNA that can be linked back to the intron genotype, but doing so would have introduced a further source of error and complicated analysis. We therefore opted for monitoring genotypic fitness by sequencing the plasmids from which the RNAs originate. This does mean that our measurements of fitness are not coupled to a specific molecular phenotype (such as splicing efficiency) – we presume (but are not entirely sure) this is what the reviewer refers to when talking about fitness being on an “arbitrary scale”. However, fitness derived in this manner has the advantage of providing information that does not start from a mechanistic preconception. We ask how variant affects survival and reproduction of the cell without presuming specific mechanism and the results can therefore capture any mechanism, including those that we did not consider initially. The challenge then becomes to tease out possibly multiple mechanisms from unbiased data.

We will tackle the reviewer’s final comment, regarding analysis of base-pair stability, below in response to one of the minor comments (point #20).

\*Minor Comments** *

The sentence in the abstract beginning "Using an in vivo report system..." is very difficult to comprehend. This is due both to the length of the sentence and the word usage. The final sentence of the abstract is similarly difficult. In general, the writing overemphasizes complexity at the cost of clarity.

We will revise the entire manuscript to make the writing both clearer and more concise.

Analysis of results in terms of "epistasis" obscures what could be a straightforward observation. This is the same as saying that mutants are not independent, or that their energetic costs are not additive. This follows obviously from the observation that the nucleotides being mutated are base-paired.

Making explicit reference to “epistasis” is a considered choice. Framing results in terms of epistasis might be less familiar to readers grounded in RNA or protein biophysics/biochemistry, but is very much at the heart of thinking about the genotype-phenotype relationship from an evolutionary perspective, where global descriptions of epistasis are commonplace and usually provide the starting point for thinking about genotype-phenotype relationships, evolution and evolvability. So what seems unnecessarily obscure when seen through the lens of one field, is natural when considered in the context of another. Importantly, it is also the central approach adopted by many if not most prior deep mutational scanning studies (see e.g. Hayden et al. 2011; Pressman et al. 2019; Zhang et al. 2009; Li et al. 2016; Puchta et al. 2016; Domingo et al. 2018; Li and Zhang 2018; Weinreich et al. 2013; Lalić and Elena 2015; Bendixsen et al. 2017 as cited on page 3 of the manuscript) so we think this framing is helpful to compare our results to prior work.

We expect that the readership will include many researchers interest in mapping genotype-phenotype-fitness relationships who will expect to see global analyses and descriptors of the type we present. We will, however, revise the manuscript to ensure that our description of the findings remains accessible to readers from other fields.

More specifically, we also note that the fact that mutations are not independent (i.e. epistasis exists) might be trivial from the fact that P1ex is a base-paired helix. The magnitude and direction (“sign”) of epistasis, however, are not. In fact, as we describe, contrary to prior DMS on RNA helices, we find a lot of positive epistasis, reflecting, as we argue, selection against excess stability of P1ex to allow subsequent formation of P10.

The novel information is the sensitivity of fitness to base pairing. This is best shown in an analysis like Figure 3A (see below), not broad measures of epistasis.

Please see responses to points #11, #12, and #16 above for an elaboration of what we consider to be the main merits of this study and why providing broad measures of epistasis is a sensible choice.

Figure 1C isn't necessary for the reader to understand the process.

We are happy to follow editorial guidance as to whether this panel is superfluous and should be removed or is worth including.

It is unclear what figure 2C is showing. It appears that the replicates are similar to each other, that 30 deg C and 37 deg C are also similar, but that +/- Kan are different. This probably doesn't need a figure in the main text.

This figure does indeed capture what the reviewer describes: genotype pools in +/-kan are least similar to each other, while 30/37ºC are similar but distinct in the +kan condition and effectively indistinguishable in the -kan condition, in line with expectations. We agree with the reviewer that this information per se is something that would typically be found in a supplementary figure. However, we would advocate for retention of this panel in the main manuscript in this instance because of the way in which it was derived: using the Bray-Curtis dissimilarity index. To our knowledge, this is the first time that Bray-Curtis dissimilarity has been used to quantify, in a principled way, the similarity between genotype pools. Borrowed from the ecology literature, the index captures both richness (number of different species/genotypes in the ecosystem/genotype pool) and relative abundance to provide an integrated measure of genotype diversity. We believe that this measure will be useful for future studies and rather than relegating the figure to the supplement, we would aim to briefly highlight its methodological novelty. *

*

Figure 3A could be the most informative part of the manuscript. However, predicted minimum free energy should be on the x-axis as the independent variable. The expectation then is that you would see a peak in fitness at some free energy, with fitness falling off both with increased and decreased stability. Furthermore, there should be more analysis along these lines. The authors should calculate helical stability for both P1ex and P10 for every mutant and compare with fitness. Mutations which affect both could also be separated out. Figure 4C comes the closest to this but views it only in terms of GC pairs; there is no reason not to quantify the energetic effects given that predictions of stability for helices is quite good. Deviations from a model invoking only helical stabilities would indicate another factor is involved (alternative base-pairing or tertiary structure, for example).

We agree with the reviewer that the axes in Figure 3A should be flipped and we will do so in the revised manuscript. We also agree that, when it comes to helical stability of P1ex, the simple expectation would be to see a peak at a certain stability with drop-offs either side, as intimated by Figure 4C. We further agree with the reviewer that Figure 4C is rather indirect and can be made more quantitative by considering helical stability across all genotypes directly. To this end, we will use one of the many tools available that allow prediction of helical stability from primary sequence (e.g. the enf2 function in RNAStructure, as used by Torgerson et al 2018 RNA, see point #24 below) and replace Figure 4C with a more quantitative fitness landscape based on these computations. To provide added confidence in the computations of helical stabilities from primary sequence in the context of our structure, we will also calculate helical stabilities from molecular dynamics simulations for the subset of genotypes we considered previously (Figure 4E/F) and see how inferred stabilities compare.

There appears to be a missing verb in the legend for figure 3A, second sentence.

We will fix this error.

Figure S5 appears to be redundant with Figure 1.

At first glance, Figure S5 does indeed appear redundant with Figure 1 but it is not. Figure S5 shows the relevant sequence of the group I intron and bordering exons in its native context, i.e. when embedded in the 23S ribosomal RNA gene of Tetrahymena thermophila, whereas Figure 1 shows the genotype of the mutant intron embedded in knt. The sequences are different. We will revise the legend to Figure S5 to make this clearer.

Figure S6 is a better analysis than what appears in the main text, and could be expanded to all base pairs.

We will expand Figure S6 to include all base pairs as suggested. We disagree that this is a better analysis compared to what appears in the main text. Rather, it provides a complementary, hypothesis-driven view whereas the analysis in the main text is more systematic and unbiased in approach. *

*

Reviewer #2 (Significance (Required)):

This manuscript largely focuses on the technical approach. The shift in analytic strategy described above would increase the conceptual impact. The conclusions are consistent with and fit in with recent uses of high-throughput sequencing to study RNA systems. For example Pitt & Ferré-D'Amaré, Science (2010) and Kobari et al, NAR (2015) describe fitness landscapes of the ligase and HDV ribozymes, respectively. Torgerson et al RNA (2018) make similar measurements on the glycine riboswitch, including a treatment of relative helix stability for two mutually exclusive conformations. The overall results are of interest to researchers in the field of noncoding RNA.

We thank the reviewer for highlighting the paper by Torgerson et al, of which – embarrassingly – we were not aware. We will make reference to this paper in a revised manuscript and highlight that riboswitches might be a good model system to further explore asymmetric constraint and selection against excess stability in an evolutionary context (also see our response to point #9 above).

As highlighted earlier, we think the main conceptual impact of our work lies not in the description of helical stabilities. Rather, it lies in a) providing a rigorous proof-of-principle that deep mutational scanning can capture multiple conformational states simultaneously, and b) that, using an unbiased machine learning approach, these states can be deconvoluted from a single fitness landscape to attribute the fitness impact of individual mutations to specific RNA conformations. A shift in analytical strategy to “cut to the chase” and narrowly focus on helical stability would be misguided in this context, as we seek to provide not only insights into the data at hand but also lay out a sound and general recipe for analysing similar datasets in the future.

There will always be times in history where a movement can be polluted by outside issues. I think of this as similar to the visions seen by Joseph Smith. The second Great awakening was a moment in time where we can look back and see some positive things but then realize that there may have been a false profit that skewed the message. The same could be said for Nat Turner. I think this is an example of mental illness and the grandiose ideas that can accompany certain diagnosis. It is unfortunate that things like this can cast a shadow onto the good.

It's unfortunate that so many men, women, and children were murdered during this rebellion. However, it is quite common for all living things to become casualties of war when there is an act of "war". I don't agree fully with Nat Turner murdering so many individuals. Nevertheless, he may have seen his rebellion as an act of God because of the way he was treated from birth. Sometimes you have to put yourself in another's shoes to understand why they say what they say and to understand their actions.

Murder is condemned in the Bible but Nat felt God called upon him to rid the world of it's evils which so happened to be the many he killed. I think if the shoe were on the other foot and it had been us in present day in his shoes we may have done the same thing. The lengths an individual will go to for freedom can come in many forms when you have been mistreated and beaten and ripped of your dignity. Just as we experience psychological events now that cause trauma. We have to acknowledged the trauma he endured and his ancestors endured which led to his breaking point along with many other's who participated in the rebellion.

Again, I'm not saying murder is okay and was the answer but I cannot make judgement on the situation when I did not live during his time, nor do I know what it is like to be stripped of your freedom and dignity. I cannot say my actions would have been of anything less than his and the others which is sad to say but truthful. All he had was his faith in God and he felt God chose him to lead and make a statement of his rebellion.

As I was reading Nat Turner’s confession, I found myself horrified and deeply moved. I could not stop reading his statement, even though it was terrifying to read. What I found the most troubling is that Nat uses verses from the Bible and saying he heard from God to justify his violent behavior. Nowadays, I am afraid if someone did as Nat had done, we might label them as psychotic. While any murder is significant, I think it must be addressed that there were over fifty men, women, and children killed by Turner and his followers. This was not one or two lives that were murdered but over fifty lives. This was a massive massacre. Turner’s reputation of being able to hear from God aided in his credibility and made others more willing to follow his lead. When he talks with the attorney, Thomas Ruffin Gray, he openly admits that God made him do it (the murders). He was not doing what he himself wanted to do but what God wanted him to do. What a terrifying thought to justify one’s actions by claiming they did it because God had told them to. Another incredible thing to consider is that Nat Turner knew there would be consequences for his actions. He was a slave who was bold and brave enough to step up and take a stand against slaveholders. While most of us may not agree with the actions taken my Turner and his followers, I do not know how we can deny where their aggression stemmed from.

