Reviewer #1 (Public Review):

Summary: The paper by McGinnis et al. uses a combination of genetic and biochemical approaches to understand how the conserved 5'-3' RNA exonuclease Xrn1 affects autophagy in response to methionine starvation in S. cerevisiae. The authors present evidence Xrn1 affects autophagy primarily via its effect on regulating TORC1 signaling. They present some evidence that Xrn1's effect on TORC1 singnaling is via its physical interaction with the SEACIT complex.

Strengths: The experiments in general for this paper are clear and have proper controls.

Weaknesses:<br /> The authors seem to try and fit the data to a simplistic model rather than embrace the complexity of the data. I will give some examples below.

1) Figure 1 clearly shows that xrn1d results in loss of tight repression of autophagy. Specifically, the 0 timepoint has increased autophagy in both the idh-GFP and ALP assays. However, it is incorrect to say that it is related in any way to methionine deprivation. The same basic pattern of regulation occurs in WT and xrn1d strains. The only difference is the "leakiness" of repression at t=0.

2) Figure 2 shows that catalytically inactive Xrn1 has the same autophagy phenotype as a deletion, indicating that Xrn1 enzymatic activity is important for function. However, it is also clear that xrn1-deletion cells expressing wt Xm1-flag do not repress autophagy as well as XRN+ cells, even though the amount of expressed protein seems similar. Does this imply the flag-tag may be a less active version of the protein? This should be discussed.

3) Figure 3 shows Xrn1-loss effects TORC signaling and that npr2-deletion inhibits autophagy. The surprising result is that a xrn1d/npr2d behaves like WT with regards to autophagy. This needs to be discussed. To me, this seems to strongly suggest that methionine repression of autophagy is occurring downstream of both xrn1 and npr2. Measuring p-S6 in the double mutant may be informative.

4) Figure 4 appears to show that even in the absence of GTR1, autophagy is repressed in rich media, active in YPL-SL, but still responds to methionine repression. This does not seem consistent with the model presented in Figure 5. Shouldn't loss of GTR1 result in repressed Torc1? The GTP and GDP-lock mutants are either all on, or all off. Why is deletion different? This needs to be explained and discussed. Also, the Figure legend does not match figures (problem after Fig4b).

5) Figure 5B shows GTR1 IP with Xrn1-FLAG. However, there are no negative controls in this experiment, so the result could be background. RNAaseA and RNA addition experiments are convincing.

6) Line 254-255. The lead sentence is simply not supported by the data. There is no evidence that Xrn1 actually affects the regulation of Gtr1/2 binding states.

7) Line 259-260. This is again overstated. Just because a mutant can be rescued by Gtr1-GTP-locked, does not say anything about RNA decay. In fact, the double mutant has extra high levels of some ATG RNA's, so I have no idea how the Gtr1 rescues.

8) Line 268-281. Your model here ignores the fact that methionine regulation takes place in the absence of both xrn1 and npr2. Therefore the model, as proposed, can't be correct.

9) Line 290-300. The slow growth rate of Xrn1 mutants may be affecting the metabolite levels. I felt that this entire paragraph was overly speculative.

This is, like THE foundational keystone document to the problem I'm trying to communicate for "builds and burdens".

Author Response

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

Public Reviews:

Reviewer #1 (Public Review):

Anderson, Henikoff, Ahmad et al. performed a series of genomics assays to study Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high-quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila. Some new analyses and a few new experiments are suggested here, which hopefully further take advantage of these data sets and make some results more conclusive.

Major comments: 1. The step-wise accumulation of H3K4me2 in bam, aly and wt testes are interesting. Is it possible to analyse the cis-acting sequences of different groups of genes with distinct H3K4me2 features, in order to examine whether there is any shared motif(s), suggesting common trans-factors that potentially set up the chromatin state for activating gene expression in a sequential manner?

While the histone H3K4me2 mark is low and more widespread at genes active in late spermatocytes and in spermatids (shown in Figure 2C and some examples in Figure 1C-D), we suggest that this may be due to a general decrease in the importance of this modification in late spermatogenesis rather than a specific feature of those genes. We point this out in lines 146-152. This idea is supported by the widespread change in RNAPII distribution in all genes in the germline, shown in Figure 3F and supplementary Figure 2.

1. Pg. 4, line 141-142: "we cannot measure H3K4me2 modification at the bam promoter in bam mutant testes or at the aly promoter in aly mutant testes", what are the allelic features of the bam mutant and aly mutant? Are the molecular features of these mutations preventing the detection of H3K4me2 at the endogenous genes' promoters? Also, the references cited (Chen et al., 2011) and (Laktionov et al., 2018) are not the original research papers where these two mutants were characterized.

We have corrected these citations to the original papers. We clarified in the text that the bamΔ86 allele is a deletion of almost all of the coding sequence (reported in Bopp, D., Horabin, J.I., Lersch, R.A., Cline, T.W., Schedl, P. (1993). Expression of the Sex-lethal gene is controlled at multiple levels during Drosophila oogenesis. Development 118(3): 797--812.). The aly1 allele is also a P element-induced mutation; it is not molecularly characterized (it was first described here: Lin, T.Y., Viswanathan, S., Wood, C., Wilson, P.G., Wolf, N., Fuller, M.T. (1996). Coordinate developmental control of the meiotic cell cycle and spermatid differentiation in Drosophila males. Development 122(4): 1331--1341.) We noticed a lack of reads for various histone modifications in aly mutants in part of the gene, suggesting that the deletion is limited to the promoter and the first exon. Signal for the H3K4me2 modification is at background levels for the distal portion of aly, suggesting that the deletion inactivates the gene.

1. The original paper that reported the Pc-GFP line and its localization is: Chromosoma 108, 83 (1999).

We are citing the first published description of this marker in the male germline (lines 291-293).

The Pc-GFP is ubiquitously expressed and almost present in all cell types. In Figure 6B, there is no Pc-GFP signals in bam and aly mutant cells.

We apologize, our labeling of the figure was easily overlooked - the bam and aly genotypes do not carry the PcGFP marker, since we didn’t need it for staging the germline nuclei. We have clarified this in the figure.

According to the Method "one testis was dissected", does it mean that only one testis was prepared for immunostaining and imaging? If so, definitely more samples should be used for a more confident conclusion.

We corrected the text to make it clear that all cytological examinations were repeated at least times (lines 438-439).

Also, why use 3rd instar larval testes instead of adult testes?

Generally, we find that immunostaining of the larval testes is cleaner, and we now mention this in the Methods (lines 439-440). We have immunostained both larval and adult testes for these markers with consistent results.

Finally, it is better to compare fixed tissue and live tissue, as the Pc-GFP signal could be lost during fixation and washing steps. Please refer to the above paper [Chromosoma 108, 83 (1999)] for Pc-GFP in spermatogonial cells and Development 138, 2441-2450 (2011) for Pc-GFP localization in aly mutant.

We are using PcGFP staining for staging with antibody detection of other chromatin features, which requires fixed material, although we have compared PcGFP signal in both live and fixed tissue. We have added the 1999 reference for nuclear staging in the male germline.

1. Ubiquitinylation of histone H2A is typically associated with gene silencing, here it has been hypothesized that ubH2A contributes to the activation of Y chromosome. This conclusion is strenuous, as it entirely depends on correlative results.

We agree that this is a correlation. We cite in the text examples where uH2A is associated with gene activation. We have added a comment to clarify that this is a correlation (lines 318-320), and now present an alternative that uH2A on the Y chromosome may be moderating expression from these highly active genes (lines 405-407).

For example, the lack of co-localization of ubH2A immunostaining and Pc-GFP are not convincing evidence that ubH2A is not resulting from PRC1 dRing activity. It would be a lot stronger conclusion by using genetic tools to show this. For example, if dRing is knocked down (using RNAi driven by a late-stage germline driver such as bam-Gal4) or mutated in spermatocytes (using mitotic clonal analysis), would they detect changes of ubH2A levels?

We have tested multiple constructs to knockdown dRING using the bam-GAL4 driver although we have not reported it in the manuscript. These knockdowns have no effect on uH2A staining in the testis, on motile sperm production, or on male fertility, although these RNAi constructs do produce Polycomb phenotypes when expressed in somatic cells from an en-GAL4 driver. This is the reason why we point out in the text that there are multiple alternative candidates for an H2A ubiquitin ligase in the Drosophila genome and that in other species RING1 is not responsible for sex body uH2A in the male germline (lines 394-396).

1. Regarding "X chromosome of males is thought to be upregulated in early germline cells", it has been shown that male-biased genes are deprived on the X chromosome [Science 299:697-700 (2003); Genome Biol 5:R40 (2004); Nature 450:238-241 (2007)], so are the differentiation genes of spermatogenesis [Cell Research 20:763-783 (2010)]. It would be informative to discuss the X chromatin features identified in this work with these previous findings.

We now mention that the Drosophila X chromosome is moderately depleted of male germline-expressed genes (lines 362-363).

For example, the lack of RNAPII on X chromosome in spermatocytes could be due to a few differentiation genes expressed in spermatocytes located on the X chromosome.

We show in Figure 3B that there is a minor non-significant reduction in RNAPII on the X chromosome in spermatocytes. This small reduction might be due to the moderate paucity of male germline-expressed genes on this chromosome, but since it is non-significant we have not discussed it.

Reviewer #2 (Public Review):

Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in Drosophila. The results are new and the experiments and analyses look well done, including with appropriate numbers of replicates. Results were parsed by comparing them among two arrest mutants and wildtype, as well as in FACS-sorted spermatocytes. The authors also profiled larval wing discs to serve as reference-somatic cells, which allowed them to focus only on features in their testis data that were associated with germ cells. Their results were further refined by categorizing the genes of interest based on available single nucleus RNA seq expression profiles. The authors document interesting phenomena, such as differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome and little or none on the X. The former is intriguing because this modification is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. The authors interpret some of their data as implying a lack of dosage compensation of the X chromosome in spermatocytes.

The data are believable and new, but it is not fully clear how to interpret them. The paper's interpretations rely on subtractive logic to parse results from mixtures of cells down to cell type, extracting spermatogonia, spermatocyte, etc. features by comparing bam mutants (only spermatogonia) to aly mutants (spermatogonia and early spermatocytes but no later stages) to wildtype (all spermatogenic stages), and extracting testis germline data by comparison to wing disc soma; their FACS sorted spermatocytes also have heterogeneity. I recognize that the present paper was a lot of work and am not suggesting that the authors redo their study using methods that give more purity and precision of stage (https://doi.org/10.1126/science.aal3096, https://doi.org/10.1101/gad.335331.119), but they should be aware of them and of their results.

The pulse-release system that the reviewer points to is an interesting system, but more limited in material and in useable markers than the systems we used here. We have added to our discussion of the the limitations of subtractive comparisons between arrest genotypes, both in regards to using mutants that may alter gene expression programs, and to how subtractive comparisons may limit our detection of differences between cell types (lines 143-147).

The conclusions about dosage compensation are indirect, but are consistent with the current model documented in the studies cited by the authors, as well as earlier studies (doi: 10.1186/jbiol30).

We disagree; our data directly speaks to the molecular mechanisms at play. Our profiling of the H4K16acetylation mark and RNAPII in isolated spermatocytes (Figure 4) demonstrates that current models are correct, and so are useful for settling this point in the literature.

Reviewer #1 (Recommendations For The Authors):

Throughout the manuscript, it is better to cite the original research papers.

We have added citations for the original characterizations of bam and aly alleles used, for the descriptions of PCGFP in spermatocytes, and for issues raised by reviewer comments.

Minor comments:

Pg.2, line 70-71: "Germline stem cells at the apical tip of the testis asymmetrically divide to birth spermatogonia", should be gonialblast.

Fixed (line 71).

Pg.2, line 71: "four rapid mitotic divisions", the spermatogonial cell cycle lasts several hours-- "rapid" is subjective and relative, better to leave this word out.

Fixed (line 71).

Reviewer #2 (Recommendations For The Authors):

Other than the major issue raised in the public review this paper only needs a few minor modifications, listed by line number below. The first one would be considered essential by this reviewer.

27: In the sentence that ends on this line, please add the word testis after Drosophila.

Fixed (line 27).

119: It must be known from the Fly Cell Atlas data whether these genes do begin to express in spermatogonia.

Collated expression values from the FCA are provided in Supplementary Table 2. In many cases there is detectable expression of these genes in spermatogonia, although transcript abundance peaks in early spermatocytes.

198: remove "distribution of".

Fixed (line 200).

311: enrichment relative to what?

Fixed (line 313). It is relative to signal in wing discs.

344: other aspects could be regulated such as elongation, termination.

We have added caveats to our speculations in this sentence (lines 340-356). The increased signal we see in gene bodies could be due to slower RNAPII elongation, but we don’t see a way that changes in termination would produce this pattern.

369: This part of the paper seems overly speculative, given the many molecular differences between dosage compensation mechanisms of Drosophila vs mammals, and studies that indicate that MSCI does occur in Drosophila (DOI: 10.3390/genes12111796).

We disagree, and this is a central point in our manuscript. The paper referred to here does not directly assess MSCI in Drosophila, instead they argue that MSCI could be the force driving the evolutionary depletion of male-germline-expressed genes they describe. These and many studies in the literature have conflated the effects of a lack of X dosage compensation and of MSCI in the male germline. Our direct measurements of RNAPII in spermatocytes demonstrates that there is no dosage compensation nor is there MSCI. Further, profiling of histone modifications associated with Drosophila somatic dosage compensation (H4K16ac) or with mammalian MSCI (uH2A, H3K9me2) show that the molecular mechanisms found in these other settings are not in play in the Drosophila male germline. As we have established these biological differences between mammals and Drosophila, it is appropriate to now speculate on why these differences may be, which we do on lines 374-384.

(several lines): Can the authors justify their assumption that chromatin features of larval wing disc cells will match those of somatic cells of adult testes?

We don’t only compare germline features to somatic cells of the wing disc, but also to genes with somatic expression in the testes annotated by FCA expression data (H3K4me2 in Figure 2C, RNAPII in Figure 3F). Note in Supplementary Figure 2 the distribution of RNAPII in whole testes (which includes somatic cells) is similar to that of larval wing discs, confirming that the differences we describe are specific to germline cells.

Reviewer #1 (Public Review):

Anderson, Henikoff and Ahmad et al. performed a series of genomics assays to study Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila.

What a nice feature

Reviewer #3 (Public Review):

Summary:<br /> This study aims to investigate the stoichiometric effect between core factors and partners forming the heterodimeric transcription factor network in living cells at endogenous expression levels. Using state-of-the-art single-molecule analysis techniques, the authors tracked individual RARα and RXRα molecules labeled by HALO-tag knock-in. They discovered an asymmetric response to the overexpression of counter-partners. Specifically, the fact that an increase in RARα did not lead to an increase in RXRα chromatin binding is incompatible with the previous competitive core model. Furthermore, by using a technique that visualizes only molecules proximal to partners, they directly linked transcription factor heterodimerization to chromatin binding.

Strengths:<br /> The carefully designed experiments, from knock-in cell constructions to single-molecule imaging analysis, strengthen the evidence of the stoichiometric perturbation response of endogenous proteins. The novel finding that RXR, previously thought to be a target of competition among partners, is in excess provides new insight into key factors in dimerization network regulation. By combining the cutting-edge single-molecule imaging analysis with the technique for detecting interactions developed by the authors' group, they have directly illustrated the relationship between the physical interactions of dimeric transcription factors and chromatin binding. This has enabled interaction analysis in live cells that was challenging in single-molecule imaging, proving it is a powerful tool for studying endogenous proteins.

Weaknesses:<br /> As the authors have mentioned, they have not investigated the effects of other T2NRs or RXR isoforms. These invisible factors leave room for interpretation regarding the origin of chromatin binding of endogenous proteins (Recommendations 4). In the PAPA experiments, overexpressed factors are visualized, but changes in chromatin binding of endogenous proteins due to interactions with the overexpressed proteins have not been investigated. This might be tested by reversing the fluorescent ligands for the Sender and Receiver. Additionally, the PAPA experiments are likely to be strengthened by control experiments (Recommendations 5).

Die WHO will bei der kommenden COP28 das Thema der Gesundheit offensiv in den Mittelpunkt stellen. Zum ersten Mal wird ein ganzer Tag Gesundheitsthemen gewidmet sein. Der Guardian hat dazu mit Maria Neira. der WHO-Verantwortlichen für Umweltgesundheit, gesprochen. https://www.theguardian.com/world/2023/nov/04/politicians-who-delay-climate-action-must-live-with-consequences-says-who-expert

Author Response

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

Public Reviews:

Reviewer #1 (Public Review):

Summary: Hansen et al. dissect the molecular mechanisms of bacterial ice nucleating proteins mutating the protein systematically. They assay the ice nucleating ability for variants changing the R-coils as well as the coil capping motifs. The ice nucleation mechanism depends on the integrity of the R-coils, without which the multimerization and formation of fibrils are disrupted.

Strengths: The effects of mutations are really dramatic, so there is no doubt about the effect. The variants tested are logical and progressively advance the story. The authors identify an underlying mechanism involving multimerization, which is plausible and compatible with EM data. The model is further shown to work in cells by tomography.

Weaknesses: The theoretical model presented for how the proteins assemble into fibrils is simple, but not supported by much data.

Agreed. This theoretical INP multimer model was introduced to promote discussion and elicit ideas on how to prove or disprove it. The length and width of the fibres are defined by cryo-ET results, in which the narrow width is just sufficient to accommodate a dimer of the INPs, and the long length requires that several INPs are joined end to end. Their antiparallel arrangement produces identical ends to the dimer and avoids steric clash of the C-terminal cap structures as well as the C-terminal GFP tag. This model can accommodate the wide range of INPs lengths seen in nature (due to different numbers of water-organizing coils) and introduced in mutagenesis experiments (Forbes et al. 2022). It defines a critical role for the R-coil subdomain in joining the dimers together and explains why this region cannot be shortened by more than a few coils either in nature or by experimentation.

In response to specific criticisms of the model (Fig. 9), we have redesigned this to be less schematic and to incorporate several copies of the AlphaFold-predicted structure.

Reviewer #2 (Public Review):

Summary:

This paper further investigates the role of self-assembly of ice-binding bacterial proteins in promoting ice-nucleation. For the P. borealis Ice Nucleating Protein (PbINP) studied here, earlier work had already determined clearly distinct roles for different subdomains of the protein in determining activity. Key players are the water-organizing loops (WO-loops) of the central beta-solenoid structure and a set of non-water-organizing C-terminal loops, called the R-loops in view of characteristically located arginines. Previous mutation studies (using nucleation activity as a read-out) had already suggested the R-loops interact with the WO loops, to cause self-assembly of PbINP, which in turn was thought to lead to enhanced ice-nucleating activity. In this paper, the activities of additional mutants are studied, and a bioinformatics analysis on the statistics of the number of WO- and R-loops is presented for a wide range of bacterial ice-nucleating proteins, and additional electron-microscopy results are presented on fibrils formed by the non-mutated PbINP in E coli lysates.

Strengths:

-A very complete set of additional mutants is investigated to further strengthen the earlier hypothesis.

-A nice bioinformatics analysis that underscores that the hypothesis should apply not only to PbINP but to a wide range of (related) bacterial ice-nucleating proteins.

-Convincing data that PbINP overexpressed in E coli forms fibrils (electron microscopy on E coli lysates).

Weaknesses:

-The new data is interesting and further strengthens the hypotheses put forward in the earlier work. However, just as in the earlier work, the proof for the link between self-assembly and ice-nucleation remains indirect. Assembly into fibrils is shown for E coli lysates expressing non-mutated pbINP, hence it is indeed clear that pbINP self-associates. It is not shown however that the mutations that lead to loss of ice-nucleating activity also lead to loss of self-assembly. A more quantitative or additional self-assembly assay could shine light on this, either in the present or in future studies.

The control cryo-ET experiment where the R-coils were deleted and INP fibres were not seen is consistent with a link between the loss of ice-nucleating activity and the loss of self-assembly. However, we agree that a more direct measurement of the physical state of INP molecules is needed to prove the link.

-Also the "working model" for the self-assembly of the fibers remains not more than that, just as in the earlier papers, since the mutation-activity relationship does not contain enough information to build a good structural model. Again, a better model would require different kinds of experiments, that yield more detailed structural data on the fibrils.

Reviewer #1 also raised these criticisms of the model, which we have responded to (above). Testing the model is a focus of our continuing experiments on INPs.

Reviewer #3 (Public Review):

Summary: in this manuscript, Hansen and co-authors investigated the role of R-coils in the multimerization and ice nucleation activity of PbINP, an ice nucleation protein identified in Pseudomonas borealis. The results of this work suggest that the length, localization, and amino acid composition of R-coils are crucial for the formation of PbINP multimers.

Strengths: The authors use a rational mutagenesis approach to identify the role of the length, localisation, and amino acid composition of R-coils in ice nucleation activity. Based on these results, the authors hypothesize a multimerization model. Overall, this is a multidisciplinary work that provides new insights into the molecular mechanisms underlying ice nucleation activity.

Weaknesses: Several parts of the work appear cryptic and unsuitable for non-expert readers. The results of this work should be better described and presented.

In revising the manuscript for reposting we have rewritten sections to make it more accessible to the non-expert. Incorporating the detailed recommendations of the reviewers has been helpful in this effort.

Recommendations for the authors: please note that you control which revisions to undertake from the public reviews and recommendations for the authors

Reviewer #1 (Recommendations For The Authors):

Introduction: Curiously, there is no mention at all in the introduction of what the biological function of these ice-nucleating proteins is.

We added the following text to the first paragraph of the Introduction: ”INP-producing bacteria are widespread in the environment where they are responsible for initiating frost (4) and atmospheric precipitation (5). As such, these bacteria play a significant role in the Earth’s hydrological cycle and in agricultural productivity.”

Line 70: TXT, SLT, and Y motifs are mentioned, but only the first is described. Also, TXT name alternates between TXT and TxT in the manuscript. (I think the latter is more correct).

These putative water-organizing motifs are introduced in the preceding paper (new ref 8). We now use TxT consistently throughout the manuscript and have converted SLT to SxT because L is an inward-pointing residue that is not directly involved in water organization.

Line 236: A construct with repeats deleted is tested for thermostability, but it is not really explained what hypothesis this experiment is supposed to test.

This is an observation that adds information about the stability of the INP multimers and will need to be explained by the structure.

Line 267: The authors test a mutant where the N-terminal coil is disrupted and find a big effect. Nevertheless, no conclusion is drawn. What does this result mean?

On the contrary, INP activity is not appreciably affected by N-terminal deletion.

Line 269: The CryoEM begins rather abruptly with technical details. Consider introducing the paragraph with a brief statement about what you want to investigate. Also, the analysis seems a little half-hearted.

Given that the authors describe other EM studies of fibrils of the same protein it would be nice with a clear statement about what is new in their study and how it compares to previous studies.

We have added this statement about why we used Cryo-EM: “The idea that INPs must assemble into larger structures to be effective at ice nucleation has persisted since their discovery (6). In the interim the resolving power of cryo-EM has immensely improved. Here we elected to use cryo-electron tomography to view the INP multimers in situ and avoid any perturbation of their superstructure during isolation.”

Fig. 7B: Single-letter amino acid codes are always capitalized.

We have revised this figure to use capital letters for the amino acids.

Fig. 9: This figure is really hard to read even though it is very simplistic. I would consider making a figure with several copies of the AlphaFold model instead. Especially panel D, I do not know what is supposed to show.

We have followed this advice and have completely revised the figure using copies of the AlphaFold model. Panel D (now C) shows two cross-sections through the AlphaFold model.

Line 355 onwards: The model of the INP is the weakest part of the manuscript. This reviewer considers that the model is crude and it is unclear what information the model is supported by. The authors might want to consider running an AlphaFold multimer to get a better model of at least the dimer.

Our objective now is to validate or disprove the model by experimentation using protein-protein cross-linking in conjunction with mass spectrometry, and higher resolution cryo-EM methods.

Reviewer #2 (Recommendations For The Authors):

I would suggest more frankly discussing the weaknesses mentioned in my public review, as well as approaches that could be used in the future to address these.

In the cryo-ET analysis, INP mutations of the R-coils that lead to loss of ice-nucleating activity fail to show fibres in the bacteria (Fig. S4), which is consistent with the loss of self-assembly. We are working on physical methods that can assess the degree of assembly of the different INP constructs and mutations. We are working to validate and improve the working model of INP multimers.

Reviewer #3 (Recommendations For The Authors):

Abstract

Line 18. Below 0 Celsius should be < 0 {degree sign}C.

Done

Line 25. E. coli should be Escherichia coli

Done

Line 29. E. coli should be in italics.

Done

Introduction

The introduction is weak and not suitable for non-expert readers. Moreover, in some parts it is cryptic and it is not clear whether the authors are describing INP in general or PbINP. The introduction should be reorganized to highlight the novelty of this paper compared to Forbes et al. 2022.

The changes we have made to the Introduction can be seen in the ‘documents compared’ version where the changes are tracked.

Line 45. It is unclear whether this paragraph is a result reported in the literature or the result of this work. Please clarify.

These are results reported in the literature as indicated by the references cited in the paragraph.

Line 54. It is not clear whether this paragraph describes PbINP or INP in general.

This paragraph begins with INPs in general and then focuses on PbINP.

Results

Line 109. This section would benefit from a paragraph in which the authors describe the rationale for this bioinformatic analysis.

We added the following Statement: “A bioinformatic analysis of bacterial INPs was undertaken to identify their variations in size and sequence to understand what is common to all that could guide experiments to probe higher order structure and help develop a collective model of the INP multimer.”

Some information is needed on the selected sequences such as sequence identity, what do the authors mean by nr database?

The abbreviation nr has been replaced by ‘non-redundant’. As explained in that same paragraph the sequences selected were those from long-read sequences that could be relied on to accurately count the number of solenoid coils.

Line 144. The standard deviation is necessary to understand whether these differences are statistically significant.

These have been added as p values.

Figure 2. I noticed that the authors used GFP-tagged PbINP. Why? In addition, panel C is never mentioned in the manuscript.

The GFP tag was used to confirm expression of the PbINP in E. coli. We have added this sentence: “As previously described these constructs were tagged with GFP as an internal control for INP production, and its addition had no measured effect on ice nucleation activity (8).”The GFP tag was also useful as in internal control for the heat denaturation experiments featured in Fig. 6, where it lost its fluorescence between 65 and 75 °C.

Fig. 2C is now cited alongside Fig. 2B.

Figure 3. In my opinion, the results of the R-coil deletion should also be shown in Figure 2. Line 171. This section is cryptic. A logo sequence or an alignment of WO-coils and R-coils of PbINP could be helpful for the reader. Instead of the architecture of the whole protein, it would be useful to have the sequence of the R-coils with the residues that the authors mutagenised.

The logo sequences are available in Fig. 1.

Line 202. Here, the authors describe a new experimental setup. As the Materials and Methods section follows the Discussion, the authors should state in the first paragraph of the Results section that IN activity was measured on whole cells.

We have now modified the introductory sentence to read: “Ice nucleation assays were performed on intact E. coli expressing PbINP to assess the activity of the incremental replacement mutants.”

Line 202. The authors investigated the effects of pH and temperature (Line 223) on the IN activity. The authors should better introduce the rationale for these experiments and how they fit within the work.

We have now modified the following sentence to provide the rationale: “To see how important electrostatic interactions were in the multimerization of PbINP as reflected by its ice nucleation activity, it was necessary to lyse the E. coli to change the pH surrounding the INP multimers.”

Line 245. This work is supported by a model provided by Alphafold. I wonder how reliable this model is; the authors should indicate the quality of the model and provide the accuracy values of the residuals.

This information is now provided in Figure S1.

Line 259. Typically in mutagenesis studies, a key residue is substituted with alanine to create a loss of function variant. In this case, the authors have made the following substitutions F1204D, D1208L, and Y1230D, it is not clear to me why the authors have replaced an aromatic residue with one of aspartic acid that is negatively charged.

We have justified these more extreme changes as follows: “For an enhanced effect of the mutations hydrophobic residues were replaced with charged ones and vice versa.”

Line 269. This paragraph seems completely unrelated to the section entitled: The β-solenoid of INPs is stabilized by a capping structure at the C terminus, but not at the N terminus.

We had omitted the sub-heading “Cryo-electron tomography reveals INPs multimers form bundled fibres in recombinant cells”, which is now in place.

Discussion

Overall, the discussion is too long and some parts appear cryptic, this section should be reorganized.

The changes we have made to the Discussion can be seen in the ‘documents compared’ version where the changes are tracked.

Line 354. It is not clear what experimental evidence supports this model. In the results, this model is never mentioned and it is not clear whether it was obtained by computational analysis or not.

The model is presented in the Discussion because it was not arrived at by experimentation but is an attempt to integrate the observations made in the Results section. The experimental evidence that supports this model is reviewed in the Discussion section: “Working model of the INP multimer is consistent with the properties of INPs and their multimers.”

Line 354. The authors used GFP-tagged PbINP. The Authors should discuss the role of GFP in this model and IN activity. A measurement of IN activity on PbINP without GFP would be useful.

We have previously shown in Ref 8 that the GFP tag has no detrimental effect on ice nucleation activity. Our model for the INP multimer can accommodate this C-terminal tag without any steric hindrance.

Line 364. The Authors hypothesize that electrostatic interactions stabilize end-to-end dimer associations. To test this hypothesis, the authors should measure the activity of IN at increasing concentrations of NaCl. It is known that high salt concentrations shield charges by preventing the formation of electrostatic intermolecular interactions.

We have added this sentence to the Discussion: “Another useful test of the electrostatic component to the multimer model would be to study the effects of increasing salt concentration on ice nucleation activity of the E. coli extracts.”

Line 439. Conclusions should be useful for the reader.

Material and Methods

In several sections, the authors refer to what has already been published in Forbes et al. However, the minimum information should also be described in this work. In addition, the Authors should indicate the number of replicates.

The ice nucleation assays on whole cells were done on the WISDOM apparatus, which integrates 100’s of individual measurements to obtain a T50 value. These T50 values were confirmed by assays on the nanoliter osmometer apparatus. The numbers of replicates used on the nanoliter osmometer apparatus are indicated by box and whisker plots in Figs. 5 & 6 with boxes and bars showing quartiles, with medians indicated by a centre line.

Line 500. This paragraph should be removed as the results are not described in the manuscript.

This is a Methods section that describes how that INPs were expression in E. coli. It has details that are important for researchers who want to repeat our findings, such as the use of the Arctic Express strain for producing INP.

Author Response

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

Reviewer #1 (Public Review):

"MAGIC" was introduced by the Rong Li lab in a Nature letters article in 2017. This manuscript is an extension of this original work and uses a genome wide screen the Baker's yeast to decipher which cellular pathways influence MAGIC. Overall, this manuscript is a logical extension of the 2017 study, however the manuscript is challenging to follow, complicated by the data often being discussed out of sequence. Although the manuscripts make claims of a mechanism being pinpointed, there are many gaps and the true mechanisms of how the factors identified in the screen influence MAGIC is not clear. A key issue is that there are many assumptions drawn on previous literature, but central aspects of the mechanisms being proposed are not adequately shown.

Key comments:

1. Reasoning and pipelines presented in the first two sections of the results are disordered and do not follow figure order. In some instances, the background to experimental analyses such as detailing the generation of spGFP constructs in the YKO mutant library, or validation of Snf1 activation are mentioned after respective results are discussed. This needs to be fixed.

We thank the reviewer for pointing out potential confusion to readers. We have revised the first two sections according to reviewer’s suggestion. (Page 4-6)

1. In general there is a lack of data to support microscopy data and supporting quantification analysis. The validity of this data could be significantly strengthened with accompanying western blots showing accumulation of a given constructs in mitochondrial sub compartments (as was the case in the lab’s original paper in 2017).

We appreciate the reviewer’s suggestion on biochemical validations. However, the validity of this imaging-based assay for detecting import of cytosolic misfolded proteins into mitochondria, including the use of FlucSM as a model misfolding-prone protein, was carefully established in our previous study by using appropriate controls, super resolution imaging, APEX-based proximity labeling, and classical biochemical fractionation and protease protection assay (Ruan et al., 2017 Nature, ref. 10). We have reminded readers of these validation experiments in the previous study on Page 4, line 14-17.

In recent years, advancements in imaging-based tools have allowed many protein interactions and dynamic processes, which were previously examined by using biochemical assays in lysates of populations of cells, to be observed with various level of quantitation in live cells with intact cellular compartments. Many of these assays, e.g., the RUSH assay for ER to Golgi transport, FRAP-based analysis for nuclear/cytoplasmic shuttling of proteins, or FRET-based assays for protein-protein interactions, have been well accepted and even embraced by the respective fields of study once validated with genetic and biochemical approaches. The advantages for live-cell imaging-based assays are often their unique ability to report dynamic processes or unstable molecular species with spatiotemporal sensitivity. Respectfully, it is our view, based on our own experience, that the traditional protease protection assay is not adequate or sufficiently quantitative for examining the presence of unstable misfolded proteins in mitochondrial sub-compartments, given the obligatorily lengthy in vitro cell lysis and mitochondrial isolation process, during which the unstable proteins are continuously being degraded. This likely explains our previous biochemical fractionation result that only weak protein signals were detected in the matrix fraction (Ruan et al., 2017 Nature, ref. 10). In addition, unlike stably folded, native mitochondrial matrix proteins, misfolded/unfolded proteins such as Lsg1 or FlucSM are highly susceptible to protease treatment. This sensitivity makes the assay unreliable for detecting such proteins if trace amount of the protease penetrates mitochondrial membranes during cell lysis even without detergent treatment.

While we agree that protease protection assay is highly valuable for qualitative detection of the presence of a protein in certain mitochondrial compartments or determining its topology on membranes, this assay (regrettably in our hands) does not allow quantitative comparisons that were necessary for this study, because of inherent sample to sample variation, yet the laborious and low throughput nature of this assay makes it difficult for adequate statistical analysis. Furthermore, the level of protein detection in various fractions is highly sensitive to how the sample is treated with protease and detergent. Our imaging-based quantification, on the other hand, allows us to compare increased or decreased presence of GFP11-tagged proteins in mitochondria under different metabolic conditions or in different mutant or wild-type strains. Data from hundreds of cells and at least three independent biological replicates allowed us to apply adequate statistical analysis to aid our conclusion.

1. Much of the mechanisms proposed relies on the Snf1 activation. This is however not shown but assumed to be taking place. Given that this activation is central to the mechanism proposed, this should be explicitly shown here - for example survey the phosphorylation status of the protein.

Both REG1 deletion and low glucose conditions have been demonstrated extensively for Snf1 phosphorylation and activation in yeast (e.g., many seminal papers from Marian Carlson’s and other lab, such as ref. 24-28). In our study, we have indeed corroborated this by showing that Mig1 was exported from the nucleus in Δreg1 mutant and in low glucose conditions (Figure 1—figure supplement 2H and I. The mechanism of Snf1-mediated nuclear export of Mig1 has been characterized in detail as well (e.g., ref. 29-31).

Recommendations for the authors: please note that you control which, if any, revisions, to undertake

Reviewer #1 (Recommendations For The Authors):

SPECIFIC COMMENTS

Genetic Screen o Line 20 - the narrative moves to SNF1, but the reasoning for the selection of this Class I substrate is not defined. What was the basis for this selection - what happened to the other Class I substrates. It is stated in the text that the other Class I proteins show the same increase in spGFP signal. The data showing this should be included in the Supp Figure 1 for transparency.

We have moved the narratives of Snf1 function to the second section and clarified that we were interested in this gene due to its central role in metabolism and mitochondrial functions that may influence MAGIC (Page 5: line 16-20). Other genes in class 1 were shown in Table S1. Detailed discussion of other genes in this category is beyond the scope of this study.

Snf1/AMPK prevents MP accumulation in mitochondria:

The FlucDM data in human RPE-1 mitochondria seems to be added to only increase the significance of the work. The mechanisms suggested here with Hap4 would not be possible in human cells as there is no homologue of this protein in human cells. Making generalisations that these pathways are conserved based on this one experiment is not appropriate.

We appreciate this feedback. Although the focus of this study is the regulation of MAGIC by the yeast AMPK Snf1, we would like to share our initial observation that suggests a similar role of AMPK in human RPE-1 cells. We acknowledge that the underlying mechanisms regarding the downstream transcription factors and pathway for misfolded protein import could be different in mammalian cells, but the overall effect of AMPK in mitochondrial biogenesis is well known to resemble that of Snf1. To avoid making over-generalization, we changed our statement of conclusion to: ‘These results suggest that AMPK in human cells regulates MP accumulation in mitochondria following a similar trend as in yeast, although the underlying mechanisms might differ between these organisms.’ (Page 7: line 2-4)

Mechanisms of MAGIC regulation by Snf1:

While the lysosome is ruled out here the authors have not considered the proteasomes. Is there a reason for this? Given accumulation of aggregates outside of mitochondria, and previous connections of the proteasome to mitochondrial quality control this would be an obvious thing to check. We examined the role of lysosomal degradation here because it is known to be activated under Snf1active condition (ref. 37). We appreciate this feedback and have included a new analysis on MG132treated FlucSM spGFP strains in which PDR5 gene was deleted to avoid drug efflux.

This result suggests that the proteosome inhibitor did not ablate the difference in FlucSM accumulation between these conditions. That MG132 promoted mitochondrial accumulation of FlucSM in both high glucose and low glucose conditions was not surprising, as FlucSM is also degraded by proteasome in the cytosol (Ruan et al., 2017 Nature, ref. 10), and preventing this pathway could divert more of such protein molecules toward MAGIC. (Page 7: line 26-29).

Line 13 "we hypothesized that elevated expression of mitochondrial preproteins induced by the activation of Snf1-Hap4 axis (REF) may outcompete MPs for import channels". This statement has some assumptions. The authors have not shown that Snf1 is activated in thier models and more importantly that they have an accumulation of mitochondrial preproteins. The data that follows using the cytosolic domains of the receptors is hard to rationalise without seeing evidence that there is in fact pre-protein accumulation or impacts on the mitochondrial proteome in this system.

As stated in our response to main point [3], Snf1 activation in reg1 mutant or in low glucose is evidenced by our data showing Mig1 export from nucleus to cytoplasm and had also been shown in many previous publications. A recent study (Tsuboi et al., 2020 eLife) also showed a dramatic increase in mitochondrial volume fraction in Δreg1 cells and wild-type cells in respiratory conditions, further supporting the role of Snf1 in mitochondrial biogenesis. We have provided relevant references in the manuscript (ref. 24-28).

The ability of Tom70 cytosolic domain (Tom70cd), which can bind mitochondrial preproteins but not localize to mitochondria due to lack of N-terminal targeting sequence, to compete with endogenous Tom70 for mitochondrial preproteins has been well documented (ref. 47-49). However, we agree with the reviewer that a future quantitative proteomics study to measure changes in mitochondrial proteome under Tom70cd over-expression could allow more accurate interpretation of our experimental result.

AMPK protects cellular fitness during proteotoxic stress:

The inhibition of preprotein import by overexpressing the cytosolic domains of receptors is not supported with some proof of principle data. If this was working as the authors assume, it is not clear why only an effect with Tom70 is observed. The majority of the mitochondrial proteome is imported via Tom20/Tom22 so this does not align with what the authors are suggesting. Is the Tom70CD and any associated Hsp proteins facilitating the observed changes to the MPs?

We thank the reviewer for raising this point. We expressed different TOM receptor cytosolic domains but found that Tom70cd had the strongest rescue on MAGIC under AMPK activation conditions. It is possible that certain Tom70 substrates or Tom70-assoicated heat shock proteins inhibit the import of MAGIC substrates. We admit that a clear explanation of this unexpected observation necessitates a better understanding of how native and MAGIC substrates are selected and imported by the outer-membrane channel. We can only offer our best interpretation based on the current state of the understanding, and we feel that we have been careful to acknowledge such in the manuscript.

While the effect of AMPK inactivation reducing FUS accumulation was striking, this was all in the context of overexpression and may not be physiologically relevant - or may occur very transiently under basal conditions. Is GST an appropriate control here, why not use WT FUS? Likewise, one representative image is shown in Figure 5 - can the authors show western blotting that mitochondrial accumulation of FUS can be reduced with AMPK activation?

We thank the reviewer for this suggestion, however, overexpressed FUS WT is also aggregation prone (Zhihui Sun et al., 2011, PloS Biology; Shulin Ju, 2011, PloS Biology; Jacqueline C. Mitchell et., 2013, Acta Neuro). We believe that GST, as a well-folded protein, is an appropriate control (Ruan et al., 2017 Nature, ref. 10). As we discussed in response to main point [1], the in vitro assay involving protease protection and western blots do not allow reliable quantitative comparison in our hands.

In text changes.

The analysis pipeline of the YKO mutant library should be introduced at the very start of the first paragraph, not the end.

Addressed on Page 4, second paragraph

"Fluc" should be introduced as "Firefly luciferase" within the first paragraph of the first section, also need to define SM and DM in FlucSM/FlucDM - these appear to be missing.

Addressed in both Introduction (Page 2: line 29; Page 3: line 8-9) and re-clarified in Result (Page 5: line 27-29)

The role of Reg1 should be explicitly stated in the text, not just in the figure.

Addressed on Page 6: line 3-6

Figure 1H legend states Reg1 (WT) is Snf1-inactive and Reg1 KO is Snf1-active. This wording is confusing and is not supported by data, but by assumption. If the authors want to use this wording then evidence needs to be provided - as suggested above.

We have changed this and other legends to only show genotypes and medium conditions.

"Tom70cd overexpression also exacerbated growth rate reduction due to FlucSM expression in HG medium (Figure 4A; Figure 4 - figure supplement 1A)" should be figure supplement 1B.

Fixed on Page 10: line 10

"These results suggest that glucose limitation protects mitochondria and cellular fitness during FlucSM induced proteotoxic stress through Snf1-dependent inhibition of MP import into mitochondria". The phrase "Snf1-dependent inhibition of MP import into mitochondria" may be misleading, as Snf1 isn't modulating import directly but is acting on transcriptional regulators to modulate mitochondrial import under stress.

We restated the conclusion as follows: ‘These results suggest that Snf1 activation under glucose limitation protects mitochondrial and cellular fitness under FlucSM-associated proteotoxic stress.’ (Page 10: line 20- 21)

"... Significantly increased the fraction of spGFP-positive and MMP-low cells in both HG and LG medium (Figure 4G-K)" should be (Figure 4J-K).

Fixed on Page 11: line 3

Reviewer #2 (Public Review):

Work of Rong Li´s lab, published in Nature 2017 (Ruan et al, 2017), led the authors to suggest that the mitochondrial protein import machinery removes misfolded/aggregated proteins from the cytosol and transports them to the mitochondrial matrix, where they are degraded by Pim1, the yeast Lon protease. The process was named mitochondria as guardian in cytosol (MAGIC).

The mechanism by which MAGIC selects proteins lacking mitochondrial targeting information, and the mechanism which allows misfolded proteins to cross the mitochondrial membranes remained, however, enigmatic. Up to my knowledge, additional support of MAGIC has not been published. Due to that, MAGIC is briefly mentioned in relevant reviews (it is a very interesting possibility!), however, the process is mentioned as a "proposal" (Andreasson et al, 2019) or is referred to require "further investigation to define its relevance for cellular protein homeostasis (proteostasis)" (Pfanner et al, 2019).

Rong Li´s lab now presents a follow-up story. As in the original Nature paper, the major findings are based on in vivo localization studies in yeast. The authors employ an aggregation prone, artificial luciferase construct (FlucSM), in a classical split-GFP assay: GFP1-10 is targeted to the matrix of mitochondria by fusion with the mitochondrial protein Grx5, while GFP11 is fused to FlucSM, lacking mitochondrial targeting information. In addition the authors perform a genetic screen, based on a similar assay, however, using the cytosolic misfolding-prone protein Lsg1 as a read-out.

My major concern about the manuscript is that it does not provide additional information which helps to understand how specifically aggregated cytosolic proteins, lacking a mitochondrial targeting signal could be imported into mitochondria. As it stands, I am not convinced that the observed FlucSM-/Lsg1-GFP signals presented in this study originate from FlucSM-/Lsg1-GFP localized inside of the mitochondrial matrix. The conclusions drawn by the authors in the current manuscript, however, rely on this single approach.

In the 2017 paper the authors state: "... we speculate that protein aggregates engaged with mitochondria via interaction with import receptors such as Tom70, leading to import of aggregate proteins followed by degradation by mitochondrial proteases such as Pim1." Based on the new data shown in this manuscript the authors now conclude "that MP (misfolded protein) import does not use Tom70/Tom71 as obligatory receptors." The new data presented do not provide a conclusive alternative. More experiments are required to draw a conclusion.

In my view: to confirm that MAGIC does indeed result in import of aggregated cytosolic proteins into the mitochondrial matrix, a second, independent approach is needed. My suggestion is to isolate mitochondria from a strain expressing FlucSM-GFP and perform protease protection assays, which are well established to demonstrate matrix localization of mitochondrial proteins. In case the authors are not equipped to do these experiments I feel that a collaboration with one of the excellent mitochondrial labs in the US might help the MAGIC pathway to become established.

We thank Reviewer 2 for these suggestions, but we would like to respectfully offer our difference in opinion:

a. Regarding the suggestion “to isolate mitochondria from a strain expressing FlucSM-GFP and perform protease protection assays”, in our previous study (Ruan et al., 2017 Nature, ref. 10), we have indeed applied two independent biochemical approaches: APEX-mitochondrial matrix proximity labeling and classic protease protection assay using non-spGFP strains, both consistently confirmed the entry of misfolded proteins into mitochondria under proteotoxic stress. Our super-resolution imaging further confirmed the import of the split GFP-labeled proteins to be inside mitochondria. Moreover, as we discussed in response to Reviewer 1’s main point [2], while the suggested biochemical assay is useful for validating topology within mitochondria, it is not quantitative and may not reliably report the in vivo accumulation of misfolded proteins in mitochondria due to the isolation process that takes hours, during which the unstable proteins could be continuously degraded within mitochondria.

While we agree with the reviewer that we do not yet understand how misfolded proteins are imported into mitochondria, it would be unfair to state “as it stands, I am not convinced..” simply because the underlying mechanism remains to be elucidated. We would like to point out that targeting sequences for many well-established mitochondrial proteins are still not well defined. It is well known that mitochondrial targeting sequences are not as uniformly predictable as, for example, nuclear targeting sequences. Our finding that deletion of TOM6 enhances the import of misfolded proteins suggest that their import may involve the TOM channel in a more promiscuous conformation, which may reduce the requirement for a specific sequence-based targeting signal associated with the substrate.

b. Regarding the role of Tom70, in our 2017 study, using proteomics and subsequently immunoprecipitation we validated the binding, albeit not necessarily direct, between misfolded protein FlucSM and Tom70. Therefore, “we speculate that protein aggregates engaged with mitochondria via interaction with import receptors such as Tom70”. Recent studies from different labs confirmed the interactions between Tom70 and aggregation prone proteins (Backes et al., 2021, Cell Reports; Liu et al., 2023, PNAS). In the current study, surprisingly, knockout of TOM70 did not block MAGIC, suggesting redundant components of mitochondria import system may facilitate the recruitment of misfolded proteins in the absence of Tom70, and this does not contradict the notion that Tom70 helps tether protein aggregates to mitochondria.

c. Regarding other studies also showing the import of misfolding or aggregation-prone cytosolic proteins into mitochondria, there have been at least several recent studies in the literature for mammalian cells involving either model substrates or disease proteins (e.g., ref. 12-15; 56-58; Vicario, M. et al. 2019 Cell Death Dis.). The studies are briefly mentioned in Introduction (Page 3, paragraph 2). The present manuscript documents a major effort from our group using whole genome screen in yeast to understand the mechanism and regulation of MAGIC. Many of the screen hits have yet to be studied in detail. We full agree that much remains to be understood about whether and how this pathway affects proteostasis and what might be the evolutionary origin for such a mechanism.

Additional comments:

The genetic screen:

The genetic screen identified five class 1 deletion strains, which lead to enhanced accumulation of Lsg1GFP and a larger set of class 2 mutants, which lead to reduced accumulation. Please note, in my opinion it is not clear that accumulation of the reporters occurs inside the mitochondria. In any case, the authors selected one single protein for further analysis: Snf1, the catalytic subunit of the yeast SNF complex, which is required for respiratory growth of yeast.

The results of the screen are not discussed in any detail. The authors mention that ribosome biogenesis factors are abundant among class 2 mutants. Noteworthy, Lsg1 is involved in 60S ribosomal subunit biogenesis. As Lsg1-GFP11 is overexpressed in the screen this should be discussed. Class 2 mutants also .include several 40S ribosomal subunit proteins (only one of the 60S subunit). What does this imply for the MAGIC model? Also, it should be discussed that the screen did not identify reg1 and hap4, which I had expected as hits based on the data shown in later parts of the manuscript.

We apologize for the confusion, but the GFP11 tag was in fact knocked into the C-terminus of Lsg1 in the endogenous LSG1 locus, and so Lsg1 was not overexpressed in the screen. We have made sure that this information is clearly conveyed in the revised manuscript (Page 4: line 20-22). How the ribosome small subunit affects MAGIC is beyond the focus of the current study and will be pursued in the future.

Regarding why certain mutants did not come out of our initial screen, this is not unexpected as the YKO collection, although extremely valuable to the community, is known to be potentially affected by false knockouts, suppressor accumulation and cross contamination (for references, e.g., Puddu et al., 2019 Nature). Additionally, high-through screens can also miss real hits. In our experience using this collection in several studies, we often found additional hits from analysis of genes implicated by known genetic or biochemical interactions.

Mutant yeast strains and growth assays:

The Δreg1 strain grows poorly in all growth conditions and frequently accumulates extragenic suppressor mutations (Barrett et al, 2012). It would be good to make sure that this is not the case in the strains employed in this study. My suggestion is to do (and show) standard yeast plating assays with the relevant mutant strains including Δreg1, snf1, hap4, Δreg1Δhap4 without the split GFP constructs and also with them (i.e. the strains that were used in the assays).

We thank the reviewer for the suggestion. We were indeed aware of potential accumulation of suppressor mutations from the YKO library. Therefore, deletion mutants like Δreg1 and loss of TFs downstream of Snf1 that we used in the study after the initial screen were all freshly made and validated. At least 3 independent colonies were analyzed for each mutant (mentioned in Methods & Materials; Page 33, line 57). Moreover, the plating assay suggested here may not reveal additional information other than growth, which was taken into consideration during our experiments.

Activation of Snf1 in the relevant strains should be tested with the commercially available antibody recognizing active Snf1, which is phosphorylated at Snf1-T210.

Snf1 activation was validated by the Mig1 exporting from the nucleus. We also noted above that many studies have clearly demonstrated Snf1 activation in reg1 mutant and under low glucose growth (e.g., ref. 24-28).

Effects of Snf1, Reg1, Hap4 and respiratory growth conditions:

The authors show that split GFP reporters show enhanced accumulation during fermentative growth, in Δsnf1, and Δreg1Δhap4 and fail to accumulate during respiratory growth, in Δreg1 and upon overexpression of HAP4. Analysis of Δhap4 should be included in Fig. 2. The suggestion that upon activation of Snf1 enhanced Hap4-dependent expression "outcompetes" misfolded protein import seems unlikely as only a fraction of mitochondrial genes is under control of Hap4. Without further experimental evidence I do not find that a valid assumption. More likely, the membrane potential plays a role: it is low during fermentative growth, in Δsnf1 and Δreg1Δhap4, and high during respiratory growth and in Δreg1 (Hübscher et al, 2016). Such an effect of the membrane potential seems to contradict the findings in the 2017 paper and the issue should be clarified and discussed. In any case, these data do not reveal that GFP reporters accumulate inside of the mitochondria. Based on the currently available evidence they may accumulate in close proximity/attached to the mitochondria. This has to be tested directly (see above).

We have included our analysis of Δhap4 in Page 8: line 14-15 and Figure 2—figure supplement 1H. Consistent with our result for Δreg1Δhap4 in glucose-rich medium, HAP4 deletion also resulted in a significant increase in mitochondrial accumulation of FlucSM in low glucose medium compared to WT. It did not have effect in high glucose condition in which Snf1 is largely inactive.

It is our view that the importance of Hap4 should not be judged by the number of nuclear encoded mitochondrial proteins they regulate. Still, this sub-group comprises a considerable number of proteins (at least 55 genes upregulated by Hap4 overexpression, ref. 43), and certain substrates may be more competitive with misfolded cytosolic proteins for import. Our genetic data strongly suggest that the inhibitory effect of active Snf1 on MAGIC is through Hap4, although we agree with the reviewer that detailed mechanism on how Hap4 substrates may compete with misfolded proteins need to be addressed in future studies.

Membrane potential is important for mitochondrial import. During respiratory growth and in Δreg1, membrane potential is well known to be elevated comparing to fermentative condition (e.g., Figure 4C). Our observation that the import of misfolded proteins into mitochondria is reduced under these conditions simply suggests that this reduction is not due to a lack of membrane potential. This is not in any way contradictory to our 2017 finding that misfolded protein import requires membrane potential (ref. 10).

Again, the accumulation of misfolded proteins in mitochondria, especially the model protein FlucSM, has been validated by using super resolution imaging (Figure 1—figure supplement 1A) in addition to the protease protection assay in our 2017 study.

Introduction and Discussion:

Both are really short, too short in my view. Please provide some background of the general principals of mitochondrial protein import and information of how exactly translocation of cytosolic, aggregated proteins (lacking targeting information) is supposed to work. I do not understand exactly how the authors actually envisage the process.

We thank the reviewer for the suggestion. In the revised manuscript, we have extended both Introduction (Page 2-3) and Discussion section (Page 11-13)

The results from the 2022 eLife paper (Liu et al, 2022), which suggests that Tom70 may "regulate both the transcription/biogenesis and import of mitochondrial proteins so the nascent mitochondrial proteins do not compromise cytosolic proteostasis or cause cytosolic protein aggregation" should be discussed with regard to the data obtained with overexpression of the Tom70 soluble domain.

We thank the reviewer for pointing out that study and we have included a brief comment in Discussion section (Page 12: line 13-16). As the function of Tom70 appears to be complex, we cannot exclude the possibility that overexpression of the cytosolic domain has additional or indirect effects in addition to that due to preprotein binding.

Andreasson, C., Ott, M., and Buttner, S. (2019). Mitochondria orchestrate proteostatic and metabolic stress responses. EMBO Rep 20, e47865.

Barrett, L., Orlova, M., Maziarz, M., and Kuchin, S. (2012). Protein kinase A contributes to the negative control of Snf1 protein kinase in Saccharomyces cerevisiae. Eukaryot Cell 11, 119-128.

Hubscher, V., Mudholkar, K., Chiabudini, M., Fitzke, E., Wolfle, T., Pfeifer, D., Drepper, F., Warscheid, B., and Rospert, S. (2016). The Hsp70 homolog Ssb and the 14-3-3 protein Bmh1 jointly regulate transcription of glucose repressed genes in Saccharomyces cerevisiae. Nucleic Acids Res. 44, 5629-5645.

Liu, Q., Chang, C.E., Wooldredge, A.C., Fong, B., Kennedy, B.K., and Zhou, C. (2022). Tom70-based transcriptional regulation of mitochondrial biogenesis and aging. Elife 11

Pfanner, N., Warscheid, B., and Wiedemann, N. (2019). Mitochondrial proteins: from biogenesis to functional networks. Nat Rev Mol Cell Biol 20, 267-284.

Ruan, L., Zhou, C., Jin, E., Kucharavy, A., Zhang, Y., Wen, Z., Florens, L., and Li, R. (2017). Cytosolic proteostasis through importing of misfolded proteins into mitochondria. Nature 543, 443-446.

I prefer to have "all in one", also due to time limitation.

It would be great to be able to upload the review file as otherwise formatting and symbols get lost.

Reviewer #3 (Public Review):

In this study, Wang et al extend on their previous finding of a novel quality control pathway, the MAGIC pathway. This pathway allows misfolded cytosolic proteins to become imported into mitochondria and there they are degraded by the LON protease. Using a screen, they identify Snf1 as a player that regulates MAGIC. Snf1 inhibits mitochondrial protein import via the transcription factor Hap4 via an unknown pathway. This allows cells to adapt to metabolic changes, upon high glucose levels, misfolded proteins an become imported and degraded, while during low glucose growth conditions, import of these proteins is prevented, and instead import of mitochondrial proteins is preferred.

This is a nice and well-structured manuscript reporting on important findings about a regulatory mechanism of a quality control pathway. The findings are obtained by a combination of mostly fluorescent protein-based assays. Findings from these assays support the claims well.

While this study convincingly describes the mechanisms of a mitochondria-associated import pathway using mainly model substrates, my major concern is that the physiological relevance of this pathway remains unclear: what are endogenous substrates of the pathway, to which extend are they imported and degraded, i.e. how much does MAGIC contribute to overall misfolded protein removal (none of the experiments reports quantitative "flux" information). Lastly, it remains unclear by which mechanism Snf1 impacts on MAGIC or whether it is "only" about being outcompeted by mitochondrial precursors.

We thank Reviewer 3 for the positive and encouraging comments on our manuscript. We agree with the reviewer that identifying MAGIC endogenous substrates and understanding what percentage of them are degraded in mitochondria are very important issues to be addressed. We are indeed carrying out projects to address these questions. We also agree with Reviewer 3 that the effect of Snf1 on MAGIC may have additional mechanisms in addition to precursors competition, such as Tom6 mediated conformational changes of TOM pores. In the revised manuscript, we had added a discussion to address these comments (Page 12: line 21-28).

Reviewer #3 (Recommendations For The Authors):

1. In their screen, the authors utilize differences in GFP intensity as a measure for import efficiency. However, reconstitution of the GFP from GFP1-10 and GFP11 in the matrix might also be affected (folding factors, differential degradation).

Upon Snf1 activation, the protein abundance of mitochondrial chaperones such as Hsp10, Hsp60, and Mdj1, and mitochondrial proteases such as Pim1 are not significantly changed (ref. 35). Therefore, it is unlikely that the folding and degradation capacity of mitochondrial matrix is drastically affected by Snf1 activation.

To examine the effect of Snf1 activation on spGFP reconstitution, Grx5 spGFP strain was constructed in which the endogenous mitochondrial matrix protein Grx5 was C-terminally tagged with GFP11 at its genomic locus, and GFP1-10 was targeted to mitochondria through cleavable Su9 MTS (MTS-mCherryGFP1-10) (ref. 10). Only modest reduction in Grx5 spGFP intensity was observed in LG compared to HG, and no significant difference after adjusting the GFP1-10 abundance (spGFP/mCherry ratio) (Figure 1— figure supplement 3A-D). These data suggest that any effect on spGFP reconstitution is insufficient to explain the drastic reduction of MP accumulation in mitochondria under Snf1 activation. Overall, our results demonstrate that Snf1 activation primarily prevents mitochondrial accumulation of MPs, but not that of normal mitochondrial proteins. (Page 6: line 17-25).

We admit, however, that to fully rule out these factors, specific intra-mitochondrial folding or degradation reporter assays would be needed.

1. Scoring of protein import always takes place using fluorescence-based assays. These always require folding of the "sensors" in the matrix. An additional convincing approach that would not rely on matrix folding could be pulse chase approaches coupled to fractionation assays and immunoprecipitation.

We thank reviewer 3 for this suggestion. In our previous study, we applied two different biochemical assays: APEX proximity labeling, and mitochondrial fractionation followed by protease protection. Both confirmed the entry of misfolded proteins into mitochondria as observed by using split GFP. As we discussed in response to Reviewer 1’s main point [3], the fractionation assays are not quantitative enough for the comparisons made in our study. In particular, during the over 2-hour assay, misfolded proteins continue to be degraded within mitochondria. By using proper controls, our spGFP system provides quantitative comparisons for mitochondrial accumulation of misfolded proteins in non-disturbed physiological conditions.

