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    BiP/GRP78 is a pro-viral factor for diverse dsDNA viruses that promotes the survival and proliferation of cells upon KSHV infection
    4
    1. EMBOpress 22 Jul 2024

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

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      Reply to the reviewers

      __Reviewer #1 (Evidence, reproducibility, and clarity (Required)):____ __ Summary: Viruses exploit host endoplasmic reticulum (ER)-resident chaperones to support new protein synthesis during viral replication. Here, Najarro et al. study the role of the ER-resident HSP70 family member Binding immunoglobulin protein (BiP) during lytic infection by the Kaposi's sarcoma-associated herpesvirus (KSHV). Using the established doxycycline-inducible lytic reactivation infection model cell line iSLK-BAC16, they showed that KSHV reactivation leads to an upregulation of total BiP protein but not RNA, and is independent of the unfolded protein response. siRNA knockdown or pharmacological inhibition by HA15 of BiP significantly reduced global viral gene expression and infectious virus production. The authors attribute this to at least the reduction of levels of the K1 gene which is required for efficient viral replication. Finally, they showed that HA15 has cytostatic activity in KSHV-transformed B cells and cytotoxic effects in KSHV-infected lymphatic endothelial cells arguing for BiP inhibition as a potential therapeutic strategy to treat KSHV-driven malignancies. The manuscript is well-written and the conclusions were generally supported by the data with a few exceptions below.

      Major comments:

      • They propose in lines 196-199 that the reduction of K1 from HA15 treatment partially explains the defect in virion production during lytic reactivation. I am not convinced that this statement is fully supported by their data. Reduction of K1 is likely a downstream consequence and not the cause of the inhibition of lytic replication.

      We thank the reviewer for this comment. We conducted a more detailed analysis of our RNAseq data in iSLK.219 cells and confirmed the downregulation of the K1 transcript in latently infected cells treated with HA15 (See Fig 3 and Sup Fig 5). It is likely that the drop in transcript levels results from IRE1-mediated degradation in a recently-described process known as RIDDLE (IRE1-mediated RNA decay lacking endomotif), in which IRE1 depletes mRNAs1*. We have included this hypothesis in the discussion. *

      Unfortunately, we cannot confirm the downregulation of K1 at the protein level in iSLK.219 cells since the antibodies are highly specific for K1 variants in PEL cells. To overcome this technical limitation, we conducted mass spectrometry analysis of the viral proteome from whole cell lysates of latent and lytic cells undergoing HA15 treatment. While we detect the expected global downregulation of viral proteins in lytic cells treated with HA15, we were not able to detect any viral proteins except for LANA in the latently infected cells, and our detection of several lytic proteins was limited. We speculate that the levels of latent viral proteins expressed in iSLK.219 cells are below the limits of detection of our assay, or that extensive modification of some of these viral proteins may hinder their detection. Due to these limitations, we decided not to include these data in the manuscript.

      • Additionally, we note that the lower levels of K1 detected in latent iSLK.219 and TREx-BCBL-1 cells treated with HA15 may affect viral reactivation, which is consistent with findings from the Damania lab showing K1's crucial role in viral replication2.*

      • *

      • The quantification of the K1 blots in Fig. 3C only has n=2. With subtle differences by eye, large error bars, and no statistical analysis, it is hard to conclude here with confidence. *

      We agree with the reviewer. We have moved the K1 blot to the Sup. Fig. 3E and adjusted the text accordingly.* *

      • Like K1, ORF45, and K8.1 proteins are similarly decreased at 24 h in Fig. 2E, suggesting that the defect is upstream of K1. Does HA15 affect the amount of endogenous and/or transgene copy of RTA being produced (hence the broader effect in early gene expression at 24h?)?

      • **To answer the Reviewer's query, we re-evaluated the impact of HA15 treatment on the activity of dox-inducible RTA. However, we think it is unlikely for HA15 to alter RTA activity since RTA does not enter the secretory pathway. *

      To evaluate the activity of RTA in HA15 treated cells, we measured the expression of the viral episome-encoded RFP reporter, driven by the viral PAN promoter4*, at 24h post-doxycycline treatment of iSLK.219 cells. We compared the response of the PAN promoter to RTA in cells treated with or without HA15 at this early timepoint, to avoid any potential confounding effects stemming from elevated endogenous RTA expression at later times post-reactivation. We demonstrate that the levels of RFP in iSLK.219 cells treated with Dox are identical in presence or absence of HA15. This result, included in Sup. Fig. 3, indicates that the activity of RTA, crucial for initiating the lytic cycle in this context, is unaffected by BiP inhibition at early times post reactivation. *

      • *

      • K1 levels appear to decrease even during latency. Are the other latent proteins also affected? What about latent genome copies?

      To address this query, we compared the Log2 fold change of latent transcripts (K1, K2, K12, ORF71, ORF72, ORF73) in the iSLK.219 RNAseq data set (Fig 3). Only the K1 transcript is reduced in HA15-treated cells. We include these data in Sup Fig 5A.

      Regarding differences in genome copies, the consistent levels of the viral genome-encoded GFP in HA15 -/+ iSLK-219 cells (Sup Fig 3) indicate no significant changes in the levels of viral genomes at 24h post-treatment (prior to DNA replication). Previous studies by our lab and others show that knockdown of the major latency protein LANA results in episomal loss and lower levels of GFP5*. These results validate the use of GFP fluorescence in iSLK.219 as a proxy for genome copies. *

      • *

      • Fig. 3C was performed in a PEL cell line which they showed to enter cytostasis upon HA15 treatment (Fig. 5). This cytostasis (rather than K1) may be the root cause of the defect in viral replication as cells could be arrested at a different stage compared to the G2 requirement for lytic replication in PEL cells (Balisteri et al., PLOS Pathogens 2016, PMID: 26891221).

      See point 2. below

      • The cytostatic effect in PEL cell lines (Fig. 5) should be demonstrated using more direct methods that measure cell cycle (e.g. PI-BrdU).

      We thank the reviewer for this comment. While more direct methods to measure the cell cycle stage affected by HA15 treatment will inform on its mechanism of action, these experiments lie outside of the scope of this manuscript and we consider are better suited for future studies on the anticancer properties of HA15. The data presented in Fig. 5 demonstrates that HA15 treatment of PEL cells causes a reduction in cell numbers without cytotoxicity, thus supporting our conclusion of a net negative effect on proliferation rather than cell death. The loss of our LN2 tank and PEL cell lines currently limits our ability to do these more detailed analyses. At the moment, we do not have an accurate estimate of how long it will take to replace these cell lines for our subsequent studies.

      • *

      • While having an uninfected B cell as a matched negative control for PEL is challenging, primary peripheral B cells (mostly of mature memory B cell stage) may not be the appropriate negative control. PEL cells are of plasma cell lineage which have unusually high protein translation and overloaded ER. The plasma cell lineage may explain the sensitivity of PEL cells to HA15. It is possible that HA15 may be toxic to plasma cells when used as a therapeutic agent.

      We agree with the reviewer on the potential impact of HA15 on plasma cell viability. Indeed, HA15 (>2uM) treatment reduces the viability of plasma cell myeloma lines (NCI-H929 and U266 cells), substantiating its use as a potential anti-cancer drug6. Although HA15 has not been tested as a therapeutic agent in humans, studies in mice have demonstrated tolerability without evident toxicity, measured as normal body weight7*. The potential therapeutic application of HA15 for cancer warrants further investigation and is beyond the scope of our manuscript. *

      • Does HA15 have cytostatic effects in uninfected or latently infected iSLK cells?

      • *

      We observed no cytostatic or cytotoxic effects in uninfected or latently infected iSLK cells exposed to up to 30uM of HA15. Although HA15 has been tested on various cancer types8*, it has not been evaluated in Renal Carcinoma Cells (RCC), the cellular background of iSLK.219 cells. The mechanism behind the resistance of these cells to HA15 eludes us, but its link to the cellular background of iSLK.219s merits exploration in future studies. *

      Minor comments: 1. Consider changing the title of line 98 to specify cell type since BiP levels do not increase in BCBL-1 (Supp. Fig. 3).

      • *

      Revised in the manuscript

      Fig. 3A may benefit from using z-scores instead of log2TPM so differences are more obvious per gene.

      Since the data have already been collected, can the authors include both latent and lytic cells with and without HA15 treatment in Fig. 3A? It may give more information for the reader. *

      *We have reanalyzed all the RNAseq data and included a z-score plot for all samples in Fig. 3. We also providing three new supplementary tables with the raw counts, the z-scores for viral genes, and the log2 of the normalized counts.

      *

      *Reviewer #1 (Significance (Required)):

      Significance: Here, the authors convincingly demonstrate the proviral role of the ER chaperone BiP during KSHV reactivation. This manuscript will be relevant to researchers in the gammaherpesvirus field. Although the authors did present some interesting data, the scope is narrow, and mechanistic studies were not pursued that would have added more insight in BiP and/or KSHV biology. For instance, how do BiP protein levels increase during reactivation (is this at the level of RNA sequestration/export, translation, or protein stability?)? How does BiP promote lytic replication?

      Field of expertise: KSHV, molecular and cell biology

      *

      * __Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ Many viruses have complex relationships with cellular ER proteostasis machinery that remain poorly understood. Here Najarro, et al. report on studies of the oncogenic gammaherpesvirus KSHV. They report that the ER chaperone BiP is upregulated in epithelial cells during KSHV lytic replication. Unexpectedly, BiP upregulation is independent of the unfolded protein response, which stimulates transcriptional activation of BiP to meet the protein folding demand in the ER. Using a combination of genetic and pharmacologic approaches (CRISPRi and selective chemical inhibitor) they demonstrate that BiP inhibition interferes with the replication of diverse enveloped viruses including poxviruses and several herpesviruses, and reduces proliferation of KSHV-infected cells.

      Figure-by-figure:

      Fig. 1: This figure convincingly demonstrates the selective upregulation of BiP at the protein level during the course of KSHV lytic replication, and that KSHV late genes are dispensable for this upregulation. It further demonstrates that BiP is not upregulated at the mRNA level at all during KSHV infection, despite the fact that the UPR-dependent BiP mRNA upregulation pathway (presumably via ATF6 and IRE1) remains functional.

      Fig. 2: This figure convincingly demonstrates that BiP ATPase activity is required to support KSHV lytic replication in both epithelial and B cell models on infection, even though it is also clear that BiP is not upregulated in the B cell model.

      Fig. 3: This data demonstrates that steady-state levels of KSHV lytic gene products are reduced following HA15-treatment, whereas later gene expression was unaffected. As an interesting side note, v-IL6 bucks the trend of HA15-mediated downregulation of viral mRNA levels, suggesting that it may be regulated in a different manner. One thing that the authors may consider is the report from Drs. Yuan Chang and Patrick Moore (PMID: 12434062) that demonstrated that the v-IL6 gene is transactivated by type I interferon. Considering the poor replication of this virus during HA15 treatment, it may be valuable to investigate IFN production by these cells, and the extent to which it is impacted by inhibition of BiP ATPase activity.*

      We thank the reviewer for bringing this report to our attention. We also found intriguing the specific transcriptional upregulation of IL6 in IFN-a treated BCP-1 cells. Although we see a dramatic upregulation of the vIL6 in HA15 treated cells, we still detect the expression of most viral genes, albeit at significantly lower levels than in untreated cells, which indicates that the viral transcriptional program in lytic+HA15 iSLK.219 cells is different from the one seen in IFN-treated BCP-1 cells. Preliminary analyses of the host transcriptome from our RNAseq results show the expression of several ISGs (OAS1, 2 and 3, IFI6, IFIT1, IFIT3, IFITM1) in lytic-untreated iSLK.219 cells, but not in those treated with HA15. Together, these observations substantiate the notion that there is no IFN-driven expression of vIL6 in HA15-treated iSLK.219 cells.

      Fig. 4: This figure demonstrates that HA15 has broad, non-cytotoxic, antiviral activity against diverse enveloped viruses.

      Figs. 5/6: These figure shows cytotoxic effects of HA15 on latently infected PEL cells, either solely infected with KSHV or co-infected with KSHV and EBV, whereas normal B cells were unaffected. HA15 was also cytotoxic to KSHV infected lymphatic endothelial cells.

      **Referees cross-commenting**

      I appreciate the insightful comments from Reviewer #1 and Reviewer #3. I think we are largely on the same page. The data is generally supportive of author's conclusions, with a few exceptions that are straightforward to address in revisions. The manuscript is limited in scope, which could also be addressed by additional experimentation if the authors are motivated to explore mechanism in greater depth. Of particular note is the lack of mechanistic insight into how BiP is upregulated at the protein level during lytic replication, if the mRNA is unchanged. The experimental approaches to this are straightforward.

      *

      *

      We appreciate the reviewers' comments on the scope of our study. The mechanism of BiP upregulation remains an outstanding question for the following technical reasons: We hypothesized that the upregulation of BiP may depend on the IRES element present in its 5' UTR9. We tested this hypothesis by transfecting iSLK.219 cells with a bicistronic Renilla-(BiP)IRES-Firefly luciferase reporter from Licursi et. al10*. Unfortunately, for reasons that still elude us, our reactivation rates in transfected cells were consistently low in all of our experiments and therefore, we were not able to measure luciferase changes consistently and reliably. A potential workaround this technical limitation is to use a lentivirus-encoded IRES reporter to a lentiviral vector, as transduction of iSLK.219 cells does not alter viral reactivation, in our experience. At the moment, we do not have access to these reporters due to our lab's move to a different institution, and the first author of our study has started the next stage of their career. Therefore, we will not be able to pursue these experiments in a timely manner. *

      • *

      *As for the scope of this manuscript, even when the mechanism of BiP upregulation in KSHV infected cells remains unsolved, we consider that the broad-spectrum antiviral effect of BiP inhibition is an exciting finding that advances the field and benefits the virology community-the proteostasis network has been seldomly explored as a potential node for broad-spectrum antiviral intervention. Our results provide important proof-of-concept to continue the investigation of factors involved in protein synthesis, folding and transport as potential targets for the development of versatile broad-spectrum antivirals. *

      Reviewer #2 (Significance (Required)):

      Strengths: This is a well-written manuscript. The text and figures are clear and accurate and the methods are sufficiently informative that the study can be reproduced. The data generally supports the authors' conclusions. BiP appears to be a druggable target with minimal off-target cytotoxicity in normal, uninfected cells, although this study does not go beyond cell culture studies to validate in vivo.

      Weaknesses: The study is somewhat limited in scope. The authors make the case for UPR transcription-independent upregulation of BiP during KSHV infection, and that late gene synthesis is dispensable, but the mechanism is not investigated further.

      Point by point discussion:

      Could an early KSHV gene product involved in this phenotype be identified by screening an ORF library or viral genome-wide CRISPRi screen?

      The question of the viral protein responsible for the upregulation of BiP during lytic infection is indeed a fascinating one. However, we suspect that the mechanism may be not specifically directed to BiP, but rather general modulation of IRES-related translation. Identifying the gene product(s) affected and corroborating IRES involvement is a major undertaking and a long-term goal requiring considerable effort. These analyses are outside the scope of this manuscript, but we will pursue them in the future.

      Or, beyond implicating viral factors in the mechanism of BiP upregulation, can some simple biochemical studies be performed to investigate BiP protein? Is the BiP mRNA more efficiently spliced and exported in KSHV infected cells?

      Do alternative translation initiation mechanisms like eIF2A play a role in boosting BiP levels during infection?

      What is the normal BiP protein turnover mechanism, and is this hindered during KSHV lytic replication? Is BiP AMPylation/de-AMPylation by FICD affected (PMID: 36041787)? These kinds of mechanistic studies are well within reach and would help extend the impact and interest to a broad audience.

      We agree on the putative involvement of translation initiation factors like eIF2A on promoting the translation of BiP (see discussion). We tested the effect of siRNA-mediated KD of eIF2A on BiP expression and found that, interestingly, the levels of BiP rose above those of controls in latent iSLK.219 cells (Data included in the manuscript and the discussion has been modified accordingly). This finding aligns with previous reports suggesting that eIF2A may suppress IRES-mediated translation in yeast cells and in mammalian in vitro translation assays. Moreover, Starck et. al11, observed a 50% increase of endogenous BiP levels in HeLa cells transfected with siRNAs against eIF2A, supporting the IRES-suppressor role for eIF2A in mammalian cells. Future work will be required to address the role of eIF2A on BiP translation. These analyses are beyond the scope our manuscript.

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

      The manuscript by Najarro et al. investigates the contribution of BiP/GRP78 to double-stranded DNA virus infection, primarily focusing on the oncogenic gammaherpesvirus Kaposi's sarcoma-associated herpesvirus (KSHV). The authors observe that BiP expression is increased in lytic iSLK.219 cells as well as in KSHV-infected LECs. Interestingly, the authors data suggest a post-translational regulation of BiP in the iSLK.219 cells. Using various knockdown approaches and chemical inhibitors the authors demonstrate that inhibition of BiP impacts KSHV reactivation in multiple cells lines. Importantly, the authors also find that BiP inhibition can selectively kill KSHV-infected cells, while sparing primary B cells. Overall, this is a very well controlled and presented manuscript. My comments for the manuscript are minor, and largely cosmetic to aid the presentation of the data.

      • Fig 1C, It would be ideal to show that PAA treatment did indeed prevent the virus from entering the late stage of gene expression.

      *We have included an immunoblot for K8.1 in Figure 1C to confirm the effect of PFA on arresting the KSHV lytic cycle. *

      Sup Fig2, should show KD efficiency of XBP1, same goes for ATF6.

      • *

      Sup. Fig. 2D shows the expression of XBP1s in NS vs. XBP1KD cells in the presence or absence of Tg. In Sup Fig. 2G we have also included a bar graph showing the efficiency of downregulation of ATF6 mRNA in the presence of the targeting sgRNA.

      Sup Fig 3. It is interesting that the authors do not see increased BiP in TREx-BCBL1-RTA cells. A potential caveat is that lytic reactivation in TREx-BCBL1-RTA cells is not as efficient as in iSLK.219 cells. Therefore, it may simply be a result of the reduced population entering the lytic cycle. It may be worth adding a comment regarding this.

      • Images of the microscopy for Figure 4 would be useful.

      Images have been included in Fig. 4

      • Add label of the cell types for Figure 5.

      DONE

      • Does HSV1, HCMV, or VacV increase BiP expression compared to mock-infected cells?

      Yes, we have included a comment on this in the discussion

      Reviewer #3 (Significance (Required)):

      Overall, this is a very well controlled and presented manuscript.

      • *

      • *

      PeerReviewed
    2. EMBOpress 22 Jul 2024

      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 #3

      Evidence, reproducibility and clarity

      The manuscript by Najarro et al. investigates the contribution of BiP/GRP78 to double-stranded DNA virus infection, primarily focusing on the oncogenic gammaherpesvirus Kaposi's sarcoma-associated herpesvirus (KSHV). The authors observe that BiP expression is increased in lytic iSLK.219 cells as well as in KSHV-infected LECs. Interestingly, the authors data suggest a post-translational regulation of BiP in the iSLK.219 cells. Using various knockdown approaches and chemical inhibitors the authors demonstrate that inhibition of BiP impacts KSHV reactivation in multiple cells lines. Importantly, the authors also find that BiP inhibition can selectively kill KSHV-infected cells, while sparing primary B cells. Overall, this is a very well controlled and presented manuscript. My comments for the manuscript are minor, and largely cosmetic to aid the presentation of the data.

      • Fig 1C, It would be ideal to show that PAA treatment did indeed prevent the virus from entering the late stage of gene expression.
      • Sup Fig2, should show KD efficiency of XBP1, same goes for ATF6.
      • Sup Fig 3. It is interesting that the authors do not see increased BiP in TREx-BCBL1-RTA cells. A potential caveat is that lytic reactivation in TREx-BCBL1-RTA cells is not as efficient as in iSLK.219 cells. Therefore, it may simply be a result of the reduced population entering the lytic cycle. It may be worth adding a comment regarding this.
      • Images of the microscopy for Figure 4 would be useful.
      • Add label of the cell types for Figure 5.
      • Does HSV1, HCMV, or VacV increase BiP expression compared to mock-infected cells?

      Significance

      Overall, this is a very well controlled and presented manuscript.

      PeerReviewed
    3. EMBOpress 22 Jul 2024

      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 #2

      Evidence, reproducibility and clarity

      Many viruses have complex relationships with cellular ER proteostasis machinery that remain poorly understood. Here Najarro, et al. report on studies of the oncogenic gammaherpesvirus KSHV. They report that the ER chaperone BiP is upregulated in epithelial cells during KSHV lytic replication. Unexpectedly, BiP upregulation is independent of the unfolded protein response, which stimulates transcriptional activation of BiP to meet the protein folding demand in the ER. Using a combination of genetic and pharmacologic approaches (CRISPRi and selective chemical inhibitor) they demonstrate that BiP inhibition interferes with the replication of diverse enveloped viruses including poxviruses and several herpesviruses, and reduces proliferation of KSHV-infected cells.

      Figure-by-figure:

      Fig. 1: This figure convincingly demonstrates the selective upregulation of BiP at the protein level during the course of KSHV lytic replication, and that KSHV late genes are dispensable for this upregulation. It further demonstrates that BiP is not upregulated at the mRNA level at all during KSHV infection, despite the fact that the UPR-dependent BiP mRNA upregulation pathway (presumably via ATF6 and IRE1) remains functional.

      Fig. 2: This figure convincingly demonstrates that BiP ATPase activity is required to support KSHV lytic replication in both epithelial and B cell models on infection, even though it is also clear that BiP is not upregulated in the B cell model.

      Fig. 3: This data demonstrates that steady-state levels of KSHV lytic gene products are reduced following HA15-treatment, whereas later gene expression was unaffected. As an interesting side note, v-IL6 bucks the trend of HA15-mediated downregulation of viral mRNA levels, suggesting that it may be regulated in a different manner. One thing that the authors may consider is the report from Drs. Yuan Chang and Patrick Moore (PMID: 12434062) that demonstrated that the v-IL6 gene is transactivated by type I interferon. Considering the poor replication of this virus during HA15 treatment, it may be valuable to investigate IFN production by these cells, and the extent to which it is impacted by inhibition of BiP ATPase activity.

      Fig. 4: This figure demonstrates that HA15 has broad, non-cytotoxic, antiviral activity against diverse enveloped viruses.

      Figs. 5/6: These figure shows cytotoxic effects of HA15 on latently infected PEL cells, either solely infected with KSHV or co-infected with KSHV and EBV, whereas normal B cells were unaffected. HA15 was also cytotoxic to KSHV infected lymphatic endothelial cells.

      Referees cross-commenting

      I appreciate the insightful comments from Reviewer #1 and Reviewer #3. I think we are largely on the same page. The data is generally supportive of author's conclusions, with a few exceptions that are straightforward to address in revisions. The manuscript is limited in scope, which could also be addressed by additional experimentation if the authors are motivated to explore mechanism in greater depth. Of particular note is the lack of mechanistic insight into how BiP is upregulated at the protein level during lytic replication, if the mRNA is unchanged. The experimental approaches to this are straightforward.

      Significance

      Strengths: This is a well-written manuscript. The text and figures are clear and accurate and the methods are sufficiently informative that the study can be reproduced. The data generally supports the authors' conclusions. BiP appears to be a druggable target with minimal off-target cytotoxicity in normal, uninfected cells, although this study does not go beyond cell culture studies to validate in vivo.

      Weaknesses: The study is somewhat limited in scope. The authors make the case for UPR transcription-independent upregulation of BiP during KSHV infection, and that late gene synthesis is dispensable, but the mechanism is not investigated further. Could an early KSHV gene product involved in this phenotype be identified by screening an ORF library or viral genome-wide CRISPRi screen? Or beyond implicating viral factors in the mechanism of BiP upregulation, can some simple biochemical studies be performed to investigate BiP protein? Is the BiP mRNA more efficiently spliced and exported in KSHV infected cells? Do alternative translation initiation mechanisms like eIF2A play a role in boosting BiP levels during infection? What is the normal BiP protein turnover mechanism, and is this hindered during KSHV lytic replication? Is BiP AMPylation/de-AMPylation by FICD affected (PMID: 36041787)? These kinds of mechanistic studies are well within reach and would help extend the impact and interest to a broad audience.

      PeerReviewed
    4. EMBOpress 22 Jul 2024

      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

      Summary:

      Viruses exploit host endoplasmic reticulum (ER)-resident chaperones to support new protein synthesis during viral replication. Here, Najarro et al. study the role of the ER-resident HSP70 family member Binding immunoglobulin protein (BiP) during lytic infection by the Kaposi's sarcoma-associated herpesvirus (KSHV). Using the established doxycycline-inducible lytic reactivation infection model cell line iSLK-BAC16, they showed that KSHV reactivation leads to an upregulation of total BiP protein but not RNA, and is independent of the unfolded protein response. siRNA knockdown or pharmacological inhibition by HA15 of BiP significantly reduced global viral gene expression and infectious virus production. The authors attribute this to at least the reduction of levels of the K1 gene which is required for efficient viral replication. Finally, they showed that HA15 has cytostatic activity in KSHV-transformed B cells and cytotoxic effects in KSHV-infected lymphatic endothelial cells arguing for BiP inhibition as a potential therapeutic strategy to treat KSHV-driven malignancies. The manuscript is well-written and the conclusions were generally supported by the data with a few exceptions below.

      Major comments:

      1. They propose in lines 196-199 that the reduction of K1 from HA15 treatment partially explains the defect in virion production during lytic reactivation. I am not convinced that this statement is fully supported by their data. Reduction of K1 is likely a downstream consequence and not the cause of the inhibition of lytic replication. Consider revising this statement in light of my comments below:
        • a. The quantification of the K1 blots in Fig. 3C only has n=2. With subtle differences by eye, large error bars, and no statistical analysis, it is hard to draw conclusions from here with confidence.
        • b. Like K1, ORF45 and K8.1 proteins are similarly decreased at 24 h in Fig. 2E suggesting that the defect is upstream of K1. Does HA15 affect the amount of endogenous and/or transgene copy of RTA being produced (hence the broader effect in early gene expression at 24h?)?
        • c. K1 levels appear to decrease even during latency. Are the other latent proteins also affected? What about latent genome copies?
        • d. Fig. 3C was performed in a PEL cell line which they showed to enter cytostasis upon HA15 treatment (Fig. 5). This cytostasis (rather than K1) may be the root cause of the defect in viral replication as cells could be arrested at a different stage compared to the G2 requirement for lytic replication in PEL cells (Balisteri et al., PLOS Pathogens 2016, PMID: 26891221).
      2. The cytostatic effect in PEL cell lines (Fig. 5) should be demonstrated using more direct methods that measure cell cycle (e.g. PI-BrdU).
      3. While having an uninfected B cell as a matched negative control for PEL is challenging, primary peripheral B cells (mostly of mature memory B cell stage) may not be the appropriate negative control. PEL cells are of plasma cell lineage which have unusually high protein translation and overloaded ER. The plasma cell lineage may explain the sensitivity of PEL cells to HA15. It is possible that HA15 may be toxic to plasma cells when used as a therapeutic agent.
      4. Does HA15 have cytostatic effects in uninfected or latently infected iSLK cells?

      Minor comments:

      1. Consider changing the title of line 98 to specify cell type since BiP levels do not increase in BCBL-1 (Supp. Fig. 3).
      2. Fig. 3A may benefit from using z-scores instead of log2TPM so differences are more obvious per gene.
      3. Since the data have already been collected, can the authors include both latent and lytic cells with and without HA15 treatment in Fig. 3A? It may give more information for the reader.

      Significance

      Here, the authors convincingly demonstrate the proviral role of the ER chaperone BiP during KSHV reactivation. This manuscript will be relevant to researchers in the gammaherpesvirus field. Although the authors did present some interesting data, the scope is narrow, and mechanistic studies were not pursued that would have added more insight in BiP and/or KSHV biology. For instance, how do BiP protein levels increase during reactivation (is this at the level of RNA sequestration/export, translation, or protein stability?)? How does BiP promote lytic replication?

      Field of expertise: KSHV, molecular and cell biology

      PeerReviewed
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    biorxiv.org/content/10.1101/2023.09.29.560238v1
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    ACE2-independent sarbecovirus cell entry is supported by TMPRSS2-related enzymes and reduces sensitivity to antibody-mediated neutralization
    4
    1. EMBOpress 21 Jul 2024

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

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      Reply to the reviewers

      Response to the reviewer's questions

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

      Using the S protein from 14 different sarbecoviruses isolated from bats or pangolin, Zhang et al. makes in this manuscript several points on sabecovirus entry. These points include ACE2 independent entry, trypsin-driven entry, RBD-dependence of trypsin-mediated entry, use of soluble proteases and TRMPRSS-family transmembrane proteases in trypsin-mediated and trypsin-independent entry, and neutralizing antibody evasion in trypsin-mediated entry. Some of these points are supported by the data presented; although there are some discrepancies, they are largely within the range of experimental error. However, some of the statements in the Title, Abstract, and main text, appear to be more than what the data support. Nonetheless, the data authors presented are informative and will help understanding sarbecovirus entry processes. __

      Thank you very much for the positive assessment of our study and for the suggestions for improvement.__

      Major points:

      Below are only a few examples of inaccurate sentences. The authors should rewrite similar statements throughout the manuscript.

      Q1: The title: "ACE2-independent sarbecovirus cell entry is supported by TMPRSS2-related enzymes and reduces sensitivity to antibody-mediated neutralization" does not correctly reflect the presented data (1) because the contribution by TMPRSS2-like enzymes was shown only when they were co-transfected during PV production, but not when they are expressed on the target cell surface, and (2) because "reduces sensitivity to antibody-mediated neutralization" was observed only for one S protein but was not observed for the other two trypsin-dependent S proteins. In addition, this point was made using one monoclonal Ab for trypsin-dependent entry, but not for the entry mediated by TMPRSS2-related enzymes as the title implies. The title sounds like the three points are interconnected and represent general phenomena. Perhaps a more accurate title could be "ACE2-independent sarbecovirus cell entry is supported by trypsin and may reduce sensitivity to a neutralizing antibody". __

      A1: __We appreciate the critique. From our perspective, the statement that ACE2-independent entry is supported by TMPRSS2-related enzymes is correct irrespective of whether these enzymes cleave the viral S protein during entry into uninfected cells or during S protein biogenesis in infected cells (in order to allow for subsequent ACE2-independent entry into uninfected cells). The reviewer is correct that rescue from antibody-mediated neutralization was only observed for one monoclonal antibody. However, we also obtained evidence that ACE2-independent entry allowed for evasion of neutralizing antibodies induced upon infection or vaccination. In order to avoid generalization, we phrased the title in a more careful fashion: "ACE2-independent sarbecovirus cell entry can be supported by TMPRSS2-related enzymes and can reduce sensitivity to antibody-mediated neutralization".

      __

      __Q2: In the Abstract, the authors state "Several TMPRSS2-related cellular proteases but not the insertion of a multibasic cleavage site into the S protein allowed for ACE2-independent entry in the absence of trypsin and may support viral spread in the respiratory tract" (lines 38-41) and "In sum, our study reports a pathway for entry into human cells that is ACE2-independent, supported by TMPRSS2-related proteases...." (lines 44-46). These sentences should be rewritten for the same reason described above for the Title. __

      __A2: __We feel that the statement that TMPRSS2-related enzymes can support ACE2-independent entry is correct. Thus, either trypsin pretreatment of particles or expression of TMPRSS2-related enzymes in particle producing cells allows for ACE2-independent entry. We rephrased our concluding sentence in a more careful fashion and now state: "In sum, our study reports a pathway for entry into human cells that is ACE2-independent, can be supported by TMPRSS2-related proteases and may be associated with antibody evasion."

      __Q3: The lines 102-105 say "...ACE2-independent, trypsin-dependent entry can modulate neutralization by the pan sarbecovirus antibody S2H97..." and the lines 427-9 say "...trypsin-dependent usage of an ACE2-independent entry pathway may result in slightly reduced susceptibility to neutralization by antibodies induced upon infection or vaccination." Because Fig 8 (S2H97 Ab) and Fig 9 (immune plasma) use Vero-ACE2-TMPRSS2 and A549-ACE2-TMPRSS2, respectively, "ACE2-independent," is incorrect here. __

      __A3: __We respectfully disagree. We have shown that certain spikes can facilitate entry into ACE2-expressing cell lines in an ACE2-dependent manner but switch to an ACE2-independent entry route upon pre-treatment of particles with trypsin and blockade of ACE2 by an antibody (Supplementary Figure 4C). In figure 8 and 9, we show that when the ACE2-dependent entry route is blocked by neutralizing antibodies, opening the ACE2-independent route reduces antibody-mediated neutralization. As a consequence, it is fair to conclude that our data indicate that usage of the ACE2-independent entry route may reduce neutralization sensitivity. We feel that this argument is further supported by our most recent data, shown as new figure 3C, which demonstrate that trypsin treatment not only allows for entry into ACE2+ cells pretreated with anti-ACE2 antibody but, more importantly, also permits entry into ACE2 KO cells.

      __

      Q4: The line 46 says "...and associated with antibody evasion", the lines 104-5 says "...and allows for partial antibody evasion in the context of plasma from COVID-19 vaccinees." and the lines 427-9 say "...may result in slightly reduced susceptibility to neutralization by antibodies..." The authors should rewrite them because the resistance to S2H97 Ab was observed with one S protein but all other trypsin-mediated entry was sensitive to S2H97 or immune plasma. __

      __A4: __We have phrased the sentences in question in a more careful fashion and now state:

      "Finally, the pan-sarbecovirus antibody S2H97 enhanced cell entry driven by two S proteins and this effect was reversed by trypsin while trypsin protected entry driven by a third S protein from neutralization by S2H97. Similarly, plasma from quadruple vaccinated individuals neutralized entry driven by all S proteins studied, and availability of the ACE2-independent, trypsin-dependent pathway reduced neutralization sensitivity. In sum, our study reports a pathway for entry into human cells that is ACE2-independent, can be supported by TMPRSS2-related proteases and may be associated with antibody evasion." (Abstract)

      "Finally, we obtained evidence that ACE2-independent, trypsin-dependent entry can modulate neutralization by the pan sarbecovirus antibody S2H97 in a spike-dependent fashion and allows for partial antibody evasion in the context of plasma from COVID-19 vaccinees." (end of introduction).

      "In sum, these results suggest that availability of the trypsin-dependent, ACE2-independent entry pathway may result in slightly reduced susceptibility to neutralization by antibodies induced upon infection or vaccination." (end of results section).

      __

      Q5: If trypsin- independent entry is still controlled by RBD, why LYRa11 and Rs7327 entry is enhanced by and RsSHC014 entry is resistant to S2H97 Ab? The authors may want to discuss possible explanations. __

      __A5: __It is at present unclear why trypsin-treatment increased S2H97-mediated inhibition of LYRa11- and Rs7327-S protein driven entry while it conferred S2H97-resistance to RsSHC014-S. One could speculate that slight differences in the S2H97 epitope of the three spike proteins alter antibody affinity and thus determine whether the antibody enhances or blocks entry.

      __

      Q6: Fig. 2B. The entry supported by ACE2 orthologs was normalized to that utilizing hACE2 after hACE2-supported entry was normalized to background entry (no-S PV). First, it is unclear why background entry is used for normalization instead of being subtracted. Second, two times of such normalization likely created huge experimental errors and might have skewed the outcomes. Thus, 14 PVs should be quantified by RT-qPCR and same genome copy number should be used to directly assess their usage of ACE2 orthologs. This way, normalization by hACE2 entry is not necessary. Background entry should be subtracted, not used for normalization. __

      __A6: __We respectfully disagree. It is fair to ask how much more efficient single cycle particles bearing a viral envelope protein enter target cells as compared to identical particles bearing no viral glycoprotein. Normalization of the data presented as a heat map (Figure 2C) was performed based on the raw data (not the "Fold over Background"-normalized data). Thus, data were only normalized once. Regarding the possibility that different particle numbers were used for the respective pseudoviruses, we would like to state that particle production efficiency was analyzed by immunoblot (based on VSV matrix protein levels) and no major differences for the different pseudoviruses were observed (please see new Supplementary figure 4A). Thus, we are confident that our results are not skewed by gross differences in pseudovirus particle numbers.

      __

      Q7: Because VSV PVs were harvested in culture media, there were serum and divalent cations. Were PVs purified before trypsin digestion? Digestion by trypsin or other proteases should be described in detail. __

      __A7: __Medium without serum was used for PV production to avoid inhibition of trypsin activity by serum components. For immunoblot samples, VSV PVs were further harvested from the culture medium and concentrated using 20% sucrose. The concentrated VSV PVs were aliquoted into separate tubes, each containing an equal volume, and treated with the specified concentrations of proteases at 37{degree sign}C, as detailed in the Materials and Methods section. Subsequently, the treated VSV PVs were mixed with an equal volume of 2x SDS loading buffer and heated at 96{degree sign}C for 10 minutes.

      __

      Q8: How was S2' fragment on the blot determined? Should be described. __

      A8: __The S2' fragment was determined based on the molecular size of the corresponding bands. This information has been added to the respective figure legends.

      Minor points.

      Q9: The line 129 says "...14 S proteins, representing all clades, were selected for detailed analyses". Correct the sentence because the S protein representing clade 5 is not included in the study. __

      A9: __We now state ""...14 S proteins, representing all clades except clade 5, were selected for detailed analyses"

      __

      __Q10: Fig 2. Because 14 S proteins and several TFR1 orthologs were used, a table describing which S isolate is derived from which animal species will help. Organizing Fig 2A and B in the same order will help reading the result. Also, indicate which clades those S proteins belong to. __

      __A10: __We have added a table providing detailed information on the spike proteins under study.

      Supplemental table 1: Information on the spike proteins under study.

      Spike

      Virus

      Identifier

      RBD clade

      Host

      Region

      SARS-2-S

      Human SARS-CoV-2 hCoV-19/Wuhan/Hu-1/2019

      GISAID: EPI_ISL_402125

      1b

      Human (Homo sapiens)

      Asia (China)

      RaTG13-S

      Bat SARSr-CoV hCoV-19/bat/Yunnan/RaTG13/2013

      GISAID: EPI_ISL_402131

      1b

      Bat (Rhinolophus affinis)

      Asia (China)

      P5L-S

      Pangolin SARSr-CoV hCoV-19/pangolin/Guangxi/P5L/2017

      GISAID: EPI_ISL_410540

      1b

      Malayan pangolin (Manis javanica)

      Asia (China)

      cDNA8-S

      Pangolin SARSr-CoV hCoV-19/pangolin/Guangdong/cDNA8-S/2019

      GISAID: EPI_ISL_471461

      1b

      Malayan pangolin (Manis javanica)

      Asia (China)

      Rs4081-S

      Bat SARSr-CoV Rs4081

      GenBank: KY417143.1

      2

      Bat (Rhinolophus sinicus)

      Asia (China)

      Rs4237-S

      Bat SARSr-CoV RS4237

      GenBank: KY417147.1

      2

      Bat (Rhinolophus sinicus)

      Asia (China)

      SARS-1-S

      Human SARS-CoV-1/Frankfurt-1

      GenBank: AY291315.1

      1a

      Human (Homo sapiens)

      Europe (Germany)

      WIV1-S

      Bat SARSr-CoV WIV1

      GenBank: KF367457.1

      1a

      Bat (Rhinolophus sinicus)

      Asia (China)

      LYRa11-S

      Bat SARSr-CoV LYRa11

      GenBank: KF569996.1

      1a

      Bat (Rhinolophus affinis)

      Asia (China)

      RsSHC014-S

      Bat SARSr-CoV RsSHC014

      GenBank: KC881005.1

      1a

      Bat (Rhinolophus sinicus)

      Asia (China)

      Rs4231-S

      Bat SARSr-CoV Rs4231

      GenBank: KY417146.1

      1a

      Bat (Rhinolophus sinicus)

      Asia (China)

      Rs4874-S

      Bat SARSr-CoV Rs4874

      GenBank: KY417150.1

      1a

      Bat (Rhinolophus sinicus)

      Asia (China)

      Rs7327-S

      Bat SARSr-CoV Rs7327

      GenBank: KY417151.1

      1a

      Bat (Rhinolophus sinicus)

      Asia (China)

      BM48-31-S

      Bat SARSr-CoV BM48-31/BGR/2008

      GenBank: GU190215.1

      3

      Rhinolophus blasii

      Europe (Bulgaria)

      __

      Q11: Fig S5. Describe cell lines used. __

      __A11: __We have added a table providing information on the cell lines used.

      Supplemental table 2: Information on the cell lines used.

      Cell line

      Species

      Organ

      Modification

      Culture medium

      Vero

      African green monkey (Cercopithecus aethiops)

      Kidney

      n.a.

      DMEM + 10% FCS + Pen/Strep

      Vero-ACE2+TMPRSS2

      African green monkey (Cercopithecus aethiops)

      Kidney

      Stable expression of human ACE2 and human TMPRSS2

      DMEM + 10% FCS + Pen/Strep + Blasticidin (2 µg/ml) + Puromycin (1 µg/ml)

      Vero-TMPRSS2

      African green monkey (Cercopithecus aethiops)

      Kidney

      Stable expression of human TMPRSS2

      DMEM + 10% FCS + Pen/Strep + Blasticidin (2 µg/ml)

      MyDauLu/47

      Bat (Myotis daubentonii)

      Lung

      n.a.

      DMEM + 10% FCS + Pen/Strep

      PipNi/3

      Bat (Pipistrellus pipistrellus)

      Kidney

      n.a.

      DMEM + 10% FCS + Pen/Strep

      Caco-2

      Human (Homo sapiens)

      Intestine

      n.a.

      MEM + 10% FCS 1% NEA + 10 mM sodium pyruvate + Pen/Strep + Puromycin (1 µg/ml)

      293T

      Human (Homo sapiens)

      Kidney

      n.a.

      DMEM + 10% FCS + Pen/Strep

      293T-ACE2

      Human (Homo sapiens)

      Kidney

      Stable expression of human ACE2

      DMEM + 10% FCS + Pen/Strep + Puromycin (1 µg/ml)

      Huh-7

      Human (Homo sapiens)

      Liver

      n.a.

      DMEM + 10% FCS + Pen/Strep

      Li7

      Human (Homo sapiens)

      Liver

      n.a.

      DMEM + 10% FCS + Pen/Strep

      A549-ACE2

      Human (Homo sapiens)

      Lung

      Stable expression of human ACE2

      DMEM/F-12 + 10% FCS + Pen/Strep + Puromycin (1 µg/ml)

      A549-ACE2+TMPRSS2

      Human (Homo sapiens)

      Lung

      Stable expression of human ACE2 and human TMPRSS2

      DMEM/F-12 + 10% FCS + Pen/Strep + Blasticidin (2 µg/ml) + Puromycin (1 µg/ml)

      Calu-3

      Human (Homo sapiens)

      Lung

      n.a.

      DMEM/F-12 + 10% FCS 1% NEA + 10 mM sodium pyruvate + Pen/Strep

      Calu-3-ACE2

      Human (Homo sapiens)

      Lung

      Stable expression of human ACE2

      DMEM/F-12 + 10% FCS 1% NEA + 10 mM sodium pyruvate + Pen/Strep + Puromycin (1 µg/ml)

      NCI-H522

      Human (Homo sapiens)

      Lung

      n.a.

      RPMI + 10% FCS 1% NEA + 10 mM sodium pyruvate + Pen/Strep

      BHK-21

      Syrian golden hamster (Mesocricetus auratus)

      Kidney

      n.a.

      DMEM + 10% FCS + Pen/Strep

      __ Q12: Fig 3 legend should indicate trypsin digestion condition (concentration and length). __

      __A12: __We have added the requested information to the respective figure legends.

      __

      Reviewer #1 (Significance (Required)):

      Because overwhelming amount of data bear large experimental errors, there are some discrepancies among the data presented. Nonetheless, most of each point the authors claim is largely supported by the data. The problem happened when the authors tried to connect the dots too much and thus overstated some conclusions. If the overstated conclusions are amended throughout the manuscript, presented data provide sufficiently useful information on sarbecovirus entry.

      __

      Thank you. We have rephrased our conclusions in a more careful fashion.

      __Reviewer #2 (Evidence, reproducibility and clarity (Required)):____

      SUMMARY: Recent work from several groups has shown that the majority of bat sarbecoviruses infect cells independent of ACE2, the receptor primarily used by sarbecoviruses that infect humans, and instead infect cells in the presence of exogenous protease including trypsin. In this study, Zhang and colleagues build on these earlier findings by demonstrating that ACE2-independent sarbecovirus entry can be mediated by other exogenous proteases and several different TMPRSS11 enzymes. Using in vitro based methods and viral pseudotypes, the authors reproduce previous findings with trypsin, demonstrate similar effects with alternative proteases and provide lines of evidence suggesting (1) trypsin treatment can impart ACE2-independence and that (2) ACE2-independence provides resistance to neutralizing antibodies. __

      Many thanks for evaluation our manuscript and for the constructive critique.__

      MAJOR COMMENTS:

      Q1: Defining sarbecovirus RBDs into clades by in del features has already been established by other groups and many studies across different disciplines now use these previously-established clades. The authors use slightly different nomenclature without any acknowledgment of the previously defined sarbecovirus RBD clades, which will lead to confusion between studies. For example, SARS-CoV-2 is generally regarded as a clade 1 RBD (with ACE2 use and both loops in tact), clade 3 includes BM48-31 and Khosta-2, clade 4 includes RatG15. __

      __A1: __We have changed the nomenclature of the different groups to "clusters" to avoid confusion. Further, we added for each cluster information on the RBD clade. Please see revised Figure 1.

      __

      Q2: Why did the authors select BM48-31 as the representative of its clade when other members of the clade have known receptors and clear phenotypes in lab assays? BM48-31 has largely failed in every lab assay by every group that has studied it. On the other hand, Khosta2 uses human ACE2, BtKY72 and other African sarbecoviruses can also use ACE2 from their host species and have low but detectable human ACE2 compatibility. It would be interesting to see how the antibody-resistance results compare with other ACE2-dependent sarbecoviruses. __

      __A2: __We have selected BM48-31 at a time when the information stated above was not available. We agree that testing additional spikes for neutralization sensitivity should be considered within future studies but also feel that solid conclusions can be drawn from the 13 spikes tested within this study.

      __

      Q3: What is the aurthors' proposed mechanism for how protease is functioning for ACE2-independent entry? For ACE2-dependent entry, TMPRSS2 cleaves spike after RBD engagement. However, in this study, TMPRSS11 enzymes only function when included in producer cells- prior to RBD engagement. Is TMPRSS11 cleaving spike during spike biogenesis (similar to furin for SARS-CoV-2) or is an alternative mechanism at play? Is TMPRSS11 secreted? If this is the case, then the enzyme may be functioning similar to the other exogenous proteases in this study. __

      __A3: __It is possible that pre-cleavage by a TMPRSS2-like enzymes (or trypsin) is needed for subsequent S protein activation by another protease, likely cathepsin B/L, for ACE2-independent entry. This would be similar to SARS-CoV-2 entry into lung cells, which depends on spike pre-cleavage by furin and spike cleavage-activation by TMPRSS2. Alternatively, the TMPRSS2-like enzymes may cleave spike at the RBD, with the cleavage eluding detection by the methods applied here, and this cleavage might be needed for engagement of the so far unknown receptor responsible for ACE2-independent entry. TMPRSS2-like enzymes can be shed into the extracellular space. However, we feel that extracellular TMPRSS-activity was not responsible for ACE2-independent entry since expression of TMPRSS2-like enzymes in target cells should have also resulted in protease shedding but failed to allow for ACE2-independent entry.

      __

      Q4: Related to comment 3: the authors study trypsin as a pre-treatment, but other studies have shown trypsin exerts activity during entry. How do the authors propose trypsin is functioning prior to RBD engagement? Is it possible that trypsin is not fully inactivated and remains partially active during entry? __

      A4: __For most experiments, trypsin was present/active during the whole entry process. Only for Figures 3B, 8 and 9 trypsin inhibitor was added prior to inoculation of target cells in order to discriminate effects of trypsin on virus particles and cells and to exclude that trypsin compromised the integrity of the antibodies under study. We speculate that trypsin cleavage even before receptor engagement can allow for ACE2-independent entry.

      __

      __Q5: I am not convinced that trypsin is driving ACE2-independent entry for ACE2-dependent viruses. The experiment performed in figure 3C is performed in African green monkey cells using an antibody directed toward human ACE2. The difference in species between antibody and antigen may influence how well the antibody binds ACE2 on the Vero cells, which may only block some ACE2-dependent viruses but not all. Curiously, the only ACE2-dependent spikes that gain "ACE2-independence" are also activated by trypsin. These blocking assay results would be more convincing in a human cell line, or a non-permissive cell line like BHKs that express the human receptor. Alternatively, knocking out ACE2 in the Vero cells may be another way to assess ACE2-independent entry. __

      __A5: __We have now examined entry into 293T WT and 293T ACE2 KO cells. Importantly, the same spikes that allow for trypsin-dependent entry into Vero-TMPRSS2 cells treated with anti-ACE2 antibody also allow for robust entry into 293T ACE2 KO cells when pretreated with trypsin, please see new figure 3C. These results confirm our previous data and validate our conclusion that some spikes facilitate ACE2-dependent entry but can switch to the ACE2-independent entry route upon pre-treatment with trypsin.

      __

      MINOR COMMENTS:

      Q6: line 148: Rs4237 is missing a clade designation __

      __A6: __Rs4237 belongs to the Asian bat cluster (RBD clade 2). This information has been added to the revised figure 1 and is further provided in the new supplemental table 1.

      __ Q7: Figure 3. The figure's main message could be improved by visually grouping the viruses according to clade. __

      __A7: __We modified all figures and now indicate for each spike to which RBD clade they belong.

      __

      Q8: Some details are missing for reproducibility, including the accession numbers of the TMPRSS enzymes used in this study __

      __A8: __We added the requested information to the Materials and methods section.

      __

      Q9: Contrary to claims in the text, this study includes a fairly small panel of spike proteins. Prior studies by Letko 2020, Starr 2022 and Roelle 2022 (cited by the authors) all measured entry for between 20-40 spikes - more twice the number in this study. __

      A9: __We apologize for the mistake and removed the statement that "...these analyses were confined to small numbers of S proteins and.."

      __

      __Q10: Line 472-473: the data presented in figure 2B shows SARS-CoV-2 has slightly better entry with pangolin ACE2 than raccoon dog. I am not sure the authors should cite this data in support of raccoon dogs as an intermediate for SARS-CoV-2. __

      A10: We feel that our statement that - based on ACE2 usage - raccoon dogs should be considered as intermediate hosts is valid since it refers to the finding that diverse sarbecoviruses used this ACE2 orthologue with highest efficiency.

      __

      Reviewer #2 (Significance (Required)):

      SIGNIFICANCE: This study provides some novel insights into proteases and sarbecovirus cell entry and highlights previously unappreciated entry factors that are key for some viruses. A major limitation of this study is its lack of mechanistic exploration. The authors data do not really elucidate how TMPRSS11 proteins mediate ACE2-independent entry, nor do the results explain how ACE2-independence is shielding viruses from neutralizing antibodies. Another limitation is in the choice of using a non-human cell line to study the blocking effect of an antibody directed toward a human protein. __

      We feel that our findings that TMPRSS2-related enzymes can support ACE2-independent entry and that ACE2-independnet entry might allow for some level of antibody evasion are novel and important. We would also like to point out that we employed a human ACE2 KO cell line to address the reviewer's reservations regarding use of a non-human primate cell line. The data obtained with the human KO cell line confirmed those obtained with anti-ACE2 antibody treated non-human primate cell line, validating our conclusions.

      __

      ADVANCE: This study nicely reproduces a number of previous findings, including: 1. sarbecovirus RBDs can be categorized into clades based on deletions in surface exposed loops 2. ACE2-independent, trypsin-dependent sarbecovirus entry - notably for Rs4081 3. the RBD in ACE2-independent sarbecoviruses controls entry 4. anti-ACE2 antibodies do not block entry for ACE2-independent sarbecoviruses as well as some ACE2-dependent sarbecoviruses 5. trypsin does not increase S proteins binding to cells 6. protease expression in target cells does not increase S-driven entry 7. a multi-basic cleavage site in spike does not compensate for exogenous protease in ACE2-independent entry

      This study has many novel advancements as well: 1. identification of other exogenous proteases that mediate ACE2-independent entry (elastase, thermolysin) 2. identification of TMPRSS11 family members that mediate trypsin-free entry for ACE2-independent viruses when produced in cells producing spike proteins but not target cells 3. ACE2-independent entry may reduce spike susceptibility to antibody neutralization __

      Thank you.__

      AUDIENCE: This study will appeal to the coronavirus research community.

      __

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)):____

      Zhang et al. analyzed the infection mechanisms of various Sarbecovirus primarily using VSV pseudoviruses with individual Sarbecovirus S proteins. The study demonstrated that many Sarbecoviruses, similar to two Sarbecoviruses that do not exhibit infectivity without trypsin, gain infectivity in human cells after processing virus particles with trypsin. This trypsin treatment is closely associated with the cleavage of the S1/S2 site of the S protein. This study demonstrated that the infection of the two viruses is not dependent on ACE2 expression, suggesting infection through receptors other than ACE2. Indeed, this study indicates that the receptor-binding domain of the S protein determines these properties. Furthermore, this study shows that some ACE2-using Sarbecoviruses also acquire ACE2-independent infectivity after trypsin treatment of virus particles. Although similar phenomena have already been reported in some Sarbecoviruses, the data in this study are more extensive, systematically conducted, and thoroughly analyzed, providing sufficient and additional evidence for the points mentioned above. The weaknesses, if pointed out, are that little progress has been made in elucidating the detailed molecular mechanism of this ACE2-independent and trypsin-dependent infection. __

      Thank you very much for reviewing our manuscript and for the positive comments.__

      Q1: To improve the study, the authors may consider the following points: • The Immunoblot data showing the expression level of ACE2-expressing cells used in the analysis of Figure 2 should be presented rather than indicated as "data not shown." __

      __A1: __The immunoblot data are now shown as new supplemental figure 3, panel B, and reveal robust expression of all ACE2 orthologues analyzed.

      __ Q2: In the explanation of Figure 2, it is stated, "all S proteins studied efficiently employed human ACE2 (lines 165-166)," but since there are significant differences in utilization levels, this description needs modification. Is it appropriate to normalize the utilization ability of human ACE2 as "1" in Figure 2B? Supplementary Figure 4 may be more relevant, and it should be considered to use it as a regular figure. __

      __A2: __We modified the text to indicate that although most spike proteins readily interacted with human ACE2, interaction efficacies greatly varied among the spike proteins ("*Thus, all S proteins studied employed human ACE2 for entry with the exception of the aforementioned S proteins of BM48-31, Rs4081 and Rs4237, which had also failed to bind to ACE2 (Figure 2B). However, although most sarbecovirus S proteins were able to readily utilize human ACE2 as an entry receptor, notable differences were observed. For instance, while *

      Particles bearing SARS-2-S, P5L-S, SARS-1-S, WIV-1-S, or Rs4874-S robustly entered BHK-21 cells expressing human ACE2, entry of particles carrying RaTG13-S, cDNA8-S, LYRa11-S, RsSHC014-S, Rs4231-S, or Rs7327-S was roughly 10- to 500-fold less efficient (Figure 2B).", see pages 7-8, lines 182-197). Further, we agree that Figure S4 contains important information for the reader and thus moved the data to main Figure 2 (as new panel B).

      __ Q3: It is concluded that Raccoon dog ACE2 is the most functional ACE2, but is it possible to quantitatively evaluate the level of difference in expression, which is challenging to adjust experimentally? It may be necessary to present data on expression levels or to pay attention to the interpretation of the data. __

      __A3: __The immunoblot data on ACE2 expression are now shown as new supplemental figure 3, panel B-C, and reveal roughly comparable expression of all ACE2 orthologues analyzed.

      __ Q4: No data are presented indicating the functionality of the BM48-31 S protein. While it is assumed that this S protein cannot function as a receptor, it cannot be denied that it may not be adequately expressed. __

      __A4: __Expression of all S proteins studied was readily detectable including BM48-31 S protein, although expression of P5L-S, cDNA8-S and BM4831-S was decreased. Please see new supplementary figure 4, panel A. Consequently, lack of cell entry by pseudoviruses bearing BM48-31-S may in fact be due to inefficient S protein incorporation into particles. This is now stated on page 8, lines 201-202.

      __ Q5: What is meant by "little impact" compared to what is mentioned? (line 306) __

      __A5: __We modified the text for clarity. The paragraph now states: "Expression of TMPRSS11A, TMPRSS11E and furin in cells producing SARS-1-S bearing particles as well as trypsin-treatment slightly improved generation of the S2 fragment (which results from cleavage at the S1/S2 site) (Figure 5E, left panel). Further, TMPRSS11D expression strongly increased production of the S2 fragment and the S2' fragment (which results from cleavage at the S2' site) while TMPRSS2 and TMPRSS13 expression and trypsin treatment only augmented production of the S2' fragment and decreased production of the S2 fragment (Figure 5E)." (please see page 14, lines 346-354).

      __

      __

      __Q6: Although VSV pseudoviruses are used to evaluate infectivity, in experiments using different conditions (e.g., Figure 5F), how is the amount of VSV pseudovirus for infection adjusted to a similar level? __

      __A6: __For infection of target cells, VSV pseudoviruses were normalized for volume. Immunoblot analysis revealed the particle preparations contained comparable amounts of VSV M protein, please see new supplemental figure 4, panel A.

      __ Q7: Citation of the paper. (lines 474-476) __

      __A7: __The requested citations have been inserted.

      __ Q8: What does "(-)" in Supplementary Figure 4 indicate? __

      A8: "(-) in former figure S4 (now Figure 2B) indicates empty vector. For clarity (and conformity with the other figures), we have changed the label to "No Spike".

      __ Q9: Is it appropriate to indicate the value of 'Pseudovirus Entry' with background fold ratio ('Fold over Background') in Figure 4B, etc (for example)? __

      __A9: __We feel that adding numerical values indicating the fold change ratios to our graphs would "overload" the figures and reduce clarity of the presented data.

      __ Reviewer #3 (Significance (Required)):

      This study is a comprehensive investigation into the function of the S protein of various Sarbecoviruses within the Coronaviridae family. The S protein is one of the most crucial proteins determining the infectivity of coronaviruses, and understanding the receptors and host cell proteases involved in cleaving the S protein is essential. The importance of furin and TMPRSS2 as proteases, and ACE2 as a receptor, has been clearly demonstrated in the infection of SARS-CoV-2, making them the foremost molecules to understand about SARS-CoV-2. However, in this study, the authors have clearly shown the existence of other significant modes of infection (independent of ACE2 and reliant on other proteases), thereby providing clear significance in this regard. Nevertheless, the current weakness, if point out, lies in the need for more depth of understanding of the specific molecular mechanisms underlying this novel mode of infection. __

      Thank you.

      PeerReviewed
    2. EMBOpress 21 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Zhang et al. analyzed the infection mechanisms of various Sarbecovirus primarily using VSV pseudoviruses with individual Sarbecovirus S proteins. The study demonstrated that many Sarbecoviruses, similar to two Sarbecoviruses that do not exhibit infectivity without trypsin, gain infectivity in human cells after processing virus particles with trypsin. This trypsin treatment is closely associated with the cleavage of the S1/S2 site of the S protein. This study demonstrated that the infection of the two viruses is not dependent on ACE2 expression, suggesting infection through receptors other than ACE2. Indeed, this study indicates that the receptor-binding domain of the S protein determines these properties. Furthermore, this study shows that some ACE2-using Sarbecoviruses also acquire ACE2-independent infectivity after trypsin treatment of virus particles. Although similar phenomena have already been reported in some Sarbecoviruses, the data in this study are more extensive, systematically conducted, and thoroughly analyzed, providing sufficient and additional evidence for the points mentioned above. The weaknesses, if pointed out, are that little progress has been made in elucidating the detailed molecular mechanism of this ACE2-independent and trypsin-dependent infection.

      To improve the study, the authors may consider the following points:

      • The Immunoblot data showing the expression level of ACE2-expressing cells used in the analysis of Figure 2 should be presented rather than indicated as "data not shown."
      • In the explanation of Figure 2, it is stated, "all S proteins studied efficiently employed human ACE2 (lines 165-166)," but since there are significant differences in utilization levels, this description needs modification. Is it appropriate to normalize the utilization ability of human ACE2 as "1" in Figure 2B? Supplementary Figure 4 may be more relevant, and it should be considered to use it as a regular figure.
      • It is concluded that Raccoon dog ACE2 is the most functional ACE2, but is it possible to quantitatively evaluate the level of difference in expression, which is challenging to adjust experimentally? It may be necessary to present data on expression levels or to pay attention to the interpretation of the data.
      • No data are presented indicating the functionality of the BM48-31 S protein. While it is assumed that this S protein cannot function as a receptor, it cannot be denied that it may not be adequately expressed.
      • What is meant by "little impact" compared to what is mentioned? (line 306)
      • Although VSV pseudoviruses are used to evaluate infectivity, in experiments using different conditions (e.g., Figure 5F), how is the amount of VSV pseudovirus for infection adjusted to a similar level?
      • Citation of the paper. (lines 474-476)
      • What does "(-)" in Supplementary Figure 4 indicate?
      • Is it appropriate to indicate the value of 'Pseudovirus Entry' with background fold ratio ('Fold over Background') in Figure 4B, etc (for example)?

      Significance

      This study is a comprehensive investigation into the function of the S protein of various Sarbecoviruses within the Coronaviridae family. The S protein is one of the most crucial proteins determining the infectivity of coronaviruses, and understanding the receptors and host cell proteases involved in cleaving the S protein is essential. The importance of furin and TMPRSS2 as proteases, and ACE2 as a receptor, has been clearly demonstrated in the infection of SARS-CoV-2, making them the foremost molecules to understand about SARS-CoV-2. However, in this study, the authors have clearly shown the existence of other significant modes of infection (independent of ACE2 and reliant on other proteases), thereby providing clear significance in this regard. Nevertheless, the current weakness, if point out, lies in the need for more depth of understanding of the specific molecular mechanisms underlying this novel mode of infection.

      PeerReviewed
    3. EMBOpress 21 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      Recent work from several groups has shown that the majority of bat sarbecoviruses infect cells independent of ACE2, the receptor primarily used by sarbecoviruses that infect humans, and instead infect cells in the presence of exogenous protease including trypsin. In this study, Zhang and colleagues build on these earlier findings by demonstrating that ACE2-independent sarbecovirus entry can be mediated by other exogenous proteases and several different TMPRSS11 enzymes. Using in vitro based methods and viral pseudotypes, the authors reproduce previous findings with trypsin, demonstrate similar effects with alternative proteases and provide lines of evidence suggesting (1) trypsin treatment can impart ACE2-independence and that (2) ACE2-independence provides resistance to neutralizing antibodies.

      Major comments:

      1. Defining sarbecovirus RBDs into clades by in del features has already been established by other groups and many studies across different disciplines now use these previously-established clades. The authors use slightly different nomenclature without any acknowledgment of the previously defined sarbecovirus RBD clades, which will lead to confusion between studies. For example, SARS-CoV-2 is generally regarded as a clade 1 RBD (with ACE2 use and both loops in tact), clade 3 includes BM48-31 and Khosta-2, clade 4 includes RatG15.
      2. Why did the authors select BM48-31 as the representative of its clade when other members of the clade have known receptors and clear phenotypes in lab assays? BM48-31 has largely failed in every lab assay by every group that has studied it. On the other hand, Khosta2 uses human ACE2, BtKY72 and other African sarbecoviruses can also use ACE2 from their host species and have low but detectable human ACE2 compatibility. It would be interesting to see how the antibody-resistance results compare with other ACE2-dependent sarbecoviruses.
      3. What is the aurthors' proposed mechanism for how protease is functioning for ACE2-independent entry? For ACE2-dependent entry, TMPRSS2 cleaves spike after RBD engagement. However, in this study, TMPRSS11 enzymes only function when included in producer cells- prior to RBD engagement. Is TMPRSS11 cleaving spike during spike biogenesis (similar to furin for SARS-CoV-2) or is an alternative mechanism at play? Is TMPRSS11 secreted? If this is the case, then the enzyme may be functioning similar to the other exogenous proteases in this study.
      4. Related to comment 3: the authors study trypsin as a pre-treatment, but other studies have shown trypsin exerts activity during entry. How do the authors propose trypsin is functioning prior to RBD engagement? Is it possible that trypsin is not fully inactivated and remains partially active during entry?
      5. I am not convinced that trypsin is driving ACE2-independent entry for ACE2-dependent viruses. The experiment performed in figure 3C is performed in African green monkey cells using an antibody directed toward human ACE2. The difference in species between antibody and antigen may influence how well the antibody binds ACE2 on the Vero cells, which may only block some ACE2-dependent viruses but not all. Curiously, the only ACE2-dependent spikes that gain "ACE2-independence" are also activated by trypsin. These blocking assay results would be more convincing in a human cell line, or a non-permissive cell line like BHKs that express the human receptor. Alternatively, knocking out ACE2 in the Vero cells may be another way to assess ACE2-independent entry.

      Minor comments:

      1. line 148: Rs4237 is missing a clade designation
      2. Figure 3. The figure's main message could be improved by visually grouping the viruses according to clade.
      3. Some details are missing for reproducibility, including the accession numbers of the TMPRSS enzymes used in this study
      4. Contrary to claims in the text, this study includes a fairly small panel of spike proteins. Prior studies by Letko 2020, Starr 2022 and Roelle 2022 (cited by the authors) all measured entry for between 20-40 spikes - more twice the number in this study.
      5. Line 472-473: the data presented in figure 2B shows SARS-CoV-2 has slightly better entry with pangolin ACE2 than raccoon dog. I am not sure the authors should cite this data in support of raccoon dogs as an intermediate for SARS-CoV-2.

      Significance

      This study provides some novel insights into proteases and sarbecovirus cell entry and highlights previously unappreciated entry factors that are key for some viruses. A major limitation of this study is its lack of mechanistic exploration. The authors data do not really elucidate how TMPRSS11 proteins mediate ACE2-independent entry, nor do the results explain how ACE2-independence is shielding viruses from neutralizing antibodies. Another limitation is in the choice of using a non-human cell line to study the blocking effect of an antibody directed toward a human protein.

      Advance

      This study nicely reproduces a number of previous findings, including: 1. sarbecovirus RBDs can be categorized into clades based on deletions in surface exposed loops 2. ACE2-independent, trypsin-dependent sarbecovirus entry - notably for Rs4081 3. the RBD in ACE2-independent sarbecoviruses controls entry 4. anti-ACE2 antibodies do not block entry for ACE2-independent sarbecoviruses as well as some ACE2-dependent sarbecoviruses 5. trypsin does not increase S proteins binding to cells 6. protease expression in target cells does not increase S-driven entry 7. a multi-basic cleavage site in spike does not compensate for exogenous protease in ACE2-independent entry

      This study has many novel advancements as well:

      1. identification of other exogenous proteases that mediate ACE2-independent entry (elastase, thermolysin)
      2. identification of TMPRSS11 family members that mediate trypsin-free entry for ACE2-independent viruses when produced in cells producing spike proteins but not target cells
      3. ACE2-independent entry may reduce spike susceptibility to antibody neutralization

      Audience:

      This study will appeal to the coronavirus research community.

      PeerReviewed
    4. EMBOpress 21 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Using the S protein from 14 different sarbecoviruses isolated from bats or pangolin, Zhang et al. makes in this manuscript several points on sabecovirus entry. These points include ACE2 independent entry, trypsin-driven entry, RBD-dependence of trypsin-mediated entry, use of soluble proteases and TRMPRSS-family transmembrane proteases in trypsin-mediated and trypsin-independent entry, and neutralizing antibody evasion in trypsin-mediated entry. Some of these points are supported by the data presented; although there are some discrepancies, they are largely within the range of experimental error. However, some of the statements in the Title, Abstract, and main text, appear to be more than what the data support. Nonetheless, the data authors presented are informative and will help understanding sarbecovirus entry processes.

      Major points:

      Below are only a few examples of inaccurate sentences. The authors should rewrite similar statements throughout the manuscript.

      1. The title: "ACE2-independent sarbecovirus cell entry is supported by TMPRSS2-related enzymes and reduces sensitivity to antibody-mediated neutralization" does not correctly reflect the presented data (1) because the contribution by TMPRSS2-like enzymes was shown only when they were co-transfected during PV production, but not when they are expressed on the target cell surface, and (2) because "reduces sensitivity to antibody-mediated neutralization" was observed only for one S protein but was not observed for the other two trypsin-dependent S proteins. In addition, this point was made using one monoclonal Ab for trypsin-dependent entry, but not for the entry mediated by TMPRSS2-related enzymes as the title implies. The title sounds like the three points are interconnected and represent general phenomena. Perhaps a more accurate title could be "ACE2-independent sarbecovirus cell entry is supported by trypsin and may reduce sensitivity to a neutralizing antibody".

      In the Abstract, the authors state "Several TMPRSS2-related cellular proteases but not the insertion of a multibasic cleavage site into the S protein allowed for ACE2-independent entry in the absence of trypsin and may support viral spread in the respiratory tract" (lines 38-41) and "In sum, our study reports a pathway for entry into human cells that is ACE2-independent, supported by TMPRSS2-related proteases...." (lines 44-46). These sentences should be rewritten for the same reason described above for the Title.<br /> 2. The lines 102-105 say "...ACE2-independent, trypsin-dependent entry can modulate neutralization by the pan sarbecovirus antibody S2H97..." and the lines 427-9 say "...trypsin-dependent usage of an ACE2-independent entry pathway may result in slightly reduced susceptibility to neutralization by antibodies induced upon infection or vaccination." Because Fig 8 (S2H97 Ab) and Fig 9 (immune plasma) use Vero-ACE2-TMPRSS2 and A549-ACE2-TMPRSS2, respectively, "ACE2-independent," is incorrect here.

      The line 46 says "...and associated with antibody evasion", the lines 104-5 says "...and allows for partial antibody evasion in the context of plasma from COVID-19 vaccinees." and the lines 427-9 say "...may result in slightly reduced susceptibility to neutralization by antibodies..." The authors should rewrite them because the resistance to S2H97 Ab was observed with one S protein but all other trypsin-mediated entry was sensitive to S2H97 or immune plasma. 3. If trypsin- independent entry is still controlled by RBD, why LYRa11 and Rs7327 entry is enhanced by and RsSHC014 entry is resistant to S2H97 Ab? The authors may want to discuss possible explanations. 4. Fig. 2B. The entry supported by ACE2 orthologs was normalized to that utilizing hACE2 after hACE2-supported entry was normalized to background entry (no-S PV). First, it is unclear why background entry is used for normalization instead of being subtracted. Second, two times of such normalization likely created huge experimental errors and might have skewed the outcomes. Thus, 14 PVs should be quantified by RT-qPCR and same genome copy number should be used to directly assess their usage of ACE2 orthologs. This way, normalization by hACE2 entry is not necessary. Background entry should be subtracted, not used for normalization. 5. Because VSV PVs were harvested in culture media, there were serum and divalent cations. Were PVs purified before trypsin digestion? Digestion by trypsin or other proteases should be described in detail. 6. How was S2' fragment on the blot determined? Should be described.

      Minor points.

      1. The line 129 says "...14 S proteins, representing all clades, were selected for detailed analyses". Correct the sentence because the S protein representing clade 5 is not included in the study.
      2. Fig 2. Because 14 S proteins and several TFR1 orthologs were used, a table describing which S isolate is derived from which animal species will help. Organizing Fig 2A and B in the same order will help reading the result. Also, indicate which clades those S proteins belong to.
      3. Fig S5. Describe cell lines used.
      4. Fig 3 legend should indicate trypsin digestion condition (concentration and length).

      Significance

      Because overwhelming amount of data bear large experimental errors, there are some discrepancies among the data presented. Nonetheless, most of each point the authors claim is largely supported by the data. The problem happened when the authors tried to connect the dots too much and thus overstated some conclusions. If the overstated conclusions are amended throughout the manuscript, presented data provide sufficiently useful information on sarbecovirus entry.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.04.18.590061v1
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    Activation of the mitochondrial unfolded protein response regulates the dynamic formation of stress granules
    4
    1. EMBOpress 19 Jul 2024

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      Reply to the reviewers

      Reviewer #1 (Evidence, reproducibility and clarity (Required)): Throughout, the authors claim that there is a cross-talk between UPRmt and SG. This is unsubstantiated and unclear.

      We strongly disagree this comment. Throughout the manuscript, we show how manipulating UPRmt signalling affects SG formation, and how manipulating SG assembly alters mitochondrial functions and UPRmt-associated mitochondrial ouputs. In addition, both other reviewers are supportive of our conclusions.

      Major: Link between UPRmt and stress granules:

      The authors claim a link between the UPRmt and stress granule formation based on the finding that the loss of ATF5 affects the expression of UPRmt markers, but not ISR markers. Yet, the authors actually show that GTPP-induced SGs form in a manner independent of ATF5 (Supp. Fig. 2). Thus, there is no data in the manuscript that substantiates this claim.

      In the revised manuscript, we show that reducing ATF5 level results in defective SG assembly, with SGs displaying small size and more numerous, reflecting a maturation defect (Sup Figure 6B, 6C and 6D). In addition, we show a clear dependence of SGs to PERK activation (see comment below) and a specific increase of the ISR main negative regulator GADD34 (Figure 2A and 2B). Therefore, we disagree with this reviewer's conclusion and provide data supporting a link between UPRmt and SG formation.

      PERK-mediated activation of the ISR. The authors claim that PERK mediates activation of the ISR following GTPP treatment. However, the experiments in Fig. 2E were done 1h after treatment. The authors in Fig. 1C nicely show that SG formation begins at 2h. Thus, it is possible that following a longer GTPP treatment (i.e. >2h) the ISR is activated by different branches; for example, the mitochondrial branch that is mediated by HRI. Thus, the authors should determine which kinase mediates ISR activation at the time point that SG formation is maximal.

      We apologise if the description of the experimental procedure was unclear. These experiments are performed at 2h post GTPP treatment as explained in the text (see line 222) and legend (see lines 715-717, Figure 2 legend), and therefore performed at a time of maximal SG induction. Therefore, the identification of PERK as the driver for eIF2α-P and SG formation is performed at a time point where SG formation is maximal.

      Role of SG-linked decrease in cellular adaptation to stress. The finding that SGs limit mitochondrial respiration is interesting. Presumably this promotes cellular adaptation to mitochondrial stresses. The authors should test whether G3BP1/2 DKO cells are more susceptible to death following longer GTPP treatments.

      We thank the reviewer for this comment. These data are presented in Figure 8, where we show that G3BP1/2 dKO cells are less viable compared to wild-type cells following GTPP treatment for up to 28 hours.

      Minor: Fig. 2C should be moved to supplemental as well as the data indicated the lack of ISR inhibition.

      Figure 2C is now supplementary Figure 3.

      Fig. 3A should have representative images of all conditions from Fig. 3B.

      This has now been included as supplementary Figure 4.

      IFAs in Fig. 3 and 4 are hard to interpret given both DAPI and G3BP1 are in shades of blue. Ideally, insets of a merged panel should show each individual panel.

      We adopted the combination cyan, magenta and clue for our images to make scientific figures accessible to readers with red/green color-blindness. For these figures, G3BP1 is in light cyan and DAPI in dark blue, a colour we adopted previously in three publications (PMID 36965618, PMID 35098996, PMID 31905230), allowing colour blind reader to appreciate the results.

      Reviewer #1 (Significance (Required)): The link between the UPRmt and SGs is interesting and would be an advance. However, the authors put forward data that indicates SGs form in an UPRmt (ATF5)- independent manner. An interesting aspect of this story for which there is data is that SGs limit mitochondrial function. This should be explored further (i.e. although it limits mitochondrial respiration, perhaps SGs protect mitochondria against chronic ISR stress).

      As suggested we now provided an extensive amount of additional data supporting a role in mitochondrial functions, with data demonstrating that the absence of SGs rescues cell viability (Figure 8A and 8B), restoring mitochondrial functions such as respiration, ATP production (Figure 6D, 6E and 6F) or translation (Figure 7A), and reducing the production mitochondrial ROS (Figure 6C) or mitochondrial fragmentation (Figure 6A and 6B).

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): Summary: The article by Lopez-Nieto Jordana et al entitled "Activation of the mitochondrial unfolded protein response regulates the dynamic formation of stress granules" describes the identification of a novel cross talk between the mitochondrial unfolded protein response (UPRmt) and the integrated stress response (ISR) and the contributory role SG regulation plays in mitochondrial function and adaptation to stress. This manuscript presents data highlighting that activation of the UPRmt results in the temporal modulation of SG formation via GADD34 levels and further this analysis by suggesting that these levels of GADD34 may enable cells to be protected from prolonged stress.

      Minor comments: This is a very well written manuscript with beautifully presented data. There are some inconsistencies/typos with the abbreviation GTPP- this needs to be checked within the manuscript but examples are on Lines: 204/206/214/324/328/357.

      This has now been corrected throughout.

      Check reference list for inconsistencies; line 680 reference has no page numbers, line 718 reference has no issue or page numbers

      This has now been corrected, references curated throughout.

      Line 255 - is it correct to say induction here? I think impairment should be used.

      This has now been corrected, see lines 283-284.

      Cell type not mentioned in Fig 2 legend.

      This has now been corrected, see line 707.

      Errors in Fig 4 legend - 4F, G do not exist.

      This has now been corrected, see lines 748-750.

      Major comments: In figure 1- the GTPP treatment only results in 25% of cells showing SGs compared with 80% in Ars treated cells. While the activation of ISR markers by GTPP treatment is convincing (in Figure 2A), What happens to overall protein synthesis levels in these cells? Puromycin incorporation assays would be a useful addition here.

      We now show in Figure 1D that GTPP treatment result in a global reduction in translation, and that cells displaying SGs present with a stronger shut-off when compared with treated cell lacking SGs.

      Fig. 1A - ATF4 upregulation is lower in ATF5 siRNA treated cells - what is % uptake of the siRNA in these cells - also see comment below. If possible, it would be nice to see the re-localisation of ATF5 to the nucleus to confirm the UPRmt activation of this protein

      These are experiments that we had planned to perform, however in our hands none of the commercially available antibodies allowed us to determine with confidence the localisation of ATF5. We have not determined the uptake of ATF5 siRNA but show by qPCR a reduction in ATF5 mRNA levels following siRNA treatment (see Figure 1A).

      Does the dispersal of SGs also correlate with a recovery of protein synthesis- there is still a relatively high level of eIF2alph-P at the 8h (from Figure 2A).

      We have not performed these experiments as we do not believe they would have added depth to our study. It is well accepted that SG disassembly results in mRNA re-entry in polysomes and the restart of translation (PMID: 30664789). SGs disappear a few minutes before translation is resumed.

      In Figure 2A the 30 min treatment of GTPP induces a robust level of eIF2α-P yet SGs are only observed following the induction of ATF4/GADD34 at 2h. Puromycin incorporation assays may also be able to shed light on the lack of SG inductions at this stage. The formation of SGs around the time when ATF4 and GADD34 are induced seems counterintuitive and should be commented on.

      As commented in response to an earlier point, our analysis shows that GTPP result in a global reduction in translation level, the assembly of SGs in a subpopulation of cells (as reported also in the context of many viral infection) may reflect cell-specific differences in the levels of eIF2α kinases and/or differences in reaching the threshold needed for eIF2α phosphorylation to induce SG assembly (as shown in PMID 30674674 and PMID 35319985).

      In line 207-208 you state that "PERK is the main eIF2α kinase responsive to GTTP. Overall, these results suggest that induction of the UPRmt is associated with an early SG assembly and ISR activation through PERK." Does the PERK inhibitor inhibit the formation of SG following GTTP treatment? # This is now shown in Figures 2E and 2F. Indeed pharmacological inhibition of PERK following GTPP treatment resulted in inhibition of SG assembly.

      Additionally, does GTPP activation of the UPRmt also induce an oxidative stress and therefore activate an additional EIF2AK such as HRI? If so could be the reason you don't get formation of SGs following Ars treatment? Have you considered what would happen if you used the UV stress which activates GCN2 followed by Ars treatment?

      As shown on Figures 2D and 2E, we could not detect contribution from the other eIF2a kinases GCN2 and PKR following GTPP treatment; and Figures 2E, 2F demonstrate that PERK inhibition is sufficient to revert eIF2a phosphorylation and ablate SG induction, as noted in the response to the point above. This strongly suggest that the eIF2a kinase HRI does not contribute to eIF2a signalling, however we do not exclude in the broader sense (beyond eIF2a signalling) an induction of oxidative during UPRmt activation. Furthermore, as shown in Figure 2D, A-92 treatment reduced p-eIF2a levels in response to UV treatment but not those induced by GTPP therefore we can exclude a contribution from GCN2. If we understand correctly, this reviewer asks what would happen if cells were UV-stressed to activate GCN2 followed by oxidative stress with arsenite. This is outside the scope of this manuscript, but based on our previous work showing that mRNA GADD34 mRNA levels act as the molecular memory of the ISR and drives cell adaptation to acute and chronic stress, we would expect that the response to a second pulse of stress would be dampened by the sustained level of GADD34 mRNA induced following the first stress (see PMID 35319985). In these previous studies we already demonstrated that induction of p-eIF2a and SGs by a first acute stress (heat shock or thapsigargin) impairs the induction of p-eIF2a and SGs by a second acute (heat shock or arsenite) or chronic (HCV infection) stress (PMID 35319985, see Figure 6; PMID: 38602876, see Figure 7).

      Overall, this and the response to the previous comment strongly support that PERK activation, and the resulting induction of GADD34, are responsible for SG regulation following GTPP treatment.

      In Figure 3, for the paraquat experiments have you missed the transient induction of SGs by only looking at 48h? You already have GADD34 levels high here so SGs/eIF2α-P levels will already be lowered.

      We have now included additional timepoints, see supplementary Figure 5, showing the absence of SGs at 1, 2, 6 and 24h post paraquat treatment, to complement the 48h treatment previously shown.

      In addition, when analysing GTPP + Ars treatment impact on SG formation (Fig 2B), could the 2 h GTPP + Ars data also be included, as this is the peak time for SG induction by GTPP

      This is now included in Figure 3B.

      In line 211 you refer to the early and late stages of the stress, how have these been defined? It seems that the ability of the UPRmt to be protective to an additional stressor is time dependent- the number of SGs that are present following the additional stress increases from 4-8h. Does this correlate with a decrease in the level of GADD34?

      We define early and late to the time points corresponding to induction (early) or disassembly (late) of SGs. Also see lines 227-230.

      In line 254 you state that ATF5 silencing didn't impact the ISR or SG formation? These data suggest that the formation of SGs is not a direct impact of activation of the UPRmt but rather activation of the cellular ISR possibly due to the proteotoxic and/or oxidative stress? Can the authors comment on this?

      We now show in supplementary Figure 6 that reducing the expression of ATF5 results in defects in SG maturation with GTPP treatment resulting in more numerous and smaller SGs. Moreover, it should be noted that HSF1, in addition to ATF5, is a key controller of UPRmt induction and future studies could aimed at dissecting the role of HSF1 in the SG-UPRmt crosstalk (discussed in lines 459-461).

      In Figure 4, If GADD34 was driving the loss of SGs in GTPP treated cells why are SGs not persistent in these KO cells. Please comment on this.

      Two phosphatases are known to catalyse eIF2a-P dephosphorylation, GADD34 and CReP. The current model proposes that GADD34, which is induced following stress, acts in a negative feedback loop to resolve cellular stress. In contrast, CReP is constitutively expressed and controls basal P-eIF2α levels independently from stress levels (PMID 27161320). In recent work, we have shown that when GADD34 expression is silenced, CReP takes over to revert eIF2a -P and therefore disassemble SGs (PMID: 38602876). This work also showed that CreP is stress-induced in the absence of GADD34. Therefore, in Figure 4 we can speculate that the absence of SGs in GTPP treated KO cells is due to the ability of CReP to compensate for the absence of GADD34. In the context of GTPP treatment followed by arsenite, GADD34 is important to increase the threshold at which SGs can form, altering the response to a second pulse of stress.

      In addition, in these GADD34KO cells there should also be a persistent level of eIF2α-P when treated with GTPP and Pq, there is some as evidenced by the quantification but this is not very convincing

      As noted here, we do provide evidence of sustained levels of eIF2a-P in cells treated with GTPP at least, the results of independent experiments (n=3) showing persistent phosphorylation when compared treatment in GADD34 KO relative to WT cells. But as noted in the point above the likely activity of CReP can compensate for the lack GADD34, and therefore dampen the amount of eIF2a phosphorylation observed.

      Fig 4B shows no cells exhibiting SG following 4h GTPP treatment, which does not correlate with other experiments in the original cell line, e.g. supp 2B - please explain. Can GTPP still activate the UPR-mt in this CRISPR control cell line

      GTPP still activates the UPRmt in the CRISPR control cell line has shown by the inhibition of arsenite-induced SGs assembly when cells are pre-treated with GTPP for 4h (Figure 4A). However, we have noted that the timings of the response to GTPP can vary slightly, impacting on the exact SG kinetics, depending on the purity of the drug (synthetised through organic routes by our collaborator Dr Altieri), with the SG peak either at 2 h or at 4 h post-GTPP treatment. Potentially live imaging of SGs in control and GADD34 KO cells would alleviate this caveat, however in the time frame of the rebuttal, further engineering of GADD34 KO and parental lines into G3BP1/2 knock-outs / GFP-G3BP1 knock-ins was not achievable.

      In Figure 5, of the 80% of SG still present in GTPP treated Sil SGs- was size or frequency impacted here too as in Pq treatment? # These data are now provided, see Figure 5C and in the result section lines 325-329. These show that GTPP treatment resulted in a reduction in average size of silvestrol-induced SGs, from 0.98 μm2 to 0.9 μm2, and increased average number of SGs, from 18 to 22, when compared to non-treated cells. Additionally, we also quantified features of Ars-induced SGs in GTPP-pretreated cells, data provided in Figure 3C and in the result section lines 245-250. The analysis showed that as paraquat, GTPP pre-treatment also impacts size and frequency of arsenite-induced SGs.

      This is just for clarification but If GTPP is a hsp90 inhibitor, is it specific to mitochondrial Hsp90 proteins?

      Indeed GTPP is specific to mitochondrial Hsp90.

      In the last results section the authors suggest that G3BP1/2 KO cells unable to assemble SGs present with improved mitochondrial function during stress. Firstly, is the UPRmt activated in these KO cells? Could the increased activity just be a consequence of the cells not being able to sense the stress and adapt? Are these cells able to recover from the GTPP stress to the same extent as the wt? Do they die at later timepoints? If you inhibited the disassembly of SGs using DYRK3 inhibitors would you decrease mitochondrial activity? # The figure below confirms the upregulation of UPRmt genes mRNA levels after GTPP treatment in U2OS G3BP1/2 dKO (rebuttal Figure 1). We did not include this in the main manuscript given it is figure heavy already and this did not add depth to our results. Our extensive additional analysis shows that cells unable to assemble SGs present with multiple restored mitochondrial functions following UPRmt induction, including increased ATP production (Fig 6D), and respiration (FIG 6E, 6F), reduced mitochondrial ROS level (Fig 6C) and fragmentation (Fig 6A, 6B). These all support a model in which SG assembled following UPRmt induction contribute to impaired mitochondrial function and that their inhibition/disassembly is necessary to restore mitochondrial homeostasis.

      Rebuttal Figure 1: RT-qPCR analysis of the UPRmt and ISR markers DNAJA3, HSPD1, CHOP and ATF4 mRNA levels in U2OS cells treated with GTPP for up to 6 h. Results shown representative of n=3, normalised to RPL9 mRNA and shown relative to DMSO.

      Reviewer #2 (Significance (Required)): Significance: This is an interesting and clearly important observation providing mechanistic insight into the role SGs may play in the cells control of mitochondrial function during stress. The functional role of SGs in disease and stress is still widely unknown and this manuscript therefore sheds light on how the cell may use SGs to modulate and adapt to mitochondrial stress. This is an exciting area of research that will be applicable to a large audience as SGs are implicated in a wide range of diseases. While the data is significant there are currently a number of important experiments required to strengthen the current observational analysis. Below are some minor and major comments linked to the manuscript. # We thank the reviewer for highlighting the importance of our work in an 'exciting area of research'.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)): As it stands, this study will be suited for a specialized cell biology journal. In order to be published in a journal of a broader readership, the authors would need to address two major points:

      1. Mitochondrial dysfunction affects cellular function in many ways. Reduced levels of ATP, oxidative stress by increased ROS levels and mitochondrial precursor proteins that challenge proteostasis in the cytosol are just three major consequences of mitochondrial defects. Arguably, for the generation of stress granules, it will be important which of these consequences of mitochondrial dysfunction are prevalent. Since mitochondrial dysfunction is an ill-defined umbrella term, this study would be stronger if the authors could link stress granule formation to the specific molecular defects that arise from specific inhibition of mitochondrial functions.

      We agree with this reviewer that mitochondrial dysfunction can take many shapes and therefore to address their comment we have now performed an extensive amount of additional experiments probing various aspects of mitochondrial functions. In addition to the data previously included we can now show to that inhibition of SG formation during UPRmt induction result in increased cell viability (Figure 8A-B), restoring mitochondrial functions such as respiration, ATP production (Figure 6C-F) or translation (Figure 7A), and reduce mitochondrial ROS (Figure 6C) or fragmentation (Figure 6A-B). These all support a model in which SGs assembled following UPRmt induction contribute to impaired mitochondrial function and that their inhibition/disassembly is necessary to restore mitochondrial homeostasis.

      1. Also stress granules are an umbrella term. Different treatments will presumably change the spectrum of transcripts that are sequestered in these granules. As mitochondrial defects remodel the transcription and translation of mitochondrial precursor proteins, the study would benefit from a comprehensive analysis of the spectrum of transcripts that are contained in granules induced by GTPP and sodium arsenite, respectively.

      Previous studies, including our own, have demonstrated that indeed different stress (or infections) can result in the assembly of compositionally distinct SGs (or SG-like foci) that sequester specific subset of mRNAs or proteins. These studies are based on affinity purification or proximity ligation approaches followed by multi-omics analysis of SG components by RNA-seq and mass spectrometry. While we agree with this reviewer that determining the composition of UPRmt-induced SGs could help understand their function, we believe these studies are outside the scope of the current manuscript, and this would instead form the basis of subsequent study and manuscript.

      Reviewer #3 (Significance (Required)): The study is interesting but descriptive. It confirms previous observations. The advance in mechanistic insights is limited. Nevertheless, the study is technically sound and of interest for a specialized readership. As it stands, the study might be published in a specialized journal. In order to be of general interest for a large and general readership, the authors will have to provide much more mechanistic and molecular insight, which will require at least another six months of work.

      We have now produced an extensive additional body of work to answer specific comments made by all three reviewers, bolstering our hypothesis, and delving deeper into the impact of SG assembly on mitochondrial functions.

      PeerReviewed
    2. EMBOpress 19 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Mitochondrial dysfunction induces a complex remodeling of gene expression. One defined branch in this response is known as the mitochondrial unfolded protein response (UPRmt). The transcription factor ATF5 acts as a key mediator of the mammalian UPRmt signaling. Moreover, mitochondrial defects also mute protein synthesis and trigger the integrated stress response (ISR). ISR is a well-characterized anti-stress routine characterized by eIF2alpha phosphorylation. The induction of cytosolic stress granules is one hallmark of ISR. In the present study, the authors observe that induction of UPRmt by inhibition of the mitochondrial HSP90 chaperone induces cytosolic stress granules. This is not unexpected given the well-established UPRmt/ISR and ISR/stress granules links. Still, the study is technically sound and extends our understanding of the effects of mitochondrial problems on the reactions in the cytosol.

      The authors compare two different inhibitors of mitochondrial functions: gamitrinib-triphenylphosphonium (GTPP) which interferes with HSP90 and whose effect on extra-mitochondrial proteostasis was well characterized by studies from Wade Harper and Christian Munch (Sutandy et al. 2023 Nature; Munch and Harper 2016 Nature); and paraquat which induces the generation of superoxide radicals from the respiratory chain. They found considerable differences of these two drugs in respect to stress granule formation which is consistent with previous observations. GTPP induces the accumulation of mitochondrial precursor proteins in the cytosol, which induces UPRmt. Defects in respiration however do not necessarily block mitochondrial protein import.

      In general, this is an interesting study that confirms previous observations. The molecular and mechanistic insights are limited and the authors neither identified the cascade of events that triggers stress granule formation upon HSP90 inhibition, nor did they analyze the transcripts that are sequestered by the cytosolic stress granules. Nevertheless, despite its rather descriptive nature, the study will be of interest for researchers studying the consequences of mitochondrial dysfunction.

      As it stands, this study will be suited for a specialized cell biology journal. In order to be published in a journal of a broader readership, the authors would need to address two major points:

      1. Mitochondrial dysfunction affects cellular function in many ways. Reduced levels of ATP, oxidative stress by increased ROS levels and mitochondrial precursor proteins that challenge proteostasis in the cytosol are just three major consequences of mitochondrial defects. Arguably, for the generation of stress granules, it will be important which of these consequences of mitochondrial dysfunction are prevalent. Since mitochondrial dysfunction is an ill-defined umbrella term, this study would be stronger if the authors could link stress granule formation to the specific molecular defects that arise from specific inhibition of mitochondrial functions.
      2. Also stress granules are an umbrella term. Different treatments will presumably change the spectrum of transcripts that are sequestered in these granules. As mitochondrial defects remodel the transcription and translation of mitochondrial precursor proteins, the study would benefit from a comprehensive analysis of the spectrum of transcripts that are contained in granules induced by GTPP and sodium arsenite, respectively.

      Significance

      The study is interesting but descriptive. It confirms previous observations. The advance in mechanistic insights is limited.

      Nevertheless, the study is technically sound and of interest for a specialized readership. As it stands, the study might be published in a specialized journal. In order to be of general interest for a large and general readership, the authors will have to provide much more mechanistic and molecular insight, which will require at least another six months of work.

      PeerReviewed
    3. EMBOpress 19 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      The article by Lopez-Nieto Jordana et al entitled "Activation of the mitochondrial unfolded protein response regulates the dynamic formation of stress granules" describes the identification of a novel cross talk between the mitochondrial unfolded protein response (UPRmt) and the integrated stress response (ISR) and the contributory role SG regulation plays in mitochondrial function and adaptation to stress. This manuscript presents data highlighting that activation of the UPRmt results in the temporal modulation of SG formation via GADD34 levels and further this analysis by suggesting that these levels of GADD34 may enable cells to be protected from prolonged stress.

      Minor comments:

      This is a very well written manuscript with beautifully presented data.

      There are some inconsistencies/typos with the abbreviation GTPP- this needs to be checked within the manuscript but examples are on Lines: 204/206/214/324/328/357.

      Check reference list for inconsistencies; line 680 reference has no page numbers, line 718 reference has no issue or page numbers

      Line 255 - is it correct to say induction here? I think impairment should be used.

      Cell type not mentioned in Fig 2 legend.

      Errors in Fig 4 legend - 4F, G do not exist.

      Major comments:

      In figure 1- the GTPP treatment only results in 25% of cells showing SGs compared with 80% in Ars treated cells. While the activation of ISR markers by GTPP treatment is convincing (in Figure 2A), What happens to overall protein synthesis levels in these cells? Puromycin incorporation assays would be a useful addition here.

      Fig. 1A - ATF4 upregulation is lower in ATF5 siRNA treated cells - what is % uptake of the siRNA in these cells - also see comment below.

      If possible it would be nice to see the re-localisation of ATF5 to the nucleus to confirm the UPRmt activation of this protein oes the dispersal of SGs also correlate with a recovery of protein synthesis- there is still a relatively high level of eIF2alph-P at the 8h (from Figure 2A).

      In Figure 2A the 30 min treatment of GTPP induces a robust level of eIF2α-P yet SGs are only observed following the induction of ATF4/GADD34 at 2h. Puromycin incorporation assays may also be able to shed light on the lack of SG inductions at this stage. The formation of SGs around the time when ATF4 and GADD34 are induced seems counterintuitive and should be commented on.

      In line 207-208 you state that "PERK is the main eIF2α kinase responsive to GTTP.Overall, these results suggest that induction of the UPRmt is associated with an early SG assembly and ISR activation through PERK." Does the PERK inhibitor inhibit the formation of SG following GTTP treatment?

      Additionally, does GTPP activation of the UPRmt also induce an oxidative stress and therefore activate an additional EIF2AK such as HRI? If so could be the reason you don't get formation of SGs following Ars treatment? Have you considered what would happen if you used the UV stress which activates GCN2 followed by Ars treatment?

      In Figure 3, for the paraquat experiments have you missed the transient induction of SGs by only looking at 48h? You already have GADD34 levels high here so SGs/eIF2α-P levels will already be lowered.

      In addition, when analysing GTPP + Ars treatment impact on SG formation (Fig 2B), could the 2 h GTPP + Ars data also be included, as this is the peak time for SG induction by GTPP

      In line 211 you refer to the early and late stages of the stress, how have these been defined? It seems that the ability of the UPRmt to be protective to an additional stressor is time dependent- the number of SGs that are present following the additional stress increases from 4-8h. Does this correlate with a decrease in the level of GADD34?

      In line 254 you state that ATF5 silencing didn't impact the ISR or SG formation? These data suggest that the formation of SGs is not a direct impact of activation of the UPRmt but rather activation of the cellular ISR possibly due to the proteotoxic and/or oxidative stress? Can the authors comment on this?

      In Figure 4, If GADD34 was driving the loss of SGs in GTPP treated cells why are SGs not persistent in these KO cells. Please comment on this.

      In addition, in these GADD34KO cells there should also be a persistent level of eIF2α-P when treated with GTPP and Pq, there is some as evidenced by the quantitation but this is not very convincing/

      Fig 4B shows no cells exhibiting SG following 4h GTPP treatment, which does not correlate with other experiments in the original cell line, e.g. supp 2B - please explain. Can GTPP still activate the UPR-mt in this CRISPR control cell line

      In Figure 5, of the 80% of SG still present in GTPP treated Sil SGs- was size or frequency impacted here too as in Pq treatment? This is just for clarification but If GTPP is a hsp90 inhibitor, is it specific to mitochondrial Hsp90 proteins?

      In the last results section the authors suggest that G3BP1/2 KO cells unable to assemble SGs present with improved mitochondrial function during stress. Firstly, is the UPRmt activated in these KO cells? Could the increased activity just be a consequence of the cells not being able to sense the stress and adapt? Are these cells able to recover from the GTPP stress to the same extent as the wt? Do they die at later timepoints?

      If you inhibited the disassembly of SGs using DYRK3 inhibitors would you decrease mitochondrial activity?

      Significance

      This is an interesting and clearly important observation providing mechanistic insight into the role SGs may play in the cells control of mitochondrial function during stress. The functional role of SGs in disease and stress is still widely unknown and this manuscript therefore sheds light on how the cell may use SGs to modulate and adapt to mitochondrial stress. This is an exciting area of research that will be applicable to a large audience as SGs are implicated in a wide range of diseases. While the data is significant there are currently a number of important experiments required to strengthen the current observational analysis. Below are some minor and major comments linked to the manuscript.

      PeerReviewed
    4. EMBOpress 19 Jul 2024

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

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      Referee #1

      Evidence, reproducibility and clarity

      The integrated stress response is activated by kinases that sense diverse stresses including viral infection and ER-linked stress and phosphorylate eIF2. This leads to the inhibition of translation initiation, the disassembly of polysomes, and the phase separation of mRNas and RNA binding proteins into stress granules (SG). Here, the authors show that treatment with GTPP, a previously established activator of the UPRmt, activates the ISR and induces the formation of stress granules. Following induction of the ISR, cells become more resistant to SG formation. The authors pinpoint this resistance to GADD34 dephosphorylation of eIF2a. Finally, the authors show that SGs limit mitochondrial respiration. These findings demonstrate the importance of putting the breaks on the ISR. Throughout, the authors claim that there is a cross-talk between UPRmt and SG. This is unsubstantiated and unclear.

      Major:

      Link between UPRmt and stress granules:

      The authors claim a link between the UPRmt and stress granule formation based on the finding that the loss of ATF5 affects the expression of UPRmt markers, but not ISR markers. Yet, the authors actually show that GTPP-induced SGs form in a manner independent of ATF5 (Supp. Fig. 2). Thus, there is no data in the manuscript that substantiates this claim.

      PERK-mediated activation of the ISR.

      The authors claim that PERK mediates activation of the ISR following GTPP treatment. However, the experiments in Fig. 2E were done 1h after treatment. The authors in Fig. 1C nicely show that SG formation begins at 2h. Thus, it is possible that following a longer GTPP treatment (ie. >2h) the ISR is activated by different branches; for example the mitochondrial branch that is mediated by HRI. Thus, the authors should determine which kinase mediates ISR activation at the time point that SG formation is maximal.

      Role of SG-linked decrease in cellular adaptation to stress.

      The finding that SGs limit mitochondrial respiration is interesting. Presumably this promotes cellular adaptation to mitochondrial stresses. The authors should test whether G3BP1/2 DKO cells are more susceptible to death following longer GTPP treatments.

      Minor:

      Fig. 2C should be moved to supplemental as well as the data indicated the lack of ISR inhibition.

      Fig. 3A should have representative images of all conditions from Fig. 3B.

      IFAs in Fig. 3 and 4 are hard to interpret given both DAPI and G3BP1 are in shades of blue. Ideally, insets of a merged panel should show each individual panel.

      Significance

      The link between the UPRmt and SGs is interesting and would be an advance. However, the authors put forward data that indicates SGs form in an UPRmt (ATF5)- independent manner. An interesting aspect of this story for which there is data is that SGs limit mitochondrial function. This should be explored further (i.e. although it limits mitochondrial respiration, perhaps SGs protect mitochondria against chronic ISR stress).

      PeerReviewed
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    biorxiv.org/content/10.1101/2023.10.26.564187v1
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    Late killing of &lt;italic&gt; Plasmodium berghei &lt;/italic&gt; in the liver by an anti-circumsporozoite protein monoclonal antibody
    4
    1. EMBOpress 18 Jul 2024

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      Reply to the reviewers

      __Dear Reviewers, __

      We would like to thank you for the time and attention dedicated to reviewing our manuscript. We have taken all the questions and comments into consideration, which we believe have helped us to improve the paper.

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

      The study by Aguirre-Botero et al. shows the dynamics of 3D11 anti-CSP monoclonal antibody (mAb) mediated elimination of rodent malaria Plasmodium berghei (Pb) parasites in the liver. The authors show that the anti-CSP mAb could protect against intravenous (i.v.) Pb sporozoite challenge along with the cutaneous challenge, but requires higher concentration of antibody. Importantly, the study shows that the anti-CSP mAb not only affects sporozoite motility, sinusoidal extravasation, and cell invasion but also partially impairs the intracellular development inside the liver parenchyma, indicating a late effect of this antibody during liver stage development. While the study is interesting and conducted well, the only novel yet very important observation made in this manuscript is the effect of the anti-CSP mAb on liver stage development.

      Major This observation is highlighted in the manuscript title but is supported by only limited data. A such it needs to be substantiated and a mechanism should be investigated. The phenomenon of intracellular effects of the anti-CSP mAb should be analyzed in much more detail. For example, can the authors demonstrate uptake of the Ab together with the parasite during hepatocyte invasion? What cellular mechanism leads to elimination?

      Lines 234 - 243; 308 - 325: These results are the gist of the entire study and also defined the title of the manuscript. Thus, it would be pre-mature to claim the substantial effect of 3D11 antibody in late killing of the parasite in the infected hepatocytes just by looking at the decreased GFP fluorescence. The authors need to at least verify the fitness of the liver stages by measuring the size of the developing parasites as well as using different parasite specific markers (UIS4, MSP1, HSP70 etc.) in immunofluorescence assays on the infected liver sections and in vitro infections.

      Response

      We greatly appreciate the comments. We have taken the suggestions into consideration and will add data, perform as well as improve the text to clarify some key concepts. We hope that these changes will increase the impact of our results. We are adding extra data showing the percentage of UIS4+ intracellular parasites at 2, 4, and 44h in control and 3D11 groups. In addition, the effect of 2h incubation of sporozoites with 3D11 on the parasite size, GFP intensity and UIS4-staining at 44h post-infection was quantified. Briefly, the percentage of UIS4-negative intracellular parasites is significantly higher than the control, but not at 44h, indicating that part of the parasite clearance is due to the absence of UIS4 secretion that could be related to the neutralizing Ab effect or the inhibition of parasites during HepG2 cell traversal. At 44h, the in vitro data show that 3D11 only significantly decreases GFP intensity without affecting size and UIS4-staining. Since (i) the inhibition of invasion parallels parasite killing in the titration curve (Fig. 4A), (ii) the post-invasion parasite elimination occurs as early as 15h (Fig. 4C), (iii) the decrease in parasite GFP intensity occurs without a change in UIS4-staining and parasite size at 48h, and (iv) we cannot dissociate non-cytotoxic from cytotoxic 3D11 effects, we concluded for the moment that the 3D11 post-invasion “late effect” is probably due to mAb cytotoxicity, which is decreasing the SPZ fitness with measurable consequences in the percentage of surviving EEF and EEF GFP intensity. However, since we cannot exclude a non-cytotoxic effect of 3D11, which its cytotoxic activity could mask, we are addressing this question in another manuscript using hmAbs against PfCSP with different cytotoxicity levels.