Support of Johnson's postulation.

This is reminiscent of the antilibrary piece

Humans are only at the top of the food chain because of their ability to make and manipulate technology - homo faber

Why?

Sounds like IBM's Watson

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Reply to the reviewers

Dear reviewers,

Thank you very much for your constructive and helpful remarks and suggestions!

We marked the changes in the manuscript in yellow.

Our replies to the specific points:

Reviewer #1 In the Introduction the authors need to cite earlier work in Chlamydomonas which first showed that binding of specific proteins to the psbA 5'UTR is correlated with increased translation in the light (Danon et al. 1991).

As suggested, we added the reference to the introduction.

Reviewer #1 The paper could be improved by testing for protein binding to the footprint region in high vs low light. An obvious candidate is HCF173.

We agree that HCF173 is an obvious candidate, although its interaction could be mediated via additional proteins. Alice Barkan’s group has demonstrated that in maize HCF173 binds to the same region upstream of the translation initiation region (McDermott et al., 2019) where we detected a footprint (Supplemental Figure S11A-D). Furthermore, McDermott et al showed that the binding sequence is conserved. We would like to analyze this question in more detail, but we have currently in the lab no approach available to specifically isolate psbA mRNA with its bound proteins for this analysis and therefore have to postpone the answer to this question to future studies.

Reviewer #2: \*Important changes to make before full submission:** 1)It is becoming clear that the translation efficiency (TE) is often not a calculation of translational output from specific mRNAs but in fact is better to be described as ribosome association. There can be many reasons for increased ribosome association including ribosome stalling and increased translational engagement. It would be good for the authors to add a simple Western blot to demonstrate directly increased protein output from psbA during high light as compared to low light treatments. This figure could be added to Figure S1.*

We want to stress that we have chosen a condition that is well known to increase psbA translation in higher plants as shown in the literature with different methods (e.g. Chotewutmontri and Barkan, 2018; Schuster et al., 2020). The protein encoded by psbA, the D1 subunit of photosystem II, has an increased turnover in high light, i.e. a higher amount of D1 has to be produced to compensate for the increased degradation of photodamaged D1 (Mulo et al., 2012; Li et al., 2018).

Although there is a lot of evidence in the literature for good correlation of translation efficiency as determined by ribosome profiling and protein synthesis, the reviewer raised a valid concern. Ribosome pausing or even ribosome stalling could also cause increased ribosome binding and thereby increased amounts of ribosome footprints. Therefore, we analyzed ribosome pausing in selected genes including psbA and rbcL. The pattern of ribosome pausing was very similar in low and high light (new Supplemental Figure 14), which rules out any ribosome stalling at specific sites or drastic changes in ribosome pausing. To analyze if there is increased ribosome pausing, we determined the fraction of footprints at pause sites compared to the total number of footprints. We used two different pause scores as cutoffs to determine pause sites. To include as many pausing events as possible, we used a pause score of 1, i.e. everything higher than the mean ribosome density per nucleotide of the corresponding coding region (Gawronski et al., 2018). This fraction was unaltered in low and high light (new Supplemental Figure 14). With a more stringent pause score of 20 (20 times higher ribosome density than the mean), an increase of ribsome pausing in high light was detected for psbA, whereas we did not find differences between high and low light for rbcL and psaA. However, this increase in pausing at the psbA mRNA is insufficient to explain the increase in the total amounts of ribosome footprints. Additional pause scores were tested, the value for the psbA fraction with a pause score of 20 included in Supplemental Figure S14 showed the largest difference.

Reviewer #2: \*Strongly suggested additions to the manuscript to improve its significance before publication** 1)Identifying the RNA-binding protein(s) (likey HCF173 which may be in a complex with other proteins) that interacts with the 5' UTR of psbA in a highlight dependent manner would increase the significance of this study. Finding that this protein binds to other plastid transcripts with weak Shine-Delgarno sequences would also be a nice addition to this study.*

See comment to reviewer 1. McDermott et al. (2019) describe HCF173 as relatively specific for psbA. Therefore, we do not assume that other genes with weak Shine-Dalgarno sequences are regulated via HCF173 but via different proteins using a similar molecular mechanism to influence the mRNA secondary structure at the translation initiation region.

Reviewer #2: \*Strongly suggested additions to the manuscript to improve its significance before publication** 2)Mutational analysis of the RBP binding site and also to change the secondary structure around the start codon based on the new structure maps to show the effects of these various changes on protein output would really provide important new findings on how important the RBP being as compared to the RNA secondary structure changes are for regulating protein output form psbA. It could also allow the demonstration of the dependence or independence of these two features on regulating translation from chloroplast mRNAs.*

We agree with the reviewer that this would be a very interesting study. Unfortunately, it requires a larger collection of lines with mutated psbA sequences. Plastid transformation in Arabidopsis thaliana is still technically demanding and time consuming. Even in the case of Nicotiana tabacum, for which plastid transformation is well established, such a project would likely need several years. We therefore think that such a study is beyond the scope of the current manuscript.

Reviewer #3 1.In this paper, author mentioned that DMS can modify four nucleotides under alkaline conditions. Because the chloroplast is slightly alkaline, the authors use DMS reactivity from 4 nucleotides to model RNA secondary structure. Based on Kevin Weeks' s paper, it shows that in cell-free condition, DMS has very limited ability to modify single-stranded G and U compared to A and C (Anthony M. Mustoe et al., 2019, PNAS 116: 24574. fig. 1B). In Lars B. Scharff' paper which is cited by the author, it is also mentioned that A and C is more reliable to model RNA secondary structure. The authors might need to calculate the correlation the DMS data and known RNA structure using G/U or all four nucleotides to show that DMS reactivity from G and U is also reliable to be used. Also in Fig. S3B, the reproducibility of G/U between replicates is not as good as A/C. I don' t think G and U can be used to predict RSS.

We agree with the reviewer that DMS reactivities at G/U are less reliable than those at A/C. This was shown by Mustoe et al. (2019) and by us for chloroplast rRNAs (Gawronski et al., 2020, Plants). We included a correlation of the known 16S rRNA secondary structure and the DMS reactivities at the different nucleotides (Supplemental Figure S5A) that demonstrates that the DMS reactivities at G/U actually contain information about rRNA secondary structure. This analysis demonstrated again that the reactivities at G/U are less reliable than at A/C. Therefore, we added an analysis of the more reliable A/C for comparison with the results for all four nucleotides (Figure 1D-F, 3C-F).

Reviewer #3 2.Is the 5'UTR the only region which has RSS change? If not, how do RSS changes in other region contribute to translation?

Translation initiation in plastids is mainly influenced by the secondary structure of the translation initiation region, especially at the cis-elements required for the recognition of the start codon. In addition, we have analyzed different other regions, e.g. the coding regions, the coding regions without the sequences next to the start codon, the end of the coding region, and the complete 5’ UTR (Supplemental Figure S14). We added a more detailed analysis of the changes of secondary structure of the coding region of those genes we focus on (Supplemental Figure S16). This shows that the secondary structure changes of the complete coding region correlate negatively with translation efficiency (see also Supplemental Figure S14G). A similar observation was made in E. coli and explained to be caused by differences in translation initiation, which are mainly influenced by the secondary structure of the translation initiation region (Mustoe et al., 2018).

Reviewer #3 3.In Fig. 2A and 2B, the DMS reactivities seem very similar under low light and high light. Why did the authors obtain significantly different RNA secondary structure? Are the parameter of low light and high light the same when modelling RNA structure?

The parameters for the RNA secondary structure predictions in Figure 2 are not identical (see Figure legend). For all structure predictions, the DMS reactivities were used as constrains, but only for the high light structure the sequence of the RNA binding protein’s footprint was forced to be single-stranded. These structure predictions are included to illustrate the mRNA structures in the presence and absence of an RNA binding protein. These structures are based on the observation that the two halves of the stem loop structure have different DMS reactivities in response to high light. The sequence including the protein footprint has lower DMS reactivities in both low and high light. This is in agreement with both a double-stranded sequence as well as a protein-bound sequence. In contrast, the other half of the stem loop, the sequence including the cis-elements of the translation initiation region, has increased DMS reactivities in high light, indicating that it is single-stranded. This suggests that there is protein binding in high light preventing the formation of the inhibitory stem loop.

Reviewer #3 4.In Fig. S12, the correlationship between HL and LL in ribo-seq and RNAseq is high, which means no significant changes upon light change. In this paper, psbA should have translation change under high light conditions. I suggest the authors to label the dot representing psbA.

Thank you very much for this suggestion! We marked psbA in the correlation plots (Supplemental Figure 12). The changes in the transcript levels are really minor, whereas for some genes the translation efficiency changes (see Figure 4 and Supplemental Figure S13).

Reviewer #3 5.I suggest to use plants at the same stage for DMS-MaPseq and SHAPE probing.

The different plant material was chosen because of the different requirements during probing. In this context, we would like to point out that observing the same changes in the translation initiation region in response to high light in different developmental stages is a stronger confirmation than observing the same response at the same developmental stage. This indicates that the response is not specific for a developmental stage.

Reviewer #3 6.In Huang's paper (Jianyan Huang et al., 2019, Cell Reports 29: 4186-4199), there are many differential express genes under high light for 0.5hr. However, in the RNAseq data here, the correlation between high light and low light conditions is very high (Fig. S12). Why? Also, it would be nice if the authors could label several DEG whose expression change under high light treatment in Fig. S12?

Supplemental Figure S12 contains only plastid-encoded RNAs, whereas Huang et al. (2019) focused on nuclear-encoded mRNAs. We clarified the figure legend of Supplemental Figure S12 by adding “of the plastid-encoded genes”. The values for the individual genes can be seen in Supplemental Figure S13.

Reviewer #3 7.For the MNase footprint method, is the as-SD region the only region show enrichment under high light conditions? Besides, please provide the detailed method of MNase footprint. Does it work for RNA footprinting?

The used methods are described under “Ribosome profiling (Ribo-seq)” and “Processing of Ribo-seq and RNA-seq reads” in Material and Methods. The approach was very similar to the one used for ribosome profiling with the difference that also smaller read lengths were included in the analysis (18-40 nt instead of 28-40 nt). We did this, because many plastid RNA binding proteins have footprints that are smaller than a ribosomal footprint. The described footprint is the only one detected near the translation initiation region of psbA. Binding of HCF173 was detected by the Barkan group in the same region using a RIP-Seq Analysis combined with RNase I digestion (McDermott et al., 2019), which confirms that our approach is working. We added a reference to the method section in the results part to clarify which approach was chosen.