1. Could the pathway be reconstituted in vitro with isolated mitochondria to test for the "competition hypothesis"

This is an excellent suggestion, but setting up such a reconstituted system is a project on its own. The study documented in this manuscript already encompasses a large amount of work that we feel should be published timely.

1. Fluorescence figures are not colour blind friendly (red-green). This should be improved by changing the color scheme.

We thank reviewer 3 for pointing this out and sincerely apologize for any inconvenience. However, we are unfortunately unable to change all images within a limited time. We will adopt another color scheme in future work.

1. spGFP in human cells appears to form "spot-like" structures. What are these granules?

We indeed observed granule-like structures by spGFP labeled FUS in mitochondria, which is interesting, but we did not investigate this further because it is a not a focus of this study.

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Reply to the reviewers

Overall, we were pleased that the reviewers found our study carefully designed and interesting. We have addressed their comments below.

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

The manuscript by Kern, et al., demonstrates that phagocytosis in macrophages is regulated in part by the intermolecular distance of phagocytosis-promoting receptors engaging phagocytic targets. Cells expressing chimeric receptors containing cytosolic domains of Fc receptors (FcR) and defined ligand-binding DNA domains were used to drive phagocytosis of opsonized glass beads coated with complementary DNA ligands of defined spacing and number. These so-called origami ligands allowed manipulation of receptor spacing following engagement, which allowed the demonstration that tight spacing of ligands (7 nm or 3.5 nm) optimized signaling for phagocytosis. The study is carefully performed and convincing. I have a few technical concerns and minor suggestions.

1. __ It is assumed that the origami preparations were entirely uniform. How much variation was there? Is that supported by TIRF microscopy of origami preparations? Was the TIRF microscopy calibrated for uniformity of fluorescence (ie., shade correction)?__ Our laboratory, Dong et al., has extensively characterized the origami uniformity and robustness of these exact pegboards. This paper was just posted on bioRxiv (Dong et. al, 2021). We have also cited this paper in our revised manuscript in reference to the characterization of the DNA origami (Line 117).

We did not use any shade correction. Instead we only collected data from a central ROI in our TIRF field. To check for uniformity of illumination, we plotted the origami pegboard fluorescent intensity along the x and y axis. We observed very modest drop off in signal - the average signal intensity of origamis within 100 pixels of the edge is 76 ± 6% the intensity of origamis in a 100 pixel square in the center of the ROI. Fitting this data with a Gaussian model resulted in very poor R values. While this may account for some of the variation in signal intensity at individual points, we expect the normalized averages of each condition to be unaffected. We have amended the methods to describe this strategy (Lines 851-854).

(Image could not be uploaded)

__ Likewise, how much variation was there in the expression of the chimeric receptors? Large variation in receptor numbers per cell could significantly alter the quantitative studies. Aside from the flow sorting for cells expressing two different molecules, how were cells selected for analysis?__

We thank the reviewer for bringing up this point. We confirmed comparable receptor expression levels at the cell cortex of the DNA CAR-𝛾 and the DNA CAR-adhesion used throughout the paper. We also have confirmed that receptor levels at the cell cortex were similar for the large DNA CAR constructs used in Figure 6C-D. This data is now included in Figures S5 and S7. We have also altered the text to include this (lines 169-172):

Expression of the various DNA CARs at the cell cortex was comparable, and engulfment of beads functionalized with both the 4T and the 4S origami platforms was dependent on the Fc𝛾R signaling domain (Figure S5).

When quantifying bead engulfment, cells were selected for analysis based on a threshold of GFP fluorescence, which was held constant throughout analysis for each individual experiment. We have amended the “Quantification of engulfment” methods section to convey this (lines 921-923).

__ The scale of the origami relative to the cells is difficult to discern in Figures 2C and D. Additional text would be helpful to indicate, for example, that the spots on the Fig. 2D inset indicate entire origami rather than ligand spots on individual origami particles.__

Thank you for pointing this out, we see how the legend was unclear and have corrected it (lines 453-454), including specifically noting “Each diffraction limited magenta spot represents an origami pegboard.” We have also outlined the cell boundary in yellow to make the cell size more clear.

__ Figure 5 legend, line 482: How was macrophage membrane visualized for these measurements?__

We have added the following clarification (line 535-536): “The macrophage membrane was visualized using the DNA CAR𝛾, which was present throughout the cell cortex.”

__ line 265: "our data suggest that there may be a local density-dependent trigger for receptor phosphorylation and downstream signaling". This threshold-dependent trigger response was also indicated in the study of Zhang, et al. 2010. PNAS.__

The Zhang et al. study was influential in our study design, and we wish to give the appropriate credit. Zhang et al. found that a sufficient amount of IgG is necessary to activate late (but not early) steps in the phagocytic signaling pathway. In contrast, our study addresses IgG concentration in small nanoclusters. We find that this nanoscale density affects receptor phosphorylation. Thus, we think these two studies are distinct and complementary.

Lines 283-287 now read:

While this model has largely fallen out of favor, more recent studies have found that a critical IgG threshold is needed to activate the final stages of phagocytosis (Zhang et al., 2010). Our data suggest that there may also be a nanoscale density-dependent trigger for receptor phosphorylation and downstream signaling.

__ line 55: Rephrase, “we found that a minimum threshold of 8 ligands per cluster maximized FcgR-driven engulfment.” It is difficult to picture how a minimum threshold maximizes something.__

We now state “we found that 8 or more ligands per cluster maximized FcgR-driven engulfment.”

__ line 184: Rephrase, "we created... pegboards with very high-affinity DNA ligands that are predicted not to dissociate on a time scale of >7 hr". Remove "not".__

Thank you for pointing this out, it is now correct.

Reviewer #1 (Significance (Required)):

This study provides a significant advance in understanding about the molecular mechanisms of signaling for particle ingestion by phagocytosis.

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

The manuscript on “Tight nanoscale clustering of Fcg-receptors using DNA origami promotes phagocytosis" studies how clustering and nanoscale spacing of ligand molecules for a chimeric Fcg-receptors influence the phagocytosis of functionalized silicon beads by macrophage cell lines. The basis of this study is the design of a chimeric Fc-receptor (DNA-CARg) comprising an extracellular SNAP-tag domain that can be loaded with single-stranded (ss) DNA, the transmembrane part of CD86 and the cytosolic part of the Fc-receptor g-chain containing an immunoreceptor tyrosine-based activation motif (ITAM) as well as a C-terminal green fluorescent protein (GFP). As control the authors used a similar designed DNA-CAR that is lacking the intracellular ITAM-containing FCg tail. The chosen target for this chimeric DNA-CAR, are silicon beads covered by a lipid bilayer that contains biotin-labelled lipids that, via Neutravidin, can be loaded with a biotinylated DNA origami pegboard displaying complimentary ss-DNA as ligand for the DNA-CAR. The DNA origami pegboard contains four ATTO647N fluorescence for visualization and the ssDNA ligand in different quantities and spacing. Using these principles, the authors study how ligand affinity, concentration and spacing influence the activation of the DNA-CARg and the engulfment of the loaded beads.

The authors show that bead engulfment is increased between 2 till 8 ssDNA ligands on the pegboard. After this, ligand numbers do not play a role anymore in the engulfment. They then study the role of the ligand spacing using pegboards that either contain 4 single strand DNA ligands in close (7nm/3,5nm) proximity or a more spaced version using 21/17,5 nm or 35/38,5 nm. The authors find that the bead engulfment is maximally and positively affected by the close spacing of the ssDNA ligands. In their final experiments the authors vary the design of the DNA-CARs by tetramerization of the ITAM-containing Fcg-signaling subunit. In their discussion the authors mention different possibilities for the effect of spacing on the engulfment process.

I think that, in general, this is an interesting study. However, it has some caveats and open issues that should be clarified before its publication.

**Major comments**

1. __ As a general comment, it is somewhat a pity that the authors did not use the endogenous FcR as a control. It would have been quite easy for the authors to place the SNAP-tag domain on the Fcg extracellular domain which would allow to do all their experiments in parallel, not only with the DNA-CAR, but also with a DNA-containing wild type receptor. Such a control would be important because, by using a CD86 transmembrane domain, the authors do not know whether the nanoscale localization of their chimeric receptors is reflecting that of the endogenous Fcg receptor.__

We agree with the reviewer completely. We have repeated experiments shown in Figure 4A with a DNA-CAR containing the Fc𝛾 transmembrane domain instead of CD86 as the reviewer suggests. We also included a DNA-CAR version of the Fc𝛾R1 alpha chain, although this construct was not expressed as well as the others. These data are now included in Figure S5, and referenced in lines 167-168.

__ An important issue that is discussed by the authors but not addressed in this manuscript is whether the different amount and spacing of the ligand is only impacting on signaling or also on the mechanical stress of the cells. Indeed, mechanical stress on the cytoskeleton arrangement could influence the engulfment process. For this, it would be very important to test that the different bead engulfment, for example, those shown in Fig. 4, is strictly dependent on signaling kinases. The authors should repeat the experiment of Fig. 4 a and b in the presence or absence of kinase inhibitors such as the Syk inhibitor R406 or the Src inhibitor PP2 to show whether the different phase of engulfment is dependent on the signaling function of these kinases. This crucial experiment is clearly missing from their study.__

We agree this is an interesting point. We find that ligand spacing affects receptor phosphorylation; however this does not preclude effects on downstream aspects of the signaling pathway. We will clarify this by adding the following comment to the manuscript (line 299-301):

While our data pinpoints a role for ligand spacing in regulating receptor phosphorylation, it is possible that later steps in the phagocytic signaling pathway are also directly affected by ligand spacing.

The DNA-CAR-adhesion in Figure 1 strongly suggests that intracellular signaling is essential for phagocytosis. We have now included additional controls using this construct as detailed in our response to point 3 below. Unfortunately, Src and Syk inhibitors or knockout abrogate Fc𝛾R mediated phagocytosis (for example, PMIDs 11698501, 9632805, 12176909, 15136586) and thus would eliminate phagocytosis in both the 4T and 4S conditions. This precludes analysis of downstream steps in the phagocytic signaling pathway.

__ Another problem of this study is that the authors show in Fig. 1A the control DNA-CAR-adhesion but then hardly use it in their study. For example, the crucial experiments shown in Fig. 4 should be conducted in parallel with DNA-CAR-adhesion expressing macrophage cells. This study could provide another indication whether or not ITAM signaling is important for the engulfment process.__

We have added this control. It is now included in Figure S5 and S7. Figure 3D also shows that the DNA-CAR-adhesion combined with the 4T origami pegboards does not activate phagocytosis and we have amended the text to make this more clear (line 152).

__ Another important aspect is how the concentration of the loaded origami pegboard is influencing the engulfment process. In particular, it would be interesting to show the padlocks with different spacings such as the 4T closed spacing versus 4s large spacing show a different dependency on the concentration of this padlock loading on the beads. This would be another important experiment to add to their study.__

We agree that this is an interesting question. We suspect that at a very high origami density, 4S signaling would improve, and potentially approach the 4T. However, we are currently coating the beads in saturating levels of origami pegboards. Thus we cannot increase origami pegboard density and address this directly.

**Minor comments:**

1. __ The definition of the ITAM is Immunoreceptor Tyrosine-based Activation Motif and not "Immune Tyrosine Activation Motif" as stated by the authors.__ We have corrected this.

__ The authors discuss that it is the segregation of the inhibitory phosphatase CD45 from the clustered Fc receptors is the major mechanism explaining their finding that 4T closed spacing is more effective than 4s large spacing. With the event of the CRISPR/Cas9 technology it is trivial to delete the CD45 gene in the genome of the RAW264.7 macrophage cell line used in this study and I am puzzled why they author are not conducting such a simple but for their study very important experiment (it takes only 1-2 month to get the results).__

This experiment may be informative but we have two concerns about its feasibility. First, CD45 is a phosphatase with many different roles in macrophage biology, including activating Src family kinases by dephosphorylating inhibitory phosphorylation sites (PMID 8175795, 18249142, 12414720). Second, CD45 is not the only bulky phosphatase segregated from receptor nanoclusters. For example, CD148 is also excluded from the phagocytic synapse (PMID 21525931). CD45 and CD148 double knockout macrophages show hyperphosphorylation of the inhibitory tyrosine on Src family kinases, severe inhibition of phagocytosis, and an overall decrease in tyrosine phosphorylation (PMID 18249142). CD45 knockout alone showed mild phenotypes in macrophages. We anticipate that knocking out CD45 alone would have little effect, and knocking out both of these phosphatases would preclude analysis of phagocytosis. Because of our feasibility concerns and the lengthy timeline for this experiment, we believe this is outside of the scope of our study.

In our discussion, we simplistically described our possible models in terms of CD45 exclusion, as the mechanisms of CD45 exclusion have been well characterized. This was an error and we have amended our discussion to read (lines 335-343):

As an alternative model, a denser cluster of ligated receptors may enhance the steric exclusion of the bulky transmembrane proteins like the phosphatases CD45 and CD148 (Bakalar et al., 2018; Goodridge et al., 2012; Zhu, Brdicka, Katsumoto, Lin, & Weiss, 2008).

Reviewer #2 (Significance (Required)):

The innovative part of this study is the combination of SNAP-tag attached, chimeric Fc-receptor with the DNA origami pegboard technology to address important open question on receptor function.

**Referees cross-commenting**

I find most of my three reviewing colleagues reasonable

I also agrée to Reviewer #1 comments 2

Likewise, how much variation was there in the expression of the chimeric receptors? Large variation in receptor numbers per cell could significantly alter the quantitative studies. Aside from the flow sorting for cells expressing two different molecules, how were cells selected for analysis?

But I want to add it is not only the amount of receptors but ils the nanoscale location that is key to receptor function

We have ensured that all receptors are trafficked to the cell surface. We have also measured their intensity at the cell cortex as discussed in response to Reviewer 1.

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

This is a very nicely done synthetic biology/biophysics study on the effect of ligands spacing on phagocytosis. They use a DNA based recognition system that the group has previously use to investigate T cell signaling, but express the SNAP tag linked transmembrane receptor in a macrophage cell line and present the ligands using DNA origami mats to control the number and spacing of complementary ligands that are designed to be in the typical range for low or high affinity FcR, a receptor that can trigger phagocytosis. The study offers some very nice quantitative data sets that will be of immediate interest to groups working in this area and, in the future, for design of synthetic receptors for immunotherapy applications. Other groups are working on similar platform for TCR. I don't feel there is any need for more experiments, but I have some questions and suggestions. Answering and considering these could clarify the new biological knowledge gained.

We thank the reviewer for their support of our manuscript. Given the reviewer’s statement that no new experiments are required, we have answered their questions to the best of our ability given the current data. Should the editor decide that any of these topics require experimental data to enhance the significance of the paper, we are happy to discuss new experiments.

Reviewer #3 (Significance (Required)):

I think the significance would be increased by addressing these questions, that would help understand how the synthesis system described related to other system directed as similar questions and more natural settings.

1. __ The densities of the freely mobile DNA ligands required to trigger phagocytosis is quite high. Was the length of the DNA duplexes optimized? The entire complex for both the intermediate and high affinity duplexes seems quite short, perhaps The extracellular domain of the DNA-CAR (SNAP tag and ssDNA strand) are approximately 10 nm (PMID 28340336). The biotinylated ligand ssDNA is attached to the bilayer via neutravidin, resulting in a predicted 14 nm intermembrane spacing. The endogenous IgG FcR complex is 11.5 nm. Bakalar et al (PMID 29958103) tested the effect of antigen height on phagocytosis and found that the shortest intermembrane distance tested (approximately 15 nm) was the most effective. As the reviewer notes, the optimal distance between macrophage and target may be larger than our DNA-CAR. However we think the intermembrane spacing in our system is within the biologically relevant range.

We saw robust phagocytosis at 300 molecules/micron of ssDNA, which is similar to the IgG density used on supported lipid bilayer-coated beads in other phagocytosis studies (PMID 29958103, 32768386). As the reviewer noticed, this is significantly higher than ligand density necessary to activate T cells (PMID 28340336). We have added a comment on ligand density to lines 96-97.

__ Are the origami mats generally laterally mobile on the bilayers. If so, what is the diffusion coefficient? Can one detect the mats accumulating in the initial interface between the bead and cell, particularly in cased where there is no phagocytosis? Would immobility of the mats make them more efficient at mediating phagocytosis compared to the monodispersed ligands, which I assume are highly mobile and might even be "slippery".__

We have confirmed that our bead protocol generally produces mobile bilayers, where his-tagged proteins can freely diffuse to the cell-bead interface (see accumulation of a his-tagged FRB binding to a transmembrane FKBP receptor at the cell-bead synapse below). We can qualitatively say that the origamis appear mobile on a planar lipid bilayer (see Dong et. al 2021 and images below). Directly measuring the diffusion coefficient on the beads is extremely difficult because the beads themselves are mobile (both diffusing and rotating), and cannot be imaged via TIRF. We do not see much accumulation of the origami at cell-bead synapses. This could reflect lower mobility of the origamis, or could be because the relative enrichment of origamis is difficult to detect over the signal from unligated origamis.

Overall, we expect the origami pegboards (tethered by 12 neutravidins) are less mobile than single strand DNA (tethered by a single neutravidin, supported by qualitative images below). We are uncertain whether this promotes phagocytosis. At least one study suggests that increased IgG mobility promotes phagocytosis (PMID 25771017). However, the zipper model would suggest that tethered ligands may provide a better foothold for the macrophage as it zippers the phagosome closed (PMID 14732161). Hypothetically, ligand mobility could affect signaling in two ways - first by promoting nanocluster formation, and second by serving as a stable platform for signaling as the phagosome closes. Since our system has pre-formed nanoclusters, the effect of ligand mobility may be quite different than in the endogenous setting.

(Image could not be uploaded)

In the above images, a 10xHis-FRB labeled with AlexaFluor647 was conjugated to Ni-chelating lipids in the bead supported lipid bilayer. The macrophages express a synthetic receptor containing an extracellular FKBP and an intracellular GFP. Upon addition of rapamycin, FRB and FKBP form a high affinity dimer, and FRB accumulates at the bead-macrophage contact sites.

(Image could not be uploaded)

In the above images, single molecules were imaged for 3 sec. The tracks of each molecule are depicted by lines, colored to distinguish between individual molecules. The scale bar represents 5 microns in both panels.

__ Breaking down the analysis into initiation and completion is interesting. When using the non-signalling adhesion constructs, would they get to the initiation stage or would that attachment be less extensive than the initiation phase.__

This is an interesting question. While we did not include the DNA-CAR-adhesion in our kinetic experiments, we have now quantified the frequency of cups that would match our ‘initiation’ criteria in 3 representative data sets where macrophages were fixed after 45 minutes of interaction with origami pegboard-coated beads. We found that an average of 16/125 of 4T beads touching DNA-CAR-adhesion macrophages met the ‘initiation’ criteria and an average of 2/125 were eaten (14% total). In comparison, we examined 4T beads touching DNA CAR𝛾 macrophages and found that on average 23/125 met the ‘initiation’ criteria, and 45/125 were already engulfed (54%). This suggests that the DNA-CAR-adhesion alone may induce enough interaction to meet our initiation criteria, but without active signaling from the FcR this extensive interaction is rare. We have added this data in a new Figure S6 and commented on this in lines 213-215.

__ It would be interesting to put these results in perspective of earier work on spacing with planar nanoarrays, although these can't be applied to beads. For integrin mediated adhesion there was a very distinct threshold for RGD ligand spacing that could be related to the size of some integrin-cytoskeletal linkers (PMID: 15067875). On the other hand, T cell activation seemed more continuous with changes in spacing over a wide range with no discrete threshold (PMID: 24117051, 24125583) unless the spacing was increased to allow access to CD45, in which case a more discrete threshold was generated (PMID: 29713075). The results here for phagocytosis with the very small ligands that would likely exclude CD45 seems to be more of a continuum without a discrete threshold, although high densities of ligand are needed. This issue of continuous sensing vs sharp threshold is biologically interesting so would be good assess this by as consistent standards are possible across systems.__

We agree that this is an interesting body of literature worth adding to our discussion. We have added a paragraph that puts our study in the context of prior work on related systems, including these nanolithography studies (Line 364-382):

How does the spacing requirements for Fc𝛾R nanoclusters compare to other signaling systems? Engineered multivalent Fc oligomers revealed that IgE ligand geometry alters Fcε receptor signaling in mast cells (Sil, Lee, Luo, Holowka, & Baird, 2007). DNA origami nanoparticles and planar nanolithography arrays have previously examined optimal inter-ligand distance for the T cell receptor, B cell receptor, NK cell receptor CD16, death receptor Fas, and integrins (Arnold et al., 2004; Berger et al., 2020; Cai et al., 2018; Deeg et al., 2013; Delcassian et al., 2013; Dong et al., 2021; Veneziano et al., 2020). Some systems, like integrin-mediated cell adhesion, appear to have very discrete threshold requirements for ligand spacing while others, like T cell activation, appear to continuously improve with reduced intermolecular spacing (Arnold et al., 2004; Cai et al., 2018). Our system may be more similar to the continuous improvement observed in T cell activation, as our most spaced ligands (36.5 nm) are capable of activating some phagocytosis, albeit not as potently as the 4T. Interestingly, as the intermembrane distance between T cell and target increases, the requirement for tight ligand spacing becomes more stringent (Cai et al., 2018). This suggests that IgG bound to tall antigens may be more dependent on tight nanocluster spacing than short antigens. Planar arrays have also been used to vary inter-cluster spacing, in addition to inter-ligand spacing (Cai et al., 2018; Freeman et al., 2016). Examining the optimal inter-cluster spacing during phagosome closure may be an interesting direction for future studies.

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Additional experiments performed in revision

In addition to these reviewer comments, we have added additional controls validating the DNA-CAR-4x𝛾 used in Figure 6c,d. We compared the DNA-CAR-4x𝛾 to versions of the DNA-CAR-1x𝛾-3x𝛥ITAM construct with the functional ITAM in the second and fourth positions (see the schematics now included Figure S7). We found that four individual receptors with a single ITAM each were able to induce phagocytosis regardless of which position the ITAM was in. However the DNA-CAR-4x𝛾 construct, which also contains 4 ITAMs, was not. This further validates the experiment presented in 6c,d. We also fixed minor errors we discovered in the presentation of data for Figures 1C and S1A.

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Reply to the reviewers

Manuscript number: RC-2023-02157

Corresponding author(s): Satish, Mishra

1. General Statements [optional]

We thank the editor and reviewers for their helpful comments. We have successfully addressed most of the comments. We are performing some additional experiments as suggested by the reviewers and will be included if considered further. We attempted to pulldown the S14 interacting partner using anti-mCherry antibody from S14-3XHA-mCherry transgenic sporozoites and then further tried to identify interactome using mass spectrometry but failed. So, accordingly, we have toned down the conclusion.

The point-by-point response to the reviewer’s comments is given as follows.

2. Description of the planned revisions

Reviewer #1:

Figure 1F You have not formally shown that this signal corresponds to palmitoylated S14. Could be heavy chain. Response: The possibility of a heavy chain is negligible because we have used sporozoite samples and probed it with an anti-rabbit antibody conjugated to HRP. Also, the size of the S14 bands does not correspond to heavy chain. However, we have toned down the conclusion. Currently, we are performing the depalmitoylation experiment, and data will be included in the next round of revision.

Reviewer #2

Line 149: To definitively state S14 is a membrane protein, biochemical assays proving such should be performed. (or perhaps genetic mutation of the predicted palmitoylation site?) Otherwise, this should be rephrased. Response: We are performing the depalmitoylation assay, and the data will be included during the second round of revision. However, we have rephrased the sentence in the current version of the manuscript.

Lines 257-258: for yeast 2-hybrid, the controls of expressing S14, GAP45 and MTIP together with control proteins where no interaction would be predicted are absent. Response: We are performing experiments with additional controls, and data will be included in the next round of revision.

Reviewer #3

Conclusions that S14 knockout does not impact the expression and organization of two surface proteins, CSP and TRAP, and two IMC rely on a qualitative analysis only. However, quantitative analysis to support their observations is missing. Response: We are quantifying the IFA images and data will be included in the next round of revision.

3. Description of the revisions that have already been incorporated in the transferred manuscript

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

Summary: The authors have identified a sporozoite gliding motility protein through bioinformatic analysis. From the main text I do not know how, or what bioinformatic analysis was performed, in order to focus on this protein which is called S14. The authors then go on to tag the protein, produce a KO and show its involvement in gliding motility. The KO shows that parasites lacking S14 fail to invade the mosquito salivary glands. This is due to a motility defect. Y2H and docking studies are used to define an interaction with MTIP and GAP45, two known components of the glideosome. Response: We identified this gene from the Kaiser et al., 2004 paper (DOI: 10.1046/j.1365-2958.2003.03909.x). The S14 was found to be highly upregulated in salivary gland sporozoites but lacked signal sequence and transmembrane domain. Next, we looked into other sporozoite proteins lacking signal sequence and transmembrane domain and found several gliding-associated proteins with similar properties. By using the guilt-by-association principle (DOI: 10.1186/gb-2009-10-4-104), we studied the following properties of existing glideosome components along with S14: (1) Classical pathway secretion using the signal peptide (SignalP, https://services.healthtech.dtu.dk/services/SignalP-5.0) (http://dx.doi.org/10.1016/j.jmb.2004.05.028). (2) Nonclassical pathway secretion (SecretomeP , https://services.healthtech.dtu.dk/services/SecretomeP-1.0/) (10.1093/protein/gzh037). (3) Presence of transmembrane domains (TMHMM , https://services.healthtech.dtu.dk/services/TMHMM-2.0/) (10.1006/jmbi.2000.4315). (4) Presence of a potential palmitoylation site (CSS-Palm, http://bioinformatics.lcd-ustc.org/css_palm) (Ren et al, 2008). This is a similar association prediction method as employed by the STRING database. However, mentioning that we identified a gliding motility protein by bioinformatic analysis was wrong, and we modified the sentence.

Major comments: The paper is sometimes hard to follow and lacks clarity. The reason: important information is omitted, or explained at the end of a section rather than at first mention; experimental details that are of essence need to be mentioned or explained in the main text; there is ample use of the word 'bioinformatic' without explaining what kind of analysis was performed in the main text. I cite from the abstract: 'In silico analysis of a novel protein, S14, which is uniquely upregulated in salivary gland sporozoites, suggested its association with glideosome-associated proteins.' I cite from the introduction: 'A study comparing transcriptome differences between sporozoites and merozoites using suppressive subtraction hybridization found several genes highly upregulated in sporozoites and named them 'S' genes (Kaiser et al, 2004). We narrowed it down to a candidate named S14, which lacked signal peptide and transmembrane domains.' From reading the main text, I do not know why Plasmodium berghei S14 was chosen in this manuscript. S14 is one of 25 transcripts identified by Kappe et al in Plasmodium yoelii (https://doi.org/10.1046/j.1365-2958.2003.03909.x) to be upregulated in sporozoites. The material and methods section does not explain either why S14 was chosen. Perhaps the authors could update Figure 2 from Kappe et al with the most recent annotations from plasmodb. Response: We have edited the manuscript for clarity and mentioned the name of the bioinformatic analysis performed. We chose S14 from Kaiser et al., 2004 (https://doi.org/10.1046/j.1365-2958.2003.03909.x) that identified transcripts in P. yoelii. We work on the rodent malaria parasite P .berghei and validated S14 transcripts by qPCR which showed its upregulation in sporozoites.

Rodent malaria parasites P. berghei and P. yoelii have been used extensively as models of human malaria. Both species have been widely used in studies on the biology of Plasmodium sporozoites and liver stages due to the availability of efficient reverse genetics technologies, and the ability to analyze these parasites throughout the life cycle stages have made these two species the preferred models for the analysis of Plasmodium gene function. A genetic screen and phenotype analysis were performed in P. berghei (DOI: 10.1016/j.cell.2017.06.030 and DOI: 10.1016/j.cell.2019.10.030) that makes in-depth characterization easier due to the availability of reagents and preliminary gene-phenotype like its dispensability in the blood. As suggested by this reviewer, we have updated the most recent annotations from PlasmoDB.

Reproducibility: None of the main Figures or Figure legends define ' N = '. For example I cite: 'The S14 KO clonal lines were first analyzed for asexual blood-stage propagation, and for this, 200 µl of iRBCs with 0.2% parasitemia was intravenously injected into a group of mice.' There are 2 mentions of 'N=' in the supplementary figures. I have not found any others.

I'm not sure what the convention is. Should unpublished data for this gene (PBANKA_0605900) found in pberghei.eu (a database for mutant berghei parasites) be cited? After all it confirms their findings.

The authors need to use more recent references for some of their statements; see some comments below. __Response: __We have mentioned N in the figures legends of the revised manuscript and also mentioned the unpublished data of RMGM. We have also added recent references in the revised manuscript.

Minor comments:

line 1-2 Add the Plasmodium species of this study.

Response: Added.

abstract Which species do you work with?

Response: We have mentioned P. berghei in the abstract of the revised manuscript.

29 mosquito salivary glands and human host hepatocytes

Response: Corrected.

30 to the glideosome, a protein complex containing [...]

Response: Corrected.

32-33 What kind of in silico analysis suggested S14 is part of the glideosome? S14 is not uniquely upregulated; there are other S-type genes identified by Kappe and Matuschewski. 25 I believe.

Response: Mentioning that in silico analysis suggested S14 is part of the glideosome was a wrong statement, and we have modified the sentence for clarity in the revised manuscript.

32 Please point out he species were S genes were identified. SGS of which species?

Response: The S genes were identified in the transcriptomic study of Plasmodium yoelii.

34 expression: change to transcription

Response: Changed.

39 What kind of in silico analysis was used here? and therefore malaria transmission

__Response: __In silico, protein-protein docking interaction analysis was used.

55 A single zygote transforms into a single ookinete, which establishes a single oocyst, which in turn can produce thousands of midgut sporozoites. Please correct the life cycle passage.

Response: Corrected. located or anchored in the IMC? And located between the IMC and plasma membrane?

Response: Glideosome is located between the plasma membrane and IMC, and the same has been corrected in the revised manuscript.

61-63 Refer to Table S1 and its contents here 64 Name the known GAPs. Response: Done.

65-67 Which transmembrane domain proteins? Please add more recent references than King 1988.

Response: We have added TRAP as a transmembrane domain protein and updated the reference.

71-72 TRAP was the first protein found to be ...

Response: Corrected.

74-76 Add additional, more recent references: for example search Frischknecht and TRAP

Response: Added.

76 S6 (TREP) is also [...]

Response: Done.

88 Some of these proteins are also expressed in ookinetes.

Response: Corrected.

89-91 The sentence needs a verb.

Response: Added.

88-96 Please add some more recent glideosome papers. After 2013.

Response: Added.

91 Why do you call it a peripheral protein?

Response: Because the GAP45 was detected at the periphery of the merozoite in P. falciparum. As there are no such reports in sporozoites hence we have removed peripheral in the revised manuscript.

91-93 There are more recent citations for GAP45 and GAP50. Response: We have added recent citations.

96 Insert a reference here.

Response: Added.

99 Please define the gliding-associated proteins. What are they? Aren't there papers on GAP40, 45 and 50? DOI: 10.1016/j.chom.2010.09.002

Response: Done.

99 .... What prompted you to identify a novel GAP? And why is S14 classified as a GAP?

Response: This was a wrong statement, which we removed in the revised manuscript.

99-102 What kind of bioinformatic study? Why was S14 chosen? Please outline how you ended up with S14. Any other proteins that came out of the bioinformatic screen from the list of S genes?

Response: We identified S14 from the Kaiser et al., 2004 paper and analyzed its properties using the “guilt-by-association” principle. The analysis showed that S14 had properties similar to GAP45 and MTIP. The S14 upregulation in sporozoites and its properties similar to known GAPs, we were prompted to study this gene's function.

How many proteins were identified in the screen for sporozoite upregulated proteins by Kappe and Matuschewski?

Response: 25 genes were identified in that paper, including the two characterized genes CSP and TRAP during that study.

102-103 Define the nonclassical secretion pathway. Please reference GAP45 and GAP50 data for the nonclassical pathway.

Response: When proteins are secreted out of the cytosol without predictable or known signal sequences or secretory motifs are classified as non-classically secreted proteins, and the pathway is called a non-classical protein secretory pathway. References: https://doi.org/10.1371/journal.pone.0125191; https://doi.org/10.1016/S0171-9335(99)80097-1; doi: 10.3389/fmicb.2016.00194

105 Please add P. berghei to the title, the abstract, the introduction.

Response: Added.

111 The results section does not outline what bioinformatic analysis was used

Response: The guilt-by-association principle was used, and it is outlined in the revised manuscript.

112-114 Please specify the exact number of upregulated in sporozoites genes. I think it was 25. And add the species the study was performed in. Why did you choose the Kappe study but not the uis genes from berghei?

Response: It was 25, and the species was P. yoellli. The domains of all 25 proteins are shown in Figure 2 of Kappe study. It intrigued us after having a glance at it. Later, we confirmed the upregulation of S14 transcripts in P. berghei sporozoites and chose to study the function of this gene.

114-115 How did you narrow it down to S14? The Kappe paper lists 25 S-type genes from P. yoelii.

Response: The domains of all 25 proteins are shown in the Kappe study. Two proteins, S14 and S15, lack signal sequence and transmembrane domain, which intrigued us after glancing at them. We chose S14 because its microarray induction is higher compared to S15.

118 Plasmodia is not the plural for a group of different Plasmodium species. Use: [...] conserved among Plasmodium spp.

Response: Corrected.

118-119 Which proteins did you analyze? And how did you analyze them? Where is the data for this analysis? Outline the amino acids that predict palmitoylation? The nonclassical pathway?

Response: The proteins we analyzed are given in Table S1. We analyzed them by the guilt-by-association principle. The data for this analysis is shown in Table S1. The amino acids predicted to be palmitoylated are C59 and C228 (S14), C5 (GAP45), C8 and C5 (MTIP). Non-classical pathway secretion was predicted by SecretomeP ( 10.1093/protein/gzh037).

119-122 Here: do you mean S14 has similar properties as GAP 45 and GAP50? Define the nonclassical pathway? How do you know S14 is in the IMC?

Response: The similar properties of S14 and GAP45 are Signal Peptide Prediction, Prediction of Non-classical pathway secretion, number of predicted transmembrane domains and prediction of Palmitoylation signal. GAP50 was wrongly mentioned here and has been removed from the revised manuscript.

When proteins are secreted out of the cytosol without predictable or known signal sequences or secretory motifs are classified as non-classically secreted proteins. The pathway is called a non-classical protein secretory pathway.

Our colocalization data of S14 with GAP45 and MTIP indicated that S14 is in the IMC.

122-123 Please reference the bioinformatic analysis plus URL that allows targeting to the IMC to be analyzed.

Response: All the URLs with references are given in the method section, lines 348-358 in the revised manuscript.

123-124 Please reference the URLs for TM, palmitoylation, and interactions analyses.

Response: All URLs with references are given in the method section, lines 348-358 in the revised manuscript.

125-127 How did you predict that S14 is secreted via the nonclassical pathway?

Response: We predicted non-classical pathway secretion of S14 using - SecretomeP (https://services.healthtech.dtu.dk/services/SecretomeP-1.0/) (10.1093/protein/gzh037).

128-130 Define the nonclassical pathway when it first appears in your manuscript.

The citation Moskes 2004 is not in the reference list

Response: The nonclassical pathway is defined in lines 105-107. The citation Moskes 2004 has been included in the revised manuscript.

132 Which membrane?

Response: Live S14-mCherry localization on the membrane does not differentiate between the outer membrane or IMC. Hence, only membrane is mentioned. Next, in Figure 4A, we confirmed S14 localization on IMC by treating sporozoites with Triton X-100 and colocalizing with IMC proteins GAP45 and MTIP.

134-135 In which species?

Response: We have mentioned P. berghei in the text in the revised manuscript.

141-142 Please include images of blood stage and liver stage parasites.

Response: Blood and liver stage images are included in the revised manuscript as Figure S2.

142-143 Which membrane?

Response: Live S14-mCherry localization on the membrane does not differentiate between the outer membrane or IMC. Hence, only membrane is mentioned. Next, in Figure 4A, we confirmed S14 localization on IMC by treating sporozoites with Triton X-100 and colocalizing with IMC proteins GAP45 and MTIP.

148-149 I cannot find the specific figure you refer to; I checked the online version of the Frenal 2010 paper.

Response: Electromobility shifts of GAP45 due to the palmitoylation have been reported in (Rees-Channer et al, 2006; DOI: 10.1016/j.molbiopara.2006.04.008). Frenal 2010 paper has stated about two bands but experimentally, it was shown in Rees-Channer et al, 2006 in Figures 1 and 2B.

175 gland, we counted [...]

Response: Corrected.

177 Compared to the

Response: Corrected.

177-179 Failed to invade (absolutely)? Or invaded in highly reduced numbers?

Response: Corrected.

182-186 Please be precise: I think you mean you let all types of mosquitoes take a blood meal; s14 knockout-infected mosquitoes did not infect mice.

Response: Corrected.

181-202 Perhaps use paragraphs to indicate the different types of experiments performed here.

Response: Done.

204 Please introduce paragraphs to identify the different experiments in this section

Response: Done.

208 Outer or inner membrane of what? IMC, the plasma membrane?

Response: We treated sporozoites with Triton X-100 to analyze whether S14 is present on the outer membrane (plasma membrane) or IMC.

228 onwards Structural models were obtained from whom? Which species did you use for the docking study? Could you use in one approach 3 berghei proteins, and confirm your docking studies with the falciparum proteins? That would strengthen your model. Should you include a negative control protein in the approach? Response: The structural models were obtained using the trROSETTA server. We used P. berghei for the docking study. In the old annotation and RMGM, the ortholog of P. berghei (PBANKA_0605900) in P.falciparum (PF3D7_1207400) was indicated. However, the updated PlasmodDB does not show PBANKA_0605900 ortholog in P. falciparum. We did try to generate structure models of P. falciparum MTIP, GAP45 and S14 using the trROSETTA server. We successfully reproduced the structure of MTIP, and GAP45 but the quality of S14 structure was unsuitable for the interaction studies. The negative control cannot be included in this kind of study because it gives a false interface, and none of the previous studies have used negative control.

250-251 Was all of the gene cloned? Please define amino acid range. discussion

Response: Full-length gene of S14, MTIP and GAP45 was cloned and the same has been mentioned in materials and methods in the revised manuscript.

Please discuss data from https://elifesciences.org/articles/77447 in relation to your protein Response: Discussed.

298-300 More recent glideosome papers exist. For example https://doi.org/10.1038/s42003-020-01283-8

Response: Included.

340 List the proteins you analysed. Add URL (websites) to the analyses tools.

Response: They are listed in Table S1. The method section gives all the URLs with references, lines 348-358 in the revised manuscript.

343 Known association from the literature: how was this done?

Response: The interactions demonstrated by different groups have been summarized in the review by Boucher & Bosch, 2015 (doi: 10.1016/j.jsb.2015.02.008).

346-349 A few glideosome components? On what basis were they selected and which are they? Response: The analysis showed that S14 had properties similar to GAP45 and MTIP. Additionally, S14 localized with GAP45 and MTIP, hence selected for interaction studies.

471 Can AlphaFold Structure Predictions be used in the docking studies?

Response: Even the Alphafold AI is trained on existing sequence/structure information despite being advertised as a de novo prediction system. That's why it can't produce good quality structures of evolutionarily unique proteins such as S14. We initially started our protein model generation by alphafold2, but the quality of the structure was very low; then we further used the trRosetta server (https://yanglab.nankai.edu.cn/trRosetta/), which shows the quality of all three protein structures above 95 after validation by using UCLA-DOE LAB-SAVES V6.0 (https://saves.mbi.ucla.edu/).

tr-Rosetta includes inter-residue distance, orientation distribution by a deep-neural network, and homologous template to improve the accuracy of models (DOI: 10.1038/s41596-021-00628-9).

We have given the model structure generated using alphafold2 for your reference.

Model generated by using AlphaFold2.ipynb (https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb#scrollTo=kOblAo-xetgx).

Structure quality assessment by __http://saves.mbi.ucla.edu/.__

GAP 45

__S14 __

MTIP

487 What parts of theses genes was cloned? Define the amino acid range.

Response: The full-length protein-encoding gene was cloned.

714 Please split the table into A Mosquito bite and B haemolymph Sporozoites Response: Done.

Figure 1 For clarity, maybe write S14::mCherry

Response: Done.

Figure 1 It would be useful to show blood stage parasite images.

Response: Blood stage parasite image is included in the revised manuscript as Figure S2.

Figure 2G Haemolymph sporozoites ?

Response: Done.

Figure 8 You argued that S14 is a membrane-bound protein through palmitoylation. Here the protein is shown to be cytoplasmic. Please update our model with more recent ones. Response: We have shown that S14 colocalizes with GAP45 and MTIP, suggesting its IMC localization. We have updated our model in Figure 8.

Figure S2B It would be good to include a positive control for these PCRs.

Response: We have replaced the figure's new gel with a positive control.

Figure S3 It would be good to include a positive control for these PCRs. Response: We already have positive controls in Figure S3C and S3F for all the primer pairs used.

Tabel S1 Table S1 is only mentioned twice in the text: lines 124 and 128. There is no mention that the table contains all (??) known gliding motility proteins.

Response: The table does not contain all the gliding proteins; however, most of the proteins mentioned in the Boucher & Bosch, 2015 paper (doi: 10.1016/j.jsb.2015.02.008) were included.

Table S1 The algorithms / websites used for bioinformatic prediction need to be listed here.

Response: Included.

Table S2 Add the plasmodb gene identifiers here. The table does not show all Plasmodium spp. but a selection. Response: All the orthologs mentioned in Figure S1 and Table S2 are not shown in the updated PlasmoDB. Accordingly, we have removed the Figure S1 and Table S2 in the revised manuscript__.__

Reviewer #1 (Significance (Required)):

General assessment: The authors provide an in-depth analyses of the Plasmodium berghei protein S14 and its involvement in gliding motility. Response: Thank you.

Advance: This paper is the first analysis of the S14 protein. The authors suggest a bridging function for the protein between MTIP and GAP45. Response: Thank you.

Audience: Gliding motility is of interest to the apicomplexan field. I think this particular proteins is specific to Plasmodium spp. Response: Thank you.

Reviewer #2

Summary:

The authors tag the sporozoite protein S14 in P. berghei and show localization near the sporozoite plasma membrane. They also convincingly show, through the generation of S14 knockout lines, that S14 is required for sporozoite motility and thereby also salivary gland and hepatocyte invasion. Their bioinformatic results support possible interactions between S14 and the inner membrane complex proteins MTIP and GAP45. These analyses were performed with these specific candidate proteins rather than being unbiased searches for potential interaction partners. The yeast 2-hybrid data to support these possible protein interactions need further controls.

Lines 143-144: Unless the sporozoites were not permeablized prior to staining, it is not clear if the protein is "on" the plasma membrane or just under the plasma membrane. Furthermore, this statement anyway seems contradictory to the authors' interpretation of Figure 4A. Response: Live S14-mCherry localization on the membrane does not differentiate between the outer membrane or IMC. Next, in Figure 4A, we confirmed S14 localization on IMC by treating sporozoites with Triton X-100 and colocalizing with IMC proteins GAP45 and MTIP. Further, we ensured that mCherrey signals were bleached post-fixation and performed IFA with and without permeabilization. We revealed the mCherry and CSP signals using Alexa 488 and Alexa 594, respectively. We observed the mCherrey signal with permeablized sporozoites, not without permeabilization.

Line 218: "This result indicates that S14 is present within the inner membrane of sporozoites." While this data shows that S14 is not in the plasma membrane of the parasite, how can the authors be sure it is at the IMC? Response: S14 colocalization with MTIP and GAP45 suggested its localization on IMC.

Line 225-226: This sentence overreaches in its conclusion. There is no indication that this protein provides the power or force behind the sporozoites forward movement. Several proteins are known to be required for gliding motility, but they are not all force-providing factors. Response: We have modified the sentence, and now it states, ‘These data demonstrate that S14 is an IMC protein, essential for the sporozoite's gliding motility.

Minor comments:

Line 99: "the role of gliding-associated proteins is unexplored" There are several publications on GAP40, GAP45 and GAP50 (some of which are referenced in the previous paragraph). Response: We have included the reference for studied proteins and modified the sentence for clarity.

Line 114: "We narrowed it down to a candidate" Narrowed down how? Or rephrase. Response: We identified the S14 gene from the Kaiser et al., 2004 paper (DOI: 10.1046/j.1365-2958.2003.03909.x) and rephrased the sentence in the revised manuscript.

Lines 120-123 are strangely written, and I don't follow the logic. What "similar properties" do GAP45 and GAP50 have with S14 and are they really indicative of function? Also if palmitoylation and myristylation and nonclassical secretion are present in most eukaryotes, why would they necessarily be evidence of IMC targeting? Response: It was wrongly written, we have modified the sentence for clarity.

Line 148-149. I did not see examples of this electromobility shift of GAP45 in this publication (although I may have overlooked it).

Response: Electromobility shifts of GAP45 due to the palmitoylation have been reported in (Rees-Channer et al, 2006; DOI: 10.1016/j.molbiopara.2006.04.008). Frenal 2010 paper has stated about two bands, but experimentally it was shown in Rees-Channer et al, 2006 in Figure 1 and 2B.

Table 1 legend should preferably specify that hemolymph sporozoites were used for IV infections. Response: Done.

Line 228: Should be rephrased for accuracy. "revealed the" should be replaced with "suggests" Response: Replaced.

Lines 305-307: I don't entirely understand the logic laid out here.

Response: This was written about GAP45 and MTIP coordination; however, it has been removed in the revised manuscript.

Lines 320-322: "We hypothesize that S14 possibly plays a structural role and maintains the stability of IMC required for the activity of motors during gliding and invasion." The data about the IMC structure shown is fluorescence microscopy - and there no change is observed in the IMC in the knockout line. I suggest removing or rephrasing this point if no extra data is provided to show this. Response: We have removed this sentence in the revised manuscript.

Reviewer #2 (Significance (Required)):

The work gives insights into an unstudied, conserved Plasmodium protein, S14, which the authors show is critical for Plasmodium transmission from mosquitoes. The parasite genetics and phenotyping demonstrating this are strong. The conclusions about interactions with glideosome/inner membrane complex components need further experimental support. The work is of interest to the Plasmodium field and may be also of interest to people interested in other protozoan parasites or in cellular motility.

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

The manuscript by Gosh and colleagues demonstrates that S14 is a glideosome-associated protein in sporozoites. S14 knockout sporozoites fail to infect mosquito salivary glands and liver cells in the mammalian host. These sporozoites are also defective in gliding motility as S14 localizes to the inner membrane. S14 was shown to interact with the glideosome-associated proteins GAP45 and MTIP using the yeast two-hybrid system. The authors also provide an in-silico prediction on the S14, GAP45 and MTIP interaction.

Major issues:

Overall, there is information lacking in the manuscript, including on the figure legends, regarding experiments replication and n analyzed.

For complementation, the authors engineered an independent S14 knockout line. For this line is clear that parasites failed to infect salivary glands contrarily to the knockout line. Despite not showing it, did the authors confirm that this knockout line has no defects in infecting mosquito midguts and producing sporozoites? Response: We analyzed the midgut for sporozoite formation, which was comparable to the original KO line, and included the data (Figure 2D) in the revised manuscript.

Did the authors conduct IV injections in mice with a higher number of sporozoites? Hemolymph sporozoites are less infectious than sporozoites collected from the salivary glands and I was wondering whether patent infections with S14 ko sporozoites can be obtained by injecting a higher inoculum. The same applies to the infectivity experiments with HepG2cells. Response: We increased the sporozoites dose and infected mice with 10,000 hemolymph sporozoites, but no infection was observed (Table 1). No EEFs were observed in HepG2 cells infected with 10,000 S14 KO hemolymph sporozoites.

Please provide information on the number of sporozoites that were analyzed in the trails experiment. Response: We analyzed 210, 225, and 212 sporozoites for WT GFP, S14 KO c1, and S14 KO c2, respectively.

Minor issues:

In Figure 1. F) WB on S14-3xHA-mCherry tagged sporozoites showing two bands on the WB. The Palm-band is only inferred thus I suggest correcting the figure to S14-3xHA-mcherry. On 1D all the mcherry signal is detected on the membrane but then on WB, a smaller fraction is palm? What is the explanation for the ratio between the two bands? Why so distinct CSP intensity bands between wt and tagged line? Were very distinct amounts of protein loaded?

Response: We have corrected the Palm-S14-3xHA-mcherry to S14-3xHA-mcherry.

This reviewer raises a valid point regarding the discrepancy between IFA and Western blot. The non-palmitoylated S14-mCherrey signal was possibly corrected after deconvolution in image 1D and mainly the membrane signal was prominent. In Figure 1C, many sporozoites show some cytosolic signal, perhaps representing non-palmitoylated S14. Western blot concentrates the protein of interest as a single band, allowing more accurate visualization of protein.

The distinct CSP intensity bands between wt and the tagged line are due to the loading of a higher amount of parasite lysate in WT lane. To ensure that the western blot signal is specific to S14, we loaded a higher amount of protein in WT.

Figure 1. A) Statistical analysis is missing. Not clear if the bars represent mean values +/- standard deviation. No information on the material and methods of how the relative expression was calculated. Response: No error bars are shown in Figure 1 because it was performed once.

In the introduction lines 54 and 58 I suggest replacing humans with mammalian host. Response: Replaced.

Line 58. Not clear why the ref Ripp et al., 2021 is used for a general sentence to introduce the Plasmodium life cycle. Response: Removed.

Line 72: I suggest replacing "TRAP mutant" with "TRAP knockouts" (Sultan et al., 1997). More recently there are TRAP mutants with impaired motility and normal invasion of mosquito salivary glands (Klug et al., 2020) Response: Replaced.

Lines 78 to 86: In this paragraph, authors refer to several proteins involved in sporozoite gliding motility and host cell invasion, however for most of the studies this conclusion comes from the characterization of knockouts defective phenotype and actually a direct role for some of these molecules in the process awaits clear demonstration. Response: We have replaced involved with implicated.

Line 78: Authors do not consider that maebl knockout sporozoites display reduced adhesion, including to cultured hepatocytes, which could contribute to the defects in multiple biological processes, such as in gliding motility, hepatocyte wounding, and invasion. Response: We have corrected maebl role in the revised manuscript.

Line 80: I suggest authors reconcile the contradictory reports in the literature on the role of TRSP in sporozoites invasion. Response: We have removed this reference in the revised manuscript.

Line 82-83: Please revise it. Response: Revised.

Table 1. Correct table as when sporozoites were transmitted by mosquito bite the term "number of sporozoites injected" does not apply. Please give more details on the bite experiments. Is this the number of mosquitoes for all four animals? For how long the mosquitoes were allowed to bite? Response: For clarity, we have split the table into A Mosquito bite and B haemolymph Sporozoites. We used ten mosquitoes/mice in the bite experiment. Mosquitos were allowed to probe for blood meal for 20 minutes, and the feeding was ensured by observing mosquitoes post-blood meal; approximately 70% of mosquitoes received the blood meal in all the cages.

Line 288 and 289. There are several publications showing that maebl knockout sporozoites are impaired at invading the mosquito salivary glands and at infecting the vertebrate host contradicting Kariu et al., 2002 findings in the vertebrate host. Response: We have removed maebl from this line.

Line 290. I suggest "was most likely due to" instead of " due to" as sporozoite adhesion to cells was not evaluated. Response: Corrected.

Line 291: "Cellular transmigration and host cell invasion are prerequisites for gliding motility" please revise. Response: Revised.

Line 437: indicate which clone was used.

Response: Indicated (3D11).

Line: 463: indicate the % of the gel in the SDS-PAGE Response: We have used 10% SDS-PAGE gel and it is indicated in the revised manuscript.

Line 499: indicate the version of the GraphPad Prism software. Response: GraphPad Prism version 9.

Figure S3 legend needs to be corrected. Panels in the figure are from A to F while in legend G and H are included. Response: Corrected.

4. Description of analyses that authors prefer not to carry out

Reviewer #2

Line 39-41: "Using in silico and the yeast two-hybrid system, we showed the interaction of S14 with the glideosome-associated proteins GAP45 and MTIP. Together, our data show that S14 is a glideosome-associated protein" Although these interactions can be speculated based on the results shown, these interactions were not confirmed in this study. Response: We attempted to pulldown the S14 interacting partner using anti-mCherry antibody from S14-3XHA-mCherry transgenic sporozoites and then further tried to identify interactome using mass spectrometry but failed. Hence, we selected two known IMC localized gliding proteins MTIP and GAP45. Performing pull-down from sporozoites is challenging, so we checked this interaction using yeast 2-hybrid assay and bioinformatic analysis for protein-protein interaction.

In order to claim interaction between S14 and IMC proteins, interaction needs to be shown experimentally. Well-controlled yeast 2-hybrid would be a start - then interaction would be more than just speculative. But immunoprecipitation from sporozoites or other biochemical interactions would give more support to this idea. Response: We attempted to pulldown the S14 interacting partner using an anti-mCherry antibody from S14-3XHA-mCherry transgenic sporozoites and then further tried to identify interactome using mass spectrometry but failed. Hence, we selected two known IMC localized gliding proteins MTIP and GAP45. Performing pull-down from sporozoites is challenging, so we checked this interaction using yeast 2-hybrid assay and bioinformatic analysis for protein-protein interaction.

Reviewer #3

The authors provide convincing data on the S14 localization in the inner membrane of sporozoites and interaction with GAP45 and MTIP using the yeast model. Did the authors consider conducting co-IP followed by MS analysis to pull down S14 in the complex with GAP45 and MTIP? Response: We attempted to pulldown the S14 interacting partner using an anti-mCherry antibody from S14-3XHA-mCherry transgenic sporozoites and then further tried to identify the interactome using mass spectrometry but failed. Hence, we selected two known IMC localized gliding proteins, MTIP and GAP45. Performing pull-down from sporozoites is challenging, so we checked this interaction using yeast 2-hybrid assay and bioinformatic analysis for protein-protein interaction.

__Reviewer #3 (Significance (Required)):____ __ Sporozoite gliding motility is a critical feature of parasite infectivity. Impairment of this important feature has been described for several mutant/knockout parasite lines. This study goes beyond the phenotypic analysis of mutant parasites to infer the role of S14 by providing more mechanistic evidence to show S14 interaction with other glideosome-associated proteins. However, this interaction was investigated using the two-hybrid system in yeast. Still, in sporozoites, no experiments were conducted to evaluate the interaction between these proteins.

Response: We attempted to pulldown the S14 interacting partner using an anti-mCherry antibody from S14-3XHA-mCherry transgenic sporozoites and then further tried to identify interactome using mass spectrometry but failed. Hence, we selected two known IMC localized gliding proteins, MTIP and GAP45. Performing pull-down from sporozoites is challenging, so we checked this interaction using yeast 2-hybrid assay and bioinformatic analysis for protein-protein interaction.

Please consider I'm not an expert on the in-silico interaction studies.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

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Referee #2

Evidence, reproducibility and clarity

Summary:

The authors tag the sporozoite protein S14 in P. berghei and show localization near the sporozoite plasma membrane. They also convincingly show, through the generation of S14 knockout lines, that S14 is required for sporozoite motility and thereby also salivary gland and hepatocyte invasion. Their bioinformatic results support possible interactions between S14 and the inner membrane complex proteins MTIP and GAP45. These analyses were performed with these specific candidate proteins rather than being unbiased searches for potential interaction partners. The yeast 2-hybrid data to support these possible protein interactions need further controls.

Major comments:

Line 39-41: "Using in silico and the yeast two-hybrid system, we showed the interaction of S14 with the glideosome-associated proteins GAP45 and MTIP. Together, our data show that S14 is a glideosome-associated protein" Although these interactions can be speculated based on the results shown, these interactions were not confirmed in this study.

Lines 143-144: Unless the sporozoites were not permeablized prior to staining, it is not clear if the protein is "on" the plasma membrane or just under the plasma membrane. Furthermore, this statement anyway seems contradictory to the authors' interpretation of Figure 4A.

Line 218: "This result indicates that S14 is present within the inner membrane of sporozoites." While this data shows that S14 is not in the plasma membrane of the parasite, how can the authors be sure it is at the IMC?

Line 149: To definitively state S14 is a membrane protein, biochemical assays proving such should be performed. (or perhaps genetic mutation of the predicted palmitoylation site?) Otherwise, this should be rephrased.

Line 225-226: This sentence overreaches in its conclusion. There is no indication that this protein provides the power or force behind the sporozoites forward movement. Several proteins are known to be required for gliding motility, but they are not all force-providing factors.

Lines 257-258: for yeast 2-hybrid, the controls of expressing S14, GAP45 and MTIP together with control proteins where no interaction would be predicted are absent.

In order to claim interaction between S14 and IMC proteins, interaction needs to be shown experimentally. Well-controlled yeast 2-hybrid would be a start - then interaction would be more than just speculative. But immunoprecipitation from sporozoites or other biochemical interactions would give more support to this idea.

Minor comments:

Line 99: "the role of gliding-associated proteins is unexplored" There are several publications on GAP40, GAP45 and GAP50 (some of which are referenced in the previous paragraph).

Line 114: "We narrowed it down to a candidate" Narrowed down how? Or rephrase.

Lines 120-123 are strangely written, and I don't follow the logic. What "similar properties" do GAP45 and GAP50 have with S14 and are they really indicative of function? Also if palmitoylation and myristylation and nonclassical secretion are present in most eukaryotes, why would they necessarily be evidence of IMC targeting?

Line 148-149. I did not see examples of this electromobility shift of GAP45 in this publication (although I may have overlooked it).

Table 1 legend should preferably specify that hemolymph sporozoites were used for IV infections.

Line 228: Should be rephrased for accuracy. "revealed the" should be replaced with "suggests"

Lines 305-307: I don't entirely understand the logic laid out here.

Lines 320-322: "We hypothesize that S14 possibly plays a structural role and maintains the stability of IMC required for the activity of motors during gliding and invasion." The data about the IMC structure shown is fluorescence microscopy - and there no change is observed in the IMC in the knockout line. I suggest removing or rephrasing this point if no extra data is provided to show this.

Significance

The work gives insights into an unstudied, conserved Plasmodium protein, S14, which the authors show is critical for Plasmodium transmission from mosquitoes. The parasite genetics and phenotyping demonstrating this are strong. The conclusions about interactions with glideosome/inner membrane complex components need further experimental support. The work is of interest to the Plasmodium field and may be also of interest to people interested in other protozoan parasites or in cellular motility.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

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Referee #1

Evidence, reproducibility and clarity

Summary: The authors have identified a sporozoite gliding motility protein through bioinformatic analysis. From the main text I do not know how, or what bioinformatic analysis was performed, in order to focus on this protein which is called S14. The authors then go on to tag the protein, produce a KO and show its involvement in gliding motility. The KO shows that parasites lacking S14 fail to invade the mosquito salivary glands. This is due to a motility defect. Y2H and docking studies are used to define an interaction with MTIP and GAP45, two known components of the glideosome.

Major comments: The paper is sometimes hard to follow and lacks clarity. The reason: important information is omitted, or explained at the end of a section rather than at first mention; experimental details that are of essence need to be mentioned or explained in the main text; there is ample use of the word 'bioinformatic' without explaining what kind of analysis was performed in the main text. I cite from the abstract: 'In silico analysis of a novel protein, S14, which is uniquely upregulated in salivary gland sporozoites, suggested its association with glideosome-associated proteins.' I cite from the introduction: 'A study comparing transcriptome differences between sporozoites and merozoites using suppressive subtraction hybridization found several genes highly upregulated in sporozoites and named them 'S' genes (Kaiser et al, 2004). We narrowed it down to a candidate named S14, which lacked signal peptide and transmembrane domains.' From reading the main text, I do not know why Plasmodium berghei S14 was chosen in this manuscript. S14 is one of 25 transcripts identified by Kappe et al in Plasmodium yoelii (https://doi.org/10.1046/j.1365-2958.2003.03909.x) to be upregulated in sporozoites. The material and methods section does not explain either why S14 was chosen. Perhaps the authors could update Figure 2 from Kappe et al with the most recent annotations from plasmodb.