      We will also test the potential post-invasion neutralizing effect of 3D11 in vitro. However, since the mAb does not affect the in vivo parasite growth from 24h to 44h, it is unlikely that it affects late intracellular development.

      ____Reviewer #1__ Minor comments __

      • Line 44 - 43: The statement is applicable only to the rodent infecting Plasmodium parasites. The authors need to clarify that.

      Responses

      This is an important clarification. We have modified the text that now reads:

      “The sporozoite surface is covered by a dense coat of the immunodominant circumsporozoite protein (CSP), shown to be an immunodominant protective antigen using a rodent malaria model”.

      • Line 68: Replace the second 'against' after the CSP with 'of'.

      It is done.

      • Line 141 - 143: The 3D11 mAb does affect the homing and killing in the blood of cutaneous injected sporozoites. The authors need to clearly state that the statement is true only for i.v. injected sporozoites.

      Thank you for the comment. Now the text reads “Altogether, these data indicate that 3D11 rather than having an early effect on i.v. inoculated sporozoites, e.g. in the homing or killing in the blood, requires more than 4 h to eliminate most parasites in the liver.”

      • Figure 3B: The numbers of sporozoites detected in the experiment varies from 0 h (line 172) to 2 h (line 184). Therefore, the numbers need to be mentioned on all the bars of each timepoint.

      This information was missing but now we have added the numbers to Figure 3B.

      • Figure 3C: If the authors have used flk1-GFP mice, then how well they were able to detect the Pb-PfCSP GFP parasites in the vessel vs. parenchyma in the intravital imaging? The representative images for Pb-PfCSP GFP should also be included.

      Since 3D11 does not target PbPf parasites most of them are motile in the movies, making them easily distinguishable from the endothelial cells. In addition, the stronger GFP intensity of sporozoites make them easily detectable in the sinusoids. Representative images were added in the supplementary figures (now Figure S3).

      • It is not mentioned anywhere how the viability of the sporozoites was determined. This has to be described especially in the methods section.

      • Also, the flow acquisition and data analysis of the sporozoites and infected HepG2 cells must be described in the method section.

      We briefly mentioned it in the results (line 228- 230): “In addition, by comparing the total number of recovered GFP+ sporozoites at 2 h in the two studied conditions, we measured the early lethality (%viable sporozoites, Figure 4B) of the anti-CSP Ab on the extracellular forms of the parasite (Figure 4A).”

      A more detailed description has been added in the methods section that now reads:

      “After 2 h, the supernatant and the trypsinized cells were analyzed by flow cytometry to quantify the amount of GFP+ events inside and outside the cells. Viability was then quantified by adding the total number of sporozoites (GPF+ events) in the supernatant, inside and outside the cells. We calculated the percentage viability by comparing the average of the total number of sporozoites in the treated samples to the average in controls using three technical replicates in each condition. Additionally, we quantify the percentage of infected cells using the total number of GFP+ events in the HepG2 gate (Figure S4). To compare the biological replicates, we further normalized to the control of each experiment. For the samples used to analyze parasite development, the cells were incubated for 15 or 44 h after sporozoite addition, and the medium was changed after 2 and 24 h. The cells were trypsinized and the percentage of intracellular parasites was determined by flow cytometry as described above (Figure S4). The prolonged effect between 2 h - 15/44 h was calculated by normalizing to the percentage of infected cells at 2 h.”

      • Figure 4: The flow layouts should be included for at least comparing the 0 vs. 5 μg/ml of 3D11 mAb concentrations.

      Flow layouts were added in the supplementary figures.

      • Line 651 (Figure S1 legend): Typographical error '14'.

      Thank you for noticing. We corrected it.

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

      Aguirre-Botero and collaborators report on the dynamics of Plasmodium parasite elimination in the liver using the 3D11 anti-CSP monoclonal antibody (mAb). By using microscopy and bioluminescence imaging in the P. berghei rodent malaria model, the authors first demonstrate that higher antibody concentrations are required for protection against intravenous sporozoite challenge, when compared to cutaneous challenge, which is not surprising. The study also shows that the 3D11 mAb reduces sporozoite motility, impairs hepatic sinusoidal barrier crossing, and more relevantly inhibits intracellular development of liver stages through its cytotoxic activity. These findings highlight the role of this specific monoclonal antibody, 3D11 mAb against CSP, in targeting sporozoites in the liver.


      Major Comments

      The study provides valuable insights into the mechanisms of protection conferred by the 3D11 anti-CSP monoclonal antibody against P. berghei sporozoites and this finding allow the field to speculate that other monoclonal antibodies against CSP of P. Falciparum may act similarly. However, an important experiment is missing that would significantly strengthen the conclusions. Specifically, the authors should perform experiments where the monoclonal antibody is added immediately after the sporozoites have completed invasion. This should be done both in vitro and in vivo to show whether the antibody has any effect on intracellular development of liver stages when added after invasion.

      While the claims are generally supported by the data presented, to comprehensively conclude the late cytotoxic effects of 3D11, the additional experiment of post-invasion antibody application is relevant. This would help determine if the observed effects are due to the antibody's action during invasion or its continued action post-invasion.

      The data and methods are presented in a manner that allows for reproducibility. The use of microscopy and bioluminescence imaging is well-documented. The experiments appear adequately replicated, and statistical analyses are appropriate.

      Response

      We thank reviewer 2 for important suggestions. To be sure that the effect might not come from the internalization of the antibodies after sporozoite invasion, we will test the potential post-invasion neutralizing effect of 3D11 in vitro. However, since the mAb does not affect the in vivo parasite growth from 24h to 44h, it is unlikely that it affects late intracellular development.

      Indeed, it is important to corroborate this effect might have a different effect using antibodies targeting P. falciparum CSP. That is why we are working in parallel with anti-PfCSP antibodies, but these data will be included in a different manuscript.

      __Reviewer #2 ____Minor Comments __

      • The text and figures are clear and accurate. Some minor typographical errors should be corrected.

      Thank you for the remark, we have worked on that and hope that the text reads better now.

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

      Aguirre-Botero et al have studied the effect of a potent monoclonal antibody against the circumsporozoite protein, the major surface protein of the malaria sporozoite. This is an elegantly designed, performed, and analyzed study. They have efficiently delineated the mode of action of anti-CSP repeat mAb and confirmed previous in vitro work (not cited) that demonstrated the same intracellular effect. Specific comments :

      • Line 51: The authors claim a correlation between high antibody levels and protection. However, they did not provide direct proof that these antibodies were responsible for protection, nor did they establish a cut-off level of anti-CSP antibodies that would distinguish between protected and unprotected individuals.

      We would first like to thank reviewer 3 for the comments. Indeed, we agree with reviewer 3, these are correlative studies where the causality cannot be established. We modified the ensuing sentence to specify the causality between anti-CSP mAbs and in vivo protection against sporozoite infection. Now the text reads: “Extensive research has demonstrated a positive correlation between high levels of anti-CSP antibodies (Abs) induced by the RTS,S/AS01 vaccine and its efficacy against malaria 11–13. Remarkably, anti-CSP monoclonal Abs (mAbs) have been proven to protect in vivo against malaria in various experimental settings, including, mice 14–21, monkeys 23, and humans 24–26”

      • Line 326: The late intrahepatic effect of mAb against the CSP repeat has been previously reported (see Figure 2, Nudelman et al, J Immunol, 1989). The effect was shown to affect the transition from liver trophozoites to liver schizonts. This study should be cited and discussed.

      Thank you for the remark. Now the text reads: Notably, a similar effect has been previously reported using sera from mice immunized with PfCSP or mAb against P. yoelii (Py) CSP. Incubation of Pf or Py sporozoites with the immune sera or mAbs not only affected sporozoite invasion in vitro but continued to affect intracellular forms for several days after invasion38,39. Additionally, using anti-PfCSP sera, it was also observed that late EEFs from sera-treated sporozoites had abnormal morphology38. Altogether, it was thus concluded that the anti-CSP Abs present in the sera had a long-term effect on the parasites38,39.

      PeerReviewed
    2. EMBOpress 18 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Aguirre-Botero et al have studied the effect of a potent monoclonal antibody against the circumsporozoite protein, the major surface protein of the malaria sporozoite. This is an elegantly designed, performed, and analyzed study. They have efficiently delineated the mode of action of anti-CSP repeat mAb and confirmed previous in vitro work (not cited) that demonstrated the same intracellular effect.

      Specific comments

      Line 51: The authors claim a correlation between high antibody levels and protection. However, they did not provide direct proof that these antibodies were responsible for protection, nor did they establish a cut-off level of anti-CSP antibodies that would distinguish between protected and unprotected individuals.

      Lone 326: The late intrahepatic effect of mAb against the CSP repeat has been previously reported (see Figure 2, Nudelman et al, J Immunol, 1989). The effect was shown to affect the transition from liver trophozoites to liver schizonts. This study should be cited and discussed.

      Significance

      A well-done study that elucidates the mechanisms of a protective monoclonal antibody against malaria sporozoites. These data are important and will interest a large audience of researchers working in infectious diseases and immunology.

      PeerReviewed
    3. EMBOpress 18 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Aguirre-Botero and collaborators report on the dynamics of Plasmodium parasite elimination in the liver using the 3D11 anti-CSP monoclonal antibody (mAb). By using microscopy and bioluminescence imaging in the P. berghei rodent malaria model, the authors first demonstrate that higher antibody concentrations are required for protection against intravenous sporozoite challenge, when compared to cutaneous challenge, which is not surprising. The study also shows that the 3D11 mAb reduces sporozoite motility, impairs hepatic sinusoidal barrier crossing, and more relevantly inhibits intracellular development of liver stages through its cytotoxic activity. These findings highlight the role of this specific monoclonal antibody, 3D11 mAb against CSP, in targeting sporozoites in the liver.


      Major Comments

      The study provides valuable insights into the mechanisms of protection conferred by the 3D11 anti-CSP monoclonal antibody against P. berghei sporozoites and this finding allow the field to speculate that other monoclonal antibodies against CSP of P. Falciparum may act similarly. However, an important experiment is missing that would significantly strengthen the conclusions. Specifically, the authors should perform experiments where the monoclonal antibody is added immediately after the sporozoites have completed invasion. This should be done both in vitro and in vivo to show whether the antibody has any effect on intracellular development of liver stages when added after invasion.

      While the claims are generally supported by the data presented, to comprehensively conclude the late cytotoxic effects of 3D11, the additional experiment of post-invasion antibody application is relevant. This would help determine if the observed effects are due to the antibody's action during invasion or its continued action post-invasion.

      The data and methods are presented in a manner that allows for reproducibility. The use of microscopy and bioluminescence imaging is well-documented. The experiments appear adequately replicated, and statistical analyses are appropriate.

      Minor Comments

      The text and figures are clear and accurate. Some minor typographical errors should be corrected.

      Significance

      The study's strengths lie in its detailed analysis of the 3D11 mAb's effect on sporozoite motility and liver stage development. The use of advanced imaging techniques adds robustness to the findings. The main limitation is the lack of data on the antibody's effect post-invasion. Additionally, the study's conclusions are based on a single monoclonal antibody and its target region, which may not be representative of other anti-CSP antibodies. Still, the findings offer insights into the cytotoxic action of anti-CSP antibodies, which could inform the development of more effective malaria vaccines and therapeutic antibodies.

      This research will primarily interest a specialized audience in malaria research, particularly those focused on vaccine development and antibody therapeutics. It also holds value for broader audiences in immunology and infectious disease research.

      My expertise: Malaria research and liver invasion by Plasmodium sporozoites

      PeerReviewed
    4. EMBOpress 18 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      The study by Aguirre-Botero et al. shows the dynamics of 3D11 anti-CSP monoclonal antibody (mAb) mediated elimination of rodent malaria Plasmodium berghei (Pb) parasites in the liver. The authors show that the anti-CSP mAb could protect against intravenous (i.v.) Pb sporozoite challenge along with the cutaneous challenge, but requires higher concentration of antibody. Importantly, the study shows that the anti-CSP mAb not only affects sporozoite motility, sinusoidal extravasation, and cell invasion but also partially impairs the intracellular development inside the liver parenchyma, indicating a late effect of this antibody during liver stage development. While the study is interesting and conducted well, the only novel yet very important observation made in this manuscript is the effect of the anti-CSP mAb on liver stage development.

      Major

      This observation is highlighted in the manuscript title but is supported by only limited data. A such it needs to be substantiated and a mechanism should be investigated.

      • The phenomenon of intracellular effects of the anti-CSP mAb should be analyzed in much more detail. For example, can the authors demonstrate uptake of the Ab together with the parasite during hepatocyte invasion? What cellular mechanism leads to elimination?

      Minor

      • Line 44 - 43: The statement is applicable only to the rodent infecting Plasmodium parasites. The authors need to clarify that.
      • Line 68: Replace the second 'against' after the CSP with 'of'.
      • Line 141 - 143: The 3D11 mAb does affect the homing and killing in the blood of cutaneous injected sporozoites. The authors need to clearly state that the statement is true only for i.v. injected sporozoites.
      • Figure 3B: The numbers of sporozoites detected in the experiment varies from 0 h (line 172) to 2 h (line 184). Therefore, the numbers need to be mentioned on all the bars of each timepoint.
      • Figure 3C: If the authors have used flk1-GFP mice, then how well they were able to detect the Pb-PfCSP GFP parasites in the vessel vs. parenchyma in the intravital imaging? The representative images for Pb-PfCSP GFP should also be included.
      • It is not mentioned anywhere how the viability of the sporozoites was determined. This has to be described especially in the methods section.
      • Also, the flow acquisition and data analysis of the sporozoites and infected HepG2 cells must be described in the method section.
      • Figure 4: The flow layouts should be included for at least comparing the 0 vs. 5 μg/ml of 3D11 mAb concentrations.
      • Lines 234 - 243; 308 - 325: These results are the gist of the entire study and also defined the title of the manuscript. Thus, it would be pre-mature to claim the substantial effect of 3D11 antibody in late killing of the parasite in the infected hepatocytes just by looking at the decreased GFP fluorescence. The authors need to at least verify the fitness of the liver stages by measuring the size of the developing parasites as well as using different parasite specific markers (UIS4, MSP1, HSP70 etc.) in immunofluorescence assays on the infected liver sections and in vitro infections.
      • Line 651 (Figure S1 legend): Typographical error '14'.

      Significance

      The phenomenon of intracellular effects of the anti-CSP Ab is the only novel observation and as such, should be analyzed in much more detail. For example, can the authors demonstrate uptake of the Ab together with the parasite during hepatocyte invasion? What cellular mechanism leads to elimination?

      PeerReviewed
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    RBM39 shapes innate immunity through transcriptional and splicing control of key factors of the interferon response
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    1. EMBOpress 18 Jul 2024

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

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      Reply to the reviewers

      1. General Statements

      We are grateful for the valuable, constructive comments of the reviewers, which helped to substantially improve the quality of our manuscript. We particularly agree that the original structure of the manuscript was confusing and in parts misleading, since we followed the history of the project, which first identified the RBM39 mediated impact on IRF3 expression, whereas the -omics studies, identifying additional factors, were done at a far later point. Many discrepancies further arose from the low sensitivity of our initial proteomics analysis, which we now repeated, thereby obtaining far more sensitive detection of the key factors we also found in the transcriptomics data.

      We have re-structured the entire manuscript by moving the -omics data from the end of the paper towards the middle and provide similar depth downstream analysis of all relevant key factors identified (RIG-I/MDA5, IFN receptors, STAT1/2), to reduce the focus on IRF3, as suggested. We further changed the title and abstract to reflect this major conceptual change. Thanks to this helpful comment, we think that our manuscript is now conceptually much clearer.

      We further added new data to support the central claims of our manuscript, including a repetition of the proteomics study. Proteomics and transcriptomics now consistently demonstrate the impact of RMB39 knockdown as well as indisulam treatment on several key factors of innate immunity, including IRF3, STAT1/2, RIG-I and MDA5 (now in Fig. 5), with IFNAR2 and IL10RB additionally found in transcriptomics. We provide additional functional evidence that IRF3 is the key factor affected in the TLR3 pathway (IRF3 overexpression, Fig. 6B, C), whereas diminished abundance of RIG-I/MAD5 is equally important in the respective pathway, thereby also affecting NF-κB response (Fig. 6F-I). We further show the functional significance of IFN-receptor/STAT downregulation on type I and III IFN responses (Fig. 7E-G).

      The reviewers also pointed to some datasets showing the expected trends, but in some cases lacking statistical significance, due to variability in knockdown efficiency. We repeated all mentioned datasets with new batches of siRNA with sufficient biological replicates (n=3). We thereby obtained consistent, statistically significant data in all cases. Importantly, all experiments implementing the RMB39.esc control now show consistent rescue (Fig2. A-E).

      To generate a homogenous experimental design for virus infections, we further added new data showing a comparable impact of siRNA knockdown (Fig. 3F) and indisulam treatment (new Fig. 3G) on Sendai virus infection in A549 cells and took this as a rationale to consistently use indisulam for all other infections.

      2. Point-by-point description of the revisions

      __Reviewer #1 (Evidence, reproducibility and clarity (Required)): __ This manuscript by Li and colleagues examines the role of RBM39 in innate immune signaling. Splicing factor RBM39 was identified through a genome wide screen with a death reporter under control of the IFIT1 promoter that got stimulated with pIC in a TLR3-dependent manner. Besides IFIT1, further experiments showed that RBM39 is also involved in optimal expression of other innate immunity genes like IFNB, CXCL10, RIG-I or MDA5. While NFkB-dependent genes seem not to depend on RBM39, for IRF3 it was shown that protein levels decrease under conditions of RBM39 depletion, because IRF3 mRNAs are (slightly) reduced and spliced differently. The sulfonamid Indisulam could largely recapitulate the phenotype of RBM39 depletion. Further analyses using proteomics and transcriptomics showed that RBM39 is required for mRNA splicing and expression of a large set of other proteins. Altogether, this well designed and written study highlights the fundamental role played by RBM39 in in maintaining the pathways of immunity and metabolism. The key conclusions are convincing but some additional experiments would strengthen them further.

      We are grateful for the very positive general comments of this reviewer.

      Major comments: - For the statistics, authors seem not to have done multiple tests but rather tested individual datasets within larger graphs against each other. Please explain where this is the case and use corrections if multiple testing was done

      We apologize for not have been clearer here, we indeed used multiple testing. In the proteomics, statistical significance was evaluated by "two-sample tests" (Student's T-test with permutation-based FDR 0.05 and 250 number of randomizations). For the analysis of RNAseq data, p values were calculated with the Wald test and corrected for multiple testing according to Benjamini-Hochberg. We have now included this information in the materials and methods section and in the respective figure legends.

      • Fig. 4 shows that RBM39 depletion reduces IFIT expression in virus infected cells and slightly increases virus replication. RBM39 has a major effect on IRF3 levels, but also on other players in innate immunity. What happens if IRF3 is ectopically expressed as in figure 5? With this experiment one could measure how high the contribution of IRF3 miss-splicing is to innate immunity.

      We thank this reviewer for the valuable suggestion. We restructured the entire manuscript, to address several reviewer comments regarding the focus on IRF3 and the lack of data on other factors in the pathway. We now clearly demonstrate that ectopic IRF3 expression entirely rescues the TLR3 response to poly(I:C) in PH5CH cells (Fig. 6B-C), which also explains the lack of impact on the NF-κB pathway (Fig. 2G-H). In contrast, overexpression of IRF3 does not rescue the RIG-I/MDA5 response in A549 cells (new data, Fig. 6F-I). Here, also the NF-κB pathway is affected by knockdown of RBM39, suggesting that reduced RIG-I/MDA5 abundance upon RMB39 knockdown substantially contributed to the diminished innate immune response.

      • Fig. 4 A uses siRNAs but B, C and D only indisulam treatment. It would be better if siRNAs would also be used for the other viruses.

      We agree that a homogenous setup for virus infection would be favorable, however, the use of different cell lines was authorative due to limited permissivess of the used cell types towards virus infection and it appeared challenging to achieve similar knockdown efficiencies. To generate a homogenous experimental design, we now added new data showing a comparable impact of siRNA knockdown (Fig. 3F) and indisulam treatment (new Fig. 3G) on Sendai virus infection in A549 cells and took this as a rationale to consistently use indisulam for all other infections.

      • RBM39 depletion strongly reduces IRF3 levels in the WB, but not so much in RT-PCR and not at all in proteomics. Is the antibody used for WB perhaps recognizing a domain that is underrepresented in isoforms after disturbed splicing? Please clarify.

      Our previous proteomics data suffered from a very low sensitivity, therefore we missed clear detection of many factors, including IRF3. We repeated the whole proteomics analysis with siRNA and indisulam treatment (new Fig. 5A, B) and now found significantly reduced IRF3 protein levels in both conditions (new Fig. S5C), in agreement with the WB data. The lower impact on IRF3 mRNA abundance is due to the additional contribution of alternative splicing (Fig. 6A, Fig. S6A-D), which both in combination affect protein abundance.

      • Volcano plots in figure 7 show a lot of hits obtained after both RBM38 siRNA and indisulam (green dots), and some that are additionally identified in transcriptomes and in proteomes (red dots). Nonetheless only innate immunity and stress response genes are marked, although they do not belong to these highly conserved classes. Please elaborate more on the most RBM39-dependent genes, e.g. by presenting them in a heat map.

      To our knowledge, our study is the first with a comprehensive comparison on the impact of RBM39 knockdown and indisulam treatment on the host cell proteome and transcriptome. However, several studies already did -omics studies on individual conditions/readouts (e.g. (Coomar et al, 2023; Dou et al, 2023; Mai et al, 2016; Nijhuis et al, 2022)). These studies already identified and described in detail key changes in transcriptome and proteome e.g. affecting genes involved in cell cycle control and metabolism, which we find as well. However, the novelty of our paper is the impact on innate immune response, we therefore rather decided to put an even stronger focus on these genes and to omit other factors, like stress response pathway components, etc.. This strategy is supported by the higher sensitivity of our new proteome analysis, which now generated a far better overlap with the transcriptomics, favoring a display setting on highlighting only those factors that were further analyzed in detail in the volcano blots (Fig. 5). Still, interested readers will find the comprehensive list of data in the supplementary Excel-datasheets as well as in our primary data in online depositories.

      Minor comments: - Some abbreviations are not explained, like PGK, siNT, siVTN

      We apologize and have added the missing explanation of abbreviations.

      • Welsch should read Welch

      Corrected.

      • Fig. 2H: were cells also stimulated and if yes, how?

      These were unstimulated conditions, to show the impact of RBM39 on basal expression of the IFNlambda receptor chains. However, we deleted this dataset due to the re-organisation of the manuscript. The analysis of the type I and type III receptor and STAT1/2 expression is now comprehensively shown in Fig. 7/S6E, F, solely based on the transcriptomic data for consistency reasons, along with the functional impact on the IFN response.

      • Fig. 6E: I cannot see a difference between to IRF3-203 and 228 isoforms. And what are the white boxes?

      • Also 6E: Location of the primers is barely visible

      Due to the re-organization of the manuscript these data are now shown in Fig. S6D. Both isoforms are indeed very similar and only differ by a very small (16nt) additional exon in isoform 228. The white boxes are exons not translated in the respective isoforms. We have included this important information in the legend to Fig. S6 and increased the arrows indicating the positions of the primer.

      • Some materials are not properly referenced, like the death reporter, the lentiviral system, or the Rift Valley fever luciferase virus

      We are sorry for the missing information, which has now been added to the materials and methods section.

      • Supplement has no page numbers

      We have added page numbers to the supplementary information.

      Reviewer #1 (Significance (Required)):

      The study advances our knowledge about the regulation of innate immunity. Strengths are the discovery of a novel layer of innate immunity regulation by splicing and the in-depth analysis of the importance of RBM39 for cellular gene expression. A potential weakness might be the focus on innate immunity as other biological functions seem even more dependent on RBM39. However, this reviewer sees the necessity that covering all aspects of RBM39 finction would be beyond the scope of a single study. The relevant literature is appropriately cited (except for some materials, see minor comments). Results will be of interest not only to people doing basic research on innate immunity, but also to those interested in gene regulation in general or to cancer researchers using indisulam

      __Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ The authors performed a CRISPR-based screen for genes required for TLR3-mediated signaling and gene expression in Hepatoma cells. Interferon-stimulated expression of an apoptosis inducer was used as a read-out system. A number of candidate genes were identified and one of these, RBM39, investigated in detail. The protein has previously been linked to both transcriptional control and RNA processing. Validation studies confirm that reduction of cellular RBM39 results in less TLR3-mediated IFN-beta synthesis and lower levels of ISG mRNA synthesis. Initial studies suggest a role of RBM39 in regulating of IRF3 levels, the transcription factor activated by TLR3 signaling to induce IFN-beta synthesis. However, the effect is variable and poorly supported by transcriptomic and proteomic data. Moreover, only one out of four cell-based viral infection models reports a substantial effect of the RBM39 knockdown.

      We apologize for the lack of consistency among several datasets, which was mainly due to the low sensitivity of the proteomic analysis. This has been repeated and now fully confirms all other data. In part due to the comments of this reviewer, we further broadened the scope of the manuscript away from IRF3, including a change of the title.

      Major comments:

      1. The data do not support the claim that RBM39 is a broadly acting player in innate immune responses. In addition, they suggest that IRF3 may not be the only relevant RBM39 target. The most informative knockdown control in this regard would be IRF3 siRNA.

      We have re-structured the entire manuscript and added new data to support the central claims of our manuscript, including a repetition of the proteomics study. Proteomics and transcriptomics now consistently demonstrate the impact of RMB39 knockdown as well as indisulam treatment on several key factors of innate immunity, including IRF3, STAT1/2, RIG-I and MDA5 (now in Fig. 5), with IFNAR2 and IL10RB additionally found in transcriptomics. We further provide functional evidence that IRF3 is the key factor affected in the TLR3 pathway (IRF3 overexpression, Fig. 6B, C), whereas diminished abundance of RIG-I/MAD5 is equally important in the respective pathway, thereby also affecting NF-κB response (Fig. 6F-I). We further show the functional significance of IFN-receptor/STAT downregulation on type I and III IFN responses (Fig. 7E-G). We hope this reviewer now agrees with our claim that RBM39 is a broadly acting player in innate immune responses.

      1. The structure of the manuscript is rather confusing because IRF3 is presented as the main RBM39 target in figures 3-6, but the -omics data in figures 7 and 8 do not support this view. The authors argue different sensitivities of the experimental approaches, but I think few people would agree that western blots are more sensitive than MS. To my opinion a narrative with less focus on IRF3 and a broader integration of candidates of the -omics approaches would be preferable.

      We are grateful for this valuable comment and fully agree that the original structure of the manuscript was confusing and in parts misleading, which was mainly due to the fact that we followed the history of the project, which first identified the RBM39 mediated impact on IRF3 expression, whereas the -omics studies, identifying additional factors, were done at a far later point. Many discrepancies further arose from the low sensitivity of our proteomics analysis, which we now repeated, thereby obtaining far more sensitive detection of the key factors we also found in the transcriptomics data. We now moved the -omics data from the end of the paper towards the middle and provide similar depth downstream analysis of all relevant key factors identified (RIG-I/MDA5, IFN receptors, STAT1/2, to reduce the focus on IRF3, as suggested. We further changed the title and abstract to reflect this major conceptual change. Thanks to this helpful comment, we think that our manuscript is now conceptually much clearer.

      Investigating the role of RBM39 by RNA-seq in pIC-treated cells would further strengthen the manuscript. It will yield a broader view of the protein's role in induced innate immunity.

      We did not add pIC treatment to the RNA-seq analysis, since, based on own experience and numerous papers, this will change the expression of literally thousands of genes. Based on the key factors of the pIC response modulated by RBM39 (RLRs and IRF3), this would very likely simply result in reduced induction of the whole ISG panel (as exemplified for IFIT1, ISG15, MxA and CXCL10 in Fig. 2B-E).

      3.The results in figures 6A-C are confusing for two reasons. First, the siRNA-mediated knockdown should result in reduced RBM39 protein as well (as shown in Fig. 3A) and, therefore, in an increase in RBM39 levels. Second, why was this effect not noted in the experiments shown in figs. 1-5? To avoid this confusion it might be good to mention which IRF3 splice isoforms are detected by the primers and antibodies used in these figures.

      Unfortunately, the reviewer seems to have conceptually misinterpreted Fig. 6A-C of the original paper, which did not show protein, but transcriptome data. We now added the corresponding data of the proteomic analysis in the new Fig. S5, for all detectable, relevant candidates, showing consistency to all previous data. The confusing point in previous Fig. 6B, which the reviewer appears to refer to, is the upregulation of RBM39 transcript levels upon indisulam treatment, which was not apparent in previous experiments, since we always used WB to show diminished RBM39 protein levels upon indisulam treatment. This increase in RBM39 mRNA is due to an autoregulation of RBM39 mRNA by protein abundance, which has been reported in literature (Campagne et al, 2023). Since this is rather confusing and not relevant for our study, we removed previous Fig. 6B and show this aspect only in the volcano blot in Fig. 5D, mentioning and citing the paper on autoregulation.

      Minor comments.

      1. Fig S1: the figure panels and legend are inconsistent. IFIT1 is labeled as ISG56 in panel S1A.

      We apologie for this inconsistency and now use IFIT1 throughout the paper.

      1. Data with the siRNA escape mutant of RBM39 are inconsistent. For example, why is its effect significantly different only in 1 out of 4 ISG in figures S2A-D?

      We apologize for the inconsistency, which is due to variability of silencing efficiency. We repeated the entire set of experiments (n=3) with a new batch of siRNA and obtained comparable, significant differences for all ISGs analyzed (new Fig. 2B-E).

      1. Line 164: the statement that TRIF and RBM39 siRNAs produce effects of similar magnitude is incorrect for the IFIT1 gene in figure S2A.

      This experiment was repeated (see previous point), now obtaining significant, more homogenous data. We have modified the text accordingly.

      4.Fig. 2H: In absence of additional evidence for functional implications, the data showing reduced IL10RB expression should be omitted.

      We omitted the data, as suggested by the reviewer, however, we provide a more in depth analysis of the type I and III IFN response in Fig. 7, based on the transcriptomic data and a functional analysis.

      5.Fig. 3: More datapoints would be needed in panel A to sustain the lack of significant difference between the untreated and escape mutant samples. Are the viability data in panels B and C normalized to untreated cells to control for Indisulam toxicity? In figure S3A the effect of the mutant is rather small. To allow for comparison, the Indisulam titration curves should be adapted to the concentrations used in Fig. 3.

      Fig. 3 (now Fig. 4) was replaced by another representative experiment, now also containing the quantification of the shown western blots, however, the statistical analysis shown in the previous version was and is based on three independent biological replicates, as indicated in the figure legend. Viability data was normalized to controls and this information is now added to the figure lengend as well. The mutant analyzed in Fig. S3A (now S4A) confers only partial resistance, which explains the limited but clear rescue. We did not include higher indisulam concentrations here due to the increased cytotoxicity of concentration above 5 µM in PH5CH, in the absence of pronounced additional effects on RBM39 abundance (Fig. 4B).

      6.RNA-seq measures steady-state RNA, not transcription.

      This is of course correct, we changed all sentences, where our wording might have indicated that we are measuring transcription by RNAseq. However, we still need to differentiate between the role of RBM39 in transcriptional regulation and splicing, where changes in RNA abundance found in RNAseq rather point to transcriptional regulation.

      Reviewer #2 (Significance (Required)):

      The identification of RBM39 as a candidate player in innate immune responses is of interest to a large scientific community with interest in signalling by pattern recognition receptors. Its role should be strengthened with additional infection models. It is puzzling that three out of four viruses don't benefit from the reduced IFN-beta synthesis in the RBM39 knockdown. Moreover, the data are not convincing (or too diverse) to nail down IRF3 as a major, or the most relevant, RBM39 target.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __ CRISPR Screen for factors that are required for dsRNA-dependent ISG production. Found a large number of hits but most did not validate in subsequent assays. The authors follow up the one candidate that did pass secondary screening criteria, RBM39, although re-expression of RBM39 only rescues the phenotype of the siRNAs against RBM39 (siRBM39) in one of the two cell lines tested. Additionally, siRBM39 impacts only a subset of polyIC-induced ISGs and does not regulate NFkB-driven gene expression. They go on to attempt to investigate the impact of siRBM39 on other key innate immune genes and proteins, although many key controls and appropriate methods are missing.

      We thank this reviewer for pointing at inconsistencies and missing controls in our manuscript. We have critically re-evaluated the respective datasets.

      Major comments: 1) The authors propose some rationale for the limited success of the screen, however, while RBM39 may have a role in dsRNA-induced innate immunity, in general the screen seems to have limited value.

      The aim of our CRISPR/Cas9 death reporter screen was the identification of so far unknown contributors to innate immune response. This was achieved by identifying a critical role of RBM39, followed by an in depth validation focusing on RBM39. We further found known components of the TLR3 pathway in our candidate list (e.g. TRIF and UNC93B1), pointing to the overall quality of the experimental setup. At no point of the manuscript we claim that our screen aimed for or delivered a comprehensive overview on innate immunity pathways. Honestly, no comparable screen (e.g. on cytopathic viruses) has delivered such data.

      2) Given that the siRBM39 clearly has off-target effects (since expression of a resistant RBM39 cDNA only gives limited rescue in many cases - Fig S2), each of the experiments in which siRBM39 is used (i.e. Fig 2) should have the RBM39.esc control - especially those that drive subsequent experiments such as the expression of IFNbeta and IFNLR1 (Fig 2a, h)

      The inconsistency in some datasets, showing all the same trends, but in some cases lacking statistical significance was due to variability in knockdown efficiency. We repeated all mentioned datasets with new batches of siRNA with sufficient biological replicates (n=3) with now all of them revealing consistent, statistically significant data. Importantly, all experiments implementing the RMB39.esc control now show consistent rescue.

      3) Since RBM39 reduction has an apparent impact even if IFNLR1-deficient cells (although need the rescue control to know if this is real) the authors conclude that RBM39 regulates the initial wave of dsRNA signaling-events, but this should be tested with the use of Ruxilitinib to block JAK-STAT signaling.

      Due to the general major re-organization of the manuscript, aiming for a less confusing data presentation and consistency towards depth of candidate evaluation, we have removed the data on the IFNLR-deficient cell line. The claim that RBM39 affects the initial wave of ISG responses is based on reduced IFNb expression, which is exclusively induced by the initial wave of ISG response and by the general impact on ISG expression, which we measure at 6h after induction, too early for autocrine IFN stimulation (Burkart et al, 2023). However, we further demonstrate that downregulation of type I and type III IFN receptors in conjunction with STAT1/2 affect the type I and the type III IFN response as well (Fig. 7E-G, in part new data). Therefore, RBM39 affects both, the intial wave and the auto-/paracrine IFN response, and we therefore undertook no further efforts to separate these effects.

      4) IRF3 expression in the Indisulam-treated cells more closely tracks cell viability than RBM39 expression. For example in Fig 3C 10 microM gives 50% IRF3 expression and 50% viability but still 95% RBB39 expression - arguing that the impact of siRBM39 on IRF3 might be very indirect (and error bars on rescue are large so unclear if the rescue really worked in Fig 3A).

      Based on this reviewer comment we re-evaluated the quantification in previous Fig. 3C (now Fig. 4C), which combines data from three independent experiments. We deeply apologize, but the initial quantification proved to be wrong, due erroneous background subtraction, which was relatively high in one of the PHH-replicates (Replicate 1, see Reviewer Fig. 1 in uploaded file). The re-evaluated quantification revealed 55% for the RBM39 abundance at 10µM indisulam, which better reflects the data shown and is now in line with the impact on cytotoxicity and IRF3 abundance.

      5) It is unclear in Fig 4 why some cell/virus combinations are tested with siRBM39 and others are tested with Indisulam. Also the conclusion that RBM39 "substantially contributes to the cell intrinsic innate immune response to viral infections" is greatly overstated given that the differences are between ~3 fold and non-significant.

      We agree that a homogenous setup for virus infection would be favorable, however, the use of different cell lines was authoritave due to limited permissivess of the used cell types towards virus infection and it appeared challenging to achieve similar knockdown efficiencies. To generate a homogenous experimental design, we now added new data showing a comparable impact of siRNA knockdown (Fig. 3F) and indisulam treatment (new Fig. 3G) on Sendai virus infection in A549 cells and took this as a rationale to consistently use indisulam for all other infections. Overall, the aim of the virus infection experiments was using a variety of natural triggers of innate immunity beyond synthetic poly(I:C). Here we found indeed significant reductions of ISG induction for all viruses tested, similar to poly(I:C), this is the basis for the statement that RBM39 contributes the cell intrinsic innate immune response to viral infections. Our experimental design did not intend to see pronounced effects on viral replication, this was only measured to secure that reduced ISG induction was not due to inhibition of viral replication. We have explained this strategy now clearer and tuned down corresponding statements, to exclude potential overinterpretation of the data.

      6) Neither DTU/DRIMseq or qPCR are valid methods to measure splice isoform differences. The authors need to use rMATS or MAJIQ and validate by gel-based RT-PCR.

      Output generated by modern alignment algorithms like salmon is suitable for studies on an isoform level (Love et al, 2018) and has been used in a variety of studies (e.g.(Jabs et al, 2020; Xiong et al, 2023). MAJIQ and rMATS are only superior tools if the detection of so far unknown isoforms is of interest (Love et al., 2018), which is beyond the scope of this project. We have validated the data for IRF3 in RT-qPCR, showing close to identical results to the DTU analysis (compare Fig. 6A and S6D). We disagree that a gel-based RT-PCR analysis would be superior here, due to the lack of quantification.

      7) The conclusions from the proteomic and transcriptomic analyses should be treated with extreme caution given the caveats of methodology and controls discussed above.

      We are aware of the caveats of these technologies. The previous proteomic analysis indeed suffered from low sensitivity, failing to detect essential candidates like IRF3. The repetition of the experiment (new Fig. 5A, B, new Fig. S5) now revealed data very consistent with the transcriptomic data. Overall, the strength of our approach is the direct comparison of siRNA based RBM39 knockdown and RBM39 depletion by indisulam throughout transcriptomics and proteomics analyses. The wide overlap argues for the validity of our data and suggests that we thereby circumvented many caveats.

      Reviewer #3 (Significance (Required)):

      Innate immune signaling is a complex and essential pathway for maintaining health. While much is known about key components of this pathway, additional regulators are likely to exist. This manuscript describes an attempt to identify new regulators of dsRNA-mediated gene expression.

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      Mai S, Qu X, Li P, Ma Q, Cao C, Liu X (2016) Global regulation of alternative RNA splicing by the SR-rich protein RBM39. Biochim Biophys Acta 1859: 1014-1024

      Nijhuis A, Sikka A, Yogev O, Herendi L, Balcells C, Ma Y, Poon E, Eckold C, Valbuena GN, Xu Y et al (2022) Indisulam targets RNA splicing and metabolism to serve as a therapeutic strategy for high-risk neuroblastoma. Nat Commun 13: 1380

      Xiong L, Liu J, Han SY, Koppitch K, Guo JJ, Rommelfanger M, Miao Z, Gao F, Hallgrimsdottir IB, Pachter L et al (2023) Direct androgen receptor control of sexually dimorphic gene expression in the mammalian kidney. Dev Cell 58: 2338-2358 e2335

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    2. EMBOpress 18 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      CRISPR Screen for factors that are required for dsRNA-dependent ISG production. Found a large number of hits but most did not validate in subsequent assays. The authors follow up the one candidate that did pass secondary screening criteria, RBM39, although re-expression of RBM39 only rescues the phenotype of the siRNAs against RBM39 (siRBM39) in one of the two cell lines tested. Additionally, siRBM39 impacts only a subset of polyIC-induced ISGs and does not regulate NFkB-driven gene expression. They go on to attempt to investigate the impact of siRBM39 on other key innate immune genes and proteins, although many key controls and appropriate methods are missing.

      Major comments:

      1. The authors propose some rationale for the limited success of the screen, however, while RBM39 may have a role in dsRNA-induced innate immunity, in general the screen seems to have limited value.
      2. Given that the siRBM39 clearly has off-target effects (since expression of a resistant RBM39 cDNA only gives limited rescue in many cases - Fig S2), each of the experiments in which siRBM39 is used (i.e. Fig 2) should have the RBM39.esc control - especially those that drive subsequent experiments such as the expression of IFNbeta and IFNLR1 (Fig 2a, h)
      3. Since RBM39 reduction has an apparent impact even if IFNLR1-deficient cells (although need the rescue control to know if this is real) the authors conclude that RBM39 regulates the initial wave of dsRNA signaling-events, but this should be tested with the use of Ruxilitinib to block JAK-STAT signaling.
      4. IRF3 expression in the Indisulam-treated cells more closely tracks cell viability than RBM39 expression. For example in Fig 3C 10 microM gives 50% IRF3 expression and 50% viability but still 95% RBB39 expression - arguing that the impact of siRBM39 on IRF3 might be very indirect (and error bars on rescue are large so unclear if the rescue really worked in Fig 3A).
      5. It is unclear in Fig 4 why some cell/virus combinations are tested with siRBM39 and others are tested with Indisulam. Also the conclusion that RBM39 "substantially contributes to the cell intrinsic innate immune response to viral infections" is greatly overstated given that the differences are between ~3 fold and non-significant.
      6. Neither DTU/DRIMseq or qPCR are valid methods to measure splice isoform differences. The authors need to use rMATS or MAJIQ and validate by gel-based RT-PCR.
      7. The conclusions from the proteomic and transcriptomic analyses should be treated with extreme caution given the caveats of methodology and controls discussed above.

      Significance

      Innate immune signaling is a complex and essential pathway for maintaining health. While much is known about key components of this pathway, additional regulators are likely to exist. This manuscript describes an attempt to identify new regulators of dsRNA-mediated gene expression.

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    3. EMBOpress 18 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The authors performed a CRISPR-based screen for genes required for TLR3-mediated signaling and gene expression in Hepatoma cells. Interferon-stimulated expression of an apoptosis inducer was used as a read-out system. A number of candidate genes were identified and one of these, RBM39, investigated in detail. The protein has previously been linked to both transcriptional control and RNA processing. Validation studies confirm that reduction of cellular RBM39 results in less TLR3-mediated IFN-beta synthesis and lower levels of ISG mRNA synthesis. Initial studies suggest a role of RBM39 in regulating of IRF3 levels, the transcription factor activated by TLR3 signaling to induce IFN-beta synthesis. However, the effect is variable and poorly supported by transcriptomic and proteomic data. Moreover, only one out of four cell-based viral infection models reports a substantial effect of the RBM39 knockdown.

      Major comments:

      1. The data do not support the claim that RBM39 is a broadly acting player in innate immune responses. In addition, they suggest that IRF3 may not be the only relevant RBM39 target. The most informative knockdown control in this regard would be IRF3 siRNA.
      2. The structure of the manuscript is rather confusing because IRF3 is presented as the main RBM39 target in figures 3-6, but the -omics data in figures 7 and 8 do not support this view. The authors argue different sensitivities of the experimental approaches, but I think few people would agree that western blots are more sensitive than MS. To my opinion a narrative with less focus on IRF3 and a broader integration of candidates of the -omics approaches would be preferable. Investigating the role of RBM39 by RNA-seq in pIC-treated cells would further strengthen the manuscript. It will yield a broader view of the protein's role in induced innate immunity.
      3. The results in figures 6A-C are confusing for two reasons. First, the siRNA-mediated knockdown should result in reduced RBM39 protein as well (as shown in Fig. 3A) and, therefore, in an increase in RBM39 levels. Second, why was this effect not noted in the experiments shown in figs. 1-5? To avoid this confusion it might be good to mention which IRF3 splice isoforms are detected by the primers and antibodies used in these figures.

      Minor comments.

      1. Fig S1: the figure panels and legend are inconsistent. IFIT1 is labeled as ISG56 in panel S1A.
      2. Data with the siRNA escape mutant of RBM39 are inconsistent. For example, why is its effect significantly different only in 1 out of 4 ISG in figures S2A-D?
      3. Line 164: the statement that TRIF and RBM39 siRNAs produce effects of similar magnitude is incorrect for the IFIT1 gene in figure S2A.
      4. Fig. 2H: In absence of additional evidence for functional implications, the data showing reduced IL10RB expression should be omitted.
      5. Fig. 3: More datapoints would be needed in panel A to sustain the lack of significant difference between the untreated and escape mutant samples. Are the viability data in panels B and C normalized to untreated cells to control for Indisulam toxicity? In figure S3A the effect of the mutant is rather small. To allow for comparison, the Indisulam titration curves should be adapted to the concentrations used in Fig. 3.
      6. RNA-seq measures steady-state RNA, not transcription.

      Significance

      The identification of RBM39 as a candidate player in innate immune responses is of interest to a large scientific community with interest in signalling by pattern recognition receptors. Its role should be strengthened with additional infection models. It is puzzling that three out of four viruses don't benefit from the reduced IFN-beta synthesis in the RBM39 knockdown. Moreover, the data are not convincing (or too diverse) to nail down IRF3 as a major, or the most relevant, RBM39 target.

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    4. EMBOpress 18 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript by Li and colleagues examines the role of RBM39 in innate immune signaling. Splicing factor RBM39 was identified through a genome wide screen with a death reporter under control of the IFIT1 promoter that got stimulated with pIC in a TLR3-dependent manner. Besides IFIT1, further experiments showed that RBM39 is also involved in optimal expression of other innate immunity genes like IFNB, CXCL10, RIG-I or MDA5. While NFkB-dependent genes seem not to depend on RBM39, for IRF3 it was shown that protein levels decrease under conditions of RBM39 depletion, because IRF3 mRNAs are (slightly) reduced and spliced differently. The sulfonamid Indisulam could largely recapitulate the phenotype of RBM39 depletion. Further analyses using proteomics and transcriptomics showed that RBM39 is required for mRNA splicing and expression of a large set of other proteins.

      Altogether, this well designed and written study highlights the fundamental role played by RBM39 in in maintaining the pathways of immunity and metabolism. The key conclusions are convincing but some additional experiments would strengthen them further.

      Major comments:

      • For the statistics, authors seem not to have done multiple tests but rather tested individual datasets within larger graphs against each other. Please explain where this is the case and use corrections if multiple testing was done
      • Fig. 4 shows that RBM39 depletion reduces IFIT expression in virus infected cells and slightly increases virus replication. RBM39 has a major effect on IRF3 levels, but also on other players in innate immunity. What happens if IRF3 is ectopically expressed as in figure 5? With this experiment one could measure how high the contribution of IRF3 miss-splicing is to innate immunity.
      • Fig. 4 A uses siRNAs but B, C and D only indisulam treatment. It would be better if siRNAs would also be used for the other viruses.
      • RBM39 depletion strongly reduces IRF3 levels in the WB, but not so much in RT-PCR and not at all in proteomics. Is the antibody used for WB perhaps recognizing a domain that is underrepresented in isoforms after disturbed splicing? Please clarify.
      • Volcano plots in figure 7 show a lot of hits obtained after both RBM38 siRNA and indisulam (green dots), and some that are additionally identified in transcriptomes and in proteomes (red dots). Nonetheless only innate immunity and stress response genes are marked, although they do not belong to these highly conserved classes. Please elaborate more on the most RBM39-dependent genes, e.g. by presenting them in a heat map.

      Minor comments:

      • Some abbreviations are not explained, like PGK, siNT, siVTN
      • Welsch should read Welch
      • Fig. 2H: were cells also stimulated and if yes, how?
      • Fig. 6E: I cannot see a difference between to IRF3-203 and 228 isoforms. And what are the white boxes?
      • Also 6E: Location of the primers is barely visible
      • Some materials are not properly referenced, like the death reporter, the lentiviral system, or the Rift Valley fever luciferase virus
      • Supplement has no page numbers

      Significance

      The study advances our knowledge about the regulation of innate immunity. Strengths are the discovery of a novel layer of innate immunity regulation by splicing and the in-depth analysis of the importance of RBM39 for cellular gene expression. A potential weakness might be the focus on innate immunity as other biological functions seem even more dependent on RBM39. However, this reviewer sees the necessity that covering all aspects of RBM39 finction would be beyond the scope of a single study.

      The relevant literature is appropriately cited (except for some materials, see minor comments). Results will be of interest not only to people doing basic research on innate immunity, but also to those interested in gene regulation in general or to cancer researchers using indisulam

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    biorxiv.org/content/10.1101/2023.10.13.562221v2
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    Resistance to PSEN1-selective &#x03B3;-secretase inhibitors in T-cell acute lymphoblastic leukemia
    4
    1. EMBOpress 17 Jul 2024

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      Reply to the reviewers

      Reply to reviewers

      We thank the reviewers for their constructive comments. We appreciate the insights that they have shared. The comments were very helpful and will be addressed in the following sections

      Reviewer 1:

      As this field is very specific and this study may not have a broadened readership, it would benefit to add some more layers of complexity hence potential interest for Notch signaling in general and/or T-ALL pathology: e.g. do the induced mutated cell lines are more aggressive than the parental cell lines in vivo? How well do these PSEN1 mutated cell lines respond to other drugs like CB-103 (in vivo and in vitro), especially the cell lines where more Notch1 cleavage was observed

      Response to reviewer 1:

      • Reviewer 1 suggested to test the sensitivity of resistant T-ALL cell lines with PSEN1 mutations to other NOTCH inhibitors, such as CB-103. In response, we plan to assess the sensitivity of our DND-41 Cas9, HPB-ALL Cas9 and RPMI-8402 Cas9 cell lines (WT and PSEN1 mutants: 275(A>Y), 275(A>Y)+276(Q>E), 421_422(->ILS)) to CB-103 using a proliferation assay (ATPlite luminescence assay) in the coming weeks. These data will provide insight in the resistance profile and will determine if the mutations conferring resistance to the PSEN1-selective gamma-secretase inhibitor also confer resistance to other inhibitors that target NOTCH1 directly. We will incorporate this data in the manuscript once the experiments are completed.
      • Reviewer 1 was wondering whether the induced mutated T-ALL cell lines are more aggressive than the parental cell line in vivo. We did not observe a significant change in proliferation in vitro for the mutated cell lines after 10-day culture with DMSO compared to parental cell line (Fig. 3). As shown in Fig. 5, certain PSEN1 mutation can enhance affinity for the NOTCH1 substrate, thereby increasing the amount of cleaved NOTCH1. Here, we could hypothesize that these PSEN1 mutations could maybe lead to a more aggressive phenotype in patients. However, the focus of this article was to determine if PSEN1 mutations lead to MRK-560 resistance. Consequently, we believe that including these additional experiments would not significantly improve the study and animal experiments would not offer a major improvement.

      *Reviewer 2: *

      The study reports an important mechanism of resistance to THE MRK-560 inhibitor. The study might benefit from a few considerations: -Test the effect of the mutations in resistance using in vivo setting (xenograft model) -The authors should ideally introduce the mutations in patient samples and repeat some of the studies using this more relevant model. -"We identified 3 types of resistance mutations.": Could mutations in the control elements of the gene (that might affect gene expression) also lead to resistance to MRK-560? Please discuss.

      *Response to reviewer 2: *

      Reviewer 2 suggested discussing whether mutations in the control elements of the PSEN1 gene could also lead to MRK-560 resistance. In this paper, we focused on a specific resistance mechanism involving mutations in the target protein. However, the reviewer's point is valid. Therefore, we will add a new section in the discussion of the revised manuscript to explore other potential resistance mechanism to MRK-560 (PTEN deletion, PSEN2 upregulation). However, we do believe that alterations of PSEN1 expression will not be an important resistance mechanism: PSEN1 expression cannot be completely silenced because NOTCH1 cleavage is necessary for cell proliferation, and higher PSEN1 expression levels will not affect drug binding/affinity.

      *Reviewer 2 suggested validating the resistance mutations in vivo using cell line xenograft or patient-derived xenograft mouse models. Our study aimed to investigate if PSEN1 mutations could confer resistance to MRK-560. We demonstrated in 2 different cell models (mouse embryonic fibroblasts and T-ALL cell lines) that the identified PSEN1 mutations resulted in higher levels of cleaved NOTCH1 compared to WT cells following MRK-560 treatment, confirming resistance. Additionally, we validated the resistance mechanisms, including the direct disruption of the drug binding pocket, a well-established resistance mechanism observed in patients treated with other targeted therapies. While in vivo validation would likely confirm the in vitro findings, we believe it requires extensive resources and would add only a marginal value to the study. *

      *Reviewer 3: *

      • Major comments
      • The authors have limited their CRISPR mutant analysis to PS1 in this paper. The molecular studies are fine, but it is unclear whether such mutants can be generated by MRK560 treatment. To clarify the significance of these mutants in vivo, they should discuss whether the mutations identified in this study are observed in cancer patients or cultured cells treated with MRK560.
      • Many of the mutants examined are similar to familial Alzheimer's disease, such as those that increase Aβ42 production (Fig. 5F). Concerning this mechanism, we would appreciate the discussion on how to establish cancer treatment strategies for patients with familial Alzheimer's disease.
      • The analysis in this paper shows that mutations in a single PSEN1 allele are sufficient to acquire resistance to MRK560. On the other hand, since duplication of genes can occur in cancer cells, there is a possibility that cancer cells with multiple PSEN1 alleles or mutants with elevated PSEN1 expression (mutations in the promoter region) may arise. In such cases, we would like to see experimental evidence as to whether resistance to MRK560 is canceled or whether mutant PS1 is selectively incorporated into functional γ-secretase.*

      *Response to reviewer 3: *

      Reviewer 3 raised a valid concern regarding the use of MRK-560 in patients with pre-existing PSEN1 mutations, particularly those with familial Alzheimer's disease, who can also develop leukemia. This is a good comment, as these patients may exhibit primary resistance to PSEN1-selective inhibitors. Consequently, we will expand our discussion to address the possibility of primary resistance to MRK-560 due to inherent PSEN1 mutations.

      Reviewer 3 suggested to discuss whether the identified mutations could be acquired during MRK-560 treatment in cell lines and/or patients. Currently, no T-ALL patients have been treated with PSEN1-selective g-secretase inhibitors and hence, no data on PSEN1 mutations in patients is available (PSEN1 is also not screened at diagnosis of T-ALL patients). However, it is known that patients treated with other targeted drugs, such as imatinib (B-ALL patients) or IDH inhibitors (AML), acquired point mutations in the target gene/protein in response to treatment, leading to resistance.1,2,3,4 Here, we also demonstrated that mutations in PSEN1 can result in MRK-560 resistance, indicating a similar resistance mechanism to those previously described and further increasing the likelihood that PSEN1 mutations will arise in patients treated with PSEN1-selective g-secretase inhibitors. Predicting these resistance mutations offers the possibility to test already other inhibitors that can overcome or prevent such resistance.

      Reviewer 3 inquired about the impact of PSEN1 gene duplications on MRK-560 resistance. First, it is important to note that PSEN1 gene duplications are not observed in T-ALL patients. Additionally, PSEN1 mutations are predominantly heterozygous and dominant. Consequently, duplication of either WT or mutated PSEN1 allele is unlikely to influence resistance to MRK-560. We believe that investigating the effect of gene duplication on MRK-560 resistance is out of scope for this paper

      1Lyczek, A., Berger, B. T., Rangwala, A. M., et al. Mutation in Abl kinase with altered drug-binding kinetics indicates a novel mechanism of imatinib resistance. Proc. Natl. Acad. Sci. U. S. A. 2021; 118 (46);.

      2Melo, J. V. & Chuah, C. Resistance to imatinib mesylate in chronic myeloid leukaemia. Cancer Lett. 2007; 249 (2); 121-132

      3Issa, G. C. & DiNardo, C. D. Acute myeloid leukemia with IDH1 and IDH2 mutations: 2021 treatment algorithm. Blood Cancer J. 2021; 11 (107); 1-7.

      4Zhuang, X., Pei, H. Z., Li, T., et al. The Molecular Mechanisms of Resistance to IDH Inhibitors in Acute Myeloid Leukemia. Front. Oncol. 2022; 12 (931462);.

      • *

      • *

      • *

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    2. EMBOpress 17 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      In this paper, the authors comprehensively investigated the mechanism of resistance acquisition to MRK560, a PS1-specific γ-secretase inhibitor, in T-ALL cells by CRISPR screening. They found multiple mutants and explored their molecular mechanisms based on the 3D structure of γ-secretase. They found that the mutants can be classified into three groups: those that inhibit the binding of PSEN1 to the compound, those that inhibit the binding of PSEN1 to the substrate, and those that inhibit the binding of MRK560.

      Major comments

      1. The authors have limited their CRISPR mutant analysis to PS1 in this paper. The molecular studies are fine, but it is unclear whether such mutants can be generated by MRK560 treatment. To clarify the significance of these mutants in vivo, they should discuss whether the mutations identified in this study are observed in cancer patients or cultured cells treated with MRK560.
      2. Many of the mutants examined are similar to familial Alzheimer's disease, such as those that increase Aβ42 production (Fig. 5F). Concerning this mechanism, we would appreciate the discussion on how to establish cancer treatment strategies for patients with familial Alzheimer's disease.
      3. The analysis in this paper shows that mutations in a single PSEN1 allele are sufficient to acquire resistance to MRK560. On the other hand, since duplication of genes can occur in cancer cells, there is a possibility that cancer cells with multiple PSEN1 alleles or mutants with elevated PSEN1 expression (mutations in the promoter region) may arise. In such cases, we would like to see experimental evidence as to whether resistance to MRK560 is canceled or whether mutant PS1 is selectively incorporated into functional γ-secretase.

      Significance

      The results of this paper advance our understanding of the molecular mechanisms by which mutations in the PSEN1 gene may lead to the acquisition of γ-secretase inhibitor resistance in T-ALL treatment strategies. On the other hand, this study alone cannot be generalized to the development of T-ALL treatment strategies in terms of gene mutation acquisition in cancer cells, because mutations in the non-coding region of the PSEN1 gene and mutants of other γ-secretase components as well as PSEN1 can occur.

      Some of the mutations found have not been previously identified and provide new insights into our understanding of the mechanisms by which PSEN1 exerts its activity. However, the mutants obtained are based on structural analysis of the MRK560 complex PSEN1, which has already been analyzed and does not provide major advances in mechanistic insights of γ-secretase.

      Given that this paper is primarily a pharmacological analysis and is limited to γ-secretase and T-ALL, the intended audience for this paper is likely to be researchers involved in cancer-related research and pharmacological research.

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    3. EMBOpress 17 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The study reports an important mechanism of resistance to THE MRK-560 inhibitor. The study might benefit from a few considerations:

      • Test the effect of the mutations in resistance using in vivo setting (xenograft model)
      • The authors should ideally introduce the mutations in patient samples and repeat some of the studies using this more relevant model.
      • "We identified 3 types of resistance mutations.": Could mutations in the control elements of the gene (that might affect gene expression) also lead to resistance to MRK-560? Please discuss.

      Significance

      It is a well-designed study

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    4. EMBOpress 17 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript, Vandersmissen et al., performed a CRISPR-mediated mutagenesis screen to identify presenilin (PSEN1) mutations that could lead to the resistance of PSEN1-selective gamma-secretase inhibitors such as MRK-560, in T-ALL. In general, the manuscript is well-written, and the experiments performed do support their claims and are well done. The authors even went on to interrogate that the mutations that confer the drug resistance were located at the enzyme-substrate interface that caused a shift in relative binding affinities towards MRK-560 and/or substrate. Another resistance mechanism involved a mutation at the enzyme-substrate interface that hindered the entrance of MRK-560 to the binding pocket. This study is quite unusual in the sense that PSEN1 mutations that confer resistance to MRK-560 in T-ALL have yet to be reported, as far as this reviewer is aware. Hence, the authors created a potential problem that has yet to exist. Although cancers do develop resistance to drugs, whether naturally occurring MRK-560-resistant T-ALL samples would be the same as described in this study is unknown. Nevertheless, it is an interesting study and can set the foundation for future studies.

      Significance

      As this field is very specific and this study may not have a broadened readership, it would benefit to add some more layers of complexity hence potential interest for Notch signaling in general and/or T-ALL pathology: e.g. do the induced mutated cell lines are more aggressive than the parental cell lines in vivo? How well do these PSEN1 mutated cell lines respond to other drugs like CB-103 (in vivo and in vitro), especially the cell lines where more Notch1 cleavage was observed?

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    Multi-protein chimeric antigens, a novel combined approach for efficiently targeting and blocking the blood stage of Plasmodium falciparum
    4
    1. EMBOpress 17 Jul 2024

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      Reply to the reviewers

      #Reviewer 1 (Evidence, reproducibility and clarity):

      This manuscript by Deshmukh et al is aimed at generating chimeric antigens that can be useful for making next generation vaccines that block blood stage infection by malaria parasite. Given that there is no blood stage vaccine against malaria and available liver stage vaccine shows only limited efficacy that too only in Africa, there is dire need for having novel approaches to generate successful vaccines. In the past attempts have been made to make multivalent vaccines but have not been successful. Nevertheless, it is still a good option as single target blood-stage vaccines have failed. Authors propose to target cytoadhesion and host erythrocyte invasion. For this purpose, they have selected epitopes from PfEMP1/VarB family members, which poses a major challenge as at least 60 genes encode them and they exhibit variations which facilitate the escape from the immune system. The other two chimeras target invasion related proteins like MSPs and adhesins shed by micronemes and rhoptries, which are critical for invasion. The reported work is interesting and provides a useful approach towards developing vaccines against blood stage infection.

      We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.

      Comments:

      1. __ The peptides used in InvB chimera did not show good reactivity especially when compared to VarB or MSP peptides. Please discuss the possible reasons.__

      Response: Thank you for pointing out the difference in the explanation. With chimeric InvP, we see a strong response against a few peptides of SERA-5 and RH-5, while other peptides, in comparison, have lesser antibody responses. We have now included the following statement detailing this difference with possible explanations in the revised manuscript (Page 8, Line 25 to 30).

      The IgG responses to chimeric InvP were slightly different from those to chimeric varB and MSP. The intensity of IgG to peptides of SERA-5 and RH-5 was very high in comparison to the rest of the peptides used in the construct, whereas in chimeric varB and MSP, the IgG titers were comparable between the peptides. This could be a result of antigen exposure in the cohort of 19 patient samples that we used, and may change when a larger sample size is considered.

      __ It will be interesting to determine if blocking a specific VarB/PfEMP1 alters expression of other members. Based on the data provided in Fig. 4E, can a chimera be designed which only includes PfEMP1 that are represented well in HBEC-5i population?__

      Response: We agree that observing the altered expression of PfEMP1 would be an interesting phenomenon to study. The blocking of PfEMP1 using anti-chimeric varB antibodies is a transient process in our assays (just enough to quantify the cytoadhesion). It may take multiple cycles with negative selection pressure on parasites for the switching to take place. Also, it will be interesting to design chimeras based on the HBEC-5i binding PfEMP1. We can certainly plan these as prospective future experiments.

      __ Some of the invasion related proteins like RH5 and EBA175 are not present at parasite surface, instead, secreted from rhoptries and micronemes. It will be nice to perform Western blots on condition medium and see if InvP (or even MSP and VarB) antibodies recognizes the secreted version of these proteins.__

      Response: We thank the reviewer for this valuable comment and the suggestive experiment. We will perform a western blot on spent media and probe using anti-chimeric MSP and InvP antibodies to detect the proteins selected in chimeric MSP and InvP antigens.

      __ Fig. 6E- Statistics need to be provided for inhibition at 12.3 and 25ug.__

      Response: We apologize for the missed statistics. It is now included in the figure panel.

      __ Plasmodium uses multiple ligand-receptor interaction, which could depend (e.g. EBA-glycohophorins) or operate independent (e.g. RH5-basigin) of sialic acid. While there is representation from candidates from both of these families, most studies especially growth rate assays (Fig. 6E) have been carried using 3D7 strain, which does not require sialic acid. It is possible that if similar experiments were performed using sialic acid-sensitive strains, InvP and MSP antibodies may cause greater inhibition of parasite growth, which may be worth testing.__

      Response: We are grateful for the suggestion of using a sialic acid-dependent strain. Indeed, the pathway of reinvasion chosen by the parasite may determine the growth inhibition assay (GIA) outcome. We will perform the GIA assay on the Dd2 strain and 3D7 with neuraminidase treatment (Sialic acid-dependent invasion). We will also note the difference in growth inhibition potential of chimeric antibodies in sialic-acid dependent and independent pathways.

      __ The direct effect of InvP and MSP Abs should be tested directly on host erythrocyte invasion.__

      Response: We thank the reviewer for this comment. We certainly can determine the inhibitory potential of anti-chimeric MSP and InvP antibodies through invasion assays. We will include the invasion inhibition potential of these antibodies in 3D7, Dd2, with neuraminidase treatment along with GIA data.

      Reviewer #1 Significance:

      Present study proposes novel strategies for the development of anti-malarial vaccine.

      #Reviewer 2 (Evidence, reproducibility and clarity):

      The manuscript describes the vaccine potential of unstructured P. falciparum merozoite protein fragments 25 amino acid long belonging to 3 different protein families. The work is well performed, easily reproducible and clearly described.

      We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.

      Reviewer #2 (Significance):

      1. The use of protein fragments whose structure can be predicted by their sequence has been exploited in many studies for the development of vaccines or other biologicals. In this studies the authors selected 3 different families belonging to the red blood stage of the parasite. The table showing the sequences selected is not readable and should be clearly provided in the supplementary section.

      Response: We apologize for the readability of the sequences. The supplementary Table 1 has the proteins selected, the sequences taken, and the precise order for the stitching.

      In addition, polymorphic residues should be highlighted.

      Response: We thank the reviewer for pointing this out. We will analyze and compile the protein sequences in 3D conformation, highlighting polymorphic residues and the peptides selected in our study.

      In addition, it is not to mention why the authors used immune rabbit sera obtained by injection of the 3 poly-epitopes instead of obtaining by affinity chromatography antigen specific human antibodies from sera of individuals living in endemic regions which could provide a direct and clear answer whether a protective vaccine could be obtained.

      Response: We agree that the clear answer to the protective function of antibodies could have been answered using human antibodies. However, we did not have a sufficient volume of patient sera to perform affinity enrichment. The use of rabbits here was to ensure the generation of antigen-specific antibody responses in ample amounts. The patient sera in quantities available were used in ELISA, epitope mapping, and IP, followed by mass-spectrometry. The IP-MS clearly shows the presence of antibodies against the proteins taken in the generation of chimeric antigens (Supplementary Figure 1 D).

      #Reviewer 3 (Evidence, reproducibility and clarity):

      Multi-protein chimeric antigens... by: Deshmukh et al

      This article addresses an extremely important objective, the development of an effective prophylactic vaccine for Malaria. The disease continues to be widespread claiming the lives of hundreds of thousands of people annually, many of them children. Despite efforts towards producing Malaria vaccines, none thus far have been sufficiently protective or long term. As the authors point out vaccines can target the parasite per se, and possibly more attractive would be to focus on parasite derived antigens expressed on the surface of infected erythrocytes, hence targeting the Blood stage of the infection, which is most directly associated with Malaria pathogenesis. The authors propose a somewhat novel approach in which they have selected an array of short (25 amino acids) segments of Plasmodium derived proteins stitched together to produce 3 chimeric recombinant proteins as potential immunogens. Although a considerable amount of work is described, the results are not compelling in proving the efficacy or advantage of using chimeric antigens as worthy vaccine candidates for Malaria.

      Unfortunately, the rationale behind the experiments are not clearly defined which is a matter of concern. In addition, details of the work done and the technical aspects needs to better explained to fully understand how and why the target segments were selected and the chimeras produced. This review focuses first on scientific issues and then format and editing, both aspects demonstrate that the manuscript in its present form requires major changes for it to be of relevance to the field. This review focuses first on issues of substance and then format and editing, both aspects disqualify the publication of the manuscript in its present form.

      We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.

      Experiments and Results:

      1. The underlying proposal claims that chimeric antigens might be advantageous in eliciting protective antibodies. The authors produced three chimeras: var, MSP and InvP. __The var chimera contains 29 segments of PfEMP1 derived from 8 alleles. The hypothesis is that by expressing 29 different segments one will produce antibodies that can better cope with the antigenic diversity of this target. Indeed, serial monoallelic expression of anyone of the 60 PfEMP1 variants of a given P. falciparum strain has been thought to mediate immune evasion. The parasite is presumed to be able to escape immune defenses, by switching and serially expressing PfEMP1 alleles. Hence, one might assume that by introducing different segments, derived from different alleles, one will gain better protection. The authors have not really tested this idea. They have produced a single chimera and tested it without controlled comparison of performance to any single segment, or for that matter compared to alternative structural domain(s) of PfEMP. This brings me to the question of how the segments were selected and why. The authors implement IEDB-AR to identify presumably preferred B-cell epitopes. The methodology relies on a number of computational methods that predict the propensity of linear segments of proteins to have, for example, secondary structures, or be surface accessible, or relatively hydrophilic or flexible, etc. IEDB-AR is a tool to assist the identification of segments (5-25 amino acids in length), that might be associated with B-cell epitopes, or at least segments comprising linear aspects of B-cell epitopes. The input is a linear sequence of an antigen, proposing linear aspects of what could be associated with B-cell epitopes. B-cell epitopes, however, are typically conformational and discontinuous. They certainly can and do contain linear segments, but even these may require 3D conformations dictated by spatial constraints imposed by the native surrounding aspects of the natural antigen. It is hard to assume that by simply stitching 29 segments, one after the other, one can provide them with the native environment for them to assume a somewhat physiologically relevant conformation. Unfortunately, the authors have not addressed the unique characteristics of the antigen they have selected. PfEMP1, for example, is a family of antigens with discrete sub-domain structures and features (DBL and CIDR for example). It would be relevant and useful to relate the segments that they chose to the natural unique domains of the antigen and how they might best present common vs variant aspects of the antigen. There are at least 30 crystal atomic structures for PfEMP1 in complex with various physiologically relevant proteins (eg ICAM etc). The authors might have considered the 3D structure of PfEMP in their analyses and at least indicated on an atomic structure where the 29 segments lie. __

      More concerning is the fact that the expression of the chimera does not produce a crisp single protein, but rather a complex of products as illustrated in the Supplement Figure 1 B. The authors simply claim that they produce the antigen for immunization of rabbits (or one rabbit?) and they collect gel-derived band(s) of what MW?? Assuming that a 25aa segment should be about 2500-2800 daltons and so 29 such segments strung together should be about 80kDa. The gel shows bands at 124kDa, and a slew of bands shorter than 71kDa. There is no mention what the expected MW should be and there is no explanation why the protein pattern contains so many bands of different sizes and what exact bands were taken for the immunogen or why.

      Response: We thank the reviewer for this comment, as it tells us the reader's perspective on how the chimeric construct part is underexplained. We have now expanded the section on chimeric construct design, the sequences used, the functional domains they belong to in the PfEMP1 protein (Supplementary Tables 1 and 2), and the expected sizes of the proteins created. As for the B-cell epitope prediction, we have used the linear epitope prediction tool. However, we will include a 3D conformational study highlighting the placement of peptides that we have used to generate chimeric antigens.

      The sequences for chimeric constructs were synthesized commercially and confirmed using Sanger sequencing. The antigens run higher than their expected molecular weights, and we have confirmed them through western blot and mass spectrometry (Supplementary Figure 1 B and C). The chimeric varB antigen specifically shows a cleaving pattern, hence the multiple bands in western blotting (we have considered the top-most band with the highest anti-his intensity). After these confirmations, the antigens were independently injected in rabbits to generate antibodies.

      Similar considerations can be made regarding the selection of the segments for the two other chimeras, although they seem to produce a single polypeptide.

      Response: The antigens were confirmed using Sanger sequencing, expression using anti-his western blot, and proteins were confirmed using mass spectrometry for all three chimeric constructs (Supplementary Figure 1 B and C).

      If the point was to test a "chimera" modality as an improved vaccine, it would have been more useful to focus on one chimera and carefully characterize it and compare it to its components used separately.

      Response: The idea of chimera arises from the fact that individual proteins/components are insufficient to generate optimal responses. The proteins considered in our study have already been validated in the field (as separate components) and show that the efficacy observed was sub-optimal. Since our rationale is to include multiple proteins to tackle the redundancy and parasite virulence, we have focused on generating three chimeric constructs covering the entire blood stage of Plasmodium falciparum. Our objective is to demonstrate that a multi-protein, multi-factorial vaccine, as a proof of concept, works better in tackling malaria. We believe that in proving so, a comparison of chimera with their individual components is an unnecessary and economically unviable.

      The authors devote much effort to the fluidics system and their assay. This might warrant a paper dedicated to the methodology they have developed.

      Response: The Plasmodium virulence genes are extensively studied for their interactions with human endothelial receptors. Unfortunately, these studies fail to take human physiological conditions into account. We wanted to test our anti-chimeric varB antibodies in the best mimicking environment possible. Hence, the efforts were devoted to developing, standardizing, and quantifying the fluidic cytoadherence system. We thank the reviewer for their kind words of encouragement on our methodology.

      Format and Editing:

      1. The manuscript is very poorly written with multiple errors throughout. The authors use abbreviations that are not defined, eg iRBC (pg 5 line 22) or sometimes incorrectly defined, eg MSP ("merozoite-specific proteins - pg 6 line 18).

      Response: We apologize for the abbreviation error. The abbreviation for iRBC is defined in the introduction section (page no 4, Line 15); hence, it is not redefined on page 5, line 22. We have corrected merozoite-specific proteins on page 6, line 18.

      The Figures are of low resolution to the extent that they can not be read (for example Figure 3 pg 34). Figure 1 is somewhat useless and misleading. In Fig1 C - the diagram illustrates 5 hypothetical chimeras where in fact only three were produced. There really is no detail or explanation as to how the chimeras were produced.

      Response: We apologize for the low resolution of the images. We have now improved the image quality. Figure 1C represents the idea of designing the construct, not the number of chimeras we generated. We apologize for this confusion and have explicitly mentioned this in the figure panel for Figure 1C. As for the design and generation of chimeric antigens, we understand that the materials and methods section is underexplained, and we have now expanded on it with all details included.

      In the construction of the chimeras there is no mention as to whether short linkers were introduced between the segments or not. What was the expected weight of the chimera? Was the order of segments random or precise and consistent? Were the constructs sequence validated in addition to the MassSpec?

      Response: We understand that the section on the chimeric construct is underexplained for the readers, and we thank the reviewer for pointing it out. We have now expanded the section on chimeric antigen design and included the details. Chimera was tested with GSGSGS linkers and without linkers for expression. The final antigen injected in rabbits was serially attached peptides without linkers. The segments stitched were in precise order, as mentioned in Supplementary Sheet 1. The construct was commercially synthesized and sequence validated along with the anti-his western blot and mass spectrometry analysis.

      The figures of the Supplement are not numbered.

      Response: We thank the reviewer for pointing this out. The figures are now numbered.

      Note that the headings in Supplement Figure 1 B and C have overlapping text.

      Response: Thank you for pointing this out. We have now rearranged the supplementary figures 1B, and 1C.

      Most disturbing is that multiple references that are incomplete. For example: in References 15, 16, 25, 26, 27 there is no indication of the Journal.

      Response: We apologize for the mistakes in referencing. These references did not have full citations in Endnote. We have now manually checked all the references and corrected the incomplete formats of the references.

      The authors mention reference 13 [2006] in claiming that the antibodies can be protective, and then support this by referring to refs 14, 15 and 16 published in 1961, 1963 and 1962 respectively. Although, old articles can be useful, but the authors should attempt to provide current proof of such basic claims.

      Response: We thank the reviewer for pointing this out. We have now separated these two statements and not mentioned the latter as a support to the former. As for references 14, 15, and 16, these were the early studies in the field that show the protective nature of antibodies through the passive immunization process and are foundations for the idea of blood stage vaccination. Current proofs of antibodies against blood-stage antigens are included for blood-stage vaccine candidates.

      Reviewer #3 (Significance):

      The goal of the study is very important.

      The hypothesis that a chimeric presentation of select peptides could be advantageous was not rigorously tested nor well controlled in a meaningful evaluation and thus no conclusion can be made. There are no comparative analyses to test their hypothesis.

      The method for selection of epitope segments is not well justified. There is little attempt to provide rationale or description of the segments chosen and how they fit within the antigens, thus justifying segments over multiple antigens.

      The grammatical errors, lack of clarity accompanied by little attention to style and readability render the manuscript quite illegible.

      There is no excuse for so many errors in the references.

      PeerReviewed
    2. EMBOpress 17 Jul 2024

      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 #3

      Evidence, reproducibility and clarity

      Multi-protein chimeric antigens... by: Deshmukh et al

      This article addresses an extremely important objective, the development of an effective prophylactic vaccine for Malaria. The disease continues to be widespread claiming the lives of hundreds of thousands of people annually, many of them children. Despite efforts towards producing Malaria vaccines, none thus far have been sufficiently protective or long term. As the authors point out vaccines can target the parasite per se, and possibly more attractive would be to focus on parasite derived antigens expressed on the surface of infected erythrocytes, hence targeting the Blood stage of the infection, which is most directly associated with Malaria pathogenesis. The authors propose a somewhat novel approach in which they have selected an array of short (25 amino acids) segments of Plasmodium derived proteins stitched together to produce 3 chimeric recombinant proteins as potential immunogens. Although a considerable amount of work is described, the results are not compelling in proving the efficacy or advantage of using chimeric antigens as worthy vaccine candidates for Malaria.

      Unfortunately, the rationale behind the experiments are not clearly defined which is a matter of concern. In addition, details of the work done and the technical aspects needs to better explained to fully understand how and why the target segments were selected and the chimeras produced. This review focuses first on scientific issues and then format and editing, both aspects demonstrate that the manuscript in its present form requires major changes for it to be of relevance to the field. This review focuses first on issues of substance and then format and editing, both aspects disqualify the publication of the manuscript in its present form.

      Experiments and Results:

      The underlying proposal claims that chimeric antigens might be advantageous in eliciting protective antibodies. The authors produced three chimeras: var, MSP and InvP.

      The var chimera contains 29 segments of PfEMP1 derived from 8 alleles. The hypothesis is that by expressing 29 different segments one will produce antibodies that can better cope with the antigenic diversity of this target. Indeed, serial monoallelic expression of anyone of the 60 PfEMP1 variants of a given P. falciparum strain has been thought to mediate immune evasion. The parasite is presumed to be able to escape immune defenses, by switching and serially expressing PfEMP1 alleles. Hence, one might assume that by introducing different segments, derived from different alleles, one will gain better protection. The authors have not really tested this idea. They have produced a single chimera and tested it without controlled comparison of performance to any single segment, or for that matter compared to alternative structural domain(s) of PfEMP. This brings me to the question of how the segments were selected and why. The authors implement IEDB-AR to identify presumably preferred B-cell epitopes. The methodology relies on a number of computational methods that predict the propensity of linear segments of proteins to have, for example, secondary structures, or be surface accessible, or relatively hydrophilic or flexible, etc. IEDB-AR is a tool to assist the identification of segments (5-25 amino acids in length), that might be associated with B-cell epitopes, or at least segments comprising linear aspects of B-cell epitopes. The input is a linear sequence of an antigen, proposing linear aspects of what could be associated with B-cell epitopes. B-cell epitopes, however, are typically conformational and discontinuous. They certainly can and do contain linear segments, but even these may require 3D conformations dictated by spatial constraints imposed by the native surrounding aspects of the natural antigen. It is hard to assume that by simply stitching 29 segments, one after the other, one can provide them with the native environment for them to assume a somewhat physiologically relevant conformation. Unfortunately, the authors have not addressed the unique characteristics of the antigen they have selected. PfEMP1, for example, is a family of antigens with discrete sub-domain structures and features (DBL and CIDR for example). It would be relevant and useful to relate the segments that they chose to the natural unique domains of the antigen and how they might best present common vs variant aspects of the antigen. There are at least 30 crystal atomic structures for PfEMP1 in complex with various physiologically relevant proteins (eg ICAM etc). The authors might have considered the 3D structure of PfEMP in their analyses and at least indicated on an atomic structure where the 29 segments lie. More concerning is the fact that the expression of the chimera does not produce a crisp single protein, but rather a complex of products as illustrated in the Supplement Figure 1 B. The authors simply claim that they produce the antigen for immunization of rabbits (or one rabbit?) and they collect gel-derived band(s) of what MW?? Assuming that a 25aa segment should be about 2500-2800 daltons and so 29 such segments strung together should be about 80kDa. The gel shows bands at 124kDa, and a slew of bands shorter than 71kDa. There is no mention what the expected MW should be and there is no explanation why the protein pattern contains so many bands of different sizes and what exact bands were taken for the immunogen or why.

      Similar considerations can be made regarding the selection of the segments for the two other chimeras, although they seem to produce a single polypeptide.

      If the point was to test a "chimera" modality as an improved vaccine, it would have been more useful to focus on one chimera and carefully characterize it and compare it to its components used separately. The authors devote much effort to the fluidics system and their assay. This might warrant a paper dedicated to the methodology they have developed.

      Format and Editing:

      The manuscript is very poorly written with multiple errors throughout. The authors use abbreviations that are not defined, eg iRBC (pg 5 line 22) or sometimes incorrectly defined, eg MSP ("merozoite-specific proteins - pg 6 line 18).

      The Figures are of low resolution to the extent that they can not be read (for example Figure 3 pg 34). Figure 1 is somewhat useless and misleading. In Fig1 C - the diagram illustrates 5 hypothetical chimeras where in fact only three were produced. There really is no detail or explanation as to how the chimeras were produced.

      In the construction of the chimeras there is no mention as to whether short linkers were introduced between the segments or not. What was the expected weight of the chimera? Was the order of segments random or precise and consistent? Were the constructs sequence validated in addition to the MassSpec?

      The figures of the Supplement are not numbered.

      Note that the headings in Supplement Figure 1 B and C have overlapping text.

      Most disturbing is that multiple references that are incomplete. For example: in References 15, 16, 25, 26, 27 there is no indication of the Journal.

      The authors mention reference 13 [2006] in claiming that the antibodies can be protective, and then support this by referring to refs 14, 15 and 16 published in 1961, 1963 and 1962 respectively. Although, old articles can be useful, but the authors should attempt to provide current proof of such basic claims.

      Significance

      The goal of the study is very important.

      The hypothesis that a chimeric presentation of select peptides could be advantageous was not rigorously tested nor well controlled in a meaningful evaluation and thus no conclusion can be made. There are no comparative analyses to test their hypothesis.

      The method for selection of epitope segments is not well justified. There is little attempt to provide rationale or description of the segments chosen and how they fit within the antigens, thus justifying segments over multiple antigens.

      The grammatical errors, lack of clarity accompanied by little attention to style and readability render the manuscript quite illegible.

      There is no excuse for so many errors in the references.

      PeerReviewed
    3. EMBOpress 17 Jul 2024

      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 #2

      Evidence, reproducibility and clarity

      The manuscript describes the vaccine potential of unstructured P. falciparum merozoite protein fragments 25 amino acid long belonging to 3 different protein families. The work is well performed, easily reproducible and clearly described.

      Referees cross-commenting

      The polymorphic residues should be highlighted in the supplementary figure.

      Significance

      The use of protein fragments whose structure can be predicted by their sequence has been exploited in many studies for the development of vaccines or other biologicals. In this studies the authors selected 3 different families belonging to the red blood stage of the parasite. The table showing the sequences selected is not readable and should be clearly provided in the supplementary section. In addition, polymorphic residues should be highlighted. In addition, it is not to mention why the authors used immune rabbit sera obtained by injection of the 3 poly-epitopes instead of obtaining by affinity chromatography antigen specific human antibodies from sera of individuals living in endemic regions which could provide a direct and clear answer whether a protective vaccine could be obtained.

      PeerReviewed
    4. EMBOpress 17 Jul 2024

      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 manuscript by Deshmukh et al is aimed at generating chimeric antigens that can be useful for making next generation vaccines that block blood stage infection by malaria parasite. Given that there is no blood stage vaccine against malaria and available liver stage vaccine shows only limited efficacy that too only in Africa, there is dire need for having novel approaches to generate successful vaccines. In the past attempts have been made to make multivalent vaccines but have not been successful. Nevertheless, it is still a good option as single target blood-stage vaccines have failed. Authors propose to target cytoadhesion and host erythrocyte invasion. For this purpose, they have selected epitopes from PfEMP1/VarB family members, which poses a major challenge as at least 60 genes encode them and they exhibit variations which facilitate the escape from the immune system. The other two chimeras target invasion related proteins like MSPs and adhesins shed by micronemes and rhoptries, which are critical for invasion. The reported work is interesting and provides a useful approach towards developing vaccines against blood stage infection.

      Comments:

      1. The peptides used in InvB chimera did not show good reactivity especially when compared to VarB or MSP peptides. Please discuss the possible reasons.
      2. It will be interesting to determine if blocking a specific VarB/PfEMP1 alters expression of other members. Based on the data provided in Fig. 4E, can a chimera be designed which only includes PfEMP1 that are represented well in HBEC-5i population?
      3. Some of the invasion related proteins like RH5 and EBA175 are not present at parasite surface, instead, secreted from rhoptries and micronemes. It will be nice to perform Western blots on condition medium and see if InvP (or even MSP and VarB) antibodies recognizes the secreted version of these proteins.
      4. Fig. 6E- Statistics need to be provided for inhibition at 12.3 and 25ug.
      5. Plasmodium uses multiple ligand-receptor interaction, which could depend (e.g. EBA-glycohophorins) or operate independent (e.g. RH5-basigin) of sialic acid. While there is representation from candidates from both of these families, most studies especially growth rate assays (Fig. 6E) have been carried using 3D7 strain, which does not require sialic acid. It is possible that if similar experiments were performed using sialic acid-sensitive strains, InvP and MSP antibodies may cause greater inhibition of parasite growth, which may be worth testing.
      6. The direct effect of InvP and MSP Abs should be tested directly on host erythrocyte invasion.

      Significance

      Present study proposes novel strategies for the development of anti-malarial vaccine.

      PeerReviewed
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    biorxiv.org/content/10.1101/2023.11.22.568251v1
  9. Jul 2024
  10. www.biorxiv.org www.biorxiv.org
    The LC3-interacting region of NBR1 is a protein interaction hub enabling optimal flux
    4
    1. EMBOpress 15 Jul 2024

      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

      Reply to the reviewers

      Manuscript number: RC-2024-02516

      Corresponding author(s): Christopher Shoemaker

      __1. __General Statements [optional]

      Thank you to all the reviewers for their helpful efforts on behalf of our manuscript. We appreciate the time and effort they have invested in providing valuable feedback.

      Overall, the positive reception from our reviewers highlighted their appreciation for our approach and findings. Moreover, their comments underscored the relevance and potential impact of our findings, particularly within the fields of autophagy and protein interaction networks. Their detailed and constructive critiques will also help refine both the content and presentation of our work.

      In response to the reviews, we have proposed targeted revisions to the manuscript, all of which are well within our lab's capabilities and can be executed efficiently. We have detailed our responses to each specific point raised by the reviewers below. * *

      • *

      __2. __Description of the planned revisions

      • *

      Reviewer #1

      Evidence, reproducibility and clarity

      1. EVIDENCE, REPRODUCIBILITY AND CLARITY Summary:

      Selective autophagy receptors (SARs) of the Sequestosome-1 like receptor group (SLRs) including SQSTM1(Sequestosome-1)/p62, NBR1, TAX1BP1, NDP52, CALCOCO1 and Optineurin are soluble SARs that engage cargo and ATG8 family proteins as well as components of the core autophagy machinery like FIP200/RBCC1 to bring about the autophagic degradation of the cargo and themselves. In the autophagic degradation of protein aggregates (aggrephagy) the most studied SAR p62 collaborates with the archetypal autophagy receptor NBR1 and also TAX1BP1 to bring about effective turnover of ubiquitinated cargos sequestered into p62 bodies or droplets by liquid-liquid phase separation. How this intricate co-operation of these SARs is orchestrated is incompletely understood. In the paper by North et al entitled "The LC3-interacting region of NBR1 is a protein interaction hub enabling optimal flux" the authors use peptide arrays to map the binding sites for ATG8-family proteins LC3A and GABARAPL1, FIP200 and TAX1BP1 to the autophagy receptor NBR1. The authors find that three short linear interaction motifs (SLiMs), the LIR, FIR and TIR interacting with ATG8 family proteins, FIP200 and TAX1BP1, respectively, partly overlap in a short region of NBR1 that can adopt different conformations to accommodate the different binding partners. In short, the different interactions are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. While the important binding determinants for ATG8 proteins and FIP200 show more overlap and it was not possible here to find mutations that distinguish LIR and FIR binding, TAX1BP1 bound more to a region downstream of the LIR and a specific mutation in NBR1 and in TAX1BP1 could abolish binding. Checking the role of phosphorylations in augmenting binding using phosphomimetic mutations it was seen that while FIP200 and Atg8-family binding were generally augmented by phosphorylation, TAX1BP1 binding did not respond to these mutations. Very interestingly, the authors found that co-expression of TAX1BP1 with tandem-tagged NBR1 in pentaKO cells (not expressing the SLRs p62, NBR1, NDP52, TAX1BP1 and OPTN) increased significantly the autophagic turnover of NBR1. None of the other SLRs could do this. Instead, this over-expression assay revealed a competition.

      Major points:

      1) In Fig 4 the peptide array binding assay is not sufficient as it is only semiquantitative. The data shown should be accompanied by a more direct binding assay allowing the determination of kDs for the binding where the WT peptides are directly compared to the phosphor mimicking mutant peptides. Here the fluorescence anisotropy assay the authors use in Suppl Fig. 1E or ITC, OctetRed96 or another assay suitable for kD determinations should be used.

      Response: Thank you for the constructive comments regarding our peptide array binding assay. We agree that the semi-quantitative nature of this method limits its ability to provide detailed binding affinity measurements. To address this, we will purify multiple peptides and assess the binding affinities between phosphomimetic+/- LIR peptides and Atg8s, FIP200, and TAX1BP1. While testing all peptides may be cost and time prohibitive, we will prioritize a representative range for this validation effort.

      2) As this paper is already dominated by the use of peptides it would significantly enhance the quality of the data if the authors had included studied with peptides phosphorylated at the specific positions to allow comparison with the phosphomimetic substitutions to aspartate.

      Response: Thank you for your insightful comment. We agree that incorporating studies with peptides phosphorylated at specific positions could provide a more nuanced comparison with the phosphomimetic substitutions to aspartate. Previous studies, including Popelka and Klionsky (2022) and Kliche et al. (2022), have indeed suggested that phosphomimetic substitutions do not perfectly replicate phosphorylation events.

      In response, we plan to order a peptide array containing phosphorylated peptides, not merely phosphomimetics, and will conduct additional experiments with TAX1BP1, FIP200, and LC3A. This approach will allow us to directly assess the effects of actual phosphorylation compared to phosphomimetic substitutions.

      While we acknowledge the possibility of subtle differences in binding affinity or regulatory interactions, we anticipate that the primary conclusions of our study—namely, that TAX1BP1 is largely insensitive to phosphorylation, whereas FIP200 and LC3A binding activities are affected—will remain unchanged. These experiments will provide valuable data to confirm the robustness of our conclusions under the conditions of true phosphorylation.

      3) The quality of the 2D peptide array probing of GST-LC3A binding in Fig 3A is poor. Is this a stripped and re-probed membrane? I do not think these data are publication quality and the experiment should be redone unless the authors have very good arguments against my suggestion. It would also be nice to see a 2D peptide array of GABARAPL1 binding too to make the comparative study complete.

      Response: Thank you for your constructive feedback regarding the quality of the 2D peptide array probing of GST-LC3A in Figure 3A. As you rightly pointed out, the membrane was indeed stripped and reprobed, with LC3A being the final probe. This method sometimes introduces artifacts, such as the 'ring' effect observed, which are common with this technique. However, the results consistently aligned with established consensus sequences for LC3, reinforcing the reliability of our findings despite the suboptimal image quality.

      Recognizing the concerns about the quality of the blot, we are prepared to repeat this experiment using a new commercial vendor, as our previous collaborator is no longer available. We anticipate some differences in the appearance of the blots due to changes in dot size and spacing from the new supplier. Given these variations, we propose adding the revised blot to the supplementary materials rather than the main figures to avoid disrupting the visual continuity of the data presentation.

      Additionally, in response to the reviewer’s suggestion, we will include a 2D peptide array probing for GABARAPL1. This will enhance the comparative analysis within our study.

      One alternative (related to Reviewer 3, comment 3) that we can deliver is using our LIR arrays to derive consensus sequences for LC3 binders and GABARAPL1 binders. In doing this, we find the same differences in LC3 and GABARAP binding preferences that were reported previously in Rogov et al 2017. Recovering these known, and somewhat subtle, differences in binding preference further bolster the validity of our approach.

      4) For the data shown in Fig 6 it should be noted that although these are very interesting results a clear limitation of the study is that the results on the autophagic turnover is based on overexpressing the SLRs in the pentaKO cells. In a physiological setting with all relevant actors in place and with a different stoichiometry the effects could likely be different.

      Response: We appreciate the observation regarding the limitations of our study due to the use of overexpressed SLRs in pentaKO cells. As the reviewer rightly points out, the stoichiometry and interaction dynamics in a physiological setting might differ significantly. Critically, after submission of this manuscript, a recent preprint by Sascha Martens’ group (Bauer et al. BioRxiv) has shown similar results using endogenously tagged p62, TAX1BP1, and NBR1. This study corroborates our results, suggesting that the interactions we observed are not merely artifacts of overexpression but reflect genuine biological phenomena. We will incorporate a detailed discussion of this study in the Discussion section of our manuscript to contextualize our findings within a more physiologically relevant framework.

      Therefore, we believe that our reductionist approach, while not fully reflective of physiological conditions, offers valuable and generalizable insights into the intricate cooperation of SARs in autophagy.

      Minor points:

      1) It would be beneficial for the reader to show a cartoon of the domain organization of both TAX1BP1 and NBR1 in Figure 1. NBR1 is shown in supplemental figure 1, but there is no depiction of the domain organization of TAX1BP1.

      Response: As suggested, a domain schematic for NBR1 and TAX1BP1 will be included.

      2) The authors say at the bottom of page 4 "Complementary in vivo studies reveal that while SLRs typically compete". But do they actually typically compete? Is this not a result of the experimental strategies employed? There is more a shortage of SLRs based on cargo competition as shown recently by Peter Kim's group that excessive pexophagy may reduce mitophagy etc. (Germain et al. 2023).

      Response: Thank you for pointing out this overstatement. We will soften this statement.

      3) In Fig. 3D it should be shown that D, E, A and V are preferred residues at position +1 for LC3A binding.

      Response: As suggested, we will amend the figure to include these residues at the +1 position.

      4) In such a 2D mutational analysis it is often just as important to determine which residues are not allowed for binding. It would therefore be nice if the authors could summarize/visualize their results in a better way in Fig 3D to also show the residues that lead to loss of binding. These could be shown below the sequence and the use of color to distinguish basic, acidic, hydrophobic and aromatic residues could be attempted.

      Response: As suggested, we will add to this figure to make it more comprehensive by including residues that are both preferred and lead to loss of binding. Furthermore, we have incorporated the use of color to distinguish the traits of different residues (basic, acidic, hydrophobic and aromatic) that are dis(favored) at each position.

      5) Line 327: To be clear about the fact that this is an overexpression assay "simultaneous expression" should be corrected to simultaneous overexpression".

      Response: We will make the suggested change.

      6) There are LIRs and FIRs that overlap and those that do not. To check the degree of overlaps that may occur among known LIRs the authors made a peptide array with 100 established LIR sequences taken from the LIR-Central database (Chatzichristofi et al., 2023). The peptide array was probed with LC3A (29 bound), GABARAPL1 (49 bound), the FIP200 Claw domain (57 bound) and the TAX1BP1 CC2 domain (49 bound). As much as one third (32) of the LIR peptides were not bound by any of the four probes. Do the authors have a good explanation for the fact that so many peptides did not bind?

      Response: Thank you for highlighting the significant number of LIR peptides that did not bind to any of the probes in our study. At first, we were similarly surprised by this. In our manuscript, we will expand on several factors that might explain this observation:

      • Specificity of Atg8 Family Proteins: The LIR-Central database indicates that these sequences bind at least one Atg8-family protein, but not necessarily all. Our assay might not have included the specific Atg8 proteins that some LIRs preferentially bind.
      • Peptide Solubility and Conformation: The solubility and conformational stability of peptides printed on an array can vary, affecting binding efficiency. Certain sequences may not adopt the optimal conformation for binding under these assay conditions.
      • Sequence Context and Accessibility: The native context in which the LIR motif is contained, including neighboring amino acids, can influence binding. Peptide arrays strip these peptides of their physiological context. As short linear interaction motifs, the assumption is that context will not strongly affect binding, but it’s known that many LIRs adopt partially structured motifs that influence binding (e.g. a C-terminal helix). Our peptide array approach is likely to impede such secondary structures from forming and may limit binding.
      • Misannotated sequences. The LIRs included from the database have varying levels of validation. Some sequences might be misannotated and, therefore, do not bind any of the probes. These discussion points will be included in the manuscript to provide a comprehensive explanation for the observed data.

      7) Strangely enough, the NBR1 peptide used in Figure 2A did not bind any of the probes while the NBR1 peptides used in Fig. 1C bound very well. Do the authors have any explanation for this?

      Response: Thank you for noting the discrepancy in NBR1 peptide binding observed in Figure 2A compared to Figure 1C. This observation was noted by all reviewers. The difference likely arises from the solubility issues associated with the NBR1 peptide in the format used for Figure 2A, where the peptide sequence included the LIR motif plus 10 amino acids on each side. The core LIR sequence of NBR1 (YIII) is highly hydrophobic, which can affect its solubility and, consequently, its observed binding in our peptide array.

      To overcome this, we optimized the LIR sequence of NBR1 for peptide arrays (amino acids 725-749), which includes seven residues before the LIR and 14 residues after. This shift enhanced solubility and facilitated more reliable probing in our experiments (notably Fig 3). In Fig2A and other assays, both the standard and the optimized formats of the NBR1 LIR were included: the standard format to maintain consistency with other LIRs extracted from the LIR-Central database and the optimized version as a control to validate our results.

      We will detail this explanation in the manuscript, clarifying the rationale behind the observed binding differences.

      Significance

      SIGNIFICANCE

      I found this paper very interesting to read with a lot of interesting new detailed and useful information on binding specificity for the proteins and motifs involved. It is a generally well performed study with interesting results. I also very much enjoyed the Discussion section which opens up for several interesting possible scenarios. The study also produced important point mutants that can be used in future studies to selectively abolish TAX1BP1 binding to NBR1. I think this is a "must read" paper for researchers interested in selective autophagy and co-operation between SARs, and more generally for getting some insight into how SLiMs may work. As such, this paper will be of interest for all interested in autophagy research and for a wider audience too as it is in essence about how overlapping SLiMs may be employed to orchestrate multiple protein-protein interactions using distinct overlapping determinants, rather than a single, convergent, SLiM. It is also one of the very few papers I have come across exploiting the power of the peptide array method so extensively with success for mapping protein binding sites.

      It could perhaps be interesting if the authors discussed their results in relation to another study from the group of Sascha Martens on the role of TAX1BP1 in p62 bodies or condensates (doi: https://doi.org/10.1101/2024.05.17.594671). These two papers should be read together as they are both very interesting and important contributions.

      Response: Thank you for pointing out this important reference that was posted shortly after our manuscript was submitted. As mentioned above, we will include an expanded discussion section to discuss these corroborating findings. We will also include a citation to Ferrari et al (PMID: ) on Tau evasion of autophagy through exclusion of TAX1BP1.

      Reviewer #2

      Evidence, reproducibility and clarity

      Summary In this manuscript, North et al. examined how short linear interaction motifs (SLiMs) help to orchester selective autophagy receptors (SARs) function during cargo engulfment in autophagosomes. In particular, the authors focused on NBR1 as a model SAR to address the role of its role in the clearance of protein aggregates (aggrephagy). Using binding assays, the authors showed that a SLiM harboring NBR1's LIR motif also mediates binding to FIP200 and TAX1BP1. Intrigued by these overlapping binding sites, the authors probed 100 LIRs for their binding to TAX1BP1's coiled-coil 2 region (CC2), FIP200's claw domain and two different ATG8 family members and found heterogenous binding pattern and distinct correlation between these four binding partners. Using mutational peptide arrays of NBR1's SLiM, the authors revealed unique binding determinants of these NBR1 partners and their potential differential regulation by phosphorylation. Taking advantage of their new NBR1 binding insights, the authors structurally modeled the binding of TAX1BP1's CC2 to NBR1's SLiM and identified crucial residues in both proteins for this interaction. Lastly, the authors turned to autophagy flux assays in cells and showed that TAX1BP1 acts synergistically with NBR1 to increase its lysosomal delivery. Overall, the claims and the conclusions are largely supported by the data. However, a few critical issues should be addressed.

      Are the data and the methods presented in such a way that they can be reproduced?

      Are the experiments adequately replicated and statistical analysis adequate?

      Major comments

      1) What are the expression levels of the different tf-SAR fusions compared to the endogenous levels of the respective SAR? And are tf-NBR1 protein levels changed upon co-expression of the other SARs?

      __Response: __We appreciate the questions concerning the expression levels of tf-SAR fusions relative to the endogenous levels of the respective SARs, similar to inquiries from Reviewer 1 (major comment 4). In our study, the levels of tf-NBR1 are notably higher than the endogenous levels. Interestingly, we observed that the co-expression of autophagy-competent NBR1 and TAX1BP1 generally leads to a decrease in the levels of both proteins, likely due to enhanced autophagic turnover. This pattern is not seen with autophagy-deficient mutants, suggesting a functional interaction affecting protein stability.

      Furthermore, a recent preprint by Sascha Martens’ group (Bauer et al., BioRxiv) has presented findings that echo our results using endogenously tagged versions of p62, TAX1BP1, and NBR1. This study supports our observations, indicating that the interactions and effects we report are not artifacts of overexpression but are reflective of genuine biological processes. These findings will be thoroughly discussed in the Discussion section of our manuscript to provide context for our results within a physiologically relevant framework.

      Therefore, we believe that our reductionist approach, while not fully reflective of physiological conditions, offers valuable and generalizable insights into the intricate cooperation of SARs in autophagy.

      2) Which of the 100 LIRs have been shown to specifically bind LC3A or GABARAPL1? The authors should include this information from the literature in Figure 2 (e.g., highlighted by color or else).

      __Response: __Thank you for your suggestion to detail the specific interactions between the 100 LIRs and Atg8 homologs like LC3A and GABARAPL1 in Figure 2. While each LIR in the LIR-Central database has been validated, detailed information on which LIRs bind specific Atg8 homologs—and with what relative affinity—is often lacking in the literature. This gap makes it challenging to present comprehensive binding preferences in a visually coherent way within Figure 2.

      Nevertheless, we recognize the value of such information. We plan to conduct a thorough literature review on all 100 LIRs included in our study. Should we find sufficient and reliable data regarding binding specificities, we will incorporate this into Figure 2, potentially using color coding or another method to highlight these relationships clearly.

      We can also perform the reciprocal experiment by using our LIR arrays to derive consensus sequences for LC3 binders and GABARAPL1 binders. In doing this, we find the same differences in LC3 and GABARAP preferences that were reported previously in Rogov et al 2017. Recovering these known, and somewhat subtle, differences in binding preference further bolster the validity of our approach. These new data will be added to the manuscript.

      3) How effective is the stripping of the peptide array? The authors should provide evidence that there is no carry over binding from sequential probing the array. As a control, the authors should at least repeat probing for the last binder in their sequential binding assay with a new peptide array that has not yet been incubated with a different binder and then stripped.

      __Response: __This is an important question, related to Reviewer 1 (comment 3), as the stripping of the peptide array can be variably affective. Prior to performing any of the arrays included in this manuscript, we did several validation arrays to identify the proper ordering of probes (e.g. what proteins can be stripped, which cannot). FIP200 and TAX1BP1 probing was performed on fresh or successfully stripped blots. LC3A probing was done last, as there is substantial previous literature defining the LC3 motif. However, the results of the LC3A binding consistently aligned with established consensus sequences for LC3, reinforcing the reliability of our findings despite the stripping process. Therefore, while stripping sometimes introduces artifacts, such as the 'ring effect’ observed in Figure 3A, the results did not appear to be influenced by prior probes.

      As suggested, we are prepared to repeat the LC3A probing on a new array to fully cement this interpretation. We note, however, that this will be done using a new commercial vendor, as our previous collaborator is no longer available (The original blots were ordered over 3 years ago). We anticipate some differences in the appearance of the blots due to changes in dot size and spacing from the new supplier. Given these variations, we propose adding the revised blot to the supplementary materials rather than the main figures to avoid disrupting the visual continuity of the data presentation.

      4) What is the number of replicates for the peptide array assays?

      __Response: __Due to cost considerations, peptide array assays in our study were conducted as one or two replicates. We understand the limitations this presents in terms of statistical robustness and variability assessment. However, where possible, we supplemented these assays with additional validation experiments and controls to ensure reliability of our findings. For critical experiments, including key interaction validations, we used independent biochemical assays to confirm the results obtained from the peptide arrays.

      5) The authors should test whether the enhancement of NBR1 flux by TAX1BP1 is only due to the contribution of an additional LIR or potential other functions of TAX1BP1 (e.g. ubiquitin binding or FIP200 binding). The authors should expand the panel shown in Figure 6E with TAX1BP1 mutant which are deficient in ubiquitin or FIP200 binding.

      __Response: __We thank the reviewer for their suggestion. We will include data with TAX1BP1 mutants that are deficient in ubiquitin or FIP200 binding

      Minor comments

      6) Molecular weight markers are missing on immunoblots.