Reviewer #1

Thank you for inviting me to review this manuscript by Paquola and colleagues, in which the authors used a combination of high-resolution anatomical data, machine learning, spectral DCM and resting functional connectivity measures to interrogate the relationship between structural and functional gradients of organization within the mesial temporal lobe.

The study is broken into four related sections. In the first section, the authors analysed vertices within a set of mesial temporal lobe structures using a random-forest algorithm, which identified a set of microstructural profiles across the structure. They then interrogated these profiles for evidence of an iso-to-allometric axis, which is a principle known to characterise the transition from 6-layered isocortex (in entorhinal cortex) to 3-layer allocortex (in the hippocampal formation). The authors found evidence consistent with this transition in the BigBrain data, particularly with respect to the skewness of the distribution of thickness across the layers.

In the second section, the authors use Spectral DCM on resting state data from a group of 40 individuals. They then relate the results of the spectral DCM model to the gradients identified using structural anatomy. This section was well-motivated and conducted.

In the third section, the authors compare the structural gradient to resting state functional connectivity with vertices within the cerebral cortex. The results here were quite compelling, showing a dissociation between the iso- and allo-cortical poles in the MTL in which the iso-cortex was correlated with fluctuations in the lateral dorsal attention and frontoparietal networks, whereas the allo-cortical pole was correlated with vertices in the default mode and medial occipital regions.

In the final section, the authors conducted a number of checks of their analysis, including an SNR test to ensure that the temporal lobes (a notorious site for MRI signal dropout) were adequate, and a substantial replication analysis. They should be commended for these steps, and also for making their code freely available.

Comments:

1) Section 1: I wonder whether the manuscript might benefit from the unpacking of the random forest results. Is there an intuitive way to characterize skewness that may benefit the reader - such as a particularly uneven spread of thickness distributed across the layers? And is this finding something that we might expect, given the hypothesized gradient of iso-to-allocortex in the MTL?

2) Section 1: Along these lines, is it fair to single out an individual measure from the random-forest regression as being the most salient? From my understanding (which might be mistaken), the weights on a particular variable in a regression need to be viewed in context of the performance of the whole model.

3) Section 2: One minor comment is that it might be helpful for the reader if the "in" and "out" effective connectivity directions were incorporated into the matrix in Figure 2A.

4) Section 2: I wasn't sure that I followed the logic of the experiment in which the authors split the MTL data into thirds to test for the consistency of their results. Were each of these sufficiently powered to allow for direct comparison with the main effect? Did the boundaries between these models cut across known regional areas? Perhaps a different way to achieve the same ends would be to use bootstrapping in order to provide a confidence interval around the relationship between structure and function?

5) Section 3: Did the authors hypothesize the iso vs. allo-cortical relationship to resting state networks a priori, or was it discovered upon exploration of the data. Either is fine, in my opinion, but I think it would benefit the reader to have these results placed in the context of the known literature.

6) Section 3: Do the authors expect that the patterns identified in the MTL will relate to subcortical gradients identified in other structures, such as the cerebellum (Guell et al., 2018), thalamus (Müller et al., 2020, and basal ganglia (Stanley et al., 2019)? See also Tian et al., 2020 for general subcortical gradients.

Reviewer #2:

General Assessment:

The role of visual experience with faces in the formation of face-specific neural "modules" is tested in a deep convolutional neural network model of object recognition, AlexNet. A modified version of the ILSVRC-2012 training dataset was constructed by removing all images with primate faces, removing remaining categories with fewer than 640 images, and re-training the deprived network: d-Alexnet. d-Alexnet was compared to pre-trained Alexnet on classification performance, quality of fit to fMRI data, strength of face-selectivity, representational similarity, and learned receptive field properties. The authors argue that face-selectivity is significantly reduced, but not eliminated, with the deprivation, and that this reduction is consistent with an interpretation that d-Alexnet represents faces more similarly to objects than Alexnet. While this work is well-motivated and timely, there are substantial issues in the conceptual approach, the methods used, clarity of the results, and most importantly, the strength of the conclusions.

Major Concerns:

1) The validity of these results is uncertain due to a) insufficient reproducibility within this work and b) fragile definitions of face-selectivity.

a) Given that small changes in weight initialization or training procedure can have a large effect on learned representations (see Mehrer et al. 2020, https://www.biorxiv.org/content/10.1101/2020.01.08.898288v1.abstract ), the authors must demonstrate that their results hold across multiple initializations of each network type. Several key results hinge on the number and identity of "face-selective" channels (Figure 2, 3c-e) and only a single instance of each model type is used. In particular, the result that 2/256 channels are "selective" in d-Alexnet compared to 4/256 in Alexnet is likely sensitive to small variations in the methods, including the choice of evaluation stimuli and the initialization of the weights. If the models were re-trained, could the ratio be 4 channels to 4 channels, 0 channels to 2 channels, or some other result? With only a single instance of each model and such a small (and potentially unstable) number of face-selective channels in each model, I am not convinced that these results support the claims made.

SUGGESTION: Report results averaged across multiple initializations of each model to demonstrate robustness. Statistical tests should be conducted across models (as if they were individual subjects) to demonstrate the significance of any effects found.

b) The definition of "selectivity" is potentially fragile and may not hold when tested with more standard evaluation sets. In the primate face-selectivity literature, functional localizers are used to compare face responses to non-face responses. These localizers have much stronger controls over low-level features than the stimuli used to evaluate selectivity in this work. I am especially concerned that the faces (from FITW) differ from non-face objects (from Caltech-256) in low-level properties such as image resolution, pose, background, contrast, luminance, and more. Furthermore, selectivity is typically defined in the field as a continuous quantity (e.g., t-contrast, d-prime, face-selectivity-index) and is not often assessed in a binary fashion by the number of units significantly more responsive to faces than the second-best category. Many of these continuous metrics also incorporate variance in responses as well as the mean of responses. Thus, the designation of channels as "selective" or "not-selective" in this work based on mean responses to only 2 of the 205 categories (L101) prevents the reader from understanding how the distribution of face-selectivity shifted under the deprivation, which is one of the primary claims. Instead, we only see the number of selective channels after a binary cutoff, which may be sensitive to initialize and the stimulus set used to evaluate selectivity.

SUGGESTION: Compute selectivity using evaluation sets in which faces are better matched to non-face objects. Report the distribution of selectivity for each channel before and after deprivation.

2) Because one model in the comparison is pre-trained and the other is trained from scratch, there is the possibility that all of the differences between the models are due to differences in the training that are independent from the content of the training images.

a) In the regression analysis, is it the case that non-selective channels also show differences in R2? For example, if the d-Alexnet is worse on the training task (d-ImageNet) than Alexnet, we expect a general reduction in its ability to explain neural responses (see e.g. Yamins et al., 2014). The claims that face-selectivity is specifically impaired in d-Alexnet need to be supported by demonstration that non-selective channels are equally good (or poor) fits to vertices in face-selective regions. Furthermore, the authors do not demonstrate that face-selective channels are better than non-selective channels in either model type, which is useful context for understanding whether the correspondence between face-selective channels and face-selective brain regions is meaningful.

SUGGESTION: report non-selective channel fits to the same vertices for each model type and compare to face-selective channel fits.

b) L366: the authors write that "the d-Alexnet was initialized with values drawn from a uniform distribution". This is not standard practice; in fact, the kernel weights in the original AlexNet model were initialized from a Gaussian distribution. To make comparisons to the non-deprived model, the authors need to also retrain the non-deprived model to account for the potential confounds between their training/initialization procedure and that used in the pre-training.

SUGGESTION: re-train the non-deprived AlexNet in-house, then compare that model to d-AlexNet.

1. A major conceptual issue is in the definition of a "face module". Despite "face module" in the title, a working definition of "face module" is not clearly provided in the manuscript. Context clues suggest that the authors may consider any face-specific process evidence of a "face module", but the experiments performed indicate that a specific set of criteria were explored: selectivity for faces, different representations for faces and non-face objects, holistic processing, etc. Especially given that the results of this work indicate some residual face-selectivity, a clear definition of "face module" - grounded in the existing literature - is needed to evaluate the claims provided.

SUGGESTION: clearly define what the "face module" is in the brain, then explain what the corresponding evidence for a "face module" would be in the DCNN.

4) A number of analyses are not well-motivated or are lacking in detail

a) The analysis of the "empirical receptive field" is lacking in detail and motivation, and the color-scale is both nonlinear and missing a label. Specific questions:

i) How should this result be compared to data in primate face-selective regions?

ii) Is this result a trivial consequence of the difference in number of activated units (panel D)?

iii) What are the units of the colormap?

iv) Why are only two channels shown for AlexNet if 4 channels are face-selective?

v) Is the extent of the empirical receptive field quantified?

vi) How should the reader think about empirical receptive fields in a weight-shared convolutional architecture?

b) The evaluation of the face-inversion test is poorly motivated. The face-inversion effect indicates that human subjects are better at remembering upright faces than inverted faces. However, the analysis performed here evaluates the magnitude of the response of face-selective channels. If anything, a classification task is needed to compare to the human task, because the "face inversion effect" cited is not simply that face-selective units respond more strongly to upright than inverted faces, but that the activation of the units supports differences in classification between upright and inverted faces.

SUGGESTION: At minimum, justify 1) why the magnitude of channel response is a good measure of the face inversion effect or 2) remove the claim that the models do/don't exhibit the behavioral effect.

Nancy Kanwisher (Reviewer #1):

Xu et al use deep nets to ask whether face selectivity, and face discrimination performance, can arise in a network that has never seen faces. By painstakingly removing all faces from the training set, and comparing Alexnet trained with and without faces, they claim to find, first, that the face-deprived network does not have deficits in face categorization or discrimination (relative to the same network trained with faces), second that the face-deprived network showed some face-selectivity, and third that face deprivation reduced face selectivity. They conclude that "domain-specificity may evolve from non-specific experience without genetic predisposition, and is further fine-tuned by domain-specific experience."

I love the question and the general strategy behind this study, and indeed we have long discussed doing something much like this in my lab, and we presented a preliminary result of this kind at VSS years ago (https://jov.arvojournals.org/article.aspx?articleid=2433862 ). It is a great use of deep nets to ask what kinds of structures can in principle arise with different kinds of training diets. Xu et al are also to be congratulated for the huge effort they went to in curating a data set of stimuli with no faces, for which they are correct no current algorithm is adequate, requiring a huge amount of labor-intensive human effort.

