test annotation

Todos os leitores podem saltar de livro em livro, pois todos são livres de escolher aquilo que querem ler. Este facto, irá permitir que estes continuem a ler diferentes tipos de livros e a "mergulhar" em diferentes realidades, mesmo que seja por pouco tempo.

O direito da privacidade, é importante porque permite que os leitores tenham uma experiência de leitura mais pessoal e privada, que se sintam mais à vontade para explorar os seus próprios pensamentos e sentimentos sobre o que leram, e não se sentirem pressionados a se conformar com as opiniões dos outros. " Vive em sociedade porque é gregário, mas lê porque se sente só.", "E ninguém nos pede contas dessa intimidade"

Ler em voz alta permite que os leitores tenham uma experiência de leitura mais rica e gratificante, melhora compreensão do texto, aprofunda a sua conexão com o texto dando vida a ele, e compartilham a sua paixão pela leitura com os outros, promovendo a conexão e o diálogo entre os entusiastas da leitura. " O desaparecimento da leitura em voz alta é muito estranho", " O homem que lê em voz alta expõe-se em absoluto."

O direito de ler não importa onde é importante, pois o ato de ler é um ato em que não se necessita de ter um espaço próprio para o fazer, ou seja, o leitor pode escolher ler em qualquer lado em que se sinta confortável para o fazer.

O direito de saltar de livro em livro abre portas para que o leitor tenha a liberdade para escolher a sua leitura, abandonar livros que não esteja a gostar e concentrar o seu tempo que lhe proporcione mais prazer, resultando numa experiência de leitura mais satisfatória e evitar as frustrações. " .. «debicar» aqui e ali sem correr o mínimo risco de decepção"

Por um lado, amar dos "heróis" dos romances é importante por permitir ao leitor desenvolver uma "satisfação imediata e exclusiva" das suas próprias emoções. Por outro lado, este mesmo mesmo direito vai também permitir ao leitor recordar as suas primeiras emoções ao ler determinado romance, o que lhe irá permitir reconciliar-se com a sua adolescência.

O direito de ler não importa onde é porque permite que os leitores tenham liberdade e flexibilidade na sua experiência de leitura. Além disso, ter o direito de ler onde quer que esteja permite que os leitores escolham a maneira mais confortável de absorver o conteúdo.

Este direito é um direito importante, uma vez que permite a cada leitor encontrar o "direito de escrever o que .quiser" mas também de todos os leitores terem os "gostos que quiserem"

É importante amar os heróis da ficção, porque eles podem nos inspirar, permitir compreender melhor o mundo e criar um sentimento de felicidade ao identificarmos com eles. Embora que nem todos sejam perfeitos, as suas falhas podem ensinar lições valiosas sobre a humanidade e a complexidade dos relacionamentos.

O direito de ler sem restrições é um direito importante para o leitor, onde permite a exploração dos seus próprios interesses, o desenvolvimento do seu senso crítico e a diversão ao longo da leitura. "o direito de ler não importa o quê, sem restrições, sem censura, sem culpa" , "este direito é fundamental para a vida, à liberdade de pensamento e à imaginação".

Reler um livro, permite ao leitor explorá-lo sob uma nova perspectiva e descobrir novos significados, de que nas outras leituras não conseguiram identificar. Além disso, reler um livro amado pode proporcionar momentos agradáveis e relaxantes.

Realmente, é aceite que os leitores não consigam terminar um livro, pois, nem todos os livros são adequados para todos os leitores. "não há vergonha em não acabar um livro" , "nem todos os livros são para todos".

O autor defende o direito dos leitores de saltarem páginas ao ler, argumentando que isso proporciona uma experiência de leitura mais livre e autónoma. Essa liberdade é importante para encontrar livros que interessam, economizar o tempo e focar nas partes relevantes do texto. "saltei páginas, sim, saltei." , "todos os miúdos deviam fazer o mesmo. " , " "rapidamente usufruir de todas as maravilhas que são consideradas inacessíveis na sua idade".

Esta secção do livro desafia a ideia tradicional de que a leitura é indispensável para a formação humana, " A ideia de que a leitura humaniza o homem", " a liberdade de ler não se acomodaria ao dever de ler". A leitura deve ser uma experiência prazerosa e enriquecedora, não como uma obrigação, já que nem todos desfrutam da leitura da mesma maneira. Ou seja, o direito de não ler é fundamental para a liberdade individual.

Ao reler, o leitor consegue "gratuitamente" voltar a viver a experiência que o livro retrata e, desta forma, através da "alegria" descobrir novas "descobertas":

É verdade, todos nós temos o direito de não acabar de ler um livro, pois podemos achar que "a história não nos prende a atenção" ou porque simplesmente achamos que existe uma "ausência de qualidade" que não justifica o leitor continuar a ler o livro.

Apesar do livro ter as paginas numeradas, o leitor tem todo o direito de saltar páginas, pois pode achar que aquela página não interessa para o livro ou porque simplesmente gosta de ler o livro sem ter em atenção a numeração das páginas.

Para este ponto, é importante salientar que todos nós enquanto leitores temos o direito de não ler livros, pois podemos não gostar de ler ou até mesmo não ter vontade de ler. Contudo, é importante salientar que mesmo não gostando de ler, este ato é importante pois vai nos permitir adquirir novas palavras.

Todos temos o direito de não ler um livro, ou porque não queremos ou não gostamos, "não gostam de ler". Mas um livro é muito mais que uma leitura, é observar as imagens, páginas e, por exemplo, as ilustrações.

É de certa forma, um direito que podemos ou não realizar ao" falar do que se leu".  Cada obra representa a "ínfima e secreta conivências" do autor para o leitor, podemos então guardar para nós essa experiência e mensagem ou contar a alguém, "ninguém nos pede contas dessa intimidade".

Este é um direito com inúmeros benefícios, que se encontra, por vezes, desaparecido,"O desaparecimento da leitura em voz alta é muito estranho"," as palavras pronunciadas começavam a ter existência fora de mim, tinham autêntica vida", atualmente e mais comum efetuar a leitura silenciada, onde o "homem que lê em voz alta" já não se expõem.

Efetivamente, é um direito que oferece conhecimento e novas experiencias, pois nunca sabemos o que pode aparecer nos livros," É a autorização que concedemos a nós próprios de retirar qualquer livro da nossa biblioteca, de o abrir onde nos apetecer e de mergulharmos nele por um instante, … ".

De facto, é um direito que assiste a todos os leitores, amar quem quiserem, até as personagens das obras, assim" amar os "heróis" dos romances", é uma "satisfação imediata e exclusiva das nossas sensações".

Na verdade, todos temos o direito de ler onde e quando quisermos, pois não existe locais próprios para realizar a leitura de um livro, além das salas de leitura.  Desta forma, podemos ler em diversos locais como café, praia, carro e em casa, por exemplo, cabe a cada leitor a escolha de um local onde se senta a vontade para efetuar a leitura do seu livro.

Na verdade, este é um direito de preferência," A propósito de "gosto"", como um romance, "há "bons" e "maus" romances", procuramos sempre os escritores e as obras que satisfação o nosso interesse, "Chegou o momento de exigirmos ao romance mais do que a satisfação imediata e exclusiva das nossas sensações".

Efetivamente, reler é um direito que permite reviver "sob outro ângulo" a narrativa, todos temos esse direito gratuitamente. É, às vezes, nessa repetição de acontecimentos que surgem "novas descobertas" e novas experiências. 

De facto, o leitor tem o poder de escolha de querer chegar ao final do livro ou apenas ler as primeiras páginas ou capítulos. Efetivamente, por não ter mais interesse na narrativa ou simplesmente ser exaustivo, " Mas não é um drama, á assim mesmo".

Os leitores têm o direito de "saltar páginas", embora estejam enumeradas, não temos de seguir essa ordem desejada," continuamos a "saltar páginas" por razões que dizem respeito apenas a nós próprios e o livro que lemos", é por isso, uma escolha de cada leitor " é uma categoria do nosso prazer de ler".

Arenito, excelentes rochas para formação de aquiferos

Entre as principais bacias, estão: - a Bacia Sedimentar Amazônica, - a Bacia Sedimentar do Meio-Norte, - a Bacia Sedimentar Central - a Bacia Sedimentar do Paraná.

O Brasil apresenta três grandes áreas de escudos cristalinos: - Escudo Cristalino das Guianas - Escudo Cristalino Brasil-Central - Escudo Cristalino Atlântico.

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Reply to the reviewers

Manuscript number: RC-2024-02438

Corresponding author(s): Ryusuke, Niwa

1. General Statements [optional]

This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

Below are quotes from the Reviewers' overall evaluations:

As might be expected based on the authors' skills and expertise, the study is well executed, nicely documented with perfect microscopy images, and well presented. It has been easy to follow. However, suitability for publication depends on where the authors aim to place their paper. Although I like the paper very much, it might seem incomplete for high-end journals.

This is a very nice paper and solid piece of work.

Its major strength is the focus on poorly studied the male reproductive organ and identification of Ldh as a novel target of JH activity in the seminal vesicles.

While the developmental roles of insect Juvenile Hormone (JH) are very well studied, its adult functions are largely unknown. Target genes of JH signaling are poorly described. This study adds significant insight into both of these aspects. The study underscores the usefulness of the JHRE-GFP reporter that identifies JH function, and not just JH presence since the reporter is only expressed after JH binding to Met and Gce, a prerequisite for JHRE reporter activation.

The authors have identified the epithelial cells of the ____Drosophila____ seminal vesicle as a JH target tissue. The authors nicely extended this finding by mining already existing expression data to identify a specific JH induced gene in these cells.

This small study reports new but limited results (one tissue of one stage, one hormone) that could be useful for specialists. The work is solid and includes controls and interpretable data.

2. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

1) The study suggests an important role for JH signaling in the SV, likely affecting reproductive capacity of males. The authors depleted the JH receptors through RNAi, achieving a loss in the expression of the WT JHRE-GFP reporter as well as of the authentic target Ldh. Surprisingly, no phenotypic consequences of the double KD of Met and gce are presented. Does that mean that there were none? The authors only discuss a potential impact of Ldh loss for metabolism. Unless I am missing something, the study reports molecular phenotypes that clearly document JH signaling in the SV but no physiological impact of loss of this JH signaling, suggesting that there may be no obvious biological role for JH in this context. I think this is unlikely. Have the authors check fertility of the males, sperm viability and quality, mating competitiveness of the RNAi males? Loss of JH epoxidation (only methyl farnesoate present) made mosquito males less fit and less reproductively competitive relative to epox+ controls (Nouzova et al., 2021, PNAS) -- btw, I think the authors should discuss this paper.

Our response: We will conduct the following experiments to answer these criticisms.

1) We will examine the male fertility by counting the number of offspring from wild-type mothers crossed with males of the seminal vesicle-specific ____Met _& _gce____ double RNAi and with males of control RNAi.

2) We will also examine the mating competitiveness of the RNAi males. In more detail, we will cross ____w1118_ (white eye) wild-type background females with (i) a mixed population of males of _w1118_ wild-type background males and_ w+_ (red eye) control RNAi males, and (ii) a mixed population of males of _w1118_ wild-type background males and_ w+ Met _& _gce____ double RNAi males. We can distinguish between the progenies from RNAi males and those from wild-type males by eye colors.

By conducting plans 1) and 2), we will also indirectly evaluate sperm viability and quality.

In addition, we will also discuss the paper of Nouzova et al. PNAS 2021 in the Discussion section.

2) The authors seem to have made no effort to distinguish between Met and Gce functions. It is always the results from the double knockdown of both paralogs that are presented. Does this mean that single-KD had no effect, thereby indicating entirely redundant functions of both proteins in the studied context? Even if so, it would be of interest to document this redundancy by showing the single-gene KD data. However, I would be surprised if both proteins were equally important in the SV. The authors checked mRNA/protein expression levels. Was any of the two paralogs prevalent in the SV?

Our response: To address this criticism, we will conduct a single transgenic RNAi experiment to knock down either Met or gce separately and assess JHRE-GFP signals in the seminal vesicles.

__ Regarding the expression of Met and gce in the seminal vesicles, a previous study (Baumann et al. Scientific Reports 7: 2132, DOI:10.1038/s41598-017-02264-41) has already reported that GFP signals are observed in the seminal vesicles of _Met-T2A-GAL4>UAS_-GFP and gce-T2A-GAL4>UAS-GFP animals. These results strongly indicate that both Met and gce are expressed in the seminal vesicles. We will describe and discuss this point in our revised manuscript. In addition, we plan to check and analyze gene expression of Met, gce, and Ldh in the seminal vesicles using a publicly-available single-cell RNA-seq database, such as _DRscDB (https://www.flyrnai.org/tools/singlecell/web/).

3) The authors argue for direct regulation of Ldh by Met/Gce (again by which one?). Oddly, the statement in the Results (l.187-188; "suggests ... direct target") is stronger than in the Discussion (l.214, "leaving open the possibility"). The putative JHREs upstream and within the Ldh gene are identified but not tested in a functional study. At least a simple luciferase reporter assay and mutagenesis of the JHREs should be attempted.

Our response: To address this criticism, we plan to conduct a luciferase-based promoter/enhancer analysis in Drosophila S2 cultured cells. A similar system was used for a JH-responsiveness of the JHRE promoter in a previous study (Jindra et al. PLoS Genetics 11: e1005394, DOI: __10.1371/journal.pgen.1005394). We will generate plasmid constructs carrying the luciferase coding regions. In these plasmids, the luciferase coding regions will be fused with the upstream region and the first intron region of Ldh possessing the intact E-boxes or the mutated E-boxes. Then, we will determine whether the luciferase activity is enhanced by the presence of a JH analog (methoprene) when E-boxes are intact. __

__ For this revision, a new collaborator, Ryosuke Hayashi (a graduate student in the Niwa lab), will participate in this analysis. Thus, he becomes a co-author in the revised manuscript.__

l.232-233. It is not surprising that the JHRR-lacZ reporter shows a different expression pattern relative to JHRE-GFP, as these are really different constructs. The problem is that JH-dependent activation of the JHRR-lacZ transgene has not been tested as thoroughly as that of JHRE-GFP. Is it inducible by added JH or methoprene?

Have the authors examined whether JHRE-lacZ expression increases with Methoprene?

Our response: We have yet to do this analysis. To address this important point from Reviewers #1 and #2, we will examine whether JHRR-lacZ expression is upregulated in the seminal vesicles of virgin males fed methoprene-supplemented food. The lacZ signals will be visualized by immunostaining with an anti-LacZ antibody.

Document testis staining of JHRE-GFP. I think the authors missed a chance by not providing a clear/nice picture of the testis staining. Stainings of testes squashed on a slide is easy and would nicely document in which cells the reporter is activated. Similarly, extracting sperm from the seminal vesicle and examining whether the sperm express JHRE-GFP would be informative.

Our response: As the reviewer suggested, we will assess JHRE-GFP signal in sperm in squashed testis samples.

Did the authors try to analyze the 66 genes identified in seminal vesicle whether they had JHRE elements? This could yield additional significant information about other JH responsive genes in the seminal vesicle.

Our response: We have yet to do this analysis. We will follow the reviewer's suggestion and examine whether the 66 genes identified in the seminal vesicle have JHRE elements.

3a. Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsRed) and JHRE-GFP overlap.

3b. Similarly, Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsREd) and JHRE-GFP overlap.

Our response: To address this question, we will generate males of Pde8-GAL4; UAS-red fluorescent protein (RedStinger, RFP, or DsRed); JHRE-GFP and observe the overlap between the red fluorescent signals and green fluorescent (JHRE-GFP) signals in the seminal vesicle epithelial cells.

Minor comments:

Fig.1a could be in a supplement.

__Our response: At this point, we are unsure whether to follow this reviewer's suggestion. This is because there are no supplemental figures in the current manuscript, so we hesitate to create a supplemental figure just for this one figure. On the other hand, three reviewers now ask us to perform various additional experiments, thus some of the new data may be shown as supplemental figures. In this case, Fig. 1a can be moved to a supplemental figure, but we would like to wait on this decision. __

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

l.25,91,117, and throughout, "JH analog" or "JHA". The authors only use methoprene, so it would be better to specifically talk about methoprene, which is a proven agonist ligand of the JHR proteins (reference 10 and/or Jindra and Bittova, 2020 [Arch Insect Biochem Physiol] for a review). This would land more credibility to using methoprene than just referring to a "JHA".

Our response: According to the reviewer's suggestion, we have replaced "JHA" with "methoprene" as many as possible. In Figures, we used "MTP" instead of "methoprene" due to space limitations.

l.42,44, "paralogs". I believe in this case the authors refer to orthologs of Met in other species. Paralogs result from gene duplications within species, such as Met and gce in cyclorrhaphous flies or Met 1 and 2 in the Lepidoptera. I recommend a recent review on all bHLH-PAS proteins featuring reconstruction of the phylogenetic position of Met/Gce (Tumova et al., 2024 in J Mol Biol).

Our response: As suggested, we have replaced "paralogs" and "paralogous" with "orthologs" and "orthologous," respectively on P3. We have also cited Tumova et al. J. Mol. Biol. 2023 as a new Ref 12.

l.54, "Met and Gce act redundantly to regulate JH-responsive gene expression". Ref 10 should be cited here as it provides functional cell-based and genetic rescue evidence for each paralog.

Our response: We have cited Ref 10 as suggested.

l.66, It would be better to start "In this study" or "Here" to distinguish from the last cited paper.

Our response:____ We created a new paragraph with the sentence "In this study..." at the beginning. We hope we understand the reviewer's suggestion correctly.

l.175, levels were

Our response: We have fixed this error in the transferred manuscript.

l.209, might be evolutionarily among.... conserved ??

Our response: We have fixed this error in the transferred manuscript.

l.226, study has

Our response: We have fixed this error in the transferred manuscript.

l.227-229. The authors are missing a paper by Shin et al., 2012 (PNAS) that shows physical interaction of Met with Cycle and their regulation of circadian gene activity and another paper by Bajgar et al., 2013 (PNAS) which describes photoperid-dependent seasonal regulation of circadian genes by Met, Clk and Cyc.

On the other hand, the cited reference [51] does NOT demonstrate Met:Clk heterodimer since coIP is by no means adequate to address complex stoichiometry. In fact, it is suspicious that Met would heterodimerize and either Cyc or Clk, as they present class II and class I bHLH-PAS proteins.

Our response: In response to both comments from Reviewer #1, ____we have cited these references and rewritten the discussion on P10-11 as below: "An interesting previous study has reported that the seminal vesicle expresses multiple clock genes such as period, Clock (Clk), and timeless, all of which are necessary for generating proper circadian rhythm [52]. In the case of the mosquito Aedes aegypti female, it is reported that JH controls gene expression via a heterodimer of Met and circadian rhythm factor Cycle (CYC) [53]. It was also suggested that Met binds directly to CLK in D. melanogaster [54]. In addition, in the linden bug, Pyrrhocoris apterus, JH alters gene expression via Met, CLK, and CYC in the gut [55]. Considering these previous reports and our results, circadian rhythm factors and JH may cooperate to regulate gene expression in the seminal vesicles."

l.245. It is not "whether", but for sure the existing reporters only reflect limited JHR activity, being based on Kr-h1 JHREs. These reporters likely uncover only a small subset of JH activity in vivo.

Our response: We have rewritten the sentence as follows: "..., more comprehensive JH reporter strains will be needed in D. melanogaster as well as other insects in future studies."

reference 10/11 is duplicated.

Our response: We have fixed this error in the transferred manuscript.

Have the authors done a careful comparison of JHRE-GFP expression and the Met/gce reporter expression described by Baumann et al (Scientific Reports | 7: 2132 | DOI:10.1038/s41598-017-02264-4)? Would be nice to add a few more sentences in the discussion.

Our response: As suggested, we have added some sentences to explain this point on Page 11 as below: "P____revious studies reported that ____Met-T2A-GAL4_ and _gce-T2A-GAL4_ labeled male accessory glands, ejaculatory duct, and testes as well as seminal vesicles. On the other hand, in our results, JHRE-GFP only labels cells in seminal vesicles and testes [21]. Considering that Met and Gce are expressed in almost all cell types of male reproductive tracts [21], more comprehensive JH reporter strains will be needed in _D. melanogaster____ as well as other insects in future studies."

• In the discussion:*

6.1 Would have liked to see a more in depth discussion of the role of the seminal vesicle. How could that be supported by JH / metabolic processes? Does it have secretory functions that might be induced by JH? Important functions relative to sperm storage? How could that relate to the finding that JH response is enhanced by mating?

Our response: Unfortunately, the function of the seminal vesicles is largely unknown. However, ____in response to the reviewer's suggestion, we have added some sentences to discuss this point and cited some references describing the seminal vesicles in insects other than the fruit fly, as follows on P9-10: "Furthermore, in some insects other than D. melanogaster, morphological and ultrastructural studies revealed that secretory vesicles were observed in the epithelial cells of the seminal vesicles [37,38,40,44]. JH is known to stimulate secretory activity in the male accessory glands of many insects [45]. Based on the JH response in the seminal vesicles, it is possible that JH signaling affects the secretory activity of the seminal vesicles in D. melanogaster."

The arrow in figure is not defined

Our response: We believe that the reviewer pointed out the arrow in Figure 1e. We have added a sentence to define the arrow in the Figure legend as "The arrow indicates the cell with a GFP signal."

Figure 2b graph labels are flipped

Our response: We have fixed the error.

Line 624: Change "Allow heads" to "Arrowheads"

Our response: We have fixed this error in the transferred manuscript.

Major Comments:

The work uses standard methods and strains. Although the specific findings are new and believable, the authors interpret them beyond what is appropriate. For example, based on increased amounts of a single RNA, they propose that JH regulates metabolism in seminal vesicles and because circadian rhythm genes were known to be expressed in this tissue they propose that JH and circadian systems work together there.

Our response: In response to the reviewer's criticisms, we have discussed our arguments more appropriately in the Discussion. For example, we have mentioned circadian rhythm more carefully on Pages 10-11 as follows: "An interesting previous study has reported that the seminal vesicle expresses multiple clock genes such as period, Clock (Clk), and timeless, all of which are necessary for generating proper circadian rhythm [52]. In case of mosquito Aedes aegypti female, it is reported that JH controls gene expression via a heterodimer of Met and circadian rhythm factor Cycle (CYC) [53]. It was also suggested that Met binds directly to CLK in D. melanogaster [54]. In addition, in the linden bug, Pyrrhocoris apterus, JH alter gene expression via Met, CLK and CYC in the gut [55]. Considering these previous reports and our results, it is possible that circadian rhythm factors and JH cooperatively regulate gene expression in the seminal vesicles."

__ Regarding Ldh, we have added a sentence on Page 10 as "Also, the biological significance of the induction of Ldh expression by JH signaling is not clear."__

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

Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

l.244, tract

Our response: We have carefully checked out the usage of "tract" and "tracts" not only on Page 11 but also throughout the manuscript. We have decided to use "tracts," but not "tract," throughout the manuscript.

6.2 What do epithelial cells of spermatheca do?

Our response: We agree with the reviewer that this is a very interesting question. However, please note that this paper focuses on males, and females are beyond our current scope. We plan to examine JHRE-GFP signals in the spermatheca in a different project. We do appreciate the reviewer's kind understanding.

6.3 How do the authors envision that JH enters the epithelial cells?

__Our response:____ We don't have any hypotheses on this point. Transporters may exist to achieve intracellular permeability of JH, but we do not think this point has been discussed in current insect physiology. Furthermore, since this issue is related to all JH-responsive cells, not just seminal vesicle epithelial cells, we do not feel the need to discuss it in this paper. __

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Referee #3

Evidence, reproducibility and clarity

Summary:

Using two existing reporters, the authors showed that cells in Drosophila seminal vesicles are responsive to JH. They believe, but do not show, that these are epithelial cells. JH response of those cell is shown to depend on the known JH receptors and to increase after mating, when JH titers are known to rise. RT-qPCRs show that Ldh expression increases in response to JH.

Major Comments:

The work uses standard methods and strains. Although the specific findings are new and believable, the authors interpret them beyond what is appropriate. For example, based on increased amounts of a single RNA, they propose that JH regulates metabolism in seminal vesicles and because circadian rhythm genes were known to be expressed in this tissue they propose that JH and circadian systems work together there.

Minor comments:

Fig.1a could be in a supplement.

Significance

General Assessment, advance, and audience:

This small study reports new but limited results (one tissue of one stage, one hormone) that could be useful for specialists. The work is solid and includes controls and interpretable data.

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Referee #2

Evidence, reproducibility and clarity

Summary:

The authors identify the epithelial layer of the Drosophila seminal vesicle as a target of Juvenile Hormone (JH) signaling as evidenced by the transcription of two different reporters that are induced by the JH receptors Met and gce via previously identified JH response elements (JHRE). In agreement with this model, the JHRE-GFP reporter is not activated in Met/gce double RNAi knockdowns. Likewise, knockdown of JHAMT, a JH biosynthetic enzyme, reduces reporter expression. That this response is mediated by Juvenile Hormone (JH) is further supported by the finding that application of Methoprene, a JH analogue, through feeding of intact animals or by adding to cultured seminal vesicles, increases reporter expression. Mating, which has previously shown to increase JH levels, similarly increases reporter expression. By mining available RNA and protein data the authors identify Lactate dehydrogenase as a gene that is specifically expressed in the seminal vehicle under JH control. These findings suggest that metabolic processes in the seminal vesicle are regulated by JH and may be important for the function of this organ.

Major comments:

• The claims and the conclusions are supported by the data

• The data and the methods presented in such a way that they can be reproduced

• The experiments adequately replicated and statistical analysis adequate

Optional suggestions for experiments that would enhance the current set of data and are not very time-intensive:

1. Document testis staining of JHRE-GFP. I think the authors missed a chance by not providing a clear/nice picture of the testis staining. Stainings of testes squashed on a slide is easy and would nicely document in which cells the reporter is activated. Similarly, extracting sperm from the seminal vesicle and examining whether the sperm express JHRE-GFP would be informative.

2. Did the authors try to analyze the 66 genes identified in seminal vesicle whether they had JHRE elements? This could yield additional significant information about other JH responsive genes in the seminal vesicle.

3. a) Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsRed) and JHRE-GFP overlap.

b) Similarly, Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsREd) and JHRE-GFP overlap.

1. Have the authors examined whether JHRE-lacZ expression increases with Methoprene?

2. Have the authors done a careful comparison of JHRE-GFP expression and the Met/gce reporter expression described by Baumann et al (Scientific Reports | 7: 2132 | DOI:10.1038/s41598-017-02264-4)? Would be nice to add a few more sentences in the discussion.

3. In the discussion:

a) Would have liked to see a more in depth discussion of the role of the seminal vesicle. How could that be supported by JH / metabolic processes? Does it have secretory functions that might be induced by JH? Important functions relative to sperm storage? How could that relate to the finding that JH response is enhanced by mating?

b) What do epithelial cells of spermatheca do?

c) How do the authors envision that JH enters the epithelial cells?

Minor comments:

• Prior studies are referenced appropriately

• The text and figures clear and accurate

• Suggestions that would help the authors improve the presentation of their data and conclusions:

• The arrow in figure is not defined

• Figure 2b graph labels are flipped

• Line 624: Change "Allow heads" to "Arrow heads"

Significance

General assessment / Advance:

While the developmental roles of insect Juvenile Hormone (JH) are very well studied, its adult functions are largely unknown. Target genes of JH signaling are poorly described. This study adds significant insight into both of these aspects. The study underscores the usefulness of the JHRE-GFP reporter that identifies JH function, and not just JH presence since the reporter is only expressed after JH binding to Met and gce, a prerequisite for JHRE reporter activation. The authors have identified the epithelial cells of the Drosophila seminal vesicle as a JH target tissue. The authors nicely extended this finding by mining already existing expression data to identify a specific JH induced gene in these cells.

• Audience: Audience interested in the role of insect hormones in general or putative reproductive function (basic research and applied (insect control) will be interested in the finding and the approaches taken by the author.

• Reviewer field of expertise: Drosophila sex-specific gene expression and function, molecular genetic approaches

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

---

Referee #1

Evidence, reproducibility and clarity

This is an interesting and straightforward study that utilizes a recently developed in vivo sensor of juvenile hormone (JH) signaling in Drosophila. The authors focus on one understudied aspect of insect reproduction, the adult male seminal vesicle (SV), as a target of JH action. Using simple genetics and gaining from previous RNA-seq and proteomics data, the authors identify lactate dehydrogenase (Ldh) as a prime candidate gene positively regulated by JH in the SV. This regulation is potentially important for the SV physiology (metabolism?) and male reproduction, although this has not been addressed (see below).

As might be expected based on the authors' skills and expertise, the study is well executed, nicely documented with perfect microscopy images, and well presented. It has been easy to follow. However, suitability for publication depends on where the authors aim to place their paper. Although I like the paper very much, it might seem incomplete for high-end journals.

Major comments:

1) The study suggests an important role for JH signaling in the SV, likely affecting reproductive capacity of males. The authors depleted the JH receptors through RNAi, achieving a loss in the expression of the WT JHRE-GFP reporter as well as of the authentic target Ldh. Surprisingly, no phenotypic consequences of the double KD of Met and gce are presented. Does that mean that there were none? The authors only discus a potential impact of Ldh loss for metabolism.

Unless I am missing something, the study reports molecular phenotypes that clearly document JH signaling in the SV but no physiological impact of loss of this JH signaling, suggesting that there may be no obvious biological role for JH in this context. I think this is unlikely. Have the authors check fertility of the males, sperm viability and quality, mating competitiveness of the RNAi males? Loss of JH epoxidation (only methyl farnesoate present) made mosquito males less fit and less reproductively competitive relative to epox+ controls (Nouzova et al., 2021, PNAS) -- btw, I think the authors should discuss this paper.

2) The authors seem to have made no effort to distinguish between Met and Gce functions. It is always the results from the double knockdown of both paralogs that are presented. Does this mean that single-KD had no effect, thereby indicating entirely redundant functions of both proteins in the studied context? Even if so, it would be of interest to document this redundancy by showing the single-gene KD data. However, I would be surprised if both proteins were equally important in the SV. The authors checked mRNA/protein expression levels. Was any of the two paralogs prevalent in the SV?

3) The authors argue for direct regulation of Ldh by Met/Gce (again by which one?). Oddly, the statement in the Results (l.187-188; "suggests ... direct target") is stronger than in the Discussion (l.214, "leaving open the possibility"). The putative JHREs upstream and within the Ldh gene are identified but not tested in a functional study. At least a simple luciferase reporter assay and mutagenesis of the JHREs should be attempted.

Minor comments and suggestions (in the order of appearance):

• l.25,91,117, and throughout, "JH analog" or "JHA". The authors only use methoprene, so it would be better to specifically talk about methoprene, which is a proven agonist ligand of the JHR proteins (reference 10 and/or Jindra and Bittova, 2020 [Arch Insect Biochem Physiol] for a review). This would land more credibility to using methoprene than just referring to a "JHA".

• l.42,44, "paralogs". I believe in this case the authors refer to orthologs of Met in other species. Paralogs result from gene duplications within species, such as Met and gce in cyclorrhaphous flies or Met 1 and 2 in the Lepidoptera. I recommend a recent review on all bHLH-PAS proteins featuring reconstruction of the phylogenetic position of Met/Gce (Tumova et al., 2024 in J Mol Biol).

• l.54, "Met and Gce act redundantly to regulate JH-responsive gene expression". Ref 10 should be cited here as it provides functional cell-based and genetic rescue evidence for each paralog.

• l.66, It would be better to start "In this study" or "Here" to distinguish from the last cited paper.

• l.175, levels were

• l.209, might be evolutionarily among.... conserved ??

• l.226, study has

• l.227-229. The authors are missing a paper by Shin et al., 2012 (PNAS) that shows physical interaction of Met with Cycle and their regulation of circadian gene activity and another paper by Bajgar et al., 2013 (PNAS) which describes photoperid-dependent seasonal regulation of circadian genes by Met, Clk and Cyc.

On the other hand, the cited reference [51] does NOT demonstrate Met:Clk heterodimer since coIP is by no means adequate to address complex stoichiometry. In fact, it is suspicious that Met would heterodimerize and either Cyc or Clk, as they present class II and class I bHLH-PAS proteins.

• l.232-233. It is not surprising that the JHRR-lacZ reporter shows a different expression pattern relative to JHRE-GFP, as these are really different constructs. The problem is that JH-dependent activation of the JHRR-lacZ transgene has not been tested as thoroughly as that of JHRE-GFP. Is it inducible by added JH or methoprene?