      __Response: __We apologize for this oversight. We will amend figure to include molecular weight markers.

      7) It would be more informative (since some proteins have more than one LIR) if the actual LIR motif would be displayed next to the peptide array (as e.g. done for NBR1) and not only in the supplements.

      __Response: __We appreciate this thoughtful input and will consider its implementation carefully. We will explore the feasibility of integrating this detail in a manner that maintains figure clarity.

      8) Along this line in Figure 2A, NBR1's LIR (marked with a red star) is among the LIRs for which no binding was observed. The authors should explain this.

      Response: Thank you for noting the discrepancy in NBR1 peptide binding observed in Figure 2A compared to Figure 1C. This observation was noted by all reviewers. The difference likely arises from the solubility issues associated with the NBR1 peptide in the format used for Figure 2A, where the peptide sequence included the LIR motif plus 10 amino acids on each side. The core LIR sequence of NBR1 (YIII) is highly hydrophobic, which can affect its solubility and, consequently, its observed binding in our peptide array.

      To overcome this, we optimized the LIR sequence of NBR1 for peptide arrays (amino acids 725-749), which includes seven residues before the LIR and 14 residues after. This shift enhanced solubility and facilitated more reliable probing in our experiments (notably Fig 3). In Fig2A and other assays, both the standard and the optimized formats of the NBR1 LIR were included: the standard format to maintain consistency with other LIRs extracted from the LIR-Central database and the optimized version as a control to validate our results.

      We will detail this explanation in the manuscript, clarifying the rationale behind the observed binding differences.

      Significance

      Collectively, the work of North and colleagues provide valuable new mechanistic insights into the network of interaction that governs the function of SARs. Importantly, this works extends the knowledge in the field that SARs are acting in an orchestrated manner which reinforces their delivery to lysosomes. However, given the involvement of several SARs in the same process, it is crucial to dissect the binding modalities among these factors. In this regard, the current study on fine mapping binding sites provides an important contribution. In particular, in probing the in vitro findings in reconstituted KO cells. This part is really strong. In addition, the identification of critical residues for these bindings events represents important tools for the autophagy community which will be among the basic research audience most interested in this technical study.

      __ __

      PeerReviewed
    2. EMBOpress 15 Jul 2024

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

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      Referee #3

      Evidence, reproducibility and clarity

      North et al., using NBR1 as a model, found that three ATG8-family proteins, FIP200, and TAX1BP1 - each bind to a short linear interaction motif (SLiM) within NBR1. Mutational peptide arrays showed that these binding events are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. They performed peptide binding arrays on >100 established LC3-interacting regions (LIRs), and showed that that FIP200 and/or TAX1BP1 binding to LIRs is a common phenomenon and suggesting LIRs as protein interaction hotspots. Comparative analysis of phosphomimetic peptides showed that while FIP200 and Atg8-family binding are generally augmented by phosphorylation, TAX1BP1 binding is nonresponsive. In vivo studies confirmed that LIR-mediated interactions with TAX1BP1 enhance NBR1 activity, increasing autophagosomal delivery by leveraging an additional LIR from TAX1BP1.

      Suggestions for further improvement of the paper:

      1. Figure 1: Data in figure 1 would be strengthened with cellular localization studies of the various constructs. What is the localization pattern of TIR mutants?
      2. Figure 2: Some more elaborate analysis and discussion is needed to explain the reason of 'never-binders'
      3. GIM (GABARAP interaction motifs) have been previously identified (Rogov et al., 2017). Can the authors extend/comment/discuss their findings in the context of GIMs?
      4. Figure 3: Data in figure 3 would be strengthened with cellular localization studies of the various constructs.
      5. The statement : 'LIR motif of NBR1 is a protein interaction hub enabling optimal flux' is not well discussed in the discussion and does not come through very clearly throughout the paper.

      Significance

      This is a very interesting and well structured study with clear and convincing data.

      PeerReviewed
    3. EMBOpress 15 Jul 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      In this manuscript, North et al. examined how short linear interaction motifs (SLiMs) help to orchester selective autophagy receptors (SARs) function during cargo engulfment in autophagosomes. In particular, the authors focused on NBR1 as a model SAR to address the role of its role in the clearance of protein aggregates (aggrephagy). Using binding assays, the authors showed that a SLiM harboring NBR1's LIR motif also mediates binding to FIP200 and TAX1BP1. Intrigued by these overlapping binding sites, the authors probed 100 LIRs for their binding to TAX1BP1's coiled-coil 2 region (CC2), FIP200's claw domain and two different ATG8 family members and found heterogenous binding pattern and distinct correlation between these four binding partners. Using mutational peptide arrays of NBR1's SLiM, the authors revealed unique binding determinants of these NBR1 partners and their potential differential regulation by phosphorylation. Taking advantage of their new NBR1 binding insights, the authors structurally modeled the binding of TAX1BP1's CC2 to NBR1's SLiM and identified crucial residues in both proteins for this interaction. Lastly, the authors turned to autophagy flux assays in cells and showed that TAX1BP1 acts synergistically with NBR1 to increase its lysosomal delivery. Overall, the claims and the conclusions are largely supported by the data. However, a few critical issues should be addressed.

      Are the data and the methods presented in such a way that they can be reproduced? Are the experiments adequately replicated and statistical analysis adequate?

      Major comments

      1. What are the expression levels of the different tf-SAR fusions compared to the endogenous levels of the respective SAR? And are tf-NBR1 protein levels changed upon co-expression of the other SARs?
      2. Which of the 100 LIRs have been shown to specifically bind LC3A or GABARAPL1? The authors should include this information form the literature in Figure 2 (e.g., highlighted by color or else).
      3. How effective is the stripping of the peptide array? The authors should provide evidence that there is no carry over binding from sequential probing the array. As a control, the authors should at least repeat probing for the last binder in their sequential binding assay with a new peptide array that has not yet been incubated with a different binder and then stripped.
      4. What is the number of replicates for the peptide array assays?
      5. The authors should test whether the enhancement of NBR1 flux by TAX1BP1 is only due to the contribution of an additional LIR or potential other functions of TAX1BP1 (e.g. ubiquitin binding or FIP200 binding). The authors should expand the panel shown in Figure 6E with TAX1BP1 mutant which are deficient in ubiquitin or FIP200 binding.

      Minor comments

      1. Molecular weight markers are missing on immunoblots.
      2. It would be more informative (since some proteins have more than one LIR) if the actual LIR motif would be displayed next to the peptide array (as e.g. done for NBR1) and not only in the supplements.
      3. Along this line in Figure 2A, NBR1's LIR (marked with a red star) is among the LIRs for which no binding was observed. The authors should explain this.

      Referee Cross-Commenting

      I find that all reviewers raised valid and important points that the authors should address to increase the quality and impact of their manuscript.

      Significance

      Collectively, the work of North and colleagues provide valuable new mechanistic insights into the network of interaction that governs the function of SARs. Importantly, this works extends the knowledge in the field that SARs are acting in an orchestered manner which reinforces their delivery to lysosomes. However, given the involvement of several SARs in the same process, it is crucial to dissect the binding modalities among these factors. In this regard, the current study on fine mapping binding sites provides an important contribution. In particular, in probing the in vitro findings in reconstituted KO cells. This part is really strong. In addition, the identification of critical residues for these bindings events represents important tools for the autophagy community which will be among the basic research audience most interested in this technical study.

      PeerReviewed
    4. EMBOpress 15 Jul 2024

      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

      Summary:

      Selective autophagy receptors (SARs) of the Sequestosome-1 like receptor group (SLRs) including SQSTM1(Sequestosome-1)/p62, NBR1, TAX1BP1, NDP52, CALCOCO1 and Optineurin are soluble SARs that engage cargo and ATG8 family proteins as well as components of the core autophagy machinery like FIP200/RBCC1 to bring about the autophagic degradation of the cargo and themselves. In the autophagic degradation of protein aggregates (aggrephagy) the most studied SAR p62 collaborates with the archetypal autophagy receptor NBR1 and also TAX1BP1 to bring about effective turnover of ubiquitinated cargos sequestered into p62 bodies or droplets by liquid-liquid phase separation. How this intricate co-operation of these SARs is orchestrated is incompletely understood. In the paper by North et al entitled "The LC3-interacting region of NBR1 is a protein interaction hub enabling optimal flux" the authors use peptide arrays to map the binding sites for ATG8-family proteins LC3A and GABARAPL1, FIP200 and TAX1BP1 to the autophagy receptor NBR1. The authors find that three short linear interaction motifs (SLiMs), the LIR, FIR and TIR interacting with ATG8 family proteins, FIP200 and TAX1BP1, respectively, partly overlap in a short region of NBR1 that can adopt different conformations to accommodate the different binding partners. In short, the different interactions are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. While the important binding determinants for ATG8 proteins and FIP200 show more overlap and it was not possible here to find mutations that distinguish LIR and FIR binding, TAX1BP1 bound more to a region downstream of the LIR and a specific mutation in NBR1 and in TAX1BP1 could abolish binding. Checking the role of phosphorylations in augmenting binding using phosphomimetic mutations it was seen that while FIP200 and Atg8-family binding were generally augmented by phosphorylation, TAX1BP1 binding did not respond to these mutations. Very interestingly, the authors found that co-expression of TAX1BP1 with tandem-tagged NBR1 in pentaKO cells (not expressing the SLRs p62, NBR1, NDP52, TAX1BP1 and OPTN) increased significantly the autophagic turnover of NBR1. None of the other SLRs could do this. Instead, this over-expression assay revealed a competition.

      Major points:

      In Fig 4 the peptide array binding assay is not sufficient as it is only semiquantitative. The data shown should be accompanied by a more direct binding assay allowing the determination of kDs for the binding where the WT peptides are directly compared to the phosphor mimicking mutant peptides. Here the fluorescence anisotropy assay the authors use in Suppl Fig. 1E or ITC, OctetRed96 or another assay suitable for kD determinations should be used.

      As this paper is already dominated by the use of peptides it would significantly enhance the quality of the data if the authors had included studied with peptides phosphorylated at the specific positions to allow comparison with the phosphomimetic substitutions to aspartate.

      The quality of the 2D peptide array probing of GST-LC3A binding in Fig 3A is poor. Is this a stripped and re-probed membrane? I do not think these data are publication quality and the experiment should be redone unless the authors have very good arguments against my suggestion. It would also be nice to see a 2D peptide array of GABARAPL1 binding too to make the comparative study complete.

      For the data shown in Fig 6 it should be noted that although these are very interesting results a clear limitation of the study is that the results on the autophagic turnover is based on overexpressing the SLRs in the pentaKO cells. In a physiological setting with all relevant actors in place and with a different stoichiometry the effects could likely be different.

      Minor points:

      It would be beneficial for the reader to show a cartoon of the domain organization of both TAX1BP1 and NBR1 in Figure 1. NBR1 is shown in supplemental figure 1, but there is no depiction of the domain organization of TAX1BP1.

      The authors say at the bottom of page 4 "Complementary in vivo studies reveal that while SLRs typically compete". But do they actually typically compete? Is this not a result of the experimental strategies employed? There is more a shortage of SLRs based on cargo competition as shown recently by Peter Kim's group that excessive pexophagy may reduce mitophagy etc. (Germain et al. 2023).

      In Fig. 3D it should be shown that D, E, A and V are preferred residues at position +1 for LC3A binding.

      In such a 2D mutational analysis it is often just as important to determine which residues are not allowed for binding. It would therefore be nice if the authors could summarize/visualize their results in a better way in Fig 3D to also show the residues that lead to loss of binding. These could be shown below the sequence and the use of color to distinguish basic, acidic, hydrophobic and aromatic residues could be attempted.

      Line 327: To be clear about the fact that this is an overexpression assay "simultaneous expression" should be corrected to simultaneous overexpression".

      There are LIRs and FIRs that overlap and those that do not. To check the degree of overlaps that may occur among known LIRs the authors made a peptide array with 100 established LIR sequences taken from the LIR-Central database (Chatzichristofi et al., 2023). The peptide array was probed with LC3A (29 bound), GABARAPL1 (49 bound), the FIP200 Claw domain (57 bound) and the TAX1BP1 CC2 domain (49 bound). As much as one third (32) of the LIR peptides were not bound by any of the four probes. Do the authors have a good explanation for the fact that so many peptides did not bind? Strangely enough, the NBR1 peptide used in Figure 2A did not bind any of the probes while the NBR1 peptides used in Fig. 1C bound very well. Do the authors have any explanation for this?

      Significance

      I found this paper very interesting to read with a lot of interesting new detailed and useful information on binding specificity for the proteins and motifs involved. It is a generally well performed study with interesting results. I also very much enjoyed the Discussion section which opens up for several interesting possible scenarios. The study also produced important point mutants that can be used in future studies to selectively abolish TAX1BP1 binding to NBR1. I think this is a "must read" paper for researchers interested in selective autophagy and co-operation between SARs, and more generally for getting some insight into how SLiMs may work. As such, this paper will be of interest for all interested in autophagy research and for a wider audience too as it is in essence about how overlapping SLiMs may be employed to orchestrate multiple protein-protein interactions using distinct overlapping determinants, rather than a single, convergent, SLiM. It is also one of the very few papers I have come across exploiting the power of the peptide array method so extensively with success for mapping protein binding sites. It could perhaps be interesting if the authors discussed their results in relation to another study from the group of Sascha Martens on the role of TAX1BP1 in p62 bodies or condensates (doi: https://doi.org/10.1101/2024.05.17.594671). These two papers should be read together as they are both very interesting and important contributions.

      PeerReviewed
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    A progeria-associated BAF-1 mutation modulates gene expression and accelerates aging in C. elegans
    4
    1. EMBOpress 11 Jul 2024

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      Reply to the reviewers

      We thank the reviewers for their positive and constructive criticism. We answer their points one by one below.

      Reviewer #1

      1.) In the baf-1 G12T mutants the authors find reduced levels of lamin in hypodermal nuclei. It would be good to also examine the dynamics of lamin in the second tissue that was subjected to DamID (intestinal cells).

      We provide a complete analysis of GFP::LMN-1 and EMR-1::mCh in control and baf-1(G12T) day 1 adults in intestine and hypodermis and at 20°C and 25°C. These data demonstrate that GFP::LMN-1 expression is reduced in baf-1(G12T) mutants in both tissue and at both temperatures. In contrast, for EMR-1::mCh a significant reduction was only observed in hypodermal nuclei at 20°C.

      The effects on GFP::LMN-1 and EMR-1::mCh in the hypodermis 20°C were reported in Figure 2E-F in the original version of our manuscript. We have moved these data to the new Supplementary Figure S5 and represent instead the data obtained for hypodermis at 25°C in Figure 2E-F for consistency with the data represented in Figure 2A-D. Data on intestine for both markers and both temperatures are also included in the new Supplementary Figure S5.

      We have modified the text as follows:

      “To test the impact of baf-1(G12T) on LMN-1, EMR-1, and BAF-1 localization in vivo, we quantified these factors at the NE of hypodermal and intestinal cells. We observed a significantly lower median GFP::LMN-1 signal at the NE in baf-1(G12T) mutants in both tissues at 20°C and 25°C (Figure ____2E; Supplementary Figure S____5A-C). In contrast, accumulation of EMR-1 at the NE was unaffected by the baf-1(G12T) mutation in both tissues at 25°C and reduced in the hypodermis at 20°C (Figure ____2F; Supplementary Figure S____5D-F). In human NGPS cells, emerin was observed to be delocalized to the ER (Janssen et al., 2022; Puente et al., 2011), but we detected no increase in cytoplasmic EMR-1::mCh signal in the mutant, indicating that this NGPS phenotype is not present in the C. elegans model. In agreement with these microscopy data, analysis of whole-worm mRNA levels by quantitative RT-PCR also revealed a significant reduction in lmn-1 expression whereas emr-1 was unaffected (Supplementary Figure S4E-F).”

      2.) The authors make a statement that EMR-1 expression was reduced in the baf-1 G12T mutant, but do not comment on LMN-1 expression. Can a statement on this be made by RT PCR?

      Our gene expression analysis by RAPID determined a significant reduction in emr-1 expression in the intestine of baf-1(G12T) mutants, using a fold change of 2 as threshold. In contrast, expression of emr-1 in hypodermis as well as baf-1 and lmn-1 expression in both tissues were not significantly different between wild type and baf-1(G12T) mutants in our RAPID data.

      We performed qRT-PCR on bulk mRNA to compare the expression of baf-1, emr-1 and lmn-1 in control versus baf-1(G12T) mutants. No differences were detected for baf-1 and emr-1 (new Supplementary Figure S4E-F). Considering that the qRT-PCR is on bulk mRNA, the emr-1 result is compatible with the RAPID data that suggest deregulation of emr-1 only in intestine and unaffected expression in the hypodermis. For baf-1 there is agreement between qRT-PCR and RAPID data from both tissues (no difference in the mutant). For lmn-1, the qRT-PCR analysis suggests a modest reduction (23%; not reaching the threshold applied in the RAPID analysis) in baf-1(G12T) mutants, which is concordant with the reduction observed in GFP::LMN-1 intensity in hypodermis and intestine by confocal microscopy (e.g. 14% reduction in median GFP::LMN-1 intensity in hypodermis at 25C; Figure 2E).

      The discordance between RAPID and live imaging for emr-1/EMR-1::mCh (a reduction in the intestine or the hypodermis according to RAPID or live imaging, respectively) is not surprising. Although mRNA and protein levels in general correlate well, often, variation in transcription can only explain We have added these two sentences to the manuscript:

      “In agreement with these microscopy data, analysis of whole-worm mRNA levels by quantitative RT-PCR also revealed a significant reduction in lmn-1 expression whereas emr-1 was unaffected (Supplementary Figure S4E-F).”

      “As described above, the amount of endogenously tagged EMR-1::mCh at the NE of intestinal cells was normal in baf-1(G12T) mutants (Supplementary Figure S5F), suggesting a cellular capacity to buffer the downregulation of emr-1 transcription (Vogel & Marcotte, 2012).”

      3.) The authors find few alterations in gene regulation of the loci which have different occupancy WT BAF-1 versus BAF-1 G12T. It was surprising to see the DamID and RNA polymerase DamID experiments be done with worms grown at 20°C, because the more penetrant phenotypes at the organismal level were observed at 25°C. Could this be the reason for the little change of chromatin occupancy of BAF-1 and BAF-1 G12T or few changes in gene expression? Would it make sense to examine the expression of some selected BAF-1 bound loci by single molecule Fish at 25°C and compare expression wt versus baf-1 G12T?

      We performed the DamID experiments at 20°C to avoid potential artifacts and/or toxicity by higher expression levels of Dam fusion proteins (Greil, Moorman, & van Steensel, 2006; Schuster et al., 2010). We note that altered UV and tert-butyl hydroperoxide was observed at 20°C, indicating that the baf-1(G12T) allele affects physiology at several temperatures. The original version of our manuscript described the expression of fluorescently tagged LMN-1 and EMR-1 in the hypodermis at 20°C (Figure 2E-F). As described above, in the revised version, we report the expression in the intestine at 20°C and in both tissues at 25°C. For GFP::LMN-1, a similar reduction in the baf-1(G12T) mutant was observed at the two temperatures in both tissues, whereas for EMR-1::mCh a reduction was only seen in the hypodermis at 20°C. Taken together, we conclude that 20°C is a suitable temperature for the DamID experiments.

      We appreciate the suggestion to study expression of genes bound by BAF-1 by smFISH. However, we anticipate that because the hypodermis is composed mostly of large syncytia covering the round body of the animal, smFISH would be difficult to quantify. Regarding loci with different occupancy of WT BAF-1 versus BAF-1(G12T), the emr-1 locus was bound in the intestine by Dam::BAF-1 but not by Dam::BAF-1(G12T) (Figure 6B). As mentioned above, we observed that emr-1 expression was reduced in intestine of baf-1(G12T) mutants, suggesting that BAF-1 binding has a positive effect of transcription of this locus.

      4.) The finding that BAF-1 nuclear envelope localization remains unchanged in the mutant stems from detection of the inserted GFP epitope. Given that the tag has an influence on the BAF-1 G12 12T mutant viability, this statement should be phrased with more care. The tag could influence the turnover of the protein for example. Maybe Western blots comparing the signal of WT BAF-1 worms and BAF-1 G12T mutant worms would be instructive to compare the levels of the protein (at 20oC and at 25oC, day 1 adults and day 8 adults).

      We performed Western blot experiments to address this. As controls, we included strains expressing equal amounts of GFP::BAF-1 and GFP::BAF-1(G12T) strains (Figure 3E and Supplementary Figure 7 in original manuscript reported equal expression of the two proteins). Surprisingly, the polyclonal anti-BAF-1 serum raised against recombinant, full-length wild type BAF-1 (Gorjanacz et al., 2007) has significantly lower affinity for mutant GFP::BAF-1(G12T) than for GFP::BAF-1, which precludes the evaluation of untagged proteins:

      Figure 1. [png file provided to reviewers - not possible to include here for technical reasons] Western blot analyses with anti-BAF-1 serum (Gorjanacz et al, 2007). (A) Embryonic extracts. A band of the expected size is observed in wildtype embryos (*), but not in baf-1(G12T) embryos. (B) Extracts from young adults. A faint band of the expected size is observed in wildtype embryos (* in lane 1; longer exposure is shown below), whereas a more prominent band is present corresponding to endogenously tagged GFP::BAF-1 (** in lane 2). The intensity of the potential GFP::BAF-1(G12T) is reduced by >80% (lane 4; >90% reduction was observed in a second experiment).

      We point out in the revised manuscript that the conclusion on equal BAF-1 and BAF-1(G12T) expression was based on endogenously tagged proteins: “Quantifying the intensity at the NE or in the nucleoplasm of hypodermal cells did not demonstrate any difference between endogenously GFP-tagged wild-type and mutant BAF-1 (Figure 3E). A small reduction in cytoplasmic signal was observed for BAF-1(G12T), however, no difference was detected in the ratio between nucleoplasmic/cytoplasmic signal (Figure 3E). Quantitative RT-PCR analysis of whole-worm RNA samples also indicated that baf-1 and baf-1(G12T) are expressed at identical levels (Supplementary Figure S4E-F).”

      5.) Line 105: typo: remove "s"

      Corrected.

      6.) Line 154: A conclusion is missing for the fog-2 experiment.

      We have modified the text as follows: “To test this possibility, we incubated baf-1(G12T) males with fog-2(q71) feminized worms that only produce oocytes and counted daily offspring. At 25°C, the fog-2(q71) allele prevents spermatogenesis specifically in XX hermaphrodites whereas X0 males are unaffected (Schedl & Kimble, 1988). We observed a reduction in brood size of approximately one third when sperm came from baf-1(G12T) males (Supplementary Figure S2B, C). Thus, we concluded that the baf-1(G12T) mutation has a negative impact on spermatogenesis. The male/female ratio in the progeny was ~1, suggesting that meiotic segregation of chromosomes was normal in baf-1(G12T) males.”

      7). Would it make sense to discuss a possible influence of altered lamin binding to the nuclear envelope in the mutant in the context of the gene expression results?

      We agree that this point is relevant, and we have added the following text to the Discussion: “At current, we can only speculate about how the NGPS mutation might affect gene expression. Proteomics analyses indicate that BAF interacts with several histones and transcription factors (Montes de Oca, Shoemaker, Gucek, Cole, & Wilson, 2009), and the differences between BAF-1 and BAF-1(G12T)’s chromatin binding profiles reported here might be accompanied by changes in the association of chromatin factors at the deregulated loci. A particularly interesting candidate is GCL-1/germ cell-less 1, a repressive factor involved in spermatogenesis (Holaska, Lee, Kowalski, & Wilson, 2003). Moreover, it is plausible that the diminished recruitment of LMN-1 to the NE in baf-1(G12T) mutants modifies its interaction with the genome and with chromatin factors.”

      8). In a nutshell, the authors have established a convincing accessible model system for studying aging, ready for consecutive testing interventions to reduce the pace of premature aging.

      We appreciate and share the opinion of the reviewer.

      Reviewer #2

      1). The value of this work is two-fold: First, it is a very robust characterization of NGPS worms. Second, this will be a very useful model for the study of NGPS. Overall, the study is well-designed, technically strong, and the results are carefully and thoughtfully interpreted, which is nicely exemplified by the discussion of the relatively small number of genes which are differentially bound by BAF1 and are also differentially expressed and the authors do a good job of not overinterpreting the data, but simply state them. The results are convincing and informative.

      We thank the reviewer for her/his positive evaluation.

      My only minor point that may make this paper marginally better is that it would be nice to have a paragraph in the Discussing elaborating on the potential and the limitations of using the worm model to understand human NGPS, for example, humans have multiple lamin proteins etc.

      We agree with the reviewer and have added the following text to the Discussion: “We note that the simplicity of invertebrates also implies certain limitations. For instance, while both human and C. elegans genomes contain a single BAF gene, humans, but not C. elegans, express multiple lamin isoforms in tissue-specific ratios that regulate chromatin organization and nuclear mechanics (Swift et al., 2013). Thus, C. elegans is not suitable to explore potential differences in how wild type and NGPS BAF interacts differently with the various lamin isoforms.”

      Reviewer #3

      1). Overall, this manuscript strongly supports the major conclusion that this C. elegans line is a powerful model for human NGPS that complements a previously reported Drosophila model. Equally importantly, from the viewpoint of fundamental discovery, this manuscript also reports major advances in understanding how BAF influences gene expression at the molecular level.

      We thank the reviewer for her/his positive evaluation.

      2). DamID-Baf-1 access to chromatin was unaffected by the G12T mutation (Fig. S7), but they successfully identified subsets of genes 'occupied' by baf-1 in specific cell types, some of which were significantly affected in opposite ways by the NGPS mutation (Fig. 4, Fig. 5). However, these important new results are described too briefly, and discussion is inadequate. E.g., in hypodermal cells, the baf-1 G12T mutation dysregulated genes encoding proteins in five categories (ribosomal, proton transport, cuticle components, cell surface, lysine acetylation), by downregulating genes in three categories (ribosomal, proton transport, histone acetylation) and upregulating three other categories (cuticle components, cell surface, apical region). In intestinal cells, the mutation dysregulated genes in 8 categories (ribosomal, response to X-ray, proton transport, proteasome binding, mitochondrial protein import, endopeptidase activity, carboxy-lyase activity, ATP generation), by downregulating genes in 5 categories (ribosomal, proton transport, peptidase activity, NAD binding, metal cluster binding) and upregulating 3 categories (ribosomal, response to external stimulation, histone acetylation). Opposite results for "ribosomal genes" is confusing. Examples of genes in each affected category are shown in Fig. 6. To fully interpret this data, and address apparently-conflicting results, further analysis is needed to determine if any affected groups of genes have shared regulators. For example, Fig 5E shows "ribosomal protein genes" are both up- and down-regulated by the mutation. The authors should consider: (a) WHICH ribosomal genes are in each category, and (b) does either group of genes have known regulators that might be differentially affected by the baf-1 mutation? Similar consideration of other sets of differentially-affected genes might provide novel insight into specific chromatin-regulatory proteins (e.g., potential baf-1 partners; see next paragraph) affected by the NGPS mutation.

      At first it may seem confusing that some ribosomal genes are downregulated while others are upregulated. However, the baf-1(G12T) mutant represents a disease situation and not a process of natural selection where one might expect “meaningful” groups of up- and down-regulated genes. We have looked closer at the individual deregulated ribosomal genes and found genes encoding structural components of large ribosomal subunits that are either upregulated (rpl-10, rpl-29, rpl-36) or downregulated (rpl-1, rpl-3, rpl-30) in the intestine. Although these opposite behaviors might seem confusing, we propose that they reflect deregulation of ribosome biosynthesis, which is in concordance with the observations in NGPS fibroblasts (Breusegem et al., 2022). We agree that it will be important to investigate how the NGPS mutation induces these oppositely directed effects on gene expression. We found a significant higher association of the 13 deregulated ribosomal genes to BAF-1(G12) than to BAF-1 in the intestine, but we believe it goes beyond the scope of this manuscript to focus on the underlying mechanisms.

      3). The current manuscript is too strictly focused on establishing C. elegans as a model for NGPS, and neglects the novel discoveries. The authors did not consider or discuss HOW a baf-1 mutation might cause such complex gene expression outcomes- given that baf-1 binds dsDNA nonspecifically. One plausible molecular explanation is that the NGPS mutation might affect baf-1 interactions with: (a) transcription factors (Requiem, RBBP4, DDB1) or chromatin-regulators (PARP1; UV-regulated interactions with DDB2 and CUL4A) identified as BAF-associated in a proteomic study (Montes de Oca et al., 2009), or (b) histone modifiers such as SET/I2PP2A (blocks H3 dephosphorylation) or H3K9 methyltransferase 'G9a' (Montes de Oca et al., 2011), or (c) other regulators that control affected genes identified in this manuscript.

      We agree that this point is very relevant, but at this point we do not have experimental support for any of these possibilities. As indicated in the response to Reviewer #2, we have added the following text to the Discussion: “At current, we can only speculate about how the NGPS mutation might affect gene expression. Proteomics analyses indicate that BAF interacts with several histones and transcription factors (Montes de Oca et al., 2009), and the differences between BAF-1 and BAF-1(G12T)’s chromatin binding profiles reported here might be accompanied by changes in the association of chromatin factors at the deregulated loci. A particularly interesting candidate is GCL-1/germ cell-less 1, a repressive factor involved in spermatogenesis (Holaska et al., 2003). Moreover, it is plausible that the diminished recruitment of LMN-1 to the NE in baf-1(G12T) mutants modifies its interaction with the genome and with chromatin factors.”

      4). Figures 1, 2, 4, 5: the graphs in Fig 1A,B,D-F and Fig 2B,D and the colorscales in Fig 4F and Fig 5E are uninterpretable when printed in black-and-white. Please fix Figs 1 and 2 using black/light-gray/white/stippled for bar graphs, and black/light-gray/solid/dotted/dashed for line graphs. Fig 2B can be fixed by direct-labeling of class numbers within each bar (instead of 'color-coding' separately).

      We thank the reviewer for this suggestion. We have modified the figures to enable better visualization when printed in BW.

      5). Revise abstract lines 40-42 ("suggesting a direct relationship between BAF-1 binding [to what?] and gene expression") to reflect the deeper analysis.

      We have rephrased this sentence, so it now reads: “Most genes deregulated by the baf-1(G12T) mutation were characterized by a change in BAF-1 association, suggesting a direct relation between association of a gene to BAF-1 and its expression.” However, we prefer to not extend into speculations in the abstract because of lack of experimental evidence.

      6). Lines 132-155 (Figure 1): The impact on sperm production suggests the NGPS mutation might affect association with Germ cell-less (GCL), a transcription repressor that competes with BAF for binding to emerin in mammalian cells (Holaska et al., 2003 JBC).

      This is indeed an interesting possibility and we have incorporated it into to Discussion (see answer to point 3 above).

      7). Lines 151-154: Did not understand the fog-2 'feminized worm' experiments. Please briefly explain for non-worm experts.

      Please see our response to Reviewer #1’s point 6.

      8). Line 190: Clarify that nuclear shapes were categorized manually by single-blind observer.

      We have amended the text: “Nuclei were manually classified by single-blind observer based on their morphology as previously described (Perez-Jimenez, Rodriguez-Palero, Rodenas, Askjaer, & Munoz, 2014), except that we introduced a fourth class to describe the most irregular nuclei (see Materials and Methods).”

      9). Line 237-252: Abnormal chromosome segregation and postmitotic nuclear assembly in all gfp::baf-1(G12T) embryos is fully consistent (not 'presumably causative'; line 251) with the embryonic loss-of-function phenotype for baf-1 (Margalit et al., 2005, PNAS) and is consistent with mutational disruption of binding to lamin (Liu J et al., 2000, MBC) and/or LEM-domain proteins (Liu J, Lee KK et al., 2003, PNAS).

      We thank the reviewer for pointing this out. We have added the following sentence: “These phenotypes are consistent with the effects of embryonic depletion of BAF-1 or LMN-1 (Liu et al., 2000; Margalit, Segura-Totten, Gruenbaum, & Wilson, 2005).”

      10). Lines 530-533: Baf-1 localization (mobility) in intestinal cells is known to change profoundly in response to heat shock, caloric restriction or food deprivation (Bar et al., 2014, MBC). It would be worthwhile testing, in future, whether the NGPS mutation affects baf-1 localization in response to these stresses.

      We appreciate this suggestion, and we agree with the reviewer that it would be important to test this in future studies.

      Other changes:

      Missing column in Table S3 added.

      Mistake if column heading in Table S4 corrected.

      Breusegem, S. Y., Houghton, J., Romero-Bueno, R., Fragoso-Luna, A., Kentistou, K. A., Ong, K. K., . . . Larrieu, D. (2022). A multiparametric anti-aging CRISPR screen uncovers a role for BAF in protein translation. bioRxiv. doi:10.1101/2022.10.07.509469

      Gorjanacz, M., Klerkx, E. P., Galy, V., Santarella, R., Lopez-Iglesias, C., Askjaer, P., & Mattaj, I. W. (2007). Caenorhabditis elegans BAF-1 and its kinase VRK-1 participate directly in post-mitotic nuclear envelope assembly. Embo J, 26(1), 132-143. doi:10.1038/sj.emboj.7601470

      Greil, F., Moorman, C., & van Steensel, B. (2006). DamID: mapping of in vivo protein-genome interactions using tethered DNA adenine methyltransferase. Methods Enzymol, 410, 342-359. doi:10.1016/S0076-6879(06)10016-6

      Holaska, J. M., Lee, K. K., Kowalski, A. K., & Wilson, K. L. (2003). Transcriptional repressor germ cell-less (GCL) and barrier to autointegration factor (BAF) compete for binding to emerin in vitro. J Biol Chem, 278(9), 6969-6975.

      Janssen, A., Marcelot, A., Breusegem, S., Legrand, P., Zinn-Justin, S., & Larrieu, D. (2022). The BAF A12T mutation disrupts lamin A/C interaction, impairing robust repair of nuclear envelope ruptures in Nestor-Guillermo progeria syndrome cells. Nucleic Acids Res. doi:10.1093/nar/gkac726

      Liu, J., Rolef Ben-Shahar, T., Riemer, D., Treinin, M., Spann, P., Weber, K., . . . Gruenbaum, Y. (2000). Essential roles for Caenorhabditis elegans lamin gene in nuclear organization, cell cycle progression, and spatial organization of nuclear pore complexes. Mol Biol Cell, 11(11), 3937-3947.

      Margalit, A., Segura-Totten, M., Gruenbaum, Y., & Wilson, K. L. (2005). Barrier-to-autointegration factor is required to segregate and enclose chromosomes within the nuclear envelope and assemble the nuclear lamina. Proc Natl Acad Sci U S A, 102(9), 3290-3295. doi:10.1073/pnas.0408364102

      Montes de Oca, R., Shoemaker, C. J., Gucek, M., Cole, R. N., & Wilson, K. L. (2009). Barrier-to-autointegration factor proteome reveals chromatin-regulatory partners. PLoS ONE, 4(9), e7050. doi:10.1371/journal.pone.0007050

      Perez-Jimenez, M. M., Rodriguez-Palero, M. J., Rodenas, E., Askjaer, P., & Munoz, M. J. (2014). Age-dependent changes of nuclear morphology are uncoupled from longevity in Caenorhabditis elegans IGF/insulin receptor daf-2 mutants. Biogerontology, 15(3), 279-288. doi:10.1007/s10522-014-9497-0

      Puente, X. S., Quesada, V., Osorio, F. G., Cabanillas, R., Cadinanos, J., Fraile, J. M., . . . Lopez-Otin, C. (2011). Exome sequencing and functional analysis identifies BANF1 mutation as the cause of a hereditary progeroid syndrome. Am J Hum Genet, 88(5), 650-656. doi:10.1016/j.ajhg.2011.04.010

      Schedl, T., & Kimble, J. (1988). fog-2, a germ-line-specific sex determination gene required for hermaphrodite spermatogenesis in Caenorhabditis elegans. Genetics, 119(1), 43-61. doi:10.1093/genetics/119.1.43

      Schuster, E., McElwee, J. J., Tullet, J. M., Doonan, R., Matthijssens, F., Reece-Hoyes, J. S., . . . Gems, D. (2010). DamID in C. elegans reveals longevity-associated targets of DAF-16/FoxO. Mol Syst Biol, 6, 399. doi:10.1038/msb.2010.54

      Swift, J., Ivanovska, I. L., Buxboim, A., Harada, T., Dingal, P. C., Pinter, J., . . . Discher, D. E. (2013). Nuclear lamin-A scales with tissue stiffness and enhances matrix-directed differentiation. Science, 341(6149), 1240104. doi:10.1126/science.1240104

      Vogel, C., & Marcotte, E. M. (2012). Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet, 13(4), 227-232. doi:10.1038/nrg3185

      PeerReviewed
    2. EMBOpress 11 Jul 2024

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

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      Referee #3

      Evidence, reproducibility and clarity

      The mechanisms of rare human progeria syndromes caused by mutations in nuclear lamina proteins (lamins or BANF1) are still poorly understood, mainly because these proteins are complicated: they interact and are structurally essential for mitosis and nuclear assembly; hence, disrupting either protein can (and often does) disrupt the other. Lamins and BANF1 also have multiple interwoven roles with other partners involved in 3D genome organization, chromatin regulation, and tissue-specific gene regulation during interphase. To focus on Nestor-Guillermo progeria syndrome (NGPS), caused by the homozygous A12T missense mutation in human BANF1, the authors inserted the corresponding G12T mutation in C. elegans baf-1. They tested potential phenotypes at multiple levels (molecular, transcriptional, cellular and organismal) extensively and rigorously, and did careful controls to determine whether BAF, a tiny (89-aa) protein, was disrupted by fusion to proteins such as GFP or TurboID. Animals carrying the G12T mutation exhibited reduced lifespan (Fig. 1, S1), lower responses to UV irradiation and heat-stress (Fig 7B, 7C), and revealed unexpected germline-specific defects in male worms (Fig. S2, S3), and altered gene expression in two tissues affected by human HGPS (Figs. 4 and 5). Overall, this manuscript strongly supports the major conclusion that this C. elegans line is a powerful model for human NGPS that complements a previously reported Drosophila model.

      Equally importantly, from the viewpoint of fundamental discovery, this manuscript also reports major advances in understanding how BAF influences gene expression at the molecular level. Through careful attention to controls, and experimental design, the authors overcome many complications that make BAF difficult to study: its essential roles in mitosis and early embryogenesis, the 'tag'-sensitivity of endogenous BAF, and the absolute necessity to study BAF in native cell types. The authors carefully compared the impacts of tagging either baf-1 or lamin, and compared wildtype versus G12T-mutated baf-1 interactions with lamin and emerin (Fig. S5, S6, S8, S9; videos S1 and S2). DamID-Baf-1 access to chromatin was unaffected by the G12T mutation (Fig. S7), but they successfully identified subsets of genes 'occupied' by baf-1 in specific cell types, some of which were significantly affected in opposite ways by the NGPS mutation (Fig. 4, Fig. 5). However, these important new results are described too briefly, and discussion is inadequate. E.g., in hypodermal cells, the baf-1 G12T mutation dysregulated genes encoding proteins in five categories (ribosomal, proton transport, cuticle components, cell surface, lysine acetylation), by downregulating genes in three categories (ribosomal, proton transport, histone acetylation) and upregulating three other categories (cuticle components, cell surface, apical region). In intestinal cells, the mutation dysregulated genes in 8 categories (ribosomal, response to X-ray, proton transport, proteasome binding, mitochondrial protein import, endopeptidase activity, carboxy-lyase activity, ATP generation), by downregulating genes in 5 categories (ribosomal, proton transport, peptidase activity, NAD binding, metal cluster binding) and upregulating 3 categories (ribosomal, response to external stimulation, histone acetylation). Opposite results for "ribosomal genes" is confusing. Examples of genes in each affected category are shown in Fig. 6. To fully interpret this data, and address apparently-conflicting results, further analysis is needed to determine if any affected groups of genes have shared regulators. For example, Fig 5E shows "ribosomal protein genes" are both up- and down-regulated by the mutation. The authors should consider: (a) WHICH ribosomal genes are in each category, and (b) does either group of genes have known regulators that might be differentially affected by the baf-1 mutation? Similar consideration of other sets of differentially-affected genes might provide novel insight into specific chromatin-regulatory proteins (e.g., potential baf-1 partners; see next paragraph) affected by the NGPS mutation.

      The current manuscript is too strictly focused on establishing C. elegans as a model for NGPS, and neglects the novel discoveries. The authors did not consider or discuss HOW a baf-1 mutation might cause such complex gene expression outcomes- given that baf-1 binds dsDNA nonspecifically. One plausible molecular explanation is that the NGPS mutation might affect baf-1 interactions with: (a) transcription factors (Requiem, RBBP4, DDB1) or chromatin-regulators (PARP1; UV-regulated interactions with DDB2 and CUL4A) identified as BAF-associated in a proteomic study (Montes de Oca et al., 2009), or (b) histone modifiers such as SET/I2PP2A (blocks H3 dephosphorylation) or H3K9 methyltransferase 'G9a' (Montes de Oca et al., 2011), or (c) other regulators that control affected genes identified in this manuscript.

      Other clarifications and revisions to improve the manuscript:

      Figures 1, 2, 4, 5: the graphs in Fig 1A,B,D-F and Fig 2B,D and the colorscales in Fig 4F and Fig 5E are uninterpretable when printed in black-and-white. Please fix Figs 1 and 2 using black/light-gray/white/stippled for bar graphs, and black/light-gray/solid/dotted/dashed for line graphs. Fig 2B can be fixed by direct-labeling of class numbers within each bar (instead of 'color-coding' separately).

      Revise abstract lines 40-42 ("suggesting a direct relationship between BAF-1 binding [to what?] and gene expression") to reflect the deeper analysis.

      Lines 132-155 (Figure 1): The impact on sperm production suggests the NGPS mutation might affect association with Germ cell-less (GCL), a transcription repressor that competes with BAF for binding to emerin in mammalian cells (Holaska et al., 2003 JBC). Lines 151-154: Did not understand the fog-2 'feminized worm' experiments. Please briefly explain for non-worm experts.

      Line 190: Clarify that nuclear shapes were categorized manually by single-blind observer.

      Line 237-252: Abnormal chromosome segregation and postmitotic nuclear assembly in all gfp::baf-1(G12T) embryos is fully consistent (not 'presumably causative'; line 251) with the embryonic loss-of-function phenotype for baf-1 (Margalit et al., 2005, PNAS) and is consistent with mutational disruption of binding to lamin (Liu J et al., 2000, MBC) and/or LEM-domain proteins (Liu J, Lee KK et al., 2003, PNAS).

      Line 424: Agree that this new C. elegans model is important and strongly complements the Drosophila NGPS model.

      Lines 463-464: Agree that future suppressor analysis in this C. elegans model will be powerfully informative.

      Lines 530-533: Baf-1 localization (mobility) in intestinal cells is known to change profoundly in response to heat shock, caloric restriction or food deprivation (Bar et al., 2014, MBC). It would be worthwhile testing, in future, whether the NGPS mutation affects baf-1 localization in response to these stresses.

      Referees cross-commenting

      I agree with the comments from both other reviewers.

      Significance

      Overall, this manuscript strongly supports the major conclusion that this C. elegans line is a powerful model for human NGPS that complements a previously reported Drosophila model.

      PeerReviewed
    3. EMBOpress 11 Jul 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Romero-Bueno et al. have generated a C.elegans model of Nestor-Guillermo Progeria Syndrome (NGPS) caused by a point mutation in the BAF1 gene and they characterize the worm model. They find reduced fertility, reduced longevity and earlier aging symptoms in mutant animals compared to wild type animals. Looking at the molecular level, the authors find reduced accumulation of lamin A and emerin at the nuclear periphery in cells from mutant animals. They also find mitotic chromosome segregation defects. Using tissue-specific DamID, they show altered binding patters of the mutant protein to genome regions and they identify some gene groups which show both changes in gene expression and BAF1 binding. Finally, they show that BAF1 mutants are more resistant to oxidative stress than wild type animals.

      The value of this work is two-fold: First, it is a very robust characterization of NGPS worms. Second, this will be a very useful model for the study of NGPS. Overall, the study is well-designed, technically strong, and the results are carefully and thoughtfully interpreted, which is nicely exemplified by the discussion of the relatively small number of genes which are differentially bound by BAF1 and are also differentially expressed and the authors do a good job of not overinterpreting the data, but simply state them. The results are convincing and informative.

      My only minor point that may make this paper marginally better is that it would be nice to have a paragraph in the Discussing elaborating on the potential and the limitations of using the worm model to understand human NGPS, for example, humans have multiple lamin proteins etc.

      Referees cross-commenting

      I am glad to see that there is strong agreement that this is a valuable study.

      Significance

      The study is significant as it introduces a new animal model system to study an ultra-rare disease. The presented results are robust and convincing. This is the first worm model for this disease and it will be of interest to those studying laminopathies. The worm model is expected to reflect some of the human disease phenotypes but not all and a discussion of the potential and the limitation of the worm model to study NGPS would be welcomed.

      PeerReviewed
    4. EMBOpress 11 Jul 2024

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

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      Specific mutations in nuclear lamina proteins such as lamin A or BAF1 can cause premature aging syndromes (Huchinson Gilford progeria or Nestor Guillermo syndrome), which show age related deterioration of nuclear morphology as a hallmark and affected individuals have a severely shortened life span. In this study Romero-Bueno et al established an animal model system for the Nestor Guillermo syndrome, by generating C. elegans strains harboring homozygous baf-1::G12A mutations. They nicely recapitulate the expected cellular and organismal phenotypes: decreased life spans of the mutant animals and faster nuclear deterioration. In addition, the authors find reduced fertility in the mutant when BAF-1 was combined with a GFP tag and synthetic lethality when the baf-1::G12T mutant is introduced into strain carrying an epitope tagged Lamin allele. At the organismal level the authors report increased resistance to oxidative stress, but reduced thermotolerance and decreased UV resistance. By conducting tissue specific DamID together with tissue specific RNA polymerase DamID, the authors find that in the baf-1::G12T mutant the overall chromatin association of chromosome arms remains largely unchanged, however a few individual loci either lost or gained BAF-1 association. The authors report that loss of BAF-1 association with chromatin correlates with gene expression in some instances, however there was no strict uniform correlation. This is not surprising, because the changes in expression could be a secondary consequence of a BAF-1-mediated change of another locus or a consequence of altered lamin nucelar envelope association. The global pattern of BAF-1 and BAF-1 G12T binding to chromatin was very similar in both genotypes. The authors find unaltered localization of BAF-1 G 12T protein at the nuclear envelope, in contrast to reduced levels of lamin and emerin. Interestingly, BAF-1 is found on sperm, in contrast to the absence of other lamina proteins, like LMN-1 or Emerin.

      Major comments:

      1. In the baf-1 G12T mutants the authors find reduced levels of lamin in hypodermal nuclei. It would be good to also examine the dynamics of lamin in the second tissue that was subjected to DamID (intestinal cells).
      2. The authors make a statement that EMR-1 expression was reduced in the baf-1 G12T mutant, but do not comment on LMN-1 expression. Can a statement on this be made by RT PCR?
      3. The authors find few alterations in gene regulation of the loci which have different occupancy WT BAF-1 versus BAF-1 G12T. It was surprising to see the DamID and RNA polymerase DamID experiments be done with worms grown at 20oC, because the more penetrant phenotypes at the organismal level were observed at 25oC. Could this be the reason for the little change of chromatin occupancy of BAF-1 and BAF-1 G12T or few changes in gene expression? Would it make sense to examine the expression of some selected BAF-1 bound loci by single molecule Fish at 25oC and compare expression wt versus baf-1 G12T?

      Minor comments:

      The finding that BAF-1 nuclear envelope localization remains unchanged in the mutant stems from detection of the inserted GFP epitope. Given that the tag has an influence on the BAF-1 G12 12T mutant viability, this statement should be phrased with more care. The tag could influence the turnover of the protein for example. Maybe Western blots comparing the signal of WT BAF-1 worms and BAF-1 G12T mutant worms would be instructive to compare the levels of the protein (at 20oC and at 25oC, day 1 adults and day 8 adults)

      Line 105: typo: remove "s"

      Line 154: A conclusion is missing for the fog-2 experiment would it make sense to discuss a possible influence of altered lamin binding to the nuclear envelope in the mutant in the context of the gene expression results?

      Referees cross-commenting I also see this as a valuable study. I regretted a bit that the analysis was not done at the higher temperature when the authors saw the most prominent phenotypes--but I suppose the analysis is very expensive and time consuming.

      Significance

      Since a long time, it has remained a matter of debate whether the progeria T to G transition in BAF-1 reduces binding of BAF-1 to lamin or whether the mutation affects the binding of BAF-1 to chromatin and thereby alters chromatin organization. Conflicting results emerged from the studies of BAF1 mutants in tissue culture cells. For this reason, this study-conducted in the context of a whole animal-is very important: it allowed the author to do their experiments with cells with unaltered ploidy, expression from the endogenous promoters and in the context of defined tissues. A second conflicting finding concerned the localization of BAF-1 G 12 to T mutant protein at the nuclear envelope: some labs find it reduced at the nuclear envelope, others find unchanged amounts at the nuclear envelope. With this work the authors contributed novel and interesting findings to those ongoing discussions, they found both altered affinity of BAF-1 with chromatin (not on a global scale, but on a local scale) and reduced affinity to lamin.

      Furthermore, this is one of the first studies mapping BAF-1 association with individual gene loci in a specific tissue and the authors showed that in a given tissue BAF-1 tends to be associated with not expressed genes. In a nutshell, the authors have established a convincing accessible model system for studying aging, ready for consecutive testing interventions to reduce the pace of premature aging. Strengths: convincing presentation of a novel genetic model system to study progeria, first study where BAF-1 bound loci were shown from the analysis of a tissue (there is a correlation of BAF-1 bound loci, which are not expressed in the examined tissue), introduction of an easy-to-handle model to search for compounds suitable for clinical intervention for progeria patients or anti-aging drugs. This study adds some clarity to conflicting views in the filed: the NGS mutation in BAF-1 both reduces the amount of lamin at the nuclear periphery and affects the affinity of BAF-1 to chromatin.

      Limitations: the observed transcriptional changes in the mutant can be either a direct consequence of BAF-1 chromatin association or a consequence of an altered lamina since lamin is less stable at the nuclear envelope. The transcriptomic analysis was not conducted at the temperature at which penetrant phenotypes at the organismal level were observed.

      Advance: Previous studies presented conflicting results about the nuclear envelope localization of BAF-1 G12T protein: this study clearly shows that the localization of the protein remains unaltered. This study also clearly demonstrates that there is less lamin at the nuclear envelope in the mutant, lending support to the in vitro findings that the mutant is compromised in Lamin binding.

      Audience: The study will be of interest to anyone who studies the nuclear lamina, the nuclear envelope, progeria, aging and stress response of an organism. Beyond this a convincing powerful novel genetic system is being presented to study progeria, which is of interest to clinicians. It is also of interest for translational research, because the system can be used to screen for compounds, which could be useful for therapeutic intervention for progeria patients or for the identification of compounds that combat aging in general. Some of the presented synthetic effects with tagged strains open the opportunity to conduct genetic suppressor screens, which would be a wonderful entry point to collect more mechanistic insights in the phenomena of aging and stress response. This genetic system is an awesome starting point for further studies and advancements of elucidating the molecular mechanism of progeria by genetic screens.

      Expertise: I am a C. elegans geneticist and appreciate that all the conflicting results from tissue culture studies can now be compared to an analysis in a more physiological setting and the context of a real tissue and a living animal. I am not really competent to judge the sensitivity of RAPID assays.

      PeerReviewed
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    Specific proteolysis mediated by a p97-directed proteolysis-targeting chimera (PROTAC)
    3
    1. EMBOpress 11 Jul 2024

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      Reply to the reviewers

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

      The paper by Salinas-Rebolledo et al. describes a novel PROTAC approach in which the UBX domain of FAF1 is fused to a nanobody that recognizes the target protein. The idea is that the UBX domain will bind the fusion protein to the p97 ATPase, a major ATPase involved in the unfolding of many proteins. The target protein recognized by the UBX-nanobody fusion (UBX-Nb) is then supposed to be unfolded in a ubiquitin-independent manner and subsequently degraded by the proteasome.

      The authors provide evidence that Ubx-Nb, containing a nanobody recognizing GFP, can colocalize with GFP fusion proteins in the nucleus and to liquid-liquid phase separation structures. Importantly, the fusion can reduce the cellular levels of the target proteins. The authors confirm that degradation triggered by Ubx-Nb is proteasome dependent. Ubx-Nb can also promote the degradation of model proteins that form aggregates relevant to neurodegenerative diseases.

      __* The major issue with the paper is that it does not provide mechanistic insight into the degradation mechanism. First, the data implicating p97 in degradation are conflicting. On the one hand, siRNA of p97 compromises degradation (although degradation is not completely inhibited; see Figure 4G), but on the other hand, an inhibitor of p97 does not have an effect. The authors have not shown that target proteins are actually unfolded by their artificial adaptor (in vitro experiments would be required). __

      __In addition, it would be important to show co-localization in vivo with p97. __

      Thus, the role of p97 is not convincingly established. Another major question is how the unfolded, non-ubiquitinated proteins would be degraded by the 26S proteasome. Is there a ubiquitin ligase required after substrate unfolding?

      Overall, the paper reports some intriguing effects of their designed PROTAC adaptor, but the mechanism by which it functions remains unclear. The findings of the manuscript appears too preliminary in its current version for it to be of value to the community.

      Responses #1

      We appreciate the detailed feedback provided and acknowledge the reviewers' concerns regarding the mechanistic insight into the degradation process. Below, we address each point raised:

      We acknowledge that our current data do not fully elucidate the degradation mechanism involving p97. Our preliminary findings suggest that while siRNA of p97 compromises degradation, this effect is not absolute. Additionally, we recognize the inconsistency observed with the p97 inhibitor, which did not affect degradation. It is important to note that the selective inhibitor used in our study binds to the D2 domains of p97, as reported by Zhou et al. (J Med Chem. 2015). There are molecules that bind to the D1 domain and enhance p97-mediated degradation (Figuerola-Conchas et al., ACS Chem Biol. 2020). The primary ATPase function of p97 is associated with the D2 domain, but ATP binding to the D1 domain is crucial for hexamer formation and N-terminal domain conformation, which regulates cofactor binding and various functions of p97. Therefore, it is possible that our p97-PROTAC activates the D1 domain or interacts with cofactors enhancing protein degradation mediated by p97.

      We plan to conduct in vitro experiments to demonstrate that target proteins are unfolded by our artificial adaptor. We have already cloned the degradation system into a bacterial expression vector to express and purify the system for these in vitro studies, which will be carried out in California. Furthermore, we aim to show in vivo co-localization with p97 in future studies.

      *We understand the importance of establishing the role of p97 convincingly. Our preliminary data indicate the presence of residual p97 in siRNA experiments. Regarding the degradation of unfolded, non-ubiquitinated proteins by the 26S proteasome, there are studies indicating that various proteins are degraded by the proteasome independently of ubiquitin. Moreover, evidence suggests that different pools of the same protein can be directed to the proteasome via both ubiquitin-dependent and ubiquitin-independent mechanisms under the same cellular conditions. Also, prior research by Butler et al. (2016) demonstrated that fusing NbSyn87 with the mouse Ornithine Decarboxylase (ODC) PEST degron effectively reduced protein levels and this reduction was achieved by harnessing the innate cellular machinery responsible for ubiquitin-independent proteolysis. *

        • Makaros Y, Raiff A, Timms RT, Wagh AR, Gueta MI, Bekturova A, Guez-Haddad J, Brodsky S, Opatowsky Y, Glickman MH, Elledge SJ, Koren I. Ubiquitin-independent proteasomal degradation driven by C-degron pathways. Mol Cell. 2023 Jun 1;83(11):1921-1935.e7. doi: 10.1016/j.molcel.2023.04.023. Epub 2023 May 17. PMID: 37201526; PMCID: PMC10237035.*
        • Butler DC, Joshi SN, Genst E, Baghel AS, Dobson CM, Messer A. Bifunctional Anti-Non-Amyloid Component α-Synuclein Nanobodies Are Protective In Situ. PLoS One. 2016 Nov 8;11(11):e0165964. doi: 10.1371/journal.pone.0165964. PMID: 27824888; PMCID: PMC5100967.*
        • Erales J, Coffino P. Ubiquitin-independent proteasomal degradation. Biochim Biophys Acta. 2014 Jan;1843(1):216-21. doi: 10.1016/j.bbamcr.2013.05.008. Epub 2013 May 14. PMID: 23684952; PMCID: PMC3770795.*
        • Donghong Ju, Youming Xie, Proteasomal Degradation of RPN4 via Two Distinct Mechanisms, Ubiquitin-dependent and -independent*, Journal of Biological Chemistry, Volume 279, Issue 23, 2004, Pages 23851-23854, ISSN 0021-9258.*
      5. *

      We also speculate that the degradation may also occur via the autophagy-lysosome pathway. These speculations will be added to the discussion section, and we plan to investigate this pathway in detail in a subsequent scientific article focused on the mechanism of action of p97-PROTAC.

      We recognize the need for further mechanistic studies and plan to publish these preliminary findings while continuing our research to elucidate the degradation mechanism. Our future work includes determining the crystal structure and conducting mass spectrometry to identify other proteins interacting with this complex, potentially aiding in degradation. We also plan to test the system in vivo using murine models with alpha-synuclein overexpression, in collaboration with researchers in Spain. This long-term project will form the basis of a subsequent publication.

      We believe that our findings present an innovative and unique tool, and this preliminary data warrant publication. We appreciate the reviewers' comments and hope that our detailed response and future research plans address their concerns.

      Minor points:

      Fig. 1B: Although emerin is reported to be a nuclear envelope protein, it is not localized to the NE, but throughout the ER, likely because the protein was too highly expressed.

      We agree with the reviewer, the overexpression of the NE could leak into the ER. We do not have specific Nanobodies to directly degrade Emerin. However, we would like to make the point that in both cases the protein will conserve a single transmembrane domain and even then, the GFP Nanobody fused to the UBX domain is able to trigger degradation

      Fig. 1B: ETV co-localization is not obvious from the figure.

      We are going to repeating the experiment and quantify the colocalization as suggested

      Fig. 4: The depletion of p97 leads to cell death, so it is unclear whether the siRNA effect is specific.

      We appreciate your comment and would like to clarify that there are published studies where the p97 gene has been silenced in HeLa cells without causing complete cell death. While it is true that a significant number of cells die post-transfection, we have observed that by changing the cell culture medium daily, the remaining cells start to grow again.

      Studies supporting our findings include:

        • Wójcik C, Yano M, DeMartino GN. RNA interference of valosin-containing protein (VCP/p97) reveals multiple cellular roles linked to ubiquitin/proteasome-dependent proteolysis. J Cell Sci. 2004 Jan 15;117(Pt 2):281-92. doi: 10.1242/jcs.00841. Epub 2003 Dec 2. PMID: 14657277. *
        • Beskow A, Grimberg KB, Bott LC, Salomons FA, Dantuma NP, Young P. A conserved unfoldase activity for the p97 AAA-ATPase in proteasomal degradation. J Mol Biol. 2009 Dec 11;394(4):732-46. doi: 10.1016/j.jmb.2009.09.050. Epub 2009 Sep 24. PMID: 19782090.*
        • Yahiro K, Tsutsuki H, Ogura K, Nagasawa S, Moss J, Noda M. Regulation of subtilase cytotoxin-induced cell death by an RNA-dependent protein kinase-like endoplasmic reticulum kinase-dependent proteasome pathway in HeLa cells. Infect Immun. 2012 May;80(5):1803-14. doi: 10.1128/IAI.06164-11. Epub 2012 Feb 21. PMID: 22354021; PMCID: PMC3347452. Additionally, although our figure does not clearly show the band corresponding to p97, upon overexposing the film, we can detect a very faint band of the protein. This indicates that there is still residual expression of p97, albeit at a lower concentration, which is consistent with a significant reduction but not a complete elimination of the protein.*

      Fig. 5C: The colocalization of GFP-HTT Q23 with UBX-Nb(GFP) is not entirely convincing.

      We are going to repeating the experiment and quantify the colocalization as suggested

      Reviewer #1 (Significance (Required)):

      Overall, the paper reports some intriguing effects of their designed PROTAC adaptor, but the mechanism by which it functions remains unclear. The findings of the manuscript appears too preliminary in its current version for it to be of value to the community.

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

      Summary:

      The authors have developed a p97-directed proteolysis-targeting chimera (PROTAC) that operates independently of ubiquitin. This system employs a camelid nanobody to selectively recognize target proteins, tethered to p97 through the UBX domain of the p97 adapter FAF1. The anti-GFP nanobody effectively targets various GFP-fusion proteins for degradation via the proteasome, relying on p97 for its mechanism of action. The authors validate the presence of p97 in brain tissues of Non-Human Primates (Nhp) Macaca fascicularis, rat (Sprague Dawley), and mouse (C57BL6/C), supported by proteasome inhibition and p97 RNA silencing data. Importantly, the p97-PROTAC mechanism operates independently of ubiquitination, demonstrated through degradation of clinically relevant proteins such as alpha-synuclein using a camelid nanobody (NbSyn87).

      Major comments:

      * Anti-GFP Nanobody clarification: Details about the original anti-GFP nanobody are unclear, which makes reproducing the current work a challenge for outside labs.

      o 20. Fulcher LJ, Macartney T, Bozatzi P, Hornberger A, Rojas-Fernandez A, Sapkota GP. An affinity-directed protein missile system for targeted proteolysis. Open Biol. Oct 2016;6(10)doi:10.1098/rsob.160255

      o I assume that the anti-GFP nanobody is aGFP from supplementary figure #2 in the Fulcher manuscript but is unclear as they also have used anti-GFP nanobody aGFP16.

      * Amino acids from FAF1-UBX domain: Further clarity is needed regarding the amino acid details from the FAF1-UBX domain, which may have been disclosed in a patent application but should be explicitly outlined in the methods section.

      We appreciate your comment regarding the need for further clarity on the amino acid details from the FAF1-UBX domain. To address this, we have added a supplementary figure which includes a table outlining the amino acid sequences of our construct and the FAF1-UBX domain. This supplementary figure provides a detailed representation of the amino acid sequences. We hope this addition meets your requirements and provides the necessary information for a comprehensive understanding of our work.

      __* Degradation of Proteins of Clinical Interest: The data presented is not convincing enough to support the stated claims that the PROTAC is clearing aggregated mutant HTT. In Figure 5, there is an abundance of GFP-HTT Q74 puncta. While the western blot data suggests a reduction of soluble GFP-HTT-Q74 protein levels, it does not account for aggregated HTT. Aggregated HTT does not efficiently enter the separating gel during electrophoresis. To make these claims the authors need to 1. Show the level of mHTT Q74 aggregation in the empty control groups so that a comparison can be visually made between empty control groups and UBX-Nb(GFP) treated groups. A similar comparison would be useful with the GFP-HTT Q23 treated cells as well. __

      * Visualization of Aggregated Proteins: The continued visibility of puncta raises doubts about the system's efficacy in degrading aggregated proteins. Including comparisons between untreated and treated cells for all test systems would strengthen the argument. It would be useful to show a comparison between the untreated controls and UBX-Nb (GFP) treated cells for all the test systems shown.

      *We acknowledge that the data presented in Figure 5 may not be sufficient to support the claim that the PROTAC is clearing aggregated mutant HTT. The western blot data suggests a reduction in soluble GFP-HTT-Q74 protein levels, but it does not account for aggregated HTT, which does not efficiently enter the separating gel during electrophoresis. We agree that more experiments will need to be performed to evaluate the impact of the p97 PROTAC on the direct turnover of the aggregates once those are form. *

      Minor comments:

      * The In-text citations should be placed outside of the sentence. Example: The ubiquitin-proteasome system (UPS) regulates protein abundance by specific E3 ubiquitin ligases, which catalyze ubiquitin chain formation on the substrates, inducing their proteasome mediated degradation. 1-4

      * Sentence two in the introduction is missing a period. It is unclear whether sentence three is a heading or part of paragraph one.

      * There are additional formatting issues. It would be easier to read the paper if there was a space between paragraphs. Page numbers would be helpful.

      * Page 2. Missing word. Inclusion body myopathy associated with Paget's disease.

      * Figure 1. D, F, and E. Missing annotation to denote significance.

      * Figure 2G Missing annotation to denote significance.

      * Figure 4. Missing annotation to denote significance for figures 4D, 4F, 4H.

      * Is Figure 4I significantly different or not? In Figure 6, you use ns to denote not significant. This feels like it is an important point that you would want to make that the effect is dependent on p97. When you knock out p97 the degradation capacity of UBX-Nb is lost.

      Response

      These changes are going to be apply

      Reviewer #2 (Significance (Required)):

      * The p97-PROTAC system is an ubiquitin-independent approach to degrade intracellular proteins. This system was able to target proteins for degradation at diverse subcellular locations, integral membrane protein residing at the inner nuclear membrane, chromatin located, and liquid-liquid phase separated compartments. The ability to clear alpha-synuclein builds on previous research suggesting that ubiquitin-independent degradation of alpha-synuclein could be a therapeutic approach to treat synucleinopathies such as Parkinson's Disease. However, the ability of this approach to clear aggregated proteins is not convincing, given the presence of visible aggregates in the treated cells.

      * The investigations with NbSyn87 build upon prior research by Butler et al. (2016), who fused NbSyn87 with the mouse Ornithine decarboxylase (ODC) PEST degron. This fusion strategy not only facilitates the targeting of alpha-synuclein but also harnesses the innate cellular machinery responsible for ubiquitin-independent proteolysis. The current approach demonstrates and alternative mechanism to direct alpha-synuclein (and other proteins) into the proteasome for ubiquitin-independent clearance.

      * At the current state of development, this research is of interest to specialized audience with antibody engineering backgrounds; however, it holds translational potential for clearance of toxic proteins.

      * My research interests is in the development of therapeutics for the treatment of neurodegenerative diseases including Huntington's Disease, Parkinson's Disease, and Alzheimer's Disease.

      PeerReviewed
    2. EMBOpress 11 Jul 2024

      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 #2

      Evidence, reproducibility and clarity

      Summary:

      The authors have developed a p97-directed proteolysis-targeting chimera (PROTAC) that operates independently of ubiquitin. This system employs a camelid nanobody to selectively recognize target proteins, tethered to p97 through the UBX domain of the p97 adapter FAF1. The anti-GFP nanobody effectively targets various GFP-fusion proteins for degradation via the proteasome, relying on p97 for its mechanism of action. The authors validate the presence of p97 in brain tissues of Non-Human Primates (Nhp) Macaca fascicularis, rat (Sprague Dawley), and mouse (C57BL6/C), supported by proteasome inhibition and p97 RNA silencing data. Importantly, the p97-PROTAC mechanism operates independently of ubiquitination, demonstrated through degradation of clinically relevant proteins such as alpha-synuclein using a camelid nanobody (NbSyn87).

      Major comments:

      • Anti-GFP Nanobody clarification: Details about the original anti-GFP nanobody are unclear, which makes reproducing the current work a challenge for outside labs.
          1. Fulcher LJ, Macartney T, Bozatzi P, Hornberger A, Rojas-Fernandez A, Sapkota GP. An affinity-directed protein missile system for targeted proteolysis. Open Biol. Oct 2016;6(10)doi:10.1098/rsob.160255
        • I assume that the anti-GFP nanobody is aGFP from supplementary figure #2 in the Fulcher manuscript but is unclear as they also have used anti-GFP nanobody aGFP16.
      • Amino acids from FAF1-UBX domain: Further clarity is needed regarding the amino acid details from the FAF1-UBX domain, which may have been disclosed in a patent application but should be explicitly outlined in the methods section.
      • Degradation of Proteins of Clinical Interest: The data presented is not convincing enough to support the stated claims that the PROTAC is clearing aggregated mutant HTT. In Figure 5, there is an abundance of GFP-HTT Q74 puncta. While the western blot data suggests a reduction of soluble GFP-HTT-Q74 protein levels, it does not account for aggregated HTT. Aggreggated HTT does not efficiently enter the separating gel during electrophoresis. To make these claims the authors need to 1. Show the level of mHTT Q74 aggregation in the empty control groups so that a comparison can be visually made between empty control groups and UBX-Nb(GFP) treated groups. A similar comparison would be useful with the GFP-HTT Q23 treated cells as well.
      • Visualization of Aggregated Proteins: The continued visibility of puncta raises doubts about the system's efficacy in degrading aggregated proteins. Including comparisons between untreated and treated cells for all test systems would strengthen the argument. It would be useful to show a comparison between the untreated controls and UBX-Nb (GFP) treated cells for all the test systems shown.

      Minor comments:

      • The In-text citations should be placed outside of the sentence. Example: The ubiquitin-proteasome system (UPS) regulates protein abundance by specific E3 ubiquitin ligases, which catalyze ubiquitin chain formation on the substrates, inducing their proteasome mediated degradation. 1-4
      • Sentence two in the introduction is missing a period. It is unclear whether sentence three is a heading or part of paragraph one.
      • There are additional formatting issues. It would be easier to read the paper if there was a space between paragraphs. Page numbers would be helpful.
      • Page 2. Missing word. Inclusion body myopathy associated with Paget's disease.
      • Figure 1. D, F, and E. Missing annotation to denote significance.
      • Figure 2G Missing annotation to denote significance.
      • Figure 4. Missing annotation to denote significance for figures 4D, 4F, 4H.
      • Is Figure 4I significantly different or not? In Figure 6, you use ns to denote not significant. This feels like it is an important point that you would want to make that the effect is dependent on p97. When you knock out p97 the degradation capacity of UBX-Nb is lost.

      Significance

      • The p97-PROTAC system is an ubiquitin-independent approach to degrade intracellular proteins. This system was able to target proteins for degradation at diverse subcellular locations, integral membrane protein residing at the inner nuclear membrane, chromatin located and liquid-liquid phase separated compartments. The ability to clear alpha-synuclein builds on previous research suggesting that ubiquitin-independent degradation of alpha-synuclein could be a therapeutic approach to treat synucleinopathies such as Parkinson's Disease. However, the ability of this approach to clear aggregated proteins is not convincing, given the presence of visible aggregates in the treated cells.
      • The investigations with NbSyn87 build upon prior research by Butler et al. (2016), who fused NbSyn87 with the mouse Ornithine decarboxylase (ODC) PEST degron. This fusion strategy not only facilitates the targeting of alpha-synuclein but also harnesses the innate cellular machinery responsible for ubiquitin-independent proteolysis. The current approach demonstrates and alternative mechanism to direct alpha-synuclein (and other proteins) into the proteasome for ubiquitin-independent clearance.
      • At the current state of development, this research is of interest to specialized audience with antibody engineering backgrounds; however, it holds translational potential for clearance of toxic proteins.
      • My research interests is in the development of therapeutics for the treatment of neurodegenerative diseases including Huntington's Disease, Parkinson's Disease, and Alzheimer's Disease.
      PeerReviewed
    3. EMBOpress 11 Jul 2024

      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

      The paper by Salinas-Rebolledo et al. describes a novel PROTAC approach in which the UBX domain of FAF1 is fused to a nanobody that recognizes the target protein. The idea is that the UBX domain will bind the fusion protein to the p97 ATPase, a major ATPase involved in the unfolding of many proteins. The target protein recognized by the UBX-nanobody fusion (UBX-Nb) is then supposed to be unfolded in a ubiquitin-independent manner and subsequently degraded by the proteasome.

      The authors provide evidence that Ubx-Nb, containing a nanobody recognizing GFP, can colocalize with GFP fusion proteins in the nucleus and to liquid-liquid phase separation structures. Importantly, the fusion can reduce the cellular levels of the target proteins. The authors confirm that degradation triggered by Ubx-Nb is proteasome dependent. Ubx-Nb can also promote the degradation of model proteins that form aggregates relevant to neurodegenerative diseases.

      The major issue with the paper is that it does not provide mechanistic insight into the degradation mechanism. First, the data implicating p97 in degradation are conflicting. On the one hand, siRNA of p97 compromises degradation (although degradation is not completely inhibited; see Figure 4G), but on the other hand, an inhibitor of p97 does not have an effect. The authors have not shown that target proteins are actually unfolded by their artificial adaptor (in vitro experiments would be required). In addition, it would be important to show co-localization in vivo with p97. Thus, the role of p97 is not convincingly established. Another major question is how the unfolded, non-ubiquitinated proteins would be degraded by the 26S proteasome. Is there a ubiquitin ligase required after substrate unfolding?

      Overall, the paper reports some intriguing effects of their designed PROTAC adaptor, but the mechanism by which it functions remains unclear. The findings of the manuscript appears too preliminary in its current version for it to be of value to the community.

      Specific points:

      Fig. 1B: Although emerin is reported to be a nuclear envelope protein, it is not localized to the NE, but throughout the ER, likely because the protein was too highly expressed.

      Fig. 1B: ETV co-localization is not obvious from the figure.

      Fig. 4: The depletion of p97 leads to cell death, so it is unclear whether the siRNA effect is specific.

      Fig. 5C: The colocalization of GFP-HTT Q23 with UBX-Nb(GFP) is not entirely convincing.

      Significance

      Overall, the paper reports some intriguing effects of their designed PROTAC adaptor, but the mechanism by which it functions remains unclear. The findings of the manuscript appears too preliminary in its current version for it to be of value to the community.

      PeerReviewed
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    The Sfp1 transcription factor integrates inputs from the TORC1 and PKA pathways
    3
    1. EMBOpress 11 Jul 2024

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      Reply to the reviewers

      Reviewer 1

      The paper is overall convincing. However, a little more attention to data presentation and possibly the addition of at least another technique (see below) would greatly strengthen the findings.

      As we hope to demonstrate below, we have taken steps to improve our manuscript on both fronts (data presentation and experimental evidence).

      The absence of statistics catches immediately the eye. I am sure that the shown differences are statistically significant (thanks to the number of analyzed cells), but reporting the result of some statistical test would help the reader in identify the relevant data in a plot. This is somehow necessary considering that sometimes in the text something is deemed to be "significant" or "not significant", and I felt that I really needed that when looking at the plot in Fig. 3D.

      To facilitate the interpretation of figures that contain data from multiple strains (such as the one mentioned by the reviewer), we have carried out a nonparametric single-step multiple comparison test (Games-Howell) to identify mutants whose means differ significantly from each other. To avoid overcrowding the figures, we have graphically summarized the p-values of all pairwise comparisons in a small matrix within the corresponding panel, and provided 99% confidence intervals and p-values of all differences in the Supplement.

      Related to the previous point: for every N/C distribution analysis, a number of analyzed cells is reported. By the way it is written, it seems that the replication relies solely by the cells in that specific population, i.e.: each cell is treated as a replicate. At least I could not find if that is not the case in the legends or in the methods. I wonder what the results would be (and their significance) if each replicate would be a new assay on another population.

      Cell populations exhibit significant variability in their phenotypic characteristics. Consequently, the quantification of a specific feature (e.g., the Sfp1 nuclear/cytoplasmic ratio) across a sample of cells from a given population results in a distribution rather than a single fixed value. For each quantification, we report the number of cells that were used to construct the corresponding distribution, i.e. the sample size. To compare samples from different populations (e.g., different Sfp1 mutant strains), we run them in parallel during microscopy experiments and compare their means, as described above. Throughout our study, we have tried to ensure that we quantify a sufficiently large number of cells to overcome cell-to-cell variability and enhance the reliability of our results.

      In this context, the question of the reviewer is not entirely clear to us, as individual measurements of a sample are not replicates. However, one can replicate the entire experiment on a different day by re-growing the different strains, running microscopy, quantifying the new movies etc. In this sense, the experiments shown in the manuscript consist of single replicates, i.e. experiments that were carried out on the same day, with all the relevant mutants and controls quantified together. However, we have monitored many of our mutants multiple times over the course of our work. For example, Fig. 1 below shows replicates of the Sfp1 N/C ratio distributions at steady-state in the analog-sensitive (A) and wild-type (B) background, which were quantified several times across various experiments. While day-to-day variability in the empirical distributions of the same mutant exists to a small extent, it is quite small.

      The scale of x axes in N/C ratio plots. Besides not being consistent throughout the figures, it originates from 1, visually enhancing the differences.

      We believe the reviewer was referring to the y-axes, as the x-axes represent time. Summarizing the N/C ratio dynamics of different Sfp1 mutants has been challenging. First, the average N/C ratios at steady-state vary considerably across different mutants, as shown in the panels that summarize steady-state N/C ratios. To compare the magnitude and features of their responses, normalization is necessary. We chose to normalize the time series of each mutant to have a mean of 1 prior to the onset of a perturbation. This allows the normalized time series to represent the percentage-wise changes in the Sfp1 N/C ratio upon perturbation.

      Using a common y-axis scale for all plots of N/C ratio dynamics not ideal, as some responses are subtler than others. Additionally, we do not believe that N/C dynamics across different figures need to (or should) be compared to each other. However, within a figure, panels that require comparison are placed in the same row and share the same y-axis scale. We believe that this approach optimizes data visualization and facilitates important visual comparisons.

      Related to the previous point: it is evident from the plots that the N/C ratio is always positive, even in the most deficient of the analyzed mutants. This implies that a relevant fraction of Sfp1 is still nuclear. I thus wonder what the impact of these mutations would be on the actual function of Sfp1. For this reason, I feel that qPCR evaluation of transcripts of Sfp1 target genes is particularly needed. Since lack of Sfp1 is known to yield some of the smallest cells possible, it would also be cool to have an estimate of the size of mutants where Sfp1 is less nuclear. These analyses could confer phenotypical relevance to the data, but would also help in assessing a currently unexplored possibility, that phosphorylation events by PKA influence Sfp1 function besides its localization, i.e.: the still somehow nuclear fraction is not as functional as wt Sfp1 in promoting transcription.

      It is indeed the case that the recorded N/C ratios are larger than 1 in all strains that we have monitored. We have never observed an N/C ratio smaller than 1 using widefield microscopy for two main reasons: first, out-of-focus light from the cytosol above and below the nucleus is added to the nuclear signal, causing the nuclear signal to always be non-zero, even for predominantly cytosolic proteins. Second, both in- and out of focus vacuoles are devoid of the fluorescent protein fusions that we quantify, which reduces the average brightness of the cytosol. For these reasons, even when a protein is largely cytosolic, the average N/C ratio over a cell population is no lower than around 1.5. Keeping these points in mind, one can observe that our most delocalized Sfp1 mutants have an N/C ratio that is around 1.6-1.7, which is very close to the lower limit. This means that these Sfp1 mutants are largely cytosolic, and the nuclear fraction (if non-zero) is quite small.

      We agree that assessing the phenotypic relevance of Sfp1 mutations is of interest. However, this was impossible with our original strains, as we introduced each Sfp1 mutant as an extra copy in the HO locus while leaving the endogenous Sfp1 locus intact. This was done in order to avoid any phenotypic changes that might result from changes in Sfp1 activity.

      To address the suggestion of the reviewer, we therefore deleted the endogenous Sfp1 copy in strains carrying sfp1PKA2A, sfp1PKA2D and sfp113A, leaving only the mutated Sfp1 copy at the HO locus. Surprisingly, the growth rate and drug sensitivity (determined by halo assays) of these single-copy mutants did not differ much in comparison to the mutants carrying the functional Sfp1 copy and from the wild-type (Supp. Figs. 4J and 7). This observation aligns with findings for the single-copy sfp1-1 mutant in [Lempiäinen et al. 2009], which corresponds to sfp1TOR7A in our work. [Lempiäinen et al. 2009] had suggested that Sch9 compensates for the loss of Sfp1 activity via a feedback mechanism, which could explain our results as well. If this is the case, acute depletion of wild-type Sfp1 could unveil transient changes in cell growth, before the compensatory effect of Sch9 was established. Unfortunately, we were unable to efficiently degrade wild-type Sfp1 carrying a C-terminal auxin-inducible degron. Instead, we followed the same approach with [Lempiäinen et al. 2009] and deleted SCH9.

      As we describe in the last section of Results, the difference was dramatic for sfp113A __mutants, which were extremely slow-growing in the absence of Sch9 (doubling time was around 4 hours, but it was hard to estimate because we could not grow the cells consistently). Interestingly, SCH9 deletion had a negative impact on sfp1__PKA2D __but not sfp1__PKA2A __cells (__Supp. Fig. 7). Overall, these results demonstrate that Sch9 can compensate for loss of Sfp1 activity, which makes it challenging to study the impact of Sfp1 mutations on cellular phenotypes.

      To further understand to what extent Sch9 compensates for loss of Sfp1 phosphorylation, we carried out RNA-seq on WT and cells carrying a single copy of sfp113A (with the endogenous SFP1 copy removed). Despite the fact that sfp113A __grow as well as WT, RNA-seq picked up several differentially expressed genes related to amino acid biosynthesis. This surprising finding is presented in the last section of Results, and in __Supplementary Figures 8, 9 and 10. We explore the relevance of these results and their connection with past literature on Sfp1 and Sch9 in the Discussion section.

      I found some typos here and there, and it would greatly help to report them if in the manuscript line numbers were included.

      We apologize for the typos. We have tried to eliminate them, and we have also added line numbers to the manuscript.

      Reviewer 2

      There is no biochemical evidence presented that the putative PKA sites (S105 and S136) are genuinely phosphorylated by PKA. The fact that they match the PKA consensus motif, alone, does not guarantee this. In order to claim that they are looking at the effect of PKA by mutagenizing these residues, the authors have to demonstrate the PKA-dependency of S105 and S136 phosphorylation by, for example, mass spec experiments or western blotting with phospho-specific antibodies (Cell Signaling Technology #9624 for example). Also, does the band-shift caused by PKA inhibition (Fig 3C) is canceled by the S105A/S136A mutation?

      We took several actions to demonstrate that the putative PKA sites are indeed phosphorylated by PKA. We first tried to detect Sfp1 phosphorylation using the antibody mentioned by the reviewer, but failed as the sensitivity of this antibody appears to be quite low. On the other hand, mass spectrometry did not produce the right fragments to detect the sites of interest. We therefore resorted to an in vitro kinase assay using [γ-32P]ATP together with purified PKA and Sfp1. Unfortunately, bacterial overexpression of MBP-tagged Tpk1, Tpk2 and Tpk3 (the catalytic subunits of PKA) was quite challenging and we were unable to produce soluble protein. We therefore resorted to commercially available bovine PKA (bPKA, PKA catalytic subunit, Sigma-Aldrich 539576), which shows high homology to the yeast Tpk kinases [Toda et al. 1987]. Moreover 87% of bPKA substrates have been shown to also be Tpk1 substrates [Ptacek et al. 2005], and bPKA has been used to identify new Tpk substrates in budding yeast [Budovskaya et al. 2005__]. As we show in the revised manuscript, bovine PKA does phosphorylate Sfp1. Moreover, phosphorylation is reduced by 50% in the double S105A, S136A mutant (Fig.1F), and becomes undetectable in the 13A mutant__ (Supp Fig. 6). Together with the rapid response of Sfp1 localization to acute PKA inhibition which we had already reported, we believe that these results provide strong evidence that Sfp1 is a direct PKA substrate, and that the two phosphosites that we identified are functional.

      As the above in vivo experiments do not exclude S105/S136 phosphorylation by other kinases downstream of PKA, in order to claim the direct phosphorylation, the authors need in vitro PKA kinase assay. These biochemical experiments are not trivial, but I think absolutely necessary for this story.

      One cannot exclude that S105/S136 are also phosphorylated by other kinases of the AGC family (note that [Lempiäinen et al. 2009] has already excluded Sch9). However, as we hope to have shown, PKA indeed phosphorylates Sfp1. Examining if other kinases besides PKA and TORC1 target Sfp1 is a very interesting question that should be addressed in future work.

      The authors only look at the localization of Sfp1. To assess its functionality and so physiological impact, it would be informative to measure the mRNA level of target ribosomal genes in various Sfp1 mutants they created.

      As we described in our response to Reviewer 1 above, we did perform RNA-seq on WT and cells carrying a single copy of sfp113A. We observed a notable absence of differentially expressed ribosomal genes and ribosome-related categories in the GO analysis (Supp. Figs. 8, 9 and 10). Together with our observations on SCH9 deletion (Supp. Fig. 7), these results suggest that Sch9 can largely compensate for the loss of Sfp1 activity. On the other hand, the emergence of differentially expressed amino acid biosynthesis genes is a finding that merits further investigation, as it connects with previous observations made with Sch9 deletion mutants and the [ISP+] prion form of Sfp1 (cf. Discussion).

      In the experiments using analog-sensitive PKA (Fig 1D and E for example), they directly compare wildtype-PKA versus analog sensitive-PKA, or with 1-NM-PP1 versus without 1-NM-PP1. This makes interpretation difficult, particularly because 1-NM-PP1 itself has a significant impact even in the wild PKA strain. The real question is the difference between wild-type Sfp1 versus mutant Sfp1. In the current form, they compare Fig 1D versus 1E, these two do not look like a single, side-by-side experiment. They should compare wild-type Sfp1 versus mutant Sfp1 side-by-side.

      Figure 1D shows that 1-NM-PP1 has a transient off-target effect on Sfp1 localization in WT cells, which could also affect Sfp1 mutants. This observation prompted us to use wild-type PKA as a control when testing the effect of 1-NM-PP1 on sfp1PKA2D in cells carrying PKAas (Figure 1E). As Fig. 1E shows, the effect of 1-NM-PP1 on sfp1PKA2D localization in PKAas cells is quite similar to the off-target effect in cells carrying sfp1__PKA2D __and wild-type PKA. This behavior of sfp1__PKA2D __is clearly different from the response of wild-type Sfp1 to PKAas inhibition, which results in sustained delocalization. We have made the latter observation repeatedly, both in this study and our previously published work [Guerra et al. 2021].

      In Figure 3, the argument around the additive effects of PKA and TORC1 is confusing. The authors say they are additive referring Figure 3E, but say they are not additive referring Figure 3B. Which is true? In fact, Figure 3B appears to show an additive effect as well.

      We did not use the word "additive" in the text, because we find it difficult to interpret. Instead, we state that PKA and TORC1 appear to control Sfp1 phosphorylation independently of each other. PKA and TORC1 phosphorylation converges to the same response, affecting Sfp1 localization. It appears that loss of either kinase delocalizes Sfp1, while loss of both kinases may only have a small additional effect.

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    2. EMBOpress 11 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      The authors investigated how Sfp1, a transcription factor for ribosomal genes, integrates signals from TORC1 and PKA pathways. They did so by analyzing the nuclear localization of the GFP-tagged Sfp1 variants harboring unphosphorylatable or phosphomimetic mutations on either TORC1 target sites, putative PKA target sites, or a combination of both. This approach was complemented by examining the effect of pharmacological inhibition of either pathway on Sfp1 localization. The obtained results support that TORC1 and PKA independently promote nuclear localization of Snf1, provided that the putative PKA sites are genuinely PKA sites (see Major point). In course of their investigation, the authors made two novel findings about the regulatory mechanism of Sfp1 localization. First, they identified the 98-106aa region as a nuclear export signal (NES). Because this region overlaps with a putative PKA site, it is conceivable that PKA regulates Sfp1 localization via altering the functionality of NES. In addition, they found that the nuclear localization of Snf1 requires its C-terminal zinc fingers, although this domain appears to work independently from TORC1- and PKA-dependent regulations.

      Major points:

      1. There is no biochemical evidence presented that the putative PKA sites (S105 and S136) are genuinely phosphorylated by PKA. The fact that they match the PKA consensus motif, alone, does not guarantee this. In order to claim that they are looking at the effect of PKA by mutagenizing these residues, the authors have to demonstrate the PKA-dependency of S105 and S136 phosphorylation by, for example, mass spec experiments or western blotting with phospho-specific antibodies (Cell Signaling Technology #9624 for example). Also, does the band-shift caused by PKA inhibition (Fig 3C) is canceled by the S105A/S136A mutation?
      2. As the above in vivo experiments do not exclude S105/S136 phosphorylation by other kinases downstream of PKA, in order to claim the direct phosphorylation, the authors need in vitro PKA kinase assay. These biochemical experiments are not trivial, but I think absolutely necessary for this story.

      Minor points:

      1. The authors only look at the localization of Sfp1. To assess its functionality and so physiological impact, it would be informative to measure the mRNA level of target ribosomal genes in various Sfp1 mutants they created.
      2. In the experiments using analog-sensitive PKA (Fig 1D and E for example), they directly compare wildtype-PKA versus analog sensitive-PKA, or with 1-NM-PP1 versus without 1-NM-PP1. This makes interpretation difficult, particularly because 1-NM-PP1 itself has a significant impact even in the wild PKA strain. The real question is the difference between wild-type Sfp1 versus mutant Sfp1. In the current form, they compare Fig 1D versus 1E, these two do not look like a single, side-by-side experiment. They should compare wild-type Sfp1 versus mutant Sfp1 side-by-side.
      3. In Figure 3, the argument around the additive effects of PKA and TORC1 is confusing. The authors say they are additive referring Figure 3E, but say they are not additive referring Figure 3B. Which is true? In fact, Figure 3B appears to show an additive effect as well.

      Significance

      TORC1 and PKA are major pro-growth signaling pathways widely conserved in eukaryotes, that often converge on the same target proteins. How the information from the two pathways is integrated is an interesting question, which the authors directly and meticulously address here with yeast Sfp1 as an example. Provided that they can demonstrate that the putative PKA sites are the real ones (this is really important- TORC1 sites are already known, what is new here is PKA sites), their data and conclusion should be of interest to the signal transduction field.

      Their additional discovery of NES and the role of zinc fingers in Sfp1 localization should be of interest to those working on Sfp1, or transcriptional regulation of ribosomal genes in general.

      My area of expertise: yeast TOR

      PeerReviewed
    3. EMBOpress 11 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      In this paper, Vuillemenot and Milias-Argeitis investigate in budding yeast the role of Protein Kinase A (PKA) in regulating through phosphorylation the subcellular localization of the transcription factor Sfp1, known for controlling transcription of RP genes. Sfp1 is very well known for being regulated by another signaling pathway, centered on the kinase TORC1. Thus, regulation of Sfp1 by PKA raises the intriguing possibility of a downstream crosstalk between the two pathways. Indeed, the authors find that Sfp1 is regulated by PKA independently from TORC1. In the study, the authors employ mainly single-cell microscopy to monitor the nucleo/cytosolic localization of Sfp1 mutants, an experimental set-up they established in a previous paper, with some contribution by PhosTag bandshift assays.

      Major comments:

      The paper is overall convincing. However, a little more attention to data presentation and possibly the addition of at least another technique (see below) would greatly strengthen the findings. Summarizing my major concerns: - The absence of statistics catches immediately the eye. I am sure that the shown differences are statistically significant (thanks to the number of analyzed cells), but reporting the result of some statistical test would help the reader in identify the relevant data in a plot. This is somehow necessary considering that sometimes in the text something is deemed to be "significant" or "not significant", and I felt that I really needed that when looking at the blot in Fig. 3D. - Related to the previous point: for every N/C distribution analysis, a number of analyzed cells is reported. By the way it is written, it seems that the replication relies solely by the cells in that specific population, i.e.: each cell is treated as a replicate. At least I could not find if that is not the case in the legends or in the methods. I wonder what the results would be (and their significance) if each replicate would be a new assay on another population. - The scale of x axes in N/C ratio plots. Besides not being consistent throughout the figures, it originates from 1, visually enhancing the differences. - Related to the previous point: it is evident from the plots that the N/C ratio is always positive, even in the most deficient of the analyzed mutants. This implies that a relevant fraction of Sfp1 is still nuclear. I thus wonder what the impact of these mutations would be on the actual function of Sfp1. For this reason, I feel that qPCR evaluation of transcripts of Sfp1 target genes is particularly needed. Since lack of Sfp1 is known to yield some of the smallest cells possible, it would also be cool to have an estimate of the size of mutants where Sfp1 is less nuclear. These analyses could confer phenotypical relevance to the data, but would also help in assessing a currently unexplored possibility, that phosphorylation events by PKA influence Sfp1 function besides its localization, i.e.: the still somehow nuclear fraction is not as functional as wt Sfp1 in promoting transcription.

      Minor comments:

      Experimental issues and suggestions on data presentation are reported in the major comments section, since I felt those were major issues.

      Just a side remark: I found some typos here and there, and it would greatly help to report them if in the manuscript line numbers were included.

      Significance

      The finding that both PKA and TORC1 impinge on Sfp1, and therefore presumably on protein synthesis, is a valuable conceptual addition to the field of cell signaling. The audience potentially interested by the findings of the study include not only yeast cell biologists, but also computational biologists interested in modeling crucial cellular processes. One example is the regulation of cell size, where TORC1, PKA and Sfp1 are already know to play a role, but were potentially missing a crosstalk link.

      As requested by Review Commons, I specify that my expertise is on TORC1/AMPK/PKA pathways, on their crosstalk and their regulation by metabolic intermediates.

      PeerReviewed
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    biorxiv.org/content/10.1101/2022.12.02.518855v2
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    Tissue inflammation induced by constitutively active STING is mediated by enhanced TNF signaling
    4
    1. EMBOpress 07 Jul 2024

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      Reply to the reviewers

      Reviewer #1:

      We thank the reviewer for his/her time and for the constructive comments. Below please find our detailed responses to your points.

      STING is a key signalling hub in the innate immune system, receiving multiple inputs from upstream activators (such as cGAS) and in turn triggering multiple downstream events (such as IFN induction, NF-kB signalling, autophagy, cell death). Mutations in the STING gene cause a rare inflammatory disease called SAVI. Using a previously established STING ki mouse that recapitulates some of the clinical observations in SAVI patients, this manuscript tests the hypothesis that TNF signalling drives pathology. Using anti-TNF antibody and TNF receptor knockout, the authors show that TNF indeed plays important roles in causing disease in this mouse model. For example, the loss of T cells and neurons is prevented when TNF signalling is blocked, and lung pathology is rescued in STING ki mice lacking TNF receptors. Overall, the manuscript is well written and laid out, and the experimental work is of a high technical standard.

      Major comments

        • Most figures show pooled data from two independent experiments including a total of 5-8 mice. Given the variability in some of the readouts, this raises the question of whether there is sufficient statistical power to draw conclusions. For example, in Figure 2, the conclusion that "Infliximab did not alter the expression of inflammatory mediators" seems questionable given the results in Figure 2F and G. Did the authors perform a power calculation? What effect size can the authors detect given the variability and number of replicates? Similarly, in Figure 3, the authors conclude that "Disruption of TNFR signaling did not significantly prevent T cell lymphopenia"; however, with some more replicates, the data in Figure 3D would likely reach significance. Similar concerns apply to several panels in Figures 4 and 6 and to Figure S5M. Ideally, the authors should perform additional repeat experiments to increase the number of replicates. If that is not possible, power calculations need to be provided and conclusions should explicitly mention the minimum effect size that the author can detect given the small sample size (for example "Infliximab did not alter the expression of inflammatory mediators more than x-fold").* Thank you for this suggestion. However, it is not possible to repeat the treatment of mice with Infliximab for generation of more replicates. The blockade of TNF signalling by treatment with drugs did not cure the murine SAVI disease. According to animal welfare restrictions, we cannot perform additional treatment experiments with Infliximab or Etanercept.

      We analysed the effect size d, f and power of all these presented results and collected them in table S4. Additional explanations about effect sizes were added in the corresponding text to Figures 2 and 3. The demonstrated results in Figure 4 and 6 already contain significant data. We did not include the calculation of effects sizes here. All effect size and power calculations are summarized in table S4.

      • The authors should not make unjustified overstatements. For example, STING KI; TNFR1/2 KO mice should not be referred to as a "new mouse model". The manuscript simply tests the role of TNFR1/2 in the already published STING N153S model. In line 687, avoid using "impressively" and in line 734 avoid using "massively".*

      • *

      Thank you for this suggestion. We changed this sentence into:…”these newly generated mouse lines of TNFR”…., see line 796. Additionally, in line 687 (actual line 705) we omitted “impressively” and in line 734 “massively produced” into “elevated” (actual line 752).

      Minor comments

      • Line 767-769: The statement that spike activates cGAS is misleading, because this effect is an indirect consequence of cell-to-cell fusion (Liu et al 2022).*

      • *

      Thank you for this suggestion. We changed this sentence into: Cell fusion caused by the SARS-CoV-2 spike protein is a potent… (actual line 785).

      Reviewer #1 (Significance (Required)):

      • *

      The main strengths of this study are (1) the use of complementary antibody-based and genetic methods to test the role of TNF signalling; (2) the use of multiple different readouts; and (3) the analysis of many different cell types / organ systems. The main weaknesses are (1) small sample sizes limiting statistical power (see above) and (2) the exclusive use of mouse models.

      • *

      Overall, my opinion is that the advance is important, both fundamentally and clinically. Studies of this and the related V154M mouse model previously showed an important role of non-IFN pathways in driving disease. This study indicates that TNF signalling may cause pathology. This not only extends our understanding of STING's role in autoinflammation but also opens a direct therapeutic avenue using approved TNF targeting drugs.

      • *

      This study will be primarily of interest to specialised audiences working on STING and SAVI, and secondarily to the wider innate immunity field.

      • *

      This reviewer has expertise in the field of nucleic acid sensing, including cGAS-STING.

      • *

      • *

      Reviewer #2:

      We thank the reviewer for his/her time and for the constructive comments. Below please find our detailed responses to your points.

      *In this paper, Luksch et al (2024) examines the role of TNF signaling in STING-associated vasculopathy with onset in infancy (SAVI). By using pharmacological inhibition and genetic inactivation of TNF receptors in a murine SAVI model (STING ki), the research found that pharmacologically inhibiting TNF signaling improved T cell lymphopenia but had limited effects on lung disease. Genetic inactivation of TNFR signaling, particularly TNFR1, enhanced thymocyte survival and expanded the peripheral T cell pool, reducing inflammation and neurodegeneration. The development and progression of severe lung disease in STING ki mice are also reliant on TNFR1 signaling, while TNFR2 deletion did not alleviate lung inflammation. The authors also explored the severe inflammatory lung disease manifestation, showing that primary lung endothelial cells in STING ki mice allowed more neutrophil attachment compared to those in STING WT mice, indicating chronic STING activity in endothelial cells disrupts the endothelial barrier and promotes severe lung disease. The study highlights TNFR signaling as crucial in SAVI and COVID-19 progression and suggests blocking TNFR1 signaling as a potential therapeutic approach for both diseases. *

      • *

      Major comments:

      The paper establishes a strong connection between TNFR1 depletion and the reduction of SAVI disease severity in lung and neuroinflammation, suggesting TNFR1 blockade as a viable therapeutic strategy for SAVI. To strengthen the arguments and improve the therapeutic potential, the authors should address the following major comments:

        • The authors conclude that TNFR1 signaling drives murine SAVI disease, as evidenced by the reduced severity of lung disease in TNFR1 -/- mice. While the genetic model is convincing, the discrepancy between pharmacological inhibition and genetic models needs clarification. Before attributing the pharmacological failure to late administration, have the authors considered that Infliximab might not sufficiently deplete TNF to achieve therapeutic benefits? In figure 2H, serum TNF levels were not significantly altered in STING ki mice treated with Infliximab. Have the authors considered using other TNF inhibitors or alternative methods to measure TNF depletion efficacy in STING ki murine models, such as qPCR, flow cytometry, or immunohistochemistry in lymph nodes or lung tissues?* Thank you for this suggestion. In a preliminary experiment, we already treated STING WT and STING ki mice with Etanercept which is not included in the paper. 3-week-old mice were treated with subcutaneously injection of 25 mg/kg Etanercept or saline, twice per week, for 7 weeks. After treatment, all mice were euthanized and single cell suspensions of blood and spleen were used for flow cytometry analysis. Lung tissue was harvested for histological analysis. Quantification of gene expression was performed by snap frozen lung and kidney tissue and quantification of secreted proteins was analysed by snap frozen serum.

      The transcription of ISGs and proinflammatory mediators in lung tissue was not significantly improved by the Etanercept treatment of mice, see additional figure below (A – D). Interestingly, the amount of secreted CXCL9 in the serum was reduced in Etanercept treated mice compared to vehicle treated mice (E). We concluded that our treatment strategy had no impact in the manifestation and progression of murine SAVI disease, in highly inflamed tissues / organs. However, we found a reduction (partially significant) of proinflammatory mediator transcriptions in the kidney of Etanercept treated mice compared to vehicle control mice. Murine SAVI disease is a systemic autoinflammatory disease without histological alteration in kidney tissue of 10 weeks old mice. Remarkably, transcription of ISGs and proinflammatory mediators is highly upregulated in SAVI mice. Treatment with Etanercept improved this aberrant gene expression in murine SAVI influenced tissue / organ (I – K). These results encouraged us to perform the treatment with infliximab because we expected a more pronounced effect since infliximab can bind the monomeric and trimeric form while etanercept can only bind to the active trimeric from of TNF.

      Etanercept treatment of STING WT (in black) and ____STING ki (in red)____ mice.

      (A) Relative expression level of Cxcl10, (B) Mx1, (C) Tnf and (D) Il1b in lung tissue of Etanercept or saline treated STING WT and STING ki mice. (E) Quantification of CXCL9, (F) CXCL10, (G) IL-6 and (H) TNF in serum samples from STING WT and STING ki mice after treatment. (I) Relative expression level of Cxcl10, (J) Mx1, (K) Tnf and (L) Il1b in kidney tissue of treated mice.

      • The TNF pathway exhibits redundancy, as multiple signaling molecules or pathways can compensate for the loss of TNF function to maintain cellular processes and immune responses. The authors showed that thymocytes of STING ki mice lacking TNFR1/2 expressed significantly lower levels of IFN-related genes (Cxcl10, Sting1), and mice lacking TNFR1 and TNFR1/2 expressed reduced levels of NF-κB-related genes. Does this imply that IFN and NF-κB pathways are downstream of TNF signaling driving SAVI progression? It would be valuable to hear the authors' comments or postulations on the potential mechanisms of TNF driving SAVI progression in the discussion, and the methods to dissect the mechanisms further using genetic or pharmacological methods.*

      Thank you for this suggestion. STING is a key player in various proinflammatory mechanism and is directly involved in IFN and NF-κB signalling. We assume that these signalling pathways are adaptable to various proinflammatory situations. Knock out of TNFR1 and TNFR1/2 results in a strong inhibition of all inflammatory reactions in the whole organisms. We think, it is not possible to conclude mechanisms of murine SAVI manifestation and progression from the results of these mouse lines only. These observations provide new hypothesis, but cannot completely explain the mechanism.

      • The authors mentioned that the pharmacological inhibition of TNF by Infliximab is ineffective due to late administration compared to the onset of SAVI. How would this affect the therapeutic treatment of TNF if the treatment is going to be later than the disease onset? Can the authors elaborate on the potential ways to circumvent the timing of treatment? Would TNFR1 antagonists experience the same issue? To understand disease progression and optimal targeting times, the creation of an inducible TNFR1/2 -/- mouse model could be beneficial. This is optional, but the authors are encouraged to comment on improving TNFR1/2 -/- mouse SAVI models to further study the therapeutic potential of TNF signaling blockage in treating SAVI.*

      We agree with the suggestion. In the next project, we want to generate STING ki mice with inducible knock out.

      Minor comments:

      • The authors separate STING WT and STING ki into different graphs, which can sometimes make it hard to compare STING WT and STING ki baseline levels. It would be beneficial to merge the two genotypes into single graphs for easier comparison.*

      Thank you for this suggestion. In the first version of this manuscript, we collected results from STING WT and STING ki mice in one graph with 8 bars in different colours and textures in the case of TNFR knock out lines. These graphs were overloaded and very confusing. It is was not possible to mark statistical calculations inside these graphs without losing the focus. Hence, we created the demonstrated design of graphs. We think this is the most convincing version.

      • Figure S5 lacks statistical annotations, although the legends mention them. Are the statistics usually shown when a comparison is mentioned in the text, or are they only displayed when the differences are significant? It would be helpful if the authors could clarify this and ensure that all relevant statistical comparisons are clearly reflected in the graphs, regardless of the significance level. This consistency would improve the clarity and interpretation of the data presented.*

      • *

      Thank you for this suggestion. We removed the significance level from the legend of Figure S5 (actually line 1199).

      • *

      The authors did an excellent job discussing the study's implications, but some of this content could be moved to the introduction. The hypothesis that "tumor necrosis factor (TNF) signaling is involved in the manifestation and progression of murine SAVI disease" can be introduced more naturally once the authors present previous findings on TNF's association with various autoimmune disorders. This would set a clear context for the study's objectives and rationale.

      We agree with this suggestion and inserted the sentence: “In our previous investigations, we observed an elevated transcription of Tnf in spleen and thymus of STING ki mice (Siedel et al., 2020).” (actual line 89/90).

      General Assessment: The study identifies enhanced TNF signaling as a driver of SAVI and specifies TNFR1 blockage as a promising treatment to reduce disease severity. It thoroughly characterizes pharmacological inhibition and genetic perturbations of TNF signaling in murine SAVI models and creates a novel mouse model for studying TNF-targeted therapies in SAVI treatment.