Nonetheless, despite my might enthusiasm for the question, the general logic of the study, and the major effort to create the training set, I do have a few significant concerns about the paper:

1) The biggest problem in the paper in my view is that although regular Alexnet saw faces in the training set, it was not trained on face discrimination, and its performance on this task is very low (66%). That is above chance but very much lower than a network that is actually trained on face discrimination. In our studies, which are typical of this literature, we find that when Alexnet is trained on the VGG-Face dataset identification of novel faces is around 85% correct (top-1). So to say that the face-deprived network performed no differently from the face-experienced network on a face discrimination task, while true, is misleading, because really this reflects the fact that neither was trained on face discrimination and both do pretty badly. And perhaps more importantly, for faces humans have learned, their typical face recognition accuracy would be way higher than 66% correct. So, the face-deprived network really does very badly compared to a real face-trained network, or to humans, and does not represent a strong case of preserved face discrimination despite lack of face experience. Instead, it reflects the kind of face recognition performance one would expect from an object recognition system or a prosopagnosic patient: above chance but not very accurate. Thus, I think the behavioral data show not preservation of face perception abilities in a network trained without faces, but low performance at face discrimination, much like a network that has seen faces but not been trained to discriminate them.

2) The claim that "face-selective channels already emerged in the d-AlexNet" is similarly overstated in my view, given that only two such units were found and the selectivity of the one we are shown (on the right in Figure 2a) is weak. Although the authors concede that the selectivity of these two units is lower than found in Alexnet trained with faces, that understates the case, as Figure 2a shows. The analysis in Figure 2b, correlating responses of face-selective channels from Alexnet to natural movies, with brain responses to the same movies, is interesting but doesn't tell us what we most need to know. Several public data sets include the magnitude of response of FFA and OFA to a set of 50-100 images, and I would find it more useful to compare those to the response of Alexnet face units to the same images.

A small point: Only human and primate faces were removed from the dataset, but I would think other animal faces (e.g. cats and dogs) should produce some relevant training. Certainly face-selective regions in the human brain respond strongly to animal faces, as several studies have shown. This might be worth considering in the discussion when potential reasons for the emergence of face-selective channels are discussed (line 229-236).

For the reasons above, I don't think the results of this study strongly support the conclusion that "the visual experience of faces was not necessary for an intelligent system to develop a face-selective module". At least the "face-specific module" so claimed is a far cry from the human face processing system in both neurally measured selectivity and behavioral performance.

Typically, we live life and abuse these "worldy things" given to us and we think we like to think we have everything we need but what I think Edwards is saying here is that yes we may be happy and think everything is going great but If you don't have a relationship with God, those worldly things are not going to save you. God is our gateway to heaven and if He takes his hand away, nothing is stopping us from going to hell. Edwards is basically saying if you are not living you're life for God as a christian, God will not give you his hand

The term "born again" is used a lot, both in the bible and in sermons and songs even to this day. To be born again in Christ is to have a new life driven by Him and moving past all the sins of your "old life." Considering how long ago this sermon was given, does anyone think that it may have had a different meaning at that point in time? If so, how has it matured into what we interpret it as today?

Jonathan Edwards is preaching to his congregation in a very vivid manner how they need to reflected on their lives and ways of living. He is trying to explain to them that giving yourself to God is the only way into salvation. Jonathan Edwards explains that if you are not born again and repent for your sins you will be going to hell. He explains that God's forgiveness of sins is the only reason they are not in hell at this moment. He explained that turning to God now and not later needs to be done before it is to late.

This is such a strong statement towards the congregation. Through this passage, the congregation could probably get a glimpse and feel it in their bones of the regret and eternal despair one might have to endure for eternity if they don't wake up from their slumbers and live a righteous life as God commands. Even the last sentence of those that have already been damned who would long for even a short moment and opportunity that the current people that are alive are currently enjoying really plants in fear of hell. Yet he goes on how many people still would be judged to hell.

While I agree with the overall message, the actual delivery is much different than what we would encounter today. In today's society, we are encouraged to be politically correct and avoid offending others; sometimes, that is not the most effective. When matters are sugar-coated, there is room for people to find some margin to justify their wrong-doings. For example, how many times after you've done something wrong, i.e., frivolously spent money, told a small lie, etc. and later found yourself trying to justify it? Edwards is leaving little room for justification and explicitly details what will happen if people do not live by God's Word. Though fear was the prevailing tactic, the goal was to have as many conversions to Christianity as possible in a time where many were desensitized to the church and beginning to lean on their own understanding. A majority of the congregation was in tears during the sermon; this can be counted as a victory for Edwards. Their reactions show that members felt convicted, which in turn, may compel them to form or strengthen their relationship with God so that they may have salvation.

Author Response

We would like to thank the three reviewers for their efforts and the constructive feedback. Below, we describe how we will address the reviewers’ comments in an updated manuscript.

Summary:

All of the reviewers expressed concerns about the advance that the work described in the paper represents. These issues were a focus of the consultation among the reviewers. The main concern is that the work needs to go beyond demonstrating that some ganglion cells exhibit nonlinear integration for naturalistic inputs - as that point is quite well established in the literature. The comparison between natural stimuli and gratings could help in this regard, but several issues confound that comparison (e.g. differences in dynamics of the two types of stimuli). These concerns are detailed in the individual reviews below.

Reviewer #1:

This paper investigates how retinal ganglion cells integrate inputs across space, with a focus on natural images. Nonlinear spatial integration is a well-studied property of ganglion cells, but it has been largely characterized using grating stimuli. A few studies have extended this to look at spatial integration in the context of natural images, but we certainly lack a comprehensive treatment of that issue. The current paper has a number of strengths - notably using a number of complementary stimuli and analysis tools to study a large population of ganglion cells and linking properties of responses to artificial stimuli with those to natural stimuli. It also has a few weaknesses (some detailed carefully in the paper) - such as the inability to identify ganglion cell types (aside from a few), and to pinpoint specific circuit mechanisms. These are limitations of the techniques used. This is not a request as much as setting the context of the contribution of the paper. Generally the paper was in good shape, and the data supported the conclusions well. I do think there are a number of issues that could be strengthened. Those are listed below in rough order of importance.

Statistical correlations in natural scenes:

A number of analyses in the paper rely on estimating the spatial contrast from an image and comparing the dependence of various measures of the cells' responses on spatial contrast. A danger in this analysis is that spatial contrast is likely correlated with many other statistical properties of the image, so attributing a given response property to spatial contrast has some potential confounds. This issue should be discussed as a possible caveat, unless the authors can rule it out. The paper, accurately, describes the results in terms of correlations (and not causal relationships), but some discussion of the complexity of natural image statistics would be helpful.

Spatial contrast is defined in our work via the variance of pixel intensity inside the receptive field. Indeed, spatial contrast may reflect different aspects of visual scenes, such as object boundaries, textures, or gradients in light intensity. Differences in the effects of these image features on a ganglion cell’s response will not be captured by our analysis. However, the goal of relating spatial contrast to spike count was primarily to analyze whether the spatial structure of light intensity inside the receptive field was related to the response of a given ganglion cell (beyond the mean illumination), and the pixel intensity variance provides a simple, straightforward measure of this spatial structure. To clarify this aspect and better relate it to the complexity of natural images, we will add a corresponding paragraph in the Discussion.

Comparison of grating and natural scene spatial scale:

The section starting around line 233 was confusing for several reasons. First, this section starts by measuring the spatial scale associated with the grating responses, and then comparing that to LN model performance for natural inputs. It's not clear why the spatial scale is the relevant aspect of the responses to gratings. Indeed, the next paragraph provides a measure of the relative sensitivity of the nonlinear and linear response components (via a comparison of F1 and F2 responses). It would be helpful to include some initial text to motivate the different measures of the grating responses and to anticipate that you will look at both spatial scale and sensitivity.

A related issue that bears more directly on the scientific conclusions comes up later in the blurring experiments. The issue is whether it is valid to directly compare the apparent spatial scale of nonlinear responses to images (estimated via blurring) with that of the grating responses. Natural images should have much higher power at low spatial frequencies, and this may strongly impact the spatial scale identified with the blurring experiments.

We agree that the writing may not have been entirely clear, and we will reorganize the material to discuss the extracted spatial scale and nonlinearity index in parallel as suggested. Regarding the difference in spatial scales from reversing gratings and blurred natural images: yes, it is also our interpretation that the power at low spatial frequencies plays a key role. Our main point here was to assess whether and to what degree the typical analyses of spatial nonlinearity as measured from reversing gratings translate to natural images despite the differences in spatial and temporal structure of the two stimulus classes. In a revised manuscript, we will make sure to earlier clarify the role of low spatial frequencies.

Clustering of orientation-selective cells:

An interesting suggestion in the paper is that the orientation-selective cells can be divided into two groups that differ in their spatial integration properties. Do these groups represent different orientations, as suggested in the text? That seems a simple piece of information to add. Related to this, I would suggest moving Figure S4 into the main text.

We do not have information about the absolute preferred orientations of the orientation-selective (OS) cells, as we did not keep track of retinal orientation when placing the retinas on the multielectrode array. At this point, we can therefore only rely on indirect analyses of relative preferred orientations between pairs of OS cells in the same retina. These indicate that pairs of two nonlinear OS cells tend to have aligned preferred orientation (and similarly for pairs of linear OFF OS cells), but pairs of a linear and a nonlinear OFF cell tend to have divergent preferred orientations. This is shown in Fig. S4C. For a revised manuscript, we will consider integrating Fig. S4 into the main text, as suggested.

Presentation of checkerboard stimuli and results:

The checkerboard analysis, particularly how it isolates properties of spatial integration, could get introduced more thoroughly for a reader unfamiliar with it. A related issue is how well the chosen isoresponse contour captures structure in the full distribution of responses. In some cases that looks pretty good, but in others it is less clear. Could you add a supplementary figure or something similar that characterizes how consistent the isoresponse contours are for different response levels?

These are good suggestions, and we will aim at clarifying the analysis as proposed and add information about the consistency of iso-response contours for different response levels. In the present analysis, the iso-response contours are used just for illustration, whereas the quantification of rectification and integration of preferred contrast are extracted from specific points in the stimulus-response space, which we found to work robustly for a population analysis without being strongly effected by threshold or saturation effects of the cells. We will explain this more clearly in a revised manuscript.