Reproducibility: None of the main Figures or Figure legends define ' N = '. For example I cite: 'The S14 KO clonal lines were first analyzed for asexual blood-stage propagation, and for this, 200 µl of iRBCs with 0.2% parasitemia was intravenously injected into a group of mice.' There are 2 mentions of 'N=' in the supplementary figures. I have not found any others.

I'm not sure what the convention is. Should unpublished data for this gene (PBANKA_0605900) found in pberghei.eu (a database for mutant berghei parasites) be cited? After all it confirms their findings.

The authors need to use more recent references for some of their statements; see some comments below.

Minor comments:

line

1-2 Add the Plasmodium species of this study. abstract Which species do you work with? 29 mosquito salivary glands and human host hepatocytes 30 to the glideosome, a protein complex containing [...] 32-33 What kind of in silico analysis suggested S14 is part of the glideosome? S14 is not uniquely upregulated; there are other S-type genes identified by Kappe and Matuschewski. 25 I believe. 32 Please point out he species were S genes were identified. SGS of which species? 34 expression: change to transcription 39 What kind of in silico analysis was used here? and therefore malaria transmission 55 A single zygote transforms into a single ookinete, which establishes a single oocyst, which in turn can produce thousands of midgut sporozoites. Please correct the life cycle passage. located or anchored in the IMC? And located between the IMC and plasma membrane? 61-63 Refer to Table S1 and its contents here 64 Name the known GAPs.

65-67 Which transmembrane domain proteins? Please add more recent references than King 1988. 71-72 TRAP was the first protein found to be ... 74-76 Add additional, more recent references: for example search Frischknecht and TRAP 76 S6 (TREP) is also [...] 88 Some of these proteins are also expressed in ookinetes. 89-91 The sentence needs a verb. 88-96 Please add some more recent glideosome papers. After 2013. 91 Why do you call it a peripheral protein? 91-93 There are more recent citations for GAP45 andGAP50. 96 Insert a reference here. 99 Please define the gliding-associated proteins. What are they? Aren't there papers on GAP40, 45 and 50? DOI: 10.1016/j.chom.2010.09.002 99 .... What prompted you to identify a novel GAP? And why is S14 classified as a GAP? 99-102 What kind of bioinformatic study? Why was S14 chosen? Please outline how you ended up with S14. Any other proteins that came out of the bioinformatic screen from the list of S genes? How many proteins were identified in the screen for sporozoite upregulated proteins by Kappe and Matuschewski? 102-103 Define the nonclassical secretion pathway. Please reference GAP45 and GAP50 data for the nonclassical pathway. 105 Please add P. berghei to the title, the abstract, the introduction. 111 The results section does not outline what bioinformatic analysis was used 112-114 Please specify the exact number of upregulated in sporozoites genes. I think it was 25. And add the species the study was performed in. Why did you choose the Kappe study but not the uis genes from berghei? 114-115 How did you narrow it down to S14? The Kappe paper lists 25 S-type genes from P. yoelii. 118 Plasmodia is not the plural for a group of different Plasmodium species. Use: [...] conserved among Plasmodium spp. 118-119 Which proteins did you analyze? And how did you analyze them? Where is the data for this analysis? Outline the amino acids that predict palmitoylation? The nonclassical pathway? 119-122 Here: do you mean S14 has similar properties as GAP 45 and GAP50? Define the nonclassical pathway? How do you know S14 is in the IMC? 122-123 Please reference the bioinformatic analysis plus URL that allows targeting to the IMC to be analyzed. 123-124 Please reference the URLs for TM, palmitoylation, and interactions analyses. 125-127 How did you predict that S14 is secreted via the nonclassical pathway? 128-130 Define the nonclassical pathway when it first appears in your manuscript. The citation Moskes 2004 is not in the reference list 132 Which membrane? 134-135 In which species? 141-142 Please include images of blood stage and liver stage parasites. 142-143 Which membrane? 148-149 I cannot find the specific figure you refer to; I checked the online version of the Frenal 2010 paper. 175 gland, we counted [...] 177 Compared to the 177-179 Failed to invade (absolutely)? Or invaded in highly reduced numbers? 182-186 Please be precise: I think you mean you let all types of mosquitoes take a blood meal; s14 knockout-infected mosquitoes did not infect mice. 181-202 Perhaps use paragraphs to indicate the different types of experiments performed here. 204 Please introduce paragraphs to identify the different experiments in this section 208 Outer or inner membrane of what? IMC, the plasma membrane? 228 onwards Structural models were obtained from whom? Which species did you use for the docking study? Could you use in one approach 3 berghei proteins, and confirm your docking studies with the falciparum proteins? That would strengthen your model. Should you include a negative control protein in the approach? 250-251 Was all of the gene cloned? Please define amino acid range. discussion Please discuss data from https://elifesciences.org/articles/77447 in relation to your protein

298-300 More recent glideosome papers exist. For example https://doi.org/10.1038/s42003-020-01283-8 340 List the proteins you analysed. Add URL (websites) to the analyses tools. 343 Known association from the literature: how was this done? 346-349 A few glideosome components? On what basis were they selected and which are they?

471 Can AlphaFold Structure Predictions be used in the docking studies? 487 What parts of theses genes was cloned? Define the amino acid range. 714 Please split the table into A Mosquito bite and B haemolymph Sporozoites Figure 1 For clarity, maybe write S14::mCherry Figure 1 It would be useful to show blood stage parasite images. Figure 1F You have not formally shown that this signal corresponds to palmitoylated S14. Could be heavy chain. Figure 2G Haemolymph sporozoites ? Figure 8 You argued that S14 is a membrane-bound protein through palmitoylation. Here the protein is shown to be cytoplasmic. Please update our model with more recent ones.

Figure S2B It would be good to include a positive control for these PCRs. Figure S3 It would be good to include a positive control for these PCRs.

Tabel S1 Table S1 is only mentioned twice in the text: lines 124 and 128. There is no mention that the table contains all (??) known gliding motility proteins. Table S1 The algorithms / websites used for bioinformatic prediction need to be listed here. Table S2 Add the plasmodb gene identifiers here. The table does not show all Plasmodium spp. but a selection.

Significance

General assessment: The authors provide an in-depth analyses of the Plasmodium berghei protein S14 and its involvement in gliding motility.

Advance: This paper is the first analysis of the S14 protein. The authors suggest a bridging function for the protein between MTIP and GAP45.

Audience: Gliding motility is of interest to the apicomplexan field. I think this particular proteins is specific to Plasmodium spp.

Wenige Tage nach dem „2023 State of the Climate report“ listet der „Interconnected Disaster Report“ der UN University sechs Bedrohungen für die lebenserhaltenden Systeme des Planeten auf, darunter Gletscherschmelze, Grundwasserverlust, Artensterben und Erhitzung. Nur ein transformativer Wandel statt aufschiebender Lösungen kann die wachsenden Risiken miteinander verbundener Katastrophen verringern. https://www.liberation.fr/environnement/climat/climat-la-vie-sur-la-planete-terre-est-en-etat-de-siege-alertent-des-scientifiques-20231025_2MHSFZZWUNHZPPBONAUFLKKUZM/

Studie: https://interconnectedrisks.org/

Merh zum 2023 State of the Climate report: https://hypothes.is/search?q=tag%3A%22report%3A%202023%20state%20of%20the%20climate%20report%22

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

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Dear Editor,

Herewith we submit our fully revised peer-reviewed preprint that had been reviewed by Review Commons. We thank the Review Commons team and reviewers for thoroughly commenting on our preprint and providing very useful additional points for consideration and discussion.

You will find - the revised manuscript (third preprint version uploaded on biorxiv)<br /> - two reviewer letters (through Review Commons), - our rebuttal letter<br /> - a revised manuscript version with highlighted changes.

Our manuscript reports that an active form of FIT, an essential transcription factor for root iron acquisition in plants, forms dynamic nuclear condensates in response to a blue light stimulus.<br /> A hallmark of our work is the thorough investigation of the nature of the FIT nuclear bodies in plant cells, that we were able to characterize as highly dynamic condensates in which active FIT homo- and heteromeric protein complexes can accumulate preferentially. Through co-localization with nuclear body markers, we found that these FIT condensates are related to speckles, which are a sub-type of nuclear bodies connected with splicing activities. This suggests that FIT condensates are linked with post-transcriptional regulation mechanisms.

The reviewers highlight that an “impressive set of microscopic techniques” has been combined to study in a unique manner the characteristics and functionalities of FIT nuclear bodies in living plant cells. We show that FIT nuclear bodies can be formed in roots of Arabidopsis thaliana. The microscopic imaging techniques we used to characterize the nature and functionalities of FIT nuclear bodies in plant cells have several constraints related to sensitivity and a required strength of fluorescent protein signal. For technical reasons to be able to apply qualitative and quantitative imaging techniques, we conducted the investigation of FIT condensates in Nicotiana benthamiana, a classical and widely used plant protein expression system.

As stated in the reviews, the connection between plant nutrition and nuclear bodies is an “unprecedented” new mode of regulation. The significance of our work is underlined by the fact that we report a “very precise cellular and molecular mechanism in nutrition” that is as yet “still largely unexplored in this context”. Therefore, our study “sheds light on the functional role of this membrane-less compartment and will be appreciated by a large audience.”

We propose that condensate formation is a mechanism that may steer iron nutrition responses by providing a link between iron and light signaling. For sessile plants, it is absolutely essential that environmental signals are sensed and integrated with developmental and physiological programs so that plants can rapidly adjust to a changing environment and potential stress situations. Since iron is a micronutrient that may be toxic when present in excess, e.g. through catalyzing oxidative stress, plants strictly control the acquisition and allocation of iron. Hence, FIT nuclear bodies may be regulatory hubs that integrate at the sub-nuclear level environmental signaling inputs in the control of micronutrient uptake, possibly connected with splicing.

Our work lays the ground for future studies that can address the proof of concept in more detailed manner in plants exposed to varying environmental conditions to reveal the interconnection of environmental and nutritional signaling.

We prepared a revised preprint in which we address all reviewer comments. Please find our revision and our detailed response to all reviewer comments.

With these changes, we hope that our peer-reviewed preprint can receive a positive vote,

We are looking forward to your response,

Sincerely

Petra Bauer and Ksenia Trofimov on behalf of all authors

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

In this paper entitled " FER-LIKE IRON DEFICIENCY-INDUCED TRANSCRIPTION FACTOR (FIT) accumulates in homo- and heterodimeric complexes in dynamic and inducible nuclear condensates associated with speckle components", Trofimov and colleagues describe for the first time the function of FIT in nuclear bodies. By an impressive set of microscopies technics they assess FIT localization in nuclear bodies and its dynamics. Finally, they reveal their importance in controlling iron deficiency pathway. The manuscript is well written and fully understandable. Nonetheless, at it stands the manuscript present some weakness by the lack of quantification for co-localization and absence controls making hard to follow authors claim. Moreover, to substantially improve the manuscript the authors need to provide more proof of concepts in A. thaliana as all the nice molecular and cellular mechanism is only provided in N. bentamiana. Finally, some key conclusions in the paper are not fully supported by the data.<br /> Please see below:

Main comments:

1) For colocalization analysis, the author should provide semi-quantitative data counting the number of times by eyes they observed no, partial or full co-localization and indicate on how many nucleus they used.

Authors:

We have added the information in the Materials and Method section, lines 731-734:

In total, 3-4 differently aged leaves of 2 plants were infiltrated and used for imaging. One infiltrated leaf with homogenous presence of one or two fluorescence proteins was selected, depending on the aim of the experiment, and ca. 30 cells were observed. Images are taken from 3-4 cells, one representative image is shown.

In all analyzed cases, except in the case of colocalization of FIT and PIF4 fusion proteins, the ca. 30 cells had the same localization and/or colocalization patterns. This information has also been added in the figure legends. Each experiment was repeated at least 2-3 times, or as indicated in the figure legend.

2) Do semi-quantitative co-localization analysis by eyes, on FIT NB with known NB makers in the A. thaliana root. For now, all the nicely described molecular mechanism is shown in N. benthamiana which makes this story a bit weak since all the iron transcriptional machinery is localized in the root to activate IRT1.

Authors:

The described approach has been very optimal, and we were able to screen co-localizing marker proteins in FIT NBs in N. benthamiana to better identify the nature of FIT NBs. This has been successful as we were able to associate FIT NBs with speckles. The N. benthamiana system allowed optimal microscopic observation of fluorescence proteins and quantification of FIT NB characteristics in contrast to the root hair zone of Arabidopsis where Fe uptake takes place. FIT is expressed at a low level in roots and also in leaves, whereby fluorescence protein expression levels are insufficient for the here-presented microscopic studies. The tobacco infiltration system is also well established to study FIT-bHLH039 protein interaction and nuclear body markers. We discuss this point in the discussion, see line 489-500.

3) The authors need to provide data clearly showing that the blue light induce NB in A. thaliana and N. benthamiana.

Authors:

For tobacco, see Figure 1B (t = 0, 5 min) and Supplemental Movies S1. For Arabidopsis, please see Figure 1A (t = 0, 90 and 120 min) and Supplemental Figure S1A. We provide an additional image of pFIT:cFIT-GFP Arabidopsis control plants, showing that NB formation is not detected in plants that were grown in white light and not exposed to blue light before inspection (Supplemental Figure S1B). We state, that upon blue light exposure, plants had FIT NBs in at least 3-10 nuclei of 20 examined nuclei in the root epidermis in the root hair zone (in three independent experiments with three independent plants). White-light-treated plants showed no NB formation unless an additional exposure to blue light was provided (in three independent experiments, three independent plants per experiment and with 15 examined nuclei per plant).

4) Direct conclusion in the manuscript:

• Line 170: At this point of the paper the author cannot claim that the formation of FIT condensates in the nucleus is due to the light as it might be indirectly linked to cell death induced by photodamaging the cell using a 488 lasers for several minutes. This is true especially with the ELYRA PS which has strong lasers made for super resolution and that Cell death is now liked to iron homeostasis. The same experiment might be done using a spinning disc or if the authors present the data of the blue light experiment mentioned above this assumption might be discarded. Alternatively, the author can use PI staining to assess cell viability after several minutes under 488nm laser.

Authors:

As stated in our response to comment 3, we have included now a white light control to show that FIT NB formation is not occurring under the normal white light conditions. Since the formation of FIT NBs is a dynamic and reversible process (Figure 1A), it indicates that the cells are still viable, and that cell death is not the reason for FIT NB formation.

• Line 273: I don't agree with the first part of the authors conclusion, saying that "wild-type FIT had better capacities to localize to NBs than mutant FITmSS271AA, presumably due its IDRSer271/272 at the C-terminus. This is not supported by the data. In order to make such a claim the author need to compare the FA of FIT WT with FITmSS271AA by statistical analysis. Nonetheless, the value seems to be identical on the graphs. The main differences that I observed here are, 1) NP value for FITmSS271AA seems to be lower compared to FIT-WT, suggesting that the Serine might be important to regulate protein homedimerization partitioning between the NP and the NB. 2) To me, something very interesting that the author did not mention is the way the FA of FITmSS271AA in the NB and NP is behaving with high variability. The FA of those is widely spread ranging from 0.30 to 0.13 compared to the FIT-WT. To me it seems that according to the results that the Serine 271/272 are required to stabilize FIT homodimerization. This would not only explain the delay to form the condensate but also the decreased number and size observed for FITmSS271AA compared to FIT-WT. As the homodimerization occurs with high variability in FITmSS271AA, there is less chance that the protein will meet therefore decreasing the time to homodimerize and form/aggregate NB.

Authors:

We fully agree. We meant to describe this result it in a similar way and thank you for help in formulating this point even better. Rephrasing might make it better clear that the IDRSer271/272 is important for a proper NB localization, lines 272-278:

“Also, the FA values did not differ between NBs and NP for the mutant protein and did not show a clear separation in homodimerizing/non-dimerizing regions (Figure 3D) as seen for FIT-GFP (Figure 3C). Both NB and NP regions showed that homodimers occurred very variably in FITmSS271AA-GFP.

In summary, wild-type FIT could be partitioned properly between NBs and NP compared to FITmSS271AA mutant and rather form homodimers, presumably due its IDRSer271/272 at the C-terminus.”

• Line 301: According to my previous comment (line 273), here it seems that the Serine 271/272 are required only for proper partitioning of the heterodimer FIT/BHLH039 between the NP and NB but not for the stability of the heterodimer formation. However, it might be great if the author would count the number of BHLH039 condensates in both version FITmSS271AA and FIT-WT. To my opinion, they would observe less BHLH039 condensate because the homodimer of FITmSS271AA is less likely to occur because of instability.

Authors:

bHLH039 alone localizes primarily to the cytoplasm and not the nucleus, and the presence of FIT is crucial for bHLH039 nuclear localization (Trofimov et al., 2019). Moreover, bHLH039 interaction with FIT depends on SS271AA (Gratz et al., 2019). We therefore did not consider this experiment for the manuscript and did not acquire such data, as we did not expect to achieve major new information.

5) To wrap up the story about the requirements of NB in mediating iron acquisition under different light regimes, provide data for IRT1/FRO2 expression levels in fit background complemented with FITmSS271AA plants. I know that this experiment is particularly lengthy, but it would provide much more to this nice story.

Authors:

Data for expression of IRT1 and FRO2 in FITmSS271AA/fit-3 transgenic Arabidopsis plants are provided in Gratz et al. (2019). To address the comment, we did here a NEW experiment. We provide gene expression data on FIT, BHLH039, IRT1 and FRO2 splicing variants (previously reported intron retention) to explore the possibility of differential splicing alterations under blue light (NEW Supplemental Figure S6 and S7, lines 454-466). Very interestingly, this experiment confirms that blue light affects gene expression differently from white light in the short-term NB-inducing condition and that blue light can enhance the expression of Fe deficiency genes despite of the short 1.5 to 2 h treatment. Another interesting aspect was that the published intron retention was also detected. A significant difference in intron retention depending on iron supply versus deficiency and blue/white light was not observed, as the pattern of expression of transcripts with respective intron retentions sites was the same as the one of total transcripts mostly spliced.

Minor comments

In general, I would suggest the author to avoid abbreviation, it gets really confusing especially with small abbreviation as NB, NP, PB, FA.

Authors:

We would like to keep the used abbreviations as they are utilized very often in our work and, in our eyes, facilitate the understanding.

Line 106: What does IDR mean?

Authors:

Explanation of the abbreviation was added to the text, lines 105-108:

“Intrinsically disordered regions (IDRs) are flexible protein regions that allow conformational changes, and thus various interactions, leading to the required multivalency of a protein for condensate formation (Tarczewska and Greb-Markiewicz, 2019; Emenecker et al., 2020).”

Line 163-164: provide data or cite a figure properly for blue light induction.

Authors:

We have removed this statement from the description, as we provide a white light control now, lines 157-158:

“When whole seedlings were exposed to 488 nm laser light for several minutes, FIT became re-localized at the subnuclear level.”

Line 188: Provide Figure ref.

Authors:

Figure reference was added to the text, lines 184-185:

“As in Arabidopsis, FIT-GFP localized initially in uniform manner to the entire nucleus (t=0) of N. benthamiana leaf epidermis cells (Figure 1B).”

Line 194: the conclusion is too strong. The authors conclude that the condensate they observed are NB based on the fact the same procedure to induce NB has been used in other study which is not convincing. Co-localization analysis with NB markers need to be done to support such a claim. At this step of the study, the author may want to talk about condensate in the nucleus which might correspond to NB. Please do so for the following paragraph in the manuscript until colocalization analysis has not been provided. Alternatively provide the co-localization analysis at this step in the paper.

Authors:

We agree. We changed the text in two positions.

Lines 176-178__: “__Since we had previously established a reliable plant cell assay for studying FIT functionality, we adapted it to study the characteristics of the prospective FIT NBs (Gratz et al., 2019, 2020; Trofimov et al., 2019).”

Lines 192-193: “__We deduced that the spots of FIT-GFP signal were indeed very likely NBs (for this reason hereafter termed FIT NBs).”

Line 214: In order to assess the photo bleaching due to the FRAP experiment the quantification of the "recovery" needs to be provided in an unbleached area. This might explain why FIT recover up to 80% in the condensate. Moreover, the author conclude that the recovery is high however it's tricky to assess since no comparison is made with a negative/positive control.

Authors:

In the FRAP analysis, an unbleached area is taken into account and used for normalization.

We reformulated the description of Figure 1F, lines 212-214:

“According to relative fluorescence intensity the fluorescence signal recovered rapidly within FIT NBs (Figure 1F), and the calculated mobile fraction of the NB protein was on average 80% (Figure 1G).”

Line 220-227: The conclusion it's too strong as I mentioned previously the author cannot claim that the condensate are NBs at this step of the study. They observed nuclear condensates that behave like NB when looking at the way to induce them, their shape, and the recovery. And please include a control.

Authors:

Please see the reformulated sentences and our response above.

Lines 176-178: “Since we had previously established a reliable plant cell assay for studying FIT functionality, we adapted it to study the characteristics of the prospective FIT NBs (Gratz et al., 2019, 2020; Trofimov et al., 2019).”

Lines 192-193: “__We deduced that the spots of FIT-GFP signal were indeed very likely NBs (for this reason hereafter termed FIT NBs).”

Line 239: It's unappropriated to give the conclusion before the evidence.

Authors:

Thank you. We removed the conclusion.

Line 240: Figure 2A, provide images of FIT-G at 15min in order to compare. And the quantification needs to be provided at 5 minutes and 15 minutes for both FIT-G WT and FIT-mSS271AA-G counting the number of condensates in the nucleus. Especially because the rest of the study is depending on these time points.

Authors:

This information is provided in the Supplemental Movie S1C.

Line 241: the author say that the formation of condensate starts after 5 minutes (line 190) here (line 241) the author claim that it starts after 1 minutes. Please clarify.

Authors:

In line 190 we described that FIT NB formation occurs after the excitation and is fully visible after 5 min. In line 241 we stated that the formation starts in the first minutes after excitation, which describes the same time frame. We rephrased the respective sentences.

Lines 185-188: “A short duration of 1 min 488 nm laser light excitation induced the formation of FIT-GFP signals in discrete spots inside the nucleus, which became fully visible after only five minutes (t=5; Figure 1B and Supplemental Movie S1A).”

Lines 239-242: “While FIT-GFP NB formation started in the first minutes after excitation and was fully present after 5 min (Supplemental Movie S1A), FITmSS271AA-GFP NB formation occurred earliest 10 min after excitation and was fully visible after 15 min (Supplemental Movie S1C).”

Line 254: Not sure what the authors claim "not only for interaction but also for FIT NB formation ". To me, the IDR is predicted to be perturbed by modeling when the serines are mutated therefore the IDR might be important to form condensates in the nucleus. Please clarify.

Authors:

The formation of nuclear bodies is slow for FITmSS271AA as seen in Figure 2. Previously, we showed that FITmSS271AA homodimerizes less (Gratz et al., 2019.) Therefore, the said IDR is important for both processes, NB formation and homodimerization. We have added this information to make the point clear, lines 253-255:

“This underlined the significance of the Ser271/272 site, not only for interaction (Gratz et al., 2019) but also for FIT NB formation (Figure 2).”

Line 255: It's not clear why the author test if the FIT homodimerization is preferentially associated with condensate in the nucleus.

Authors:

We test this because both homo- and heterodimerization of bHLH TFs are generally important for the activity of TFs, and we unraveled the connection between protein interaction and NB formation. We state this in lines 228-232.

Line 269-272: It's not clear to what the authors are referring to.

Authors:

We are describing the homodimeric behavior of FIT and FITmSS271AA assessed by homo-FRET measurements that are introduced in the previous paragraph, lines 256-268.

Line 309: This colocalization part should be presented before line 194.

Authors:

We find it convincing to first examine and characterize the process underlying FIT NB formation, then studying a possible function of NBs. The colocalization analysis is part of a functional analysis of NBs. We thank the reviewer for the hint that colocalization also confirms that indeed the nuclear FIT spots are NBs. We will take this point and discuss it, lines 516-522:

“Additionally, the partial and full colocalization of FIT NBs with various previously reported NB markers confirm that FIT indeed accumulates in and forms NBs. Since several of NB body markers are also behaving in a dynamic manner, this corroborates the formation of dynamic FIT NBs affected by environmental signals.”

“In conclusion, the properties of liquid condensation and colocalization with NB markers, along with the findings that it occurred irrespective of the fluorescence protein tag preferentially with wild-type FIT, allowed us to coin the term of ‘FIT NBs’.”

Line 328: add the ref to figure, please.

Authors:

Figure reference was added to the text, lines 330-332:

“The second type (type II) of NB markers were partially colocalized with FIT-GFP. This included the speckle components ARGININE/SERINE-RICH45-mRFP (SR45) and the serine/arginine-rich matrix protein SRm102-mRFP (Figure 5).”

Line 334: It seems that the size of the SR45 has an anormal very large diameter between 4 and 6 µm. In general a speckle measure about 2-3µm in diameter. Can the author make sure that this structure is not due to overexpression in N. benthamiana or make sure to not oversaturate the image.

Authors:

Thank you for this hint. Indeed, there are reports that SR45 is a dynamic component inside cells. It can redistribute depending on environmental conditions and associate into larger speckles depending on the nuclear activity status (Ali et al., 2003). We include this reference and refer to it in the discussion, lines 557-564:

“Interestingly, typical FIT NB formation did not occur in the presence of PB markers, indicating that they must have had a strong effect on recruiting FIT. This is interesting because the partially colocalizing SR45, PIF3 and PIF4 are also dynamic NB components. Active transcription processes and environmental stimuli affect the sizes and numbers of SR45 speckles and PB (Ali et al., 2003; Legris et al., 2016; Meyer, 2020). This may indicate that, similarly, environmental signals might have affected the colocalization with FIT and resulting NB structures in our experiments. Another factor of interference might also be the level of expression.”

Line 335: It seems that the colocalization is partial only partial after induction of NB. The FIT NB colocalize around SR45. But it's hard to tell because the images are saturated therefore creating some false overlapping region.

Authors:

The localization of FIT with SR45 is partial and occurs only after FIT has undergone condensation, see lines 335-338.

Line 344-345: It's unappropriated to give the conclusion before the evidence.

Authors:

We explain at an earlier paragraph that we will show three different types of colocalization and introduce the respective colocalization types within separate paragraphs accordingly, see lines 314-321.

Line 353: increase the contrast in the image of t=5 for UAP56H2 since it's hard to assess the colocalization.

Authors:

This is done as noted in the figure legend of Figure 6.

Line 381-382: "In general" does not sound scientific avoid this kind of wording and describe precisely your findings.

Authors:

We rephrased the sentence, line 387-388:

Localization of single expressed PIF3-mCherry remained unchanged at t=0 and t=15 (Supplemental Figure S5A).

Line 384-385: Provide the data and the reference to the figure.

Authors:

We apologize for the misunderstanding and rephrased the sentence, line 389-391:

After 488 nm excitation, FIT-GFP accumulated and finally colocalized with the large PIF3-mCherry PB at t=15, while the typical FIT NBs did not appear (Figure 7A)

Line 386: The structure in which FIT-G is present in the Figure 7A t=15 is not alike the once already observed along the paper. This could be explained by over-expression in N. benthamiana. Please explain.

Authors:

Thank you for the hint. We discuss this in the discussion part, see lines 555-568.

Line 393: Explain and provide data why the morphology of PIF4/FIT NB do not correspond to the normal morphology.

Authors:

Thank you for the valuable hints. Several reasons may account for this and we provide explanations in the discussion, see lines 555-568.

Line 396-398: It seems also from the data that co-expression of PIF4 of PIF3 will affect the portioning of FIT between the NP and the NB.

Authors:

We can assume that residual nucleoplasm is depleted from protein during NB formation. This is likely true for all assessed colocalization experiments. We discuss this in lines 492-494.

The discussion is particularly lengthy it might be great to reduce the size and focus on the main findings.

Authors:

We shortened the discussion.

Referees cross-commenting

All good for me, I think that the comments/suggestions from Reviewer #2 are valid and fair. If they are addressed they will improve considerably the manuscript.

Reviewer #1 (Significance):

This manuscript is describing an unprecedent very precise cellular and molecular mechanism in nutrition throughout a large set of microscopies technics. Formation of nuclear bodies and their role are still largely unexplored in this context. Therefore, this study sheds light on the functional role of this membrane less compartment and will be appreciated by a large audience. However, the fine characterization is only made using transient expression in N. Bentamiana and only few proofs of concept are provided in A. thaliana stable line.

Reviewer #2 (Evidence, reproducibility and clarity):

The manuscript of Trofimov et al shows that FIT undergoes light-induced, reversible condensation and localizes to nuclear bodies (NBs), likely via liquid-liquid phase separation and light conditions plays important role in activity of FIT. Overall, manuscript is well written, authors have done a great job by doing many detailed and in-depth experiments to support their findings and conclusions.

However, I have a number of questions/comments regarding the data presented and there are still some issues that authors should take into account.

Major points/comments:

1) Authors only focused on blue light conditions. Is there any specific reason for selecting only blue light and not others (red light or far red)?

Authors:

There are two main reasons: First, in a preliminary study (not shown) blue light resulted in the formation of the highest numbers of NBs. Second, iron reductase activity assays and gene expression analysis under different light conditions showed a promoting effect under blue light, but not red light or dark red light (Figure 9). This indicated to us, that blue light might activate FIT, and that active FIT may be related to FIT NBs.

2) Fig. 3C and D: as GFP and GFP-GFP constructs are used as a reference, why not taking the measurements for them at two different time points for example t=0 and t=5 0r t=15???

Authors:

Free GFP and GFP-GFP dimers are standard controls for homo-FRET that serve to delimit the range for the measurements.

3) Line 27-271: Acc to the figure 3d, for the Fluorescence anisotropy measurement of NBs appears to be less. Please explain.

Authors:

FA in NBs with FITmSS271AA is variable and the value is lower than that of whole nucleus but not significantly different compared with that in nucleoplasm. We describe the results of Figure 3D in lines 272-275.

4) Figure 4: For the negative controls, data is shown at only t=0, data should be shown at t=5 also to prove that there is no decrease in fluorescence in these negative controls when they are expressed alone without bhlh39 as there is no acceptor in this case.

Authors:

Neither for FIT/bHLH039 nor the FITmSS271AA/bHLH039 pair, there is a significant decrease in the fluorescence lifetime values between t=0 and t=5/15. FIT-G is a control to delimit the range. The interesting experiment is to compare the protein pairs of interest between the different nuclear locations at t=5/15.

5) Line 300-301: In Figure 4D and 4E. Fluorescence lifetime of G measurement at t=0 seems very similar for both FIT-G as well as FITmSS but if we look at the values of t=0 for FIT-G+bhlh039 it is greater than 2.5 and for FITmSS271AA-G+bhlh039 it is less which suggests more heterodimeric complexes to be formed in FITmSS271AA-G+bhlh039. Similar pattern is observed for NBs and NPs, according to the figure 4d and E.

Therefore, heterodimeric complexes accumulated more in case of FITmSS271AA-G+bhlh039 as compared to FIT-G+bhlh039 (if we compare measurement values of Fluorescence lifetime of G of FITmSS271AA-G+bhlh039 with FIT-G+bhlh039).

Please comment and elaborate about this further.

Authors:

These conclusions are not valid as the experiments cannot be conducted in parallel. Since the experiments had to be performed on different days due to the duration of measurements including new calibrations of the system, we cannot compare the absolute fluorescence lifetimes between the two sets.

6) Figure 4: For the negative controls, data is shown at only t=0, data should be shown at t=5 also to prove that there is no decrease in fluorescence in these negative controls when they are expressed alone without bhlh39 as there is no acceptor in this case.

Authors:

Please see our response to your comment 4).

7) Line 439-400: As iron uptake genes (FRO2 and IRT1) are more induced in WT under blue light conditions and FRO2 is less induced in case of red-light conditions. So, what happens to Fe content of WT grown under blue light or red light as compared to WT grown under white light. Perls/PerlsDAb staining of WT roots under different light conditions will add more information to this.

Authors:

We focused on the relatively short-term effects of blue light on signaling of nuclear events that could be related to FIT activity directly, particularly gene expression and iron reductase activity as consequence of FRO2 expression. These are both rapid changes that occur in the roots and can be measured. We suspect that iron re-localization and Fe uptake also occur, however, in our experience differences in metal contents will not be directly significant when applying the standard methods like ICP-MS or PERLs staining.

Minor comments:

Line 75-76: Rephrase the sentence

Authors:

We rephrased the sentence, lines 73-74:

“As sessile organisms, plants adjust to an ever-changing environment and acclimate rapidly. They also control the amount of micronutrients they take up.”

Line 119: Rephrase the sentence

Authors:

We rephrased the sentence, line 118-119:

“Various NBs are found. Plants and animals share several of them, e.g. the nucleolus, Cajal bodies, and speckles.”

Line 235-236: rephrase the sentence

Authors:

We rephrased the sentence, line 232-234:

“In the work of Gratz et al. (2019), the hosphor-mimicking FITmS272E protein did not show significant changes in its behavior compared to wild-type FIT.”

Line 444: Correct the sentence “Fe deficiency versus sufficiency”

Authors:

We corrected that, line 449-451:

“In both, the far-red light and darkness situations, FIT was induced under iron deficiency versus sufficiency, while on the other side, BHLH039, FRO2 and IRT1 were not induced at all in these light conditions (Figure 9I-P).”

Referees cross-commenting

I agree with R1 suggestions/comments and i think manuscript quality will be much better if authors carry out the experiments suggested by R1. I believe this will also strengthen their conclusions.

Reviewer #2 (Significance):

Overall, manuscript is well written, authors have done a nice job by doing several key experiments to support their findings and conclusions. However, the results and manuscript can be improved further by addressing some question raised here. This study is interesting for basic scientists which unravels the crosstalk of light signaling in nutrient signaling pathways.

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

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Reply to the reviewers

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

*In their study, Yamano et al. dissect the mechanism of TBK1 activation and downstream effects, especially in its relation to mitophagy adaptor OPTN. The authors find that OPTN's interaction with ubiquitin and the autophagy machinery, forming contact sites between mitochondria and autophagic membranes, results in TBK1 accumulation and subsequent autophosphorylation. Based on these findings, the authors propose a self-propagating feedback loop wherein OPTN phosphorylation by TBK1 promotes recruitment and accumulation of OPTN to damaged mitochondria and specifically the autophagosome formation site. This formation site is then involved in TBK1 autophosphorylation, and the activated TBK1 can then further phosphorylate other pairs of OPTN and TBK1. A OPTN monobody investigation strengthens their findings. *

*Critique: *

• It would be helpful if the authors could more clearly highlight the previous findings in OPTN-TBK1 relationship and which gaps in the understanding their study addresses.* We thank the reviewer for this comment. As suggested, we have highlighted previous findings and detailed in the Discussion how the study advances our understanding of TBK1 activation.

• It is not always clear whether experiments have been replicated sufficiently; this should be indicated in the figure descriptions.* In the original manuscript, most of the data shown was derived from duplicated experiments. For the revised version, we repeated experiments as needed to generate the replication necessary (i.e, N = 3) for determining statistical significance. Error bars and statistical significance have been added to the graphs and figure legends accordingly.

• During the discussion, references to the figures that indicate conclusions should be added where appropriate.* We thank the reviewer for the suggestion. References to figures have been added were appropriate to the Discussion.

*Figure 1 / Result "OPTN is required for TBK1 phosphorylation and subsequent autophagic Degradation": *

*o In a) the TBK1 and TOMM20 blots feature an image artefact that makes it appear like the blots are stitched together or there was a problem with the digital imager. The quantification in b) seems to be missing replications. *

We found that the artifact came from an automatic pixel interpolation process in Adobe Photoshop when the image was rotated by a small angle. We have provided the original immunoblotting data below as evidence that the data were not stitched from separate images. More accurate representations of the images without the artifact are now shown in Fig1 A of the revised manuscript.

For Fig 1b, the experiment was independently replicated three times with error bars added to each plot on the graph.

*o g) should feature the wt cell line on the same blot for better comparability as well as quantification and replication like done in f) *

As suggested, we have included the WT cell line in the immunoblot (See Fig 1g). In addition, Reviewer 2 asked that we provide data for Penta KO cells without exogenous expression of the autophagy adaptors and expressed concern regarding the lower expression of NDP52 relative to OPTN. To address these issues, we repeated the mitophagy experiments and detected phosphorylated TBK1 in six different cell lines: WT, Penta KO, Penta KO stably expressing OPTN at both low and high expression levels, and Penta KO stably expressing NDP52 at low and high expression levels. Immunoblots of phos-TBK1(pS172), TBK1, OPTN, NDP52, TOMM20, and actin were generated under four different conditions (DMSO, valinomycin for 1 hr, valinomycin for 3 hrs, and valinomycin in the presence of bafilomycin for 3 hrs). In addition, phos-TBK1 abundance in the six cell lines was determined in response to val and baf for 3 hrs and the expression levels of NDP52 and OPTN were similarly determined in response to DMSO. Error bars based on three independent experiments have been incorporated into the data, which are shown in Figure 1g and 1h of the revised manuscript.

*o h) is missing the blots for controls actin and TOMM20 *

Immunoblots for actin and TOMM20 have been added, please see Fig 1i in the revised manuscript.

*o In the text to e/f), the authors write that NDP52 KO effect on pS172 are comparable to controls, though the quantitation in f) indicates that pS172 signal is indeed significantly reduced compared to wt *

The reviewer is correct, the phos-TBK1 (pS172) signal in NDP52 KO cells is reduced compared to that in WT cells, but is only moderately lower in NDP52 KO cells relative to OPTN KO. We regret the error, which has been corrected in the revised manuscript.

*o In the text to h/i), the authors write "there was a significant increase in the TBK1 pS172 signal in cells overexpressing OPTN", though the quantification in i) does not indicate significance levels *

We performed statistical analyses on the phos-TBK1 (pS172) levels between cells with or without OPTN overexpression and have added the degree of significance to Fig 1j. As indicated in the original manuscript, there was a significant increase in phos-TBK1 (pS172) levels when OPTN was overexpressed.

*Figure 2 / Result "OPTN association with the autophagy machinery is required for TBK1 activation": ** o In b), pTBK1 at val 1 hr only features one dot/experiment per cell line *

Three independent replicates of the experiment (val 1 hr) were performed. The levels of phos-TBK1 (pS172), total TBK1, and actin were quantified, and the graph was remade with error bars and statistical significance incorporated. Please see Fig 2b in the revised manuscript.

*o In the text to c), the authors claim that the mutants reduce/abolish the recruitment of OPTN to the autophagosome site. A costain for LC3, as done for SupFig 1b, would be necessary to support that specific claim. *

To address the reviewer’s concern regarding the recruitment of OPTN mutants to the autophagosomal formation site, we performed two different experiments. First, when OPTN WT is recruited to the contact site between the autophagosomal formation site and damaged mitochondria, it should be heterogeneously distributed across mitochondria. In contrast, OPTN mutants that are unable to associate with the autophagosome formation sites should be largely localized to damaged mitochondria since the mutants are still capable of binding ubiquitin. When we examined the mitochondrial distribution of OPTN WT following valinomycin treatment for 1 hr, more than 80% of the Penta KO cells exhibited a heterogeneous distribution, whereas only 10% of the cells showed a similar distribution for OPTN 4LA or OPTN 4LA/F178A (please see Fig 2g in the revised manuscript). Although the OPTN F178A mutant exhibited 50% heterogeneous distribution (Fig 2g), this may be because OPTN F178A retains the ability to interact with ATG9A vesicles. In fact, our previous mitophagy analyses (Keima-based FACS analysis, Yamano et al 2020 JCB), which are strongly correlated with OPTN mitochondrial distribution, showed that the OPTN F178A mutant moderately (~ 60%) induced mitochondrial degradation. This degradation effect was slightly higher (80%) with OPTN WT but significantly lower (9%) with the 4LA/F178A mutant. In the second experiment, Penta KO cells expressing either OPTN WT or the OPTN mutants were immunostained for exogenous FLAG-tagged OPTN, endogenous WIPI2, and HAP60 (a mitochondrial marker) after valinomycin treatment for 1 hr (see Fig 2e and 2f in the revised manuscript). Because LC3B is assembled on the autophagosomal formation site as well as completed autophagosomes, we detected endogenous WIPI2 because WIPI2 is only recruited to autophagosomal formation sites (Dooley et al. 2014 Mol Cell). Confocal microscopy images and their associated quantification data indicate that WIPI2 foci formation during mitophagy was reduced in Penta KO cells expressing the OPTN mutants (4LA, F178A and 4LA/F178A) as compared to Penta KO cells expressing OPTN WT.

*o d) and g) as simple confirmations of KO/KD efficiency might be better suited for the supplemental part, or blots for FIP/ATG be included with the blots in e) and h) *

Based on the reviewer comments, we performed additional experiments related to Figure 2 and have incorporated the new data into the revised figure. The original Figure 2d, e, f, g, h, and I have been moved to supplemental Figure 5.

*o In the text to e), the authors claim that the levels of pS172 in the KO cell lines did not increase during mitophagy, though the blot and quantification in f) seem to indicate an increase. The results therefore don't seem to align completely with the claims that pS172 generation in response to mitophagy requires the autophagy machinery, or that FIP200 and ATG9A rather than ATG5 are critical for TBK1 phosphorylation. *

Although newly generated pS172 TBK1 was reduced in FIP200 KO and ATG9A KO cells relative to WT cells, the signals gradually increased. In the autophagy KO cell lines (FIP200 KO and ATG9A KO), phos-TBK1 accumulates prior to mitophagy stimulation. Although suggesting it is mitophagy-independent, phos-TBK1 accumulation prior to mitophagy stimulation in autophagy KO cell lines complicated interpretation of the results. To avoid this issue, we used siRNA to transiently knock down FIP200 and ATG9A. As shown in the original manuscript (Fig 2g, h, I in the original manuscript, supplementary Fig 5d, e, f in the revised manuscript), knockdown of FIP200 and ATG9A prior to mitophagy induction allowed us to observe mitophagy-dependent phosphorylation of TBK1. This result strongly suggests that the autophagy machinery does induce TBK1 phosphorylation in response to Parkin-mediated mitophagy. However, TBK1 phosphorylation still increases, albeit very slightly, in the FIP200 and ATG9A knock down cells. Thus, it may be reasonable to assume that OPTN-dependent phosphorylation of TBK1 can occur to a certain degree even in the absence of autophagy components. We have noted this in the Discussion.

While conducting experiments for the revised manuscript, we determined that TAX1BP1 is responsible for the accumulation of phos-TBK1 in the autophagy KO cell lines under basal conditions. When TAX1BP1 is knocked down in FIP200 KO or ATG9A KO cells, the basal accumulation of phos-TBK1 was eliminated and then we could observe mitophagy-specific TBK1 phosphorylation (please see Fig 2h, i, j, k in the revised manuscript). These results showed that mitophagy-dependent phos-TBK1 is largely attenuated in FIP200KO and was almost completely eliminated in ATG9A KO cells (Fig 2k in the revised manuscript).

*o f) is missing significance indications. Its description has a typo: "bad" instead of "baf" *

Newly synthesized pTBK1 (pS172) during mitophagy was quantified and statistical significance incorporated into the figure (please see supplementary Fig 5c). The identified typo has been corrected.

*Figure 3 / Result "TBK1 activation does not require OPTN under basal autophagy conditions": *

*o In the text to SupFig2, the authors claim that pS172 levels are significantly elevated, but no significance levels are indicated *

Statistical significance was determined for all proteins shown in original supplementary Fig 2 and the results have been incorporated into the relevant figure. The original supplementary Fig 2 is now supplementary Fig 6.

*o In the text to a), NBR1 is claimed to colocalize with Ub, but no costaining with Ub is shown. The claimed lacking colocalization of OPTN with Ub is not obvious from the images; a quantification might be appropriate. *

Since the anti-NBR1 antibody used in the original manuscript is derived from mouse, we were unable to use it in conjunction with the mouse ubiquitin antibody. Because ubiquitin-positive foci and NBR1-positive foci contain p62 (original Fig 3a) and NBR1 and p62 are known to tightly interact each other (Kirkin et al. 2009 Mol Cell and Sanchez-Martin et al. 2020 EMBO Rep), we stated that "NBR1 colocalizes with Ub". However, the reviewer is correct. To remedy this confusion, we obtained a rabbit anti-NBR1 antibody (a gift from the Masaaki Komatsu group) and used it to co-immunostain with anti-Ub antibodies (please see supplementary Fig 7a of the revised manuscript). NBR1 foci colocalize with both ubiquitin and p62 in FIP200 KO and ATG9A KO cells. Further, based on comments from Reviewer 2, we purchased several anti-TBK1 antibodies and identified one that was able to detect endogenous TBK1 by immunostaining (see Figure 1 for reviewers in our response to Reviewer 2 below). Using this anti-TBK1 antibody, we showed that a part of TBK1 also associates with ubiquitin and p62-positive aggregates.

*o In the text to b), the authors make reference to significant changes, but replication/ quantification/ significance testing is missing. *

We independently performed the same experiments three times. The levels of TBK1, phos-TBK1 (pS172), all five autophagy adaptors, and TOMM20 in both the supernatants and pellets have been quantified with error bars and statistical significance indicated. These results have been incorporated into Figure 3c in the revised manuscript.

*Figure 4b) is missing the pTBK1 data that is referenced in the text. In the text to figure 5 c/d), the authors claim that certain mutants have no significant effect on mitophagy, though d) is missing significance testing *

*Figure 6 c/d/i) appear to be missing replication. *

For Figure 4b, phos-TBK1 was immunoblotted (See Fig 4b of the revised manuscript). For Figure 5b and d, statistical significance was determined for the effect of TBK1 mutations on autophosphorylation and OPTN phosphorylation and the effect of the TBK1 mutants on Parkin-mediated mitophagy. For Figure 6 c/d/I, the experiment was repeated; error bars and statistical significance have been added to the associated graphs.

*Reviewer #1 (Significance (Required)): Removal of damaged mitochondria by the mitophagy pathway provides an important safeguarding mechanism for cells. The Pink1/Parkin mechanism linked to numerous modulators and adaptor proteins ensures an efficient targeting of damaged mitochondria to the phagophore. The Ser/Thr kinase TBK1, in addition of multiple roles in innate immunity, is a major mitophagy regulator as has been revealed by the Dikic and Youle groups in 2016 (Richter et al., PNAS). The mechanistic insights provided by this manuscript add to a growing body of studies of how the autophagy machinery interconnects with cellular signalling networks. Although parts of the results need to be further validated, the data shown is of high quality, revealing an important conceptual advance. The paper is interesting and of general relevance beyond the signalling and autophagy community. *

We would like to thank Reviewer 1 for the comments and suggestions, many of which improved our manuscript. We hope that the reviewer’s comments have been adequately addressed in the revised manuscript.

*Reviewer #2 (Evidence, reproducibility and clarity (Required)): Summary In this manuscript, Yamano and colleagues show that as for Sting-mediated TBK1 activation, Optn provides a platform for TBK1 activation by autophosphorylation and that TBK1 is activated after the interaction of Optn with the autophagy machinery and ubiquitin and not before. They show that TBK1 phosphorylation is blocked by bafilomycine A1, an inhibitor of vacuolar ATPases that blocks the late phase of autophagy. Furthermore, they demonstrate that Optn is require for TBK1 phosphorylation since variation of Optn expression regulates TBK1 phosphorylation in response to PINK/Parkin-mediated autophagy. Interestingly, using immunofluorescence microscopy, they show that Optn forms sphere like structures at the surface of damage mitochondria which are more dispersed in the absence of TBK1. In addition, TBK1 is also recruited at the surface of damage mitochondria and as Optn and NDP52 (but not p62) colocalize with LC3B in response to PINK/Parkin-mediated mitophagy. Next, it is demonstrated that the Leucin zipper and LIR domains of Optn (which modulate Optn interaction with autophagosome) play an important role for TBK1 activation. Additionally, the autophagy core is shown to be required for TBK1 activation. Under basal conditions, depletion of the autophagosome machinery leads to an increase in autophagy receptors (except Optn) and TBK1 phosphorylation which colocalize with ubiquitin in insoluble moieties. In contrast, Optn remains cytosolic and is dispensable for TBK1 activation in these conditions. Then, using the fluoppi technic, the authors demonstrate that the generation of Optn-Ubiquitin condensates recruits and activates TBK1. They express in HCT116 TBK1-deficient cells engineered or pathological ALS mutations of TBK1 that affect ubiquitin interaction, structure, dimerization and kinase activity of TBK1. The expression level of TBK1 was only affected by the dimerization-deficient mutations. None of the mutations impaired Optn and TBK1 ubiquitination. Interestingly, some ALS-associated mutations affect TBK1 activity and it is said in the text that the dimerization-deficient mutations of TBK1 affect its activity proportionally to their level of expression, which is not really correct (the expression level of the mutants is very heterogenous and not always correlate to their activity). Regarding their effect on mitophagy, the authors claim that the phosphorylation of TBK1 correlate with mitophagy which is not really the case. By using TBK1 inhibitor or TBK1-depleted cells, the authors conclude that TBK1 is the only kinase phosphorylating Optn. However, BX-795 is not completely specific to TBK1. Finally, the authors use monobodies against Optn effective in inhibiting mitophagy in NDP52 KO cells. Some of the monobodies have been shown to form a ternary complex with Optn and TBK1, while others compete for the interaction between Optn and TBK1 which involves the amino-terminal region of Optn and the C-terminal region of TBK1. Monobodies that compete for the interaction of Optn with TBK1 could alter the cellular distribution of Optn and inactivate TBK1, but they do not alter the ubiquitination of Optn. Finally, these monobodies inhibit 50% of mitophagy. *

*Major and minor points: Introduction The first paragraph of the Introduction section is confused and difficult to read. First and second paragraphs (page 3 and top of page 4) are dedicated to macroautophagy processes but ended with one sentence on Parkin-mediated autophagy without further introduction, while all processes regarding mitophagy are detailed in the next paragraph. Links between ideas developed are also somewhat missing. For example, in page 6, the three last sequences detailed the phosphorylation of autophagosome component, the fact that Optn and TBK1 genes are involved in neurodegenerative diseases and autophosphorylation of TBK1 as a pre-requirement for TBK1 activation without evident links between them, except "interestingly". *

In response to the reviewer’s suggestion, we have rewritten the Introduction. The first paragraph focused on introducing the molecular mechanism underlying macroautophagy and the second paragraph focused on Parkin-mediated mitophagy. As the reviewer indicated, the ALS mutations and TBK1 phosphorylation during Parkin-mediated mitophagy are not well related, so we moved the background material on the relationship between OPTN and TBK1 in neurodegenerative diseases to the beginning of the section describing Figure 5. We believe these changes have made the Introduction easier to read and understand.

*Results *

*Major points: *

*1- Results are often over-interpreted regarding data obtained leading to inadequate conclusions (see below for details); *

We regret the reviewer’s concerns regarding over-interpretation. To address this issue, we have carefully considered the data, performed additional experiments where necessary, and rewritten the results accordingly. Please see our point-by-point responses below.

*2- Quantification of protein levels detected by western blot are provided as "relative intensities" without referring to specific loading control or to total protein when -phosphorylated forms are quantified (Fig. 1b, 1d, 1f, 1i, 2b, 2f, 2i, 5b, 7b, supplemental figures 2b). *

For the immunoblots, we loaded the same amount of total cell lysate and the phosphorylated forms were quantified relative to the total protein input. This has been mentioned in the Materials and Methods.

*3- In western blotting experiments, authors described slower migrating bands as "ubiquitinated" forms of detected proteins, but never provided experimental evidences that it could be the case. Use of non-specific deubiquitinase incubation of extracts prior to western blot could help to correctly identified ubiquitination versus other post-translational modifications such as phosphorylation, glycosylation, acetylation etc... *

We appreciate the reviewer’s suggestion. The cell lysates after mitophagy induction were incubated in vitro with a recombinant USP2 core domain (non-specific DUB), and then immunoblotted. As shown in supplemental Fig 1 of the revised manuscript, the slower migrating OPTN bands disappeared in a USP2-dependent manner. The slower migrating NDP52 and TOMM20 bands likewise disappeared. These results confirm that the slower migrating OPTN, NDP52, and TOMM20 bands are ubiquitinated.

*4- Conclusions from data obtained by immunofluorescent imaging are often drawn from only one image presented without further statistical analysis. *

Statistical significance was determined for the immunofluorescent data (original figures 1j, 2c and 3a). Please see Fig 1l, 2f, 2g, and 3a in the revised manuscript.

*Page 7: - authors referred to TBK1 phosphorylation induced by mitophagy induction as "TBK1 phosphorylation induced by Parkin-mediated ubiquitination" while mitophagy can be induced independently of Parkin (ex: via mitochondrial receptors) and without any evidence (according to referee's knowledge) of a link between ubiquitination by Parkin and TBK1 phosphorylation. *

As the reviewer indicated, Parkin-independent and ubiquitination-independent mitophagy pathways are also known (i.e. receptor-mediated mitophagy driven by NIX, BNIP3, BCL2L13, FKBP8, FUNDC1, or Atg32). Therefore, references to "mitophagy" in our manuscript were reworded as "Parkin-mediated mitophagy". Since TBK1 phosphorylation is observed before mitochondria are degraded and is dependent on Parkin-mediated ubiquitin (for example, see Fig 1c), we use the phrase "TBK1 phosphorylation triggered by Parkin-mediated OMM ubiquitination".

*Fig 1g: Western blots performed in Penta KO cells without exogene expression of any autophagy receptors should be provided as control. Furthermore, lower expression of NDP52 relative to that of Optn (using flag antibodies) should be discussed as it can explained the differential levels in TBK1 phosphorylation observed. *

As suggested, we repeated the experiment using Penta KO cells in the absence of exogeneous autophagy adaptor expression. Furthermore, we expressed different amounts of NDP52 and OPTN (indicated as low and high in the figure) in Penta KO cells to rule out the possibility that higher TBK1 phosphorylation is induced by simple overexpression of autophagy adaptor (please see Fig 1g and h in the revised manuscript). At high NDP52 expression (2.5-3.0-fold higher than endogenous NDP52), phosphorylated TBK1 was reduced to ~30% the level of that observed in WT cells after 3 hrs with val and baf. In contrast, Penta KO cells with higher OPTN expression (3.0-fold higher than endogenous OPTN) had phosphorylated TBK1 signals that were 2-fold higher than those in WT cells. Based on these results, we concluded that OPTN is an important adaptor for TBK1 activation during Parkin-mediated mitophagy.

*Page 8: Supplemental Fig 1a: - The inability of authors to observe TBK1 endogenous signal in HeLa cells using commercially available antibodies is surprising as many publications reported successful staining (see Figure 1 of Suzuki et al. 2013 Cell type-specific subcellular localization of phospho-TBK1 in response to cytoplasmic viral DNA. PLoS One. 8:e83639 among others) as well as commercial promotion (see Anti-NAK/TBK1 antibody from Abcam reference: ab235253). *

For the original manuscript, anti-TBK1 antibodies purchased from abcam (ab235253), CST (#3013S), Proteintech (28397-1-AP), and GeneTex (GTX12116) for immunostaining were unable to yield TBK1-positive signals (please see Fig 1 for reviewers below). WT and TBK1-/- HCT116 cells stably expressing Parkin were treated with valinomycin for 1 hr and immunostained with the indicated antibodies. Anti-phos-TBK1 antibody (CST, #5483) was used as a positive control. Based on these results, we stated in the original manuscript that the "endogenous TBK1 signal could not be observed using commercially available antibodies". At the reviewer’s suggestion, we purchased anti-TBK1 antibodies from abcam (ab40676) and CST (#38066). As shown in the figure below, the immunofluorescent signals generated by these antibodies were detected in WT, but not in TBK1-/- cells. The CST (#38066) antibody yielded a stronger signal, most of which was on damaged mitochondria. Thanks to this suggestion, we repeated the experiment using the new anti-TBK1 antibody. Furthermore, based on a suggestion from Reviewer 3, we detected mitochondrial recruitment of TBK1 during mitophagy stimulation (valinomycin for 30 min or 2 hrs in the presence and absence of bafilomycin; supplemental Fig 2 in the revised manuscript). We also detected association of endogenous TBK1 with ubiquitin-positive condensates in WT, FIP200KO, and ATG9A KO cells (Fig 3a and supplementary Fig 7a in the revised manuscript).

*- Conclusions of the localization of signal on mitochondria (dispersed, in the periphery or at contact sites) are clearly over-interpreted in the absence of other membrane or autophagosome specific labeling and statistical colocalization analyses of multiple images. It is particularly difficult to assess any difference between Tax1BP1, p62 and NBR1 localization on mitochondria subdomains. *

We previously expressed each FLAG-tagged autophagy adaptor in Penta KO cells and observed their localization during Parkin-mediated mitophagy and found that exogenous FLAG-tagged OPTN and NDP52, but not p62, colocalized with LC3B (Yamano et al 2020 JCB). No one has assessed and compared the localization of all five endogenous autophagy adaptors. Although we still believe that the results (supplemental Fig1 in the original manuscript) are informative for researchers in the autophagy field, we decided to remove that data from the revised manuscript since they are not the main focus of the study. We will consider publishing those data elsewhere in the future after co-staining with autophagosome markers and assessing the statistical significance of colocalization as the reviewer suggested.

*Page 9: *

*- First part of results ended without any conclusions. *

As detailed in the previous response, we have removed results for mitophagic recruitment of autophagy adaptors (supplementary Figure 1 in the original manuscript).

*- The observation that "TBK1 phosphorylation was not apparent in the Optn mutant cell lines, even after 3 hrs of valinomycin, ..." is inconsistent with detection of bands with anti-pS172-TBK1 antibodies in Fig 2a detected at 1hr (with F178A) and 3 hrs (4LA, F178A, and 4LA/F178A mutants) of treatment. *

We apologize for the confusion. This statement was clearly our mistake. We had intended to state when "all autophagy adaptors are deleted" no phosphorylated TBK1 was observed. We have rewritten this part as "TBK1 phosphorylation was not apparent in the Penta KO cells even after 3 hrs with valinomycin".

*- Similarly, decreased levels of phosphorylated TBK1 stated for F178A mutant was only observed at 1 but not 3hrs or at 3hrs in the presence of bafilomycin. *

Based on the mitophagy assay previously reported (Yamano et al 2020 JCB), the F178A mutant only moderately inhibited mitophagy (60% mitophagy with the F178A mutant vs 80% mitophagy with OPTN WT). Conversely, the 4LA mutant and 4LA/F178A double mutant had stronger inhibitory effects on mitophagy (35% for 4LA and 9% mitophagy for 4LA/F178A). Therefore, the levels of phos-TBK1 after 1 hr with valinomycin or 3 hrs with valinomycin in the presence of bafilomycin are consistent with mitophagy progression. When mitophagy proceeds efficiently, the amount of phos-TBK1 in the 1 hr val samples is reduced relative to the 3 hr val samples due to autophagic degradation.

To more clearly observe and compare the levels of mitophagy-dependent phos-TBK1 among Penta KO cells expressing OPTN WT and the mutants, we treated cells with valinomycin in the presence of bafilomycin for 0, 0.5, 1, and 2 hrs and quantified phos-TBK1. The results are shown in Fig 2c and d in the revised manuscript. The phos-TBK1 signal increased over time with val and baf treatment in all OPTN expressing cells. Cells with OPTN WT generated the most phos-TBK1, whereas the signal generated by the F178A mutant was 75% that of the OPTN WT-expressing cells and the 4LA and 4LA/F178A mutants were about 40%. The experiments were independently replicated three times and error bars and statistical significance were incorporated into the associated graph. These results indicate that OPTN association with the autophagy machinery, in particular ATG9A vesicles, is important for TBK1 activation.