      *However, the study is limited in characterizing the discrepancy between pharmacological inhibition and genetic depletion of TNF and understanding the underlying mechanisms of TNF driving chronic STING activation and tissue inflammation. *

      Advances: The study extends knowledge in the field by demonstrating that enhanced TNF signaling drives SAVI, establishing causation rather than mere correlation. The authors provide strong rationale for treating SAVI with TNF inhibitors/blockage, previously used in other autoimmune disorders like IBD or Crohn's disease, but not in SAVI. They also present a valuable genetic model for studying TNFR signaling blockage in SAVI progression, which is important for both the field of SAVI and future therapy development.

      Audience: The research provides translational and clinical insights by suggesting that targeting TNFR1 signaling could inspire novel treatments for SAVI. The study also advances basic research on SAVI disease progression. Immunologists and clinicians studying and treating autoimmune disorders are the intended audience, but the findings have broader implications. The study highlights the potential role of TNF signaling in COVID-19 disease progression and treatment, thus attracting interest beyond the field of autoimmune disorders.

      • *

      Field of expertise:

      cGAS-STING regulation in chromosomally unstable cancers, genomic instability, nuclear envelope rupture and repair

      Do not have sufficient expertise in:

      Immunological underpinning of autoimmune disorders, clinical models or manifestations of SAVI

      • *

      • *

      Reviewer #3:

      We thank the reviewer for his/her time and for the constructive comments. Below please find our detailed responses to your points.

      • *

      Uncontrolled activation of STING is linked to autoinflammatory disease "STING-associated vasculopathy with onset in infancy (SAVI)". The authors had previously published a mouse model of SAVI, which was generated by knocking in the disease causing variant N153S into the endogenous murine Sting1 gene (STING ki) (Luksch et.al., 2019). In the current study, the author further investigated the role of tumor necrosis factor (TNF) signaling in manifestation and progression of murine SAVI disease by using the approach of pharmacologic and genetic inhibition of TNF receptors TNFR1 and TNFR2. Overall, the authors were able to demonstrate the following novel findings:

      • *

      1) Infliximab treatment of STING ki mice significantly increased the number of blood CD8+ T cells and thymic cells count. The authors claimed that the pharmacological inhibition of TNF signalling has a partial rescue effect of T cell lymphopenia. However, pharmacologic inhibition of TNF signalling however has no effect on lung disease.

      2) On the other hand, STING ki;Tnfr1-/- (lacking TNFR1) showed the similar modest rescue of the CD8+ T and CD4+ T cells in blood compared to the WT C57BL/6 (BL6) but not with STING ki;Tnfr2-/- (lacking TNFR2). STING ki;Tnfr1-/-, STING ki;Tnfr2-/- and STING ki;Tnfr1/2-/- had modest rescue of thymic cell count and reduced spleen cell count (reduced splenomegaly). Along with the rescued thymic content and reduced splenomegaly, genetic ablation of TNF signalling (STING ki;Tnfr1-/-) also prevented manifestation of severe inflammatory lung disease.

      3) To investigate the role of lung endothelial cells in the development of interstitial lung disease, primary murine lung endothelial cells from STING WT, STING ki and STING WT;Tnfr1/2-/- and STING ki;Tnfr1/2-/- mice were isolated and bulk RNAseq was performed. This showed decreased level of several proinflammatory cytokines (e.g. Tnf, Il1b) and chemokines (e.g. Cxcl1, Cxcl2, Cxcl9, Cxcl10, Ccl2, Ccl3 and Ccl4) in STING ki mice lacking TNFR1/2 compared to STING ki mice.

      4) Neutrophils were isolated from bone marrow and were added to cultured primary lung endothelial cell monolayers. The experiments demonstrated that the attachment and transmigration of neutrophil cells were dependent on expression of STING gain-of-function mutation in endothelial cells.

      • *

      A few points require clarification before publication of this study.

      • Tnfr1-/-, Tnfr2-/- and Tnfr1/2-/- did not show any statistical significant improvement of thymic cell count in STING ki mice. As such, the statement in the conclusion/summary section of discussion regarding Tnfr1 can restore thymocyte numbers should be toned-down.
      • Thank you for this suggestion. In Figure 4 E, we demonstrated that knock out of TNFR1 leads to increasing of SP CD8 thymocyte count and partially of SP CD4 thymocyte count (Fig. 4 D). In agreement with this suggestion, we marked this subpopulation of thymocytes in the discussion and summary section, see actual line 684 and see actual line 794.

      2) The section on Neuroinflammation and neurodegeneration and dependency of TNFR1/2 signaling is very currently difficult to follow (based on how the data are presented in figures and text). This section requires to be re-written for clarity.

      • *

      Thank you for this suggestion. We re-wrote this section, see line 472 - 499.

      Neuroinflammation and neurodegeneration in dependency of TNFR1/2 signaling

      The extent of inflammation in mouse brain resulting from constitutive activation of STING N153S was reported by quantifying the density of Iba1-positive microglia (Fig.5 A). Consistent with our previous findings (Szego et al., 2022), the density of Iba1-positive microglia in the substantia nigra was higher in STING ki;BL6 mice than in STING WT mice (Fig.5 B). TNFR deficiency did not affect neuroinflammation because there was no significant difference between the density of Iba1-positive microglia between STING ki;BL6 mice and STING ki;Tnfr1/2-/- mice (Fig.5 B). This suggests that the TNF pathway is not required for STING-induced microglia activation in the substantia nigra.

      In addition, we measured the extent of STING-induced astrogliosis by quantifying the density of GFAP-positive cells (Fig. 5 A). Consistent with our previous findings, the density of GFAP-positive astroglia was higher in STING ki than in STING WT mice (Fig. 5C). Yet, as for microglia, there was no significant difference between the density of GFAP-positive astroglia between STING ki;BL6 mice and STING ki;Tnfr1/2-/- mice (Fig.5 C), suggesting that the TNF pathway is not required for STING-induced astrogliosis in the substantia nigra.

      Finally, we measured the extent of STING-induced neurodegeneration by quantifying the density of TH-positive dopaminergic neurons in the substantia nigra (Fig. 5A). As in our previous findings, the density of TH-positive neurons was lower in STING ki;BL6 mice than in STING WT mice (Fig.5 D). The density of TH-positive neurons in the substantia nigra of STING ki;Tnfr1/2-/- mice was higher than the density of TH-positive neurons in the substantia nigra of STING ki;BL6 mice (Fig. 5 D), suggesting that the STING-induced degeneration of TH-positive neurons was blunted in Tnfr1/2-/- mice and that TNFR1/2 are involved in the STING-induced degeneration of dopaminergic neurons.

      Hence, there is a discrepancy between STING-induced effects on glial cells as opposed to STING-induced effects on neurons. The dependence of STING-induced neurodegeneration but not glial response on TNFR1/2 suggests that the STING-induced degeneration of dopaminergic neurons is not a direct consequence of microglia or astroglia activation. This is consistent with the emerging concept of a neuron-specific inflammatory response (Welikovitch et al., 2020).

      *The powerful use of in vivo genetic KO models and TNF inhibitor makes this study a valuable contribution to the field - helping further decipher the importance of the NF-KB/TNF branch of STING in SAVI (knowledge gap). The audience for this work would be specialised to STING biology and potential clinical treatments of SAVI. *

      • *

      Our expertise is in nucleic acids sensing (such as STING) and auto-immunity.

      PeerReviewed
    2. EMBOpress 07 Jul 2024

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

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      Referee #3

      Evidence, reproducibility and clarity

      Uncontrolled activation of STING is linked to autoinflammatory disease "STING-associated vasculopathy with onset in infancy (SAVI)". The authors had previously published a mouse model of SAVI, which was generated by knocking in the disease causing variant N153S into the endogenous murine Sting1 gene (STING ki) (Luksch et.al., 2019). In the current study, the author further investigated the role of tumor necrosis factor (TNF) signaling in manifestation and progression of murine SAVI disease by using the approach of pharmacologic and genetic inhibition of TNF receptors TNFR1 and TNFR2. Overall, the authors were able to demonstrate the following novel findings:

      1. Infliximab treatment of STING ki mice significantly increased the number of blood CD8+ T cells and thymic cells count. The authors claimed that the pharmacological inhibition of TNF signalling has a partial rescue effect of T cell lymphopenia. However, pharmacologic inhibition of TNF signalling however has no effect on lung disease.
      2. On the other hand, STING ki;Tnfr1-/- (lacking TNFR1) showed the similar modest rescue of the CD8+ T and CD4+ T cells in blood compared to the WT C57BL/6 (BL6) but not with STING ki;Tnfr2-/- (lacking TNFR2). STING ki;Tnfr1-/-, STING ki;Tnfr2-/- and STING ki;Tnfr1/2-/- had modest rescue of thymic cell count and reduced spleen cell count (reduced splenomegaly). Along with the rescued thymic content and reduced splenomegaly, genetic ablation of TNF signalling (STING ki;Tnfr1-/-) also prevented manifestation of severe inflammatory lung disease.
      3. To investigate the role of lung endothelial cells in the development of interstitial lung disease, primary murine lung endothelial cells from STING WT, STING ki and STING WT;Tnfr1/2-/- and STING ki;Tnfr1/2-/- mice were isolated and bulk RNAseq was performed. This showed decreased level of several proinflammatory cytokines (e.g. Tnf, Il1b) and chemokines (e.g. Cxcl1, Cxcl2, Cxcl9, Cxcl10, Ccl2, Ccl3 and Ccl4) in STING ki mice lacking TNFR1/2 compared to STING ki mice.
      4. Neutrophils were isolated from bone marrow and were added to cultured primary lung endothelial cell monolayers. The experiments demonstrated that the attachment and transmigration of neutrophil cells were dependent on expression of STING gain-of-function mutation in endothelial cells.

      A few points require clarification before publication of this study.

      1. Tnfr1-/-, Tnfr2-/- and Tnfr1/2-/- did not show any statistical significant improvement of thymic cell count in STING ki mice. As such, the statement in the conclusion/summary section of discussion regarding Tnfr1 can restore thymocyte numbers should be toned-down.
      2. The section on Neuroinflammation and neurodegeneration and dependency of TNFR1/2 signaling is very currently difficult to follow (based on how the data are presented in figures and text). This section requires to be re-written for clarity.

      Significance

      The powerful use of in vivo genetic KO models and TNF inhibitor makes this study a valuable contribution to the field - helping further decipher the importance of the NF-KB/TNF branch of STING in SAVI (knowledge gap). The audience for this work would be specialised to STING biology and potential clinical treatments of SAVI.

      Our expertise is in nucleic acids sensing (such as STING) and auto-immunity.

      PeerReviewed
    3. EMBOpress 07 Jul 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Short summary

      In this paper, Luksch et al (2024) examines the role of TNF signaling in STING-associated vasculopathy with onset in infancy (SAVI). By using pharmacological inhibition and genetic inactivation of TNF receptors in a murine SAVI model (STING ki), the research found that pharmacologically inhibiting TNF signaling improved T cell lymphopenia but had limited effects on lung disease. Genetic inactivation of TNFR signaling, particularly TNFR1, enhanced thymocyte survival and expanded the peripheral T cell pool, reducing inflammation and neurodegeneration. The development and progression of severe lung disease in STING ki mice are also reliant on TNFR1 signaling, while TNFR2 deletion did not alleviate lung inflammation. The authors also explored the severe inflammatory lung disease manifestation, showing that primary lung endothelial cells in STING ki mice allowed more neutrophil attachment compared to those in STING WT mice, indicating chronic STING activity in endothelial cells disrupts the endothelial barrier and promotes severe lung disease. The study highlights TNFR signaling as crucial in SAVI and COVID-19 progression and suggests blocking TNFR1 signaling as a potential therapeutic approach for both diseases.

      Major comments:

      The paper establishes a strong connection between TNFR1 depletion and the reduction of SAVI disease severity in lung and neuroinflammation, suggesting TNFR1 blockade as a viable therapeutic strategy for SAVI. To strengthen the arguments and improve the therapeutic potential, the authors should address the following major comments: - The authors conclude that TNFR1 signaling drives murine SAVI disease, as evidenced by the reduced severity of lung disease in TNFR1 -/- mice. While the genetic model is convincing, the discrepancy between pharmacological inhibition and genetic models needs clarification. Before attributing the pharmacological failure to late administration, have the authors considered that Infliximab might not sufficiently deplete TNF to achieve therapeutic benefits? In figure 2H, serum TNF levels were not significantly altered in STING ki mice treated with Infliximab. Have the authors considered using other TNF inhibitors or alternative methods to measure TNF depletion efficacy in STING ki murine models, such as qPCR, flow cytometry, or immunohistochemistry in lymph nodes or lung tissues? - The TNF pathway exhibits redundancy, as multiple signaling molecules or pathways can compensate for the loss of TNF function to maintain cellular processes and immune responses. The authors showed that thymocytes of STING ki mice lacking TNFR1/2 expressed significantly lower levels of IFN-related genes (Cxcl10, Sting1), and mice lacking TNFR1 and TNFR1/2 expressed reduced levels of NF-κB-related genes. Does this imply that IFN and NF-κB pathways are downstream of TNF signaling driving SAVI progression? It would be valuable to hear the authors' comments or postulations on the potential mechanisms of TNF driving SAVI progression in the discussion, and the methods to dissect the mechanisms further using genetic or pharmacological methods. - The authors mentioned that the pharmacological inhibition of TNF by Infliximab is ineffective due to late administration compared to the onset of SAVI. How would this affect the therapeutic treatment of TNF if the treatment is going to be later than the disease onset? Can the authors elaborate on the potential ways to circumvent the timing of treatment? Would TNFR1 antagonists experience the same issue? To understand disease progression and optimal targeting times, the creation of an inducible TNFR1/2 -/- mouse model could be beneficial. This is optional, but the authors are encouraged to comment on improving TNFR1/2 -/- mouse SAVI models to further study the therapeutic potential of TNF signaling blockage in treating SAVI.

      Minor comments:

      • The authors separate STING WT and STING ki into different graphs, which can sometimes make it hard to compare STING WT and STING ki baseline levels. It would be beneficial to merge the two genotypes into single graphs for easier comparison.
      • Figure S5 lacks statistical annotations, although the legends mention them. Are the statistics usually shown when a comparison is mentioned in the text, or are they only displayed when the differences are significant? It would be helpful if the authors could clarify this and ensure that all relevant statistical comparisons are clearly reflected in the graphs, regardless of the significance level. This consistency would improve the clarity and interpretation of the data presented.
      • The authors did an excellent job discussing the study's implications, but some of this content could be moved to the introduction. The hypothesis that "tumor necrosis factor (TNF) signaling is involved in the manifestation and progression of murine SAVI disease" can be introduced more naturally once the authors present previous findings on TNF's association with various autoimmune disorders. This would set a clear context for the study's objectives and rationale.

      Significance

      General Assessment: The study identifies enhanced TNF signaling as a driver of SAVI and specifies TNFR1 blockage as a promising treatment to reduce disease severity. It thoroughly characterizes pharmacological inhibition and genetic perturbations of TNF signaling in murine SAVI models and creates a novel mouse model for studying TNF-targeted therapies in SAVI treatment. However, the study is limited in characterizing the discrepancy between pharmacological inhibition and genetic depletion of TNF and understanding the underlying mechanisms of TNF driving chronic STING activation and tissue inflammation.

      Advances: The study extends knowledge in the field by demonstrating that enhanced TNF signaling drives SAVI, establishing causation rather than mere correlation. The authors provide strong rationale for treating SAVI with TNF inhibitors/blockage, previously used in other autoimmune disorders like IBD or Crohn's disease, but not in SAVI. They also present a valuable genetic model for studying TNFR signaling blockage in SAVI progression, which is important for both the field of SAVI and future therapy development.

      Audience: The research provides translational and clinical insights by suggesting that targeting TNFR1 signaling could inspire novel treatments for SAVI. The study also advances basic research on SAVI disease progression. Immunologists and clinicians studying and treating autoimmune disorders are the intended audience, but the findings have broader implications. The study highlights the potential role of TNF signaling in COVID-19 disease progression and treatment, thus attracting interest beyond the field of autoimmune disorders.

      Field of expertise:

      cGAS-STING regulation in chromosomally unstable cancers, genomic instability, nuclear envelope rupture and repair

      Do not have sufficient expertise in:

      Immunological underpinning of autoimmune disorders, clinical models or manifestations of SAVI

      PeerReviewed
    4. EMBOpress 07 Jul 2024

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

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      Referee #1

      Evidence, reproducibility and clarity

      Review Commons STING SAVI May 2024

      STING is a key signalling hub in the innate immune system, receiving multiple inputs from upstream activators (such as cGAS) and in turn triggering multiple downstream events (such as IFN induction, NF-kB signalling, autophagy, cell death). Mutations in the STING gene cause a rare inflammatory disease called SAVI. Using a previously established STING ki mouse that recapitulates some of the clinical observations in SAVI patients, this manuscript tests the hypothesis that TNF signalling drives pathology. Using anti-TNF antibody and TNF receptor knockout, the authors show that TNF indeed plays important roles in causing disease in this mouse model. For example, the loss of T cells and neurons is prevented when TNF signalling is blocked, and lung pathology is rescued in STING ki mice lacking TNF receptors. Overall, the manuscript is well written and laid out, and the experimental work is of a high technical standard.

      Major comments

      1. Most figures show pooled data from two independent experiments including a total of 5-8 mice. Given the variability in some of the readouts, this raises the question of whether there is sufficient statistical power to draw conclusions. For example, in Figure 2, the conclusion that "Infliximab did not alter the expression of inflammatory mediators" seems questionable given the results in Figure 2F and G. Did the authors perform a power calculation? What effect size can the authors detect given the variability and number of replicates? Similarly, in Figure 3, the authors conclude that "Disruption of TNFR signaling did not significantly prevent T cell lymphopenia"; however, with some more replicates, the data in Figure 3D would likely reach significance. Similar concerns apply to several panels in Figures 4 and 6 and to Figure S5M. Ideally, the authors should perform additional repeat experiments to increase the number of replicates. If that is not possible, power calculations need to be provided and conclusions should explicitly mention the minimum effect size that the author can detect given the small sample size (for example "Infliximab did not alter the expression of inflammatory mediators more than x-fold").
      2. The authors should not make unjustified overstatements. For example, STING KI; TNFR1/2 KO mice should not be referred to as a "new mouse model". The manuscript simply tests the role of TNFR1/2 in the already published STING N153S model. In line 687, avoid using "impressively" and in line 734 avoid using "massively".

      Minor comments

      1. Line 767-769: The statement that spike activates cGAS is misleading, because this effect is an indirect consequence of cell-to-cell fusion (Liu et al 2022).

      Significance

      The main strengths of this study are (1) the use of complementary antibody-based and genetic methods to test the role of TNF signalling; (2) the use of multiple different readouts; and (3) the analysis of many different cell types / organ systems. The main weaknesses are (1) small sample sizes limiting statistical power (see above) and (2) the exclusive use of mouse models.

      Overall, my opinion is that the advance is important, both fundamentally and clinically. Studies of this and the related V154M mouse model previously showed an important role of non-IFN pathways in driving disease. This study indicates that TNF signalling may cause pathology. This not only extends our understanding of STING's role in autoinflammation but also opens a direct therapeutic avenue using approved TNF targeting drugs.

      This study will be primarily of interest to specialised audiences working on STING and SAVI, and secondarily to the wider innate immunity field.

      This reviewer has expertise in the field of nucleic acid sensing, including cGAS-STING.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.04.25.591149v1
  15. www.biorxiv.org www.biorxiv.org
    An Alzheimer's disease-associated common regulatory variant in a PTK2B intron alters microglial function
    3
    1. EMBOpress 05 Jul 2024

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

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      Reply to the reviewers

      Response to Reviewers

      We thank the reviewers for their comments and suggestions, which we think are helpful and will improve the manuscript, and intend to address with the changes and planned revisions below.

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

      Bello et al look at the SNP rs28834970 associated with Alzheimer's disease (AD), with C being the risk allele, on chromatin accessibility and expression of a nearby gene, PTK2B, in microglia. Their contention is that the single SNP affects chromatin accessibility and binding of the transcription factor CEBP[beta] in an intronic region of PTK2B and thereby affects PTKB expression. I had a few questions that I think are critical to be addressed. Please note that my numbering of panels is based on the figures, not the legends, which do not seem to quite agree with each other. There are also some figure legends that say "IFNg" while the figures say "LPS", which should be fixed.

      We apologise for the mistake in the figure legend that made this confusing, which we have now revised.

      The abstract says that editing a line that is homozygous for protective alleles to homozygous for risk results in "subtle downregulation of PTK2B expression". It isn't clear to me that the presented data fully supports this contention, which is central to the argument of the paper. In figure 2e, the authors show in both RNAseq and ddPCR that there is numerically lower PTK2B expression but this is not indicated to be statistically significant by one-way paired ANOVA. If there is no nominally significant difference in the edited lines, compared to the proposed significant differences in lines carrying the full risk haplotype (figure 1), then it would not seem sensible to ascribe the effects to the single edited base pair.

      We agree with the reviewer that given the effect of the SNP on PTK2B expression in the edited lines is small and only significant in macrophages, we should not interpret the effects to be mediated solely through PTK2B expression, and have substantially reworded the manuscript accordingly.

      Whilst the effects in the eQTL analysis are significant, it is worth noting that this is likely due to the much larger number of donors (133-217) giving greater power to detect the subtle changes in expression (~1.1 to 2 fold in eQTL). This change is of a similar magnitude in our SNP edited lines (~1.2 fold in SNP edited lines) as would be expected of most common regulatory variants so we believe that it could be the primary causal variant. However, we cannot exclude that other variants in the haplotype could contribute to the effect, so have also reworded accordingly to make this clear.

      Given this uncertainty about the overall strength of effect of the single base pair change it would seem important to evaluate the proposed mechanism of CEBPb binding. It wasn't clear whether the ATAC-seq data summarized in the volcano plot in 2C is proposed to be a cause or a consequence of the CEBPb binding change. I am assuming that the 'fold change' estimate here is CC compared to TT, which would be consistent with direction of effect in figure 1, but please clarify.

      We apologise for the mistake in the figure legend that made this confusing, which we have now revised along with clarification in the revised text. It is difficult to be sure whether changes in chromatin accessibility are a cause or consequence of CEBPb binding, but the fact that the binding of CEBPb is increased in the CC allele (Fig 2a, Fig 2c), that the C allele better matches the consensus sequence (Fig 2b) and there is increased chromatin accessibility (Fig 2a, Supp Fig 3b) suggests that CEBPb binding is causing the formation of the region of chromatin accessibility.

      In contrast to the subtle effects at PTK2B, the global transcriptional effects in figure 3 look quite strong. Are any of these changes dependent on PTK2B, that is to say, are they mimicked by partial suppression of PTK2B expression or activity?

      We agree that the downstream effects of the SNP are much stronger than the effects on PTK2B expression, and we have substantially reworded the manuscript to make it clear that we are unsure that the effects of the SNP are all mediated via PTK2B.

      However, we note that there is evidence in the literature of a loss in CCL4 and CCL5 expression upon PTK2B knockout in macrophages (https://www.nature.com/articles/s41467-021-27038-5) and inhibition of PTK2B in monocytes results in a reduction in CCL5 and CXCL1 (https://www.nature.com/articles/s41598-019-44098-2) consistent with our observations.

      Experiments to manipulate PTK2B expression in microglia and readout changes at the RNA level would take a few months to complete, but we would be willing to do this if the reviewer felt this was necessary.

      Finally, in figure 4, it should be clarified as to why lower expression of PTK2B would be expected to have a detrimental effect on Alzheimer's risk. If understood correctly, and again fixing the figure legends would be helpful, the CC edited lines (risk) have lower chemokine induction than the unedited TT lines.

      We apologise for the error in this figure which we have corrected in the revised version. You are correct that the CC lines have a lower chemokine level in both unstimulated and stimulated cells, and we have now discussed further how this may be linked to increased disease risk.

      "Even though overexpression of these chemokines is characteristic of neuroinflammation, correlated with disease progression and found in late stages of AD, knockout of chemokines, such as CCL2, and chemokine receptors, such as CCR2 and CCR5, in mice is associated with increased Aβ deposition and accumulation [47,50-52,107]. It has also been found that patients carrying CCR5Δ32 mutation, which prevents CCR5 surface expression, develop AD at a younger age[108]. Therefore, we hypothesize that in individuals carrying the C/C allele of rs28834970 downregulation of these chemokines in macrophages and microglia harbouring the C/C allele of rs28834970 affects Aβ-induced microglia chemotaxis, leukocytes recruitment and clearance of Aβ, and may increase the risk of developing symptomatic AD"

      Reviewer #1 (Significance (Required)):

      Going from GWAS hits, which represent blocks of high LD inherited variants, to single functional variants is a difficult problem in human genetics. The current paper attempts to isolate the effect of a single variant within an LD block on IPSC derived macrophages and microglia. This idea might be useful in nominating PTK2B as a therapeutic target for AD, although there is some question in my mind as to direction of effect.

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

      SUMMARY: In this manuscript the authors explore the biological effects of an intronic SNP in the PTK2B gene, previously shown to be associated with late onset Alzheimer's disease (AD) risk. Based on the likely effect of the SNP locus on PTK2B expression in the macrophage lineage, the authors explore the consequences of introducing with the Crispr/Cas9 technique the biallelic SNP base change (C/C vs T/T) in a human IPSC line that is then differentiated into macrophages or microglia. They observe that C/C increases chromatin accessibility and CEBPb binding in comparison to T/T, with a slight decrease in PTK2B expression, significant in macrophages but not in microglia. The authors then investigate the transcriptome changes induced by the C/C mutation and find alteration in many genes, including a decreased expression of a number of cytokine or receptor proteins involved in inflammatory responses. The authors also mention a decreased effect on IFNg-induced reduced mobility but the data are missing (see Figure errors below). Overall the authors propose that the risk SNP is associated with a decreased PTK2B expression and hypothesize a link between this change and a decreased function of macrophages/microglia that may contribute to AD pathology.

      MAJOR COMMENTS

      1- The authors claim that their results show that the investigated SNP has a causal effects in "microglial function" (Title) and in Alzheimer's disease (AD) (Abstract 2nd sentence "Here we validate a causal single nucleotide polymorphism (SNP) associated with an increased risk of Alzheimer's disease". The word "causal" is repeated many times. However the authors should qualify their claim with respect to AD. Their results do show that the SNP has an effect on chromatin accessibility, CEBP binding, PTK2B expression and transcriptome, but the link between these changes is not formally demonstrated and their potential role in AD-like phenotype is not explored. The "causal" role is not formally and logically demonstrated. It remains an interesting, plausible hypothesis and the results provide strong arguments in support of that hypothesis but do not prove it, yet.

      Concerning the title, "causal effects on microglial function" is awkward, anything that has effects is logically "causal" in these effects. The title should be "... has effects on microglial functions" or "... alters microglial function".

      We agree with the reviewer that given the effect of the SNP on PTK2B expression in the edited lines is small and only significant in macrophages, we should not interpret the effects to be mediated solely through PTK2B expression, or that they cause AD. We have substantially reworded the manuscript throughout to account for this.

      2- One major difficulty in the results is to link the slight decrease in PTK2B transcript, which is only significant in macrophages, with the rest of the phenotype. Because what matters to make this link is not the mRNA but the protein, and because mRNA levels are often not strictly correlated with the protein levels, the authors should measure the PTK2B/PYK2 protein levels in their differentiated cell lines in basal conditions and following activation (as they do for other readouts) using immunoblotting. A robust and significant diminution in PYK2 protein would strongly support its role in linking PTK2B expression and transcriptome change.

      We have performed preliminary analyses of PTK2B expression by Western blot in these cell lines after differentiation, but were unable to observe a significant change in abundance in the edited cell lines. This is not unexpected given the results at the RNA level, since the effect size of this common regulatory variant is likely very small (estimated to be ~1.2 fold from the eQTL analysis), and likely within the variability of this assay.

      As mentioned above, we have reworded the manuscript to avoid interpreting that the effects of rs28834970 are mediated solely through effects on PTK2B expression. We think that an experiment to manipulate PTK2B levels (see next point) may be a better way to demonstrate whether these effects are mediated through PTK2B expression.

      An optional additional key experiment would be to reverse the transcriptome phenotype by increasing the expression of PTK2B (e.g. by cDNA transfection). Note that these points are important because an alternative hypothesis to explain the effects of C/C mutation on macrophage function would be that the C/C mutation has a long distance effect on other chromatin regions with key role in regulating these cells.

      We agree that this would be a valuable experiment, and are planning additional experiments to investigate the effect of manipulating PTK2B levels (through knockout) on microglia.

      3- The manuscript contains several errors in the figures and figure legends. In Fig. 2 the legends for the figure items are shuffled. Figure 4 and Supplementary Figure 5 are duplicates of the same one. Consequently important data are not presented.

      We apologise for the errors in these figures that were due to a mistake during uploading where the incorrect versions were used. The legends for figure 2 and panels in figure 4 have now been corrected, and show the effects of rs28834970 on microglial migration and chemokine release in the presence or absence of IFNg.

      4- When the number of replicates is small (e.g. n = 3) it is preferable to use non parametric tests (rank analysis, e.g. Mann Whitney's test) rather than t test. This applies to Figures 2D (current legend 2A), 2E (current legend 2B), Figure 4A-C, Supplementary Figures 2A, 2B. In Supplementary Fig 4E (MARCO) the number of replicates (presumably 3 because based on RNAseq) and the used test are not indicated. Is it the RNAseq statistical analysis?

      We thank the reviewer for this comment. We acknowledge that the t-test may lead to inflated false discovery rates. However, it has been shown that for small sample sizes parametric tests have a power advantage compared to non-parametric ones that may outweigh the possibly exaggerated false positives. See https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02648-4#Sec3 which states:

      "In conclusion, when the per-condition sample size is less than 8, parametric methods may be used because their power advantage may outweigh their possibly exaggerated false positives."

      We have also modified the legend of supplementary figure 4E to clarify the number of replicates used.

      5- In addition to the above comment on tests, when the number of replicates is small it is not appropriate (and misleading) to show box plots or bars with SEM. In the indicated figures the individual data points should be shown.

      We now show individual replicates on box plots (Figure 2D, 2E and supp figure 4E).

      MINOR COMMENTS:

      a- Macrophages and microglia are very similar cell types. Could the authors comment more on the differences they observe and how they are related to those previously described?

      We have now referenced the original papers and commented on the markers that we see differentially expressed, notably P2RY12 which is a key homeostatic microglia marker that distinguishes these cells from macrophages.

      b- In Fig. 2A CEBPb cut and run plot, the differences are not limited to the SNP immediate vicinity, there are also visible differences between T/T and C/C plots in at least a 40-kb range. Is it due to multiple interactions of CEBPb? How can the point difference have broad consequences? Please explain this potentially interesting and relevant finding.

      Whilst there may be small changes in CEBPb binding at the second intronic PTK2B chromatin peak, this is not statistically significant given the variability between repeats. In fact, the only significant change we see in CEBPb binding genome-wide is at the locus overlapping the SNP (Fig 2c).

      c- Potentially cis-altered genes near the SNP include CHRNA2 and EPHX2 (see Sup. Fig. 3a). Their expression may not be detected in macrophage lineage. If this is the case please indicate in the text, otherwise please include the corresponding data in Sup. Fig. 3b to show the presence or absence of SNP-induced change.

      You are correct that CHRNA2 and EPHX2 are not expressed in our macrophages or microglia, and we have now explicitly stated this in the revised text.

      d- In general the Figures are not of very high quality and are difficult to read or understand without constantly going back and forth to the legends (which are mislabeled in some instances). To improve:

      . Please increase font size whenever possible.

      . Please improve Fig. 1d by indicating the position of the SNP, numbering the exons (an intermediate scale plot may be necessary and lines on bottom trace are hardly visible).

      . Please indicate the correct color code for T/T and C/C in Fig 3a and b, left panels, which currently doesn't match.

      . Please label the Venn's diagrams comparisons in Sup. Fig. 4b.

      . In the text and legends the Figure items are identified with letters in upper case, in the figures they are in lower case. Please be consistent.

      We have improved the resolution of the images in the pdf and Fig 1d has been revised to include the position of the SNP. The colour code for T/T and C/C is correct in fig 3a and 3b, but since the PCA plots are independently created, we would not always expect the position of the T/T and C/C alleles to be the same. The Venn diagrams in Sup Fig 4b have been updated, and the letters for the figure panels made consistently upper case throughout.

      e- In Fig. 2D and 2E, the Y axes should start at zero to avoid artificially increasing the visual differences. If there is a strong reason not to do so (I don't see any here), the Y axis should be clearly interrupted to avoid confusion.

      We have altered this accordingly.

      f- In the introduction the authors provide some background about previous work about the potential role of PTK2B/PYK2 in AD pathophysiology. The cited preclinical results suggest that PTK2B activity could have a deleterious effect (references in the manuscript). In contrast, some other reports (PMID: 29803828, 33718872) suggest a protective effect of PTK2B/PYK2. Because the evidence in the current manuscript suggests that the risk-associated SNP results in a decreased function of PTK2B/PYK2 (through decreased levels), at least in cells of the macrophage lineage, the authors could broaden their discussion to include these results.

      We have now discussed the conflicting evidence in the revised manuscript.

      Reviewer #2 (Significance (Required)):

      ADVANCE: Late onset Alzheimer's disease is a major medical issue. It has a complex genetic risk component with many associated loci identified in GWAS. Most of these have only a small individual impact on the risk. One of the SNPs associated with increased risk (rs28834970) is located in an intron of the PTK2B gene. Although various reports have investigated the role of the PTK2B gene product, the tyrosine kinase PYK2, in several AD models, the possible link with rs28834970, is unclear.

      An important point is to determine whether TàC SNP corresponding to rs28834970 alters PTK2B expression and how it does so. An alternative hypothesis could be that the SNP has a strong linkage disequilibrium with an unidentified allele in human populations that could be responsible for AD risk. The current manuscript is a significant step forward in addressing that question. By generating a biallelic C/C SNP mutation in a human IPSC line the current study allows to eliminate such linked contribution.

      The strength of the manuscript is to show an effect on chromatin accessibility, CEBP binding and possibly PTK2B transcripts. It also provides interesting evidence of a broad effect of the C/C mutation on the transcriptome of macrophage lineage cells. In its current form the manuscript presents weaknesses that could be improved. These flaws include issues with the presentation discussed above and the uncomplete demonstration that it is the decrease in PTK2B expression that causes the macrophage/microglia phenotype. If these flaws were overcome the paper would represent a significant advance.

      AUDIENCE: The expected audience is specialized in AD with a possible broader range if all weaknesses are addressed.

      REVIEWER EXPERTISE: Basic science close to the field.

      PeerReviewed
    2. EMBOpress 05 Jul 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary: In this manuscript the authors explore the biological effects of an intronic SNP in the PTK2B gene, previously shown to be associated with late onset Alzheimer's disease (AD) risk. Based on the likely effect of the SNP locus on PTK2B expression in the macrophage lineage, the authors explore the consequences of introducing with the Crispr/CAS9 technique the biallelic SNP base change (C/C vs T/T) in a human IPSC line that is then differentiated into macrophages or microglia. They observe that C/C increases chromatin accessibility and CEBPb binding in comparison to T/T, with a slight decrease in PTK2B expression, significant in macrophages but not in microglia. The authors then investigate the transcriptome changes induced by the C/C mutation and find alteration in many genes, including a decreased expression of a number of cytokine or receptor proteins involved in inflammatory responses. The authors also mention a decreased effect on IFNg-induced reduced mobility but the data are missing (see Figure errors below). Overall the authors propose that the risk SNP is associated with a decreased PTK2B expression and hypothesize a link between this change and a decreased function of macrophages/microglia that may contribute to AD pathology.

      Major comments:

      1. The authors claim that their results show that the investigated SNP has a causal effects in "microglial function" (Title) and in Alzheimer's disease (AD) (Abstract 2nd sentence "Here we validate a causal single nucleotide polymorphism (SNP) associated with an increased risk of Alzheimer's disease". The word "causal" is repeated many times. However the authors should qualify their claim with respect to AD. Their results do show that the SNP has an effect on chromatin accessibility, CEBP binding, PTK2B expression and transcriptome, but the link between these changes is not formally demonstrated and their potential role in AD-like phenotype is not explored. The "causal" role is not formally and logically demonstrated. It remains an interesting, plausible hypothesis and the results provide strong arguments in support of that hypothesis but do not prove it, yet. Concerning the title, "causal effects on microglial function" is awkward, anything that has effects is logically "causal" in these effects. The title should be "... has effects on microglial functions" or "... alters microglial function".
      2. One major difficulty in the results is to link the slight decrease in PTK2B transcript, which is only significant in macrophages, with the rest of the phenotype. Because what matters to make this link is not the mRNA but the protein, and because mRNA levels are often not strictly correlated with the protein levels, the authors should measure the PTK2B/PYK2 protein levels in their differentiated cell lines in basal conditions and following activation (as they do for other readouts) using immunoblotting. A robust and significant diminution in PYK2 protein would strongly support its role in linking PTK2B expression and transcriptome change. An optional additional key experiment would be to reverse the transcriptome phenotype by increasing the expression of PTK2B (e.g. by cDNA transfection). Note that these points are important because an alternative hypothesis to explain the effects of C/C mutation on macrophage function would be that the C/C mutation has a long distance effect on other chromatin regions with key role in regulating these cells.
      3. The manuscript contains several errors in the figures and figure legends. In Fig. 2 the legends for the figure items are shuffled. Figure 4 and Supplementary Figure 5 are duplicates of the same one. Consequently important data are not presented.
      4. When the number of replicates is small (e.g. n = 3) it is preferable to use non parametric tests (rank analysis, e.g. Mann Whitney's test) rather than t test. This applies to Figures 2D (current legend 2A), 2E (current legend 2B), Figure 4A-C, Supplementary Figures 2A, 2B. In Supplementary Fig 4E (MARCO) the number of replicates (presumably 3 because based on RNAseq) and the used test are not indicated. Is it the RNAseq statistical analysis?
      5. In addition to the above comment on tests, when the number of replicates is small it is not appropriate (and misleading) to show box plots or bars with SEM. In the indicated figures the individual data points should be shown.

      Minor comments:

      • a. Macrophages and microglia are very similar cell types. Could the authors comment more on the differences they observe and how they are related to those previously described?
      • b. In Fig. 2A CEBPb cut and run plot, the differences are not limited to the SNP immediate vicinity, there are also visible differences between T/T and C/C plots in at least a 40-kb range. Is it due to multiple interactions of CEBPb? How can the point difference have broad consequences? Please explain this potentially interesting and relevant finding.
      • c. Potentially cis-altered genes near the SNP include CHRNA2 and EPHX2 (see Sup. Fig. 3a). Their expression may not be detected in macrophage lineage. If this is the case please indicate in the text, otherwise please include the corresponding data in Sup. Fig. 3b to show the presence or absence of SNP-induced change.
      • d. In general the Figures are not of very high quality and are difficult to read or understand without constantly going back and forth to the legends (which are mislabeled in some instances). To improve:
        • Please increase font size whenever possible.
        • Please improve Fig. 1d by indicating the position of the SNP, numbering the exons (an intermediate scale plot may be necessary and lines on bottom trace are hardly visible).
        • Please indicate the correct color code for T/T and C/C in Fig 3a and b, left panels, which currently doesn't match.
        • Please label the Venn's diagrams comparisons in Sup. Fig. 4b.
        • In the text and legends the Figure items are identified with letters in upper case, in the figures they are in lower case. Please be consistent.
      • e. In Fig. 2D and 2E, the Y axes should start at zero to avoid artificially increasing the visual differences. If there is a strong reason not to do so (I don't see any here), the Y axis should be clearly interrupted to avoid confusion.
      • f. In the introduction the authors provide some background about previous work about the potential role of PTK2B/PYK2 in AD pathophysiology. The cited preclinical results suggest that PTK2B activity could have a deleterious effect (references in the manuscript). In contrast, some other reports (PMID: 29803828, 33718872) suggest a protective effect of PTK2B/PYK2. Because the evidence in the current manuscript suggests that the risk-associated SNP results in a decreased function of PTK2B/PYK2 (through decreased levels), at least in cells of the macrophage lineage, the authors could broaden their discussion to include these results.

      Significance

      Advance: Late onset Alzheimer's disease is a major medical issue. It has a complex genetic risk component with many associated loci identified in GWAS. Most of these have only a small individual impact on the risk. One of the SNPs associated with increased risk (rs28834970) is located in an intron of the PTK2B gene. Although various reports have investigated the role of the PTK2B gene product, the tyrosine kinase PYK2, in several AD models, the possible link with rs28834970, is unclear.

      An important point is to determine whether TC SNP corresponding to rs28834970 alters PTK2B expression and how it does so. An alternative hypothesis could be that the SNP has a strong linkage disequilibrium with an unidentified allele in human populations that could be responsible for AD risk. The current manuscript is a significant step forward in addressing that question. By generating a biallelic C/C SNP mutation in a human IPSC line the current study allows to eliminate such linked contribution.

      The strength of the manuscript is to show an effect on chromatin accessibility, CEBP binding and possibly PTK2B transcripts. It also provides interesting evidence of a broad effect of the C/C mutation on the transcriptome of macrophage lineage cells. In its current form the manuscript presents weaknesses that could be improved. These flaws include issues with the presentation discussed above and the uncomplete demonstration that it is the decrease in PTK2B expression that causes the macrophage/microglia phenotype. If these flaws were overcome the paper would represent a significant advance.

      Audience: The expected audience is specialized in AD with a possible broader range if all weaknesses are addressed.

      Reviewer Expertise: Basic science close to the field.

      PeerReviewed
    3. EMBOpress 05 Jul 2024

      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

      Bello et al look at the SNP rs28834970 associated with Alzheimer's disease (AD), with C being the risk allele, on chromatin accessibility and expression of a nearby gene, PTK2B, in microglia. Their contention is that the single SNP affects chromatin accessibility and binding of the transcription factor CEBP[beta] in an intronic region of PTK2B and thereby affects PTKB expression. I had a few questions that I think are critical to be addressed. Please note that my numbering of panels is based on the figures, not the legends, which do not seem to quite agree with each other. There are also some figure legends that say "IFNg" while the figures say "LPS", which should be fixed.

      The abstract says that editing a line that is homozygous for protective alleles to homozygous for risk results in "subtle downregulation of PTK2B expression". It isn't clear to me that the presented data fully supports this contention, which is central to the argument of the paper. In figure 2e, the authors show in both RNAseq and ddPCR that there is numerically lower PTK2B expression but this is not indicated to be statistically significant by one-way paired ANOVA. If there is no nominally significant difference in the edited lines, compared to the proposed significant differences in lines carrying the full risk haplotype (figure 1), then it would not seem sensible to ascribe the effects to the single edited base pair.

      Given this uncertainty about the overall strength of effect of the single base pair change it would seem important to evaluate the proposed mechanism of CEBPb binding. It wasn't clear whether the ATAC-seq data summarized in the volcano plot in 2C is proposed to be a cause or a consequence of the CEBPb binding change. I am assuming that the 'fold change' estimate here is CC compared to TT, which would be consistent with direction of effect in figure 1, but please clarify.

      In contrast to the subtle effects at PTK2B, the global transcriptional effects in figure 3 look quite strong. Are any of these changes dependent on PTK2B, that is to say, are they mimicked by partial suppression of PTK2B expression or activity?

      Finally, in figure 4, it should be clarified as to why lower expression of PTK2B would be expected to have a detrimental effect on Alzheimer's risk. If understood correctly, and again fixing the figure legends would be helpful, the CC edited lines (risk) have lower chemokine induction than the unedited TT lines.

      Significance

      Going from GWAS hits, which represent blocks of high LD inherited variants, to single functional variants is a difficult problem in human genetics. The current paper attempts to isolate the effect of a single variant within an LD block on IPSC derived macrophages and microglia. This idea might be useful in nominating PTK2B as a therapeutic target for AD, although there is some question in my mind as to direction of effect.

      PeerReviewed
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    biorxiv.org/content/10.1101/2023.11.04.565613v2
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    Phosphoproteomic analysis reveals the diversity of signaling behind ErbB inhibitor-induced phenotypes
    4
    1. EMBOpress 05 Jul 2024

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

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      Reply to the reviewers

      The manuscript " Phosphoproteomic analysis reveals the diversity of signaling behind ErbB inhibitor-induced phenotypes" authored by Drs. Katri Vaparanta, Anne Jokilammi, Johannes Merilahti, Johanna Örling, Noora Virtanen, Cecilia Sahlgren, Klaus Elenius and Ilkka Paatero was reviewed in Review Commons, and we carried out a full revision based on the received reviewer comments.

      The comments from three reviewers and our point-by-point reply is here below. After each of reviewer´s comment, our reply is formatted in bold.

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

      In this study, Vaparanta and co-workers used zebrafish embryos as model to analyze the impact of ErbB tyrosine kinase inhibitors on signaling pathways at the whole organism level. Experimentally, zebrafish embryos were exposed for 1 hour to a single dose of 3 different ErbB tyrosine kinase inhibitors and the global phosphoproteome of the embryos was analyzed by MS/MS. The authors show that the 3 inhibitors differentially modulate the activity of PI3K/Akt, p38 MAPK, Notch, Hippo-YAP/TAZ and β-catenin signaling pathways, associated with different neurological and myocardial phenotypic changes. Using small molecule inhibitors of selective signaling pathways, they show that perturbation of different signaling pathways may induce similar phenotypes in zebrafish embryos.

      Specific comments:

      1. The observation that exposure of zebrafish embryos to lapatinib, gefitinib and AG1478 leads to different global phosphoproteomic changes and to differential modulation of cellular signaling pathways was predictable and supported by an abundant literature. These 3 inhibitors differentially inhibit ErbB homo- and heterodimers and hit many other kinases. This point should be discussed in the paper.

      Indeed, the kinase inhibitors do have different selectivity for the ErbB family kinases as pointed out by the reviewer. We have now discussed this point in the manuscript (new Supplemental Table 1) and added additional data from embryos treated with different ErbB kinase inhibitors with similar selectivity profiles into the manuscript (new Supplemental Figure 3-4). The ErbB family kinase selectivity profile of the inhibitors, however, does not fully explain why treatment with lapatinib (EGFR/ErbB2 inhibitor) induced the most unique phosphoproteomic changes from AG1478 (EGFR/ErbB2/ErbB4 inhibitor) and gefitinib (EGFR inhibitor) treatment in zebrafish embryos. This point is now discussed in the manuscript.

      AG1478 is a first-generation tyrphostin while gefitinib and lapatinib are FDA-approved drugs. These compounds not only have different selectivity profiles, but also different pharmacological properties. Do the authors have any information about the permeability, distribution or concentration of the compounds in zebrafish embryos? Otherwise, how can they compare their effects?

      __The reviewer points out correctly, that not only selectivity but also several other parameters could differ between compounds. The logic of our experimentation was to utilize differences in the properties of inhibitors to get new insights into underlying biological processes. These utilized differences could arise from not only selectivity but also as well from pharmacokinetic and –dynamic properties. Although it can be useful to understand these differences, this information per se is not needed to identify differentially regulated pathways that could affect the studied phenotypes. This is now better clarified in the discussion section. Our data indicates that ErbB inhibition profile explains a significant proportion, but not all, of observed signaling differences (Supplemental Fig. 3C). __

      One major limitation of this study is that phosphoproteomic analysis was performed at a single time point and with a single dose of inhibitor, which compromises the interpretation of the findings. How was the dose of each inhibitor selected?

      The doses were chosen based on our previous work (Paatero et al, 2019; Vaparanta et al, 2023), where with these inhibitor concentrations we were able to maximize the phenotypic effects without causing significant mortality. This is now mentioned in the results section of the manuscript. Higher dosages were lethal for the embryos, especially of AG1478, which is why a lower concentration of this inhibitor was used. The higher toxicity of AG1478 at lower concentrations compared to other ERBB inhibitors has also been previously noted by another group (Pruvot et al, 2014). Similar concentrations of the inhibitors have also been previously used by other groups with zebrafish embryos (Tran et al, 2007; Gallardo et al, 2015; Zhang et al, 2021; Du et al, 2024)__. __

      One approach for better exploiting the data would be to correlate changes in phosphopeptides with the kinome selectivity of the inhibitors.

      Indeed, we have now correlated our results from these inhibitors with other ErbB inhibitors of similar ErbB family kinase selectivity. The phosphoproteomic changes induced by inhibitors with similar ErbB family kinase selectivity significantly correlate (P = 0.0002, r:0.80 ,R2:0.65, Supplemental Fig. 3C) indicating that the ErbB selectivity plays a major role in determining the phosphoproteomic changes induced by these inhibitors. We also performed a correlation analysis between dimensionality-reduced phosphoproteomic changes and inhibitor selectivity. There was no significant correlation between the changes in the phosphoproteome and the ERBB selectivity of the inhibitors (P=0.1551, One-tailed Pearson correlation). Taken together, these results indicate that while the phosphoproteomic changes induced by these inhibitors can be reproduced by other inhibitors with similar ERBB selectivity profiles, inhibiting only a subset of the ERBB kinases (especially EGFR and ERBB2, but not ERBB4) produces a unique signaling signature that is not recapitulated with pan-ERBB inhibitor treatment. This information may be of interest since both lapatinib (EGFR/ERBB2 inhibitor) and neratinib (pan-ERBB inhibitor) are both used in the clinic to treat HER2-positive breast cancer. Our data indicates that the administration of these inhibitors to patients will likely have a differential global effect on cell signaling.

      In the same vein, the signaling inhibitors used in Fig. 4 to dissect the phenotypic impact of distinct signaling pathways are non-selective, precluding any rigorous interpretation of the data. This confounding factor should at least be discussed in the manuscript. Again, the choice of the different doses of inhibitors is not justified.

      Indeed, like all inhibitors, the inhibitors we utilized in Figure 4 can have some off-target effects. We aimed to use the concentration known by previous literature to have a measurable effect on the physiology of the zebrafish embryo (Fujii et al, 2000; Geling et al, 2002; Vasilyev et al, 2012; Jiang et al, 2023)__. These concentrations for different inhibitors were different in the literature, which is why different concentrations of the different inhibitors were used. We couldn’t find a reference for the concentration for VT-103, so a 30µM concentration was selected. With this concentration, the size of the embryo hearts was significantly reduced (P

      The effect of inhibitors on the motility of embryos appears variable. For example, lapatinib markedly decreases motility in Fig. 4E but has no effect in Fig. 4F. Any explanation?

      Different inhibitor concentrations were used in Figure 4E and Figure 4F. This has been now more clearly indicated in the manuscript in the results section and the figure legend. The lower inhibitor dosages in Figure 4F were to reduce the mortality and allow motility analyses of the embryos treated with a combination of the inhibitors analyses to facilitate observation of potential synergistic actions of inhibitors in co-treated embryos.

      The conclusion that ErbB inhibitors induce similar phenotypes by perturbing different signaling pathways is not justified.

      We have now softened our conclusions in the manuscript in the results section by replacing the sentence:” Taken together, these results suggest that AG1478 and lapatinib induce similar phenotypes by partially perturbing different signaling pathways in zebrafish embryos.” With the sentences: ” Taken together, these results suggest that AG1478 and lapatinib induce similar phenotypes but perturb different signaling pathways. Inhibition of these pathways induce similar phenotypes to lapatinib or AG1478 treatment in zebrafish embryos.”.

      I have a few suggestions which could enhance the study's contribution to the field-

      1. The rationale for this study should be elaborated further. What new information is expected to emerge from these studies, independently of the conceptual and technical limitations outlined above?

      We have now further elaborated the rationale of the study in the introduction section.

      The advantage of studying the whole organism instead of selected tissues is questionable. Analyzing a mixture of organs may mask subtle and physiologically relevant alterations of signaling pathways in specific tissues.

      We agree with the reviewer that if the researcher’s interests reside in a specific tissue then a more targeted approach should be applied to probe the phosphoproteome of this tissue. However, sometimes a more global view of the inhibitor effects is required especially when it is unknown which tissues are affected by the inhibitor treatment. Ideally, the global approach would be followed by a more targeted approach on the tissues that are indicated to be affected by the inhibitor. One must also consider the feasibility, time consumption and costs of probing all tissues separately. If only the targeted approach is applied, the information on what pathway activities are globally most affected in the organism by the inhibitor treatment can be hard to estimate.

      Can the authors correlate neurological and myocardial phenotypes extrapolated from their study with pharmacological effects observed in mice or humans treated with these compounds?

      __We have now correlated our findings in the discussion section with the previous literature on the phenotypes of ErbB inhibitor-treated and ErbB receptor knock-out mice and with the reported adverse effects of ErbB inhibitor treatment in the clinic. __

      Reviewer #1 (Significance (Required)):

      The authors show that the 3 inhibitors differentially modulate the activity of PI3K/Akt, p38 MAPK, Notch, Hippo-YAP/TAZ and β-catenin signaling pathways, associated with different neurological and myocardial phenotypic changes. Using small molecule inhibitors of selective signaling pathways, they show that perturbation of different signaling pathways may induce similar phenotypes in zebrafish embryos.

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

      In this study, the authors assess the effects of various ErbB receptor family tyrosine kinase inhibitors on the phosphoproteome of late embryonic and early larval stages of zebrafish. MS, Western blotting, and analysis of a transgenic zebrafish Notch signaling reporter line data suggest differential but overlapping effects of treatment with gefitinib, lapatinib and AG1478. Selected deregulated pathways are further assessed using a range of candidate downstream pathway-targeting inhibitors. Inhibitor treatment followed by quantification of spontaneous larval motility and heart ventricle wall area, which were previously found by the authors to be affected by AG1478 and lapatinib treatment, identifies involved downstream signaling pathways.

      Major comments:

      While I do not question the validity of the presented data showing phosphoproteome perturbations resulting from the performed ErbB inhibitor treatments, the treatment regimens used to assess the differential effects of the compounds may be insuffient to substantiate general statements comparing the phenotypic and phosphorylation effects of lapatinib, gefitinib and AG1478 beyond the effects of the specific doses applied to the embryo media. Unless directly quantified, it is difficult to reliably predict the in vivo dose resulting from drug administered to the embryo medium, and therefore a dose may be too high or too low for drug-to-drug comparison. Rationale for chosen dose of drugs should be provided. If available, inclusion of quantitative data on the drug-induced change in phosphorylation status of the drug target(s) is encouraged, and the discussion of the phosphoproteomic and phenotypical data should include this information.

      The reviewer points out correctly, that not only selectivity but also several other parameters could differ between compounds. The logic of our experimentation was to utilize differences in the properties of inhibitors to get new insights into underlying biological processes. These utilized differences could arise from not only selectivity but also as well from pharmacokinetic and –dynamic properties. Although it can be useful to understand these differences, this information per se is not needed for the identification of differentially regulated pathways that could affect the studied phenotypes. This is now better clarified in the manuscript.

      The rationale for the chosen drug doses has now been added to the manuscript in the results section. We used drug concentrations that were known to produce a phenotypic effect without causing significant mortality in the zebrafish embryos.

      The ErbB receptors themselves are expressed at low levels, and unfortunately, we couldn´t reliably observe phosphopeptides of ErbB tyrosine autophosphorylation sites. To address this issue from a different angle, we treated embryos with other ErbB inhibitors exhibiting similar ErbB inhibition profiles as AG1478, lapatinib, and gefitinib (Supplemental Figure 3-4). This data indicates that the ErbB inhibition profile correlates quite well with the observed changes in the downstream signaling pathways p38, pAkt, pErk and Notch (Figure 3C and 4C).

      Husbandry: The statement that "Zebrafish were maintained (...) following standard procedures." is insufficient without a specific reference. Please provide details on water quality parameters, temperature, light/darkness cycle and feeding regimen.

      The requested information has now been added to the manuscript.

      Western analysis: How many embryos were pooled in each sample? Please specify standard protocol or provide reference.

      We have now amended the western analysis chapter in the materials and methods section as suggested by the reviewer. Five embryos were pooled for each sample.

      Ventricle growth assay: The method of ventricle wall quantification is insufficiently described and might result in unnecessarily high variation. At which stage of the cardiac contraction-relaxation cycle were ventricle wall thickness and ventricle area measured? The confounding effect of contraction could be avoided altogether by stopping the heartbeat pharmacologically e.g. by administration of blebbistatin or verapamil. Subtracting ventricle lumen area from total ventricle area seems a much more direct measure of ventricle wall area than the estimation obtained by multiplying ventricle wall thickness with ventricle area.

      We apologize for the mistake in the materials methods section, where we had written area instead of perimeter. We have now amended the ventricle growth assay chapter in the materials and methods sections and added more details on the ventricle wall area estimation. The ventricle wall area was measured from high-speed movies in diastole and systole, and the average perimeter over these states was reported. The ventricle wall thickness was only measured in systole. We chose this quantification method since the lumen area is difficult to estimate in the systole.

      Phosphopeptide enrichment: How many embryos per sample? Final DMSO concentration is not stated.

      __Twenty embryos per sample and 1% DMSO was used. This information is now included in the materials and methods section. __

      P-values are presented for comparison of select groups only and a statement that e.g. only P-values We have added the recommended statement and the mean/median value with deviation values for the data indicated by the reviewer in the figure legends.

      Minor comments:

      Overall, the manuscript is well written and data and methods are well presented.

      The relevant targets within the ErbB family of receptors should be introduced including information on well-established functions and downstream signaling pathways to enable the non-specialist reader to place the presented data in the context of known gene and protein function. Furthermore, conservation of target proteins in zebrafish should be touched upon.

      We have now rewritten the introduction and results sections to include information on the ErbB family kinase selectivity of these inhibitors, the well-established functions and the target downstream pathways of ErbB receptors. We have now performed a multiple sequence alignment on the kinase domain of the ErbB receptors in human and zebrafish to estimate the conservation of the inhibitor targets in the zebrafish model. Human ErbB kinase domains had a high 86+/-9% sequence identity with zebrafish counterparts (Supplemental Figure 2) compared to 67+/-14% identity with the other ErbB kinase domain sequences in zebrafish (P=0.012).

      Given different target profiles of the tested drugs among receptors of the ErbB family, differences in protein phosphorylation perturbations and in treatment-induced phenotypes may not be unexpected. Statements such as: "An unexpectedly large cluster of phosphopeptides that were increased in lapatinib-treated embryos but reduced in AG1478 and gefitinib treated embryos was detected" and "AG1478 and lapatinib may induce similar phenotypes by partially perturbing different signaling pathways in zebrafish embryos" should be discussed in the context of known drug target(s) and their functions.

      We have now rewritten these statements as suggested by the reviewer and the target profiles are now discussed in the manuscript.

      **Referee Cross-commenting**

      I agree with the other reviewers on almost all points.

      1) While the sensitivity to smaller or highly local effects is most likely reduced using the whole organism approach compared to e.g. single tissue analysis, I do believe that it is highly relevant due to its ability to identify potential effects beyond a single tissue or organ.

      2) I maintain that while the presented data nicely show the effects of each administered dose of the individual compounds, the data does not allow for meaningful drug-to-drug comparisons without quantitative information on in vivo dose or direct target effect. If such information cannot be included, cross-drug conclusions and discussion should be done very carefully.

      Reviewer #2 (Significance (Required)):

      The evaluation of systemic molecular and phenotypic consequences of anti-cancer drugs in a vertebrate model system represents a relevant advancement. Although drug effects are likely to differ somewhat between embryonic and larval zebrafish and human cancer patients, the authors' comparison of obtained zebrafish data with human data supports translatability of the presented phosphoproteomics data. Also, the presented data pose a relevant advancement facilitating the informed use of the tested inhibitors as tools in basic science.

      Expertise: Molecular biology, signaling, zebrafish. Limited expertise in omics data analysis and pharmacology.

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

      The authors evaluated selected EGFR inhibitors developed as targeted cancer therapeutics, using zebrafish embryos and larvae as an in vivo model system. They performed mass spectrometry to analyze phosphorylation levels in target proteins, in combination with western blotting and gene set enrichment analyses; using this data, they assessed overlap between the inhibitors and overlap with known human data. They also performed imaging and locomotion analyses to assess alterations in phenotypes and phosphorylation-dependent signaling due to the inhibitor(s). The study generates novel information that is potentially relevant to the toxicity and efficacy of clinically used kinase inhibitors.

      • The statistical analyses are appropriate to the data and the experimental design.

      • The claims made by the authors are consistent with the data. In my opinion, the following revisions are needed for the manuscript to be accepted for publication:

      • There is no mention of Gefitinib in the Abstract; please include it.

      Gefitinib is now included in the Abstract.

      Please state the target selectivity profiles (from known preclinical and/or clinical data) of the three inhibitors used.

      __These are now presented in supplemental data (Supplemental Table 1), and analysed in relation to the observed signaling changes (Supplemental Figures 3 and 4). __

      Please clarify whether the residues mentioned in the phospho-specific antibody data refer to zebrafish or human proteins.

      Residues refer to human proteins as they are more widely used. This is now more clearly indicated in the materials and methods section.

      Please state whether the pan-antibodies corresponding to the phospho-specific antibody targets were used, and mention any problems associated with their use. This will help readers not familiar with antibody use in zebrafish experiments. It will also help emphasize the value of mass spectrometric analysis in zebrafish protein work.

      __As pointed out, the target specificity of antibodies is not often defined in zebrafish models on residue level, and phospho-specific antibodies may bind several closely related targets. The availability of robustly validated antibodies for zebrafish work, especially for phosphospecific epitopes, is quite limiting and therefore other, non-antibody-based techniques would be highly useful. This is now discussed in the manuscript. The phosphorylation site-specific antibodies used in this study indeed recognize the phosphorylated residue in several protein family members which further complicates the result interpretation. This is less of a limitation in the DIA-MS based phosphoproteomics approach which is now additionally discussed in the manuscript. __

      Please attempt to describe the clinically documented cardiovascular and neurological effects of the inhibitors and any correlation(s) with your data. This will enhance the impact of the study.

      See our reply for reviewer#1, comment 3.

      **Referee Cross-commenting**

      The common points raised in all the Reviews are the following:

      1. The rationale of the study should be described in more detail, especially the utility of zebrafish as an in vivo model, addressing its advantages and limitations.

      This is now discussed more extensively in the manuscript.

      The findings need to be described in the context of the target selectivity profiles and clinical effects of the inhibitors, especially the approved inhibitors (Gefitinib and Lapatinib).

      We have added data on target selectivity profiles (Supplemental Table 1), target conservation (Supplemental Figure 2) and also compared our observations to zebrafish embryos treated with other ErbB inhibitors with similar ErbB selectivity profiles (Supplemental Figure 3 and 4).

      1. In my opinion, while the comments regarding target site drug concentration (within the embryos/larvae) and dose-response are relevant, I consider these experiments to be appropriate in a more detailed follow-up study.

      We agree with the reviewer that the comprehensive pharmacokinetic studies fall outside the scope of this manuscript. As discussed before, in this manuscript we utilize differential inhibitor properties to gain new insight into phenotypes and underlying biological processes. This logic works even if the differences arise from properties other than the target selectivity.

      One of the main value additions of the study is that it highlights a useful alternative to conventional strategies used in preclinical cellular and mammalian model studies of kinase inhibitors. I would urge the authors to discuss specific future directions, giving due importance to all the reviewers' comments.

      This is now more extensively elaborated in the discussion section.

      Reviewer #3 (Significance (Required)):

      The experiments are well-described and provide sufficient information and detail for readers to understand and reproduce.

      The study is highly relevant to the use of zebrafish as a whole-organism model for in vivo evaluation of drugs, specifically kinase inhibitors.

      References

      Du K, Liu Y, Zhang L, Peng L, Dong W, Jiang Y, Niu M, Sun Y, Wu C, Niu Y et al (2024) Lapatinib combined with doxorubicin causes dose-dependent cardiotoxicity partially through activating the p38MAPK signaling pathway in zebrafish embryos. Biomed Pharmacother 175. doi:10.1016/J.BIOPHA.2024.116637.

      Fujii R, Yamashita S, Hibi M, Hirano T (2000) Asymmetric p38 activation in zebrafish: Its possible role in symmetric and synchronous cleavage. Journal of Cell Biology 150. doi:10.1083/jcb.150.6.1335.

      Gallardo VE, Varshney GK, Lee M, Bupp S, Xu L, Shinn P, Crawford NP, Inglese J, Burgess SM (2015) Phenotype-driven chemical screening in zebrafish for compounds that inhibit collective cell migration identifies multiple pathways potentially involved in metastatic invasion. DMM Disease Models and Mechanisms 8. doi:10.1242/dmm.018689.

      Geling A, Steiner H, Willem M, Bally-Cuif L, Haass C (2002) A γ-secretase inhibitor blocks Notch signaling in vivo and causes a severe neurogenic phenotype in zebrafish. EMBO Rep 3. doi:10.1093/embo-reports/kvf124.

      Jiang Y, Zhao X, Chen J, Aniagu S, Chen T (2023) PM2.5 induces cardiac malformations via PI3K/akt2/mTORC1 signaling pathway in zebrafish larvae. Environmental Pollution 323. doi:10.1016/j.envpol.2023.121306.

      Paatero I, Veikkolainen V, Mäenpää M, Schmelzer E, Belting HG, Pelliniemi LJ, Elenius K (2019) ErbB4 tyrosine kinase inhibition impairs neuromuscular development in zebrafish embryos. Mol Biol Cell 30. doi:10.1091/mbc.E18-07-0460.

      Pruvot B, Curé Y, Djiotsa J, Voncken A, Muller M (2014) Developmental defects in zebrafish for classification of EGF pathway inhibitors. Toxicol Appl Pharmacol 274. doi:10.1016/j.taap.2013.11.006.

      Tran TC, Sneed B, Haider J, Blavo D, White A, Aiyejorun T, Baranowski TC, Rubinstein AL, Doan TN, Dingledine R et al (2007) Automated, quantitative screening assay for antiangiogenic compounds using transgenic zebrafish. Cancer Res 67. doi:10.1158/0008-5472.CAN-07-3126.

      Vaparanta K, Jokilammi A, Paatero I, Merilahti JA, Heliste J, Hemanthakumar KA, Kivelä R, Alitalo K, Taimen P, Elenius K (2023) STAT5b is a key effector of NRG ‐1/ ERBB4 ‐mediated myocardial growth . EMBO Rep 24. doi:10.15252/embr.202256689.

      Vasilyev A, Liu Y, Hellman N, Pathak N, Drummond IA (2012) Mechanical stretch and PI3K signaling link cell migration and proliferation to coordinate epithelial tubule morphogenesis in the zebrafish pronephros. PLoS One 7. doi:10.1371/journal.pone.0039992.

      Xin M, Kim Y, Sutherland LB, Qi X, McAnally J, Schwartz RJ, Richardson JA, Bassel-Duby R, Olson EN (2011) Development: Regulation of insulin-like growth factor signaling by Yap governs cardiomyocyte proliferation and embryonic heart size. Sci Signal 4. doi:10.1126/scisignal.2002278.

      Zhang Y, Cai Y, Zhang SR, Li CY, Jiang LL, Wei P, He MF (2021) Mechanism of hepatotoxicity of first-line tyrosine kinase inhibitors: Gefitinib and afatinib. Toxicol Lett 343. doi:10.1016/j.toxlet.2021.02.003.

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    2. EMBOpress 05 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      The authors evaluated selected EGFR inhibitors developed as targeted cancer therapeutics, using zebrafish embryos and larvae as an in vivo model system. They performed mass spectrometry to analyze phosphorylation levels in target proteins, in combination with western blotting and gene set enrichment analyses; using this data, they assessed overlap between the inhibitors and overlap with known human data. They also performed imaging and locomotion analyses to assess alterations in phenotypes and phosphorylation-dependent signaling due to the inhibitor(s). The study generates novel information that is potentially relevant to the toxicity and efficacy of clinically used kinase inhibitors.

      • The statistical analyses are appropriate to the data and the experimental design.
      • The claims made by the authors are consistent with the data.

      In my opinion, the following revisions are needed for the manuscript to be accepted for publication:

      1. There is no mention of Gefitinib in the Abstract; please include it.
      2. Please state the target selectivity profiles (from known preclinical and/or clinical data) of the three inhibitors used.
      3. Please clarify whether the residues mentioned in the phospho-specific antibody data refer to zebrafish or human proteins.
      4. Please state whether the pan-antibodies corresponding to the phospho-specific antibody targets were used, and mention any problems associated with their use. This will help readers not familiar with antibody use in zebrafish experiments. It will also help emphasize the value of mass spectrometric analysis in zebrafish protein work.
      5. Please attempt to describe the clinically documented cardiovascular and neurological effects of the inhibitors and any correlation(s) with your data. This will enhance the impact of the study.

      Referee Cross-commenting

      The common points raised in all the Reviews are the following:

      1. The rationale of the study should be described in more detail, especially the utility of zebrafish as an in vivo model, addressing its advantages and limitations.
      2. The findings need to be described in the context of the target selectivity profiles and clinical effects of the inhibitors, especially the approved inhibitors (Gefitinib and Lapatinib).
      3. In my opinion, while the comments regarding target site drug concentration (within the embryos/larvae) and dose-response are relevant, I consider these experiments to be appropriate in a more detailed follow-up study.
      4. One of the main value additions of the study is that it highlights a useful alternative to conventional strategies used in preclinical cellular and mammalian model studies of kinase inhibitors. I would urge the authors to discuss specific future directions, giving due importance to all the reviewers' comments.

      Significance

      The experiments are well-described and provide sufficient information and detail for readers to understand and reproduce.

      The study is highly relevant to the use of zebrafish as a whole-organism model for in vivo evaluation of drugs, specifically kinase inhibitors.

      PeerReviewed
    3. EMBOpress 05 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      In this study, the authors assess the effects of various ErbB receptor family tyrosine kinase inhibitors on the phosphoproteome of late embryonic and early larval stages of zebrafish. MS, Western blotting, and analysis of a transgenic zebrafish Notch signaling reporter line data suggest differential but overlapping effects of treatment with gefitinib, lapatinib and AG1478. Selected deregulated pathways are further assessed using a range of candidate downstream pathway-targeting inhibitors. Inhibitor treatment followed by quantification of spontaneous larval motility and heart ventricle wall area, which were previously found by the authors to be affected by AG1478 and lapatinib treatment, identifies involved downstream signaling pathways.

      Major comments:

      While I do not question the validity of the presented data showing phosphoproteome perturbations resulting from the performed ErbB inhibitor treatments, the treatment regimens used to assess the differential effects of the compounds may be insuffient to substantiate general statements comparing the phenotypic and phosphorylation effects of lapatinib, gefitinib and AG1478 beyond the effects of the specific doses applied to the embryo media. Unless directly quantified, it is difficult to reliably predict the in vivo dose resulting from drug administered to the embryo medium, and therefore a dose may be too high or too low for drug-to-drug comparison. Rationale for chosen dose of drugs should be provided. If available, inclusion of quantitative data on the drug-induced change in phosphorylation status of the drug target(s) is encouraged, and the discussion of the phosphoproteomic and phenotypical data should include this information.

      Husbandry: The statement that "Zebrafish were maintained (...) following standard procedures." is insufficient without a specific reference. Please provide details on water quality parameters, temperature, light/darkness cycle and feeding regimen.

      Western analysis: How many embryos were pooled in each sample? Please specify standard protocol or provide reference. Ventricle growth assay: The method of ventricle wall quantification is insufficiently described and might result in unnecessarily high variation. At which stage of the cardiac contraction-relaxation cycle were ventricle wall thickness and ventricle area measured? The confounding effect of contraction could be avoided altogether by stopping the heartbeat pharmacologically e.g. by administration of blebbistatin or verapamil. Subtracting ventricle lumen area from total ventricle area seems a much more direct measure of ventricle wall area than the estimation obtained by multiplying ventricle wall thickness with ventricle area.

      Phosphopeptide enrichment: How many embryos per sample? Final DMSO concentration is not stated. P-values are presented for comparison of select groups only and a statement that e.g. only P-values < 0.05 are plotted would be helpful if applicable. Also, please provide mean +/- standard deviation for data presented in figures 3A, 3B, 4C, 4E, and 4F.

      Minor comments:

      Overall, the manuscript is well written and data and methods are well presented. The relevant targets within the ErbB family of receptors should be introduced including information on well-established functions and downstream signaling pathways to enable the non-specialist reader to place the presented data in the context of known gene and protein function. Furthermore, conservation of target proteins in zebrafish should be touched upon.

      Given different target profiles of the tested drugs among receptors of the ErbB family, differences in protein phosphorylation perturbations and in treatment-induced phenotypes may not be unexpected. Statements such as: "An unexpectedly large cluster of phosphopeptides that were increased in lapatinib-treated embryos but reduced in AG1478 and gefitinib treated embryos was detected" and "AG1478 and lapatinib may induce similar phenotypes by partially perturbing different signaling pathways in zebrafish embryos" should be discussed in the context of known drug target(s) and their functions.

      Referee Cross-commenting

      I agree with the other reviewers on almost all points.

      1. While the sensitivity to smaller or highly local effects is most likely reduced using the whole organism approach compared to e.g. single tissue analysis, I do believe that it is highly relevant due to its ability to identify potential effects beyond a single tissue or organ.
      2. I maintain that while the presented data nicely show the effects of each administered dose of the individual compounds, the data does not allow for meaningful drug-to-drug comparisons without quantitative information on in vivo dose or direct target effect. If such information cannot be included, cross-drug conclusions and discussion should be done very carefully.

      Significance

      The evaluation of systemic molecular and phenotypic consequences of anti-cancer drugs in a vertebrate model system represents a relevant advancement. Although drug effects are likely to differ somewhat between embryonic and larval zebrafish and human cancer patients, the authors' comparison of obtained zebrafish data with human data supports translatability of the presented phosphoproteomics data. Also, the presented data pose a relevant advancement facilitating the informed use of the tested inhibitors as tools in basic science.

      Expertise: Molecular biology, signaling, zebrafish. Limited expertise in omics data analysis and pharmacology.

      PeerReviewed
    4. EMBOpress 05 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      In this study, Vaparanta and co-workers used zebrafish embryos as model to analyze the impact of ErbB tyrosine kinase inhibitors on signaling pathways at the whole organism level. Experimentally, zebrafish embryos were exposed for 1 hour to a single dose of 3 different ErbB tyrosine kinase inhibitors and the global phosphoproteome of the embryos was analyzed by MS/MS. The authors show that the 3 inhibitors differentially modulate the activity of PI3K/Akt, p38 MAPK, Notch, Hippo-YAP/TAZ and β-catenin signaling pathways, associated with different neurological and myocardial phenotypic changes. Using small molecule inhibitors of selective signaling pathways, they show that perturbation of different signaling pathways may induce similar phenotypes in zebrafish embryos.

      Specific comments:

      1. The observation that exposure of zebrafish embryos to lapatinib, gefitinib and AG1478 leads to different global phosphoproteomic changes and to differential modulation of cellular signaling pathways was predictable and supported by an abundant literature. These 3 inhibitors differentially inhibit ErbB homo- and heterodimers and hit many other kinases. This point should be discussed in the paper.
      2. AG1478 is a first-generation tyrphostin while gefitinib and lapatinib are FDA-approved drugs. These compounds not only have different selectivity profiles, but also different pharmacological properties. Do the authors have any information about the permeability, distribution or concentration of the compounds in zebrafish embryos? Otherwise, how can they compare their effects?
      3. One major limitation of this study is that phosphoproteomic analysis was performed at a single time point and with a single dose of inhibitor, which compromises the interpretation of the findings. How was the dose of each inhibitor selected?
      4. One approach for better exploiting the data would be to correlate changes in phosphopeptides with the kinome selectivity of the inhibitors.
      5. In the same vein, the signaling inhibitors used in Fig. 4 to dissect the phenotypic impact of distinct signaling pathways are non-selective, precluding any rigorous interpretation of the data. This confounding factor should at least be discussed in the manuscript. Again, the choice of the different doses of inhibitors is not justified.
      6. The effect of inhibitors on the motility of embryos appears variable. For example, lapatinib markedly decreases motility in Fig. 4E but has no effect in Fig. 4F. Any explanation?
      7. The conclusion that ErbB inhibitors induce similar phenotypes by perturbing different signaling pathways is not justified.

      I have a few suggestions which could enhance the study's contribution to the field-

      1. The rationale for this study should be elaborated further. What new information is expected to emerge from these studies, independently of the conceptual and technical limitations outlined above?
      2. The advantage of studying the whole organism instead of selected tissues is questionable. Analyzing a mixture of organs may mask subtle and physiologically relevant alterations of signaling pathways in specific tissues.
      3. Can the authors correlate neurological and myocardial phenotypes extrapolated from their study with pharmacological effects observed in mice or humans treated with these compounds?

      Significance

      The authors show that the 3 inhibitors differentially modulate the activity of PI3K/Akt, p38 MAPK, Notch, Hippo-YAP/TAZ and β-catenin signaling pathways, associated with different neurological and myocardial phenotypic changes. Using small molecule inhibitors of selective signaling pathways, they show that perturbation of different signaling pathways may induce similar phenotypes in zebrafish embryos.

      PeerReviewed
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    Polarised subcellular activation of ROPs by specific ROPGEFs drives pollen germination in Arabidopsis thaliana
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    1. EMBOpress 05 Jul 2024

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      Reply to the reviewers

      Response to Reviewer #1:

      We agree with Reviewer 1 that a function of ROPGEFs in this process was expected to some degree. However, we want to point out that this manuscript focuses on the requirement of ROPGEFs and especially the spatio-temporal description of ROP signalling polarisation and activation during pollen germination. Moreover, different to the downstream ROPs, we show ROPGEFs do not act strictly redundant, confirming results from root hair initiation and providing additional evidence that multiple signalling pathways are required for pollen germination and that ROPGEFs might be essential for bringing specificity to these signals.

      Major comments:

      1. Only one GEF11 mutant line, gef11-t1, was analyzed for germination ratio. It is presumptuous to conclude that GEF11 has no function in the pollen germination of Arabidopsis thaliana (line 241- line 242).

      After the initial negative results, we did not focus on GEF11 further. Thus, we fully agree that it is presumptuous to make such strong statements about the role of GEF11 during pollen germination. We generated additional gef11 mutant alleles for this revision plan using CRISPR/Cas9 as no other suitable lines were available. Moreover, we now have additional higher-order mutants available to demonstrate the function of GEF11 during pollen germination. These additional lines were generated and confirmed and are growing right now. Thus, we will be able to implement new results addressing this point timely, allowing us to make a more founded statement about the function of GEF11 (see Response to Reviewer #2).

      Minor comments:

      1. In Figure 2A, pollen germination ratio was not provided for the single mutants gef8-c△3 and gef9-c△

      This is due to the generation process of the CRISPR/Cas9 alleles. These alleles were generated by a construct mutating both genes simultaneously; thus, these mutants are unavailable as single mutant lines. Instead of separating these alleles by outcrossing, we included additional single mutant alleles for both GEFs with a similar deletion. As all these CRISPR/Cas9 mutants have a complete deletion of the GEF-ORF, we are sure about the loss of the according GEF function. Additional alleles account for possible unspecific effects.

      In Figure 3D, the subcellular localization of GEF12GEF8C is fuzzy. Better imaging is needed.

      We agree that the quality of these images is not ideal due to this specific line having less fluorescent signal. We screened for more lines of this construct and already performed more experiments. We will provide better images for this genotype.

      In Figure 3E, it is intriguing that both GEF8-S518A and GEF8-S518D are not associated with the PM in germinating pollen grains. Does it mean that phosphorylation at S518 is not relevant to polar distribution of GEF8?

      We also find this very intriguing as we did not expect this result. However, we interpret it slightly differently in the way that the S518 site is relevant for GEF polarisation, which might be conferred by RLK interaction. We think both mutant forms alter this potential association with RLKs, thus losing polarisation. We will include more imaging experiments of these constructs and additional lines to strengthen our results. Moreover, we generated lines to study these lines' functionality and complementation capacity, which will be included in a revised manuscript.

      T-DNA insertion lines, gef11-t1 and gef12-t1, need to be verified by PCRs in Figure S3D.

      Thanks for pointing this out. This control should be provided, and we will include the verification in the supplement.

      Response to Reviewer #2:

      Like Reviewer #2, we are also very intrigued by the biphasic accumulation of GEFs, as this is an entirely novel feature of this process. Like Reviewer #2, we also interpret this as an exploration and establishment phase, which could help us to understand how the pollen germination site is decided in species without aperture-dependent pollen germination.

      Major comments:

      1. In line 241, the authors conclude that GEF11 has no function in pollen germination. However, it is likely that GEF11 also plays a redundant role as GEF12 does. I recommend the authors check the phenotypes of gef11,gef12 double mutant and gef8,gef9,gef11 triple mutant to confirm that GEF11 has indeed no function. Otherwise, this conclusion should be better rephrased.

      This point is well justified and similar to the comment of Reviewer #1. As stated before, we had to generate additional lines for this. We will analyse an additional gef11 allele, gef8/gef11 and gef9/11 double mutants, and gef9/11/12 triple mutants to address the function of GEF11 in more detail. The conclusions of the original manuscript will, of course, be adjusted according to the new results.

      Although GEF12 is in the cytosol, the strong pollen germination defects in gef8,gef9,gef12 triple mutants do indicate a critical role of GEF12. Is it possible that GEFs could function in the cytosol? The authors can test this possibility by examining the rescuing ability of several constructs that express, for example, GEF12, GEF12(+GEF8C), GEF8(SA), or GEF8(SD) in gef8. The authors may not perform all of these rescue experiments, but some of the mentioned lines are already in hands. They could readily check the phenotypes.

      We thank the Reviewer for this great point. This information is crucial to discriminate the function of the individual GEFs. We have generated new lines expressing some of the mentioned constructs in the gef8 background to address this. We now have lines that complement gef8 with GEF12, GEF12GEF8C, GEF8S518A, GEF8S518D, and GEF8ΔC. We are currently performing experiments which determine the functionality of these constructs, which will allow us to make more conclusive statements about the function of GEFs in the cytosol and how important the PRONE domain alone, or the membrane attachment of GEFs, is for their function.

      The authors conclude that the C-terminus of GEF8 and GEF9 is necessary and sufficient for membrane localization because GEF8/9C can target GEF12 PRONE domain to the membrane. It is intriguing whether the C-terminus alone could confer membrane targeting ability. Currently, it is not fully understood how GEFs localize to the membrane. Examining the localization of GEF8/9C itself would help clarify this and improve our understanding of GEF regulation. Alternatively, the authors may discuss evidence that supports or disagrees with this possibility.

      This is a good suggestion by the reviewer and indeed intriguing if the C-Terminus alone could confer membrane attachment. Meanwhile, we obtained plants expressing such constructs, showing that the C-terminus alone is insufficient for membrane attachment. This is not surprising, as these domains are largely disordered, and we suspect that the context of an adjacent PRONE domain is required to carry out this function. We will include our new results in the revised manuscript.

      Minor comments:

      1. The N- and C-terminus of GEF8 are predicted to inhibit complex formation. How is the prediction performed? Do the authors use monomer prediction or multimer prediction? Alphafold2 has a low accuracy in predicting non-conserved regions. How confident are the predicted inhibitory contacts?

      We used multimer-prediction of Alphafold2 for the shown structures. However, we fully agree that the predicted structures of Alphafold have low accuracy in that regard, especially for disordered domains like this. We will provide confidence models and predicted aligned error (PAE) plots for this structure. Additionally, we will put our conclusions in a better perspective of these structure confidences and tone down our interpretations of this section.

      Localization of ROPs and calcium reporter in Figure 4 appears to be variable. It would help clarify the specific effects on each reporter if the authors present these data more quantitatively.

      We agree with the reviewer that some of the observations are variable. We will provide the data more quantitatively, including overviews of which percentage we observed the described phenomena and a more quantitative analysis of the strength and timing of signal accumulation (see also Response to Reviewer #3).

      Response to Reviewer #3:

      Major points:

      1. One of my major points is that the manuscript is now mainly based on the observations of individual pollen grains. These are then subjected to well-performed image analysis approaches but still represent somewhat anecdotal evidence (Fig 1A, B, Fig 3C-E, etc). The analysis and (numerical) presentation of a more robust data sample (which I presume the authors have acquired) would strengthen the ms considerably. This goes beyond the Figs - e.g. in l. 164-165 authors state rather vaguely, "we observed that mCit-GEF8 and mCit-GEF9 accumulated at a defined region in the cell periphery, which strongly correlated with the future germination site." Here, I would appreciate the data showing the actual correlation, if every germinated pollen grain displays GEF8/9 accumulation, whether there is a population of pollen grains showing the GEF8/9 transient but not germinating, etc...

      We very much appreciate the reviewer's comment, as this version of the manuscript indeed seems like we made our conclusions based on observations made from individual pollen. However, this is not the case. As the reviewer suspected, more data is available but not included in the manuscript. We have multiple observations for each of the shown constructs and only show a representative one. Furthermore, we imaged more pollen germination events of lines that showed variability and included additional lines for some constructs. We will provide a more quantitative analysis of the results to better represent the variability of the individual constructs, and we will adjust the manuscript accordingly (see comment 2).

      Where the authors analyse multiple cells, we are still missing some info - e.g. it is not stated what the error bars in Fig 1C, D represents (SD, SEM, CI?), size of the sample, etc. In any case, it is evident that there is quite substantial variability in the data, which is understandable. Maybe the authors can plot the individual profile lines along the average? Plus, GEF9 seem to have the maximum pre-germination localisation at -5 min rather than -9 min.

      We agree with the Reviewer that information is missing or not obviously stated. We will correct this for the revised manuscript. Moreover, we agree that the suggested way of showing the data would provide more information and allow a better representation of the results and their variability. This can be seen in the reviewer's interpretation of the results of GEF9. In this case, we see some variability in the timing of GEF9 accumulation, leading to the peak maximum shift. In a revised manuscript, we will, as suggested, show the data as individual lines, providing a better representation of the data. Moreover, we will include such representations for other used constructs to provide a general, more quantitative data analysis (see comment 1).

      I know it is very challenging, but the ms would be much stronger with the in vivo imaging of pollen germination on stigmatic papillae (i) GEF8/9 in wt, (ii) gef8/9 double mutant. This would bring crucial data about the role of the GEF polar domain and its functional relation to pollination.

      This would indeed be great to see. We put an effort into establishing such in vivo imaging experiments with our fluorescent markers. However, we cannot image these events in an in vivo setup (at least with our resources). This has two reasons: 1. The events are very fast and limited to a small region at the pollen-papilla contact side, which we have issues resolving optically and timely. 2. The used marker lines only have a low fluorescent level due to the native promoter, and stronger expression would lead to overexpression artefacts. In vitro, it is difficult to see the observed signal accumulation. In the in vivo situation, we are facing additional diffraction of the papilla cells, which would make the observation of GEF accumulation impossible with our microscopes.

      The phylogeny presented in Fig S1 is only rudimental and not very interesting. Given the author's results, I would love to see if GEF8/9 orthologs also exist in species with defined pollen apertures (where establishing a dynamic site makes little sense). The authors touch on this (L409-411), but it would deserve better analysis and discussion.

      We agree with the reviewer that studying GEF function/accumulation in species with aperture-dependent germination would be interesting. However, we can not conclude functional orthologs in other species based on phylogeny. Such phylogenetic analyses were done, for example, by Kim et al. (BMC Plant Biology, 2020, doi: 10.1186/s12870-020-2298-5). The issue is that all Arabidopsis pollen-expressed GEFs form a closed phylogenetic group without allowing the interpretation of which rice homolog is the functional ortholog of the respective Arabidopsis GEF (this is the same for maize). Thus, such phylogenetic analyses are not conclusive, and they would require experimental data to prove orthology. However, we agree that this point can be interpreted and discussed better, and we will include this in the revised manuscript.

      I am not entirely convinced by the authors' interpretation of rather strange S518 mutation data. Could S518A mutation affect overall GEF8 structure/stability?

      We were also suspicious about these results, as they were unexpected (see also Response to Reviewer #1). To confirm these results, we made additional lines for these constructs, double-checked that the constructs were correct and made more observations for both GEF8S18A and GEF8S18D. Additionally, we started investigating the functionality of these constructs and have this data available timely. Preliminary results suggest that the constructs are partial to fully functional compared to the WT GEF8, arguing against these mutations' effect on structure or stability. We will include more data for these constructs in a revised manuscript to allow a more conclusive interpretation of these unexpected observations.

      Although the authors cannot observe the localisation of ROPs in the plasma membrane, they see the apparent accumulation of active ROP marker CRIB4 there - implying that ROPs must localise to the pollen PM at the germination site. This discrepancy should be solved or at least discussed more.

      The reviewer is correct in that we cannot observe ROP accumulation but rather the accumulation of ROP activity (as seen by CRIB4). This is in line with the observation made by Xiang et al. (2023, Plant Physiology, doi: 10.1093/plphys/kiad196), which also cannot find ROP accumulation. We are convinced that ROPs are present at the plasma membrane of the pollen germination site, but no accumulation is observable. We believe this is due to a high mobility of ROPs and that no accumulation is required, as only a few ROPs are sufficient to activate downstream signals. We will discuss these results in more detail in a revised manuscript to better explain the observed discrepancy.

      Given that calcium oscillates very rapidly in pollen and pollen tubes (with frequency ~6-20s), the profound, long-term changes in calcium levels reported by the authors can hardly be referred to as oscillations. The phenomenon observed should again be analysed using a bigger sample.

      We agree that the terminology is not good, as it suggests similarities to the oscillations found in pollen tubes. Thus, we will change the revised manuscript and refer to the changes in Ca2+ levels as “elevations”. Moreover, we will provide a more quantitative analysis and a bigger sample size, as stated in Response to Reviewer #2.

      Minor points:

      1. In Fig 1F, GEF12 also seems to be polarly localised to the future site.

      The chosen sample is not ideal, as it looks like GEF12 would also slightly accumulate. However, as seen in the quantification of this cell, GEF12 does not significantly accumulate at the pollen germination site, and we never observed any accumulation of GEF12 that is comparable to GEF8 or GEF9. We will include another sample of this colocalisation in the revised manuscript to avoid misinterpretation of the data.

      It is difficult to make any assumptions based on the AlphaFold2 predictions without showing their confidence assessments (e.g., PAE plots). The authors state this themselves in the discussion (L. 447-449).

      As the Response to Reviewer #2 stated, we will include structures with confidence values and PAE plots in the supplement. We additionally tone down our interpretation of these structure predictions to make clear that these structures should be interpreted carefully.

      On one hand the authors repeatedly state that pollen GEFs do act in a redundant manner (and provide some evidence for it), on the other hand the absence of an in vivo phenotype for single and double knockout lines and only mild phenotype for a triple ko line does suggest a level of redundancy. This should be rephrased.

      We agree that this is not clearly phrased. In a revised version, we will change the manuscript to indicate which type and level of redundancy are described. We will discriminate between genetic redundancy, as seen in the mild in vivo effects, and non-redundant molecular function, as observed by protein localisation.

      PeerReviewed
    2. EMBOpress 05 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      This manuscript investigates the role of PRONE ROP GEFS in germinating Arabidopsis pollen. Given that the molecular mechanisms underlying cellular polarisation in pollen germinating pollen grains are still largely unknown (as opposed to the tip growth of elongating pollen tubes), this manuscript deals with an important topic. Moreover, it builds on the excellent previous research from the lead author, which uncovered ROP GEFs as principal polarisation players during root hair initiation. Here, the authors found that out of five pollen-expressed GEFS, two (GEF8 and 9) mark a future germination site with remarkable spatiotemporal dynamics. Using the genetic tools, GEF8 and 9 were shown to be important for pollen germination in vitro and participate in germination in vivo. Generally, this is an exciting topic, and I quite enjoyed reading the manuscript. However, there are several aspects of the work, which - when addressed - would significantly improve the overall message presented by the authors.

      Major points

      1. One of my major points is that the manuscript is now mainly based on the observations of individual pollen grains. These are then subjected to well-performed image analysis approaches but still represent somewhat anecdotal evidence (Fig 1A, B, Fig 3C-E, etc). The analysis and (numerical) presentation of a more robust data sample (which I presume the authors have acquired) would strengthen the ms considerably. This goes beyond the Figs - e.g. in l. 164-165 authors state rather vaguely, "we observed that mCit-GEF8 and mCit-GEF9 accumulated at a defined region in the cell periphery, which strongly correlated with the future germination site." Here, I would appreciate the data showing the actual correlation, if every germinated pollen grain displays GEF8/9 accumulation, whether there is a population of pollen grains showing the GEF8/9 transient but not germinating, etc...
      2. Where the authors analyse multiple cells, we are still missing some info - e.g. it is not stated what the error bars in Fig 1C, D represents (SD, SEM, CI?), size of the sample, etc. In any case, it is evident that there is quite substantial variability in the data, which is understandable. Maybe the authors can plot the individual profile lines along the average? Plus, GEF9 seem to have the maximum pre-germination localisation at -5 min rather than -9 min.
      3. I know it is very challenging, but the ms would be much stronger with the in vivo imaging of pollen germination on stigmatic papillae (i) GEF8/9 in wt, (ii) gef8/9 double mutant. This would bring crucial data about the role of the GEF polar domain and its functional relation to pollination.
      4. The phylogeny presented in Fig S1 is only rudimental and not very interesting. Given the author's results, I would love to see if GEF8/9 orthologs also exist in species with defined pollen apertures (where establishing a dynamic site makes little sense). The authors touch on this (L409-411), but it would deserve better analysis and discussion.
      5. I am not entirely convinced by the authors' interpretation of rather strange S518 mutation data. Could S518A mutation affect overall GEF8 structure/stability?
      6. Although the authors cannot observe the localisation of ROPs in the plasma membrane, they see the apparent accumulation of active ROP marker CRIB4 there - implying that ROPs must localise to the pollen PM at the germination site. This discrepancy should be solved or at least discussed more.
      7. Given that calcium oscillates very rapidly in pollen and pollen tubes (with frequency ~6-20s), the profound, long-term changes in calcium levels reported by the authors can hardly be referred to as oscillations. The phenomenon observed should again be analysed using a bigger sample.

      Minor points

      1. In Fig 1F, GEF12 also seems to be polarly localised to the future site.
      2. It is difficult to make any assumptions based on the AlphaFold2 predictions without showing their confidence assessments (e.g., PAE plots). The authors state this themselves in the discussion (L. 447-449).
      3. On one hand the authors repeatedly state that pollen GEFs do act in a redundant manner (and provide some evidence for it), on the other hand the absence of an in vivo phenotype for single and double knockout lines and only mild phenotype for a triple ko line does suggest a level of redundancy. This should be rephrased.

      Significance

      General assessment

      I believe that both strenghts and limitations are evident form the list above. I feel this a study with great potential, which can be improved by textual ammendments and by several additional experiments that do not require the generation of new genetic material.

      Advance

      This ms builds on the results obtained previously by the lead author and does advance the knowledge of the field of plant cell polarity substantially.

      Audience

      The ms is targeted for the basic research audience, particularly for plant scientists.

      Expertise of the reviewer

      Pollen biology, membrane trafficking, phylogenetic analyses, protein biochemistry.

      PeerReviewed
    3. EMBOpress 05 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      In this study, Bouatta et al. report the function of RopGEFs in pollen germination. The authors analyzed all of the five RopGEFs, namely RopGEF8/9/11/12/13, that have been shown to be expressed in mature pollen tubes, and found that only GEF8/9/11/12 are detectable. In addition, GEF8 and GEF9 localize to germination sites, while GEF11 and GEF12 are cytosolic. Through a series of phenotype analyses and live-cell imaging, the authors show that GEF8, GEF9, and GEF12 are required for pollen germination while GEF11 is not. The authors also provide evidence that GEF8 and GEF9 are targeted to the membrane via the C-terminus, where they activate ROPs and calcium signaling.

      Major comments:

      1. In line 241, the authors conclude that GEF11 has no function in pollen germination. However, it is likely that GEF11 also plays a redundant role as GEF12 does. I recommend the authors check the phenotypes of gef11,gef12 double mutant and gef8,gef9,gef11 triple mutant to confirm that GEF11 has indeed no function. Otherwise, this conclusion should be better rephrased.
      2. Although GEF12 is in the cytosol, the strong pollen germination defects in gef8,gef9,gef12 triple mutants do indicate a critical role of GEF12. Is it possible that GEFs could function in the cytosol? The authors can test this possibility by examining the rescuing ability of several constructs that express, for example, GEF12, GEF12(+GEF8C), GEF8(SA), or GEF8(SD) in gef8. The authors may not perform all of these rescue experiments, but some of the mentioned lines are already in hands. They could readily check the phenotypes.
      3. The authors conclude that the C-terminus of GEF8 and GEF9 is necessary and sufficient for membrane localization because GEF8/9C can target GEF12 PRONE domain to the membrane. It is intriguing whether the C-terminus alone could confer membrane targeting ability. Currently, it is not fully understood how GEFs localize to the membrane. Examining the localization of GEF8/9C itself would help clarify this and improve our understanding of GEF regulation. Alternatively, the authors may discuss evidence that supports or disagrees with this possibility.

      Minor comments:

      1. The N- and C-terminus of GEF8 are predicted to inhibit complex formation. How is the prediction performed? Do the authors use monomer prediction or multimer prediction? Alphafold2 has a low accuracy in predicting non-conserved regions. How confident are the predicted inhibitory contacts?
      2. Localization of ROPs and calcium reporter in Figure 4 appears to be variable. It would help clarify the specific effects on each reporter if the authors present these data more quantitatively.

      Significance

      Advance:

      ROP GTPases and RopGEFs are critical regulators of cell polarity, but how they initiate polarity remains unclear. This study uses pollen germination as a model to address this question. It systematically analyzed all pollen-specific GEFs and found that GEF8 and GEF9 are critical regulators of pollen germination and polarity initiation. Importantly, GEF8 and GEF9 undergo biphasic accumulation, suggesting polarity is established through a transient exploration phase. This study provides a comprehensive view of the functions of GEFs in polarity initiation, which will be of interest not only to readers who work on pollen germination and growth but also to those who study cell polarity and morphogenesis in general. In my view, the most novel part of this study is that GEFs play overlapping but non-identical roles in polarity establishment and undergo transient accumulation during the polarity initiation process.

      Limitations:

      This study shows that GEFs use the C-terminus for membrane targeting and GEFs can activate ROPs and calcium signaling during pollen germination. These mechanisms could be largely inferred from previous studies in mature pollen tubes or others. Advancements in the regulation of GEF such as how the C-terminus mediates GEF localization, e.g. whether through direct interaction with the PRONE domain in a phosphorylation-dependent manner, would further increase the novelty of this work.

      PeerReviewed
    4. EMBOpress 05 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      In the manuscript, the Denninger group reported the identification of ROPGEF8/9 as the key ROPGEFs for ROP activation during pollen germination, a process of polarity establishment. By examining the subcellular localization of pollen-expressed/enriched GEFs using their own promoter and fluorescence protein fusions, the authors convincingly showed the spatiotemporal distribution of GEF8 and GEF9 during pollen germination. By characterizing pollen germination of gef mutants, the authors demonstrated that GEF8 and GEF9 are critical for the process, with GEF12 playing a redundant role likely as a compensation response. The authors further showed that C-termini of GEF8/9, previously demonstrated as an inhibitory domain for GDP-GTP exchange, was critical for the polar distribution. The C-termini of GEFs interact with PRK. The authors reported that the phosphorylation of GEFs at C-termini was critical for their polar distribution. By examining the dynamic localization of active ROP biosensor CRIBRIC4, the authors demonstrated that GEF8/9 were critical for polar distribution of active ROPs at future germination sites. By introducing a calcium biosensor, the authors showed that calcium gradient, a key downstream process of ROP signaling, was compromised by functional loss of GEF8/9 during pollen germination.

      Major comments

      Only one GEF11 mutant line, gef11-t1, was analyzed for germination ratio. It is presumptuous to conclude that GEF11 has no function in the pollen germination of Arabidopsis thaliana (line 241- line 242).

      Minor comments

      In Figure 2A, pollen germination ratio was not provided for the single mutants gef8-c△3 andgef9-c△2.

      In Figure 3D, the subcellular localization of GEF12GEF8C is fuzzy. Better imaging is needed.

      In Figure 3E, it is intriguing that both GEF8-S518A and GEF8-S518D are not associated with the PM in germinating pollen grains. Does it mean that phosphorylation at S518 is not relevant to polar distribution of GEF8?

      T-DNA insertion lines, gef11-t1 and gef12-t1, need to be verified by PCRs in Figure S3D.

      Significance

      The identification of ROPGEF8/9 as the key ROPGEFs for ROP activation during pollen germination is a step forward in understanding ROP signaling. Useful but not unexpected.

      Pollen germination is a process of polarity establishment, similar to root hair initiation. Compared to pollen tube growth and root hair growth, processes of polarity maintenance, the role of ROP signaling was less clear. Recently, Xiang et al. (2023, Plant Physiol) reported an essential role of ROP1/3/5 and their downstream components BDR8/9 in pollen germination. Consistently with polar ROP activation, Ca2+ and post-Golgi secretion were polar. The current work is one step ahead, showing GEF8/9 as the upstream GEFs for this process, comparable to GEF3/4 during root hair initiation (Denninger et al., 2019, Curr Biol). The identification of the C-terminal phosphorylate site in GEF8/9 is informative. It was reported previously that PRKs interact with the C-termini of GEFs to release their auto-inhibition (Gu et al., 2006, Plant Cell; Zhang and McCormick, et al., 2007, Proc Nat Acad Sci USA, Zhao et al., 2013, J Exp Bot) and PRKs were reported to phosphorylate GEF (Chang et al., 2013, Mol Plant). Thus, results reported in the current work indicate that phosphorylation of GEFs likely by PRKs is a critical step for the establishment of polarity domain for pollen germination. From this perspective, it would be more mechanistically sound to investigate the role of PRKs in spatiotemporal polarization of GEFs during pollen germination.

      Researchers working on cell signaling and cell morphogenesis in plants will be interested.

      My lab works on cell morphogenesis and ROP signaling. This manuscript exactly falls within the expertise of my field.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.01.11.575165v1
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    Deep super-resolution imaging of thick tissue using structured illumination with adaptive optics
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    1. EMBOpress 04 Jul 2024

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      Reply to the reviewers

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      Reply to the Reviewers

      We want to thank the three reviewers for their invaluable and constructive feedback. We respond to each comment individually, describing how we plan to address them in our revised manuscript.

      Reviewer #1

      1. Given the emphasis on super-resolution imaging deep inside a sample, we were surprised to see no mention of other forms of structured illumination that allow super-resolution imaging in samples thicker than a single cell. These include the 'spot-scanning' implementations of SIM that offer better imaging at depth by virtue of pinholes, and include MSIM, iSIM, and rescan confocal technologies. The two-photon / AO implementation of iSIM seems particularly germane, e.g. https://pubmed.ncbi.nlm.nih.gov/28628128/ Please consider citing these works, as they help place the existing work into context.

      Response:

      We want to thank reviewer #1 for the good point. To address this comment, we plan to add to the discussion section a description of these super resolution techniques, together with other SIM methods, explaining how they compare to our approach.

      1. As we're sure the authors appreciate, besides aberrations, a major additional obstacle to 3D SIM in thick tissues is the presence of out-of-focus background. Indeed, this point was mentioned by Gustafsson in his classic 2008 paper on 3D SIM (https://pubmed.ncbi.nlm.nih.gov/18326650/): 'The application area of three-dimensional structured illumination microscopy overlaps with that of confocal microscopy, but the two techniques have different and complementary strengths. Structured illumination microscopy offers higher effective lateral resolution, because it concentrates much of the excitation light at the very highest illumination angles, which are most effective for encoding high-resolution information into the observed data, whereas confocal microscopy spreads out its illumination light more or-less uniformly over all available angles to form a focused beam. For very thick and compactly fluorescent samples, however, confocal microscopy has an advantage in that its pinhole removes out-of focus light physically. Structured illumination microscopy is quite effective at removing out-of-focus light computationally, because it is not subject to the missing-cone problem, but computational removal leaves behind the associated shot noise. Therefore confocal microscopy may be preferable on very thick and dense samples, for which the in-focus information in a conventional microscope image would be overwhelmed by out-of-focus light, whereas structured illumination microscopy may be superior in a regime of thinner or sparser samples.' This point is not mentioned at all in the manuscript, yet we are certain it is at least partially responsible for the residual image artifacts the authors mention. Please discuss the problem of out of focus light on 3D samples, particularly with an eye to the 'spot-scanning' papers mentioned above.

      Response:

      We appreciate this significant obstacle and we want to thank Reviewer #1 for emphasising its importance. To address the comment, we plan to add a discussion of the significance of out-of-focus light to SIM imaging to the introduction, results, and discussion sections of the manuscript.

      1. The authors use a water dipping lens, yet they image into samples that are mounted on coverslips, i.e. they use a dipping lens to image through a coverslip:

      This almost certainly introduces spherical aberration, which the authors seem to observe: see attached pdf for reference

      We find this troubling, as it seems that in the process of building their setup, the authors have made a choice of objective lens that introduces aberrations - that they later correct. At the very least, this point needs to be acknowledged in the manuscript (or please correct us if we're wrong) - as it renders the data in Figs. 3-4 somewhat less compelling than if the authors used an objective lens that allowed correction through a coverglass, e.g. a water dipping lens with a correction collar. In other words, in the process of building their AO setup, the authors have introduced system aberrations that render the comparison with 3D SIM somewhat unfair. Ideally the authors would show a comparison with an objective lens that can image through a glass coverslip.

      Response:

      We want to thank Reviewer #1 for raising this point, which we did not describe clearly enough, leading to confusion. We should have made it clearer that we used a water dipping/immersion objective lens with a correction collar which extends from no coverslip (dipping) up to well beyond a standard #1.5 (170 um thick) coverslip. We adjusted this collar before each image acquisition session, to ensure that the system is optimised for each experiment individually and that the spherical aberrations are minimal before any DM-based correction. We plan to elaborate and emphasise this point in several places in the revised manuscript, including in the figure legends, materials and methods and results sections, to avoid any ambiguity and confusion about the use of the correction collar and this particular water immersion/dipping objective lens.