Drift in responses over time:

Some of the rasters - e.g. the bottom left in Figure 1C - show considerable drift over time. It is important that this drift not be interpreted as a failure of the LN model and hence indicative of nonlinear spatial integration. Can you test for drift like this across cells, and exclude any that seem potentially problematic? More generally, some assurance that the variability in the responses for a given generator signal value is real variability across images is needed.

The presentation of all 300 natural images over ten trials takes about 50 minutes and some drift over this period seems unavoidable. To minimize systematic effects of experimental drift on the measured average responses for different images, we applied randomization within trials, which assured that all images were presented once in random order in each trial before the next trial started. In addition, to quantify the real variability over images of the average response for a given generator signal, we applied a goodness-of-fit measure (CCnorm) that takes into account variability over trials.

We now also tested directly for the drift mentioned by the reviewer, but observed sizeable effects in only a small subset of cells that were included in the analysis. In most cases, drift corresponded to a global scaling that approximately affected responses to all images proportionally. This is reflected in a high correlation over images between the average responses of the first five and last five trials; 94% of analyzed cells had a correlation coefficient of at least 0.7. Such global scaling of responses does not affect the analysis of differences in average responses. In a revised manuscript, we will provide analyses of drift effects and exclude cells that contain drift effects that appear to deviate from global response scaling.

Reviewer #2:

Summary:

Understanding how retinal ganglion cells respond to natural stimuli is a central but daunting question, which retinal neurophysiologists have begun to tackle recently. Here Karamanlis and Gollisch perform large-scale multi-electrode recordings in the mouse retina and demonstrate that the responses of many ganglion cells cannot be predicted by standard linear-nonlinear models (L-LN). They go on to test a variety of clever artificial stimuli that emphasize and allow for the quantification of the non-linear aspects of RGCs responses and convincingly demonstrate that non-linear processing is associated with sensitivity to fine spatial contrasts (subunits) and local rectification. While these aspects of RGC receptive fields have been previously described, demonstrating their applicability to natural vision is a significant advancement.

Major Comments:

My first main concern is with the way the paper is written. It does not highlight the significant advancements but rather emphasizes what is already known from other studies. For example, many of the conclusions of non-linear spatial integration & signal rectification arising in bipolar cells have been well described previously. By contrast, novel aspects like the sensitivity of reversal gratings being unrelated to LN model performance for natural scenes should be explained more in detail. The authors should more clearly state the major advancements that are being made here beyond what has already been shown previously (e.g. Turner and Rieke, 2016)

It is possible that our efforts to provide context by relating our results to established findings in retinal signal integration overshadowed the novel aspects of our work. As suggested, we will aim at pointing out these aspects more clearly. For example, compared to the work of Turner and Rieke (2016), we a) focused on a different species with more diversity in accessible RGC types, b) generalized the connection of spatial integration and natural scene encoding to a wider range of cell types (e.g. including also spatially linear and nonlinear ON-OFF cells as well as cells that are inversely sensitive to spatial contrast), and c) developed methods to assess and quantitatively characterize subunit nonlinearities with multielectrode recordings of many cells in parallel, without the need for intracellular recordings or knowledge of the receptive field location.

Second, the authors never include non-linear subunits in their model to demonstrate improved performance. Testing models with filters that incorporate rectification and convexity as experimentally determined will enable them to show their utility more convincingly. Without this, the reader is left with the conclusion that there are RGCs that exhibit non-linear or linear spatial integration (already known) and that non-linear integrators cause LN models to perform poorly with natural images (Turner and Rieke, 2016).

The aim of the present work was to assess how well models with linear receptive fields account for responses to natural images in various cells of the mouse retina and whether the models’ shortcomings can be related to the cells’ spatial stimulus integration characteristics. While we agree that models with nonlinear subunits could help support the conclusions, fitting such models to recorded data is – we believe – beyond the scope of the current manuscript. The many parameters of nonlinear subunit models, such as the number, shape, and layout of subunits or their nonlinearity and weight, all likely vary considerably across the diverse population of cells in our recordings. To avoid extensive parameter fitting, simplified models with ad hoc selection of subunit layouts and nonlinearities could help assess whether spatial nonlinearities are important, as in the work by Turner and Rieke (2016). Instead, as an alternative, we chose to analyze the importance of spatial nonlinearities via the effect of spatial contrast in images with similar mean intensity in the receptive field (e.g. Fig. 2). For our data, an advantage of this approach is that it is directly applicable to cell types with diverse spatial integration characteristics, such as the cells that are inversely sensitive to spatial contrast, which wouldn’t be captured by a standard subunit model with rectifying subunit nonlinearities. In future work, however, we plan to analyze subunit models that can account for the diversity of observed response patterns.

Third, I'm not sure how 'natural' their natural images are, given static images are flashed over the cell intermittently. While such stimuli might simulate some sort of saccadic eye movements, whether this is relevant for mouse vision is not clear. Would linear models be more predictive for responses to natural movies? Some discussion on this issue would be helpful.

Rather than aiming for fully natural movie-like stimuli, we used flashed images in our work to focus on aspects of spatial integration. This indeed entails a simplification of the temporal structure of natural stimuli, which was intended, but it preserves natural spatial structure, such as the occurrence of objects, boundaries, textures, and intensity gradients, as well as continuously decreasing power for higher spatial frequencies. Nonlinear spatial integration in the presence of this natural spatial structure will likely also shape responses under natural movies. To clarify this approach, we will re-evaluate our wording regarding the application of natural stimuli in our work and discuss the simplification compared to natural movies, as suggested.

Reviewer #3:

The manuscript by Karamanlis and Gollisch examines the responses of mouse retinal ganglion cells (RGCs) to natural stimuli. The primary conclusion of the manuscript is that spatial integration of stimuli within the receptive field is nonlinear. This nonlinear integration is consistent with "local signal rectification". This results in a set of RGCs that are sensitive to spatial contrast within the RF. The Authors also note the presence of cells that are suppressed by contrast and cells that prefer uniform stimulation of the RF. To reach these conclusions the authors use multi-electrode array recordings from isolated mouse retina. Spatial RFs are estimated using white noise stimuli, which are then used to generate a null-model for linear spatial summation. They compare predictions of this null-model to the responses of the same RGCs to briefly flashed natural images. The authors find some RGCs that are consistent with this null model and many that are not consistent. The authors correlate deviations from linear spatial summation to deviations revealed by contrast reversing gratings. They also used a mixed-contrast, flashed-checkerboard paradigm to map the contrast tuning and rectification of RF subunits. Finally, the authors show that some of these results track with functionally distinct RGC types such as direction-selective and "IRS" RGCs.

The data and analyses presented in this manuscript are high quality. However, I think the study is largely consistent with many previous studies that demonstrate nonlinear spatial integration among RGCs in the mammalian (including mouse) retina. I think the Authors view the use of natural stimuli as a major departure from previous work, but I'm not convinced of this for two reasons. First, I don't see a compelling reason to think that results using contrast reversing gratings or other 'textured stimuli' (e.g. Schwartz et al Nat Neuro 2012) would fail to generalize to flashed natural scenes. Second, the implicit claim here is that a 200ms flashed natural scene interleaved with an 800ms gray screen is a natural stimulus. I think this assumes a lot about the space-time separability of the RF mechanisms, and these assumptions are not well justified.

Major Concerns:

1) I think the introduction of the manuscript is building a straw man argument, suggesting that many (or most) scientists think the retina is predominantly linear. A pubmed search of 'retinal ganglion cell' and 'nonlinear' produced more than 300 studies. Specifying subunit nonlinearity produces 28 studies. The discovery of subunit nonlinearities is roughly 50 years old and many manuscripts demonstrate Y-like receptive fields are more common across RGC types than X-like receptive fields.

The goal of our work was not to show that receptive fields of mouse retinal ganglion cell are (often) spatially nonlinear, but to test whether these nonlinearities matter for natural images. It is conceivable that spatial nonlinearities as measured with typical artificial stimuli such as spatial gratings or spatiotemporal white noise are not (as) relevant for natural images because the simultaneous occurrence of strong positive and negative contrast inside a receptive field is much rarer in natural images. Indeed, in our work we find that traditional measurements of spatial nonlinearities with reversing gratings do not provide a robust quantitative prediction of whether spatial nonlinearities matter under natural images for a given ganglion cell. As laid out in the Introduction, there is surprisingly little research yet on how spatial nonlinearities affect the encoding of natural images, and in a revised version of the manuscript, we will aim at clarifying that this is the focus of our work here.

2) The authors seem to be arguing that the spatial nonlinearities engaged by the contrast reversing gratings are not the same as those engaged by their natural scenes (Figure 3). However, I think the authors are assuming too much that the spatial and temporal components of the RFs are separable. The flashed natural scenes are interleaved with relatively long gray screens. The contrast reverse granting are reversed in a square-wave fashion with no interleaved gray screen. These distinct spatiotemporal dynamics in the stimuli seem likely to explain the difference. This would also seem likely to explain why the flashed checkerboards in Figure 4 produced results more correlated to flashed scenes in Figure 1. In summary, I don't see a strong reason to think the authors are observing anything other than subunit rectification of the sort described by Hochstein and Shapley in the 1970s and followed up in many subsequent studies.

We do not think that spatial nonlinearities as observed with reversing gratings or with natural stimuli are related to different mechanisms. The point of our analysis was rather to assess whether typical assessments of spatial nonlinearities with reversing gratings allow quantitative predictions about the relevance of spatial nonlinearities under flashed natural images, and we find that this is often not the case. We believe that this is largely due to the differences in spatial structure, in particular, the prevalence of high-contrast edges in the gratings. Yet, indeed, differences in temporal stimulus structure might also contribute. We actually tested flash-like presentations of gratings in some of our recordings, and results were quite similar to those obtained with contrast-reversing gratings and led to the same conclusions. We will describe this in the revised manuscript for clarification.

3) It is not clear to this reviewer that flashed natural images interleaved by a gray screen is qualitative more natural than white noise, sinusoidal gratings, or square-wave gratings.

The spatial structure of natural images is the focus of the present work. It is in this aspect that flashed photographs are more natural than typical artificial stimuli like spatiotemporal white noise or gratings. In particular, natural images contain a broad spectrum of spatial frequencies with relatively more power at smaller frequencies, and they combine occasional edges with intensity gradients and textures. Gratings, for example, are characterized by high power at large spatial frequencies, that is, high spatial contrast, which is well suited for triggering effects of spatial nonlinearities but occurs much more rarely in natural images. Thus, understanding whether spatial nonlinearities are important in a natural setting requires considering stimuli that match the natural spatial structure. It seems likely that nonlinear spatial integration observed under flashed presentation of natural images remains relevant when stimuli are supplemented with natural temporal structure, even though the latter may likely trigger additional effects that shape the responses (e.g. adaptation or nonlinear temporal integration).