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*The results and their repartition between figure 2 d, e, f, g, h, I and figure 3 is a bit confusing. In these experiments, it is shown Figure 2 that the absence or depletion of the autophagy machinery increase the phosphorylation of TBK1 and in Figure 3 it is shown that not only the phosphorylation of TBK1 accumulate but also the expression of NDP52, Tax1BP1 and p62. Is it because their degradation by autophagy is blocked (like for phosphoTBK1)? *

The reviewer is correct that autophagy adaptors other than OPTN (especially TAX1BP1, p62 and NBR1) are constantly degraded by macro/micro autophagy (Mejlvang et al. 2018 J Cell Biol and Yamano et al. 2021 BBA Gen Subj). Therefore, these adaptors accumulate in autophagy deficient cell lines (original Fig 3). In this study, we found that in the absence of mitophagy stimulation phos-TBK1 accumulates in autophagy deficient cell lines. This suggests that the accumulated autophagy adaptors induce TBK1 phosphorylation under basal conditions. In the original manuscript, we claimed that TBK1 phosphorylation under basal conditions does not require OPTN since in FIP200 KO and ATG9A KO cells it did not accumulate and did not primarily colocalize with ubiquitin- and TBK1-positive foci (original Fig 3). To gain more direct evidence for the revised manuscript, we performed additional experiments and discovered that TAX1BP1 is the adaptor responsible for TBK1 autophosphorylation under basal autophagy. We treated FIP200KO and ATG9A KO cells with siRNAs against OPTN, NDP52, TAX1BP, p62, and NBR1, and immunoblotted total cell lysates with an anti-phos-TBK antibody. As shown in Fig 3f in the revised manuscript, TAX1BP1 siRNA treatment decreased phos-TBK1 levels without affecting total TBK1. This result indicates that the accumulation of TAX1BP1 in the FIP200 KO and ATG9A KO cells induced TBK1 autophosphorylation under basal conditions. Considering this result, we treated WT, FIP200 KO, and ATG9A KO cells with TAX1BP1 siRNA, and then induced Parkin-mediated mitophagy with valinomycin in the presence of bafilomycin. This strategy eliminated the basal accumulation of phos-TBK1 and allowed us to focus on mitophagy-dependent TBK1 phosphorylation. Please see revised Fig 2h, I, j, and k. The results showed that mitophagy-dependent phos-TBK1 is predominantly attenuated in FIP200 KO and ATG9A KO cells. In Figs 2 and 3, we would like to emphasize that OPTN is required for TBK1 phosphorylation in response to Parkin-mediated mitophagy, whereas TAX1BP1 is required for TBK1 phosphorylation in basal autophagy. Since Reviewer 3 commented that interpretation of the data in original Figs 2d, e, and f was challenging, we elected to move those results to the supplemental figures. We have incorporated the newly acquired data (mitophagy using FIP200 KO or ATG9A KO with TAX1BP1 siRNA cells) into the main figure. We believe that this makes the text easier for readers to understand.

*- Fig 2c: conclusions on *

*the reduction of recruitment of Optn mutants on autophagosome formation seem over-interpreted as: *

*1- no labeling with LC3 has been used to identified autophagsome, *

*2- immunofluorescent signals observed with mutants are dispersed throughout the entire mitochondria network (see the merged images) rendering impossible to distinguish between autophagosome-associated mitochondria and others. *

*The following conclusive sentence stating that association of Optn to damaged mitochondria is not sufficient for TBK1 activation based solely on IF of figure 2c seems therefore unrelated to the obtained data. *

To address concerns about the recruitment of OPTN mutants to the autophagosome formation site, we performed additional experiments. Penta KO cells and those expressing OPTN WT and mutants were treated with valinomycin for 1 hr, and FLAG-tagged OPTN, endogenous WIPI2, and HAP60 (mitochondrial marker) were detected by immunostaining. We detected endogenous WIPI2 because WIPI2 is recruited only to autophagosome formation sites (Dooley et al. 2014 Mol Cell), whereas LC3B assembles on autophagosome formation sites and is also associated with completed autophagosomes. Confocal microscopy images showed that cup-shaped OPTN WT that had been recruited to damaged mitochondria colocalized with WIPI2. Quantification further showed that during mitophagy the number of WIPI2 foci seen in cells expressing OPTN WT decreased in Penta KO cells and cells expressing OPTN mutants (4LA, F178A and 4LA/F178A). These data are shown in Fig 2e and f in the revised manuscript. In addition, we quantified the number of cells that either exhibited heterogeneous or homogeneous recruitment of OPTN to damaged mitochondria after treatment with valinomycin for 1 hr. More than 80% of Penta KO cells with OPTN WT had heterogeneous OPTN recruitment, whereas this distribution was only present in 10% of cells expressing either OPTN 4LA or OPTN 4LA/F178A. Although cells expressing the OPTN F178A mutant exhibited 50% heterogeneous recruitment, this may be because the mutant can interact with ATG9A. As mentioned above, our previous mitophagy analyses (Keima-based FACS analysis, Yamano et al 2020 JCB) showed that the OPTN F178A mutant induced ~60% mitochondrial degradation (which is correlated strongly with OPTN distribution), whereas it was 80% with OPTN WT and 9% with 4LA/F178A.

*- Fig 2d: authors should explain why ATG KO cells displayed lipidated LC3B in the absence of efficient autophagy processes. *

We thank the reviewer for the suggestion. We added the following sentence to explain the function of ATG5 in LC3B lipidation. "Since LC3B lipidation is catalyzed by ATG5, but not FIP200 and ATG9A, the lipidated form disappears only in ATG5 KO cells (Hanada et al 2007 J Biol Chem). "

*- Fig 2e: despite authors statement that TBK1 phosphorylation did not increase during mitophagy in ATG KO cells, increased pS172-TBK1 is visible in FIP200 and ATG5 KO cells especially between 1 and 3 hrs of stimulation, leading to inaccurate conclusions that TBK1 phosphorylation requires the autophagy machinery. Therefore, overall assumption that both ubiquitination and autophagy subunits are required for TBK1 autophosphorylation appears erroneous. *

As the reviewer indicated, phos-TBK1 levels gradually increased in ATG KO cells. The main text was rewritten to more accurately reflect this increase. Based on experiments using the monobodies and those conducted during the revision process, it is apparent that although the autophagy machinery may not be completely essential for TBK1 phosphorylation, it clearly facilitates TBK1 phosphorylation in response to Parkin-mediated mitophagy.

*Page 12: *

*- Fig 3a: conclusion that Optn signal is more cytosolic and did not localize with Ub condensates seems speculative as based on: *

*1- only one immunofluorescence image without statistical analysis *

*2- Optn and Ub signals are lower in images with Optn is analyzed compared to other images in which NDP52, TAX1BP1 and NBR1 are detected. *

To address these concerns, we compared and quantified the signal intensities of all endogenous autophagy adaptors in FIP200 KO and ATG9A KO cells. The quantification data are shown in Fig 3a and the immunofluorescence images are shown in supplementary Fig 6a of the revised manuscript.

*- Fig 3b: interpretation of western blot data is uncertain due to lack of appropriate loading control, especially with pellets (P) extracts. In addition, it is not clear how to conclude from the experiments in Fig 3b that autophagy adaptors other than Optn mediate TBK1 phosphorylation. *

When autophagy is inhibited, p62 accumulates in the cytosol as aggregates (Komatsu et al. 2007 Cell). Therefore, p62 should be a positive control. Indeed, Fig 3b in the original manuscript (Fig 3b and c in the revised manuscript) showed that the amount of p62 in the pellet fraction was elevated in FIP200 KO and ATG9A KO cells. Furthermore, these aggregates were also observed in the imaging data (Fig 3a and supplementary Fig 7 in the revised manuscript). As the reviewer indicated, the original manuscript did not clarify whether autophagy adaptors other than OPTN mediated TBK1 phosphorylation; however, our revised results clearly demonstrate that TAX1BP1 is the adaptor responsible inducing TBK1 autophosphorylation when basal autophagy is impaired (please see Fig 3f in the revised manuscript).

*Minor point: reference is missing in the last sentence of the paragraph stating that K48-linked chains dominate when autophagy pathways are impaired. *

While several autophagy adaptors preferentially interact with K48-linked ubiquitin chains (Donaldson et al. 2003 PNAS etc), TRAF6 is recruited to ubiquitin-condensates via p62-mediated K63-linked ubiquitination (Linares et al. 2013 Mol Cell). Furthermore, K33-linked ubiquitin chains are also present in p62-positive condensates (Nibe et al. 2018 Autophagy). Because it’s not clear which ubiquitin-linkage is dominant in the condensates, we decided to delete the sentence. We regret the confusion.

*Page 13: *

*Conversely to Optn, they find that the other autophagic receptors localize in insoluble fractions (what does it mean?) independently of TBK1 expression (experiments with DKO cells) and also independently of Optn (where is this shown?). Altogether, these experiments are far from the message of the manuscript. The title of the paragraph "TBK1 activation does not require Optn under basal autophagy conditions" is not correct because even if the level of expression of autophagic receptors and TBK1 phosphorylation are increase in response to the depletion of the autophagy machinery, it does not increase autophagy. *

According to the suggestion, we changed the title of the paragraph to "TAX1BP1, but not OPTN, mediates TBK1 phosphorylation when basal autophagy is impaired." In addition, we rewrote this section.

*- Fig 3d: authors should mention the nature of the upper band observed in Optn western blot and show the same experiment in since solely TBK1 depleted cells since they stated that "electrophoretic migration of Optn was not affected by TBK1 deletion". In addition, suggesting from these sole experiments that "NP52, TAX1BP1, p62, NBR1 and AZI2 form Ub-positive condensates where TBK1 is activated" seems over-interpretated. *

Reviewer 3 suggested we characterize the upper band in the OPTN blot (Fig 3d in the original manuscript). To determine if the band is genuine OPTN, we used phostag-PAGE to analyze cell lysates from cells treated with control siRNA or OPTN siRNA and found that both the lower and upper bands were OPTN species (please see "Figure 2 for reviewers" in our response to Reviewer 3). The same pattern was reported by the Wade Harper group (Heo et al. 2015 Mol Cell). They showed that the OPTN double band pattern on phos-tag PAGE was not affected by TBK1 deletion. We have cited this literature where appropriate in the revised manuscript. In WT cells, it is difficult to detect phosphorylation of autophagy adaptors by TBK1 because basal autophagy constantly degrades them. That’s why we used autophagy KO cell lines.

*Page 14: *

*- Fig 4: TBK1 phosphorylation was analyzed in Fig4d and not in Fig4b as stated. In addition, it is rather difficult to conclude from artificial multimerization experiments, as the authors have done, that interaction between Optn and autophagy components contributes to Optn multimerization in genuine conditions. *

Detection of phos-TBK1 has been corrected to Fig 4b. Although artificial, the fluoppi assay provides insights into how OPTN activates TBK1 and how the autophagy machinery contributes to TBK1 activation via OPTN. To determine if artificial OPTN multimerization could bypass the autophagy machinery requirement, we used the fluoppi assay. This assay was important for us to conclude that the autophagy machinery and Parkin-mediated ubiquitination allow OPTN to be assembled in close proximity to where TBK1 is activated. The main text was rewritten to better convey the benefits of the fluoppi assay.

*Page 15: *

*This work could have therapeutic consequences but the pathological mutants of TBK1 used affect ALS (Figure 5) while in the discussion it is proposed that monobodies could have a therapeutic interest in familial forms of glaucoma due to the E50K mutation of Optn. It should be better to target only one pathology. *

Both TBK1 and OPTN are causative genes for ALS and many pathogenic mutations are known to impact their function. In this study, we focused on ALS mutations in TBK1 that affect self-dimerization and investigated their impact in response to Parkin-mediated mitophagy. We created the monobodies as a tool to physically inhibit OPTN assembly at the contact site. Although our monobodies inhibit Parkin-mediated mitophagy, they would not be a useful therapeutic strategy for ALS due to the loss of function with the TBK1 mutations. However, because TBK1 E50K is a glaucomatous mutation that causes OPTN-TBK1 to bind more tightly, our monobodies might be applicable to glaucomatous pathology since they could disrupt this interaction. We thus feel that it is appropriate to mention the potential of the monobodies and their future utility in the Discussion.

*- Fig 5c, d: Authors stated that degree of TBK1 autophosphorylation correlated with OPTN phosphorylation at S177 whereas phosphorylated TBK1 is unaffected by L693Q and V700Q mutants that display decreased phosphorylated Optn In addition, authors interpretation of Figure 5 data is clearly problematic as they stated that: *

*1- neither 693Q and V700Q mutants had "significant effect on mitophagy", while decreasing efficiency from 78% to 37-51% *

*2- but conclude that 49.7% mitophagy levels of R357Q mutant is significant mitochondrial degradation. *

*Overall conclusion that mitophagy efficiency is correlated with phosphorylated TBK1 levels is therefore inaccurate. *

We regret that this section did not sufficiently describe the data. Reviewer 3 also noted that the text referencing Fig 5 was difficult to interpret. One of the reasons for the complicated data interpretation is the number of TBK1 mutants used. The L693Q and V700Q mutations used by Li et al. (2016 Nat Commun) were expected to inhibit Parkin-mediated mitophagy since those authors reported that the mutations prevented interactions with OPTN. However, our in-cell assay showed that the two mutations only moderately affected Parkin-mediated mitophagy. Furthermore, both the L693Q and V700Q mutations were engineered based on the X-ray structure, rather than being authentic pathogenic ALS mutations. To avoid any potential confusion, we decided to remove the L693Q and V700A data. We have re-evaluated the other data and have rewritten this section accordingly. Please see the revised main text.

*Discussion *

*Minor points: *

*page 20: - reference is missing in the sentence "Optn cannot oligomerize on its own on ubiquitin-decorated mitochondria". *

We have provided the appropriate reference.

*Major points: *

*Authors stated that they showed that Optn recruitment to damaged mitochondria, itself, is insufficient for TBK1 autophosphorylation, but did not show experiment of Optn recruitment to mitochondria and its consequences on TBK1 phosphorylation in the absence of mitophagy induction signal. Authors could for example target HA-Ash-6Ub to mitochondria in order to artificially recruit hAG-Optn to "ubiquitinated" mitochondria in the absence of mitophagy signal. *

We showed that the efficiency of TBK1 autophosphorylation was reduced in cells expressing the OPTN 4LA/F178A mutant, which cannot interact with the autophagy machinery (Fig 2c and d in the revised manuscript). Cells with FIP200 or ATG9A knockdown also have reduced phos-TBK1 (pS172) as shown in supplementary Fig 5e and f. The rate of phos-TBK1 (pS172) generation in ATG9AKO cells during Parkin-mediated mitophagy is reduced relative to that in WT cells (Fig 2j and k). Since a small amount of phos-TBK1 was generated in both ATG9A knockdown and KO cells (supplementary Fig 5e, f, Fig 2j and k), we concur that it would be premature to conclude that phosphorylation of TBK1 does not occur at all when autophagy core components are absent. A small amount of phos-TBK1 may be generated by OPTN that is freely distributed on the outer mitochondrial membrane. In the revised manuscript, we mention the possibility that TBK1 might be phosphorylated by OPTN independent of the autophagy machinery and were careful to avoid over-interpretation.

As shown in Fig 4, fusing OPTN with an Azami-Green tag can induce artificial multimerization and trigger the generation of phos-TBK1 (pS172). Therefore, we expect that mitochondria-targeted HA-Ash-6Ub would induce TBK1 phosphorylation in a hAG-OPTN-dependent manner as was observed with cytosolic HA-Ash-6Ub (Fig 4). The accumulation of OPTN at the contact site in Parkin-mediated mitophagy is important for TBK1 phosphorylation. Even if OPTN is forced to anchor to the mitochondria, this would induce isolation membrane formation and subsequent autophosphorylation of TBK1. Therefore, the utility of forcing OPTN to anchor to mitochondria is questionable.

*Similarly, experimental approaches used by authors lack dynamics parameters to conclude on formation and elongation of isolation membranes and contacts sites that could be probably obtained through video microscopy. *

Based on the reviewer’s comment, we performed time-lapse microscopy to observe OPTN recruitment to the contact site and followed its movement along with the elongation of isolation membranes during Parkin-mediated mitophagy. HeLa cells stably expressing GFP-OPTN and pSu9-mCherry (a mitochondrial marker) were treated with valinomycin (please see Fig 2l in the revised manuscript). Initial recruitment of GFP-OPTN near mitochondria was evident as small dot-like structures that then elongated over time to become cup-shaped structures and culminated in the formation of spherical structures. Considering the colocalization of OPTN with WIPI1/WIPI2 (markers of autophagosome formation site) in Fig 2e and supplementary Fig 2a, the time-lapse images strongly suggest that OPTN assembles at contact sites followed by elongation in tandem with isolation membranes during Parkin-mediated mitophagy.

*Finally, the model proposed by the authors does not take into account data showing that Optn basally interacts with ubiquitinated mitochondria and LC3 family members (see Wild et al., Phosphorylation of the autophagy receptor optineurin restricts Salmonella growth. Science. 2011 333:228-33), although at lower levels compared to induced conditions, relativizing the impact of the proposed model. *

According to the Reviewer 2 comment, we again read the Science paper (Wild et al. 2011) but could not find data showing that OPTN basally interacts with ubiquitinated mitochondria. At least, we think that under steady state conditions without mitophagy induction, mitochondrial ubiquitination and mitochondrial localization of OPTN are undetectable as shown in supplementary Figure 2 in our revised manuscript.

*In conclusion, this manuscript represents a lot of work but the experiments often lack controls and are over-interpretated. *

***Referees cross-commenting** *

*In my opinion, what emerges from these 3 reviews is that the results lack controls or have not been repeated enough to support the message that the interaction of Optn with ubiquitin and the ubiquitination machinery is sufficient to activate TBK1. In particular, as reviewer 1 says, the phosphorylation kinetics shown in Figure 1a are not consistent with TBK1 phosphorylation following the interaction of Optn with the ubiquitination machinery and ubiquitin. In Figure 1e, there is a decrease in TBK1 phosphorylation in contrast to WTcells as mentioned by Reviewer 1. In agreement with Reviewer 1, we believe that the WT cells are missing in Figure 1g. *

*With regard to Figure 2c, we agree with reviewer 1 that an LC3 label is missing in order to be able to interpret the data. In Figure 2e and f, we agree with reviewer 1 that it is difficult to understand why TBK1 phosphorylation increases in the absence of the autophagy machinery (FIP200 KO and ATG5KO). In Figure 3, loading controls are missing for 3b and c. The TBK1 KO cells alone are missing in Fig 2d. In Figure 2b, pTBK1 is missing. In agreement with reviewer 3, we believe that the data with fluoppi contradict the message of the manuscript since they show that TBK1 can be phosphorylated by ubiquitin in the absence of the ubiquitination machinery. In agreement with reviewer 3, we believe that the experiments in Figure 5 are very difficult to interpret. The first reviewer is right to ask the question of the replicates for figures 6c and d. *

We appreciate the summary of the reviewers’ comments. To address their concerns, we have included the appropriate controls and included the results of three independent experiments in the graphs, which now include appropriate error bars and statistical significance. Thus, we believe we have answered the most critical comments concerning the lack of controls.

In Fig 1a, phos-TBK1 was maximal following 30 min of valinomycin treatment. We confirmed using microscopy-based observations that recruitment of endogenous TBK1 and OPTN and the generation of phos-TBK1 and phos-OPTN at contact sites (marked by WIPI1) near damaged mitochondria was also maximal after 30 min of valinomycin treatment (supplementary Fig 2 and 3). Therefore, the kinetics of phos-TBK1 and phos-OPTN generation are consistent with the recruitment of OPTN-TBK1 to the contact site.

The data presented in Fig 2 clearly indicate that the autophagy components are involved in phos-TBK1 generation during Parkin-mediated mitophagy. Therefore, the claim that ubiquitination machinery is sufficient for TBK1 activation is incorrect. Although we agree that the autophagy gene deletions cannot completely inhibit TBK1 autophosphorylation, mitophagy-dependent generation of phos-TBK1 is largely impaired by ATG9A KO (Fig 2j and k). Thus, there is no doubt that isolation membrane formation is important for TBK1 activation following Parkin-mediated mitophagy.

Fig 1e - The reviewer is correct that phos-TBK1 is reduced in the NDP52 knockout. We have rewritten the main text. It is also true that NDP52 has a smaller effect on TBK1 autophosphorylation as compared to OPTN.

Fig 1g - Immunoblots using total cell lysates prepared from six different cell lines (WT, Penta KO alone, Penta KO stably expressing low or high OPTN or NDP52) under four different conditions (DMSO, valinomycin 1 hr, valinomycin 3 hrs, valinomycin + bafilomycin 3 hrs) showed that OPTN is a rate-limiting factor for TBK1 phosphorylation. Please see Fig 1g and h in the revised manuscript

Fig 2c - The recruitment of OPTN WT and associated mutants to the contact site was re-examined by immunostaining with WIPI2 labeling. We found that OPTN WT was both efficiently recruited to and formed the contact site. In contrast, the OPTN 4LA/F178A mutant was unable to interact with FIP200/LC3/ATG9A and was uniformly (i.e. homogenously) distributed on damaged mitochondria with the rate of autophagosome site formation reduced. Please see Fig 2e, f, g in the revised manuscript.

Fig 2e and f - KO of the autophagy core components FIP200 and ATG9A increased phos-TBK1 under basal, non-mitophagy-associated conditions (see Fig 3). The levels of autophagy adaptors other than OPTN also increased in FIP200 KO and ATG9A KO cells. Furthermore, as shown in Fig 3a and supplementary Fig 7, both phos-TBK1 and the autophagy adaptors accumulated in Ub-positive condensates. Based on previous reports (Mejlvang 2018 J Cell Biol), TAX1BP1, p62, and NBR1 have short half-lives and are quicky degraded by macro/micro autophagy. The accumulation of phos-TBK1 in the absence of autophagy occurs because autophagy-dependent degradation of TAX1BP1 (and other adaptors) is inhibited. This allows for the formation of Ub-positive condensates, which brings TBK1 into sufficient proximity for activation. This has been noted in the revised manuscript.

Fig 3b and 3c - We wonder if the "loading controls are missing for Fig 3b and 3c" statement might be a misinterpretation by the reviewer as TOMM20 was used as the loading control in the original Fig 3b. It was recovered in the supernatant fractions of WT, FIP200 KO, and ATG9A KO cells, indicating that the accumulation of autophagy adaptors in the pellet fractions depends on autophagy gene deletion. Similarly, actin and TOMM20 were used as loading controls in the original manuscript Fig 3c.

Fig 2d (perhaps meant to be Fig 3d) – A previous study reported that phos-tag PAGE blot of OPTN in TBK1 KO cells alone revealed no differences between WT and TBK1 KO cells (Heo et al 2015 Mol Cell). We cited this reference in the revised manuscript.

Fig 2b (perhaps meant to be Fig 4b) - Immunoblots of phos-TBK1 have been incorporated into the results of Fig 4b in the revised manuscript.

Fig 4 - We show in Fig 2 that induction of Parkin-mediated mitophagy promotes OPTN accumulation at contact sites formed by isolation membranes and ubiquitinated mitochondria, and that autophagy core subunits are required for efficient generation of phos-TBK1. Fig 3 shows that phos-TBK1 accumulates in Ub-positive condensates with TAX1BP1, rather than OPTN, and that it is responsible for phos-TBK1 accumulation. Together, these results suggest a model in which TBK1 is activated when OPTN and TBK1 are positioned near each other. We hypothesized that if we could force OPTNs into close proximity the autophagy machinery requirement for TBK1 activation might be bypassed. To assess this model, we designed the fluoppi assay shown in Fig 4. This assay was critical in that it provided an important clue for the molecular mechanism that OPTN and the autophagy machinery use to cooperatively induce TBK1 trans-autophosphorylation. Because the original manuscript may not have sufficiently conveyed our reasoning for the fluoppi analysis, we have rewritten this section. The main point of the fluoppi assay is that engineered OPTN multimerization was able to bypass the autophagy requirement for TBK1 activation.

Fig 5 - For easier interpretation, the L693Q and V700Q data, which are not related to ALS pathology, have been removed.

Fig 5d – Statistical significance has been determined for the mitophagy results and the main text has been rewritten for better clarity.

Fig 6c, d, and I – The experiments were independently replicated more than three times with statistical support and error bars incorporated into the associated graphs.

*Reviewer #2 (Significance (Required)): *

*this manuscript represents a lot of work but the experiments often lack controls and are over-interpretated. The manuscript is for a broad audience. *

For the revised manuscript, additional experiments were carefully performed with appropriate controls and the manuscript was rewritten to address concerns regarding over-interpretation. We hope that we have adequately addressed the reviewer’s comments.

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

*The authors investigated the mechanisms by which TBK1 is phosphorylated and thus activated in PINK1/Parkin-mediated mitophagy. They show data indicating that OPTN, by interacting both with ubiquitin-coated mitochondria and with the autophagy machinery, provides a platform where OPTN-bound TBK1 can be hetero-autophosphorylated by adjacent TBK1. *

*According to the prevailing model (prior to this manuscript), TBK1 activation via autophosphorylation leads to TBK1-mediated phosphorylation of OPTN S177 and subsequent pOPTN-mediated recruitment of autophagic isolation membranes to the mitochondria. However, based on the model provided in this manuscript, OPTN needs to interact first with both autophagic membranes and ubiquitin before TBK1 can become activated. *

*This is an important topic. Overall, the experimental data are of high scientific quality. For the most part, the manuscript is clearly written. The figures have been made with great care. The novel insights are relevant. However, a number of issues need to be addressed or clarified. *

*Major comments: *

• Fig. 1a-b shows that pTBK1 (pS172) formation already peaks after 30 min of valinomycin. Even when bafilomycin is added, pTBK1 level already reaches a near maximum after 30 min of valinomycin. If the model proposed by the authors is correct and pTBK1 (pS172) formation requires extensive interaction of OPTN with both ubiquitin and autophagic isolation membranes, they should be able to show (by immunostaining) that OPTN already extensively forms peri-mitochondrial cup/sphere-shaped structures that colocalize with isolation membrane markers after only 30 min of valinomycin. In the present manuscript, they only show formation of such structures after 1-3 h of valinomycin.* We thank the reviewer for the critical comments. Based on the suggestion, we performed immunostaining to observe the recruitment of TBK1 and OPTN to damaged mitochondria as well as the generation of phos-TBK1 (pS172) and phos-OPTN (pS177). HeLa cells stably expressing Parkin and 3HA-WIPI1 were treated with valinomycin for 30 min, and then TBK1, OPTN, phos-TBK1, and phos-OPTN were immunostained along with 3HA-WIPI1 (a marker of the autophagosome formation site) and TOMM20 (a mitochondria marker). Please see supplementary Fig 2a and 3a in the revised manuscript. The TBK1, OPTN, phos-TBK1, and phos-OPTN signals formed dot-like, cup-shaped, and/or spherical structures, most of which were peri-mitochondrial and colocalized with 3HA-WIPI1. In separate experiments, HeLa cells stably expressing Parkin were treated with valinomycin in the presence or absence of bafilomycin for 30 min or 2 hrs and then immunostained. Please see supplementary Fig 2b in the revised manuscript. After 30 min valinomycin in the absence of bafilomycin, many TBK1 and OPTN signals were observed on damaged mitochondria. These signals were quantified from more than 160 cells for each of the four conditions. Each microscopic image generated contained 18-36 cells and corresponds to one dot in supplementary Fig 2c. Based on these results, the abundance of TBK1 and OPTN on mitochondria after 30 min of valinomycin was much higher than that after 2 hrs with valinomycin (supplementary Fig 2c). Similar results were obtained for phos-TBK1 and phos-OPTN (supplementary Fig 3b and c). These results are consistent with the immunoblot data (Fig1a and b).

Furthermore, we show that Parkin expression levels affect the amount of phos-TBK1 generated during mitophagy. Please see supplementary Fig 4 in the revised manuscript. When PARKIN was integrated into HeLa cells under a CMV promoter via an AAVS1 (Adeno-associated virus integration site 1)-locus, the resultant cell line (referred to as high-Parkin) had higher Parkin levels than HeLa cells in which PARKIN was introduced by retrovirus infection (referred to as low-Parkin). In high-Parkin HeLa cells, phos-TBK1 levels reached a maximum after 30 min with valinomycin, while in low-Parkin HeLa cells, phos-TBK1 levels were comparable after 30 min and 1 hr. High-Parkin HeLa was used for Fig 1a, b, c, and d as well as supplementary Fig 1, 2, 3 and 4. For all other Figs, PARKIN genes were introduced by retrovirus infection. This is one of the reasons why val was used for 30 min in Fig1, but 1-3 hrs for the other Figs. Because 3 hrs valinomycin treatment may be unsuitable for evaluating OPTN recruitment to mitochondria/isolation membrane contact sites, we deleted the original Fig 2c and replaced it with the val 1 hr data (Please see Fig 2e in the revised manuscript).

• The authors propose that OPTN needs to interact both with ubiquitin on mitochondria and with isolation membrane proteins such as ATG9A to allow TBK1 phosphorylation. However, their fluoppi experiments in Fig. 4 seem to contradict this. In the fluoppi experiments, the authors generate multimeric OPTN-Ub foci and this is apparently sufficient to induced TBK1 phosphorylation at S172 (shown in 4d,f). In this experiment, there is no induction of autophagy or formation of isolation membranes, and TBK1 nevertheless gets activated.*

Figure 2 demonstrates that both ubiquitin on mitochondria and formation of the isolation membranes are needed to provide a platform for OPTN to assemble in close proximity to each other and subsequently induce TBK1 autophosphorylation. To determine if OPTN proximity is sufficient for TBK1 autophosphorylation (i.e., if engineered OPTN multimerization can bypass the autophagy machinery requirement for TBK1 autophosphorylation), we used the fluoppi assay. The results clearly showed that engineered OPTN multimerization induced TBK1 autophosphorylation without the need for the autophagy machinery. Although this is not a mitophagy experiment, the fluoppi assay provided crucial insights into the molecular mechanism underlying OPTN-mediated TBK1 autophosphorylation. The main text was rewritten to provide more clarity regarding the purpose of the fluoppi experiments.

• Can the authors be more concrete/specific in the discussion about the molecular mechanisms that explain why this 'platform' that is created by OPTN-autophagy machinery interactions is so crucial for TBK1 activation? If I understand the model in Fig. 7D correctly, the OPTN-autophagy machinery interactions are mainly important because they reduce the distance between OPTN-bound TBK1 molecules so that they can trans-phosphorylate each other. But if TBK1 autophosphorylation was just a matter of proximity between OPTN-bound TBK1 molecules, interaction of OPTN with densely ubiquitinated mitochondria should already be sufficient for TBK1 phosphorylation. When multiple OPTN molecule bind to one ubiquitin chain or to closely adjacent ubiquitin chains (similar to the fluoppi experiments), TBK1 molecules binding to OPTN would be expected to be already closely enough to one another for trans-autophosphorylation.*

The amount of phos-TBK1 during Parkin-mediated mitophagy was reduced in cells with the OPTN 4LA/F178A mutant, which cannot interact with the autophagy machinery (e.g. FIP200, ATG9A, and LC3) but can be targeted to mitochondria (see Fig 2c, d). ATG9AKO cells also had reduced amounts of phos-TBK1 relative to WT cells (See Fig 2j, k). Therefore, rather than OPTN-ubiquitin freely diffusing laterally on the outer membrane, we suggest that the contact site OPTN forms with ubiquitin and the autophagy machinery provides a more suitable platform for TBK1 autophosphorylation because it maintains TBK1 in a proximal position for a longer period of time.

The OPTN UBAN domain binds a ubiquitin-chain composed of two ubiquitin molecules (Oikawa et al. 2016 Nat Comm), and during Parkin-mediated mitophagy only shorter length poly-ubiquitin chains are generated on the mitochondrial surface (Swatek et al. 2019 Nature). Based on those findings, it is unlikely that multiple OPTN bind to one ubiquitin chain. Of course, we cannot rule out the possibility that TBK1 autophosphorylation does not occur on mitochondria in the absence of autophagy components. While full activation of TBK1 requires OPTN to associate with the isolation membrane, initial TBK autophosphorylation at the onset of mitophagy may occur based only on the OPTN-ubiquitin interaction. These explanations have been added to the Discussion in the revised manuscript.

Furthermore, based on comments from Reviewer 2, we performed time-lapse microscopy to observe OPTN dynamics during Parkin-mediated mitophagy (please see Fig 2l). HeLa cells stably expressing GFP-OPTN and pSu9-mCherry (a mitochondrial marker) were treated with valinomycin. GFP-OPTN was initially a peri- mitochondrial dot-like structure that elongated over time to a cup-shaped structure and which eventually ended up forming a spherical structure. The time-laps imaging showed that, at least in WT cells, OPTN is directly recruited to the contact sites and elongates along with the isolation membranes. We thus concluded that TBK1 is activated (autophosphorylated) at the contact site rather than on the outer membrane where OPTN-TBK can move freely.

• Fig. 5c,d and P. 16: the mitophagy experiments in TBK1-/- cells expressing the different mutant forms of TBK1 are hard to interpret because it is not clear which mitophagy differences are statistically significant. The main text about this part (p. 16) is also confusing.*

We regret the confusion. Reviewer 2 also noted that the main text for Fig 5 was difficult to interpret. One of the reasons that complicated interpretation of the data is the number of TBK1 mutants used. The L693Q and V700Q mutations used by Li et al. (2016 Nat Commun) were expected to inhibit mitophagy since those authors reported that the mutations prevented interactions with OPTN. However, our in-cell assay showed that the two mutants only moderately affected Parkin-mediated mitophagy. Furthermore, both L693Q and V700Q were engineered based on the X-ray structure and are not ALS pathogenic mutations. To simplify the data and to make data interpretation easier, we decided to delete the L693Q and V700A data. We also determined statistical significance and rewrote this section.

• Many graphs lack statistics: Fig. 2b (pTBK1), Fig. 2f, Fig. 5b, Fig. 5d, Fig. 6c.*

We apologize for the lack of statistical analyses. We repeated experiments (if the experiments had not been independently performed more than three times) with statistical significance and error bars incorporated into the relevant figures.

*Other comments: *

• Fig. 1a: how do they know that the upper OPTN band is ubiquitinated OPTN? Reviewer 2 raised the same question. To demonstrate that the upper OPTN band is ubiquitinated, cell lysates after mitophagy induction were incubated in vitro* with a recombinant USP2 core domain, and the samples immunoblotted. As shown in supplementary Fig 1 in the revised manuscript, the upper OPTN band disappeared in a USP2-dependent manner. The upper NDP52 and TOMM20 bands similarly disappeared. Therefore, the upper OPTN, NDP52 and TOMM20 bands observed after mitophagy induction are ubiquitinated.

• Fig. 1a,b: the bafilomycin stabilization of pTBK1, OPTN and pOPTN indicates that these proteins are substantially degraded by autophagy within 30-60 minutes. This seems extremely fast for mitophagy completion. Please discuss.*

According to Kulak et al. (2014 Nat Methods), autophagy adaptor abundance (OPTN: 2.32E+4 and NDP52: 3.34E+4 in HeLa cell line) is low compared to that of mitochondria (TOMM20: 1.45E+6 in HeLa cell line). This is one of the reasons why autophagic degradation of adaptors is easier to see. Degradation of phos-TBK1 was likewise easy to detect, whereas total TBK1 was not. This discrepancy is likely based on differences in the abundance of phos-TBK1 and total TBK1. In addition, because autophagy adaptors are localized outside of the mitochondrial membrane they may be easier targets for lysosomal degradation than matrix proteins, which are localized inside the outer and inner membranes.

• Fig. 1a and rest of the manuscript: is there a reason why the authors only looked at S177 phosphorylation of OPTN and not also at OPTN S473, which is also phosphorylated by TBK1?*

Both mass spectrometry and mutational analyses indicated that OPTN S473 is phosphorylated during Parkin-mediated mitophagy and that OPTN phosphorylated at S473 strongly binds ubiquitin chains (Richter et al. 2016 PNAS and Heo et al. 2015 Mol Cell). However, because a phos-S473 OPTN antibody is, to the best of our knowledge, currently not commercially available, we did not focus on S473 phosphorylation.

• Fig. 1e-f: the main text states that "NDP52 KO effects on the pS172 signal were comparable to controls", but the blot in 1e and the graph in 1f indicate a difference between NDP52KO and WT (significant difference shown in 1f). This is confusing.*

We regret the over-interpretation. As the reviewer indicated, the amount of phos-TBK generated in response to mitophagy was reduced in NDP52 KO cells relative to that in WT cells. This has been corrected. We would like to emphasize that, unlike OPTNdeletion, NDP52 deletion has relatively minor effects on TBK1 phosphorylation.

• P. 9: "TBK1 phosphorylation however was not apparent in the OPTN mutant lines, even after 3 hrs with valinomycin, indicating that autophagy adaptors are essential for TBK1 activation (Fig. 2a)". However, the pTBK1 blot in Fig. 1a does show pTBK1 formation in the OPTN mutant (4LA etc.) lines. This is confusing.*

We apologize for this error. We intended to state “TBK1 phosphorylation was not apparent in the Penta KO cells without OPTN expression even after 3 hrs with valinomycin, indicating that autophagy adaptors are essential for TBK1 activation”. This sentence has been corrected in the revised manuscript.

• P. 10: "we subtracted the basal phosphorylation signal from that generated post-valinomycin (1 hr) and bafilomycin (3 hr)". Do they mean "from that generated post-valinomycin (3 hr) and bafilomycin (3 hr)?*

The reviewer is correct, we have corrected the error.

• P. 10, same paragraph: "the phosphorylation signal was ~90 but was less than 30 in ATG9A KO cells." Unclear what they mean by 90 and 30. 90% and 30%? 90-fold and 30-fold?*

The newly generated pTBK1 levels following Parkin-mediated mitophagy were calculated as pTBK1 [val & baf 3 hrs] minus pTBK1 [DMSO]. Since pTBK1 [val & baf 3 hrs] in WT cells is set to 100%, the newly generated pTBK1 in WT cells was 100% - 5% = 95%. The calculated values for pTBK1 [DMSO] and pTBK1 [val & baf 3 hrs] in ATG9A KO cells were ~55% and ~85%, respectively. Consequently, newly generated pTBK1 in the ATG9A KO cells is ~85% - ~55% = 30%. For clarity, we modified the figure to make the meaning of the numbers more apparent.

• Fig. 3a: Do they have an idea what kind of ubiquitinated substrates are contained in the ubiquitin-positive condensates that accumulate in FIP200 KO and ATG9A KO cells (i.e. without valinomycin treatment)?*

According to Kishi-Itakura et al. (2014 J Cell Sci), ferritin accumulates in the p62 condensates in FIP200 KO and ATG9A KO cells. However, it is unknown if the ferritin in the condensates is ubiquitinated. In the original manuscript, we confirmed by immunostaining that the p62-NBR1 condensates contain ferritin (Fig 3a in the original manuscript and supplementary Fig 7b in the revised manuscript).

• P. 12 and Fig. 3a: please explain why they look at ferritin, to improve readability.*

We thank the reviewer for the suggestion. As mentioned, ferritin is a known substrate that accumulates in p62 condensates, we thus sought to confirm its presence. We have included this explanation in the revised manuscript.

• Fig. 3a: please also include Ub stain for NBR1.*

We thank the reviewer for the suggestion. We obtained a rabbit anti-NBR1 antibody that allowed us to co-immunostain with the mouse anti-ubiquitin antibody (please see supplementary Fig 7b in the revised manuscript).

• Fig. 3d: the OPTN blot shows 2 OPTN bands. What does the upper OPTN band represent here?*

To determine if the two bands are genuine OPTN, total cell lysates prepared from HeLa cells treated with control siRNA or OPTN siRNA were subjected to phos-tag PAGE followed by immunoblotting with an anti-OPTN antibody. As shown below (Figure 2 for reviewers), the two bands (indicated as blue arrowheads) were absent in the OPTN knock down cells, indicating that both are derived from OPTN. Since phosphorylated species migrate slower in phos-tag PAGE, the upper band might be a phosphorylated form. The specific Ser/Thr phosphorylated in OPTN, however, remains to be determined. Heo et al. (2015 Mol Cell) also reported the two OPTN bands on phos-tag PAGE and that both were unchanged in TBK1 KO cells, suggesting that at least the upper band is not affected by TBK1.

• P. 14 and Fig. 4b: "Here, we found that phosphorylation of ... TBK1 (S172) was induced by the OPTN-ub fluoppi (Fig. 4b)." However, Fig 4b does not show a pTBK1 blot.*

We immunoblotted phos-TBK1. Please see Fig 4b in the revised manuscript.

*Reviewer #3 (Significance (Required)): *

*The novel insights are relevant. *

*According to the prevailing model (prior to this manuscript), TBK1 activation via autophosphorylation leads to TBK1-mediated phosphorylation of OPTN S177 and subsequent pOPTN-mediated recruitment of autophagic isolation membranes to the mitochondria. However, based on the model provided in this manuscript, OPTN needs to interact first with both autophagic membranes and ubiquitin before TBK1 can become activated. *

Based on our time-lapse microscopy observations (Fig 2l), OPTN recruited to the vicinity of mitochondria was visible as a small dot-like structures that likely correspond to contact sites between mitochondria and the isolation membrane since OPTN colocalizes with WIPI1 (please see supplementary Fig 2). These results support our proposed model that OPTN interacts with both isolation membranes and ubiquitin at the onset of mitophagy. Without TBK1 activation, OPTN can interact with ATG9A vesicles, a seed for isolation membrane formation (Yamano et al 2020 JCB), and TBK1 can interact with the PI3K complex (Nguyen et al 2023 Mol Cell). Therefore, OPTN-TBK1 can be recruited to the contact site from the very beginning of mitophagy induction prior to TBK1 being fully activated. Furthermore, the proposed model also includes an OPTN-TBK1 positive feedback loop; however, the earliest reactions in the positive feedback loop are too difficult to observe. For example, it’s widely known that PINK1 and Parkin form a positive feedback loop to generate ubiquitin-chains on damaged mitochondria, but the initial reaction has yet to be observed. It remains unclear if PINK1 is the first to phosphorylate mitochondrial ubiquitin (if this is the case, it remains unknown how ubiquitin comes to mitochondria) or if cytosolic Parkin first adds ubiquitin to the outer membrane albeit with very weak activity. Similarly, in our proposed model, we cannot determine the earliest OPTN-TBK1 reaction. As described in the Discussion in the revised manuscript, it remains possible that in the absence of autophagy machinery OPTN distributed freely on the outer membrane can induce trans-autophosphorylation, albeit weakly, as the earliest reaction.

We would like to thank Reviewer 3 for the critical comments and suggestions. We have performed several of the suggested experiments, added new data, and rewritten the text. We hope that these changes have sufficiently addressed the reviewer’s concerns.

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Author Response

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

Cook, Watt, and colleagues previously reported that a mouse model of Spinocerebellar ataxia type 6 (SCA6) displayed defects in BDNF and TrkB levels at an early disease stage. Moreover, they have shown that one month of exercise elevated cerebellar BDNF expression and improved ataxia and cerebellar Purkinje cell firing rate deficits. In the current work, they attempt to define the mechanism underlying the pathophysiological changes occurring in SCA6. For this, they carried out RNA sequencing of cerebellar vermis tissue in 12-month-old SCA6 mice, a time when the disease is already at an advanced stage, and identified widespread dysregulation of many genes involved in the endo-lysosomal system. Focusing on BDNF/TrkB expression, localization, and signaling they found that, in 7-8 month-old SCA6 mice early endosomes are enlarged and accumulate BDNF and TrkB in Purkinje cells. Curiously, TrkB appears to be reduced in the recycling endosomes compartment, despite the fact that recycling endosomes are morphologically normal in SCA6. In addition, the authors describe a reduction in the Late endosomes in SCA6 Purkinje cells associated with reduced BDNF levels and a probable deficit in late endosome maturation.

We would like to thank the reviewers for their careful reading of the paper, their feedback has helped us to add information and experiments to the paper that enhance the clarity of the findings.

Strengths:

The article is well written, and the findings are relevant for the neuropathology of different neurodegenerative diseases where dysfunction of early endosomes is observed. The authors have provided a detailed analysis of the endo-lysosomal system in SCA6 mice. They have shown that TrkB recycling to the cell membrane in recycling endosomes is reduced, and the late endosome transport of BDNF for degradation is impaired. The findings will be crucial in understanding underlying pathology. Lastly, the deficits in early endosomes are rescued by chronic administration of 7,8-DHF.

We thank the reviewers for their positive feedback on this work.

Weaknesses:

The specificity of BDNF and TrkB immunostaining requires additional controls, as it has been very difficult to detect immunostaining of BDNF. In addition, in many of the figures, the background or outside of Purkinje cell boundaries also exhibits a positive signal.

We agree with the reviewers that the performance of the BDNF and TrkB antibodies is an important concern. We have ourselves had difficulties with the performance of many antibodies and the images in this paper are the result of many years of optimization. We have therefore added further detail about the antibody optimization to the methods section of this paper, and have carried out new staining experiments with additional controls. We have added 2 new figure panels in supplementary figures 3 and 4 to demonstrate these tests.

In the case of anti-BDNF antibodies, we have tested several antibodies and staining protocols and found that in our hands, the only antibody that reliably stained BDNF with a good signal to noise ratio was the one used in this paper (abcam ab108319). Even for this antibody, the staining was greatly enhanced by the use of a heat induced epitope retrieval (HIER) step, which allowed the visualization of BDNF within intracellular structures such as endosomes. When we quantified the intensity of this staining in our previous paper, the results were in agreement with those from a BDNF ELISA used to measure levels of BDNF in the cerebellar vermis of WT and SCA6 mice (Cook et al., 2022), which corroborates these results. As the staining was carried out in tissue sections and not dissociated cells, we also see positive signal from the BDNF staining outside of the Purkinje cells, since BDNF acts on cell-surface receptors and is thus released into the extracellular space around cells (Kuczewski et al., 2008) and is detectable in the extracellular matrix (Lam et al., 2019) and presynaptic terminals around neurons (Camuso et al., 2022; Choo et al., 2017). This is in contrast to studies that image BDNF mRNA with in-situ hybridization, which labels BDNF mRNA predominantly found in cells, and cannot tell us about sub-cellular or extracellular localization of BDNF protein. Together, these factors explain why we observe staining that is not cell- limited, but extends into the space around the cells of interest.

We have added an additional supplemental figure to demonstrate the importance of using HIER when staining slices with anti-BDNF (Supplementary figure 3). We tested HIER protocols that involved heating the slices to 95°C in a variety of buffers. The buffers tested were sodium citrate buffer (10 mM sodium citrate, 0.05% Tween 20, pH 6), Tris buffer (10mM TBS, 0.05% Tween 20, pH 10), EDTA buffer (1mM EDTA, 0.05% Tween 20, pH 8) and neutral PBS. The PBS produced the best result, enhancing the staining of both anti-BDNF and anti-EEA1 antibodies (Supplementary figure 3). Therefore all slices stained using those antibodies were heated to 95°C in PBS using a heat block or thermocycler for 10 minutes, then allowed to cool before staining proceeded.

The antibody we use (abcam ab108319) has been used in hundreds of other publications, including Javed et al., 2021 who ectopically expressed BDNF and noted colocalization between the antibody staining and the GFP tag of the BDNF construct, and Lejkowska et al., 2019 who overexpressed BDNF and saw a dramatic increase in antibody staining as well. The colocalization between ectopically expressed BDNF and the antibody in these studies demonstrates the specificity of the antibody.

However, to further validate antibody specificity we used liver tissue as a negative control. In liver tissue from rodents and humans, the majority of the liver contains negligible levels of BDNF (Koppel et al., 2009; Vivacqua et al., 2014), see also the Human Protein Atlas. The exception is some cholangiocytes: epithelial cells that express BDNF at high levels (Vivacqua et al., 2014). We obtained liver tissue from a WT mouse that was undergoing surgery for an unrelated project and fixed and processed the tissue as we did for brain tissue (outlined in methods section). As we would expect, most of the cells in the liver showed BDNF immunoreactivity that was comparable to background levels (Supplementary figure 3). Interestingly, we were also able to detect sparse highly BDNF-positive cells in the liver, presumed cholangiocytes (Supp. Fig. 3). This pattern of liver BDNF expression is as predicted in the literature, and thus acts as a control for our antibody. We therefore believe that in our hands this antibody is able to stain BDNF with an appropriate degree of specificity.

We also carried out staining experiments using a second anti-TrkB antibody that we had previously used to detect TrkB via Western bloing. We carried out immunohistochemistry as previously described using tissue sections from a WT mouse. The staining with the two different antibodies was carried out at the same time and all other reagents were kept constant. We found that both antibodies labelled TrkB in a similar pattern of localization, including in the early endosomes of the Purkinje cells (Supplementary figure 4). The second antibody however did have a lower signal to noise ratio and so we believe that the original anti-TrkB antibody used in this manuscript (EMD Millipore ab9872) is optimal for staining cerebellar tissue sections in our hands.

One important concern about the conclusions is that the RNAseq experiment was conducted in 12-month- old SCA6 mice suggesting that the defects in the endo-lysosomal system may be caused by other pathophysiological events and, likewise, the impairment in BDNF signaling may also be indirect, as also noted by the authors. Indeed, Purkinje cells in SCA6 mice have an impaired ability to degrade other endocytosed cargo beyond BDNF and TrkB, most likely because of trafficking deficits that result in a disruption in the transport of cargo to the lysosomes and lysosomal dysfunction.

We agree with the reviewers that the defects in the endo-lysosomal system may be caused by other events occurring in the course of disease progression. As mentioned by the reviewers, we have noted this possibility in the text. Detailed investigation into the sequence of events and the root causes of signaling disruption in SCA6 merits future study and we aim to address this in future work. We have expanded this explanation in the text.

Moreover, the beneficial effects of 7,8-DHF treatment on motor coordination may be caused by 7,8-DHF properties other than the putative agonist role on TrkB. Indeed, many reservations have been raised about using 7,8-DHF as an agonist of TrkB activity. Several studies have now debunked (Todd et al. PlosONE 2014, PMID: 24503862; Boltaev et al. Sci Signal 2017, PMID: 28831019) or at the very least questioned (Lowe D, Science 2017: see Discussion: https://www.science.org/content/blog-post/those-compounds-aren-t- what-you-think-they-are Wang et al. Cell 2022 PMID: 34963057). Another interpretation is that 7,8-DHF possesses antioxidant activity and neuroprotection against cytotoxicity in HT-22 and PC12 cells, both of which do not express TrkB (Chen et al. Neurosci Lett 201, PMID: 21651962; Han et al. Neurochem Int. 2014, PMID: 24220540). Thus, while this flavonoid may have a beneficial effect on the pathophysiology of SCA6, it is most unlikely that mechanistically this occurs through a TrkB agonistic effect considering the potent anti-oxidant and anti-inflammatory roles of flavonoids in neurodegenerative diseases (Jones et al. Trends Pharmacol Sci 2012, PMID: 22980637).

We thank the reviewers for raising this important point. We have noted in our previous paper (Cook et al., 2022) that 7,8-DHF may not be acting as a TrkB agonist in SCA6 mice, and are in agreement that other explanations are possible. We have now added information to the text of this paper to highlight this possibility. We did show in our previous paper that 7,8-DHF administration activates Akt signaling in the cerebellum of SCA6 mice, a signaling event that is known to take place downstream of TrkB activation. Additionally, 7,8-DHF treatment led to the increase of TrkB levels in the cerebellum of SCA6 mice (Cook et al., 2022), implicating TrkB in the mechanism of action, even if mechanistically, this is not via direct TrkB activation alone. However, even if the mechanism is currently incompletely explained, we believe that 7,8- DHF remains a valuable treatment strategy for SCA6. We have tried to rewrite the Discussion to highlight what we think is the most important takeaway: that 7,8-DHF can rescue endosomal and other deficits in SCA6, even if we do not currently know the full mechanism of action. We have therefore amended the text to add more detail about other potential explanations for the mechanism of action of 7,8-DHF.

References

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Choo M, Miyazaki T, Yamazaki M, Kawamura M, Nakazawa T, Zhang J, Tanimura A, Uesaka N, Watanabe M, Sakimura K, Kano M. 2017. Retrograde BDNF to TrkB signaling promotes synapse elimination in the developing cerebellum. Nat Commun 8:195. doi:10.1038/s41467-017-00260-w

Cook AA, Jayabal S, Sheng J, Fields E, Leung TCS, Quilez S, McNicholas E, Lau L, Huang S, Watt AJ. 2022. Activation of TrkB-Akt signaling rescues deficits in a mouse model of SCA6. Sci Adv 8:3260. doi:10.1126/sciadv.abh3260

Javed S, Lee YJ, Xu J, Huang WH. 2021. Temporal dissection of Rai1 function reveals brain-derived neurotrophic factor as a potential therapeutic target for Smith-Magenis syndrome. Hum Mol Genet 31:275–288. doi:10.1093/HMG/DDAB245

Koppel I, Aid-Pavlidis T, Jaanson K, Sepp M, Pruunsild P, Palm K, Timmusk T. 2009. Tissue-specific and neural activity-regulated expression of human BDNF gene in BAC transgenic mice. BMC Neurosci 10:68. doi:10.1186/1471-2202-10-68

Kuczewski N, Porcher C, Ferrand N, Fiorentino H, Pellegrino C, Kolarow R, Lessmann V, Medina I, Gaiarsa JL. 2008. Backpropagating action potentials trigger dendritic release of BDNF during spontaneous network activity. J Neurosci 28:7013–7023. doi:10.1523/JNEUROSCI.1673-08.2008

Lam D, Enright HA, Cadena J, Peters SKG, Sales AP, Osburn JJ, Soscia DA, Kulp KS, Wheeler EK, Fischer NO. 2019. Tissue-specific extracellular matrix accelerates the formation of neural networks and communities in a neuron-glia co-culture on a multi-electrode array. Sci Rep 9. doi:10.1038/s41598- 019-40128-1

Lejkowska R, Kawa MP, Pius-Sadowska E, Rogińska D, Łuczkowska K, Machaliński B, Machalińska A. 2019. Preclinical Evaluation of Long-Term Neuroprotective Effects of BDNF-Engineered Mesenchymal Stromal Cells as Intravitreal Therapy for Chronic Retinal Degeneration in Rd6 Mutant Mice. Int J Mol Sci 2019, Vol 20, Page 777 20:777. doi:10.3390/IJMS20030777

Vivacqua G, Renzi A, Carpino G, Franchitto A, Gaudio E. 2014. Expression of brain derivated neurotrophic factor and of its receptors: TrKB and p75NT in normal and bile duct ligated rat liver. Ital J Anat Embryol 119:111–129. doi:10.13128/IJAE-15138

Author Response

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

We thank the reviewers and editor for their thoughful and careful evaluation of our manuscript. We appreciate your time and effort and have incorporated many of these suggestions to improve our revised manuscript.

Reviewer #1 (Public Review):

Summary: Cullinan et al. explore the hypothesis that the cytoplasmic N- and C-termini of ASIC1a, not resolved in x-ray or cryo-EM structures, form a dynamic complex that breaks apart at low pH, exposing a C-terminal binding site for RIPK1, a regulator of necrotic cell death. They expressed channels tagged at their N- and C-termini with the fluorescent, non-canonical amino acid ANAP in CHO cells using amber stop-codon suppression. Interaction between the termini was assessed by FRET between ANAP and colored transition metal ions bound either to a cysteine reactive chelator attached to the channel (TETAC) or metal-chelating lipids (C18-NTA). A key advantage to using metal ions is that they are very poor FRET acceptors, i.e. they must be very close to the donor for FRET to occur. This is ideal for measuring small distances/changes in distance on the scales expected from the initial hypothesis. In order to apply chelated metal ions, CHO cells were mechanically unroofed, providing access to the inner leaflet of the plasma membrane. At high pH, the N- and C- termini are close enough for FRET to be measured, but apparently too far apart to be explained by a direct binding interaction. At low pH, there was an apparent increase in FRET between the termini. FRET between ANAP on the N-and Ctermini and metal ions bound to the plasma membrane suggests that both termini move away from the plasma membrane at low pH. The authors propose an alternative hypothesis whereby close association with the plasma membrane precludes RIPK1 binding to the C-terminus of ASIC1a.

Strengths: The findings presented here are certainly valuable for the ion channel/signaling field and the technical approach only increases the significance of the work. The choice of techniques is appropriate for this study and the results are clear and high quality. Sufficient evidence is presented against the starting hypothesis.

Weaknesses: I have a few questions about certain controls and assumptions that I would like to see discussed more explicitly in the manuscript.

My biggest concern is with the C-terminal citrine tag. Might this prevent the hypothesized interaction between the N- and C-termini? What about the serine to cysteine mutations? The authors might consider a control experiment in channels lacking the C-terminal FP tag.

While it is certainly possible that the C-terminal citrine tag is preventing the hypothesized interaction between the intracellular termini, there are a few things that mitigate (but not eliminate) this concern. First, previous work looking at the interaction between the intracellular termini used FPs on both the N- and C-termini and concluded that in fact there is an interaction (PMID:31980622). Our channels have only a single FP, and we use a higher resolution FRET approach. Second, we aVach our citrine tag with a 11-residue linker, allowing for enhanced flexibility of the region and hopefully allowing for more space for an interaction that was posited to be between the very proximal part of the C-terminus (near the membrane and away from the tag) and the untagged N-terminus. Third, we previously showed that Stomatin, a much larger protein than the NTD, could bind the distal C-terminus of rASIC3 with a large fluorescent protein connected by the same linker on the C-terminus. In the case of Stomatin, the interaction involved the residues at the distal portion of the C-terminus close to the bulky FP. Interestingly, while we did not publish this, without this flexible linker, Stomatin could not regulate the channel and likely did not bind.

Despite this, we agree that this is possible and have added a statement in our limitations section explicitly saying this.

Figure 2 supplement 1 shows apparent read-through of the N-terminal stop codons. Given that most of the paper uses N-terminal ANAP tags, this figure should be moved out of the supplement. Do Nterminally truncated subunits form functional channels? Do the authors expect N-terminally truncated subunits to co-assemble in trimers with full-length subunits? The authors should include a more explicit discussion regarding the effect of truncated channels on their FRET signal in the case of such co-assembly.

The positions that show readthrough (E6, L18, H515) were not used in the study. We eliminated them largely on the basis of these westerns. We elected to put the bulk of the blots in the supplement simply because of how many there were. We believe this is the best compromise. It allows us to show representative blots for all our positions without making an illegible figure with 7 blots.

The N-terminally truncated subunits would create very short peptides that are not able to create functional channels. A premature stop at say E8 would create a 7-mer. Our longest N-terminal truncation would only create a protein of 32 amino acids. These don’t contain the transmembrane segments and thus cannot make functional channels.

As the epitope used for the western blots in Figure 2 and supplements is part of the C-terminal tag, these blots do not provide an estimate of the fraction of C-terminally truncated channels (those that failed to incorporate ANAP at the stop codon). What effect would C-terminally truncated channels have on the FRET signal if incorporated into trimers with full-length subunits?

Alternatively, C-terminally truncated subunits would be able to form functional channels because they contain the full N-terminus, the transmembrane domains, the extracellular domain and a portion of the C-terminus. We don’t think this is a major contaminant to our experiments. The only two C-terminal ANAP positions we use are 464 and 505. In each of these cases, they are only used for memFRET. The ones that do not contain ANAP are essentially “invisible” to the experiment. Since we are measuring their proximity to the membrane, having some missing should not maVer. However, there is some chance that truncations in some subunits could allosterically affect the position of the CT in other subunits. We have added a discussion of this in the manuscript.