      1. The authors tend to include numbers for resolution without statistics. This renders the comparisons meaningless in my opinion; ideally every number would have a mean and error bar associated with it. We have included specific examples in the minor comments below.

      Response:

      This is a good point, which we address below, in three minor comments. In summary, to address this comment, we plan to include statistical information in the revised manuscript.

      1. In Fig. 5, after the 'multipoint AO SIM', the SNR in some regions seems to decrease after AO: see attached pdf for reference

      Please comment on this issue.

      Response:

      We want to thank Reviewer #1 for the insightful comment. There are multiple phenomena in effect here, which cause the drop in intensity. The most prominent one is photobleaching, as the AO image stack (right) was acquired after the bypass one (left). To address this comment, we plan to add additional data and to include a brief discussion about this issue and other related points.

      1. Please provide timing costs for the indirect AO methods used in the paper, so the reader understands how this time compares to the time required for taking a 3D SIM stack. In a similar vein, the authors in Lines 213-215, mention a 'disproportionate measurement time' when referring to the time required for AO correction at each plane - providing numbers here would be very useful to a reader, so they can judge for themselves what this means. What is the measurement time, why is it so long, and how does it compare to the time for 3D SIM? It would also be useful to provide a comparison between the time needed for AO correction at each (or two) planes without remote focusing (RF) vs. with RF, so the reader understands the relative temporal contributions of each part of the method. We would suggest, for the data shown in Fig. 5, to report a) the time to acquire the whole stack without AO (3D SIM only); b) the time to acquire the data as shown; c) the time to acquire the AO stack without RF. This would help bolster the case for remote focusing in general; as is we are not sure we buy that this is a capability worth having, at least for the data shown in this paper.

      Response:

      We agree that the timing (and other) costs can be an important consideration, and we want to thank Reviewer #1 for bringing up this good point. To address this issue, we plan to expand our description of the AO methods, also including numbers for the time it takes to perform the different parts. In terms of comparisons, the RF makes no contribution to the timing costs of the aberration correction, a point that we want to make clearer in the results and the methods and materials sections, as the two are independent processes in our approach. Instead, the RF can be compared to standard focusing with a piezo stage, a point which we discuss in the supplementary material. We plan to make this point clearer in the discussion section of the main manuscript, and to emphasise better the advantages of the RF in terms of imaging speed.

      1. Some further discussion on possibly extending the remote focusing range would be helpful. We gather that limitations arose from an older model of the DM being used, due to creep effects. We also gather from the SI that edge effects at the periphery of the DM was also problematic. Are these limitations likely non-issues with modern DMs, and how much range could one reasonably expect to achieve as a result? We are wondering if the 10 um range is a fundamental practical limitation or if in principle it could be extended with commercial DMs.

      Response:

      Regrettably, we were not able to try other DMs on the Deep3DSIM system. However, Jiahe and colleagues show in [1] that similar DM-based remote focusing, even with the same model deformable mirror, can be pushed to 120 um (Strehl ratio >0.8) with a 0.42 NA dry lens (20 mm WD) and close-loop wavefront compensation operation. While this is not directly translatable to high NA 3D-SIM imaging, we expect that with a stable version of the same DM the useable RF range could be easily increased twice or even more. We thank Reviewer #1 for the good comment, which we plan to address by revising the text to make the limitations clearer and by citing relevant studies.

      [1] Cui, J., Turcotte, R., Emptage, N. J., & Booth, M. J. (2021). Extended range and aberration-free autofocusing via remote focusing and sequence-dependent learning. Optics Express, 29(22), 36660-36674.

      Minor comments:

      1. The paper mentions Ephys multiple times, even putting micromanipulators into Fig. 1 - although it is not actually used in this paper. If including in Figure 1, please make it clear that these additional components are aspirational and not actually used in the paper.

      Response:

      Although not shown in the context of this paper, the Deep3DSIM system was built specifically around experiments such as electrophysiology, which can benefit from the upright configuration and the water-dipping-capable objective lens. To address this comment, we plan to clarify the role of the micromanipulators and to update Figure 1 accordingly.

      1. The abstract mentions '3D SIM microscopes', 'microscopes' redundant as the 'm' in 'SIM' stands for 'microscope'.

      Response:

      We accept that “3D SIM microscopes” sounds repetitious and we plan to revise the wording of the abstract to “3D SIM system”.

      1. 'fast optical sectioning', line 42, how can optical sectioning be 'fast'? Do they mean rapid imaging with optical sectinong?

      Response:

      Yes, we meant rapid imaging with optical sectioning. We plan to change the wording to make it less ambiguous.

      1. line 59, 'effective imaging depth may be increased to some extent using silicone immersion objectives', what about water immersion objectives? We would guess these could also be used.

      Response:

      Yes, water immersion objective lenses also fall in the same category and we plan to rephrase this part to state it explicitly.

      1. line 65 - evidence for 'water-dipping objectives are more sensitive to aberrations' ? Please provide citation or remove. They are certainly more prone to aberrations if used with a coverslip as done here.

      Response:

      The refractive index (RI) of cells and tissues [1] is closer to the RI of silicone oil (~1.4) than it is to water (~1.33). Therefore, because of the larger difference in RI, imaging with a water-dipping objective lens is more prone to aberrations from RI mismatch. We plan to rephrase this argument to make it clearer.

      [1] Jacques, S. L. (2013). Optical properties of biological tissues: a review. Physics in Medicine & Biology, 58(11), R37.

      1. 'fast z stacks' is mentioned in line 103. How fast is fast?

      Response:

      The speed would depend on the way Z-stacks are being acquired. For example, acquisitions with two channels would be at least twice as fast, because of the ability to do simultaneous imaging on the Deep3DSIM system. Likewise, experiments that can benefit from the remote focusing can be several times faster than using a Z piezo stage, and this point is discussed in the supplementary material (section “Step response”). Finally, thanks to the electronic design of the imaging system, orchestrating everything via digital logic (e.g. TTL) signals, and thanks to the elaborate control software, we can ensure that all image acquisitions are carried out as quickly as possible, operating near the limit of the underlying hardware devices. We plan to explain these points in a clear way in the discussion section, and we plan to provide more numbers in the supplementary material.

      1. line 116 'we imaged 100 nm diameter green fluorescent beads'. Deposited on glass? Given that this paper is about imaging deep this detail seems worth specifying in the main text.

      Response:

      Yes, in this case the beads were deposited on glass. We plan to include this detail in the description of the experiment.

      1. lines 127-130, when describing changes in the bead shape with numbers for the FWHM, please provide statistics - quoting single numbers for comparison is almost useless and we cannot conclude that there is a meaningful improvement without statistics.

      Response:

      We agree with this comment. We plan to include statistical information for all the FWHM numbers.

      1. In the same vein, how can we understand that remote focus actually improves the axial FWHM of the widefield bead? Is this result repeatable, or it just noise?

      Response:

      The lower axial FWHM with remote focusing is likely caused by data fitting or quantification error. Together with the inclusion of statistical information, we plan to review all the resolution values and to ensure that they are accurate and sensible.

      1. line 155, 'Because of the high spatial information...' -> 'Because of the high resolution spatial information...'

      Response:

      We agree with this comment. To address it, we plan to rephase this part.

      1. When quoting estimated resolution #s from microtubules (lines 158-163) similarly please provide statistics as for beads.

      Response:

      We agree with this comment. To address it, we plan to include statistical information for the resolution values from microtubules.

      1. It seems worth mentioning the mechanism of AO correction (i.e. indirect sensing) in the main body of the text, not just the methods.

      Response:

      We agree with this comment. To address it, we plan to describe briefly the aberration correction method in the introduction or the results section.

      1. How long do the AO corrections take for the datasets in the paper?

      Response:

      The duration of the aberration correction routines is directly proportional to the number of Zernike modes, the number of iterations, the exposure time of the camera, and other parameters. In our experiments, it was usually in the order of tens of seconds. To address this comment, and in line with the sixth major comment, we plan to include more details about the timing of the different parts of the AO methods.

      1. Were the datasets in Fig. 2-4 acquired with remote focusing, or in conventional z stack mode? Please clarify this point in the main text and the figure captions.

      Response:

      The only data acquired with RF in Fig. 2-4 are one bead in Fig. 2A and another bead in Fig. 2B, both labelled accordingly. We plan to make it clearer in the text that the rest of Figure 2, as well as Figures 3 and 4, were acquired with the piezo Z stage.

      1. It would be helpful when showing z projections in Figs. 3-5 to indicate the direction of increasing depth (we assume this is 'down' due to the upright setup, but this would be good to clarify)

      Response:

      The direction is indicated by the arrows labelled with ‘Z’. We plan to clarify this in the figure captions.

      1. line 174, 'showed significant improvements in both intensity and contrast after reconstruction' - we see the improvements in contrast and resolution, it is harder to appreciate improvements in intensity. Perhaps if the authors showed some line profiles or otherwise quantified intensity this would be easier to appreciate.

      Response:

      We agree with this comment. To address it, we plan to change Figure 3 to illustrate the improvement in intensity, likely with line profiles, as suggested by the reviewer.

      1. line 195 'reduced artefacts' due to AO. We would agree with this statement - the benefit from AO is obvious, and yet there are still artefacts. If the authors could clarify what these (residual) artefacts are, and their cause (out of focus light, uncorrected residual aberrations, etc) this would be helpful for a reader that is not used to looking at 3D SIM images.

      Response:

      We agree with this comment. To address it, we plan to explain this point in both the results and the discussion sections.

      1. Line 197, 'expected overall structure', please clarify what is expected about the structure and why.

      Response:

      We agree with this comment. To address it, we plan to describe better the Canoe (Cno) protein, including an explanation of its expression pattern, which is the honeycomb-like structure observed in the images.

      1. Line 199, what is a 'pseudo structure'?

      Response:

      We used this expression to refer to unclear (e.g. dim, fuzzy) structures. We plan to improve the wording of that part of the results section.

      1. Fig. 4B, 'a resolution of ~200 nm is retained at depth', please clarify how this estimate was obtained, ideally with statistics.

      Response:

      We agree with this comment. To address it, we plan to clarify this point in the results section, including statistical information.

      1. Fig. 4D, please comment on the unphysical negative valued intensities in Fig. 4D, ideally explaining their presence in the caption. It would also be helpful to highlight where in the figure these plots arise, so the reader can visually follow along.

      Response:

      We agree with this comment. To address it, we plan to explain how negative intensities arise in SIM reconstruction, often a result of spherical aberrations, and we plan to indicate where the line profile in Figure 4D comes from.

      1. Line 245, 'rapid mitosis'. What does rapid mean, i.e. please provide the expected timescale for mitosis.

      Response:

      The mitotic cycles at this developmental stage are short, e.g. 5 minutes per mitosis, compared to those of somatic cells where it takes several hours. We plan to include this information in the main text.

      1. For the data in Fig. 6, was remote refocusing necessary?

      Response:

      Yes, it was necessary because the point of Figure 6 is to demonstrate the combination of remote focusing and SIM super-resolution in live samples. Drosophila embryos are a very good sample for this kind of demonstration, because they are often subject to micromanipulation (e.g. injection and electrophysiology), and these are the kind of experiments that can benefit greatly from the optical axial scanning of the remote focusing, where the sample can remain stationary. However, there is nothing preventing the imaging of this kind of sample with a piezo Z stage or with some other kind of mechanical actuator. In this sense, the remote focusing is not strictly necessary but still much more convenient in some applications. We plan to make this point clearer in the discussion section.

      1. What is the evidence for 'reduced residual aberrations', was a comparative stack taken without AO? In general we feel that the results shown in Fig. 6 would be stronger if there were comparative results shown without AO (or remote focusing).

      Response:

      We agree with this comment. In general, it is difficult to make direct comparisons (e.g. as in Figures 3-5) with live samples, because of the dynamic character of the samples, where it is often impossible to capture the same scene more than once. To address this comment, we plan to revise the wording of the relevant part of the results section, to ensure that the data in Figure 6 is properly described.

      1. Line 350, 'incorporation of denoising algorithms' - citations would be helpful here.

      Response:

      We agree with this comment. To address it, we plan to add references to the relevant statement, showing examples of denoising in 3D-SIM imaging and reconstruction.

      1. Line 411, 'All three were further developed and improved' - vague, how so?

      Response:

      A detailed breakdown of all the changes is available on the respective software repositories. We also plan to add a summary in the supplementary material.

      1. Sensorless AO description; how many Zernike modes were corrected?

      Response:

      We usually corrected 8 modes: Z5 to Z11 and Z22, using Noll indexing. We plan to add a table to the supplementary material, describing which modes were corrected for each dataset.

      1. Multi-position aberration correction. Was the assumption of linearity in the Zernike correction verified or met? Why is this a reasonable assumption?

      Response:

      By their very definition, some aberrations, such as defocus and spherical aberrations, change linearly with depth. Others are also proportional to the imaging depth, and first-order approximation (i.e. straight line) is the most sensible for just two correction points, as is the case with the dataset presented in Figure 5. We plan to explain this point better in the results section.

      1. Fig. S1B is not useful; if the idea is to give a visual impression of the setup, we would recommend providing more photos with approximate distances indicated so that the reader has a sense of the scale of the setup. As is - it looks like a photograph of some generic optical setup.

      Response:

      We agree with this comment. To address it, we plan on including more photos in the supplementary material, to give a better sense of the scale.

      1. SI pattern generation - 'the maximum achievable reconstruction resolution was only slightly reduced to about 95% of the theoretical maximum'. We don't understand this sentence, as the resolution obtained on the 100 nm beads is considerably worse than 95% of the theoretical maximum. Or do the authors mean 95% of the theoretical maximum given their pitch size of 317 nm for green and 367 nm for red?

      Response:

      Limiting the stripe width to about 90% of what is achievable leads to a reduction of the theoretical maximum resolution to 95% of what it could be. We plan to rephrase this part to make it clearer.

      1. SI Deformable mirror calibration 'spanning the range [0.1, 0.9]' - what are the units here?

      Response:

      These are normalised control amplitudes, i.e. [10%, 90%], which means that they are unitless. We plan to explain this in a clearer way.

      1. What are the units in Fig. S5C, S5D?

      Response:

      Errors are in radians, defined by the calibration interferometric wavefront sensor. We plan on updating the figure to include this information.

      1. It would be useful to define 'warmup' also in the caption of SI Fig. S6A.

      Response:

      We agree with this comment. We plan to change the caption of Figure S6A to clarify this point.

      1. SI Remote Focusing, 'four offsets, {-5 mm, -2.5 mm, 2.5 mm, 5 mm}...' are the units mm or um?

      Response:

      The units are supposed to be um (micrometres). We plan on fixing this error.

      1. '...whereas that of the 10 beads was...' here, do the authors mean the position of the beads derived from the movement of the piezo stage, as opposed to the remote focusing?

      Response:

      This is the average standard deviation between the 10 different beads, all from volumes acquired with remote focusing. We plan on rephrasing this part to make it clearer.

      1. The authors refer to the 'results from Chapter 3.2'. What are they talking about? Do they mean a supplementary figure, or earlier supplementary results? In general, we found the discussion in this paragraph difficult to follow.

      Response:

      This is a remnant from an earlier version of the document which used numbered sectioning. Chapter 3.2 is referring to the section titled “Characterisation of drift and temperature effects”. We plan on revising this paragraph to make it clearer.

      1. Supplementary Fig. 9 seems to be not referred to anywhere in the text.

      Response:

      We agree with this comment. To address this issue, we plan on referring to this figure in the main text.

      1. Since the paper emphasizes 3D SIM, OTFs along the axial direction would also be useful to show, in addition to the lateral OTFs shown in Fig. 2D.

      Response:

      We agree with this comment. To address it, we plan on adding orthogonal views of the OTFs to the supplementary material.

      1. When the sample is moved by the piezo, the axial phase of the 3D-SIM illumination pattern is stable as the sample is scanned through the illumination pattern. When remote focusing is performed, the sample is always stable so the axial phase of the 3D-SIM illumination pattern is presumably changing with remote focusing. Can the authors clarify if the 3D SIM illumination pattern is scanned when remote focusing is applied, or is the intensity pattern stable in z?

      Response:

      Yes, the illumination pattern is scanned. We plan on clarifying how the structured illumination works in the case of remote focusing in the supplementary material.

      1. In Supplementary Fig. 9, primary spherical is referred to twice, both at index 11 and 22. The latter is presumably secondary spherical?

      Response:

      Yes, it is supposed to be secondary spherical aberrations. We plan on fixing this error.

      1. we do not understand the x axis label, in Fig. S4D, is it really [0, 50, 50, 50] as written?

      Response:

      The labels of the x-axis are not well formatted. There are three range of [0, 50] where only the first zero is properly displayed. We will revise this part of the figure to make it clear.

      Reviewer #2

      1. The authors have provided an incomplete description of the structured illumination microscopy (SIM) reconstruction process. It is unclear whether the approach is based on 2D interference SIM configurations or 3D interference patterns. Furthermore, the specific algorithm utilized for image reconstruction has not been elucidated. Elaborating on these aspects is crucial as they significantly influence the interpretation of the resulting data.

      Response:

      We want to thank Reviewer #2 for bringing our attention to the incomplete description of the reconstruction process. Our approach was based on 3D interference patterns and it was carried out using the Gustafsson’s reconstruction techniques as implemented by the softWoRx software, designed for the OMX 3D-SIM microscopes. To address this comment, we plan to revise the manuscript and to include more details about the 3D-SIM reconstruction techniques in the methods and materials section.

      1. The authors have stated that sample-induced aberrations caused by RI inhomogeneities within the specimen is another major reason for causing artifacts generation. Literature has demonstrated that RI inhomogeneities can lead to non-local distortions in the grid pattern, which suggests that applying uniform reconstruction parameters across the entire image may not be viable. Traditional artifact remediation using the classical Wiener method is likely insufficient under these conditions (PMID: 33896197). The existing adaptive optics (AO) approach, which employs a deformable mirror (DM) alongside an sCMOS camera, is inadequate for tackling the issue at hand. Actually the assertion made in the paper that "aberrations change approximately linearly with depth" is seemingly contradicted by simulations referenced in the cited literature (PMID: 33896197). Consequently, it appears that the current methodology might only achieve a partial mitigation of the problems associated with spherical aberration resulting from RI mismatches. It is advisable, therefore, that the authors explicitly acknowledge this limitation in their manuscript to prevent any potential misinterpretation by readers.

      Response:

      We are thankful for the thoughtful comment by Reviewer #2. The focus of our work was not the use of advanced 3D-SIM reconstruction and aberration correction methods; instead, we used standard ones which are not able to deal perfectly with anisoplanitism, i.e. when the aberrations vary laterally. As such, our approach provides an average reconstruction and correction across the field of view. In our particular setup this anisoplanitism was not very significant, but we agree that it could be an issue for optical systems with very wide field of view. To address this good point, we plan on clarifying these potential issues in the results and the discussion sections.

      1. In Figure 2, the use of COS-7 cells, which are known for their relatively thin axial dimension, for the experiments raises an eyebrow. Notably, there are ample instances in existing research where both 2D-SIM and 3D-SIM, without the integration of adaptive optics, have yielded high-quality super-resolution images of structures such as tubulin and the endoplasmic reticulum. In addition, the authors did not present a direct comparison between BP-SIM and AO-SIM here. Without this comparative analysis, it remains ambiguous whether the enhancements in resolution and contrast and the reduction in artifacts can genuinely be attributed to the mitigation of spherical aberration. To clarify this, it would be beneficial for the authors to include side-by-side comparisons of these modalities to demonstrate the specific improvements attributed to AO-SIM.

      Response:

      We are grateful to Reviewer #2 for this helpful comment. In Figure 2, we demonstrate the performance we get out of 3D-SIM in terms of optical resolution. We do not make any statements about the impact of the aberration correction on image quality. Nevertheless, to address this comment, we plan to revise the figure to explain more clearly and explicitly this point.

      1. In Figures 3 and 4, the authors have illustrated the enhancements achieved through the application of AO. However, there is a discernible presence of hammer-stroke and honeycomb artifacts in pre-AO imaged data, which seem to originate from the amplification of the incorrectly moved out-of-focal background in the frequency domain. Various strategies have been previously suggested to address these specific artifacts, encompassing methods like subtracting background noise in the raw images or employing selective frequency spectrum attenuation techniques, such as Notch filtering and High-Fidelity SIM. To facilitate a more comprehensive understanding, I would recommend that the authors incorporate into their study a comparison that includes BP-SIM data that has undergone either background subtraction or frequency spectrum attenuation. This added data would enable a more complete evaluation and comparison regarding the merits and impact of their AO approach.

      Response:

      We thank the reviewer for this excellent suggestion and we agree that a pre-processing step, such as background subtraction or frequency spectrum attenuation, can help with the reduction of artefacts. To address this comment, we will re-analyse our data and apply these techniques, and we will add the data to the manuscript, with an appropriate revision to the text.

      Reviewer #3

      1. There is an overall reference in the manuscript of the novelty possible range of applications of using an upright microscope configuration. Examples mentioned are tissue-based imaging, access to whole-mount specimens for manipulation and electrophysiology. However, authors fail to present any such applications. There is not a single example presented which could not have been obtained with an inverted microscope. Could the authors provide an example where a water-dipping is used. Expanded samples could be one case, since the thickness of the gel makes it difficult to image with an inverted microscope. Another possible example would be to label the extracellular space and do shadow imaging of the tissue (SUSHI PMID: 29474910). ExM might be simpler to do as part of revising the manuscript than SUSHI.

      Response:

      We are thankful to Reviewer #3 for these interesting comments. To address this comment, we will emphasise more clearly that Figure 6 of our manuscript shows a sample that is often part of live imaging experiments that require microinjection and even electrophysiology. Our aim was to show the proof of principle and the potential of such experiments, rather than to carry out real and complex experiments using electrophysiology or microinjection. Regarding providing an example where water-dipping is used, this is already present in the same Figure 6, which we will describe more explicitly and fully in the revised manuscript. The reviewer’s comments on expansion microscopy and SUSHI are interesting, but the primary purpose of our microscope system is to facilitate super resolution live cell imaging experiments. Nevertheless, to address this comment, we will add an explanation of the relevance of our approach to improving deep super resolution imaging of expanded specimens.

      1. On the main text it is described a 5-fold volumetric resolution, which is confusing since authors only mention lateral and axial resolutions. Their measurements correspond to a ~1.6-fold lateral improvement and ~1.7-fold axial improvement. These are however not the 95% of the achievable resolution theoretical maximum, as stated in p7 SI (2 fold increase of 282nm), but only the 80-85%. This point should be rephrased in the manuscript.

      Response:

      We want to thank Reviewer #3 for bringing up this important point. To address it, we plan to make changes to the text, both in the main manuscript and in the supplementary material, to make it clearer what are the resolution improvement that we achieve and what are the limitations to our approach.

      1. [OPTIONAL] p4 and related to figure 2, it would be important to report also measurements of beads with SIM but without AO, just as done for WF. Is there an improvement of using AO on SIM? This is reported for the fixed cells but not for the beads.

      Response:

      We found no significant improvement in resolution when AO was applied to SIM. To address this comment, we plan to add the extra data to Figure 2, demonstrating this point.

      1. Figure 2, it is odd the comparison between WF+/- AO and SIM +/- AO are done using different cellular structures. Since wavelengths used are not the same it is difficult to interpret if there is any improvement of using AO on SIM compared to SIM without AO. Same questions arise as above, Is there an improvement of using AO on SIM?

      Response:

      We agree that the data in Figure 2C and 2D is presented in unusual way. Our intention was not to make a comparison between bypass and AO, but instead to characterise the super-resolution capabilities of the system. We use different channels because doing -/+ AO consecutively leads to noticeable intensity drop due to photobleaching. We are grateful to Reviewer #3 for the valuable comment, which we plan to address by revising Figure 2.

      1. "A significant benefit and uniqueness of the Deep3DSIM design is its upright configuration, whereas commercial SIM systems are built around inverted microscopes and are usually restricted to imaging thin samples, such as cultured cells." (p5) is not correct. The commercial DeepSIM module from CREST Optics can be mounted on an inverted microscope as well as image deep into tissue (seehttps://crestoptics.com/deepsim/ and application notes therein) and be used with essentially any objective. This point should be rephrased in the text.

      Response:

      We want to thank Reviewer #3 for bringing our attention to this error. Of course, we meant commercial 3D-SIM systems, such as GE Healthcare DeltaVision OMX and Nikon N-SIM. To address this issue, we plan to rephrase this part of the results section. Regarding the commercial DeepSIM module from CREST Optics, as far as we can tell, it uses a different method – 2D lattice multi-spot SIM – which comes at the cost of signal loss when sample-induced aberrations are strong. This is very different from our method, which uses a deformable mirror to manipulate the phase information of both the excitation and the emission light at the back-pupil plane of the objective lens, which can theoretically provide 2× resolution enhancement with no signal lost.

      1. Fig 3 reports the improvements of AO on SIM for imaging over 10um in tissue. What are the Zernike modes measured? Or how does the pupil look like before and after correction? It would be also good to report the Fourier amplitudes as done in Fig 2C as a quantitative measure of improvement. It would be good to point out the artifacts observed on the BP SIM image reconstruction (labelled with 3x, fringes are noticeable).

      Response:

      We thank Reviewer #3 for the good suggestions. We plan to add information about the measured Zernike modes to the results section, as well as to add a brief discussion about the noticeable reconstruction artefacts. In terms of pupil and Fourier amplitudes, we plan to change Figure 3 to include all this information or, alternatively, to include it in the supplementary material.

      1. Many key details relating to image acquisition and AO correction are missing for all figures. How is the AO optimization implemented? Is it implemented via a genetic algorithm (progressive optimization of parameters) or using more clever strategies? Not clear if the optimization is implemented using images obtained with flat illumination or after SIM imaging/processing of a given dataset. How long does the AO optimization take? How sensitive to noise is the process? What metric do they use to estimate the sensorless AO correction? On pag12, they say "Fourier domain image metric" for measurements with fine details; otherwise, ISOsense when not high frequencies are present. Could the authors report the formula used to calculate the first metric? What do they consider to be low and high frequencies in this case? Is there a reason why ISOsense is not always used, or is there an automatic way to choose between the two? How many images were acquired for AO correction? Which samples were corrected with ISOsense and which ones with Fourier domain image metric? (see for example the detailed experimental reporting in the Supp Mat from Lin et al Nat Commun 2021).

      Response:

      We are grateful to Reviewer #3 for the extensive list of questions. The optimisation is done via non-linear least square, it uses widefield images, and it is performed before the actual image acquisition, i.e. well before any SIM reconstruction takes place. The methods used for aberration correction are described in the Methods and materials section, and further in the cited literature, e.g. Antonello et al 2020 and Hall et al 2020. ISOsense needs to be manually chosen over the Fourier image metric, and this should be done when large mode biases lead to small changes in the metric value, which is likely to happen when there are little or no sharp features in the images. One of the disadvantages of our implementation of ISOsense is that the structured illumination pattern is continuously exposed over the sample, which leads to photobleaching and phototoxicity. None of the datasets shown in the manuscript use ISOsense. To address all of the questions from this comment, we plan to significantly expand our descriptions of the AO methods, both in the main text and in the supplementary material.

      1. Fig 4. Data presented for larval brain tissue is a very clear example of adding AO to image deep into tissue as the effect at ~130 cannot be understated. Here too, it would be also good to report the Fourier amplitudes as done in Fig 2C as a quantitative measure of improvement and possibly the SNR of reconstructed images. Having a way to quantitatively describe how much better are those images would be great. Also, what are the aberrations corrected? Can the wavefront or Zernike amplitude of the modes be reported? Same as for Fig 3, details about AO correction are missing.

      Response:

      We are grateful to Reviewer #3 for the helpful comment. We will address it by adding the Fourier amplitudes to Figure 4, as suggested, and by reporting the Zernike mode amplitudes of the aberration corrections.

      1. [OPTIONAL] "It is worth noting that aberrations can differ across larger fields, and therefore, after applying an average correction, residual aberrations can still be observed in some regions of the AO-corrected bead images. However, the overall PSF shapes were still dramatically improved with AO compared to the equivalent without AO." This point is very interesting although not result either in the main text or in the SI is presented.

      Response:

      The residual aberrations are present in the right image of Figure 4B, although we did not highlight them specifically. We are thankful to Reviewer #3 for the good suggestion and we plan to implement it by changing Figure 4 to show a few of the beads with residual aberrations.

      1. "As we found that the aberrations change approximately linearly in depth, we could measure the aberration in two planes and calculate the corrections in intermediate planes by interpolation, an approach which we termed "multi-position AO"." This is, personally, one of the major contributions of this work to the community. Unfortunately, it is not reported in detail. Not only for SIM but for imaging with WF or confocal, such linear change for aberrations with depth is not well known. Again, here the details of AO correction and image metrics are missing. To establish that for most thick biological structures 'aberrations change approximately linearly in depth' would be foundational to the widespread use of AO within standard imaging. Would it be possible for the authors to elaborate on this point and present detailed results? What is the error from measuring and correcting more than 2 planes? What is the error from just measuring and AO correcting at the deeper plane, i.e. from a single measurement? Authors could also show a case in which a linear assumption works nicely (or how well it works). For example, comparing an intermediate plane (or a plane beyond) imaged after AO optimization or after coefficient interpolation of the Zernike modes and compare it against correcting directly that plane.

      Response:

      Some aberrations, such as defocus and spherical aberrations, are mathematically defined as varying linearly with depth. The change in other aberrations with depth can also be estimated with a linear model, which is a standard first-order approximation in the case of two datapoints, such as corrections done in Figure 5. It is not possible to do regression analysis with just a single point, so it is impossible to apply our multi-position AO at a single plane. We are grateful to Reviewer #3 for the constructive comment. To address the questions in this comment, we plan to provide a more detailed description of the correction estimation methods to the results section, as well as a discussion on the accuracy of the linear model in the discussion section.

      1. The image of the cos-7 cell in metaphase, for Fig 5 is, however, very disappointing. See Fig 1 of Novak et al Nat Commun 2018 for an example of a single z-plane of a cell in metaphase. Having the possibility to correct for the entire 3D volume, I would expect amazing 3D volumes (movies and/or projections) associated with this imaging which are not presented.

      Response:

      We thank Reviewer #3 for the interesting comment. The example in Novak et al 2018 was acquired with STED microscopy, which is an entirely different imaging method and thus produces different results. Nevertheless, we will revise the discussion of Figure 5 to ensure that the right expectations are set.

      1. In Figure 6, they use AO in remote configuration mode to allow imaging of live specimens. It needs to be clarified if this is an a priori characterization that is then kept fixed while recording in time. The last acquired volume of fig 6A and B have a higher amount of artifacts with respect to time 00:00. Are those artifacts due to lower SNR (maybe due to sample bleaching) or due to some change in the aberrations of the specimen?

      Response:

      We want to thank Reviewer #3 for the valuable comment. We assume that by change in artefacts, Reviewer #3 is referring to the overall green fluorescent structure. Indeed, this last volume shows the anaphase to telophase transition where the mitotic spindle is being reorganised and disassembled. As such, the structure is much less well-defined than in the first volume. The changes in aberrations over time are not particularly significant in this case, and the photobleaching is not that impactful in such an experiment where relatively thin volumes are acquired with substantial time delay between them. To address this comment, we plan to revise the discussion of the figure and to ensure that the scene observed in the last volume is clearer.

      1. "These results demonstrate that the remote focusing functionality of the system can be successfully applied for live 3D-SIM experiments, allowing four-dimensional acquisition while keeping the specimen stationary, thus avoiding the usual agitation and perturbations associated with mechanical actuation." Generally, this statement is true, but for the specific example shown of drosophila embryogenesis is it relevant? If they use piezo-driven Z-stack imaging with AO, does that lead to incorrect reconstructions or motion-induced artifacts? Related to the results shown in Fig 6, the fair comparison would be AO SIM vs SIM (without AO), not AO SIM vs AO WF.

      Response:

      We are grateful to Reviewer #3 for the insightful comment. Drosophila embryos are quite robust to perturbations due to their shape and size, and the restrictions imposed by SIM experiments (e.g. small Z steps and Z levels held for long periods of time) make motion-induced artefacts not very impactful. Regarding the results, the point of Figure 6 is not to demonstrate the advantages of aberration correction, which we do not claim in the caption or in the relevant part of the discussion, but to demonstrate that remote focusing works well with 3D-SIM reconstruction, which is known to have stringent requirements about the image quality. To address this comment, we plan to revise the figure and its relevant part of the results section.

      1. When performing remote focusing, is the effective NA of the imaged plane changing with respect to the NA of the objective used at its focal plane?

      Response:

      We thank Reviewer #3 for the good question. The effective NA is not altered by the remote focusing. We plan to mention this detail in the results section.

      1. [OPTIONAL] Did the authors run calculations to explore whether a commercial upright microscope could be used instead of their design? Are there any fundamental flaws that would make impossible using a commercial base? If not, could an AO SIM module be designed such that it adds on a commercial base? It would be important to discuss this point.

      Response:

      We thank Reviewer #3 for bringing up this interesting point. A lot of considerations, calculations, and modelling were done in the design of the Deep3DSIM system. Of course, the use of a commercial upright microscope stand was part of the deliberation. One of the obvious limitations is the difficult access to the pupil-conjugated plane. On the other hand, a commercial microscope stand is not well compatible with many of the key parts of the system, which were designed around specific biological applications, such as dual camera system for fast live simultaneous imaging and the heavy-duty Z stage intended to support two heavy micromanipulators. To address this comment, we plan to add a discussion of the compatibility of Deep3DSIM with commercial microscope stands to the discussion section and the supplementary material.

      Minor comments:

      1. Fig 2 lacks a color bar for D panels, which is in log scale. Authors should also show the Fourier transform along the z direction.

      Response:

      The colour mapping in Figure 2 uses the lookup tables called Cyan Hot and Orange Hot, as indicated in the caption, which come from the ImageJ software. To address this comment, we plan to improve the caption to reflect the fact that the plots are in log scale. We also want to include Fourier transforms along Z, either in the figure itself or in the supplementary material.

      1. p4, "Such minor aberrations tend to be insignificant in conventional microscopy modalities such as widefield and confocal (Wang and Zhang, 2021). Therefore..." If optical aberrations are insignificant for single cells in widefield and confocal why do experiments here? These sentences should be rephrased to motivate better the experiments performed.

      Response:

      We agree with this comment. To address it, we plan to rephrase this part of the results section to motivate better the experiments.

      1. Imaged microtubules look abnormal, 'dotty' (figure 2) in both WF and SIM. See https://sim.hms.harvard.edu/portfolio/microtubules/ or Fig 1 of Wegel, et al Dobbie Sci Rep 2016, for better examples of continuous microtubule structures as imaged with SIM.

      Response:

      The dottiness of the microtubule structures is not related to the SIM reconstruction, because the same dottiness is seen in the respective WF data, too. It is a product of the sample preparation and it has only aesthetic significance. Nevertheless, to address this comment we plan to mention the dottiness in the results section.

      1. Is also the remote focusing performed via optimization of metrics similar to the one used for compensating aberrations?

      Response:

      Yes, as mentioned in the Methods and materials (p. 13), the calibration of the remote focusing involved sensorless aberration correction of several Zernike modes, such as defocus and spherical aberrations.

      1. Figure 2, the order of names on the top right of the panel should match the order of curves presented.

      Response:

      We agree with this comment. To address it, we plan to reorder the curves in Figure 2.

      1. I value the efforts to improve open-source tools for system and AO control and GUI. And those tools seemed to have been modified for this work, although those modifications are not described. Would it be possible for the authors to describe those modifications?

      Response:

      A detailed breakdown is publicly available at the respective software repositories. To address this comment, we plan to add a summary of software changes to the supplementary material.

      1. Reported average values of the FWHM of imaged beads in 3D (p4) require also to report errors associated with those measurements.

      Response:

      We agree with this comment. To address it, we plan to add statistical information to the FWHM values on page 4.

      1. Page 13, second paragraph states that "The results from chapter 3.2..." I believe that was a copy/paste from a thesis but should be corrected for a peer-reviewed publication, as there is no chapter 3.2.

      Response:

      This is a leftover from an older version of the document which used numbered sectioning. In this case “chapter 3.2” refers to subsection “Characterisation of drift and temperature effects”. We plan on fixing this mistake in the revised manuscript.

      PeerReviewed
    2. EMBOpress 04 Jul 2024

      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 #3

      Evidence, reproducibility and clarity

      Summary

      The work of Wang et al entitled "Deep super-resolution imaging of thick tissue using structured illumination with adaptive optics" presents the use of a deformable mirror to simultaneously perform adaptive optics 'AO' and remote focusing 'RF' on a custom-designed upright microscope configuration. The work is novel and represents a timely application of this type of technology to imaging biological specimens. AO enables the correction of refractive index mismatch and sample-induced aberrations while remote focusing allows focusing through the sample without moving the specimen or the objective. The use of AO improves the final image reconstructed using a traditional SIM processing strategy. I greatly value the idea presented (SI pattern generation p7 Supp Inf) about maximizing the contrast of the projected structured illumination. This could be an excellent way to improve SIM imaging since image reconstructions suffer from artifacts when signal to noise ratio is low. However, since it is only one of the factors considered for reducing the stripe width it is unclear how it compares to imaging with the width that maximizes resolution.

      Authors do also a very good job describing, characterizing and designing experiments to deal with instabilities exhibited by the deformable mirror.

      One of the key aspects of the paper, that could be stressed more, is that including AO gives access to better-quality raw images that are then be used for standard reconstruction pipeline SIM processing. When aberrations are compensated, the illumination pattern closely matches what is expected by the SIM image formation model. Since these raw recorded images are sharper and closer to the actual assumption behind the SIM image reconstruction model, they will have a major positive impact in reducing artifacts that the inversion algorithm is returning. This is particularly evident in Figure 4.

      Major comments:

      • There is an overall reference in the manuscript of the novelty possible range of applications of using an upright microscope configuration. Examples mentioned are tissue-based imaging, access to whole-mount specimens for manipulation and electrophysiology. However, authors fail to present any such applications. There is not a single example presented which could not have been obtained with an inverted microscope. Could the authors provide an example where a water-dipping is used. Expanded samples could be one case, since the thickness of the gel makes it difficult to image with an inverted microscope. Another possible example would be to label the extracellular space and do shadow imaging of the tissue (SUSHI PMID: 29474910). ExM might be simpler to do as part of revising the manuscript than SUSHI.
      • On the main text it is described a 5-fold volumetric resolution, which is confusing since authors only mention lateral and axial resolutions. Their measurements correspond to a ~1.6-fold lateral improvement and ~1.7-fold axial improvement. These are however not the 95% of the achievable resolution theoretical maximum, as stated in p7 SI (2 fold increase of 282nm), but only the 80-85%. This point should be rephrased in the manuscript.
      • [OPTIONAL] p4 and related to figure 2, it would be important to report also measurements of beads with SIM but without AO, just as done for WF. Is there an improvement of using AO on SIM? This is reported for the fixed cells but not for the beads.
      • Figure 2, it is odd the comparison between WF+/- AO and SIM +/- AO are done using different cellular structures. Since wavelengths used are not the same it is difficult to interpret if there is any improvement of using AO on SIM compared to SIM without AO. Same questions arise as above, Is there an improvement of using AO on SIM?
      • "A significant benefit and uniqueness of the Deep3DSIM design is its upright configuration, whereas commercial SIM systems are built around inverted microscopes and are usually restricted to imaging thin samples, such as cultured cells." (p5) is not correct. The commercial DeepSIM module from CREST Optics can be mounted on an inverted microscope as well as image deep into tissue (see https://crestoptics.com/deepsim/ and application notes therein) and be used with essentially any objective. This point should be rephrased in the text.
      • Fig 3 reports the improvements of AO on SIM for imaging over 10um in tissue. What are the Zernike modes measured? Or how does the pupil look like before and after correction? It would be also good to report the Fourier amplitudes as done in Fig 2C as a quantitative measure of improvement. It would be good to point out the artifacts observed on the BP SIM image reconstruction (labelled with 3x, fringes are noticeable).
      • Many key details relating to image acquisition and AO correction are missing for all figures. How is the AO optimization implemented? Is it implemented via a genetic algorithm (progressive optimization of parameters) or using more clever strategies? Not clear if the optimization is implemented using images obtained with flat illumination or after SIM imaging/processing of a given dataset. How long does the AO optimization take? How sensitive to noise is the process? What metric do they use to estimate the sensorless AO correction? On pag12, they say "Fourier domain image metric" for measurements with fine details; otherwise, ISOsense when not high frequencies are present. Could the authors report the formula used to calculate the first metric? What do they consider to be low and high frequencies in this case? Is there a reason why ISOsense is not always used, or is there an automatic way to choose between the two? How many images were acquired for AO correction? Which samples were corrected with ISOsense and which ones with Fourier domain image metric? (see for example the detailed experimental reporting in the Supp Mat from Lin et al Nat Commun 2021).
      • Fig 4. Data presented for larval brain tissue is a very clear example of adding AO to image deep into tissue as the effect at ~130 cannot be understated. Here too, it would be also good to report the Fourier amplitudes as done in Fig 2C as a quantitative measure of improvement and possibly the SNR of reconstructed images. Having a way to quantitatively describe how much better are those images would be great. Also, what are the aberrations corrected? Can the wavefront or Zernike amplitude of the modes be reported? Same as for Fig 3, details about AO correction are missing.
      • [OPTIONAL] "It is worth noting that aberrations can differ across larger fields, and therefore, after applying an average correction, residual aberrations can still be observed in some regions of the AO-corrected bead images. However, the overall PSF shapes were still dramatically improved with AO compared to the equivalent without AO." This point is very interesting although not result either in the main text or in the SI is presented.
      • "As we found that the aberrations change approximately linearly in depth, we could measure the aberration in two planes and calculate the corrections in intermediate planes by interpolation, an approach which we termed "multi-position AO"." This is, personally, one of the major contributions of this work to the community. Unfortunately, it is not reported in detail. Not only for SIM but for imaging with WF or confocal, such linear change for aberrations with depth is not well known. Again, here the details of AO correction and image metrics are missing. To establish that for most thick biological structures 'aberrations change approximately linearly in depth' would be foundational to the widespread use of AO within standard imaging. Would it be possible for the authors to elaborate on this point and present detailed results? What is the error from measuring and correcting more than 2 planes? What is the error from just measuring and AO correcting at the deeper plane, i.e. from a single measurement? Authors could also show a case in which a linear assumption works nicely (or how well it works). For example, comparing an intermediate plane (or a plane beyond) imaged after AO optimization or after coefficient interpolation of the Zernike modes and compare it against correcting directly that plane.
      • The image of the cos-7 cell in metaphase, for Fig 5 is, however, very disappointing. See Fig 1 of Novak et al Nat Commun 2018 for an example of a single z-plane of a cell in metaphase. Having the possibility to correct for the entire 3D volume, I would expect amazing 3D volumes (movies and/or projections) associated with this imaging which are not presented.
      • In Figure 6, they use AO in remote configuration mode to allow imaging of live specimens. It needs to be clarified if this is an a priori characterization that is then kept fixed while recording in time. The last acquired volume of fig 6A and B have a higher amount of artifacts with respect to time 00:00. Are those artifacts due to lower SNR (maybe due to sample bleaching) or due to some change in the aberrations of the specimen?
      • "These results demonstrate that the remote focusing functionality of the system can be successfully applied for live 3D-SIM experiments, allowing four-dimensional acquisition while keeping the specimen stationary, thus avoiding the usual agitation and perturbations associated with mechanical actuation." Generally, this statement is true, but for the specific example shown of drosophila embryogenesis is it relevant? If they use piezo-driven Z-stack imaging with AO, does that lead to incorrect reconstructions or motion-induced artifacts? Related to the results shown in Fig 6, the fair comparison would be AO SIM vs SIM (without AO), not AO SIM vs AO WF.
      • When performing remote focusing, is the effective NA of the imaged plane changing with respect to the NA of the objective used at its focal plane?
      • [OPTIONAL] Did the authors run calculations to explore whether a commercial upright microscope could be used instead of their design? Are there any fundamental flaws that would make impossible using a commercial base? If not, could an AO SIM module be designed such that it adds on a commercial base? It would be important to discuss this point.

      Minor comments

      • Fig 2 lacks a color bar for D panels, which is in log scale. Authors should also show the Fourier transform along the z direction.
      • p4, "Such minor aberrations tend to be insignificant in conventional microscopy modalities such as widefield and confocal (Wang and Zhang, 2021). Therefore..." If optical aberrations are insignificant for single cells in widefield and confocal why do experiments here? These sentences should be rephrased to motivate better the experiments performed.
      • Imaged microtubules look abnormal, 'dotty' (figure 2) in both WF and SIM. See https://sim.hms.harvard.edu/portfolio/microtubules/ or Fig 1 of Wegel, et al Dobbie Sci Rep 2016, for better examples of continuous microtubule structures as imaged with SIM.
      • Is also the remote focusing performed via optimization of metrics similar to the one used for compensating aberrations?
      • Figure 2, the order of names on the top right of the panel should match the order of curves presented.
      • I value the efforts to improve open-source tools for system and AO control and GUI. And those tools seemed to have been modified for this work, although those modifications are not described. Would it be possible for the authors to describe those modifications?
      • Reported average values of the FWHM of imaged beads in 3D (p4) require also to report errors associated with those measurements.
      • Page 13, second paragraph states that "The results from chapter 3.2..." I believe that was a copy/paste from a thesis but should be corrected for a peer-reviewed publication, as there is no chapter 3.2.

      Referee Cross-Commenting

      The other two reviewers raise relevant and important points that would contribute to the overall improvement of the work. I think that authors should try to address most, if not all, of the comments as long as they don't require more than 3-6 months to get done.

      Significance

      General assessment:

      Although a very good and timely idea is presented the overall the manuscript still needs a lot of work. There is a lack of many key details of AO correction, all applications chosen could have been done in an inverted scope and some of the example images reported are suboptimal (Fig 2 and 5) that need further experimental work. Details and metrics, one example of the advantage of using an upright microscope and overall better examples of imaged cells could be provided.

      This work builds upon recent work of implementing AO for 3D SIM (Lin et al Nat Commun 2021) to propose to use a deformable mirror to perfrom AO as well as remote focusing in an upright microscope configuration.

      Audience: this work will be of interest for a specialized group of researchers, but it will contribute to the goal of adding AO tools to every microscope that will greatly impact the whole imaging community.

      PeerReviewed
    3. EMBOpress 04 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The authors want to develop a structured illumination microscopy (SIM) system for deep tissue superresolution imaging. Here they have developed a SIM system based on the upright configration, and use deformable mirror to compensate for the relection index (RI) mismatch and improve the resolution and contrast in deep tissues. They also showed examples of SR imaging of COS-7 cells and Drosophila larval brains and embryos.

      However, I do have some concerns regarding the paper.

      1. The authors have provided an incomplete description of the structured illumination microscopy (SIM) reconstruction process. It is unclear whether the approach is based on 2D interference SIM configurations or 3D interference patterns. Furthermore, the specific algorithm utilized for image reconstruction has not been elucidated. Elaborating on these aspects is crucial as they significantly influence the interpretation of the resulting data.
      2. The authors have stated that sample-induced aberrations caused by RI inhomogeneities within the specimen is another major reason for causing artifacts generation. Literature has demonstrated that RI inhomogeneities can lead to non-local distortions in the grid pattern, which suggests that applying uniform reconstruction parameters across the entire image may not be viable. Traditional artifact remediation using the classical Wiener method is likely insufficient under these conditions (PMID: 33896197). The existing adaptive optics (AO) approach, which employs a deformable mirror (DM) alongside an sCMOS camera, is inadequate for tackling the issue at hand. Actually the assertion made in the paper that "aberrations change approximately linearly with depth" is seemingly contradicted by simulations referenced in the cited literature (PMID: 33896197). Consequently, it appears that the current methodology might only achieve a partial mitigation of the problems associated with spherical aberration resulting from RI mismatches. It is advisable, therefore, that the authors explicitly acknowledge this limitation in their manuscript to prevent any potential misinterpretation by readers.
      3. In Figure 2, the use of COS-7 cells, which are known for their relatively thin axial dimension, for the experiments raises an eyebrow. Notably, there are ample instances in existing research where both 2D-SIM and 3D-SIM, without the integration of adaptive optics, have yielded high-quality super-resolution images of structures such as tubulin and the endoplasmic reticulum. In addition, the authors did not present a direct comparison between BP-SIM and AO-SIM here. Without this comparative analysis, it remains ambiguous whether the enhancements in resolution and contrast and the reduction in artifacts can genuinely be attributed to the mitigation of spherical aberration. To clarify this, it would be beneficial for the authors to include side-by-side comparisons of these modalities to demonstrate the specific improvements attributed to AO-SIM.
      4. In Figures 3 and 4, the authors have illustrated the enhancements achieved through the application of AO. However, there is a discernible presence of hammer-stroke and honeycomb artifacts in pre-AO imaged data, which seem to originate from the amplification of the incorrectly moved out-of-focal background in the frequency domain. Various strategies have been previously suggested to address these specific artifacts, encompassing methods like subtracting background noise in the raw images or employing selective frequency spectrum attenuation techniques, such as Notch filtering and High-Fidelity SIM. To facilitate a more comprehensive understanding, I would recommend that the authors incorporate into their study a comparison that includes BP-SIM data that has undergone either background subtraction or frequency spectrum attenuation. This added data would enable a more complete evaluation and comparison regarding the merits and impact of their AO approach.

      Significance

      The authors want to develop a structured illumination microscopy (SIM) system for deep tissue superresolution imaging. Here they have developed a SIM system based on the upright configration, and use deformable mirror to compensate for the relection index (RI) mismatch and improve the resolution and contrast in deep tissues.

      PeerReviewed
    4. EMBOpress 04 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Review, 3D SIM + AO, Wang and coworkers

      In this manuscript, Wang and coworkers report an upright 3D SIM system with adaptive optics (AO) correction. They demonstrate that AO improves imaging into thick 3D samples, including Drosophila larval brain. They also explore the use of remote focusing with their setup. The authors clearly demonstrate a gain with AO, and we are convinced that the microscope they build offers some utility over existing state of the art, particularly in samples thicker than a single cell. That said, we have concerns with the manuscript that we would like to see addressed before recommending publication:

      • Given the emphasis on super-resolution imaging deep inside a sample, we were surprised to see no mention of other forms of structured illumination that allow super-resolution imaging in samples thicker than a single cell. These include the 'spot-scanning' implementations of SIM that offer better imaging at depth by virtue of pinholes, and include MSIM, iSIM, and rescan confocal technologies. The two-photon / AO implementation of iSIM seems particularly germane, e.g. https://pubmed.ncbi.nlm.nih.gov/28628128/ Please consider citing these works, as they help place the existing work into context.
      • As we're sure the authors appreciate, besides aberrations, a major additional obstacle to 3D SIM in thick tissues is the presence of out-of-focus background. Indeed, this point was mentioned by Gustafsson in his classic 2008 paper on 3D SIM (https://pubmed.ncbi.nlm.nih.gov/18326650/): 'The application area of three-dimensional structured illumination microscopy overlaps with that of confocal microscopy, but the two techniques have different and complementary strengths. Structured illumination microscopy offers higher effective lateral resolution, because it concentrates much of the excitation light at the very highest illumination angles, which are most effective for encoding high-resolution information into the observed data, whereas confocal microscopy spreads out its illumination light more or-less uniformly over all available angles to form a focused beam. For very thick and compactly fluorescent samples, however, confocal microscopy has an advantage in that its pinhole removes out-of focus light physically. Structured illumination microscopy is quite effective at removing out-of-focus light computationally, because it is not subject to the missing-cone problem, but computational removal leaves behind the associated shot noise. Therefore confocal microscopy may be preferable on very thick and dense samples, for which the in-focus information in a conventional microscope image would be overwhelmed by out-of-focus light, whereas structured illumination microscopy may be superior in a regime of thinner or sparser samples.' This point is not mentioned at all in the manuscript, yet we are certain it is at least partially responsible for the residual image artifacts the authors mention. Please discuss the problem of out of focus light on 3D samples, particularly with an eye to the 'spot-scanning' papers mentioned above.
      • The authors use a water dipping lens, yet they image into samples that are mounted on coverslips, i.e. they use a dipping lens to image through a coverslip: see attached pdf for reference

      This almost certainly introduces spherical aberration, which the authors seem to observe: see attached pdf for reference

      We find this troubling, as it seems that in the process of building their setup, the authors have made a choice of objective lens that introduces aberrations - that they later correct. At the very least, this point needs to be acknowledged in the manuscript (or please correct us if we're wrong) - as it renders the data in Figs. 3-4 somewhat less compelling than if the authors used an objective lens that allowed correction through a coverglass, e.g. a water dipping lens with a correction collar. In other words, in the process of building their AO setup, the authors have introduced system aberrations that render the comparison with 3D SIM somewhat unfair. Ideally the authors would show a comparison with an objective lens that can image through a glass coverslip. - The authors tend to include numbers for resolution without statistics. This renders the comparisons meaningless in my opinion; ideally every number would have a mean and error bar associated with it. We have included specific examples in the minor comments below. - In Fig. 5, after the 'multipoint AO SIM', the SNR in some regions seems to decrease after AO: see attached pdf for reference

      Please comment on this issue.

      • Please provide timing costs for the indirect AO methods used in the paper, so the reader understands how this time compares to the time required for taking a 3D SIM stack. In a similar vein, the authors in Lines 213-215, mention a 'disproportionate measurement time' when referring to the time required for AO correction at each plane - providing numbers here would be very useful to a reader, so they can judge for themselves what this means. What is the measurement time, why is it so long, and how does it compare to the time for 3D SIM? It would also be useful to provide a comparison between the time needed for AO correction at each (or two) planes without remote focusing (RF) vs. with RF, so the reader understands the relative temporal contributions of each part of the method. We would suggest, for the data shown in Fig. 5, to report a) the time to acquire the whole stack without AO (3D SIM only); b) the time to acquire the data as shown; c) the time to acquire the AO stack without RF. This would help bolster the case for remote focusing in general; as is we are not sure we buy that this is a capability worth having, at least for the data shown in this paper.
      • Some further discussion on possibly extending the remote focusing range would be helpful. We gather that limitations arose from an older model of the DM being used, due to creep effects. We also gather from the SI that edge effects at the periphery of the DM was also problematic. Are these limitations likely non-issues with modern DMs, and how much range could one reasonably expect to achieve as a result? We are wondering if the 10 um range is a fundamental practical limitation or if in principle it could be extended with commercial DMs.

      Minor comments

      • The paper mentions Ephys multiple times, even putting micromanipulators into Fig. 1 - although it is not actually used in this paper. If including in Figure 1, please make it clear that these additional components are aspirational and not actually used in the paper.
      • The abstract mentions '3D SIM microscopes', 'microscopes' redundant as the 'm' in 'SIM' stands for 'microscope'.
      • 'fast optical sectioning', line 42, how can optical sectioning be 'fast'? Do they mean rapid imaging with optical sectinong?
      • line 59, 'effective imaging depth may be increased to some extent using silicone immersion objectives', what about water immersion objectives? We would guess these could also be used.
      • line 65 - evidence for 'water-dipping objectives are more sensitive to aberrations' ? Please provide citation or remove. They are certainly more prone to aberrations if used with a coverslip as done here.
      • 'fast z stacks' is mentioned in line 103. How fast is fast?
      • line 116 'we imaged 100 nm diameter green fluorescent beads'. Deposited on glass? Given that this paper is about imaging deep this detail seems worth specifying in the main text.
      • lines 127-130, when describing changes in the bead shape with numbers for the FWHM, please provide statistics - quoting single numbers for comparison is almost useless and we cannot conclude that there is a meaningful improvement without statistics.
      • In the same vein, how can we understand that remote focus actually improves the axial FWHM of the widefield bead? Is this result repeatable, or it just noise?
      • line 155, 'Because of the high spatial information...' -> 'Because of the high resolution spatial information...'
      • When quoting estimated resolution #s from microtubules (lines 158-163) similarly please provide statistics as for beads.
      • It seems worth mentioning the mechanism of AO correction (i.e. indirect sensing) in the main body of the text, not just the methods.
      • How long do the AO corrections take for the datasets in the paper?
      • Were the datasets in Fig. 2-4 acquired with remote focusing, or in conventional z stack mode? Please clarify this point in the main text and the figure captions.
      • It would be helpful when showing z projections in Figs. 3-5 to indicate the direction of increasing depth (we assume this is 'down' due to the upright setup, but this would be good to clarify)
      • line 174, 'showed significant improvements in both intensity and contrast after reconstruction' - we see the improvements in contrast and resolution, it is harder to appreciate improvements in intensity. Perhaps if the authors showed some line profiles or otherwise quantified intensity this would be easier to appreciate.
      • line 195 'reduced artefacts' due to AO. We would agree with this statement - the benefit from AO is obvious, and yet there are still artefacts. If the authors could clarify what these (residual) artefacts are, and their cause (out of focus light, uncorrected residual aberrations, etc) this would be helpful for a reader that is not used to looking at 3D SIM images.
      • Line 197, 'expected overall structure', please clarify what is expected about the structure and why.
      • Line 199, what is a 'pseudo structure'?
      • Fig. 4B, 'a resolution of ~200 nm is retained at depth', please clarify how this estimate was obtained, ideally with statistics.
      • Fig. 4D, please comment on the unphysical negative valued intensities in Fig. 4D, ideally explaining their presence in the caption. It would also be helpful to highlight where in the figure these plots arise, so the reader can visually follow along.
      • Line 245, 'rapid mitosis'. What does rapid mean, i.e. please provide the expected timescale for mitosis.
      • For the data in Fig. 6, was remote refocusing necessary?
      • What is the evidence for 'reduced residual aberrations', was a comparative stack taken without AO? In general we feel that the results shown in Fig. 6 would be stronger if there were comparative results shown without AO (or remote focusing).
      • Line 350, 'incorporation of denoising algorithms' - citations would be helpful here.
      • Line 411, 'All three were further developed and improved' - vague, how so?
      • Sensorless AO description; how many Zernike modes were corrected?
      • Multi-position aberration correction. Was the assumption of linearity in the Zernike correction verified or met? Why is this a reasonable assumption?
      • Fig. S1B is not useful; if the idea is to give a visual impression of the setup, we would recommend providing more photos with approximate distances indicated so that the reader has a sense of the scale of the setup. As is - it looks like a photograph of some generic optical setup.
      • SI pattern generation - 'the maximum achievable reconstruction resolution was only slightly reduced to about 95% of the theoretical maximum'. We don't understand this sentence, as the resolution obtained on the 100 nm beads is considerably worse than 95% of the theoretical maximum. Or do the authors mean 95% of the theoretical maximum given their pitch size of 317 nm for green and 367 nm for red? SI Deformable mirror calibration

      'spanning the range [0.1, 0.9]' - what are the units here?

      What are the units in Fig. S5C, S5D?

      It would be useful to define 'warmup' also in the caption of SI Fig. S6A. SI Remote Focusing, 'four offsets, {-5 mm, -2.5 mm, 2.5 mm, 5 mm}...' are the units mm or um? '...whereas that of the 10 beads was...' here, do the authors mean the position of the beads derived from the movement of the piezo stage, as opposed to the remote focusing? The authors refer to the 'results from Chapter 3.2'. What are they talking about? Do they mean a supplementary figure, or earlier supplementary results? In general, we found the discussion in this paragraph difficult to follow. Supplementary Fig. 9 seems to be not referred to anywhere in the text. - Since the paper emphasizes 3D SIM, OTFs along the axial direction would also be useful to show, in addition to the lateral OTFs shown in Fig. 2D. - When the sample is moved by the piezo, the axial phase of the 3D-SIM illumination pattern is stable as the sample is scanned through the illumination pattern. When remote focusing is performed, the sample is always stable so the axial phase of the 3D-SIM illumination pattern is presumably changing with remote focusing. Can the authors clarify if the 3D SIM illumination pattern is scanned when remote focusing is applied, or is the intensity pattern stable in z? - In Supplementary Fig. 9, primary spherical is referred to twice, both at index 11 and 22. The latter is presumably secondary spherical? - we do not understand the x axis label, in Fig. S4D, is it really [0, 50, 50, 50] as written? see attached pdf for reference

      Referee Cross-Commenting

      I don't have much to add; the other reviewers raise good points and I think it would be good if the authors could respond to their feedback in a revised manuscript.

      Significance

      Nearly all fluorescence images deteriorate as a function of depth. Methods to ameliorate this depth-dependent degradation are thus of great practical value, as they improve the information content of images and thus (hopefully) biological insight. In this work, the authors develop a method to improve super-resolution imaging (3D SIM) at depth, by combining it with adaptive optics.

      PeerReviewed
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    biorxiv.org/content/10.1101/2023.12.21.572818v2
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    Trazodone, dibenzoylmethane and tauroursodeoxycholic acid do not prevent motor dysfunction and neurodegeneration in Marinesco-Sj&#x00F6;gren syndrome mice
    3
    1. EMBOpress 04 Jul 2024

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      Reply to the reviewers

      Reviewer #1:

      This study provides negative in vivo evidence for the use of two PERK inhibitors and of TUDCA for the treatment of Sli1-related Marinesco-Sjögren syndrome (MSS).

      Overall, the manuscript reports a substantial amount of work and the study could be published in its present format. The experiments are well described in terms of methodology and appropriate analysis has been applied. Claims are proportionate and not overstated

      I would have only minor comments related to some clarifications that the authors could make in the present manuscript and a suggestion for experiments that could improve the manuscript.

      First, although this is not my expertise, the in vitro analysis of CHOP luciferase assays suggests that very high concentrations, in particular of TUDCA, are needed to observe an effect. The authors may wish to clarify their opinion and whether this could be the reason why in vivo they have been unable to obtain any inhibition of the PERK pathway.

      The reviewer is correct in pointing out that high concentrations of trazodone, DBM and TUDCA were required to inhibit the PERK pathway in the CHOP::luciferase reporter cell lines. However, as we state in the Discussion, we do not think that their lack of effect in vivo was due to insufficient drug levels, since woozy mice were treated with trazodone, DBM or TUDCA according to dose regimens and administration routes that have proved effective in other neurodegenerative disease mouse models. Moreover, our analysis did not find major differences in drug bioavailability between mice with the woozy genetic background (CXB5/ByJ) and C57BL/6J mice in which these drugs had shown neuroprotective effects (see also the response to the next point).

      Second, it seems to me that when measuring the Trazodone metabolism there is a difference between acute and chronic treatment. It would be worth discussing what the authors make of that and what is more relevant (I assume chronic) to the disease model outcome.

      We realized that the nomenclature used in Figures 6 and 7 was confusing, leading the reader to think there were differences in trazodone levels between chronically and acutely treated mice.

      The experiment shown in Figure 6 was designed to test whether there were differences in trazodone pharmacokinetics and metabolism between mice of the woozy strain, which have the CXB5/ByJ genetic background, and C57BL/6J mice in which trazodone had shown neuroprotective effects in previous studies. In contrast, Figure 7 illustrates the levels of trazodone and m-CPP in control and woozy mice (both of which have the CXB5/ByJ genetic background) that had been chronically treated with trazodone for 5 weeks. These are the same animals as in Figure 3, as we state in Figure 7 legend. Therefore one should compare the levels of trazodone and m-CPP in Figure 7 with those of the "woozy" group (CXB5/ByJ genetic background) in Figure 6. This comparison shows that trazodone and m-CPP levels are comparable after chronic and acute (6h) treatment.

      To avoid confusion, we have changed the mouse nomenclature. We have renamed the control group of mice as "CT" (previously "WT") throughout the text and figures. In Figure 6, we have used CXB5/ByJ instead of "woozy" to emphasize the comparison between the different genetic backgrounds (CXB5/ByJ vs C57BL/6J). Finally, we have replaced the colors of symbols in Figure 7 in order to match those of Figure 3. We have also made the description and discussion of these results clearer in the revised manuscript.

      With respect to the experiments a simple and informative addition would be the evaluation of the PERK pathway in mice treated with TUDCA, as this is missing.

      The effect of TUDCA treatment on the PERK pathway is shown in Figure 5, where we measured CHOP mRNA levels in Purkinje cells microdissected from mice treated with 0.4% TUDCA in the chow, and in Figure 9C and D, where we measured the percentage of CHOP-immunopositive Purkinje cells in the cerebellum of same groups of mice by immunohistochemistry.

      Figure 10 illustrates the results of an additional experiment in which woozy mice were treated with 500 mg/kg TUDCA intraperitoneally (ip), to test whether this alternative dosing regimen was any better. Like the treatment per os, TUDCA ip had no beneficial effect on motor dysfunction. Therefore we deemed it unnecessary to check the effect on PERK pathway inhibition in this group of mice.

      A more difficult but potentially more interesting line of investigation is that of searching for potential actions of Trazodone that are PERK independent and might be responsible for the partial rescue observed in the beam walking test, which is much more sensitive and specific than rotarod, so worth considering. Assuming authors want to go down this route and add significance to their study my suggestion would be an unbiased RNA seq from the brain samples they already have. However, this is a suggestion to steer the study towards a more positive outcome and it is not necessary to support their current conclusions.

      We agree with the reviewer that it would be interesting to investigate the mechanism by which trazodone slightly ameliorated the motor performance of woozy mice in the beam walking test. In the Discussion, we speculated that this could be due to an effect of trazodone on cerebellar serotonergic neurotransmission, which would require electrophysiological investigations to demonstrate. Of course, other mechanisms may also be operative, which RNA seq may help identify, as the reviewer suggests. However, this would be a complex and lengthy investigation, the results of which would not change the main conclusions of the present paper. We plan to explore this line of investigation in a future study.

      Reviewer #2:

      Lavigna et al. described the effect of Trazodone in Marinesco-Sjögren syndrome model mice. Although the results are somewhat disappointing, this research has provided fundamental evidence for the future development of MSS therapeutics. There are few minor comments to further improve the manuscript

      Major comment<br /> P14<br /> "Trazodone metabolism to m-CPP was slightly impaired in woozy mice compared to C57BL/6J mice. This was evident from the m-CPP/trazodone ratio, calculated on the AUC0-t in the plasma, which was 0.34 in woozy and 0.67 in C57BL/6J mice."

      Why was the concentration different between WT and woozy mice? Which organ mainly contributes to the metabolism of trazodone? Is the function of this target organ different between WT and woozy mice?<br /> Similar to trazodone, m-CPP clearance from plasma was slightly faster in woozy than in C57BL/6J mice.<br /> Is m-CPP eliminated via the kidney? Or liver? Why is there a difference? Does SIL1 functions in liver or kidney? Needs discussion. This is the same for brain m-CPP levels.

      As explained in the response to the second comment of reviewer #1, "woozy" in Figure 6 referred to mice with the CXB5/ByJ genetic background, and in this experiment we compared trazodone pharmacokinetics and metabolism between CXB5/ByJ and C57BL/6J mice. We have modified the nomenclature of Figure 6 and the Results to make this clear.

      Trazodone undergoes extensive hepatic metabolism, and only a small percentage is excreted unchanged in the urine. Metabolism involves hydroxylation, oxidation and dealkylation reactions, forming in particular the 5HT-active metabolite m-CPP (by CYP3A4). This and other metabolites are mainly excreted in urine, as conjugates [1-3]. The slight differences in trazodone pharmacokinetics and metabolism between the CXB5/ByJ and C57BL6/J mice shown in Figure 6 is not attributable to loss of SIL1 function, since both groups of mice carried wild-type Sil1 alleles, but is most likely due to subtle differences between the two strains, for example in the binding to plasma proteins, metabolic enzymes, transporters and/or the excretion processes. The available data do not allow to clarify this issue.

      The main point, however, is that no major differences were found in the plasma and brain concentrations of trazodone between these two strains of mice, which could have explained the lack of efficacy of trazodone in woozy mice, as we now further stress in the revised Discussion.

      Minor comments

      P3 L5 mutation should be variant.

      This has been changed.

      P4 L1 eIF2a-P should be phosphorylated eIF2α (p-eIF2α). The reviewer prefers (p-eIF2α) than (eIF2α-p) throughout the manuscript.

      There is no standard rule for indicating phosphorylated proteins, and phosphorylated eIF2α is referred to in various ways in different papers, with the "p" in capital or lowercase, preceding or following the protein name, separated by a dash or not. We would prefer to maintain the current nomenclature for consistency with our previous publications, unless the Editor deems otherwise.

      P9 L11 M-CPP should be fully spelled out the first time it appears. m-Chlorophenylpiperazine (m-CPP)

      M-CPP is spelled out the first time it appears in the Material and Methods, subheading Drug treatments and bioanalysis.

      Please explain the difference between the expected function of trazodone and its metabolite m-CPP. Why m-CPP is not effective.

      Based on the observation that mice of the woozy strain had lower brain levels of m-CPP than C57BL6/J mice (Figure 6), we hypothesized that the lack of effect of trazodone in woozy mice could be due to m-CPP mediating the PERK signaling inhibitory activity of trazodone. However, experiments in CHOP::luciferase reporter cells demonstrated that m-CPP does not inhibit PERK signaling (Figure 2D). The precise mechanism by which trazodone inhibits PERK signaling is not known [4], which makes it difficult to speculate why its main metabolite, m-CPP, does not exhibit this activity.

      P11 L3 Fig. 3 Fig. 3A and B?

      Yes, we specifically refer to panels A and B of Figure 3. We have indicated this in the revised manuscript.

      P11 L6 at 7 weeks of age?

      We have re-done the statistical analysis by two-way ANOVA and reported the results in the legend to Figure 3. There is a significant difference between vehicle- and trazodone-treated woozy mice in the number of missteps when the two groups are compared globally. No statistically significant difference in the number of missteps is detected at specific time points by post-hoc analysis. There is no statistically significant difference between vehicle- and trazodone-treated woozy mice in the time to traverse the beam. The Results section has been revised accordingly.

      P12 L17 ~4 times, 4 times? Please state the exact value.

      Done.

      Figure 7 Why are brain m-CPP levels higher than plasma levels? Is trazodone metabolized in brain tissue?

      Trazodone is extensively metabolized in the liver through Cytochrome P450 (Rotzinger et al., 1999). It is well documented that m-CPP readily passes the blood-brain barrier, much better than the parent compound, explaining its high brain levels [2].

      P19 L7 ISRIB; please fully spell out the first time it appears.

      Done.

      References

      1. Rotzinger S, Bourin M, Akimoto Y, Coutts RT, Baker GB (1999) Metabolism of some “second”- and “fourth”-generation antidepressants: iprindole, viloxazine, bupropion, mianserin, maprotiline, trazodone, nefazodone, and venlafaxine. Cell Mol Neurobiol 19:427– 442. https://doi.org/10.1023/a:1006953923305
      2. Caccia S, Ballabio M, Samanin R, Zanini MG, Garattini S (1981) (--)-m-Chlorophenyl- piperazine, a central 5-hydroxytryptamine agonist, is a metabolite of trazodone. J Pharm Pharmacol 33:477–478. https://doi.org/10.1111/j.2042-7158.1981.tb13841.x
      3. DeVane CL, Boulton DW, Miller LF, Miller RL (1999) Pharmacokinetics of trazodone and its major metabolite m-chlorophenylpiperazine in plasma and brain of rats. Int J Neuropsychopharm 2:17–23. https://doi.org/10.1017/S1461145799001303
      4. Halliday M, Radford H, Zents KAM, Molloy C, Moreno JA, Verity NC, Smith E, Ortori CA, Barrett DA, Bushell M, Mallucci GR (2017) Repurposed drugs targeting eIF2alpha-P-mediated translational repression prevent neurodegeneration in mice. Brain 140:1768– 1783. https://doi.org/10.1093/brain/awx074
      PeerReviewed
    2. EMBOpress 02 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      Lavigna et al. described the effect of Trazodone in Marinesco-Sjögren syndrome model mice. Although the results are somewhat disappointing, this research has provided fundamental evidence for the future development of MSS therapeutics. There are few minor comments to further improve the manuscrip

      Major comment

      P14 "Trazodone metabolism to m-CPP was slightly impaired in woozy mice compared to C57BL/6J mice. This was evident from the m-CPP/trazodone ratio, calculated on the AUC0-t in the plasma, which was 0.34 in woozy and 0.67 in C57BL/6J mice."

      Why was the concentration different between WT and woozy mice? Which organ mainly contributes to the metabolism of trazodone? Is the function of this target organ different between WT and woozy mice? Similar to trazodone, m-CPP clearance from plasma was slightly faster in woozy than in C57BL/6J mice. Is m-CPP eliminated via the kidney? Or liver? Why is there a difference? Does SIL1 functions in liver or kidney? Needs discussion. This is the same for brain m-CPP levels.

      Minor comments

      P3 L5 mutation should be variant. P4 L1 eIF2a-P should be phosphorylated eIF2α (p- eIF2α). The reviewer prefers (p- eIF2α) than (eIF2α-p) throughout the manuscript.

      P9 L11 M-CPP should be fully spelled out the first time it appears. m-Chlorophenylpiperazine (m-CPP) Please explain the difference between the expected function of trazodone and its metabolite m-CPP. Why m-CPP is not effective.

      P11 L3 Fig. 3 Fig. 3A and B? P11 L6 at 7 weeks of age? P12 L17 ~4 times, 4 times? Please state the exact value.

      Figure 7 Why are brain m-CPP levels higher than plasma levels? Is trazodone metabolized in brain tissue?

      P19 L7 ISRIB; please fully spell out the first time it appears.

      Referees cross-commenting

      Since the viewpoints of Reviewer 1 and Reviewer 2 are different, it would be a good report if both comments are satisfied.

      Significance

      What are the strongest and most important aspects?

      The author tested three potential drug candidates for MSS in MSS model mice in vivo. In addition, the author performed a PK study.

      What aspects of the study should be improved or could be developed?

      The description of the PK study is not sufficient to explain why the PK is different between the WT and the woozy mice is different.

      PeerReviewed
    3. EMBOpress 02 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      This study provides negative in vivo evidence for the use of two PERK inhibitors and of TUDCA for the treatment of Sli1-related Marinesco-Sjögren syndrome (MSS).

      Overall, the manuscript reports a substantial amount of work and the study could be published in its present format. The experiments are well described in terms of methodology and appropriate analysis has been applied. Claims are proportionate and not overstated

      I would have only minor comments related to some clarifications that the authors could make in the present manuscript and a suggestion for experiments that could improve the manuscript.

      First, although this is not my expertise, the in vitro analysis of CHOP luciferase assays suggests that very high concentrations, in particular of TUDCA, are needed to observe an effect. The authors may wish to clarify their opinion and whether this could be the reason why in vivo they have been unable to obtain any inhibition of the PERK pathway. Second, it seems to me that when measuring the Trazodone metabolism there is a difference between acute and chronic treatment. It would be worth discussing what the authors make of that and what is more relevant (I assume chronic) to the disease model outcome.

      With respect to the experiments a simple and informative addition would be the evaluation of the PERK pathway in mice treated with TUDCA, as this is missing.

      A more difficult but potentially more interesting line of investigation is that of searching for potential actions of Trazodone that are PERK independent and might be responsible for the partial rescue observed in the beam walking test, which is much more sensitive and specific than rotarod, so worth considering. Assuming authors want to go down this route and add significance to their study my suggestion would be an unbiased RNA seq from the brain samples they already have. However, this is a suggestion to steer the study towards a more positive outcome and it is not necessary to support their current conclusions.

      Significance

      My expertise is in the characterization of preclinical models of neurodegenerative diseases. This study is significant in the field because it reveals the complications arising when searching for non toxic PERK inhibitors for MSS. There is no current treatment for MSS and this study can help directing future studies towards more promising alternatives. Of course, providing only negative results is a limitation and the study would greatly increase its overall impact and significance if the effect of Trazodone would be further investigated.

      PeerReviewed
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    Genotype-specific differences in infertile men due to loss-of-function variants in M1AP or ZZS genes
    4
    1. EMBOpress 04 Jul 2024

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      Reply to the reviewers

      Reviewer #1 (Evidence, reproducibility and clarity):

      This manuscript compiles LoF variants of M1AP and ZZS proteins (i.e., SHOC1, TEX11 and SPO16) that almost certainly underlie infertility and reports the first case of an infertile man homozygous for a variant in SPO16. The authors validated interactions between human M1AP and ZZS that were found in mice. Analyzing testicular samples from infertile men revealed that those with deficiencies in SHOC1, TEX11 or SPO16 exhibited early meiotic arrest without haploid germ cells, whereas those with M1AP variants displayed a predominant metaphase I arrest with rare haploid germ cells. Further investigations showed that disrupted SHOC1, TEX11 or SPO16 led to defective synapsis and pairing of homologous chromosomes and unpaired DNA DSBs, while M1AP mutations reduced CO events. Importantly, men with LoF variants in M1AP can father healthy children by medically assisted reproduction. Overall, the results are clear and convincing in defining likely causative variants in infertility patients.

      Response: We thank reviewer #1 for the appreciation of our work. We already addressed the suggestions raised by reviewer# 1 to improve our manuscript.

      I have a few minor comments for improving the manuscript:<br /> • No statistical analyses were performed. The meaning of error bars was not mentioned. It is essential to specify the minimum number of seminiferous tubules counted for each patient.

      Response: We added the statistical analysis. We described now in more clarity that all round tubules in a patient's testicular section were counted (l. 646-653).

      • Allele frequencies of variants are not provided.

      Response: We added the allele frequencies from gnomAD v4.1.0 (SNVs) and gnomAD SVs v2.1 (CNVs) in Table 1.

      • Figure 4 should clearly label the representations of each color channel.

      Response: Thanks for this suggestion. We labelled each color channel accordingly.

      • The authors should clearly label the bands of SPO16 in the right panel of Figure 1B.

      Response: We labelled the SPO16 band in Figure 1B more clearly.

      • Appendix Figure S1B and S2B, what does "rat" mean in "rat Ins2 Ex3/4/"?

      Response: In the minigene assay, an artificial gene was constructed with exon 3 and 4 from the insulin 2 gene of the species rat (Rattus norvegicus). We described this in more detail in the Appendix methods section (l. 119) and in the Figure legend S1B and S2B.

      Reviewer #1 (Significance):

      Overall, this study significantly contributes to the understanding of some genetic causes of human infertility and offers a potential avenue to treat patients with M1AP variants/ mutants. Since no knock-in animal model was applied to mimic the subtle phenotype variations observed in patients, the functionality of truncated proteins remains unexplored. For example, it is unclear why the germ cells in patient M3260 with the SHOC1 variant can progress to round spermatids (Fig. 2C), while those in Shoc1 KO mice (10.1093/molehr/gaac015) and other patients cannot. However, this is a minor concern.

      Response: Thanks for this comment. SHOC1 variant c.1939+2T>C present in M3260 is a predicted splice site variant. In vitro it results in an in-frame exon skipping as shown by the minigene assay (Appendix Figure S2) that is predicted to lead to a loss of only 4% of the protein. We assume that this does not result in a complete loss but only in an impaired protein function enabling significantly reduced progression of spermatogenesis up to the round spermatid stage in few cells (l. 354-360). We addressed this in more detail in the results section (l. 145ff and l. 189ff) and in the Appendix Figure S2 legend. Accordingly, SHOC1 variant c.1939+2T>C is not a LoF variant and we excluded it from the quantification of subsequent analyses. Immunohistological staining of this patients was excluded from Appendix Figure S6, S7, S9, S10, and S11 and incorporated into Appendix Figure S2.

      In addition, the recurrent M1AP c.676dup was functionally analysed in our previous work (Wyrwoll et al., 2020, PMID: 32673564). We detected M1AP mRNA in a testicular biopsy from one patient showing that this variant leads not to degradation of the mRNA. Furthermore heterologous expression of the mutant M1AP cDNA in HEK293T cells led to the production of a truncated protein that presumably leads to loss of protein function. We added this information in l. 136. Furthermore, our preliminary experiments of co-immunoprecipitation of truncated M1AP with TEX11 hint to an abolished protein-protein interaction caused by M1AP c.676dup and thus a loss of protein function.

      Our field of expertise is gametogenesis and meiosis in mice.

      Reviewer #2 (Evidence, reproducibility and clarity):

      Summary:<br /> This interesting manuscript provides evidence for the biological and clinical relevance in human males of mutations in genes encoding M1AP and other related proteins. In mice, M1AP, "meiosis 1 associated protein," is known to associate with several proteins (SHOC1, TEX11, and SPO16) in the ZZS complex that promotes DNA recombination and crossover formation during meiosis I prophase. Mutation of these proteins in model organisms disrupts the process of recombination and cause arrest of spermatocytes prior to the first meiotic division. Here the authors took advantage of their MERGE (Male Reproductive Genomics) cohort to screen for human loss-of-function (LoF) mutations in the relevant ZZS complex and M1AP genes and to associate these with human male reproductive phenotypes. They found that men with deficiency of ZZS proteins SHOC1, TEX11 or SPO16 genes were infertile, exhibiting arrest of germ cell development early in meiotic prophase, with aberrations of chromosome synapsis and failure to repair DNA double-strand breaks (DSBs). In interesting contrast, men with M1AP mutations exhibited metaphase arrest, and indeed, in some cases, produced haploid spermatids, which in medically assisted reproduction (ICSI), led to the birth of offspring. Because they demonstrate that M1AP interacts with the other proteins, the authors conclude that M1AP is a "catalyzer," but not essential, for the processes of synapsis, recombination, and formation of haploid gametes.

      Major Comments:<br /> The work is clearly presented with detailed methods that should allow adaptation in other laboratories.<br /> Overall, this study is a tour de force with what was no doubt difficult archival samples. The histology is generally of good quality, supporting the conclusions about progress of meiotic prophase in the mutant samples. The images of H&E-stained tissue are particularly striking, especially those in supplemental figures.

      Response: We thank Reviewer #2 for the appreciation of our work and the suggestions to improve our manuscript. To provide transparency of our work, we plan to upload each (immuno-) histologically stained testicular section shown in the Main and Appendix Figures in the microscopy image repository OMERO/Open Microscopy Environment (OME).

      That said, and with particular reference to Fig. 3A, it is difficult to sub-stage meiotic prophase by immunocytochemistry, even in optimal samples, with only one marker (in this case gH2AX). The staging here is also at odds with the statement in the subsequent section (and Fig. 4B) on absence of pachytene cells in men with mutation of SHOC1, TEX11, or SPO16.

      Because precise stages of arrest probably cannot be determined in these samples, the authors would be wiser to use phrases such as "zygotene-like"

      Response: We agree with the reviewer that it is indeed difficult to sub-stage meiotic prophase based on IHC for one marker. A precise sub-staging of the meiotic prophase would require identifying the stage of the seminiferous epithelium. The cycle of the human seminiferous epithelium has been subdivided into 12 stages based on the acrosomal development made visible by immunohistochemistry for acrosin. However, in order to properly evaluate the human germ cell associations, only seminiferous tubules showing a well-preserved seminiferous epithelium with no apparent damage to the epithelium and the peritubular wall can be considered. In addition, all the different generations of germ cells have to be present as well as at least six spermatids (Muciaccia et al., 2013, PMID: 23946533). As these requirements cannot be fulfilled in the testicular tissue of men with a meiotic arrest as due to LoF variants in M1AP or the ZZS genes, we followed the reviewer's suggestion and have modified the respective phrases throughout the text, e.g. to 'zygotene-like'.

      The authors should also clarify how it was confirmed that the metaphase-like cells were spermatocytes and not spermatogonia (given that gH2AX signal is weak or unclear in some such nuclei). Readers with a focus on the more regularly staged mouse or rat tubules would appreciate a few more guidelines to criteria for staging human tubules.

      Response: We thank the reviewer for raising this point. In order to confirm that the metaphase-like cells were indeed spermatocytes we will perform additional IHC staining for γH2AX and MAGEA4 on sequential testis sections (distance 3 µm) on representative samples of the patient cohort as well as controls as the hosts of both antibodies are mice. For a few more guidelines on the criteria for staging human tubules, please refer to the response to the previous point.

      Evidence for the birth of a (healthy) child from one individual with M1AP mutation verges on the anecdotal (N=1). It is interesting but raises multiple questions and concerns about both the frequency of chromosomal abnormalities in such individuals and the transmission of the mutant alleles.

      Response: We understand very well, that the evidence based on N=1 seems to be sparse. Nevertheless, if it is in principle possible for a man affected by bi-allelic M1AP LoF variants to conceive a child by ICSI then it could be also possible for other couples with a similar genetic condition (M1AP LoF), and thus providing a proof-of-principle (l. 417f). Reviewer #2 is completely right with the concerns regarding chromosomal aberrations and the transmission of the mutant allele. Thus, it is essential for clinicians/geneticists to counsel the affected couple carefully about the small but existed chance to have a biological own child and the accompanied potential but so far unexplored risks as outlined in l. 435ff. Our future research project will address this open and highly relevant question.

      The authors conclude that the M1AP protein is an essential "catalyzer" in the meiotic recombination pathway. However, it is not clear from the data presented that M1AP in fact has enzymatic catalysis activity or exactly when and how it participates. Because the word "catalyzer" is not buttressed with hard or convincing evidence, the authors should consider other ways to describe the proposed role of M1AP, perhaps as a "putative component" and/or "modifier" of the recombination pathway.

      Response: We appreciate the reviewer's advice, and changed the wording to "functional enhancer".

      Minor comments:<br /> Fig. 1A - these are nice illustrations, but overly simplified with respect to timing (synapsis is not completed in zygonema)

      Response: We completely agree that Figure 1A is a simplified depiction that could not reflect the temporally and spatially highly complex processes of meiosis. By adding a second dotted box and describing the process in the Figure legend in more detail, we tried to reduce the simplification. Nonetheless, we believe that this simplified schematic help readers, who are less familiar with the progression of meiosis to contextualise the described processess.

      Fig. 1B - greater clarity in legend would be appreciated

      Response: We described Figure 1B in more detail.

      Figs. 2A & 3A - colors in bar graphs are difficult to discriminate

      Response: We improved the discrimination of bar graphs accordingly.

      Fig. 4A - with full appreciation for the difficulty with this material, the images are of low contrast and require considerable enlargement

      Response: We agree with this opinion; and we increased the contrast. In addition, we will improve the way of representation in a revised Figure 4 in the complete revision of the manuscript in accordance with the suggestions of all three Reviewers.

      Reviewer #2 (Significance):

      This is a very interesting paper, which I evaluated from the perspective of a reproductive geneticist with expertise in meiosis and interest in infertility. I think this report will be of interest to clinicians because it identifies a gene possibly linked to marginal fertility and establishes human protein interactions similar to those previously identified in mice. It reinforces the importance of ZZS genes in humans. The contributions of this report to the field of meiosis confirm previous evidence on M1AP, including mutant phenotypes and protein interactions, extending them to humans. We can thus appreciate the conserved function of the mammalian M1AP protein, but as yet the molecular mechanisms of M1AP are not clarified.

      Response: We gratefully thank Reviewer #2 for the thorough evaluation of our work and appreciate the recognition of the significance. Indeed, it was not possible to clarify the molecular mechanisms of M1AP that, hopefully, could be identified as soon as human specific antibodies, which will function in the needed applications, will be available. Additionally, we will perform further experiments as suggested by Reviewer #3 to gain a better understanding of the processess involved. Clarifying the underlying molecular mechanism is not only one of our highest interest but will also be important for the scientific community.

      Reviewer #3 (Evidence, reproducibility and clarity):

      In this manuscript, Rotte et al. investigate the meiotic molecular function in human of the M1AP protein and of the ZZS complex (SCHOC1, TEX11 and SPO16 proteins). The ZSS complex is a key player of meiotic recombination. It is a sub-complex of the conserved family of the ZMM proteins, essential for the formation of class I crossovers, a proper chromosomes segregation and fertility. Understanding its mode of action, regulation and conservation in human is thus a crucial issue in the fields of meiosis and human reproduction, with potential implications for patients. In that context, the recent identification of the protein M1AP as a partner of the ZSS proteins raise the question of its role, function and conservation. The aim of this study is thus of primary importance.<br /> To perform this molecular characterization, the authors made a cohort (24 total) of men carrying LoF variants in M1AP and ZSS genes. They performed a molecular biology analysis to assess the physical interaction between the human M1AP protein and the three components of the ZSS complex. Their results confirm a previous work performed in mice, mentioned by the authors.<br /> Then, they took advantage of available biopsies from different mutant men to perform a histological and cytological analysis of the impact of the different mutations on meiosis. The main conclusions are that in human, similarly to what is known in different organisms (ranging from yeast to mice), the ZSS complex is essential for crossover formation, synapsis and spermatogenesis, and that defect in the genes is associated with a premature prophase I arrest and no sperm formation. The authors also showed that M1AP protein plays a role in meiotic progression, but to a lesser extend compare to the ZSS proteins, with a metaphase I arrest, an undetectable recombination phenotype, apart of a reduced crossover number and, spermatozoa can form in its absence.

      Major points:<br /> The authors investigate the physical interaction between M1AP and the ZSS members through a single approach: Co-IP of tagged proteins after expression in human HEK293T cells. This approach is informative, but to reinforce the conclusions the authors should provide data from independent approaches: yeast two hybrid, expression of recombinant proteins followed by pull down, co-immunostaining (TEX11 antibodies were used in the study and M1AP antibody is present in the literature) are possible non-exclusive approaches to decipher, more in details, the interaction. Moreover, understanding the hierarchy of interactions appears important to understand its rational, regulation and function. What is the meaning of a M1AP interaction with all the members of the complex? Remains an open question.

      Response: We thank Reviewer #3 for this comment. In an independent approach we aimed to specify the interaction of M1AP to the ZZS proteins. Thus, we already cloned truncated versions of M1AP to refine the binding site of M1AP to the ZZS proteins (Figure R1). In a preliminary experiment, we co-transfected full-length as well as truncated forms of M1AP with TEX11 and showed via Co-IP that the interaction is only possible with full-length M1AP. Within the full-revision, we plan to finalise these experiments and thus validate the specifity of the interaction between M1AP and TEX11 and thereby gain more insight into the interaction/hierarchy of the interaction of M1AP with the ZZS complex.

      Figure R1 Tolerance landscape of M1AP NM_001321739.2 illustrating the respective regions selected for mutagenesis of truncated M1AP constructs. Adapted from MetaDome.

      Moreover, in the last couple of years, we spent enormous resources (personnel, time, financial) to get a functional antibody against human M1AP, including testing of different commercial (and already published) antibodies, creating three customised antibodies against different M1AP polypeptides, a nanobody raised against the complete M1AP protein (failed because of the impossibility to purify the protein), and contacting the authors of previously published customised M1AP antibodies (Arango et al., 2013/PMID 23269666 and Li et al. 2023/PMID 36440627). Figure R2 recapitulates some of our attempts. Moreover, we published the initial attempts of establishing an M1AP antibody in Wyrwoll et al., 2020/PMID 32673564. Unfortunately, no human M1AP-specific antibody is available.

      Additionally, we tested different TEX11, SHOC1 and SPO16 antibodies in immunohistochemistry and SHOC1 and SPO16 antibodies in immunofluorescence of spermatocyte spreads, which did not result in a specific staining (Figure R3). Due to the lack of a human specific antibody against M1AP as well as antibodies against SHOC1 and SPO16, we are not able to localise these proteins in patient testicular sections to address this highly interesting research question that remains of great interest within our work on M1AP.

      Figure R2. Attempts to locate M1AP in the human testis. Previous attempts to identify a commercially available antibody that reliably detects M1AP in the human testis have not been successful (Wyrwoll et al., 2020/ PMID 32673564). Accordingly, we tried to produce a human-specific antibody in cooperation with companies specified in antibody customisation (Eurogentec, Biotem). The last attempt, conducted with Biotem, is exemplarily shown in this figure. A. Human M1AP protein sequence (NP_620159.2) highlighting the antibody epitopes (orange) that were selected so that in men carrying the M1AP LoF variant c.676dup p.Trp226Leufs*4 in a homozygous state, the respective antibody should not be able to bind due to the protein truncation. For rabbit immunisation, both epitopes were pooled. B. HEK293T cells were transfected with DYK-tagged M1AP plasmids, either expressing the wildtype (WT) or the truncated protein (W226L). Sera of day (D) 28 and 42 of the immunised rabbit as well as the purified antibody product, a commercially available anti-M1AP antibody (HPA), and anti-DYK control antibody specificity was confirmed by Western blotting. C. Customised anti-M1AP antibody validation in human testicular control and D. M1AP-deficient tissue did not yield in a reliable staining. Various protocol optimisations were tested (different antigen retrieval, adapted blocking and antibody dilution solution, various primary and secondary antibody concentrations). Date shown represents the best result, respectively. The application of both sera and the purified antibody for spermatocyte spreading was tested in parallel and has not been successful either (data not shown). SC: Sertoli cells, SPC: spermatocytes, M-I: metaphase I cells, RS: round spermatids, ES: elongated spermatids. The scale bar represents 100 µm and 10 µm.

      Figure R3. Efforts to identify human-specific antibodies for ZZS localisation. A. Commercially available antibodies for ZZS were tested via Western blotting, aiming to reliably detect SHOC1, SPO16, and TEX11 in human testicular biopsies. HA-tagged wildtype plasmid DNA (WT) was transfected in HEK293T cells and the anti-HA antibody was used as a positive control. Only one antibody detected TEX11 reliable in the purified lysates (anti-TEX11: HPA002950). B.-D. Immunohistochemical staining was performed with all antibodies on human testicular and is representatively shown for anti-SHOC1: #BS155344-R, anti-SPO16: #BS15024-R, and anti-TEX11: HPA002950. Only the anti-TEX11 (#HPA002950) was found to be specific. However, presumably due to the fixation with Bouin's solution, staining could not reliably be repeated in all samples and was not implied in this study. Various protocol optimisations were tested (different antigen retrieval, adapted blocking and antibody dilution solution, various primary and secondary antibody concentrations). Date shown represents the best result, respectively. The application of all antibodies for spermatocyte spreading was tested in parallel and have not been successful (data not shown), except for anti-TEX11 (#HPA002950, Appendix Figure S13). SC: Sertoli cells, SPC: spermatocytes, RS: round spermatids, ES: elongated spermatids. The scale bar represents 100 µm and 10 µm.

      The ZZS mutants have a defect in gH2AX pattern, a defect in synapsis and no MLH1 foci, associated to apoptosis and prophase I arrest. M1AP mutation has a minor impact. The characterization of the effect of the different mutations (in particular M1AP) on the recombination process should be addressed further, by cytological means. For example, effect on strand invasion and ssDNA production should be monitored using RPA, DMC1 and RAD51 antibodies. The impact on alternative resolution pathway (e.g. BLOOM dependent) should be tested as well as the effect on other ZMM proteins, in particular MSH4-5, should be investigated. These experiments are essential to characterize, at the molecular level, the function of the different proteins during recombination.

      Response: We thank the reviewer for this suggestion and highly appreciate to investigate the different pathways in more depth. We plan to perform additional immunofluorescence staining of spermatocyte spreads of identified patients compared to the control in the planned revision for a better understanding of M1AP within human recombination. We already ordered the antibodies against meiotic marker proteins as suggested by the Reviewer.

      We would like to take the opportunity to refer to the extremely limited access to cryopreserved testicular material of the patients presented in this manuscript: for each gene (M1AP, SHOC1, TEX11, SPO16) we were lucky to get one testicular biopsy specimen from one man for only one preparation of spermatocyte spreads. We hope for the Reviewer's understanding that we cannot address each requested staining albeit this would be of highest interest. However, we are very confident that we will provide additional staining added to the yet shown to improve the understanding of M1AP's function on human male meiotic recombination.

      In the same line, TEX11 staining in M1AP mutant should be more documented and in particular the different stages shown, as well as the foci counting, to have a quantitative result, that can be compared to MLH1. Moreover, co-immunostaining of different markers with TEX11: RPA, DMC1, MSH and MLH1 are also important to understand how the pathway is perturbed and the recruitment delayed/affected.

      Response: In the planned revision, we will include the TEX11 foci counting using the acquired images that will be compared to MLH1 foci quantification. In addition, we plan additional co-immunostaining of TEX11 with different markers dependent on the availability of testicular material. Due to the limited resources of cryopreserved material, we cannot repeat the TEX11 staining in the patients with M1AP LoF variant for documentation of different stages. Slides that have already been stained are unfortunately bleached and cannot be re-analysed.

      The published M1AP antibody should be tested to investigate its perturbation in the absence of the ZZS proteins and the hierarchy of event.

      Response: As already outlined above, we tried to get any functional M1AP antibody for several years, which was not possible (Figure R2). Thus, we unfortunately cannot address this comment via this approach albeit this research question remains of great interest within our work on M1AP.

      OPTIONAL: the obligatory crossover was measured, a comment or calculation of interference would be very interesting, and it seems doable using the MLH1 counting, to test whether thses mutants have an effect on this process.

      Response: We thank Reviewer #3 for the suggestion of this interesting question that was not within our focus so far. Due to the limited material and the small number of cells from which we could digitally separate the chromosomes, we believe that the sample size is insufficient to obtain a statistically significant result.

      Minor comments<br /> As written, the title is misleading, the paper does not investigate the impact of M1AP in ZSS recombination. Such study implies to study genetic interactions or the genetic dependency between the different proteins, which is not the case here.

      Response: Thanks for this comment. We changed the title to "Genotype-specific differences in infertile men due to loss-of-function variants in M1AP or ZZS genes".

      Labelled on histological images is not clear. The authors should clearly explain to what marker each staining correspond.

      Response: We changed the labelling accordingly.

      L67 to 72: the authors should update and use more accurate citations for meiotic recombination.

      Response: Thanks for this suggestion. In this section, we have described the fundamental processes of meiosis, which have been repeatedly reviewed by renowned scientists. We have therefore chosen four well-cited expert reviews from different groups as references (PMID: 29385397, 24050176, 27648641, 35613017).

      L76: the ZMM are specifically involved in the resolution of class I crossover. Please rephrase.

      Response: We rephrased the sentence and changed it throughout the manuscript.

      L94: Strictly, the author identified an interaction, they didn't establish how the interaction takes place.

      Response: We rephrased the sentence.

      FigS13: TEX11 staining should be presented with foci counting as a main figure.

      Response: We plan to restructure Figure 4 along with the new meiosis specific markers and will consider this comment.

      L255: MLH1 does not quantify homologous recombination but, class I crossovers.

      Response: We rephrased the sentence.

      L352: The sentence is hard to understand, rephrase please.

      Response: We rephrased the sentence.

      Reviewer #3 (Significance):

      In general, the paper is well written and easy to follow. However, in light of the importance of the questions for the field of meiosis, it currently seems a little superficial, in particular if the authors aim at addressing the molecular function of the different proteins. The role of the ZSS proteins and M1AP in the control of meiotic recombination, at the molecular level is very important to decipher and additional experiments might help to better address this question. In addition, the functional links between M1AP and ZSS remains unclear and to investigate further.<br /> This study gives information for human process, and can be compared to more advanced work done with mice.<br /> This study will be important for the community working on meiosis in mammals, but also for people interested in reproduction.

      Response: We thank Reviewer #3 for the thorough evaluation and acknowledgment of the significance of our work. We appreciate the suggestion of performing additional experiments to gain a better and more in depth understanding of the molecular pathways involved. We hope for the Reviewer's understanding that we cannot address all raised comments due to the limited material and the difficulty to get human specific antibodies in a research field that primarily works with highly valuable mouse models.

      peerReviewed
    2. EMBOpress 04 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, Rotte et al. investigate the meiotic molecular function in human of the M1AP protein and of the ZZS complex (SCHOC1, TEX11 and SPO16 proteins). The ZSS complex is a key player of meiotic recombination. It is a sub-complex of the conserved family of the ZMM proteins, essential for the formation of class I crossovers, a proper chromosomes segregation and fertility. Understanding its mode of action, regulation and conservation in human is thus a crucial issue in the fields of meiosis and human reproduction, with potential implications for patients. In that context, the recent identification of the protein M1AP as a partner of the ZSS proteins raise the question of its role, function and conservation. The aim of this study is thus of primary importance.

      To perform this molecular characterization, the authors made a cohort (24 total) of men carrying LoF variants in M1AP and ZSS genes. They performed a molecular biology analysis to assess the physical interaction between the human M1AP protein and the three components of the ZSS complex. Their results confirm a previous work performed in mice, mentioned by the authors.

      Then, they took advantage of available biopsies from different mutant men to perform a histological and cytological analysis of the impact of the different mutations on meiosis. The main conclusions are that in human, similarly to what is known in different organisms (ranging from yeast to mice), the ZSS complex is essential for crossover formation, synapsis and spermatogenesis, and that defect in the genes is associated with a premature prophase I arrest and no sperm formation. The authors also showed that M1AP protein plays a role in meiotic progression, but to a lesser extend compare to the ZSS proteins, with a metaphase I arrest, an undetectable recombination phenotype, apart of a reduced crossover number and, spermatozoa can form in its absence.

      Major points:

      The authors investigate the physical interaction between M1AP and the ZSS members through a single approach: Co-IP of tagged proteins after expression in human HEK293T cells. This approach is informative, but to reinforce the conclusions the authors should provide data from independent approaches: yeast two hybrid, expression of recombinant proteins followed by pull down, co-immunostaining (TEX11 antibodies were used in the study and M1AP antibody is present in the literature) are possible non-exclusive approaches to decipher, more in details, the interaction. Moreover, understanding the hierarchy of interactions appears important to understand its rational, regulation and function. What is the meaning of a M1AP interaction with all the members of the complex? Remains an open question.

      The ZZS mutants have a defect in H2AX pattern, a defect in synapsis and no MLH1 foci, associated to apoptosis and prophase I arrest. M1AP mutation has a minor impact. The characterization of the effect of the different mutations (in particular M1AP) on the recombination process should be addressed further, by cytological means. For example, effect on strand invasion and ssDNA production should be monitored using RPA, DMC1 and RAD51 antibodies. The impact on alternative resolution pathway (e.g. BLOOM dependent) should be tested as well as the effect on other ZMM proteins, in particular MSH4-5, should be investigated. These experiments are essential to characterize, at the molecular level, the function of the different proteins during recombination.

      In the same line, TEX11 staining in M1AP mutant should be more documented and in particular the different stages shown, as well as the foci counting, to have a quantitative result, that can be compared to MLH1. Moreover, co-immunostaining of different markers with TEX11: RPA, DMC1, MSH and MLH1 are also important to understand how the pathway is perturbed and the recruitment delayed/affected.

      The published M1AP antibody should be tested to investigate its perturbation in the absence of the ZZS proteins and the hierarchy of event.

      OPTIONAL: the obligatory crossover was measured, a comment or calculation of interference would be very interesting, and it seems doable using the MLH1 counting, to test whether thses mutants have an effect on this process.

      Minor comments

      As written, the title is misleading, the paper does not investigate the impact of M1AP in ZSS recombination. Such study implies to study genetic interactions or the genetic dependency between the different proteins, which is not the case here.

      Labelled on histological images is not clear. The authors should clearly explain to what marker each staining correspond.<br /> L67 to 72: the authors should update and use more accurate citations for meiotic recombination.

      L76: the ZMM are specifically involved in the resolution of class I crossover. Please rephrase.

      L94: Strictly, the author identified an interaction, they didn't establish how the interaction takes place.

      FigS13: TEX11 staining should be presented with foci counting as a main figure.

      L255: MLH1 does not quantify homologous recombination but, class I crossovers.

      L352: The sentence is hard to understand, rephrase please.

      Significance

      In general, the paper is well written and easy to follow. However, in light of the importance of the questions for the field of meiosis, it currently seems a little superficial, in particular if the authors aim at addressing the molecular function of the different proteins. The role of the ZSS proteins and M1AP in the control of meiotic recombination, at the molecular level is very important to decipher and additional experiments might help to better address this question. In addition, the functional links between M1AP and ZSS remains unclear and to investigate further.

      This study gives information for human process, and can be compared to more advanced work done with mice.<br /> This study will be important for the community working on meiosis in mammals, but also for people interested in reproduction.

      peerReviewed
    3. EMBOpress 04 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      This interesting manuscript provides evidence for the biological and clinical relevance in human males of mutations in genes encoding M1AP and other related proteins. In mice, M1AP, "meiosis 1 associated protein," is known to associate with several proteins (SHOC1, TEX11, and SPO16) in the ZZS complex that promotes DNA recombination and crossover formation during meiosis I prophase. Mutation of these proteins in model organisms disrupts the process of recombination and cause arrest of spermatocytes prior to the first meiotic division. Here the authors took advantage of their MERGE (Male Reproductive Genomics) cohort to screen for human loss-of-function (LoF) mutations in the relevant ZZS complex and M1AP genes and to associate these with human male reproductive phenotypes. They found that men with deficiency of ZZS proteins SHOC1, TEX11 or SPO16 genes were infertile, exhibiting arrest of germ cell development early in meiotic prophase, with aberrations of chromosome synapsis and failure to repair DNA double-strand breaks (DSBs). In interesting contrast, men with M1AP mutations exhibited metaphase arrest, and indeed, in some cases, produced haploid spermatids, which in medically assisted reproduction (ICSI), led to the birth of offspring. Because they demonstrate that M1AP interacts with the other proteins, the authors conclude that M1AP is a "catalyzer," but not essential, for the processes of synapsis, recombination, and formation of haploid gametes.