4) The null-model constructed by the authors in Figure 1 assumes the RF follows a specific functional form (e.g. Gaussian). However, many studies show that individual RFs frequently exhibit strong deviations from a Gaussian RF. To what extent are the deviations from the null model produced by deviations from linear summation or just linear mechanisms that deviate from the specific parametric form imposed by the model?

Measuring the detailed structure of receptive fields (RFs) with high precision from time-limited experiments is a challenge, and using a fitted (elliptical) Gaussian profile is a standard procedure for limiting the effect of noise in the RF structure. We also tried using the pixel-wise spatial profile obtained from the reverse-correlation analysis as a spatial filter, but results were similar, yet often more noisy. We therefore settled on the standard procedure of using a Gaussian fit to the RF. Deviations from the Gaussian profile can indeed contribute to deviations of the model. Yet, for natural images, which have most of their power in low spatial frequencies, these deviations are likely to be small. Furthermore, our subsequent analyses show that the Gaussian RF model provides a useful baseline because it allows us to extract the relation between model deviations and image structure. In addition, the results from the model analysis were supported by the findings under presentation of blurred natural images, which did not require any assumptions about the underlying RF model. In a revised manuscript, we will point out that relying on Gaussian RFs is a choice that we make and that deviations of the receptive field structure may contribute to decreased model performance, but that the subsequent analyses support the usefulness of the applied Gaussian RF model.

5) It was unclear how the authors rule out the contribution of differences in (nonlinear) temporal integration to the effects in this study. In general, RGC RFs are not space-time separable, and it seems that the analyses in the manuscript assume they are.

Our choice of using flashed images as stimuli with no temporal structure beyond onset and offset and assessing responses via elicited spike counts was motivated by focusing on spatial stimulus integration and minimizing effects of temporal processing. Nonetheless, our extraction of receptive fields from measurements under spatiotemporal white-noise stimulation uses a space-time separation of the spike-triggered average. Thus, the lack of space-time separability of ganglion cell receptive fields can contribute to the putative underestimation of surround components, which we have discussed in the manuscript. In a revised manuscript, we will add an explicit reference to the issue of space-time separability.

6) This study overlaps significantly with Cao, Merwine and Grzywacs (2011), 'Dependence of retinal Ganglion cell's responses on local textures of natural scenes', Journal of Vision. This article is not cited here, but in my view, the major conclusions are similar.

Thank you for pointing us to this paper, which is indeed relevant for our work. Both the Cao et al. paper and our manuscript evaluate the effect of spatial contrast in natural images by relating spatial contrast to response deviations from a linear-RF model, albeit with different methods. An important difference, apart from the different species, is that our work then focuses on relating the identified effects of spatial contrast to functional characterizations of the specific nonlinear operations inside the receptive field (e.g. rectification). Furthermore, we also focus on the diversity of spatial-integration properties between cells and cell types, including the description of spatially linear cells and cells that are inversely sensitive to spatial contrast. In a revised manuscript, we will add a comparison to the methods and results from Cao et al.

7) In my experience, the strength of subunit rectification can be labile during ex vivo experiments. What controls have the author's performed to ensure the effect they are studying remain stable over the duration of their recordings?

Experimental rundown could, of course, affect subunit rectification as well as other response aspects, such as overall sensitivity. However, we observed that responses for different repeats of the same natural images were typically quite stable over the course of the hour-long stimulus. As also discussed in the response to Reviewer 1, we now analyzed how responses to late trials deviated from responses to early trials and found that only a small subset of cells displayed sizeable drift. Furthermore, those cases were mostly affected by a global drift in response size, keeping the relative responses for different images approximately constant. (For 94% of cells, the correlation of images was larger than 0.7 between average responses for the first five and for the last five trials; approximately on the level of estimated random trial-by-trial variability.) This indicates that the features of stimulus integration did not change substantially over the course of the experiment. In addition, nonlinearities as assessed with our flashed checkerboards were strongly correlated to nonlinearities under natural images, despite the fact that these stimuli were applied 1-2 hours apart. Thus, the strength of subunit rectification appears to be sufficiently stable to allow comparison over different stimuli.

Reviewer #1:

This paper investigates how retinal ganglion cells integrate inputs across space, with a focus on natural images. Nonlinear spatial integration is a well-studied property of ganglion cells, but it has been largely characterized using grating stimuli. A few studies have extended this to look at spatial integration in the context of natural images, but we certainly lack a comprehensive treatment of that issue. The current paper has a number of strengths - notably using a number of complementary stimuli and analysis tools to study a large population of ganglion cells and linking properties of responses to artificial stimuli with those to natural stimuli. It also has a few weaknesses (some detailed carefully in the paper) - such as the inability to identify ganglion cell types (aside from a few), and to pinpoint specific circuit mechanisms. These are limitations of the techniques used. This is not a request as much as setting the context of the contribution of the paper. Generally the paper was in good shape, and the data supported the conclusions well. I do think there are a number of issues that could be strengthened. Those are listed below in rough order of importance.

Statistical correlations in natural scenes:

A number of analyses in the paper rely on estimating the spatial contrast from an image and comparing the dependence of various measures of the cells' responses on spatial contrast. A danger in this analysis is that spatial contrast is likely correlated with many other statistical properties of the image, so attributing a given response property to spatial contrast has some potential confounds. This issue should be discussed as a possible caveat, unless the authors can rule it out. The paper, accurately, describes the results in terms of correlations (and not causal relationships), but some discussion of the complexity of natural image statistics would be helpful.

Comparison of grating and natural scene spatial scale:

The section starting around line 233 was confusing for several reasons. First, this section starts by measuring the spatial scale associated with the grating responses, and then comparing that to LN model performance for natural inputs. It's not clear why the spatial scale is the relevant aspect of the responses to gratings. Indeed, the next paragraph provides a measure of the relative sensitivity of the nonlinear and linear response components (via a comparison of F1 and F2 responses). It would be helpful to include some initial text to motivate the different measures of the grating responses and to anticipate that you will look at both spatial scale and sensitivity. A related issue that bears more directly on the scientific conclusions comes up later in the blurring experiments. The issue is whether it is valid to directly compare the apparent spatial scale of nonlinear responses to images (estimated via blurring) with that of the grating responses. Natural images should have much higher power at low spatial frequencies, and this may strongly impact the spatial scale identified with the blurring experiments.

Clustering of orientation-selective cells:

An interesting suggestion in the paper is that the orientation-selective cells can be divided into two groups that differ in their spatial integration properties. Do these groups represent different orientations, as suggested in the text? That seems a simple piece of information to add. Related to this, I would suggest moving Figure S4 into the main text.

Presentation of checkerboard stimuli and results:

The checkerboard analysis, particularly how it isolates properties of spatial integration, could get introduced more thoroughly for a reader unfamiliar with it. A related issue is how well the chosen isoresponse contour captures structure in the full distribution of responses. In some cases that looks pretty good, but in others it is less clear. Could you add a supplementary figure or something similar that characterizes how consistent the isoresponse contours are for different response levels?

Drift in responses over time:

Some of the rasters - e.g. the bottom left in Figure 1C - show considerable drift over time. It is important that this drift not be interpreted as a failure of the LN model and hence indicative of nonlinear spatial integration. Can you test for drift like this across cells, and exclude any that seem potentially problematic? More generally, some assurance that the variability in the responses for a given generator signal value is real variability across images is needed.

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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Molenaars et al., describe a protocol to extract and quantify a wide range of polar and apolar metabolites from the same C. elegans sample using methanol-chloroform based phase separation. The authors assess the method across different input amounts, in comparison to a 1-phase extraction method and through metabolic perturbations using RNAi against several metabolic enzymes. Finally, they provide a metabolomics analysis of metabolite variation across several C. elegans strains. The data are of overall high quality and presented in a clearly written manuscript.

We really appreciate the positive words from the reviewer.

To help assessing the value of the method to other approaches, several controls are suggested below:

1.Fig.1: Metabolite abundance in the polar phase should be compared to 1-phase extraction methods (analogous to Fig. 2I, which compares metabolites in the apolar phase to 1-phase extraction)

We acknowledge the apparent asymmetry in the text; comparing our two-phase method to a single phase lipidomics method indeed suggests a similar comparison for metabolomics. However, our established polar metabolomics method has always been based on this exact two-phase extraction. The current method exclusively asks whether it is possible to integrate our dedicated lipidomics platform into our established two-phase polar metabolomics method, by utilizing the apolar phase that is usually discarded. This way, the method enables comprehensive metabolomics/lipidomics screening while limiting the need of culturing twice the amount of material.

Our manuscript does not necessarily ask the more fundamental question of the advantages of a one-phase vs two-phase extraction for polar metabolites. Interestingly, the one-phase vs two-phase metabolomics methods have been compared previously and the authors show here that the two-phase method achieved broader metabolite coverage, satisfactory extraction reproducibility, acceptable recovery and safety (DOI: 10.1038/srep38885). This is most probably due to the cHILIC column being sensitive for contamination and therefore excluding lipids from your samples is beneficial for measuring polar metabolites. We hence believe that developing a single phase polar method would appear superfluous for the purpose of this study.

2.Are polar metabolites also detected in the apolar phase? Can the less hydrophobic lipids missing from the apolar phase detected in the polar phase?

This is an interesting question that mostly relates to the lyso-lipids that are not detected in the lipid phase of our two-phase extraction. The first point to make is that sample solvents that are used at the final stage of extraction are not compatible between methods. In other words, the solvent we normally use for the lipids phase (xxx) cannot be injected on the cHILIC column. So, in a practical sense, we would not be able to measure these compounds, even if they would technically be dissolved in the other layer. However, we tried a few different alternative approaches to get more information on this point:

We have attempted to integrate the lyso-lipids in the cHILIC measurements, in the polar layer, using the polar sample solvents. This was unsuccessful; no reproducible peaks, not even the internal standards, were measured. We will include a note on these results in our manuscript. We have, albeit for a different sample matrix, attempted to dissolve both layers of the two-phase extraction in the cHILIC sample solvents. While we cannot guarantee this for all metabolites, it appears that most polar metabolites are exclusively found in the polar layer. We were not able to integrate even a single peak from any of the sugar, amino acids, nucleotides, etc in the apolar layer dissolved in polar solvents. We have reconstituted both the polar and apolar layer of our two-phase extraction in 50:50 methanol:chloroform and analyzed them on the lipidomics platform. We did find some of the lipid internal standards partition to the polar phase, especially LPG (and to a lesser extent LPE and LPA) compared to for instance PE, SM, PG and PC that all end up in the apolar phase. We will include these data in the revised manuscript as a supplemental figure as it demonstrates that the lyso-lipids are poorly measured in the two-phase extraction. This is also why in the text we advise to use the dedicated one-phase extraction when interested primarily in these species.