Some general discussion of these results in the context of trimeric channels would be helpful. Is the putative interaction of the termini within or between subunits? Are the distances between subunits large enough to preclude FRET between donors on one subunit and acceptor ions bound on multiple subunits?

Thank you for this comment. We did not directly test whether the distances are within or between subunits. We considered using a concatemer to do this, however, the concatemeric channels do not express particularly well. Then, UAA incorporation hurts the expression as well. It was unlikely we would be able to get sufficient expression for tmFRET.

However, the Maclean group has previously tested this using FRET between concatenated subunits and determined that FRET is stronger within than between subunits. We have updated the manuscript to reflect a more thorough discussion of our results in the context of their trimeric assembly.

The authors conclude that the relatively small amount of FRET between the cytoplasmic termini suggests that the interaction previously modeled in Rosetta is unlikely. Is it possible that the proposed structure is correct, but labile? For example, could it be that the FRET signal is the time average of a state in which the termini directly interact (as in the Rosetta model) and one in which they do not?

The proposed RoseVa model does not include the reentrant loop of the channel, so it is probable that this model would change if it were redone to include this new feature of the channel.

However, we do discuss the limitation of FRET as a method that measures a time average that is weighted towards closest approach in our discussion section. The termini are most certainly dynamic and it is possible that spend some time in close proximity. Given that FRET is biased towards closest approach, we actually think this strengthens our argument that the termini don’t spend a great deal of time in complex. In addition, our MST data suggests that the termini do not bind. We have added some commentary on this to the discussion section for clarity.

Reviewer #2 (Public Review):

Summary:

The authors use previously characterised FRET methods to measure distances between intracellular segments of ASIC and with the membrane. The distances are measured across different conditions and at multiple positions in a very complete study. The picture that emerges is that the N- and C-termini do not associate.

Strengths:

Good controls, good range of measurements, advanced, well-chosen and carefully performed FRET measurements. The paper is a technical triumph. Particularly, given the weak fluorescence of ANAP, the extent of measurements and the combination with TETAC is noteworthy.

The distance measurements are largely coherent and favour the interpretation that the N and C terminus are not close together as previously claimed.

Weaknesses:

One difficulty is that we do not have a positive control for what binding of something to either N- or Cterminus would look like (either in FRET or otherwise).

We acknowledge that this is a challenge for the approach. Having a positive control for binding would be great but we are not sure such a thing exists. You could certainly imagine a complex between two domains where each label (ANAP and TETAC) are pointed away from one other (giving comparatively modest quenching) or one where they are very close (giving comparatively large quenching), both of which could still be bound. This is essentially a less significant version of the problem with using FPs to measure proximity…they are not very good proxies for the position of the termini. These small labels are certainly beVer proxies but still not perfect. Our conclusion here is based more on the totality of the data. We tried many combinations and saw no sign of distances closer than ~ 20A at resting pH. We think the simplest explanation is that they are not close to one another but we tried to lay out the limitations in the discussion.

One limitation that is not mentioned is the unroofing. The concept of interaction with intracellular domains is being examined. But the authors use unroofing to measure the positions, fully disrupting the cytoplasm. Thus it is not excluded that the unroofing disrupts that interaction. This should be mentioned as a possible (if unlikely) limitation.

Thank you for your comment. We discuss unroofing as a potential limitation because it exposes both sides of the plasma membrane to changes in pH. We have updated this section to include acknowledgement of the possibility that unroofing disrupts the interaction via washout of other critical proteins.

Reviewer #3 (Public Review):

Summary: The manuscript by Cullinan et al., uses ANAP-tmFRET to test the hypothesis that the NTD and CTD form a complex at rest and to probe these domains for acid-induced conformational changes. They find convincing evidence that the NTD and CTD do not have a propensity to form a complex. They also report these domains are parallel to the membrane and that the NTD moves towards, and the CTD away, from the membrane upon acidification.

Strengths:

The major strength of the paper is the use of tmFRET, which excels at measuring short distances and is insensitive to orientation effects. The donor-acceptor pairs here are also great choices as they are minimally disruptive to the structure being studied.

Furthermore, they conduct these measurements over several positions with the N and C tails, both between the tails and to the membrane. Finally, to support their main point, MST is conducted to measure the association of recombinant N and C peptides, finding no evidence of association or complex formation.

Weaknesses:

While tmFRET is a strength, using ANAP as a donor requires the cells to be unroofed to eliminate background signal. This causes two problems. First, it removes any possible low affinity interacting proteins such as actinin (PMID 19028690). Second, the pH changes now occur to both 'extracellular' and 'intracellular' lipid planes. Thus, it is unclear if any conformational changes in the N and CTDs arise from desensitization of the receptor or protonation of specific amino acids in the N or CTDs or even protonation of certain phospholipid groups such as in phosphatidylserine. The authors do comment that prolonged extracellular acidification leads to intracellular acidification as well. But the concerns over disruption by unroofing/washing and relevance of the changes remain.

We acknowledge that unroofing is a limitation of our approach and noted it in the discussion. However, we have updated the section to include the possibility that the act of unroofing and washing could also disrupt the potential interaction between the intracellular domains as well as between these domains and other intracellular proteins. This was the best approach we could use to address our questions and it required that we unroof the cells. However, we look forward to future studies or new techniques that do not require the unroofing of the cells.

The distances calculated depend on the R0 between donor and acceptor. In turn, this depends on the donor's emission spectrum and quantum yield. The spectrum and yield of ANAP is very sensitive to local environment. It is a useful fluorophore for patch fluorometry for precisely this reason, and gating-induced conformational changes in the CTD have been reported just from changes in ANAP emission alone (PMID 29425514). Therefore, using a single R0 value for all positions (and both pHs at a single position) is inappropriate. The authors should either include this caveat and give some estimate of how big an impact changes spectrum and yield might have, or actually measure the emission spectra at all positions tested.

This is a reasonable concern and one we considered. Measuring the quantum yield would be quite difficult. However, we have measured spectra at a number of positions and see a relatively minimal shik in the peak. Most positions peak between 481 and 484nm. If you calculate the difference in R0 using theoretical spectra with a blue shik of 20nm, the difference in R0 is only ~1.5A. A shik of 20nm is on the higher side of anything we have seen in the literature (PMID 30038260) and since even with that large a shik, the difference is minimal we do not think measuring spectra for each position would impact the overall conclusions presented. As you noted, though, the quantum yield also changes. Assuming a change in yield from 0.22 to 0.47, the largest we found reported in the literature (PMID:29923827) , the R0 would increase by 2A. This same paper showed that the blue shiked position was the one with the higher extinction coefficient so these changes would be working in opposition to one another making the difference in R0 even smaller. It is important to note, that while tmFRET is a much more powerful measure of distance than standard FRET, these distances, as you point out, are quite challenging to measure precisely. Our conclusions are based less on the absolute distances and more on the observation that no positions show large quenching and that if there is any change upon acidification, it is in the wrong direction.

Overall, the writing and presentation of figures could be much improved with specific points mentioned in the recommendations for authors section.

See below.

The authors argue that the CTD is largely parallel to the plasma membrane, yet appear to base this conclusion on ANAP to membrane FRET of positions S464 and M505. Two positions is insufficient evidence to support such a claim. Some intermediate positions are needed.

We do not see in the paper where we suggest that the CTD is parallel. However, your point that we could try and determine if this was the case is correct. However, we aVempted to create several other CTD TAG mutants but struggled with readthrough and poor expression of these mutants so we opted to just include S464 and M505. Our point from these data is only that the distal CTD (505) must spend significant time near the membrane to explain our FRET data.

Upon acidification, NTD position Q14 moves towards the plasma membrane (Figure 8B). Q14 also gets closer to C515 or doesn't change relative to 505 (Figures 7C and B) upon acidification. Yet position 505 moves away from the membrane (Figure 8D). How can the NTD move closer to the membrane, and to the CTD but yet the CTD move further from the membrane? Some comment or clarification is needed.

This is a reasonable question and one that is hard to definitively answer. Our goal here was to test the hypothesis that the termini are bound at rest. Mapping the precise positions of the termini is difficult for reasons we will enumerate in the question that asks why we didn’t make a model. There are potentially multiple explanations but the easiest one would be that the CTD could move away from the membrane but closer to Q14, for instance, if the distal termini, say, rotated towards the NTD. This would move 505 closer and have no impact on whether or not the NTD and CTD moved away or toward the membrane.

Reviewer #1 (Recommendations For The Authors):

Minor concerns

The authors show the spectrum of ANAP attached to beads and use this spectrum to calculate R0 for their FRET measurements. Peak ANAP fluorescence is dependent on local environment and many reports show ANAP in protein blue-shiked relative to the values reported here. How would this affect the distance measurements reported?

This is an important point. See above for the answer.

Could the lack of interaction between the N- and C-terminal peptides in Figure 7 arise from the cysteine to serine mutations or lack of structure in the synthetic peptides. How were peptide concentrations measured/verified for the experiment?

It is possible that cysteine to serine mutations could prevent the interaction. It is also possible that these peptides are not capable of adopting their native fold without the presence of the plasma membrane or due to being synthetically created. However, the termini are thought to be largely unstructured. We received these peptides in lyophilized form at >95% purity and resuspended to our desired stock concentration (3 mM C-terminus, 1 mM N-terminus). Even if our concentration was off, we see no signs of interaction up to quite a high concentration.

How was photobleaching measured for correcting the data?

We executed several mock experiments at various TAG positions using either pH 8 and pH 6, where we performed the experiments as usual but with a mock solution exchange when we would normally add the metal. We normalized the L-ANAP fluorescence to the first image and averaged together these values for pH 8 and pH 6. We then corrected using Equation 2 in the manuscript..

We have updated the methods to include how we adjusted for bleaching.

The authors may wish to make it more explicit that their Zn2+ controls also preclude the possibility that a changing FRET signal between ANAP and citrine may affect their data.

Thank you for this comment. We agree, it would strengthen the manuscript to include this statement. We have now included this.

It might be useful to the reader if the authors could include (as a supplement) plots of their data (like in Figure 6), in which FRET efficiency has been converted to distance.

We considered this idea as well but felt like showing the actual data in the figures and the distances in a table would be best.

Figure 5D is mentioned in the text before any other figures. This is unconventional. Could this panel be moved to Figure 1 or the mention moved to later?

Changed

western blot is not capitalized.

Changed.

Figure 1, the ANAP structure shown is the methyl ester, which is presumably cleaved before ANAP is conjugated to the tRNA. The authors may wish to replace this with the free acid structure.

This is a fair point. We originally used the methyl ester structure to indicate the version of ANAP we chose to use. However, you are correct that the methyl ester is cleaved before conjugation to the tRNA. We replaced the methyl ester with the free acid structure to clarify this.

Figures 1 and 4 should have scale bars for the images.

Scale bars have been added to figures 1, 4, and 5.

In Figure 3, the letters in the structures (particularly TETAC) are way too small. Please increase the font size.

Changed

In Figure 3 and Figure 3 supplement 1, the axes are labeled "Absorbance (M-1cm-1)." Absorbance is dimensionless. The authors are likely reporting the extinction coefficient.

Thank you for catching this. We adjusted the axes to extinction coefficient.

In Figures 5 B and C, it might be clearer if the headers read "Initial, +Cu2+/TETAC, DTT" rather than "Initial, FRET, Recovery."

Changed

The panel labels for Figure 8 seem to be out of order.

Changed

The L for L-ANAP should be rendered, by convention, in small caps.

This is a good example of learning something new from the review process. This is the first I have ever heard of small caps. We can find no other papers that use small caps for L-ANAP so I am not 100% sure what convention this is referring to and don’t want to change the wrong thing in the paper. We are happy to change if the editorial staff at eLife agree but have lek this for now.

Reviewer #2 (Recommendations For The Authors):

With so many distances measured, why was not even a basic structural model attempted?

We certainly considered it, but a number of things lead us to conclude that it might imply more certainty about the structure of these termini than we hope to give. 1) Given that the FRET is a time average of positions, these distance constraints would not do much constraining. 2) Given that the termini are likely unstructured and flexible this makes the problem in 1 worse. 3) There is no structural information to use as a starting point for a model. 4) The flexibility of the linkers for each FRET pair also introduces uncertainty. This can, in theory, be modeled as they do in EPR but all of this together made us decide not to do this. What we hope readers take home, is the overall picture of the data is not consistent with the original RIPK1 hypothesis.

Maybe it would be good to draw a band on the graphs in Figure 6 for the FRET signal expected for interaction (and thus, disfavoured by these data). This would at least give context.

We agree this could be helpful, but it is not so easy to do. What distance would we choose? We could put a line at ~5Å (the model predicted distance). As we noted above, a number of distances could be compatible with an interaction. However, we think it’s unlikely that if a complex was formed that none of our measurements would show a distance closer than 20Å at rest and that an unbinding event would then lead to a decrease in distance. This, to us, is the take home message.

Minor points:

"Aker unroofing the cells, only fluorescence associated with the "footprint", or dorsal surface, of the cell membrane is lek behind."

The authors use dorsal and ventral in this section to describe parts of an adherent cell. But in the first instance, they remove the dorsal part of the cell, and then in this phrase, the dorsal part is lek behind....I am a bit confused.

Thank you for pointing out this mistake, we have fixed this. It is indeed the ventral surface lek behind.

"bind at rest an" - and?

Changed

"One previous study used a different approach to try and map the topography of the intracellular termini of ASIC1a comparable to our memFRET experiments." I think a citation is due.

Citation added

"great deal of precedent" even if this result is from my own lab, I would prefer that the authors note that it's one study from one lab! I think best just to delete "great deal of".

“Great deal of” deleted

I think the column "Significance" in the tables is unnecessary when the P value is given.

Thank you for this suggestion. We agree and have made the change.

Figure 7a Q14TAG has a clearly bimodal distribution at pH 8. What could be the meaning of this result? The authors do not mention it that I could find. Perhaps there is no meaning. The authors should state what they think is (or is not) going on.

This is a good question and we don’t have a good answer. It appears to be experimental variability. The data from the “low fret” in this experimental condition all came from the same days. So something was different that day. We considered that they might be outliers to exclude but thought showing all of our data was the beVer path. We reperformed the ANOVA here separating out the “outlier” day and nothing of substance changed. Both populations were still different with P value less than 0.001.

Typo: Lumencore

Changed

Maybe just a matter of taste but the panel created with Biorender in Figure 8 is not attractive and depicts the channel differently to in Figure 5D, which is again different from Figure 1A. Surely one advantage of using computer-generated artwork could be to have consistency.

We agree and have used the same cartoon for all of our images with the one exception being the schematics that are just meant to show the positions that are present in each bar graph.

Figure 4A was squashed to fit (text aspect ratio is wrong).

Fixed

Reviewer #3 (Recommendations For The Authors):

Citrine is used to report incorporation. Yet citrine has a strong tendency to dimerize (PMID 27240257). Did the authors use mCitrine or just Citrine? This is quite important in interpreting their data.

Thank you for pointing out this important distinction. We use mCitirine which we have added to the methods.

The manuscript has numerous instances of imprecise language. For example, page 10, last para, first line, "previous studies have looked at..." or page 7, final paragraph "tell a similar story". Related, the figures could be much better. For example, in Figure 1, where the authors depict the anap chemical in red, as opposed to the blue one might expect of a blue emiqng fluorophore. In figure 6, ANAP is also in red with the quenching group in green. This is opposite to how one typically thinks of FRET with the warmer color being the acceptor not the donor. Moreover, the pH 6 condition is also colored the same shade of red as the ANAP. Labels of Cys positions would again be useful here. In Figure 3, the heteroatoms of TETAC and C18-NTA are very small and difficult to see. It would also be good to label these structures, and the spectra below, so the reader can tell at a glance without looking at the caption, what the structures and spectra arise from. Also, how are the absorption spectra normalized? This is not discussed in the methods. The lack of attention to presentation mars an otherwise nice study.

Thank you for these points. We have made modifications to the manuscript to address these comments.

Abstract, second last line "Aker prolonged acidification, ...", 'prolonged' could be interpreted as 'it takes a while for the domain to move' or 'the movement only happens aker a while'. This not what the authors intend to convey. Consider modifying to just 'Aker acidification,'

We updated the main text to indicate that prolonged acidification is intended to describe acidification that occurs over the minutes timescale.

Pdf page 6, bottom para on Anap incorporation not altering channel function: What is meant by 'steady state pH dependence of activation'? This implies the authors applied a pH stimulus, then waited until equilibrium was achieved ie. until desensitization was complete and measured the current at that point. It seems more likely they simply applied different pH stimuli and measured the peak response and that the use of 'steady state' here is a typo.

We removed the phrase steady state.

Same section, controls of electrophysiology allude to 485, 505 and 515 ANAP-containing channels. In fact, the authors have no way of determining what fraction (if any) of the pH evoked currents arise from channels containing Anap in those positions versus from simply having a translation stop but still functioning. This should be mentioned.

This is correct. We cannot be sure the CTD TAG positions are not a mixture of ANAP-containing channels and truncations. See above for why we do not think this a big concern for the FRET experiments. Functionally, though, you are correct that we cannot tell. We now mention this in the paper.

Methods, the abbreviation for SBT should be defined somewhere.

Added.

Methods, unroofing section, middle paragraph, the authors use nM not nm to list wavelengths of light.

Changed.

Figure 3C-D: There's an unexpected blip in the Anap emission spectra at ~500 nm. Are the grating efficiency of the spectrograph and quantum efficiency of the camera accounted for in these spectra?

This is a good question. The data are not corrected for either camera efficiency or grating efficiency. We don’t have easy access to the actual data (although we can see a pdf version of each). There is a liVle blip in the grating efficiency graph that could partly explain the blip in our spectra.

Figure 5C, were recovery experiments routinely done? If so, would be good to show more than n = 1 in the plot to get an idea of reproducibility.

Recovery experiments were done in every experiment but are not shown for simplicity. We have included all FRET and recovery data for position Q14TAG-C469 at pH 6 in figure 5C to show reproducibility of our FRET and recovery data.

Table 1, considering adding a Δ distance column (pH 8 versus 6) so the magnitude of changes are more easily seen.

This is a reasonable suggestion but we decided not to include a Δ distance column. The data are whole numbers and people can easily determine the Δ distance. We felt that including that column would bring too much focus on what we think are preVy small changes. Our hope is that readers take away that the data are not consistent with complex formation between the determine and focus less on absolute distances.

Figure 7A, Q14tag pH 8 condition has a quite a bit of spread and, likely, two populations. These data, as well as G11, are unlikely to be parametric and hence ANOVA is inappropriate. A normality test, and likely Kruskal-Wallis test is called for.

Aker testing for normality, the data for Q14TAG C485 pH8 are non-normally distributed. However, a Kruskal Wallis is a non-parametric test for a one-way ANOVA and not applicable here. We separated the data out into population 1 and 2 and repeated the two-way ANOVA statistical test. When Q14TAG pH 8 is split into 2 populations, the statistics hardly change. When the data is not separated, Q14TAG pH 8 relative to pH 6 has a p-value <0.0001. When the 2 populations are separated, both populations relative to Q14TAG pH 6 still have a p-value of <0.0001.

Reviewer #1 (Public Review):

Cullinan et al. explore the hypothesis that the cytoplasmic N- and C-termini of ASIC1a, not resolved in x-ray or cryo-EM structures, form a dynamic complex that breaks apart at low pH, exposing a C-terminal binding site for RIPK1, a regulator of necrotic cell death. They expressed channels tagged at their N- and C-termini with the fluorescent, non-canonical amino acid ANAP in CHO cells using amber stop-codon suppression. Interaction between the termini was assessed by FRET between ANAP and colored transition metal ions bound either to a cysteine reactive chelator attached to the channel (TETAC) or metal-chelating lipids (C18-NTA). A key advantage to using metal ions is that they are very poor FRET acceptors, i.e. they must be very close to the donor for FRET to occur. This is ideal for measuring small distances/changes in distance on the scales expected from the initial hypothesis. In order to apply chelated metal ions, CHO cells were mechanically unroofed, providing access to the inner leaflet of the plasma membrane. At high pH, the N- and C- termini are close enough for FRET to be measured, but apparently too far apart to be explained by a direct binding interaction. At low pH, there was an apparent increase in FRET between the termini. FRET between ANAP on the N-and C-termini and metal ions bound to the plasma membrane suggests that both termini move away from the plasma membrane at low pH. The authors propose an alternative hypothesis whereby close association with the plasma membrane precludes RIPK1 biding to the C-terminus of ASIC1a.

The findings presented here are certainly valuable for the ion channel/signaling field and the technical approach only increases the significance of the work. The choice of techniques is appropriate for this study and the results are clear and high quality. Sufficient evidence is presented against the starting hypothesis. I have a few questions about certain controls and assumptions that I would like to see discussed more explicitly in the manuscript.

--As discussed by the authors, the C-terminal citrine could potentially disrupt the hypothesized interaction between the N- and C-termini.

--There is apparent read-through of some of the stop codons in the absence of ANAP, which could complicate interpretation of the experiments. The largest amount of read-through is for the E6TAG, L18TAG, and H515TAG constructs, which were not used for further experiments. However, some degree of read-through is evident from western blots for V10TAG, Q14TAG, L41TAG, and A44TAG as well.

Since the epitope used for western blots is on the C-terminus of the protein, the blots do not show the fraction of truncated protein. As discussed by the authors, N-terminally truncated constructs would be too small to assemble into channels. In constructs with the TAG codon towards the C-terminus, there is the potential for co-assembly of full-length and truncated subunits into trimers. Truncated subunits would not contribute directly to the fluorescence signal, but could potentially have allosteric effects on the position of the C-termini of full-length ANAP-tagged constructs in the context of a mixed channel.

reply to u/Low-Appointment-2906 at https://www.reddit.com/r/books/comments/17pitv9/when_does_annotating_books_become_a_distraction/

Through the middle ages, bookmakers would not only leave significant margins for readers to annotate, but they also illuminated books and included drolleries which readers in the know would use in conjunction with the arts of memory (from rhetoric) to memorize portions of texts more easily. I strongly suspect this isn't what booktokkers are doing; their practice is likely more like the sorts of decorative #ProductivityPorn one sees in the Bullet journal and journaling spaces. It's performative content creation.

Those interested in refining their practices of "reading with a pen in hand", continuing the "great conversation" or having "conversations with their texts" might profitably start with Mortimer J. Adler's essay: “How to Mark a Book” (Saturday Review of Literature, July 6, 1941). In his 1975 KCET series How to Read a Book, which was based on their book of the same name, Adler mentioned to Charles Van Doren that he would buy new copies of books so he could re-annotate them without being distracted by his older annotations.

Some have solved the problem of distracting annotations by interleaving their books so they've got lots of blank space to write their notes. It's a rarer practice now, but some publishers still print Bibles with blank pages every other page for this practice. Others put their annotations and notes into commonplace books or on index cards for their card index/zettelkasten.

As some have mentioned, friends and lovers through time have shared books with annotations as a way of sharing their thoughts. George Custer and his wife Elizabeth did this with Tennyson.

If you're interested in annotating digitally online, perhaps check out Hypothes.is where I've seen teachers and students using social annotation to read and make sense of books [example]. I've also seen groups of people use this tool for hosting online book groups/clubs.

If you're in it for fun, you might appreciate:

• https://archaeologyofreading.org/
• https://booktraces-public.lib.virginia.edu/
• My digital annotations on annotation

And those wishing to delve more deeply into the history and power of annotation might look at: Kalir, Remi H., and Antero Garcia. Annotation. The MIT Press Essential Knowledge Series. MIT Press, 2019. https://mitpressonpubpub.mitpress.mit.edu/annotation.

Good luck annotating! 📝

Author Response

The following is the authors’ response to the previous reviews

Reviewer #1 (Public Review):

Comments on the original submission:

Trypanosoma brucei undergoes antigenic variation to evade the mammalian host's immune response. To achieve this, T. brucei regularly expresses different VSGs as its major surface antigen. VSG expression sites are exclusively subtelomeric, and VSG transcription by RNA polymerase I is strictly monoallelic. It has been shown that T. brucei RAP1, a telomeric protein, and the phosphoinositol pathway are essential for VSG monoallelic expression. In previous studies, Cestari et al. (ref. 24) has shown that PIP5pase interacts with RAP1 and that RAP1 binds PI(3,4,5)P3. RNAseq and ChIPseq analyses have been performed previously in PIP5pase conditional knockout cells, too (ref. 24). In the current study, Touray et al. did similar analyses except that catalytic dead PIP5pase mutant was used and the DNA and PI(3,4,5)P3 binding activities of RAP1 fragments were examined. Specifically, the authors examined the transcriptome profile and did RAP1 ChIPseq in PIP5pase catalytic dead mutant. The authors also expressed several C-terminal His6-tagged RAP1 recombinant proteins (full-length, aa1300, aa301-560, and aa 561-855). These fragments' DNA binding activities were examined by EMSA analysis and their phosphoinositides binding activities were examined by affinity pulldown of biotin-conjugated phosphoinositides. As a result, the authors confirmed that VSG silencing (both BES-linked and MES-linked VSGs) depends on PIP5pase catalytic activity, but the overall knowledge improvement is incremental. The most convincing data come from the phosphoinositide binding assay as it clearly shows that N-terminus of RAP1 binds PI(3,4,5)P3 but not PI(4,5)P2, although this is only assayed in vitro, while the in vivo binding of full-length RAP1 to PI(3,4,5)P3 has been previously published by Cestari et al (ref. 24) already. Considering that many phosphoinositides exert their regulatory role by modulate the subcellular localization of their bound proteins, it is reasonable to hypothesize that binding to PI(3,4,5)P3 can remove RAP1 from the chromatin. However, no convincing data have been shown to support the author's hypothesis that this regulation is through an "allosteric switch".

Comments on revised manuscript:

In this revised manuscript, Touray et al. have responded to reviewers' comments with some revisions satisfactorily. However, the authors still haven't addressed some key scientific rigor issues, which are listed below:

1) It is critical to clearly state whether the observations are made for the endogenous WT protein or the tagged protein. It is good that the authors currently clearly indicate the results observed in vivo are for the RAP1-HA protein. However, this is not as clearly stated for in vitro EMSA analyses. In addition, in discussion, the authors simply assumed that the c-terminally tagged RAP1 behaves the same as WT RAP1 and all conclusions were made about WT RAP1.

There are two choices here. The authors can validate that RAP1-HA still retains RAP1's essential function as a sole allele in T. brucei cells (as was recommended previously). Indeed, HA-tagged RAP1 has been studied before, but it is the N-terminally HA-tagged RAP1 that has been shown to retain its essential functions. Adding the HA tag to the C-terminus of RAP1 may well cause certain defects to RAP1. For example, N-terminally HA-tagged TERT does not complement the telomere shortening phenotype in TERT null T. brucei cells, while C-terminally GFP-tagged TERT does, indicating that HA-TERT is not fully functional while TERT-GFP likely has its essential functions (Dreesen, RU thesis). Although RAP1-HA behaves similar to WT RAP1 in many ways, it is still not fully validated that this protein retains essential functions of RAP1. By the way, it has been published that cells lacking one allele of RAP1 behave as WT cells for cell growth and VSG silencing (Yang et al. 2009, Cell; Afrin et al. 2020, mSphere). In addition, although RAP1 may interact with TRF weakly, the interaction is direct, as shown in yeast 2-hybrid analysis in (Yang et al. 2009, Cell).

Alternatively, if the authors do not wish to validate the functionality of RAP1-HA, they need to add one paragraph at the beginning of the discussion to clearly state that RAP1-HA may not behave exactly as WT RAP1. This is important for readers to better interpret the results. In addition, the authors need to tune down the current conclusions dramatically, as all described observations are made on RAP1-HA but not the WT RAP1.

The results with RAP1-HA are consistent with previous knowledge of RAP1 interactions with telomeric proteins and DNA. Hence, the C-terminal HA-tagged RAP1 seems, by all measures, functional. Nevertheless, to make it clear for the reader, we added a note in the discussion, lines 244-246: “Although we showed that C-terminal HA-tagged RAP1 protein has telomeric localization (Cestari et al. 2015, PNAS) and interactions with other telomeric proteins (Cestari et al. 2019 Mol Cell Biol); we cannot rule out potential differences between HA-tagged and non tagged RAP1.”

For a similar reason, the current EMSA results truly reflect how C-terminally His6-tagged RAP1 and RAP1 fragments behave. If the authors choose not to remove the His6 tag, it is essential that they use "RAP1-His6" to refer to these recombinant proteins. It is also essential for the authors to clearly state in the discussion that the tagged RAP1 fragments bind DNA, but the current data do not reveal whether WT RAP1 binds DNA. In addition, the authors incorrectly stated that "disruption of the MybL domain sequence did not eliminate RAP1-telomere binding in vivo" (lines 165-166). In ref 29, deletion of Myb domain did not abolish RAP1-telomere association. However, point mutations in MybL domain that abolish RAP1's DNA binding activities clearly disrupted RAP1's association with the telomere chromatin. Therefore, the current observation is not completely consistent with that published in ref 29.

We stated in line 149-150 “…we expressed and purified from E. coli recombinant 6xHistagged T. brucei RAP1 (rRAP1)”. To clarify to the authors, we replaced rRAP1 with rRAP1-His throughout the manuscript and figures. As for the statement that “disruption of the MybL domain sequence did not eliminate RAP1-telomere binding in vivo" (lines 165-166).”. We removed the statement from the manuscript.

2) There is no evidence, in vitro or in vivo, that binding PI(3,4,5)P3 to RAP1 causes conformational change in RAP1. The BRCT domain of RAP1 is known for its ability to homodimerize (Afrin et al. 2020, mSphere). It is therefore possible that binding of PI(3,4,5)P3 to RAP1 simply disrupts its homodimerization function. The authors clearly have extrapolated their conclusions based on available data. It is therefore important to revise the discussion and make appropriate statements.

We did not state that PI(3,4,5)P3 causes RAP1 conformational changes. We discussed the possibility. We stated in lines 199-201: “PI(3,4,5)P3 inhibition of RAP1-DNA binding might be due to its association with RAP1 N-terminus causing conformational changes that affect Myb and MybL domains association with DNA.” This is a reasonable discussion, given the data presented in the manuscript.

Reviewer #2 (Public Review):

In this manuscript, Touray et al investigate the mechanisms by which PIP5Pase and RAP1 control VSG expression in T. brucei and demonstrate an important role for this enzyme in a signalling pathway that likely plays a role in antigenic variation in T. brucei. While these data do not definitively show a role for this pathway in antigenic variation, the data are critical for establishing this pathway as a potential way the parasite could control antigenic variation and thus represent a fundamental discovery.

The methods used in the study are generally well-controlled. The authors provide evidence that RAP1 binds to PI(3,4,5)P3 through its N-terminus and that this binding regulates RAP1 binding to VSG expression sites, which in turn regulates VSG silencing. Overall their results support the conclusions made in the manuscript. Readers should take into consideration that the epitope tags on RAP1 could alter its function, however.

There are a few small caveats that are worth noting. First, the analysis of VSG derepression and switching in Figure 1 relies on a genome which does not contain minichromosomal (MC) VSG sequences. This means that MC VSGs could theoretically be mis-assigned as coming from another genomic location in the absence of an MC reference. As the origin of the VSGs in these clones isn't a major point in the paper, I do not think this is a major concern, but I would not over-interpret the particular details of switching outcomes in these experiments.

We agree with the reviewer and thus made no speculations on minichromosomes. The data analysis must rely on the available genome, and the reference genome used is well-assembled with PacBio sequences and Hi-C data (Muller et al. 2018, Nature).

Another aspect of this work that is perhaps important, but not discussed much by the authors, is the fact that signalling is extremely poorly understood in T. brucei. In Figure 1B, the RNA-seq data show many genes upregulated after expression of the Mut PIP5Pase (not just VSGs). The authors rightly avoid claiming that this pathway is exclusive to VSGs, but I wonder if these data could provide insight into the other biological processes that might be controlled by this signaling pathway in T. brucei.

We published that the inositol phosphate pathway also plays a role in T. brucei development (Cestari et al. 2018, Mol Biol Cell; reviewed by Cestari I 2020, PLOS Pathogens)

Overall, this is an excellent study which represents an important step forward in understanding how antigenic variation is controlled in T. brucei. The possibility that this process could be controlled via a signalling pathway has been speculated for a long time, and this study provides the first mechanistic evidence for that possibility.

Reviewer #1 (Recommendations For The Authors):

Please see the public review for recommendations.1. It is critical to clearly state whether the observations are made for the endogenous WT protein or the tagged protein. It is good that the authors currently clearly indicate the results observed in vivo are for the RAP1-HA protein. However, this is not as clearly stated for in vitro EMSA analyses. In addition, in discussion, the authors simply assumed that the c-terminally tagged RAP1 behaves the same as WT RAP1 and all conclusions were made about WT RAP1.

There are two choices here. The authors can validate that RAP1-HA still retains RAP1's essential function as a sole allele in T. brucei cells (as was recommended previously). Indeed, HA-tagged RAP1 has been studied before, but it is the N-terminally HA-tagged RAP1 that has been shown to retain its essential functions. Adding the HA tag to the C-terminus of RAP1 may well cause certain defects to RAP1. For example, N-terminally HA-tagged TERT does not complement the telomere shortening phenotype in TERT null T. brucei cells, while C-terminally GFP-tagged TERT does, indicating that HA-TERT is not fully functional while TERT-GFP likely has its essential functions (Dreesen, RU thesis). Although RAP1-HA behaves similar to WT RAP1 in many ways, it is still not fully validated that this protein retains essential functions of RAP1. By the way, it has been published that cells lacking one allele of RAP1 behaves as WT cells for cell growth and VSG silencing (Yang et al. 2009, Cell; Afrin et al. 2020, mSphere). In addition, although RAP1 may interact with TRF weakly, the interaction is direct, as shown in yeast 2-hybrid analysis in (Yang et al. 2009, Cell).

Alternatively, if the authors do not wish to validate the functionality of RAP1-HA, they need to add one paragraph at the beginning of the discussion to clearly state that RAP1-HA may not behave exactly as WT RAP1. This is important for readers to better interpret the results. In addition, the authors need to tune down the current conclusions dramatically, as all described observations are made on RAP1-HA but not the WT RAP1.

The results with RAP1-HA are consistent with previous knowledge of RAP1 interactions with telomeric proteins and DNA. Hence, the C-terminal HA-tagged RAP1 seems, by all measures, functional. Nevertheless, to make it clear for the reader, we added a note in the discussion, lines 244-246: “Although we showed that C-terminal HA-tagged RAP1 protein has telomeric localization (Cestari et al. 2015, PNAS) and interactions with other telomeric proteins (Cestari et al. 2019 Mol Cell Biol); we cannot rule out potential differences between HA-tagged and non tagged RAP1.”

For a similar reason, the current EMSA results truly reflect how C-terminally His6-tagged RAP1 and RAP1 fragments behave. If the authors choose not to remove the His6 tag, it is essential that they use "RAP1-His6" to refer to these recombinant proteins. It is also essential for the authors to clearly state in the discussion that the tagged RAP1 fragments bind DNA, but the current data do not reveal whether WT RAP1 binds DNA. In addition, the authors incorrectly stated that "disruption of the MybL domain sequence did not eliminate RAP1-telomere binding in vivo" (lines 165-166). In ref 29, deletion of Myb domain did not abolish RAP1-telomere association. However, point mutations in MybL domain that abolish RAP1's DNA binding activities clearly disrupted RAP1's association with the telomere chromatin. Therefore, the current observation is not completely consistent with that published in ref 29.

We stated in lines 149-150 “…we expressed and purified from E. coli recombinant 6xHistagged T. brucei RAP1 (rRAP1)”. To clarify to the authors, we replaced rRAP1 with rRAP1-His throughout the manuscript text. As for the statement that “disruption of the MybL domain sequence did not eliminate RAP1telomere binding in vivo" (lines 165-166).”. We removed the statement from the manuscript.

2) There is no evidence, in vitro or in vivo, that binding PI(3,4,5)P3 to RAP1 causes conformational change in RAP1. The BRCT domain of RAP1 is known for its ability to homodimerize (Afrin et al. 2020, mSphere). It is therefore possible that binding of PI(3,4,5)P3 to RAP1 simply disrupts its homodimerization function. The authors clearly have extrapolated their conclusions based on available data. It is therefore important to revise the discussion and make appropriate statements.

We did not state that PI(3,4,5)P3 causes RAP1 conformational changes. We discussed the possibility. We stated in lines 199-201: “PI(3,4,5)P3 inhibition of RAP1-DNA binding might be due to its association with RAP1 N-terminus causing conformational changes that affect Myb and MybL domains association with DNA.” This is a reasonable discussion, given the data presented in the manuscript.

tag

Reviewer #2 (Public Review):

Casp11 is a cytosolic sensor for LPS in mice (orthologue of Casp4/5 in human). It is an important innate sensor of intracellular infection. Casp11 activity results in cleavage and activation of the pore-forming protein Gasdemin D (GSDMD) leading to lytic death (pyroptosis), of an infected cell. How exactly Casp11 signals upon LPS detection is beginning to be understood, but the picture is incomplete. Previous reports suggested that upon LPS detection, Casp11 dimerizes and undergoes auto-processing to form a pyroptosis-competent enzyme. The prediction from these studies was that the formation of a fully functional Casp11 signalling complex involves two steps: inducible dimerization and auto-processing.

In this study, authors used fluorescently tagged Casp11 reporter fusions, to report that detection of cytosolic LPS induces Casp11 assembly into a large perinuclear speck to form a signalling complex, where GSDMD can be processed. Such signalling complex resembles signalling specks formed upon the activation of other canonical inflammasomes.

Strengths:

Results are clean, experiments well controlled, and support the conclusions. Overall conclusions fit nicely in the general principle of innate signalling, whereby activation of many innate sensors results in their inducible assembly into higher-order oligomeric signalling complexes, called supra-molecular organizing centers (SMOCs).

A surprising finding from this work was that catalytically inactive Casp11 (C254A mutant) did not form signalling specks, despite being able to bind LPS and dimerise. This model is proposed where LPS binding to the CARD domain of Casp11 and Casp11 dimerization is necessary but not sufficient to mediate Casp11 speck formation within cells. The Casp11 catalytic activity is needed to facilitate the assembly of the higher-order, pyroptosis-competent Casp11 signalling platform. The model is further supported by experimental evidence that auto-processing of Casp11, by an exogenous protease TEV, (i.e. in the absence of LPS), is sufficient to mediate speck assembly in cells expressing wild type, but not catalytically inactive Casp11 mutant.

Possible technical improvements:

In general, the authors achieved their aims, and the results support the conclusions.

For technical robustness, it would be nice to consider a few controls:<br /> (a) Visualise Casp11 specks using constructs with smaller tags, and test whether tag placement on N or C terminus matters for speck formation; or<br /> (b) Biochemically crosslink and isolate endogenous, untagged Casp11 specks upon LPS transfection of primed macrophages (e.g. after priming through IFNs or TLRs). This would mimic the natural upregulation and activation of endogenous Casp11.<br /> (c) Test what happens after actual intracellular pathogen detection when the pathogen itself serves as a signalling platform? Are specks stills formed (or even needed)?

The broad impact of the work, implication, and questions for future work:

Results of this study would suggest that the enzymatic activity of Casp11 in macrophages may be highly restricted to the speck location, similar to what was described for Casp1. This may explain the very restricted substrate repertoire of Casp11 in cells, likely controlled by the substrate recruitment to the speck. This also opens avenues for follow-up work to answer several emerging questions:

1. After LPS binding and dimerization, why Casp11 must undergo intra-molecular processing to induce the formation of a pyroptosis-competent speck? Is there any substrate for LPS-bound, uncleaved Casp11 (beyond Casp11 itself), before Casp11 forms a full speck for GSDMD processing? The only currently known targets of Casp11 activity are itself, and GSDMD. Also, after intradomain linker cleavage of Casp11, what additional substrate must the cleaved Casp11 process to allow full speck formation?

2. Can activity probes be designed to detect the location of the active Casp11, and if so, would the activity of Casp11 be restricted to the speck? Is there a second cleavage event that would eventually dissociate Casp11 from the speck, to terminate its signalling? If not, how is speck activity terminated? If specks are released by lysis, are they capable of seeding new speck formation in neighbouring phagocytes, in prion-like behaviour previously described for canonical ASC speck?

3. What is the role of macrophage priming in speck formation, and what roles, if any GBPs play in speck formation?

4. Does this model apply to human orthologues, Casp4/5?

Author Response

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

Reviewer #1 (Public Review):

Several concerns are raised from the current study.

1) Previous studies showed that iTregs generated in vitro from culturing naïve T cells with TGF-b are intrinsically unstable and prone to losing Foxp3 expression due to lack of DNA demethylation in the enhancer region of the Foxp3 locus (Polansky JK et al, Eur J Immunol., 2008, PMID: 18493985). It is known that removing TGF-b from the culture media leads to rapid loss of Foxp3 expression. In the current study, TGF-b was not added to the media during iTreg restimulation, therefore, the primary cause for iTreg instability should be the lack of the positive signal provided by TGF-b. NFAT signal is secondary at best in this culturing condition.

In restimulation, void of TGFb is necessary to cause iTreg instability. Otherwise, the setup is similar to the iTreg-inducing environment (Author response image 1). On the other hand, the ultimate goal of this study is to provide a scenario that bears some resemblance of clinical treatment, where TGFb may not be available. The reviewer is correct in stating that TGFb is essential for iTreg stability, we are studying the role played by NFAT in iTreg instability in vitro, and possibly in potential clinical use of iTreg .

Author response image 1.

Restimulation with TGFb will persist iTreg inducing environment, resulting in less pronounced instability. Sorted Foxp3-GFP+ iTregs were rested for 1d, and then rested or restimulated in the presence of TGF-β for 2 d. Percentages of Foxp3+ cells were analyzed by intracellular staining of Foxp3 after 2 d.

2) It is not clear whether the NFAT pathway is unique in accelerating the loss of Foxp3 expression upon iTreg restimulation. It is also possible that enhancing T cell activation in general could promote iTreg instability. The authors could explore blocking T cell activation by inhibiting other critical pathways, such as NF-kb and c-Jun/c-Fos, to see if a similar effect could be achieved compared to CsA treatment.

We thank the reviewer for this suggestion. We performed this experiment according to see extent of the role that NFAT plays, or whether other major pathways are involved. As Author response image 2 shows, solely inhibiting NFAT effectively rescued the instability of iTreg. The inhibition of NFkB (BAY 11-7082), c-Jun (SP600125), or a c-Jun/c-Fos complex (T5224) had no discernable effect, or in one case, possibly further reduction in stability. These results may indicate that NFAT plays a crucial and special role in TCR activation, which leads to iTreg instability. Other pathways, as far as how this experiment is designed, do not appear to be significantly involved.

Author response image 2.

Comparing effects of NFAT, NF-kB and c-Jun/c-Fos inhibitors on iTreg instability. Sorted Foxp3-GFP+ iTregs were rested for 1d, then restimulated by anti-CD3 and CD28 in the presence of listed inhibitors. Percentages of Foxp3+ cells were analyzed by intracellular staining after 2d restimulation.

3) The authors linked chromatin accessibility and increased expression of T helper cell genes to the loss of Foxp3 expression and iTreg instability. However, it is not clear how the former can lead to the latter. It is also not clear whether NFAT binds directly to the Foxp3 locus in the restimulated iTregs and inhibits Foxp3 expression.

T helper gene activation is likely to cause instability in iTregs by secreting more inflammatory cytokines, as shown in Figure Q9, for example, IL-21 secretion. Further investigation is needed to understand how these genes contribute to Foxp3 gene instability exactly. With our limited insight, there may be two possibilities. 1. IL-21 directly affects Foxp3 through its impact on certain inflammation-related transcription factors (TFs). 2. There could be an indirect relationship where NFAT has a greater tendency to bind to those inflammatory TFs when iTreg instability appears, promoting the upregulation of these Th genes like in activated T cells, while being less likely to bind to SMAD and Foxp3, representing a competitive behavior. We at the moment cannot comprehend the intricacies that lead to the differential effects on T helper genes and Treg related genes.

With that said, we have previously attempted to explore the direct effect of NFAT on Foxp3 gene locus. Foxp3 transcription in iTregs primarily relies on histone modifications such as H3K4me3 (Tone et al., 2008; Lu et al., 2011) rather than DNA demethylation (Ohkura et al., 2012; Hilbrands et al., 2016). Previous studies have reported that NFAT and SMAD3 can together promote the histone acetylation of Foxp3 genes (Tone et al., 2008). In our previous set of experiments, we simultaneously obtained information of NFAT binding sites and H3K4me3. In Foxp3 locus, we observed a decreasing trend in NFAT binding to the CNS3 region of Foxp3 in restimulated iTregs compared to resting iTregs (Author response image 3). Additionally, the H3K4me3 modification in the CNS3 region of Foxp3 decreased upon iTreg restimulation, but inhibiting NFAT nuclear translocation with CsA could maintain this modification at its original level (Author response image 3).

Author response image 3.

The NFAT binding and histone modification on Foxp3 gene locus. Genome track visualization of NFAT binding profiles and H3K4me3 profiles in Foxp3 CNS3 locus in two batches of dataset.

Based on these preliminary explorations, it is concluded that NFAT can directly bind to the Foxp3 locus, and it appears that NFAT decreases upon restimulation, resulting in a decrease in H3K4me3, ultimately leading to the close association of NFAT and Foxp3 instability. However, due to limited sample replicates, these data need to be verified for more solid conclusions. We speculate that during the induction of iTregs, NFAT may recruit histone-modifying enzymes to open the Foxp3 CNS3 region, and this effect is synergistic with SMAD. When instability occurs upon restimulation, NFAT binding to Foxp3 weakens due to the absence of SMAD's assistance, subsequently reducing the recruitment of histone modifications enzyme and ultimately inhibiting Foxp3 transcription.

Reviewer #2 (Public Review):

(1) Some concerns about data processing and statistic analysis.

The authors did not provide sufficient information on statistical data analysis; e.g. lack of detailed descriptions about

-the precise numbers of technical/biological replicates of each experiment

-the method of how the authors analyze data of multiple comparisons... Student t-test alone is generally insufficient to compare multiple groups; e.g. figure 1.

These inappropriate data handlings are ruining the evidence level of the precious findings.

We thank the reviewer for pointing out this important aspect. In the figure legend, numbers of independently-performed experiment repeats are shown as N, biological replicates of each experiment as n. Student’s t test was used for comparing statistical significance between two groups. In this manuscript, all calculations of significant differences were based on comparisons between two groups. There were no multiple conditions compared simultaneously within a single group, and thus, no other calculation methods were used.

(2) Untransparent data production; e.g. the method of Motif enrichment analysis was not provided. Thus, we should wait for the author's correction to fully evaluate the significance and reliability of the present study.

Per this reviewer’s request, we have provided detailed descriptions of the data analysis for Fig 5, including both the method section and the Figure legend, as presented below:

“The peaks annotations were performed with the “annotatePeak” function in the R package ChIPseeker (Yu et al, 2015).

The plot of Cut&Tag signals over a set of genomic regions were calculated by using “computeMatrix” function in deepTools and plotted by using “plotHeatmap” and “plotProfile” functions in deepTools. The motif enrichment analysis was performed by using the "findMotifsGenome.pl" command in HOMER with default parameters.

The motif occurrences in each peak were identified by using FIMO (MEME suite v5.0.4) with the following settings: a first-order Markov background model, a P value cutoff of 10-4, and PWMs from the mouse HOCOMOCO motif database (v11).”

Additionally, we have also supplemented the method section with further details on the analysis of RNA-seq and ATAC-seq data.

(3) Lack of evidence in human cells. I wonder whether human PBMC-derived iTreg cells are similarly regulated.

This is a rather complicated issue, human T cells express FoxP3 upon TCR stimulation (PNAS, 103(17): 6659–6664), whose function is likely to protect T cells from activation induced cell death, and does not offer Treg like properties. In contrast in mice, FoxP3 can be used as an indicator of Treg. Currently, this is not a definitive marker for Treg in human, our FoxP3 based readouts do not apply. Nevertheless, we have now investigated whether inhibiting calcium signaling or NFAT could enhance the stability of human iTreg. As shown in Author response image 4, we found that the proportion of Foxp3-expressing cells did not show significant changes across the different conditions, while the MFI analysis revealed that CsA-treated iTreg exhibited higher Foxp3 expression levels compared to both restimulated iTreg and rest iTreg. However, CM4620 had no significant effect on Foxp3 stability, consistent with the observation of its limited efficacy in suppressing human iTreg long term activation. In summary, our results suggest that inhibiting NFAT signaling through CsA treatment can help maintain higher levels of Foxp3 expression in human iTreg.

Author response image 4.

Effect of inhibiting NFAT and calcium on human iTreg stability. Human naïve CD4 cells from PBMC were subjected to a two-week induction process to generate human iTreg. Subsequently, human iTreg were restimulated for 2 days with dynabeads followed by 2 days of rest in the prescence of CsA and CM-4620. Four days later, percentages of Foxp3+ cells and Foxp3 mean fluorescence intensity (MFI) were analyzed by intracellular staining.

(4) NFAT regulation did not explain all of the differences between iTregs and nTregs, as the authors mentioned as a limitation. Also, it is still an open question whether NFAT can directly modulate the chromatin configuration on the effector-type gene loci, or whether NFAT exploits pre-existing open chromatin due to the incomplete conversion of Treg-type chromatin landscape in iTreg cells. The authors did not fully demonstrate that the distinct pattern of chromatin regional accessibility found in iTreg cells is the direct cause of an effector-type gene expression.

To our surprise, the inhibition of NFkB (BAY 11-7082), c-Jun (SP600125), and the c-Jun/c-Fos complex (T5224) resulted in minimal alterations, as shown in Fig Q1. This seems to argue that NFAT may play a more special role in events leading iTreg instability.

We hypothesize that NFAT takes advantage of pre-existing open chromatin state due to the incomplete conversion of chromatin landscape in iTreg cells. Because iTreg cells, after induction, already exhibit inherent chromatin instability, with highly-open inflammatory genes. Furthermore, when iTreg cells were restimulated, the subsequent change in chromatin accessibility was relatively limited and not rescued by NFAT inhibitor treatment (Author response image 5). Therefore, in the case of iTreg cells, we propose that NFAT exploits the easy access of those inflammatory genes, leading to rapid destabilization of iTreg cells in the short term.

In contrast, tTreg cells possess a relatively stable chromatin structure in the beginning, it would be interesting to investigate whether NFAT or calcium signaling could disrupt chromatin accessibility during the activation or expansion of tTreg cells. It is possible that NFAT might cause the loss of the originally established demethylation map and open up inflammatory loci, thereby inducing a shift in gene transcriptional profiles, equally leading to instability.

Author response image 5.

Chromatin accessibility of Rest, Retimulated, CsA/ORAIinh treated restimulated iTreg. PCA visualization of chromatin accessibility profiles of different cell types. Color indicates cell type.

To establish a direct relationship between gene locus accessibility and its overexpression, a controlled experimental approach can be employed. One such method involves precise manipulation of the accessibility of a specific genomic locus using CRISPR-mediated epigenetic modifications at targeted loci. Subsequently, the impact of this manipulation on the expression level of the target gene can be precisely examined. By conducting these experiments, it will be possible to determine whether the augmented gene accessibility directly causes the observed gene overexpression.

Reviewer #1 (Recommendations For The Authors):

1) It might be helpful to add TGF-b to the iTreg restimulation culture to remove the influence of the lack of TGF-b from the equation, and measure the influence of SOCE/NFAT on iTreg instability.

Please refer to Author response image 1.

2) Alternatively, authors can also culture iTreg cells with TGF-b for 2 weeks when they undergo epigenetic changes and become more stabilized (Polansky JK et al, Eur J Immunol., 2008, PMID: 18493985). At this point, the stabilized iTregs can be used to measure the influence of SOCE/NFAT on iTreg instability.

In the study conducted by Polansky, it was observed in Figure 1 that prolonged exposure to TGF-β fails to induce stable Foxp3 expression and demethylation of the Treg-specific demethylated region (TSDR). Based on this finding, we could consider exploring alternative approaches to obtain a more stabilized iTreg population. One such approach could be isolating Foxp3+helios-Nrp1- iTreg cells directly from the peripheral in vivo, which are also known as pTregs. Generally, pTreg cells generated in vivo tend to be more stable compared to iTreg cells induced in vitro, and they already exhibit partial demethylation of the Treg signature, as shown in Fig 6C (Polansky JK et al, Eur J Immunol., 2008, PMID: 18493985). Investigating the role of NFAT and calcium signaling in pTreg cells would provide further insights into the additional roles of NFAT in Treg phenotypical transitions, particularly its role in chromatin accessibility.

3) In Figure 3, NFAT binding to the inflammatory genes in iTreg cells was even stronger than in activated T conventional cells. This is possibly due to Tconv cells being stimulated only once while iTregs were restimulated. A fair comparison should be conducted with restimulated activated conventional T cells.

Figure 3 demonstrates the accessibility of inflammatory gene loci, rather than NFAT binding. Comparing restimulated Tconvs with restimulated iTreg cells is indeed a valuable suggestion, as their activation state and polarization in iTreg directions could lead to distinct chromatin accessibility. Although one is activated long term regularly and the other is activated long term under iTreg polarization, it is highly likely that the chromatin state of both activated Tconvs and iTreg cells is highly open, especially in terms of the accessibility of inflammatory genes. This may provide us with a new perspective to understand iTreg cells, but will unlikely affect our central conclusion.

4) In the in vivo experiment in Figure 6, a control condition without OVA immunization should be included as a baseline.

We have performed this experiment in the absence of OVA, as depicted in Author response image 6. In the absence of OVA immunization, both WT-ORAI and DN-ORAI iTreg exhibited substantial stability, although DN-ORAI demonstrated a slightly less stable trend. Upon activation with 40ug and 100ug of OVA, DN-ORAI iTreg demonstrated enhanced stability than WT-ORAI iTreg, maintaining a higher proportion of Foxp3 expression.

Author response image 6.

Stability of DN-ORAI iTreg in vivo with or without OVA immunization. WT-ORAI/DN-ORAI-GFP+-transfected CD45.2+ Foxp3-RFP+ OT-II iTregs were transferred i.v. into CD45.1 mice. Recipients were left or immunized with OVA323-339 in Alum adjuvant. On day 5, mLN were harvested and analyzed for Foxp3 expression by intracellular staining.

Reviewer #2 (Recommendations For The Authors):

Major

Some concerns about the data processing and statistic analysis, as mentioned in the public review. In the figure legend, what does it mean e.g. n=3, N=3? Technical triplicate experiments? Three mice? Independently-performed three experiments? The authors should define it at least in the "Statistical analysis" in the method section otherwise the readers cannot determine the reason why they mainly use SEM for the data description.

Moreover, in some cases, the number of experiments was not sure; e.g., Fig.1B, Fig. 5.

How did the authors analyze data including multiple comparisons? Student t-test alone is generally insufficient to compare multiple groups; e.g. figure 1.

We thank the reviewer for pointing out this omission. Now, in the figure legend, numbers of independently-performed experiment repeats are shown as N, biological replicates of each experiment as n. For Fig. 1B, N=2, and for Fig 5, we have acquired NFAT Cut&Tag data for 2 times, N=2. Student’s t test was used for comparing statistical significance between two groups. In this manuscript, all calculations of significant differences were based on comparisons between two groups. There were no multiple conditions compared simultaneously within a single group, and thus, no other calculation methods were involved apart from the Student's t-test.

In Figure 1A, the difference in suppressiveness seemed subtle. Data collection of multiple doses of Tconv:Treg ratio will enhance the reliability of such kind of analysis.

We have now attempted the suppression assay with varying Treg:Tconv ratios and observed that the suppressive effect of iTreg was more obvious than that of tTreg when co-cultured at a 1:1 ratio with Tconv cells. However, as the cell number of tTreg and iTreg decreased, the inhibitory effects converged.

Author response image 7.

Compare multiple dose of Tconv:Treg ratio in suppression function CFSE-labelled OT-II T cells were stimulated with OVA-pulsed DC, then different number of Foxp3-GFP+ iTregs and tTregs were added to the culture to suppress the OT-II proliferation. After 4 days, CFSE dilution were analyzed. Left, Representative histograms of CFSE in divided Tconvs. Right, graph for the percentage of divided Tconvs.

In Figure 3F, to which group did the shaded peaks belong? In this context, the authors should focus on "Activation Region" peaks (open chromatin signature in both TcAct & iTreg defined in Fig. 4D) but I did not find the peak in the focusing DNA regions in TcAct (e.g. the shaded regions in IL-4 loci). The clear attribution of the peaks to the heatmap will enhance the visibility and understanding of readers.

We have selected some typical peaks that belong to Fig 3D. These genes encompass some T-cell activation-associated transcription factors, such as Irf4, Atf3, as well as multiple members of the Tnf family including Lta, Tnfsf4, Tnfsf8, and Tnfsf14. Additionally, genes related to inflammation such as Il12rb2, Il9, and Gzmc are included. These genes show elevated accessibility upon T-cell activation, partially open in activated nTreg cells, referred to as the "Activation Region." They collectively exhibit high accessibility in iTreg cells, which may contribute to their instability.

Author response image 8.

Chromatin accessibility of some “Activation Region”. Genomic track showing chromatin accessibility of Irf4, Atf3, Lta, Tnfsf8, Tnfsf4, Tnsfsf14, Il12rb2, Il9, Gzmc in activated Tconv and iTreg.

In Figure 4A/S4A, the information on cell death will help the understanding of readers because the sustained SOCE is associated with cell survival as shown in Fig. S2. The authors can discuss the relationships between cell death and Foxp3 retention, which potentially leads to a further interesting question; e.g. the selective/resistance to activation-induced cell death as the identity of Treg cells.

As shown in Author response image 9, activated iTreg cells indeed exhibit a certain degree of cell death compared to resting iTreg cells. The inhibition of NFAT by CsA enhances the survival rate of iTreg cells, but the inhibition of ORAI by CM-4620 leads to more severe cell death. The cell death induced by CsA and CM-4620 is not consistent, indicating that there may not be a direct proportional relationship between cell death and the expression of Foxp3 and Treg identity.

Author response image 9.

Relationship of cell death and Foxp3 stability in restimulated iTregs.<br /> Sorted Foxp3-GFP+ iTregs were rested for 1d, then restimulated by anti-CD3 and CD28 in the presence of CsA or CM-4620. After 2d restimulation, live cell percentage were analyzed by staining of Live/Dead fixable Aqua, and percentages of Foxp3+ cells were analyzed by intracellular staining of Foxp3. Upper, live cell percentage of iTregs. Lower, percentages of Foxp3 in iTregs.

In Figure 5, the information for the data interpretation was insufficient.

We have provided detailed descriptions of the data analysis for Fig 5, including both the method section and the Figure legend, as presented below:

“The peaks annotations were performed with the “annotatePeak” function in the R package ChIPseeker (Yu et al, 2015). The plot of Cut&Tag signals over a set of genomic regions were calculated by using “computeMatrix” function in deepTools and plotted by using “plotHeatmap” and “plotProfile” functions in deepTools. The motif enrichment analysis was performed by using the "findMotifsGenome.pl" command in HOMER with default parameters. The motif occurrences in each peak were identified by using FIMO (MEME suite v5.0.4) with the following settings: a first-order Markov background model, a P value cutoff of 10-4, and PWMs from the mouse HOCOMOCO motif database (v11).”

Additionally, we have also supplemented the method section with further details on the analysis of RNA-seq and ATAC-seq data.

The correlation between the open chromatin status of the gene loci described in Fig.5E and the expression at mRNA level? e.g.; Do iTreg-Act cells produce a higher level of IL-21 than nTreg-act? The analysis in Fig.5F-G should be performed in parallel with nTreg cells to emphasize the distinct NFAT-chromatin regulation in iTreg cells.