      Major Comments:

      The work is clearly presented with detailed methods that should allow adaptation in other laboratories.<br /> Overall, this study is a tour de force with what was no doubt difficult archival samples. The histology is generally of good quality, supporting the conclusions about progress of meiotic prophase in the mutant samples. The images of H&E-stained tissue are particularly striking, especially those in supplemental figures. That said, and with particular reference to Fig. 3A, it is difficult to sub-stage meiotic prophase by immunocytochemistry, even in optimal samples, with only one marker (in this case gH2AX). The staging here is also at odds with the statement in the subsequent section (and Fig. 4B) on absence of pachytene cells in men with mutation of SHOC1, TEX11, or SPO16. Because precise stages of arrest probably cannot be determined in these samples, the authors would be wiser to use phrases such as "zygotene-like." The authors should also clarify how it was confirmed that the metaphase-like cells were spermatocytes and not spermatogonia (given that gH2AX signal is weak or unclear in some such nuclei). Readers with a focus on the more regularly staged mouse or rat tubules would appreciate a few more guidelines to criteria for staging human tubules.<br /> Evidence for the birth of a (healthy) child from one individual with M1AP mutation verges on the anecdotal (N=1). It is interesting but raises multiple questions and concerns about both the frequency of chromosomal abnormalities in such individuals and the transmission of the mutant alleles.<br /> The authors conclude that the M1AP protein is an essential "catalyzer" in the meiotic recombination pathway. However, it is not clear from the data presented that M1AP in fact has enzymatic catalysis activity or exactly when and how it participates. Because the word "catalyzer" is not buttressed with hard or convincing evidence, the authors should consider other ways to describe the proposed role of M1AP, perhaps as a "putative component" and/or "modifier" of the recombination pathway.

      Minor comments:

      Fig. 1A - these are nice illustrations, but overly simplified with respect to timing (synapsis is not completed in zygonema)

      Fig. 1B - greater clarity in legend would be appreciated

      Figs. 2A & 3A - colors in bar graphs are difficult to discriminate

      Fig. 4A - with full appreciation for the difficulty with this material, the images are of low contrast and require considerable enlargement

      Significance

      This is a very interesting paper, which I evaluated from the perspective of a reproductive geneticist with expertise in meiosis and interest in infertility. I think this report will be of interest to clinicians because it identifies a gene possibly linked to marginal fertility and establishes human protein interactions similar to those previously identified in mice. It reinforces the importance of ZZS genes in humans. The contributions of this report to the field of meiosis confirm previous evidence on M1AP, including mutant phenotypes and protein interactions, extending them to humans. We can thus appreciate the conserved function of the mammalian M1AP protein, but as yet the molecular mechanisms of M1AP are not clarified.

      peerReviewed
    4. EMBOpress 04 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript compiles LoF variants of M1AP and ZZS proteins (i.e., SHOC1, TEX11 and SPO16) that almost certainly underlie infertility and reports the first case of an infertile man homozygous for a variant in SPO16. The authors validated interactions between human M1AP and ZZS that were found in mice. Analyzing testicular samples from infertile men revealed that those with deficiencies in SHOC1, TEX11 or SPO16 exhibited early meiotic arrest without haploid germ cells, whereas those with M1AP variants displayed a predominant metaphase I arrest with rare haploid germ cells. Further investigations showed that disrupted SHOC1, TEX11 or SPO16 led to defective synapsis and pairing of homologous chromosomes and unpaired DNA DSBs, while M1AP mutations reduced CO events. Importantly, men with LoF variants in M1AP can father healthy children by medically assisted reproduction. Overall, the results are clear and convincing in defining likely causative variants in infertility patients.

      I have a few minor comments for improving the manuscript:

      • No statistical analyses were performed. The meaning of error bars was not mentioned. It is essential to specify the minimum number of seminiferous tubules counted for each patient.
      • Allele frequencies of variants are not provided.
      • Figure 4 should clearly label the representations of each color channel.
      • The authors should clearly label the bands of SPO16 in the right panel of Figure 1B.
      • Appendix Figure S1B and S2B, what does "rat" mean in "rat Ins2 Ex3/4/"?

      Significance

      Overall, this study significantly contributes to the understanding of some genetic causes of human infertility and offers a potential avenue to treat patients with M1AP variants/ mutants. Since no knock-in animal model was applied to mimic the subtle phenotype variations observed in patients, the functionality of truncated proteins remains unexplored. For example, it is unclear why the germ cells in patient M3260 with the SHOC1 variant can progress to round spermatids (Fig. 2C), while those in Shoc1 KO mice (10.1093/molehr/gaac015) and other patients cannot. However, this is a minor concern.

      Our field of expertise is gametogenesis and meiosis in mice.

      peerReviewed
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    Multiple independent losses of crossover interference during yeast evolutionary history
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    1. EMBOpress 04 Jul 2024

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      Reply to the reviewers

      Author responses

      __Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

      In their manuscript, Dutta and colleagues compared the meiotic recombination landscapes between five budding yeast species. In the first part of the work, the authors constructed a high-resolution map of meiotic recombination events in Kluyveromyces lactis supported by high-quality genome assemblies for two strains of this yeast. Then, partially repeating their CO and NCO mapping strategy, they compared a number of meiotic recombination parameters between the five species (sometimes three, depending on the quality of the data for each species). They particularly focused on key parameters for meiotic recombination, such as crossover interference and homeostasis and obligate crossover. Although the analysis is interesting, it is underdeveloped in many places and lacks the general conclusions regarding the evolution of recombination and the broader perspective that would be expected from a comparison of these phenomena in budding yeasts.

      [R] Tackling the evolution of recombination is ambitious. Here, with a dataset of five species, it is hard to draw strong evolutionary conclusions besides the variations in the crossover (CO) landscapes and the control of CO formation that we observed, which is already significant. The multiple losses of CO interference that we describe here may constitute our strongest evolutionary conclusion. It potentially underscores the minor evolutionary advantage associated to CO interference at least in budding yeasts. In this context, we changed the title to be more factual and updated the text to better highlight the significance and implications of our findings.

      Major comments:

      The authors indicate that the distribution of hotspots and coldspots is not preserved between species, but this finding is not properly documented. I think it would be useful to include recombination maps in a main figure for all species (or at least for S. cerevisiae, K. lactis and L. waltii) with the elements highlighted. This will allow for a visual illustration of the variability in the recombination landscape between the studied species. [R] The genomes of the species show blocks of synteny but overall, they are not collinear and therefore, it is not possible to have a direct comparison of the recombination maps. In our previous work, we have highlighted the non-conservation of CO hotspots between S. cerevisiae, L. kluyveri and L. waltii (Brion et al. 2017; Dutreux et al. 2023). Briefly, we retrieved conserved syntenic blocks in L. kluyveri and L. waltii genomes containing at least two S. cerevisiae orthologs associated with one hotspot. L. waltii shares only five out of the 92 S. cerevisiae crossover hotspots (RHO5, SLS1, GYP6, OLE1 and MRPL8), while L. kluyveri shares only one. L. waltii and L. kluyveri share no crossover hotspots. In addition, our current study shows that none of the K. lactis hotspot is conserved in any of the four other species (response figure 1 and new supplementary figure S11).

      Response Figure 1. Density of crossovers along the genome using a 5 kb window in the S. cerevisiae genome (Mancera et al. 2008; Oke et al. 2014; Krishnaprasad et al. 2015 combined dataset). Horizontal dotted green line represents crossover hotspot significance threshold. Solid spheres represent the conserved CO hotspots with either L. kluyveri (red) or L. waltii (blue). None of the 92 S. cerevisiae crossover hotspot is conserved in L. lactis.

      Although analyses analogous to those presented in Fig. S5 had already been published in other comparisons of the recombination landscape in yeast (e.g. Dutreux et al., 2023), I think that Figs. S5A and S5B are worth to be presented in the main figures (not supplementary data). In many species of eukaryotes, the detection of NCOs is practically impossible, therefore only results for COs are presented. Therefore, it is perhaps also worth discussing the fact that the relationship applies to all recombination events and not only COs, and therefore is related to the regulation of DSBs frequency and not individual DSBs repair pathways.

      [R] Figures S5A-B are now included in the main figure, Figure 2B. The association holds true for all total recombination (CO+NCO) events as well, new supplementary figure S6A.

      The authors find that CO coldspots were associated with DNA repair genes. Unfortunately, an equivalent analysis was not performed for all recombination events (CO + NCO). I presume this approach is based on the belief that COs are more mutagenic than NCOs. However, recent studies in humans suggest that, at least in mammals, meiotic DSBs themselves are mutagenic, regardless of the pathway used for their repair (Hinch et al., Science 2023). Therefore, I would suggest repeating the analysis also considering NCOs (although I am aware that the picture of NCOs may be incomplete). I would also like to see some graphical representation of the analysis. Is it possible to perform a classic analysis of coldspots/hotspot enrichment in relation to gene ontology?

      [R] As suggested, we performed the analysis to independently detect coldspots for all recombination events (CO+NCO). Based on a threshold of

      In relation to the previous point - it may be worth repeating this type of analysis also for other yeasts used in this study, or at least for S. cerevisiae, to be able to consider the extent to which this relationship is universal and dependent on the meiotic DSB repair pathway.

      [R] The analysis regarding the CO coldspots has been performed in the other species as well. As mentioned in the main text, although some overlap between CO coldspots and DNA repair genes has been observed in the other species as well, we observed a significant enrichment in K. lactis only, maybe because the dataset is larger than in the other species.

      In Fig. S7, the point where WGD occurred is marked in the wrong place, or at least that is what the sentence in the text says ("The Lachancea and Kluyveromyces species branched from the Saccharomyces lineage more than 100 million years ago, before to the ancestral whole-genome duplication (WGD) event specific of the S. cerevisiae lineage").

      [R] We regret the oversight and have corrected the figure.

      The result presented in Fig. S8 is interesting and should be shown in the main figures. Perhaps it would be worth adding an illustration illustrating simple versus complex COs.

      [R] The old Figure S8 is now a part of main Figure 2C-D with the illustrations describing the CO types.

      The last part of the results includes an analysis of the evolutionary rates of the ZMM genes. In the discussion, the authors should also refer the results of this analysis to the previous analysis of the overrepresentation of DNA repair genes in recombination coldspots. I understand that ZMM are not DNA repair proteins in the strict sense, but I think it is worth familiarizing readers with the authors' view on this matter. Moreover, I would suggest showing where MLH1 and MLH3 are located on the plot in Fig. 6 (especially the meiosis-specific MLH3), whether the selection pressure acts on them as on ZMM proteins, or rather as on DNA repair proteins. Showing the SLX4 and MUS81 would also be interesting.

      [R] Figure 6 has been updated as suggested and now shows the Mlh1, Mlh3, Slx4 and Mus81 dN/dS values for the three species.

      I feel like the discussion is underdeveloped. I missed a deeper summary of the comparison between meiotic recombination among the tested budding yeasts in the context of the presence and absence of functional ZMM. Even the title of the work is not properly developed in the manuscript text. The analysis shows that it is not the presence of a functional ZMM pathway or its lack that introduces differences between the individual recombination landscapes, although ZMM determines the presence of proper CO interference. With the caveat that for L. kluyveri it is basically unknown whether it has a functional ZMM or not. Maybe confirming the lack of expression of some ZMM genes in meiosis of this species would answer the question of how it should be treated?

      [R] We agree with this reviewer that our original title was imprecise, so we changed it to be more factual, emphasizing on the multiple losses of crossover interference in budding yeasts. As stated above, it potentially underscores the minor/negligible evolutionary advantage associated to CO interference at least in budding yeasts. From there, it is hard to draw deeper conclusions since the actual roles/functions of CO interference are still under debate, notably in yeasts where the CO frequency tends to be high. We improved the discussion to better highlight these points.

      We also agree that a deeper characterization of the ZMM factors persisting in the non-Saccharomyces yeasts would be informative, but we believe it is beyond the scope of the current manuscript and more suitable for a follow up work. However, our recent publication about L. kluyveri (Legrand et al 2024) shows that Zip3 is properly expressed in meiosis and behaves as in S. cerevisiaesince it is located at DSB sites. Furthermore, we have unpublished transcriptomic data (Response Figure 2) showing that all the ZMM genes from L. kluyveri are specifically induced in meiosis (fold increase >16 at least compared to pre-sporulation conditions). Therefore, so far, although the level of CO interference in L. kluyveri is minimal, there is no indication that the ZMM genes are mis regulated.

      Response Figure 2. Transcriptomic data showing that all the ZMM genes from L. kluyveri are specifically induced in meiosis (Unpublished data from Llorente Lab, CRCM, Marseille).

      Minor comments:

      In general, Figure captions are imprecise, many of them lack clear information explaining what is depicted. Authors should remember that figure legends should be self-sufficient. [R] The figure legends have been updated and are now self-sufficient.

      In the revised manuscript, I would suggest placing figure numbers on the figures and using line numbering, which would facilitate the reception of the work and possible reference to its individual elements in the review.

      [R] We regret the omission. Figure numbers, Line numbers and Page numbers have been added.

      Reviewer #1 (Significance (Required)):

      The study provides a new insight into the variation in recombination landscape within budding yeast species with a special emphasis on crossover control. This includes also de novo assemblies of Kluyveromyces lactis genome and high-resolution tetrad-based maps of meiotic recombination events. Previously, recombination maps of different yeast species were compared, however this study focuses on budding yeasts, some of which lost ZMM pathway and differ in some crossover parameters, like interference and homeostasis. Although the analysis is interesting, it lacks the general conclusions regarding the evolution of recombination and the broader perspective that would be expected from a comparison of these phenomena in budding yeasts.

      __Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

      This paper describes the genome-wide mapping of meiotic recombination in non-Saccharomyces yeast, Kluyveromyces lactis. By using heterologous parental strains, the authors mapped crossovers (COs) and noncrossovers (NCOs) on the genome of K. lactis which lacks proteins necessary for CO formation such as S. cerevisiae, mammals and plants. This is an extension of previous works by the authors' group which mapped CO and NCO in different yeast, Lachancea kluyveri and L. waltii by a similar approach. The authors found that CO frequencies in K. lactis are much lower than those in S. cerevisiae and COs showed weaker interference, which facilitates the non-random distribution of COs along a chromosome. Overall, the experiments and informatic analyses have been done in good quality and the results are convincing. The paper provides additional new information on the landscape of meiotic recombination in different yeast species. These results are of great interest to researchers in the field of meiotic recombination and evolution of meiosis. There are some issues that the authors may be able to address before the publication.

      Major points: While the authors noted that K. lactic shows the loss of a pro-CO factors (ZMM protein), Spo16, and Msh5 (due to the introduction of an in-frame stop codon), it still possesses other proteins such as Zip1, Zip2, Zip3, Zip4/Spo22, Mer3, and Msh4. It is still likely that these pro-CO factors control CO formation (and interference) in this yeast. It would be nice for the authors to study whether the knockout of these genes is dispensable for CO formation and interference in meiosis. A similar analysis should be done for L. kluyveri which retains all ZMM genes, but this is clearly out of the scope of this paper.

      [R] The question of the functions of the remaining ZMM factors is indeed interesting and related to point #8 from reviewer 1 (please see above). Although this is beyond the scope of our work, we would like to refer here to work from Amy McQueen's lab using L. lactis Zip1 in S. cerevisiae (Voelkel-Meiman 2015). This study shows that L. lactis Zip1 does not allow synaptonemal complex assembly in S. cerevisiae but allows CO formation independently of the Msh4/5 complex but that depend on Zip2/4/Spo16 and Mlh1/3 for their resolution. Overall, these results suggests that L. lactis Zip1 at least retained ancestral functions shared with S. cerevisiae Zip1. However, it is not possible to conclude if the lack of full complementation of L. lactis Zip1 in S. cerevisiae comes from functional divergence or simply by the inability of L. lactis Zip1 to function properly in a heterologous context.

      Minor points:

      No page number, no main Figure number. It is hard to review this paper. [R] We regret the oversight. Figure numbers, Line numbers and Page numbers have been added.

      References: In some cases, in the Introduction, the authors referred to review papers such as Pyatnitskaya et al. (2019) for ZMM proteins while in the other parts, they referred to original papers; for example, three papers for Mlh1-Mlh3. If the number of references is not limited, original papers should be cited in the text.

      [R] We regret this omission. Original papers have now been included in the citations.

      Figure 3A, page 9, second paragraph: When the authors compared CO and NCO densities, it would be nice to show P-values for the comparison.

      [R] p-values have now been added to the updated figure.

      Please show a ratio of CO to NCO in each yeast in Figure 3B in the second paragraph of page 9 in the main text.

      [R] The ratios have now been included in the figure for both the CO:NCO ratios and CO:corrected_NCO ratios, in the main text and figure legends.

      Figure S5 and page 7, the first paragraph and page 9, third paragraph: CO/NCO densities (negative correlation to chromosome sizes) in S. cerevisiae should be checked with or without short chromosomes (I, III, and VI), which show very unique regulation of meiotic DSB formation (see Murakami et al. Nature 2020).

      [R] Even excluding the small chromosomes, the size dependent trend persists for S. cerevisiae and S. paradoxus.

      Table S7: Please add the S. cerevisiae gene name such as ZIP1 next to S. cerevisiae orthologs such as YDR285W. Moreover, please explain the column in detail or clarify the data. What does "meiosis" mean here? For example, YJL074C is SMC3, which is expressed in mitosis as well as in meiosis. The same is true for YGL163C, which is RAD54, which plays a minor role in meiosis, but plays a critical in mitotic DSB repair.

      [R] We corrected Table S7 as desired by systematically including the standardized gene names.

      The Gene Ontology (GO) annotation is a statement about the function of a particular gene. It offers a structured framework and a comprehensive set of concepts to describe the functions of gene products across all organisms. It is specifically crafted to support the computational representation of biological systems. In our specific case, we only looked at genes with the gene ontology annotation "meiosis". Together, these statements comprise a "snapshot" of current biological knowledge and is by no means absolute. This has been detailed in the supplementary Table S7.

      Reviewer #2 (Significance (Required)):

      This study provides the landscape of meiotic recombination in non-Saccharomyces yeast, Kluyveromyces lactis. The genome-wide recombination map in K. lactis shows lower crossover frequencies with weaker crossover interference than those in S. cerevisiae. Overall, the experiments and informatic analyses have been done in good quality and the results are convincing. The paper provides additional new information on the landscape of meiotic recombination in different yeast species, particularly in terms of the evolution of meiotic recombination. These results are of great interest to researchers in the field of meiotic recombination and evolution of meiosis.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      Dutta et al. have compiled a genome-wide meiotic recombination map for Kluyveromyces lactis and compared it to a compilation of meiotic recombination maps for four other species, two of which (Lachancea kluyveri and Lachancea waltii), like K. lactis, predate the genome duplication event that produced the other two (Saccharomyces cerevisiae and S. paradoxus). Meiosis in many species studied (including metazoans and plants) shows control over the number and distribution of crossovers, which are critical for faithful chromosome segregation during meiosis. This takes the form of crossover interference, where crossovers are spaced more evenly than expected by chance, and crossover homeostasis, where many fewer chromosomes lack a crossover than is expected by chance. While both of the post-duplication species show both crossover interference and homeostasis, none of the pre-duplication species show crossover homeostasis, and crossover interference is very weak. In two cases (K. lactis and L. waltii), this can be explained by mutational loss of a few of the genes (called the ZMM genes) that promote meiotic crossovers in many species. However, L. kluyveribehavior cannot be explained in this way. Recombination hotspots are present but are not shared between the pre-duplication species or between the pre- and post-duplication species, perhaps not surprising for species that diverged more that 100 million years ago. Overall, this work will be a useful contribution to our understanding of the different possible flavors of meiotic recombination mechanisms and control that are possible (and, one might add, promote long-term species viability). A) Evaluation, reproducibility and clarity The work presented in this paper is straightforward and unimpeachable and will largely be of interest to those studying meiotic recombination, be it mechanistic studies or studies of the implications for population genetics. The analysis is technically correct, although there are some aspects where a slightly different emphasis should be considered (see comments below). However, the data and the analysis could stand as they currently are, without further revision.

      Suggestions are below. 1. (trivial) it would have been useful if pages and lines were numbered.

      [R] We regret the oversight. Figure numbers, Line numbers and Page numbers have been added.

      "Across the 205 meioses...". In general, it would be desirable to apply compensation for the fact that NCOs and COs are differently detected. Since, in K. lactis, 35% of COs are not accompanied by detectable gene conversion, it seems reasonable to apply a correction to measured NCOs here and throughout the paper, regardless of the species. For example, if one assumes that 35% of NCOs are not detected, how does this affect estimates of chromosomes that do not appear to have undergone interhomolog recombination? Estimates of CO/NCO bias? In a similar vein, if the CO event is not considered (just the conversion events associated with it), how does this affect measures of conversion tract lengths in COs and NCOs?

      [R] We thank the reviewer for this suggestion. We have performed the correction for the NCO estimates as described in Mancera et al. 2008, on a per tetrad basis across all the species. The fraction of missed NCOs were 7%, 34%, 30%, 23% and 25% respectively for S. paradoxus, S. cerevisiae, K. lactis, L. waltii and L. kluyveri. The fraction of missed NCOs depend upon the parental marker density. In addition, we performed the CO:NCO bias analysis both with the detected and the corrected NCO frequencies and the trends remain unchanged (Now included in figure 3). Finally, we refrain from using the corrected NCO frequencies while reporting the NCO frequencies (Table 1, main text) to maintain uniformity with our previous work and since, these corrections do not alter any results.

      It might be useful to report recombination event frequencies in terms of events/chromosome, as this, rather than event/unit distance, is functionally more relevant. In the same vein, it might be useful to consider total event homeostasis, in addition to just crossover homeostasis.

      [R] This has been updated as suggested. .

      An interesting observation is that two of the three pre-duplication species clearly at one time had a full complement of ZMM genes but lost some due to mutation. Have there ever been attempts to detect either synaptonemal complex or axial elements in these species?

      [R] This is related to point #8 from reviewer 1 and to the major point of reviewer 2 (please see above).

      To our knowledge, cytological observations of synaptonemal complex (SC) or axial elements have been performed in L. kluyverionly by us and the SC is clearly visible (Legrand et al 2024).

      However, it is key to remind here that K. lactis axis protein encoding genes HOP1 and RED1 have been cloned by the Roeder's lab by functional complementation of S. cerevisiae corresponding mutants, supporting the functional conservation of these genes (Smith and Roeder 2000). Finally, as mentioned above, K. lactis Zip1 retained at least some function of the ancestral Zip1 protein that are also shared by the S. cerevisiae protein (Voelkel-Meiman 2015).

      The observation of elevated evolutionary rates in ZMM genes is also intriguing, but it would help if "dN/dS ratio" was defined.

      [R] It is now defined in the text.

      The observation of frequent E0 chromosomes is taken to suggest efficient achiasmate segregation; has the "corrected" NCO frequency been considered? Do the different frequencies of E0 chromosomes predict the different spore viabilities seen between species?

      [R] E0 is not predictive at all of the spore viability as we have shown in previous studies (see L. kluyveri - Brion et al. 2017, L. waltii-Dutreux et al. 2023). In addition, this has been shown is S. cerevisiae as well (Nishant et al. 2009).

      Figure 3A-what would this look like if it were plotted as "Events per chromosome" rather than per megabase?

      [R] We changed the figure (now figure 2A) and plotted as events per chromosome to show the variability of events at the chromosome level.

      Figure legends tend to be unreasonably terse, which makes figures more difficult to interpret.

      [R] This has been updated as suggested.

      PeerReviewed
    2. EMBOpress 04 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Dutta et al. have compiled a genome-wide meiotic recombination map for Kluyveromyces lactis and compared it to a compilation of meiotic recombination maps for four other species, two of which (Lachancea kluveri and Lachancea waltii), like K. lactis, predate the genome duplication event that produced the other two (Saccharomyces cerevisiae and S. paradoxus). Meiosis in many species studied (including metazoans and plants) shows control over the number and distribution of crossovers, which are critical for faithful chromosome segregation during meiosis. This takes the form of crossover interference, where crossovers are spaced more evenly than expected by chance, and crossover homeostasis, where many fewer chromosomes lack a crossover than is expected by chance. While both of the post-duplication species show both crossover interference and homeostasis, none of the pre-duplication species show crossover homeostasis, and crossover interference is very weak. In two cases (K. lactis and L. waltii), this can be explained by mutational loss of a few of the genes (called the ZMM genes) that promote meiotic crossovers in many species. However, L. kluyveri's behavior cannot be explained in this way. Recombination hotspots are present but are not shared between the pre-duplication species or between the pre- and post-duplication species, perhaps not surprising for species that diverged more that 100 million years ago. Overall, this work will be a useful contribution to our understanding of the different possible flavors of meotic recombination mechanisms and control that are possible (and, one might add, promote long-term species viability).

      A) Evaluation, reproducibility and clarity

      The work presented in this paper is straightforward and unimpeachable, and will largely be of interest to those studying meiotic recombination, be it mechanistic studies or studies of the implications for population genetics. The analysis is technically correct, although there are some aspects where a slightly different emphasis should be considered (see comments below). However, the data and the analysis could stand as they currently are, without further revision. Suggestions are below.

      1. (trivial) it would have been useful if pages and lines were numbered.
      2. "Across the 205 meioses...". In general, it would be desirable to apply compensation for the fact that NCOs and COs are differently detected. Since, in K. lactis, 35% of COs are not accompanied by detectable gene conversion, it seems reasonable to apply a correction to measured NCOs here and throughout the paper, regardless of the species. For example, if one assumes that 35% of NCOs are not detected, how does this affect estimates of chromosomes that do not appear to have undergone interhomolog recombination? Estimates of CO/NCO bias? In a similar vein, if the CO event is not considered (just the conversion events associated with it), how does this affect measures of conversion tract lengths in COs and NCOs?
      3. It might be useful to report recombination event frequencies in terms of events/chromosome, as this, rather than event/unit distance, is functionally more relevant. In the same vein, it might be useful to consider total event homeostasis, in addition to just crossover homeostasis.
      4. An interesting observation is that two of the three pre-duplication species clearly at one time had a full complement of ZMM genes, but lost some due to mutation. Have there ever been attempts to detect either synaptonemal complex or axial elements in these species?
      5. The observation of elevated evolutionary rates in ZMM genes is also intriguing, but it would help if "dN/dS ratio" was defined.
      6. The observation of frequent E0 chromosomes is taken to suggest efficient achiasmate segregation; has the "corrected" NCO frequency been taken into account? Do the different frequencies of E0 chromosomes predict the different spore viabilities seen between species?
      7. Figure 3A-what would this look like if it were plotted as "Events per chromosome" rather than per megabase?
      8. Figure legends tend to be unreasonably terse, which makes figures more difficult to interpret.

      Significance

      This paper adds to our understanding of the spectrum of meiotic recombination behaviors that are possible, and thus is of interest primarily to those who study meiotic recombination. It expands significantly the number of species for which meiotic recombination has been analyzed, and in particular has the surprising finding that loss of crossover control by mutation of the existing crossover machinery is remarkably common, with four of the six yeast species (I include here Schizzosaccharomyces pombe) lacking crossover interference. It will be a substantial, solid contribution to the field.

      My expertise: meiosis, recombination, yeast, chromatin, chromosomes

      PeerReviewed
    3. EMBOpress 04 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      This paper describes the genome-wide mapping of meiotic recombination in non-Saccharomyces yeast, Kluyveromyces lactics. By using heterologous parental strains, the authors mapped crossovers (COs) and noncrossovers (NCOs) on the genome of K. lactics which lacks proteins necessary for CO formation such as S. cerevisiae, mammals and plants. This is an extension of previous works by the authors's group which mapped CO and NCO in different yeast, Lachancea kluyveri and L. waltii by a similar approach. The authors found that CO frequencies in K. lactics are much lower than those in S. cerevisiae and COs showed weaker interference, which facilitates the non-random distribution of COs along a chromosome. Overall, the experiments and informatic analyses have been done in good quality and the results are convincing. The paper provides additional new information on the landscape of meiotic recombination in different yeast species. These results are of great interest to researchers in the field of meiotic recombination and evolution of meiosis. There are some issues that the authors may be able to address before the publication.

      Major points:

      While the authors noted that K. lactics shows the loss of a pro-CO factors (ZMM protein), Spo16, and Msh5 (due to the introduction of an in-frame stop codon), it still possesses other proteins such as Zip1, Zip2, Zip3, Zip4/Spo22, Mer3, and Msh4. It is still likely that these pro-CO factors control CO formation (and interference) in this yeast. It would be nice for the authors to study whether the knockout of these genes is dispensable for CO formation and interference in meiosis. A similar analysis should be done for L. klyuveri which retains all ZMM genes, but this is clearly out of the scope of this paper.

      Minor points:

      1. No page number, no main Figure number. It is hard to review this paper.
      2. References: In some cases in the Introduction, the authors referred to review papers such as Pyatnitskaya et al. (2019) for ZMM proteins while in the other parts, they referred to original papers; for example, three papers for Mlh1-Mlh3. If the number of references is not limited, original papers should be cited in the text.
      3. Figure 3A, page 9, second paragraph: When the authors compared CO and NCO densities, it would be nice to show P-values for the comparison.
      4. Please show a ratio of CO to NCO in each yeast in Figure 3B in the second paragraph of page 9 in the main text.
      5. Figure S5 and page 7, the first paragraph and page 9, third paragraph: CO/NCO densities (negative correlation to chromosome sizes) in S. cerevisiae should be checked with or without short chromosomes (I, III, and VI), which show very unique regulation of meiotic DSB formation (see Murakami et al. Nature 2020).
      6. Table S7: Please add the S. cerevisiae gene name such as ZIP1 next to S. cerevisiae orthologs such as YDR285W. Moreover, please explain the column in detail or clarify the data. What does "meiosis" mean here? For example, YJL074C is SMC3, which is expressed in mitosis as well as in meiosis. The same is true for YGL163C, which is RAD54, which plays a minor role in meiosis, but plays a critical in mitotic DSB repair.

      Significance

      This study provides the landscape of meiotic recombination in non-Saccharomyces yeast, Kluyveromyces lactics. The genome-wide recombination map in K. lactis shows lower crossover frequencies with weaker crossover interference than those in S. cerevisiae. Overall, the experiments and informatic analyses have been done in good quality and the results are convincing. The paper provides additional new information on the landscape of meiotic recombination in different yeast species, particularly in terms of the evolution of meiotic recombination. These results are of great interest to researchers in the field of meiotic recombination and evolution of meiosis.

      I have been studying meiotic recombination. On the other hand, because of my limited experience, I can not evaluate bioinformatics parts in this paper.

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    4. EMBOpress 04 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      In their manuscript, Dutta and colleagues compared the meiotic recombination landscapes between five budding yeast species. In the first part of the work, the authors constructed a high-resolution map of meiotic recombination events in Kluyveromyces lactis supported by high-quality genome assemblies for two strains of this yeast. Then, partially repeating their CO and NCO mapping strategy, they compared a number of meiotic recombination parameters between the five species (sometimes three, depending on the quality of the data for each species). They particularly focused on key parameters for meiotic recombination, such as crossover interference and homeostasis and obligate crossover. Although the analysis is interesting, it is underdeveloped in many places and lacks the general conclusions regarding the evolution of recombination and the broader perspective that would be expected from a comparison of these phenomena in budding yeasts.

      Major comments:

      1. The authors indicate that the distribution of hotspots and coldspots is not preserved between species, but this finding is not properly documented. I think it would be useful to include recombination maps in a main figure for all species (or at least for S. cerevisiae, K. lactis and L. waltii) with the elements highlighted. This will allow for a visual illustration of the variability in the recombination landscape between the studied species.
      2. Although analyzes analogous to those presented in Fig. S5 had already been published in other comparisons of the recombination landscape in yeast (eg, Dutreux et al., 2023), I think that Figs. S5A and S5B are worth to be presented in the main figures (not supplementary data). In many species of eukaryotes, the detection of NCOs is practically impossible, therefore only results for COs are presented. Therefore, it is perhaps also worth discussing the fact that the relationship applies to all recombination events and not only COs, and therefore is related to the regulation of DSBs frequency and not individual DSBs repair pathways.
      3. The authors find that CO coldspots were associated with DNA repair genes. Unfortunately, an equivalent analysis was not performed for all recombination events (CO + NCO). I presume this approach is based on the belief that COs are more mutagenic than NCOs. However, recent studies in humans suggest that, at least in mammals, meiotic DSBs themselves are mutagenic, regardless of the pathway used for their repair (Hinch et al., Science 2023). Therefore, I would suggest repeating the analysis also taking into account NCOs (although I am aware that the picture of NCOs may be incomplete). I would also like to see some graphical representation of the analysis. Is it possible to perform a classic analysis of coldspot/hotspot enrichment in relation to gene ontology?
      4. In relation to the previous point - it may be worth repeating this type of analysis also for other yeasts used in this study, or at least for S. cerevisiae, to be able to consider the extent to which this relationship is universal and dependent on the meiotic DSB repair pathway.
      5. In Fig. S7, the point where WGD occurred is marked in the wrong place, or at least that is what the sentence in the text says ("The Lachancea and Kluyveromyces species branched from the Saccharomyces lineage more than 100 million years ago, before to the ancestral whole-genome duplication (WGD) event specific of the S. cerevisiae lineage").
      6. The result presented in Fig. S8 is interesting and should be shown in the main figures. Perhaps it would be worth adding an illustration illustrating simple versus complex COs.
      7. The last part of the results includes an analysis of the evolutionary rates of the ZMM genes. In the discussion, the authors should also refer the results of this analysis to the previous analysis of the overrepresentation of DNA repair genes in recombination coldspots. I understand that ZMM are not DNA repair proteins in the strict sense, but I think it is worth familiarizing readers with the authors' view on this matter. Moreover, I would suggest showing where MLH1 and MLH3 are located on the plot in Fig. 6 (especially the meiosis-specific MLH3), whether the selection pressure acts on them as on ZMM proteins, or rather as on DNA repair proteins. Showing the SLX4 and MUS81 would also be interesting.
      8. I feel like the discussion is underdeveloped. I missed a deeper summary of the comparison between meiotic recombination among the tested budding yeasts in the context of the presence and absence of functional ZMM. Even the title of the work is not properly developed in the manuscript text. The analysis shows that it is not the presence of a functional ZMM pathway or its lack that introduces differences between the individual recombination landscapes, although ZMM determines the presence of proper CO interference. With the caveat that for L. kluyveri it is basically unknown whether it has a functional ZMM or not. Maybe confirming the lack of expression of some ZMM genes in meiosis of this species would answer the question of how it should be treated?

      Minor comments:

      1. In general, Figure captions are imprecise, many of them lack clear information explaining what is depicted. Authors should remember that figure legends should be self-sufficient.
      2. In the revised manuscript, I would suggest placing figure numbers on the figures and using line numbering, which would facilitate the reception of the work and possible reference to its individual elements in the review.

      Significance

      The study provides a new insight into the variation in recombination landscape within budding yeast species with a special emphasis on crossover control. This includes also de novo assemblies of Kluyveromyces lactis genome and high-resolution tetrad-based maps of meiotic recombination events. Previously, recombination maps of different yeast species were compared, however this study focuses on budding yeasts, some of which lost ZMM pathway and differ in some crossover parameters, like interference and homeostasis.

      Although the analysis is interesting, it lacks the general conclusions regarding the evolution of recombination and the broader perspective that would be expected from a comparison of these phenomena in budding yeasts.

      PeerReviewed
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    Structure of the Pseudomonas aeruginosa PAO1 Type IV pilus
    4
    1. EMBOpress 03 Jul 2024

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      I thank the Referees for their...

      Referee #1

      1. The authors should provide more information when...

      Responses + The typical domed appearance of a hydrocephalus-harboring skull is apparent as early as P4, as shown in a new side-by-side comparison of pups at that age (Fig. 1A). + Though this is not stated in the MS 2. Figure 6: Why has only...

      Response: We expanded the comparison

      Minor comments:

      1. The text contains several...

      Response: We added...

      Referee #2

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    2. EMBOpress 03 Jul 2024

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript Ochner et al. report the 3.2 Å cryo-EM structure of the type IV pilus (minus PilY1 adhesin) from P. aeruginosa PAO1. The authors demonstrate that the conserved N-terminal helix of pilin subunits (PilA) form a tubular arrangement within the hydrophobic core of the pilus whereas the divergent C-terminal pilin globular domain decorates the periphery of the pilus. Comparisons are then made against T4P structures from other organisms, highlighting interesting differences including a shorter rod diameter and lack of solvent-accessible loops for which the authors propose reduces proteolysis of the T4P compared to other organisms.

      Major comments:

      The results of this manuscript are convincing. The models and cryo-EM volumes, which are already accessible from the PDB and EMDB, are of good quality with no obvious issues. The conclusions drawn from the model are not speculative. While extensive mutagenesis experiments could help delineate critical residues involved in T4P assembly and clarify involvement in adhesion/biofilm formation, these would have to be done in the native organism, would require a significant amount of time and effort, and would be beyond the scope of the current manuscript.

      Minor comments:

      The figures are excellent and clear, and the text is well-written, with results easy to interpret.

      One of the strengths of this paper is the comparative analyses across current bacterial T4P structures. In this respect, I would have liked a more thorough analysis here: - While differences in helical parameters, rod diameter, and rod length are presented, a figure showing comparison of surface electrostatics and/or hydrophobicity could help delineate differences (if any) across these species, which may reflect the different environments these bacteria inhabit.<br /> - A consurf representation of PilA is shown in Fig. 3h. It would be helpful to include either the sequence alignment used for this analysis or a sequence alignment for all the species presented in the manuscript, to show precisely which residues are absolutely conserved across these species.<br /> - A panel showing their full T4P as a surface with Consurf coloring would be informative to show conservation across the entire pilus and not just a PilA subunit. - The authors state that the models in Fig. 3 were aligned based on the matchmaker function in Chimera. Wouldn't the poor sequence conservation of the C-terminal globular domain of PilA drive the alignment towards the N-terminal helix? In that case, wouldn't using a comparative alignment strategy that focuses on the model itself (LSQ) or secondary structure elements (SSM) which would drive the alignment more towards the globular domain be more reflective of the full pilin subunit? - Related to the point above, it would be useful to include a table highlighting pairwise RMSDs across all models presented in this manuscript.

      Significance

      The authors rightfully highlight the importance of P. aeruginosa T4P in the development of biofilms; structural analyses of these pili are of clinical importance and of interest to researchers involved in bacterial motility.

      To date, various structures of T4P and T4P subunits across a variety of bacterial have been solved by X-ray crystallography and cryo-EM (PDB: 9EWX (this study), 6GV9, 5VXX, 6XXD, 6VK9, 8TJ2). It appears that another group has recently published a slightly lower resolution (3.6 Å vs 3.2 Å) cryo-EM structure (PDB: 8TUM) of the T4P of P. aeruginosa PAO1 (Thongchol et al., Science, 2024). The model from this latter publication appears to be identical to the model presented in this manuscript. Since this work has now been published (with models being released mid-March 2024), and since Ochner et al.'s manuscript only appeared on Biorxiv on April 9th 2024, I feel it would have been appropriate and necessary to cite this paper. And while the Thongchol publication reduces the novelty of Ochner et al.'s manuscript, there is some merit in the comparative analyses performed, which if expanded upon, could further strengthen this manuscript enough to stand on its own.

      Field of expertise: cryo-EM, bacterial secretion, membrane proteins

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    3. EMBOpress 03 Jul 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript by Ochner et al. reports the cryo-EM structure of the Type 4 pili of Pseudomonas aeruginosa at decent 3.2 resolution with fully resolved pilin fold. It is a straightforward report, using state-of-the-art microscopy and data processing approaches as usual for the group and the figures and data representation are clear. The main findings of the work is that it visualizes the assembled pilus of an important pathogen (Pseudomonas aeruginosa is one of the ESKAPE pathogens with particularly impressive adaptability and Type IV pili are important for substrate colonization and biofilm formation). The PilA pilin fold is not far from that of a previously crystallized isolated homolog from the PAK strain (core hydrophobic N-helix, globular b-sheet-containing exposed CTD) and presents a central melting of the core helix also observed among multiple other PilA homologs from solved G- pilin structures. The main difference for the PAO1 pilus is the tight packing in a significantly thinner filament, which lacks protruding loops or other secondary structure insertions in the core pilin fold. The authors propose that this could lead to increased stability such as to proteases.

      Again, the study is quite straightforward and besides the standard and well-executed EM workflow, it uses the classical approaches for pilus overexpression and purification (a PilT mutant that cannot retract and presents more T4P; well established mechanical shearing protocol for surface release, etc.). The structure is at decent resolution allowing full backbone tracing and side-chain resolution for confident model building, etc. The figures are clear, even if I would encourage some more vivid or at least contrasting colors for the cartoon model in Fig. 2 and some more detailed surface and conservation analyses, especially in terms of packing and surface exposure.

      Minor comment: The electron density maps, atomic models and validation reports should be available for the review process. The refinement statistics in the table are very good and the figures and supplementary movie present clear densities but this should be standard protocol and could help with constructive suggestions from the reviewers. Large map files, etc can be provided via a link if too big for upload directly through the manuscript tracking system.

      Significance

      My main concern with this work is that it is quite minimalistic in terms of biology/physiology, especially in light of the many G- pili structures available, some of which the authors nicely review in terms of specific structural parameters. The hypothesis of increased protease or perhaps mechanical resistance is tantalizing but how the compact pilus fold actually affects Pseudomonas aeruginosa in its physiology is unclear. Are there any other differences in the surface properties relative to other pili (charge, surface motif conservation, etc.) and could they have relevance in terms of interactions with the substrate, another matrix component or a peculiar niche within the host? As a PilA mutant should be easy to get from a number of laboratories, how would a Pseudomonas delta-PilA mutant behave in terms of twitching motility, surface attachment and biofilm formation if complemented with PaO1 PilA vs. other pilins from Table S2 or a pilin with an engineered hybrid architecture (e.g. a loop or b-hairpin insertion)? If such heterologous/engineered pili are incubated with a mild protease mix, would they indeed exhibit increased fragmentation relative to the wt PAO1 pili? To me, most of these assays are relatively easy to be attempted in terms of molecular biology, phenotypic assays and in vitro biochemistry (e.g. plasmid-based complementation if full genetics are judged beyond the scope/time available, twitching, pellicle formation, SDS-PAGE of protease-treated sheared pili) and could really shed more specific insights light into the peculiarities of Pseudomonas T4P function, rather than just present the next resolved filament among the multiple other T4P already out there.

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    4. EMBOpress 03 Jul 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      The study titled "Structure of the Pseudomonas aeruginosa PAO1 Type IV pilus" by Ochner and colleagues utilised cryo-electron microscopy (cryo-EM) to determine and describe the atomic structure of a complete type IV pilus (T4P) filament from Pseudomonas aeruginosa in its native state at an impressive resolution of 3.2 Å. The authors use state-of-the-art cryo-EM methodology, and the detailed description of their procedures allows for an adequate replication of the results. The T4P are essential for the virulence of P. aeruginosa, which is a clinically important human pathogen, as they play a crucial role in biofilm formation, a major factor in its resistance to antibiotics and ability to cause infections. Therefore, understanding the molecular mechanisms behind the ability of these bacteria to establish infections is vital, and this high-resolution structure of T4P provides valuable insight into this process.

      Overall, this reviewer acknowledges the importance of the structure presented here and its significance to our understanding of P. aeruginosa infection and persistence, and hence is positive about the publication of the results, however, at its current state the manuscript raises the major questions outlined below, which must be addressed and corrected.

      Major comments

      The authors propose a model where T4P interact with the type IV secretion systems (T4SS) in the P. aeruginosa membrane. However, there is no current evidence in the literature to support a direct interaction between T4P and T4SS as these are functional and structural distinct secretion systems. T4P biogenesis is mediated by a specialised secretion complex (homologous to type II secretion systems), spanning both bacterial membranes and consisting of the outer membrane secretin subcomplex, the alignment subcomplex, and the inner membrane motor complex. This reviewer recommends that authors refer to the comprehensive review by Hospenthal and colleagues [PMID: 28496159] that details the T4P biogenesis and Craig and colleagues [PMID: 30988511] that provides an in-depth analysis of T4P secretin architecture. This reviewer recommends the authors to remove any misleading claims regarding a T4P-T4SS interaction. Furthermore, the introduction would benefit from a brief overview of the T4P biogenesis and secretin architecture to prevent any further confusion. While this study offers a higher resolution structure of P. aeruginosa T4P (3.2 Å) compared to the previously described work on the P. aeruginosa T4P (8 Å) described by Wang and colleagues [PMID: 28877506], the manuscript fails to convey the significance of this improvement. The authors should directly compare the new structure with the previously obtained cryo-EM structure, similarly to how they tackled the comparison to the X-ray crystallography structure (Figure S6). A dedicated figure visualising the key differences and benefits associated with the higher resolution is necessary to highlight the manuscript's significance. Furthermore, the authors should specify that the reported T4P belongs to the type IVa category and the "globular domain" of PilA should be further differentiated into the αβ loop and D region - widely accepted motifs present in the structures of type IV pilins [PMID: 31784891]. Highlighting them is crucial due to their roles in receptor binding, microcolony formation, and antigenic variation, warranting their inclusion in the manuscript. A more detailed display of intersubunit interactions, including the types and numbers of interactions is also recommended, however optional. Previous studies [PMID: 27698424, PMID: 28609682] hypothesize that disordered loops might be involved in significant T4P stretching, the authors should address how the lack of these structures in their model might affect the filament dynamics. Lastly, the study lacks experimental validation of the structure, either within the study or referenced from the existing literature and very weakly connects the structure to T4P's biological functions, such as twitching motility or DNA acquisition. For instance, a comparison could be drawn between the surface charge of the pili and its DNA binding capacity. Additionally, the T4P secretin complex of P. aeruginosa documented in [PMID: 27705815] should be modelled alongside the obtained T4P structure to compare the structure diameter with the PilQ secretin lumen. These revisions will strengthen the manuscript by addressing crucial points and highlighting the significance of the high-resolution T4P structure.

      Minor comments

      Figure 2 For consistency, the colours of PilA subunits between panels (a) and (d) should match.

      Figure 3 For clarity, pilins should be coloured by domain.

      L41 The word "surfaces" or "target receptors" rather than just "substrates" would be more accurate.

      L87 Rather than "other bacteria" consider using "wild-type strains".

      L145-147 For clarity, residues C134 and C147 that form a disulfide bond in the C-terminal loop should be displayed in the figure.

      L371 For consistency, "h" should be in brackets, following the authors' style.

      Significance

      General assessment:

      The significance of the study stems from a resolution improvement from the previously reported type IV pilus of P. aeruginosa by Wang and colleagues [PMID: 28877506] and complements well the X-ray crystallography data obtained previously by Craig and colleagues [PMID: 12769840]. Due to the role of T4P in the virulence of P. aeruginosa, the structure provides important biological information about the molecular mechanism of its niche establishment. Moreover, the structure can be used in subsequent drug design against P. aeruginosa infections.

      Nature of advance:

      The nature of the advance provided by this study is in the added structural detail of the T4P due to the obtained higher resolution of the map. Usually, the highest resolution structure is used to derive the conclusions about the biological functions of the filament, hence the structure provided here will be referenced as the final P. aeruginosa T4P structure in further studies.

      Audience:

      The higher resolution structure compared to the previously described will be interesting to the translational/clinical drug discovery audiences, which require a high-resolution structure for accurate drug design.

      Field of expertise:

      Type IV secretion systems, bacterial conjugation, conjugative pili.

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    Caspase cleavage of Influenza A virus M2 disrupts M2-LC3 interaction and regulates virion production
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    1. EMBOpress 02 Jul 2024

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      Reply to the reviewers

      We thank the reviewers for their positive assessment of our manuscript. We agree that there are some further experiments suggested by the reviewers that would enhance our study. We have highlighted further proposed experimental work in bold for clarity.

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

      1. EVIDENCE, REPRODUCIBILITY AND CLARITY Summary: The Matrix 2 (M2) protein of influenza A virus (IAV) is a single pass transmembrane protein known to act as a tetrameric ion channel that is important for both viral entry and egress. The paper by Figueras-Nova et al. entitled "Caspase cleavage of Influenza A virus M2 disrupts M2-LC3 interaction and regulates virion production" reports on the regulation of IAV virion production through a regulatory interplay between a caspase cleavage site and a LC3 interacting region (LIR) motif in M2. In its C-terminal cytoplasmic tail the IAV M2 protein contains a C-terminal LIR motif interacting with LC3. The authors show that this LIR motif is preceded by a functional caspase cleavage motif cleaved predominantly by caspase-6, with some contribution from caspase-3: The motif 82-SAVD-85 directs cleavage after the aspartate (D) at position 85. The cleavage leads to loss of the remaining C terminal sequence from amino acid 86 to 97. The core LIR motif 91-FVSI-94 LIR motif is then lost from M2 which can no longer bind LC3. As previously described by the same group using point mutations in the LIR motif (Ref 12.), loss of a functional LIR., here by caspase- mediated deletion of the LIR, affects the virion production and inhibits filamentous budding. LC3B lipidation is increased upon treatment with a caspase inhibitor. The authors show for the first time that LC3 is included into IAV virions via binding to M2. Furthermore, they also report a co-crystal structure of the M2 C terminus (aa 70-97), containing the caspase cleavage site and LIR, and LC3B (aa 3-125) adding new insights into this interaction and showing that the caspase cleavage site is in a flexible region N-terminal to the LIR. This work shows how caspase cleavage may modulate LC3B lipidation, trafficking to the plasma membrane, incorporation of LC3B in the virions, filamentous budding and virion production (viral titer).

      Major comments: The findings reported here are very well supported by the data shown. This is a very clearly written paper with well described and nicely visualized results that are accompanied by adequate statistical analyses.

      We thank the reviewer for their assessment of our manuscript.

      The authors report a new way the LC3B binding to the C-terminal tail of the M2 proteins is regulated and suggest that this is an adaptation the virus has made to adjust virion production to host cell status by hijacking the function of host caspases. They show that the caspase cleavage motif is evolutionary conserved and use that as an argument. Perhaps it could be discussed if it also could be an argument that the host protects itself against a too massive virion production as this could be too detrimental to the host? Would it not also be an evolutionary advantage to the virus in the long run by avoiding killing the host?

      This is an interesting point. We agree there could be advantage for the virus not to overproduce virions under certain circumstances. Consistent with this caspase-6 deficient mice had increased mortality in response to IAV PR8 infection, and presented and increase in viral spread in the lungs (Zheng, 2021; doi: 10.1016/j.cell.2020.03.040). This is also relevant for the comments made by Reviewer 2. The manuscript will be updated to include a discussion of this point.

      A question I may raise which is optional as it may be too much work to address as part of this study is if the reported regulation of LC3B binding has any role in regulating the ion channel function of the M2 tetramer?

      It is well established that there is no impact of distal C-terminal truncations on M2 ion channel activity (Cady et al., 2009, doi: 10.1021/bi9008837 Schnell and Chou, doi: 10.1038/nature06531; Nguyen et al., 2008, doi: 10.1021/bi801315m; Tobler et al., 1999, doi: 10.1128/jvi.73.12.9695-9701.1999). This is also consistent with data from our lab (Ulferts et al., 2021, doi: 10.1016/j.celrep.2021.109899, Beale et al., 2014, doi: 10.1016/j.chom.2014.01.006) as well as others (Ren et al., 2015, doi: 10.1128/JVI.00576-15) showing the effects of the LIR motif and the proton channel are distinct. We appreciate the reviewer suggesting further work here as optional, but there is already compelling evidence to show there is no substantial effect of the LIR motif on ion channel activity. (See also Reviewer 2 points 4 and 5).

      Minor comments: Delete "with" in line 145.

      This will be changed in the updated manuscript.

      Line 217: It should be written more specifically how "cells were surface stained with M2"

      The protocol for surface staining of M2 will be explained in more detail in the updated manuscript.

      1. SIGNIFICANCE

      This is a very well performed study with a sound experimental strategy and well performed assays with clear results increasing our insight into the interplay between the Influenza A virus and host cells. Although caspase mediated cleavage of the autophagy receptor and signaling scaffold protein p62 (Ref. 25), removing the LIR and LC3-binding, has been reported before I consider this study as novel in reporting this type of regulation of LC3 binding. The cleavage of p62 deletes a large part of the protein while here it is a "clean" deletion of the LIR sequence representing a conceptual advance of regulation of LC3 binding. The study also reports for the first time on LC3B incorporated into virions. The effects on trafficking to the plasma membrane and viral budding and virion production are similar to those reported before (Ref. 12) using viruses with point mutations crippling the LIR motif. This research will be of interested to all studying virus- host interaction and to the autophagy field both as a non autophagic role of LC3B, and as a regulatory mechanism of LIR-LC3B interactions involving the irreversible caspase cleavage-mediated deletion of the LIR motif.

      We thank the reviewer for this assessment of our manuscript.

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

      The influenza A virus (IAV) M2 protein is small transmembrane protein which plays a role in virus entry and egress. In a previous study, Beale et al. (2014) identified an LC3-interacting region (LIR) in the M2 cytoplasmic domain that was found to recruit the LC3B protein to the plasma membrane. Recombinant IAV harboring mutations in the LIR motif showed reduced particle stability and lost filamentous morphology.

      In the present study, Figueras-Novoa et al. show that the LIR motif is removed in response to activation of cellular caspases. The authors demonstrate that in in IAV-infected THP-1 cells M2 is partially cleaved at the motif (82)SAVD(85)¯A by caspase 6. Caspase inhibitors abolished cleavage, and a mutant virus harboring the D85A substitution was found to be resistant to caspase action. A crystal structure of purified M2 C- terminus and LC3B revealed that the caspase cleavage site lies in a flexible region that is accessible to caspases.

      Mutant virus encoding a truncated M2 protein (M2D86-97) was unable to interact with LC3, in accordance with the absence of the LIR motif. The M2D86-97 mutant showed reduced lipidation of LC3, while enhanced lipidation of LC3 was observed when wild-type virus-infected cells were treated with caspase inhibitors. The authors also observed that cell surface transport of M2D86-97 but not M2-D85A was impaired. However, in purified virus particles a mix of cleaved and uncleaved M2 was detected. The authors also demonstrated that lipidated LC3B was present in purified virions of wild-type virus particles but even more abundant in M2-D85A virions. Finally, M2D86-97 mutants produced significantly less infectious particles compared to wild-type virus while the D85A cleavage mutant replicated to similar titers than wt virus.

      Based on these findings the authors concluded that caspases regulate the interaction of M2 protein with LC3 which impacts virion production. Specifically, they propose that caspase-mediated removal of the LIR motif may enable a switch between filamentous and non-filamentous budding in response to depletion of cellular resources. However, the authors were unable to rescue a filamentous IAV with a truncated M2 protein and therefore could not provide direct proof for their guess.

      While the data are sound and presented well, they do not support the conclusions of the authors.

      1. To the authors opinion, the conserved caspase cleavage site in the M2 protein might provide an evolutionary advantage for the virus. However, the M2-D85A mutation has no effect on viral replication, so the biological significance of why M2 needs to be cleaved at all is unclear. The conclusion that caspase-induced M2 cleavage is a fine-tuning mechanism of IAV has not been supported by experiments.

      We thank the reviewer for the assessment of our data. We think the reviewer is specifically objecting to the phrase “We conclude that this highly conserved interaction and cleavage act as a regulatory mechanism exploited by IAV to fine-tune virion production in different cellular contexts.” This is a reasonable inference from our results, but we accept that it is not proven. We will change the wording to make it clear this has not been definitively demonstrated.

      1. The finding that the permanently truncated IAV M2 mutant virus was substantially attenuated does not necessarily mean that abrogation of M2-LC3 interaction was responsible for this attenuation. As the M2 protein plays a role in virus budding at the plasma membrane (recruitment of M1 protein, induction of membrane curvature, membrane scission), the impaired transport of the truncated M2 protein might already explain that the virus was attenuated and that incorporation of the protein into the viral envelope was reduced.

      We will confirm this further with additional experiments using LIR mutants. Recapitulating the plasma membrane transport defect of truncated M2 with LIR mutants including the newly characterised M2D87A and M2D88A mutants and a more severe mutant with a FVSI_AAAA substitution would strongly imply this truncation mutant phenotype is due to the lack of LIR motif.

      1. It is also not clear whether the loss of the C-terminal 11 amino acids may have affected the interaction of the M2 protein with other proteins such as TRAPPC6A-delta (Zhu et al., 2017).

      This is a reasonable point, however Zhu et al., 2017 (https://doi.org/10.1128/jvi.01757-16) reported that the interaction with TRAPPC6A retains M2 intracellularly. If the phenotype observed with our truncation was due to the loss of interaction with TRAPPC6A, the opposite phenotype would be observed (more M2 in the plasma membrane with the truncated M2∆86-97 mutant). To address this point directly we will attempt to rescue an M2 mutant virus that has disrupted the reported TRAPPC6A binding site and assess M2 plasma membrane localization.

      The authors did not rule out whether the truncation of the M2 protein by 11 amino acids would have an effect on proton channel activity. Proton channel activity, however, might be important to preserve the metastable conformation of HA in the secretory pathway and might be also important for virus uncoating.

      M2D86-97 induced less LC3 lipidation than wild-type M2 or the D85A mutant. The remaining lipidation was attributed to the ion channel activity of the M2 protein. Can the authors rule out that the truncation of the M2 protein led to reduced ion channel activity which in turn led to reduced LC3B lipidation?

      We have addressed points 4 and 5 in response to Reviewer 1.

      The suggested role of caspase cleavage as a regulatory switch between filamentous and spherical virions (lines 304- 313) is highly speculative as long as the authors do not provide any experimental proof for it. The authors indicated that they were unable to rescue filamentous IAV with M2D86-97. However, would it be possible to use caspase inhibitors to test their hypothesis?

      We acknowledge that M2∆86-97 could not be rescued in a filamentous background. The use of caspase inhibitors would only increase the amount of full length M2 present, and does not provide an alternative strategy for increasing the proportion of truncated M2. However, since M2∆86-97 mutant could not be rescued, we will attempt to rescue additional LIR motif mutants to address this point. In particular, D87A and D88A mutants could be generated in a MUd background, as well as the F91S mutant.

      The authors used only the PR8 strain for their studies, a highly cell culture-adapted strain with spherical morphology. Are the findings obtained with this strain are also valid for others IAV strains?

      As we highlight in Figure 2I, both the caspase cleavage motif and LIR motif are highly conserved in human IAV strains. PR8 was used as it is the reverse genetic system in use and approved for use in the lab. We will attempt to address this by testing whether other IAV strains we are able to obtain also undergo caspase mediated cleavage of M2. If possible, we will obtain recent clinical isolates to show cleavage of M2 in a strain that has not adapted to cell culture.

      1. The authors mainly used the THP-1 cells for their studies, a human macrophage-like cell line. However, human IAV mostly replicate in epithelial cells of the respiratory tract and cause only abortive infections of macrophages. Why did the authors choose this cell line? Can the findings obtained with this cell line be translated to epithelial cells of the airways?

      THP-1 cells are widely used for the study of caspase activity. However, we also show M2 cleavage in MDCK cells and HAP1 cells. PR8 infection of A549 cells does not induce significant amounts of cell death in the infection time points used and, as caspase activation is linked to cell death, we did not observe M2 cleavage in this cell type. We will attempt to infect some epithelial cell types to confirm this phenotype.

      1. Minor issues:

      2. Fig. 1C: There seem to be quite some differences in the cleavage efficiency of M2 between panels A, B, C, and D? Any explanations?

      Different cell types (THP-1 cells and HAP1 cells) are used for the experiments mentioned above, which accounts for the different amount of M2 cleavage.

      • Fig. 1: Panel E: The labeling of the first amino acids as aa 76 seems to be wrong!

      We thank the reviewer for pointing this out, this will be corrected in the updated manuscript.

      Line 147: ...caspase mediated disruption of the M2-LC3 interaction (Fig 2A-B). Should be Fig. 2A-C.

      This sentence was referring to Figure 2A-B, as it refers to LC3B lipidation and not the coIP. This sentence will be changed in the text to reflect the intended meaning.

      • Growth kinetics of the various mutant viruses are missing?

      __We will provide growth kinetics for the relevant mutants _(M2D85A and M2∆86-97).___

      • Line 195: The authors speculate that aa85 is important for viral fitness: That should be demonstrated!

      This speculation is based on the very strong conservation of D85 in human IAV strains. The importance of D85 in viral fitness (permitting cleavage of M2) is only likely to be directly demonstrable in transmission models (for example ferrets) which is not feasible or justifiable.

      Reviewer #2 (Significance (Required)):

      Authors concluded that caspases regulate the interaction of M2 protein with LC3 which impacts virion production. Specifically, they propose that caspase-mediated removal of the LIR motif may enable a switch between filamentous and non-filamentous budding in response to depletion of cellular resources. However, the authors were unable to rescue a filamentous IAV with a truncated M2 protein and therefore could not provide direct proof for their guess. +<br /> +

      • As stated in the response to the comments above, we will attempt to rescue LIR mutant viruses (____D87A and D88A) in a MUd background which would provide further support for our hypothesis. Our data has significance for the understanding of the cell biology of influenza infection as commented on by Reviewers 1 and 3.

        • Reviewer #3 (Evidence, reproducibility and clarity (Required)): Summary : In this article, the authors identify a caspase cleavage site in the influenza A virus (IAV) Matrix 2 protein (M2) that leads to a truncated form of M2 deleted from its C-term LC3-interacting region (LIR). This cleaved form of M2 is seen and accumulates starting at 12 hours post-infection. IAV expressing M2 delta 86-97 mutant, corresponding to cleaved M2, seems to disrupt LC3B localization to cell plasma membrane upon infection. The authors also show that the IAV M2 delta 86-97 has a reduced viral titer compared to IAV WT. Overall the data are quite exciting where the authors identify the specific caspase responsible for the cleavage and show the residues of M2 necessary for LC3 interaction. However, some of the data showing the consequence of the cleavage for viral replication could be better clarified.

      We thank Reviewer 3 for their kind comments and we propose further experiments to clarify the consequences of cleavage.

      Major comments: - In Fig3A-B, the authors seek to demonstrate that the localization of M2 to the plasma membrane requires LIR motif. However, the representative images for cell infected with the delta 86-97 mutant show relatively few cell are expressing M2 raising questions of the infectivity of this mutant virus or if the overall expression of M2 in this assay is less for the delta 86-97 mutant. The authors should consider first quantifying the ratio of M2 cell surface staining over total M2 staining and second re-evaluate the representative images chosen.

      __We will include more examples of permeabilised cells in which comparable numbers of cells are M2 positive between mutants. We will also include high-content microscopy based quantification to support this. __To clarify, we confirm that the quantification of M2 intensity in the plasma membrane is carried out relative to the number of M2 positive cells, as the reviewer agrees is the most accurate way. To avoid confusion, we will update figure legends to describe more accurately the quantification process. A comparison between surface M2 and total M2 cannot be done on an individual cell basis, as once cells are permeabilized (to look for internal M2), robust differentiation between surface and internal M2 is difficult. The above clarification and additional data should provide the necessary support for our conclusions.

      • In fig3E, it is unclear what is being quantified in the graph as the legend and text lines 222-223 mention that spot intensity was measured but the y axis indicates LC3 relocalization intensity. Given LC3 is punctated particularly in the cytosol, It is unclear which spots of LC3 they are referring to. Based on the images shown, using a graph with LC3 surface staining as performed for M2 would clarify the data. The authors should clarify the reporting of these data in the results section. Additionally, the images of the control non-infected cells should be added to 3C.

      We agree with the reviewer on this point. The figure will be updated to describe more accurately what is being quantified. Additionally, images for uninfected cells in 3C will be added.

      • The data in Fig4 and FigS3 need to be strengthened to be conclusive. The volcano plot in FigS3A indicates that there is more LC3B and IAV proteins in M2 D85A than M2delta86-97. However in Fig4E, both LC3 I and LC3 II are increased in virions M2 delta 86-97 compared to M2 D85A which is opposite to the authors' conclusions in lines 244-245. In other words, the total amount of lipidated LC3 is higher in virions from IAV M2 without LIR motif than M2 with LIR. LC3II/I ratio in fig4F would suggest in virions containing M2 with LIR motif, LC3B II may be preferentially incorporated compared to virions containing M2 without LIR, which incorporates both LC3B I and LC3B II. Since this is a critical point made by the authors, performing a co-immunoprecipitation of M2 D58A and M2delta86-97 in the particles and then assessing for binding of LC3 I or II would bolster their conclusions.

      Figure 4F quantifies the ratio of LC3II to LC3I in infectious particles. Another two repeats used to quantify this ratio will be shown in addition, with a better representation of increased amounts of lipidated LC3II in M2D85A infectious particles, as well as an increased LC3II/LC3I ration in said particles when compared to M2∆86-97. Because of the low yield acquired from the purification of IAV virions, performing an IP would be difficult. Even if this were technically feasible it would not prove that M2 is binding LC3 inside the virion – we do not make this claim in our paper, merely that LC3B can be detected in the purified viral particles. We will clarify this point in the revised manuscript.

      • In Fig4J, even if statistically significant, the PFU difference between M2 D85A and M2 delta86-97 is minimal, performing growth curve assay would help appreciate this difference over time. In Thp1 cells, as the authors show caspase cleavage of M2 at time point 12h 14h 16hpi etc... (fig1), they should also show PFU data at these same time points for M2 mutant D85A compared to WT and M2 delta 86-97.

      We agree with the reviewer and indeed this was a point we attempted to make in our manuscript: Figure 4J shows a statistically significant difference between the titers. However, in the text we state that, even though statistically significant, the difference is much smaller than in other titer quantifications performed. Given the nature of a plaque assay, differences of less than a log fold cannot be considered as definitively indicating biological significance. We will clarify this in a revised manuscript. We will also provide the relevant growth kinetics (as per response to Reviewer 2).

      • The title of Fig4 and FigS3 and in text line 226 should be changed as M2 incorporation into virions is not shown and not described in the text. Plus, in figS3B, the authors show that between the M2 mutants, there is no difference in the abundance of M2 and other viral proteins compared to M1.

      The title of Figures 4 and S3 will be changed to more accurately reflect all of the points made by the figure.

      • In the image shown in Fig4H the number of plaques is higher for M2delta86-97 even though the size in smaller than M2 WT. Could the authors clarify in the text of the results section how they quantify PFU in their plaque assay and if they used a size criterion when quantifying the number of plaques?

      The images of plaques are taken at different dilutions, with the M2∆86-97 image belonging to two dilutions lower than the M2WT image. We will include the calculation used for PFU/mL, which does not take into account plaque size. Furthermore, images of the whole plate, showing plaqued serial dilutions will be shown.

      • In fig3B, the legend indicates 8 hpi but on the graphs it is 9 hpi.

      We thank the reviewer for pointing out this mistake. Both should read 8 hpi, this will be corrected in the new manuscript.

      Reviewer #3 (Significance (Required)):

      The authors demonstrated that IAV M2 binding to LC3 is regulated by caspase cleavage. The authors clearly identify the cleavage site and the caspase involved: caspase 6. The cleaved form of M2 seems relevant to IAV infection as it is accumulating after 12hpi. Using a M2 mutant D85A that cannot be cleaved by caspase 6 and truncated M2 mutant delta86-97 mimicking caspase cleaved M2, the authors are able to elegantly address the role of M2 cleavage. However, the importance of M2 caspase cleavage on IAV infection is not demonstrated. Eventually, addressing the impact of the caspase cleavage of M2 LIR motif on autophagy or CASM would be interesting. - Advance: conceptual. - Audience: basic research, specialized in virology, specialized in autophagy. - Field of expertise: virology, autophagy.

      We agree with the reviewer that we have made a conceptual advance in our understanding of the cell biology of influenza A virus infection. We have also determined the structure of the terminal part of the M2 tail in complex with LC3B. The biological importance of the phenotypes we show are most likely in transmission of the virus between hosts, which for IAV would require animal experiments outside the scope of this study. We have demonstrated regulation of the LIR motif by caspase cleavage in a variety of ways, using cell biological and biochemical methods. IAV is a very significant human and animal pathogen, and we believe we have made an important advance in describing a host-pathogen interaction of relevance for viral egress.

      PeerReviewed
    2. EMBOpress 02 Jul 2024

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

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      In this article, the authors identify a caspase cleavage site in the influenza A virus (IAV) Matrix 2 protein (M2) that leads to a truncated form of M2 deleted from its C-term LC3-interacting region (LIR). This cleaved form of M2 is seen and accumulates starting at 12 hours post-infection. IAV expressing M2 delta 86-97 mutant, corresponding to cleaved M2, seems to disrupt LC3B localization to cell plasma membrane upon infection. The authors also show that the IAV M2 delta 86-97 has a reduced viral titer compared to IAV WT. Overall the data are quite exciting where the authors identify the specific caspase responsible for the cleavage and show the residues of M2 necessary for LC3 interaction. However, some of the data showing the consequence of the cleavage for viral replication could be better clarified.

      Major comments:

      • In Fig3A-B, the authors seek to demonstrate that the localization of M2 to the plasma membrane requires LIR motif. However, the representative images for cell infected with the delta 86-97 mutant show relatively few cell are expressing M2 raising questions of the infectivity of this mutant virus or if the overall expression of M2 in this assay is less for the delta 86-97 mutant. The authors should consider first quantifying the ratio of M2 cell surface staining over total M2 staining and second re-evaluate the representative images chosen.
      • In fig3E, it is unclear what is being quantified in the graph as the legend and text lines 222-223 mention that spot intensity was measured but the y axis indicates LC3 relocalization intensity. Given LC3 is punctated particularly in the cytosol, It is unclear which spots of LC3 they are referring to. Based on the images shown, using a graph with LC3 surface staining as performed for M2 would clarify the data. The authors should clarify the reporting of these data in the results section. Additionally, the images of the control non-infected cells should be added to 3C.
      • The data in Fig4 and FigS3 need to be strengthened to be conclusive. The volcano plot in FigS3A indicates that there is more LC3B and IAV proteins in M2 D85A than M2delta86-97. However in Fig4E, both LC3 I and LC3 II are increased in virions M2 delta 86-97 compared to M2 D85A which is opposite to the authors' conclusions in lines 244-245. In other words, the total amount of lipidated LC3 is higher in virions from IAV M2 without LIR motif than M2 with LIR. LC3II/I ratio in fig4F would suggest in virions containing M2 with LIR motif, LC3B II may be preferentially incorporated compared to virions containing M2 without LIR, which incorporates both LC3B I and LC3B II. Since this is a critical point made by the authors, performing a co-immunoprecipitation of M2 D58A and M2delta86-97 in the particles and then assessing for binding of LC3 I or II would bolster their conclusions.
      • In Fig4J, even if statistically significant, the PFU difference between M2 D85A and M2 delta86-97 is minimal, performing growth curve assay would help appreciate this difference over time. In Thp1 cells, as the authors show caspase cleavage of M2 at time point 12h 14h 16hpi etc... (fig1), they should also show PFU data at these same time points for M2 mutant D85A compared to WT and M2 delta 86-97.

      Minor comments:

      • The title of Fig4 and FigS3 and in text line 226 should be changed as M2 incorporation into virions is not shown and not described in the text. Plus, in figS3B, the authors show that between the M2 mutants, there is no difference in the abundance of M2 and other viral proteins compared to M1.
      • In the image shown in Fig4H the number of plaques is higher for M2delta86-97 even though the size in smaller than M2 WT. Could the authors clarify in the text of the results section how they quantify PFU in their plaque assay and if they used a size criterion when quantifying the number of plaques?
      • In fig3B, the legend indicates 8 hpi but on the graphs it is 9 hpi.

      Significance

      The authors demonstrated that IAV M2 binding to LC3 is regulated by caspase cleavage. The authors clearly identify the cleavage site and the caspase involved: caspase 6. The cleaved form of M2 seems relevant to IAV infection as it is accumulating after 12hpi. Using a M2 mutant D85A that cannot be cleaved by caspase 6 and truncated M2 mutant delta86-97 mimicking caspase cleaved M2, the authors are able to elegantly address the role of M2 cleavage. However, the importance of M2 caspase cleavage on IAV infection is not demonstrated.<br /> Eventually, addressing the impact of the caspase cleavage of M2 LIR motif on autophagy or CASM would be interesting.

      • Advance: conceptual.
      • Audience: basic research, specialized in virology, specialized in autophagy.
      • Field of expertise: virology, autophagy.
      PeerReviewed
    3. EMBOpress 02 Jul 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      The influenza A virus (IAV) M2 protein is small transmembrane protein which plays a role in virus entry and egress. In a previous study, Beale et al. (2014) identified an LC3-interacting region (LIR) in the M2 cytoplasmic domain that was found to recruit the LC3B protein to the plasma membrane. Recombinant IAV harboring mutations in the LIR motif showed reduced particle stability and lost filamentous morphology.

      In the present study, Figueras-Novoa et al. show that the LIR motif is removed in response to activation of cellular caspases. The authors demonstrate that in in IAV-infected THP-1 cells M2 is partially cleaved at the motif (82)SAVD(85)A by caspase 6. Caspase inhibitors abolished cleavage, and a mutant virus harboring the D85A substitution was found to be resistant to caspase action. A crystal structure of purified M2 C- terminus and LC3B revealed that the caspase cleavage site lies in a flexible region that is accessible to caspases.

      Mutant virus encoding a truncated M2 protein (M286-97) was unable to interact with LC3, in accordance with the absence of the LIR motif. The M286-97 mutant showed reduced lipidation of LC3, while enhanced lipidation of LC3 was observed when wild-type virus-infected cells were treated with caspase inhibitors. The authors also observed that cell surface transport of M286-97 but not M2-D85A was impaired. However, in purified virus particles a mix of cleaved and uncleaved M2 was detected. The authors also demonstrated that lipidated LC3B was present in purified virions of wild-type virus particles but even more abundant in M2-D85A virions. Finally, M286-97 mutants produced significantly less infectious particles compared to wild-type virus while the D85A cleavage mutant replicated to similar titers than wt virus.

      Based on these findings the authors concluded that caspases regulate the interaction of M2 protein with LC3 which impacts virion production. Specifically, they propose that caspase-mediated removal of the LIR motif may enable a switch between filamentous and non-filamentous budding in response to depletion of cellular resources. However, the authors were unable to rescue a filamentous IAV with a truncated M2 protein and therefore could not provide direct proof for their guess.

      While the data are sound and presented well, they do not support the conclusions of the authors.

      1. To the authors opinion, the conserved caspase cleavage site in the M2 protein might provide an evolutionary advantage for the virus. However, the M2-D85A mutation has no effect on viral replication, so the biological significance of why M2 needs to be cleaved at all is unclear. The conclusion that caspase-induced M2 cleavage is a fine-tuning mechanism of IAV has not been supported by experiments.
      2. The finding that the permanently truncated IAV M2 mutant virus was substantially attenuated does not necessarily mean that abrogation of M2-LC3 interaction was responsible for this attenuation. As the M2 protein plays a role in virus budding at the plasma membrane (recruitment of M1 protein, induction of membrane curvature, membrane scission), the impaired transport of the truncated M2 protein might already explain that the virus was attenuated and that incorporation of the protein into the viral envelope was reduced.
      3. It is also not clear whether the loss of the C-terminal 11 amino acids may have affected the interaction of the M2 protein with other proteins such as TRAPPC6A-delta (Zhu et al., 2017).
      4. The authors did not rule out whether the truncation of the M2 protein by 11 amino acids would have an effect on proton channel activity. Proton channel activity, however, might be important to preserve the metastable conformation of HA in the secretory pathway and might be also important for virus uncoating.
      5. M286-97 induced less LC3 lipidation than wild-type M2 or the D85A mutant. The remaining lipidation was attributed to the ion channel activity of the M2 protein. Can the authors rule out that the truncation of the M2 protein led to reduced ion channel activity which in turn led to reduced LC3B lipidation?
      6. The suggested role of caspase cleavage as a regulatory switch between filamentous and spherical virions (lines 304- 313) is highly speculative as long as the authors do not provide any experimental proof for it. The authors indicated that they were unable to rescue filamentous IAV with M286-97. However, would it be possible to use caspase inhibitors to test their hypothesis?
      7. The authors used only the PR8 strain for their studies, a highly cell culture-adapted strain with spherical morphology. Are the findings obtained with this strain are also valid for others IAV strains?
      8. The authors mainly used the THP-1 cells for their studies, a human macrophage-like cell line. However, human IAV mostly replicate in epithelial cells of the respiratory tract and cause only abortive infections of macrophages. Why did the authors choose this cell line? Can the findings obtained with this cell line be translated to epithelial cells of the airways?

      Minor issues:

      • Fig. 1C: There seem to be quite some differences in the cleavage efficiency of M2 between panels A, B, C, and D? Any explanations?
      • Fig. 1: Panel E: The labeling of the first amino acids as aa 76 seems to be wrong!
      • Line 147: ...caspase mediated disruption of the M2-LC3 interaction (Fig 2A-B). Should be Fig. 2A-C.
      • Growth kinetics of the various mutant viruses are missing?
      • Line 195: The authors speculate that aa85 is important for viral fitness: That should be demonstrated!

      Significance

      Authors concluded that caspases regulate the interaction of M2 protein with LC3 which impacts virion production. Specifically, they propose that caspase-mediated removal of the LIR motif may enable a switch between filamentous and non-filamentous budding in response to depletion of cellular resources. However, the authors were unable to rescue a filamentous IAV with a truncated M2 protein and therefore could not provide direct proof for their guess.

      PeerReviewed
    4. EMBOpress 02 Jul 2024

      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

      Summary:

      The Matrix 2 (M2) protein of influenza A virus (IAV) is a single pass transmembrane protein known to act as a tetrameric ion channel that is important for both viral entry and egress. The paper by Figueras-Nova et al. entitled "Caspase cleavage of Influenza A virus M2 disrupts M2-LC3 interaction and regulates virion production" reports on the regulation of IAV virion production through a regulatory interplay between a caspase cleavage site and a LC3 interacting region (LIR) motif in M2. In its C-terminal cytoplasmic tail the IAV M2 protein contains a C-terminal LIR motif interacting with LC3. The authors show that this LIR motif is preceded by a functional caspase cleavage motif cleaved predominantly by caspase-6, with some contribution from caspase-3: The motif 82-SAVD-85 directs cleavage after the aspartate (D) at position 85. The cleavage leads to loss of the remaining C terminal sequence from amino acid 86 to 97. The core LIR motif 91-FVSI-94 LIR motif is then lost from M2 which can no longer bind LC3. As previously described by the same group using point mutations in the LIR motif (Ref 12.), loss of a functional LIR., here by caspase- mediated deletion of the LIR, affects the virion production and inhibits filamentous budding. LC3B lipidation is increased upon treatment with a caspase inhibitor. The authors show for the first time that LC3 is included into IAV virions via binding to M2. Furthermore, they also report a co-crystal structure of the M2 C terminus (aa 70-97), containing the caspase cleavage site and LIR, and LC3B (aa 3-125) adding new insights into this interaction and showing that the caspase cleavage site is in a flexible region N-terminal to the LIR. This work shows how caspase cleavage may modulate LC3B lipidation, trafficking to the plasma membrane, incorporation of LC3B in the virions, filamentous budding and virion production (viral titer).

      Major comments:

      The findings reported here are very well supported by the data shown. This is a very clearly written paper with well described and nicely visualized results that are accompanied by adequate statistical analyses. The authors report a new way the LC3B binding to the C-terminal tail of the M2 proteins is regulated and suggest that this is an adaptation the virus has made to adjust virion production to host cell status by hijacking the function of host caspases. They show that the caspase cleavage motif is evolutionary conserved and use that as an argument. Perhaps it could be discussed if it also could be an argument that the host protects itself against a too massive virion production as this could be too detrimental to the host? Would it not also be an evolutionary advantage to the virus in the long run by avoiding killing the host? A question I may raise which is optional as it may be too much work to address as part of this study is if the reported regulation of LC3B binding has any role in regulating the ion channel function of the M2 tetramer?

      Minor comments:

      Delete "with" in line 145. Line 217: It should be written more specifically how "cells were surface stained with M2" In the Introduction a description of what filamentous vs "spherical" budding is, could perhaps be included as I missed that reading through, although it comes in the end of the Discussion.

      Significance

      This is a very well performed study with a sound experimental strategy and well performed assays with clear results increasing our insight into the interplay between the Influenza A virus and host cells. Although caspase mediated cleavage of the autophagy receptor and signaling scaffold protein p62 (Ref. 25), removing the LIR and LC3-binding, has been reported before I consider this study as novel in reporting this type of regulation of LC3 binding. The cleavage of p62 deletes a large part of the protein while here it is a "clean" deletion of the LIR sequence representing a conceptual advance of regulation of LC3 binding.

      The study also reports for the first time on LC3B incorporated into virions.

      The effects on trafficking to the plasma membrane and viral budding and virion production are similar to those reported before (Ref. 12) using viruses with point mutations crippling the LIR motif. This research will be of interested to all studying virus- host interaction and to the autophagy field both as a non autophagic role of LC3B, and as a regulatory mechanism of LIR-LC3B interactions involving the irreversible caspase cleavage-mediated deletion of the LIR motif.

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    biorxiv.org/content/10.1101/2024.04.04.588074v1
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    Exploring the molecular composition of the multipass translocon in its native membrane environment
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    biorxiv.org/content/10.1101/2023.11.28.569136v1
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    Congress of multiple dimers is needed for cross-phosphorylation of IRE1α and its RNase activity
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    Recurrent Evolutionary Innovations in Rodent and Primate Schlafen Genes
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    1. EMBOpress 27 Jun 2024

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      The authors do not wish to provide a response at this time

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      Referee #3

      Evidence, reproducibility and clarity

      This study by Mordier and colleagues represents an in depth analysis to clarify the evolutionary history and processes of the rapidly evolving Schlafen gene family with a strong focus on primates and rodents.

      The study is of high quality in my opinion, though I do have some minor comments:

      1. Fig 2 and Fig 4B present inferred phylogenetic trees of schalfens in primates and rodents - these trees appear to be unrooted or rooted on a single species rather than an outgroup/gene. I suggest that the authors consider whether an outgroup gene could be included or if an outgroup free approach could be used to estimate the position of the root. This is important because the use of an unrooted tree to make inferences on gene family evolution has important implications - for example, there are no clades in an unrooted tree (Wilkinson et al 2007, Trends Ecol Evol).
      2. Schlafen proteins beyond mammals are referred to as SLFN11, it is not clear why this is the case because they seem to be co-orthologous to all mammal schalfen groups (except SLFNL1) based on supplementary figure S2. In this context, perhaps this image should form part of the main text?
      3. For blast searches parameters should be included - what cutoffs were implied for similarity searches etc. Related to this on line 120-121 homology is described as 'significant'. Homology refers to an evolutionary relationship, sequence similarity may be significant or not based on the search performed but homology is qualitative and simply detectable or not.
      4. The first results section describes the results of phylogenetic analyses, however this section relies heavily on what might better be considered interpretation of these analyses, this is great and should be included but I suggest that the branching patterns in the trees and bootstrap values supporting relationships between genes are also reported in the text to link interpretations to actual results.
      5. Bustos 2009 included viral genes belonging to the family in their analyses and I think it may be pertinent to do so here also to determine if the results are consistent or not.
      6. Was a rate heterogeneity (e.g. gamma rates / +G) parameter considered in phylogenetic analyses or model testing, it is not reported here and very rare for this not to improve model fit and phylogenetic accuracy.
      7. The authors state that all data are available in public databases, but this is not the case for the results they generated. Making various file types produced in this study would be good - e.g. alignments, phylogenetic tree files, structures, etc.

      Significance

      This study is an important step forward in clarifying our understanding of schalfen evolution. I think the manuscript will be of interest to a number of research areas, including gene family evolution because of its focus on an unusually rapidly evolving gene cluster and to those working on the schalfen gene families functional importance in development and immunity. The results may also draw interest from those interested in the confluence of protein structure, function, and evolution. My expertise In the context of this study is in the phylogenetics and evolution of rapidly evolving gene families.

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    3. EMBOpress 27 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      In the current manuscript, Mordier et al. combine bioinformatic searches, synteny, and phylogenetic analysis to reconstruct the duplicative history of the Schlafen Genes in rodents and primates and then use molecular evolution analyses in combination with structural modeling to make inferences regarding the role of natural selection in the evolution of this gene family. The study represents an update on Bustos et al. (2009), who had already presented evidence that Positive Darwinian selection was likely a factor in the diversification of these genes in mammals. In this context, the contribution of this paper is the identification of sites that are candidates to be evolving under natural selection, and the structural exploration of the location of these sites in the proteins. CODEML strength lies in the detection of signatures of positive selection at the codon level, but it is not that accurate when it comes to pinpointing the actual sites that might be under selection. Hence, without experimental data, these inferences remain speculative. The manuscript is well-written and represents an update on the evolution of this gene family.

      Major Issues

      The rationale for the choice of species included in the analyses is never presented, and some of it is hard to understand. Why do authors exclude the platypus but include non-mammalian lobe-finned vertebrates is not clear. If they are going to discuss the evolution of these genes outside mammals, the authors need to survey a much wider array of genomes. Even within mammals, there is little discussion on why some species were included and others not. I think that focusing the study on rodents and primates is OK, but I also think that providing a strong justification of the selection of species to include in the study and a tree that justifies splitting the focus on rodents and primates would also be important.

      In the trees in Figures 2 and 4, several genes considered as orthologs are not in monophyletic groups. These pattern aligns well with the birth-and-death model of gene family evolution, and has implications for their molecular evolution analyses. The authors need to address this issue explicitly. I would use topology tests to evaluate whether these deviations from the expected topology are significant. In addition, the relevant tests to report here are M8 vs M7 and M8 vs M8a. The M0 vs M1a comparison does not provide evidence for positive Darwinian selection. If the M8 vs M7 and M8 vs M8a tests are not significant, the inferences about sites evolving with dN/dS>1 are not really valid.

      CODEML can implements models that are designed to test patterns of gene family evolution, contrasting pre and post duplication branches, which I think would be of value in this family.

      Some analyses are described very succinctly, which would make replication challenging.

      Minor Issues

      Could 2R be responsible for the emergence of SLFN and SLFNL1?

      There are several minor issues authors should fix in a revised manuscript. In general, because results are presented before the materials and methods, I think it is easier for readers to have some of the information in the results section.

      They need to be consistent in using italics for species names as well as for capitalization.

      In the Alignment and maximum-likelihood phylogenies section the authors indicate that they used either Muscle or Mafft for the alignments. What was the rationale for picking one alignment over the other for a given gene? In this section, they also indicate the selected a best-fitting model of substitution using SMS, but then indicate that they used JTT for protein alignments and HKY for nucleotide alignments.

      How did the authors ensure that nucleotide alignments remained in frame?

      Significance

      I think this is a significant contribution to our understanding of the evolution of the Schlafen gene family. There are two key contributions here: the demonstration that gene conversion is a factor obscuring relationships among genes in this gene family, and the mapping of amino acids inferred be evolving under positive selection to structurally important residues of the proteins. These residues should be of interest for functional assays that evaluate the functional role of these proteins.

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    4. EMBOpress 27 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Mordier et al. used in-depth phylogenomic methods to analyze the evolution of the mammalian Schlafen gene family. They identified a novel orphan Schlafen-related gene that arose in jawed vertebrates, and they assigned orthology between Schlafen cluster paralogs. This will allow for further accurate selection studies. Throughout the entire manuscript, the authors use nomenclature predating structural and biochemical studies. The nomenclature is purely based on sequence similarities, which are sometimes very weak and not convincing, and not based on the known function of the protein. In my opinion, this causes confusion and does not help scientists in the field. Especially in Figure 3, I wouldn't call it RNAse E (AlbA); instead, tRNA recognition site,endoribonuclease domain, SLFN core domain are the correct domain designations. Since SLFN11 is not a GTPase, why do the authors name the domain GTPase domain? Actually, the SWADL domain comprises a SWAVDL instead of a SWADL sequence motif. Hence, I would name the domain SWAVDL domain instead of SWADL domain, which is, in my opinion, misleading and was wrongly chosen in initial publications.

      In e.g. Figure 3 SLFN11 structure it would be better if the authors illustrated the important residues concerning the known RNase active site and ssDNA binding site. Further, a close-up of the SLFN11 interface with labeled amino acids involved in the interaction and highlighting the residues undergoing positive selection would help understand the evolutionary adaptation.

      Although, according to Metzner et al., the SLFN11 dimer is built up by two interfaces (I and II), where Interface I is situated in the C-terminal helicase domain and Interface II in the N-terminal SLFN11 core domain. It would be helpful for the reader if the authors stuck to this already introduced and widely accepted nomenclature in the field.

      In addition to the antiviral function, SLFN11 expression levels have been reported to show a strong positive correlation with the sensitivity of tumor cells to DNA damaging agents (DDAs). Hence, SLFN11 can serve as a biomarker to predict the response to, e.g., platinum-based drugs. It was revealed that SLFN11 exerts its function by direct recruitment to sites of DNA damage and stalled replication forks in response to replication stress induced by DDAs. Could the authors include this different molecular function of SLFN11 in their discussion of SLFN11s evolution and positive selection?

      Even though it seems unclear from the genetic and evolutionary aspect (Figure 4), mouse Slfn8 and Slfn9 complement human cells lacking SLFN11 during the replication stress response and seem to resemble the function of SLFN11 (Alvi et al. 2023). The authors of this study claim that Slfn8/9 genes may share an orthologous function with SLFN11. Could the authors comment on that discrepancy?

      Significance

      In general, the work is well conducted and provides valuable new insights in an important and growing field of research. However, there are some limitations to the study including the disregard of known protein function (e.g. SLFN11) and the usage of a purely sequence similarity based nomenclature.

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    Translation inhibition efficacy does not determine the Plasmodium berghei liver stage antiplasmodial efficacy of protein synthesis inhibitors
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    Capsular Polysaccharide Restrains Type VI Secretion in Acinetobacter baumannii
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    1. EMBOpress 26 Jun 2024

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

      #1) Summary: The transport of effector proteins across membranes from the producing bacterium into a target cell is at the core of bacterial secretion systems. How an additional layer in form of a capsule affects effector export and the susceptibility towards effector import is not fully understood. Here, Flaugnatti and colleagues combined bacterial genetics with phenotypic assays and electron microscopy to demonstrate a dual role of a bacterial capsule in preventing T6SS-mediated effector export and promoting protection from effector import by another bacterium's T6SS. The wide variety of methods used, complementation of the mutants, and validation of the findings across strains strengthen the author's conclusions. Although the main conclusions seem straight forward, the authors unravel the unexpected complexity underlying these phenotypes with strong mechanistic work. In brief, a capsule-deficient mutant (∆itra) is shown to assemble its T6SS similar to the WT, yet secretes more Hcp than the WT and is better in T6SS-mediated killing of other bacteria. A capsule-overproducing mutant (∆bfmS) shows both, a partial deficiency in T6SS assembly and an additional reduction in exported Hcp, and is worse in T6SS-mediated killing than the WT. A mutant with a capsule similar to WT and deficient in cell sensing (∆tslA) forms the least T6SS apparatuses and is yet better in T6SS-mediated killing than the overcapsulated mutant. Together, these data show an effect of the capsule on (i) T6SS apparatus assembly, (ii) effector export, (iii) effector import, and (iv) the need for clearance of accumulating non-secreted Hcp by ClpXP. The work on a clinical isolate of Acinetobacter tumefaciens and the data on an impaired T6SS activity on other cells by antibiotic-induced capsulation is a strong demonstration of the work's clinical relevance in addition to the findings' conceptual novelty.

      • In my view, the manuscript is outstanding with very high quality of experimental data, very well written text and very clear presentation of the data in figures. A few minor comments and suggestions below that I think would strengthen the manuscript.*

      __ Authors’ reply #1: __We thank the reviewer for their enthusiasm.

      • *

      Major comment:

      #2) OPTIONAL: Fig. 4c/l. 320: Having an indirect effect of an antibiotic on T6SS activity by antibiotic-induced capsule formation is very intriguing and contributes to the clinical relevance of the overall findings. When I saw the data in Fig. 4c, the graph instantaneously reminded me of the panel in Fig. 2a, where a similar phenotype is observed by changing the predator:prey ratio in the absence of any antibiotic. The authors themselves comment on the possibility of antibiotic-induced, reduced predator growth (and thereby a change in predator:prey ratio) as a one factor impacting the phenotype here. I am wondering if this data could be strengthened or better disentangled to test more precisely if it is the antibiotic induced capsule formation per se that affects T6SS-mediated killing by A. baumanii in the presence of antibiotics. Would it help to take the bfmS mutant along as a control for direct comparison to see if antibiotic-induced capsule formation of the WT to similar levels of the mutant results in the same killing phenotype? Would it help to test for T6SS-mediated killing in the presence and absence of antibiotics at multiple predator:prey ratios? Could the effect of the antibiotic on A. baumanii growth be measured and considered when choosing the ratio at which the bacteria are mixed?

      __ Authors’ reply #2: __The point raised by the reviewer is very important. As we have stated in the manuscript, the capsule-induced production using antibiotics impacts the growth of A. baumannii and could therefore change the predator-prey ratio, potentially affecting the observed phenotype. However, the antibiotic is expected to equally impact the non-encapsulated ΔitrA strain, yet this strain maintains very strong T6SS killing activity in the presence of chloramphenicol. Thus, we do not believe the predator-prey ratio is causing the observed effect. To address this point more directly, we nonetheless propose to: i) repeat the experiments with different predator-prey ratios (1:1, 2:1, and 5:1), and ii) include a bfmS mutant as a control.

      Minor comments:

      #3) Figure 1D, l. 155, I might have missed this, do the authors happen to have the numbers of E. cloacae as well? This would strengthen the claim on A. baumannii survival because of E. cloacae is being killed.

      __ Authors’ reply #3: __The reviewer is correct; we did not include the survival of E. cloacae in the initial manuscript due to technical reasons (counter-selection of E. cloacae). However, we propose to repeat the experiment using an E. cloacae strain carrying a plasmid conferring kanamycin resistance. This will allow us to counter-select E. cloacae after contact with the A. baumannii predator to determine if E. cloacae is killed by A. baumannii in a T6SS-dependent manner.

      #4) Figure 2, I suggest to write out the species name of the prey in the box with the ratio. With E. cloacae being referred to in the previous figure and starting with similar letters than E. coli, I wasn't sure at first sight what E. c. refers to.

      __ Authors’ reply #4: __We appreciate the comment and will revise the figure as suggested.

      #5) use of the term "T6SS activity" throughout the manuscript (e.g. l. 182, l. 187). I leave this up to the authors. To me, it seems like an umbrella term for the initial observation and I see that such a term can be very handy for the writing. I just would like to mention that the use of the term was not always intuitive to me and sometimes even a bit misleading. For example, l. 182 refers to "increased T6SS activity". As a reader, I only know about 'T6SS activity on other cells' or 'a T6SS-mediated effect on other cells' at this point. T6SS apparatus assembly/firing activity is tested for specifically later and it turns out to differ between mutants. By the time the term is used in the discussion, it captures multiple nuanced phenotypes described by then. The more precise definition of the term in l. 200 helped to capture what exactly is meant by the authors.

      __ Authors’ reply #5: __We propose rephrasing the sentences to include the term "T6SS-secretion activity" when referring to Hcp secretion assays and "T6SS-mediated killing activity" when referring to killing experiments.

      __#6) __l. 198-199 "Collectively, our findings indicate that CPS does not hinder the secretion process of the T6SS or the consequent elimination of competing cells". I might be missing something, I cannot entirely follow this sentence. Didn't the authors just show that the CPS does hinder T6SS-mediated elimination of competing cells in panel 2A and less secreted Hcp in the encapsulated WT compared to the non-encapsulated mutant in panel 2B?

      __ Authors’ reply #6:__ We thank the reviewer for this comment. We realize that the sentence wasn’t well phrased, resulting in confusion. What we meant was that the T6SS is functional regarding its T6SS-mediated killing and secretion in the WT strain, while we also showed that the non-capsulated strain kills and secretes more T6SS material in the supernatant. Thus, there seems to be a balance between capsule production and T6SS activity in the WT. We will revise the sentence to better reflect this meaning.

      #7) l. 224, typo, "in"

      __ Authors’ reply #7:__ We will correct this typo. Thank you.

      • *

      #8) Two connected comments: l. 338, Just a thought, I am wondering about the title of the section. After reading it a second time, I think it is technically correct. When reading it first, I was a bit confused when getting to the data because apparatus assmebly is impaired in the capsule-overproducing strain and although "preserved", doesn't the data indicate that there is less T6SS assembly in the bfmS mutant and that this might be because of less cell sensing and isn't this a main point that there is a difference in apparatus assembly in the capsule overproducing strain compared to WT (other than no difference in apparatus assembly in the strain without capsule)? To me it seems not fully acknowledged as a finding in the interpretation of the data that less cells of the bfmS mutant have a T6SS apparatus. Isn't that interesting? A title along the lines of "Capsule-overproducing strain has preserved sensory function and assembles less T6SS apparatuses" would have been more intuitive for me. l. 352, In case I didn't miss a reference to this data earlier in the manuscript, I am wondering if it would be worth mentioning the finding on the reduced apparatus assembly of the bfmS mutant earlier, together with Figure 3 already. At least a sentence that mentions already that there is more coming later. When I got to this line in the manuscript and read the findings on the apparatus assembly, I first needed to go back to figure 3 and look at the data there again in light of this finding. It is mentioned here on the side but I think very important for the interpretation of the phenotypic data of the bfmS mutant shown earlier, isn't it? The tslA mutant is used beautifully here.

      __ Authors’ reply #8:__ We thank the reviewer for the suggestion and the kind comment about the beautiful usage of the tslA mutant. We will modify the title of the corresponding paragraph as suggested to make it more intuitive.

              Regarding the comment about mentioning the T6SS apparatus assembly defect in the *bfmS* mutant earlier, we respectfully disagree. While we agree that this point is important and can partially explain the difference in killing activity, we believe that showing it together with the *tslA* mutant (Figure 5) makes more sense and is easier for the reader to understand.

      #9) Discussion: optional comment. On the one hand, I like the concise discussion. On the other hand, I see more potential here for bringing it all together (potentially at the expense of shortening some of the introduction). I think the subtleties of the findings are complex. For example, I could envision a graphical summary with a working model on all the effects of a capsule on the T6SS and its potential clinical relevance making the study accessible to even more readers.

      __ Authors’ reply #9: __In the revised manuscript, we will include a graphical summary/model.

      Significance

      #10) General assessment: I consider the story very strong in terms of novelty, experimental approaches used, quality of the data, quality of the writing and figures of the manuscript. In my view, the aspects that could be improved are optional/minor and concern only one figure and some phrasing.

      • Advance: I see major advance in the findings (i, mechanistic) on the mechanism of how the capsule interferes with T6SS, (ii, fundamental) on the discovery of ClpXP degrading Hcp, and (iii, clinical) on the meaning of antibiotic treatment for the T6SS of this clinically relevant and often multi-drug resistant bacterial species, which strongly complements existing work on the T6SS and antibiotics in A. baumanii (e.g. of the Feldman group). As the authors write themselves, the starting points of the study of a capsule protecting from a T6SS and the effect of a T6SS on other cells being negatively impacted by a capsule were known, although not studied in one species and not understood mechanistically.*

      • Audience: I see the result of interest to a broad audience in the fields of bacteria-bacteria interactions, Acinetobacter baumanii, type VI secretion, antimicrobial resistance, bacterial capsules.*

      __ Authors’ reply #10: __We once again thank the reviewer and highly appreciate their positive and constructive feedback on our work. We hope the reviewer will be satisfied with the revised version of our manuscript.

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

      #11) In the manuscript by Flaugnatti et al., the authors provide clear evidence of the interplay between capsule outer coat production and the Type VI secretion system (T6SS) in Acinetobacter baumannii. The authors demonstrate that the presence of the capsule or the activity of the T6SS enhances survival against attacking bacteria. However, they also show that in their model bacterium, the (over)production of the capsule likely hinders T6SS dynamics, thereby reducing overall killing efficiency. Additionally, they reveal that the amount of the T6SS component Hcp is regulated in cells that can no longer assemble and/or secrete via the T6SS, presumably by the ClpXP protease. Overall, the experiments are well designed, and most conclusions are supported by the data and appropriate controls. I have however some suggestions that could further strengthen the manuscript prior to publication.

      __ Authors’ reply #11: __We are grateful for the reviewer’s enthusiasm and will implement their comments and suggestions in the revised version of the manuscript.

      Major comments:

      #12) Line 164. The authors use E. coli as prey to test the T6SS activity of A. baumannii. Why not directly use the E. cloacae strain (with or without T6SS) for this purpose? This would provide direct evidence that A. baumannii uses its T6SS to kill E. cloacae, thus confirming the authors conclusions in this section.

      __ Authors’ reply #12: __We thank the reviewer for this comment. We used E. coli to assess the functionality of the T6SS in different strains of A. baumannii, as it is commonly done in the T6SS field. However, as suggested by reviewer 1 (see comment #3) and in response to this query, we will also provide survival data of E. cloacae in the revised manuscript using a plasmid-carrying E. cloacae derivative that allows direct selection.

      #13) In Figure 2, the authors show that a non-capsulated strain kills more effectively and secretes more than a WT, but has a similar number of T6SS. They suggest in their conclusion that "the observed increase in T6SS activity in the non-capsulated strain suggests a compensatory mechanism for the absence of the protective capsule layer." This conclusion implies the presence of an "active" regulatory mechanism that would increase the number of successful T6SS firing events, which has not been demonstrated. Could it not simply be that the capsule blocks some shots that cannot penetrate and are therefore ineffective? This hypothesis is mentioned in lines 204-208. The authors should clarify the conclusion of this section. Given the challenge this may pose in A. baumannii, I suggest that the authors quantify the assembly/firing dynamics of the T6SS under WT and ΔitrA conditions. This would help distinguish between the two hypotheses explaining better firing in non-capsulated cells: i.e., if the number of assembled T6SS is the same in both strains (Fig 2C & 2D), do non-capsulated cells assemble/fire faster, indicating an adaptation in regulation, or do we observe the same dynamics, suggesting a simple physical barrier blocking the passage of certain T6SS firing events?

      __ Authors’ reply #13:__ We realize that the sentence, and more specifically the word "compensatory," might have been misleading and thank the reviewer for bringing this to our attention. What we meant to convey is that there is a balance between capsule production and T6SS activity; if disturbed, the balance shifts in one direction or the other. Specifically, there is more protection through the production of a thicker capsule (e.g., in the ∆bfmSmutant or under sub-MIC conditions of antibiotics, regulated by the Bfm system, as mentioned in the text) or more T6SS activity when less capsule is present (e.g., in the ΔitrA mutant, which we propose is caused by the lack of the steric hindrance). We will rephrase this sentence in the revised manuscript to better convey this message.

              Regarding the quantification of T6SS dynamic assembly/firing events between the capsulated (WT) and non-capsulated (ΔitrA) strains, we do not think this is required for this study, as the amount of secreted Hcp reflects the overall activity of the system. Importantly, we also do not have the technical means to quantify assembly/firing rates under Biosafety 2 conditions, as this requires specialized microscopes with very fast acquisition options (see, for instance, Basler, Pilhofer *et al.*, 2012, *Nature*). Indeed, very few labs in the T6SS field have been able to measure such rates.

      #14) Line 428-429. It is mentioned that the deletion of lon does not have a notable effect. However, I observe that the absence of Lon alone causes a more rapid degradation of Hcp in the cells compared to the WT strain (Fig 7B). How do the authors explain that the absence of this protease (whether under conditions of Hcp accumulation or not) increases the degradation of this protein in the cell? This explanation should be included in the manuscript.

      __ Authors’ reply #14: __That’s a fair point. We didn’t address this point further, as the deletion of lon didn’t resolve the issue of why Hcp is degraded. In fact, the opposite seems to be the case, as there is less Hcp in the ∆lon strain compared to the WT. While this observation is not directly relevant to the question of why Hcp is degraded late during growth in secretion-impaired strains, we will properly mention it in the revised manuscript.

              Please also note that a strong growth defect of a Δ*lon*Δ*clpXP* double mutant impaired further investigation in this direction.
      • *

      Minor comments:

      #15) Throughout the manuscript, the authors use the term "predator" to refer to A. baumannii. Predation is a specific phenomenon that involves killing for nourishment. To my knowledge, the T6SS has never been shown to be a predation weapon but rather a weapon for interbacterial competition, which is a different concept. If this has not been demonstrated in A. baumannii, the authors should replace the term "predator" with "attacker" (or an equivalent term) to clarify the context.

      __ Authors’ reply #15: __We thank the reviewer for this comment. The term “predator,” as highlighted by the reviewer, typically implies killing for nourishment/cellular products. In the context of T6SS, it facilitates the killing of competitors, releasing DNA into the environment that can subsequently be acquired through natural competence for transformation, as observed in species like Vibrio cholerae (our work by Borgeaud et al., 2015, Science) or other Acinetobacter species such as Acinetobacter baylyi (Ringel et al., 2017, Cell Rep.; Cooper et al., 2017, eLife). The acquisition of DNA reflects the killing for cellular products of the prey. As most A. baumannii strains are also naturally competent, this justifies the usage of the predator and prey nomenclature.

              Apart from this fact, it seems to be a matter of nomenclature, with many papers in the field using one term or the other. Yet, ultimately, this doesn’t change any of the scientific findings. Therefore, to satisfy the reviewer, we will change “predator” to “attacker” throughout the revised manuscript.