3.Fig.3l-n: The authors claim that extracting metabolites from the polar and apolar phases of the same sample leads to better cross-correlation than if metabolites are extracted from different samples using methods optimized for the respective metabolite classes. To provide experimental evidence, metabolite abundance should be compared directly when metabolites are extracted from the same or from different samples using suitable methods.

We agree with this point. We will amend the text to not overstate these advantages.

Reviewer #1 (Significance (Required)):

The methodological and conceptual advancement of the present study is rather incremental. The authors essentially use the classical chloroform/methanol/water phase separation protocols developed by Bligh & Dyer and Folch, which have been used extensively for lipid extraction for many decades now. However, the effort to carefully measure the metabolites contained in the aqueous phase is laudable. For method validation, the authors use well-understood perturbations that yield predictable results. Overall, I consider the study more appropriate for a publication as a methods protocol, which could be of interest to the metabolomics community, rather than as a research paper.

We agree; our goal was indeed to create and share a method, we will make sure to emphasize this in our cover letter.

While the extraction method we use is not novel per se and based on classical extraction procedures, it is important to underscore that we are only now able to use these extractions in combination with high-resolution mass spectrometry. This opens new opportunities for basic discovery. The efficiency we achieve by using both phases of the two-phase procedure makes our method highly attractive for hypothesis generation, especially in sample sets where limited amounts of material are available.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The authors provide a detailed description of a method to analyse both polar as well as lipophilic metabolites from the same nematode sample. This provides significant advantages over methods using individual samples. Moreover and by using internal standards they establish an extremely good correlation of individual metabolites. This paper is of immediate importance for the worms community and beyond.

We are very grateful to receive this positive response from the reviewer and for highlighting the advantages of our described method also beyond the worm community.

**Major comments:**

none **Minor comments:**

The correction process using internal standards could be described a bit more detailed.

In our revised manuscript, we will describe the internal standard use and corrections in more detail in the text. In summary: internal standards are selected for specific metabolites based on their Pearson correlation and %CV. Subsequently, metabolite peak areas were divided by the area of the appropriate internal standard. This corrects for any loss of sample during sample prep, for instance during the isolation of the two layers.

Jenni Watts has written a nice Worm Book chapter on lipids which may be cited in addition to reference 17, since it covers many of the metabolites and related enzymes contained in this manuscript

We will include a reference to this Worm book chapter reviewing fat regulation in C. elegans in our paper, thank you for the suggestion.

Reviewer #2 (Significance (Required)):

see above

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

The manuscript is well written and consider. However, there is room for further improvements:

We thank the reviewer for the positive response and for the suggestions raised.

1) Author need to write exactly how many metabolites not just >, semi-quantitative analysis of >100 polar (metabolomics) and >1000 apolar (lipidomics) metabolites in C. elegans, for example they did with other papers in Table 1

We understand that this might appear vague. The notation was a compromise, based on the following considerations:

1. The maximum number of reported metabolites can be different to the number of analyzed metabolites in a specific experiment or even a specific sample. For instance, our method is perfectly capable of measuring creatine metabolism –we have standards for these metabolites and they can be reliably measured–, however we have not yet been able to detect these metabolites in elegans. Some mutants also lose abundance of a certain metabolite to the point of it not being reliably measurable, which means they are filtered out in the bioinformatics.
2. Since the initial draft of our manuscript we have been able, and will continue to be able, to add new metabolites to our analysis, as we perform a full scan over the range of m/z 50-1200. Because of this, we felt it more accurate to state that we can measure >100 metabolites, instead of a specific number.

   2) Authors also need to clarify on number of samples in the result section while describing the statistical analysis.

We understand this point raised by the reviewer and will specify not only the number of samples, but also that they are indeed biological replicates. This will be included in the figure legends.

Reviewer #3 (Significance (Required)):

This might be interesting paper for the research community who work with C.elegans (metabolism or in general)

Thank you, we are in fact utilizing this double extraction for other non-worm samples such as mice an human tissues and we believe this could also benefit the research community beyond the model organism C. elegans.

The authors must deposit the raw data and make it available for the public, so they could also benefit from this good work.

It is our full intention to share our data in a convenient and standardized way through for instance the MetaboLights database (https://www.ebi.ac.uk/metabolights/). We agree and changes will be implemented as suggested.

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

**Summary:** The authors present a method for extraction of both lipid and polar metabolites from the model organism C. elegans. This extraction method is based on the well-established Blyth and Dyer method, with a slight modification to retain and utilize both the organic and non-polar fractions for LCMS analysis. They applied and tested this method against a monophasic extraction utilizing the same solvent system. They report that there is a loss of metabolites in the non-polar fraction to the polar fraction (of more polar metabolites) and small differences between the monophasic and biphasic extractions. They also expanded on the linearity of the extraction efficiency by increasing the number of worms. Further they applied the single extraction method to both knockdown mutants of C. elegans and Recombinant Inbred Lines derived from N2 and the natural isolate CB4856 to determine whether this method would still be able to differentiate the metabolome between the genetically different C. elegans populations.

We thank the reviewer for their comments and suggestions.

**Major comments:**

*Are the key conclusions convincing?*

As a whole the conclusions are convincing and valid.

We appreciate that the reviewer considers our work convincing and valid.

*Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?*

The use of the adjective "robust" is, to an extent, erroneous. As defined, a robust method implies that the method is capable of withstanding small (deliberate or not) changes or variations. In this case the robustness of the method was not assessed and not clear how replication was carried out.

We have in fact performed analysis on both biological replicates and repeated injections of pooled samples to determine robustness. We will clarify the biological replicates in the text and will place the pooled QC samples in the main text with additional explanation and relevant statistics such as % coefficient of variance (%CV) between them. For clarity, we plotted %CV of all polar as well as apolar metabolites. For polar metabolites 97% of the metabolites had a %CV lower than 30. For apolar metabolites 86% of the metabolites had a %CV lower than 30.

*Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.*

Reproducibility would need to be assessed/quantified to establish how robust the method is. Even though linearity with an increase in the number of worms is a good indication, it does not satisfactorily establish the robustness of the method. The use of replicates to assess the agreement between measurements (i.e. bland-Altman plots), linearity as well as coefficients of variation (included in the sup material but not clear in the body of the manuscript) would characterize the methods best. The isolation of each variance originating from instrumental (pooled quality controls), biological (biological replication) and sample preparation (multiple extractions from the same biological source) is critical.

We have these data and will elaborate on this in our revised manuscript. We will discuss the quality control samples more prominently in the main body of the manuscript, and show one or more figures that specifically address both analytical and biological variance (see rebuttal figure 2). In summary, we assessed this variance using (a) a repeated injection of a pooled QC sample, and (b) biological replicates prepared individually. Especially the latter condition, in which we assess biological variance is representative for the actual method application. The %CV under these conditions is ≤20% for the majority of metabolites, which is why we consider our method robust.

*Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.*

The suggested experiments are in-fact just further analysis with the already collected data. There would be no need for further experiments, however it is not clear whether pooled QCs/or reference materials were used and the number of replicates per experimental design.

All the data are available. These analyses will be included in the revision.

*Are the data and the methods presented in such a way that they can be reproduced?*

The methods are very well described. My only comment is to address how the replicates were grown/created and how many per strain/group. If the replicate measurements were done on the same samples (repeated injections), I believe that would weaken the findings (if not invalidate them altogether), however if these were biological replicates from independent starting populations the findings are valid and convincing.

We performed bona fide biological replicates. We will explicitly mention this in the paper together with the other descriptions of our validation protocols.

*Are the experiments adequately replicated and statistical analysis adequate?*

As per my above comments.

**Minor comments:**

*Specific experimental issues that are easily addressable.*

It is not clear how the sample preparation process was carried out (randomization, run order, QCs etc). As per the guidelines widely accepted from –Broadhurst, D., Goodacre, R., Reinke, S.N. et al. Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies. Metabolomics 14, 72 (2018). https://doi.org/10.1007/s11306-018-1367-3.

We will provide details on the analysis itself in a table. In summary: Samples were measured in a random order, with blanks and QC samples throughout the run.

*Are prior studies referenced appropriately?*

A major reference that has applied this extraction method before in the same model organism is missing:

Castro, C., Sar, F., Shaw, W.R. et al. A metabolomic strategy defines the regulation of lipid content and global metabolism by Δ9 desaturases in Caenorhabditis elegans. BMC Genomics 13, 36 (2012). https://doi.org/10.1186/1471-2164-13-36

We will include this paper in our references. We would like to note though that this method requires not just an LC system to analyze lipids, but also GC with additional derivatization steps. Our method achieves comprehensive lipidomics using a single technique and no additional derivatization.

Further a recent publication that goes beyond the work described by the authors using similar approach: MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses. Ernesto S. Nakayasu, Carrie D. Nicora, Amy C. Sims, Kristin E. Burnum-Johnson, Young-Mo Kim, Jennifer E. Kyle, Melissa M. Matzke, Anil K. Shukla, Rosalie K. Chu, Athena A. Schepmoes, Jon M. Jacobs, Ralph S. Baric, Bobbie-Jo Webb-Robertson, Richard D. Smith, Thomas O. Metz mSystems May 2016, 1 (3) e00043-16; DOI: 10.1128/mSystems.00043-16

We will also include this paper, reporting 51 polar metabolites and 84 lipid species, in our references. While we recognize that they also make use of both phases and the protein pellet, we think our method is much more practical in several key ways:

Our metabolomics platform provides twice as many species and our lipids platform exceeds their analytical capabilities 10 fold. This means a far better coverage of differences within metabolite and lipid classes, allowing for far more intricate patterns to be detected. We show this for instance in our plots comparing carbon chain length to degree of saturation (Fig 4 and S2 in original manuscript); a comparison that is only possible with the data density that our method offers. The MPLEx metabolomics method also requires the use of a GC system and derivatization steps, while our method does not, making it much more user friendly and requiring only a single analytical system.

*Are the text and figures clear and accurate?*

Yes *Do you have suggestions that would help the authors improve the presentation of their data and conclusions? *

The figures, overall are of exceptional quality.