• l.244, tract

• l.245. It is not "whether", but for sure the existing reporters only reflect limited JHR activity, being based on Kr-h1 JHREs. These reporters likely uncover only a small subset of JH activity in vivo.

reference 10/11 is duplicated.

Significance

This is a very nice paper and solid piece of work.

Its major strength is the focus on poorly studied the male reproductive organ and identification of Ldh as a novel target of JH activity in the seminal vesicles.

The weakness is the limitation to molecular phenotypes without showing physiological relevance of JHR signaling in the seminal vesicles for male reproductive fitness. Evidence for the Ldh gene being directly regulated by the JHR is indirect.

These limitations will likely reduce the impact of this work although otherwise it would be of great interest to the larger community of developmental biologists and insect endocrinologists.

Roni Jacobson's article in Wired magazine, "I've Been Cyberstalked Since I Was 12," is a harrowing account of the long-term effects of cyberstalking. Jacobson shares her disturbing experience that began at a young age, with a man named Daniel whom she met at camp in 2001 (when she was twelve). Daniel used various methods to harass her and even her family, friends, and employer over the next fifteen years. The article effectively draws attention to those who are cyberstalked. Jacobson's story is not only a personal reflection, but also a critical commentary on the need for stronger cybersecurity measures and legal protections for victims of cyberstalking. The article is important in raising awareness of cyberstalking and advocating for systemic changes to better support victims.

In many cases, after we register some software, they will leak our personal information such as mobile phone number and name. This will cause some scammers to make harassing calls, send harassing messages or email boxes. These harassing messages are quite confusing. When we answer the call or believe it, they will ask us for money and may even become unsafe. In addition, some pornographic harassing messages will appear in stranger messages on Instagram.

Exponering för antingen den första gången resulterar i att antikropps-producerande celler aktiveras och producerar immunoglobulin lgE som binder till lgE-receptorer på mastceller. Vid återexponering för antigen (eller allergener) reagerar antigen med lgE molekylerna vilket triggar igång utsöndring av histamin, leukotriener (kemokiner, heparin) - detta sätter igång en plötslig allergisk reaktion.

När ett visst antigen som kroppen redan sedan tidigare utsatts för och visat känslighet för återkommer reagerar mastceller genom att utsöndra ämnen som reagerar på detta - i form av allergiska reaktioner.

Mastceller kan vi hitta extra mycket av kring små blodkärl men även i vävnaderna kring matsmältnings- och respiratoriska kanaler vilket tyder på att mast celler bildas strategiskt på de platser som är extra utsatta för mikroorganismer.

Mastceller är oftast oval-formade och dessa kan vi hitta i bindväv. Dessa celler är fyllda med basofila granuler - en typ av vita blodkroppar vars funktion är att bilda och transportera histamin (allergi respons) men även heparin och prostaglandiner - sätter igång inflammation (de är alla antikroppar). - Prostaglandin: ett hormonliknande ämne som kontrollerar blodtryck och glatt muskulatur. - Heparin: förhindrar bildning av blodproppar genom att minska blodets förmåga att levra sig (koagulera)

makrofager deriveras från monocyter, som finns i blodet men tar sig in till bindväv genom epitelvävnad för att där utvecklas och få sina makrofaga egenskaper.

Mononuclear phagocyte system = mononukleär fagocytsystem är det system som visar sambandet mellan en grupp av liknande celler - de är makrofagliknande.

Det finns en tabell: 5-2 - som listar alla de olika liknande cellerna som Mikko även sagt är bra att hålla koll på!!

Alla dessa klarar oftast att leva länge och kan överleva i relativt inaktiv vävnad för månader eller år och aktiveras vid inflammation eller skadade organ. Denna grupp av celler bidrar på olika sätt till återhämtning av vävnad.

Typiska drag hos makrofager är dess irregulära ytor med både in- och utbuktningar - detta när makrofager är i sitt aktiva stadie. Man kan även se en tydlig nukleol - ett litet organ i den eukaryota cellkärnan. Nukleolen kan anses vara en "suborganell" eftersom den finns inne i en primär organell, cellkärnan. Nukleolen är sfärisk, membranlös och omges av kromatin. Den har troligen en funktion vid RNA-syntesen och vid bildningen av ribosomer. - wikipedia

Makrofager är en typ av celler vars syfte är att byta ut proteinfibrerna i stroma och att bryta ner celler i apoptos, vävnadsskräp och annat material som ej behövs. Dessa hittas i rikliga mängder särskilt i kirng inflammerade vävnader.

Form och storlek på makrofager kan variera efter funktion - typiskt för makrofagers cellkärna är att de inte är centralt belägna - "eccentrically located" - och är "kidney-shaped"

create list dir

noResolve

x

Part 2

donc : je dirai de revoir un peu l'équilibre de ta structure, enrichir un peu le premier propos sur lequel tu passes un peu vite, ensuite c'est davantage sur le flot de l'écriture : tu commences avec une belle prose et puis ça vrille complet, est-ce que tu peux essayer de filer tes images et tes tournures de phrases autour de l'aveuglement tout au long du txte ? particulièrement dans les parties techniques ? cela facilitera la lecture et donnera plus de corps à ta question.

une majuscule à chaque mot

je rappellerai ici ce que tu as dit en premier temps pour rappeler ta problématique

je dirai de grossir ta première sous-partie sinon d'en faire une intro et de structurer celle-ci en plusieurs points

hummm, suis pas sûre du gras en revanche un graphique

rappel de la structure organique de l'ordinateur de von Neumann ?

je développerai cette idée aussi, je te conseille Bonaccorsi (qui cite Christin en plus) : elle parle de déliaison

trop rapide speedy : faut pas lâcher ça comme ça à ton lecteurice

j'ai du mal à voir en quoi l'écriture numérique est une perte de signification par rapport à des systèmes d'écriture qui sont déjà parvenus à des abstractions signifiantes en tant que tel (qui se rappelle que le a est une tête de boeuf). Je pense que ce passage doit être un peu développé

en revanche, toujours une virgule avant mais parce que c'est une rupture (la virgule varie selon l'évidence ce qui suit donc pas de virgule avant puisque, une virgule avant car)

pas de virgule avant un ni, je crois

peut-être une petit image ou un graphique pour illustrer cette idée ?

un peu trop emphatique je dirai

il faut un lien un peu plus direct entre les deux parties, en quoi elles font avancer ta question et s'y raccroche en wagon

je suis pas sûre de comprendre le propos ici et ça semble en contradiction avec le dialogue dont tu parles plus haut

pourquoi tu mets les références ici ? ça trouble un peu

ça devient progressivement plus clair c'est un beau début, très recherche-création, mais je pense qu'il faut au moins que tu glisses une phrase cash un peu béton et surtout claire sur l'argumentaire

c'est très mystérieux les vibrations dont tu parles, presque du spiritisme... peut-être avant de donner ton objectif de lecture, tu pourrais expliciter de quelles vibrations tu parles

Version 3 of this preprint has been peer-reviewed and recommended by Peer Community in Microbiology.<br /> See the peer reviews and the recommendation.

You are censoring free speech by doing this.

Creating scenarios in her head, delusional and desperate/needy. not in a bad way

Can we get an estimate of the build time? We are waiting and we are not sure how long to wait...

https://stats.stackexchange.com/q/555855

If we don't have any parameters, do we need to change .env.dist to .env?

output

亚马逊盈利第一的 巨星科技- 浙江 比Anker 还厉害

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open empty directory

sepcial IPFS address

development hosted IPFS

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Szentföld

[Crusades]https://hu.wikipedia.org/wiki/Keresztes_h%C3%A1bor%C3%BAk)

középkor, 11. századtól a 15. századig

Author response:

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

eLife assessment

In their valuable study, Chen et al. aim to define the neuronal role of HMMR, a microtubule-associated protein typically associated with cell division. Their findings suggest that HMMR is necessary for proper neuronal morphology and the generation of polymerizing microtubules within neurites, potentially by promoting the function of TPX2. While the study is recognized as a first step in deciphering the influence of HMMR on microtubule organization in neurons, reviewers note the current work has important gaps and would benefit from further exploration of the mechanism of microtubule stability by HMMR, the link between HMMR-mediated microtubule generation and morphogenesis, and the physiological implications of disrupting HMMR during neuronal morphogenesis.

Public Reviews:

Reviewer #1 (Public Review):

The microtubule cytoskeleton is essential for basic cell functions, enabling intracellular transport, and establishment of cell polarity and motility. Microtubule-associated proteins (MAPs) contribute to the regulation of microtubule dynamics and stability - mechanisms that are specifically important for the development and physiological function of neurons. Here, the authors aimed to elucidate the neuronal function of the MAP Hmmr, which they had previously identified in a quantitative study of the proteome associated with neuronal microtubules.

The authors conduct well-controlled experiments to demonstrate the localization of endogenous as well as exogenous Hmmr on microtubules within the soma as well as all neurites of hippocampal neurons. Functional analysis using gain- and loss-of-function approaches demonstrates that Hmmr levels are crucial for neuronal morphogenesis, as the length of both dendrites and axons decreases upon loss of Hmmr and increases upon Hmmr overexpression. In addition to length alterations, the branching pattern of neurites changes with Hmmr levels. To uncover the mechanism of how Hmmr influences neuronal morphology, the authors follow the lead that Hmmr overexpression induces looped microtubules in the soma, indicative of an increase in microtubule stability. Microtubule acetylation indeed decreases and increases with Hmmr LOF and GOF, respectively. Together with a rescue of nocodazole-induced microtubule destabilization by Hmmr GOF, these results argue that Hmmr regulates microtubule stability. Highlighted by the altered movement of a plus-end-associated protein, Hmmr also has an effect on the dynamic nature of microtubules. The authors present evidence suggesting that the nucleation frequency of neuronal microtubules depends on Hmmr's ability to recruit the microtubule nucleator Tpx2. Together, these data add novel insight into MAP-mediated regulation of microtubules as a prerequisite for neuronal morphogenesis. While the data shown support the author's conclusions, the study also has several weaknesses:

• The study appears incomplete as the initial proteomics analysis which is referenced as an entry into the study is not presented. This surely is the authors' choice, however, without presenting this data set, it would make more sense if the authors first showed the localization of Hmmr on neuronal microtubules and then started with the functional analysis.

The reviewer suggests moving the Hmmr localization data in front of the loss- and gain-of-function data because we did not present the proteomics data. However, we still believe placing the loss- and gain-of-function data in the beginning is the better arrangement. This is because it allows the audience to see the drastic changes on neuronal morphology when HMMR is depleted or overly abundant. It also provides a better linkage between HMMR’s localization on microtubules and its effect on the stability and dynamics of microtubules.

• Neurite branching is quantified, but the methods used are not consistent (normalized branch density vs. Sholl analysis) and there is no distinction between alterations of branching in dendrites vs. axons. This information should be added as it could prove informative with respect to the physiological function of Hmmr in neurite branching.

Sholl analysis is considered the gold standard in neurite branching analyses. However, in the knockdown experiment (Figure 1A~1E), HMMR-depleted neurons exhibited extremely short axons (<100 μm) and dendrites (<40 μm). Using Sholl analysis to assess the branching of these Hmmrdepleted neurons became unsuitable. That is why we used normalized branch density (Figure 1E) in the knockdown experiment and Sholl analysis (Figure 1J) in the overexpression experiment.

Regarding the branching difference between axons and dendrites, only axons exhibit branches at 4 DIV. Therefore, the branching analysis focuses on axons rather than on dendrites. We have revised the manuscript to clarify this.

• The authors show that altered Hmmr levels affect neurite branching and identify an effect on microtubule stability and dynamics as a molecular mechanism. However, how branching correlates with or is regulated by Hmmr-mediated microtubule dynamics is neither addressed experimentally nor discussed by the authors. The physiological significance of altered neuronal morphogenesis also lacks discussion.
• To discuss how branching correlates with or is regulated by HMMR-mediated microtubule dynamics, we have added the following paragraph into the Discussion section:

“It has been shown that compromising microtubule nucleation in neurons by SSNA1 mutant overexpression prevents proper axon branching (Basnet et al., 2018). Additionally, dendritic branching in Drosophila sensory neurons depends on the orientation of microtubule nucleation. Nucleation that results in an anterograde microtubule growth leads to increased branching, while nucleation that results in a retrograde microtubule growth leads to decreased branching (Yalgin et al., 2015). These results demonstrate the importance of microtubule nucleation on neurite branching. It is conceivable that overexpressing a microtubule nucleation promoting protein such as HMMR results in an increase of branching complexity.”

• In terms of discussing the physiological significance of altered neuronal morphogenesis. We have added the following paragraph to the Discussion section:

“Neurons are the communication units of the nervous system. The formation of their intricate shape is therefore crucial for the physiological function. Alterations in neuronal morphogenesis have a profound impact on how nerve cells communicate, leading to a variety of physiological consequences. These consequences include impaired neural circuit formation and function, compromised signal transmission between neurons, as well as altered anatomical structure of the CNS. Depending on the specific type and location of the morphogenetically altered neurons, the physiological consequences can include neurological disorders such as autism spectrum disorder (Berkel et al., 2012) and schizophrenia (Goo et al., 2023), as well as learning and memory deficits (Winkle et al., 2016). However, due to the involvement of HMMR on mitosis, most HMMR mutations are associated with familial cancers (based on ClinVar data).”

• Multiple times, the manuscript lacks a rationale for an experimental approach, choice of cell type, time points, regions of interest, etc. Also, a meaningful description of the methods and for how data were analyzed is missing, making the paper hard to read for someone not directly from the field.

We understand the reviewer’s comments regarding the lack of rationale for choosing the experimental approach, choice of cell type, time points, regions of interest, etc. As a result, we have added the rationales where appropriate to help readers from other fields to better understand the choice of cell type, time points, regions of interest, etc. A brief explanation is shown below:

• Approach and timing: We employed both electroporation (immediate but milder expression) and lipofectamine transfection (delayed but stronger expression). We prioritized knocking down HMMR early in development, so electroporation was used. For overexpression experiments, we chose lipofectamine which allows high protein expression level to be achieved.

• Cell selection: Hippocampal neurons were chosen in experiments that involve morphological quantification due to their homogeneous morphology. On the other hand, cortical neurons were selected in experiments that require large amounts of neurons and/or experiments where we want to demonstrate the universality of a proposed hypothesis.

• Regions of interest (ROIs): In our previous publication (Chen et al., 2017), it was discovered that a significant reduction of EB3 emanation frequency can be detected at the tip and the base of the neurite but not in the middle of the neurite in TPX2-depleted neurons. The reason for this difference is due to the presence of GTP-bound Ran GTPase (RanGTP) at the tip and the base of the neurite. Since RanGTP has also been shown to regulate the interaction between HMMR and TPX2 in the cell-free system (Scrofani et al., 2015), it is possible that the same phenomenon can be observed in HMMR-depleted neurons. This is why we examined those 3 ROIs in Figure 4.

Reviewer #2 (Public Review):

The mechanism of microtubule formation, stabilization, and organization in neurites is important for neuronal function. In this manuscript, the authors examine the phenotype of neurons following alteration in the level of the protein HMMR, a microtubule-associated protein with established roles in mitosis. Neurite morphology is measured as well as microtubule stability and dynamic parameters using standard assays. A binding partner of HMMR, TPX2, is localized. The results support a role for HMMR in neurons.

The work presented in this manuscript seeks to determine if a MAP called HMMR contributes to microtubule dynamics in neurons. Several steps, including validation of the RNAi, additional statistical analysis, use of cells at the same age in culture, and better documentation in figures, would increase the impact of the work.

In many places, the data can be improved which might make the story more convincing. As presented, the results show that HMMR is distributed as puncta on neurons with data coming from a single HMMR antibody, and some background staining that was not discussed. In the discussion the authors state that HMMR impacts microtubule stability, which was evaluated by the presence of post-translational modification and resistance to nocodazole; the data are suggestive but not entirely convincing. The discussion also states that HMMR increases the “amount” of growing microtubules which was measured as the frequency of comet appearance. The authors did not comment on how the number of growing microtubules results in the observed morphological changes.

We actually tested several HMMR antibodies, including E-19 (Santa Cruz, sc-16170), EPR4054 (Abcam, ab124729), and a variety of antibodies provided by Prof. Eva Turley. E-19 performed the best in immunofluorescence (IF) staining and knockdown validation. The other antibodies either failed to detect HMMR in IF staining or generate excessive background signal. We understand that the final images are produced using a single antibody. But since we meticulous validated this antibody and that the localization of overexpressed HMMR is consistent with the endogenous HMMR, we are very confident about our data generated using this single antibody.

We have added the following paragraph in the Discussion section to elucidate how the number of growing microtubules result in the observed morphological changes such as an increase of axon branches:

“It has been shown that compromising microtubule nucleation in neurons by SSNA1 mutant overexpression prevents proper axon branching (Basnet et al., 2018). Additionally, dendritic branching in Drosophila sensory neurons depends on the orientation of microtubule nucleation. Nucleation that results in an anterograde microtubule growth leads to increased branching, while nucleation that results in a retrograde microtubule growth leads to decreased branching (Yalgin et al., 2015). These results demonstrate the importance of microtubule nucleation on neurite branching. It is conceivable that overexpressing a microtubule nucleation promoting protein such as HMMR results in an increase of branching complexity.

Reviewer #1 (Recommendations for The Authors):

(1) The manuscript jumps extensively between main figures and supplementary figures. Please check whether parts of the supplement could be moved to the main figures.

We understand the frustration of moving back and forth between the main figures and supplementary figures. After examining the manuscript, we decided to combine Figure 2A with Figure S3.

(2) In Figure 1, total neurite length between days 3 and 4 DIV does not appear to change - can this be true?

Please check or else explain.

We carefully re-examined our raw data and found out the total neurite length of 4 DIV hippocampal neurons expressing non-targeting shRNA (Figure 1B) and that of 3 DIV hippocampal neurons expressing AcGFP (Figure 1G) are indeed very similar. The explanation is that the 3 DIV hippocampal neurons used for Figure 1G was cultured in low-density and in the presence of cortical neuron-conditioned neurobasal medium (as written in Methods, Neuron culture and transfection section). The low-density culture with minimal overlapping neurites allowed us to better quantify total neurite length, because neurons expressing AcGFP-mHMMR sprouted long and highly branched axons. However, the addition of cortical neuron-conditioned neurobasal medium promoted neurite elongation. This is the reason why the total neurite length of 4 DIV hippocampal neurons expressing non-targeting shRNA (Figure 1B) and that of 3 DIV hippocampal neurons expressing AcGFP (Figure 1G) is similar.

(3) Groen et al. have shown that Hmmr also bundles microtubules, a mechanism that surely is important for neuronal microtubules. Please discuss.

We thank the reviewer for pointing out that HMMR also bundles microtubules and have added this to our revised Discussion section:

“It has been shown that the Xenopus HMMR homolog XRHAMM bundles microtubules in vitro (Groen et al., 2004). In addition, deleting proteins which promote microtubule bundling (e.g., doublecortin knockout, MAP1B/MAP2 double knockout) leads to impaired neurite outgrowth (Bielas et al., 2007; Teng et al., 2001). These observations are consistent with our data that overexpressing HMMR leads to the increased axon and dendrite outgrowth, while depleting it results in the opposite phenotype (Figure 1).”

(4) Please explain why in Figure 4, cortical neurons were chosen for analysis and why and how the three different ROIs were picked.

To answer the question why we chose cortical neurons for the analyses in Figure 4, it will be important to explain why we used hippocampal neurons for other figures. Primary hippocampal neurons have a high homogeneity in terms of their morphology. This uniform morphology allows more consistent morphological quantification. Figure 4, however, does not involve morphological quantification. We are more confident to conclude that HMMR regulates microtubule dynamics if this effect can be detected in the relatively heterogeneous cortical neurons. These are the reasons why we chose to analyze cortical neurons in Figure 4.

In our previous publication (Chen et al., 2017), it was discovered that a significant reduction of EB3 emanation frequency can be detected at the tip and the base of the neurite but not in the middle of the neurite in TPX2-depleted neurons. The reason for this difference is due to the presence of GTP-bound Ran GTPase (RanGTP) at the tip of the neurite and in the soma. Since RanGTP has also been shown to regulate the interaction between HMMR and TPX2 in the cell-free system (Scrofani et al., 2015), it is possible that the same phenomenon can be observed in HMMR-depleted neurons. This was why we examined those 3 ROIs in Figure 4.

(5) Microtubule looping has been shown to occur in regions prior to branch formation (e.g. Dent et al. 2004). As the authors identify increased looping upon Hmmr GOF, this should be discussed.

We thank the reviewer for pointing out that microtubule looping occurs in regions of branch formation and have added this to our revised discussion:

“It is worth noting that the elevated level of HMMR increases the branching density of axons (Figure 1J) and promotes the formation of looped microtubules (Figure 3A). This is consistent with the observations that looped microtubules are often detected in regions of axon branch formation (Dent et al., 1999; Dent and Kalil, 2001; Purro et al., 2008).”

Reviewer #2 (Recommendations for The Authors):

(1) The work seeks to gain insight into microtubule behavior in neurons, an important issue.

(2) Several steps, including validation of the RNAi, additional statistical analysis, use of cells at the same age in culture, and better documentation in figures, would increase the impact of the work.

(3) Figure 1 documents the results of experiments in which the HMMR protein was depleted using shRNA. A western blot of cell extracts from control and depleted cells is needed to verify that the protein level is reduced; alternatively, documentation of the reduction in RNA levels in treated cells could be provided. Neurite, axon, and dendrite length and branch density are measured. The neurite length is in microns, and the axon length is normalized to 100% of the non-treated cells. Please use the same for measures for easier comparison. Looking at the images in Figure 1, the length of the dendrites does not look different in the examples shown, whereas the axon appears shorter. This impression is not supported by the quantification. Are representative images shown? Additionally, the authors should report the values for each replicate of the experiment and compare the three averages rather than comparison of lengths from all measurements. A related issue is that the dendrites do not look longer in panel F, following overexpression of HMMR. For examples of using averages of replicates see: https://pubmed.ncbi.nlm.nih.gov/32346721/

The reviewer mentioned that Western blot of cell extracts or RNA quantification from control and depleted cells are needed to verify that the protein level is reduced.

Unfortunately, these assays are extremely difficult to perform in primary neurons due to the low transfection efficiency. We believe that the consistent knockdown phenotype from 3 different shRNA sequences (Figure 1A-D) and the immunofluorescence staining in depleted primary neurons (Figure S2) are sufficient to confirm that HMMR level is reduced.

We revised Figure 1C, 1D, 1H, 1I so that axon and dendrite lengths are all in micron.

We selected another image for the non-targeting control in Figure 1A to better demonstrate the reduction of dendrite length when HMMR is knocked down.

We thank the reviewer for the suggestion of comparing the three average values rather than comparing all measurements. We have performed statistical analyses for all our data using the average values and revised the graphs accordingly. While the P-values changed, our conclusions remain the same.

We thank the reviewer for pointing out this discrepancy and have selected another image of the AcGFP control for Figure 1F to better demonstrate the increase of dendrite length when HMMR is overexpressed.

(4) Given the changes in neurite morphology, the authors examine the localization of endogenous and overexpressed. The supplemental figures (see S2 and S3) show evidence that HMMR is present in a punctate pattern by conventional immunofluorescence. This is reasonable evidence that the protein is in a linear pattern along cytoskeletal microtubules and that the signal is present in puncta. Please move this to the main text, perhaps replacing Figure 2A, which is low magnification and very hard to see the HMMR staining. Additionally, the level of overexpression of HMMR is not mentioned. Please address this; were cells with similar levels of overexpression selected? Did the result depend on the overexpression? A related issue is the DIV for the cells - some are examined earlier and some at later times; does this impact the results? Please provide information or perform experiments with consistent timing. For the immunofluorescence, were multiple antibodies tried to see if the result was the same with each? Were different fixations, in addition to methanol, utilized?

We have replaced Figure 2A with Figure S3 based on the reviewer’s suggestion.

In the HMMR overexpression experiments, we used HMMR antibody and immunofluorescence staining to confirm that the overexpression is achieved. However, we did not quantify to what extend HMMR was overexpressed.

We performed all the depletion experiments on 4 DIV to maximize knockdown efficiency and performed all the overexpression experiments on 3 DIV to prevent excessive axon fasciculation. Nonetheless, we examined the effect of HMMR depletion on neuronal morphology on 3 DIV. The trend of reduced total neurite length, axon length, and dendrite length can be observed, but no statistical significance can be detected. We also examined the effect of HMMR overexpression on neuronal morphology on 4 DIV and did observe an increase of total neurite length, axon length, and dendrite length. But the overlapping and bundled axons made reliable quantification extremely difficult.

We actually tested multiple HMMR antibodies, such as E-19 (Santa Cruz, sc-16170), EPR4054 (Abcam, ab124729), and a variety of antibodies provided by Prof. Eva Turley. E19 performed the best in immunofluorescence (IF) staining and knockdown validation. The other antibodies either failed to detect HMMR in IF staining or generate excessive background signal. We also tested various fixation methods, including 37°C formaldehyde fixation, -20°C methanol fixation, 37°C formaldehyde followed by -20°C methanol fixation. All fixation methods generated similar IF staining pattern using the E-19 antibody, but 3.7% formaldehyde fixation produced the highest signal.

(5) In Figure 2 C it is hard to see DAPI fluorescence. Are the white areas in the merge with bright cell nuclei? Is Figure 2C control or overexpressing cells? If this is endogenous, is there less signal in PLA compared with S4, which was in culture longer and is overexpressed prior to using PLA for detection?

The white areas in Figure 2C the reviewer mentioned are not cell nuclei, they are actually bubbles formed within the mounting medium.

HMMR detected in Figure 2C is endogenous. We did not quantitatively compare the PLA signals in Figure 2C and those in Figure S4. This is because the PLA signals in Figure 2C are generated using anti-HMMR (to detect endogenous HMMR) and anti-β-III-tubulin antibodies while those in Figure S4 are generated using anti-AcGFP (to detect overexpressed AcGFP-mHMMR) and anti-β-III-tubulin antibodies. Since the affinity of the two antibodies (i.e., anti-HMMR and anti-AcGFP) toward their antigens is different, comparing the PLA signals is not informative.

(6) The images of the endogenous HMMR (Fig S3) and the PLA with tubulin and HMMR antibodies are not the same (2C). The "dots" in PLA are widely separated; gauging from the marker bar length of 50 μm, the small clusters of dots are about 10 μm apart. In Figure S3, the puncta are much more closely spaced, appearing almost in a linear fashion along the microtubules. Enlarging the PLA image shows that each dot is very small - just a few pixels - please provide additional explanation including the minimal detection limit for the method, and why the images differ. If the standard immunofluorescence signal was enhanced, for example with the use of two secondaries, what is observed? Is the distribution of HMMR similar for both dendrites and axons? Microtubule polarity differs in these locations, so greater attention to this point seems of interest. There is a significant amount of punctate HMMR in the cytoplasm (or outside the cytoplasm?) in Figure S5; this is concerning. Please outline the cell edge for ease of visualization. What is the distribution of HMMR in a cell that has been treated with cold and/or nocodazole to disassemble the microtubules? is the signal lost?

The reasons images of the endogenous HMMR (Figure S3) and the PLA with tubulin and HMMR antibodies (Figure 2C) differ are due to the following reasons. o PLA utilizes two primary antibodies to target two different epitopes on HMMR and βIII-tubulin. It is conceivable that not every anti-HMMR antibody has the correct orientation and/or proximity (<40 nm) toward the anti-β-III-tubulin antibody to enable DNA amplification. This results in the shortage of PLA puncta compared to immunofluorescence signals.

• The creator of PLA has pointed out that in situ PLA is a method based upon equilibrium reactions and several enzymatic steps. Therefore, only a fraction of the inter-acting molecules is detected (Weibrecht et al., 2010).

We have not used signal enhancing immunofluorescence staining methods [e.g., using tertiary antibodies or tyramide signal amplification (TSA)] to detect HMMR. This is mainly because HMMR signal is strong enough to be detected using standard immunofluorescence staining.

Regarding the question “Is the distribution of HMMR similar for both dendrites and axons?” The reviewer raised a very important issue about the polarity difference of microtubules in axons (uniform) and dendrites (mixed). We were aware of such issue and very carefully examined the distribution and signal intensity of HMMR in axons vs dendrites. However, no differences were detected.

The reviewer mentioned that “there is a significant amount of punctate HMMR in the cytoplasm (or outside the cytoplasm?) in Figure S5; this is concerning. Please outline the cell edge for ease of visualization.” Instead of outlining the cell edge, we have selected another image to facilitate the visualization of HMMR signals. There are indeed HMMR signals outside the cell. However, these outside signals are usually weaker and smaller in size compared to those inside the cell.

After the examination of neurons expressing AcGFP-mHMMR with or without 100 nM nocodazole treatment, we did not notice any difference of AcGFP-mHMMR in distribution. We did not examine the distribution and signal intensity of the endogenous HMMR.

(7) To determine if HMMR alters microtubule stability, the authors examine the distribution of acetylated tubulin and resistance to nocodazole-induced microtubule disassembly. In Figure 3 please show immunofluorescence images of the acetylated tubulin staining, not just the ratio images; the color is not obviously different in the various panels shown. For statistical analysis, see the comment above for Figure 1. For the nocodazole experiment, a similar change in neurite length following drug treatment was observed (Figure 3H), for the experimental and control, even though the starting length was greater in the overexpressing cells. Please consider the possibility that in both cases the microtubules are only partially resistant to nocodazole and that HMMR is not changing the fraction of microtubules that are sensitive to the drug. The cells were treated at 3 DIV; the authors note that more stable microtubules accumulate with time; how does time in culture impact stability? Often, acute treatment with a high concentration of nocodazole is used to assay microtubule stability; here the authors used a low (nM) concentration for 2 days (chronic). Why not use a higher concentration (1-10 μM) for a shorter incubation? The data show that overexpression of HMMR results in curved, buckled microtubules are these microtubules more acetylated and/or retained after nocodazole treatment?

The reviewer suggested that we show immunofluorescence images of the acetylated tubulin staining, not just the ratio images. But we still believe showing the ratio images is the better approach. This is because the microtubules density can be different from neuron to neuron. Showing acetylated tubulin may provide a false impression when the overall microtubule density is higher or lower in a particular neuron. We realized that “16 colors” pseudo-color scheme has the cyan color at the lower intensity which can sometimes be confused with the white color at the higher intensity. Therefore, we changed the pseudocolor from “16 colors” to “fire” for Figure 3B and 3E to better visualize these images so that they appear more consistent with the quantitative data.

The reviewer raised a very good question regarding the possibility that HMMR is not changing the fraction of microtubules that are sensitive to nocodazole. We re-conducted the same experiment and used a series of different nocodazole concentrations. While the addition of nocodazole causes a concentration-dependent reduction of total neurite length in both AcGFP and AcGFP-mHMMR expressing neurons, there are subtle differences in the susceptibility of neurite length to the concentration of nocodazole. 1) 10 nM nocodazole treatment causes a significant reduction of neurite length in AcGFP expressing neurons, but not in AcGFP-mHMMR expressing neurons. This result indicates that AcGFP-mHMMR expression increases the tolerance of neurite elongation toward 10 nM nocodazole treatment. 2) 50 nM and 100 nM nocodazole treatment exhibits no statistical significance in AcGFP expressing neurons, suggesting that 50 nM nocodazole has reached maximal effectiveness. In AcGFP-mHMMR expressing neurons, 100 nM nocodazole further reduces the neurite length compared to the 50 nM group. These results argue against the possibility that HMMR does not change the fraction of microtubules that are sensitive to nocodazole. We have revised Figure 3H accordingly.

The reviewer asked why we did not use the acute nocodazole treatment (μM concentration) to assess the effect of Hmmr on microtubule stability. This is because we used the neurite length as an indicator for microtubule stability. That is why the chronic treatment was chosen to produce a more detectable effect on neurite length.

The reviewer asked whether the looped microtubules caused by HMMR overexpression are more acetylated and/or nocodazole resistant. While we do not have direct evidence to answer the reviewer’s question, we can deduce the answer from our observations. We noticed that looped microtubules are only present when HMMR is highly expressed (i.e., using lipofection to introduce HMMR-expressing plasmid) but not when HMMR is mildly expressed (i.e., using electroporation to introduce HMMR-expressing plasmid). From these observations, we can conclude that HMMR is more abundantly present on looped microtubules. Since HMMR overexpression leads to higher microtubule acetylation (Figure 3E), looped microtubules which contains more HMMR are most likely to be more acetylated.