      #16) Line 274. Since the authors stated that in the Wzc mutant, the capsule is "predominantly found in the supernatant and only loosely attached to the cell," this result is not unexpected. This finding is also consistent with the previous results from Fig. 3A & B, which show sensitivity to complement-mediated killing and the weak amount of (ab)normal CPS produced in that strain, further confirmed by Fig. 3E.

      __ Authors’ reply #16__: We fully agree with the reviewer’s suggestion and will remove the statement.

      #17) Line 299. The authors speculate that "... T6SS may deploy through gaps akin to arrow-slits in the capsule's mesh...". However, this is very unlikely since a WT strain kills (Fig. 3C) and secretes (Fig. 2B & 3D) less effectively than the itrA mutant, suggesting that the T6SS is not assembled in the "right places" devoid of CPS; otherwise, we would expect similar T6SS activity. Based on the results in Fig. 2 (and my earlier comment), this implies that A. baumannii assembles its T6SS randomly, and in the presence of the capsule, its shots would need to be in the right place to penetrate the envelope and reach the target. Could the authors comment on this point and provide a model figure to better visualize the interplay between the capsule and T6SS under the three major conditions: WT, non-capsulated, and capsule overproduction?

      __ Authors’ reply #17: __We thank the reviewer and agree with their comment. We discussed the hypothesis of T6SS deployment through gaps, drawing a parallel to what was proposed for biofilm and T6SS in V. cholerae(Toska et al., 2018, PNAS). However, as mentioned earlier, we believe that the effect of the capsule on T6SS activity is primarily due to steric hindrance, which increases the distance between the T6SS apparatus and the prey cell. To clarify our findings further, we will include a model summarizing our results, as requested by reviewer 1 (see comment #9).

      __ #18)__ In Fig. 5A, the microscopy panels should be adjusted to the same dynamic range as the WT (which represents a true signal), which does not appear to be the case for the tlsA mutant panel for instance. The image gives the impression of a large amount of free TssB-msfGFP in the cytoplasm. However, this effect is due to the dynamic range being adjusted to display a signal. This observation is consistent with the fact that the amount of TssB-msfGFP protein is identical across all strains (Fig. S2F).

      __ Authors’ reply #18: __We will adjust the images to the range of the WT in the revised manuscript, as suggested. However, regardless of how these images are presented, the enumeration of T6SS structures will remain unchanged, which was the sole point of this experiment.

      • *

      #19) Unless I am mistaken, the authors do not comment on the fact that in a ΔbfmS strain, the number of T6SS is halved compared to a WT or ΔitrA strain. If capsule overproduction only partially limits the TslA-dependant T6SS assembly, how can this result be explained? Is it related to the degradation of Hcp in this background, which ultimately limits the formation of T6SS? If so, it would be interesting to mention this connection in the section "Prolonged secretion inhibition triggers Hcp degradation”

      __ Authors’ reply #19: __We did mention that the T6SS assembly of the ΔbfmS mutant is reduced compared to the WT (or ΔitrA), likely due to the defect in sensing the prey (lines 369-374 and 468-472 of the initial manuscript). However, we will revise the sentence to improve clarity in the revised version of the manuscript.

      Significance

      #20) This work is highly intriguing as it not only delves into the specific mechanisms involved but also connects fundamental elements in bacterial competition, i.e., the necessity for self-protection and aggression for survival. The manuscript offers valuable insights into cellular dynamics at a microscale level and prompts new inquiries into the regulation of these systems on a population scale. The work is well-done and the writing is also clear. I am convinced that this work represents another significant step towards understanding bacterial mechanisms and will undoubtedly spark considerable interest in the field.

      __ Authors’ reply #20: __We sincerely thank reviewer #2 for their constructive inputs, which will improve our manuscript.

      • *

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

      #21) The manuscript by Flaugnatti et al investigates the relationship between functions of the T6SS in A. baumannii and production of capsular polysaccharide. The manuscript argues that (1) capsule protects A. baumannii against T6SS-mediated attack by other bacteria, (2) capsule also interferes with the bacterium's own T6SS activity, and (3) the T6SS inner tube protein Hcp is regulated by degradation by ClpXP. The main critiques regard the first two conclusions, which seem to be based solely on use of a mutant that has a confounding effect as described below; and to strengthen the third claim by further exploring the results of overexpressing Hcp and by determining whether there is a fitness benefit for Hcp regulation.

      __ Authors’ reply #21: __We thank reviewer #3 for their relevant input. We will conduct additional experiments based on their comments, and these will be incorporated into the revised manuscript.

      • *

      __Main items:____ __

      #22) Throughout the paper, an itrA deletion mutant is used as the capsule-deficient strain and conclusions are drawn about role of capsule based on this mutant. However, itrA deletion also eliminates the protein O-glycosylation pathway (Lees-miller et al 2013), a potential confounder. Analysis of mutants specifically deficient in the high-molecular weight capsule but not protein glycosylation, and/or mutants in the protein o-glycosylation enzyme, should be incorporated into the study to enhance the ability to make conclusions about the role of the capsule.

      __ Authors’ reply #22: __Fair point. We thank the reviewer for this important suggestion. To distinguish between the O-glycosylation pathway and capsule production, we will generate a ∆pglL strain (specific to O-glycosylation), as suggested, and will repeat the key experiments (similar to Fig. 2A and 2B). We are almost done with the engineering of this mutant strain and therefore don’t expect any major delays.

      #23) Evidence could be provided to support the idea raised in lines 482-483 that T6SS component accumulation is toxic ("degradation [of T6SS components] could serve as a strategy to alleviate proteotoxic stress..."). For example, growth curves of ∆clpXP strains with and without hcp could be analyzed, to determine how degrading Hcp is helping the bacteria.

      __ Authors’ reply #23: __We will perform growth curves of ΔclpXP strains with and without hcp, as suggested by the reviewer. However, we are uncertain whether we will be able to observe differences between these strains, as the conditions under which such degradation is significant may be challenging to replicate under standard laboratory conditions.

      __#24) __The possible ClpXP recognition sequence identified at the C terminus of Hcp is interesting-does overexpression of an Hcp variant lacking/altered in this motif alter its protein levels compared to WT Hcp?

      __ Authors’ reply #24: __We thank the reviewer for this suggestion. We are in the process of performing the suggested experiment and will include the data in the manuscript.

      __Minor items:____ __

      #25) *A better explanation could be provided for why overexpressing hcp in WT but not in ∆hcp leads to increased Hcp protein levels. There is a statement about Hcp being regulated post transcriptionally, possibly by degradation (lines 422-423), but would that not also result in regulation in the WT strain? *

      __ Authors’ reply #25: __The reviewer is absolutely correct here. Despite careful genetic engineering, we believe that the hcp mutant used may have a polar effect, causing Hcp accumulation only in the ∆hcp + p-hcp strain but not in the WT + p-hcp strain, which remains capable of secretion. The ∆hcp strain therefore mimics the secretion-impaired tssB mutant. We will clarify this in the revised manuscript.

      #26) *An untreated control is needed in Fig. 4B. *

      __ Authors’ reply #26: __The untreated samples were shown in all previous figures. However, we understand the reviewer's point and will repeat the experiment with the untreated control included in the same experiment.

      #27) *line 179: please clarify "reflecting better invading bacteria" *

      __ Authors’ reply #27: __We appreciate the reviewer mentioning this oversight. We meant to compare this to a situation where a bacterium invades an already existing community, resulting in a predator-prey ratio below 1. We will clarify this further in the revised manuscript.

      #28) *line 351: consider rewording the statement that ∆tslA results in decreased in T6SS assembly and activity using the tssB-msfGFP microscopy assay; it is not clear that activity is measured in this assay. *

      __ Authors’ reply #28: __The reviewer is correct. We will revise the sentence accordingly to better reflect the T6SS assembly.

      #29) *lines 260-265: This experiment could use clarifying, but it would seem that it requires analysis of the secreted capsule levels in the tssB mutant to show it does not produce extracellular capsule to the same extent that ∆bfmS does. *

      __ Authors’ reply #29: __We thank the reviewer for the suggestion and will include these experimental data in the revised manuscript.

      #30) *Fig. 6C and 7A labelling could be improved to avoid potential confusion that the bar graphs are quantifying the western blot. E.g., could add a corresponding vertical label to the Western data, or consider changing "relative expression of hcp" to something reflecting analysis of transcript levels. *

      __ Authors’ reply #30: __We will improve this figure by splitting the qPCR and Western blot data into independent panels. This will eliminate any confusion.

      #31) lines 416-417 and Fig. 7A: states that "hcp mRNA levels increased significantly", but more careful wording could be used because the WT's transcript change is not significant after overexpression (though it is significant in ∆hcp).

      __ Authors’ reply #31: __Point well taken. We will improve the sentence (and Figure) to make its meaning unambiguous.

      • *

      #32) lines 479-480 states that in secretion-impaired strains accumulation of Hcp is mitigated by ClpXP; while this was shown for ∆tssB, was this also the case for ∆bfmS?

      __ Authors’ reply #32: __This is indeed an interesting suggestion. We are in the process of generating the double mutant ∆bfmS∆clpXP and will include the experimental results in the revised manuscript.

      Significance

      #33) *The strengths of the study are the focus on a clinically significant pathogen, the potential novel roles for the important capsule virulence factor of A. baumannii, and the identification of novel points of control of the T6SS. The analyses of T6SS function are thorough and carefully performed. *

      __ Authors’ reply #33: __We thank the reviewer for their comments, which we believe will significantly strengthen our work, particularly regarding the capsule aspect.

      PeerReviewed
    2. EMBOpress 26 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      The manuscript by Flaugnatti et al investigates the relationship between functions of the T6SS in A. baumannii and production of capsular polysaccharide. The manuscript argues that (1) capsule protects A. baumannii against T6SS-mediated attack by other bacteria, (2) capsule also interferes with the bacterium's own T6SS activity, and (3) the T6SS inner tube protein Hcp is regulated by degradation by ClpXP. The main critiques regard the first two conclusions, which seem to be based solely on use of a mutant that has a confounding effect as described below; and to strengthen the third claim by further exploring the results of overexpressing Hcp and by determining whether there is a fitness benefit for Hcp regulation.

      Main items:

      • Throughout the paper, an itrA deletion mutant is used as the capsule-deficient strain and conclusions are drawn about role of capsule based on this mutant. However, itrA deletion also eliminates the protein O-glycosylation pathway (Lees-miller et al 2013), a potential confounder. Analysis of mutants specifically deficient in the high-molecular weight capsule but not protein glycosylation, and/or mutants in the protein o-glycosylation enzyme, should be incorporated into the study to enhance the ability to make conclusions about the role of the capsule.
      • Evidence could be provided to support the idea raised in lines 482-483 that T6SS component accumulation is toxic ("degradation [of T6SS components] could serve as a strategy to alleviate proteotoxic stress..."). For example, growth curves of ∆clpXP strains with and without hcp could be analyzed, to determine how degrading Hcp is helping the bacteria.
      • The possible ClpXP recognition sequence identified at the C terminus of Hcp is interesting--does overexpression of an Hcp variant lacking/altered in this motif alter its protein levels compared to WT Hcp?

      Minor items:

      • A better explanation could be provided for why overexpressing hcp in WT but not in ∆hcp leads to increased Hcp protein levels. There is a statement about Hcp being regulated post transcriptionally, possibly by degradation (lines 422-423), but would that not also result in regulation in the WT strain?
      • An untreated control is needed in Fig. 4B.
      • line 179: please clarify "reflecting better invading bacteria"
      • line 351: consider rewording the statement that ∆tslA results in decreased in T6SS assembly and activity using the tssB-msfGFP microscopy assay; it is not clear that activity is measured in this assay.
      • lines 260-265: This experiment could use clarifying, but it would seem that it requires analysis of the secreted capsule levels in the tssB mutant to show it does not produce extracellular capsule to the same extent that ∆bfmS does.
      • Fig. 6C and 7A labelling could be improved to avoid potential confusion that the bar graphs are quantifying the western blot. E.g., could add a corresponding vertical label to the Western data, or consider changing "relative expression of hcp" to something reflecting analysis of transcript levels.
      • lines 416-417 and Fig. 7A: states that "hcp mRNA levels increased significantly", but more careful wording could be used because the WT's transcript change is not significant after overexpression (though it is significant in ∆hcp)
      • lines 479-480 states that in secretion-impaired strains accumulation of Hcp is mitigated by ClpXP; while this was shown for ∆tssB, was this also the case for ∆bfmS?

      Significance

      The strengths of the study are the focus on a clinically significant pathogen, the potential novel roles for the important capsule virulence factor of A. baumannii, and the identification of novel points of control of the T6SS. The analyses of T6SS function are thorough and carefully performed.

      PeerReviewed
    3. EMBOpress 26 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      In the manuscript by Flaugnatti et al., the authors provide clear evidence of the interplay between capsule outer coat production and the Type VI secretion system (T6SS) in Acinetobacter baumannii. The authors demonstrate that the presence of the capsule or the activity of the T6SS enhances survival against attacking bacteria. However, they also show that in their model bacterium, the (over)production of the capsule likely hinders T6SS dynamics, thereby reducing overall killing efficiency. Additionally, they reveal that the amount of the T6SS component Hcp is regulated in cells that can no longer assemble and/or secrete via the T6SS, presumably by the ClpXP protease. Overall, the experiments are well designed, and most conclusions are supported by the data and appropriate controls. I have however some suggestions that could further strengthen the manuscript prior to publication.

      Major comments:

      Line 164. The authors use E. coli as prey to test the T6SS activity of A. baumannii. Why not directly use the E. cloacae strain (with or without T6SS) for this purpose? This would provide direct evidence that A. baumannii uses its T6SS to kill E. cloacae, thus confirming the authors conclusions in this section.. In Figure 2, the authors show that a non-capsulated strain kills more effectively and secretes more than a WT, but has a similar number of T6SS. They suggest in their conclusion that "the observed increase in T6SS activity in the non-capsulated strain suggests a compensatory mechanism for the absence of the protective capsule layer." This conclusion implies the presence of an "active" regulatory mechanism that would increase the number of successful T6SS firing events, which has not been demonstrated. Could it not simply be that the capsule blocks some shots that cannot penetrate and are therefore ineffective? This hypothesis is mentioned in lines 204-208. The authors should clarify the conclusion of this section. Given the challenge this may pose in A. baumannii, I suggest that the authors quantify the assembly/firing dynamics of the T6SS under WT and ΔitrA conditions. This would help distinguish between the two hypotheses explaining better firing in non-capsulated cells: i.e., if the number of assembled T6SS is the same in both strains (Fig 2C & 2D), do non-capsulated cells assemble/fire faster, indicating an adaptation in regulation, or do we observe the same dynamics, suggesting a simple physical barrier blocking the passage of certain T6SS firing events? Line 428-429. It is mentioned that the deletion of lon does not have a notable effect. However, I observe that the absence of Lon alone causes a more rapid degradation of Hcp in the cells compared to the WT strain (Fig 7B). How do the authors explain that the absence of this protease (whether under conditions of Hcp accumulation or not) increases the degradation of this protein in the cell? This explanation should be included in the manuscript.

      Minor comments:

      • a) Throughout the manuscript, the authors use the term "predator" to refer to A. baumannii. Predation is a specific phenomenon that involves killing for nourishment. To my knowledge, the T6SS has never been shown to be a predation weapon but rather a weapon for interbacterial competition, which is a different concept. If this has not been demonstrated in A. baumannii, the authors should replace the term "predator" with "attacker" (or an equivalent term) to clarify the context.
      • b) Line 274. Since the authors stated that in the Wzc mutant, the capsule is "predominantly found in the supernatant and only loosely attached to the cell," this result is not unexpected. This finding is also consistent with the previous results from Fig. 3A & B, which show sensitivity to complement-mediated killing and the weak amount of (ab)normal CPS produced in that strain, further confirmed by Fig. 3E.
      • c) Line 299. The authors speculate that "... T6SS may deploy through gaps akin to arrow-slits in the capsule's mesh...". However, this is very unlikely since a WT strain kills (Fig. 3C) and secretes (Fig. 2B & 3D) less effectively than the itrA mutant, suggesting that the T6SS is not assembled in the "right places" devoid of CPS; otherwise, we would expect similar T6SS activity. Based on the results in Fig. 2 (and my earlier comment), this implies that A. baumannii assembles its T6SS randomly, and in the presence of the capsule, its shots would need to be in the right place to penetrate the envelope and reach the target. Could the authors comment on this point and provide a model figure to better visualize the interplay between the capsule and T6SS under the three major conditions: WT, non-capsulated, and capsule overproduction?
      • d) In Fig. 5A, the microscopy panels should be adjusted to the same dynamic range as the WT (which represents a true signal), which does not appear to be the case for the tlsA mutant panel for instance. The image gives the impression of a large amount of free TssB-msfGFP in the cytoplasm. However, this effect is due to the dynamic range being adjusted to display a signal. This observation is consistent with the fact that the amount of TssB-msfGFP protein is identical across all strains (Fig. S2F).
      • e) Unless I am mistaken, the authors do not comment on the fact that in a ΔbfmS strain, the number of T6SS is halved compared to a WT or ΔitrA strain. If capsule overproduction only partially limits the TslA-dependant T6SS assembly, how can this result be explained? Is it related to the degradation of Hcp in this background, which ultimately limits the formation of T6SS? If so, it would be interesting to mention this connection in the section "Prolonged secretion inhibition triggers Hcp degradation."

      Referee Cross-Commenting

      Overall, I agree with the concerns raised by reviewers 1 and 3. This (already) very good manuscript will undoubtedly benefit from these comments.

      Significance

      This work is highly intriguing as it not only delves into the specific mechanisms involved but also connects fundamental elements in bacterial competition, i.e., the necessity for self-protection and aggression for survival. The manuscript offers valuable insights into cellular dynamics at a microscale level and prompts new inquiries into the regulation of these systems on a population scale. The work is well-done and the writing is also clear.

      I am convinced that this work represents another significant step towards understanding bacterial mechanisms and will undoubtedly spark considerable interest in the field.

      Expertise: T6SS, fluorescence microscopy, predation, interbacterial competition

      PeerReviewed
    4. EMBOpress 26 Jun 2024

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

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The transport of effector proteins across membranes from the producing bacterium into a target cell is at the core of bacterial secretion systems. How an additional layer in form of a capsule affects effector export and the susceptibility towards effector import is not fully understood. Here, Flaugnatti and colleagues combined bacterial genetics with phenotypic assays and electron microscopy to demonstrate a dual role of a bacterial capsule in preventing T6SS-mediated effector export and promoting protection from effector import by another bacterium's T6SS. The wide variety of methods used, complementation of the mutants, and validation of the findings across strains strengthen the author's conclusions.

      Although the main conclusions seem straight forward, the authors unravel the unexpected complexity underlying these phenotypes with strong mechanistic work. In brief, a capsule-deficient mutant (∆itra) is shown to assemble its T6SS similar to the WT, yet secretes more Hcp than the WT and is better in T6SS-mediated killing of other bacteria. A capsule-overproducing mutant (∆bfmS) shows both, a partial deficiency in T6SS assembly and an additional reduction in exported Hcp, and is worse in T6SS-mediated killing than the WT. A mutant with a capsule similar to WT and deficient in cell sensing (∆tslA) forms the least T6SS apparatuses and is yet better in T6SS-mediated killing than the overcapsulated mutant. Together, these data show an effect of the capsule on (i) T6SS apparatus assembly, (ii) effector export, (iii) effector import, and (iv) the need for clearance of accumulating non-secreted Hcp by ClpXP.

      The work on a clinical isolate of Acinetobacter tumefaciens and the data on an impaired T6SS activity on other cells by antibiotic-induced capsulation is a strong demonstration of the work's clinical relevance in addition to the findings' conceptual novelty.

      In my view, the manuscript is outstanding with very high quality of experimental data, very well written text and very clear presentation of the data in figures. A few minor comments and suggestions below that I think would strengthen the manuscript.

      Major comment:

      OPTIONAL: Fig. 4c/l. 320: Having an indirect effect of an antibiotic on T6SS activity by antibiotic-induced capsule formation is very intriguing and contributes to the clinical relevance of the overall findings. When I saw the data in Fig. 4c, the graph instantaneously reminded me of the panel in Fig. 2a, where a similar phenotype is observed by changing the predator:prey ratio in the absence of any antibiotic. The authors themselves comment on the possibility of antibiotic-induced, reduced predator growth (and thereby a change in predator:prey ratio) as a one factor impacting the phenotype here. I am wondering if this data could be strengthened or better disentangled to test more precisely if it is the antibiotic induced capsule formation per se that affects T6SS-mediated killing by A. baumanii in the presence of antibiotics. Would it help to take the bfmS mutant along as a control for direct comparison to see if antibiotic-induced capsule formation of the WT to similar levels of the mutant results in the same killing phenotype? Would it help to test for T6SS-mediated killing in the presence and absence of antibiotics at multiple predator:prey ratios? Could the effect of the antibiotic on A. baumanii growth be measured and considered when choosing the ratio at which the bacteria are mixed?

      Minor comments:

      • Figure 1D, l. 155ff, I might have missed this, do the authors happen to have the numbers of E. cloacae as well? This would strengthen the claim on A. baumanii survival because of E. cloacae is being killed.
      • Figure 2, I suggest to write out the species name of the prey in the box with the ratio. With E. cloacae being referred to in the previous figure and starting with similar letters than E. coli, I wasn't sure at first sight what E. c. refers to.
      • use of the term "T6SS activity" throughout the manuscript (e.g. l. 182, l. 187). I leave this up to the authors. To me, it seems like an umbrella term for the initial observation and I see that such a term can be very handy for the writing. I just would like to mention that the use of the term was not always intuitive to me and sometimes even a bit misleading. For example, l. 182 refers to "increased T6SS activity". As a reader, I only know about 'T6SS activity on other cells' or 'a T6SS-mediated effect on other cells' at this point. T6SS apparatus assembly/firing activity is tested for specifically later and it turns out to differ between mutants. By the time the term is used in the discussion, it captures multiple nuanced phenotypes described by then. The more precise definition of the term in l. 200 helped to capture what exactly is meant by the authors.
      • l. 198f "Collectively, our findings indicate that CPS does not hinder the secretion process of 199 the T6SS or the consequent elimination of competing cells". I might be missing something, I cannot entirely follow this sentence. Didn't the authors just show that the CPS does hinder T6SS-mediated elimination of competing cells in panel 2A and less secreted Hcp in the encapsulated WT compared to the non-encapsulated mutant in panel 2B?
      • l. 224, typo, "in"
      • Two connected comments: l. 338, Just a thought, I am wondering about the title of the section. After reading it a second time, I think it is technically correct. When reading it first, I was a bit confused when getting to the data because apparatus assmebly is impaired in the capsule-overproducing strain and although "preserved", doesn't the data indicate that there is less T6SS assembly in the bfmS mutant and that this might be because of less cell sensing and isn't this a main point that there is a difference in apparatus assembly in the capsule overproducing strain compared to WT (other than no difference in apparatus assembly in the strain without capsule)? To me it seems not fully acknowledged as a finding in the interpretation of the data that less cells of the bfmS mutant have a T6SS apparatus. Isn't that interesting? A title along the lines of "Capsule-overproducing strain has preserved sensory function and assembles less T6SS apparatuses" would have been more intuitive for me. l. 352, In case I didn't miss a reference to this data earlier in the manuscript, I am wondering if it would be worth mentioning the finding on the reduced apparatus assembly of the bfmS mutant earlier, together with Figure 3 already. At least a sentence that mentions already that there is more coming later. When I got to this line in the manuscript and read the findings on the apparatus assembly, I first needed to go back to figure 3 and look at the data there again in light of this finding. It is mentioned here on the side but I think very important for the interpretation of the phenotypic data of the bfmS mutant shown earlier, isn't it? The tslA mutant is used beautifully here.
      • Discussion: optional comment. On the one hand, I like the concise discussion. On the other hand, I see more potential here for bringing it all together (potentially at the expense of shortening some of the introduction). I think the subtleties of the findings are complex. For example, I could envision a graphical summary with a working model on all the effects of a capsule on the T6SS and its potential clinical relevance making the study accessible to even more readers.

      Significance

      General assessment

      I consider the story very strong in terms of novelty, experimental approaches used, quality of the data, quality of the writing and figures of the manuscript. In my view, the aspects that could be improved are optional/minor and concern only one figure and some phrasing.

      Advance

      I see major advance in the findings (i, mechanistic) on the mechanism of how the capsule interferes with T6SS, (ii, fundamental) on the discovery of ClpXP degrading Hcp, and (iii, clinical) on the meaning of antibiotic treatment for the T6SS of this clinically relevant and often multi-drug resistant bacterial species, which strongly complements existing work on the T6SS and antibiotics in A. baumanii (e.g. of the Feldman group). As the authors write themselves, the starting points of the study of a capsule protecting from a T6SS and the effect of a T6SS on other cells being negatively impacted by a capsule were known, although not studied in one species and not understood mechanistically.

      Audience

      I see the result of interest to a broad audience in the fields of bacteria-bacteria interactions, Acinetobacter baumanii, type VI secretion, antimicrobial resistance, bacterial capsules

      PeerReviewed
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    The type of DNA damage response after Decitabine treatment depends on the level of DNMT activity
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    idh-1 neomorphic mutation confers sensitivity to vitamin B12 via increased dependency on one-carbon metabolism in Caenorhabditis elegans
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    1. EMBOpress 25 Jun 2024

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      Reply to the reviewers

      We thank all three reviewers for their insightful comments. Based on this feedback, we have performed additional experiments, and revised our manuscript. Below, we address each comment and describe the revisions.

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

      Summary: Ponomarova et al. showed that neomorphic idh-1 mutation results in increased levels of cellular D-2HG. The authors compared the high D-2HG phenotypes by D-2HG dehydrogenase mutant and identified vitamin B12 dependent vulnerability differences. The downregulated gene function of glycine cleavage system involved in one-carbon donor units exacerbates the phenotypes while adding one-carbone donors suppresses the phenotype. They concluded that the idh-1neo mutation imposes a dependency on the one-carbon pool. The manuscript is very interesting but I think the manuscript should be modified to be more clear for broad audiences.

      Concerns: The authors mention a number of examples for metabolic changes of D-2HG in the first paragraph of introduction. I think that a metabolic map explaining the changes helps readers to understand the questions proposed by the authors.

      Thank you for this suggestion. A figure illustrating the contributing factors in D-2HG metabolism has been added to the manuscript (Figure 1A).

      The authors say that D-2HG affects carcinogenesis in many ways, citing previous works. They should say a higher concentration of D-2HG does affect carcinogenesis or not in dhgd loss of function, if they assume the concentration is most important for carcinogenesis.

      Thank you for pointing this out. We have added this information in lines 70-72 of the revised manuscript: "Increased levels of D-2HG caused by the inhibition of D-2-hydroxyglutarate dehydrogenase activity have also been associated with different cancers (PMID: 29339485, PMID: 34296423, PMID: 35007759)."

      Line 110, mode should be read as model, I guess.

      Thank you - we have corrected this error.

      In Figure 4C, concentrations of formate are shown; 0. 20, 40, 80, 160 mM. Is this correct? the high concentration of substrates changes the osmotic pressure of the medium. Also, high concentration of formic acid is toxic to animals. Considering the concentration of vitamin B12 was 64 nM, I wonder concentration unit of formate is also nM.

      We confirm that we supplemented the media with formate in the millimolar range. The highest doses of supplemented formate somewhat slowed the development of P0 animals, but they consistently produced viable progeny. To clarify this we have added the following line to the text on lines 184-187: "The highest doses of supplemented formate somewhat slowed the development of P0 animals, but restored the survival of idh-1neo embryos to wild-type levels on a regular diet of E. coli OP50 as well as the diet of RNAi-competent E. coli HT115."

      Additionally, the use of sodium formate ensured that the pH of the media remained unchanged.

      I could not understand how embryonic and larval lethality confer the same mechanisms on animal carcinogenesis. Could you explain the logic link between lethal mutation and carcinogenesis. Or do the two phenotypes share only a part of metabolic changes?

      Thank you for this suggestion. We have added this in lines 242-246 of the Discussion:

      "While our results have focused on how the neomorphic idh-1 mutation affects the developing embryo, proliferating cancer cells also have been shown to have increased demand for 1C units, for instance, to synthesize nucleosides (33)(PMID: 24657017). Thus, we can speculate that cancers with mutated IDH1 may be increasingly sensitive to depletion of the 1C pool, also."

      Vitamin B12 is an essential substance and deficiency in humans results in sever diseases. Is the lethal phenotype by treatment of idh-1neo mutants comparable to humans? Is the concentration of vitamin B12 similar in humans?

      The daily dose of human vitamin B12 (cobalamin) in supplements can reach 12.5 µg per kg (PMID: 18606874), while we supplement the media fed to worms with approximately 55 µg cobalamin per kg (64 nM adenosylcobalamin). No known adverse effects are associated with excessive intake of vitamin B12 by healthy individuals; therefore, no tolerable upper intake level has been set (PMID: 23193625). However, the impact of vitamin B12 on patients with IDH1neo-positive cancers has not been studied.

      Reviewer #1 (Significance (Required)):

      I think that the manuscript is interesting and may lead an important progress of this field. However, in general, metabolic disorders are difficult to understand for the people outside the speciality. The authors should explain carefully the structure/property, pathways, enzyme functions, and concentration effects of substances of interest.

      See above, we hope these edits are sufficient.

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

      Increased levels of the metabolite D-2HG (derived from alpha-KG) are associated with multiple disorders. In a previous study, the authors showed that in C. elegans dhgd-1 deletion mutants, embryonic lethality resulting from the accumulation of D-2HG in is caused by a lack of ketone bodies. In this study, the authors generated a new model of D-2HG accumulation in C. elegans, idh-1neo, in order to further understand how D-2HG exerts its toxic effects in different contexts. This allele mimics mutations found in neomorphic mutations of human IDH1 that lead to abnormal D-2HG production from alpha-KG. Interestingly, the authors find that idh-1neo mutants are distinct from animals lacking the D-2HG dehydrogenase dhgd-1 previously reported. Specifically, while vitamin B12 rescues the embryonic lethality in dhgd-1 deletion animals, it enhances the lethality of idh-1neo animals. Through an elegant genetic screen, and complementation studies with specific metabolites, they provide compelling evidence that this vitamin B12-dependent enhancement is due to depletion of the 1C pool. Specifically, a reverse genetic screen revealed that inactivation of components of the 1 C-producing glycine cleavage system (GCS) results in embryonic lethality in idh-1neo, but not wildtype animals. Complementation studies with specific metabolites show that replenishing C groups is sufficient to reverse embryonic lethality.

      This is a very clear, well written paper. Experiments are well controlled and executed, figures are of the highest quality and conclusions are convincing. Prior studies are appropriately referenced. No additional experiments are required by this reviewer.

      Minor points 1) In Figure 2A could authors explain how beta-alanine (increased) is different from alanine (decreased). As a non-specialist this is not clear to me.

      Thank you for pointing this out. We added this explanation to the figure legend (lines 510-512).

      2) Did the authors test inactivation of the lipoamide dehydrogenase (dld-1) has the same effect as the other identified components of the GCS?

      The dld-1 RNAi clone was present in the metabolic library that we screened but was not identified as a "hit." We have added the following in lines 164-168 of the revised manuscript: "Two other GCS genes, gcsh-2 and dld-1 were not identified as 'hits'. gcsh-2 is associated with the same reaction as gcsh-1, indicating that the latter encodes an active enzyme (30). dld-1 functions in other metabolic processes, particularly in lactate/pyruvate metabolism, and confers embryonic lethality when knocked down in wild type animals (31)".

      **Referees cross-commenting**

      Comments to Reviewer #3: 1/ The authors treat the idh-1neo worms with vitamin B12 to reduce 3HP concentrations. The authors should consider conducting experiments to reduce 3HP by other means also. This would help establish a causal relationship between the D-2HG accumulation and observed phenotypes.

      The authors show that adding vitamin B12 to the diet of the idh-1neo significantly increased their D-2HG levels. Furthermore, dhgd-1 RNAi drives a further increase in D-2HG in idh-1neo animals and led to 100% penetrant embryonic lethality among the F1 generation of idh-1neo animals. Together I think this provided strong evidence for a causal relationship between the D-2HG accumulation and observed phenotypes. Further characterizing these phenotypes would be interesting but is beyond the scope of this paper.

      4/ The authors should clarify whether it is really vitamin B12 or any other metabolite from the bacteria (like methionine) that is bringing about the phenotypes. Have they tested metabolically inactive bacteria?

      the authors show that supplementing B12-treated idh-1neo animals with formate (another 1C donor) restored the survival of idh-1neo embryos, supporting a role for B12 in depletion of the 1C pool. They also show that suppressing Met/SAM cycle genes in idh-1neo prevent 1C depletion and restore availability of 1C units. So the evidence that 1C unit depletion is at the core of the observed phenotypes is pretty convincing

      7/ The authors should conduct metabolomic profiling to examine changes in metabolic pathways, including 1C, glycine metabolism, glucose metabolism etc, in idh-1neo animals subjected to GCS gene knockdown, and vitamin B12 supplementation.

      Not clear how these experiments would add to this story. Open up another line of research

      8/ The audience will be limited to the field although the study pertains to an oncometabolite. The study value would have improved if the authors had included cancer cell data. Also, the phenotype studied has not been mechanistically linked to the oncometabolite function, making the study academic in nature.

      The intetest of this study is that it is being carried out in an organismal context.

      Reviewer #2 (Significance (Required)):

      As a geneticist with a general interest in metabolomics I find this an elegans study that offers new insight into how IDH-1 and -2 neomorphic mutations affect metabolic rewiring in the context of a whole animal. Although similarities are observed between idh-1neo mutants and animals lacking the D-2HG dehydrogenase dhgd-1, both of which have increased levels of the metabolite D-2HG, specific metabolic differences are observed. The identification of 1C unit deficiency as a driver of lethality in idh-1neo mutants is highly significant given the central importance of 1C metabolism. This study should therefore be of interest to a wide audience.

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

      Ponomarova et al presents a short follow up of their previous study to elucidate the role of a oncogenic variant of idh-1 that increases the 3HP levels, similar to the Ddhgd-1 mutant. Using a combination of metabolomics and genetics, they show that the defect in idh-1neo worms on high vitamin B12 diet is the draining of the 1C pool, distinct from the mechanisms of lethality observed in the Ddhgd-1 mutant. While the findings are interesting, there is a lack of mechanistic understanding of the basis of the phenotype observed. Moreover, the authors do not establish the link between the oncometabolite, that should support uncontrolled cell division, with the observed phenotype. Some control experiments are missing and should be included in the revised manuscript. there could be many other The comments on the manuscript are as follows, in no particular order:

      1. The authors treat the idh-1neo worms with vitamin B12 to reduce 3HP concentrations. The authors should consider conducting experiments to reduce 3HP by other means also. This would help establish a causal relationship between the D-2HG accumulation and observed phenotypes.

      To further examine the link between 3HP and idh-1neo embryonic lethality, we targeted hphd-1 by RNAi, which increases 3HP levels (Ponomarova et al., 2023). Hphd-1 knockdown did not induce lethality in the wild-type or exacerbate lethality in idh-1neo animals (Figure S3), further demonstrating that lack of 3HP degradation is not linked to this phenotype (lines 143-145).

      Also, see cross-comments from Reviewer #2 above.

      The authors should investigate the functional impact of HPHD-1 inhibition on 3-hydroxypropionate levels and D-2HG accumulation by RNAi knockdown of HPHD-1 in idh-1neo animals.

      We have now performed the suggested experiment please see response to comment 1 above.

      The authors do not clearly mention clearly which diet in some of their experiments. This is imporant since the two diets used (OP50 and HT115) differ in their vitamin B12 content, and thus could have different consequences.

      We added this information in figures, figure legends, and lines 259-260 of the revised manuscript.

      The authors should clarify whether it is really vitamin B12 or any other metabolite from the bacteria (like methionine) that is bringing about the phenotypes. Have they tested metabolically inactive bacteria?

      The reviewer correctly points out that bacterial metabolism may play a role in the effects exerted by vitamin B12. We have not tested metabolically inactivated bacteria, however, our RNAi experiments (Figure 4E) demonstrate that supplemented vitamin B12 acts through the Met/SAM cycle in idh-1neo animals. Please also see cross-comments from Reviewer #2.

      The authors consistently use 64 nM of Vitamin B12. Will the hphd-1 mutant and the idh-1neo mutant have different vitamin B12 thresholds for the observed phenotypes?

      Thank you for raising this interesting point. While 64 nM vitamin B12 virtually eliminates 3HP accumulation in idh-1 animals (Figure 2D), we have not tested if this dose is sufficient to eliminate 3HP accumulation in hphd-1 mutant. However, potential differences in 3HP levels in idh-1neo and hphd-1 animals treated with vitamin B12 would not contradict our conclusion that 3HP is not the cause of embryonic lethality in idh-1neo mutant animals.

      Figure 3b: HT115 has inherently high levels of vitamin B12 so the RNAi effect of genes should be seen on the OP50 diet supplemented with B12.

      Despite reports of elevated B12 levels in E. coli HT115, vitamin B12-induced embryonic lethality of idh-1neo on a diet of OP50 is more severe than on a diet of HT115 bacteria (Figure 4C). Therefore, it may be harder to quantify synthetic lethal interaction of idh1-neo with GCS RNAi knockdown using OP50 strains (which would need to be created).

      The authors should conduct metabolomic profiling to examine changes in metabolic pathways, including 1C, glycine metabolism, glucose metabolism etc, in idh-1neo animals subjected to GCS gene knockdown, and vitamin B12 supplementation.

      While these results would be interesting and further our understanding of metabolic changes that occur in idh-1neo mutant animals we think they are beyond the scope of the manuscript. Also, please see cross-comments from Reviewer #2.

      Perform rescue experiments using different one-carbon donors (e.g., formate, serine) to restore embryonic viability in idh-1neo mutants under conditions of vitamin B12-induced stress. Quantify the efficacy of these interventions using developmental assays.

      In addition to formate rescue experiments (Figure 4C), we supplemented idh-1neo animals with serine (Figure 4D and S7). Similar to formate, serine supplementation resulted in the rescue of idh-1neo embryonic lethality on an E. coli OP50 diet (lines 187-189). The lack of rescue on an HT115 diet could be due to HT115 bacteria containing more glycine (Gao et al., 2017), which might limit the efficiency of serine conversion to glycine needed for 1C unit production.

      Provide experimental evidence to show that idh-1neo animals possess an alternative source of energy.

      We have previously found that diminished production of ketone bodies in ∆dhgd-1 mutants causes embryonic lethality that can be rescued by exogenous supplementation of ketone body 3-hydroxybutyrate (Ponomarova et al., 2023). In contrast to dhgd-1 mutants, idh-1neo embryonic lethality fails to respond to supplemented 3-hydroxybutyrate (Figure S4), indicating the lethality associated with the idh-1neo mutation is caused by a different mechanism, i.e., a depletion in 1C-units.

      The authors use vitamin B12 to inhibit the shunt pathway (line 127). They should explore alternate strategies to do the same, like gene knockdown.

      Please see our response to comment 1 above where we discuss RNAi knock-down of the shunt pathway gene, hphd-1.

      It is not clear why the authors did not follow up with the other phenotypes of the idh-1neo that were visible without the Vitamin B12 supplementation. They should follow up with this and also other phenotypes to explore the broader physiological consequences of D-2HG accumulation.

      We agree that the other physiological consequences of D-2HG accumulation are interesting, and we plan to investigate them in our future studies.

      The authors should include control experiments without supplementation of vitamin B12, ketone bodies etc. in each of their figures.

      We thank the reviewer for this suggestion. We have added these data (Figures S5, 6, 7, and 8).

      The authors posit that the idh-1neo depletes the 1C pool leading to the observed lethality. So, when they supply formate to replenish it, they rescue the lethality of the B12-treated worms. Similar results are obtained by knocking down the enzymes. So where are the 1C units going? Understanding this will provide the much-needed mechanistic understanding to this study.

      We appreciate this insightful comment and expand our discussion to elaborate on this issue (lines 224-227). "We propose that a lack of 1C units in idh-1neo can impede pyrimidine biosynthesis via thymidylate synthase tyms-1, which uses 1C units to generate dTMP. Supporting this hypothesis, RNAi of tyms-1 causes embryonic lethality (36-38)."

      It may be important to measure the D-2HG levels in the mitochondria vs the cytosol.

      While this is an interesting point, we think that this line of inquiry is beyond the scope of this work (and is technically challenging).

      The idh-1neo is an oncometabolite. The authors do not show any data to indicate whether this mutant has any defect in cell division/cell cycle in the somatic tissue or germline.

      In this study we primarily focused on the molecular changes in the metabolic network that occur in idh-1neo mutant animals, which we think is an important advance in understanding the basis for how this mutation affects IDH function. Additional phenotypic outcomes of these perturbed metabolic processes will be the basis of future studies.

      Reviewer #3 (Significance (Required)):

      The audience will be limited to the field although the study pertains to an oncometabolite. The study value would have improved if the authors had included cancer cell data. Also, the phenotype studied has not been mechanistically linked to the oncometabolite function, making the study academic in nature.

      While we agree that the link between idh-1neo, 2HG production and oncometabolite function has not been directly shown we think that our study adds important molecular understanding of metabolic changes that occur in relation to idh-1neo function which are important for future studies of how this mutation affects carcinogenesis. Also, please see cross-comments from Reviewer #2.

      In addition, we specified statistical significance in Figure 2, described statistical tests used (lines 361-363) and corrected a few grammatical errors throughout the text.

      PeerReviewed
    2. EMBOpress 25 Jun 2024

      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 #3

      Evidence, reproducibility and clarity

      Ponomarova et al presents a short follow up of their previous study to elucidate the role of a oncogenic variant of idh-1 that increases the 3HP levels, similar to the dhgd-1 mutant. Using a combination of metabolomics and genetics, they show that the defect in idh-1neo worms on high vitamin B12 diet is the draining of the 1C pool, distinct from the mechanisms of lethality observed in the dhgd-1 mutant. While the findings are interesting, there is a lack of mechanistic understanding of the basis of the phenotype observed. Moreover, the authors do not establish the link between the oncometabolite, that should support uncontrolled cell division, with the observed phenotype. Some control experiments are missing and should be included in the revised manuscript. there could be many other The comments on the manuscript are as follows, in no particular order:

      1. The authors treat the idh-1neo worms with vitamin B12 to reduce 3HP concentrations. The authors should consider conducting experiments to reduce 3HP by other means also. This would help establish a causal relationship between the D-2HG accumulation and observed phenotypes.
      2. The authors should investigate the functional impact of HPHD-1 inhibition on 3-hydroxypropionate levels and D-2HG accumulation by RNAi knockdown of HPHD-1 in idh-1neo animals.
      3. The authors do not clearly mention clearly which diet in some of their experiments. This is imporant since the two diets used (OP50 and HT115) differ in their vitamin B12 content, and thus could have different consequences.
      4. The authors should clarify whether it is really vitamin B12 or any other metabolite from the bacteria (like methionine) that is bringing about the phenotypes. Have they tested metabolically inactive bacteria?
      5. The authors consistently use 64 nM of Vitamin B12. Will the hphd-1 mutant and the idh-1neo mutant have different vitamin B12 thresholds for the observed phenotypes?
      6. Figure 3b: HT115 has inherently high levels of vitamin B12 so the RNAi effect of genes should be seen on the OP50 diet supplemented with B12.
      7. The authors should conduct metabolomic profiling to examine changes in metabolic pathways, including 1C, glycine metabolism, glucose metabolism etc, in idh-1neo animals subjected to GCS gene knockdown, and vitamin B12 supplementation.
      8. Perform rescue experiments using different one-carbon donors (e.g., formate, serine) to restore embryonic viability in idh-1neo mutants under conditions of vitamin B12-induced stress. Quantify the efficacy of these interventions using developmental assays.
      9. Provide experimental evidence to show that idh-1neo animals possess an alternative source of energy.
      10. The authors use vitamin B12 to inhibit the shunt pathway (line 127). They should explore alternate strategies to do the same, like gene knockdown.
      11. It is not clear why the authors did not follow up with the other phenotypes of the idh-1neo that were visible without the Vitamin B12 supplementation. They should follow up with this and also other phenotypes to explore the broader physiological consequences of D-2HG accumulation.
      12. The authors should include control experiments without supplementation of vitamin B12, ketone bodies etc. in each of their figures.
      13. The authors posit that the idh-1neo depletes the 1C pool leading to the observed lethality. So, when they supply formate to replenish it, they rescue the lethality of the B12-treated worms. Similar results are obtained by knocking down the enzymes. So where are the 1C units going? Understanding this will provide the much-needed mechanistic understanding to this study.
      14. It may be important to measure the D-2HG levels in the mitochondria vs the cytosol.
      15. The idh-1neo is an oncometabolite. The authors do not show any data to indicate whether this mutant has any defect in cell division/cell cycle in the somatic tissue or germline.

      Significance

      The audience will be limited to the field although the study pertains to an oncometabolite. The study value would have improved if the authors had included cancer cell data. Also, the phenotype studied has not been mechanistically linked to the oncometabolite function, making the study academic in nature.

      PeerReviewed
    3. EMBOpress 25 Jun 2024

      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 #2

      Evidence, reproducibility and clarity

      Increased levels of the metabolite D-2HG (derived from alpha-KG) are associated with multiple disorders. In a previous study, the authors showed that in C. elegans dhgd-1 deletion mutants, embryonic lethality resulting from the accumulation of D-2HG in is caused by a lack of ketone bodies. In this study, the authors generated a new model of D-2HG accumulation in C. elegans, idh-1neo, in order to further understand how D-2HG exerts its toxic effects in different contexts. This allele mimics mutations found in neomorphic mutations of human IDH1 that lead to abnormal D-2HG production from alpha-KG. Interestingly, the authors find that idh-1neo mutants are distinct from animals lacking the D-2HG dehydrogenase dhgd-1 previously reported. Specifically, while vitamin B12 rescues the embryonic lethality in dhgd-1 deletion animals, it enhances the lethality of idh-1neo animals. Through an elegant genetic screen, and complementation studies with specific metabolites, they provide compelling evidence that this vitamin B12-dependent enhancement is due to depletion of the 1C pool. Specifically, a reverse genetic screen revealed that inactivation of components of the 1 C-producing glycine cleavage system (GCS) results in embryonic lethality in idh-1neo, but not wildtype animals. Complementation studies with specific metabolites show that replenishing C groups is sufficient to reverse embryonic lethality.

      This is a very clear, well written paper. Experiments are well controlled and executed, figures are of the highest quality and conclusions are convincing. Prior studies are appropriately referenced. No additional experiments are required by this reviewer.

      Minor points

      1. In Figure 2A could authors explain how beta-alanine (increased) is different from alanine (decreased). As a non-specialist this is not clear to me.
      2. Did the authors test inactivation of the lipoamide dehydrogenase (dld-1) has the same effect as the other identified components of the GCS?

      Referees cross-commenting

      Comments to Reviewer #3:

      1/ The authors treat the idh-1neo worms with vitamin B12 to reduce 3HP concentrations. The authors should consider conducting experiments to reduce 3HP by other means also. This would help establish a causal relationship between the D-2HG accumulation and observed phenotypes.

      The authors show that adding vitamin B12 to the diet of the idh-1neo significantly increased their D-2HG levels. Furthermore, dhgd-1 RNAi drives a further increase in D-2HG in idh-1neo animals and led to 100% penetrant embryonic lethality among the F1 generation of idh-1neo animals. Together I think this provided strong evidence for a causal relationship between the D-2HG accumulation and observed phenotypes. Further characterizing these phenotypes would be interesting but is beyond the scope of this paper.

      4/ The authors should clarify whether it is really vitamin B12 or any other metabolite from the bacteria (like methionine) that is bringing about the phenotypes. Have they tested metabolically inactive bacteria?

      the authors show that supplementing B12-treated idh-1neo animals with formate (another 1C donor) restored the survival of idh-1neo embryos, supporting a role for B12 in depletion of the 1C pool. They also show that suppressing Met/SAM cycle genes in idh-1neo prevent 1C depletion and restore availability of 1C units. So the evidence that 1C unit depletion is at the core of the observed phenotypes is pretty convincing

      7/ The authors should conduct metabolomic profiling to examine changes in metabolic pathways, including 1C, glycine metabolism, glucose metabolism etc, in idh-1neo animals subjected to GCS gene knockdown, and vitamin B12 supplementation.

      Not clear how these experiments would add to this story. Open up another line of research

      8/ The audience will be limited to the field although the study pertains to an oncometabolite. The study value would have improved if the authors had included cancer cell data. Also, the phenotype studied has not been mechanistically linked to the oncometabolite function, making the study academic in nature.

      The intetest of this study is that it is being carried out in an organismal context.

      Significance

      As a geneticist with a general interest in metabolomics I find this an elegans study that offers new insight into how IDH-1 and -2 neomorphic mutations affect metabolic rewiring in the context of a whole animal. Although similarities are observed between idh-1neo mutants and animals lacking the D-2HG dehydrogenase dhgd-1, both of which have increased levels of the metabolite D-2HG, specific metabolic differences are observed. The identification of 1C unit deficiency as a driver of lethality in idh-1neo mutants is highly significant given the central importance of 1C metabolism. This study should therefore be of interest to a wide audience.

      PeerReviewed
    4. EMBOpress 25 Jun 2024

      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

      Summary:

      Ponomarova et al. showed that neomorphic idh-1 mutation results in increased levels of cellular D-2HG. The authors compared the high D-2HG phenotypes by D-2HG dehydrogenase mutant and identified vitamin B12 dependent vulnerability differences. The downregulated gene function of glycine cleavage system involved in one-carbon donor units exacerbates the phenotypes while adding one-carbone donors suppresses the phenotype. They concluded that the idh-1neo mutation imposes a dependency on the one-carbon pool. The manuscript is very interesting but I think the manuscript should be modified to be more clear for broad audiences.

      Concerns:

      The authors mention a number of examples for metabolic changes of D-2HG in the first paragraph of introduction. I think that a metabolic map explaining the changes helps readers to understand the questions proposed by the authors.

      The authors say that D-2HG affects carcinogenesis in many ways, citing previous works. They should say a higher concentration of D-2HG does affect carcinogenesis or not in dhgd loss of function, if they assume the concentration is most important for carcinogenesis.

      Line 110, mode should be read as model, I guess.

      In Figure 4C, concentrations of formate are shown; 0. 20, 40, 80, 160 mM. Is this correct? the high concentration of substrates changes the osmotic pressure of the medium. Also, high concentration of formic acid is toxic to animals. Considering the concentration of vitamin B12 was 64 nM, I wonder concentration unit of formate is also nM.

      I could not understand how embryonic and larval lethality confer the same mechanisms on animal carcinogenesis. Could you explain the logic link between lethal mutation and carcinogenesis. Or do the two phenotypes share only a part of metabolic changes?

      Vitamin B12 is an essential substance and deficiency in humans results in sever diseases. Is the lethal phenotype by treatment of idh-1neo mutants comparable to humans? Is the concentration of vitamin B12 similar in humans?

      Significance

      I think that the manuscript is interesting and may lead an important progress of this field. However, in general, metabolic disorders are difficult to understand for the people outside the speciality. The authors should explain carefully the structure/property, pathways, enzyme functions, and concentration effects of substances of interest.

      PeerReviewed
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    Zebrafish reveal new roles for Fam83f in hatching and the DNA damage-mediated autophagic response
    4
    1. EMBOpress 24 Jun 2024

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      Reply to the reviewers

      __Reviewer #1 (Evidence, reproducibility and clarity (Required)):_ _ __ In this manuscript, Jones et al. report on a potential role for fam83fa in zebrafish hatching, radiation response and autophagy. The authors are commended for generating multiple KO lines and maternal-zygotic embryos for analysis. However, important controls are lacking and the data is circumstantial throughout with very little mechanistic insight into the precise roles, if any, of fam83f in these processes.

      We thank the reviewer for recognizing the strengths of our manuscript, and highlighting areas we might improve. Please see the specific comments below addressing the points raised. In respect of mechanistic insight, while we agree that our manuscript does not provide this, it was not intended to. Rather, we aim to communicate our descriptive findings on the role of Fam83fa in vivo, providing data for follow-up studies by other researchers into the mechanistic role of Fam83fa.

      1. Validation of the KO phenotypes (hatching, IR sensitivity) requires rescue with WT fam83fa WT mRNA, but not 1-500 or fam83fb mRNA.

      We thank the reviewer for raising the issue of rescue experiments. Such experiments are frequently used in knock-down experiments, where non-specificity may be a problem, but they are used more rarely in genetic knock-outs, where the gene defect is well defined. In the case of Fam83fa, a particular difficulty is that overexpression of fam83fa itself causes a p53-mediated DNA damage response (DDR) (Salama et al., 2019). Moreover, we have shown by both qRT-PCR and western blotting that injection of fam83fa mRNA into zebrafish embryos (the traditional technique by which rescue experiments are performed) induces a p53-mediated DDR. As a result, it would be very difficult to interpret the results of any rescue experiment, because one would have to be absolutely certain that levels of fam83fa re-expression recapitulate and do not exceed endogenous levels. As a tool for specificity, we therefore used more than one fam83fa-/- mutant line, carrying a different genomic mutation, and validated that the same phenotype was present in both. We are happy to provide the qRT-PCR and western blot data confirming the results of fam83fa mRNA injection, if required. We have included an additional section into the manuscript detailing this issue. 2.

      While the hatching phenotype (Fig 3) is convincing, there is no data on HG development in the null embryos. Does the HG develop normally in the absence of fam83fb? If so, this would support the authors conclusions that the role of fam83fb is functional rather than developmental (indirect effect). In situs as in Fig.1 might be helpful here.

      Thank you to the reviewer for this helpful suggestion. We agree that we did not investigate whether the hatching gland develops normally in the MZ-fam83fa-/- mutant embryos. No gross morphological differences were observed that led us to investigate this, although we agree it is an interesting question for a future project. In terms of functional vs developmental effects, we are confident that MZ-fam83fa-/- mutant embryos develop at a normal temporal rate, as evidenced by the machine learning based classifier used to assess temporal developmental trajectory (Figure S3 and Jones et al., 2022, 2024). This strongly suggests that the effect of fam83fa KO is functional rather than indirect and caused by (for example) developmental delay.

      While the IR sensitivity phenotype (Fig S4) is convincing, IR-induced cell death/apoptosis was not analyzed. There is a large literature describing straightforward assays for cell death/apoptosis detection in zebrafish with assays such as acridine orange or TUNEL labeling, or active casp3 whole-mount IF. Is IR-induced cell death enhanced in fam83fa KOs?

      We thank the reviewer for their positive comments and agree that investigating the nature of the cell death occurring following IR would be very interesting. We did make use of both acridine orange and TUNEL labeling following injection of fam83fa mRNA (see 1 above), and whilst the assays themselves were relatively straightforward, due to technical issues the quantification of fluorescence intensity was not. Similarly, we suspect that a significant degree of necrosis is also occurring, which further complicates the issue of data interpretation from both these approaches. We do, however, think this is an important avenue of questioning, and hope that other researchers will explore the mechanism of IR induced cell death in the MZ-fam83fa-/- mutants in the future,

      Similarly, there are multiple tools to assay autophagy in zebrafish (e.g., Moss et al., Histochem Cell Biol 2020, PMC7609422; Mathai et al., Cells 2017, PMC5617967). Is autophagy affected in the KOs, with or without IR? These experiments might directly implicate fam83fa in autophagy.

      We agree that there are exciting tools with which to assay autophagy in zebrafish, and although we considered some of these, including caudal fin regeneration, we deemed these experiments to be beyond the descriptive scope of this paper, given the time and resources available to us. We hope that other researchers will use our data as a basis for investigating the role of Fam83fa in autophagy further, using assays such as these suggested by the reviewer.

      Figure 4: Isn't there a slight reduction in p53 induction at 10 hours?

      Although the western blot in Figure 4A gives this impression, this is probably due to loading variability (see the anti-β-actin loading control band). Moreover, over three independent experiments (Figure 4B), this apparent difference is not statistically significant. Taken together with other evidence that the p53-mediated DNA damage response is not affected in MZ-fam83fa-/- mutants, we are confident there is no detectable change in the level of stabilized p53 in the MZ-fam83fa-/- mutants compared to WT.

      Given the widely documented, dominant role of p53 in zebrafish IR-sensitivity, the authors should test if the IR sensitivity of fam83fa KO animals is p53-dependent, ideally via a cross into p53 null, but at least via injection of p53 morpholinos.

      We agree that p53 is widely documented as playing an essential role in the IR induced DNA damage response in zebrafish. All our experiments suggest there is no difference between the levels of p53 (protein or mRNA) or any of the p53-induced downstream effectors (that we tested) in MZ-fam83fa-/- mutants compared to WT embryos. This was true whether or not the embryos were subjected to genotoxic stressors, including IR treatment. We therefore conclude that the increased sensitivity phenotype we observe as a result of loss of Fam83fa is not caused by a change in p53 activity, at least not as part of the DNA damage response.

      Do autophagy inhibitors phenocopy the hatching and IR-sensitivity defects of fam83fa embryos? Do the inhibitors exacerbate the mutant phenotypes or synergize with M or Z mutant phenotypes? (I may have missed this but do M and Z fam83fa null embryos have any phenotype? Or do the phenotypes only manifest in MZ embryos?)

      This is an excellent question, and indeed one we attempted to address. We tried to optimize several autophagy inhibitors including bafilomycin A1, chloroquine and wortmannin, as well as the proteasomal inhibitor MG132. In addition, we tried to optimize the autophagy promoters Torin1 and rapamycin. Unfortunately, we regularly saw global effects in zebrafish embryos that were difficult to characterize and control by dosage. At the same time, we were also working to confirm the specific effects of these drugs on autophagy using p62 and LC3-I and LC3-II western blots, which themselves were difficult to optimize. We attempted to optimize these experiments for 6 months before the COVID lockdown occurred, at which point they were abandoned. We would be delighted for future researchers to continue these experiments, as we are now unable to pursue this further due to closure of the Smith lab, but we agree that these are very pertinent questions. We hope the descriptive data provided in our paper will prompt other researchers in the autophagy field to further explore the role of Fam83fa in autophagy. In response to the zygotic phenotype question, this was something we did not investigate. As there was no immediately apparent phenotype in the zygotic generation, for ease of screening larger numbers of embryos we proceeded immediately to the maternal-zygotic (MZ) generation.

      Reviewer #1 (Significance (Required)):

      The role of Fam83f is not known. This study in zebrafish might be the first to clarify the function of this protein in vivo.

      We thank the reviewer for this positive insight, and we agree that our work is the first do so in vivo.

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

      Fam83f is one of the proteins about which little is known. The authors Jones et al., tried to shed light on Fam83f function by knocking out the gene in zebrafish. Here they found that fam83 is expressed in the hatching gland and that larvae without Fam83f hatch significantly earlier than wild-type animals. The authors furthermore investigated the response of fam83f knock-out animals to DNA damage and found increased sensitivity to ionizing radiation and MMS. In order to find out more about Fam83f function in the DNA damage response, the authors performed RNA-seq after employing DNA damage and here they saw upregulation of several autophagy/lysosome-associated proteins and downregulation of some phosphatidylinositol-3-phosphate binding proteins, among others. Finally, the authors found that Fam83f is targeted to the lysosome. The manuscript is overall well written and clear in its general statement.

      We thank the reviewer for their encouraging comments.

      In the manuscript, the authors describe the investigation of several aspects of Fam83f function and particularly the role in hatching seems to be important for Fam83f as the gene is strongly expressed in the hatching gland and its absence leads to a clear and considerable earlier hatching. Unfortunately, all aspects of Fam83f function that are described in the manuscript are investigated very superficially, the conclusions are not supported by data and important controls are lacking. As such, the RNA-seq results are not confirmed by qRT-PCR, the role of the Fam83f LIR domain is not confirmed by co-IPs and it has not been investigated whether the presence of Fam83f in lysosomes is due to its degradation or whether it has a function in this cellular compartment.

      We thank the reviewer for their input and will address each point raised below: -

      • All aspects of Fam83f function are investigated superficially.

      We agree that we have not provided an in-depth analysis of the mechanistic role of Fam83fa. It was because there were so many roles that we decided to make this paper rather descriptive in nature, hoping that the observations will prove useful to other researchers who may wish to define the mechanistic roles of Fam83fa more deeply. Even without in-depth investigation, our findings are previously unreported and the phenotypes we report are clear. We have amended our manuscript to make it apparent that this paper is intended to be descriptive in nature, and we hope this addresses this issue.

      • Important controls are lacking - RNA-seq results are not confirmed by qRT-PCR

      We thank the reviewer for their comment. We did not include qRT-PCR data as a control for the RNA-seq data because 1) each RNA-seq experiment was repeated on three biological replicates across three independent experiments and 2) we conducted RNA-seq on two different MZ-fam83fa-/- mutant lines and only considered genes that were mis-regulated in both mutants. Taken together, we considered this to be sufficient validation for the manuscript. However, we also performed confirmatory qRT-PCR for several of the differentially expressed genes identified, including the three main PI(3)P binding genes. We have now included these data in the supplementary information as an additional control - see Figure S6G which is now also referred to in the main text, and additional primer sequences have been added to Table S1.

      • The role of the Fam83f LIR domain is not confirmed by co-Ips

      We agree with the reviewer that this is an important experiment, and we worked closely with Dr Brian Ludwig and Dr Karen Vousden (The Francis Crick Institute) to test this. We tried to express zebrafish Atg8 and Gabarap (the two main ATG8 proteins that bind to LIR domains) but were unable to express sufficient levels of protein to perform the co-Ips. The text in the manuscript has now been amended to reflect that this experiment is required to confirm the role of the putative LIR domain in Fam83fa.

      • *it has not been investigated whether the presence of Fam83f in lysosomes is due to its degradation or whether it has a function in this cellular compartment *

      Whilst we agree with the reviewer that this is an important question, we did not intend this paper to expand beyond a descriptive role of the observations we made following the loss of Fam83fa in vivo. These are important questions to follow up on to determine the mechanism of action of Fam83fa, and we hope that other researchers will pursue these avenues of investigation following the publication of our observations.

      Also, there is no leading concept in the manuscript. Starting from a role in hatching, the authors go to the DNA damage response and finally to the presence of Fam83f in lysosomes. How are these different aspects linked? Is the presence of Fam83f in lysosomes important for the suppression of hatching and how does Fam83f delays this process? (One would have wished that the authors would not have been that broad and were more focused on a particular aspect which then could have been investigated in depth.)

      We agree with the reviewer that the paper gives a broad overview of our observations and does not examine the underlying mechanisms in detail. However, we believe that descriptive papers such as this, where observations following genetic perturbation are reported, are equally important, providing as they do important foundational data for other researchers to take forward. We do postulate on the links between the hatching, DNA damage and lysosomal phenotypes we observe in the discussion section, and we have expanded on this following the reviewers' comments, to make our hypothesized link between these phenomena clearer.

      Specific comments: - All materials should be described in material and methods including the antibodies that have been used

      The antibodies used together with concentrations and catalog numbers are now in Materials and Methods

      • Abbreviations should be explained

      The manuscript has been revised to ensure all abbreviations are explained. We thank the reviewer for bringing this oversight to our attention.

      • Figure 4A: Levels of p53 should also be shown for untreated fam83f -/-KO1 and KO2 animals

      The authors thank the reviewers for raising this point. Extracts from untreated MZ-fam83fa-/- KO1 and KO2 embryos were not included on this particular blot, as p53 was observed to be undetectable in all embryos, across all our experiments (WT and both mutants) unless genotoxic stress was applied. No quantification could therefore be performed as the expression level was essentially zero. However, we have now included an example p53 western blot in Supplemental Figure 5A, which shows WT, MZ-fam83fa-/- KO1 and MZ-fam83fa-/- KO2 untreated blots for p53 (all undetectable) alongside treated embryos (detected).

      • Some references are missing (e.g. page 17, lane 320/321: As this group of cells arises....)

      This citation and reference have now been added; thank you to the reviewer for highlighting this omission.

      • Lane 369: The authors write about 4 KO lines but only two are shown in the figure.

      We thank the reviewer for this observation. In Figure 2B only KO1 and KO2 schematic diagrams are shown for simplicity (as these are the lines taken forward for further investigation). We have now amended the manuscript text to make this clear.

      • Lane 374/375: The NMD is not proven

      Absolutely - we have now revised the text to change this sentence accordingly and thank the reviewer for noting this.

      • Lane 380: how can RNA levels of fam83fa be upregulated when the gene has been knocked out? Why are these genes only upregulated in KO1? How relevant is this?

      This was a typographical error, and we are very grateful to the reviewer for picking up on this. It should have read 'fam83fb'. As nonsense-mediated decay and associated transcriptional adaptation have been previously reported in zebrafish, this finding may be of considerable interest to the community. It is a side observation, and not necessarily directly related to the role of Fam83fa in vivo, but we felt it important to include. Indeed, as a result of this observation we have recently shared our MZ-fam83fa-/- lines with another group who are planning to investigate precisely this question - why are fam83fb and fam83g only upregulated in KO1?

      • Figure 3C is not mentioned in the text and lacks any labelling

      Figure 3C is now clearly referred to in the text and a label added to the figure.

      • Lane 434/435: all relevant data should be shown (can be done as supplementary figure)

      We have now amended this to include an additional supplemental figure (Figure S5A).

      • Lane 434: The reference to the figure seems to be incorrect (5A4A)

      Amended accordingly - thank you for pointing out this mistake.

      • Figure 4C and 4D: what is the difference?

      Thank you to the reviewer for noticing this omission. These data are from t1 (+2hrs) and t2 (+10hrs) and have now been labelled accordingly.

      • S5C and S5D: why are there 3 clusters?

      We thank the reviewer for raising this as it has provided us with an opportunity to present our data more clearly. There are 3 clusters that represent the combination of the two first principal components, which are time and treatment. Therefore, the clusters represent i) untreated at t1, ii) treated at t1 and iii) treated at t2. However, having two plots with different color schemes made this confusing/misleading. We have now replaced the two PCA plots with one that is colored and labelled accordingly with the 3 aforementioned clusters.

      • Lane 495 to 505: What does this mean that the GO analysis shows upregulation and downregulation of endopeptidases and why "in contrast"?

      We thank the reviewer for this comment, and we agree that this paragraph was misleading/confusing. This has now been rewritten in the main text, clarifying that endopeptidases were consistently upregulated at both timepoints.

      Reviewer #2 (Significance (Required)):

      The strength of the manuscript is certainly that it provides inside into Fam83f function as there is not much known about Fam83f.

      We thank the reviewer for the positive comment, and we agree that very little is known about this highly conserved protein.

      These study is probably most interesting for people in the zebrafish and related fields as the authors convincingly show the expression of Fam83f in the hatching gland and also the earlier hatching in the absence of the protein is very clear.

      Thank you for the positive feedback.

      The weakness of the study is clearly that it does not provide an in-depth analysis. As such, it shows that Fam83f is involved in hatching and can delay the process but it remains elusive how this is achieved. (Likwise, also the investigation into the DNA damage response remains very superficial and does not prove a specific role for Fam83f in the DNA damage response or whether the increased sensitivity is more unspecifically caused by the absence of a gene or eventually even connected to the earlier hatching.

      Please refer to responses above (and changes made to the manuscript) clarifying that this study is intended to be descriptive, and provides important foundational data for further in-depth mechanistic studies by other researchers interested in the role of Fam83fa in vivo.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)):_ _ __ In their manuscript "Zebrafish reveal new roles for Fam83f in hatching and the DNA damage-mediated autophagic response", Jones et al. provide an interesting exploration for the function of a poorly studied protein, Fam83f in embryonic development. Using the zebrafish as a model organism, the study combines loss-of-function genetics, phenotypic analysis and RNA-sequencing to characterize and explore the result of Fam83f loss. Upon critical review of the manuscript and the results we offer suggestions to improve the manuscript (see 'minor technical issues'). Additionally, we would like to highlight a weakness of the study in making the connection between Fam83f to the observed phenotype (increased sensitivity to DNA damage), see 'major issues'.

      Major issues:

      Most of our concern stems from relatively incomplete connection of the loss of fam83f to increased sensitivity to DNA-damage and lysosome function.

      Please refer to comments above and changes made to the manuscript to clarify this is a descriptive paper that is not intended to provide in-depth mechanistic insight into the role of Fam83fa.

      Is the increased sensitivity in fam83f KO embryos a direct effect to fam83f loss? A rescue experiment (by introduction of Fam83fa mRNA into their KO2 fish line) in the presence of ionizing radiation would help us understand the functional role of this protein in this process. Furthermore, can overexpression of any of the down-regulated genes involved in lysosome function restore the early hatching phenotype or the sensitivity to DNA damage? Fam83fa rescue experiments would be very difficult to interpret - please see comments above and the corresponding changes to our manuscript.

      In terms of over-expressing some of the downregulated genes identified in the RNA-seq and qRT-PCR to see if the phenotype can be rescued, we feel these are excellent suggestions and we hope other researchers in future will attempt such experiments.

      Minor technical issues:

      -Methods line 203, clarify how many embryos were used per sample for RNA-seq (this was only described as 15 embryos in the main body results text).

      Text has been amended to clarify this. We thank the reviewer for noticing this oversight.

      -Comment about the expansion of fam83f orthologs in mammals (8) as opposed to only 2 in zebrafish

      We apologize for any confusion: mammals do not have 8 fam83f orthologs. Mammals and zebrafish have 8 FAM83 genes (FAM83A-FAM83H). Zebrafish, unlike mammals, have genome duplication and although mammals have only one FAM83F gene, zebrafish have two: Fam83fa and Fam83fb. We trust this clarifies this issue and believe this to be clear in our main text. However, we are happy to make any suggested amendments should the reviewer consider our wording confusing.

      -Supplementary figure 1C: please include representative images of secondary axis formation in fam83fa overexpressed Xenopus embryos.

      We have not included any images as these are already published in our related paper on FAM83F (Dunbar et al., 2020) which we refer to in the figure legend text. No additional images were captured specifically for this publication.

      -Provide more information about the mis-regulated genes in the RNA-seq analysis, how many are up or down regulated? Perhaps a better plot than a Venn diagram can be an MA-plot with the Venn diagram moved to a supplementary figure.

      The Venn diagrams in Figure 5A-C are to illustrate the number of differentially expressed genes that are shared between KO1 and KO2 (whether up or down regulated), and only those that are common to both lines are taken forward. Following the reviewer's comments, we have now displayed the behavior of the common genes across all replicates in one heatmap, with the data normalized to the WT untreated samples, and the normalized variance stabilized count indicates whether a gene is up or down regulated across each of the replicates and conditions. We believe this addresses the reviewer's comment as these data are now displayed in a more direct way and the genes that are consistently up or downregulated across all replicates (and indeed those that are not) can be clearly seen. We thank the reviewer for raising this and improving our data representation.

      -A better comparison of mis-regulated genes in the fam83f knockouts would be a comparison of KO2 and perhaps KO3, as the compensatory effects in KO1 can lead to additional indirect effect on the transcriptome. We understand the time and cost involved in this experiment and suggest that the differential gene expression analysis be performed individually on up or down regulated genes from KO2, or a comparison of such analysis will be provided with the differential gene expression analysis that was performed on shared mis-regulated genes between KO1 and KO2.

      The reviewer raises an excellent point. At the time of experimental design, we were concerned that omitting KO1 in favor of another line (e.g. KO3) would bias our results by excluding potentially important data. Similarly, as transcriptional adaptation occurs in a sequence specific manner, and the phenotype was present in KO1 regardless, we didn't want to exclude these data. However, with hindsight, we agree that it may have been prudent to exclude KO1 on this basis, and we may have seen an increased concordance of differentially expressed genes (DEGs) between KO2 and KO3. However, this is not possible to repeat now due to the Smith lab closing, and our documented findings are valid and important regardless. We acknowledge however that, with hindsight, what the reviewer suggests may have been better experimental design.

      -Can you confirm with the RNA-seq analysis that fam83g is upregulated in KO1 as opposed to KO2? (i.e. can the compensatory analysis you have observed with qRT-PCR be confirmed with the RNA-seq data?)

      This is an excellent question, and we thank the reviewer for raising this. fam83fb passed our threshold for significance to be deemed as differentially expressed (upregulated) in KO1 only, in accordance with our qRT-PCR data. fam83g did not pass the significance threshold, but perhaps this is not surprising as both fam83fb and fam83g are expressed at particularly low levels to start with and would probably require much greater sequencing depth to be detected.

      Reviewer #3 (Significance (Required)):

      There is fundamental value in clarifying the in vivo function of poorly characterized protein-coding genes. This study fills a gap in the literature, but the broader conceptual impact is limited. The authors do a thorough job at generating and characterizing CRISPR/Cas9 mediated knock-out zebrafish animals. It is further commended that the authors do a meticulous job in a quantitative description of the resulting phenotype. This is a thorough study, with the only major concern being the lack of rescue experiments that would be needed to substantiate the the role of fam83f in sensitivity to DNA damage and lysosome function.

      We thank the reviewer for their comments and trust we have addressed the issues concerned with the changes described above.

      PeerReviewed
    2. EMBOpress 24 Jun 2024

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

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      Referee #3

      Evidence, reproducibility and clarity

      In their manuscript "Zebrafish reveal new roles for Fam83f in hatching and the DNA damage-mediated autophagic response", Jones et al. provide an interesting exploration for the function of a poorly studied protein, Fam83f in embryonic development. Using the zebrafish as a model organism, the study combines loss-of-function genetics, phenotypic analysis and RNA-sequencing to characterize and explore the result of Fam83f loss. Upon critical review of the manuscript and the results we offer suggestions to improve the manuscript (see 'minor technical issues'). Additionally, we would like to highlight a weakness of the study in making the connection between Fam83f to the observed phenotype (increased sensitivity to DNA damage), see 'major issues'.

      Major issues:

      Most of our concern stems from relatively incomplete connection of the loss of fam83f to increased sensitivity to DNA-damage and lysosome function.

      Is the increased sensitivity in fam83f KO embryos a direct effect to fam83f loss? A rescue experiment (by introduction of Fam83fa mRNA into their KO2 fish line) in the presence of ionizing radiation would help us understand the functional role of this protein in this process. Furthermore, can overexpression of any of the down-regulated genes involved in lysosome function restore the early hatching phenotype or the sensitivity to DNA damage?

      Minor technical issues:

      • Methods line 203, clarify how many embryos were used per sample for RNA-seq (this was only described as 15 embryos in the main body results text).
      • Comment about the expansion of fam83f orthologs in mammals (8) as opposed to only 2 in zebrafish
      • Supplementary figure 1C: please include representative images of secondary axis formation in fam83fa overexpressed Xenopus embryos.
      • Provide more information about the mis-regulated genes in the RNA-seq analysis, how many are up or down regulated? Perhaps a better plot than a Venn diagram can be an MA-plot with the Venn diagram moved to a supplementary figure.
      • A better comparison of mis-regulated genes in the fam83f knockouts would be a comparison of KO2 and perhaps KO3, as the compensatory effects in KO1 can lead to additional indirect effect on the transcriptome. We understand the time and cost involved in this experiment and suggest that the differential gene expression analysis be performed individually on up or down regulated genes from KO2, or a comparison of such analysis will be provided with the differential gene expression analysis that was performed on shared mis-regulated genes between KO1 and KO2.
      • Can you confirm with the RNA-seq analysis that fam83g is upregulated in KO1 as opposed to KO2? (i.e. can the compensatory analysis you have observed with qRT-PCR be confirmed with the RNA-seq data?)

      Significance

      There is fundamental value in clarifying the in vivo function of poorly characterized protein-coding genes. This study fills a gap in the literature, but the broader conceptual impact is limited. The authors do a thorough job at generating and characterizing CRISPR/Cas9 mediated knock-out zebrafish animals. It is further commended that the authors do a meticulous job in a quantitative description of the resulting phenotype. This is a thorough study, with the only major concern being the lack of rescue experiments that would be needed to substantiate the the role of fam83f in sensitivity to DNA damage and lysosome function.

      PeerReviewed
    3. EMBOpress 24 Jun 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Fam83f is one of the proteins about which little is known. The authors Jones et al., tried to shed light on Fam83f function by knocking out the gene in zebrafish. Here they found that fam83 is expressed in the hatching gland and that larvae without Fam83f hatch significantly earlier than wild-type animals. The authors furthermore investigated the response of fam83f knock-out animals to DNA damage and found increased sensitivity to ionizing radiation and MMS. In order to find out more about Fam83f function in the DNA damage response, the authors performed RNA-seq after employing DNA damage and here they saw upregulation of several autophagy/lysosome-associated proteins and downregulation of some phosphatidylinositol-3-phosphate binding proteins, among others. Finally, the authors found that Fam83f is targeted to the lysosome. The manuscript is overall well written and clear in its general statement. In the manuscript, the authors describe the investigation of several aspects of Fam83f function and particularly the role in hatching seems to be important for Fam83f as the gene is strongly expressed in the hatching gland and its absence leads to a clear and considerable earlier hatching. Unfortunately, all aspects of Fam83f function that are described in the manuscript are investigated very superficially, the conclusions are not supported by data and important controls are lacking. As such, the RNA-seq results are not confirmed by qRT-PCR, the role of the Fam83f LIR domain is not confirmed by co-IPs and it has not been investigated whether the presence of Fam83f in lysosomes is due to its degradation or whether it has a function in this cellular compartment. Also, there is no leading concept in the manuscript. Starting from a role in hatching, the authors go to the DNA damage response and finally to the presence of Fam83f in lysosomes. How are these different aspects linked? Is the presence of Fam83f in lysosomes important for the suppression of hatching and how does Fam83f delays this process? (One would have wished that the authors would not have been that broad and were more focused on a particular aspect which then could have been investigated in depth.)

      Specific comments:

      • All materials should be described in material and methods including the antibodies that have been used
      • Abbreviations should be explained
      • Figure 4A: Levels of p53 should also be shown for untreated fam83f -/-KO1 and KO2 animals
      • Some references are missing (e.g. page 17, lane 320/321: As this group of cells arises....)
      • Lane 369: The authors write about 4 KO lines but only two are shown in the figure.
      • Lane 374/375: The NMD is not proven
      • Lane 380: how can RNA levels of fam83fa be upregulated when the gene has been knocked out? Why are these genes only upregulated in KO1? How relevant is this?
      • Figure 3C is not mentioned in the text and lacks any labelling
      • Lane 434/435: all relevant data should be shown (can be done as supplementary figure)
      • Lane 434: The reference to the figure seems to be incorrect (5A<->4A)
      • Figure 4C and 4D: what is the difference?
      • S5C and S5D: why are there 3 clusters?
      • Lane 495 to 505: What does this mean that the GO analysis shows upregulation and downregulation of endopeptidases and why "in contrast"?

      Significance

      The strength of the manuscript is certainly that it provides inside into Fam83f function as there is not much known about Fam83f.

      These study is probably most interesting for people in the zebrafish and related fields as the authors convincingly show the expression of Fam83f in the hatching gland and also the earlier hatching in the absence of the protein is very clear.

      The weakness of the study is clearly that it does not provide an in-depth analysis. As such, it shows that Fam83f is involved in hatching and can delay the process but it remains elusive how this is achieved. (Likwise, also the investigation into the DNA damage response remains very superficial and does not prove a specific role for Fam83f in the DNA damage response or whether the increased sensitivity is more unspecifically caused by the absence of a gene or eventually even connected to the earlier hatching.

      PeerReviewed
    4. EMBOpress 24 Jun 2024

      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

      In this manuscript, Jones et al. report on a potential role for fam83fa in zebrafish hatching, radiation response and autophagy. The authors are commended for generating multiple KO lines and maternal-zygotic embryos for analysis. However, important controls are lacking and the data is circumstantial throughout with very little mechanistic insight into the precise roles, if any, of fam83f in these processes.

      1. Validation of the KO phenotypes (hatching, IR sensitivity) requires rescue with WT fam83fa WT mRNA, but not 1-500 or fam83fb mRNA.
      2. While the hatching phenotype (Fig 3) is convincing, there is no data on HG development in the null embryos. Does the HG develop normally in the absence of fam83fb? If so, this would support the authors conclusions that the role of fam83fb is functional rather than developmental (indirect effect). In situs as in Fig.1 might be helpful here.
      3. While the IR sensitivity phenotype (Fig S4) is convincing, IR-induced cell death/apoptosis was not analyzed. There is a large literature describing straightforward assays for cell death/apoptosis detection in zebrafish with assays such as acridine orange or TUNEL labeling, or active casp3 whole-mount IF. Is IR-induced cell death enhanced in fam83fa KOs?
      4. Similarly, there are multiple tools to assay autophagy in zebrafish (e.g., Moss et al., Histochem Cell Biol 2020, PMC7609422; Mathai et al., Cells 2017, PMC5617967). Is autophagy affected in the KOs, with or without IR? These experiments might directly implicate fam83fa in autophagy.
      5. Figure 4: Isn't there a slight reduction in p53 induction at 10 hours?
      6. Given the widely documented, dominant role of p53 in zebrafish IR-sensitivity, the authors should test if the IR sensitivity of fam83fa KO animals is p53-dependent, ideally via a cross into p53 null, but at least via injection of p53 morpholinos.
      7. Do autophagy inhibitors phenocopy the hatching and IR-sensitivity defects of fam83fa embryos? Do the inhibitors exacerbate the mutant phenotypes or synergize with M or Z mutant phenotypes? (I may have missed this but do M and Z fam83fa null embryos have any phenotype? Or do the phenotypes only manifest in MZ embryos?)

      Significance

      The role of Fam83f is not known. This study in zebrafish might be the first to clarify the function of this protein in vivo.

      PeerReviewed
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    Dynamic map illuminates Hippo to cMyc module crosstalk driving cardiomyocyte proliferation
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    1. EMBOpress 24 Jun 2024

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      Reply to the reviewers

      We thank the reviewer for their careful evaluation and constructive criticisms of our manuscript. We also appreciate the positive review by all three reviewers. The reviewers noted:

      • "The computational model in this manuscript can be a tool to discover unknown molecular pathways interactions in cardiomyocyte proliferation."
      • "This is an interesting study reporting the generation of a computational model of cardiomyocyte proliferation, which predicts molecular drivers of cell cycle progression."
      • "The model provides a convenient systems framework to prioritize potential signaling drivers of therapeutic modulators of cardiomyocyte proliferation." We have responded to all reviewer comments and have outlined the corresponding additions and changes to the manuscript.

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

      Summary:

      In the manuscript by Harris et al. titled "Dynamic map illuminates Hippo to cMyc module crosstalk driving cardiomyocyte proliferation," the authors developed a computational model of cardiac proliferation signaling that incorporates various regulatory networks (cytokinesis, mitosis, DNA replication, etc.) to predict molecular drivers (genes) that support cardiomyocyte proliferation. Published research articles on cardiomyocyte proliferation in multiple contexts (different species, ages, in vitro and in vivo, etc) were used to build and validate the computational model. The authors found using their model that different processes during cardiomyocyte proliferation may or may not be context-dependent. For example, DNA replication is regulated differently in conditions with high Neuregulin compared to high YAP, whereas mitosis and cytokinesis regulation is similar in these conditions. To experimentally validate their model, the authors used an in vitro system to test the effects of YAP on 3 connected pathways; in the context of YAP activation, inhibition of PI3K, cMyc, or FoxM1 was combined to assay cell-cycle markers in cultured neonatal rat ventricular cardiomyocytes. Cell-cycle marker expression in cardiomyocytes was attenuated by inhibition of cMyc or PI3K, suggesting that these pathways are involved in YAP-mediated cardiomyocyte proliferation. While this model can be a good tool to gain new insights on interactions between molecular pathways, there are a few questions to be addressed prior to publication.

      We appreciate the Reviewer's positive remarks about important findings in our manuscript and the ability of our model to be a tool to gain insights on interactions between molecular pathways to regulate cardiomyocyte proliferation. We have strived to address their points, as shown below.

      Major Comments:

      1. One of the potential uses for this computational model is to discover new interactions between known pathways that are involved in cardiomyocyte proliferation. However, this would be more powerful if factors such as species, age (neonate vs. adult), and experimental design (in vivo vs. in vitro) were accounted for, as new node inputs or a combination of existing node input activity values. This is very important because cardiomyocyte proliferation can drastically vary depending on these experimental factors. We agree that future extensions of this model accounting for species, age, and experimental design may enable an understanding of how these factors regulate proliferation. While this model's predictions are most relevant to immature cardiomyocytes, we note that it is the first systems model of the molecular network regulating cardiomyocyte proliferation. We extensively validated it against neonatal cardiomyocyte literature and then made new predictions regarding Hippo-cMyc pathways, which we validated in new cardiomyocyte experiments and against data in adult mice. This provides a strong foundation for future extensions. We now address this potential in the Discussion:

      "While our model's predictions are most relevant to immature cardiomyocytes, it is the first systems model of the molecular network regulating cardiomyocytes. In the future, we hope that we and others may extend this model to identify how factors like species, age, and experimental design regulate proliferation. However, these endeavors would span multiple manuscripts, and the field currently lacks sufficient stage-specific data. For example, a previous foundational computational model of cardiomyocyte electrophysiology (Luo and Rudy, Circ Res 1994) focused on adult guinea pigs. This model became the foundation for a range of developmental and species-specific models in electrophysiology (Tusscher et al, AJP 2004,; Courtemanche eta al, AJP 1998; Paci et al, ABME 2013). We believe the open availability of our code will enable similar dissemination and extension for additional factors." Line 651-661

      For reference:

      Luo and Rudy, Circ Res 1994, >2.1k citations; Tusscher et al, AJP 2004, >1.7k citations; Courtemanche et al, AJP 1998, 1.5K citations; Paci et al, ABME 2013, 147 citations

      The finding that cardiomyocyte proliferation is context-dependent is very exciting and warrants further investigation/validation. The authors state that different sets of nodes/modules are affected by neuregulin activation compared to YAP activation. This should be experimentally validated - qPCR/Western blots on sets of genes that are predicted to be differentially regulated in the high neuregulin context vs the high YAP context.

      We agree that the model's prediction of context-dependent cardiomyocyte proliferation is very exciting. To further validate these predictions, we have performed additional experiments to validate context-dependent changes of phospho-ERK treated with Nrg and TT10. Using a high throughput capillary electrophoresis western blot system, we observed that with a short treatment of 30 min, Nrg induces greater phosphor-ERK compared to TT10, which validates our model predictions at short time intervals. Additionally, the model predicted greater p-AKT with 30 min treatment with Nrg compared to TT10. To validate this prediction, we now compare to Western blots from Hara et al. examining p-AKT in Nrg and TT10-treated cells. Validating our model predictions, their data show that Nrg induces greater p-AKT than with TT10. We have added new panels C, D, and E to Figure 4.

      Figure 4: Influence of node knockdowns shifts with context, revealing crosstalk from Hippo to Growth Factor modules.

      (A) Total influence of node knockdowns on the DNA replication, mitosis, and cytokinesis modules, compared across multiple signaling contexts: baseline, high Nrg, and high YAP. Total influence sums the overall effect of a node knockdown on a network module. (B) The total influence of each network module varies depending on whether a basal state, high Nrg, or high YAP signaling context is applied. (C) Capillary electrophoresis western blot for phosphorylated ERK, beta-actin, and GAPDH from neonatal cardiomyocytes treated with Nrg or TT10 for 30 min. (D) Model predictions of AKT and ERK activity of acute response to Nrg or TT10 (time constants for gene expression set to 100). (E) Quantification of effects of Nrg or TT10 treatment on p-ERK (from Western blot in panel C, n = 3) or p-AKT (from Western blot from (Hara et al., 2018), n = 1).

      The overall description of the model can be improved. For example, how are the input and parameters set to validate or predict different experimental observations? What is the steady state activity of each of the nodes and does this make sense biologically? Including a few more sentences to explain the model would help with overall understanding for an uninformed reader.

      We have addressed the following questions provided by the reviewer in the methods and results section of the manuscript:

      How are the input and parameters set to validate or predict different experimental observations?

      __ __"At baseline, input reaction weight parameters (w) were set based on information from the literature describing the baseline state of these inputs in the heart (each input reaction weight can be found in Supplemental File 1). To simulate experiments with biochemical stimuli, input reaction weights were increased to 0.8 or 1. To simulate experiments with inhibition or knockdown, the corresponding maximum species value (ymax) was set to 0.1 or 0. Complete annotations for all validation simulations are provided in Supplemental File 2." Line 154-160

      What is the steady-state activity of each of the nodes and does this make sense biologically?

      "Steady-state activity of model nodes was obtained by running the model until there was a __ __

      Minor Comments:

      Line 124 - The use of "species" and "reactions" is confusing to uninformed readers. Do you mean nodes and interactions/bridges?

      We now further clarify these terms in the manuscript:

      "As in past network models (Zeigler et al., PMID 27017945; Tan et al., PMID 29131824; Kraeutler et al PMID 21087478), species (or nodes) refer to a small molecule, gene, protein, or process. Reactions (or edges) are activating or inhibiting relationships between network species." Line 143-146

      Line 130 - I could not find Supplementary File 2, which includes the references

      We apologize for the error. Supplementary File 2 references articles and resources used to build the model. These files are now attached.

      Line 257 - What is the meaning of the directional arrows in Fig 1A?

      We clarified the Fig 1A legend:

      "Arrows between modules represent one or more reactions that link species from one module to species in another module. " Line 594-595

      Line 301 - Unclear what default values mean here. Please elaborate and provide an example of how this is reasonable.

      We have added further descriptions of default values in reference to the parameters to the manuscript.

      "A previous study identified default values of the parameters (ymax, EC50, W, etc.) that most accurately predict the results of knockdown screens compared to a model where all biochemical parameters were measured experimentally (Kraeutler et al 2010). Subsequent studies started from these default values and further demonstrated that model accuracy was robust to random variation in the parameters (Tan et all 2017, Zeigler et al 2017). Consistent with these prior models, we performed robustness analysis that demonstrates that the CM proliferation model accuracy (compared against 78 experiments) is maintained at >80% with up to 35% variation in ymax, 30% variation with w, and a variation of >50% with EC50 (Figure S4)." Line 305-312

      Supplemental FigS2 - Why would knockdown of PKA, Lats1 or SMAD3 have the exact same effects on node activation? This is seen with multiple other genes was well (IGF and FGF for example).

      PKA, Lats1, and SMAD3 all inhibit cell cycle progression in part through cMyc. Therefore, their knockdown have similar effects on downstream signaling and proliferation. Similarly, IGF and FGF both stimulate Ras and PI3K via similar mechanisms, which is consistent with experimental studies of IGF- and FGF-dependent proliferation.

      Reviewer #1 (Significance (Required)):

      The computational model in this manuscript can be a tool to discover unknown molecular pathway interactions in cardiomyocyte proliferation. The novelty lies in the ability to adjust any parameter or the entire setting/context. While this sounds very exciting, improvement of the model to account for age, experimental conditions (in vivo vs in vitro), and species (human, pig, mouse) could lead to increase prediction accuracy. Additionally, more robust validation of context-dependent interactions between signaling pathways would also increase overall enthusiasm for the manuscript. Readers interested in a systems biology approach to cardiomyocyte proliferation, or researchers probing molecular interactions during cardiomyocyte proliferation would be interested in using such a model to discover novel contexts/combinations in which cardiomyocyte proliferation is more likely.

      The reviewer comes from a varied training background and is qualified to evaluate this manuscript in full - BS in biomedical engineering and mathematics. PhD in biomedical engineering (molecular biology, cardiac electrophysiology). Postdoctoral training in cardiac regeneration and immunity.

      We appreciate the positive comments about our model of the cardiomyocyte proliferation network. As described above, we believe that we have addressed the concerns with additional experimental validation.

      The manuscript submitted by Harris and colleagues collates a molecular map of cardiomyocyte cell cycle activation through mathematical modeling of previously published experimental results. They attempt to validate the constructed model several ways: 1) through testing results compiled from additional literature, 2) through in vitro analysis, and 3) through in vivo supporting data. When validating through additional literature the model proves quite reliable particularly for prediction of effects on synthesis, mitosis, and cytokinetic entry, but was less reliable (or insufficiently tested) at predicting completion of these stages as determined by polyploidization and multinucleation. A potentially novel observation which arose from the model - that hippo nodule connects to the growth factor nodule through PI3K, Myc, and FoxM1 - was partially confirmed with in vitro experiments, though a few experiments are warranted.

      We appreciate the reviewer's recognition of the important contributions of this model of the cardiomyocyte proliferation network. We have addressed the concerns below.

      Major comments:

      • The model is admittedly weakest in its handling of completion of cytokinesis resulting in new daughter cells (i.e. proliferation) versus failure to complete either M phase or cytokinesis resulting in the much more common cellular phenotypes - polyploidy and multinucleation. Notably, very few molecules were "tested" for this output (figure 2) and this proved the least reliable aspect of the model/map. I wonder if the authors consulted the literature on somatic polyploidization at all when building the model (files not provided as indicated, see minor comment 1 below )? And if not, would doing so help strengthen this arm of their map? There are some great reviews on the topic (see PMIDs 25921783, 23849927, 30021843) - while admittedly much of the work is done on other cell types (i.e. trophoblast giant cells and hepatocytes) maybe understanding the molecular intricacies in these cells could be incorporated to strengthen the predictive model in cardiomyocytes. Notably, PMID 23849927 even provides a table of citations about key nodes in the model influencing polyploidy. To validate this model, we used entirely cardiomyocyte specific studies. We appreciate the reviewer's reference to PMID 23849927, which enabled us to add two additional experiments to the validation table in Figure 2. That paper found that overexpression of either cMyc or cyclin D increases polyploidy, which both matched our new simulations in the updated Figure 2.

      Motivated by the reviewer's citation of PMID 23849927, we further validated the model against polyploidization data from multiple cell types, finding an 85.7% accuracy (6 of 7 experiments) as now shown in Supplementary Figure S7.

      We included an additional discussion of polyploidization in the manuscript.

      "Our model validation is notably weakest in predicting experiments on polyploidization, indicating a need to better characterize polyploidy and cytokinesis pathways. Because such data are limited in cardiomyocytes, we performed an additional validation against polyploidization experiments from other cell types as summarized in Pandit et al. Our CM proliferation model predicted 85% (6 of 7) experiments. Future experiments are needed to identify conserved or differential mechanisms of polyploidization and cytokinesis in cardiomyocytes." Line 587-594

      • Paragraph on the cytokinesis module (lines 364-377) is confusing - not sure what the takeaway message is. Also, while progression through G1/S and G2/M are "required" for cytokinesis they on their own are not sufficient (lines 366-368), this perhaps goes back to major comment 1. We agree this sentence was confusing, it was meant to be introductory rather than stating a particular result. We removed that sentence and further revised our description of the output module to clarify the model structure:

      "The output module interlinks the phenotypic outputs of the other modules, representing how experimentally measured aspects of cell cycle activity (DNA replication by EdU or Ki67), mitosis by phospho-Histone 3 (pHH3), abscission by cytokinetic midbody converge on polyploidy, binucleation, or cytokinesis (e.g. completed proliferation) (Figure 1G)." Line 283-286

      Minor comments:

      • Use of the word "Proliferation" should be reserved for situations where the authors can clearly say a new daughter cell was born. In many instances, "cell cycle activation" or "cell cycle progression" might be better terms. As suggested by the reviewer, we now use "cell cycle progression" in 7 instances, reserving "proliferation" for cell cycle progression through cytokinesis. In the remaining 90 instances, we refer to proliferation based on the model's predictions of completed cell division based on the combined DNA replication, mitosis, and cytokinesis pathways in the "output module". We retain "proliferation" in the title because the model encompasses the entire proliferation process from cell cycle entry through cytokinesis.

      • Supplementary Files 1 & 2 or Supplementary Document 2 were not provided or not found during review, thus we were unable to confirm which literature were used to build and validate the model. Thank you, we have included Supplementary Files 1 and 2 along with supplementary document 2 in the submission.

      • Figures are too small, particular Figure 1 We have enlarged Figure 1.

      • "E2F" should be specified as E2F1-3 yield quite distinct results from E2F7/8. We have changed "E2F" to "E2F123"

      • Text corresponding to Figure 5 does not reference most of the panels in the Figure. i.e. figures are not "cited" in the text We have made sure that each panel in Figure 5 is referenced in the text addressing the figure. We have also bolded all references to Figure 5.

      • Figure 5C - why is there no bars for PI3K. Text claims it was predicted by the model, but the data are missing? We apologize for the confusion regarding Figure 5C, in which the bar for PI3K was near zero. We now clarify this in the legend.

      "Predicted DNA replication and mitosis activity is close to zero when PI3K is inhibited alone and when PI3K is inhibited in combination with TT10 treatment."

      • Data provided in figure 5D & E are insufficient on their own to claim "proliferation". Perhaps adding total cardiomyocyte numbers, where one would expect expansion compared to control. We agree that Ki67 and pH3 are not sufficient to claim "proliferation", so we modified the Figure 5 legend to:

      "Prediction and experimental validation of cardiomyocyte cell cycle progression mediated by the Hippo pathway via PI3K, cMyc, and FoxM1."

      We previously found that cardiomyocyte numbers without live tracking are not sufficient to robustly measure proliferation (Woo et al, J Mol Cardiol, 2019).

      • Consider adding a details about the p-values to the figure legend in figure 5. Thank you for this suggestion p-value information has been added to the legend of Figure 5. We use *** Our literature-based validation in Figure 2 focused on 78 experiments that examined well-established and corroborated aspects of cardiomyocyte proliferation. Later in the paper, we focused on a newly predicted mechanism of cardiomyocyte proliferation involving small number of comparisons that would naturally have a lower a priori probability of validation in vitro neonatal experiments (Figure 5) and adult mouse experiments (Figure 6). Therefore, in the revised text we focus on the specific comparisons rather than statistics.

      "Based on predictions from this validated model, we hypothesized that YAP drove proliferation via PI3K, cMyc and FoxM1. To test this model-driven hypothesis, we accurately predicted TT10-induced DNA replication that is suppressed by inhibition of PI3K, cMyc and to a lesser extent FoxM1 (Figure 5D). These model predictions were further validated using RNA-seq and ATAC-seq data from adult mouse hearts showing that constitutively active YAPS5A induces expression of Myc and FoxM1 as well as increased chromatin accessibility at PI3Kca and Myc." Line 454-468

      In the discussion, we add:

      "Further model revision is needed based on these molecular mechanisms of YAP-TEAD-Myc interactions to distinguish between chromatin accessibility, transcription factor binding, and gene expression." Line 649-651

      As it stands now, the generated map largely constitutes already known details offering few if any new insights; however, if updated as new results arise AND made available as a public tool, the model could prove to be a highly valuable resource to the field.

      We thank the reviewer for recognizing our model as a valuable resource and public tool. We have made our model publicly available on GitHub at https://github.com/saucermanlab/Cardiomyocyte-Proliferation-Network.

      The virtual knockdown screens in Figure 3, 4 and 5 provide a wide range of new insights, which we clarify in new text.

      "Because this is a literature-based network model, each component or direct interaction has been studied individually. However, our model makes much broader predictions of how these components interact to regulate proliferation, beyond the ~30 papers available for validation on the response of this system to perturbations shown in Figure 3. For example, Supplemental Figure S3 provides ~5000 predictions of how each protein responds to knockdown of every other protein. These predictions led to new insights into how YAP regulates proliferation via cMyc (experimentally validated in Figure 5 in vitro and Figure 6 in vivo), as well as many other insights that can be validated in future studies. These future studies will be aided by the open-source availability of our model on GitHub." Line 563-571

      __ I have expertise in cardiomyocyte cell cycle and polyploidization.__

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

      The authors generated a computational model of cardiomyocyte proliferation, which predicts molecular drivers of cell cycle progression. Interestingly, the model correctly predicts the outcome of 95% independent experiments from the literature. The model also elucidated crosstalk between the growth factor and Hippo modules and the authors identified key hubs for which the Hippo signaling pathway regulates cardiomyocyte proliferation. The model provides a convenient systems framework to prioritize potential signaling drivers of therapeutic modulators of cardiomyocyte proliferation.

      Reviewer #3 (Significance (Required)):

      This is an interesting study reporting the generation of a computational model of cardiomyocyte proliferation, which predicts molecular drivers of cell cycle progression. The program may provide a convenient framework prioritizing potential signaling drivers of therapeutic modulators of cardiomyocyte proliferation. However, the overall impact of the study appears modest since it is unclear whether the study allows elucidation of the unique properties of cardiomyocyte proliferation in adult hearts (i.e. they hardly proliferate) and the validation study was conducted only in neonatal myocytes. The field has seen many studies with neonatal myocytes but the findings are not always translatable to adult cardiomyocytes.

      We thank the reviewer for recognizing the importance of our work that provides a framework for prioritizing potential signaling drivers of therapeutic modulators of CM proliferation.

      Neonatal studies are the most prevalent with cardiomyocyte proliferation literature, making it the most robust starting point that allows for rigorous validation. Based on the high performance of the model against neonatal data, in the future we expect this model to be a stepping stone towards adaptions to understand differences in the adult cardiomyocyte proliferation network. We have updated our model discussion on future directions on this point.

      "While our model's predictions are most relevant to immature cardiomyocytes, it is the first molecular network model of cardiomyocyte proliferation. In the future, this model will enable extensions to identify how factors like species, age and experimental design regulate proliferation. However, such endeavors would span multiple manuscripts and the field currently lacks sufficient stage-specific data. For example, the highly influential computational model of Luo and Rudy focused on adult guinea-pig cardiomyocyte electrophysiology (Luo and Rudy, Circ Res 1994). That model became the foundation for a wide range of development- and species-specific models in electrophysiology (Tusscher et al, AJP 2004,; Courtemanche eta al, AJP 1998; Paci et al, ABME 2013). We believe the open availability of our code will enable similar dissemination and extension for additional factors regulating cardiomyocyte proliferation." Line 655-665

      The authors described that "Literature articles used for model development came from multiple cell types due to limited CM data." It is unclear whether this would allow the identification of unique mechanisms present in cardiomyocytes. As the authors admitted, the fact that the model predictions and experimental observations for polyploidization did not match clearly suggests the complexity surrounding the possibility of cell phenotypes in cardiomyocyte populations. The authors could have addressed whether this model allows the identification of unique mechanisms mediating cardiomyocyte proliferation in the adult heart.

      Although we necessarily included literature on other cell types to support network reactions, all of the experimental validation in Figure 2 was with cardiomyocyte data (~33 publications). 80% of experiments were from neonatal CMs, 10% from adult CMs, 5% from in vivo studies, and the other 5% from hiPSC-derived cardiomyocytes as annotated in Supplemental File 3.

      At this time, there is insufficient data from which to make a model focused only on adult CMs. The mode's open-source availability enables future extensions that examine age and species-dependent mechanisms of cardiomyocyte proliferation. We updated the manuscript, addressing the ability of our model to adapt to new information.

      "This model provides an initial network framework for integrating additional discoveries in cardiomyocyte proliferation. As more information becomes available in cardiomyocyte proliferation literature the model can be adapted. Additionally, the field can use our open-sourced model to adapt this model to other developmental stages or species." Line 671-674

      Acknowledging the limited data on cardiomyocyte polyploidy, we performed a new separate validation of 7 experiments in non-myocytes from PMID 23849927, finding an 85.7% accuracy (new Supplementary Figure S7).

      Please provide more information regarding the rationale for having six modules in the authors' model, including the growth factor and the Hippo pathway.

      We revised the text to clarify the motivation for the six modules:

      "Our initial review of the literature indicated multiple complex molecular pathways that regulate cardiomyocyte proliferation, including growth factors, Hippo signaling, G1/S transition, G2/M transition, or cytokinesis pathways (Hashmi and Ahmad, PMID: 31205684; Payan et al, PMID: 30930108; Moral et al., PMID: 35008660; Wang et al., PMID: 30111784; Johnson et al., PMID: 34360531). Several review articles (Zheng et al, PMID: 32664346; Mia and Singh, PMID: 31632964; Diaz Del Moral et al, PMID: 35008660; Besson et al, PMID: 18267085; Wang et al, PMID: 19216791)) also organized the literature based on these distinct pathways or processes, which we used to define the boundaries of the six modules. However, how these molecular pathways work together is not well characterized. Therefore, we designed the model to incorporate each of these established modules and how they work together to drive cardiomyocyte proliferation." Line 550-557

      The extent of cardiomyocyte proliferation at baseline is very low in the adult heart. The model identified 25 nodes that may influence baseline proliferation. Is there any evidence to support the involvement of these mechanisms in baseline cardiomyocyte proliferation in vivo?

      We agree with the reviewer that proliferation at baseline is very low in the adult heart, and also rather low in neonatal cardiomyocytes. As shown in Figure S4A, we performed a virtual knockdown screen under baseline conditions that showed that no genetic knockdowns caused a substantial decrease in DNA replication or cytokinesis, consistent with a low baseline proliferation rate.

      We describe this point about baseline proliferation in revised text:

      "A complete virtual knockdown screen of the model was done under baseline conditions in Figure S4A, which showed that no knockdowns caused substantial decreases in DNA replication or cytokinesis. This is consistent with a low baseline proliferation rate described in cardiomyocyte literature." Line 354-357

      The validation study was conducted with neonatal rat ventricular cardiomyocytes. This study could have been repeated with adult cardiomyocytes since they are more resistant to proliferation and, thus, the Myc may not work as expected. In addition, the authors could have commented on the mechanism through which chromatin opening and YAP allow transcription of Myc in the heart.