As per current scientific consensus, Box plots should also be overlaid with the actual datapoints (which was aptly done for the bar charts and other plots).

The supplementary data even though comprehensive is hard to understand. A "readme" file detailing what data each file contains would improve readability and comply with FAIR principles.

We agree that a readme file would make the supplemental data more understandable. We will provide such a file. For the box plots we will show the actual data points in our revised manuscript.

Reviewer #4 (Significance (Required)):

Even though the approach is not novel and has long been used in Natural Products Chemistry and in other organisms, it's highly significant to set an extraction method standard for the field of C. elegans metabolomics (including myself doing metabolomics and natural products chemistry with LCMS and NMR). However, this manuscript does not cover the technical aspects of the method with sufficient depth to hallmark this method as the standard for the field. Further information is needed to fill the missing gaps (as highlighted by the authors). Ratios between solvent and biological material amounts, reproducibility, recovery rates (even though buried in the supplementary files) and metabolite coverage are still missing.

As a side note, the disparity between the monophasic and biphasic extractions could be overcome by a sequential extraction of the same sample, with no incurred cost on performance (and removing the much-dreaded pipetting uncertainty near the line between solvents). The second aspect of the manuscript, which initially was a welcoming idea (and important), became >50% of the manuscript creating a disconnect between the information set by the abstract and introduction and the results/conclusion. The work is extremely relevant in both sections of the manuscript, but the technical aspect is still lacking details and/or analysis.

Strongly suggested: explicit compliance with the minimum reporting standards as per the Metabolomics Standards Initiative (MSI) and deposition of the data to a metabolomics repository (i.e. Metabolights or Metabolomics Workbench). These are internationally accepted requirements for metabolomics publications.

We are aware that the extraction itself is an analytical chemistry staple. However, it is precisely in this fact that we find novelty. It should be noted that both of the other papers mentioned by the reviewers that have attempted to integrate lipidomics and metabolomics have had to resort to labor intensive (as well as possibly expensive and destructive) derivatization steps and a separate analysis on GC. Our method does not have these requirements. It is indeed a single and very common extraction, after which each dried phase is reconstituted and immediately injected. But this simplicity is not a concession, as our metabolome coverage is easily more comprehensive than the other mentioned methods. We therefore feel that this simplicity should not discount our currently presented method, but be considered an additional advantage.

Sequential extractions may be an option to consider. However, we feel like they are less user friendly and unneeded. Because we use internal standards, it is never an issue to pipet slightly more or less of any particular sample; making it easy to avoid the line between solvents.

We will explicitly clarify where we already comply with the standards (such as the analysis of biological replicates and repeated injection of a QC sample) and are confident we can add figures and further information such as deposition of our data to comply with the rest.

REFEREES CROSS-COMMENTING

Completely agree with reviewer #1 comments, they are on point and I completely missed it. Relevant and should be addressed.

Reviewers #2 points out work worth acknowledging, the internal standard work was quite thorough and well designed.

Reviewer #3 and my comments overlap nicely, the need for further description of samples/replication and deposition of data in a metabolomics repository.

Further work is required to make this a good publication and standard for the field, without this extra work addressing the reviewers comments I feel this work could be to certain degree misleading and/or incomplete putting in cause its publication potential.

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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

We thank the reviewers for their feedback and encouragement. We have now fully revised the manuscript to address all comments. Our specific responses are provided below and we have highlighted changes in the text. The major additions are:

• analysis of simulated time-courses with lower temporal resolution
• analysis of ex vivo PER2::LUCIFERASE SCN recordings
• analysis of simulated time-courses with Poisson distributions of noise
• plotted summary statistics for several figures
• mathematical formula and explanation in the Methods Overall, these revisions have strengthened our findings and improved the manuscript, particularly in demonstrating that the issues with the chi-square periodogram are not specific to sampling interval or data type.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

**Summary:**

Tackenberg & Hughey investigate the reliability of a popular period estimation algorithm, the chi-square periodogram. They find a bias in the estimation, and through careful investigation identify the cause. This is a well executed and well presented study.

**Comments:**

In Figs 2+3 the authors show that the discontinuity in periodogram coincides with the number of complete cycles, K. However, in Fig 2C there are several other positions where K abruptly changes, but little effect on the chi-squared statistic is observed. Can the authors offer an explanation as to why the magnitude of the discontinuities differ?

We have taken a closer look at how each component of the chi-square statistic calculation changes at points where K decreases, and have found that discontinuities do always occur at these points. In addition to the obvious effect of the K * N term on the sudden decreases, we found that the sum of squares of the column means alone (the primary component of the numerator) also changes abruptly at each transition point of K. As a result, the discontinuity magnitude is likely roughly proportional to the amplitude of the chi-square statistic at that point.

An important claim is that the discontinuity is observed in multiple software implementations. However, the plots of Supplementary Fig 1C,D are presented too small to evaluate this claim.

In Supplemental Fig. 1C-D, the critical information is the shape of the periodogram and the presence of a discontinuity, so we believe the plot sizes are appropriate.

It may be of interest to apply the algorithms to a single-cell experimental data set which are qualitatively different (e.g., oscillation shape, damping).

We have created a new supplemental figure (Supplemental Fig. 8) by applying the strategy and visualization used in Fig. 6 to SCN PER2::LUC recordings instead of wheel-running data, and have updated the text accordingly.

Reviewer #1 (Significance (Required)):

It has been previously shown that the chi-square periodogram algorithm has performance shortcomings for the analysis of circadian data (e.g. Zielinski et al., 2004). However, this study demonstrates exactly why, giving more conclusive evidence to support the conclusion that it should be avoided. This will be useful to many in the mammalian circadian community. It should be noted however that other algorithms are already favoured by other ciock communities (e.g. plant), even if a rigorous understanding of the biases were lacking.

The methods developed here will be valuable for future comparisons of circadian algorithms. Of particular importance will be comparing algorithms for analysis of single-cell rhythms or non-stationary rhythms.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Chi-squared periodograms (CSP) are routinely used in circadian biology. In particular, this test has been used to determine circadian period in behavioral data (e.g. actigraphy) in mammals, flies and other species. This paper suggests that CSP, in some circumstances (e.g. where there are discontinuities), that CSP could be improved by changing the algorithm. They propose different steps to do this (e.g. using their greedy CSP code) and/or by using alternative tests such as Lomb-Scargle.

The authors use simulated data to demonstrate their findings, and whilst I can see the benefits of this, it would be useful to benchmark the algorithms on actual real world circadian data (e.g. actograms from mouse or fly experiments). Although these types of data may not be publicly available, it would be highly likely to be available from multiple labs in the circadian field. In particular, fly datasets will be abundant in many clock labs. This would aid the utility of the papers findings for the field.

Fig. 6 is entirely based on real-world circadian data (mouse wheel-running activity), as is the newly added Supplemental Fig. 8.

Reviewer #2 (Significance (Required)):

The paper is helpful for the circadian field when dealing with datasets that may contain discontinuities.

It appears that the paper will be primarily useful for behavioral data, rather than, for example, transcriptomic time courses, since these tend to be much shorter and less sample intensive. Thus, it would be useful for circadian (and other) researchers analysing activity data in particular.

My expertise is in circadian rhythms, both behavioural and molecular (e.g. sequencing) level analyses. Thus, I would be a possible end-user for the algorithms in this paper.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

**Summary:**

The authors identify a serious flaw in a popular method called Chi-squared periodogram (CSP) for period estimation in circadian rhythms. They systematically get to the source of the problem -- a discontinuity in the test statistic. This flaw leads to a bias in the period estimate. They present two modifications to the CSP, one of which they prefer. Nevertheless, they show that other more flexible methods such as Lomb-Scargle Periodogram work well without this discontinuity (bias) issue.

**Major Comments:**

1.One thing the authors do not include is timeseries lengths of non-integer days. Would it not be an interesting suggestion to choose a non-integer length time course, which is not a multiple of the periods of interest, and still continue using CSP as is ? This is also rather counter-intuitive.

Figs. 3A and 6 and newly added Supplemental Fig. 8 use non-integer (24-h) days.

2.I suppose the authors use a sampling resolution of 6min with wheel-running activity in mind. But it would be worth it in the interest of completeness to also consider a lower resolution. There is nothing in this study that ties it to the specific application, is it not?

Although a sampling resolution of 6 minutes is not specific to wheel-running activity, we have added an analysis identical to that of Fig. 5 but with a resolution of 20 minutes (Supplemental Fig. 5). Additionally, the PER2::LUC SCN recordings analyzed in Supplemental Fig. 8 have a sampling resolution of 20 minutes.

3.The authors discuss only the mean absolute error in the text but isn't the direction (sign) of the error also of interest. As far as I can see in Fig 5, conservative CSP overestimates and greedy CSP generally underestimates periods.

We discuss both the error (references to Fig. 5A) and absolute error (references to Fig. 5B) in the text. We feel the interpretation suggested by the reviewer may be too reliant on the results of 3-day simulations, as the apparent underestimation by greedy appears far less substantial in simulations of 6 and 12 days.

**Minor Comments:**

1.I would like to see the formulae for the ratio of variances and p-values to be clear about how the authors computed the CSP. They describe it in words already, but I think some mathematics is warranted here.

We have added the formula for the standard chi-square periodogram to the Methods section.

2.It is nice to the see the raw data in the plots. But I would like to see the plot of the summary statistics (mean and variance/st. dev) for each of scatter plots to judge the size of bias. It is not easy to do this with the Excel sheet.

We have overlaid a black circle representing the median and a vertical black line representing the 5th-95th percentile range onto Fig. 5 and Supplemental Figs. 3-7.

Reviewer #3 (Significance (Required)):

The authors present a sobering perspective on the chi-squared periodogram, which is still very popular among empirical biologists. They plainly show using artificial data that it is better to avoid the CSP when possible, although they suggest improvements to the CSP. The authors provide an R package to perform the analysis.

There have been previous work that have highlighted other limitations of the CSP. This might be considered one more nail in the coffin of the CSP.

I think this paper would be interest to both computational biologists and wet-lab biologists, but I think it ought to have a greater influence on the latter as the former already resort to more sophisticated approaches.

My expertise is in Computational and Theoretical biology.

Perhaps change "file" to "disk" as suggested by fat16.h. This part was very confusing.

Also, there was no mentioning in the instructions that the root directory entries may not be exactly located as described in the picture, so perhaps change "78*512" to something like "depending on bpb".

I'm not sure if these choices were intended to make sure that we carefully looked at the code documentations instead of just the instructions, but I think these parts should be adjusted so that other students aren't confused.