(8) An additional measure of microtubule dynamics is to measure the growth of microtubules using a live cell marker for microtubule plus ends. Such experiments were performed, using tagged EB3. The images are rather fuzzy. Parameters of microtubule dynamics were measured at three locations - is there data that the authors can cite about any differences in dynamics in control cells at these locations? They look very similar, so it is not clear why the different locations were used. It is not possible to learn much from the kymographs which look similar for all panels; I would remove these unless they can be changed or labeled to help the reader. Data is presented for three shRNA reagents. No data are presented to document the extent to which the protein is depleted with these reagents. This should be fixed. Alternatively, an RNAi pool could be utilized. Is there a control for off-target effects? For the analysis were all the comets used to generate the average values? What about a comparison of the average of each trial - not each comet?

In our previous publication (Chen et al., 2017), it was discovered that a significant reduction of EB3 emanation frequency can be detected at the tip and the base of the neurite but not in the middle of the neurite in TPX2-depleted neurons. The reason for this difference is due to the presence of RanGTP at the tip and the base of the neurite. Since RanGTP has also been shown to regulate the interaction between HMMR and TPX2 in the cell-free system (Scrofani et al., 2015), it is possible that the same phenomenon can be observed in HMMR-depleted neurons. This is why we examined those 3 ROIs in Figure 4.

We notice that photobleaching causes the EB3-mCherry signal to diminish at later time points, which made it difficult to observe the differences amongst kymographs. In the revised Figure 4B and 4D, we removed the second half of all the kymographs to make the differences more obvious.

The reviewer mentioned that there are no data documenting the extent to which the protein is depleted with the shRNAs. These data are shown in Figure S2, in which we quantified the HMMR protein level in the soma and along the neurite in neurons expressing different shRNA molecules.

The reviewer asked whether there is a control for off-target effects. The answer is yes. We performed the rescue experiment to control for off-target effects, which is shown in Figure S1.

We revised Figure 4 so that the dynamic properties of EB3 are quantified using the average of each experimental repetition.

(9) In a final experiment, the authors examine the distribution of TPX2, a binding partner of HMMR. Include a standard immunofluorescence in addition to PLA to illustrate the distribution of TPX2. The quantification used was the inter puncta distance; please quantify the signal in control and treated cells.

The reviewer asked us to include a standard immunofluorescence staining to illustrate the distribution of TPX2. We have done that in our previous publication (Chen et al., 2017) and TPX2 localizes primarily to the centrosome (https://www.nature.com/articles/srep42297/figures/2). In order to enhance the weak signal of TPX2 along the neurite, we actually needed to use PLA in that publication (https://www.nature.com/articles/srep42297/figures/3).

Proximity ligation assay (PLA) generates fluorescent signals based on a local enzymatic reaction which catalyzes the amplification of a specific DNA sequence that can then be detected using a red fluorescent probe. Because this enzymatic reaction is not linear, the amount of amplified DNA nor the intensity of the fluorescence does not correlate with the strength of the interaction (Soderberg et al., 2006). As a result, quantification of PLA is typically done by counting the number of fluorescent puncta per unit area or by calculating the area containing fluorescent signal (not signal intensity) per unit area in the case that PLA signals are too strong and coalesced. That is why our quantification is based on the distance between PLA fluorescent puncta, not the fluorescent signal intensity.

References

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Reviewer #1 (Public Review):

The microtubule cytoskeleton is essential for basic cell functions, enabling intracellular transport, and establishment of cell polarity and motility. Microtubule-associated proteins (MAPs) contribute to the regulation of microtubule dynamics and stability - mechanisms that are specifically important for the development and physiological function of neurons. Here, the authors aimed to elucidate the neuronal function of the MAP Hmmr, which they had previously identified in a (yet unpublished) quantitative study of the proteome associated with neuronal microtubules. The authors conduct well-controlled experiments to demonstrate the localization of endogenous as well as exogenous Hmmr on microtubules within the soma as well as all neurites of hippocampal neurons. Functional analysis using gain- and loss-of-function approaches demonstrates that Hmmr levels are crucial for neuronal morphogenesis, as the length of both dendrites and axons decreases upon loss of Hmmr and increases upon Hmmr overexpression. In addition to length alterations, the branching pattern of neurites changes with Hmmr levels. To uncover the mechanism of how Hmmr influences neuronal morphology, the authors follow the lead that Hmmr overexpression induces looped microtubules in the soma, indicative of an increase in microtubule stability. Microtubule acetylation indeed decreases and increases with Hmmr LOF and GOF, respectively. Together with a rescue of nocodazole-induced microtubule destabilization by Hmmr GOF, these results argue that Hmmr regulates microtubule stability. Highlighted by the altered movement of a plus-end-associated protein, Hmmr also has an effect on the dynamic nature of microtubules. The authors present evidence suggesting that the nucleation frequency of neuronal microtubules depends on Hmmr's ability to recruit the microtubule nucleator Tpx2. The authors discuss how branching may be regulated by Hmmr-mediated microtubule dynamics and speculate about the physiological significance of altered neuronal morphogenesis. Together, their work adds novel insight into MAP-mediated regulation of microtubules as a prerequisite for neuronal morphogenesis.

eLife assessment

In their valuable study, Chen et al. investigate the neuronal role of HMMR, a microtubule-associated protein typically associated with cell division. Their findings indicate that HMMR is necessary for proper neuronal morphology and the generation of polymerizing microtubules within neurites, potentially by promoting the function of TPX2. This solid body of work is the first step in deciphering the influence of a mitotic microtubule-associated protein in organizing microtubules in neurons and will be of interest to the neurobiology and cytoskeleton fields.

Reviewer #2 (Public Review):

The mechanism of microtubule formation, stabilization, and organization in neurites is important for neuronal function. In this manuscript, the authors examine the phenotype of neurons following alteration in the level of the protein HMMR, a microtubule-associated protein with established roles in mitosis. Neurite morphology is measured as well as microtubule stability and dynamic parameters using standard assays. A binding partner of HMMR, TPX2, is localized. The results support a role for HMMR in microtubule stabilization in neurons.

The results show that HMMR is distributed as puncta on neurons using standard immunofluorescence and PLA. Depletion of HMMR reduced neurite length and extent of branching; reduced post-translational acetylation of neurite microtubules. Conversely, overexpression of HMMR increased resistance to nocodazole. The parameters of microtubule dynamics were also impacted by reduction or overexpression of HMMR. The authors discuss the possibility HMMR regulates neurite morphological changes via regulation of microtubule nucleation and dynamics.

3 -ème étude donc 2 -ème argument épistémique lui aussi pour appuyer le propos originel

ici on remarque que la communication est surtout interactive, mais l'enfant saura il appliquer ce qu'il a appris virtuellement, au réel? Car le passage de l'environnement virtuel a l'environnement réel, peut être troublant, surtout lorsque l'ont sait que les enfants autiste ont besoin d'avoir des repère précis et régulier, ces repère sauront ils les retrouver dans une communication avec les autres

ici les résultats de l'expérience semblent positifs mais indiquent, que les support technologiques doivent répondre a certaines condition, ce qui précise quels type d'outils doivent être utilisés

deuxième expérience à l'appui pour démontrer son point: les nouvelles technologies peuvent aider les enfants autistes

étude qui inclus désormais un nombre plus large d'enfant et pas seulement les enfants autistes. les enfants sont issus d'école différentes et elle propose plusieurs type d'application dispersé sur plusieurs domaine différents, ce qui permet d'avoir des information plus précise et sures que la première étude. de plus le temps d'action est plus long, on comptera 13 session ici contre 6 lors de l'étude précédente

les tablettes numérique seraient plus facilement maniable pour les enfants atteint d'autisme, en effet ils rencontrent souvent des problèmes de motricité. ici le geste se passe directement sur l'écran et l'enfant n'a donc pas a penser a mettre sa main sur la souris il peut donc mieux se concentrer en reportant toute son attention vers la tablette et onc ce qui se passe dans l'écran uniquement

une critique que l'on pourrait émettre est le nombre insuffisant de participants. en effet si sur ces 5 enfants les résultats sont encourageant, ils ne peuvent pas être pris pour certitude, en d'autres terme, ce qui fonctionne pour ces enfants sélectionnés pour l'étude, ne fonctionnera peut être pas pour d'autres enfants

Ici l'autrice nous indique que l'imitation, peut poser problèmes pour les enfants autistes dans leur apprentissage de la vie, et dans leur relation avec les autres. Néanmoins elle souligne que selon l'etude mentionnée les jeux interactifs peuvent aider a reduire l'impact négatif de l'imitation. ( argument épistémique, fait + connaissance =conclusion)

Author response:

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

Reviewer #1 (Public Review):

Summary:

The authors set up a pipeline for automated high-throughput single-molecule fluorescence imaging (htSMT) in living cells and analysis of molecular dynamics

Strengths:

htSMT reveals information on the diffusion and bound fraction of molecules, dose-response curves, relative estimates of binding rates, and temporal changes of parameters. It enables the screening of thousands of compounds in a reasonable time and proves to be more sensitive and faster than classical cell-growth assays. If the function of a compound is coupled to the mobility of the protein of interest, or affects an interaction partner, which modulates the mobility of the protein of interest, htSMT allows identifying the modulator and getting the first indication of the mechanism of action or interaction networks, which can be a starting point for more in-depth analysis.

Weaknesses:

While elegantly showcasing the power of high-throughput measurements, the authors disclose little information on their microscope setup and analysis procedures. Thus, reproduction by other scientists is limited. Moreover, a critical discussion about the limits of the approach in determining dynamic parameters, the mechanism of action of compounds, and network reconstruction for the protein of interest is missing. In addition, automated imaging and analysis procedures require implementing sensitive measures to assure data and analysis quality, but a description of such measures is missing.

The reviewer rightly highlights both the power and complexity in high throughput assay systems, and as such the authors have spent significant effort in first developing quality control checks to support screening. We discuss some of these as part of the description and characterization of the platform. We added additional details into the manuscript to help clarify. The implementation of our workflow for image acquisition, processing and analysis relies heavily on the specifics of our lab hardware and software infrastructure. We have added additional details to the text, particularly in the Methods section, and believe we have added enough information that our results can be reproduced using the suite of tools that already exist for single molecule tracking.

The reviewer also points out that all assays have limitations, and these have not been clearly identified as part of our discussion of the htSMT platform. We have also added some comments on the limitations of the current system and our approach.

Reviewer #2 (Public Review):

Summary:

McSwiggen et al present a high throughput platform for SPT that allows them to identify pharmaceutics interactions with the diffusional behavior of receptors and in turn to identify potent new ligands and cellular mechanisms. The manuscript is well written, it provides a solid new mentor and a proper experimental foundation

Strengths:

The method capitalizes and extends to existing high throughput toolboxes and is directly applied to multiple receptors and ligands. The outcomes are important and relevant for society. 10^6 cells and >400 ligands per is a significant achievement.

The method can detect functionally relevant changes in transcription factor dynamics and accurately differentiate the ligand/target specificity directly within the cellular environment. This will be instrumental in screening libraries of compounds to identify starting points for the development of new therapeutics. Identifying hitherto unknown networks of biochemical signaling pathways will propel the field of single-particle live cell and quantitative microscopy in the area of diagnostics. The manuscript is well-written and clearly conveys its message.

Weaknesses:

There are a few elements, that if rectified would improve the claims of the manuscript.

The authors claim that they measure receptor dynamics. In essence, their readout is a variation in diffusional behavior that correlates to ligand binding. While ligand binding can result in altered dynamics or /and shift in conformational equilibrium, SPT is not recording directly protein structural dynamics, but their effect on diffusion. They should correct and elaborate on this.

This is an excellent clarifying question, and we have tried to make it more explicit in the text. The reviewer is absolutely correct; we’re not using SPT to directly measure protein structural dynamics, but rather the interactions a given protein makes with other macromolecules within the cell. So when an SHR binds to ligand it adopts conformations that promote association with DNA and other protein-protein interactions relevant to transcription. This is distinct from assays that directly measure conformational changes of the protein.

L 148 What do the authors mean 'No correlation between diffusion and monomeric protein size was observed, highlighting the differences between cellular protein dynamics versus purified systems'. This is not justified by data here or literature reference. How do the authors know these are individual molecules? Intensity distributions or single bleaching steps should be presented.

The point we were trying to make is that the relative molecular weights for the monomer protein (138 kDa for Halo-AR, 102 kDa for ER-Halo, 122 kDa for Halo-GR, and 135 kDa for Halo-PR) is uncorrelated with its apparent free diffusion coefficient. Were we to make this measurement on purified protein in buffer, where diffusion is well described by the Stokes Einstein equation, one would expect to see monomer size and diffusion related. We’ve clarified this point in the manuscript.

Along the same lines, the data in Figs 2 and 4 show that not only the immobile fraction is increased but also that the diffusion coefficient of the fast-moving (attributed to free) is reduced. The authors mention this and show an extended Fig 5 but do not provide an explanation.

This is an area where there is still more work to do in understanding the estrogen receptor and other SHRs. As the reviewer says, we see not only an increase in chromatin binding but also a decrease in the diffusion coefficient of the “free” population. A potential explanation is that this is a greater prevalence of freely-diffusing homodimers of the receptor, or other protein-protein interactions (14-3-3, P300, CBP, etc) that can occur after ligand binding. Nothing in our bioactive compound screen shed light on this in particular, and so we can only speculate and have refrained from drawing further conclusions in the text.

How do potential transient ligand binding and the time-dependent heterogeneity in motion (see comment above) contribute to this? Also, in line 216 the authors write "with no evidence" of transient diffusive states. How do they define transient diffusive states? While there are toolboxes to directly extract the existence and abundance of these either by HMM analysis or temporal segmentation, the authors do not discuss or use them.

Throughout the analysis in this work, we consider all of tracks with a 2-second FOV as representative of a single underlying population and have not looked at changes in dynamics within a single movie. As we show in the supplemental figures we added (see Figure 3, figure supplement 1), this appears to be a reasonable assumption, at least in the cases we’ve encountered in this manuscript. For experiments involving changes in dynamics over time, these are experiments where we’ve added compound simultaneous with imaging and collect many 2-second FOVs in sequence to monitor changes in ER dynamics. In this case when we refer to “transient states,” we are pointing out that we don’t observe any new states in the State Array diagram that exist in early time points but disappear at later time point.

The reviewer suggests track-level analysis methods like hidden Markov models or variational Bayesian approaches which have been used previously in the single molecule community. These are very powerful techniques, provided the trajectories are long (typically 100s of frames). In the case of molecules that diffuse quickly and can diffuse out of the focal plane, we don’t have the luxury of such long trajectories. This was demonstrated previously (Hansen et al 2017, Heckert el al 2022) and so we’ve adopted the State Array approach to inferring state occupations from short trajectories. As the reviewer rightly points out, this approach potentially loses information about state transitions or changes over time, but as of now we are not aware of any robust methods that work on short trajectories.

The authors discuss the methods for extracting kinetic information of ligand binding by diffusion. They should consider the temporal segmentation of heterogenous diffusion. There are numerous methods published in journals or BioRxiv based on analytical or deep learning tools to perform temporal segmentation. This could elevate their analysis of Kon and Koff.

We’re aware of a number of approaches for analyzing both high framerate SMT as well as long exposure residence time imaging. As we say above, we’re not aware of any methods that have been demonstrated to work robustly on short trajectories aside from the approaches we’ve taken. Similarly, for residence time imaging there are published approaches, but we’re not aware of any that would offer new insight into the experiments in this study. If the reviewer has specific suggestions for analytical approaches that we’re not aware of we would happily consider them.

Reviewer #3 (Public Review):

Summary:

The authors aim to demonstrate the effectiveness of their developed methodology, which utilizes super-resolution microscopy and single-molecule tracking in live cells on a high-throughput scale. Their study focuses on measuring the diffusion state of a molecule target, the estrogen receptor, in both ligand-bound and unbound forms in live cells. By showcasing the ability to screen 5067 compounds and measure the diffusive state of the estrogen receptor for each compound in live cells, they illustrate the capability and power of their methodology.

Strengths:

Readers are well introduced to the principles in the initial stages of the manuscript with highly convincing video examples. The methods and metrics used (fbound) are robust. The authors demonstrate high reproducibility of their screening method (R2=0.92). They also showcase the great sensitivity of their method in predicting the proliferation/viability state of cells (R2=0.84). The outcome of the screen is sound, with multiple compounds clustering identified in line with known estrogen receptor biology.

Weaknesses:

• Potential overstatement on the relationship of low diffusion state of ER bound to compound and chromatin state without any work on chromatin level.

We appreciate the reviewers caution in over-interpreting the relationship between an increase in the slowest diffusing states that we observe by SMT and bona fide engagement with chromatin. In the case of the estrogen receptor there is strong precedent in the literature showing increases in chromatin binding and chromatin accessibility (as measured by ChIP-seq and ATAC-seq) upon treatment with either estradiol or SERM/Ds. Taken together with the RNA-seq, we felt it reasonable to assume all the trajectories with a diffusion coefficient less that 0.1 µm2/sec were chromatin bound.

• Could the authors clarify if the identified lead compound effects are novel at any level?

Most of the compounds we characterize in the manuscript have not previously been tested in an SMT assay, but many are known to functionally impact the ER or other SHRs based on other biochemical and functional assays. We have not described here any completely novel ER-interacting compounds, but to our knowledge this is the first systematic investigation of a protein showing that both direct and indirect perturbation can be inferred by observing the protein’s motion. Especially for the HSP90 inhibitors, the observation that inhibiting this complex would so dramatically increase ER chromatin-binding as opposed to increasing the speed of the free population is counterintuitive and novel.

• More video example cases on the final lead compounds identified would be a good addition to the current data package.

Reviewer #1 (Recommendations For The Authors):

General:

• More information on the microscope setup and analysis procedures should be given. Since custom code is used for automated image registration, spot detection, tracking, and analysis of dynamics, this code should be made publicly available.

Results:

• line 97: more details about the robotic system and automatic imaging, imaging modalities, and data analysis procedures should be given directly in the text.

Additional information added to text and methods

• line 100: we generated three U2OS cell lines --> how?

Additional information added to text and methods

• line 101: ectopically expressing HaloTag fused proteins --> how much overexpression did cells show?

The L30 promoter tends to produce fairly low expression levels. The same approach was used for all ectopic expression plasmids, and for the SHRs the expression levels were all comparable to endogenous levels. We have not checked this for H2B, Caax and free Halo but given that the necessary dye concentration to achieve similar spot densities is within a 10-fold range for all constructs, its reasonable to say that those clonal cell lines will also have modest Halotag expression.

• line 107: Single-molecule trajectories measured in these cell lines yielded the expected diffusion coefficients --> how was data analysis performed?

Additional information added to text and methods

• line 109: how was the localization error determined?

Additional information added to text and methods

• line 155: define occupation-weighted average diffusion coefficient.

Additional information added to text and methods

• line 157: with 34% bound in basal conditions and 87% bound after estradiol treatment  contradicts figure 2b, where the bound fraction is up to 50% after estradiol treatment.

Line 157 is the absolute fraction bound, figure 2b is change in fbound

• line 205: Figure 2c is missing.

Fixed

• line 215: within minutes --> how was this data set obtained? which time bins were taken?

Additional information added to text and methods

• line 216: with no evidence of transient diffusive states  What is meant by transient diffusive state? It seems all time points have a diffusive component, which decreases over time.

Additional information added to text and methods

The diffusive peak decreases, the bound peak increases but no other peaks emerge during that time (e.g. neither super fast nor super slow)

• line 225: it seems that fbound of GDC-0810 and GDC-0927 are rather similar in FRAP experiments, please comment, how was FRAP done?

FRAP is in the methods section. The curves and recovery times are quite distinct, is the reviewer looking at

• line 285: reproducibly: how often was this repeated?

Information added to the manuscript

• line 285: it would be necessary to name all of the compounds that were tested, e.g. with an ID number in the graph and a table. This also refers to extended data 7 and 8.

Additional supplemental file with the list of bioactive compounds tested will be included.

• line 290/1: what is meant by vendor-provided annotation was poorly defined?

Additional information added to text and methods. Specifically, the “other” category is the most common category, and it includes both compounds with unknown targets/functions as well as compound where the target and pathway are reasonably well documented. Hence, we applied our own analysis to better understand the list of active compounds.

Figures:

• fig. 2-6: detailed statistics are missing (number of measured cells, repetitions, etc.).

We have added clarifying information, including an “experiment design and sample size” section in the Methods.

• fig. 3: the authors need to give a list with details about the 5067 compounds tested,

Additional supplemental file with the list of bioactive compounds tested will be included.

• extended data 1c: time axis does not correspond to the 1.5s of imaging in the text, results line 127.

Axes fixed

• extended data 3: panel c and d are mislabeled.

Panel labels fixed

Methods:

• line 746: HILO microscope: the authors need to explain how they can get such large fields of view using HILO

Additional details added to the materials and methods. The combination of the power of the lasers, the size of the incident beam out of the fiber optic coupling device and the sCMOS camera are the biggest components that enable detection over a larger field of view.

• line 761: it is common practice to publish the analysis code. Since the authors wrote their own code, they should publish it

Our software contains proprietary information that we cannot yet release publicly. Comparable results can be achieved with HILO data using publicly-available tools like utrack. State Arrays code is distributed and the parameters used are listed in the M&M.

Reviewer #2 (Recommendations For The Authors):

The writing and presentation are coherent, concise, and easy to follow.

The authors should consider justifying the following:

Why is 1.5s imaging time selected? Topological and ligand variations may last significantly longer than this. The authors should present at least for one condition the same effect images for longer.

Related to the similar comment above, we added a figure examining the jump length distribution as a function of frame. Over the 6 seconds of data collection the jump length distribution is unchanged, suggesting it is reasonable to consider all the trajectories within an FOV as representative of the same underlying dynamical states.

The authors miss the k test or T test in their graphs.

We chose to apply the Kurskal-Wallis test in the context of the bioactive screen to assess whether a grouping of compounds based on their presumed cellular target was significantly different from the control even when individual compounds might not by themselves raise to significance. In this case many of the pathway inhibitors are subtle and not necessarily obvious in their difference. In the other cases throughout the manuscript, whether two conditions are statistically distinguishable is rarely in question and of far less importance to the conclusions in the manuscript than the magnitude of the difference. We’ve added statistical tests where appropriate.

The overall integrated area of Fig 4a appears to reduce upon ligand addition. Data appear normalized but the authors should also add N (number of molecules) on top of the graphs.

While the integrated area may appear to decrease, all State Array analysis is performed by first randomly sampling 10,000 trajectories from the assay well and inferring state distribution on those 10,000. This has been clarified in the figure legend and in the Methods.

Minor

Extended Figure 3 legend c, d appear swapped and incorrectly named in the text.

Panel labels fixed

L 197 but this appears not to BE a general feature of SHRs (maybe missing Be).

Error fixed

L205 authors refer to Figure 2c, which does not exist.

Panel reference fixed

Reviewer #3 (Recommendations For The Authors):

Among minor issues:

In Figure 1B, if the authors could specify how they discriminate the specific cell lines from the mixed context, it would enhance clarity. Could they perform additional immunofluorescence to understand how the assignment is determined? Alternatively, could they also show the case with isolated cell lines in an unmixed context?

Immunofluorescence would be a challenge given that there is not a good epitope to distinguish the three ectopically-expressed genes from each other or from endogenous proteins in the case of H2B and CaaX. We are really reliant on the single cell dynamics to determine the likely cell identity. That said, we’ve added graphs of a number of individual cell State Arrays from the same data graphed in 1A which support the notion that it’s reasonable to assume a cells identity given the observed dynamics.

In Extended Figure 2F: possibly a CHip-Seq experiment would be more directly qualified to state the effect of ER ligand on ER ability to bind chromatin.

This is true. Presumably ER that is competent at activating transcription of ER-responsive genes is also capable of binding DNA. ChIP would be the more direct measure, but would not address whether the protein was functional. We chose to balance these measuring these two aspects of ER biology by pairing dynamics with the end-point transcription readout.

In Figure 3: A representation with plate-by-plate orientation along the x-axis, with controls included in each plate, would be more appropriate to reflect the consistency of the controls used in the assay across different plates. Currently, all controls are pooled in one location, and we cannot appreciate how the controls vary from plate to plate.

Figure added to the supplement

Also in this figure, a general workflow of the screen down to segmentation/analysis would be a great add-on.

New figure added to the supplement and reflected in the textual description of the platform

In Extended Figures 3B and C an add-on of the positive and negative control would make the figure more convincing.

Addressed as part of figure added to the supplement

Is there any description of compound leads identified that is novel in nature in relation to impact on ER, and if so could it be stated more clearly in the text as novel finding?

To our knowledge, the impact of HSP inhibition in increasing ER-chromatin association has never been described, neither has the link between inhibition post-translation modifying enzymes like the CDKs or mTOR and ER dynamics ever been described. We added clarifying text to the manuscript

eLife assessment

This work presents an important technological advance, in the form of a high throughput platform for Single Particle Tracking allowing us to measure millions of cells and thousands of compounds per day. Analysis of the diffusional behaviour of fluorescently-tagged targets permits the identification of, and differentiation between, small molecules that bind directly or affect the target indirectly. The methodology and metrics employed are compelling, leading to the identification of multiple compounds that effectively change the diffusive state of the estrogen receptor, the POC target of the study.

Reviewer #1 (Public Review):

Summary:

The authors set up a pipeline for automated high-through single-molecule fluorescence imaging (htSMT) in living cells and analysis of molecular dynamics.

Strengths:

htSMT reveals information on the diffusion and bound fraction of molecules, dose-response curves, relative estimates on binding rates, and temporal changes of parameters. It enables the screening of thousands of compounds in a reasonable time and proves to be more sensitive and faster than classical cell-growth assays. If the function of a compound is coupled to the mobility of the protein of interest or affects an interaction partner, which modulates the mobility of the protein of interest, htSMT allows identifying the modulator and getting the first indication on the mechanism of action or interaction networks, which can be a starting point for more in-depth analysis. The authors describe their automated imaging and analysis procedures as well as the measures taken to assure data and analysis quality.

Weaknesses:

While elegantly showcasing the power of high-throughput measurements, htSMT relies on a sophisticated robot-based workflow and several microscopes for parallel imaging, thus limiting wide-spread application of htSMT by other scientists.

Reviewer #3 (Public Review):

Summary:

The authors aim to demonstrate the effectiveness of their developed methodology, which utilizes super-resolution microscopy and single-molecule tracking in live cells on a high-throughput scale. Their study focuses on measuring the diffusion state of a molecule target, the estrogen receptor, in both ligand-bound and unbound forms in live cells. By showcasing the ability to screen 5067 compounds and measure the diffusive state of the estrogen receptor for each compound in live cells, they illustrate the capability and power of their methodology.

Readers are well introduced to the principles in the initial stages of the manuscript with highly convincing video examples. The methods and metrics used (fbound) are robust. The authors demonstrate high reproducibility of their screening method (R2=0.92). They also showcase the great sensitivity of their method in predicting the proliferation/viability state of cells (R2=0.84). The outcome of the screen is sound, with multiple compounds clustering identified in line with known estrogen receptor biology.

This article points out the importance of understanding the demographics and engagement patterns on social media platforms like Twitter, especially regarding their impact on public discourse and political narratives. This article is mainly about discussing the characteristics and behaviors of U.S. adult Twitter users compared to the general public. It reveals that Twitter users are younger, more educated, and more likely to identify as Democrats. Additionally, it indicates that a small group of Twitter users contribute a significant portion of tweets, showing the disparity in users' engagement levels.

I think social media platforms should implement clear guidelines and effective moderation tools to encourage good crowdsourcing. The platform's rule should outline acceptable behavior and consequences for violations. Also, active community engagement, including incentives for quality contributions and education on responsible online behavior, can be effective. In addition, transparency about data usage and decision-making processes builds trust and encourages users to participate positively.

Author response:

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

Reviewer #1:

Detection of early-stage colorectal cancer is of great importance. Recently, both laboratory scientists and clinicians have reported different exosomal biomarkers to identify colorectal cancer patients.

Here, the authors exhibited a full RNA landscape for plasma exosomes of 60 individuals, including 31 colorectal cancer (CRC) patients, 19 advanced adenoma (AA) patients, and 10 noncancerous controls. RNAs with high fold change, high absolute abundance, and various module attribution were used to construct RT-qPCR-based RNA models for CRC and AA detection.

Overall, this is a well-performed proof-of-concept study to highlight exosomal RNAs as potential biomarkers of early-stage colorectal cancer and its precancerous lesions.

Thank you for your careful evaluation and valuable suggestions, which have provided valuable guidance for the improvement of our paper. In response to your feedback, we have implemented the following improvements.

(1) Depicting the full RNA landscape of circulating exosomes is still quite challenging. The authors annotated 58,333 RNA species in exosomes, most of which were lncRNAs, but the authors do not explain how they characterized those RNAs.

Author response and action taken: Thanks for your comments. In the Supplementary Methods section titled "Identification of mRNAs and lncRNAs", we have provided a comprehensive explanation on the characterization of mRNAs and lncRNAs to address the concerns you raised. Characterization of long-chain RNAs is a great challenge. For lncRNA analysis, the transcriptome was assembled using the Cufflinks and Scripture based on the reads mapped to the reference genome. The assembled transcripts were annotated using the Cuffcompare program from the Cufflinks package. The unknown transcripts were used to screen for putative lncRNAs.

(2) The authors tested their models in a medium size population of 124 individuals, which is not enough to obtain an accurate evaluation of the specificity and sensitivity of the biomarkers proposed here. External validation would be required.

Author response and action taken: Thanks for your comments. We fully acknowledge the significance of external validations in the evaluation of diagnostic model performance. Unfortunately, as a pilot study, we currently do not have the conditions for a multicenter investigation. To mitigate result bias and overfitting effects, we implemented a rigorous variable selection strategy and enhanced model stability through 10-fold cross-validation. In the meantime, we will persist in our efforts to elevate the quality of our research and seek additional resources for external validation in future studies.

Reviewer #2:

The authors present an important study on the potential of small extracellular vesicle (sEV)-derived RNAs as biomarkers for the early detection of colorectal cancer (CRC) and precancerous adenoma (AA). The authors provide a detailed analysis of the RNA landscape of sEVs isolated from participants, identifying differentially expressed sEV-RNAs associated with T1a stage CRC and AA compared to normal controls. The paper further categorises these sEV-RNAs into modules and constructs a 60-gene model that successfully distinguishes CRC/AA from NC samples. The authors also validate their findings using RT-qPCR and propose an optimised classifier with high specificity and sensitivity. Additionally, the authors discuss the potential of sEV-RNAs in understanding CRC carcinogenesis and suggest that a comprehensive biomarker panel combining sEV-RNAs and proteins could be promising for identifying both early and advanced CRC patients. Overall, the study provides valuable insights into the potential clinical application of sEV-RNAs in liquid biopsy for the early detection of CRC and AA.

Major strengths:

(1) Comprehensive sEV RNA profiling: The study provides a valuable dataset of the whole-transcriptomic profile of circulating sEVs, including miRNA, mRNA, and lncRNA. This approach adds to the understanding of sEV-RNAs' role in CRC carcinogenesis and facilitates the discovery of potential biomarkers.

(2) Detection of early-stage CRC and AA: The developed 60-gene t-SNE model successfully differentiated T1a stage CRC/AA from normal controls with high specificity and sensitivity, indicating the potential of sEV-RNAs as diagnostic markers for early-stage colorectal lesions.

(3) Independent validation cohort: The study combines RNA-seq, RT-qPCR, and modelling algorithms to select and validate candidate sEV-RNAs, maximising the performance of the developed RNA signature. The comparison of different algorithms and consideration of other factors enhance the robustness of the findings.

Thank you for your careful evaluation and valuable suggestions. These comments have been highly valuable for the performance evaluation and clinical applications of our work. In response to your feedback, we have implemented the following improvements.

(1). Lack of analysis on T1-only patients in the validation cohort: While the study identifies key sEV-RNAs associated with T1a stage CRC and AA, the validation cohort is only half of the patients in T1(25 out of 49). It would be better to do an analysis using only the T1 patients in the validation cohort, so the conclusion is not affected by the T2-T3 patients.

Author response and action taken: Thanks for your comments. This feedback is essential for ensuring consistency in the results with our previous findings. In this context, we revalidated various diagnostic panels using exclusively Stage I patients (Figure 7—figure supplement 2). To minimize the potential overfitting effect due to the reduction in sample size after partitioning, we implemented a 10-fold cross-validation for each panel and these panels exhibit promising performance in Stage I colorectal cancer (CRC) patients.