We have now compared the secretion levels of IL-21 in tTreg and iTreg upon activation and treated with CsA by ELISA. As shown in Author response image 10, tTreg did not secrete IL-21 regardless of activation status (undetectable), while iTreg did not secrete IL-21 at resting state but exhibited IL-21 secretion after 48 h of activation. Moreover, the secretion of IL-21 was inhibited by CsA and CM-4620 treatment. This observation aligns with our earlier findings where we observed nuclear binding of NFAT to gene loci of these cytokines, enhancing their expression and pushing iTreg unstable under inflammatory conditions. These findings further underscore the likelihood that the inhibition of calcium and NFAT signaling might contribute to the stabilization of iTreg by suppressing the secretion of inflammatory cytokines.

Author response image 10.

IL-21 secretion in tTreg and iTreg upon activation.<br /> iTregs and tTregs were sorted and restimulated with anti-CD3 and anti-CD28 antibodies, in the presence of CsA and CM-4620. Cell culture supernatant were harvested after 2 d restimulation and IL-21 secretion was analyzed by ELISA.

Performing a parallel comparison of NFAT activity between tTreg and iTreg cells was initially part of our experimental plan. However, it proved challenging in practice, as we encountered difficulties in efficiently infecting tTreg cells with NFAT-flag. Consequently, we could not obtain a sufficient number of tTreg cells for conducting Cut&Tag experiments.

Based on our observations, we speculate that there might be substantial differences in the accessibility of genes in tTreg cells, leading to considerable variations in the repertoire of genes available for NFAT to regulate. As a result, we expect significant differences in the nuclear localization and activity of NFAT between iTreg and tTreg cells.

In Figure 6C, what does the FCM plot between Foxp3-CFSE look like?

The authors can discuss the mechanism of ORAI-DN-mediated through such analysis; e.g. the possibility that selective proliferation defect by ORAI-DN in Foxp3- cells led to an increased percentage of Foxp3, not only just unstable transcription of Foxp3.

This is an in vitro experiment to assess the suppressive effect of iTreg on Tconv proliferation. Therefore, CFSE is used to stain Tconv cells, but not iTreg cells, so we did not detect proliferation feature of iTreg.

Minor

Confusing terminology of "tTreg" at line 47, etc. "natural Treg" contains both thymic-derived Treg and periphery-derived Treg cells. (A Abbas et al. Nat Immunol. 2013)

We have now changed the designation to tTreg at line 47. tTreg refers to thymus-derived regulatory T cells, while nTreg includes both tTreg and pTreg. However, it is important to note that the Treg cells used in our study were isolated from the spleen of 2-4-month-old Foxp3-GFP or Foxp3-RFP mice. The CD4+ T cells were first enriched using the CD4 Isolation kit, and the FACSAriaII was utilized to collect CD4+ Foxp3-GFP/RFP+ Treg cells. Subsequently, Helios and Nrp-1 staining revealed that the majority of these cells were nTreg, with only approximately 6% being pTreg. Overall, we consider the cells we used as tTreg.

In all FCM analyses, the authors should clarify how to detect Foxp3 expression; Foxp3-GFP/Foxp3-RFP/Intracellular staining like Figure S5A (but not specified in the other FCM plots)

All Foxp3 expressions in the article were assessed using intracellular staining, as described in the methods section, and we have added specific descriptions to each figure legend. The reason for employing intracellular staining is that we used Foxp3-IRES-GFP mice, where GFP and Foxp3 are not fused into a single protein, existing as separate proteins after expression. Therefore, during induction, the appearance of GFP protein might potentially represent the presence of Foxp3. However, in cases of Foxp3 instability, the degradation of GFP protein may not be entirely synchronized with that of Foxp3 protein, making GFP an unreliable indicator of Foxp3 expression levels. As a result, for the purification of pure iTreg cells, we used Foxp3-GFP/RFP fluorescence, while for observing instability, we employed intranuclear staining of Foxp3.

In Figure 6B, the captions were lacking in the two graphs on the right side

The two restimulation conditions, 0.125+0.25 and 0.25+0.5, have been added into Fig 6B right side.

In Figure S2, the annotation of the x-y axis was missing.

Added.

Lack of reference at line 292.

Reference 42-46 were added.

In the method section, the authors should note the further product information of antibodies and reagents to enhance reproducibility and transparency. Making a list that clarifies the suppliers, Ab clone, product IDs, etc. is encouraged. The authors did not specify the supplier of recombinant proteins and which type of TGF-beta (TGF-beta 1, 2, or 3?).

A detailed description of the mice, antibodies, Peptide recombinant protein, commercial kit, and software has been provided and incorporated into the methods section.

In the method section, the authors should clarify which Foxp3-reporter strain. There are many strains of Foxp3-reporter mice in the world. In line 373, is the "FoxP3-IRES-GFP transgenic mice" true? Knock-in strain or BAC-transgene?

This mouse is a gift from Hai Qi Lab in Tsinghua University. They acquired this mouse strain from Jackson Laboratory, and the strain name is B6.Cg-Foxp3tm2Tch/J, Strain #:006772. An IRES-EGFP-SV40 poly A sequence was inserted immediately downstream of the endogenous Foxp3 translational stop codon, but upstream of the endogenous polyA signal, generating a bicistronic locus encoding both Foxp3 and EGFP.

The age of mice used in the experiments should be specified, and confusing words such as "young" should not be used in any method descriptions; e.g. line 405.

The detailed mouse age has been added in the methods section. “To prepare Tconv, tTreg and iTreg for experiments, spleen was isolated from 2-4-month-old Foxp3-GFP mice for Tconv and tTreg sorting, and 6-week-old mice for iTreg induction.”

The method of how the original ATAC-seq/Cut & Tag data were generated was not described in the method section.

Added in method section.

The reference section was incomplete, and the style was not unified. e.g.; ref 7, 24, 25, 26 ... I gave up checking all.

The style of ref 7, 22, 24, 26, 28, 31, 33, 35 were modified.

Changes in manuscript:

Author Name: “Huiyun Lv” to “Huiyun Lyu”.

Fig 1A was updated according to Reviwer 2’s suggestion.

Fig S3E and associated description was added according to Reviwer 2’s suggestion.

Fig S4C and associated description was added according to Reviwer 1’s suggestion.

Fig 5H and associated description was added according to Reviwer 2’s suggestion.

Fig 6D were updated according to Reviwer 1’s suggestion.

Fig 2D was corrected, the labels for gapdh and actin in the iTreg panel were inadvertently switched. The mistake has been rectified, and the original gel image will be provided.

Fig 2A and Fig 4A was updated.

The style of Fig 6B and Fig S2A was modified.

Method:

Mice: FoxP3-IRES-GFP with more description.

Flow Cytometry sorting and FACS: the detailed mouse age has been added. RNA-seq analysis, ATAC-sequencing, ATAC-seq analysis, Cut&Tag assay, Cut&Tag data analysis: more description was added.

Statistical analysis: “Numbers of independently-performed experiment repeats are shown as N, biological replicates of each experiment as n.” were added.

Reference: Ref 42-46 and 49-52 were added. The style of ref 7, 22, 24, 26, 28, 31, 33, 35 were corrected.

A detailed description of the mice, antibodies, Peptide recombinant protein, commercial kit, and software has been provided.

Reviewer #2 (Public Review):

Summary:

Chew et al describe interaction of the flavivirus protein NS1 with HDL using primarily cryoEM and mass spec. The NS1 was secreted from dengue virus infected Vero cells, and the HDL were derived from the 3% FBS in the culture media. NS1 is a virulence factor/toxin and is a biomarker for dengue infection in patients. The mechanisms of its various activities in the host are incompletely understood. NS1 has been seen in dimer, tetramer and hexamer forms. It is well established to interact with membrane surfaces, presumably through a hydrophobic surface of the dimer form, and the recombinant protein has been shown to bind HDL. In this study, cryoEM and crosslinking-mass spec are used to examine NS1 secreted from virus-infected cells, with the conclusion that the sNS1 is predominantly/exclusively HDL-associated through specific contacts with the ApoA1 protein.

Strengths:

The experimental results are consistent with previously published data.

Weaknesses:

CryoEM:

Some of the neg-stain 2D class averages for sNS1 in Fig S1 clearly show 1 or 2 NS1 dimers on the surface of a spherical object, presumably HDL, and indicate the possibility of high-quality cryoEM results. However, the cryoEM results are disappointing. The cryo 2D class averages and refined EM map in Fig S4 are of poor quality, indicating sub-optimal grid preparation or some other sample problem. Some of the FSC curves (2 in Fig S7 and 1 in Fig S6) have extremely peculiar shapes, suggesting something amiss in the map refinement. The sharp drop in the "corrected" FSC curves in Figs S5c and S6c (upper) indicate severe problems. The stated resolutions (3.42 & 3.82 Å) for the sNS1ts-Fab56.2 are wildly incompatible with the images of the refined maps in Figs 3 & S7. At those resolutions, clear secondary structural elements should be visible throughout the map. From the 2D averages and 3D maps shown in the figures this does not seem to be the case. Local resolution maps should be shown for each structure.

The samples were clearly challenging for cryoEM, leading to poor quality maps that were difficult to interpret. None of the figures are convincing that NS1, Ab56.2 or Fab56.2 are correctly fit into EM maps. There is no indication of ApoA1 helices. Details of the fit of models to density for key regions of the higher-resolution EM maps should be shown and the models should be deposited in the PDB. An example of modeling difficulty is clear in the sNS1ts dimer with bound Fab56.2 (figs 3c & S7e). For this complex, the orientation of the Fab56.2 relative to the sNS1ts dimer in this submission (Fig 3c) is substantially different than in the bioRxiv preprint (Fig 3c). Regions of empty density in Fig 3c also illustrate the challenge of building a model into this map.

Mass spec:

Crosslinking-mass spec was used to detect contacts between NS1 and ApoA1, providing strong validation of the sNS1-HDL association. As the crosslinks were detected in a bulk sample, they show that NS1 is near ApoA1 in many/most HDL particles, but they do not indicate a specific protein-protein complex. Thus, the data do not support the model of an NS1-ApoA1 complex in Fig 4d. Further, a specific NS1-ApoA1 interaction should have evidence in the EM maps (helical density for ApoA1), but none is shown or mentioned. If such exists, it could perhaps be visualized after focused refinement of the map for sNS1ts-HDL with Fab56.2 (Fig S7d). The finding that sNS1-ApoA1 crosslinks involved residues on the hydrophobic surface of the NS1 dimer confirms previous data that this NS1 surface engages with membranes and lipids.

Sample quality:

The paper lacks any validation that the purified sNS1 retains established functions, for example the ability to enhance virus infectivity or to promote endothelial dysfunction. Peculiarities include the gel filtration profiles (Fig 2a), which indicate identical elution volumes (apparent MWs) for sNS1wt-HDL bound to Ab562 (~150 kDa) and to the ~3X smaller Fab56.2 (~50 kDa). There should also be some indication of sNS1wt-HDL pairs crosslinked by the full-length Ab, as can be seen in the raw cryoEM micrograph (Fig S5b).

Obtaining high quality structures is often more demanding of sample integrity than are activity assays. Given the low quality of the cryoEM maps, it's possible that the acidification step in immunoaffinity purification damaged the HDL complex. No validation of HDL integrity, for example with acid-treated HDL, is reported. Acid treatment is perhaps discounted by a statement (line 464) that another group also used immunoaffinity purification in a recent study (ref 20) reporting sNS1 bound to HDL. However the statement is incorrect; the cited study used affinity purification via a strep-tag on recombinant sNS1.

Discussion:

The Discussion reflects a view that the NS1 secreted from virus-infected cells is a 1:1 sNS1dimer:HDL complex with the specific NS1-ApoA1 contacts detected by crosslinking mass spec. This is inconsistent with both the neg-stain 2D class average with 2 sNS1 dimers on an HDL (Fig S1c) and with the recent study of Flamand & co-workers showing 1-3 NS1 dimers per HDL (ref 20). It is also ignores the propensity of NS1 to associate with membranes and lipids. It is far more likely that NS1 association with HDL is driven by these hydrophobic interactions than by specific protein-protein contacts. A lengthy Discussion section (lines 461-522) includes several chemically dubious or inconsistent statements, all based on the assumption that specific ApoA1 contacts are essential to NS1 association with HDL and that sNS1 oligomers higher than the dimer necessarily involve ApoA1 interaction, conclusions that are not established by the data in this paper.

Reply to u/Wooden-School-4091 at https://www.reddit.com/r/Zettelkasten/comments/17kui2u/analog_zettelkasten_for_natural_sciences/

Given that Carl Linnaeus "invented" the standardized 3x5 inch index card and used it heavily in his scientific work (read Isabelle Charmantier and Staffan Müller-Wille's works for more on his practice), and a variety of others including me, use it for mathematics, physics, chemistry, biology, etc., Zettelkasten can certainly be used for STEM, STEAM, and any of the natural sciences.

See also, notes and links at: https://hypothes.is/users/chrisaldrich?q=tag%3A%22zettelkasten+for+studying%22

If I were using it for classes/university/general studying via lectures, I'd base my practice primarily on Cornell Notes in combination with creating questions/cards for spaced repetition and/or a variation on Leitner's System.

Some of the best material on spaced repetition these days can be found via:

• Soren Bjornstad: https://controlaltbackspace.org/repeat/
• Piotr Wozniak: https://super-memory.com/articles/20rules.htm

and other material on their sites.

Beyond this, I'd focus my direct zettelkasten practice less on the learning portion and more on the developing or generating ideas portion of the work. Some of my practice with respect to mathematics can be found here: https://www.reddit.com/r/Zettelkasten/comments/17bqztm/applying_zettelkasten_for_math_heavy_subjects/

For those interested, it may bear mentioning that Bjornstad, an engineer at Remnote, has a TiddlyWiki-based zettelkasten at https://zettelkasten.sorenbjornstad.com/#PublicHomepage:PublicHomepage which he demonstrates with a walk through at https://www.youtube.com/watch?v=GjpjE5pMZMI

Author Response

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

We are very grateful to the reviewers for their thoughtful comments on the manuscript and to the editors for their assessment.

We thank the reviewers for their positive feedback and appreciate that they consider our method a valid addition to previously established systems for generating recombinant RNA viruses.

To strengthen this point, we have now included additional validation by the rescue of recombinant Chikungunya and Dengue virus from viral RNA directly, using the CLEVER protocol. This strengthens the potential of this method as a reverse genetics platform for positive-stranded viruses in general.

The supportive data has been amended in the Results section, taken into account in Materials and Methods, and the corresponding supplementary figure (Figure S4) has been added.

One key point raised by one of the reviewers, a comparison with different systems, could not be addressed in this manuscript as our lab does not at all perform BAC cloning. We currently do not have the necessary expertise to conduct an unbiased side-by-side comparison.

All other comments were addressed in detail, either by including additional data or through specific clarification in the revised text. We are grateful for the careful review and constructive criticisms raised by the reviewers and feel that the corrections and additions have significantly improved the manuscript.

We have revised the latest version posted May 30, 2023 on bioRxiv (https://doi.org/10.1101/2023.05.11.540343).

Reviewer #1:

Public Review:

In this manuscript, Kipfer et al describe a method for a fast and accurate SARS-CoV2 rescue and mutagenesis. This work is based on a published method termed ISA (infectious subgenomic amplicons), in which partially overlapping DNA fragments covering the entire viral genome and additional 5' and 3' sequences are transfected into mammalian cell lines. These DNA fragments recombine in the cells, express the full length viral genomic RNA and launch replication and rescue of infectious virus.

CLEVER, the method described here significantly improves on the ISA method to generate infectious SARS-CoV2, making it widely useful to the virology community.

Specifically, the strengths of this method are:

1) The successful use of various cell lines and transfection methods.

2) Generation of a four-fragment system, which significantly improves the method efficiency due to lower number of required recombination events.

3) Flexibility in choice of overlapping sequences, making this system more versatile.

4) The authors demonstrated how this system can be used to introduce point mutations as well as insertion of a tag and deletion of a viral gene.

5) Fast-tracking generation of infectious virus directly from RNA of clinical isolates by RT-PCR, without the need for cloning the fragments or using synthetic sequences.

One weakness of the latter point, which is also pointed out by the authors, is that the direct rescue of clinical isolates was not tested for sequence fidelity.

The manuscript clearly presents the findings, and the proof-of-concept experiments are well designed.

Overall, this is a very useful method for SARS-CoV2 research. Importantly, it can be applicable to many other viruses, speeding up the response to newly emerging viruses than threaten the public health.

We thank the reviewer for this positive feedback and the summary of the main points. Nevertheless, we would like to comment on point 5): “the direct rescue of clinical isolates was not tested for sequence fidelity”

This impression by the reviewer suggests that the data was not sufficient on this point. However, the sequence fidelity after direct rescue from RNA was indeed tested in this study, even on a clonal level (please see: Table S2, or raw NGS data SRX20303605 - SRX20303607). For higher clarity, we added the following sentence to the manuscript:<br /> “Indeed, a slight increase of unintentional mutations was observed when sequencing clonal virus populations rescued from RNA directly”.

Recommendations for the authors:

Minor Points:

1) On page 8, the authors write: "levels correlated very well with the viral phenotype". This sentence is not clear. Please clarify what you mean by "viral phenotype". Do you mean CPE on Vero cells?

We corrected the sentence to: “(…) staining intensity and patterns correlated very well with the wild-type phenotype.”

2) Page 9 "sequences were analyzed with a cut-off of 10%. Cutoff of what? please clarify.

The sentence was rephrased to: “(…)mutations with a relative abundance of >10% in the entire virus population were analyzed”

3) Page 15: The authors refer to the time required for completion of each step of the process. It would be helpful and informative for the readers to include a panel in figure 4, visualizing the timelines.

We included a timeline in Figure 4, Panel A.

4) Materials and methods, first paragraph: Please specify which human samples were collected. Do the authors refer to clinical virus isolates?

We added the following information to the Materials and Methods section:<br /> “Human serum samples for neutralization assays were collected from SARS-CoV-2 vaccinated anonymous donors (…)”

Clinical virus isolates (Material and Methods; Virus) were used for control experiments, neutralization assays, or as templates for RT-PCR.

5) Supplementary figure 4A: The color scheme makes it hard to differentiate between the BA.1 and BA.5 fragments. Please choose colors that are not as similar to each other.

Colors were adapted for better distinction.

Reviewer #2:

Public Review:

The authors of the manuscript have developed and used cloning-free method. It is not entirely novel (rather it is based on previously described ISA method) but it is clearly efficient and useful complementation to the already existing methods. One of strong points of the approach use by authors is that it is very versatile, i.e. can be used in combination with already existing methods and tools. I find it important as many laboratories have already established their favorite methods to manipulate SARS-CoV-2 genome and are probably unwilling to change their approach entirely. Though authors highlight the benefits of their method these are probably not absolute - other methods may be as efficient or as fast. Still, I find myself thinking that for certain purposes I would like to complement my current approach with elements from authors CLEVER method.

The work does not contain much novel biological data - which is expected for a paper dedicated to development of new method (or for improving the existing one). It may be kind of shortcoming as it is commonly expected that authors who have developed new methods apply it for discovery of something novel. The work stops on step of rescue the viruses and confirming their biological properties. This part is done very well and represents a strength of the study. The properties of rescued viruses were also studied using NSG methods that revealed high accuracy of the used method, which is very important as the method relies on use of PCR that is known to generate random mistakes and therefore not always method of choice.

What I found missing is a real head-to-head comparison of the developed system with an existing alternatives, preferably some PCR-free standard methods such as use of BAC clones. There are a lot of comparisons but they are not direct, just data from different studies has been compared. Authors could also be more opened to discuss limitations of the method. One of these seems to be rather low rescue efficiency - 1 rescue event per 11,000 transfected cells. This is much lower compared to infectious plasmid (about 1 event per 100 cells or so) and infectious RNAs (often 1 event per 10 cells, for smaller genomes most of transfected cells become infected). This makes the CLEVER method poorly suitable for generation of large infectious virus libraries and excludes its usage for studies of mutant viruses that harbor strongly attenuating mutations. Many of such mutations may reduce virus genome infectivity by 3-4 orders of magnitude; with current efficiencies the use of CLEVER approach may result in false conclusions (mutant viruses will be classified as non-viable while in reality they are just strongly attenuated).

We thank reviewer 2 for the careful review of our work and the valuable feedback. We agree that a direct comparison with other (PCR-free) methods such as BAC cloning, could be useful for demonstrating the unique benefits of the CLEVER method. However, as our laboratory does not use any BAC or YAC cloning methods, we could not ensure an unbiased side-byside comparison using different techniques.

We would like to highlight the avoidance of any yeast/bacterial cloning steps that render the CLEVER protocol significantly faster and easier to handle. A visualization of the key steps that could be skipped using CLEVER in comparison to common reverse genetics methods is given in Figure 6.

Further, we firmly believe that the benefits of the CLEVER method become especially apparent for large viral genomes such as the one of SARS-CoV-2, where assembly, genome amplification and sequence verification of plasmid DNA are highly inefficient and more timeconsuming than for small viruses like DENV, CHIKV or HIV.

We agree with the reviewer that the overall transfection and recombination efficiencies observed with CLEVER seemed rather low. Although data on transfection/rescue efficiency is known for many techniques and viruses, we did not find any published data on the reconstitution of SARS-CoV-2 or viruses with similar genome sizes. Therefore, a useful comparator for our observations in relation to other techniques is currently simply missing. We therefore emphasize that the efficiencies of CLEVER were achieved with one of the largest plus-stranded RNA virus genomes, and our data can’t be directly compared to transfection efficiencies of short infectious RNAs.

On the contrary, it was rather interesting to observe the very high rescue efficiency of infectious virus progeny. During the two years of establishing and validating the CLEVER protocol, we reached success rates for the genome reconstitution after transfection of >95 %. This was even obtained with highly attenuated mutants including rCoV2∆ORF3678 (joint deletion of ORF3a, ORF6, ORF7a, and ORF8) (Liu et al., 2022)(see Author response image 1). We amended this data in response to the reviewers’ comment and as an example of the successful rescue of an attenuated virus from five overlapping genome fragments (fragments A, B, C, D1, and D2∆ORF3678).

The latter data were not added to the main manuscript since in this case the deletions were introduced using a different method: from the plasmid-based DNA fragment D2∆ORF3678 and not directly from PCR-based mutagenesis.

Further, CLEVER was used for related substantial manipulations, including the complete deletion of the Envelope gene (E) which led to the creation of a single-cycle virus that may serve as a live, replication-incompetent vaccine candidate (Lett et al., 2023).

Author response image 1.

rCoV2∆ORF3678. Detection of intracellular SARS-CoV-2 nucleocapsid protein (N, green) and nuclei (Hoechst, blue) in Vero E6TMPRSS2 cells infected with rCoV2∆ORF3678 by immunocytochemistry. Scalebar is 200 µm in overview and 50 µm in ROI images.

Recommendations for the authors:

The work is nicely presented and the method authors has developed is clearly valuable. As indicated in Public review section the work would benefit from direct comparison of CLEVER with that of infectious plasmid (or RNA) based methods; direct comparison of data would be more convincing that indirect one. Authors should also discuss possible limitations of the method - this is helpful for a reader.

We were not able to perform a direct comparison of CLEVER with other methods (see our statement above).

We added the following section to the discussion: “Along with the advantages of the CLEVER protocol, limitations must be considered: Interestingly, virus was never rescued after transfecting Vero E6 cells, as has been observed previously (Mélade et al., 2022). Whether this is due to low transfection efficiency or the cell’s inability to recombine remains to be elucidated. Other cell lines not tested within this study will have to be tested for efficient recombination and virus production first. Further, the high sequence integrity of rescued virus is highly dependent on the fidelity of the DNA polymerase used for amplification. The use of other enzymes might negatively influence the sequence integrity of recombinant virus, as it has been observed for the direct rescue from viral RNA using a commercially available onestep RT-PCR kit. Another limitation when performing direct mutagenesis is the synthesis of long oligos to create an overlapping region. Repetitive sequences, for example, can impair synthesis, and self-annealing and hairpin formation increase with prolonged oligos.”

Some technical corrections of the text would be beneficial. In all past of the text the use of terms applicable only for DNA or RNA is mixed and creates some confusion. For example, authors state that "the human cytomegalovirus promoter (CMV) was cloned upstream of 5' UTR and poly(A) tail, the hepatitis delta ribozyme (HDVr) and the simian virus 40 polyadenylation signal downstream of the 3' UTR". Strictly speaking it is impossible as such a construct would contain dsDNA sequence (CMV promoter) followed by ssRNA (5'UTR, polyA tail and HDV ribozyme) and then again dsDNA (SV40 terminator). So, better to be correct and add "sequences corresponding to", "dsDNA copies of" to the description of RNA elements

We thank the reviewer for the advice but would like to state that in scientific language it is common to assume that nucleic acid cloning is based on DNA.

We have corrected the description in the Methods section: “The human cytomegalovirus promoter (CMV) was cloned upstream of the DNA sequence of the viral 5’UTR; herein, the first five nucleotides (ATATT) correspond to the 5’UTR of SARS-CoV. Sequences corresponding to the poly(A) tail (n=35), the hepatitis delta virus ribozyme (HDVr), and the simian virus 40 polyadenylation signal (SV40pA) were cloned immediately downstream of the DNA sequence of the viral 3’UTR.”

For ease of reading and for consistent terminology, we kept the original spelling in the rest of the manuscript.

In description of neutralization assay authors have used temperature 34 C for incubation of virus with antibodies as well as for subsequent incubation of infected cells. Why this temperature was used?

The following sentence was added (Materials and Methods; Cells): “A lower incubation temperature was chosen based on previous studies (V’kovski et al., 2021).”

References

Lett MJ, Otte F, Hauser D, Schön J, Kipfer ET, Hoffmann D, Halwe NJ, Ulrich L, Zhang Y, Cmiljanovic V, Wylezich C, Urda L, Lang C, Beer M, Mittelholzer C, Klimkait T. 2023. Single-cycle SARS-CoV-2 vaccine elicits high protection and sterilizing immunity in hamsters. doi:10.1101/2023.05.17.541127

Liu Y, Zhang X, Liu J, Xia H, Zou J, Muruato AE, Periasamy S, Kurhade C, Plante JA, Bopp NE, Kalveram B, Bukreyev A, Ren P, Wang T, Menachery VD, Plante KS, Xie X, Weaver SC, Shi P-Y. 2022. A live-attenuated SARS-CoV-2 vaccine candidate with accessory protein deletions. Nat Commun 13:4337. doi:10.1038/s41467-022-31930-z

V’kovski P, Gultom M, Kelly JN, Steiner S, Russeil J, Mangeat B, Cora E, Pezoldt J, Holwerda M, Kratzel A, Laloli L, Wider M, Portmann J, Tran T, Ebert N, Stalder H, Hartmann R, Gardeux V, Alpern D, Deplancke B, Thiel V, Dijkman R. 2021. Disparate temperaturedependent virus–host dynamics for SARS-CoV-2 and SARS-CoV in the human respiratory epithelium. PLoS Biol 19:e3001158. doi:10.1371/journal.pbio.3001158

Joint Public Review:

In this manuscript, Kipfer et al describe a method for a fast and accurate SARS-CoV2 rescue and mutagenesis. This work is based on a published method termed ISA (infectious subgenomic amplicons), in which partially overlapping DNA fragments covering the entire viral genome and additional 5' and 3' sequences are transfected into mammalian cell lines. These DNA fragments recombine in the cells, express the full length viral genomic RNA and launch replication and rescue of infectious virus.

CLEVER, the method described here significantly improves on the ISA method to generate infectious SARS-CoV2, making it widely useful to the virology community.

Specifically, the strengths of this method are:<br /> 1) The successful use of various cell lines and transfection methods.<br /> 2) Generation of a four-fragment system, which significantly improves the method efficiency due to lower number of required recombination events.<br /> 3) Flexibility in choice of overlapping sequences, making this system more versatile.<br /> 4) The authors demonstrated how this system can be used to introduce point mutations as well as insertion of a tag and deletion of a viral gene.<br /> 5) Fast-tracking generation of infectious virus directly from RNA of clinical isolates by RT-PCR, without the need for cloning the fragments or using synthetic sequences.<br /> 6) The authors further expanded this method to work on additional plus-strand RNA viruses beyond SARS-CoV-2 (CHIKV, DENV)

The manuscript clearly presents the findings, and the proof-of-concept experiments are well designed.

Overall, this is a very useful method for SARS-CoV2 research. Importantly, it can be applicable to many other viruses, speeding up the response to newly emerging viruses than threaten the public health.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, the authors have applied an asymmetric split mNeonGreen2 (mNG2) system to human iPSCs. Integrating a constitutively expressed long fragment of mNG2 at the AAVS1 locus, allows other proteins to be tagged through the use of available ssODN donors. This removes the need to generate long AAV donors for tagging, thus greatly facilitating high-throughput tagging efforts. The authors then demonstrate the feasibility of the method by successfully tagging 9 markers expressed in iPSC at various, and one expressed upon endoderm differentiation. Several additional differentiation markers were also successfully tagged but not subsequently tested for expression/visibility. As one might expect for high-throughput tagging, a few proteins, while successfully tagged at the genomic level, failed to be visible. Finally, to demonstrate the utility of the tagged cells, the authors isolated clones with genes relevant to cytokinesis tagged, and together with an AI to enhance signal-to-noise ratios, monitored their localization over cell division.

Strengths:<br /> Characterization of the mNG2 tagged parental iPSC line was well and carefully done including validation of a single integration, the presence of markers for continued pluripotency, selected off-target analysis, and G-banding-based structural rearrangement detection.

The ability to tag proteins with simple ssODNs in iPSC capable of multi-lineage differentiation will undoubtedly be useful for localization tracking and reporter line generation.

Validation of clone genotypes was carefully performed and highlights the continued need for caution with regard to editing outcomes.

Weaknesses:<br /> IF and flow cytometry figures lack quantification and information on replication. How consistent is the brightness and localization of the markers? How representative are the specific images? Stability is mentioned in the text but data on the stability of expression/brightness is not shown.

The localization of markers, while consistent with expectations, is not validated by a second technique such as antibody staining, and in many cases not even with Hoechst to show nuclear vs cytoplasmic.

For the multi-germ layer differentiation validation, NCAM is also expressed by ectoderm, so isn't a good solo marker for mesoderm as it was used. Indeed, the kit used for the differentiation suggests Brachyury combined with either NCAM or CXCR4, not NCAM alone.

Only a single female parental line has been generated and characterized. It would have been useful to have several lines and both male and female to allow sex differences to be explored.

The AI-based signal-to-noise enhancement needs more details and testing. Such models can introduce strong assumptions and thus artefacts into the resolved data. Was the model trained on all markers or were multiple models trained on a single marker each? For example, if trained to enhance a single marker (or co-localized group of markers), it could introduce artefacts where it forces signal localization to those areas even for others. What happens if you feed in images with scrambled pixel locations, does it still say the structures are where the training data says they should be? What about markers with different localization from the training set? If you feed those in, does it force them to the location expected by the training data or does it retain their differential true localization and simply enhance the signal?

Reviewer #3 (Public Review):

The authors report on the engineering of an induced Pluripotent Stem Cell (iPSC) line that harbours a single copy of a split mNeonGreen, mNG2(1-10). This cell line is subsequently used to take endogenous protein with a smaller part of mNeonGreen, mNG2(11), enabling the complementation of mNG into a fluorescent protein that is then used to visualize the protein. The parental cell is validated and used to construct several iPSC lines with endogenously tagged proteins. These are used to visualize and quantify endogenous protein localisation during mitosis.

I see the advantage of tagging endogenous loci with small fragments, but the complementation strategy has disadvantages that deserve some attention. One potential issue is the level of the mNG2(1-10). Is it clear that the current level is saturating? Based on the data in Figure S3, the expression levels and fluorescence intensity levels show a similar dose-dependency which is reassuring, but not definitive proof that all the mNG2(11)-tagged protein is detected.

Do the authors see a difference in fluorescence intensity for homo- and heterozygous cell lines that have the same protein tagged with mNG2(11)? One would expect two-fold differences, or not?

Related to this, would it be favourable to have a homozygous line for expressing mNG2(1-10)?

The complementation seems to work well for the proteins that are tested. Would this also work for secreted (or other organelle-resident) proteins, for which the mNG2(11) tag is localised in a membrane-enclosed compartment?

The authors present a technological advance and it would be great if others could benefit from this as well by having access to the cell lines.

eLife assessment

This study describes a method to track MHC class II binding peptides on dendritic cell (DC) surfaces using a tetracystein tag and a thiol-reactive dye, which can then be investigated in vitro and in vivo. This is a valuable study for the impact on immunology and potentially other areas where the detection of cell-associated peptides is required. The methods are convincing based on the use of MHC class I/II deficient mice that have significantly reduced signal, but the non-zero background is detected, and it is not clear that this is lower than if the peptides were directly labelled with fluorophores.

Reviewer #1 (Public Review):

Summary:<br /> The authors develop a method to fluorescently tag peptides loaded onto dendritic cells using a two-step method with a tetracystein motif modified peptide and labelling step done on the surface of live DC using a dye with high affinity for the added motif. The results are convincing in demonstrating in vitro and in vivo T cell activation and efficient label transfer to specific T cells in vivo. The label transfer technique will be useful to identify T cells that have recognised a DC presenting a specific peptide antigen to allow the isolation of the T cell and cloning of its TCR subunits, for example. It may also be useful as a general assay for in vitro or in vivo T-DC communication that can allow the detection of genetic or chemical modulators.

Strengths:<br /> The study includes both in vitro and in vivo analysis including flow cytometry and two-photon laser scanning microscopy. The results are convincing and the level of T cell labelling with the fluorescent pMHC is surprisingly robust and suggests that the approach is potentially revealing something about fundamental mechanisms beyond the state of the art.

Weaknesses:<br /> The method is demonstrated only at high pMHC density and it is not clear if it can operate at at lower peptide doses where T cells normally operate. However, this doesn't limit the utility of the method for applications where the peptide of interest is known. It's not clear to me how it could be used to de-orphan known TCR and this should be explained if they want to claim this as an application. Previous methods based on biotin-streptavidin and phycoerythrin had single pMHC sensitivity, but there were limitations to the PE-based probe so the use of organic dyes could offer advantages.

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Referee #3

Evidence, reproducibility and clarity

The study performed by Niphadkar et al. seeks to uncover the role of the phosphatase Ppg1 in regulating gluconeogenesis during post-diauxic shift in S. cerevisiae. Thea authors show that loss or inactivation of Ppg1p affects production of gluconeogenic products incl. trehaloase and glycogen. The authors show that assembly of the Far complex required the activity of Ppg1 and is required to maintain gluconeogenic outputs after glucose depletion.

The manuscript is clearly written and methods well considered, no omics-methods have been included. Especially phosphoproteomics would be relevant to include. Specifically, the tracing experiments are an interesting and appropriate approach to confirm effects on gluconeogeneisis etc. Yet, working with regulation of posttranslational modifications (phosporylations) it is surprising that the authors only to a limited extent examine phosphorylation events, and not all examine or discuss specific phosphorylation events of e.g. Far11.

The study is interesting and provides new insights into regulation of glucose metabolism in yeast, however, there are serious concerns that need to be addressed before it can be reconsidered for publication.

Major points:

The authors use electrophoretic mobility assays w/wo CIP to address the phosphorylation state of Far11. They show in figure 3E that the mobility of Far11 depends on Ppg1 activity and can be affected by CIP. Why is the mobility of Far11 not affected in e.g. figure 3D?

There are several sites in Far11 previously reported to be phosphorylated, see e.g. Bodenmiller et al 2010 (Science Signal.) Are there sites that are specifically regulated (dephosphorylated) by Ppg1? or by other phosphatases? kinases?

Here, it would be appropriate to apply phosphoproteomics to examine Far11 phosphorylation in Ppg1 knock out cells or in cells with inactivated Ppg1.

The authors show that the levels of Ppg1 remain constant during growth in YPD medium, while the levels of Far11 increased after 24hrs of growth in YPD medium, and thus argue that the amount of Far complex itself increases in post-diauxic phase. The authors need to show that the level of complex indeed increases.

The authors also apply fluorescence microscopy to address the localization of the Far11 complex etc. The quality of the shown images should be improved, also merged images should be shown. Only one single image containing one cell is shown, images should ideally show additional cells in the same image, alternatively, additional images should be shown.

Minor points:

Does the FLAG tag affect activity of Ppg1?

Significance

The study is interesting and provides new insights into regulation of glucose metabolism in yeast, however, there are serious concerns that need to be addressed before it can be reconsidered for publication.

The manuscript is of broad interests for an audience primarily interested glucose metabolism and signalling in yeast.

The name's that kids gave to their games back then were insane. Why was this such a fun game to play though? in Mexico tag was called* la roña * which was a name for chicken pox

Obsidian for Academic Publishing - A Walkthrough with Jason Yuh (6)

Jason menciona que su forma de investigación está hecha a partir de capítulos y no de ideas.

Anthony comenta sobre "serendipity": encontrar conexiones que no encontraría por sí mismo. No las encuentra buscando "serendipity connections", sino cuando está buscando otra cosa siguiendo links. Y de repente aparece, cuando está haciendo links con otras notas.

Jason usa tags como keywords. Pero eventualmente, cuando el concepto crece, hace una nota: ej. "Innovation".

Tiene secciones de:

• teoría y metodología -síntesis (con una lista de textos que ha leído, con sus respectivos links, así hace un poco un outline de su tesis) -To-Do (autores que necesita leer para el tema...).

Importante hacer esto, con mis notas de cada concepto. O quizás con una nota más extensa para trabajar en varios conceptos que se relacionan.

Obsidian for Academic Publishing - A Walkthrough with Jason Yuh (0)

Anthony's Desk

1:02:33

https://youtu.be/P3Hlo1DMdQQ

... which may have really happened, per se, but it didn't wholly incorporate (subsume/cannibalize) conventional desktop publishing, which is still in 2023 dominated by office suites (a la MS Word) or (perversely) browser-based facsimiles like Google Docs. Because the Web as it came to be used turned out to be as a sui generis medium, not exactly what TBL was aiming for, which was giving everything (everything—including every existing thing) its own URL.

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Referee #3

Evidence, reproducibility and clarity

This manuscript presents the cis-regulatory analysis of the enhancers controlling prox1a gene in zebrafish. Authors used both evolutionary conservation and existing single-cell ATAC data to highlight the major role of two elements. I feel that the transgenesis work is quite solid and the main conclusions interesting. However, I feel the authors need to provide some extra validations for some of the analysis.

1. the authors did not discuss the fact that euteleosts underwent an extra whole genome duplication and that prox1a might have a paralogue. They also perform genome alignment using non-duplicated outgroups (gar, xenopus) without discussing. I am a bit skeptical about the use of mVISTA on relatively short expert of sequence aroudn a gene, as it is not able to capture the global molecular evolution parameters. I think the authors should also examine some of the precomputed phastCons / phylocons data performed and available on UCSC to confirm their findings. probably they should also examien a few more fish genome. I don't find this evolutioanry analysis extremely convinced and careful - which doesn't mean that the conclusions are wrong.
2. I find the presentation, fairly obscure, the writing is quite convoluted, and the figures are very dense and not super explanatory, I would urge to improve (this is not helped by the fact that figure are their leged and presented at distinct places of this manuscript). For instance, I think having. a figure summarising signal from evolutionary conservation, scATAC and chromatin marks altogether would be quite essential.
3. I also find the reanalysis of the single-cell ATAC described too scarcely: which are the genes used to identify the different cell populations?
4. I feel the one additional experiment that the authors could have done would have been to use their construct to isolate the different cells population of interest and perform some regulatory profiling scuh as ATAC-seq or cut-and-tag on this population, to have a direct, in situ evidence of the activity of these regulatory elements.?

I also feel that the evolutionary aspect could be discussed a bit more, what are the differences between the diffeerent vertebrate lineage, etc...

(p7) active enhancer in a tissue: while ATAC gives a good indicated of accessibility it is not an indicate of activity as for instance H3K27Ac would be.

Significance

I think this is an interesting piece of work, which elaborates on previous studies on prox1a involvment in the lymphatic system but it doesn not bring essentially new perspective on the question.

DOI: 10.1101/2023.10.16.562573

Resource: SCR_022636

Curator: @scibot

SciCrunch record: RRID:SCR_022636

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What is this?

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Reply to the reviewers

[The “revision plan” should delineate the revisions that authors intend to carry out in response to the points raised by the referees. It also provides the authors with the opportunity to explain their view of the paper and of the referee reports.

1. General Statements [optional]

In this paper we describe the new finding that the epicardial deposits the extracellular matrix component laminin onto the apical ventricular surface during cardiac development. We identify a novel role for the apicobasal polarity protein Llgl1in timely emergence of the epicardium and deposition of this apical laminin, alongside a requirement for Llgl1 in maintaining integrity of the ventricular wall at the onset of trabeculation.

We thank the reviewers for their very positive appraisal of our manuscript, and for their helpful suggestions for useful revisions. In particular we would like to highlight the broad interest they feel this manuscript holds, not only contributing conceptual advances to our understanding of multiple aspects of cardiac development, but also to cell and developmental biologists working in epithelial polarity and extracellular matrix function. We also note their positive appraisal of the rigor of the study and quality of the manuscript.

2. Description of the planned revisions

Reviewer 1

1a) It is mentioned that llgl1 CRISPR/Cas9 mutants are viable as adults on pg. 3 of the Results section. Have the authors examined heart morphology in these mutants in juvenile or adult fish?

We have some historical data on adult llgl1 mutant survival that we plan to include in the study.

Reviewer 2

2a) The authors note an interesting observation with apical and basal laminin deposition dynamics surrounding cardiomyocytes, and that Llg1 has a role in apical Laminin deposition (however, highly variable at 80 hpf as Figure 3M shows). They carry out a very nice study in which they overexpress Llgl1 tagged with mCherry in the myocardium and show that there is no rescue of the extruding cardiomyocyte defect or Laminin deposition. However, there is still a possibility that the tagged Llgl1 in the transgene Tg(myl7:Llg1-mCherry)sh679 might not be functional due to improper protein folding or interference by the mCherry tag. The authors should supplement their approach with a transplantation experiment to generate mosaic llgl1 mutant animals and assess whether llgl1 mutant cardiomyocytes extrude at a higher rate than the control. This would provide definitive evidence that Llg1l acts in a cell non-autonomous manner.

We agree with the reviewer, and propose to perform transplant experiments, transplanting cells from llgl1 mutants into wild type siblings, and quantify cell extrusion to determine whether llgl1 mutant cells are extruded more frequently than wild type.

2b) The data in this manuscript appears to point that Llgl1 regulates Laminin deposition mainly in epicardial cells to regulate their dissemination/migration across the ventricular myocardial surface. It would be important to test this cell-autonomous function with the transplant experiment (above point) and examine whether llgl1 mutant epicardial cells fail to migrate and deposit Laminin. It might be possible to perform a rescue experiment through overexpression of Llgl1 in epicardial cells (if possible, there is a tcf21:Gal4 line available).

Similar to above, we propose to perform transplant experiments, transplanting cells from llgl1 mutants or wild type siblings into wild type siblings or llgl1 mutants, respectively, and in this instance quantify contribution of transplanted cells to epicardial coverage.

2c) In the Discussion, the authors propose that Llgl1 acts in two ways: Laminin deposition in epicardial cells that suppress cell extrusion and polarity regulation in cardiomyocytes to promote trabeculation. It would be important to test the second hypothesis on trabeculation and polarity regulation by using the myocardial-specific overexpression/rescue of Llgl1 in llgl1 mutants, and then quantifying the trabeculating cardiomyocytes and analyze Crb2a localization. This experiment can distinguish whether this trabeculation phenotype is rescued independently of the apical Laminin deposition that has been included in Figure S5.

To help address the second part of our hypothesis laid out in the discussion, we propose to quantify trabecular organisation and Crb2a localisation in llgl1 mutants either carrying the myl7:llgl1-mCherry construct, or mCherry-negative controls.

2d) The potential mis-localization of Crb2a in the llgl1 mutants is interesting, but this effect appears to be quite mild, and as the authors note, resolve by 80 hpf. Considering the role of Lgl in Drosophila in shifting Crb complex localization during early epithelial morphogenesis, it would be worth performing the analysis at earlier timepoints (between 55 and 72 hpf) to determine whether Llgl1 is indeed important for the progressive apical relocalization of Crb2a.

We will expand our description of this in the mutants by performing analysis of Crb2a at earlier timepoints in the llgl1 mutant (55hpf and 60hpf).

2e) OPTIONAL: It might be worth testing other antibodies that could mark the apical (particularly aPKC which is known to phosphorylate and regulate the Crb complex) and basolateral domains (Par1, Dlg) of the cardiomyocytes to definitively conclude that the epithelial integrity of the cells is affected. Although there are no reports of working antibodies marking the basal domain in zebrafish, there is at least a Tg(myl7:MARCK3A-RFP) line published (Jimenez-Amilburu et al. (2016)) - which the authors can inject to examine the localization in mosaic hearts.

We plan to assess localisation of aPKC (see section 4 for response to other suggested polarity protein analyses).

2f) Have the authors quantified the numbers of total cardiomyocytes in llgl1 mutants to correlate how many cells are lost as a consequence of extrusion? What is the physiological impact of this extrusion (ejection fraction, total cardiac volumes, sarcomere organization)?

We have some of this data already which we will include in the manuscript (cell number, myocardial volume). We agree that the analysis of cardiac function could be more extensive, and we will perform more detailed analysis of cardiac function, including e.g. ejection fraction. Sarcomere organisation has been previously described in llgl1 mutants by Flinn et al, 2020, so we do not plan to replicate this data.

2g) The lamb1a and lamc1 mutant phenotypes were nicely analyzed. However, there is basement membrane deposition on both the apical and basal sides of the cardiomyocytes. Therefore, it is unclear whether the cardiomyocyte extrusion is completely caused by loss of apical basement membrane, or whether the loss of basal basement membrane could compromise the myocardial tissue integrity. The authors should clarify this conclusion in the text.

We will address this further in the text, but will also include 55hpf Laminin staining data for llgl1 mutants to reinforce our message.

2h) The authors note that Llgl1-mCherry in the Tg(myl7:Llg1-mCherry)sh679 line localizes to the basolateral domain of the cardiomyocytes, which is valuable confirmation that Llgl1 protein is spatially restricted. However, only 1 timepoint (55 hpf) is noted. It would be important to perform Llgl1 localization across different developmental timepoints (at least until 80 hpf) to examine the dynamics of this protein during trabeculation and apical extrusion, and potentially correlate it with Crb2a localization for a better understanding of the apicobasal machinery in cardiomyocytes.

We already have some of this data and will include extra timepoints in a revised version of the manuscript

2i) The phenotypes of llgl1 mutants described here differ compared to the previous study by Flinn et al. (2020). In particular, whereas the mutants generated in this study have only mild pericardial edema and are adult viable, approximately one third of llgl1mw3 (Flinn et al. (2020)) died at 6 dpf. Is this caused by the different natures of the mutations in the llgl1 gene? Is there a possibility that the llgl1sh598 is a hypomorphic allele since the targeted deletion is in a more downstream sequence (in exon 2) compared to the llgl1mw3 (deletion in exon 1) allele?

We thank the reviewer for noticing these subtle differences between the two llgl1 mutants. Indeed, while we occasionally see llgl1sh598 mutants with the severe phenotype described by Flinn et al, this is a small minority which we did not quantify. Our mutation is indeed slightly further downstream than that described by Flinn et al, however we believe that this will have a neglible effect on Llgl1 function. Our llgl1sh589 mutation results in truncation shortly into the WD40 domain, and importantly completely lacks the Lgl-like domain, which is responsible for the specific function of Llgl1 likely through its ability to interact with SNAREs to regulate cargo delivery to membranes (Gangar et al, Current Biology 2005).

Interestingly, Flinn et al report no increased phenotypic severity in their maternal-zygotic llgl1 mutants when compared to zygotic mutants. Conversely, we often observed very severe phenotypes in MZ llgl1sh589 mutants, including failure of embryos during blastula stages, apparently through poor blastula integrity. We did not include this information in the manuscript due to space constraints. However, we argue that together these differences between the two alleles may not be due to hypomorphism of our llgl1sh589 allele, but rather differences in genetic background that may amplify specific phenotypes. We plan to include a short sentence summarising the above in combination with planned experiments described below to address the reviewer’s next comment.

2j) Suggested experiment: qPCR of regions downstream of the deletion to make sure that the transcript is absent/reduced in the llgl1sh598 mutants. Alternatively, immunostaining or Western blot would be an even better option to ensure there is no Llgl1 protein production - there is an anti-Llgl1 antibody available that works for Western blots in zebrafish (Clark et al. (2012)).

We plan to analyse llgl1 expression in llgl1 mutants using qPCR.

Reviewer 3

3a) Major - the authors describe that llgl1 mutants exhibit transient cardiac edema at 3 dpf, which is resolved by 5 dpf, and claim that the mutants are viable. This statement needs to be better supported - What is the proportion of mutants that survive to adulthood? The embryonic phenotypes are pretty variable - are the mutants that survive the ones with a less severe phenotype? Is there a gross defect in the adult heart of these animals?

In line with comments from Reviewers 1 and 2 above, we will include a description of the data we have from adult animals (historical data, not generation of new animals).

3b) Major - Many of the phenotypes described here -most importantly, the defects on epicardial development- could result from hemodynamic defects in llgl1 mutants. The authors claim that function is unaffected in these animals, but this has only been addressed by measuring heartbeat. The observation that the cardiac function in these animals is normal would conflict with a previous description (PMID: 32843528) that demonstrates that llgl1 mutant animals show significant hemodynamic defects, which would cause epicardial defects. Thus, this aspect of the work needs to be better addressed.

In line with our comments to point 2f) from Reviewer 2, we will perform a more in-depth functional analysis on llgl1 mutant larvae.

3c) The phenotypes related to forming multiple layers in the heart (Fig. 1) could be more convincing. In some figures, the authors use a reporter that labels the myocardial cell membrane, but in Figure 1 this is not used. Showing a myocardial membrane marker (for example, the antibody Alcama, Zn-8) would significantly strengthen this observation.

We will describe trabecular phenotypes in more detail using the suggested antibody to highlight membranes.

3d) The analysis of Crumbs redistribution (Fig. 2) is quite interesting. Still, given that the authors have a transgenic model to rescue llgl1 expression in cardiomyocytes, they could move from correlative evidence to experimental demonstration of the role of llgl1 in Crumbs localization.

Similar to our response to comment 2c) from Reviewer 2, we plan to address this

3. Description of the revisions that have already been incorporated in the transferred manuscript

Reviewer 1:

Although information is provided in the introduction and discussion on the role of the Llgl1 homolog in Drosophila and speculation on LLGL1 contributing to heart defects in SMS patients in the discussion, have Llgl1 homologs been examined in other vertebrate animal models during heart development or regeneration?

With the exception of the Flinn et al paper, we find no published studies assessing the role of Llgl1 in heart development or regeneration in other vertebrates, and have updated the introduction to highlight this fact:

‘Zebrafish have two Lgl homologues, llgl1 and llgl2, and llgl1 has previously been shown to be required for early stages of heart morphogenesis (Flinn et al. 2020). However, although Llgl1 expression has also been reported in the developing mouse heart and both adult mouse and human hearts (Uhlén et al. 2015; Klezovitch et al. 2004), whether llgl1 plays a role in ventricular wall development has not been examined.’

In Fig. 4J-M', there is no Cav1 signals after wt1a MO but still laminin signals. Where these laminins come from?

The residual laminin staining observed in wt1a morphants is located at the basal surface of cardiomyocytes (while the apical laminin signal is lost, in line with the epicardial deposition of laminin at the apical ventricle surface). This basal laminin is likely deposited earlier during heart tube development by either the myocardium, endocardium or both, and thus unaffected by later formation of the epicardium. We reason this since a) it is present at the basal cardiomyocyte surface at 55hpf (see Fig 2); b) we have previously identified both myocardial and endocardial expression of laminin subunits at 26hpf and 55hpf (Derrick et al, Development, 2021); c) sc-RNA-seq analysis of hearts at 48hpf demonstrates that laminin subunits, e.g. lamc1 are expressed in myocardial and endocardial cells (Nahia et al, bioRxiv, 2023), also in line with our previous ISH analysis. We have included a sentence to reflect this in the results section:

Conversely, *wt1a* morphants retain deposition of laminin at the basal CM surface, likely from earlier expression and deposition of laminin by either myocardial or endocardial cells (Derrick et al. 2021; Nahia et al. 2023), which is unaffected by later epicardial development.

On page 3 of the manuscript, Fig. 1A should be included with Fig. 1B in the first sentence of paragraph 2 of the Results subsection "Llgl1 regulates ventricular wall integrity and trabeculation".

Amended

It would be beneficial to readers to briefly describe what cell type the transgenic reporters label when mentioned in the Results section to help readers unfamiliar with zebrafish.

We have updated the text to read:

We further analysed heart morphology using live lightsheet microscopy of *Tg(myl7:LifeActGFP);Tg(fli1a:AC-TagRFP)* double transgenic wild-type and *llgl1* mutant embryos, allowing visualisation of myocardium (green) and endocardium (magenta) respectively. Comparative analysis of overall heart morphology between 55hpf and 120hpf when looping morphogenesis is complete, revealing that *llgl1* mutants continue to exhibit defects in heart morphogenesis (Fig S1S-X).

Reviewer 3

(Optional) There is laminin in the luminal side of the heart before there is any epicardial invasion. What is the source of this laminin? The techniques the authors have used (i.e., chromogenic ISH) are fine, but a more detailed analysis using fluorescent ISH (i.e., RNAScope) would be much more definitive.

This is related to our response to Reviewer 1 (above) – where we have included the following text included in manuscript: Conversely, *wt1a* morphants retain deposition of laminin at the basal CM surface, likely from earlier expression and deposition of laminin by either myocardial or endocardial cells (Derrick et al. 2021; Nahia et al. 2023), which is unaffected by later epicardial development. We hope this clarifies our proposed origins for the earlier laminin deposition.

4. Description of analyses that authors prefer not to carry out

Reviewer 1:

As pan-epicardial transgenes like tcf21 reporters have been widely used, the authors should use such reporters to verify the expression of laminin gene expression in epicardial cells, and the efficacy and efficiency of depleting epicardial cells after wt1 MO injection.

Several studies have demonstrated that the epicardium is not a heterogeneous population – for example, tcf21 is not expressed in all epicardial cells and thus not a pan-epicardial reporter (Plavicki et al, BMC Dev Biol, 2014, Weinberger et al, Dev Cell, 2020) – the suggested analysis would not necessarily be conclusive, and more detailed study would require acquisition of three new transgenic lines. Furthermore, we believe the evidence we present in the paper supports our claim: 1) We show expression of two laminin subunits in a thin mesothelial layer directly adjacent to the myocardium, specifically in the location of the epicardium; 2) sc-RNA seq analyses have also identified laminin expression in epicardial cells at 72hpf (where lamc1a is identified as a marker of the epicardium); 3) We demonstrate 100% efficacy of our wt1a knockdown as assayed by Cav1 expression, an established epicardial marker (Grivas et al, 2020, Marques et al, 2022) which in sc-RNA seq data is expressed at high levels broadly in the epicardial cell population (Nahia et al, 2023), representing a good assay for presence of epicardium. However, we propose to perform ISH analysis of laminin subunit expression in wt1a MO to investigate whether the mesothelial laminin-expressing layer we observe adjacent to the myocardium is absent upon loss of wt1a.

Reviewer 2:

The data in this manuscript appears to point that Llgl1 regulates Laminin deposition mainly in epicardial cells to regulate their dissemination/migration across the ventricular myocardial surface. It would be important to test this cell-autonomous function with the transplant experiment (above point) and examine whether llgl1 mutant epicardial cells fail to migrate and deposit Laminin. It might be possible to perform a rescue experiment through overexpression of Llgl1 in epicardial cells (if possible, there is a tcf21:Gal4 line available).

We do not propose to perform this experiment using a tcf21:Gal4 line, as this would likely require at least 6 months to either import and quarantine, or generate the necessary stable lines. Furthermore, as mentioned above, tcf21 is not a pan-epicardial marker, and the extent and timing of the Gal4:UAS system may make this challenging to determine whether llgl1 has been expressed early or broadly enough. We will instead attempt transplantation experiments.

OPTIONAL: It might be worth testing other antibodies that could mark the apical (particularly aPKC which is known to phosphorylate and regulate the Crb complex) and basolateral domains (Par1, Dlg) of the cardiomyocytes to definitively conclude that the epithelial integrity of the cells is affected. Although there are no reports of working antibodies marking the basal domain in zebrafish, there is at least a Tg(myl7:MARCK3A-RFP) line published (Jimenez-Amilburu et al. (2016)) - which the authors can inject to examine the localization in mosaic hearts.

We will assess localisation of aPKC, but we do not plan to analyse the other components. Analysis of basolateral domains (Par1, Dlg, Mark3a-RGP), will not necessarily assess epithelial integrity, as suggested, but rather apicobasal polarity – which we already assess using Crb2a, and additionally plan to assess aPKC to accompany the Crb2a analysis. Since the reviewer suggests this as an optional experiment we prioritise their other suggested experiments that we think more directly address the main messages of the manuscript.

OPTIONAL: Gentile et al. (2021) found that reducing heartbeat led to decreased cardiomyocyte extrusion in snai1b mutants. The authors could look into the contribution of mechanical pressure through contraction in the apical cardiomyocyte extrusion, and test whether reducing contraction (tnnt2 morpholino, chemical treatments) partly rescues the llgl1 mutant phenotypes.

The relationship between cardiac function and myocardial wall integrity appears to be complex. The paper referred to by the reviewer indeed finds that reduction in heartbeat leads to decreased CM extrusion upon loss of the EMT-factor Snai1b. Previous studies have also found that endothelial flow-responsive genes klf2a/b are required to maintain myocardial ventricular wall integrity at later stages in a contractility-dependent manner (Rasouli et al, 2018). However, contractility is also required early for pro-epicardial emergence, but plays a lesser role in expansion of the epicardial layer on the myocardial surface (Peralta, 2013). Unpicking the relationship between the forces induced by mechanical contraction of the ventricular wall, contractility-based induction of e.g klf2 expression, and the impact of contractile forces on proepicardial development or epicardial expansion will be complex. We therefore think the proposed experiment will be difficult to interpret whatever the outcome, and argue that dissecting this relationship is beyond the scope of revisions for this paper.

Reviewer 3

How llgl1 relates to epicardial biology is left entirely unexplored in this work. Do proepicardial cells show any defect in cell polarization related to llgl1 absence?

We agree with the reviewer that we do not delve into the mechanisms underlying regulation of epicardial development by llgl1, and that this is an interesting question. Our scope for this manuscript was to understand the mechanisms by which llgl1 regulates integrity of the ventricular wall, and feel that uncovering the molecular mechanisms by which llgl1 regulates timely epicardial emergence is a larger question that would require substantial investigation (for example, if and when llgl1 PE cells do exhibit apicobasal defects, how this impacts timing of cluster release etc). We think these are important questions that would be better answered in detail in a separate manuscript.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #2

Evidence, reproducibility and clarity

Summary: The manuscript by Pollitt et al. explores the functions of llgl1, which encodes a critical component of the basolateral domain complex, during cardiac development in zebrafish. The authors observed that llgl1 mutants exhibited compromised myocardial tissue integrity with significantly higher numbers of apically extruding cardiomyocytes. Llgl1 appears to primarily function during epicardial cell spreading on the myocardial tissue, as myocardial-specific overexpression of llgl1 did not rescue llgl1 mutant phenotypes. llgl1 mutants exhibited impaired epicardial coverage and subsequently Laminin deposition on the apical side of the cardiomyocytes. Functional linkage between Laminin/the basement membrane was identified, as extruding cardiomyocytes were also observed in mutants of two core laminin genes, lamb1a and lamc1. The epicardial defects were transmitted to myocardial tissue defects, marked by mis-localization of the apical polarity protein Crumbs2a during early heart development. Overall, the authors provide a nice study that strengthens the role of apicobasal factors in myocardial tissue morphogenesis and that sheds light on the role of epicardial-derived basement membrane in maintaining myocardial tissue integrity.