Author response image 1.

The ROC analysis of different sEV-RNA signatures in the prediction of Stage I CRC patients by different algorithms (a: 6-gene panel; b: 7-gene panel; c: 8-gene panel; d: 9-gene panel).

(2). Lack of performance analysis across different demographic and tumor pathology factors listed in Supplementary Table 12. It's important to know if the sEV-RNAs identified in the study work better/worse in different age/sex/tumor size/Yamada subtypes etc.

Author response and action taken: Thanks for your comments. This feedback will be immensely beneficial for clinical diagnosis. Similarly, cross-validation was performed in this section. We assessed the discriminative effects of CRC on NC, taking into account different age groups, genders, tumor sizes, and anatomical locations (Figure 7—figure supplement 3). Overall, these sEV RNA panels perform better in individuals under the age of 55 and in female patients. There is no significant difference in discriminative effects across different tumor sizes. Compared to rectal cancer, the discriminative effects are better in colon cancer.

Author response image 2.

The ROC analysis of different sEV-RNA signatures for predicting CRC patients using the Lasso regression algorithm in different clinical parameters (ab: age; cd: gender; ef: tumor size; gh: anatomical position).

eLife assessment

This study presents a useful description of RNA in extracellular vesicles (EV-RNAs) and highlights the potential to develop biomarkers for the early detection of colorectal cancer (CRC) and precancerous adenoma (AA). The data were analysed using overall solid methodology and would benefit from further validation of predicted lncRNAs and biomarker validation at each stage of CRC/AA to evaluate the potential application to early detection of CRC and AA.

Joint Public Review:

Detection of early-stage colorectal cancer is of great importance. Laboratory scientists and clinicians have reported different exosomal biomarkers to identify colorectal cancer patients. This is a proof-of-principle study of whether exosomal RNAs, and particularly predicted lncRNAs, potential biomarkers of early-stage colorectal cancer and its precancerous lesions.

Strengths:

The study provides a valuable dataset of the whole-transcriptomic profile of circulating sEVs, including miRNA, mRNA, and lncRNA. This approach adds to the understanding of sEV-RNAs' role in CRC carcinogenesis and facilitates the discovery of potential biomarkers.

The developed 60-gene t-SNE model successfully differentiated T1a stage CRC/AA from normal controls with high specificity and sensitivity, indicating the potential of sEV-RNAs as diagnostic markers for early-stage colorectal lesions.

The study combines RNA-seq, RT-qPCR, and modelling algorithms to select and validate candidate sEV-RNAs, maximising the performance of the developed RNA signature. The comparison of different algorithms and consideration of other factors enhance the robustness of the findings.

Weaknesses:

Validation in larger cohorts would be required to establish as biomarkers, and to demonstrate whether the predicted lncRNAs implicated in these biomarkers are indeed present, and whether they are robustly predictive/prognostic.

Author response:

Following our first submission last August, we have received positive feedback on the relevance and interesting aspect of our work. However, a functional validation was requested to strengthen our findings. Specifically, the rejection was motivated as such:

“Although the authors presented certain pieces of evidence from hMSC cell line experiments and mouse subcutaneous implantation studies, indicating the involvement of elements from eECM in endogenous repair, the study is not of sufficient depth. Additional validation of the findings within a context such as bone repair/regeneration is lacking.”

We have addressed the raised concern by implementing the following major changes:

(1) An ex vivo Chorioallantoic Membrane (CAM) assay was performed, to functionally assess the angiogenic potential of VEGF-edited ECMs. We confirmed the capacity of engineered ECMs to promote vessel formation, in line with ectopic in vivo assessment in mouse. Findings are implemented as Figure 2A, 2B and 2C, and as Supplementary figure 2A.

(2) The regenerative potential of RUNX2-edited ECMs was evaluated in a rat osteochondral defect model. The model was selected in order to assess both the potential of our engineered ECMs to participate in cartilage and/or bone regeneration. In short, our findings demonstrate that RUNX2edited eECMs significantly enhanced cartilage regeneration. In contrast, the non-edited ECMs exhibiting clear sign of cartilage hypertrophy- could not promote joint repair in the model. Findings are implemented in an entirely new figure panel (Figure 5), with Supplementary Figure 5, Table 1 and supplementary Table 1.

In addition, beyond the suggested functional validation of our eECMs we have also compiled new data reinforcing our previous claim. This is now implemented as:

• Figure 1G: Immunofluorescence stainings of engineered cartilage ECMs generated by the MSOD-B and MSOD-BΔV1 lines, respectively. These stainings confirmed strong content in collagen type I and collagen type X in the tissues, while vascular endothelial growth factor (VEGF) is poorly detectable in the edited MSOD-BΔV1 ECMs.

• Figure 3I: A 2D osteogenic differentiation assessment of the MSOD-B and MSOD-BΔR1 cells was performed in vitro. We could confirm the functional impact of RUNX2 knock-down on the osteogenic potential of MSOD-BΔR1 cells, as no mineralized matrix was deposited by the cells.

• Figure 3J: We implemented a gene expression profile analysis of MSOD-B and MSOD-BΔR1, stimulated or not with pro-osteogenic medium for three weeks. In line, with the results presented in Figure 3I, we could confirm an impairment in the expression of key osteoblastic-associated genes (RUNX2, COLX, ALPL) in MSOD-BΔR1 cells.

Altogether, we have compiled additional in vitro and in vivo evidence on the impact of CRISPR/Cas9 knock-out leading to eECMS customized in composition and function. Our findings significantly consolidate and strengthen our previous observations.

eLife assessment

The study presents a potentially useful approach to genetically modify cells to produce extracellular matrices with altered compositions. The evidence supporting the authors' conclusions regarding the chondrogenicity of lyophilized constructs is considered incomplete, as the study does not adequately demonstrate the formation of a histologically identifiable cartilaginous matrix. The study also lacks several significant details and does not have sufficient power to support the conclusions.

Reviewer #1 (Public Review):

Summary:

The authors aimed to modify the characteristics of the extracellular matrix (ECM) produced by immortalized mesenchymal stem cells (MSCs) by employing the CRISPR/Cas9 system to knock out specific genes. Initially, they established VEGF-KO cell lines, demonstrating that these cells retained chondrogenic and angiogenic properties. Additionally, lyophilized carriage tissues produced by these cells exhibited retained osteogenic properties.

Subsequently, the authors established RUNX2-KO cell lines, which exhibited reduced COLX expression during chondrogenic differentiation and notably diminished osteogenic properties in vitro. Transplantation of lyophilized carriage tissues produced by RUNX2-KO cell lines into osteochondral defects in rat knee joints resulted in the regeneration of articular cartilage tissues as well as bone tissues, a phenomenon not observed with tissues derived from parental cells. This suggests that gene-edited MSCs represent a valuable cell source for producing ECM with enhanced quality.

Strengths:

The enhanced cartilage regeneration observed with ECM derived from RUNX2-KO cells supports the authors' strategy of creating gene-edited MSCs capable of producing ECM with superior quality. Immortalized cell lines offer a limitless source of off-the-shelf material for tissue regeneration.

Weaknesses:

Most data align with anticipated outcomes, offering limited novelty to advance scientific understanding. Methodologically, the chondrogenic differentiation properties of immortalized MSCs appeared deficient, evidenced by Safranin-O staining of 3D tissues and histological findings lacking robust evidence for endochondral differentiation. This presents a critical limitation, particularly as authors propose the implantation of cartilage tissues for in vivo experiments. Instead, the bulk of data stemmed from type I collagen scaffold with factors produced by MSCs stimulated by TGFβ.

The rationale behind establishing VEGF-KO cell lines remains unclear. What specific outcomes did the authors anticipate from this modification?

Insufficient depth was given to elucidate the disparity in osteogenic properties between those observed in ectopic bone formation and those observed in transplantation into osteochondral defects. While the regeneration of articular cartilage in RUNX2-KO ECM presents intriguing results, the study lacked an exploration into underlying mechanisms, such as histological analyses at earlier time points.

Reviewer #2 (Public Review):

The manuscript submitted by Sujeethkumar et al. describes an alternative approach to skeletal tissue repair using extracellular matrix (ECM) deposited by genetically modified mesenchymal stromal/stem cells. Here, they generate a loss of function mutations in VEGF or RUNX2 in a BMP2-overexpressing MSC line and define the differences in the resulting tissue-engineered constructs following seeding onto a type I collagen matrix in vitro, and following lyophilization and subcutaneous and orthotopic implantation into mice and rats. Some strengths of this manuscript are the establishment of a platform by which modifications in cell-derived ECM can be evaluated both in vitro and in vivo, the demonstration that genetic modification of cells results in complexity of in vitro cell-derived ECM that elicits quantifiable results, and the admirable goal to improve endogenous cartilage repair. However, I recommend the authors clarify their conclusions and add more information regarding reproducibility, which was one limitation of primary-cell-derived ECMs.

Overcoming the limitations of native/autologous/allogeneic ECMs such as complete decellularization and reduction of batch-to-batch variability was not specifically addressed in the data provided herein. For the maintenance of ECM organization and complexity following lyophilization, evidence of complete decellularization was not addressed, but could be easily evaluated using polarized light microscopy and quantification of human DNA for example in constructs pre and post-lyophilization. It would be ideal to see minimization of batch-to-batch variability using this approach, as mitigation of using a sole cell line is likely not sufficient (considering that the sole cell line-derived Matrigel does exhibit batch-to-batch and manufacturer-to-manufacturer variability).

I recommend adding details regarding experimental design and outcomes not initially considered. Inter- and intra-experimental reproducibility was not adequately addressed. The size of in vitro-derived cartilage pellets was not quantified, and it is not clear that more than one independent 'differentiation' was performed from each gene-edited MSC line to generate in vitro replicates and constructs that were implanted in vivo.

The use of descriptive language in describing conclusions may mislead the reader and should be modified accordingly throughout the manuscript. For example, although this reviewer agrees with the comparative statements made by the authors regarding parental and gene-edited MSC lines, non-quantifiable terms such as 'frank' 'superior' (example, line 242) are inappropriate and should rather be discussed in terms of significance. Another example is 'rich-collagenous matrix,' which was not substantiated by uniform immunostaining for type II collagen (line 189).

I have similar recommendations regarding conclusive statements from the rat implantation model, which was appropriately used for the purpose of evaluating the response of native skeletal cells to the different cell-derived ECMs. Interpretations of these results should be described with more accuracy. For example, increased TRAP staining does not indicate reduced active bone formation (line 237). Many would not conclude that GAGs were retained in the RUNX2-KO line graft subchondral region based on the histology. Quantification of % chondral regeneration using histology is not accurate as it is greatly influenced by the location in the defect from which the section was taken. Chondral regeneration is usually semi-quantified from gross observations of the cartilage surface immediately following excision. The statements regarding integration (example line 290) are not founded by histological evidence, which should show high magnification of the periphery of the graft adjacent to the native tissue.

Reviewer #3 (Public Review):

Summary:

In this study, the authors have started off using an immortalized human cell line and then gene-edited it to decrease the levels of VEGF1 (in order to influence vascularization), and the levels of Runx2 (to decrease chondro/osteogenesis). They first transplanted these cells with a collagen scaffold. The modified cells showed a decrease in vascularization when VEGF1 was decreased, and suggested an increase in cartilage formation.

In another study, the matrix generated by these cells was subsequently remodeled into a bone marrow organ. When RUNX2 was decreased, the cells did not mineralize in vitro, and their matrices expressed types I and II collagen but not type X collagen in vitro, in comparison with unedited cells. In vivo, the author claims that remodeling of the matrices into bone was somewhat inhibited. Lastly, they utilized matrices generated by RUNX2 edited cells to regenerate chondro-osteal defects. They suggest that the edited cells regenerated cartilage in comparison with unedited cells.

Strengths:

-The notion that inducing changes in the ECM by genetically editing the cells is a novel one, as it has long been thought that ECM composition influences cell activity.

-If successful, it may be possible to make off-the-shelf ECMS to carry out different types of tissue repair.

Weaknesses:

-The authors have not generated histologically identifiable cartilage or bone in their transplants of the cells with a type I scaffold.

-In many cases, they did not generate histologically identifiable cartilage with their cell-free-edited scaffold. They did generate small amounts of bone but this is most likely due to BMPs that were synthesized by the cells and trapped in the matrix.

-There is a great deal of missing detail in the manuscript.

-The in vivo study is underpowered, the results are not well documented pictorially, and are not convincing.

-Given the fact that they have genetically modified cells, they could have done analyses of ECM components to determine what was different between the lines, both at the transcriptome and the protein level. Consequently, the study is purely descriptive and does not provide any mechanistic understanding of what mixture of matrix components and growth factors works best for cartilage or bone. But this presupposes that they actually induced the formation of bona fide cartilage, at least.

eLife assessment

This important study, which presents novel data on variation in sperm whale communication, contributes to a richer understanding of the social transmission of vocal styles across neighbouring clans. The evidence is solid but could be further improved with some clarification of the specialized measurements and terms used, particularly for comparisons to other taxa. This research will be of interest for bioacoustics and animal communication specialists, particularly those working on social learning and culture.

Reviewer #1 (Public Review):

Summary:

This manuscript presents evidence of 'vocal style' in sperm whale vocal clans. Vocal style was defined as specific patterns in the way that rhythmic codas were produced, providing a fine-scale means of comparing coda variations. Vocal style effectively distinguished clans similar to the way in which vocal repertoires are typically employed. For non-identity codas, vocal style was found to be more similar among clans with more geographic overlap. This suggests the presence of social transmission across sympatric clans while maintaining clan vocal identity.

Strengths:

This is a well-executed study that contributes exciting new insights into cultural vocal learning in sperm whales. The methodology is sound and appropriate for the research question, building on previous work and ground-truthing much of their theories. The use of the Dominica dataset to validate their method lends strength to the concept of vocal style and its application more broadly to the Pacific dataset. The results are framed well in the context of previous works and clearly explain what novel insights the results provide to the current understanding of sperm whale vocal clans. The discussion does an overall great job of outlining why horizontal social learning is the best explanation for the results found.

Weaknesses:

The primary issues with the manuscript are in the technical nature of the writing and a lack of clarity at times with certain terminology. For example, several tree figures are presented and 'distance' between trees is key to the results, yet 'distance' is not clearly defined in a way for someone unfamiliar with Markov chains to understand. However, these are issues that can easily be dealt with through minor revisions with a view towards making the manuscript more accessible to a general audience.

I also feel that the discussion could focus a bit more on the broader implications - specifically what the developed methods and results might imply about cultural transmission in other species. This is specifically mentioned in the abstract but not really delved into in detail during the discussion.

Reviewer #2 (Public Review):

Summary:

The current article presents a new type of analytical approach to the sequential organisation of whale coda units.

Strengths:

The detailed description of the internal temporal structure of whale codas is something that has been thus far lacking.

Weaknesses:

It is unclear how the insight gained from these analyses differs or adds to the voluminous available literature on how codas varies between whale groups and populations. It provides new details, but what new aspects have been learned, or what features of variation seem to be only revealed by this new approach?<br /> The theoretical basis and concepts of the paper are problematical and indeed, hamper potentially the insights into whale communication that the methods could offer. Some aspects of the results are also overstated.

Reviewer #3 (Public Review):

Summary:

The study presented by Leitao et al., represents an important advancement in comprehending the social learning processes of sperm whales across various communicative and socio-cultural contexts. The authors introduce the concept of "vocal style" as an addition to the previously established notion of "vocal repertoire," thereby enhancing our understanding of sperm whale vocal identity.

Strengths:

A key finding of this research is the correlation between the similarity of clan vocal styles for non-ID codas and spatial overlap (while no change occurs for ID codas), suggesting that social learning plays a crucial role in shaping symbolic cultural boundaries among sperm whale populations. This work holds great appeal for researchers interested in animal cultures and communication. It is poised to attract a broad audience, including scholars studying animal communication and social learning processes across diverse species, particularly cetaceans.

Weaknesses:

In terms of terminology, while the authors use the term "saying" to describe whale vocalizations, it may be more conservative to employ terms like "vocalize" or "whale speech" throughout the manuscript. This approach aligns with the distinction between human speech and other forms of animal communication, as outlined in prior research (Hockett, 1960; Cheney & Seyfarth, 1998; Hauser et al., 2002; Pinker & Jackendoff, 2005; Tomasello, 2010).

Author response:

We thank the reviewers for their positive assessments and constructive feedback.

In light of their comments, we will aim to improve the explanation of the methods and interpretation of results, as well as their relation to well-established literature in this research area.

The major contributions of our work are threefold:

• First, we introduce a novel way of analyzing codas that specifically targets subcoda structures by considering inter-click intervals within codas in terms of transition probabilities. By describing codas’ click patterns via Variable Length Markov Chains, we do not need to consider codas in their entirety, but we can detect coda subunits.This enables a new dimension for quantitatively comparing differences among various individuals, social units, and clans; which we term ‘vocal style’.

• Using this approach, we reinforce findings from past research, including the idea that identity codas function as symbolic markers of vocal clan identity (Hersh et al., 2022; Sharma et al., 2024). More importantly, we offer new insights into the function of non-identity codas, which comprise the majority of coda types produced by sperm whales but have been largely uncharacterized. 

• Our work reveals that non-identity coda vocal styles are more similar for spatially overlapped clans, and suggests that this similarity in style may be maintained by social learning across clan boundaries. This opens up a paradigm shift in our understanding of between-clan acoustic interactions.

From a broader perspective, our work builds on two well-established research areas: the form and function of sperm whale codas, and statistical generative models, specifically Variable Length Markov Chains on finite data spaces. Our methods, results, and interpretations are grounded in theories and concepts from these fields.

For clarity, we will ensure that our terminology aligns with field standards and existing research. We will clearly introduce each key theory or concept at first mention and justify its relevance. In particular, we will clarify the definition and meaning of the distance between subcoda trees for a general audience. We agree with the reviewers’ comments on the broader implications and will refine our work accordingly.

eLife assessment

This important study highlights the role of SLAM-SAP signaling in shaping innate-like γδ T cell subsets, providing compelling evidence for the importance of SLAM-SAP in immune system regulation, and the potential implications of the findings for tumor surveillance and infectious disease management. The work will be of broad interest to immunologists.

Author response:

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

eLife assessment

Both reviewers positively received the manuscript, in general. The agreement was that the manuscript presented valuable findings, using solid techniques and approaches, that shed additional light into how the canine distemper virus hemagglutinin might engage cellular receptors and how that engagement impacts host tropism. While both reviewers appreciated the X-ray crystallographic data, they also felt that the AFM experiments could have been performed at a higher standard and that the interpretation of the results ensuing from those AFM experiments could have been explained more thoroughly and in simpler terms. An additional missed opportunity of the current manuscript is the lack of comparison of the crystal structure to that of the already published cryo-EM structure, for context.

Thank you very much for constructive comments of the editor and reviewers. Following your comments, we have changed the text related to the AFM experiments with simpler terms as follows.

“When CDV-H was loaded onto a mica substrate and scanned with a cantilever to acquire images of attached molecules, the CDV-H dimer was observed as two globules clustered together in most cases, but sometimes, each domain moved independently (Fig. 7B and Supplementary Movie). Time-course analysis of the dynamics of the representative CDV-H dimer showed that CDV-H could adopt both associated and dissociated forms (Fig. 7C). The distances between the domains were calculated by measuring those between the centers of mass of each domain. Finally, the distribution of distances between each head domain in the CDV-H dimers showed approximately 15 nm as a major peak (Fig. 7D). This is a reasonable length for the linker between the head domain dimers.” in Page 11, Lines 8-17.

With regards to the structural comparison between cryo-EM structure published in Proc. Natl. Acad. Sci. U. S. A. (2023) 120, e2208866120 and our crystal structure, we have compared these structures for Cα on page 6 and added the following text. “A recent cryo-EM structure of the wild-type CDV-H ectodomain revealed that the head dimer is located on one side of the stalk region in solution (Proc. Natl. Acad. Sci. U. S. A. (2023) 120, e2208866120)” in Page 14, Lines 22-24.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

Fukuhara, Maenaka, and colleagues report a crystal structure of the canine distemper virus (CDV) attachment hemagglutinin protein globular domain. The structure shows a dimeric organization of the viral protein and describes the detailed amino-acid side chain interactions between the two protomers. The authors also use their best judgement to comment on predicted sites for the two cellular receptors - Nectin-4 and SLAM - and thus speculate on the CDV host tropism. A complementary AFM study suggests a breathing movement at the hemagglutinin dimer interface.

Strengths:

The study of CDV and related Paramyxoviruses is significant for human/animal health and is very timely. The crystallographic data seem to be of good quality.

Thank you very much for the constructive comment of the reviewer.

Weaknesses:

While the recent CDV hemagglutinin cryo-EM structure is mentioned, it is not compared to the present crystal structure, and thus the context of the present study is poorly justified. Additionally, the results of the AFM experiment are not unexpected. Indeed, other paramyxoviral RBP/G proteins also show movement at the protomer interface.

Thank you very much for constructive comments of the reviewer. When we submitted our manuscript to e-life, cryo-EM structure just published in Proc. Natl. Acad. Sci. U. S. A. (2023) 120, e2208866120 a week ago was not able to be available. Following the comment of the reviewer, we have added the text about the structural comparison between the cryo-EM structure and our crystal structure. We also have changed the text related to the AFM experiments to tone down the movement of the protomer interfaceas follows.

“This observation raises the possibility that each head domain of CDV-H also dissociates and moves flexibly, as shown in the structure of Nipah virus (NiV)-G protein, previously (Science (2022) 375, 1373–1378).” in Page 11, Lines 4-6.

Reviewer #2 (Public Review):

Summary:

The authors solved the crystal structure of CDV H-protein head domain at 3,2 A resolution to better understand the detailed mechanism of membrane fusion triggering. The structure clearly showed that the orientation of the H monomers in the homodimer was similar to that of measles virus H and different from other paramyxoviruses. The authors used the available co-crystal strictures of the closely related measles virus H structures with the SLAM and Nectin4 receptors to map the receptor binding site on CDV H. The authors also confirmed which N-linked sites were glycosylated in the CDV H protein and showed that both wildtype and vaccine strains of CDV H have the same glycosylation pattern. The authors documented that the glycans cover a vast majority of the H surface while leaving the receptor binding site exposed, which may in part explain the long-term success of measles virus and CDV vaccines. Finally, the authors used HS-AFM to visualize the real-time dynamic characteristics of CDV-H under physiological conditions. This analysis indicated that homodimers may dissociate into monomers, which has implications for the model of fusion triggering.

The structural data and analysis were thorough and well-presented. However, the HS-AFM data, while very exciting, was not presented in a manner that could be easily grasped by readers of this manuscript. I have some suggestions for improvement.

(1) The authors claim their structure is very similar to the recently published croy-EM structure of CDV H. Can the authors provide us with a quantitative assessment of this statement?

Thank you very much for constructive comments of the reviewer. When we submitted our manuscript to e-life, cryo-EM structure just published in Proc. Natl. Acad. Sci. U. S. A. (2023) 120, e2208866120 a week ago was not able to be available. Following the comment of the reviewer, we have added the text about the structural comparison between the cryo-EM structure and our crystal structure. We also have changed the text related to the AFM experiments to tone down the movement of the protomer interface as follows.

“This observation raises the possibility that each head domain of CDV-H also dissociates and moves flexibly, as shown in the structure of Nipah virus (NiV)-G protein, previously (Science (2022) 375, 1373–1378).” in Page 11, Lines 4-6.

(2) The results for the HS-AFM are difficult to follow and it is not clear how the authors came to their conclusions. Can the authors better explain this data and justify their conclusions based on it?

Thank you very much for constructive comments of the reviewer. Following your comments, we have changed the text related to the AFM experiments with simpler terms as follows.

“When CDV-H was loaded onto a mica substrate and scanned with a cantilever to acquire images of attached molecules, the CDV-H dimer was observed as two globules clustered together in most cases, but sometimes, each domain moved independently (Fig. 7B and Supplementary Movie). Time-course analysis of the dynamics of the representative CDV-H dimer showed that CDV-H could adopt both associated and dissociated forms (Fig. 7C). The distances between the domains were calculated by measuring those between the centers of mass of each domain. Finally, the distribution of distances between each head domain in the CDV-H dimers showed approximately 15 nm as a major peak (Fig. 7D). This is a reasonable length for the linker between the head domain dimers.” in Page 11, Lines 8-17.

(3) The fusion triggering model in Figure 8 is ambiguous as to when H-F interactions are occurring and when they may be disrupted. The authors should clarify this point in their model.

Thank you very much for constructive comments of the reviewer. Following your comments, we have changed the Figure 8 and its legend.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(1) AFM experiments with SLAM or Nectin-4 immobilized on the cantilever would be much more informative.

Thank you very much for the constructive comment of the reviewer. We will try this experiment in the next paper.

(2) The authors should compare their crystal structure to that of the reported cryo-EM structure.

With regards to the structural comparison between cryo-EM structure published in Proc. Natl. Acad. Sci. U. S. A. (2023) 120, e2208866120 and our crystal structure, we have added the text.

(3) Figure 1D - why does the beta2 MG negative control have such a high SPR signal?

Thank you very much for the constructive comment of the reviewer. The immobilization levels for b 2-microglobulin (beta2 MG), CDV-OP-H and CDV-5VD-H were similar, 1204.7 RU, 1235.7 RU, and 1504.5 RU, respectively. We applied relatively high concentrations (5 mM) of dNectin4 and hNectin4 onto the chip to determine low-affinity dissociation constants. Then, the signals for beta2 MG (negative control) were high. In other SPR experiments for cell surface receptors, such high signals for beta2 MG were often observed in our previous paper, Kuroki et al., J. Immunol. 2019 Dec 15;203(12):3386-3394. doi: 10.4049/jimmunol.1900562. Therefore, we think that these SPR signals are not unusual.

(4) Figure 1C - please indicate the Ve volume for the peak and add in Ve for standard.

Thank you very much for the constructive comment of the reviewer. We have indicated the Ve volume for the peak and added in Ve for standard in Figure 1C.

(5) The authors mention that one of the chains in the asymmetric unit was better resolved than the other. Please show regions of the atomic model fit regions of the electron density to convince the reader of the quality of your data.

Thank you very much for the constructive comment of the reviewer. We have added new Supplementary figure 2 for comparison of electron density maps of chains A and B.

(6) Table 2 indicates that the difference between Rw and Rf values is larger than 5% which indicates slight overfitting during refinement. Please provide details of your refinement strategy and attempt simulated annealing as a strategy to reduce this delta.

Thank you very much for the constructive comment of the reviewer. We further introduced TLS and NCS parameters for the refinement. Consequently, the R/Rfree factors became 0.2645/0.3092. Simulated annealing had been already carried out. All the refinement statistics in the table 2 are updated.

Reviewer #2 (Recommendations For The Authors):

(1) The authors' fusion triggering model was difficult to follow. For example, this sentence was difficult to understand: "The other possible models may include the monomer-dimer-tetramer transition facilitated by receptor binding for the fusion."

Thank you very much for the constructive comment of the reviewer. Following your comments, we have removed the above sentences and have added the detail mechanism of the proposed model in Discussion. Furthermore, we have changed the Figure 8 and its legend for readers to understand more clearly.

(2) Figure 5A is not called out in the main text.

Thank you very much for the constructive comment of the reviewer. Following your comments, we have added the text as follows.

“the crystal structure of MeV-H in complex with hNectin-4 showed that the H-SLAM interaction consists of three main sites (Fig. 5A) (Nat. Struct. Mol. Biol. (2013) 20, 67–72).” in Page 11, Lines 4-6.

(3) Page 9, Line 4: interspaces? Perhaps interphases.

Thank you very much for the constructive comment of the reviewer. We have changed the term “interspaces” to “internal spaces”.

(4) Page 12, penultimate line: The authors mention "epitopes for anti-MeV-H Abs." Do they mean anti-CDV-H Abs?

Thank you very much for the constructive comment of the reviewer. Following your comments, we have changed the “anti-MeV-H Abs” to “anti-morbillivirus H neutralizing antibodies”.

(5) The paper will benefit from an English language editor to help clarify what the authors are trying to convey.

Thank you very much for the constructive comment of the reviewer.

We have asked a English proof reading company to check.

eLife assessment

The manuscript presents valuable findings, using solid techniques and approaches, that shed additional light into how the canine distemper virus (CDV) hemagglutinin might engage cellular receptors and how that engagement impacts host tropism. The structural data and their analysis were thorough and well-presented. The HS-AFM data, which indicate that homodimers may dissociate into monomers - and thus have significant implications for the model of fusion triggering - are very exciting, but require further validation, perhaps by alternate approaches, to bolster the current molecular model of the CDV fusion triggering.

Reviewer #2 (Public Review):

The authors solved the crystal structure of CDV H-protein head domain at 3,2 A resolution to better understand the detailed mechanism of membrane fusion triggering. The structure clearly showed that the orientation of the H monomers in the homodimer was similar to that of measles virus H and different from other paramyxoviruses. The authors used the available co-crystal strictures of the closely related measles virus H structures with the SLAM and Nectin4 receptors to map the receptor binding site on CDV H. The authors also confirmed which N-linked sites were glycosylated in the CDV H protein and showed that both wildtype and vaccine strains of CDV H have the same glycosylation pattern. The authors documented that the glycans cover a vast majority of the H surface while leaving the receptor binding site exposed, which may in part explain the long-term success of measles virus and CDV vaccines. Finally, the authors used HS-AFM to visualize the real-time dynamic characteristics of CDV-H under physiological conditions. This analysis indicated that homodimers may dissociate into monomers, which has implications for the model of fusion triggering.

The structural data and analysis were thorough and well-presented. The HS-AFM data, while very exciting, needs to be further validated, perhaps by alternate approaches to further support the authors' model describing the molecular dynamics of fusion triggering.

moet zijn leakage (ik dacht dat we dit allang aangepast hadden)

This only adds confusion, may be entirely delelted.

The descending order, NL: aflopende volgorde

Is important to note

The more you learn, the more you tend to feel that you're "invincible".

You're gonna get humbled, soon.

W.S.V. Desda

Hype, dit ben ik

Nuttig

Nuttig

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

Learn more at Review Commons

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Reply to the reviewers

We thank the reviewers for their time and effort to improve and clarify our manuscript. We now have addressed the reviewers’ suggestions in full on a point-by-point basis. Revisions in the manuscript file are highlighted in yellow.

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

Supernumerary centrosomes are observed in the majority of human tumors. In cells they induce abnormal mitosis leading to chromosome missegregation and aneuploidy. In animal models it is demonstrated that extra centrosomes are sufficient to drive tumor formation. Previous work studying the impact of centrosome amplification on tumor formation in vivo used Plk4 overexpression to drive the formation of supernumerary centrosomes. In this manuscript Moussa and co-workers from the Krämer group developed a mouse model in which centrosome amplification is triggered by the overexpression of the structural centrosomal protein STIL rather than the kinase Plk4 in order to a) assess the potential for centrosome amplification induced by STIL overexpression to drive tumor formation and b) to rule out any potential non-centrosomal related effects of the kinase Plk4 on tumor formation.* The authors show that STIL ovexrexpression in cells (MEFs) drives centrosome amplification and aberrant mitosis (Fig. 1), leading to chromosome missegregation and aneuploidy (Fig. 2). They also show that STIL overexpression is linked to reduced cellular proliferation and apoptosis (Fig 3). The authors then present in vivo experiments performed in mice. They observed that STIL expression causes embryonic lethality, microcephaly and a reduced lifespan (Fig 4). Despite increased STIL mRNA levels they do not detect elevated STIL protein levels in adult tissues except for the spleen. They do not detect significant increase of centrosome amplification or aneuploidy in animal tissues (Fig 4) and they conclude of a STIL translational shut down in most adult tissues. The authors then assess the impact of STIL overexpression on tumor formation. They observed a reduced spontaneous tumor formation despite elevated STIL mRNA levels in both healthy and tumor (lymphomas) tissues of mice overexpressing STIL. They don't detect increased centrosome amplification and aneuploidy in lymphomas from STIL overexpressing mice compared to lymphomas naturally occurring in control animals (Fig 5). Finally, they found that STIL overexpression suppresses chemical skin carcinogenesis using a combination of tamoxifen induction of STIL in the skin with DMBA/TPA carcinogenic treatment (Fig 7). They link this effect to an increased number of centriole and a reduction in cycling cells number in the skin of STIL overexpressing mice (Fig 6).

The manuscript is written in a clear manner. The experimental approaches are properly designed and the experimental methods are described in sufficient details. Most of the experimental data present a good number of replicates. The figures are generally well assembled despite some errors in a few panels/legends (see major and minor points). Most of the conclusions are supported by the experimental data. However, a few specific points or interpretations are not convincingly supported by the experimental data (see major points) and will need to be revised and/or reformulated.

Major points:

1. Figures 1D and F show that MEFs hemizygous (CMV-STIL+/-) and homozygous (CMV-STIL+/+) for STIL present similar level of centrosome amplification and aberrant mitosis. Although, despite these similarities the homozygous MEFs display about two time more micronuclei and chromosomes aberrations (Fig. 2). The authors explain this discrepancy by the fact that MEFs homozygous for STIL have reduced proliferation and an increased propension to stay in interphase compared to hemizygous MEFs (Fig. 3). I don't understand why an interphase arrest would lead to a higher chromosomal instability resulting in higher micronuclei formation and abnormal karyotypes since those phenotypes are the consequences of abnormal mitosis occurring in cycling cells. I would rather argue that Homozygous MEFs are more prone to cell cycle arrest because of mitotic errors, but those mitotic errors cannot be explained by the centrosome status or the mitotic figures quantified in homozygous MEFs. Therefore, the authors explanation written as: "Graded inhibition of proliferation and accumulation of cells in interphase explains why CMV-STIL+/- and CMV-STIL+/+ MEFs contain increasing frequencies of micronuclei and aberrant karyotypes (Fig. 2) despite similar levels of supernumerary centrosomes" is not right for me. The authors should reformulate this section of the manuscript so their conclusion fit their data. The differences between hemi and homozygotes MEFs regarding chromosome stability could come from mitotic errors they did not spot using fixed immunofluorescence images of mitotic MEFs. Thus, as an optional additional experiment, analyzing live mitosis of MEFs could potentially help reconciliate results from mitotic figures and from karyotypes.*

We basically agree with the reviewer and have therefore reanalyzed our data on centriole numbers in a time-dependent manner. As already shown in Figure 3L of the initial manuscript version, the number of both CMV-STIL+/- and CMV-STIL+/+ MEFs with supernumerary centrioles increases with passaging from passage 3 (p3) to p6. Also, in this experiment amplified centrioles were more frequent in CMV-STIL+/+ compared to CMV-STIL+/- MEFs in both passages (p3 and p6) analyzed. We have therefore now pooled the data and substituted the former Figure panel 1D by these combined results. As the results of Figure 1F and especially those for the CMV-STIL+/+ MEFs had to rely on very low mitotic figure counts, because these cells only very rarely divide (as shown in Figure 3A; mitosis frequency of CMV-STIL+/+ MEFs 0.12%), we have now deleted Figure panel 1F from the manuscript. For the same reason - an extremely low proliferation and division rate of especially CMV-STIL+/+ MEFs - live cell imaging to detect different types of mitotic errors, is unfortunately not feasible.

Figure 5 panel F does not support the claim of the main text and does not match the legend of the figure: In the text the authors wrote: "Ki67 immunostaining revealed that, ..., proliferation rates were elevated independent from lymphoma genotypes". If the authors claim and increased cell proliferation in lymphoma compared to lymph nodes, which is expected, they should show the data for the lymph node in the graph. In addition, in the legend the authors mentioned a "Percentage of Ki67-positive cells in healthy spleens and lymphomas from mice with the indicated genotypes." Since there are three genotypes and two tissue types but the figure presents a graph with only three bars did the Spleen and lymphoma data were combined? Or did some data were not inserted in the graph? Thus, since the data does not support the claim for an increased cell proliferation in lymphoma, the authors explanation for the increased protein level observed in these lymphomas (Fig. 5 panel E) is not supported. Therefore, the authors need to present the correct data in the figure or to change their conclusion. They will also need to correct the figure legend and to add a panel with images illustrating the Ki67 labelling in the different tissues in the figure.

We apologize for this mistake and have corrected the legend to Figure panel 5F, which now reads: “Percentage of Ki67-positive cells in two B6-STIL, two CMV-STIL+/- and one CMV-STIL+/+ lymphoma. For comparison, frequencies of Ki67-positive cells in healthy lymph nodes from B6-STIL mice are displayed. Data are means ± SEM from at least two independent immunostainings per lymphoma or healthy lymph node. P-values were calculated using the one-way ANOVA with post-hoc Tukey test for multiple comparison. For space reasons, only statistically significant differences are displayed”.

   We agree with the reviewer that for comparison Ki67 immunostainings of healthy lymph node tissue was missing in the graph and have therefore added this information to the figure panel, which shows increased proliferation of lymphoma compared to normal lymph node cells. Also, a panel with images illustrating Ki67 labelling in healthy lymph node and lymphomas from different genotypes has been added to the figure (panel 5G).

• *

__Minor points:____* * __1. In the introduction, page 4 paragraph 3, the authors wrote: "To assess the impact of centrosome amplification on CIN, senescence, lifespan and tumor formation in vivo without interfering with extracentrosomal traits,..." they need to clarify what they meant by extracentrosomal traits.

As requested by the reviewer we have modified the respective sentence, which now reads: “To assess the impact of centrosome amplification on CIN, senescence, lifespan and tumor formation in vivo with an orthologous approach without interfering with PLK4, we generated transgenic mouse models overexpressing the structural centrosome protein STIL, …”.

• *

In the 1st paragraph of the results, page 4, the authors wrote: "leads to ubiquitous transgene expression at levels similar to the CAG promoter used in most..." but there is no link to a figure presenting the mRNA levels in those mice (potentially Fig. 4F and Fig. S6). Also, in the references cited for comparison, to my knowledge, there was no measurement of Plk4 mRNA levels in tissues in the work from Marthiens and colleagues, in this work the authors assess the expression of the Plk4 transgene by investigating the presence of the protein.

To show STIL transgene expression levels in our system, we have now linked Figure panels 1A (STIL mRNA expression in MEFs), 1B (STIL protein expression in MEFs) and Supplemental Fig. S2 (Supplemental Fig. S6 of the previous manuscript version showing STIL mRNA levels in healthy mouse tissues) to this statement as suggested. In the references now cited for comparison (Kulukian et al. 2015; Vitre et al. 2015; Sercin et al. 2016) PLK4 transgene mRNA (Kulukian et al. 2015; Sercin et al. 2016) and protein levels (Vitre et al. 2015) are shown.

• *

Page 5 second line the authors wrote: "Despite the graded increase in Plk4 expression, CMV-STIL+/- and, CMV-STIL+/+ MEFs exhibited a similar increase in supernumerary centrioles". The authors must meant increase in STIL expression or do they have data not shown about an increase of Plk4 expression? Then they explain this absence of difference in supernumerary centriole by the ability of "excess Plk4" to access the centrosome, again they probably meant STIL. Regarding this point and related to Major Point 1 it might be worth for the authors to quantify actual extra centrosomes in mitosis rather than cells with more than 4 centrioles in interphase (as in Fig. 1C, D). They might find differences in the number of centrosomes in hemizygous versus homozygous MEFs.

We indeed meant STIL instead of PLK4 and have corrected the mistake. As described in our response to the reviewer’s major point 1 we have now reanalyzed our data on centriole numbers in a time-dependent manner. As already shown in Figure 3L of the initial manuscript version, the frequency of both CMV-STIL+/- and CMV-STIL+/+ MEFs with supernumerary centrioles increases with passaging from passage 3 (p3) to p6. Also, in this experiment amplified centrioles were more frequent in CMV-STIL+/+ compared to CMV-STIL+/- MEFs in both passages (p3 and p6) analyzed. We have therefore now pooled and substituted the former Figure panel 1D by these combined results.

Page 5, in the first paragraph the authors mention "the rate of respective mitotic aberrations..." without defining the mitotic aberrations. For instance, in panel 1E a metaphase with 4 centrosomes is shown for CMV-STIL+/- while an anaphase with an unknown number of clustered centrosomes is presented for CMV-STIL+/+. Classifying the different types of aberrant mitotic figures (i.e: multipolar anaphases versus bipolar with clustered centrosomes) might help the authors identify differences between hemi and homozygous MEFS that may explain the differences in the proportions of chromosomes aberrations they present in Fig. 2.

As described in our response to the reviewer’s major point 1 the number of mitotic figures that could be analyzed was extremely low, especially for CMV-STIL+/+ MEFs, which do only rarely divide (mitosis frequency of CMV-STIL+/+ MEFs 0.12%). Therefore, although certainly of value, classification of different types of mitotic aberrations is unfortunately not feasible.

• *

In Fig 4A the number of mice analyzed should be mentioned.

After mating of B6-STIL transgenic animals with CMV-CRE mice and further breeding of successive generations, we obtained a total of 198 pups over four generations, 162 of which were born alive: 116 B6-STIL wildtype animals, 27 CMV-STIL+/- and 19 CMV-STIL-/- mice. We have now added these numbers to the figure legend.

• *

In Fig. 5E, the band corresponding to STIL protein is difficult to visualize in the B6-STIL control, it is therefore difficult to compare its level to the level of STIL protein in the CMV-STIL hemizygotes and homozygotes. If possible, it would improve the manuscript to present a blot with clearer results.

We have tried to improve the quality by repeating the Western blot. Due to the small size of healthy mouse lymph nodes, resulting in low protein yields, only lysates from lymphomas were left, and these were of poor quality with a high lipid content. We therefore tried to delipidate the lymphoma lysates and hope that the result of the new blot is now somewhat clearer. Due to the low lymphoma frequency in CMV-STIL hemizygotes and homozygotes (only 2 in each case) we were unfortunately not able to prepare fresh lysates.

Related to Figure 6B the authors wrote a "5 to 10 fold-increased expression..." in the text while panel 6B show a maximum of 8 fold increase.

The respective statement has been rephrased according to the reviewer´s suggestion.

__Reviewer #1 (Significance (Required)): ______ *Centrosome amplification is a demonstrated cause of genomic instability and tumor development as shown in multiple previous work performed in mice. In this work, Moussa and co-workers developed a mouse model that does not depends on Plk4 to trigger centrosome amplification but which depends on the overexpression of the centrosome structural protein STIL. This effort is welcome as previous works could not formally rule out potential role of Plk4, not related to its centrosome duplication function, on tumor formation. The authors show that their system is functional in MEFs where STIL overexpression drives centrosome amplification and aneuploidy. Unfortunately, in vivo, despite elevated level of STIL mRNA they do not detect centrosome amplification in tissues and consequently, they do not observe an increase rate of aneuploidy and tumor formation. This result is not surprising as previous studies using strong promoters (comparable to the one used to drive STIL expression in this study) to induce Plk4 overexpression led to similar results, i.e. an absence of centrosome amplification in adult tissues and no effects on tumor formation. Therefore, the results and the concepts proposed in this work are not novel but they reinforce previous studies showing the deleterious effect of high level of centrosome amplification on cells. This work also confirms that strong mechanisms, here the authors propose a translational shut-down, are preventing the apparition or the persistence of high level of centrosome amplification in animal tissues. By complementing existing results with the use of an alternate experimental approach this study will be of interest for the scientific community working on the basic biological mechanisms driving aneuploidy and tumor development.*

__Reviewer #2 (Evidence, reproducibility and clarity (Required)):______ *In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model.

Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases. *

__Major Issues____* * __1. Many of the figure panels lack appropriate statistical analyses to support the conclusions (see details below). This needs to be rectified.

In view of the limited number of mice (due to an increased frequency of pups that died around birth) and the resulting impossibility of performing several (>3) independent experiments in many cases, we have decided to limit the statistics in the main text to a descriptive analysis without mentioning inferences (p-values). Nevertheless, we have now included the missing statistical analyses in the figure panels and/or legends. However, the reported p-values (*p≤0.05, **p≤0.01, ***p≤0.001; ns, not significant) should be interpreted as descriptive rather than confirmatory values.

• *

The authors suggest that the interpretation of PLK4 over-expression studies are hampered by the possibility of centriole/centrosome independent PLK4 roles and that STIL overexpression circumvents some of these issues. Although orthologous approaches to problems are always desired, STIL itself has also been implicated in other cellular processes, such as the Sonic hedgehog pathway (Carr AL, 2014) and in cell motility (Liu Y, 2020). In addition, the data presented in the manuscript are suggestive of a STIL function in the mouse that is independent of centriole number. The authors demonstrate that the amount of centriole over-duplication in MEFs containing a single copy of the STIL over-expression locus is equivalent to that of MEFs carrying two copies. However, in most other assays, the homozygous lines display more severe phenotypes, suggesting that STIL might have a function outside centriole duplication. The authors need to discuss this further in a revised manuscript.

As described in our response to major point 1 and minor point 3 of reviewer 1 we have now reanalyzed our data on centriole numbers in a time-dependent manner. As already shown in Figure 3L of the initial manuscript version, the number of both CMV-STIL+/- and CMV-STIL+/+ MEFs with supernumerary centrioles increases with passaging from passage 3 (p3) to p6. Also, in this experiment amplified centrioles were more frequent in CMV-STIL+/+ compared to CMV-STIL+/- MEFs in both passages (p3 and p6) analyzed. We have therefore now pooled the data and substituted the former Figure panel 1D by these combined results, which show that, similar to other models, also regarding STIL overexpression the homozygous line displays a more severe phenotype, which does therefore per se not argue for a STIL function outside the centrosome. However, as a few recent studies indeed suggest additional roles of STIL, we have amended the respective passages in the revised version of the manuscript accordingly.

• *

Why did the authors use the p53 R127H mutant instead of a p53 knockout or null allele system? The R127H mutant has a gain-of-function phenotype and cells expressing this mutant display different phenotypes than a p53 null. The primary conclusion in one of the references cited by the authors (Caulin C, 2007) is that p53R127H is a gain-of-function mutant and behaves distinct from loss-of-function p53 mutations, such as deletions using floxed alleles. Throughout the manuscript, the authors use terms that suggest the R127H allele is equivalent to a loss of function mutant. Given that supernumerary centriole growth arrest is universally suppressed by inactivation of p53 it is somewhat surprising that this pathway is not active in response to STIL over-expression. The authors should confirm this key conclusion by depleting p53 in MEFs using RNAi, or by using mice where complete inactivation of p53 can be achieved.

We agree with the reviewer that the p53-R172H mutant version of p53 is not equivalent to a p53 knockout. We have therefore and as suggested by reviewer 3 as well (see also our response to point 3 of reviewer 3) corrected the wording and have substituted “absence of p53” by “interference with p53 function” where appropriate. In addition, we now have added data to the manuscript, which show that neither p53 expression nor p53-S18 phosphorylation becomes induced during prolonged cultivation and passaging of CMV-STIL transgenic MEFs (see Figure 3B of the revised manuscript). Importantly, this finding is in line with a recent report showing that PLK4-induced extra centrosomes may not rely on p53 for tumor suppression and cell death induction (Braun et al.: Extra centrosomes delay DNA damage-driven tumorigenesis. Sci. Adv. 10: eadk0564, 2024). Similarly, it has been recently shown that centrosome amplification increases apoptosis independently of p53 in PLK4-overexpressing cells treated with DNA-damaging agents (Edwards et al.: Centrosome amplification primes for apoptosis and favors the response to chemotherapy in ovarian cancer beyond multipolar divisions. bioRxiv 2023.07.28.550973, 2023). Therefore, these findings and references have now been added to results and discussion sections of the revised manuscript.

   A plethora of p53-related findings in mouse models, including the majority of results on PLK4-induced tumor formation in mice, is based on p53 knockouts, a situation that is only rarely found in human cancers. In contrast, the p53-R172H missense mutation in mice corresponds to the p53-R175H mutation in human tumors, which has the highest occurrence in diverse human cancer types among all p53 hotspot mutations, and results in a transcriptionally inactive protein that accumulates in cells, similar to the majority of naturally occurring versions of mutant p53 (Yao et al.: Protein-level mutant p53 reporters identify druggable rare precancerous clones in noncancerous tissues. Nat Cancer 4: 1176-1192, 2023; Chiang et al.: The function of mutant p53-R175H in cancer. Cancers 13: 4088, 2021). We therefore believe that it more faithfully recapitulates the situation in p53-mutant tumors than a p53 knockout.

   Although basically an important and valid experiment, depleting p53 in STIL-transgenic MEFs using RNAi is not easily done as (i) transfection of MEFs per se is difficult and (ii) STIL-overexpressing MEFs do only slowly proliferate and are prone to senescence and apoptosis (see Figure 3), all phenotypes which are even further exacerbated after transfection. Generation of STIL-transgenic mice with complete inactivation of p53 on the other hand is an extremely time-consuming endeavor that would lead to a significant delay of publication of our results. Given that currently similar data are published by other groups (Braun et al.: Extra centrosomes delay DNA damage-driven tumorigenesis. Sci. Adv. 10: eadk0564, 2024; Edwards et al.: Centrosome amplification primes for apoptosis and favors the response to chemotherapy in ovarian cancer beyond multipolar divisions. *bioRxiv* 2023.07.28.550973, 2023), we do not think that this would be appropriate.

__Minor Issues and details____* * __Figure 1 1. Panel E. It is unclear what the authors are calling an 'aberrant mitosis'. Typically an aberrant mitosis refers to chromosomal abnormalities such as multipolar spindles, anaphase bridges or micronuclei (which they quantify in Figure 2). The aberrant mitotic figures presented in Figure 1E show a clustered metaphase with 4 centrosomes (2 per pole; 2 centrioles per centrosome) for CMV-STIL+/- MEFs and a clustered telophase with 2 centrosomes (1 per pole; 5 centrioles per centrosome) for CMV-STIL+/+ MEFs. This is now specified in detail in the legend to Figure 1E.

• *

Panel E. Please include images representing a normal mitosis from control cells derived from B6-STIL mice.

As suggested, we have now included a representative image of a normal mitosis from B6-STIL control mice.

Figure 2____ 1. Panels B, E and F. Statistical significance is not indicated between B6-STIL and CMV-STIL+/- or CMV-STIL+/- and CMV-STIL+/+. The authors indicated a 'graded' phenotype which is qualitatively apparent, but should be backed by statistical analysis.

We have now included a statistical analysis. However, and as already described in our answer to major issue 1 of this reviewer, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Can the authors indicate how they scored a tetraploid cell? Some of the cells are 100% tetraploid while others contain other aberrations.

According to the International System for Human Cytogenomic Nomenclature (ISCN) version from 2020, polyploidy is defined by the modal numbers of chromosomes in the karyotype. A number of 81-103 chromosomes is called near-tetraploid, at which a hypotetraploidy (81-91 chromosomes) is distinguished from a hypertetraploidy (93-103 chromosomes) (An International System for Human Cytogenomic Nomenclature, Karger (2020), Eds.: McGowan-Jordan, Hastings, Moore). For mouse karyotypes respective numbers were recalculated on the basis of a diploid chromosome content of 40 instead of 46 chromosomes. To be strictly in accordance with this nomenclature, we have exchanged the term "tetraploid" by "near-tetraploid".

__ Is the height of the rows in Panel D significant? What are the solid black rows?______ We thank the reviewer for this comment/observation. We have now increased the resolution of this part of the figure. Unfortunately, the resolution had deteriorated so much when the pdf file was created that individual lines were no longer recognizable. The height of the lines should be identical, as single lines correspond to the karyotypes of each metaphase cell analyzed, while chromosomes are plotted as columns. The solid black lines separate independently established MEF lines with the indicated STIL genotypes from each other. At least 20 metaphase cells per MEF line were analyzed. We have now explained these points in the figure legend.

Figure 3____ 1. Panels C, F, G, and K require statistical analyses.

We have now included the appropriate statistical analyses in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Panel D should be quantified.

We have now included a quantification of the protein bands in panels B, E (former panel D), and K of the revised manuscript and explained the quantification procedure in detail in the methods section.

Panel E. mRNA expression is quantified in RPKM here, while GeTMM is used in Figures 3I and Supplementary Figures S2 and S6. Is there a reason this panel uses a different method? RPKM can be used for intra-sample comparisons, but is not ideal for comparison among different samples.

We now uniformly quantify mRNA expression in GeTMM in all figures of the revised manuscript version as requested.

• *

Panel G. Can the authors show the original FACS profiles in Supplementary material?

As requested, we have now included representative examples of original FACS profiles from the cell cycle analyses into Supplemental Figure S5.

• *

Panel H. Requires molecular weight markers

Molecular weight markers for the DNA ladder (L) with the corresponding bp size have now been included into the Figure panel (formerly 3H, 3I in the revised version of the manuscript).

• *

__ Panel J. Missing B6-STIL control. Quantify Western blots.______ We have now included an immunoblot showing STIL protein expression levels in passage p1-p5 of B6-STIL control MEFs as well as a quantification of the protein bands into the Figure panel (formerly 3J, 3K in the revised version of the manuscript). The quantification procedure has been explained in detail in the methods section of the revised manuscript version.

Figure 4____ 1. The authors mention 'Simultaneously, we found an increased frequency of pups that died around birth.' Can the data for this be included?

After mating B6-STIL transgenic animals with CMV-CRE mice and further breeding of successive generations, we obtained a total of 198 pups over four generations, of which 162 were born alive: 116 B6-STIL wildtype animals, 27 CMV-STIL+/- and 19 CMV-STIL+/+ mice. We have now added these numbers to the figure legend. Stillbirths increased over the generations: while in the first generation after mating B6-STIL animals with CMV-CRE mice all pups (B6-STIL wildtype animals and STIL heterozygotes) were born alive, in the fourth generation (from mating CMV-STIL transgenic mice with each other) 54% of the pups were stillborn. We have now included this observation into the main text to further emphasize the impact of STIL overexpression on perinatal lethality.

Panels B and D. Please include the data for CMV-STIL+/-.

We now have included a representative H&E-stained histological section of a CMV-STIL+/- mouse brain into Figure panel 4D as suggested by the reviewer. For space reasons we have not added an extra image of a CMV-STIL+/- total brain into Figure panel 4B, as this does not add novel information.

Panels C, F and K require statistics.

As requested, we have now included the appropriate statistical analysis in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

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Panel F. Include statistical analysis.

We have now included the appropriate statistical analysis in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Panel G/H. The levels of STIL in the CMV-STIL+/+ spleen are higher than the other samples, yet there is no concomitant increase in centriole overduplication. Can the authors comment on this?

Interestingly, we indeed found a higher STIL protein expression level in spleen tissue from CMV-STIL+/+ as compared to B6-STIL control and CMV-STIL+/- mice. Nevertheless, the amount of splenocytes with supernumerary centrioles was only marginally increased in these animals. A similar finding has recently been described for B lymphocytes with upregulated PLK4 expression after PLK4 transgene induction by exposure to doxycycline in vivo (Braun et al.: Extra centrosomes delay DNA damage-driven tumorigenesis. Sci. Adv. 10: eadk0564, 2024). Here, the lack of B cells with supernumerary centrioles despite increased PLK4 levels was explained by increased apoptosis and thereby selection against and rapid loss of PLK4-overexpressing cells. In line, we show that CMV-STIL+/+ MEFs have increased rates of senescence and apoptosis (Fig. 4).

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__ Panel J. The font within the plots is difficult to read. ______ We thank the reviewer for this comment/observation. We have now increased the resolution of this figure panel, and the font is now outside of the plots.

Figure 5____** s should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments. No further statistical analysis can be done for panel D as in some cases (lymph node from B6-STIL mouse, lymphoma from CMV-STIL+/+ mouse) only one measurement exists.

Panel F. The legend indicates that these data are from spleens and lymphomas. Is this correct? Would the results from non-lymphoma cells in the spleen mask the results from lymphoma cells?

We apologize for this mistake and have corrected the legend to Figure panel 5F, which now reads: “Percentage of Ki67-positive cells in two B6-STIL, two CMV-STIL+/- and one CMV-STIL+/+ lymphoma. For comparison, frequencies of Ki67-positive cells in healthy lymph nodes from B6-STIL mice are displayed. Data are means ± SEM from at least two independent immunostainings per lymphoma or healthy lymph node. P-values were calculated using the one-way ANOVA with post-hoc Tukey test for multiple comparison. For space reasons, only statistically significant differences are displayed”.

• *

Panel F. The authors indicate that 'In line, assessment of lymphomas from B6-STIL control, CMV-STIL+/- and CMV-STIL+/+ mice by Ki67 immunostaining revealed that, corresponding to STIL protein levels, proliferation rates were elevated independent from lymphoma genotypes'. However, Ki67 levels, the marker for proliferation actually decreased in these samples indicating less proliferative cells. This needs to be clarified since the data shown appears to show the opposite of what is stated in the mansucript....

As noticed by the reviewer further below, differences in the percentages of Ki67-positive, proliferating cells between lymphomas from B6-STIL, CMV-STIL+/- and CMV-STIL+/+ mice were statistically not significant. However, we have now for comparison added the results of Ki67 immunostaining of healthy lymph node tissue to Figure panel 5F, which show increased proliferation of lymphoma compared to normal lymph node cells. Also, a panel with images illustrating Ki67 labelling in healthy lymph node and lymphomas from different genotypes has been added to the figure (panel 5G). These data reveal that, independent from the genotype, proliferation rates of lymphoma cells are increased as compared to healthy lymph nodes, thereby further corroborating our assumption that STIL protein levels in lymphomas are increased as a consequence of their increased proliferation and independent from STIL transgene expression.

• *

Corresponding to point 3 above, the authors suggest that 'STIL protein expression is a consequence of increased lymphoma cell proliferation.' This hypothesis cannot explain STIL protein levels if proliferation has actually decreased.

Please see our response to point 3 above.

• *

Corresponding to point 3 and 4 above, the actual data is marked as non-significant indicating there is actually no proliferative difference among the samples.

This is correct. See also our comments to point 3 and 4 above.

__ Panel 5I. The authors state that 'On the other hand, overall levels of chromosomal copy number aberrations were higher in lymphomas (mean gains + losses: 225.2 Å} 173.7 Mb) as compared to healthy tissues (mean gains + losses: 87.3 Å} 127.5 Mb; p=0.06), irrespective of their STIL transgene status (Fig. 4J; Fig. 5I), although the difference did not quite reach statistical significance.' The authors need to soften this statement since statistically, the samples are not different. For example, 'On the other hand, overall levels of chromosomal copy number aberrations appeared to trend higher in lymphomas as compared to healthy tissues irrespective of their STIL transgene status, although the difference did not quite reach statistical significance.'______ The statement was rephrased according to the reviewer´s suggestion.

Figure 6____ 1. Panels A, B, and C require statistical analysis.

We have now included the appropriate statistical analyses into panels A, B, and C in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

The figure legend references to panels C and D appear to be swapped.

We thank the reviewer for this comment/observation. We have corrected this mistake.

Panel F. Indicate that the samples are not significantly different.

We have now included the appropriate statistical analysis including the indication that the samples are not statistically significantly different.

• *

__ Corresponding to point 3, the authors indicate that 'the proportion of Ki67-positive cycling cells was lower in tamoxifen-treated... ... although the difference did not quite reach statistical significance.' The authors need to soften this statement to reflect that the samples are not statistically different (i.e. 'appeared lower' or similar).______ The statement was rephrased according to the reviewer´s suggestion.

__Figure 6 and 7 _ Do you have data for B6-STIL animals treated with and without tamoxifen? The experiments as shown demonstrate the differences between control and tamoxifen-treated animals of the same genotype, but it is unclear if any of these effects are due to the underlying genotypes or from tamoxifen itself. ___ The experiments presented in Figures 6 and 7 have not been performed in B6-STIL control mice with and without tamoxifen treatment.

Supplemental Figure 1____ 1. Please include molecular weight marker for this and all panels showing PCR products.

Molecular weight markers for the DNA ladder (L) with the corresponding bp size have now been included into all Figure panels showing PCR products as requested.

The B6-STIL and CMV-STIL+/- lines should contain a larger MW band corresponding to the STIL-F and STIL-R PCR product. Please show if possible.

We thank the reviewer for the important remark. We agree that there should be a large PCR product band at around 3000 bp containing the bacterial neomycin phosphotransferase gene (TK-neo-pA) and the STOP cassette in the B6-STIL control mice/MEFs, and two PCR product bands (large: 3000 bp, small: 410 bp) in the heterozygous CMV-STIL+/-mice/MEFs. When we began with genotyping, we did indeed observe both bands depending on the STIL background (see figure below). However, the band intensity of the larger PCR product was relatively weak (arrowheads) compared to the smaller PCR product, and its visibility was dependent on genomic DNA input and PCR efficiency. During the PCR optimization process, the PCR conditions were changed in such a way that the yield of the small band were increased despite small input amounts of genomic DNA, but at the expense of the large PCR product band (arrows). At the end of the optimization process the larger PCR product had almost disappeared, making the discrimination between heterozygous CMV-STIL+/- and homozygous CMV-STIL-/- DNA difficult. Therefore, we decided to additionally check for STOP cassette excision in a second PCR approach in parallel. In the genotyping results shown in Supplemental Figure S1B, which have been produced after PCR optimization, no larger STIL PCR product band was visible anymore.

__Supplemental Figure 6 _ 1. The 'Spleen' sample is missing the B6-STIL control data. 'Liver' is missing CMV-STIL+/+. Please include or indicate why they are missing. The plot order of the samples differs for 'Liver' (red, black) compared to the others (black, red, blue). Indicate statistical significances. ___ We apologize for this mistake, have corrected the Figure (formerly Supplemental Figure S6, S2 in the revised version of the manuscript), and have included the missing spleen and liver samples.

• *

General issues ____ 1. The materials and methods indicate that HPRT and PIPB were used as reference genes, but only HPRT is referred to in the qPCR figure legend.

We thank the reviewer for this comment/observation. As generally recommended (Vandesomele et al., Genome Biol 3(7): research0034.1-research0034.11, 2002; Kozer and Rapacz, J Appl Genet 54(4): 391-406, 2013) we used both reference genes for accurate normalization of qPCR in all experiments. We have now corrected this mistake in the figure legend.

• *

Figure panels 1F and 3C display 95% confidence intervals while others use SEM. Is there a reason for this?

In the two referenced figures (former Figure 1F has been deleted from the manuscript, see also our comment to point 1 of reviewer #1 for reasons; Figure 3C of the former manuscript is now Figure 3D in the revised manuscript version) the endpoint variable was defined by whether individual cells in a single experiment showed a certain property or not (binary variables). By definition, these kinds of variables show a nonsymmetric error structure, which cannot be expressed properly by a single value such as the standard error (SEM), but can be covered correctly by a confidence interval. For the same reason, Fisher’s exact tests were employed to obtain p-values in these situations. In the other figures, the relevant endpoint variables were roughly normally distributed, either directly, or due to them being an average of many values. In this case, a symmetric SEM was thus considered sufficient, and t-tests were used for p-values. To make this clear in the figures, we used different display options to distinguish between error bars showing SEM or 95% CI.

__Reviewer #2 (Significance (Required)): ______ *In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model. Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases. *

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): ______ Previously it has been proposed that supernumerary centrioles play important deleterious effects in vivo including increased tumorigenesis. However, the work was inconclusive because the way of inducing centriole amplification via the PLK4 kinase could have induced other effects besides supernumerary centrioles. To resolve this question, the authors generated a mouse model of centrosome amplification, in which the structural centriole protein STIL is overexpressed. Using this mouse model in vivo along with mutant mouse embryonic feeder (MEF) lines in vivo, the authors test out the role of centrosome amplification in vivo in animal development, lifespan, and tumorigenesis. They report both embryonic lethality, defects in brain development, and shortened life span in these mice. They also find that skin tumorigenesis is reduced in the mutant mice, and demonstrates that the STIL overexpression effects are not perturbed in a dominant negative p53 model. The authors demonstrate that STIL overexpression causes centrosome amplification accompanied by aneuploidy, which however is highly deleterious for cell fitness even in the absence of p53. Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the broader readership.

This study is thorough and well executed and there is a significant body of work that leads to solid conclusions. The data is convincing, and the figure are well presented. It was refreshing to read this paper, as it was not so cluttered with data that the message gets murky, yet the data was clearly very substantial. The text is clear and easy to follow.