Major comments

• The authors note an interesting observation with apical and basal laminin deposition dynamics surrounding cardiomyocytes, and that Llg1 has a role in apical Laminin deposition (however, highly variable at 80 hpf as Figure 3M shows). They carry out a very nice study in which they overexpress Llgl1 tagged with mCherry in the myocardium and show that there is no rescue of the extruding cardiomyocyte defect or Laminin deposition. However, there is still a possibility that the tagged Llgl1 in the transgene Tg(myl7:Llg1-mCherry)sh679 might not be functional due to improper protein folding or interference by the mCherry tag. The authors should supplement their approach with a transplantation experiment to generate mosaic llgl1 mutant animals and assess whether llgl1 mutant cardiomyocytes extrude at a higher rate than the control. This would provide definitive evidence that Llg1l acts in a cell non-autonomous manner.
• The data in this manuscript appears to point that Llgl1 regulates Laminin deposition mainly in epicardial cells to regulate their dissemination/migration across the ventricular myocardial surface. It would be important to test this cell-autonomous function with the transplant experiment (above point) and examine whether llgl1 mutant epicardial cells fail to migrate and deposit Laminin. It might be possible to perform a rescue experiment through overexpression of Llgl1 in epicardial cells (if possible, there is a tcf21:Gal4 line available).
• In the Discussion, the authors propose that Llgl1 acts in two ways: Laminin deposition in epicardial cells that suppress cell extrusion and polarity regulation in cardiomyocytes to promote trabeculation. It would be important to test the second hypothesis on trabeculation and polarity regulation by using the myocardial-specific overexpression/rescue of Llgl1 in llgl1 mutants, and then quantifying the trabeculating cardiomyocytes and analyze Crb2a localization. This experiment can distinguish whether this trabeculation phenotype is rescued independently of the apical Laminin deposition that has been included in Figure S5.
• The potential mis-localization of Crb2a in the llgl1 mutants is interesting, but this effect appears to be quite mild, and as the authors note, resolve by 80 hpf. Considering the role of Lgl in Drosophila in shifting Crb complex localization during early epithelial morphogenesis, it would be worth performing the analysis at earlier timepoints (between 55 and 72 hpf) to determine whether Llgl1 is indeed important for the progressive apical relocalization of Crb2a. OPTIONAL: It might be worth testing other antibodies that could mark the apical (particularly aPKC which is known to phosphorylate and regulate the Crb complex) and basolateral domains (Par1, Dlg) of the cardiomyocytes to definitively conclude that the epithelial integrity of the cells is affected. Although there are no reports of working antibodies marking the basal domain in zebrafish, there is at least a Tg(myl7:MARCK3A-RFP) line published (Jimenez-Amilburu et al. (2016)) - which the authors can inject to examine the localization in mosaic hearts.
• Have the authors quantified the numbers of total cardiomyocytes in llgl1 mutants to correlate how many cells are lost as a consequence of extrusion? What is the physiological impact of this extrusion (ejection fraction, total cardiac volumes, sarcomere organization)?
• The lamb1a and lamc1 mutant phenotypes were nicely analyzed. However, there is basement membrane deposition on both the apical and basal sides of the cardiomyocytes. Therefore, it is unclear whether the cardiomyocyte extrusion is completely caused by loss of apical basement membrane, or whether the loss of basal basement membrane could compromise the myocardial tissue integrity. The authors should clarify this conclusion in the text.

Minor comments

• The authors note that Llgl1-mCherry in the Tg(myl7:Llg1-mCherry)sh679 line localizes to the basolateral domain of the cardiomyocytes, which is valuable confirmation that Llgl1 protein is spatially restricted. However, only 1 timepoint (55 hpf) is noted. It would be important to perform Llgl1 localization across different developmental timepoints (at least until 80 hpf) to examine the dynamics of this protein during trabeculation and apical extrusion, and potentially correlate it with Crb2a localization for a better understanding of the apicobasal machinery in cardiomyocytes.
• The phenotypes of llgl1 mutants described here differ compared to the previous study by Flinn et al. (2020). In particular, whereas the mutants generated in this study have only mild pericardial edema and are adult viable, approximately one third of llgl1mw3 (Flinn et al. (2020)) died at 6 dpf. Is this caused by the different natures of the mutations in the llgl1 gene? Is there a possibility that the llgl1sh598 is a hypomorphic allele since the targeted deletion is in a more downstream sequence (in exon 2) compared to the llgl1mw3 (deletion in exon 1) allele? Suggested experiment: qPCR of regions downstream of the deletion to make sure that the transcript is absent/reduced in the llgl1sh598 mutants. Alternatively, immunostaining or Western blot would be an even better option to ensure there is no Llgl1 protein production - there is an anti-Llgl1 antibody available that works for Western blots in zebrafish (Clark et al. (2012)).
• Closeups needed for Figure 3I-L' - difficult to assess mis-localization or differences in Laminin staining. Contrary to the quantification or conclusion, the Laminin staining appears stronger in llgl1 mutants compared to wild types in Figure 3I' and J'.
• OPTIONAL: Gentile et al. (2021) found that reducing heartbeat led to decreased cardiomyocyte extrusion in snai1b mutants. The authors could look into the contribution of mechanical pressure through contraction in the apical cardiomyocyte extrusion, and test whether reducing contraction (tnnt2 morpholino, chemical treatments) partly rescues the llgl1 mutant phenotypes.

Significance

As someone with expertise in cardiac development and cellular behaviours, I find this study provides strong and convincing quantitative data on the role of Llgl1 in suppressing cardiomyocyte extrusion and promoting epicardial dissemination on the ventricular surface. The genetic experiments, including mutant analysis and myocardial-specific rescue, were carefully performed in a region-specific manner, which provides much insight into the non-uniformity of myocardial tissue integrity. The generation of Tg(myl7:llgl1-mCherry) line is also a valuable tool for researchers in the field interested in understanding apicobasal polarity and cardiomyocyte development and regeneration.

A limitation of the study is the unclear link between epithelial polarity and basement membrane deposition, and how they synchronize to regulate cardiomyocyte integrity. The llgl1 mutant phenotype in increasing cardiomyocyte apical extrusion and Crb2 localization is interesting; however, the authors note that this appears to be a phenotype induced by epicardial defects. Epicardial cells are not known to exhibit apicobasal polarity and are fibroblastic by nature. Thus, the cellular mechanisms by which Llg1 regulates epicardial cell morphology or behaviours, and how it functions to regulate polarity in cardiomyocytes are not clearly defined in this work. In addition, clarification of the cell autonomous functions of Llgl1 in epicardial cells and/or cardiomyocytes would strengthen the findings.

Overall, the findings of this study would be of interest to cell and developmental biologists in the fields of epithelial polarity, cardiac morphogenesis, and extracellular matrix function. It provides nice conceptual advance in further elucidating the mechanisms that underlie myocardial tissue integrity and epicardial-myocardial interactions.

lustig. schon bald (diesen winter? nächsten winter?) wird die mehrheit verhungern und erfrieren,<br /> und die sogenannte "opposition" beschäftigt sich mit kleinscheiss.

wir brauchen viel mehr extremismus und viel mehr radikale lösungen (selbstversorgung...),<br /> und nicht diese schwule weichgespülte "wir sind was besseres" gelaber.

die AFD hat jeden tag angst vor parteiverbot,<br /> also werden so "radikale typen" wie ich von anfang an rausselektiert.

dabei sollten so "radikale typen" wie ich eine blutige revolution (einen militärputsch) führen,<br /> und die ganzen versager und verräter vom alten system an die wand stellen.

aber auf revolution habt ihr gar keine lust, ihr wollt auch nur reformen, und noch mehr gesetze,<br /> aber es gibt keine politische lösung, weil das system ist radikal falsch, also nicht reformierbar.

deswegen, für mich sind graue wölfe 1000 mal interessanter als die AFD.<br /> ich bin sowieso kein christ oder jude, aber auch kein moslem.<br /> einfach nur pragmatisch, ein echter "wissenschaftler", einer der wissen schafft.

"Their evil designs run against nature." -- Kevin Alfred Strom

(ich freu mich schon auf den prozess wegen "gefühlsverletzung", ich lach mich tot...)

Der Sturm Otis, der die Küste bei Acapulco verwüstet hat, hat sich in nur einem Tag von einem tropischen Sturm zu einem Hurrikan der Kategorie 5 entwickelt. Es ist noch unklar worauf dieser enorme Gewinn an Intensität zurückgeht. https://www.nytimes.com/2023/10/25/world/americas/hurricane-otis-mexico-intensity-surprise.html

There's nothing special about Web Components; the author could have just as easily put the script block itself there.

Die Internationale Energieagentur IEA hält eine Begrenzung der globalen Erhitzung aufgrund des schnellen Wachstums bei den erneuerbaren Energien für sehr schwierig, aber noch möglich. In ihrem Jahresbericht kommt sie zu dem Ergebnis, dass der Höhepunkt der Nachfrage nach Kohle, Gas und Öl bis 2030 erreicht werden wird. Die Energiepolitik der wichtigen Staaten ist aber bei der Umstellung auf Erneuerbare bei weitem nicht so ehrgeizig, als es nötig ist. https://www.liberation.fr/environnement/grace-aux-energies-bas-carbone-limiter-le-rechauffement-climatique-reste-possible-affirme-lagence-internationale-de-lenergie-20231024_YF7ZJA7WBFACRFIVCBRONJPKAA/

World Energy Outlook 2023: https://origin.iea.org/reports/world-energy-outlook-2023

Mehr zum World Energy Outlook 2023: https://hypothes.is/search?q=tag%3A%22report%3A%20World%20Energy%20Outlook%202023%22

Durch die Verschiebung des Verbots neuer Benzin- und Dieselautos bleibt Großbritannien hinter seinen Selbstverpflichtungrn bei der Dekarbonisierung zurück. Der Guardian berichtet anlässlich des neuen IEA-Beichts über wachsenden Druck auf Rishi Sunak und gibt dabei einen Überblick über die nötigen Investitionen in Erneuerbare. https://www.theguardian.com/business/2023/oct/24/sunak-faces-further-pressure-over-net-zero-u-turn-iea-warning-energy-watchdog

Mehr zum World Energy Outlook 2023: https://hypothes.is/search?q=tag%3A%22report%3A%20World%20Energy%20Outlook%202023%22

Der Standardbericht zu dem neuen State of the climate-Report konzentriert sich auf die Forderung nach sofortigen Veränderungen in der Wirtschaft. Er enthält auch eine Übersicht zu den Temperaturanomalien in Österreich in diesem Jahr. https://www.derstandard.at/story/3000000192443/hoechsttemperaturen-wie-2023-gab-es-womoeglich-erstmals-seit-100000-jahren

Mehr zum State of the climate 2023-Report: https://hypothes.is/search?q=tag%3A%22report%3A%202023%20state%20of%20the%20climate%22;

Author Response

eLife assessment

This study presents potentially valuable results on glutamine-rich motifs in relation to protein expression and alternative genetic codes. The author's interpretation of the results is so far only supported by incomplete evidence, due to a lack of acknowledgment of alternative explanations, missing controls and statistical analysis and writing unclear to non experts in the field. These shortcomings could be at least partially overcome by additional experiments, thorough rewriting, or both.

We thank both the Reviewing Editor and Senior Editor for handling this manuscript and will submit our revised manuscript after the reviewed preprint is published by eLife.  

Reviewer #1 (Public Review):

Summary

This work contains 3 sections. The first section describes how protein domains with SQ motifs can increase the abundance of a lacZ reporter in yeast. The authors call this phenomenon autonomous protein expression-enhancing activity, and this finding is well supported. The authors show evidence that this increase in protein abundance and enzymatic activity is not due to changes in plasmid copy number or mRNA abundance, and that this phenomenon is not affected by mutants in translational quality control. It was not completely clear whether the increased protein abundance is due to increased translation or to increased protein stability.

In section 2, the authors performed mutagenesis of three N-terminal domains to study how protein sequence changes protein stability and enzymatic activity of the fusions. These data are very interesting, but this section needs more interpretation. It is not clear if the effect is due to the number of S/T/Q/N amino acids or due to the number of phosphorylation sites.

In section 3, the authors undertake an extensive computational analysis of amino acid runs in 27 species. Many aspects of this section are fascinating to an expert reader. They identify regions with poly-X tracks. These data were not normalized correctly: I think that a null expectation for how often poly-X track occur should be built for each species based on the underlying prevalence of amino acids in that species. As a result, I believe that the claim is not well supported by the data.

Strengths

This work is about an interesting topic and contains stimulating bioinformatics analysis. The first two sections, where the authors investigate how S/T/Q/N abundance modulates protein expression level, is well supported by the data. The bioinformatics analysis of Q abundance in ciliate proteomes is fascinating. There are some ciliates that have repurposed stop codons to code for Q. The authors find that in these proteomes, Q-runs are greatly expanded. They offer interesting speculations on how this expansion might impact protein function.

Weakness

At this time, the manuscript is disorganized and difficult to read. An expert in the field, who will not be distracted by the disorganization, will find some very interesting results included. In particular, the order of the introduction does not match the rest of the paper.

In the first and second sections, where the authors investigate how S/T/Q/N abundance modulates protein expression levels, it is unclear if the effect is due to the number of phosphorylation sites or the number of S/T/Q/N residues.

There are three reasons why the number of phosphorylation sites in the Q-rich motifs is not relevant to their autonomous protein expression-enhancing (PEE) activities:

First, we have reported previously that phosphorylation-defective Rad51-NTD (Rad51-3SA) and wild-type Rad51-NTD exhibit similar autonomous PEE activity. Mec1/Tel1-dependent phosphorylation of Rad51-NTD antagonizes the proteasomal degradation pathway, increasing the half-life of Rad51 from ∼30 min to ≥180 min (Ref 27; Woo, T. T. et al. 2020).

1. T. T. Woo, C. N. Chuang, M. Higashide, A. Shinohara, T. F. Wang, Dual roles of yeast Rad51 N-terminal domain in repairing DNA double-strand breaks. Nucleic Acids Res 48, 8474-8489 (2020).

Second, in our preprint manuscript, we have also shown that phosphorylation-defective Rad53-SCD1 (Rad51-SCD1-5STA) also exhibits autonomous PEE activity similar to that of wild-type Rad53-SCD (Figure 2D, Figure 4A and Figure 4C).

Third, as revealed by the results of our preprint manuscript (Figure 4), it is the percentages, and not the numbers, of S/T/Q/N residues that are correlated with the PEE activities of Q-rich motifs.

The authors also do not discuss if the N-end rule for protein stability applies to the lacZ reporter or the fusion proteins.

The autonomous PEE function of S/T/Q-rich NTDs is unlikely to be relevant to the N-end rule. The N-end rule links the in vivo half-life of a protein to the identity of its N-terminal residues. In S. cerevisiae, the N-end rule operates as part of the ubiquitin system and comprises two pathways. First, the Arg/N-end rule pathway, involving a single N-terminal amidohydrolase Nta1, mediates deamidation of N-terminal asparagine (N) and glutamine (Q) into aspartate (D) and glutamate (E), which in turn are arginylated by a single Ate1 R-transferase, generating the Arg/N degron. N-terminal R and other primary degrons are recognized by a single N-recognin Ubr1 in concert with ubiquitin-conjugating Ubc2/Rad6. Ubr1 can also recognize several other N-terminal residues, including lysine (K), histidine (H), phenylalanine (F), tryptophan (W), leucine (L) and isoleucine (I) (Bachmair, A. et al. 1986; Tasaki, T. et al. 2012; Varshavshy, A. et al. 2019). Second, the Ac/N-end rule pathway targets proteins containing N-terminally acetylated (Ac) residues. Prior to acetylation, the first amino acid methionine (M) is catalytically removed by Met-aminopeptides, unless a residue at position 2 is non-permissive (too large) for MetAPs. If a retained N-terminal M or otherwise a valine (V), cysteine (C), alanine (A), serine (S) or threonine (T) residue is followed by residues that allow N-terminal acetylation, the proteins containing these AcN degrons are targeted for ubiquitylation and proteasome-mediated degradation by the Doa10 E3 ligase (Hwang, C. S., 2019).

A. Bachmair, D. Finley, A. Varshavsky, In vivo half-life of a protein is a function of its amino-terminal residue. Science 234, 179-186 (1986).

T. Tasaki, S. M. Sriram, K. S. Park, Y. T. Kwon, The N-end rule pathway. Annu Rev Biochem 81, 261-289 (2012).

A. Varshavsky, N-degron and C-degron pathways of protein degradation. Proc Natl Acad Sci 116, 358-366 (2019).

C. S. Hwang, A. Shemorry, D. Auerbach, A. Varshavsky, The N-end rule pathway is mediated by a complex of the RING-type Ubr1 and HECT-type Ufd4 ubiquitin ligases. Nat Cell Biol 12, 1177-1185 (2010).

The PEE activities of these S/T/Q-rich domains are unlikely to arise from counteracting the N-end rule for two reasons. First, the first two amino acid residues of Rad51-NTD, Hop1-SCD, Rad53-SCD1, Sup35-PND, Rad51-ΔN, and LacZ-NVH are MS, ME, ME, MS, ME, and MI, respectively, where M is methionine, S is serine, E is glutamic acid and I is isoleucine. Second, Sml1-NTD behaves similarly to these N-terminal fusion tags, despite its methionine and glutamine (MQ) amino acid signature at the N-terminus.

The most interesting part of the paper is an exploration of S/T/Q/N-rich regions and other repetitive AA runs in 27 proteomes, particularly ciliates. However, this analysis is missing a critical control that makes it nearly impossible to evaluate the importance of the findings. The authors find the abundance of different amino acid runs in various proteomes. They also report the background abundance of each amino acid. They do not use this background abundance to normalize the runs of amino acids to create a null expectation from each proteome. For example, it has been clear for some time (Ruff, 2017; Ruff et al., 2016) that Drosophila contains a very high background of Q's in the proteome and it is necessary to control for this background abundance when finding runs of Q's.

We apologize for not explaining sufficiently well the topic eliciting this reviewer’s concern in our preprint manuscript. In the second paragraph of page 14, we cite six references to highlight that SCDs are overrepresented in yeast and human proteins involved in several biological processes (32, 74), and that polyX prevalence differs among species (43, 75-77).

1. Cheung HC, San Lucas FA, Hicks S, Chang K, Bertuch AA, Ribes-Zamora A. An S/T-Q cluster domain census unveils new putative targets under Tel1/Mec1 control. BMC Genomics. 2012;13:664.

2. Mier P, Elena-Real C, Urbanek A, Bernado P, Andrade-Navarro MA. The importance of definitions in the study of polyQ regions: A tale of thresholds, impurities and sequence context. Comput Struct Biotechnol J. 2020;18:306-13.

3. Cara L, Baitemirova M, Follis J, Larios-Sanz M, Ribes-Zamora A. The ATM- and ATR-related SCD domain is over-represented in proteins involved in nervous system development. Sci Rep. 2016;6:19050.

4. Kuspa A, Loomis WF. The genome of Dictyostelium discoideum. Methods Mol Biol. 2006;346:15-30.

5. Davies HM, Nofal SD, McLaughlin EJ, Osborne AR. Repetitive sequences in malaria parasite proteins. FEMS Microbiol Rev. 2017;41(6):923-40.

6. Mier P, Alanis-Lobato G, Andrade-Navarro MA. Context characterization of amino acid homorepeats using evolution, position, and order. Proteins. 2017;85(4):709-19.

We will cite the two references by Kiersten M. Ruff in our revised manuscript.

K. M. Ruff and R. V. Pappu, (2015) Multiscale simulation provides mechanistic insights into the effects of sequence contexts of early-stage polyglutamine-mediated aggregation. Biophysical Journal 108, 495a.

K. M. Ruff, J. B. Warner, A. Posey and P. S. Tan (2017) Polyglutamine length dependent structural properties and phase behavior of huntingtin exon1. Biophysical Journal 112, 511a.

The authors could easily address this problem with the data and analysis they have already collected. However, at this time, without this normalization, I am hesitant to trust the lists of proteins with long runs of amino acid and the ensuing GO enrichment analysis.

Ruff KM. 2017. Washington University in St.

Ruff KM, Holehouse AS, Richardson MGO, Pappu RV. 2016. Proteomic and Biophysical Analysis of Polar Tracts. Biophys J 110:556a.

We thank Reviewer #1 for this helpful suggestion and now address this issue by means of a different approach described below.

Based on a previous study (43; Palo Mier et al. 2020), we applied seven different thresholds to seek both short and long, as well as pure and impure, polyX strings in 20 different representative near-complete proteomes, including 4X (4/4), 5X (4/5-5/5), 6X (4/6-6/6), 7X (4/7-7/7), 8-10X (≥50%X), 11-10X (≥50%X) and ≥21X (≥50%X).

To normalize the runs of amino acids and create a null expectation from each proteome, we determined the ratios of the overall number of X residues for each of the seven polyX motifs relative to those in the entire proteome of each species, respectively. The results of four different polyX motifs are shown below, i.e., polyQ (Author response image 1), polyN (Author response image 2), polyS (Author response image 3) and polyT (Author response image 4).

Author response image 1.

Q contents in 7 different types of polyQ motifs in 20 near-complete proteomes. The five ciliates with reassigned stops codon (TAAQ and TAGQ) are indicated in red. Stentor coeruleus, a ciliate with standard stop codons, is indicated in green.  

Author response image 2.

N contents in 7 different types of polyN motifs in 20 near-complete proteomes. The five ciliates with reassigned stops codon (TAAQ and TAGQ) are indicated in red. Stentor coeruleus, a ciliate with standard stop codons, is indicated in green.

Author response image 3.

S contents in 7 different types of polyS motifs in 20 near-complete proteomes. The five ciliates with reassigned stops codon (TAAQ and TAGQ) are indicated in red. Stentor coeruleus, a ciliate with standard stop codons, is indicated in green.  

Author response image 4.

T contents in 7 different types of polyT motifs in 20 near-complete proteomes. The five ciliates with reassigned stops codon (TAAQ and TAGQ) are indicated in red. Stentor coeruleus, a ciliate with standard stop codons, is indicated in green.

The results summarized in these four new figures support that polyX prevalence differs among species and that the overall X contents of polyX motifs often but not always correlate with the X usage frequency in entire proteomes (43; Palo Mier et al. 2020).

Most importantly, our results reveal that, compared to Stentor coeruleus or several non-ciliate eukaryotic organisms (e.g., Plasmodium falciparum, Caenorhabditis elegans, Danio rerio, Mus musculus and Homo sapiens), the five ciliates with reassigned TAAQ and TAGQ codons not only have higher Q usage frequencies, but also more polyQ motifs in their proteomes (Figure 1). In contrast, polyQ motifs prevail in Candida albicans, Candida tropicalis, Dictyostelium discoideum, Chlamydomonas reinhardtii, Drosophila melanogaster and Aedes aegypti, though the Q usage frequencies in their entire proteomes are not significantly higher than those of other eukaryotes (Figure 1). Due to their higher N usage frequencies, Dictyostelium discoideum, Plasmodium falciparum and Pseudocohnilembus persalinus have more polyN motifs than the other 23 eukaryotes we examined here (Figure 2). Generally speaking, all 26 eukaryotes we assessed have similar S usage frequencies and percentages of S contents in polyS motifs (Figure 3). Among these 26 eukaryotes, Dictyostelium discoideum possesses many more polyT motifs, though its T usage frequency is similar to that of the other 25 eukaryotes (Figure 4).

In conclusion, these new normalized results confirm that the reassignment of stop codons to Q indeed results in both higher Q usage frequencies and more polyQ motifs in ciliates.  

Reviewer #2 (Public Review):

Summary:

This study seeks to understand the connection between protein sequence and function in disordered regions enriched in polar amino acids (specifically Q, N, S and T). While the authors suggest that specific motifs facilitate protein-enhancing activities, their findings are correlative, and the evidence is incomplete. Similarly, the authors propose that the re-assignment of stop codons to glutamine-encoding codons underlies the greater user of glutamine in a subset of ciliates, but again, the conclusions here are, at best, correlative. The authors perform extensive bioinformatic analysis, with detailed (albeit somewhat ad hoc) discussion on a number of proteins. Overall, the results presented here are interesting, but are unable to exclude competing hypotheses.

Strengths:

Following up on previous work, the authors wish to uncover a mechanism associated with poly-Q and SCD motifs explaining proposed protein expression-enhancing activities. They note that these motifs often occur IDRs and hypothesize that structural plasticity could be capitalized upon as a mechanism of diversification in evolution. To investigate this further, they employ bioinformatics to investigate the sequence features of proteomes of 27 eukaryotes. They deepen their sequence space exploration uncovering sub-phylum-specific features associated with species in which a stop-codon substitution has occurred. The authors propose this stop-codon substitution underlies an expansion of ploy-Q repeats and increased glutamine distribution.

Weaknesses:

The preprint provides extensive, detailed, and entirely unnecessary background information throughout, hampering reading and making it difficult to understand the ideas being proposed. The introduction provides a large amount of detailed background that appears entirely irrelevant for the paper. Many places detailed discussions on specific proteins that are likely of interest to the authors occur, yet without context, this does not enhance the paper for the reader.

The paper uses many unnecessary, new, or redefined acronyms which makes reading difficult. As examples:

(1) Prion forming domains (PFDs). Do the authors mean prion-like domains (PLDs), an established term with an empirical definition from the PLAAC algorithm? If yes, they should say this. If not, they must define what a prion-forming domain is formally.

The N-terminal domain (1-123 amino acids) of S. cerevisiae Sup35 was already referred to as a “prion forming domain (PFD)” in 2006 (Tuite, M. F. 2006). Since then, PFD has also been employed as an acronym in other yeast prion papers (Cox, B.S. et al. 2007; Toombs, T. et al. 2011).

M. F., Tuite, Yeast prions and their prion forming domain. Cell 27, 397-407 (2005).

B. S. Cox, L. Byrne, M. F., Tuite, Protein Stability. Prion 1, 170-178 (2007).

J. A. Toombs, N. M. Liss, K. R. Cobble, Z. Ben-Musa, E. D. Ross, [PSI+] maintenance is dependent on the composition, not primary sequence, of the oligopeptide repeat domain. PLoS One 6, e21953 (2011).

(2) SCD is already an acronym in the IDP field (meaning sequence charge decoration) - the authors should avoid this as their chosen acronym for Serine(S) / threonine (T)-glutamine (Q) cluster domains. Moreover, do we really need another acronym here (we do not).

SCD was first used in 2005 as an acronym for the Serine (S)/threonine (T)-glutamine (Q) cluster domain in the DNA damage checkpoint field (Traven, A. and Heierhorst, J. 2005). Almost a decade later, SCD became an acronym for “sequence charge decoration” (Sawle, L. et al. 2015; Firman, T. et al. 2018).

A. Traven and J, Heierhorst, SQ/TQ cluster domains: concentrated ATM/ATR kinase phosphorylation site regions in DNA-damage-response proteins. Bioessays. 27, 397-407 (2005).

L. Sawle and K, Ghosh, A theoretical method to compute sequence dependent configurational properties in charged polymers and proteins. J. Chem Phys. 143, 085101(2015).

T. Firman and Ghosh, K. Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins. J. Chem Phys. 148, 123305 (2018).

(3) Protein expression-enhancing (PEE) - just say expression-enhancing, there is no need for an acronym here.

Thank you. Since we have shown that addition of Q-rich motifs to LacZ affects protein expression rather than transcription, we think it is better to use the “PEE” acronym.

The results suggest autonomous protein expression-enhancing activities of regions of multiple proteins containing Q-rich and SCD motifs. Their definition of expression-enhancing activities is vague and the evidence they provide to support the claim is weak. While their previous work may support their claim with more evidence, it should be explained in more detail. The assay they choose is a fusion reporter measuring beta-galactosidase activity and tracking expression levels. Given the presented data they have shown that they can drive the expression of their reporters and that beta gal remains active, in addition to the increase in expression of fusion reporter during the stress response. They have not detailed what their control and mock treatment is, which makes complete understanding of their experimental approach difficult. Furthermore, their nuclear localization signal on the tag could be influencing the degradation kinetics or sequestering the reporter, leading to its accumulation and the appearance of enhanced expression. Their evidence refuting ubiquitin-mediated degradation does not have a convincing control.

Based on the experimental results, the authors then go on to perform bioinformatic analysis of SCD proteins and polyX proteins. Unfortunately, there is no clear hypothesis for what is being tested; there is a vague sense of investigating polyX/SCD regions, but I did not find the connection between the first and section compelling (especially given polar-rich regions have been shown to engage in many different functions). As such, this bioinformatic analysis largely presents as many lists of percentages without any meaningful interpretation. The bioinformatics analysis lacks any kind of rigorous statistical tests, making it difficult to evaluate the conclusions drawn. The methods section is severely lacking. Specifically, many of the methods require the reader to read many other papers. While referencing prior work is of course, important, the authors should ensure the methods in this paper provide the details needed to allow a reader to evaluate the work being presented. As it stands, this is not the case.

Thank you. As described in detail below, we have now performed rigorous statistical testing using the GofuncR package.

Overall, my major concern with this work is that the authors make two central claims in this paper (as per the Discussion). The authors claim that Q-rich motifs enhance protein expression. The implication here is that Q-rich motif IDRs are special, but this is not tested. As such, they cannot exclude the competing hypothesis ("N-terminal disordered regions enhance expression").

In fact, “N-terminal disordered regions enhance expression” exactly summarizes our hypothesis.

On pages 12-13 and Figure 4 of our preprint manuscript, we explained our hypothesis in the paragraph entitled “The relationship between PEE function, amino acid contents, and structural flexibility”.

The authors also do not explore the possibility that this effect is in part/entirely driven by mRNA-level effects (see Verma Na Comms 2019).

As pointed out by the first reviewer, we show evidence that the increase in protein abundance and enzymatic activity is not due to changes in plasmid copy number or mRNA abundance (Figure 2), and that this phenomenon is not affected by translational quality control mutants (Figure 3).

As such, while these observations are interesting, they feel preliminary and, in my opinion, cannot be used to draw hard conclusions on how N-terminal IDR sequence features influence protein expression. This does not mean the authors are necessarily wrong, but from the data presented here, I do not believe strong conclusions can be drawn. That re-assignment of stop codons to Q increases proteome-wide Q usage. I was unable to understand what result led the authors to this conclusion.

My reading of the results is that a subset of ciliates has re-assigned UAA and UAG from the stop codon to Q. Those ciliates have more polyQ-containing proteins. However, they also have more polyN-containing proteins and proteins enriched in S/T-Q clusters. Surely if this were a stop-codon-dependent effect, we'd ONLY see an enhancement in Q-richness, not a corresponding enhancement in all polar-rich IDR frequencies? It seems the better working hypothesis is that free-floating climate proteomes are enriched in polar amino acids compared to sessile ciliates.

Thank you. These comments are not supported by the results in Figure 1.

Regardless, the absence of any kind of statistical analysis makes it hard to draw strong conclusions here.

We apologize for not explaining more clearly the results of Tables 5-7 in our preprint manuscript.

To address the concerns about our GO enrichment analysis by both reviewers, we have now performed rigorous statistical testing for SCD and polyQ protein overrepresentation using the GOfuncR package (https://bioconductor.org/packages/release/bioc/html/GOfuncR.html). GOfuncR is an R package program that conducts standard candidate vs. background enrichment analysis by means of the hypergeometric test. We then adjusted the raw p-values according to the Family-wise error rate (FWER). The same method had been applied to GO enrichment analysis of human genomes (Huttenhower, C., et al. 2009).

Curtis Huttenhower, C., Haley, E. M., Hibbs, M., A., Dumeaux, V., Barrett, D. R., Hilary A. Coller, H. A., and Olga G. Troyanskaya, O., G. Exploring the human genome with functional maps, Genome Research 19, 1093-1106 (2009).

The results presented in Author response image 5 and Author response image 6 support our hypothesis that Q-rich motifs prevail in proteins involved in specialized biological processes, including Saccharomyces cerevisiae RNA-mediated transposition, Candida albicans filamentous growth, peptidyl-glutamic acid modification in ciliates with reassigned stop codons (TAAQ and TAGQ), Tetrahymena thermophila xylan catabolism, Dictyostelium discoideum sexual reproduction, Plasmodium falciparum infection, as well as the nervous systems of Drosophila melanogaster, Mus musculus, and Homo sapiens (74). In contrast, peptidyl-glutamic acid modification and microtubule-based movement are not overrepresented with Q-rich proteins in Stentor coeruleus, a ciliate with standard stop codons.

1. Cara L, Baitemirova M, Follis J, Larios-Sanz M, Ribes-Zamora A. The ATM- and ATR-related SCD domain is over-represented in proteins involved in nervous system development. Sci Rep. 2016;6:19050.

Author response image 5.

Selection of biological processes with overrepresented SCD-containing proteins in different eukaryotes. The percentages and number of SCD-containing proteins in our search that belong to each indicated Gene Ontology (GO) group are shown. GOfuncR (Huttenhower, C., et al. 2009) was applied for GO enrichment and statistical analysis. The p values adjusted according to the Family-wise error rate (FWER) are shown. The five ciliates with reassigned stop codons (TAAQ and TAGQ) are indicated in red. Stentor coeruleus, a ciliate with standard stop codons, is indicated in green.

Author response image 6.

Selection of biological processes with overrepresented polyQ-containing proteins in different eukaryotes. The percentages and numbers of polyQ-containing proteins in our search that belong to each indicated Gene Ontology (GO) group are shown. GOfuncR (Huttenhower, C., et al. 2009) was applied for GO enrichment and statistical analysis. The p values adjusted according to the Family-wise error rate (FWER) are shown. The five ciliates with reassigned stops codons (TAAQ and TAGQ) are indicated in red. Stentor coeruleus, a ciliate with standard stop codons, is indicated in green.

Reviewer #2 (Public Review):

Summary:<br /> This study seeks to understand the connection between protein sequence and function in disordered regions enriched in polar amino acids (specifically Q, N, S and T). While the authors suggest that specific motifs facilitate protein-enhancing activities, their findings are correlative, and the evidence is incomplete. Similarly, the authors propose that the re-assignment of stop codons to glutamine-encoding codons underlies the greater user of glutamine in a subset of ciliates, but again, the conclusions here are, at best, correlative. The authors perform extensive bioinformatic analysis, with detailed (albeit somewhat ad hoc) discussion on a number of proteins. Overall, the results presented here are interesting, but are unable to exclude competing hypotheses.

Strengths:<br /> Following up on previous work, the authors wish to uncover a mechanism associated with poly-Q and SCD motifs explaining proposed protein expression-enhancing activities. They note that these motifs often occur IDRs and hypothesize that structural plasticity could be capitalized upon as a mechanism of diversification in evolution. To investigate this further, they employ bioinformatics to investigate the sequence features of proteomes of 27 eukaryotes. They deepen their sequence space exploration uncovering sub-phylum-specific features associated with species in which a stop-codon substitution has occurred. The authors propose this stop-codon substitution underlies an expansion of ploy-Q repeats and increased glutamine distribution.

Weaknesses:<br /> The preprint provides extensive, detailed, and entirely unnecessary background information throughout, hampering reading and making it difficult to understand the ideas being proposed.<br /> The introduction provides a large amount of detailed background that appears entirely irrelevant for the paper. Many places detailed discussions on specific proteins that are likely of interest to the authors occur, yet without context, this does not enhance the paper for the reader.

The paper uses many unnecessary, new, or redefined acronyms which makes reading difficult. As examples: (1) Prion forming domains (PFDs). Do the authors mean prion-like domains (PLDs), an established term with an empirical definition from the PLAAC algorithm? If yes, they should say this. If not, they must define what a prion-forming domain is formally. (2) SCD is already an acronym in the IDP field (meaning sequence charge decoration) - the authors should avoid this as their chosen acronym for Serine(S) / threonine (T)-glutamine (Q) cluster domains. Moreover, do we really need another acronym here (we do not). (3) Protein expression-enhancing (PEE) - just say expression-enhancing, there is no need for an acronym here.

The results suggest autonomous protein expression-enhancing activities of regions of multiple proteins containing Q-rich and SCD motifs. Their definition of expression-enhancing activities is vague and the evidence they provide to support the claim is weak. While their previous work may support their claim with more evidence, it should be explained in more detail. The assay they choose is a fusion reporter measuring beta-galactosidase activity and tracking expression levels. Given the presented data they have shown that they can drive the expression of their reporters and that beta gal remains active, in addition to the increase in expression of fusion reporter during the stress response. They have not detailed what their control and mock treatment is, which makes complete understanding of their experimental approach difficult. Furthermore, their nuclear localization signal on the tag could be influencing the degradation kinetics or sequestering the reporter, leading to its accumulation and the appearance of enhanced expression. Their evidence refuting ubiquitin-mediated degradation does not have a convincing control.

Based on the experimental results, the authors then go on to perform bioinformatic analysis of SCD proteins and polyX proteins. Unfortunately, there is no clear hypothesis for what is being tested; there is a vague sense of investigating polyX/SCD regions, but I did not find the connection between the first and section compelling (especially given polar-rich regions have been shown to engage in many different functions). As such, this bioinformatic analysis largely presents as many lists of percentages without any meaningful interpretation. The bioinformatics analysis lacks any kind of rigorous statistical tests, making it difficult to evaluate the conclusions drawn.

The methods section is severely lacking. Specifically, many of the methods require the reader to read many other papers. While referencing prior work is of course, important, the authors should ensure the methods in this paper provide the details needed to allow a reader to evaluate the work being presented. As it stands, this is not the case.

Overall, my major concern with this work is that the authors make two central claims in this paper (as per the Discussion).

The authors claim that Q-rich motifs enhance protein expression. The implication here is that Q-rich motif IDRs are special, but this is not tested. As such, they cannot exclude the competing hypothesis ("N-terminal disordered regions enhance expression"). The authors also do not explore the possibility that this effect is in part/entirely driven by mRNA-level effects (see Verma Na Comms 2019). As such, while these observations are interesting, they feel preliminary and, in my opinion, cannot be used to draw hard conclusions on how N-terminal IDR sequence features influence protein expression. This does not mean the authors are necessarily wrong, but from the data presented here, I do not believe strong conclusions can be drawn.

That re-assignment of stop codons to Q increases proteome-wide Q usage. I was unable to understand what result led the authors to this conclusion. My reading of the results is that a subset of ciliates has re-assigned UAA and UAG from the stop codon to Q. Those ciliates have more polyQ-containing proteins. However, they also have more polyN-containing proteins and proteins enriched in S/T-Q clusters. Surely if this were a stop-codon-dependent effect, we'd ONLY see an enhancement in Q-richness, not a corresponding enhancement in all polar-rich IDR frequencies? It seems the better working hypothesis is that free-floating climate proteomes are enriched in polar amino acids compared to sessile ciliates. Regardless, the absence of any kind of statistical analysis makes it hard to draw strong conclusions here.

This is a concept hard for many to imagine nowadays given how reliant and incorporated media is in various popular culture

Signature tagged mutagenesis, tag is kanamycin resistance; integrate into genome and then look for unusual phenotypes (kanamycin resistance), when found, this phenotype indicates that the gene relating to the usual phenotype was inactivated

Author Response

Reviewer #1 (Public Review):

The work by Yijun Zhang and Zhimin He at al. analyzes the role of HDAC3 within DC subsets. Using an inducible ERT2-cre mouse model they observe the dependency of pDCs but not cDCs on HDAC3. The requirement of this histone modifier appears to be early during development around the CLP stage. Tamoxifen treated mice lack almost all pDCs besides lymphoid progenitors. Through bulk RNA seq experiment the authors identify multiple DC specific target gens within the remaining pDCs and further using Cut and Tag technology they validate some of the identified targets of HDAC3. Collectively the study is well executed and shows the requirement of HDAC3 on pDCs but not cDCs, in line with the recent findings of a lymphoid origin of pDC.

1) While the authors provide extensive data on the requirement of HDAC3 within progenitors, the high expression of HDAC3 in mature pDCs may underly a functional requirement. Have you tested INF production in CD11c cre pDCs? Are there transcriptional differences between pDCs from HDAC CD11c cre and WT mice?

We greatly appreciate the reviewer’s point. We have confirmed that Hdac3 can be efficiently deleted in pDCs of Hdac3fl/fl-CD11c Cre mice (Figure 5-figure supplement 1 in revised manuscript). Furthermore, in those Hdac3fl/fl-CD11c Cre mice, we have observed significantly decreased expression of key cytokines (Ifna, Ifnb, and Ifnl) by pDCs upon activation by CpG ODN (shown in Author response image 1). Therefore, HDAC3 is also required for proper pDC function. However, we have yet to conduct RNA-seq analysis comparing pDCs from HDAC CD11c cre and WT mice.

Author response image 1.

Cytokine expression in Hdac3 deficient pDCs upon activation

2) A more detailed characterization of the progenitor compartment that is compromised following depletion would be important, as also suggested in the specific points.

We thank the reviewer for this constructive suggestion. We have performed thorough analysis of the phenotype of hematopoietic stem cells and progenitor cells at various developmental stages in the bone marrow of Hdac3 deficient mice, based on the gating strategy from the recommended reference. Briefly, we analyzed the subpopulations of progenitors based on the description in the published report by "Pietras et al. 2015", namely MPP2, MPP3 and MPP4, using the same gating strategy for hematopoietic stem/progenitor cells. As shown in Author response image 2 and Author response image 3, we found that the number of LSK cells was increased in Hdac3 deficient mice, especially the subpopulations of MPP2 and MPP3, whereas no significant changes in MPP4. In contrast, the numbers of LT-HSC, ST-HSC and CLP were all dramatically decreased. This result has been optimized and added as Figure 3A in revised manuscript. The relevant description has been added and underlined in the revised manuscript Page 6 Line 164-168.

Author response image 2.

Gating strategy for hematopoietic stem/progenitor cells in bone marrow.

Author response image 3.

Hematopoietic stem/progenitor cells in Hdac3 deficient mice

Reviewer #2 (Public Review):

In this article Zhang et al. report that the Histone Deacetylase-3 (HDAC3) is highly expressed in mouse pDC and that pDC development is severely affected both in vivo and in vitro when using mice harbouring conditional deletion of HDAC3. However, pDC numbers are not affected in Hdac3fl/fl Itgax-Cre mice, indicating that HDCA3 is dispensable in CD11c+ late stages of pDC differentiation. Indeed, the authors provide wide experimental evidence for a role of HDAC3 in early precursors of pDC development, by combining adoptive transfer, gene expression profiling and in vitro differentiation experiments. Mechanistically, the authors have demonstrated that HDAC3 activity represses the expression of several transcription factors promoting cDC1 development, thus allowing the expression of genes involved in pDC development. In conclusion, these findings reveals HDAC3 as a key epigenetic regulator of the expression of the transcription factors required for pDC vs cDC1 developmental fate.

These results are novel and very promising. However, supplementary information and eventual further investigations are required to improve the clarity and the robustness of this article.

Major points

1) The gating strategy adopted to identify pDC in the BM and in the spleen should be entirely described and shown, at least as a Supplementary Figure. For the BM the authors indicate in the M & M section that they negatively selected cells for CD8a and B220, but both markers are actually expressed by differentiated pDC. However, in the Figures 1 and 2 pDC has been shown to be gated on CD19- CD11b- CD11c+. What is the precise protocol followed for pDC gating in the different organs and experiments?

We apologize for not clearly describing the protocols used in this study. Please see the detailed gating strategy for pDC in bone marrow, and for pDC and cDC in spleen (Figure 4 and Figure 5). These information are now added to Figure1−figure supplement 3, The relevant description has been underlined in Page 5 Line 113-116, in revised manuscript.

We would like to clarify that in our study, we used two different panels of antibody cocktails, one for bone marrow Lin- cells, including mAbs to CD2/CD3/TER-119/Ly6G/B220/CD11b/CD8/CD19; the other for DC enrichment, including mAbs to CD3/CD90/TER-119/Ly6G/CD19. We included B220 in the Lineage cocktails to deplete B cells and pDCs, in order to enrich for the progenitor cells from bone marrow. However, when enriching for the pDC and cDC, B220 or CD8a were not included in the cocktail to avoid depletion of pDC and cDC1 subsets . For the flow cytometry analysis of pDCs, we gated pDCs as the CD19−CD11b−CD11c+B220+SiglecH+ population in both bone marrow and spleen. The relevant description has been underlined in the revised manuscript Page 16 Line 431-434.

2) pDC identified in the BM as SiglecH+ B220+ can actually contain DC precursors, that can express these markers, too. This could explain why the impact of HDAC3 deletion appears stronger in the spleen than in the BM (Figures 1A and 2A). Along the same line, I think that it would important to show the phenotype of pDC in control vs HDAC3-deleted mice for the different pDC markers used (SiglecH, B220, Bst2) and I would suggest to include also Ly6D, taking also in account the results obtained in Figures 4 and 7. Finally, as HDCA3 deletion induces downregulation of CD8a in cDC1 and pDC express CD8a, it would important to analyse the expression of this marker on control vs HDAC3-deleted pDC.

We agree with the reviewer’s points. In the revised manuscript, we incorporated major surface markers, including Siglec H, B220, Ly6D, and PDCA-1, all of which consistently demonstrated a substantial decrease in the pDC population in Hdac3 deficient mice. Moreover, we did notice that Ly6D+ pDCs showed higher degree of decrease in Hdac3 deficient mice. Additionally, percentage and number of both CD8+ pDC and CD8- pDC were decreased in Hdac3 deficient mice (Author response image 4). These results are shown in Figure1−figure supplement 4 of the revised manuscript. The relevant description has been added and underlined in the revised manuscript Page 5 Line 121-125.

Author response image 4.

Bone marrow pDCs in Hdac3 deficient mice revealed by multiple surface markers

3) How do the authors explain that in the absence of HDAC3 cDC2 development increased in vivo in chimeric mice, but reduced in vitro (Figures 2B and 2E)?

As shown in the response to the Minor point 5 of Reviewer#1. Briefly, we suggested that the variabilities maybe explained by the timing of anaysis after HDAC3 deletion. In Figure 2C, we analyzed cells from the recipients one week after the final tamoxifen treatment and observed no significant change in the percentage of cDC2 when further pooled all the experiment data. In Figure 2E, where tamoxifen was administered at Day 0 in Flt3L-mediated DC differentiation in vitro, the DC subsets generated were then analyzed at different time points. We observed no significant changes in cDCs and cDC2 at Day 5, but decreases in the percentage of cDC2 were observed at Day 7 and Day 9. This suggested that the cDC subsets at Day 5 might have originated from progenitors at a later stage, while those at Day 7 and Day 9 might originate form the earlier progenitors. Therefore, based on these in vitro and in vivo experiments, we believe that the variation in the cDC2 phenotype might be attributed to the progenitors at different stages that generated these cDCs.

4) More generally, as reported also by authors (line 207), the reconstitution with HDAC3-deleted cells is poorly efficient. Although cDC seem not to be impacted, are other lymphoid or myeloid cells affected? This should be expected as HDAC3 regulates T and B development, as well as macrophage function. This should be important to know, although this does not call into question the results shown, as obtained in a competitive context.

In this study, we found no significant influence on T cells, mature B cells or NK cells, but immature B cells were significantly decreased, in Hdac3-ERT2-Cre mice after tamoxifen treatment (Figure 6). However, in the bone marrow chimera experiments, the numbers of major lymphoid cells were decreased due to the impaired reconstitution capacity of Hdac3 deficient progenitors. Consistent with our finding, it has been reported that HDAC3 was required for T cell and B cell generation, in HDAC3-VavCre mice (Summers et al., 2013), and was necessary for T cell maturation (Hsu et al., 2015). Moreover, HDAC3 is also required for the expression of inflammatory genes in macrophages upon activation (Chen et al., 2012; Nguyen et al., 2020).

5) What are the precise gating strategies used to identify the different hematopoietic precursors in the Figure 4 ? In particular, is there any lineage exclusion performed?

We apologize for not describing the experimental procedures clearly. In this study we enriched the lineage negative (Lin−) cells from the bone marrow using a Lineage-depleting antibody cocktail including mAbs to CD2/CD3/TER-119/Ly6G/B220/CD11b/CD8/CD19. We also provide the gating strategy implemented for sorting LSK and CDP populations from the Lin− cells in the bone marrow (Author response image 5), shown in the Figure 3A and Figure4−figure supplement 1 of revised manuscript.

Author response image 5.

Gating strategy for LSK, CD115+ CDP and CD115− CDP in bone marrow

6) Moreover, what is the SiglecH+ CD11c- population appearing in the spleen of mice reconstituted with HDAC3-deleted CDP, in Fig 4D?

We also noticed the appearance of a SiglecH+CD11c− cell population in the spleen of recipient mice reconstituted with HDAC3-deficient CD115−CDPs, while the presence of this population was not as significant in the HDAC3-Ctrl group, as shown in Figure 4D. We speculate that this SiglecH+CD11c− cell population might represent some cells at a differentiation stage earlier than pre-DCs. Alternatively, the relatively increased percentage of this population derived from HDAC3-deficient CD115−CDP might be due to the substantially decreased total numbers of DCs. This could be clarified by further analysis using additional cell surface markers.

7) Finally, in Fig 4H, how do the authors explain that Hdac3fl/fl express Il7r, while they are supposed to be sorted CD127- cells?

This is indeed an interesting question. In this study, we confirmed that CD115−CDPs were isolated from the surface CD127− cell population for RNA-seq analysis, and the purity of the sorted cells were checked (Author response image 6), as shown in Figure4−figure supplement 1 in revised manuscript.

The possible explanation for the expression of Il7r mRNA in some HDAC3fl/fl CD115−CDPs, as revealed in Figure 4H by RNA-seq analysis, could be due to a very low level of cell surface expression of CD127, these cells therefore could not be efficiently excluded by sorting for surface CD127- cells.

Author response image 6.

CD115−CDPs sorting from Hdac3-Ctrl and Hdac3-KO mice

8) What is known about the expression of HDAC3 in the different hematopoietic precursors analysed in this study? This information is available only for a few of them in Supplementary Figure 1. If not yet studied, they should be addressed.

We conducted additional analysis to address the expression of Hdac3 in various hematopoietic progenitor cells at different stages, based on the RNA-seq analyis. The data revealed a relatively consistent level of Hdac3 expression in progenitor populations, including HSC, MMP4, CLP, CDP and BM pDCs (Author response image 7). That suggests that HDAC3 may play an important role in the regulation of hematopoiesis at multiple stages. This information is now added in Figure1−figure supplement 1B of revised manuscript.

Author response image 7.

Hdac3 expression in hematopoietic progenitor cells

9) It would be highly informative to extend CUT and Tag studies to Irf8 and Tcf4, if this is technically feasible.

We totally agree with the reviewer. We have indeed attempted using CUT and Tag study to compare the binding sites of IRF8 and TCF4 in wild-type and Hdac3-deficient pDCs. However, it proved that this is technically unfeasible to get reliable results due to the limited number of cells we could obtain from the HDAC3 deficient mice. We are committed to explore alternative approaches or technologies in future studies to address this issue.

eLife assessment

This study examines the expression of HDAC3 within DC compartment. Taking advantage of tamoxifen inducible ERT2-cre mouse model they observe the dependency of pDCs but not cDCs on HDAC3. The requirement of this histone modifier appears to occur during development around the CLP stage. Tamoxifen treated mice lack almost all pDC besides lymphoid progenitors. RNA seq studies identify multiple DC specific target genes within the remaining pDC - using Cut and Tag technology they validate some of the identified targets of HDAC3. Taken together, this study shows the requirement of HDAC3 on pDC but not cDC, congruent with the recent findings of a lymphoid origin of pDC.

Reviewer #1 (Public Review):

The work by Yijun Zhang and Zhimin He at al. analyzes the role of HDAC3 within DC subsets. Using an inducible ERT2-cre mouse model they observe the dependency of pDCs but not cDCs on HDAC3. The requirement of this histone modifier appears to be early during development around the CLP stage. Tamoxifen treated mice lack almost all pDCs besides lymphoid progenitors. Through bulk RNA seq experiment the authors identify multiple DC specific target gens within the remaining pDCs and further using Cut and Tag technology they validate some of the identified targets of HDAC3.<br /> Collectively the study is well executed and shows the requirement of HDAC3 on pDCs but not cDCs, in line with the recent findings of a lymphoid origin of pDC.

While the authors provide extensive data on the requirement of HDAC3 within progenitors, the high expression of HDAC3 in mature pDCs may underly a functional requirement. Have you tested INF production in CD11c cre pDCs? Are there transcriptional differences between pDCs from HDAC CD11c cre and WT mice?

A more detailed characterization of the progenitor compartment that is compromised following depletion would be important, as also suggested in the specific points.

Reviewer #2 (Public Review):

In this article Zhang et al. report that the Histone Deacetylase-3 (HDAC3) is highly expressed in mouse pDC and that pDC development is severely affected both in vivo and in vitro when using mice harbouring conditional deletion of HDAC3. However, pDC numbers are not affected in Hdac3fl/fl Itgax-Cre mice, indicating that HDCA3 is dispensable in CD11c+ late stages of pDC differentiation. Indeed, the authors provide wide experimental evidence for a role of HDAC3 in early precursors of pDC development, by combining adoptive transfer, gene expression profiling and in vitro differentiation experiments. Mechanistically, the authors have demonstrated that HDAC3 activity represses the expression of several transcription factors promoting cDC1 development, thus allowing the expression of genes involved in pDC development. In conclusion, these findings reveals HDAC3 as a key epigenetic regulator of the expression of the transcription factors required for pDC vs cDC1 developmental fate.

These results are novel and very promising. However, supplementary information and eventual further investigations are required to improve the clarity and the robustness of this article.

Major points<br /> 1) The gating strategy adopted to identify pDC in the BM and in the spleen should be entirely described and shown, at least as a Supplementary Figure. For the BM the authors indicate in the M & M section that they negatively selected cells for CD8a and B220, but both markers are actually expressed by differentiated pDC. However, in the Figures 1 and 2 pDC has been shown to be gated on CD19- CD11b- CD11c+. What is the precise protocol followed for pDC gating in the different organs and experiments?

2) pDC identified in the BM as SiglecH+ B220+ can actually contain DC precursors, that can express these markers, too. This could explain why the impact of HDAC3 deletion appears stronger in the spleen than in the BM (Figures 1A and 2A). Along the same line, I think that it would important to show the phenotype of pDC in control vs HDAC3-deleted mice for the different pDC markers used (SiglecH, B220, Bst2) and I would suggest to include also Ly6D, taking also in account the results obtained in Figures 4 and 7. Finally, as HDCA3 deletion induces downregulation of CD8a in cDC1 and pDC express CD8a, it would important to analyse the expression of this marker on control vs HDAC3-deleted pDC.

3) How do the authors explain that in the absence of HDAC3 cDC2 development increased in vivo in chimeric mice, but reduced in vitro (Figures 2B and 2E)? More generally, as reported also by authors (line 207), the reconstitution with HDAC3-deleted cells is poorly efficient. Although cDC seem not to be impacted, are other lymphoid or myeloid cells affected? This should be expected as HDAC3 regulates T and B development, as well as macrophage function. This should be important to know, although this does not call into question the results shown, as obtained in a competitive context.

4) What are the precise gating strategies used to identify the different hematopoietic precursors in the Figure 4 ? In particular, is there any lineage exclusion performed? Moreover, what is the SiglecH+ CD11c- population appearing in the spleen of mice reconstituted with HDAC3-deleted CDP? Data shown in Figure 4F should be expressed as log2 and not10. Finally, how do the authors explain that Hdac3fl/fl express Il7r, while they are supposed to be sorted CD127- cells?

5) What is known about the expression of HDAC3 in the different hematopoietic precursors analysed in this study? This information is available only for a few of them in Supplementary Figure 1. If not yet studied, they should be addressed.

6) It would be highly informative to extend CUT and Tag studies to Irf8 and Tcf4, if this is technically feasible.

Author Response

Reviewer #1 (Public Review):

This is a very exciting manuscript from Meng Wang's lab on lysosomal proteomics. They used several different protein tags to identify the lysosomal proteome. The exciting findings include A) specific lysosomal proteins exist in a tissue-specific manner B) lipl-4 overexpression and daf-2 extend life span using different mechanisms C) identification of novel lysosomal proteins D) demonstration of the function of several lysosomal proteins in regulation lysosome abundance and function.

We thank the reviewer for finding our manuscript exciting.

Reviewer #2 (Public Review):

In this manuscript, Yu and colleagues profile the lysosome content in C. elegans. They implement lysosome immunoprecipitation (Lyso-IP) for C. elegans and they convincingly show that this method successfully isolates lysosomes from whole worms. The authors find that the lysosomes of worms overexpressing the lysosomal lipase lipl4 are enriched for AMPK subunits and nucleoporins and that these proteins are required for the longevity of lipl-4 overexpressing worms. The authors also show that this is specific to this longevity pathway given that another long-lived worm strain (daf2) does not exhibit enrichment for nucleoporins nor does it require them for longevity. The authors go on to express the Lyso-IP tag in different tissues of C. elegans (muscle, hypodermis, intestine, neurons) and identify the tissue-specific lysosome proteomes. Finally, the authors use this method to identify lysosome proteins in mature lysosomes and they find new proteins that regulate lysosomal acidification.

The authors present a powerful tool to unbiasedly identify lysosome-associated proteins in C. elegans, and they provide an in-depth assessment of how this method can be used to understand longevity pathways and identify novel proteins. Understanding lysosomal differences in specific tissues or in response to different longevity conditions are exciting as it provides new insight into how organelles could control specific homeostasis responses. This tool and proteomics datasets also represent a great resource for the C. elegans community and should pry open new studies on the regulation and role of the lysosome at the organismal level.

We truly appreciate that the reviewer’s positive comment on our work.

Addressing the following suggestions would help strengthen this already strong manuscript. First, it would be helpful to validate selected candidates from the tissuespecific Lyso-IP to verify that the protocol is still specific with lower sample amounts. Second, it would be helpful to provide more details on the methods, notably for sample preparation and analysis, so that it can serve as a guideline for the community. Third, the manuscript contains a lot of data and conditions, which is great, but they may also feel disconnected in some cases and it could be helpful to focus the study on the main key findings.

We thank the reviewer’s comments. As suggested by the reviewer, we have also generated a CRISPR knock-in line for one hypodermis-specific candidate Y58A7A.1 that encodes a copper transporter and validated its hypodermis-specific lysosomal localization (new Supplementary Figure 2E).

As suggested by the reviewer, we have extended the method section on Lyso-IP to include more details. We believe that the new version should be sufficient for any lab to follow this protocol and conduct their own analyses. We will also take advantage of the eLife “Request a Protocol” feature to share the detailed version of the Lyso-IP method with researchers who are interested.

We have thoroughly reorganized the manuscript to increase the textual clarity and improve the connection between different analyses and results.

Reviewer #3 (Public Review):

The manuscript by Ji et al dissects the important role of lysosomes in cellular metabolism and signaling and their regulation by various associated proteins. The authors utilized deep proteomic profiling in C.Elegans to identify lysosome-associated proteins involved in regulating longevity and discovered the recruitment of AMPK and nucleoporin proteins in response to increased lysosomal lipolysis. Additionally, the authors found lysosomal heterogeneity across different tissues and specific enrichment of the Ragulator complex on Cystinosin-positive lysosomes.

Strengths of this work include the utilization of deep proteomic profiling to identify novel lysosome-associated proteins involved in longevity regulation, as well as the discovery of lysosomal heterogeneity and specific protein enrichments across different worm tissues. These findings point to a complex interplay between lysosomal protein dynamics, signal transduction, organelle crosstalk, and organism longevity.