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There really are only minor aspects of this paper that need correction, in my opinion. The text should be thoroughly checked for typos, few extra redundant words here and there, and a couple of confusing sentences.______ As suggested by the reviewer we have rechecked the manuscript for typos, redundancies, and confusing sentences and corrected where necessary and appropriate. __* *

For example, the last sentence in abstract is confusing 'These results suggest that supernumerary centrosomes... [result in]... tumor formation' because it should read 'reduced tumor formation' or 'impairs tumorigenesis' or otherwise be written more clearly because it seems to convey the opposite message the way it is right now. ______ We thank the reviewer for this comment and have corrected the sentence, which now reads: “These results suggest that supernumerary centrosomes impair proliferation in vitro as well as in vivo, resulting in reduced lifespan and delayed spontaneous as well as carcinogen-induced tumor formation”. The p53 dominant negative mutant is not exactly a KO so it is not fair to say "in the absence of p53"; the verbiage should be corrected and checked throughout the paper - perhaps 'interfering with p53 normal function' is more appropriate.__ As suggested by the reviewer we have corrected the wording and have substituted “absence of p53” by “interference with p53 function” where appropriate. The sentence "Senescence- and apoptosis-driven depletion of the stem cell pool may explain reduced life span and tumor formation in STIL transgenic mice." from discussion is highly speculative and should be edited to clearly convey its speculative nature or removed entirely. ______ We agree with the reviewer and have deleted the sentence from the discussion section of the manuscript.

__Reviewer #3 (Significance (Required)): ______ Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the scientific community. It adds to previous work on another centriole related protein PLK4 kinase that led to very different conclusions.

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 #3

Evidence, reproducibility and clarity

Previously it has been proposed that supernumerary centrioles play important deleterious effects in vivo including increased tumorigenesis. However, the work was inconclusive because the way of inducing centriole amplification via the PLK4 kinase could have induced other effects besides supernumerary centrioles. To resolve this question, the authors generated a mouse model of centrosome amplification, in which the structural centriole protein STIL is overexpressed. Using this mouse model in vivo along with mutant mouse embryonic feeder (MEF) lines in vivo, the authors test out the role of centrosome amplification in vivo in animal development, lifespan, and tumorigenesis. They report both embryonic lethality, defects in brain development, and shortened life span in these mice. They also find that skin tumorigenesis is reduced in the mutant mice, and demonstrates that the STIL overexpression effects are not perturbed in a dominant negative p53 model. The authors demonstrate that STIL overexpression causes centrosome amplification accompanied by aneuploidy, which however is highly deleterious for cell fitness even in the absence of p53. Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the broader readership. This study is thorough and well executed and there is a significant body of work that leads to solid conclusions. The data is convincing, and the figure are well presented. It was refreshing to read this paper, as it was not so cluttered with data that the message gets murky, yet the data was clearly very substantial. The text is clear and easy to follow.

• There really are only minor aspects of this paper that need correction, in my opinion. The text should be thoroughly checked for typos, few extra redundant words here and there, and a couple of confusing sentences.
• For example, the last sentence in abstract is confusing 'These results suggest that supernumerary centrosomes... [result in]... tumor formation' because it should read 'reduced tumor formation' or 'impairs tumorigenesis' or otherwise be written more clearly because it seems to convey the opposite message the way it is right now.
• The p53 dominant negative mutant is not exactly a KO so it is not fair to say "in the absence of p53"; the verbiage should be corrected and checked throughout the paper - perhaps 'interfering with p53 normal function' is more appropriate.
• The sentence "Senescence- and apoptosis-driven depletion of the stem cell pool may explain reduced life span and tumor formation in STIL transgenic mice." from discussion is highly speculative and should be edited to clearly convey its speculative nature or removed entirely.

Significance

Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the scientific community. It adds to previous work on another centriole related protein PLK4 kinase that led to very different conclusions.

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

In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model.

Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases.

Major Issues

1. Many of the figure panels lack appropriate statistical analyses to support the conclusions (see details below). This needs to be rectified.
2. The authors suggest that the interpretation of PLK4 over-expression studies are hampered by the possibility of centriole/centrosome independent PLK4 roles and that STIL overexpression circumvents some of these issues. Although orthologous approaches to problems are always desired, STIL itself has also been implicated in other cellular processes, such as the Sonic hedgehog pathway (Carr AL, 2014) and in cell motility (Liu Y, 2020). In addition, the data presented in the manuscript are suggestive of a STIL function in the mouse that is independent of centriole number. The authors demonstrate that the amount of centriole over-duplication in MEFs containing a single copy of the STIL over-expression locus is equivalent to that of MEFs carrying two copies. However, in most other assays, the homozygous lines display more severe phenotypes, suggesting that STIL might have a function outside centriole duplication. he authros need to discuss this further in a revised manuscript.
3. Why did the authors use the p53 R127H mutant instead of a p53 knockout or null allele system? The R127H mutant has a gain-of-function phenotype and cells expressing this mutant display different phenotypes than a p53 null. The primary conclusion in one of the references cited by the authors (Caulin C, 2007) is that p53R127H is a gain-of-function mutant and behaves distinct from loss-of-function p53 mutations, such as deletions using floxed alleles. Throughout the manuscript, the authors use terms that suggest the R127H allele is equivalent to a loss of function mutant. Given that supernumerary centriole growth arrest is universally suppressed by inactivation of p53 it is somewhat surprising that this pathway is not active in response to STIL over-expression. The authors should confirm this key conclusion by depleting p53 in MEFs using RNAi, or by using mice where complete inactivation of p53 can be achieved.

Minor Issues and details

Figure 1

1. Panel E. It is unclear what the authors are calling an 'aberrant mitosis'. Typically an aberrant mitosis refers to chromosomal abnormalities such as multipolar spindles, anaphase bridges or micronuclei (which they quantify in Figure 2).
2. Panel E. Please include images representing a normal mitosis from control cells derived from B6-STIL mice.

Figure 2

1. Panels B, E and F. Statistical significance is not indicated between B6-STIL and CMV-STIL+/- or CMV-STIL+/- and CMV-STIL+/+. The authors indicated a 'graded' phenotype which is qualitatively apparent, but should be backed by statistical analysis.
2. Can the authors indicate how they scored a tetraploid cell? Some of the cells are 100% tetraploid while others contain other aberrations.
3. Is the height of the rows in Panel D significant? What are the solid black rows?

Figure 3

1. Panels C, F, G, and K require statistical analyses.
2. Panel D should be quantified.
3. Panel E. mRNA expression is quantified in RPKM here, while GeTMM is used in Figures 3I and Supplementary Figures S2 and S6. Is there a reason this panel uses a different method? RPKM can be used for intra-sample comparisons, but is not ideal for comparison among different samples.
4. Panel G. Can the authors show the original FACS profiles in Supplementary material?
5. Panel H. Requires molecular weight markers
6. Panel J. Missing B6-STIL control. Quantify Western blots.

Figure 4

1. The authors mention 'Simultaneously, we found an increased frequency of pups that died around birth.' Can the data for this be included?
2. Panels B and D. Please include the data for CMV-STIL+/-.
3. Panels C, F and K require statistics.
4. Panel F. Include statistical analysis.
5. Panel G/H. The levels of STIL in the CMV-STIL+/+ spleen are higher than the other samples, yet there is no concomitant increase in centriole overduplication. Can the authors comment on this?
6. Panel J. The font within the plots is difficult to read.

Figure 5

1. Panels B, D and G require statistics.
2. Panel F. The legend indicates that these data are from spleens and lymphomas. Is this correct? Would the results from non-lymphoma cells in the spleen mask the results from lymphoma cells?
3. Panel F. The authors indicate that 'In line, assessment of lymphomas from B6-STIL control, CMV-STIL+/- and CMV-STIL+/+ mice by Ki67 immunostaining revealed that, corresponding to STIL protein levels, proliferation rates were elevated independent from lymphoma genotypes'. However, Ki67 levels, the marker for proliferation actually decreased in these samples indicating less proliferative cells. This needs to be clarified since the data shown appears to show the opposite of what is stated in the mansucript....
4. Corresponding to point 3 above, the authors suggest that 'STIL protein expression is a consequence of increased lymphoma cell proliferation.' This hypothesis cannot explain STIL protein levels if proliferation has actually decreased.
5. Corresponding to point 3 and 4 above, the actual data is marked as non-significant indicating there is actually no proliferative difference among the samples.
6. Panel 5I. The authors state that 'On the other hand, overall levels of chromosomal copy number aberrations were higher in lymphomas (mean gains + losses: 225.2 Å} 173.7 Mb) as compared to healthy tissues (mean gains + losses: 87.3 Å} 127.5 Mb; p=0.06), irrespective of their STIL transgene status (Fig. 4J; Fig. 5I), although the difference did not quite reach statistical significance.' The authors need to soften this statement since statistically, the samples are not different. For example, 'On the other hand, overall levels of chromosomal copy number aberrations appeared to trend higher in lymphomas as compared to healthy tissues irrespective of their STIL transgene status, although the difference did not quite reach statistical significance.'

Figure 6

1. Panels A, B, and C require statistical analysis.
2. The figure legend references to panels C and D appear to be swapped.
3. Panel F. Indicate that the samples are not significantly different.
4. Corresponding to point 3, the authors indicate that 'the proportion of Ki67-positive cycling cells was lower in tamoxifen-treated... ... although the difference did not quite reach statistical significance.' The authors need to soften this statement to reflect that the samples are not statistically different (i.e. 'appeared lower' or similar).

Figure 6 and 7

Do you have data for B6-STIL animals treated with and without tamoxifen? The experiments as shown demonstrate the differences between control and tamoxifen-treated animals of the same genotype, but it is unclear if any of these effects are due to the underlying genotypes or from tamoxifen itself.

Supplemental Figure 1

1. Please include molecular weight marker for this and all panels showing PCR products.
2. The B6-STIL and CMV-STIL+/- lines should contain a larger MW band corresponding to the STIL-F and STIL-R PCR product. Please show if possible.

Supplemental Figure 6

1. The 'Spleen' sample is missing the B6-STIL control data. 'Liver' is missing CMV-STIL+/+. Please include or indicate why they are missing. The plot order of the samples differs for 'Liver' (red, black) compared to the others (black, red, blue). Indicate statistical significances.

General issues

1. The materials and methods indicate that HPRT and PIPB were used as reference genes, but only HPRT is referred to in the qPCR figure legend.
2. Figure panels 1F and 3C display 95% confidence intervals while others use SEM. Is there a reason for this?

Significance

In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model.

Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases.

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

Supernumerary centrosomes are observed in the majority of human tumors. In cells they induce abnormal mitosis leading to chromosome missegregation and aneuploidy. In animal models it is demonstrated that extra centrosomes are sufficient to drive tumor formation. Previous work studying the impact of centrosome amplification on tumor formation in vivo used Plk4 overexpression to drive the formation of supernumerary centrosomes. In this manuscript Moussa and co-workers from the Krämer group developed a mouse model in which centrosome amplification is triggered by the overexpression of the structural centrosomal protein STIL rather than the kinase Plk4 in order to a) assess the potential for centrosome amplification induced by STIL overexpression to drive tumor formation and b) to rule out any potential non-centrosomal related effects of the kinase Plk4 on tumor formation. The authors show that STIL ovexrexpression in cells (MEFs) drives centrosome amplification and aberrant mitosis (Fig. 1), leading to chromosome missegregation and aneuploidy (Fig. 2). They also show that STIL overexpression is linked to reduced cellular proliferation and apoptosis (Fig 3). The authors then present in vivo experiments performed in mice. They observed that STIL expression causes embryonic lethality, microcephaly and a reduced lifespan (Fig 4). Despite increased STIL mRNA levels they do not detect elevated STIL protein levels in adult tissues except for the spleen. They do not detect significant increase of centrosome amplification or aneuploidy in animal tissues (Fig 4) and they conclude of a STIL translational shut down in most adult tissues. The authors then assess the impact of STIL overexpression on tumor formation. They observed a reduced spontaneous tumor formation despite elevated STIL mRNA levels in both healthy and tumor (lymphomas) tissues of mice overexpressing STIL. They don't detect increased centrosome amplification and aneuploidy in lymphomas from STIL overexpressing mice compared to lymphomas naturally occurring in control animals (Fig 5). Finally, they found that STIL overexpression suppresses chemical skin carcinogenesis using a combination of tamoxifen induction of STIL in the skin with DMBA/TPA carcinogenic treatment (Fig 7). They link this effect to an increased number of centriole and a reduction in cycling cells number in the skin of STIL overexpressing mice (Fig 6).

The manuscript is written in a clear manner. The experimental approaches are properly designed and the experimental methods are described in sufficient details. Most of the experimental data present a good number of replicates. The figures are generally well assembled despite some errors in a few panels/legends (see major and minor points). Most of the conclusions are supported by the experimental data. However, a few specific points or interpretations are not convincingly supported by the experimental data (see major points) and will need to be revised and/or reformulated.

Major points:

1. Figures 1D and F show that MEFs hemizygous (CMV-STIL+/-) and homozygous (CMV-STIL+/+) for STIL present similar level of centrosome amplification and aberrant mitosis. Although, despite these similarities the homozygous MEFs display about two time more micronuclei and chromosomes aberrations (Fig. 2). The authors explain this discrepancy by the fact that MEFs homozygous for STIL have reduced proliferation and an increased propension to stay in interphase compared to hemizygous MEFs (Fig. 3). I don't understand why an interphase arrest would lead to a higher chromosomal instability resulting in higher micronuclei formation and abnormal karyotypes since those phenotypes are the consequences of abnormal mitosis occurring in cycling cells. I would rather argue that Homozygous MEFs are more prone to cell cycle arrest because of mitotic errors, but those mitotic errors cannot be explained by the centrosome status or the mitotic figures quantified in homozygous MEFs. Therefore, the authors explanation written as: "Graded inhibition of proliferation and accumulation of cells in interphase explains why CMV-STIL+/- and CMV-STIL+/+ MEFs contain increasing frequencies of micronuclei and aberrant karyotypes (Fig. 2) despite similar levels of supernumerary centrosomes" is not right for me. The authors should reformulate this section of the manuscript so their conclusion fit their data. The differences between hemi and homozygotes MEFs regarding chromosome stability could come from mitotic errors they did not spot using fixed immunofluorescence images of mitotic MEFs. Thus, as an optional additional experiment, analyzing live mitosis of MEFs could potentially help reconciliate results from mitotic figures and from karyotypes.
2. Figure 5 panel F does not support the claim of the main text and does not match the legend of the figure: In the text the authors wrote: "Ki67 immunostaining revealed that, ..., proliferation rates were elevated independent from lymphoma genotypes". If the authors claim and increased cell proliferation in lymphoma compared to lymph nodes, which is expected, they should show the data for the lymph node in the graph. In addition, in the legend the authors mentioned a "Percentage of Ki67-positive cells in healthy spleens and lymphomas from mice with the indicated genotypes." Since there are three genotypes and two tissue types but the figure presents a graph with only three bars did the Spleen and lymphoma data were combined? Or did some data were not inserted in the graph? Thus, since the data does not support the claim for an increased cell proliferation in lymphoma, the authors explanation for the increased protein level observed in these lymphomas (Fig. 5 panel E) is not supported. Therefore, the authors need to present the correct data in the figure or to change their conclusion. They will also need to correct the figure legend and to add a panel with images illustrating the Ki67 labelling in the different tissues in the figure.

Minor points:

1. In the introduction, page 4 paragraph 3, the authors wrote: "To assess the impact of centrosome amplification on CIN, senescence, lifespan and tumor formation in vivo without interfering with extracentrosomal traits,..." they need to clarify what they meant by extracentrosomal traits.
2. In the 1st paragraph of the results, page 4, the authors wrote: "leads to ubiquitous transgene expression at levels similar to the CAG promoter used in most..." but there is no link to a figure presenting the mRNA levels in those mice (potentially Fig. 4F and Fig. S6). Also, in the references cited for comparison, to my knowledge, there was no measurement of Plk4 mRNA levels in tissues in the work from Marthiens and colleagues, in this work the authors assess the expression of the Plk4 transgene by investigating the presence of the protein.
3. Page 5 second line the authors wrote: "Despite the graded increase in Plk4 expression, CMV-STIL+/- and, CMV-STIL+/+ MEFs exhibited a similar increase in supernumerary centrioles". The authors must meant increase in STIL expression or do they have data not shown about an increase of Plk4 expression? Then they explain this absence of difference in supernumerary centriole by the ability of "excess Plk4" to access the centrosome, again they probably meant STIL. Regarding this point and related to Major Point 1 it might be worth for the authors to quantify actual extra centrosomes in mitosis rather than cells with more than 4 centrioles in interphase (as in Fig. 1C, D). They might find differences in the number of centrosomes in hemizygous versus homozygous MEFs.
4. Page 5, in the first paragraph the authors mention "the rate of respective mitotic aberrations..." without defining the mitotic aberrations. For instance, in panel 1E a metaphase with 4 centrosomes is shown for CMV-STIL+/- while an anaphase with an unknown number of clustered centrosomes is presented for CMV-STIL+/+. Classifying the different types of aberrant mitotic figures (i.e: multipolar anaphases versus bipolar with clustered centrosomes) might help the authors identify differences between hemi and homozygous MEFS that may explain the differences in the proportions of chromosomes aberrations they present in Fig. 2.
5. In Fig 4A the number of mice analyzed should be mentioned.
6. In Fig. 5E, the band corresponding to STIL protein is difficult to visualize in the B6-STIL control, it is therefore difficult to compare its level to the level of STIL protein in the CMV-STIL hemizygotes and homozygotes. If possible, it would improve the manuscript to present a blot with clearer results.
7. Related to Figure 6B the authors wrote a "5 to 10 fold-increased expression..." in the text while panel 6 B show a maximum of 8 fold increase.

Significance

Centrosome amplification is a demonstrated cause of genomic instability and tumor development as shown in multiple previous work performed in mice. In this work, Moussa and co-workers developed a mouse model that does not depends on Plk4 to trigger centrosome amplification but which depends on the overexpression of the centrosome structural protein STIL. This effort is welcome as previous works could not formally rule out potential role of Plk4, not related to its centrosome duplication function, on tumor formation.

The authors show that their system is functional in MEFs where STIL overexpression drives centrosome amplification and aneuploidy. Unfortunately, in vivo, despite elevated level of STIL mRNA they do not detect centrosome amplification in tissues and consequently, they do not observe an increase rate of aneuploidy and tumor formation. This result is not surprising as previous studies using strong promoters (comparable to the one used to drive STIL expression in this study) to induce Plk4 overexpression led to similar results, i.e. an absence of centrosome amplification in adult tissues and no effects on tumor formation.

Therefore, the results and the concepts proposed in this work are not novel but they reinforce previous studies showing the deleterious effect of high level of centrosome amplification on cells. This work also confirms that strong mechanisms, here the authors propose a translational shut-down, are preventing the apparition or the persistence of high level of centrosome amplification in animal tissues.

By complementing existing results with the use of an alternate experimental approach this study will be of interest for the scientific community working on the basic biological mechanisms driving aneuploidy and tumor development.

Hype, dit gaan wij doen!

Punt?

Tegenstrijdig?

More data = More accurate results

Try flying to the moon, you'll at least reach the stratosphere

动态合批（Dynamic Batching）是一种在实时渲染过程中提高性能的技术。它的核心思想是将多个小的渲染对象合并为一个批次，以减少向图形硬件提交绘制调用的次数，从而提高渲染效率。

合批的重要性 在3D图形渲染中，每次绘制调用都会产生一定的 CPU/GPU 通信开销。特别是在实时渲染环境（如视频游戏）中，成百上千个对象如果都单独提交，会产生严重的性能问题。通过合批，可以显著减少绘制调用次数，从而提升整体渲染性能。

静态合批 vs 动态合批 静态合批： 在场景预处理阶段，将所有不会移动的对象（静态对象）合并为一个或多个大的几何体。 优点是批处理量稳定，但缺点是无法处理移动或动画的对象。 动态合批： 在每一帧渲染时，对移动的、动画的或频繁变化的对象进行实时合批。 动态合批可以在场景中灵活处理动态对象，但它需要更复杂的逻辑来实时检测哪些对象可以合并。 动态合批的工作流程 对象分类： 在渲染时，实时检测哪些对象具有相似的特性（如相同的材质、纹理、着色器等）。 具有相同特性且符合条件的对象将被分配到同一批次中。 几何合并： 将符合条件的多个对象的几何数据合并成一个大的缓冲区。 为每个对象的顶点和索引数据设置正确的偏移量，以确保合并后的几何体仍然保持各自的形状。 绘制提交： 将合并后的缓冲区一次性提交给 GPU 进行绘制。 优点 性能提升：减少了绘制调用的次数，提高渲染效率。 灵活性：可以处理场景中各种动态对象的合批需求。 挑战 额外开销：实时合并数据会增加 CPU 的开销，并可能引入延迟。 条件要求：并不是所有对象都可以被合批，必须满足特定的条件才能有效合并。

Adipocyter = fettceller, hittas i de flesta organs bindvävnad. Dessa stora celler är specialiserade på lipidförvaring i cytoplasman och har i syfte att agera stötdämpande - mer djupgående i kapteil 6 om fettceller.

Aktivt fibroblast har mer rikligt och irreguljärt cytoplasma (med mycket RER, välutvecklad golgi apparat...)

Fibrocyter, den inaktiva formen av fribroblaster, brukar vara "spindle-shaped (idk), mindre RER och har en mörkare mer ihopdragen cellkärna

Fibroblaster som är aktiva har stora cellkärnor som är "euchromatic" dvs. löst packat kromatin som brukar vara en del av transkriptionsprocessen. Fibroblaster som är inaktiva - även kallat fibrocyter - är mindre i storlek vars cellkärna är mer "heterochromatic" dvs. tätt ihoppackat.

Fibroblaster är den vanligast förekommande celltypen i bindväv och producerar majoriteten av den extracellulära vävnaden: - kollagen-sekret - elastin Båda dessa formar långa fibrer men vi har även - GAGs - proteoglykaner - glykoprotein (klister)

x

多重采样（Multisampling）是一种抗锯齿技术，用于减少3D图形渲染中的锯齿现象。锯齿现象是一种在边缘出现的锯齿状边缘或台阶效应，通常发生在斜线、曲线或高对比度的边缘上。多重采样通过对像素的多次采样，创建更平滑的边缘，使图像更真实。

原理 多重采样的原理是将一个像素划分为多个子像素，对每个子像素进行采样，从而为每个像素计算出更精确的颜色和深度值。最终的像素值则是这些子像素的加权平均结果。

工作流程 多次采样： 为每个像素创建多个子像素（通常称为样本点）。 对每个样本点进行渲染，包括颜色和深度信息。 样本融合： 根据各个样本点的颜色和深度值，计算出最终的像素颜色。 这种平均的结果可以让像素的边缘变得平滑，从而减少锯齿效应。 常见的多重采样类型 2x、4x、8x 多重采样： 表示对每个像素使用2、4或8个样本点进行采样。更多的样本点通常会产生更好的抗锯齿效果，但也会增加计算量。 MSAA（Multisample Anti-Aliasing，多重采样抗锯齿）： 是一种常见的多重采样抗锯齿技术，提供了平衡性能和质量的方案。 SSAA（Supersample Anti-Aliasing，超级采样抗锯齿）： 更高级的抗锯齿技术，通过在高分辨率下渲染场景再缩小到目标分辨率来实现抗锯齿效果，但性能开销更大。

PBR（Physically Based Rendering，基于物理的渲染）是一种渲染方法，基于模拟现实世界中物理光照和材质的相互作用，为3D渲染提供更真实的视觉效果。PBR 工作流程涉及一套特定的技术和材质参数，使得不同的渲染引擎和艺术团队都可以创建一致且真实的图像。

PBR 工作流程的主要步骤 建立模型： 3D 模型是工作流程的基础。建模过程中应保持拓扑结构合理，并为 PBR 材质做好 UV 贴图。 定义材质参数： PBR 使用一组标准的参数来描述材质。主要的 PBR 材质参数包括： Albedo（反照率）：无光照条件下材质的基础颜色，不包括高光或阴影信息。 Metalness（金属度）：材质是金属还是非金属。金属通常反射率高、无漫反射；非金属通常具有漫反射并反射环境光。 Roughness（粗糙度）：决定表面反射光的粗糙程度。光滑的表面有强烈的高光反射，粗糙的表面则产生漫反射。 Normal Map（法线贴图）：模拟表面细节，以创建比模型实际几何形状更精细的纹理。 Ambient Occlusion（环境遮蔽）：模拟阴影区域以增加模型的深度和现实感。 Emissive（自发光）：指定材质是否发光以及发光的颜色。 灯光和环境： PBR 使用物理准确的光照模型。需要对场景中不同类型的光源（点光源、方向光源、聚光灯等）进行设置。 环境光照图或 HDR（高动态范围）图可提供周围环境的反射和照明效果。 渲染引擎配置： 不同的渲染引擎有不同的配置要求，但通常都会提供 PBR 材质支持。 通过配置引擎中的光照模型、阴影设置以及后处理效果，可以确保获得最佳的视觉效果。 测试与调整： 在实际渲染场景中测试材质和光照效果，查看模型在不同光照和环境下的表现。 根据测试结果调整各个材质参数，使效果更贴近现实。 优点 一致性：由于 PBR 是基于物理的光照模型，它可以在不同渲染环境和引擎之间提供一致的视觉效果。 效率：统一的材质参数减少了需要调整的项目，使得艺术家能够更快制作内容。 真实性：通过模拟真实世界的光照和材质相互作用，PBR 能产生更逼真的图像

Reviewer #2 (Public Review):

Summary:

The manuscript by Djebar et al investigated the role and the underlying mechanism of the ciliary transition zone protein Rpgrip1l in zebrafish spinal alignment. They showed that rpgrip1l mutant zebrafish develop a nearly full penetrance of body curvature at juvenile stages. The mutant fish have cilia defects associated with ventricular dilations and loss of the Reissner fibers. Scoliosis onset and progression are also strongly associated with astrogliosis and neuroinflammation, and anti-inflammatory drug treatment prevents scoliosis in mutant zebrafish, suggesting a novel pathogenic mechanism for human idiopathic scoliosis. This study is quite comprehensive with high-quality data, and the manuscript is well written, providing important information on how the ciliary transition zone protein functions in maintaining the zebrafish body axis straightness.

Strengths:

Very clear and comprehensive analysis of the mutant zebrafish.

Weaknesses:

(1) In Figures 1D-G, magnified high-resolution pictures are required to show there are indeed no vertebral malformations.

(2) Are the transcriptome data and proteomic data consistent? Consistent targets in both analyses should be highlighted.

(3) What is the role of Anxa2 in neuroinflammation? Is increased Anxa2 expression in rpgrip1l mutant zebrafish reduced after anti-inflammatory drug treatment? What is the expression level of anxa2 in cep290 mutant zebrafish?

(4) More background about Rpgrip1l should be provided in the introduction, particularly the past studies of the mammalian homolog of Rpgrip11, if there are any.

(5) Is there any human disease associated with Rpgrip1l? Do these patients have scoliosis phenotype?

(6) A summary diagram at the end would be helpful for understanding the main findings.

eLife assessment

This valuable study analyzes the role of the ciliary transition zone protein rpgrip1l in the development of the scoliotic phenotype in zebrafish. Through convincing proteomic and experimental validation in vivo, the authors demonstrated increased Annexin A2 expression in the brain and increased LCP1+ immune cell infiltration in scoliosis fish. These findings provide additional evidence for the previously proposed role of neuroinflammation in the development of idiopathic scoliosis in zebrafish.

Reviewer #1 (Public Review):

Summary:

In this study, Djebar et al. perform a comprehensive analysis of mutant phenotypes associated with the onset and progression of scoliosis in zebrafish ciliary transition zone mutants rpgrip1l and cep290. They determine that rpgrip1l is required in foxj1a-expressing cells for normal spine development, and that scoliosis is associated with brain ventricle dilations, loss of Reissner fiber polymerization, and the loss of 'tufts' of multi-cilia surrounding the subcommissural organ (the source of Reissner substance). Informed by transcriptomic and proteomic analyses, they identify a neuroinflammatory response in rpgrip1l and cep290 mutants that is associated with astrogliosis and CNS macrophage/microglia recruitment. Furthermore, anti-inflammatory drug treatment reduced scoliosis penetrance and severity in rpgrip1l mutants. Based on their data, the authors propose a feed-forward loop between astrogliosis, induced by perturbed ventricular homeostasis, and immune cell recruitment as a novel pathogenic mechanism of scoliosis in zebrafish ciliary transition zone mutants.

Strengths:

(1) Comprehensive characterization of the causes of scoliosis in ciliary transition zone mutants rpgrip1l and cep290.

(2) Comparison of rpgrip1l mutants pre- and post-scoliosis onset allowed authors to identify specific phenotypes as being correlated with spine curvature, including brain ventricle dilations, loss of Reissner fiber, and loss of cilia in proximity to the sub-commissural organ.

(3) Elegant genetic demonstration that increased urotensin peptide levels do not account for spinal curvature in rpgrip1l mutants.

(4) The identification of astrogliosis and Annexin over-expression in glial cells surrounding diencephalic and rhombencephalic ventricles as being correlated with scoliosis onset and severe curve progression is a very interesting finding, which may ultimately inform pathogenic mechanisms driving spine curvature

Weaknesses:

(1) The fact that cilia loss/dysfunction and Reissner fiber defects cause scoliosis in zebrafish is already well established in the literature, as is the requirement for cilia in foxj1a-expressing cells.

(2) Neuroinflammation has already been identified as the underlying pathogenic mechanism in at least 2 previously published scoliosis models (zebrafish ptk7a and sspo mutants).

(3) Anti-inflammatory drugs like aspirin, NAC, and NACET have also previously been demonstrated to suppress scoliosis onset and severe curve progression in these models.

Therefore, although similar observations in rpgrip1l and cep290 mutants (as reported here) add to a growing body of literature that supports a common biological mechanism underlying spine curvature in zebrafish, the novelty of reported findings is diminished.

(4) Although authors demonstrate that astrogliosis and/or macrophage or microglia cell recruitment are correlated with scoliosis, they do not formally demonstrate that these events are sufficient to drive spine curvature. Thus, the functional consequences of astrogliosis and microglia infiltration remain uncertain.

(5) The authors do not investigate the effect of anti-inflammatory treatments on other phenotypes they have correlated with spinal curve onset (like ventricle dilation, Reissner fiber loss, and multi-cilia loss around the subcommissural organ). This would help to identify causal events in scoliosis.

Reviewer #3 (Public Review):

Summary:

This paper describes a new mechanism of clearance of protein aggregates occurring during mitosis.

The authors have observed that animal cells can clear misfolded aggregated proteins at the end of mitosis. The images and data gathered are solid, convincing, and statistically significant. However, there is a lack of insight into the underlying mechanism. They show the involvement of the ER, ATPase-dependent, BiP chaperone, and the requirement of Cdk1 inactivation (a hallmark of mitotic exit) in the process. They also show that the mechanism seems to be independent of the APC/C complex (anaphase-promoting complex). Several points need to be clarified regarding the mechanism that clears the aggregates during mitosis:

• What happens in the cell substructure during mitosis to explain the recruitment of BiP towards the aggregates, which seem to be relocated to the cytoplasm surrounded by the ER membrane.

• How the changes in the cell substructure during mitosis explain the relocation of protein aggregates during mitosis.

• Why BiP seems to be the main player of this mechanism and not the cyto Hsp70 first described to be involved in protein disaggregation.

Strengths:

Experimental data showing clearance of protein aggregates during mitosis is solid, statistically significant, and very interesting.

Weaknesses:

Weak mechanistic insight to explain the process of protein disaggregation, particularly the interconnection between what happens in the cell substructure during mitosis to trigger and drive clearance of protein aggregates.

eLife assessment

How misfolded proteins are segregated and cleared is a significant question in mechanistic cell biology, since clearance of these aggregates can protect against pathologies that may otherwise arise. The authors discover a cell cycle stage-dependent clearing mechanism that involves the ER chaperone BiP, the proteosome, and CDK inactivation, but is curiously independent of the APC. These are valuable and interesting new observations, but the evidence supporting these claims is incomplete, and needs to be strengthened and further validated.

Reviewer #1 (Public Review):

Strengths:

The manuscript utilizes a previously reported misfolding-prone reporter to assess its behaviour in ER in different cell line models. They make two interesting observations:

(1) Upon prolonged incubation, the reporter accumulates in nuclear aggregates.

(2) The aggregates are cleared during mitosis. They further provide some insight into the role of chaperones and ER stressors in aggregate clearance. These observations provide a starting point for addressing the role of mitosis in aggregate clearance. Needless to say, going ahead understanding the impact of aggregate clearance on cell division will be equally important.

Weaknesses:

The study almost entirely relies on an imaging approach to address the issue of aggregate clearance. A complementary biochemical approach would be more insightful. The intriguing observations pertaining to aggregates in the nucleus and their clearance during mitosis lack mechanistic understanding. The issue pertaining to the functional relevance of aggregation clearance or its lack thereof has not been addressed. Experiments addressing these issues would be a terrific addition to this manuscript.

Reviewer #2 (Public Review):

Summary:

The authors provide an interesting observation that ER-targeted excess misfolded proteins localize to the nucleus within membrane-entrapped vesicles for further quality control during cell division. This is useful information indicating transient nuclear compartmentalization as a quality control strategy for misfolded ER proteins in mitotic cells, although endogenous substrates of this pathway are yet to be identified.

Strengths:

This microscopy-based study reports unique membrane-based compartments of ER-targeted misfolded proteins within the nucleus. Quarantining aggregating proteins in membrane-less compartments is a widely accepted protein quality control mechanism. This work highlights the importance of membrane-bound quarantining strategies for aggregating proteins. These observations open up multiple questions on proteostasis biology. How do these membrane-bound bodies enter the nucleus? How are the single-layer membranes formed? How exactly are these membrane-bound aggregates degraded? Are similar membrane-bound nuclear deposits present in post-mitotic cells that are relevant in age-related proteostasis diseases? Etc. Thus, the observations reported here are potentially interesting.

Weaknesses:

This study, like many other studies, used a set of model misfolding-prone proteins to uncover the interesting nuclear-compartment-based quality control of ER proteins. The endogenous ER-proteins that reach a similar stage of overdose of misfolding during ER stress remain unknown.

The mechanism of disaggregation of membrane-trapped misfolded proteins is unclear. Do these come out of the membrane traps? The authors report a few vesicles in living cells. This may suggest that membrane-untrapped proteins are disaggregated while trapped proteins remain aggregates within membranes.

The authors figure out the involvement of proteasome and Hsp70 during the disaggregation process. However, the detailed mechanisms including the ubiquitin ligases are not identified. Also, is the protein ubiquitinated at this stage?

This paper suffers from a lack of cellular biochemistry. Western blots confirming the solubility and insolubility of the misfolded proteins are required. This will also help to calculate the specific activity of luciferase more accurately than estimating the fluorescence intensities of soluble and aggregated/compartmentalized proteins. Microscopy suggested the dissolution of the membrane-based compartments and probably disaggregation of the protein. This data should be substantiated using Western blots. Degradation can only be confirmed by Western blots. The authors should try time course experiments to correlate with microscopy data. Cycloheximide chase experiments will be useful.

The cell models express the ER-targeted misfolded proteins constitutively that may already reprogram the proteostasis. The authors may try one experiment with inducible overexpression.

It is clear that a saturating dose of ER-targeted misfolded proteins activates the pathway. The authors performed a few RT-PCR experiments to indicate the proteostasis-sensitivity. Proteome-based experiments will be better to substantiate proteostasis saturation.

The authors should immunostain the nuclear compartments for other ER-membrane resident proteins that span either the bilayer or a single layer. The data may be discussed.

All microscopy figures should include control cells with similarly aggregating proteins or without aggregates as appropriate. For example, is the nuclear-targeted FlucDM-EGFP similarly entrapped? A control experiment will be interesting. Expression of control proteins should be estimated by western blots.

There are few more points that may be out of the scope of the manuscript. For example, how do these compartments enter the nucleus? Whether similar entry mechanisms/events are ever reported? What do the authors speculate? Also, the bilayer membrane becomes a single layer. This is potentially interesting and should be discussed with probable mechanisms. Also, do these nuclear compartments interfere with transcription and thereby deregulate cell division? What about post-mitotic cells? Similar deposits may be potentially toxic in the absence of cell division. All these may be discussed.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Boudjerna and Balagé et al. aim to elucidate the spatial origin of centriole amplification and the mechanisms behind the formation of an apical-basal body patch in multiciliated cells (MCCs). To this end, they focused on the role of microtubules and developed new tools for spatiotemporal and high-resolution analysis of different stages of centriole amplification, including the centrosome stages, A-stage, G-stage, and MCC-stage. Among these tools, the MEF-MCC cells grown on micropatterns stands out for its versatility as it is not tissue-specific and does not require epithelial cell-to-cell contact for differentiation. Additionally, the Cen2-GFP; mRuby-Deup1 knock-in mouse model was used to study different stages of centriole amplification in physiological brain MCCs. This model offers an advantage over the previously described Cen2-GFP model by enabling the resolution of early events in centriole amplification through the visualization of Deup1-positive structures and their dynamics. Finally, the authors leveraged powerful imaging techniques, including super-resolution microscopy, the U-ExM, and high-resolution live cell imaging in order to detect and track centriole amplification, elongation, disengagement, and migration.

By combining the MEF-MCC and knock-in mouse model with spatiotemporal imaging in control and nocodazole-treated cells(treated acutely or chronically), the authors define the sequence of events during centriole amplification, revealing the critical roles of microtubules for the first time. Initially, the centrosome-mediated microtubule network forms, organizing a pericentrosomal nest from which procentrioles and deuterosomes emerge. Their findings indicate the importance of microtubules in recruiting and maintaining pericentriolar material clouds that contain DEUP1, PCNT, SAS6, PLK1, PLK4, and tubulins. Following the amplification stage, the procentrioles mature, leading to cells displaying numerous MTOCs, as demonstrated by regrowth experiments. Mature centrioles then disengage from deuterosomes, attach to the nuclear envelope, and migrate to the apical surface facilitated by microtubules.

Strengths:

The manuscript provides new insights into the regulatory function of microtubules in centriole amplification. Addressing the role of microtubules during different stages of centriole amplification required the development of new tools to study brain MCCs, which will be useful in future studies of MCCs. A notable strength of this manuscript is the authors' thorough and quantitative analysis of highly dynamic processes in MCCs. The precision and detail in describing these dynamic events are impressive. This comprehensive analysis advances our understanding of MCC biology.

Weaknesses:

The role of microtubules and other molecular players during different stages of centriole amplification in brain MCCs can be further studied and strengthened using the tools developed in the manuscript. A more quantitative description of some of the analysis performed in the manuscript is required to strengthen the conclusions.

eLife assessment

In this important study, Boudjema et al. use cell culture models and advanced microscopic imaging to provide detailed analyses of the cellular events underlying centriole amplification, apical migration, and assembly of hundreds of motile cilia in multi-ciliated cells. This largely descriptive work provides a better understanding of this process that is of interest to cell biologists studying centrioles and cilia. Most of the claims are supported by the data, but the study would benefit from additional analyses regarding the roles of microtubules, which are currently incomplete, and from text editing to improve accessibility and readability, especially for a wider audience.

Reviewer #1 (Public Review):

The manuscript by Boudjema et al. describes the cellular events underlying centriole amplification and apical migration to allow the assembly of hundreds of motile cilia in multi-ciliated cells. For this, they use cell culture models in combination with fixed and live cell imaging using antibody staining and fluorescence from endogenously tagged centriole and deuterostome markers, respectively. The work is largely descriptive and functional analyses are restricted to treatment with the microtubule depolymerizing drug nocodazole. The imaging is state-of-the-art including confocal microscopy, live imaging with optical sectioning and high optical and temporal resolution, as well as super-resolution imaging by ultra-expansion microscopy.

The study does a good job of providing a very detailed description of the dynamics of centrioles and deuterostomes that lead to centriole amplification and apical migration in multiciliated cells. This detailed view was missing in previous work. It also reveals the involvement of microtubules at multiple steps: the formation of a cloud of deuterostome precursors, the nuclear envelope tethering of newly formed centrioles, their separation, and their migration to the apical surface.

It would have been useful to expand the analysis of the role of microtubules by including analyses of the requirement for specific microtubule motors, for a better understanding and additional evidence that microtubule-based transport is involved. A weak point is that there is no visualization of microtubules together with deuterosomes and centrioles at the different steps of centriole amplification and migration, to directly address how these structures may interact with and move along microtubules.

Overall, apart from experimental aspects and since this is largely a descriptive study, the manuscript would benefit from more precise language and a better description of the complex events underlying centriole amplification and movements.

Reviewer #2 (Public Review):

This important work will be of interest to centriole and cilia cell biologists. It describes in detail how microtubules control multiple aspects of centriole amplification in brain multiciliated cells. This study provides a greater time-resolved and molecular proteomic mapping of the different steps involved, with or without microtubule disruption. Boudjema et al. show that microtubules are important throughout the centriole amplification process, from the early stages, where the procentrioles emerge from a pericentriolar "nest", through the growth stage where microtubules maintain the perinuclear localisation, to the detachment stage, where microtubules assist in perinuclear disengagement and apical migration. The results are generally well supported by the evidence, but the manuscript would benefit significantly from some heavy editing to introduce more niche terms, standardize abbreviations in text, and labels on figures to help bring the readers, especially non-specialists, along with them - increasing the accessibility of their work.

Reviewer #3 (Public Review):

Summary:

The authors want to prove that there is a redox potential between germline stem cells (GSCs) and somatic cyst stem cells (CySCs) in the Drosophila testis, with ROS being higher in the former compared to the latter. They also want to prove that ROS travels from CySCs to GSCs. Finally, they begin to characterize the phenotypes caused by loss of SOD (which normally lowers ROS levels) in the tj- lineage and how this impacts the germline.

Strengths:

The role of SOD in somatic support cells is an under-explored area.

Weaknesses:

The authors fall short of accomplishing their goals. There are issues with the concept of the paper (ROS gradient between cells that causes a transfer of ROS across membranes for homeostasis), the data, the figures, and the scholarship of the testis. I have discussed each of the points in detail below. These weaknesses negatively impact the conclusions put forward by the authors. In short, their data is not compelling: there is no evidence provided by the authors that ROS diffuses from CySCs to GSCs as most of the claims about stem cells are founded on data about differentiating germ and somatic cells. The somatic SOD depletion phenotype is incompletely characterized and several pathways appear to change in these cells, including reduced Egfr signaling, increased Tor signaling, and increased Hh signaling. None of these results are sufficiently followed up on. And none of them are considered relative to their known roles in the testis. For example, high Hh signaling in CySCs increases their competitiveness with GSCs. Increased Tor signaling in all CySCs does not affect the CySC lineage. Reduced Egfr signaling in CySCs reduces the number of CySCs and reduces/inhibits abscission between GSCs-gonialblasts.

Major issues:

(1) Data<br /> a. Problems proving which mitochondria are associated with which lineage.<br /> b. There is no evidence that ROS diffuses from CySCs into GSCs.<br /> c. The changes in gst-GFP (redox readout) are possibly seen in differentiating germ cells (i.e., spermatogonia) but not in GSCs. This weakens their model that ROS in CySC is transferred to GSCs.<br /> d. Most of the paper examines the effect of SOD depletion (which should increase ROS) on the CySC lineage and GSC lineage. One big caveat is that tj-Gal4 is expressed in hub cells (Fairchild, 2016) so the loss of SOD from hub cells may also contribute to the phenotype. In fact, the niche in Figure 2D looks larger than the niche in the control in Figure 2C, arguing that the expression of Tj in niche cells may be contributing to the phenotype. The authors need to better characterize the niche in tj>SOD-RNAi testes.<br /> e. The tj>SOD-RNAi phenotype is an expansion of the Zfh1+ CySC pool, expansion of the Tj+ Zfh1- cyst cells (both due to increased somatic proliferation) and a non-autonomous disruption of the germline.<br /> f. I am not convinced that MAPK signaling is decreased in tj>SOD-i testes. Not only is this antibody finicky, but the authors don't have any follow-up experiments to see if they can restore SOD-depleted CySCs by expressing an Egfr gain of function. Additionally, reduced Egfr activity causes fewer somatic cells (not more) (Amoyel, 2016) and also inhibits abscission between GSCs and gonialblasts (Lenhart 2015), which causes interconnected cysts of 8- to 16 germ cells with one GSC emanating from the hub.<br /> g. The increase in Hh signaling in SOD-depleted CySCs would increase their competitiveness against GSCs and GSCs would be lost (Amoyel 2014). The authors need to validate that Hh protein expression is indeed increased in SOD-depleted CySCs/cyst cells and which cells are producing this Hh. Normally, only hub cells produce Hh (Michel, 2012; Amoyel 2013) to promote self-renewal in CySCs.<br /> h. The increase in p4E-BP is an indication that Tor signaling is increased, but an increase in Tor in the CySC lineage does not significantly affect the number of CySCs or cyst cells (Chen, 2021). So again I am not sure how increased Tor factors into their phenotype.<br /> i. The over-expression of SOD in CySCs part is incomplete. The authors would need to monitor ROS in these testes. They would also need to examine with tj>SOD affects the size of the hub.

(2) Concept<br /> Why would it be important to have a redox gradient across adjacent cells? The authors mention that ROS can be passed between cells, but it would be helpful for them to provide more details about where this has been documented to occur and what biological functions ROS transfer regulates.

(3) Issues with scholarship of the testis<br /> a. Line 82 - There is no mention of BMPs, which are the only GSC-self-renewal signal. Upd/Jak/STAT is required for adhesion of GSCs to the niche but not self-renewal (Leatherman and Dinardo, 2008, 2010). The author should read a review about the testis. I suggest Greenspan et al 2015. The scholarship of the testis should be improved.<br /> b. Line 82-84 - BMPs are produced by both hub cells and CySCs. BMP signaling in GSCs represses bam. So it is not technically correct to say the CySCs repress bam expression in GSCs.<br /> c. Throughout the figures the authors score Vasa+ cells for GSCs. This is technically not correct. What they are counting is single, Vasa+ cells in contact with the niche. All graphs should be updated with the label "GSCs" on the Y-axis.

(4) Issues with the text<br /> a. Line 1: multi-lineage is not correct. Multi-lineage refers to stem cells that produce multiple types of daughter cells. GSCs produce only one type of offspring and CySCs produce only one type of offspring. So both are uni-lineage. Please change accordingly.<br /> b. Lines 62-75 - Intestinal stem cells have constitutively high ROS (Jaspar lab paper) so low ROS in stem cell cells is not an absolute.<br /> c. Line 79: The term cystic is not used in the Drosophila testis. There are cyst stem cells (CySCs) that produce cyst cells. Please revise.<br /> d. Line 90 - perfectly balanced is an overstatement and should be toned down.<br /> e. Line 98 - division of labour is not supported by the data and should be rephrased.<br /> f. Line 200 - the authors provide no data on BMPs - the GSC self-renewal cue - so they should avoid discussing an absence of self-renewal cues.

(5) Issues with the figures<br /> a. The images are too small to appreciate the location of mitochrondria in GSCs and CySCs.<br /> b. Figure 1<br /> i. cell membranes are not marked, reducing the precision of assigning mitochondria to GSC or CySCs. It would be very helpful if the authors depleted ATP5A from GSCs and showed that the puncta are reduced in these cells and did a similar set of experiments for the tj-Gal4 lineage. It would also be very helpful if the authors expressed membrane markers (like myr-GFP) in the GSC and then in the CySC lineage and then stained with ATP5A. This would pinpoint in which cells ATP5A immunoreactivity is occurring.<br /> ii. The presumed changes in gst-GFP (redox readout) are possibly seen in differentiating germ cells (i.e., spermatogonia) but not in GSC.<br /> iii. Panels F, Q, and S are not explained and currently are irrelevant.<br /> c. Figure 3K - The evidence to support less Ecad in GSCs in tj>SOD-i testes is not compelling as the figure is too small and the insets show changes in Ecad in somatic cells, not GSC.<br /> d. Figure 4:<br /> i. Panel A, B The apparent decline (not quantified) may not contribute to the phenotype.<br /> ii. dpERK is a finicky antibody and the authors are showing a single example of each genotype. This is an important experiment because the authors are going to use it to conclude that MAPK is decreased in the tj>SOD-i samples. However, the authors don't have any positive (dominant-active Egfr) or negative (tj>mapk-i). As is standing the data are not compelling. The graph in F does not convey any useful information.<br /> e. Figure S1D - cannot discern green on black. It is critical for the authors to show monochromes (gray scale) for the readouts that they want to emphasize. I cannot see the green on black in Figure S1D.<br /> f. Figure S4 - there is no quantification of the number of Tj cells in K-N.

(6) Issues with Methods<br /> a. Materials and Methods are not described in sufficient depth - please revise.<br /> b. Note that tj-Gal4 has real-time expression in hub cells and this is not considered by the authors. The ideal genotype for targeting CySCs is tjGal4, Gal80TS, hh-Gal80. Additionally, the authors do not mention whether they are depleting throughout development into adulthood or only in adults. If the latter, then they must have used a temperature shift like growing the flies at 18C and then upshifting to 25C or 29C during adult stages.<br /> c. The authors need to show data points in all of the graphs. Some graphs do this but others do not.<br /> d. The authors state that all data points are from three biological replicates. This is not sufficient for GSC and CySC counts. Most labs count GSCs and CySCs from at least 10 testes of the correct genotype.

eLife assessment

This work focuses on the role of Reactive Oxygen Species (ROS) signaling in cyst stem cells of the Drosophila testis. In particular, the authors suggest that ROS can act as signaling molecules between somatic and germ stem cells of the testis. The work is potentially useful, although the evidence that supports the authors' claims is incomplete.

Reviewer #1 (Public Review):

The manuscript by Majhi and colleagues describes the effects of manipulating ROS levels in somatic stem cells of the testis on overall testis architecture, signaling, and function. The conclusions made by the authors are somewhat difficult to judge as the changes to the testis cell types are mostly not apparent in the representative images shown. This is true in examining gstD1-GFP expression and in the analysis of cell types and behaviours (e.g. cell cycle) and cell signaling pathway activity. Thus, the reader is left to try and interpret the quantification of the data to justify the authors' conclusions, but it is often not clear how the quantification was accomplished. For example, it is not clear how CySC vs. GSC quantification is done when the molecular markers used do not define the surface of these cells (plasma membrane) and mark different cellular compartments (Tj is nuclear while Vasa is perinuclear or cytoplasmic). Why the changes reported in quantification are not apparent in the specific example images chosen for the figures is worrisome. I'm much more used to being able to clearly see what the authors are reporting in the images, and then using the quantification to illustrate the range of data observed and demonstrate statistical significance. For this reason, I'm very concerned about the strength and validity of the conclusions. In addition, while many different characteristics of the testis somatic and germline cells are analyzed, a general and consistent view of how ROS affects these cells is not presented. In particular, one of the principle conclusions, that ROS signaling in the CySCs affects ROS signaling in the GSCs, is not well-supported by the data presented.

Specific Comments:

In Figure 1, it is very difficult to identify where CySCs end and GSCs begin without using a cell surface marker for these different cell types. In addition, the methods for quantifying the mitochondrial distribution in GSCs vs. CySCs are very much unclear, and appear to rely on colocalization with molecular markers that are not in the same cellular compartment (Tj-nuclear vs Vasa-perinuclear and cytoplasmic), the reader has no way to determine the validity of the mitochondrial distribution. Similarly, the labeling with gstD1-GFP is also very much unclear - I see little to no GFP signal in either GSCs or CySCs in panels 1G-K. Lastly, while the expression of SOD in CySCs does increase the gstD1-GFP signal in CySCs, the effects on GSCs claimed by the authors are not apparent.

In Figure 2, while the cell composition of the niche region does appear to be different from controls when SOD1 is knocked down in the CySCs, at least in the example images shown in Figures 2A and B, how cell type is quantified in Figures 2E-G is very much unclear in the figure and methods. Are these counts of cells contacting the niche? If so, how was that defined? Or were additional regions away from the niche also counted and, if so, how were these regions defined?

In Figure 3, it is quite interesting that there is an increase in Eya+, differentiating cyst cells in SOD1 knockdown animals, and that these Eya+ cells appear closer to the niche than in controls. However, this seems at odds with the proliferation data presented in Figure 2, since Eya+ somatic cells do not normally divide at all. Are they suggesting that now differentiating cyst cells are proliferative? In addition, it is important for them to show example images of the changes in Socs36E and ptp61F expression.

Overall, the various changes in signaling are quite puzzling-while Jak/Stat signaling from the niche is reduced, hh signaling appears to be increased. Similarly, while the authors conclude that premature differentiation occurs close to the niche, EGF signaling, which occurs from germ cells to cyst cells during differentiation, is decreased. Many times these changes are contradictory, and the authors do not provide a suitable explanation to resolve these contradictions.

Reviewer #2 (Public Review):

Summary:

In this work, the authors investigate the role of the Superoxide disumutase 1 (Sod1) enzyme, which acts to reduce the reactive oxygen species load, in the Drosophila testis. They show that the knockdown of Sod1 in somatic cells impacts stem cell numbers both autonomously in the soma and non-autonomously in the germline. Somatic stem cell numbers are increased, while germline stem cells are decreased and differentiate prematurely. The authors then show that in somatic Sod1 knockdowns, several signalling pathways are disrupted and that these may be responsible at least in part for the phenotypes observed. Finally, over-expression of Sod1 in the soma results in opposite phenotypes, suggesting that ROS levels do play a role in maintaining the balance between both stem cell populations in the testis.

Strengths:

The main strength of this work is to show a previously unappreciated role for Sod1 (and presumably by extension of ROS) in the Drosophila testis and in the regulation of stem cell self-renewal and differentiation. The authors use multiple readouts to show that the knockdown of Sod1 in the soma increases the number of somatic cells and also drives a non-autonomous, premature differentiation of germ cells. They also quantify the early differentiation of the germline using two different methods. Importantly, overexpression of Sod1 produces opposite phenotypes to knockdown, strengthening the conclusions.

Weaknesses:

Although the data presented are interesting, an important weakness of the manuscript as it currently stands is that many statements are not fully supported by the data. In particular, the authors do not provide any evidence of "cell redox-pairs" as indicated in the manuscript title, nor of intercellular redox gradients, as stated in several places throughout. While the data are consistent with non-autonomous regulation of ROS levels, this would not constitute a gradient. However, and crucially, there is no evidence provided to show that Sod1 manipulation in the soma is affecting ROS levels in the germline and that any of the phenotypes observed are a consequence of elevated ROS in the germline, rather than indirect effects caused by dysregulation of somatic self-renewal and differentiation, which is known to impact the germline. Indeed, there are many published reports of autonomous manipulations in the soma that influence either germline stem cell number (eg PMID: 19797664 among others) or differentiation (eg PMID: 17629483). The latter example is particularly relevant as the authors show altered somatic ERK levels, and the role of somatic ERK in promoting germ cell development is well established (PMID: 11048722, 11048723,...). Thus, whether Sod1 plays any non-autonomous role in controlling germ cell fate through ROS in the germline directly, or whether the phenotypes observed can all be explained by autonomous effects on somatic cell behaviour is debatable, but the experiments presented here do not distinguish between these two hypotheses. The only evidence presented by the authors for a non-autonomous role of Sod1 is the expression of a GFP reporter for gstD1. The quantifications and images are not clear and do not show unambiguously that this reporter is expressed in germ cells. Indeed, the quantifications show overlap between somatic and germline markers, suggesting that either the images themselves or the way they are quantified does not allow the authors to distinguish between the two cell types. Similarly, the claim that somatic mitochondria are enriched at the CySC-GSC interface and that this distribution maintains the redox balance in the niche is not supported by any experimental data. CySCs are extremely thin cells and much of the space is occupied by the nucleus (PMID: 114676), therefore it is likely that mitochondria would be enriched at the periphery. A careful analysis would be necessary to show that this enrichment is specific to the interface with GSCs. Moreover, no experiments are conducted to test whether mitochondrial distribution in CySCs has any impact on GSCs. Finally, no experiments are conducted to show definitively that the phenotypes observed upon Sod1 knockdown are indeed due to increased ROS, while this claim is made several times in the text. At present, the data presented here can support a role for Sod1 in somatic CySCs, but much more caution is required in attributing this to either ROS or intercellular ROS signaling. Therefore, several claims made in the title and throughout the text are not supported by evidence.

Besides this central point, there are other areas that should be improved. In particular, the data using the Fucci reporter to show accelerated proliferation do not appear convincing. It would seem that the proportions of cells in each phase are roughly similar, just that there are more cycling cells. A careful analysis of these results would distinguish between these two and determine whether Sod1 knockdown simply impairs differentiation (and therefore results in more somatic cells proliferating) or whether it speeds up the cell cycle (resulting in an increased mitotic index as suggested, but this requires a ratio to be shown). Similarly, several quantifications are not clearly explained, making it hard to understand what is being measured. As an example, while the decrease in pERK in CySCs is clear from the image and matched in the quantification, the increase in cyst cells is not apparent from the fire LUT used. The change in fluorescence intensity therefore may be that more cells have active ERK, rather than an increase per cell (similar arguments apply to the quantifications for p4E-BP or Ptc). Therefore, it is hard to know whether Sod1 knockdown results in increased or decreased signaling in individual cells.

Impact of study:

Demonstrating intercellular communication through ROS and its importance in maintaining the balance between two stem cell populations would be a finding of interest to a broad field. However, it remains to be demonstrated that this is the case, and given this, this study will have a limited impact.

Reviewer #3 (Public Review):

The authors tested a dietary intervention focused on improving meal regularity in this interesting paper. The study, a two-group, single-center, randomized, controlled, single-blind trial, utilized a smartphone application to track participants' meal frequencies and instructed the experimental group to confine their eating to these times for six weeks. The authors concluded that improving meal regularity reduced excess body weight despite food intake not being altered and contributed to overall improvements in well-being.

The concept is interesting, but the need for more rigor is of concern.

A notable limitation is the reliance on self-reported food intake, with the primary outcome being self-reported body weight/BMI, indicating an average weight loss of 2.62 kg. Despite no observed change in caloric intake, the authors assert weight loss among participants.

The trial's reliance on self-reported caloric intake is problematic, as participants tend to underreport intake; for example, in the NEJM paper (DOI: 10.1056/NEJM199212313272701), some participants underreported caloric intake by approximately 50%, rendering such data unreliable and hence misleading. More rigorous methods for assessing food intake are available and should have been utilized. Merely acknowledging the unreliability of self-reported caloric intake is insufficient as it would still leave the reader with the impression that there is no change in food intake when we actually have no idea if food intake was altered. A more robust approach to assessing food intake is imperative. Even if a decrease in caloric intake is observed through rigorous measurement, as I am convinced a more rigorous study would unveil testing this paradigm, this intervention may merely represent another short-term diet among countless others that show that one may lose weight by going on a diet, principally due to heightened dietary awareness.

Furthermore, the assessment of circadian rhythm using the MCTQ, a self-reported measure of chronotype, may not be as reliable as more objective methods like actigraphy.

Given the potential limitations associated with self-reported data in both dietary intake and circadian rhythm assessment, the overall impact of this manuscript is low. Increasing rigor by incorporating more objective and reliable measurement techniques in future studies could strengthen the validity and impact of the findings.

eLife assessment

This study investigates a dietary intervention that employs a smartphone app to promote meal regularity, which may be useful. Despite no observed changes in caloric intake, the authors report significant weight loss. While the concept is very interesting and deserves to be studied due to its potential clinical relevance, the study's rigor needs to be revised, notably for its reliance on self-reported food intake, a highly unreliable way to assess food intake. Additionally, the study theorizes that the intervention resets the circadian clock, but the study needs more reliable methods for assessing circadian rhythms, such as actigraphy.

Reviewer #1 (Public Review):

The authors Wilming and colleagues set out to determine the impact of regularity of feeding per se on the efficiency of weight loss. The idea was to determine if individuals who consume 2-3 meals within individualized time frames, as opposed to those who exhibit stochastic feeding patterns throughout the circadian period, will cause weight loss.

The methods are rigorous, and the research is conducted using a two-group, single-center, randomized-controlled, single-blinded study design. The participants were aged between 18 and 65 years old, and a smartphone application was used to determine preferred feeding times, which were then used as defined feeding times for the experimental group. This adds strength to the study since restricting feeding within preferred/personalized feeding windows will improve compliance and study completion. Following a 14-day exploration phase and a 6-week intervention period in a cohort of 100 participants (inclusive of both the controls and the experimental group that completed the study), the authors conclude that when meals are restricted to 45min or less durations (MTVS of 3 or less), this leads to efficient weight loss. Surprisingly, the study excludes the impact of self-reported meal composition on the efficiency of weight loss in the experimental group. In light of this, it is important to follow up on this observation and develop rigorous study designs that will comprehensively assess the impact of changes (sustained) in dietary composition on weight loss. The study also reports interesting effects of regularity of feeding on eating behavior, which appears to be independent of weight loss. Perhaps the most important observation is that personalized interventions that cater to individual circadian needs will likely result in more significant weight loss than when interventions are mismatched with personal circadian structures. One are of concern for the study is its two-group design; however, single-group cross-over designs are tedious to develop, and an adequate 'wash-out' period may be difficult to predict. A second weakness is not considering the different biological variables and racial and ethnic diversity and how that might impact outcomes. In sum, the authors have achieved the aims of the study, which will likely help move the field forward.

Reviewer #2 (Public Review):

Summary:

The authors investigated the effects of the timing of dietary occasions on weight loss and well-being with the aim of explaining if a consistent, timely alignment of dietary occasions throughout the days of the week could improve weight management and overall well-being. The authors attributed these outcomes to a timely alignment of dietary occasions with the body's own circadian rhythms. However, the only evidence the authors provided for this hypothesis is the assumption that the individual timing of dietary occasions of the study participants identified before the intervention reflects the body's own circadian rhythms. This concept is rooted in understanding of dietary cues as a zeitgeber for the circadian system, potentially leading to more efficient energy use and weight management. Furthermore, the primary outcome, body weight loss, was self-reported by the study participants.

Strengths:

The innovative focus of the study on the timing of dietary occasions rather than daily energy intake or diet composition presents a fresh perspective in dietary intervention research. The feasibility of the diet plan, developed based on individual profiles of the timing of dietary occasions identified before the intervention, marks a significant step towards personalised nutrition.

Weaknesses:

Several methodological issues detract from the study's credibility, including unclear definitions not widely recognized in nutrition or dietetics (e.g., "caloric event"), lack of comprehensive data on body composition, and potential confounders not accounted for (e.g., age range, menstrual cycle, shift work, unmatched cohorts, inclusion of individuals with normal weight, overweight, and obesity). The primary outcome's reliance on self-reported body weight and subsequent measurement biases further undermines the reliability of the findings. Additionally, the absence of registration in clinical trial registries, such as the EU Clinical Trials Register or clinicaltrials.gov, and the multiple testing of hypotheses which were not listed a priori in the research protocol published on the German Register of Clinical Trials impede the study's transparency and reproducibility.

Achievement of Objectives and Support for Conclusions:

The study's objectives were partially met; however, the interpretation of the effects of meal timing on weight loss is compromised by the weaknesses mentioned above. The evidence only partially supports some of the claims due to methodological flaws and unstructured data analysis.

Impact and Utility:

Despite its innovative approach, significant methodological and analytical shortcomings limit the study's utility. If these issues were addressed, the research could have meaningful implications for dietary interventions and metabolic research. The concept of timing of dietary occasions in sync with circadian rhythms holds promise but requires further rigorous investigation.

Reviewer #1 (Public Review):

In this work, the authors provide a valuable transcriptomic resource for the intermediate free-living transmission stage (miracidium larva) of the blood fluke. The single-cell transcriptome inventory is beautifully supplemented with in situ hybridization, providing spatial information and absolute cell numbers for many of the recovered transcriptomic states. The identification of sex-specific transcriptomic states within the populations of stem cells was particularly unexpected. The work comprises a rich resource to complement the biology of this complex system, however falls short in some technical aspects of the bioinformatic analyses of the generated sequence data.

(1) Four sequencing libraries were generated and then merged for analysis, however, the authors fail to document any parameters that would indicate that the clustering does not suffer from any batch effects.

(2) Additionally, the authors switch between analysis platforms without a clear motivation or explanation of what the fundamental differences between these platforms are. While in theory, any biologically robust observation should be recoverable from any permutation of analysis parameters, it has been recently documented that the two popular analysis platforms (Seurat - R and scanPy - python) indeed do things slightly differently and can give different results (https://www.biorxiv.org/content/10.1101/2024.04.04.588111v1). For this reason, I don't think that one can claim that Seurat fails to find clusters resolved by SAM without running a similar pipeline on the cluster alone as was done with SAM/scanPy here. The manuscript itself needs to be checked carefully for misleading statements in this regard.

(3) Similarly, the manuscript contains many statements regarding clusters being 'connected to', or forming a 'bridge' on the UMAP projection. One must be very careful about these types of statements, as the relative position of cells on a reduced-dimension cell map can be misleading (see Chari and Pachter 2023). To support these types of interpretations, the authors should provide evidence of gene expression transitions that support connectivity as well as stability estimates of such connections under different parameter conditions. Otherwise, these descriptors hold little value and should be dropped and the transcriptomic states simply defined as clusters with no reference to their positions on the UMAP.