One weakness of this work may be the limited scope of the study, as it focuses primarily on the identification and characterization of lysosome-associated proteins involved in longevity regulation, with limited mechanistic follow-up and some unsubstantiated claims.

We thank the reviewer for her/his helpful comments and suggestions. The primary goal of this manuscript is to provide new methods and resource to the community. We did have several biological findings from the current study, and mechanistic follow-up with these findings will be interesting future topics but may beyond the scope of the current manuscript. In addition, we have provided new experimental results to further support several claims that the reviewer has commented on.

Reviewer #2 (Public Review):

In this manuscript, Yu and colleagues profile the lysosome content in C. elegans. They implement lysosome immunoprecipitation (Lyso-IP) for C. elegans and they convincingly show that this method successfully isolates lysosomes from whole worms. The authors find that the lysosomes of worms overexpressing the lysosomal lipase lipl-4 are enriched for AMPK subunits and nucleoporins and that these proteins are required for the longevity of lipl-4 overexpressing worms. The authors also show that this is specific to this longevity pathway given that another long-lived worm strain (daf-2) does not exhibit enrichment for nucleoporins nor does it require them for longevity. The authors go on to express the Lyso-IP tag in different tissues of C. elegans (muscle, hypodermis, intestine, neurons) and identify the tissue-specific lysosome proteomes. Finally, the authors use this method to identify lysosome proteins in mature lysosomes and they find new proteins that regulate lysosomal acidification.

The authors present a powerful tool to unbiasedly identify lysosome-associated proteins in C. elegans, and they provide an in-depth assessment of how this method can be used to understand longevity pathways and identify novel proteins. Understanding lysosomal differences in specific tissues or in response to different longevity conditions are exciting as it provides new insight into how organelles could control specific homeostasis responses. This tool and proteomics datasets also represent a great resource for the C. elegans community and should pry open new studies on the regulation and role of the lysosome at the organismal level.

Addressing the following suggestions would help strengthen this already strong manuscript. First, it would be helpful to validate selected candidates from the tissue-specific Lyso-IP to verify that the protocol is still specific with lower sample amounts. Second, it would be helpful to provide more details on the methods, notably for sample preparation and analysis, so that it can serve as a guideline for the community. Third, the manuscript contains a lot of data and conditions, which is great, but they may also feel disconnected in some cases and it could be helpful to focus the study on the main key findings.

reply to u/IamOkei at https://www.reddit.com/r/Zettelkasten/comments/17beucn/comment/k5s6aek/?utm_source=reddit&utm_medium=web2x&context=3

u/IamOkei, I know you've got a significant enough practice that not much of what I might suggest may be helpful beyond your own extension of what you've got and how it is or isn't working for you. Perhaps chatting with a zettelkasten therapist may be helpful? Does anyone have "Zettelkasten Whisperer" on a business card yet?! More seriously, I occasionally dump some of my problems and issues into a notebook, unpublished on my blog, or even into a section of my own zettelkasten, which I never index or reconsult, as a helpful practice. Others like Henry David Thoreau have done something like this and there's a common related practice of writing "Morning Pages" that you can explore. My own version is somewhat similar to the idea of rubber duck debugging but focuses on my own work. You might try doing something like this in one of Bob Doto's cohorts or by way of private consulting sessions. Another free version of this could be found by participating in Will's regular weekly posts/threads "Share with us what is happening in your ZK this week" at https://forum.zettelkasten.de/. It's always a welcoming and constructive space. There are also some public and private (I won't out them) Discords where some of the practiced hands chat and commiserate with each other. Even the Obsidian PKM/Zettelkasten Discord channels aren't very Obsidian/digital-focused that you couldn't participate as an analog practitioner. I've even found that participating in book clubs related to some of my interests can be quite helpful in talking out ideas before writing them down. There are certainly options for working out and extending your own practice.

Beyond this, and without knowing more of your specific issues, I can only offer some broad thoughts which expand on some of the earlier discussion above.

I recommend stripping away Scheper's religious fervor, some of which he seems to have thrown over lately along with the idea of a permanent note or "main card" (something I think is a grave mistake), and trying something closer to Luhmann's idea of ZKII.

An alternate method, especially if you like a nice notebook or a particular fountain pen, might be to take all of your basic literature/fleeting notes along with the bibliographic data in a notebook and then just use your analog index cards/slips to make your permanent notes and your index.

Ultimately it's all a lot of the same process, though it may come down to what you want to call it and your broad philosophy. If you're anti-antinet, definitely quit using the verbiage for the framing there and lean toward the words used by Ahrens, Dan Allosso, Gerald Weinberg, Mark Bernstein, Umberto Eco, Beatrice Webb, Jacques Barzun & Henry Graff, or any of the dozens of others or even make up your own. Goodness knows we need a lot more names and categories for types of notes—just like we all need another one page blog post about how the Zettelkasten method works by someone who's been at it for a week. Maybe someone will bring all these authors to terms one day?

Generally once you know what sorts of ideas you're most interested in, you take fewer big notes on administrivia and focus more of your note taking towards your own personal goals and desires. (Taking notes to learn a subject are certainly game, but often they serve little purpose after-the-fact.) You can also focus less on note taking within your entertainment reading (usually a waste) and focusing more heavily on richer material (books and journal articles) that is "above you" in Adler's framing. You might make hundreds of highlights and annotations in a particular book, but only get two or three serious ideas and notes out of it ultimately. Focus on this and leave the rest. If you're aware of the Pareto principle or the 80/20 rule, then spend the majority of your time on the grander permanent notes (10-20%), and a lot less time worrying about the all the rest (the 80-90%).

In the example above relating to Marx, you can breeze through some low level introductory material for context, but nothing is going to beat reading Marx himself a few times. The notes you make on his text will have tremendously more value than the ones you took on the low level context. A corollary to this is that you're highly unlikely to earn a Ph.D. or discover massive insight by reading and taking note posts on Twitter, Medium, or Substack (except possibly unless your work is on the cultural anthropology of those platforms).

A lot of the zettelkasten spaces focus heavily on the note taking part of the process and not enough on the quality of what you're reading and how you're reading it. This portion is possibly more valuable than the note taking piece, but the two should be hand-in-glove and work toward something.

I suspect that most people who have 1000 notes know which five or ten are the most important to where they're going and how they're growing. Focus on those and your "conversations with texts" relating to those. The rest is either low level context for where you're headed or either pure noise/digital exhaust.

If you think of ideas as incunables, which notes will be worth of putting on your tombstone? In other words: What are your "tombstone notes"? (See what I did there? I came up with another name for a type of note, a sin for which I'm certainly going to spend a lot of time in zettelkasten purgatory.)

This is a test. I'm trying out syncing Hypothes.is with Obsidian

Der Teufel ist ein Imitator, aber ein schlechter.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

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Referee #1

Evidence, reproducibility and clarity

Summary: Sharma, et al. report the characterization of the polar tube (PT) from the microsporidian species, Vairimorpha necatrix, using a combination of optical microscopy, cryo-ET, and proteomics. The polar tube is a fascinating invasion apparatus which mediates the translocation of the parasite into the inside of a host cell to initiate infection. Similar to results obtained previously in other species, the authors show that PT firing in Vairimorpha necatrix is extremely fast, occurring on the order of 1 sec, and that the extruded PT is over 100 microns long in this species. Using cryo-ET to image the PT at a high resolution, they find that it exists in two major states: both an empty state and a state filled with cargo, and that the thickness of the tube wall changes when cargo is present. Strikingly, the authors observed that one of the cargo components, the ribosomes, are organized ordered array that may have helical symmetry. Finally, the authors took advantage of a naturally occurring "His tag" on PTP3 to affinity purify PTP3-containing protein complexes and analyze the composition using proteomics.

Major comments

ln 139-140: The absolute handedness of something can be very tricky to determine by cryo-ET (but certainly is possible). Variable hardware configurations between microscopes and differing conventions between software packages (e.g., for what direction is a positive tilt angle) can lead to inversion of the apparent handedness in the final tomogram. How certain are the authors that the absolute handedness is indeed right handed, as this seems to vary between the various display items in the manuscript? For example, in Fig 1c, my impression is that ribosome helices are left handed, as they are also in the supplemental movie. If this isn't known with certainty, perhaps it would be sufficient to describe the apparent helical symmetry but state that the handedness is ambiguous.

Minor comments

ln 39-40: Perhaps also cite the E. cuniculi genome paper?

ln 97-98: It is interesting that the PT shortens in V. necatrix as well, and while I can pick this out in some of the individual traces in Sup Fig. 1b, it seems to get washed out in the trend line and isn't super obvious. If it isn't to laborious, it could be nice to add a panel showing the quantification of this (e.g., plotting the final length of each PT as a percentage of the maximum length achieved).

ln 98-100: Strictly speaking, I don't think the referenced figure shows the sporoplasm being transformed into an extended conformation, only that it is spherical upon exit. Simply reword this to make clear that the deformations are inferred to occur but not directly observed.

Because PT firing is so fast, the probability of trapping a PT in the process of transporting cargo would be pretty low. So then why does the PT still contain cellular cargo like ribosomes inside in the tomograms? Should these not have emerged in the sporoplasm which would enter the host cell? Are these "defective" spores that have failed to complete sporoplasm transport? Perhaps this is worth discussing.

ln 118: The authors note an apparent correlation between the phase of germination and the thickness of the tube wall but don't specify what this correlation is. Is it thicker in the early phase and thinner in later phase, or vice versa? One could imagine "empty" tubes existing before or after sporoplasm transport, for example, so I'm not sure I follow how the phase is being inferred from the tomograms.

ln 119-120: What is the evidence that the outer layer is made of PTPs, or that it is even protein (for example, as opposed to cell wall-like carbohydrate polymers)? I think this seems like a very reasonable hypothesis, but I would suggest explaining the logic and ensuring the degree of uncertainty is conveyed clearly. In light of this, I would also suggest changing figure labels, etc, that refer to the PTP layer (e.g., Fig. 3, PTPc and PTPe labels).

ln 121, 123: "sheathed by a thin layer" and "enveloped by a thick outer layer": is this an additional layer being described? Or is this referring to the putative PTP layer, and that its thickness is variable?

ln 125-126: While I understand how some features, like ribosomes, proteasomes, and generic membrane compartments could be identified, it is unclear to me how one would recognize the nucleus when inside the PT, nor are any examples shown. If the data is clear, perhaps the authors could show it in a figure? Otherwise, I suggest removing the claim regarding the nucleus.

The arrangement of the ribosomes in a subset of tubes is really fascinating! While the number of observations is relatively small (n=5), it seems like it should be possible to comment preliminarily on whether there is much variability in their helical arrangement. Do the helical parameters vary much between observations? Does the til, pitch, etc vary much, are the 5 occurrences very similar? Is there any sign that they are associated with a membrane? Also, since the ribosomes form a lattice-like arrangement, it seems like it would be possible to trace ribosome helices in both the left and right handed directions. How did the authors decide between the two possibilities? This doesn't seem to be discussed.

Fig. 2e: Are the two different colors/orientations meant to represent the two protamers of the ribosome dimer? When refined subvolumes are mapped back onto the original tomogram do the authors observe a similar crystalline arrangement of particles as in their segmentation? Are the orientations of the ribosomes correlated, and do the provide any evidence for the dimeric arrangement mentioned? The PlaceObjects plugin for Chimera can be very helpful for visualizing this: https://www.biochem.mpg.de/7939908/Place-Object

Supp figure 4(b-d): Perhaps these models could be colored by pLDDT scores (with a key indicating the color scheme), so the reader can assess the quality of the predictions?

How were the measurements of the membrane thickness and putative PTP layer carried out? On the tomogram projections? STAs? How were the boundaries of the layers established (e.g., map threshholding if STA?)? This information appears to be missing from the methods.

Some tubes that are labeled as 'PTempty' actually contain cargo and look dense (example supp. Fig 2c, left and middle panels). Is it fair to classify these as empty tubes?

Fig. 3d: I am not entirely clear on what is being shown here. Are independent reconstructions of PTcargo and PTempty superposed (aligned on membrane)? The description in the figure legend doesn't clearly say what is being displayed. I think it might be more clear to show these side-by-side instead of superposed (i.e., 4 panels instead of 2).

Sup Fig 1: Define S and SP in legend or just spell out on figure? Missing x-axis label on panel b.

Fig. 4b and Sup Fig 2a: The depictions of the PT in the spore here are left-handed. In a few species, the coil of the PT was found to form a right-handed helix (Jaroenlak, et al.), and it seems plausible that this may be a general feature that would be conserved across microsporidia. I appreciate that it might not be actually known to be right-handed in V. necatrix, but if there is no strong data either way, perhaps it would make sense for these depictions of the PT to be right-handed.

I think all three of us are more or less in consensus about this manuscript, and I largely agree with the other reviewers comments. I think after addressing reviewer suggestions, this will be a pretty nice story.

Significance

Overall, this manuscript from Sharma, et al. presents interesting new findings about the structure and cargo transport function of the microsporidian PT. Microsporidia infect a wide range of hosts, including humans, and how the PT mediates parasite entry into cells is poorly understood. The approaches used in this study are appropriate for tackling the questions at hand, and appear to be generally well executed and interpreted. The observation that ribosomes assemble into an array within the PT is very unexpected and quite fascinating, and may be of broader interest to researchers working on ribosome structure and function, in addition to researchers studying microsporidia. The approach to investigating proteins interacting with PTP3 was quite elegant, and yielded a list of potential interactors that appears to be of very high quality and is highly plausible based on the literature field. We think this work is a substantial advance in the field and provides important new insights into the organization of the PT. - Please define your field of expertise with a few keywords to help the authors contextualize your point of view:

Structural biology, microsporidia - Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

We are not experts in proteomics/mass spectrometry

reply to u/Wooden-School-4091 at https://www.reddit.com/r/Zettelkasten/comments/172ujnk/should_i_use_zettelkasten/

This comes up fairly frequently. See https://hypothes.is/users/chrisaldrich?q=tag%3A%27zettelkasten+for+studying%27 and related links for other variations and advice on this theme.

ja. fehler:

In Bayern hat sich eine konservative Mehrheit gebildet, die 67,4 Prozent der abgegebenen Stimmen erhalten hat: CSU (die Union wird hier mitgerechnet unter zumindest potentiell noch konservativ, die Red.), Freie Wähler und AfD.

die einzige "konservative" partei ist die AFD, alle anderen sind betrüger ("conservatives in name only").

aber die AFD war noch nie teil einer regierung, sonst würde man sehen: auch die AFD kann nichts ändern, weil alle entscheidungen kommen von oben, und politiker verkaufen diese entscheidungen nach unten, wie in einer dauerwerbesendung. deswegen, auch die AFD ist nur "controlled opposition".

wenn politiker wirklich mal rebellieren gegen "oben", dann wird die zentralbank einfach die geldzahlungen einstellen, und am nächsten tag ist die regierung pleite. schon heute sind alle regierungen pleite, und leben von kredit von der zentralbank.

Gebt mir die Kontrolle über die Währung einer Nation, und es ist mir gleichgültig, wer die Gesetze macht.

-- Amschel Mayer Rothschild

deswegen: politik ist zeitverschwendung. aktivismus heisst selbsthilfe, selbstorganisation, kleinstaaten.

Reviewer #1 (Public Review):

Summary:<br /> Cincotta et al set out to investigate the presence of glucocorticoid receptors in the male and female embryonic germline. They further investigate the impact of tissue-specific genetically induced receptor absence and/or systemic receptor activation on fertility and RNA regulation. They are motivated by several lines of research that report inter and transgenerational effects of stress and or glucocorticoid receptor activation and suggest that their findings provide an explanatory mechanism to mechanistically back parental stress hormone exposure-induced phenotypes in the offspring.

Strengths:<br /> - A chronological immunofluorescent assessment of GR in fetal and early life oocyte and sperm development.<br /> - RNA seq data that reveal novel cell type specific isoforms validated by q-RT PCR E15.5 in the oocyte.<br /> - 2 alternative approaches to knock out GR to study transcriptional outcomes. Oocytes: systemic GR KO (E17.5) with low input 3-tag seq and germline-specific GR KO (E15.5) on fetal oocyte expression via 10X single cell seq and 3-cap sequencing on sorted KO versus WT oocytes - both indicating little impact on polyadenylated RNAs<br /> - 2 alternative approaches to assess the effect of GR activation in vivo (systemic) and ex vivo (ovary culture): here the RNA seq did show again some changes in germ cells and many in the soma.<br /> - They exclude oocyte-specific GR signaling inhibition via beta isoforms.<br /> - Perinatal male germline shows differential splicing regulation in response to systemic Dex administration, results were backed up with q-PCR analysis of splicing factors.

Weaknesses:<br /> - The presence of a protein cannot be entirely excluded based on IF data (staining of spermatids is referred to but not shown).<br /> - The authors do not consider post-transcriptional level a) modifications also trigged by GR activation b) non-coding RNAs (not assessed by seq).<br /> - Sequencing techniques used are not total RNA but either are focused on all polyA transcripts (10x) or only assess the 3' prime end and hence are not ideal to study splicing, The number of replicates in the low input seq is very low and hence this might be underpowered. Since Dex treatment showed some (modest) changes in oocyte RNA - effects of GR depletion might only become apparent upon Dex treatment as an interaction.<br /> - Effects in oocytes following systemic Dex might be indirect due to GR activation in the soma.<br /> - Even though ex vivo culture of ovaries shows GR translocation to the nucleus it is not sure whether the in vivo systemic administration does the same.

The conclusion that fetal oocytes are "intrinsically buffered to GR signalling" is very strong, given that "only" poly A sequencing and few replicates of 3-prime sequencing have been analyzed and information is lacking on whether GR is activated in germ cells in the systemically dex-injected animals.

This work is a good reference point for researchers interested in glucocorticoid hormone signaling fertility and RNA splicing. It might spark further studies on germline-specific GR functions and the impact of GR activation on alternative splicing.

While the study provides a characterization of GR and some aspects of GR perturbation, and the negative findings in this study do help to rule out a range of specific roles of GR in the germline, there is still a range of other potential unexplored options. The introduction of the study eludes to implications for intergenerational effects via epigenetic modifications in the germline, however, it does not mention that the indirect effects of reproductive tissue GR signaling on the germline have indeed already been described in the context of intergenerational effects of stress. Also, the study does not assess epigenetic modifications.

The conclusion that the persistence of a phenotype for up to three generations suggests that stress can induce lasting epigenetic changes in the germline is misleading. For the reader who is unfamiliar with the field, it is important to define much more precisely what is referred to as "a phenotype". Furthermore, this statement evokes the impression that the very same epigenetic changes in the germline have been observed across multiple generations.

The evidence of the presence of GR in the germline is also somewhat limited - since other studies using sequencing have detected GR in the mature oocyte and sperm.

The discussion ends again on the implications of sex-specific differences of GR signaling in the context of stress-induced epigenetic inheritance. It states that the observed differences might relate to the fact that there is more evidence for paternal lineage findings, without considering that maternal lineage studies in epigenetic inheritance are generally less prevalent due to some practical factors - such as more laborious study design making use of cross-fostering or embryo transfer. Since the authors comment on RNA-mediated inheritance it seems inevitable to again consider indirect effects.

The impact of free international financial markets on East Asia, as viewed through the lens of this section's framework, is complex. On one hand, these markets have stimulated economic growth in the region by facilitating investment and access to global capital, which has the potential to positively affect individuals' financial wealth and physical assets. However, the benefits have not been equally distributed, contributing to growing income disparities. According to SSRN, "growth-promoting economic freedoms hamper future progress by raising inequalities." The disparities are rooted in differences in education, gender, and social class, influenced by institutions and technology.

Therefore, while free international financial markets have brought economic opportunities to East Asia, they have also exacerbated income inequality, highlighting the need to address these disparities by considering the interplay between institutions, technology, and individual endowments to achieve a more balanced outcome in the region.

Works Cited: Ilkay Yılmaz , Mehmet Murat Balkan , Mehmet Nasih Tağ Income Inequality and Economic Freedom: The 2000s

$18 /LOC

Author Response

Reviewer #1 (Public Review):

The manuscript by Royall et al. builds on previous work in the mouse that indicates that neural progenitor cells (NPCs) undergo asymmetric inheritance of centrosomes and provides evidence that a similar process occurs in human NPCs, which was previously unknown.

The authors use hESC-derived forebrain organoids and develop a novel recombination tag-induced genetic tool to birthdate and track the segregation of centrosomes in NPCs over multiple divisions. The thoughtful experiments yield data that are concise and well-controlled, and the data support the asymmetric segregation of centrosomes in NPCs. These data indicate that at least apical NPCs in humans undergo asymmetric centrosome inheritance. The authors attempt to disrupt the process and present some data that there may be differences in cell fate, but this conclusion would be better supported by a better assessment of the fate of these different NPCs (e.g. NPCs versus new neurons) and would support the conclusion that younger centriole is inherited by new neurons.

We thank the reviewer for their supportive comments (“…thoughtful experiments yield data that are concise and well-controlled…”).

Reviewer #2 (Public Review):

Royall et al. examine the asymmetric inheritance of centrosomes during human brain development. In agreement with previous studies in mice, their data suggest that the older centrosome is inherited by the self-renewing daughter cell, whereas the younger centrosome is inherited by the differentiating daughter cell. The key importance of this study is to show that this phenomenon takes place during human brain development, which the authors achieved by utilizing forebrain organoids as a model system and applying the recombination-induced tag exchange (RITE) technology to birthdate and track the centrosomes.

Overall, the study is well executed and brings new insights of general interest for cell and developmental biology with particular relevance to developmental neurobiology. The Discussion is excellent, it brings this study into the context of previous work and proposes very appealing suggestions on the evolutionary relevance and underlying mechanisms of the asymmetric inheritance of centrosomes. The main weakness of the study is that it tackles asymmetric inheritance only using fixed organoid samples. Although the authors developed a reasonable mode to assign the clonal relationships in their images, this study would be much stronger if the authors could apply time-lapse microscopy to show the asymmetric inheritance of centrosomes.

We thank the reviewer for their constructive and supportive comments (“…the study is well executed and brings new insights of general interest for cell and developmental biology with particular relevance to developmental neurobiology….”). We understand the request for clonal data or dynamic analyses in organoids (e.g., using time-lapse microscopy). We also agree that such data would certainly strengthen our findings. However, as outlined above (please refer to point #1 of the editorial summary), this is unfortunately currently not feasible. However, we have explicitly discussed this shortcoming in our revised manuscript and why future experiments (with advanced methodology) will have to do these experiments.

Reviewer #3 (Public Review):

In this manuscript, the authors report that human cortical radial glia asymmetrically segregates newly produced or old centrosomes after mitosis, depending on the fate of the daughter cell, similar to what was previously demonstrated for mouse neocortical radial glia (Wang et al. 2009). To do this, the authors develop a novel centrosome labelling strategy in human ESCs that allows recombination-dependent switching of tagged fluorescent reporters from old to newly produced centrosome protein, centriolin. The authors then generate human cortical organoids from these hESCs to show that radial glia in the ventricular zone retains older centrosomes whereas differentiated cells, i.e. neurons, inherit the newly produced centrosome after mitosis. The authors then knock down a critical regulator of asymmetric centrosome inheritance called Ninein, which leads to a randomization of this process, similar to what was observed in mouse cortical radial glia.

A major strength of the study is the combined use of the centrosome labelling strategy with human cortical organoids to address an important biological question in human tissue. This study is similarly presented as the one performed in mice (Wang et al. 2009) and the existence of the asymmetric inheritance mechanism of centrosomes in another species grants strength to the main claim proposed by the authors. It is a well-written, concise article, and the experiments are well-designed. The authors achieve the aims they set out in the beginning, and this is one of the perfect examples of the right use of human cortical organoids to study an important phenomenon. However, there are some key controls that would elevate the main conclusions considerably.

We thank the reviewer for their overall support of our findings (“..authors achieve the aims they set out in the beginning, and this is one of the perfect examples of the right use of human cortical organoids to study an important phenomenon…”). We also understand the reviewer’s request for additional experiments/controls that “…would elevate the main conclusions considerably.”

1) The lack of clonal resolution or timelapse imaging makes it hard to assess whether the inheritance of centrosomes occurs as the authors claim. The authors show that there is an increase in newly made non-ventricular centrosomes at a population level but without labelling clones and demonstrating that a new or old centrosome is inherited asymmetrically in a dividing radial glia would grant additional credence to the central conclusion of the paper. These experiments will put away any doubt about the existence of this mechanism in human radial glia, especially if it is demonstrated using timelapse imaging. Additionally, knowing the proportions of symmetric vs asymmetrically dividing cells generating old/new centrosomes will provide important insights pertinent to the conclusions of the paper. Alternatively, the authors could soften their conclusions, especially for Fig 2.

We understand the reviewer’s request. As outlined above (please refer to point #1 of the editorial summary), we had tried previously to add data using single cell timelapse imaging. However, due to the size and therefore weakness of the fluorescent signal we had failed despite extensive efforts. According to the reviewer’s suggestion we have now explicitly discussed this shortcoming and softened our conclusions.

2) Some critical controls are missing. In Fig. 1B, there is a green dot that does not colocalize with Pericentrin. This is worrying and providing rigorous quantifications of the number of green and tdTom dots with Pericentrin would be very helpful to validate the labelling strategy. Quantifications would put these doubts to rest. Additionally, an example pericentrin staining with the GFP/TdTom signal in figure 4 would also give confidence to the reader. For figure 4, having a control for the retroviral infection is important. Although the authors show a convincing phenotype, the effect might be underestimated due to the incomplete infection of all the analyzed cells.

We have included more rigorous quantifications in our revised manuscript.

For Figure 1: There are indeed some green speckles that might be misinterpreted as a green centrosome. However, the speckles are usually smaller and by applying a strict size requirement we exclude speckles. To check whether the classifier might interpret any speckles as centrosomes, we manually checked 60 green “dots” that were annotated as centrosome. From these images all green spots detected as centrosome co-localized with Pericentrin signal (Images shown in Author response image 1).

For Figure 4: as we are comparing cells that were either infected with a retrovirus expressing scrambled or Ninein-targeting shRNA we compare cells that experienced a similar treatment. Besides that, only cells infected with the virus express Cre-ERT2 whereby only the centrosomes of targeted cells were analyzed. Accordingly, we only compare cells expressing scrambled or Ninein-targeting shRNA, all surrounding “wt” cells are not considered.

Author response image 1.

Pictures used to test the classifier. Each of the green “dots” recognized by the classifier as a Centriolin-NeonGreen-containing centrosome (green) co-localized with Pericentrin signal (white).

3) It would be helpful if the authors expand on the presence of old centrosomes in apical radial glia vs outer radial glia. Currently, in figure 3, the authors only focus on Sox2+ cells but this could be complemented with the inclusion of markers for outer radial glia and whether older centrosomes are also inherited by oRGCs. This would have important implications on whether symmetric/asymmetric division influences the segregation of new/old centrosomes.

That is an interesting question and we do agree that additional analyses, stratified by ventricular vs. oRGCs would be interesting. However, at the time points analysed there are only very few oRGCs present (if any) in human ESC-derived organoids (Qian et al., Cell, 2016). However, we have now added this point for future experiments to our discussion.

Reviewer #1 (Public Review):

The manuscript by Royall et al. builds on previous work in the mouse that indicates that neural progenitor cells (NPCs) undergo asymmetric inheritance of centrosomes and provides evidence that a similar process occurs in human NPCs, which was previously unknown.

The authors use hESC-derived forebrain organoids and develop a novel recombination tag-induced genetic tool to birthdate and track the segregation of centrosomes in NPCs over multiple divisions. The thoughtful experiments yield data that are concise and well-controlled, and the data support the asymmetric segregation of centrosomes in NPCs. These data indicate that at least apical NPCs in humans undergo asymmetric centrosome inheritance. The authors attempt to disrupt the process and present some data that there may be differences in cell fate, but this conclusion would be better supported by a better assessment of the fate of these different NPCs (e.g. NPCs versus new neurons) and would support the conclusion that younger centriole is inherited by new neurons.

Reviewer #2 (Public Review):

Royall et al. examine the asymmetric inheritance of centrosomes during human brain development. In agreement with previous studies in mice, their data suggest that the older centrosome is inherited by the self-renewing daughter cell, whereas the younger centrosome is inherited by the differentiating daughter cell. The key importance of this study is to show that this phenomenon takes place during human brain development, which the authors achieved by utilizing forebrain organoids as a model system and applying the recombination-induced tag exchange (RITE) technology to birthdate and track the centrosomes.

Overall, the study is well executed and brings new insights of general interest for cell and developmental biology with particular relevance to developmental neurobiology. The Discussion is excellent, it brings this study into the context of previous work and proposes very appealing suggestions on the evolutionary relevance and underlying mechanisms of the asymmetric inheritance of centrosomes. The main weakness of the study is that it tackles asymmetric inheritance only using fixed organoid samples. Although the authors developed a reasonable mode to assign the clonal relationships in their images, this study would be much stronger if the authors could apply time-lapse microscopy to show the asymmetric inheritance of centrosomes.

Homeless people are actually getting their basic necessities covered and it helps with better hygiene that other people living in those cabins and camps desperately needed.

Author Response

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

We thank the reviewers for their thoughtful assessment of our work and their valuable critiques which we will address in the “Recommendations for the authors” section below. In particular, we appreciate Reviewer #3 noting the value of the C. elegans model system and our efforts to bridge models with our study. We agree with the reviewer that there is a need to clarify the rationale, presentation and interpretation of our results. We have substantially revised the text in our manuscript and Figure legend to address this issue, and provided extensive new commentary and citations to lay out the logic behind our experiments. Indeed, it was our oversight not being more thorough about this initially. We have further adjusted our conclusions to be less unequivocal. Finally, we added an RPM-1 signaling diagram (Fig. 8A) to more clearly annotate the players in the RPM-1/MYCBP2 signaling network that were evaluated genetically in Fig. 8. Importantly, we provide clearer commentary on how genetic enhancer effects with known RPM-1 binding proteins and the absence of genetic suppression in vab-1/Eph receptor double mutants with components of the RPM-1/FSN-1 ubiquitin ligase complex are consistent with the biochemical finding that MYCBP2 stabilizes but does not degrade EphB2. Text edits reflecting these points are in the abstract, the C. elegans results section starting on line 411, and the discussion on lines 499, 502-504 and 541.

Following extensive discussions between the three reviewers, all three agree that the C. elegans data, as presented, does not add to, and in fact might harm, your bottom line. Our combined suggestion is to take this data out unless you plan to improve it substantially. All reviewers are perplexed by Figure 2F and the presumed interactions of cytosolic proteins with the extracellular domain of EPHB2. At the very least, please provide some suggestions/model/interpretation.

We have adjusted our manuscript substantially to address this. Please see detailed comments in the individual Reviewer sections below.

We would like to thank the reviewers for their thorough examination of our manuscript, constructive criticisms, and helpful suggestions.

Reviewer #1 (Recommendations For The Authors):

The work is extensive in my view, and mostly of high quality. See minor comments on some of the figures below.

Thank you very much.

Two more major comments :

• I don't think the C. elegans work adds to - in fact I think it hurts - the statement that this regulatory mechanism is specific to EphB2. I would advise the authors to take it out.

We agree that C. elegans has a sole Eph receptor called VAB-1 and is therefore not a specific model for EPH2B. However, testing MYCBP2 specificity for EPHB2 was not the goal or our perceived value for the C. elegans experiments. We now clarify this in the text of the Results section.

Rather, we are providing evidence that the C. elegans ephrin receptor interacts genetically with known MYCBP2/RPM-1 binding proteins. Moreover, we now provide an extensive array of citations to note that genetic enhancer interactions between different RPM-1/MYCBP2 binding proteins is well established. The reviewer has nicely highlighted for us that we handled the C. elegans genetics in too cursory a fashion in our original manuscript. We appreciate this being noted and have now aimed to make this substantially clearer. We hope the reviewer agrees that our revised C. elegans section accomplishes this goal.

Furthermore, we extensively revised the text of the Results to emphasize a key point: our observation that axon termination defects are not suppressed in vab-1; fsn-1 and vab-1; rpm-1 double mutants excludes the possibility that the VAB-1 Eph receptor is a substrate that is inhibited or degraded by the RPM-1/FSN-1 ubiquitin ligase complex. If the VAB-1 Eph receptor were ubiquitinated and degraded by the RPM-1/FSN-1 complex, we would have observed a suppression of phenotype in vab-1; rpm-1 double mutants. The precedent for this genetic relationship between the RPM-1 ubiquitin ligase and its substrates that are degraded has been established by several prior studies (PMID: 15707898; PMID: 31676756; PMID: 35421092). We now more clearly note that the absence of genetic suppression in vab-1; rpm-1 double mutants and vab-1; fsn-1 double mutants is consistent with the non-canonical stabilizing role of MYCBP2 on EPHB2 that was observed in our biochemical experiments with mammalian cells.

We also adjusted the text of the manuscript to stress that we are testing genetic interactions between the VAB-1 Eph receptor and known RPM-1 binding proteins. This is a key point, as genetic enhancer interactions are consistent with the Eph receptor functioning in the RPM-1 signaling network. This concept has been well established for RPM-1 binding proteins as now noted in our revised text with an extensive number of additional citations to published work.

Based on the above arguments, we respectfully disagree with the reviewer that our C. elegans data should be removed from the paper. To re-iterate, we are not trying to evaluate specificity for MYCBP2 and EPHB2 in C. elegans. Rather, our goals are twofold: 1) To ask whether there is an evolutionarily conserved functional genetic link between Eph receptors and known RPM-1 binding proteins. 2) To provide further in vivo genetic evidence invalidating the hypothesis that Ephrin receptors could be ubiquitination substrates that are inhibited/degraded by MYCBP2.

Text edits reflecting these points are in the abstract, the C. elegans results section starting on line 411, and the discussion on lines 499, 502-504 and 541.

• The cellular responses are not robust and the effects of MYCBP2 KO - although significant - are minor in most cases. But I don't think more experiments will help here.

We interpret the comment about the robustness to mean that the extent to which a given cellular response is affected by the loss of MYCBP2 is minor. First, the cellular responses themselves are typical of previous studies and depend on the cellular biology underlying them. For example, a growth collapse of ~50-60% over a background of 10% (Fig. 7) is typical for these sorts of assays (PMID: 37369692; PMID: 33972524; PMID: 17785182). A decrease of cell area by ~25% (Fig. 3) is quite substantial if one considers how much of a cell’s volume is taken up by the nucleus and organelles. Second, the phenotypes elicited by the loss of MYCBP2 are likely brought on by a decrease in EphB2 protein levels, but not its complete absence, as suggested by our biochemical experiment. Given that EphB2 complete loss only affects the cellular responses to a limited extent, the minor effects are not a surprise (e.g. for GC collapse: PMID: 23143520). Nevertheless, the subtle changes in cellular phenotypes, elicited by EPHB2 signaling are often sufficient to achieve proper cell positioning and cell response to guidance cues. For instance, regulation of the growth cone collapse of the outgrowing axons requires delicate changes that are dynamic and temporal.

Minor:

Fig 1C - EPHA3 and EPHB2 seem to run in different sizes, is this the case? In 2A they run at the same size.

We believe this size discrepancy is due to different percentages of SDS-PAGE gels used to resolve proteins. In Fig. 1C, we used a 6% gel for a Western blot analysis of both EPHA3/-B2-FLAG (~130 kDa) and MYCBP2 (~510 kDa). In Fig. 2A however, we performed Western blot analysis using 10% resolving gel to separate and detect EPHA3/-B2-FLAG along with MYC-FBXO45 (~30 kDa). We have reviewed the results obtained from additional biological replicates of this experiment, and observed a similar pattern in gel migration of EPHA3/-B2-FLAG across all replicates.

Fig1F - I can't trust the MYCBP2 blot.

Indeed, the MYCBP2-EPHB2 co-IP with endogenous proteins was not convincing. We now repeated this experiment using rat cortical neurons, and the results replace the previous Fig. 1F panel as mentioned on line 158.

In Fig2b the authors claim that there is enhancement in the binding of MYCBP2 and EPHB2 upon FBXO45 expression. For this type of statement quantification is required.

The quantification is now included in Fig. 2C and its significance is mentioned on line 180. Our conclusion about the enhancement stands.

Fig2G - it remained unclear to me where the binding site to MYCBP2 is, how long is the cytoplasmic tail in the DeltaICD protein?

Based on our experimental observations from Fig. 2E-H, we concluded that the fragment encompassing the extracellular domain(s) and/or transmembrane (TM) domain of EPHB2 is necessary for the protein complex formation with MYCBP2. We would like to accentuate that the EPHB2-MYCBP2 interaction might not be direct, and might involve other transmembrane protein(s) acting as a scaffold for EPHB2 and MYCBP2 binding. We did not pursue experiments to determine the exact region of the extracellular-TM portion of EPHB2 that is required for the interaction with MYCBP2.

The cytoplasmic tail in ΔICD protein consists of 25 aa of the N-terminal fragment of EPHB2 juxtamembrane (JM) region, which is adjacent to the TM helix, and followed by the 8 aa FLAG tag (EPHB2 ΔICD domain composition: extracellular domains – TM domain – 25 aa fragment of JM region – FLAG). We have determined the TM and JM sequences based on Hedger et al. (PMID: 25779975) and included the N-terminal portion of the JM region to facilitate proper ΔICD protein localization within the plasma membrane (PMID: 35793621). We modified the schematic in Fig. 2G to better visualise the EPHB2 truncations and now provide information on their size in the figure legend.

Always good to have a model of how all these proteins work together.

While we acknowledge that this would be helpful, we do not have a clear answer on how the EPHB2-MYCBP2 complex formation occurs. This requires further elucidation of the putative proteins involved in this ternary complex or testing the possibility that a MYCBP2 fragment is extruded extracellularly. Without these experiments there are too many possibilities to summarise into a clear model figure. We thus did not make any edits regarding these possibilities in the section starting on line 195.

Reviewer #2 (Recommendations For The Authors):

Overall, the experiments are classical experiments of co-immunoprecipitations, swapping experiments, collapse assays, and stripe assays which all are well carried out and are convincing.

Thank you for your encouraging comments.

Controls for the stripe assay may include Fc / Fc stripe assays.

We have performed these control experiments and now include their quantifications in the results sectioning concerning Fig. 3, starting on line 249, and those concerning Fig. 6 on line 381.

It is not clear to me why SD and not SEM has been used here for presentations.

Standard deviation (SD) measures the dispersion of a dataset relative to its mean. The standard error of the mean (SEM) measures how much discrepancy is likely in a sample’s mean compared with the population mean. Thus, SEM includes a statistical inference about the sampling distribution while SD is a less “processed” measurement that by definition is larger than SEM. SEM might make the data look less dispersed and many journals encourage the use of SD in bar graphs (PMID: 16223828).

Fig 7A: it is rather difficult to see 'branches' in Fig. 7A, better pictures and close-ups should be provided. How are branches defined? This piece of work needs more attention.

To remedy this shortcoming, we now provide inverted images with GFP signal in dark pixels overlaid on Fc (white) / eB2 (pink) stripes next to the original images.

Reviewer #3 (Recommendations For The Authors):

1) My most important suggestion to the authors would be to more carefully describe the results and their interpretation of the results. Sometimes, the distinction is not clear.

We modified the text throughout the manuscript to address this.

2) There are several cases, when the authors report on trends that are not statistically significant (1D, for example), or report no change, when it is clear that the addition of one more sample could have dramatically made a difference (4M - see point 12).

We agree that some of the nonsignificant differences could become significant if we added more Ns. But we prefer not to move our experimental design towards N-chasing and p-hacking (PMID: 25768323). The number of biological replicates is normally pre-determined before the onset of the experiment. Of course, some replicates can be discarded if there is a valid reason, such as a technical issue with the experiment or a positive control not working but this is not relevant for the dataset we have provided.

3) Data in 1F is very difficult to interpret.

As in response to Reviewer #1: Indeed, the MYCBP2-EPHB2 co-IP with endogenous proteins was not convincing. We now repeated this experiment using rat cortical neurons, and the improved results are in revised Fig. 1F.

4) Figure 2 puts Figure 1 in a strange perspective. If I understand correctly, fig 2 claims that EPHB2 interaction with MYCBP2 depends on FBXO45 - if that is the case then how does the binding in Figure 1 occur?

Indeed, we propose that the EPHB2-MYCBP2 interaction depends on FBXO45. In Fig. 2, we reveal that FBXO45 enhances the formation of the EPHB2-MYCBP2 complex. Thus, we suspect that the endogenous FBXO45 present in HeLa cells and neurons would mediate the interaction between EPHB2 and MYCBP2 in Fig. 1 experiments. We were unable to show this by Western blotting due to lack of reliable commercial antibodies against FBXO45, the complex containing endogenous FBXO45 and EPHB2 is also implied by our AP-MS data (Fig. 1B) and published databases.

5) I am still trying to wrap my mind around the results in 2G-H. So do MYCBP2 and FBXO45 bind the extracellular domain of EPHBP2? What does that mean?

(see also our response to Reviewer #1, end of their section) Based on our experimental observations from Fig. 2G-H, we conclude that the fragment encompassing the extracellular domain(s) and/or transmembrane domain of EPHB2 is necessary for the protein complex formation with MYCBP2 and FBXO45. Although there is a possibility that MYCBP2 directly binds the extracellular portion of EPHB2, we have not formally tested this hypothesis. MYCBP2 has been previously shown to interact with the extracellular portion of transmembrane N-cadherin (CDH2) via BioID proximity labeling and AP-MS proteomics approaches (PMID: 32341084).

Considering the results in Fig. 2A-B, we suspect that EPHB2-MYCBP2 interaction is indirect, as FBXO45 enhances this association. Secretion of FBXO45 and direct binding of FBXO45 to the extracellular cadherin (EC1-2) domains of N-cadherin has been documented (PMID: 25143387; PMID: 32341084). Although, not tested, this is also a possibility for EPHB2-FBXO45 mode of interaction. Nevertheless, we also cannot rule out the possibility that an unknown transmembrane protein binds EPHB2 extracellularly and the same unknown protein binds MYCBP2/FBXO45 intracellularly. Resolving this model is beyond the scope of this study and will require us to pursue extensive new lines of investigation.

6) I don't understand the stable Hela cell line CRISPR - is this a stable MYCBP2 deletion? In which case why is there only a reduction, not complete elimination of the protein? Or, is this a stable integration of a plasmid generating gRNA against MYCBP2? In which case, I would expect a homozygous null to emerge at some point. In any case, this is not well explained.

These lines are not derived from single cells infected with the CRISPR sgRNA-carrying viruses, therefore they are not clonal and probably contain some cells that express normal levels of MYCBP2, hence its detection on a Western. This is now clarified starting on line 221 and on line 608.

7) In 3C - is this the right statistical analysis?? I would say you want to claim the different effect of the control +/- eB2 compared to the effect in the mutant +/- eB2. Still should be significant but I think a more correct analysis.

We now include this comparison in Fig. 3C as well in the results section starting on line 234.

8) The robustness of the assay in Figure 3D is underwhelming – how was the area measured?

This is a live imaging experiment. Fig. 3D plots cell area at 60 minutes after ephrin-B2 addition as a fraction of the same cell’s area at 0 minutes (ephrin-B2 addition). For control cells that is a decrease of ~25%. If one considers that a cell’s nucleus and organelles like the Golgi Apparatus take up most of its volume, the magnitude is not that surprising.

9) Figure 3F – did you try to plot the relative area of overlap divided by the total cellular area? You might get a more striking phenotype. Also – claiming that this confirms that MYCBP2 is REQUIRED for EPHB2 function is a bit overstated, especially given that we don’t know (do you?) the EPHB2 mutant phenotype in this assay.

We preferred to stay with the original method of image quantification which we use for other assays. With respect to the requirement of MYCBP2 for EPHB2 function in the stripe assay, our logic is rooted in the observation that native HeLa cells do not respond to ephrin-B2 stripes (45.46 ± 7.62% of cells on eB2 stripes v. Fc; data not shown). When they are transfected with EPHB2 expression plasmids they do, therefore we assume that EPHB2 expression endows them with a sensitivity to eB2 stripes. A loss of MYCBP2 attenuates this sensitivity. We clarified this starting on line 246 and on line 251.

10) I didn't quite get the difference between 4A and 4B.

We apologize for the confusion. In Fig 4A, we used a stable HeLa cell line that has tetracycline-inducible expression of EPHB2-FLAG. Using these cells, we subsequently generated CTRLCRISPR or MYCBP2CRISPR cells. In these cells we then induced EPHB2 expression with tetracycline and observed that deletion of MYCBP2 resulted in the reduction of EPHB2 protein levels. To confirm this observation and to rule out the possibility that EPHB2 protein reduction is an effect of the CRISPR lines generation, we tested whereas MYCBP2 deletion reduces EPHB2, which has been transiently overexpressed (Fig. 4B). We hence conclude that loss of MYCBP2 decreases EPHB2 that was either expressed from a stable locus (Fig. 4A) or from transient transfection (Fig. 4B). We modified the Results section starting on line 262 to make this point clear.

11) The entire link to lysosomal degradation should be strengthened. Perhaps I am confused, but if the reduced EPHB2 levels in MYCBP2 mutant cells result from impaired lysosomal degradation then inhibiting the lys-deg should bring the protein levels back to normal (i.e. CRISPR control) - no? As currently presented, I do not understand nor do I think the claim is strongly supported by the data.

Before treatment with inhibitors, EPHB2 levels in MYCBP2CRISPR cells are already 40% lower than they are in CTRLCRISPR cells and in all our attempts, inhibitors can only rescue/restore EPHB2 in MYCBP2CRISPR cells to a level that is lower than in CTRLCRISPR cells. But this restoration is greater in MYCBP2CRISPR than in MYCBP2CTRL cells (BafA1: 19% increase in CTRL cells and 40% in MYCBP2CRISPR cells; CoQ: 10% comparing to 35%). This indicates that EPHB2 degradation through the lysosomal pathway in MYCBP2CRISPR cells is stronger, explaining why EPHB2 degradation is promoted in MYCBP2CRISPR cells, compatible with reduced EPHB2 levels and enhanced EPHB2 ubiquitination.

12) 4M, O - reporting ns based on these data seems a bit strange to me... Add one point and it will be strongly significant.

See our response to point (2), above. We prefer not to invoke potential p-hacking.

13) 7d - so what are you claiming? That the cellular response to eB1 but not eB2 is affected by the addition of FBD1? this is almost the opposite of what you wrote in the text...

We treated the cells with two different ephrin-B ligands to make a stronger conclusion. When using ephrin-B1, growth cone collapse in FBD1 WT is not significant comparing to Fc treatment. When using ephrin-B2, growth cone collapse in FBD1 WT is not as significant as it is in FBD1 mut group (* versus ). We interpret this as meaning that the EPHB2-mediated growth cone collapse to both ligands is dampened, when we disrupt the EPHB2-MYCBP2 association. The difference between these two ligands might be due to their different affinities for the receptor or signalling kinetics.

14) By far the weakest link in this paper is the worm part. I think it's a pity because strengthening this would affect the significance of the finding. First, the authors mention new genes without introducing their relationship to the signaling pathway tested. Second, the textual logics should be strengthened. Finally and most importantly, when the difference between the phenotypic severity is so strong (vab-1 and rpm-1) then I think it's impossible to say anything from the double mutant.

We appreciate the reviewer noting that they appreciate the value and importance of the C. elegans model. The goals of our C. elegans experiments were twofold:

1) To evaluate genetic interactions between the VAB-1 Eph receptor and known RPM-1 binding proteins. This was not clearly explained in the original manuscript nor was the published precedent for these types of genetic enhancer experiments provided. We have now rectified this by substantially revising the text of the Results C. elegans section starting on line 431 and by adding several citations.

2) Our C. elegans genetics confirmed that the VAB-1 Eph receptor is not inhibited/degraded by the RPM-1/MYCBP2 ubiquitin ligase complex. We have now revised the text to draw this point out more clearly.

To further address the reviewer’s concerns, we have added a new schematic (Fig. 8A) to show the relationship between the RPM-1 and the RPM-1 binding proteins (FSN-1/FBXO45 and GLO-4/SERGEF) we are testing. We chose FSN-1 because it is part of the RPM-1 ubiquitin ligase complex and we chose GLO-4 because it functions outside the context of RPM-1 ubiquitin ligase signaling via the GLO-1 Rab GTPase to influence late endosomal/lysosomal biogenesis.

Regarding the reviewer’s concern that different penetrance/frequency of defects between rpm-1 mutants and vab-1 mutants means outcomes with vab-1; rpm-1 double mutants cannot be interpreted. We respectfully disagree. An extensive number of published studies have demonstrated that RPM-1 binding proteins have milder phenotypes than rpm-1 mutants and display genetic enhancer effects as double mutants with one another (PMID:17698012, PMID: 22357847, PMID: 25010424, PMID: 24810406). We now make this point much more clearly. While the frequency of axon termination defects in rpm-1 mutants is high it is not completely saturated as the defect is not 100%. Moreover, a major point of the vab-1; rpm-1 double mutants is that they do not have a significant reduction in phenotypic penetrance/frequency. Thus, our system is fully capable of resolving genetic suppression, which did not occur. We now make this point much more carefully and clearly.

To further address the reviewer’s concern, we have softened language about the VAB-1/Eph receptor functioning in the same pathway as RPM-1 throughout the manuscript. While we think this is still the case, because the frequency of axon termination defects is not fully saturated in rpm-1 mutants and defects could potentially become more severe (i.e. the hook might occur closer to the head of the animal rather than in the midbody). Nonetheless, this is not a critical point and we think it is more important to be clear about the two major goals and objectives of our C. elegans experiments. We hope the reviewer agrees that our rationale, logic and conclusions are more clearly and accurately drawn in the revised paper.

• for: BEBE, biologger Ethogram Benchmark

该接口返回当前活动文件内容

We have to admit that people nowadays cannot live without social media. Living in 2023, I believe that social media is no longer a tool to communicate, it is becoming more and more diverse and combines all kinds of functions such as a platform to show people "who they are". I know too many people who are social phobias but are a "stars" on social media. Back then, people like them would be judged as "people who don't live on the Internet", however, no one would tag them as "strange" anymore. Therefore, yes, social media has been included in real life and is making real life better and more diverse.

reply to u/RobThomasBouchard at https://www.reddit.com/r/antinet/comments/16v8tfq/starting_a_blog/

The answer is:<br /> D: Start a "blog" where you post your notes as status updates and interlink them a bit. When you've got enough, you organize them into a mini thesis and write a longer article/blog post about it.

Examples: - https://hypothes.is/users/chrisaldrich?q=tag%3A%22thought%20spaces%22 and - https://indieweb.org/commonplace_book#The_IndieWeb_site_as_a_Commonplace_book

tl;dr: Use your website like a public, online zettelkasten. 🕸️🗃️

test

With the introduction of deepfakes into society it is very important that online users educate themselves on how to properly spot these videos. It would be nice if platforms could tag these videos with warnings but since most don't, it is crucial to fact check each piece of content that may seem suspicious.

this I don't quite understand

Jerry Michalski says that The Brain provides him with a "neighborhood perspective" of ideas when he reduces the external link number for his graph down to 1.

This is similar to Nicholas Luhmann's zettelkasten which provided neighborhoods of related notes based on distance from any particular note.

Also similar to oral cultures who relied on movement through their environment for encoding memories and later remembering them. [I'll use the tag "environmental memory" to track this until a better name comes along.]

reply to u/JonasanOniem at https://www.reddit.com/r/Zettelkasten/comments/16ss0yu/linking_new_notes/

This sort of practice is harder when you start out in most digital apps because there is usually no sense of "closeness" of ideas in digital the way that is implied by physical proximity (or "neighborhood") found in physical cards sitting right next to or around each other. As a result, you have to create more explicit links or rely on using tags (or indexing) when you start. I've not gotten deep into the UI of Zettlr, but some applications allow the numbering (and the way numbered ideas are sorted in the user interface) to allow this affordance by creating a visual sense of proximity for you. As you accumulate more notes, it becomes easier and you can rely less on tags and more on direct links. Eventually you may come to dislike broad categories/tags and prefer direct links from one idea to another as the most explicit tag you could give a note . If you're following a more strict Luhmann-artig practice, you'll find yourself indexing a lot at the beginning, but as you link new ideas to old, you don't need to index (tag) things as heavily because the index points to a card which is directly linked to something in the neighborhood of where you're looking. Over time and through use, you'll come to recognize your neighborhoods and the individual "houses" where the ideas you're working with all live. As an example, Luhmann spent his life working in sociology, but you'll only find a few links from his keyword register/subject index to "sociology" (and this is a good thing, otherwise he'd have had 90,000+ listings there and the index entry for sociology would have been utterly useless.)

Still, given all this, perhaps as taurusnoises suggests, concrete examples may help more, particularly if you're having any issues with the terminology/concepts or how the specific application affordances are being presented.

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:

1. If doable, image dynein and dynactin simultaneously in the Halo-DYNC1H1/DCTN4-SNAP iNeurons. Co-movement of dynein and dynactin towards the somatodendritic compartment and their separate movement in the anterograde direction along the axon would provide the most convincing evidence for the key claims of the manuscript.

Please see the planned revision section for our response

Reviewer #2:

Major comment (requires additional experimentation)

1. While the data presented do certainly suggest that dynein and Lis1 are transported anterogradely on separate vesicular cargoes from dynactin and Ndel1, the study would be much stronger if supported by dual imaging of dynein and dynactin to prove that these proteins do indeed move in association with separate vesicular populations. I would like to see dual-color kymograph traces showing that the proteins move independently. The authors should be able to accomplish this using their dual Halo-DYNC1H1/DCTN4-SNAP hESC line. To acquire and analyze this data might take several months, but it would greatly strengthen this paper. If the authors do this experiment, they may also be able to address the mechanism of reversal of anterograde cargoes which they speculate about in the Discussion, which would add even more interest and insight.

Please see the planned revision section for our response

Minor comments (addressable without additional experimentation)

1. The authors deduce that 1-4 Halo fluorochromes corresponds to 1-2 dynein molecules. This implies that the cells are homozygous for the Halo tag, but I do not see this addressed explicitly. The authors should state explicitly whether the lines generated for their study are heterozygous or homozygous for the tag. If the cells are heterozygous, which would seem most likely, then they may be underestimating the number of dyneins per spot and should take this into account.

We have added whether lines are homozygous or heterozygous to the manuscript. We also include a new Supplementary Figure panel (Fig S6) showing the genotyping data. In summary, all lines are homozygous except for PAFAH1B1-Halo (hESCs) which is heterozygous.

1. Why are the moving spots lower in intensity than the NEM-treated static spots. It appears to suggest that they may be associated with different structures. This should be clarified and discussed.

Our data suggest that the fast-moving spots have fewer dyneins than NEM treated static spots. We suggest this is because the fast-moving cargos are smaller than the average cargo and therefore have fewer dyneins on them. This is also supported by the smaller number of dyneins reported previously on endosomes as compared to the large lysosomes. We have clarified this in the discussion (page 7-8).

1. The authors state in the Results that most of the dynein spots were diffusing, often along microtubules, but they do not visualize microtubules so how do they know this? They may need to remove the phrase "often along microtubules".

This has been removed.

1. At the end of the Introduction the authors state that their data "allow us to understand how the dynein machinery drives long-range transport in the axon". This is an overstatement. The "how" in this sentence is not addressed in this study.

We have softened the sentence by adding the phrase “better understand”.

1. The conclusion that dynein binds to cargos stably throughout their transport along the axon is based on measurements of the fastest moving cargoes but the authors do not provide data on the distribution of velocities for the entire population of retrograde cargoes. It is not valid to extrapolate the behavior of a small number of cargoes to the entire population. The average may be much slower than the fastest cargoes. Moreover, even for the fastest organelles the authors cannot say that the dynein is stably bound because they did not track single cargoes and thus do not know that the cargoes moved continuously in one single bout of movement for 500 µm; it is possible that the cargoes moved in multiple consecutive bouts interrupted by brief pauses and dynein motors may have exchanged between bouts.

We have added a section to the discussion to highlight that other cargos may behave differently from the fastest ones (page 7). We have also clarified the assumptions that lead us to expect a slower arrival time of the first signal (page 5).

1. The authors say that "it is clear that at least some dyneins remain on cargoes throughout their transport along the axon". As explained above, the data do not prove this so this statement should be removed.

We have softened this sentence from “it is clear” to “our results suggest” and explained in more detail why we make this conclusion

1. The authors note that most of the dynein spots were not moving processively and state that this is consistent with prior studies showing that only a subset of dynein is actively involved in transport. However, as they note elsewhere, dynein is both motor and cargo and most axonal dynein is transported at slow average velocities so maybe they should be more explicit about what they mean by "involved in transport".

We have clarified we mean fast axonal transport and thank the reviewer for highlighting this point.

1. When the authors note that most of the dynein in axons is transported in the slow component of axonal transport, they should also cite the work of Pfister and colleagues who were the first to show this (PMID 8824315 and 8552592).

This was an omission on our part. The references have now been added.

1. The authors propose that dynein and Lis1 are transported together but there were significantly fewer anterogradely transported Lis1 particles than dynein particles. This should be discussed.

We have added more information to the discussion. Although we cannot rule out this effect being due to the heterozygous tagging of our LIS1 cell line, we do not witness the same decrease in events in the retrograde direction. Therefore, we believe there is a subset of anterogradely moving dynein lacking LIS1. As discussed in the manuscript, this subset may already be bound to dynactin and therefore not require LIS1.

1. For the statistical analysis, the authors should provide p values in the legends for the comparisons that are judged to be "not significant". The authors should also be consistent in how they label differences that are not significant - they mark them as "ns" in Fig. 1, but in the other figures they do not, leaving some ambiguity about whether particular comparisons were not tested or were found to be not significant. For example, in Fig. 4C the average speed of the dynactin is about 0.5 µm/s greater than for the other proteins and the spread in the data suggest that this could be significant, but no significance is indicated on the plot, implying p>0.05. It is not clear how confident we can be that there is no difference.

We have now included all p values in the figure legends and have removed the “ns” in Fig 1D. In our revised manuscript, only significant differences are highlighted in the figures.

Reviewer #3:

• if I look at the kymographs, trajectories appear rather complex, pausing, standing still, moving and everything mixed. The explanation of how actual trajectories are extracted and on what basis is very short, too short for me. I think the authors should expand this. Furthermore, I think it would be good if the authors would present, in their kymographs examples of the tracked (and also the not included) tracks. Maybe in supplementary info.

The analysis of this data used the Trackmate Fiji plugin. This tracks spots frame to frame in a movie and then outputs the data of the tracks. No data was extracted from kymographs but they were used as a graphical illustration of the moving spots. To better explain our analysis pipeline, we have expanded our methods section and have added an example of a tracked movie (Video 15) as well as highlighted the tracked spots in one kymograph example (Figure 7S).

• I found 'velocity' ill defined. I get the impression, judging from the number of points (compared to the other parameters) that the authors determine the average velocity of each individual trajectory. That is an important parameter (but should indeed be called 'trajectory averaged' velocity), but might not be the only one useful to learn from the data, where trajectories do not always appear to have constant speeds (pausing, etc.). Why do the authors not determine point-to-point velocities and plot histograms of those for all the trajectories (simply plot histograms of all the displacements between subsequent data points in trajectories)? This might provide great insight into the actual maximum velocity and the fraction of pausing or moving in opposite direction etc., providing much more molecular detail than currently extracted from the data.

The reviewer is correct. We have measured the average velocity of the spots from the beginning of the track to the end. We have clarified this in the text. Furthermore, as stated above in the revision plan, we are currently doing the additional analysis and will include it in the final revision

• I was a bit surprised to read that the authors have gone to the effort to create a dual-color labeled cell line, but did not do actual correlative two-color measurements (or at least show them). It would be so insightful to see dynein and dynactin move separately in the anterograde direction.

Please see the planned revision section for our response.