(4) The underlying support for the clusters as transcriptomically unique identities is not well supported by the dot plots provided. The authors used very permissive parameters to generate marker lists, which hampers the identification of highly specific marker genes. This permissive approach can allow for extensive lists of upregulated genes for input into STRING/GO analyses, this is less useful for evaluating the robustness of the cluster states. Running the Seurat::FindAllMarkers with more stringent parameters would give a more selective set of genes to display and thereby increase the confidence in the reader as to the validity of profiles selected as being transcriptomically unique.

(5) Figure 5B shows a UMAP representation of cell positions with a statement that the clustering disappears. As a visual representation of this phenomenon, the UMAP is a very good tool, however, to make this statement you need to re-cluster your data after the removal of this gene set and demonstrate that the data no longer clusters into A/B and C/D. Also, as a reader, these data beg the question: which genes are removed here? Is there an over-representation of any specific 'types' of genes that could lead to any hypotheses of the function? Perhaps the STRING/GO analyses of this gene set could be informative.

(6) How do the proportions of cell types characterized via in situ here compare to the relative proportions of clusters obtained? It does not correspond to the percentages of the clusters captured (although this should be quantified in a similar manner in order to make this comparison direct: 10,686/20,478 = ~50% vs. 7%), how do you interpret this discrepancy? While this is mentioned in the discussion, there is no sufficient postulation as to why you have an overabundance of the stem cells compared to their presence in the tissue. While it is true that you could have a negative selection of some cell types, for example as stated the size of the penetration glands exceeds both that of the 10x capabilities (40uM), and the 30uM filters used in the protocol, this does not really address why over half of the captured cells represent 'stem cells'. A more realistic interpretation would be biological rather than merely technical. For example, while the composition of the muscle cells and the number of muscle transcriptomes captured are quite congruent at ~20%, the organism is composed of more than 50% of neurons, but only 15% of the transcriptomic states are assigned to neuronal. Could it be that a large fraction of the stem cells are actually neural progenitors? Are there other large inconsistencies between the cluster sizes and the fraction of expected cells? Could you look specifically at early transcription factors that are found in the neurons (or other cell types) within the various stem cell populations to help further refine the precursor/cell type relationships?

eLife assessment

This is a valuable study in which the authors provide an expression profile of the human blood fluke, Schistosoma mansoni. A strength of this solid study is in its inclusion of in situ hybridisation to validate the predictions of the transcript analysis.

Reviewer #2 (Public Review):

Summary:

In this manuscript the authors have generated a single-cell atlas of the miracidium, the first free-living stage of an important human parasite, Schistosoma mansoni. Miracidia develop from eggs produced in the mammalian (human) host and are released into freshwater, where they can infect the parasite's intermediate snail host to continue the life cycle. This study adds to the growing single-cell resources that have already been generated for other life-cycle stages and, thus, provides a useful resource for the field.

Strengths:

Beyond generating lists of genes that are differentially expressed in different cell types, the authors validated many of the cluster-defining genes using in situ hybridization chain reaction. In addition to providing the field with markers for many of the cell types in the parasite at this stage, the authors use these markers to count the total number of various cell types in the organism. Because the authors realized that their cell isolation protocols were biasing the cell types they were sequencing, they applied a second method to help them recover additional cell types.

Schistosomes have ZW sex chromosomes and the authors make the interesting observation that the stem cells at this stage are already expressing sex (i.e. W)-specific genes.

Weaknesses:

The sample sizes upon which the in situ hybridization results and cell counts are based are either not stated (in most cases) or are very small (n=3). This lack of clarity about biological replicates and sample sizes makes it difficult for the reader to assess the robustness of the results and the extremely small sample sizes (when provided) are a missed opportunity to explore the variability of the system, or lack thereof.

Although assigning transcripts to a given cell type is usually straightforward via in situ experiments, the authors fail to consider the potential difficulty of assigning the appropriate nuclei to cells with long cytoplasmic extensions, like neurons. In the absence of multiple markers and a better understanding of the nervous system, it seems likely that the authors have overestimated the number of neurons and misassigned other cell types based on their proximity to neural projections.

The conclusion that germline genes are expressed in the miracidia stem cells seems greatly overstated in the absence of any follow-up validation. The expression scales for genes like eled and boule are more than 3 orders of magnitude smaller than those used for any of the robustly expressed genes presented throughout the paper. These scales are undefined, so it isn't entirely clear what they represent, but neither of these genes is detected at levels remotely high (or statistically significant) enough to survive filters for cluster-defining genes. Given that germ cells often develop early in embryogenesis and arrest the cell cycle until later in development, and that these transcripts reveal no unspliced forms, it seems plausible that the authors are detecting some maternally supplied transcripts that have yet to be completely degraded.

Reviewer #1 (Public Review):

Summary:

The article explores the connection between immunogenic cell death (ICD)-related genes and bladder cancer prognosis, immune infiltration, and response to therapy. The study identifies a risk-scoring model involving four ICD-related genes (CALR, IL1R1, IFNB1, IFNG), showing a correlation between higher risk scores and weaker anti-tumor immune function.

Strengths:

The significance lies in the potential for personalized treatment guidance in bladder cancer. The establishment of a risk-scoring model to predict patient survival is noteworthy.

Weaknesses:

However, the identification of ICD-related genes is somewhat conventional, focusing on known genes regulating cancer immune response. To enhance the significance of the risk-scoring model, it would be better if the authors could validate the model across various cancer types. The strength of evidence appears moderate, but broader applicability would strengthen the findings.

eLife assessment

This study investigates the associations of four ICD-related genes in bladder cancer with increased immune cell infiltration and more prolonged survival. The study is valuable because it identifies a risk-scoring model, showing a correlation between high-risk scores based on four ICD-related genes and weak anti-tumour immune function. However, the evidence supporting the association of these genes and immunotherapy response is incomplete.

Reviewer #2 (Public Review):

Immunogenic cell death (ICD) can lead to the release of factors such as DAMPs which promote an adaptive immune response. In the context of cancer, there is clear evidence of anti-tumour benefits as a result of ICD, perhaps induced by chemotherapy.

Lilong et al used TCGA data to explore whether a previously published 34 gene 'ICD-related' signature could stratify bladder cancer patients by prognosis and ultimately predict patient survival. The gene signature contains many genes involved in inflammation and immunity (IFNg, IL6, TNF, IL17A, TLR4, CD8B, etc) and those related to ICD (such as CALR, HMGB1, HSP, NLRP3, etc). The authors divide patients into 'ICD-high' and '-low' based on the expression of this gene set and find that 'ICD-high' is associated with longer survival in TCGA bladder cancer data. The authors further argue that ICD-high group responds better to PD1 therapies. From this 34-gene signature, it appears that LASSO regularisation and Cox analysis identifies a four-gene 'risk' signature (CALR, IL1R1, IFNB1, IFNG) which is associated with shorter patient survival and lower immunotherapy response rates. This is the primary finding. Their methodology is very similar to a publication in 2021 in Frontiers in Immunology instead in the context of head and neck squamous cell carcinoma. This paper is not referenced.

In terms of the strengths of the work, it is certainly plausible that the author's four gene signature has an association with survival in bladder cancer, at least based on the two datasets studied. However, the relatedness of their findings to ICD is unconvincing, and glaring omissions from the manuscript in terms of methods limit confidence in the work. The authors show a potential association with bladder cancer patient survival and their four gene signatures, but substantial revisions are required for this to be appropriately evidenced.

Reviewer #2 (Public Review):

Summary:

The authors provide compelling evidence that stimulation of epidermal cells in Drosophila larvae results in the stimulation of sensory neurons that evoke a variety of behavioral responses. Further, the authors demonstrate that epidermal cells are inherently mechanoresponsive and implicate a role for store-operated calcium entry (mediated by Stim and Orai) in the communication to sensory neurons.

Strengths:

The study represents a significant advance in our understanding of mechanosensation. Multiple strengths are noted. First, the genetic analyses presented in the paper are thorough with appropriate consideration to potential confounds. Second, behavioral studies are complemented by sophisticated optogenetics and imaging studies. Third, identification of roles for store-operated calcium entry is intriguing. Lastly, conservation of these pathways in vertebrates raise the possibility that the described axis is also functional in vertebrates.

Weaknesses:

The study has a few conceptual weaknesses that are arguably minor. The involvement of store-operated calcium entry implicates ER calcium store release. Whether mechanical stimulation evokes ER calcium release in epidermal cells and how this might come about (e.g., which ER calcium channels, roles for calcium-induced calcium release etc.) remains unaddressed. On a related note, the kinetics of store-operated calcium entry is very distinct from that required for SV release. The link between SOC and epidermal cells-neuron transmission is not reconciled. Finally, it is not clear how optogenetic stimulation of epidermal cells results in the activation of SOC.

eLife assessment

This is an important work and provides a significant advance in our understanding of mechanosensation in the epidermis. The evidence presented is solid, however, additional work such as testing whether the activation time can be shorter, addressing the mechanism underlying endoplasmic reticulum calcium release, and improving the clarity of writing and rigor of analysis would strengthen the study. This work will be of broad interest to neurobiologists, epithelial cell biologists, and mechanobiologists.

Reviewer #1 (Public Review):

Summary:

In this meticulously conducted study, the authors show that Drosophila epidermal cells can modulate escape responses to noxious mechanical stimuli. First, they show that activation of epidermal cells evokes many types of behaviors including escape responses. Subsequently, they demonstrate that most somatosensory neurons are activated by activation of epidermal cells, and that this activation has a prolonged effect on escape behavior. In vivo analyses indicate that epidermal cells are mechanosensitive and require stored-operated calcium channel Orai. Altogether, the authors conclude that epidermal cells are essential for nociceptive sensitivity and sensitization, serving as primary sensory noxious stimuli.

Strengths:

The manuscript is clearly written. The experiments are logical and complementary. They support the authors' main claim that epidermal cells are mechanosensitive and that epidermal mechanically evoked calcium responses require the stored-operated calcium channel Orai. Epidermal cells activate nociceptive sensory neurons as well as other somatosensory neurons in Drosophila larvae, and thereby prolong escape rolling evoked by mechanical noxious stimulation.

Weaknesses:

Core details are missing in the protocols, including the level of LED intensity used, which are necessary for other researchers to reproduce the experiments. For most experiments, the epidermal cells are activated for 60 s, which is long when considering that nocifensive rolling occurs on a timescale of milliseconds. It would be informative to know the shortest duration of epidermal cell activation that is sufficient for observing the behavioral phenotype (prolongation of escape behavior) and activation of sensory neurons.

You do not have control over identifying information

Your Pseudonym should work under your control and anything related to that

eLife assessment

The study presents important findings on the role of MSI2-HOXA9 translocation in chronic myeloid leukemia. The authors provide convincing evidence supporting the role of this translocation in leukemogenesis by using elegant mouse modeling and in vitro mechanistic studies. Consistent with the reviews, the studies can be strengthened with further murine and cell line experiments.

Reviewer #1 (Public Review):

This is a very interesting study by Kyle Spinler et al., demonstrating the novel role of MSI2-HOXA9 translocation in the development and pathogenesis of blast crisis CML. The authors employed appropriate in vitro and in vivo assays, including a sophisticated transplantation-based model of CML, which is well-established in the field of studying the pathogenesis of CML. Additionally, the authors successfully concluded that the MSI2 RNA binding domain RRM1 has a preferential impact on the growth of blast crisis CML.

The quality of this research article could be significantly enhanced by addressing the following points:

Major:

(1) Do mice with BCR-ABL/MSI2-HOXA9 leukemia have an increased pool of leukemic stem cells (LSC), or do they have an increased propensity to develop blast cells? Is it the number of LSCs that has increased, or is it the function of LSC to give rise to the disease that has increased? It is not clear if the detected differences in Lineage-negative cells (Figure S1D) were detected in vitro in retrovirally transduced cells or were detected in vivo in transplanted mice. If the differences were detected in vitro, could the author confirm the same findings in vivo? This will greatly enhance the understanding of in vivo disease pathogenesis and could directly link the aggressivity of the disease (shortened survival) with an increased stem cell-like population.

(2) The authors suggest that BCR-ABL/MSI2-HOXA9 leads to the development of blast crisis-CML. One of the main characteristics of blast crisis-CML is drug resistance. Is BCR-ABL/MSI2-HOXA9 leukemia resistant to classical CML treatment drugs?

(3) The authors have emphasized the heightened expression of Polrmt in delineating the mitochondrial phenotype of BCR-ABL/MSI2-HOXA9 leukemia cells. However, the regulatory mechanism governing the expression of Polrmt by MSI2-HOXA9 has not been clearly demonstrated by the authors. Unveiling this mechanism would constitute a novel finding and significantly elevate the quality of the research.

(4) Did the authors observe any survival differences between BCR-ABL/NUP98-HOXA9 and BCR-ABL/MSI2-HOXA9?

Reviewer #2 (Public Review):

The manuscript titled, "Identification of a Musashi2 translocation as a novel oncogene in myeloid leukemia" by Spinler et al. studies the functional role of the translocation t(7;17)(p15;q23), resulting in MSI2/HOXA9 fusion gene, as a secondary driver in bcCML. MSI2-HOXA9 forced expression along with BCR-ABL enhances colony formation and leads to a more aggressive disease in vivo. Depletion of the RNA binding domain RRM1 or RRM2 of MSI2 led to a significant reduction in colony formation, with RRM1 depletion specifically impacting differentiation and blast cell counts. Mechanistically, the authors find that MSI2-HOXA9 aberrantly localizes to the nucleus, elevating the expression of mitochondrial polymerase Polrmt, thereby leading to upregulation of mitochondrial components and enhancing mitochondrial function and basal respiration. Overall, this study examines how the rare MSI2-HOXA9 fusion gene can act as a novel cooperating oncogene and could serve as a secondary hit in the progression of CML to blast crisis.

Strengths:

(1) Demonstration that MSI2-HOXA9 contributes to oncogenesis in the BCR-ABL context.

(2) Development of a novel cooperativity model for BCR-ABL and provides additional supporting data for the role of MSI2 in leukemogenesis.

(3) Evidence that MSI2-HOXA9 acts uniquely compared to MSI2 alone through nuclear vs. cytoplasmic localization and activation of mitochondrial polymerase Polrmt.

Weaknesses:

(1) MSI2-HOXA9 fusion is extremely rare as it has been only found in a handful of patients and it is not clear whether other MSI2 fusions function in a similar manner.

(2) The mechanism needs to be strengthened since MSI2 alone or the HOXA9 mutant may not be linked to the mitochondrial mechanism.

(3) It is not clear that the mitochondrial pathway is sufficient for the MSI2-HOXA9 oncogenic mechanism.

Author response:

We are grateful to the reviewers for their interest and enthusiasm about the work, and deeply appreciate their constructive comments and suggestions. Our responses are below

(1) Do mice with BCR-ABL/MSI2-HOXA9 leukemia have an increased pool of leukemic stem cells (LSC), or do they have an increased propensity to develop blast cells? Is it the number of LSCs that has increased, or is it the function of LSC to give rise to the disease that has increased? It is not clear if the detected differences in Lineage-negative cells (Figure S1D) were detected in vitro in retrovirally transduced cells or were detected in vivo in transplanted mice. If the differences were detected in vitro, could the author confirm the same findings in vivo? This will greatly enhance the understanding of in vivo disease pathogenesis and could directly link the aggressivity of the disease (shortened survival) with an increased stem cell-like population.

We find that BCR-ABL/MSI2-HOXA9 leads to a marked increase in Lineage negative (Lin-) cells which contains the LSC fraction. Specifically, the LSC containing fraction represented 14.1% of the BCR-ABL driven disease and 56.7% of the BCR-ABL and MSI2-HOXA9 driven disease (p<.0001). This suggests that MSI2-HOXA9 triggers the expansion of the undifferentiated LSC containing pool. In addition, the blast frequency was also increased albeit to a lesser extent, with 63.8% blasts (SEM 1.1) for BCR-ABL and 83.3% (SEM 3.1) for BCR-ABL/MSI2-HOXA9 (p=.0001). This suggests that the resulting aggressive disease seen with MSI2-HOXA9 is a consequence of a large increase in undifferentiated  LSC containing cells, as well as the resulting increase in the blast count. The Lin- cells were analyzed from fully established leukemias in vivo (Fig. S1D)

(2) The authors suggest that BCR-ABL/MSI2-HOXA9 leads to the development of blast crisis-CML. One of the main characteristics of blast crisis-CML is drug resistance. Is BCR-ABL/MSI2-HOXA9 leukemia resistant to classical CML treatment drugs?

The sensitivity to Imatinib is a very interesting question. In general, while differentiated cells in CML are sensitive to Imatinib, the more undifferentiated cells (LSCs) are resistant1,2. Based on the fact that therapy resistance in blast crisis is largely driven by the undifferentiated fraction of leukemia cells, and given that BCR-ABL/MSI2-HOXA9 driven disease harbors a larger fraction of these undifferentiated cells, we would predict that BCR-ABL/MSI2-HOXA9 leukemia would also be more resistant to imatinib. However, this would need to be experimentally demonstrated and is an important question to address.

(3) The authors have emphasized the heightened expression of Polrmt in delineating the mitochondrial phenotype of BCR-ABL/MSI2-HOXA9 leukemia cells. However, the regulatory mechanism governing the expression of Polrmt by MSI2-HOXA9 has not been clearly demonstrated by the authors. Unveiling this mechanism would constitute a novel finding and significantly elevate the quality of the research.

Since Polrmt and mitochondrial genes are transcribed in the nucleus we explored whether MSI2-HOXA9 may control mitochondrial gene expression by triggering expression of Polrmt and other key transcription factors. Consistent with this possibility, MSI2-HOXA9 was preferentially found in the nucleus relative to MSI2. In addition, there were 10 occurrences of the minimal MSI2 RRM1 consensus binding sequence UAGU within the Polrmt transcript. While this is consistent with the possibility that Polrmt expression can be post-transcriptionally modulated by MSI2-HOXA9, this needs to be experimentally validated using Clip Seq analysis with wild type MSI2 as well as the MSI2-HOXA9 fusion protein in context of blast crisis CML.

(4) Did the authors observe any survival differences between BCR-ABL/NUP98-HOXA9 and BCR-ABL/MSI2-HOXA9?

In previous work from our lab we have found that the median survival for BCR-ABL/NUP98-HOXA9 was 17 days, and with BCR-ABL/ MSI2-HOXA9 was 18.5 days (p value of 0.22). This suggests that there is not a significant difference in survival times between the leukemias driven by the distinct alleles, and they may be equally aggressive.

(1) MSI2-HOXA9 fusion is extremely rare as it has been only found in a handful of patients and it is not clear whether other MSI2 fusions function in a similar manner.

We were very surprised and excited to see the large number of translocations in solid cancers that involve MSI2.  Interestingly, MSI2 translocations occurred both at the N and the C terminus.  Distinct translocations are likely to have unique roles in each disease context. For example, if MSI2’s 5 prime end is part of a translocation, it may functionally contribute via its promoter to drive expression in immature cells and could thus activate oncogenic signals (e.g. controlled by the partner gene) in immature cells which are inherently more susceptible to transformation (Eµ-myc is an example of such a translocation). If Msi2’s RRM domains are part of the fusion, they could bind and target RNAs aberrantly (such as in the wrong cell and the wrong time) and lead to activation of downstream oncogenic mediators. To fully understand the role of each of these translocations in each specific cancer, we would need to experimentally test their impact by ectopic expression in the appropriate cell of origin and domain mapping the basis of any impact in the relevant cancer models as we have done for MSI2-HOXA9 in blast crisis CML in the work we report here.   While this is an intensive undertaking, it is nonetheless important future work as it will undoubtedly lead to new insight about MSI2 linked translocations in diverse solid cancers such as breast cancer and lung cancer.

(2) The mechanism needs to be strengthened since MSI2 alone or the HOXA9 mutant may not be linked to the mitochondrial mechanism. (3) It is not clear that the mitochondrial pathway is sufficient for the MSI2-HOXA9 oncogenic mechanism.

Our observation that MSI2-HOXA9 triggered changes in mitochondrial function was of particular interest as it was (to our knowledge) uncharted in context of Msi2 signaling in cancer, thus leading us to explore this further.  However, multiple other signals are likely downstream regulators and these may well act cooperatively with, or independently of, the heightened­­ mitochondrial function we report here. Among these pathways, the most likely mediators included oncogenic programs related to the Wnt pathway including Wnt, Fzd 3 and Frat1, and those related to the Notch pathway including-Tribbles and Hey1 as well as other stem cell genes such as Aldh1. These programs have been previously implicated in the regulation of myeloid leukemia3-11 and could well mediate the impact of the MSI2-HOXA9 translocation. The relative contribution of mitochondrial metabolism and that of developmental and stem cell signals to the onset of MSI2-HOXA9 driven blast crisis CML is an important avenue of future work.

References

(1) Corbin, A. S., Agarwal, A., Loriaux, M., Cortes, J., Deininger, M. W. & Druker, B. J. 2011. Human chronic myeloid leukemia stem cells are insensitive to imatinib despite inhibition of BCR-ABL activity. J Clin Invest 121: 396-409. PMC3007128.

(2) Graham, S. M., Jørgensen, H. G., Allan, E., Pearson, C., Alcorn, M. J., Richmond, L. & Holyoake, T. L. 2002. Primitive, quiescent, Philadelphia-positive stem cells from patients with chronic myeloid leukemia are insensitive to STI571 in vitro. Blood 99: 319-325.

(3) Gurska, L. M., Ames, K. & Gritsman, K. 2019. Signaling Pathways in Leukemic Stem Cells. Adv Exp Med Biol 1143: 1-39. PMC7249489.

(4) Narendra, G., Raju, B., Verma, H. & Silakari, O. 2021. Identification of potential genes associated with ALDH1A1 overexpression and cyclophosphamide resistance in chronic myelogenous leukemia using network analysis. Med Oncol 38: 123.

(5) Ran, D., Schubert, M., Pietsch, L., Taubert, I., Wuchter, P., Eckstein, V., Bruckner, T., Zoeller, M. & Ho, A. D. 2009. Aldehyde dehydrogenase activity among primary leukemia cells is associated with stem cell features and correlates with adverse clinical outcomes. Exp Hematol 37: 1423-1434.

(6) Reya, T., Duncan, A. W., Ailles, L., Domen, J., Scherer, D. C., Willert, K., Hintz, L., Nusse, R. & Weissman, I. L. 2003. A role for Wnt signalling in self-renewal of haematopoietic stem cells. Nature 423: 409-414.

(7) Riether, C., Schürch, C. M., Bührer, E. D., Hinterbrandner, M., Huguenin, A. L., Hoepner, S., Zlobec, I., Pabst, T., Radpour, R. & Ochsenbein, A. F. 2017. CD70/CD27 signaling promotes blast stemness and is a viable therapeutic target in acute myeloid leukemia. J Exp Med 214: 359-380. PMC5294846.

(8) Riether, C., Schürch, C. M., Flury, C., Hinterbrandner, M., Drück, L., Huguenin, A. L., Baerlocher, G. M., Radpour, R. & Ochsenbein, A. F. 2015. Tyrosine kinase inhibitor-induced CD70 expression mediates drug resistance in leukemia stem cells by activating Wnt signaling. Sci Transl Med 7: 298ra119.

(9) Venton, G., Pérez-Alea, M., Baier, C., Fournet, G., Quash, G., Labiad, Y., Martin, G., Sanderson, F., Poullin, P., Suchon, P., Farnault, L., Nguyen, C., Brunet, C., Ceylan, I. & Costello, R. T. 2016. Aldehyde dehydrogenases inhibition eradicates leukemia stem cells while sparing normal progenitors. Blood Cancer J 6: e469. PMC5056970.

(10) Yin, D. D., Fan, F. Y., Hu, X. B., Hou, L. H., Zhang, X. P., Liu, L., Liang, Y. M. & Han, H. 2009. Notch signaling inhibits the growth of the human chronic myeloid leukemia cell line K562. Leuk Res 33: 109-114.

(11) Kang, Y. A., Pietras, E. M. & Passegué, E. 2020. Deregulated Notch and Wnt signaling activates early-stage myeloid regeneration pathways in leukemia. J Exp Med 217. PMC7062512.

eLife assessment

This study provides useful data substantiating a role of long noncoding RNAs in liver metabolism and organismal physiology. With murine knockout and knockin models, the authors invoke a previously unidentified role for the lncRNA Snhg3 in fatty liver. While certain findings are backed by solid evidence, other conclusions require more support and should be consolidated with existing paradigms in the field.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors investigate the contributions of the long noncoding RNA snhg3 in liver metabolism and MAFLD. The authors conclude that liver-specific loss or overexpression of Snhg3 impacts hepatic lipid content and obesity through epigenetic mechanisms. More specifically, the authors invoke that the nuclear activity of Snhg3 aggravates hepatic steatosis by altering the balance of activating and repressive chromatin marks at the Pparg gene locus. This regulatory circuit is dependent on a transcriptional regulator SNG1.

Strengths:

The authors developed a tissue-specific lncRNA knockout and KI models. This effort is certainly appreciated as few lncRNA knockouts have been generated in the context of metabolism. Furthermore, lncRNA effects can be compensated in a whole organism or show subtle effects in acute versus chronic perturbation, rendering the focus on in vivo function important and highly relevant. In addition, Snhg3 was identified through a screening strategy and as a general rule the authors the authors attempt to follow unbiased approaches to decipher the mechanisms of Snhg3.

Weaknesses:

Despite efforts at generating a liver-specific knockout, the phenotypic characterization is not focused on the key readouts. Notably missing are rigorous lipid flux studies and targeted gene expression/protein measurement that would underpin why the loss of Snhg3 protects from lipid accumulation. Along those lines, claims linking the Snhg3 to MAFLD would be better supported with careful interrogation of markers of fibrosis and advanced liver disease. In other areas, significance is limited since the presented data is either not clear or rigorous enough. Finally, there is an important conceptual limitation to the work since PPARG is not established to play a major role in the liver.

Reviewer #2 (Public Review):

Through RNA analysis, Xie et al found LncRNA Snhg3 was one of the most down-regulated Snhgs by a high-fat diet (HFD) in mouse liver. Consequently, the authors sought to examine the mechanism through which Snhg3 is involved in the progression of metabolic dysfunction-associated fatty liver diseases (MASLD) in HFD-induced obese (DIO) mice. Interestingly, liver-specific Sngh3 knockout was reduced, while Sngh3 over-expression potentiated fatty liver in mice on an HFD. Using the RNA pull-down approach, the authors identified SND1 as a potential Sngh3 interacting protein. SND1 is a component of the RNA-induced silencing complex (RISC). The authors found that Sngh3 increased SND1 ubiquitination to enhance SND1 protein stability, which then reduced the level of repressive chromatin H3K27me3 on PPARg promoter. The upregulation of PPARg, a lipogenic transcription factor, thus contributed to hepatic fat accumulation.

The authors propose a signaling cascade that explains how LncRNA sngh3 may promote hepatic steatosis. Multiple molecular approaches have been employed to identify molecular targets of the proposed mechanism, which is a strength of the study. There are, however, several potential issues to consider before jumping to a conclusion.

(1) First of all, it's important to ensure the robustness and rigor of each study. The manuscript was not carefully put together. The image qualities for several figures were poor, making it difficult for the readers to evaluate the results with confidence. The biological replicates and numbers of experimental repeats for cell-based assays were not described. When possible, the entire immunoblot imaging used for quantification should be presented (rather than showing n=1 representative). There were multiple mislabels in figure panels or figure legends (e.g., Figure 2I, Figure 2K, and Figure 3K). The b-actin immunoblot image was reused in Figure 4J, Figure 5G, and Figure 7B with different exposure times. These might be from the same cohort of mice. If the immunoblots were run at different times, the loading control should be included on the same blot as well.

(2) The authors can do a better job in explaining the logic for how they came up with the potential function of each component of the signaling cascade. Sngh3 is down-regulated by HFD. However, the evidence presented indicates its involvement in promoting steatosis. In Figure 1C, one would expect PPARg expression to be up-regulated (when Sngh3 was down-regulated). If so, the physiological observation conflicts with the proposed mechanism. In addition, SND1 is known to regulate RNA/miRNA processing. How do the authors rule out this potential mechanism? How about the hosting snoRNA, Snord17? Does it involve the progression of NASLD?

(3) The role of PPARg in fatty liver diseases might be a rodent-specific phenomenon. PPARg agonist treatment in humans may actually reduce ectopic fat deposition by increasing fat storage in adipose tissues. The relevance of the findings to human diseases should be discussed.

the "marriage debt"

DiMe

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eLife assessment

This is a mechanistic study showing the effect of combining inhibition of autophagy (through ULK1/2) and KRAS (using sotorasib) on KRAS mutant NSCLC making the study valuable to cancer biologists and more broadly in a clinical setting. The evidence generated by GEM mouse models and cell lines is solid but could be further strengthened by increasing the mouse cohort size. This study holds translational relevance beyond NSCLC to other indications that carry KRAS mutations.

Reviewer #1 (Public Review):

Summary:

Given that KRAS inhibition approaches are a relatively new innovation and that resistance is now being observed to such therapies in patients with NSCLC, investigation of combination therapies is valuable. The manuscript furthers our understanding of combination therapy for KRAS mutant non-small cell lung cancer by providing evidence that combined inhibition of ULK1/2 (and therefore autophagy) and KRAS can inhibit KRAS-mutant lung cancer growth. The manuscript will be of interest to the lung cancer community but also to researchers in other cancer types where KRAS inhibition is relevant.

Strengths:

The manuscript combines cell line, cell line-derived xenograft, and genetically-engineered mouse model data to provide solid evidence for the proposed combination therapy.

The manuscript is well written, and experiments are broadly well performed and presented.

Weaknesses:

With 3-4 mice per group in many experiments, experimental power is a concern and some comparisons (e.g. mono vs combination therapy) seem to be underpowered to detect a difference. Both male and female mice are used in experiments which may increase variability.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Ghazi et reported that inhibition of KRASG12C signaling increases autophagy in KRASG12C-expressing lung cancer cells. Moreover, the combination of DCC 3116, a selective ULK1/2 inhibitor, plus sotorasib displays cooperative/synergistic suppression of human KRASG12C-driven lung cancer cell proliferation in vitro and tumor growth in vivo. Additionally, in genetically engineered mouse models of KRASG12C-driven NSCLC, inhibition of either KRASG12C or ULK1/2 decreases tumor burden and increases mouse survival. Additionally, this study found that LKB1 deficiency diminishes the sensitivity of KRASG12C/LKB1Null-driven lung cancer to the combination treatment, perhaps through the emergence of mixed adeno/squamous cell carcinomas and mucinous adenocarcinomas.

Strengths:

Both human cancer cells and mouse models were employed in this study to illustrate that inhibiting ULK1/2 could enhance the responsiveness of KRASG12C lung cancer to sotorasib. This research holds translational importance.

Weaknesses:

Additional validation of certain data is necessary.

(1) mCherry-EGFP-LC3 reporter was used to assess autophagy flux in Figure 1A. Please explain how autophagy status (high, medium, and low) was defined. It's also suggested to show WB of LC3 processing in different treatments as in Figure 1A at 48 hours.

(2) For Figures 1J, K, and L, please provide immunohistochemistry (IHC) images demonstrating RAS downstream signaling blockade by sotorasib and autophagy blockade by DCC 3116 in tumors.

(3) Given that both DCC 3116 and ULK1K46N exhibit the ability to inhibit autophagy and synergize with sotorasib in inhibiting cell proliferation, in addition to demonstrating decreased levels of pATG13 via ELISA assay, please include Western blot analyses of LC3 or p62 to confirm the blockade of autophagy by DCC 3116 and ULK1K46N in Figure 1 & Figure 2.

(4) Since adenocarcinomas, adenosquamous carcinomas (ASC), and mucinous adenocarcinomas were detected in KL lung tumors, please conduct immunohistochemistry (IHC) to detect these tumors, including markers such as p63, SOX2, Katrine 5.

(5) Please provide the sample size (n) for each treatment group in the survival study (Figure 4E). It appears that all mice were sacrificed for tumor burden analysis in Figure 4F. However, there doesn't seem to be a significant difference among the treatment groups in Figure 4F, which contrasts with the survival analysis in Figure 4E. It is suggested to increase the sample size in each treatment group to reduce variation.

(6) In KP mice (Figure 5), it seems that a single treatment alone is sufficient to inhibit established KP lung tumor growth. Combination treatment does not further enhance anti-tumor efficacy. Therefore, this result doesn't support the conclusion generated from human cancer cell lines. Please discuss.