      We agree that Myc is likely less proliferative in adult hearts. While our model was extensively validated against neonatal cardiomyocytes (Figure 2 for literature, Figure 5 for new neonatal experiments), only 10% of literature-based validations in Figure 2 are from adult cardiomyocytes due to limited data. However, in Figure 6 we validate YAP-dependent signaling to Myc, PI3K, and FOXM1 using RNA-seq and ATAC-seq data from Monroe et al. from adult mouse cardiomyocytes in vivo. While molecular mechanisms of YAP regulation of Myc are not characterized in the heart, based on the reviewer's suggestion, we add new discussion on YAP-Myc interaction in other cells:

      "Overexpression of Myc induces cardiomyocyte proliferation in vitro and in vivo in several contexts, with open chromatin and Myc binding near mitotic genes (PMID: 32286286). But to our knowledge, crosstalk of YAP with Myc has not been reported in the heart. Our model prediction and experiments in neonatal cardiomyocytes support a YAP-TEAD-Myc pathway for cardiomyocyte proliferation. Further, our analysis of ATAC-seq and RNA-seq data from Monroe et al. validate that YAP induces Myc chromatin availability and gene expression in adult mouse hearts.

      In MDA-MB-231 breast cancer cells, YAP/TAZ/TEAD bind directly to Myc enhancers through chromatin looping, with decreased acetylation of H3K27 and cell proliferation upon YAP/TAZ knockdown (26258633). YAP-TEAD-Myc signaling regulates the proliferation of cancer cells (26258633), tumorigenesis (29416644), and the growth of Drosophila imaginal discs (20951343). In the future, computational models and experiments are needed to better resolve how YAP promotes proliferation via Myc in the adult heart, including regulation by Mycn (30315164), cyclin T1 (32286286)."Line 632-644

      PeerReviewed
    2. EMBOpress 24 Jun 2024

      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 #3

      Evidence, reproducibility and clarity

      The authors generated a computational model of cardiomyocyte proliferation, which predicts molecular drivers of cell cycle progression. Interestingly, the model correctly predicts the outcome of 95% independent experiments from the literature. The model also elucidated crosstalk between the growth factor and Hippo modules and the authors identified key hubs for which the Hippo signaling pathway regulates cardiomyocyte proliferation. The model provides a convenient systems framework to prioritize potential signaling drivers of therapeutic modulators of cardiomyocyte proliferation.

      Significance

      This is an interesting study reporting the generation of a computational model of cardiomyocyte proliferation, which predicts molecular drivers of cell cycle progression. The program may provide a convenient framework prioritizing potential signaling drivers of therapeutic modulators of cardiomyocyte proliferation. However, the overall impact of the study appears modest since it is unclear whether the study allows elucidation of the unique properties of cardiomyocyte proliferation in adult hearts (i.e. they hardly proliferate) and the validation study was conducted only in neonatal myocytes. The field has seen many studies with neonatal myocytes but the findings are not always translatable to adult cardiomyocytes.

      The authors described that "Literature articles used for model development came from multiple cell types due to limited CM data." It is unclear whether this would allow the identification of unique mechanisms present in cardiomyocytes. As the authors admitted, the fact that the model predictions and experimental observations for polyploidization did not match clearly suggests the complexity surrounding the possibility of cell phenotypes in cardiomyocyte populations. The authors could have addressed whether this model allows the identification of unique mechanisms mediating cardiomyocyte proliferation in the adult heart.

      Please provide more information regarding the rationale for having six modules in the authors' model, including the growth factor and the Hippo pathway.

      The extent of cardiomyocyte proliferation at baseline is very low in the adult heart. The model identified 25 nodes that may influence baseline proliferation. Is there any evidence to support the involvement of these mechanisms in baseline cardiomyocyte proliferation in vivo?

      The validation study was conducted with neonatal rat ventricular cardiomyocytes. This study could have been repeated with adult cardiomyocytes since they are more resistant to proliferation and, thus, the Myc may not work as expected. In addition, the authors could have commented on the mechanism through which chromatin opening and YAP allow transcription of Myc in the heart.

      PeerReviewed
    3. EMBOpress 24 Jun 2024

      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 #2

      Evidence, reproducibility and clarity

      The manuscript submitted by Harris and colleagues collates a molecular map of cardiomyocyte cell cycle activation through mathematical modeling of previously published experimental results. They attempt to validate the constructed model several ways: 1) through testing results compiled from additional literature, 2) through in vitro analysis, and 3) through in vivo supporting data. When validating through additional literature the model proves quite reliable particularly for prediction of effects on synthesis, mitosis, and cytokinetic entry, but was less reliable (or insufficiently tested) at predicting completion of these stages as determined by polyploidization and multinucleation. A potentially novel observation which arose from the model - that hippo nodule connects to the growth factor nodule through PI3K, Myc, and FoxM1 - was partially confirmed with in vitro experiments, though a few experiments are warranted.

      Major comments:

      1. The model is admittedly weakest in its handling of completion of cytokinesis resulting in new daughter cells (i.e. proliferation) versus failure to complete either M phase or cytokinesis resulting in the much more common cellular phenotypes - polyploidy and multinucleation. Notably, very few molecules were "tested" for this output (figure 2) and this proved the least reliable aspect of the model/map. I wonder if the authors consulted the literature on somatic polyploidization at all when building the model (files not provided as indicated, see minor comment 1 below)? And if not, would doing so help strengthen this arm of their map? There are some great reviews on the topic (see PMIDs 25921783, 23849927, 30021843) - while admittedly much of the work is done on other cell types (i.e. trophoblast giant cells and hepatocytes) maybe understanding the molecular intricacies in these cells could be incorporated to strengthen the predictive model in cardiomyocytes. Notably, PMID 23849927 even provides a table of citations about key nodes in the model influencing polyploidy.
      2. Paragraph on the cytokinesis module (lines 364-377) is confusing - not sure what the takeaway message is. Also, while progression through G1/S and G2/M are "required" for cytokinesis they on their own are not sufficient (lines 366-368), this perhaps goes back to major comment 1.

      Minor comments:

      1. Use of the word "Proliferation" should be reserved for situations where the authors can clearly say a new daughter cell was born. In many instances "cell cycle activation" or "cell cycle progression" might be better terms.
      2. Supplementary Files 1 & 2 or Supplementary Document 2 were not provided or not found during review, thus we were unable to confirm which literature were used to build and validate the model.
      3. Figures are too small, particular Figure 1
      4. "E2F" should be specified as E2F1-3 yield quite distinct results from E2F7/8.
      5. Text corresponding to Figure 5 does not reference most of the panels in the Figure. i.e. figures are not "cited" in the text
      6. Figure 5C - why is there no bars for PI3K. Text claims it was predicted by the model, but the data are missing?
      7. Data provided in figure 5D & E are insufficient on their own to claim "proliferation". Perhaps adding total cardiomyocyte numbers, where one would expect expansion compared to control.
      8. Consider adding a details about the p-values to the figure legend in figure 5.
      9. Data presented in figure 6 do not "validate" the model. Rescue experiments as were provided in vitro would be necessary or at minimum YAP/TEAD binding to the promoters (ATAC insufficient). Alternatively, walking back these statements, might be easiest.
      10. Validation studies through the literature suggested ~94% fidelity. The invitro validation suggests 66% reliability of model? The in vivo 33%? Perhaps this should be added as a discussion point - can the authors comment on the loss of fidelity as the rigor/complexity of the experiment increased?

      Significance

      As it stands now, the generated map largely constitutes already known details offering few if any new insights; however, if updated as new results arise AND made available as a public tool, the model could prove to be a highly valuable resource to the field.

      I have expertise in cardiomyocyte cell cycle and polyploidization

      PeerReviewed
    4. EMBOpress 24 Jun 2024

      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

      Summary:

      In the manuscript by Harris et al. titled "Dynamic map illuminates Hippo to cMyc module crosstalk driving cardiomyocyte proliferation," the authors developed a computational model of cardiac proliferation signaling that incorporates various regulatory networks (cytokinesis, mitosis, DNA replication, etc.) to predict molecular drivers (genes) that support cardiomyocyte proliferation. Published research articles on cardiomyocyte proliferation in multiple contexts (different species, ages, in vitro and in vivo, etc) were used to build and validate the computational model. The authors found using their model that different processes during cardiomyocyte proliferation may or may not be context-dependent. For example, DNA replication is regulated differently in conditions with high Neuregulin compared to high YAP, whereas mitosis and cytokinesis regulation is similar in these conditions. To experimentally validate their model, the authors used an in vitro system to test the effects of YAP on 3 connected pathways; in the context of YAP activation, inhibition of PI3K, cMyc, or FoxM1 was combined to assay cell-cycle markers in cultured neonatal rat ventricular cardiomyocytes. Cell-cycle marker expression in cardiomyocytes was attenuated by inhibition of cMyc or PI3K, suggesting that these pathways are involved in YAP-mediated cardiomyocyte proliferation. While this model can be a good tool to gain new insights on interactions between molecular pathways, there are a few questions to be addressed prior to publication.

      Major Comments:

      1. One of the potential uses for this computational model is to discover new interactions between known pathways that are involved in cardiomyocyte proliferation. However, this would be more powerful if factors such as species, age (neonate vs. adult), experimental design (in vivo vs. in vitro) are accounted for, as new node inputs or a combination of existing node input activity values. This is very important because cardiomyocyte proliferation can drastically vary depending on these experimental factors.
      2. The finding that cardiomyocyte proliferation is context-dependent is very exciting and warrants further investigation/validation. The authors state that different sets of nodes/modules are affected by neuregulin activation compared to YAP activation. This should be experimentally validated - qPCR/Western blots on sets of genes that are predicted to be differentially regulated in the high neuregulin context vs the high YAP context.
      3. The overall description of the model can be improved. How are the modules and overarching model built from published results? For example, how are the input and parameters set to validate or predict different experimental observations? What is the steady-state activity of each of the nodes and does this make sense biologically? Includng a few more sentences to explain the model would help with overall understanding for an uninformed reader.

      Minor Comments:

      Line 124 - The use of "species" and "reactions" is confusing to uninformed readers. Do you mean nodes and interactions/bridges?

      Line 130 - I could not find Supplementary File 2, which includes the references?

      Line 251 - "theseanal"

      Line 257 - What is the meaning of the directional arrows in Fig 1A?

      Line 301 - Unclear what default values mean here. Please elaborate and provide an example of how this is reasonable?

      Supplemental Fig S2 - Why would knockdown of PKA, Lats1, or SMAD3 have the exact same effects on node activation? This is seen with multiple other genes as well (IGF and FGF for example).

      Significance

      The computational model in this manuscript can be a tool to discover unknown molecular pathway interactions in cardiomyocyte proliferation. The novelty lies in the ability to adjust any parameter or the entire setting/context. While this sounds very exciting, improvement of the model to account for age, experimental conditions (in vivo vs in vitro), and species (human, pig, mouse) could lead to increase prediction accuracy. Additionally, more robust validation of context-dependent interactions between signaling pathways would also increase overall enthusiasm for the manuscript. Readers interested in a systems biology approach to cardiomyocyte proliferation, or researchers probing molecular interactions during cardiomyocyte proliferation would be interested in using such a model to discover novel contexts/combinations in which cardiomyocyte proliferation is more likely.

      The reviewer comes from a varied training background and is qualified to evaluate this manuscript in full - BS in biomedical engineering and mathematics. PhD in biomedical engineering (molecular biology, cardiac electrophysiology). Postdoctoral training in cardiac regeneration and immunity.

      PeerReviewed
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    PARP1 condensates differentially partition DNA repair proteins and enhance DNA ligation
    3
    1. EMBOpress 23 Jun 2024

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      Reply to the reviewers

      The authors do not wish to provide a response at this time.

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    2. EMBOpress 23 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Sang and colleagues present in vitro evidence for purified PARP1 forming condensates with DNA under certain conditions. They report the PARP1/DNA/NaCl concentration ranges under which these condensates form, and the impact of adding the PARP1 substrate NAD+ that allows poly(ADP-ribose) production. The results are presented clearly for the most part. One wonders if these in vitro conditions are really representative of DNA repair foci; however, the study adds new information that will be useful to the field. As noted below, there is some concern about the lack of reversibility of the condensates.

      • DNA curtains assay. The imaging buffer is listed as including 25 mM NaCl and 2 mM MgCl2. Were these experiments performed in conditions of higher ionic strength? The lack of a response to the addition of NAD+ is puzzling. It seems that the condensing of the DNA is not reversible. For the data in panel C, would the DNA return to extended form upon further flow of buffer only? The data give the impression that the assay conditions promote a one-way road to an irreversible state, and it is hard to see how this should be interpreted. A different single-molecule study indicated that PARP1 condensation of long DNA is reversible with NAD+ addition (PMID 34380612). The different outcomes should be discussed.
      • DNA ligase assay. Figure 5E,F. How can it be certain that the ligation is actually taking place in the condensates under these conditions? Can the Cy5 signal be shown? Is there a way to separate the condensates from the dilute phase, and then analyze the ligation state of the DNA? Also, the reactions could be performed under the same conditions (e.g. uM concentrations of LigIII and XRCC1) as presented in the rest of the figure.

      The discussion mentions the impact of HPF1 on PARP1 and that the research team has used HPF1 in the past. Is there a reason for excluding it from the current study? In particular in an effort to address the reversibility/mobility of the condensates?

      Supp. Figure 1F. It would be useful to convert the ng/uL concentrations to micromolar concentrations, perhaps in the legend for each nucleic acid. This would make the results easier to relate to the rest of the data that is generally listed in micromolar.

      Figure 6A. ZnF3, BRCT, and WGR domains of PARP1 also bind to DNA and should probably be included, as it could help explain why full-length PARP1 is needed for the most robust condensate formation.

      Supp. Figure 1G. The legend for this panel indicates absence or presence of NAD+, and that the DNA concentration is indicated, but this does not seem consistent with the figure panel.

      Results, first sentence. There is a missing parenthesis.

      Figure 2G,H. It would be useful to see the plot of the other replicates of the fusion experiments.

      page 3. "(data not shown)" Probably worth including.

      page 4. "(Supp. Fig. 3B and 3D)" Also Supp. Fig. 3C ?

      Referees cross-commenting

      Reviewer #1 comments are clearly stated and justified. There is good overlap in the feedback.

      Significance

      Strength: the study provides parameters for studying PARP1 condensate formation. Differential impact on repair factors is interesting.

      Limitation: the reconstitution is missing elements that could have a very big impact (e.g. nucleosomes).

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    3. EMBOpress 23 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      PARP1 plays important roles in the recognition and repair of DNA damage, primarily by catalyzing the formation of PAR at DNA breaks, which assembles various repair factors and other PAR-binding proteins. The anionic PAR scaffold was previously proposed to induce condensation of phase separating proteins including FUS (PMIDs: 26317470, 26286827), and PARP1 was recently reported to form condensates at DNA breaks to promote nucleosome dynamics and DNA end synapsis (PMIDs: 38320550, 38215753). However, several aspects of PARP1-dependent repair condensate formation and how such condensates contribute functionally to repair have remained unclear. Here, Sang et al. show that purified PARP1 forms viscous droplets in vitro in a DNA binding-dependent manner, enhanced by PAR. Interestingly, the downstream DNA repair factors XRCC1, POLB, DNA Ligase III, and FUS co-assemble with PARP1 and damaged DNA, albeit with different enrichment patterns, resulting in multiphase condensates. Functionally, the authors not only confirm a DNA end bridging function by PARP1-mediated condensation, but also report enhanced DNA end ligation. Their in vitro experiments, which are state-of-the-art and are overall well controlled, despite lacking an in vivo counterpart, provide an important step forward in the reconstitution of multi-step DNA repair reactions in repair condensates.

      Major comments:

      1. In addition to the short oligonucleotides that were used in this study to evaluate DNA-dependent PARP1 condensation (Table S2), the use of circular plasmid DNA (nicked or broken to resemble SSBs or DSBs, respectively) should be considered to corroborate key findings.
      2. Although not essential for the main conclusions, it would be very interesting to address the role of PARG on PAR-dependent multiphase condensates. Based on the methods section, the authors have purified full-length PARG, so experiments to address the consequences of PARG-dependent PAR degradation on repair condensates and their disassembly seem feasible.
      3. If PAR increases the internal dynamics and mobility of PARP1 in condensates, why does it not seem to affect the DNA end bridging function?
      4. Catalytically inactive mutants of PARP1 could be employed to separate the PARP1-dependent DNA end bridging function from PAR-dependent modulation of PARP1 dynamics in condensates. Additionally, it would help to show that the DNA end bridging function depends on the ZnF domains and can be modulated by conditions that alter PARP1 condensation (see also point 6).
      5. The differential organization of XRCC1, LIG3, POLB, and FUS is intriguing, but the implications of this behavior remain unclear. Can the droplet assays be adapted to inform about the sequence of events from DNA damage recognition by PARP1 and PAR induction to the handing over of the break site to LIG3 for end ligation?
      6. The increase in end ligation, which correlates with PARP1- and PAR-dependent condensate formation, is very interesting. However, from the experimental setup it seems unclear if the observed effect is due to condensation or simply PARylation. Additional controls would be needed to substantiate a functional role of condensation for ligation (as implied also in the title of the manuscript). Perhaps it is feasible to modulate condensation (e.g. enhanced by crowding agents, reduced by salt or by 1,6-hexanediol) without affecting PARylation, and then reassess how this affects ligation.

      Minor comments:

      1. Please double-check if previous studies reaching similar conclusions are referenced appropriately.
      2. Please carefully double-check if all references to figure panels are correct.
      3. Please carefully double-check if the methods descriptions and discussion match the displayed experimental procedures and results.
      4. Supplemental Figure 3 seems to contain only negative results. Consider showing experimental conditions with the same proteins or protein combinations that result in droplet formation as well.

      Referees cross-commenting

      The comments by reviewer #2 seem comprehensible and justified. Similar points are addressed, e.g. major points 2, 3, and 6 in review #1.

      Significance

      Several new and exciting findings on PARP1-dependent and PAR-modulated repair condensate formation are presented, including the multiphase behavior and the functional contribution to DNA compaction, end synapsis, and ligation. The study extends previous work on PARP1/PAR-triggered liquid demixing and complements very new and recently published work by the Alberti and Kay labs on PARP1 condensation at DSBs. The study makes an important step forward towards the reconstitution of DNA repair reactions inside multi-component repair condensates in vitro, which may eventually allow making testable predictions for repair condensate functions in vivo. Strengths of the current study include complementary state-of-the-art in vitro techniques such as biochemical assays, multi-component droplet assays, and single molecule experiments, which were conceived and conducted carefully. Limitations relate primarily to the undemonstrated relevance in cells, which may, however, be beyond the scope of the current study. A broad audience of basic researchers in the areas of genome stability and biomolecular condensates will likely be interested in this study.

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    Modelling quiescence exit of glioblastoma stem cells reveals a key role for FoxO6
    4
    1. EMBOpress 22 Jun 2024

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

      The majority of the conclusions are well supported by strong experimental evidence. The only area where that is not fully the case is the role of Pak1 as a downstream effector of FoxG1-FoxO6 and its effects on macropinocytosis. To further strengthen this claim, the authors should demonstrate that ablation of Pak1 can rescue the functional consequences of forced FoxO6 expression and whether overexpression of Pak1 rescues quiescence exit in FoxO6 knockout. Thank you to the reviewer for these helpful suggestions. To investigate the effects of Pak1 ablation, and therefore more directly the link between FOXG1 and FoxO6 and macropinocytosis, we tested the published Pak1 inhibitor IPA-3. Unfortunately, to distinguish the role of Pak1 in quiescence exit and macropinocytosis, we would need a dosage of IPA-3 that is efficacious but does not affect cell proliferation. It was not possible to optimise such a dosage (a dosage of 10uM is shown to be efficacious at inhibiting Pak1 (Verma et al, 2020; Wong et al, 2013) however even at 2.5uM we see significant cell death in our cells. Indeed, this is potentially due to pleiotropic roles for Pak1.

      Also, it is not feasible to overexpress Pak1 in the FoxO6 KO cells with inducible FOXG1. To ensure we are investigating quiescence exit this would need to be in an inducible manner; however, re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels by excising the existing transgene.

      As shown in Figure S3, we do not observe clear vacuole formation in F6 (FOXG1-inducible) cells upon Dox addition. As detailed in the discussion, we hypothesise that FoxO6-induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Indeed, active Pak1 has been found to modulate pinocytic cycling, enhancing both FITC-dextran uptake and efflux (Dharmawardhane et al, 2000). We therefore would not hypothesise that high Pak1 levels alone would be sufficient to drive quiescence exit.

      Alternatively, the macropinocytosis observed may be a metabolic stress response because of the hyperactivation of signalling pathways upon FoxO6 overexpression. Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017).

      We believe the observed macropinocytosis phenotype upon Foxo6 overexpression, and the changes in Pak1 expression upon Foxo6 loss or FOXG1 induction provide interesting insights into the function of this underexplored FoxO family member. However, currently we are unable to demonstrate a direct link between these processes and have therefore modified the text to reflect this (see lines 292-4, 330-3, 365-8).

      • The manuscript stresses the role of NSC quiescence exit in GBM and demonstrates that FoxG1 KO reduces FoxO6 levels in a murine GBM cell line but a BMP4-mediated quiescence and dox-induced FoxG1 over-expression or an abolishment of cell cycle re-entry thereof by reduced FoxO6 levels in the case of FoxG1 KO is lacking. But this would significantly substantiate the relevance of the findings. *

      Mouse GBM cells have elevated levels of FoxG1 and have been shown to be refractory to BMP4-mediated quiescence entry, maintaining colony formation following BMP treatment (Bulstrode et al, 2017). It is therefore challenging to specifically investigate cell cycle re-entry/ quiescence exit using these mouse GBM cells, or indeed any GBM cell line due to their inability to respond fully to BMP cues (Caren et al, 2015). It has also been shown by Bulstrode et al, 2017 that Foxg1 null mouse neural stem cells show an increased propensity to exit cycle in response to BMP treatment, and reduced colony formation on return to EGF/FGF-2 growth factors. FOXG1 null cell lines therefore show a reduced response to BMP cues, making it difficult to explore quiescence exit per se.To navigate this, instead we investigated Dox-induced FOXG1 overexpression in FoxO6 WT and KO mouse NS cells, which display similar quiescence characteristics upon BMP treatment (Figure 4).

      • In the introduction and discussion, FoxO6 is mentioned for its oncogenic roles in various cancers but no reference to GBM specifically is cited. It feels like a missed opportunity to not show evidence of this in the IENS cell line that has reduced levels of FoxO6; is there an effect in their proliferative capacity? What are the expression levels of Pak1 following FoxG1 KO in IENS cells? *

      Thank you for the helpful suggestion. It is indeed true the literature on FoxO6 in GBM is lacking, explaining the absence of citations on this. On investigation of expression of the proliferation marker Ki67 in these cells we found no significant difference in expression, now shown in Figure 1H. This is in fitting with previous findings of our lab (Bulstrode et al, 2017) which show that FOXG1 is dispensable for the maintenance of continued NSC or GSC proliferation in vitro. We investigated the expression levels of Pak1 following FOXG1 KO in IENS and found a decrease in both KO lines compared to parental cells (updated Figure 6F).

      As explained in our discussion, these data suggest that Foxg1/FoxO6/Pak1 are not functionally important in sustaining GSC/NSC proliferation, as shown by the lack of proliferation defects upon Foxg1 or FoxO6 deletion (Bulstrode et al, 2017), but impact regulatory transitions, as cells prepare to exit quiescence into the proliferative radial-glia like state.

      *Minor comments *

      - Fig1A shows 4 and 2-fold respectively for the two mouse NSC lines, not 17 and 4-fold increase as written on manuscript, please adjust accordingly.

      The qRT-PCR data are presented as log2(fold change) or - ddCt, where this value equals zero for the calibrator sample, as indicated in the figure legends and axes. The data are presented in this way to enable accurate visualisation of up- and down-regulation of gene expression. Data are stated as ‘fold increase’ in the text for ease of reading, which we have clarified in the text and figure legends (e.g. lines 154 and 176).

        • Fig2G manuscript reports a 235-fold upregulation, but graph looks more like a 7 or 8-fold as shown on Fig1A for the F6 NSC line. I would recommend checking the fold changes reported throughout the paper. *

      See previous comment above. The qRT-PCR data are presented as log2(fold change) or - ddCt, where this value equals zero for the calibrator, as indicated in the figure legends and axes. The data are presented in this way to enable accurate visualisation of up- and down-regulation of gene expression. Data are stated as ‘fold increase’ in the text for ease of reading, which we have clarified in the text and figure legends (e.g. lines 154 and 176).

      • The manuscript describes the increase of FOXG1 after BMP4-induced cell cycle exit as compared to non-BMP4 treated cells (p.8 first paragraph), but I am wondering if this expression is rather compared to dox negative and not vs BMP4 negative treatment. *

      Data are presented relative to the non-BMP treated (EGF/FGF-2) control throughout the manuscript for consistency. This is to enable changes in expression between -Dox and +Dox to be visualised throughout the quiescence-exit time course relative to the initial starting population in EGF/FGF-2 growth media, prior to BMP treatment.

        1. In Fig2G it is interesting that FoxO6 is upregulated in BMP4 treated throughout the experiment with highest values at day10 post treatment. At the same time, non-BMP4 treated cells keep decreasing their FoxO6 levels dramatically but there is no mention or reference to this effect.*

      In Figure 2G, all cells have been treated with BMP4, prior to return to growth media (EGF/FGF) with or without Dox. It is true that in the +Dox condition with FOXG1 induction, FoxO6 levels continue to increase up to Day 10, perhaps reflective of the expansion of a highly proliferative radial glia-like population.

        1. Fig2 would benefit from a western blot like Fig1D where FoxG1 and FoxO6-HA protein levels are also shown in dox-treated comparing BMP4-treated vs non-treated. *

      Due to the lack of specific FoxO6 antibodies and the absence of a FoxO6-HA tag in this cell line, it is not possible to perform protein analysis of FoxO6 levels in this figure as for Figure 1D.

      • The colonies in Fig3E should be quantified, as their ability to form neurospheres seems somewhat compromised upon FoxO6 KO. Fig3B and 3F could perhaps be consolidated into one panel in the interest of space and presentation. *

      Good suggestion. We have now consolidated Fig 3B and 3F into one panel (now Figure 3F) as suggested by the reviewer. We performed additional replicates for Figure 3E to quantify the colony formation efficiency. This showed a small but insignificant decrease in colony forming ability in the KO cells (Figure 3E). Importantly the FoxO6 null cells do form colonies, and our results show that FoxO6 is not essential for proliferation or colony formation of NSCs in EGF/FGF-2 – this therefore does not account for the complete loss in colony formation we see the in the FoxO6 KO cells upon FOXG1 induction.

      • Fig4A shows vs "parental" non-BMP on y axis but wouldn't this show fold change of dox+ parental vs parental. The authors should clarify this. *

      All samples in Figure 4A are compared to parental cells in EGF/FGF-2, i.e. non-BMP treated, as the calibrator sample where log2(fold change) equals zero. We chose to set a single calibrator sample for all data (parental and FoxO6 KO cells included) to allow us to compare changes in FOXG1 transgene across the entire experiment.

      • Perhaps the authors can add a non-BMP4 treated count of % FOXG1 positive cells to Fig4C for reference. *

      As shown in Figure 4A, both parental and FoxO6 KO cells show similar, i.e. negligible, FOXG1 transgene expression without Dox, compared to the parental non-BMP4 treated control, therefore negligible FOXG1-V5 positive cells are seen by ICC. We have edited Figure 4A to include a non-BMP treated and BMP-treated control to show the negligible FOXG1-V5 expression by qPCR as controls.

      • The sentence mentioning Fig5D for the first time (p.10 third paragraph) needs rephrasing for clarity and should also call out Fig5C for the mCherry expression live cell imaging data where appropriate. Fig5D does not appear to be live imaging as implied by the text. If vacuole formation is observed already as early as 10-11h after Dox induction, then it should be shown somewhere in Fig5. Vacuole formation is shown with a higher magnification image inset only in the 22h timepoint image. I think Fig5E should be more substantiated with some sort of quantification, e.g. % of vacuoles positive for EEA1 and/or LAMP1. *

      We apologise for this. The first reference to Figure 5D one line 234 should refer to Figure 5C, this has now been corrected in the text. Vacuoles are visible in Figure 5C panel 10 h 30 min, however, to make this clearer we have also supplied an accompanying movie of the live imaging (Movie 1). The imaging in Fig 5E has not been quantified as this imaging was performed with the purpose of confirming the vacuole structures seen are not simply enlarged lysosomes, due to their similarity in appearance to those published elsewhere (Ramosaj et al, 2021; Leeman et al, 2018). Instead, we have provided Western blotting data in Figure S5E to support this conclusion that there is no clear increase in EEA1 or LAMP1 (early endosomal or lysosomal) expression upon FoxO6-HA induction.

      *- Could the authors comment on the lack of proliferative advantage of the FoxO6 overexpression. FigS3 shows Edu staining, but there is no proliferation assay in either Fig5 or S3. What would be the effect of FoxO6 overexpression on BMP4-mediated quiescence with or without FoxG1 over-expression? *

      Induction of FoxO6-HA overexpression does not provide a proliferative advantage to the cells. Looking at individual cells, those with high FoxO6-HA levels seem to associate with EdU negativity. In Figure S3 we provide quantitative EdU incorporation assay as a proliferation assay (quantification of the number of cells cycling, therefore incorporating EdU, within a 24h pulse period). Quantification of the EdU staining in Figure S3G is provided in Figure S3H. We have now clarified this in the text on page 11, lines 263-4.

      Unfortunately, due to transgene overexpression using the PiggyBac transposon method, it is not feasible to overexpress FoxO6 and FOXG1 in the same cell line, as re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels and make results difficult to interpret. Given the association of vacuolated cells with EdU negativity, we predict that FoxO6 overexpression would not give an advantage for quiescence exit. Indeed, BMP-treated cells with FoxO6 overexpression show a decrease in EdU positivity, as shown in Figure S3H. As discussed in the text, we hypothesise that cells with FoxO6 overexpression are in a stalled state, potentially due to signalling hyperactivation. While this may not be physiological, it gives us clues as to the function and downstream targets of FoxO6, which remain uncharacterised.

      *- Can the authors clarify if there is a proliferation change in F6 cells in Fig6F as in Fig2F? Fig6F shows Pak1 is already upregulated in quiescent NSCs, what are the expression levels of Pak1 in FoxO6 -/- ANS4 cells upon FoxG1-mediated quiescence exit as shown in Fig4? Is there a particular reason why the F6 cell line data is shown only up to day2 post Dox-induction rather than d4 or d10? For consistency with the rest of similar experimental data this timeline should be extended. Does Pak1 remain elevated, plateaus or keeps reducing further post day2? *

      The data is (previous) Figure 6F is the same assay and cell line as presented in Figure 2, but at an early timepoint (Day 2) during the quiescence exit assay. We have provided in the panel qRT-PCR analysis of Ki67 to show that cells begin to show increased proliferation at this timepoint. Due to our hypothesis that Pak1 is required at an early transition point, we decided to analyse this expression at an earlier timepoint than Figure 2. We have also repeated this at D10 (data below), showing Pak1 levels continue to increase with time, along with FoxO6 and the proliferative marker Ki67. Due to technical issues with variable FOXG1 transgene levels we were unable to analyse Pak1 expression levels in FoxO6+/- ANS4 cells upon FOXG1-mediated quiescence exit.

      *15 . Reviewer #1 (Significance (Required)): *

      The study provides a conceptual advance for exit from stem cell quiescence. There is strong evidence provided for murine neural stem cells, but the link to GBM cancer stem cells is less developed (but perhaps this is the subject of a separate manuscript).

      While FoxG1 is a known regulator of neurodevelopment and glioblastoma, the functions of FoxO6 have not been studied in the context of neural stem cells. In my view, this study should be of high interest to audiences in both neurodevelopment and cancer research. * Expertise: glioblastoma, cancer stem cells, neurodevelopment *

      We have edited the text and title to clarify that neural stem cells are used here as a model for GSCs with high levels of FOXG1 (e.g. lines 36 and 69).

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

      *Major comments: *

      -The choice of NSCs as a main experimental model to understand the effects of FoxG1 and FoxO6 is not fully justified. The authors had previously shown that FoxG1 is expressed at very low levels in NSCs (Fig. 1A in Bulstrode et al. 2017). FoxO6 also seems to be barely expressed in NSCs (Fig. 1 of the current manuscript) and, in addition, its levels seem to go further down as cells exit quiescence (-Dox line in Fig. 2H). Therefore, these two genes do not seem to play an important role in the normal exit from quiescence of NSCs, with FoxO6 only affecting FoxG1 overexpression-induced exit from quiescence. * * *If the aim is to mimic a GBM-like state by FoxG1 overexpression, this should be made much clearer in the text, including title and abstract. In that case, the authors should also show a direct comparison of the levels of FoxG1 in GBM and upon Dox-induced overexpression in NSCs. *

      We agree with this criticism and suggestion to fix this. It is indeed our aim to mimic a GBM-like state by inducing FOXG1 overexpression and we should have made that more explicit. All experiments are performed in the context of high FOXG1 level. Like Foxg1, FoxO6’s homeostatic roles may be subtle in adulthood, and mostly involved in neural plasticity (Yu et al, 2019). This is in keeping with our finding that basal FoxO6 levels are low in adult NSCs and not required for sustained proliferation but are important for cell state transitions. If the FoxO6 levels activated by elevated FOXG1 represent an acquired dependency of GBM, there may be a therapeutic window to target this pathway. However, given the poorly understood roles of FoxO6, further work is needed to determine its specific value as a therapeutic target. We have modified the title and the text to make this clearer. This is also stated in the first paragraph of the results section on page 7 (line 148).

      We have provided below a Western Blot (Bulstrode, 2016) in which FOXG1 levels in F6 cells induced with Dox (1000 ng/ml the dosage used) with the GBM cell lines G7 and G144, and the normal NS cell line U5. This shows that the FOXG1 levels induced are significantly higher than found in normal neural stem cells (mouse or human). This model has been previously used and published in Bulstrode et al, 2017, upon which this manuscript expands.

      *-While the authors state that they aim to study NSC quiescence, they use a protocol that is closer to modelling astrocytic differentiation. In fact, in their previous work, they use this very same protocol (removal of growth factors and addition of BMP) to study the role of FoxG1 and Sox2 on astrocyte de-differentiation (Bulstrode et al. 2017). While there is arguably no perfect in vitro model of NSC quiescence, the current standard in the field is treatment with both BMP and FGF for 48 to 72 hours (e.g.: Mira et al., 2010, Martynoga et al., 2013, Knobloch et al., 2017, Leeman et al., 2020). BMP alone is regarded as a pro-astrocytic differentiation cue, and 24 hours might not be enough for NSCs to fully commit to either differentiation or quiescence. Therefore, either the claims in the paper are changed to match the astrocytic differentiation model, or a standard quiescence protocol should be used throughout to confirm the findings also apply to the exit from quiescence of NSCs. *

      We agree with the reviewer that there is indeed no perfect in vitro model of NSC quiescence and thank the reviewer for this useful discussion. Coincident with this project, this was an active area of research from our laboratory as explored by Marques-Torrejon et al, 2021 (Nature Comms). After 24 h BMP4 treatment, we found that adult mouse NS cells: exit cell cycle, are growth factor unresponsive, obtain an astrocytic morphology, upregulate astrocytic markers such as Gfap and Aqp4, and downregulate radial glia/NS cell markers such as Nestin and Olig2 (Figure 3).

      We therefore initially viewed them as terminally differentiated. However, the exact state of these cells is difficult to define due to the lack of definitive markers and transcriptional differences that can distinguish terminally differentiated GFAP-expressing astrocytes from quiescent type B SVZ NS cells (which also express GFAP) (Bulstrode et al, 2017; Doetsch et al, 1999; Codega et al, 2014). Findings from our laboratory later suggested some NS cell markers are maintained following BMP4 treatment and these cells can be forced back into cycle with combined Wnt/EGF signalling, or FGF/BMP signalling (Marques-Torrejon et al 2021). This suggests in vitro NS cells may lie along a continuous spectrum of states from dormant quiescent, activated quiescent (primed for cell cycle re-entry) to actively proliferating, similar to that observed in vivo in the mouse SVZ (Dulken et al, 2017). Indeed, after 24 h BMP4 treatment, we observe a minimal level of colony formation in no Dox controls following 10 days of exposure to the growth factors EGF/FGF-2 (Figure 2D-F).

      These non-cycling BMP4-induced astrocytic cells might therefore be better viewed as dormant quiescent NSCs, hence our reference as quiescent NSCs. The assay conditions used in this manuscript differ to those of Marques-Torrejon et al, in terms of density and length of BMP4 treatment; it is therefore likely that our BMP-treated cells are at different stages along the continuum between dormancy and primed quiescent states. Importantly, regardless of the exact cell type induced by 24 h BMP4 treatment, we have considered the changes induced by FOXG1 overexpression, in comparison to the effect of NS cell media alone.

      *-The FoxO6-induced vacuole formation in NSCs is a very interesting finding. However, so far it was only observed upon FoxO6 overexpression. To claim vacuolization is required for quiescence exit, the authors should show whether this phenomenon is also observed upon normal exit from quiescence and FoxG1-induced reactivation of NSCs. From the author's own data, Pak1 (which induces vacuolization) is unlikely to reactivate NSCs, as its expression is highest in BMP-treated cells (Figure 6F). The authors should show whether some vacuolization is present at these stage in NSCs and if not, discuss the possible interplay between Pak1 and FoxO6 in vacuole formation and quiescence exit. *

      As detailed in the discussion, we hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Indeed, active Pak1 has been found to modulate pinocytic cycling, enhancing both FITC-dextran uptake and efflux (Dharmawardhane et al, 2000). Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017).

      We do not see clear evidence of vacuoles in FOXG1-induced reactivation of NSCs – this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation. While this may not be physical, it gives us clues as to the function and downstream targets of FoxO6, which remain uncharacterised (such as a link of FoxO6 and FOXG1 with Pak1-related pathways). Demonstrating a requirement for vacuolisation in quiescence exit is outwidth this manuscript and therefore we are careful not to claim this. We have modified the text to clarify this.

      As the reviewer noted, it is interesting that Pak1 is highest in BMP-treated cells; it seems that BMP signalling itself is triggering elevated Pak1 levels, likely as cells undergo extensive cell shape changes during the transition from proliferation to quiescence. However, in EGF/FGF-2, Pak1 levels decrease, and our data suggests that FOXG1/FoxO6 are required to increase or maintain Pak1, potentially to again enable the cell shape/metabolic changes required on quiescence exit. We have added to the text to expand upon this observation on page 14 (lines 330-333). -Finally, the data on the regulation of Pak1 expression by FoxO6 is insufficient to draw any strong conclusions. Downregulation of Pak1 in FoxO6 cells is not enough evidence to claim a direct regulation. The authors should show whether Pak1 levels are increased after FoxO6 overexpression and whether FoxG1 is downregulated in FoxO6 KO NSCs (indirectly affecting Pak1 expression).

      We have performed qRT-PCR analysis of Foxg1 expression in FoxO6 KO NSCs and see no consistent difference in expression, indicating this is not indirectly affecting Pak1 expression (see below, 1). We have also investigated Pak1 levels upon FoxO6 overexpression, over a time course following Dox addition (see below, 2). Interestingly, when FoxO6 is overexpressed, Pak1 is not clearly upregulated at any time-point. It may be that as Pak1 is already expressed in the -Dox controls, due to its roles in a variety of cellular functions, that the levels are saturated already. It is clear that Pak1 expression decreases upon FoxO6 loss in EGF/FGF (without coincident Foxg1 downregulation) and in F6 cells, higher FOXG1 correlates with higher Pak1 in EGF/FGF. Together with the induction of macropinocytosis upon FoxO6 overexpression, these data provide interesting insights into the potential pathways downstream of Foxo6 in controlling quiescence exit, directly or indirectly related to Pak1 signalling. We have modified the text to reflect this on page 14 (lines 330-333).

      Minor comments: * Please state in the main text that NSCs are derived from the SVZ. *

      This has been added to the text on page 7 (line 149) and is in the methods ‘Cell Culture’ section.

      Reviewer #2 (Significance (Required)):

      As I said before, I find this work tackles a very important question, how is the exit from quiescence controlled in NSCs. This manuscript will be of interest to researchers in the fields of adult stem cell biology and adult neurogenesis. While my expertise lies mostly on NSC biology, this work is of potential great interest for the cancer field, particularly for brain cancer research. Elucidating the mechanisms GBM cells use to exit quiescence is crucial in order to avoid the relapse of this aggressive form of brain cancer. To increase the relevance of the work to the cancer community, some of the key findings should be reproduced with GBM cells. It would be particularly important to show whether Pak1 induced vacuolization and macropinocytosis can be observed in GBM cells.

      As detailed in the discussion, we hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017). We do not see clear evidence of vacuoles in FOXG1-indued reactivation of NSCs– this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation. We do not therefore think macropinocytosis per se would be observed in quiescence exit of GBM cells – indeed a normal form of macropinocytosis-induced cell death called methuosis has been observed in GBM cells with hyperactivated Ras signalling (Overmeyer et al, 2008). However, this phenotype still gives us clues as to the function of FoxO6 in quiescence exit in GSCs and the downstream signalling pathways it may regulate, such as Pak1-related signalling (discussed on lines 330-3 and 366-9).

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

      Summary: * The overall objective of the paper is to investigate the mechanisms by which co-option of the activity of developmental master lineage regulators by cancer cells allows them to gain fitness. To answer this question, they focus on FOXG1. This TF acts during the specification of the telecephalon. Its expression can be increased in Glioblastoma (GBM) and, more importantly for the paper, FOXG1 has previously been shown to promote exit from quiescence of glioblastoma stem cells (GSCs) and non-transformed neural stem cells (NSCs). In a previous screen, the authors identified FoxO6 as a potential direct target gene of FOXG1. In this paper, they showed that with the gain of expression for FOXG1 in NSCs and loss of FOXG1 in GSCs, FoxO6 is increased or decreased, respectively. Loss of FoxO6 in NSCs does not alter their cell cycle or cell shape and specification. Yet, loss of FoxO6 in NSCs blocks FOXG1-mediated exit from quiescence. To understand the mechanisms, they decided to overexpress FoxO6 in NSCs and demonstrated that the cells undergo macropinocytosis, a process by which cells can engulf large amount of nutriments from the external medium. It remains to be determined whether this macropinocytosis occurs in cells overexpressing FOXG1 and GSCs. The authors provide a first answer by showing that overexpression of FOXG1 induces not only FoxO6 but also the expression of PAK1, one of the key kinases that regulates the membrane engulfment of macropinocytosis in NSCs. In GSC lines, the decrease of FOXO6 decreases PAK1 levels. *

      Major comments: * The paper describes interesting and convincing results (number of cell lines, repeated experiments seems sufficient) but it is difficult to reconcile them all in a single model, and this diminishes the impact of the study. Epistatic interactions between FoxG1, FoxO6, PAK1 and macropinocytosis are not always studied in the same cell models. Whether FOXG1-induced exit from quiescence of NSCs is dependent on a FOXG1-->FOXO6-->PAK1-->Macropinocytosis axis remains to be demonstrated. Also does such an axis operate in tumor cells remains to be fully assessed? In particular, if FoxO6 overexpression in NSCs can induce macropinocytosis, is this cellular process induced by FoxO6 downstream of FOXG1 activity during NSC quiescence exit? Is PAK1 a relay of FoxO6? Experiments looking at macropinocytosis and the involvement of PAK1 in the cell models of Figure 4 will definitely help to bridge the different results all together. *

      We thank the reviewer for this useful insight and discussion for future work.

      To directly investigate the effects of Pak1 ablation, and therefore more directly the link between FOXG1 and FoxO6 and macropinocytosis, we tested the published Pak1 inhibitor IPA-3. Unfortunately, to distinguish the role of Pak1 in quiescence exit and macropinocytosis, we would need a dosage of IPA-3 that is efficacious but does not affect cell proliferation. It was not possible to optimise such a dosage (a dosage of 10uM is shown to be efficacious at inhibiting Pak1 (Verma et al, 2020; Wong et al, 2013) however even at 2.5uM we see significant cell death in our cells. Indeed, this is potentially due to the variety of cellular functions Pak1 is involved in. Conversely, it is not feasible to overexpress Pak1 in the FoxO6 KO cells with inducible FOXG1. To ensure we are investigating quiescence exit this would need to be in an inducible manner; however, re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels (through excision of the existing transgene) and therefore make results difficult to interpret.

      We hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes (as detailed in the text discussion). Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017). We do not see clear evidence of vacuoles in FOXG1-induced reactivation of NSCs– this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation and therefore not a physiological process in quiescence exit. We do not therefore think macropinocytosis per se would be observed in quiescence exit of GBM cells – indeed a normal form of macropinocytosis-induced cell death called methuosis has been observed in GBM cells with hyperactivated Ras signalling (Overmeyer et al, 2008).

      However, we believe the observed macropinocytosis phenotype upon Foxo6 overexpression, and the changes in Pak1 expression upon Foxo6 loss or FOXG1 induction provide interesting insights into the function of this underexplored FoxO family member, in GSCs and the downstream signalling pathways it may control, such as Pak1-related signalling. We have modified the text to reflect the limitations of our current data and discuss this (lines 330-3 and 366-9).

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    2. EMBOpress 22 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      The overall objective of the paper is to investigate the mechanisms by which co-option of the activity of developmental master lineage regulators by cancer cells allows them to gain fitness. To answer this question, they focus on FOXG1. This TF acts during the specification of the telecephalon. Its expression can be increased in Glioblastoma (GBM) and, more importantly for the paper, FOXG1 has previously been shown to promote exit from quiescence of glioblastoma stem cells (GSCs) and non-transformed neural stem cells (NSCs). In a previous screen, the authors identified FoxO6 as a potential direct target gene of FOXG1. In this paper, they showed that with the gain of expression for FOXG1 in NSCs and loss of FOXG1 in GSCs, FoxO6 is increased or decreased, respectively. Loss of FoxO6 in NSCs does not alter their cell cycle or cell shape and specification. Yet, loss of FoxO6 in NSCs blocks FOXG1-mediated exit from quiescence. To understand the mechanisms, they decided to overexpress FoxO6 in NSCs and demonstrated that the cells undergo macropinocytosis, a process by which cells can engulf large amount of nutriments from the external medium. It remains to be determined whether this macropinocytosis occurs in cells overexpressing FOXG1 and GSCs. The authors provide a first answer by showing that overexpression of FOXG1 induces not only FoxO6 but also the expression of PAK1, one of the key kinases that regulates the membrane engulfment of macropinocytosis in NSCs. In GSC lines, the decrease of FOXO6 decreases PAK1 levels.

      Major comments:

      The paper describes interesting and convincing results (number of cell lines, repeated experiments seems sufficient) but it is difficult to reconcile them all in a single model, and this diminishes the impact of the study. Epistatic interactions between FoxG1, FoxO6, PAK1 and macropinocytosis are not always studied in the same cell models. Whether FOXG1-induced exit from quiescence of NSCs is dependent on a FOXG1-->FOXO6-->PAK1-->Macropinocytosis axis remains to be demonstrated. Also does such an axis operate in tumor cells remains to be fully assessed? In particular, if FoxO6 overexpression in NSCs can induce macropinocytosis, is this cellular process induced by FoxO6 downstream of FOXG1 activity during NSC quiescence exit? Is PAK1 a relay of FoxO6? Experiments looking at macropinocytosis and the involvement of PAK1 in the cell models of Figure 4 will definitely help to bridge the different results all together.

      Minor comments:

      No minor comments

      Significance

      Understanding how hijacking of developmental programs by tumour cells contributes to their fitness is important for the design of cancer therapies, as these programs often confer resistance to tumour cells. Although it has been shown that FOXG1, this master TF of telencephalon specification, can give cells the ability to leave quiescence, the downstream mechanisms were unknown. The identification of FoxO6 as a relay for FOXG1 and the suggestion that this may involve macropinocytosis and the PAK1 enzyme is interesting. FoxO6 acts differently from other members of the FoxO family and PAK1 could indeed be targeted. If the authors can integrate several of their findings into a single model, their paper should be of interest to oncologists, developmental biologists and cell biologists.

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    3. EMBOpress 22 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      This manuscript by Ferguson et al. identifies FoxO6 as a FoxG1 target that promotes the reactivation of neural stem cells (NSCs). Quite remarkably, FoxO6 is dispensable for the proliferation or entry into quiescence of NSCs but required for their FoxG1-dependent reactivation. The authors claim that Pak1-induced macropinocytosis is required for quiescence exit and show that Pak1 expression depends on both FoxG1 and FoxO6. These findings are very interesting and could potentially help better understand the regulation of NSC quiescence. In addition, as the authors point out, they could shed light on the regulation of the exit of quiescence of glioblastoma multiforme (GBM) cells, which express higher levels of FoxG1 and FoxO6 than NSCs. The experiments are overall of high quality, with the authors making an appropriate and efficient use of CRISPR technologies to control the expression of their genes of interest in cultured NSCs. However, the findings are mostly the result of overexpression in NSCs (which do not seem to express FoxG1 or FoxO6) and the quiescence model used is neither the standard in the field nor appropriate to draw strong conclusions about quiescence exit in NSCs or GBM cells.

      Major comments:

      • The choice of NSCs as a main experimental model to understand the effects of FoxG1 and FoxO6 is not fully justified. The authors had previously shown that FoxG1 is expressed at very low levels in NSCs (Fig. 1A in Bulstrode et al. 2017). FoxO6 also seems to be barely expressed in NSCs (Fig. 1 of the current manuscript) and, in addition, its levels seem to go further down as cells exit quiescence (-Dox line in Fig. 2H). Therefore, these two genes do not seem to play an important role in the normal exit from quiescence of NSCs, with FoxO6 only affecting FoxG1 overexpression-induced exit from quiescence. If the aim is to mimic a GBM-like state by FoxG1 overexpression, this should be made much clearer in the text, including title and abstract. In that case, the authors should also show a direct comparison of the levels of FoxG1 in GBM and upon Dox-induced overexpression in NSCs.
      • While the authors state that they aim to study NSC quiescence, they use a protocol that is closer to modelling astrocytic differentiation. In fact, in their previous work, they use this very same protocol (removal of growth factors and addition of BMP) to study the role of FoxG1 and Sox2 on astrocyte de-differentiation (Bulstrode et al. 2017). While there is arguably no perfect in vitro model of NSC quiescence, the current standard in the field is treatment with both BMP and FGF for 48 to 72 hours (e.g.: Mira et al., 2010, Martynoga et al., 2013, Knobloch et al., 2017, Leeman et al., 2020). BMP alone is regarded as a pro-astrocytic differentiation cue, and 24 hours might not be enough for NSCs to fully commit to either differentiation or quiescence. Therefore, either the claims in the paper are changed to match the astrocytic differentiation model, or a standard quiescence protocol should be used throughout to confirm the findings also apply to the exit from quiescence of NSCs.
      • The FoxO6-induced vacuole formation in NSCs is a very interesting finding. However, so far it was only observed upon FoxO6 overexpression. To claim vacuolization is required for quiescence exit, the authors should show whether this phenomenon is also observed upon normal exit from quiescence and FoxG1-induced reactivation of NSCs. From the author's own data, Pak1 (which induces vacuolization) is unlikely to reactivate NSCs, as its expression is highest in BMP-treated cells (Figure 6F). The authors should show whether some vacuolization is present at these stage in NSCs and if not, discuss the possible interplay between Pak1 and FoxO6 in vacuole formation and quiescence exit.
      • Finally, the data on the regulation of Pak1 expression by FoxO6 is insufficient to draw any strong conclusions. Downregulation of Pak1 in FoxO6 cells is not enough evidence to claim a direct regulation. The authors should show whether Pak1 levels are increased after FoxO6 overexpression and whether FoxG1 is downregulated in FoxO6 KO NSCs (indirectly affecting Pak1 expression).

      Minor comments:

      Please state in the main text that NSCs are derived from the SVZ.

      Significance

      As I said before, I find this work tackles a very important question, how is the exit from quiescence controlled in NSCs. This manuscript will be of interest to researchers in the fields of adult stem cell biology and adult neurogenesis. While my expertise lies mostly on NSC biology, this work is of potential great interest for the cancer field, particularly for brain cancer research. Elucidating the mechanisms GBM cells use to exit quiescence is crucial in order to avoid the relapse of this aggressive form of brain cancer. To increase the relevance of the work to the cancer community, some of the key findings should be reproduced with GBM cells. It would be particularly important to show whether Pak1 induced vacuolization and macropinocytosis can be observed in GBM cells.

      PeerReviewed
    4. EMBOpress 22 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      The authors investigate mechanisms of quiescence and cell cycle entry in neural stem cells. Expanding on previous work, they show that FoxO6 is a target gene of FOXG1 in neural stem cells and glioma cancer stem cells. FoxO6 is upregulated following activation of stem cells from quiescence but is not required for proliferation. Continued over expression of FoxO6 leads to macropinocytosis through Pak1, indicating a link between FoxO6 and actin remodelling.

      Major comments

      The majority of the conclusions are well supported by strong experimental evidence. The only area where that is not fully the case is the role of Pak1 as a downstream effector of FoxG1-FoxO6 and its effects on macropinocytosis. To further strengthen this claim, the authors should demonstrate that ablation of Pak1 can rescue the functional consequences of forced FoxO6 expression and whether overexpression of Pak1 rescues quiescence exit in FoxO6 knockout.

      The manuscript stresses the role of NSC quiescence exit in GBM and demonstrates that FoxG1 KO reduces FoxO6 levels in a murine GBM cell line but a BMP4-mediated quiescence and dox-induced FoxG1 over-expression or an abolishment of cell cycle re-entry thereof by reduced FoxO6 levels in the case of FoxG1 KO is lacking. But this would significantly substantiate the relevance of the findings. In the introduction and discussion, FoxO6 is mentioned for its oncogenic roles in various cancers but no reference to GBM specifically is cited. It feels like a missed opportunity to not show evidence of this in the IENS cell line that has reduced levels of FoxO6; is there an effect in their proliferative capacity? What are the expression levels of Pak1 following FoxG1 KO in IENS cells?

      Minor comments

      • Fig1A shows 4 and 2-fold respectively for the two mouse NSC lines, not 17 and 4-fold increase as written on manuscript, please adjust accordingly.
      • Fig2G manuscript reports a 235-fold upregulation, but graph looks more like a 7 or 8-fold as shown on Fig1A for the F6 NSC line. I would recommend checking the fold changes reported throughout the paper.
      • The manuscript describes the increase of FOXG1 after BMP4-induced cell cycle exit as compared to non-BMP4 treated cells (p.8 first paragraph), but I am wondering if this expression is rather compared to dox negative and not vs BMP4 negative treatment.
      • In Fig2G it is interesting that FoxO6 is upregulated in BMP4 treated throughout the experiment with highest values at day10 post treatment. At the same time, non-BMP4 treated cells keep decreasing their FoxO6 levels dramatically but there is no mention or reference to this effect.
      • Fig2 would benefit from a western blot like Fig1D where FoxG1 and FoxO6-HA protein levels are also shown in dox-treated comparing BMP4-treated vs non-treated.
      • The colonies in Fig3E should be quantified, as their ability to form neurospheres seems somewhat compromised upon FoxO6 KO. Fig3B and 3F could perhaps be consolidated into one panel in the interest of space and presentation.
      • Fig4A shows vs "parental" non-BMP on y axis but wouldn't this show fold change of dox+ parental vs parental. The authors should clarify this.
      • Perhaps the authors can add a non-BMP4 treated count of % FOXG1 positive cells to Fig4C for reference.
      • The sentence mentioning Fig5D for the first time (p.10 third paragraph) needs rephrasing for clarity and should also call out Fig5C for the mCherry expression live cell imaging data where appropriate. Fig5D does not appear to be live imaging as implied by the text. If vacuole formation is observed already as early as 10-11h after Dox induction, then it should be shown somewhere in Fig5. Vacuole formation is shown with a higher magnification image inset only in the 22h timepoint image. I think Fig5E should be more substantiated with some sort of quantification, e.g. % of vacuoles positive for EEA1 and/or LAMP1.
      • Could the authors comment on the lack of proliferative advantage of the FoxO6 overexpression. FigS3 shows Edu staining, but there is no proliferation assay in either Fig5 or S3. What would be the effect of FoxO6 overexpression on BMP4-mediated quiescence with or without FoxG1 over-expression?
      • Can the authors clarify if there is a proliferation change in F6 cells in Fig6F as in Fig2F? Fig6F shows Pak1 is already upregulated in quiescent NSCs, what are the expression levels of Pak1 in FoxO6 -/- ANS4 cells upon FoxG1-mediated quiescence exit as shown in Fig4? Is there a particular reason why the F6 cell line data is shown only up to day2 post Dox-induction rather than d4 or d10? For consistency with the rest of similar experimental data this timeline should be extended. Does Pak1 remain elevated, plateaus or keeps reducing further post day2?

      Significance

      The study provides a conceptual advance for exit from stem cell quiescence. There is strong evidence provided for murine neural stem cells, but the link to GBM cancer stem cells is less developed (but perhaps this is the subject of a separate manuscript). While FoxG1 is a known regulator of neurodevelopment and glioblastoma, the functions of FoxO6 have not been studied in the context of neural stem cells. In my view, this study should be of high interest to audiences in both neurodevelopment and cancer research.

      Expertise: glioblastoma, cancer stem cells, neurodevelopment

      PeerReviewed
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    biorxiv.org/content/10.1101/2022.06.30.498283v1
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    Long non-coding RNAs regulate the expression of cell surface receptors in plants
    3
    1. EMBOpress 21 Jun 2024

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      The authors do not wish to provide a response at this time.

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    2. EMBOpress 21 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      In this ms, the authors searched using bioinformatic approaches for the presence of natural antisense RNAs (cis-NATs) linked to LRR-RLK genes, a large gene family containing many major regulators of plant growth, to detect a potential novel mechanism for their post-transcriptional regulation. They detected a large proportion of LRR-RLK genes containing cis-NATs. TO address their potential functions, they overexpressed specific cis-NATs against Bri1, CLV1 and SOBIR1 and observed phenotypes reminiscent of the respective mutant in these genes. This means that these cis-NATs can act in trans on the endogenous loci. The authors detected reduction in expression of the cognate LRR-RLK in several transgenic lines except for SOBIR1 where a minor change in protein production was found. Then, they prepare transgenic GUS lines with the promoters of the NATs and detect variable levels of expression. In addition, expressing the NATs under epidermal specific promoters but not in a control promoter induced differences in BRI1 expression specifically in the plants. Finally, they search for the presence of NATs linked to LRR-RLK loci in other plants.

      The paper is interesting but the message about NAT regulation is overstated and there are several conclusions that require major additional experiments

      1. There are no experiences with mutant NATs to confirm a potential linkage to the regulation of LRR-RLK complementary transcript. Overexpressing a NAT may lead to several artefacts, including the artificial silencing of the endogenous loci (expressing a complementary RNA). Hence, it cannot be concluded that this regulation occurs in planta only based on overexpressing lines. The use of rdr6 mutants or similar may also serve to discard potential alternative NAT regulations.
      2. Complementing a bri1 mutant (or in other RLK) with construct expressing the BRI1 locus with or without the NAT (e.g. with or without its promoter) is a much cleaner manner to show NAT regulation. CRISPR or other manipulation may allow to create mutants in the NAT alone to see the effects on its cis-target as well as its eventual trans action on other LRR-RLK (as apparently acts in trans).
      3. The trans-NAT experiments will minimally require genome-wide RNAseq studies to see the level of cross-talk of a trans NAT. Even though the phenotype is related, there may be very general misregulation triggered by the NAT. A minimum is to pass all studied RLK in all the lines to define certain "specificity" of action.
      4. To propose a translational regulation for SOBIR1 with its present data is an overstatement for me. Is the antisense nuclear or accumulate in ribosomes? Can the NAT lead to a change in the recruitment into ribosomes (without changing mRNA levels). There may be indirect effects that can explain these changes in protein accumulation
      5. The GUS plants need to be shown in detail, with a more precise tissular localisation and compared to the cognate LRR-RLK. Can BRI1 expression be monitored in TRANS-NAT BRI1 vs wt using in situ or BRI1-GFP fusions. TO show the expression patterns of the antisense and the target will further support the proposed specificity regulation. What happens with other LRR-RLKs? Kinetics of expression along development in trans NATs and wt will be a possibility
      6. The epidermal connection is interesting but there is any evidence about the "cell specificity" expression of BRI1 or the differential expression of BRI1 in cells containing or not the NATs?
      7. The extrapolation to crops might be interesting if some features are conserved (e.g. BRI1 homologs contain NATs of the same size or similar cell-specific regulation). As many genes have NATs, this evolutionary argument of the presence of NATs is not convincing to conclude about a regulatory mechanism permitting "to engineer improved crop performances".

      Significance

      The paper in its present form is very limited and the major strength is the occurrence of similar phenotypes when NATs are overexpressed and the mutant cognate mRNAs. Alternative explanations of the reported data are possible and should be discarded and better presented. This paper does not advance in NAT regulatory mechanisms to be relevant for a broad audience in life sciences. However, the subject of LRR-RLK regulation is of great interest to the plant community as several critical growth regulators act through LRR-RLKs.

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    3. EMBOpress 21 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The authors investigate the role of antisense transcription (cis-NATs) at Leucine-rich repeat receptor-like kinases (LRR-RLK) genes in plants. They find that many LRR-RLK genes are associated with cis-NATs, through data-mining and RT-PCR in Arabidopsis. For functional studies, they selected three cis-NATs for over-expression, from the BRI1, CLV1 and SOBIR genes, where over-expression has phenotypic consequences for the plants. They use reporter gene assays to study cisNAT expression is regulated across development. The authors examine the relationship between cis-NATs and LRR-RLKs in tomato and rice, where they also detect a high fraction of LRR-RLKs associated with cis-NATs.

      Major comments:

      • Over-expression of cis-NATs is used to support a functional role. Here, the experimental design leaves open if the effect is explained by a trans-acting role on the corresponding sense RNA (as the authors interpret), or, if the over-expression constructs trigger co-suppression of the corresponding sense RNAs. The authors should distinguish these possibilities prior to publication in a journal. It makes a big difference. Co-suppression would be a very different mechanism that is independent of the RNA functions the authors propose. The authors need to rule it out.

      Minor comments:

      • The authors use older resources to examine antisense transcription. In some sense, this makes it even more impressive that so many LRR-RLK genes are associated with antisense transcription, but it would be nice to include more recent data support the conclusions. In particular Araport11 is not considered a high-quality annotation (PMID: 34266383). The manuscript could benefit from the integration of some more recent genome-annotations, or genome browser screenshots for some the genes (e.g. BRI1, CLV1 and SOBIR) that shows some of the more recent methods (reviewed in PMID: 36259932). A lot of these data are even accessible on the TAIR website.

      Significance

      General assessment:

      The authors observe cisNATs at LRR-RLK genes. These findings hint at a contribution of cisNATs to LRR-RLK regulation that has not received much attention yet. For functional characterization, the authors rely on over-expression of cis-NATs. Here, I am sceptical, this the results could also fit a model where cisNAT OE may trigger siRNA formation and silencing of the endogenous locus (TGS/co-suppression).

      Advance: The manuscript uncovers cisNATs as potential large-scale regulators of LRR-RLK genes.

      Audience: Plant scientists interested in gene expression and cellular roles of LRR-RLK genes.

      Reviewer expertise: Plant lncRNA, genome annotation, plant gene expression, epigenetics.

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    biorxiv.org/content/10.1101/2024.04.22.590565v1
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    In vitro reconstitution reveals membrane clustering and RNA recruitment by the enteroviral AAA+ ATPase 2C
    5
    1. EMBOpress 20 Jun 2024

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      Reply to the reviewers

      We would like to thank all reviewers for their detailed and constructive feedback, which substantially helped improve the manuscript. We apologise for the time taken for the revisions, which was partially due to the first author (successfully) writing and defending her PhD thesis in the same time frame. We would like to point out already here that, based on reviewers' feedback, main figure 6 is completely redone and the conclusions of this figure have changed substantially. We no longer suggest RNA chaperoning activity (it was identified as being due to the high concentration of TEV protease, in a control suggested by the reviewers). Instead, our refined assay conditions with lower TEV protease concentration identified ribonuclease activity of membrane-bound full-length 2C, which is consistent with a publication from 2022 (PMID: 35947700).

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

      Evidence, reproducibility, and clarity

      Summary:

      In this study by Shankar and colleagues, the authors aim to understand the structure and function of the enterovirus 2C protein, a putative viral helicase with AAA+ ATPase activity. Using poliovirus (as a model enterovirus) 2C, the author's propose the protein contains two amphipathic helices (AH1 and AH2) at the N-terminus that are divided by a conserved glycine. Using purified MBP-tagged 2C and N-terminal 2C truncations, their data suggests AH1 is primarily responsible for clustering at membranes, whilst AH2 is the main mediator of 2C oligmerisation and membrane binding. Furthermore, 2C was suggested to be able to recruit RNA to membranes, with a preference for dsRNA, and the author's data implies that the helicase activity of 2C is ATP-independent. Instead, the ATP activity appears to be required for 2C hexamer formation or chaperone activity. The manuscript is generally well written /presented and the author's present very interesting data which raises several questions, some of which require additional experimentation to help support the author's conclusions. Specific comments are as follows.

      We thanks the reviewer for the overall positive assessment, as well as the specific comments below.

      Major Comments:

      1. The authors use four main constructs throughout the paper: full-length 2C, 2C with deletion of AH1 (ΔAH1), 2C with both AH1 and AH2 deleted (ΔMBP) and 2C with an extended N-terminal deletion. From this, the author's draw conclusions on the function of both AH1 and AH2. One of the author's main conclusions is that AH2 is the main mediator of 2C membrane association (e.g., in line 169). However, is it possible to conclude the relative importance of AH1 vs AH2 without testing a construct containing the deletion of AH2 only (ΔAH2)? This should be generated and used alongside this data to fully define the relative importance of AH1 and AH2 in these assay and remove the possibility that the deletion of AH1 changes the structure and/or function of AH2, which could also result in the observed differences.

      This was a very good suggestion. We expressed and purified the ΔAH2 protein requested by the reviewer and characterized its oligomeric state as well as its membrane binding. It turns out, as suspected, that the ΔAH2 protein behaves very similarly to the ΔMBD protein (i.e. it does not form higher order oligomers and does not bind membranes). The changes in the manuscript due to this addition are many but can primarily be found in main figures 2-3 and their associated supplementary figures.

      Previous structural predictions of 2C do not appear to have two separate AHs at the N-terminus. Are the AH1 and AH2 structures predicted to be formed in the context of the entire 2C protein, 2BC precursors and polyprotein? Are there structural approaches that could provide experimental evidence for two separate AH at the N-terminus?

      This is a good point. Previous predictions were not that detailed, partially since they were done in the pre-alphafold era. Unfortunately, we cannot think of a tractable experimental method that could verify the split nature of the amphipathic helix in the only context that would matter: the protein bound to a membrane. A long-term goal would be in situ structures of full-length 2C on membranes using cryo-electron tomography, but our current sample and data sets are not sufficient for this. We added a mention of the long-term need for experimental structures of full-length 2C on lines 315-318 in the discussion.

      Why are the 2C dimers (lines 137-138) not apparent on the mass photometry data presented (figure 2)?

      Different constructs were measured by mas photometry and SEC-MALS. Also, the required concentration is 100-1000x lower for mass photometry which will affect a dynamic equilibrium in case the same construct were measured by the two methods.

      It appeared that binding of ΔMBD-2C was better when POPS is in the membrane (line 174). What is the explanation for this and was this finding significant?

      Well spotted. It may mean that 2C has a second, lower affinity membrane-binding site which is charge-dependent somewhere outside the MBD. We now added a mention of this in the discussion, lines 321-323.

      From the author's data on lipid drop clustering they conclude ΔAH1 is more effective for clustering, however, the ΔAH1 construct produces pentamers not hexamers (from Figure 2). Is formation of hexamers related to or required for membrane clustering?

      ΔAH1 is LESS effective at clustering, not more. As for the mention of pentamers in the original submission: we now think this was an unfortunate choice of words. The mass photometry data for 2C(ΔAH1) could more parsimoniously be interpreted as a mix of hexamers and other (unknown to us) smaller oligomers such as trimers. We have removed all mentions of pentamers.

      The replicon data presented in Figure 7 should include a replication-defective control (e.g., polymerase mutant), in order to compare how defective in replication ΔAH1 and ΔMBP deletions are compared to a fully-defective construct. Likewise, deletion of ΔAH1 in this construct is likely to affect processing of the viral polyprotein where several previous studies with picornaviruses have demonstrated that the residues in the P2'-P4' positions can change cleavage efficiency (e.g., PMID: 2542331), or the structure of 2C, leading to the reduction of replication.

      Thanks for these good comments. We made the polymerase-dead (GDD-to-GAA) replicon and remeasured it side by side with the 2C replicons. It has a similar luciferase activity indicating that no replication takes place in the 2C deletion replicons. This is shown in the new figure 7. As for the possibility or processing defects, we mentioned this in the original discussion and have now cited the reference suggested by the reviewer in this context (line 324).

      How does the author's model of ATPase-independent helicase activity and an APT-dependent required RNA chaperone activity fit with 2 step model for RNA binding and ATPase activity suggested by Yeager et al (PMID: 36399514)?

      Acting upon comments from other reviewers, we completely redid the "helicase assay" in the revised manuscript. It turns out that the ATP-independent unwinding activity in the original submission was an artefact of the assay conditions (specifically, of the TEV protease at the higher concentration we used in the old assay). In our improved assay we neither see helicase activity nor ATP-independent RNA chaperoning activity.

      Optional major comments that would increase the significance of the work:

      All of the optional comments below are exceptionally interesting. But given the long time needed for the several major changes to this manuscript (e.g. the ΔAH2 protein characterization and reoptimisation of the helicase assay) we believe it is more sensible to address them in future studies, for which the 2C reconstitution system can be used.

      The preference for dsRNA over ssRNA appears to be quite small (Figure 5d). In the context of a viral infection where ssRNA is likely to outnumber dsRNA at different times during infection is this preference physiologically relevant? In relation to this, what size stretch of dsRNA is required for preference, and could this correspond to cis-acting RNA structural elements, dsRNA as it escapes 3D polymerase or as part of the RF and RI forms (PMID: 9343205)? What is the proposed mechanism of how dsRNA outcompetes membrane tethering of 2C? OPTIONAL The author's study has been conducted in the absence of other viral non-structural proteins. What is the physiological importance of the observations, such as membrane interaction/clustering or RNA binding when presented in the context of the other replication machinery. OPTIONAL Do 2C monomers, dimers and hexamers have different functions in viral replication perhaps at different stages of replication and which of these forms are relevant during viral infection or can they all be detected during infection? Can any suggested separate functional arrangements be separated by genetic complementation experiments? OPTIONAL

      Minor comments:

      1. The author's appear to interchange between naming/nomenclature of the constructs which makes it confusing to follow (for example, ΔMBD is the same as 2C(41-329) likewise, 2C(Δ115) is sometimes called 2C(116-329)). It would be much easier to follow if the naming of constructs was consistent throughout (unless I am misunderstanding some subtlety in the difference between such constructs).

      Thanks very much for spotting this. We have fixed it.

      The author's suggest a pentamer arrangement for the ΔAH1 construct, however in the mass photometry data (figure 2D), a hexamer is indicated with the arrow. It would be helpful to change the label to indicate the size of the pentamer where this is being generated, not the hexamer.

      As mentioned above, we think the "pentamer" designation of the original manuscript was unfortunate. It is more parsimonious to interpret this as a mix of states, hexamer and undefined snaller.

      In most figures, data for full-length 2C, ΔAH1 and ΔMBP is shown. However data for ΔMBP is missing in Figure 4. Using ΔMBP may demonstrate even lower clustering, hinting that AH2 is also involved in this process.

      Thanks for this comment. In our view, it can be derived from figure 3 (which shows lack of binding to PC/PE membranes) that the ΔMBD construct would not cluster membranes under the conditions of the assay (clustering requires concomitant binding to two membranes). We now describe our rationale for this on lines 220-222. However, we did include the ΔMBD protein in the new negative staining TEM supplementary figure where it and ΔAH2 show no signs of clustering (figure S10).

      I think it would be better for normalise the data in the flotation experiments such that the percentage of 2C in the upper faction is presented as relative to the amount of lipid in the upper fraction (presented in Figure S4).

      The change suggested by the reviewer would make it impossible to show the important no-liposome control (leftmost bar in Fig. 3C) in the same plot as the other measurements. We believe that would unnecessarily complicate the figure. Thus, we opted to keep the measurement that are normalised by lipid fluorescence in the supplementary figure. Instead, we now added another mention of this supplementary figure in the legend to main figure 3.

      At several places (e.g., lines 232 and 272) the author's refer to "realistic systems". I think the term "physiologically relevant" might be more appropriate.

      Agreed and changed throughout.

      Line 237: I think "y" is a typo and should read "by".

      Thanks. This text was reworked due to the major changes to figure 6.

      Reviewer #1 (Significance (Required)):

      Significance

      I have limited expertise with structural biology but specialise my research on positive-sense RNA virus replication, structure and function. This research is of interest to a broad audience of researchers investigating many positive-sense RNA viruses, which extends beyond the viral family studied here. The work utilises novel techniques to begin to understand the specific roles of 2C in poliovirus replication. The author's data add important incremental new insight into recent studies on viral helicase proteins as referenced in the study, however, a key limitation is understanding the importance/relevance of their observations during a viral infection.

      We thanks the reviewer for this positive and nuanced appraisal of our work.

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

      The authors present an alternative assay system to investigate picornavirus 2C, a protein that is tricky to analyze biochemically in its full length form because of an amphipathic helix at the N-terminus. Poliovirus 2C is expressed with an N-terminal MBP tag, a 50kD protein that helps with solubility as is commonly used for 2C investigations. A difference here is that liposomes are included to mimic membranes for 2C attachment. The key findings are that 2C induces clustering of of liposomes, that double stranded RNA binding by 2C impacts this clustering effect and that a free N-terminus (after cleavage of MBP by TEV protease) is needed for RNA binding and an ATP independent (ie non helicase) RNA duplex separation activity.

      Major:

      In the floatation assays in figure 3 the authors use a system where MBP-2C is fluorophore-labeled with ATTO488 on exposed cysteines. Poliovirus and other enterovirus 2C has a very well characterized zinc finger domain that has cysteines coordinating a zinc ion. Mutation experiments previously showed that these cysteines are necessary for viral replication and 2C stability. Have the authors controlled for disruption of the zinc finger domain by the labelling of cysteines with ATT0488 and checked if the protein remains folded?

      We completely agree with the reviewer and apologise for the omission in the original submission. We have now included a Zn content measurement, which shows unchanged levels between labelled and unlabelled 2C protein (Figure S7). Also, we now in the revised manuscript explicitly describe our original reasoning for labelling on native cysteines: the presence of two cysteines which are not necessary for viral replication and which are more solvent exposed-exposed (and thus more likely to be labelled) in the crystal structure of the soluble fragment of 2C (lines 176-181).

      In the analysis of the amphipathic helix, did the authors include membranes in their structural predictions o just the free helix? How does inclusion of membranes impact the predictions? In the predictions in Figure D, only 2 of 4 show a kink and there doesn't seem to be a correlation between those that predict a kink or not and whether the hydrophobic side is aligned in Figure S1.

      Unfortunately, predicting a protein structure with the interacting membrane is beyond what is currently doable with protein prediction methods (one would have to combine protein structure predictions with molecular dynamics simulations including a membrane). Based on general principles of protein structure, it is likely that there is some flexibility around G17. Thus there may not be a single "kink angle" for any given virus, but we believe that the presence of the kink (and offset hydrophobic surfaces) for a number of viruses lends credibility and robustness to the observation. We added some descriptions of this thinking on lines 126-127.

      Based on previous structures of 2C from different viruses the N-terminal amphipathic helix containing region is predicted to localize on one face of the predicted hexametric structure tethering 2C to the membrane. How does the authors hypothesized model explain 2C dependent clustering? is there evidence that 2C hexamers can oligomerize further into dodecamers for example, maintaining separate faces to enable N-terminal interaction with different membranes? What is the distance between the liposomes in figure 4 at the points of density attributed to 2C? How does this compare to the size of 2C determined in previous structural studies? Is it consistent with one hexamer/2 hexamers sitting on top of one another?

      These are very interesting questions but we believe it is prudent to limit our speculation at this point. Eventually, we hope that larger data sets of cryo-electron tomography, coupled to subtomogram averaging, may provide a more definitive answer. What we managed to do with our current cryo-electron tomography data set is to estimate the volume of individual protein densities, and from the volume calculate an estimated molecular mass of the individual complexes seen in the tomograms. This correlates very well with 2C hexamers (new figure 4D).

      In the Discussion lines 278-285 the authors suggest that having MBP attached may reflect the polyprotein condition. Can they make a construct with MBP-2B2C to examine interaction with liposomes and assess 2C function?

      This is a highly relevant question, but the biochemistry of 2BC is even more challenging than 2C, and we are unfortunately nowhere near being able to work with purified 2BC at the moment.

      Discussion lines 293-296, the possibility of two different populations of 2C, binding RNA or membranes cannot be excluded, there is much more 2C around late in infection that present in early infection- the model in figure 8 doesn't acknowledge/capture this.

      We have changed the model figure such that more 2C is seen later, and the clustering function is also seen late in infection. The original discussion text referred to (which is unchanged) talks about a "preferential role in RNA replication and particle assembly at later time points" specifically for this reason. We hope the new figure 8 is better at conveying this message.

      Discussion lines 313-317, the authors don't reference a study where a mutant of foot-and-mouth disease virus 2C lacking the n-terminal amphipathic helix that could bind but not hydrolyze ATP, hexamerized in the presence of RNA that seems pertinent here (PMID: 20507978).

      Thanks for the suggestion. However, after the extensive changes we made to the revised to figure 6 based on excellent reviewer comments (essentially: the RNA chaperoning activity turned out to be an artefact, the improved assay shows no sign of RNA unwinding but instead of 2C-mediated ribonuclease activity), these sentence of the original discussion lost most of their context and we opted to remove them.

      Some evidence of MBP-2C cleavage by TEV in the different assays used should be presented as this is a major focus of discussion and currently no gels show TEV cleavage is happening.

      Thanks for the suggestion - we agree. We now show these in the new supplementary figures S5 and S12.

      Reviewer #2 (Significance (Required)):

      The work presents an additional methodology to investigate a a protein that has previously been difficult to study. The authors acknowledge that there is still a lot of 2C biology that remains to be discovered.

      Thanks, we agree.

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

      The manuscript provides insights into the role of the N-terminus in membrane binding and its importance in the various functions of 2C.

      Major issues

      Line 103-119. Is this novel? I thought people had done a lot of bioinformatic analysis of PV 2C (especially Wimmer) who also did mutational work to analyse the importance of various amino acids in the N-terminal helix. I feel like the paper in general, and this section in particular, underplays the large body of work that has been done on the amphipathic helix by various groups.

      We apologise if our original manuscript didn't sufficiently acknowledge previous work in the field. In the first sentence of the mentioned paragraph (now lines 112-113) , we did however cite several papers that have previously addressed the amphipathic nature of the N-terminus of 2C. We have now added two more references along the same line, and changed the wording in a way that we hope better bring across that the amphipathic nature per se has been studies before. We would be happy to add more specific references if the reviewer has any suggestions. However, the rest of our analysis IS indeed novel for the following reasons: (i) we show that the amphipathic region is not a simple, single amphipathic helix, but instead has a conserved glycine (helix breaker/destabiliser residue) and two distinct amphipathic stretches before and after this region, (ii) we use alphafold2 (not available at the time of the earlier work) to provide the first reliable structural models of the membrane-binding domain. These models consistently, across several enterovirus 2C proteins, reveal that the hydrophobic surfaces of the first and second amphipathic regions, on either side of the conserved glycine 17, are offset from one another. This lends additional credibility to the distinct nature of these regions which have not previously been identified as such and which we also show in the biochemical assays to be functionally distinct. We have now also added a clarification to the Discussion that the N-terminus of 2C had previously been identified as its membrane-binding domain and we cite references for this. We hope that these changes will sufficiently acknowledge earlier work in the field while clearly pointing out the advance that our paper makes.

      Line 132. Did you validate your column with known MW standards? The peak for full length and deltaAH1 look fairly standard for 2C, in that you have a mixture of species. Not sure you can say it is a hexamer when it is such a broad peak. C doesn't really help you too much since the counts at 400 (pentamer) and 480 (hexamer) are almost the same with quite large error bars. Like most people that have worked with 2C I think the best you can say is that you are making some kind of oligomerized 2C that includes hexamer, pentamer, etc. Why no dimer for MBP-2C and MBP-2C(delta AH1) when compared to the other constructs?

      We did not calibrate the gel filtration column since the outcome would anyway be a more crude estimate of molecular mass than the mass photometry and SEC-MALS measurements. But we do agree with the reviewer on the broad mass photometry peaks. To address this experimentally, we compared the existing MBP-2C spectra to new recordings on apoferritin, a highly stable homomultimeric protein complex of a similar mass to aa MBP-2C hexamer. The apoferritin mass estimate is overlayed with the full-length MBP-2C in the new figure 2D and the corresponding supplementary figure S3. This indeed shows that the MBP-2C peak is broader, i.e. consistent with a mix of species which are predominantly but not only hexamers. We describe and discuss this on lines 145-149. As for the mention of pentamers in the original submission: we now think this was an unfortunate choice of words. The mass photometry data for 2C(ΔAH1) could more parsimoniously be interpreted as a mix of hexamers and other (unknown to us) smaller oligomers such as trimers. We have removed all mentions of pentamers.

      Line 143. Does your data show that there are two amphipathic helices? Bioinformatics suggests it but your experiments just show the importance of the two areas in oligomerization, not that it is forming two helices.

      We agree that the choice of words was not idea and have now changed it to "structure predictions indicate" (lines 162).

      Figure S2. Your preps are still relatively dirty, which isn't ideal for biochemical assays. Especially lane 3, where you are looking at 50-60% purity. I don't want you to re-run experiments but I think you need to comment on the purity of the protein you are working with. Also I don't like that you removed the top and bottom of the SDS-PAGE. How much protein never entered the gel. Is there a big fat band at 20 kDa? You need to have the full gel here. Did you measure 260 nm of the preps as well to see if you had bound RNA to the 2C?

      Thanks for the comment, we agree that our original submission lacked detail in the description of the protein purification. This is now addressed with the new figure S2 which shows size exclusion chromatograms of the fluorophore-labelled proteins (same chromatograms as in figure 2) and the corresponding uncropped gels imaged both in the stain-free channel (showing all proteins) and in the fluorescence channel. The A260/A280 ratio measured for all proteins shows that they are free of nucleic acids at the point of imaging. The protein preps are not 100% homogeneous but we do believe that they are more than 50-60% pure.

      Lines 170. Wasn't this done in the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles"? I don't see it referenced. What is novel about the current work when compared to that paper? Any differences?

      Thanks for pointing this out. The referenced study worked with a synthesized, isolated peptide corresponding to AH2 (i.e. not with full protein). An amphipathic peptide outside the context of its protein cannot be expected to recapitulate the properties of the entire protein, e.g. since it is not spatially constrained in how it interactis with membranes. As one example (relating to the title of that paper) we don't see full-length 2C protein tubulating membranes the way the isolated peptide does. As for the reviewer's question about novelty, the paper mentioned does not identify the split nature of the amphipathic region, does not consider the role of AH1, does not characterise the membrane-binding properties of full-length 2C with respect to liposome membrane composition and size, does not identify and characterise the membrane clustering properties of 2C, nor its interactions with nucleic acid when bound to a membrane. However, we do agree that we should have cited the paper in our manuscript. We now cite it in the discussion, lines 320-321.

      I'm surprised by the lack of electron microscopy (negative stain mostly) of both the oligomerized 2C and the various liposomes. I know the Carlson group is a microscopy group so why the lack of validation using electron microscopy of the various DLS experiments? I know you did cryo-ET for one of the constructs but I think negative stain electron microscopy of other constructs would be useful.

      Thanks for the suggestion. As suggested, we have now expanded the analysis with negative staining EM of several more constructs studied by DLS. It can be found in the new supplementary figure S10.

      Figure 4C. What evidence is there that this is 2C apart from you added it to the liposomes? It also comes back to the relative impurity of your protein prep. Could this be E.coli contamination?

      Thanks for this comment. We have now added a new supplementary figure (S5) showing SDS-PAGE gels of the reactions used for flotation and DLS assays - which are identical to the cryo-ET samples. In addition, we estimated the molecular mass of the individual, putative 2C desities in the cryo-electron tomograms by measuring their volume. This analysis, which can be found in the new figure 4D, shows that the estimated mass of individual protein densities is consistent with a hexamer of full-length 2C. In addition, we mention in the discussion the long-term need to determine high-resolution structures of membrane-bound 2C using cryo-ET and subtomogram averaging (lines 315-318).

      Figure 8. Is this model supported by the data in this paper? Your cryo-ET says that 2C is there but that isn't supported by any other data. How is the dsRNA protected from the innate immune system in this model? is it just sat out in the cytosol? How is the nascent ssRNA packeged into the capsid? Is there competition between the dsRNA and capsid for 2C binding (which your model suggests)? I know it sounds like I am being overly critical of the model but in my opinion there are still too many unanswered questions in the field to come up with a half decent model.

      Thanks for this comment. We are the first to agree that our understanding of the roles of 2C is far from complete! We should have been more clear that the model figure represents some of the roles of 2C identified to date, and does not claim to be complete. However we do feel that a model figure serves a purpose of putting our findings into a context, and also providing testable hypotheses for future research . As for the question, some of the roles of 2C shown in the model figure (in particular, particle assembly) are rather supported but earlier work of ourselves and others. We have now produced a new model figure and changed the figure legend to better reflect the incompleteness of the current understanding, and the origin of the different parts of the model figure. In addition, we extended the final paragraph of the discussion (which lists still-unknown aspects of 2C) with the reviewer's mention of dsRNA shielding from innate immunity (lines 374-375). The other aspects mentioned by the reviewer as not yet fully understood are already mentioned in that paragraph.

      Minor issues

      Lines 43-45: I feel like you underplay the success of the poliovirus vaccination program. Approximately 30 of WPV1 in 2022 and the full eradication of WPV2 and 3. Vaccine derived polio is still an issue but even that is relatively low compared to where the world was in the 1950s.

      We agree that the previous wording was not ideal. We replaced it and added another recent reference - related to the type 2 vaccine switch (lines 47-49).

      Line 66. I agree there are 11 individual proteins but I feel like this leaves out the fact that some of the uncleaved precursors appear to have some functions, for example 2BC.

      Good point. We have now added a mention of 2BC and the fact that it has distinct functions to the introduction (lines 70-71). 2BC is also mentioned in the legend of the model figure (figure 8).

      Line 56: LD needs to be defined.

      Well spotted thanks. Since the abbreviation was not used anywhere else we opted to spell it out instead (line 59).

      Line 75. I think you have misrepresented Xia et al here. They clearly say that in their study that they show helicase and chaperone activity. I never managed to repeat that work but you should still report what they claim. One major thing is that they used insect expressed protein, whereas most people (including myself and in the paper under review) use E.coli expressed protein. Do post translational modifications play an important role in function?

      You are right that the reference to their paper for this statement was incorrect. We have now made this part of the introduction more explicit (lines 82-83) and we also in the new discussion mention the possibility of e.g. post-translational modifications affecting 2C helicase activity, under reference to Xia et al (lines 359-361)

      Line 103. Need to make it clear here it is poliovirus 2C.

      Thanks, we added it (line 112).

      Line 135. I assume you mean kDa instead of uM?

      It should actually be μM. It is the solution concentration at which the assay was performed. We added some words to clarify this (line 154).

      Figure 3. What do you mean by "Only 2C"? Is that MBP-2C? Maybe I am reading the data wrong but adding TEV does nothing? How do you know TEV is removing the MBP? It looks like MBP-2C binds to the liposomes just the same as cleaved MBP-2C. I see in line 165 you acknowledge this. Could an alternative conclusion for line 168 be that MBP isn't being cleaved off but that AH2 is too small to be exposed in that construct? Did you do that construct without MBP being cleaved? I think you need to confirm that MBP is being cleaved off.

      Thanks for spotting this mistake. It should indeed be MBP-2C (in the absence of liposomes). We corrected figure 3. Also, in response to this comment and similar ones, we have now added a new supplementary figure showing SDS-PAGE gels of the reaction loaded onto flotation assays and DLS (figure S5). It shows that MBP-2C is cleaved.

      Line 184. Is there a reason you use the 2019 paper as a reference instead of the far earlier Bienz et al papers? I'd suggest they are the seminal papers on 2C membrane association. Once again how is this work different from the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles" paper?

      See our response above of the paper mentioned here (which we have now cited). As for why we cite the 2019 paper here: our statement pertains specifically to the contact sites between lipid droplets and replication organelles, not to the membrane binding of 2C per se. We have now added a more general mention of membrane remodelling by non-structural proteins in the introduction, where we cite on of the Bienz papers (lines 75-77).

      Figure 5D. So only 1-3% of RNA is found in the upper fraction? Is that significant enough to say that dsRNA was recruited significantly more than ssRNA? How confident are you in your quantification of the starting amounts of RNA?

      We agree that the fraction is low, however, the fluorescence signal is very clearly above background. We are thus confident in the measurement. The low percentage at the end of the experiment likely has a simple physico-chemical explanation: in a dynamic equilibrium in a density gradient, whatever RNA dissociates during the run will migrate away from the 2C-vesicle fraction and not be able to rebind. We still tried to address this concern by a complementary experiment where we used fluorescence anisotropy to measure binding of RNA to 2C on vesicles. While the measurements showed the same tendency, they curves were not clean enough to be published, which we think is due to the complex system with 2C bound to vesicles and clusters of vesicles. Still, in view of the relatively low percentage of measured recruitment we opted to adjust the paper title and the title of figure 5 (including the subheading related to figure 5) to put less emphasis on the dsRNA recruitment.

      Line 223. Any idea why the MBP needs to be cleaved off? Clearly the MDB is accessible or it would not bind to the liposomes.

      Since we have no data directly supporting this we prefer not to speculate in the paper. But one guess would be that the NTD of 2C, as implicated by previous publications, has a dual role in membrane binding and RNA binding. It may be that it can bind membrane while conjugated to MBP, but needs MBP to be removed in order to simultaneously bind membrane and RNA.

      Line 237: missing "b" in "by"

      Thanks. This paragraph was rewritten in the light of the changes to figure 6.

      Figure 6. I don't fully understand the results here. Earlier you showed that the delta MBD didn't really bind SUV. So presumably it isn't really membrane bound. Why does it have similar activity to full-length MBP in your helicase assay if membrane is important? Did you do SUV and TEV protease only control?

      We are very grateful to this reviewer (and others) for pointing out the need for a TEV control. When performing the control, we found that the TEV protease, at the high concentrations initially used, surprisingly had an artefactual RNA chaperone-like effect on its own. We then proceeded to titrate down the TEV protease concentration to the point where it no longer interfered. At this TEV protease concentration, although 2C was substantially cleaved (see the new supplementary figure S12), we could no longer detect an RNA chaperone activity. Thus, the contents of the new figure 6, and its conclusions, have been substantially changed. We now focused our attention on the remaining effect that 2C has on RNA: single-strand ribonuclease activity. These experiments were all conducted in the presence of RNase inhibitors, and the presence of Mg2+-dependent ribonuclease activity parallels a recent publication that found this for truncated 2C from hepatitis A and several enteroviruses.

      Line 257: "staring"?

      Thanks, corrected. A staring glycine would indeed be something strange.

      Line 336. Need to change the u to mu.

      Thanks, corrected.

      Any discussion on your observation in Figure 1D that EV71 and CVB3 don't appear to have AH1 and AH2 or do you think that the domains are conserved across the different viruses?

      Thanks for bringing this up. Based on this and a comment from another reviewer, we have now clarified our thinking around this. Since the glycine will introduce some flexibility between AH1 and AH2, we cannot say from the single alphafold predictions that this is THE kink angle. The presence of the kink in the predictions of several MBDs lends more credibility to the robustness of the observation, but most importantly the hydrophobic surfaces in AH1 and AH2 are non-aligned for ALL sequences we looked at. This is now described on lines 126-128.

      Table 1 (and possibly elsewhere): an apostrophe is not the prime symbol. 5' compared to 5′.

      Thanks, we corrected this throughout.

      Line 702 "and" should be "an".

      Thanks, corrected.

      I couldn't open one of the movies (140844_0_supp_2820374_a2g272.avi).

      Sorry to hear this, we will check the movie again.

      Reviewer #3 (Significance (Required)):

      Overall I liked the paper and is worth publishing. One of the issues in the 2C field is the difficulty in making pure 2C and carrying out in vitro assays that correlate with what is observed in the natural infection. I think this paper suffers from similar struggles with a 2C preparation that doesn't appear that pure. I think it also suffers from not having 2C from a wild-type infection. I don't think that it is feasible to get that kind of 2C but by once again using a recombinant protein from E.coli we are left with another manuscript that provides conflicting evidence of the functions of 2C without a definitive answer. The experiments are well done, although are missing some controls and the manuscript is laid out in a logical manner and is relatively easy to follow.

      We thanks the reviewer for these comments. We believe that we have now provided better information regarding the purification of the recombinant 2C protein, and we do think that the controls present in the original manuscript and the revised manuscript alleviate the concerns about lack of specificity. Of course, isolating 2C vesicles from wildtype infection would be another interesting way of approaching its function, but such an approach would come with its own set of challenges related e.g. to the presence of confounding host factors.

      Reviewer #4 (Evidence, reproducibility and clarity (Required)):

      This is an interesting manuscript that reports the development of an in vitro membrane assay for probing the biochemical functions of the enterovirus 2C protein. The technique is interesting because it can be applied to 2C proteins from other members of the picornavirus family, an important group of mammalian pathogens. It has the capacity to probe different functions (e.g. membrane clustering, ATPase activity, RNA-binding and manipulation activities).

      Overall, the manuscript is well written and gives a clear account of the work undertaken. It adds insight to previous studies of enteroviral (and picornaviral) 2C proteins, providing confirmation of some earlier work in a more physiological context and some new insights, particularly into the membrane and RNA binding aspects of 2C.

      That said, there are a number of places where some amendment of the claims made is required to provide a more precise statement of the findings of this work. These are listed below.

      We thank the reviewer for this positive feedback on our work, as well as for the specific comments below.

      Line 21 (Abstract) - The authors claim to have shown that a conserved glycine divides the N-terminal membrane-binding domain into 2 helices. I would suggest instead what they have produced are computational predictions that this is the case - some way short of an experimental demonstration. Sequence analysis predicts helical secondary structure in the N-terminus and indeed Alphafold2 also predicts a helical structure, but these predictions require experimental verification. The authors should therefore rewrite sections that claim to have shown the presence of 2 helices. In doing so, they should perhaps also comment on the fact that Alphafold2 does not predict 2 helices in this region for all enteroviruses (see Fig 1D). Moreover, the sequence analysis in Fig. S1 shows the presence of two Lys residues in the segment 17-38; it would be interesting for the reader to have these indicated in the figures showing the Alphafold2 prediction - do they in any way interrupt the hydrophobic face of the predicted helix?

      Thanks very much for this comment, which is in line with what other reviewers also wrote. We agree, and changed the abstract sentence. We have also rewritten the manuscripts in several places to address the limits of structure predictions and the eventual need for an experimental structure of full-length membrane-bound 2C (lines 126-128 and 315-318).

      Line 82 (Introduction) - The authors write that the membrane binding domain (MBD) of poliovirus has been shown to mediate hexamerisation, citing Adams et al (2009) - reference 43. However, that is not what this paper shows. Rather it provides evidence of aggregation of an MBP-2C fusion protein into forms that ranged from tetramer to octamer, but no evidence that these aggregates assume functional forms (e.g. the presumed hexameric ring structure characteristic of the AAA+ ATPase family to which 2C belongs). As far as I am aware the first demonstration of hexameric ring formation by a picornaviral 2C protein was for the 2C of foot-and-mouth disease virus (see Sweeney et al, JBC, 2010). Although this is not an enterovirus, this finding was later confirmed for Echovirus 30 (ref 51). I should declare an interest here: the Sweeney paper is from my lab. I will leave it to the editor and the authors to determine how to write a more precise account of the early observations of hexamerisation in picornaviral and enteroviral 2C proteins.

      Thanks very much for this insightful comment. As a response to this and other similar comments, we are much more cautious about our wording in the revised manuscript (see also response to comment below. In the part of the introduction discussed here (now lines 89-91) we now use the original wording of the Adams paper ("oligomerization"). In the context of that new text we didn't feel that Sweeney et al paper was a suitable reference, but we now cite it in the later mention of 2C's oligomeric/hexameric state in the first part of the Results (lines 137-138 ).

      Line 132 - the authors used mass photometry to investigate oligomeric forms of their MBP-2C constructs and state that for the full length 2C protein "the high-mass peak closely corresponds to a hexamer". While it is true that the peak shown in Fig 2C aligns with the expected MW for an MBP-2C hexamer, the peak is very broad, indicative of the presence of other oligomeric states with lower and higher numbers of monomers. This should be commented on. Indeed, the finding seems to echo the early findings of Adams et al (ref 43) with poliovirus MBP-2C.

      Thanks for this comment, which was also made by another reviewer. We cite here what we replied to that reviewer

      ...we do agree with the reviewer on the broad mass photometry peaks. To address this experimentally, we compared the existing MBP-2C spectra to new recordings on apoferritin, a highly stable homomultimeric protein complex of a similar mass to aa MBP-2C hexamer. The apoferritin mass estimate is overlayed with the full-length MBP-2C in the new figure 2D and the corresponding supplementary figure S3. This indeed shows that the MBP-2C peak is broader, i.e. consistent with a mix of species which are predominantly but not only hexamers. We describe and discuss this on lines 145-149.

      Line 143 - for the reasons given above, this summary paragraph represents too strong a statement of what has been observed.

      We agree, and changed the paragraph. It now only refers to "oligomerization" (lines 162-164).

      Line 197 - I note that the authors did not test the membrane clustering capabilities of the 2C(41-329) construct. Although the 2C(deltaAH1) construct had already shown a significant loss of activity, the shorter construct could still have been a useful control. I don't think it is necessary for this experiment to be done, but if the authors have a rationale for not performing the experiment, perhaps they could include it in a revised manuscript.

      Thanks for the suggestion. The rationale is that a protein that doesn't bind a membrane in the first place will also not cluster them (an action that requires binding TWO membranes). We now describe our reasoning on lines 220-222. Nevertheless, we did test these constructs in the new supplementary figure showing negative staining TEM (figure S10).

      Line 223 - typo. I think you mean MBD.

      Thanks! Corrected (now line 257).

      Line 215 - the authors observed that the presence of ssDNA reduced membrane clustering and conclude that "nucleic acid binding partially outcompetes membrane tethering activity". Two things: (1) although I agree is it likely that this effect is due to binding of DNA to 2C, binding has not been demonstrated experimentally so the authors should be more careful in how they describe their result; (2) there is no data presented to show that RNA binding reduces membrane tethering so at best I think the conclusion has to be that the data are consistent with the notion that DNA binding reduces membrane tethering. It would of course be interesting to see the effects of RNA and I'm curious to know why the assay was not performed.

      Thanks for the comment. The honest answer is that previous publications (primarily Yeager et al, NAR 2022) convinced us that the outcome should be near-identical with DNA, so we chose DNA oligos because they are cheaper and easier to work with. But we agree with the reviewer that RNA is of course more relevant. We now present a comparison at 5 μM of ssDNA and ssRNA, which in fact shows a slightly stronger effect on membrane clustering by RNA (figure 5C). In the light of this additional experiment, we feel that some of the text changes suggested by the reviewer may no longer be necessary.

      Line 237 - typo: by, not y

      Thanks. In the light of the extensive changes to figure 6 this text was removed.

      Line 284 - the authors claim that 2C may only bind RNA after the N-terminus is liberated from 2B in infected cells, since cleavage of the MBP tag from their construct was needed for 2C to bind RNA in their in vitro assay. However, this does not automatically follow given the large structural differences between MBP and 2B and the fact that the authors have not tested the RNA binding capacity of a 2BC fusion protein. Their claim here is too strong and should be re-written.

      We agree, and have added a discussion along the lines suggested by the reviewer (line 330-332).

      Line 293 - The authors speculate that RNA binding might cause a shift between the membrane clustering activities and the role of the protein in RNA replication. However, since they have not shown that RNA binding reduces membrane clustering, this is too speculative.

      In our revised manuscript we have studied the effect of RNA on membrane binding, thus we feel that this text is relevant in the context of the extended experiments.

      Line 299-317 - within this discussion is the assumption that in their assay system enterovirus 2C adopts the ring-like hexameric structure typical of AAA+ ATPases. While I agree this may well be the case, it has not been demonstrated in this study so the authors should make clear they are making this assumption. The same applies to the legend of Fig 8.

      This part of the discussion was extensively rewritten after our changes to figure 6. We now only refer to "hexamer" once in the corresponding part of the discussion, where we talk about structural models of hexamers produced by other groups who have crystallised fragments of 2C. There we believe we should refer to hexamers to accurately cite their work.

      We are not sure what the reviewer is referring to when it comes to the legend for figure 8: the original legend had no reference to the oligomeric state of 2C. We have substantially changed figure 8 and its legend and the new figure and legend make no references to hexamers/oligomers.

      Line 302 - the authors claim to have shown that 2C is 'selective' for dsRNA. I think at best they have shown a preference for binding dsRNA over ssRNA.

      We changed the wording (line 349). We have also changed the title of the paper where we removed "double-stranded".

      Line 313 - The sentence starting "A recent study..." needs a reference.

      The revised discussion no longer contains this sentence.

      Line 332 - the full sequence of the synthetic gene used in this study should be made available (e.g. as supplementary information or a deposited sequence with an accession number). This is a critical point before the paper can be published.

      We will of course submit the sequences as supplementary data. Thanks for the reminder.

      Line 362 - the authors should describe the likely points of attachment of fluorophores and comment on how this labelling might affect 2C function.

      Thanks for the comment. In response to this and a similar comment from another reviewer, we discuss the likely conjugation site of the fluorophore (lines 175-181), and also (due to the proximity to the Zn finger) provide a new measurement showing that equal amounts of Zn can be detected in the labelled and unlabelled protein (figure S7).

      Line 372 - Is a single protein standard (BSA) sufficient to calibrate the SEC-MALS system?

      Yes, it is the recommended procedure (note that SEC-MALS is only dependent on scattering, not elution volumes etc).

      Reviewer #4 (Significance (Required)):

      As stated above this is an interesting study that presents findings from a novel assay. It will be of interest to picornavirologists and the wider community interested in the mechanisms of AAA+ ATPases.

      We thanks the reviewer for this positive appraisal of our work.

      PeerReviewed
    2. EMBOpress 20 Jun 2024

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

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      Referee #4

      Evidence, reproducibility and clarity

      This is an interesting manuscript that reports the development of an in vitro membrane assay for probing the biochemical functions of the enterovirus 2C protein. The technique is interesting because it can be applied to 2C proteins from other members of the picornavirus family, an important group of mammalian pathogens. It has the capacity to probe different functions (e.g. membrane clustering, ATPase activity, RNA-binding and manipulation activities).

      Overall, the manuscript is well written and gives a clear account of the work undertaken. It adds insight to previous studies of enteroviral (and picornaviral) 2C proteins, providing confirmation of some earlier work in a more physiological context and some new insights, particularly into the membrane and RNA binding aspects of 2C.

      That said, there are a number of places where some amendment of the claims made is required to provide a more precise statement of the findings of this work. These are listed below.

      Line 21 (Abstract) - The authors claim to have shown that a conserved glycine divides the N-terminal membrane-binding domain into 2 helices. I would suggest instead what they have produced are computational predictions that this is the case - some way short of an experimental demonstration. Sequence analysis predicts helical secondary structure in the N-terminus and indeed Alphafold2 also predicts a helical structure, but these predictions require experimental verification. The authors should therefore rewrite sections that claim to have shown the presence of 2 helices. In doing so, they should perhaps also comment on the fact that Alphafold2 does not predict 2 helices in this region for all enteroviruses (see Fig 1D). Moreover, the sequence analysis in Fig. S1 shows the presence of two Lys residues in the segment 17-38; it would be interesting for the reader to have these indicated in the figures showing the Alphafold2 prediction - do they in any way interrupt the hydrophobic face of the predicted helix?

      Line 82 (Introduction) - The authors write that the membrane binding domain (MBD) of poliovirus has been shown to mediate hexamerisation, citing Adams et al (2009) - reference 43. However, that is not what this paper shows. Rather it provides evidence of aggregation of an MBP-2C fusion protein into forms that ranged from tetramer to octamer, but no evidence that these aggregates assume functional forms (e.g. the presumed hexameric ring structure characteristic of the AAA+ ATPase family to which 2C belongs). As far as I am aware the first demonstration of hexameric ring formation by a picornaviral 2C protein was for the 2C of foot-and-mouth disease virus (see Sweeney et al, JBC, 2010). Although this is not an enterovirus, this finding was later confirmed for Echovirus 30 (ref 51). I should declare an interest here: the Sweeney paper is from my lab. I will leave it to the editor and the authors to determine how to write a more precise account of the early observations of hexamerisation in picornaviral and enteroviral 2C proteins. Line 132 - the authors used mass photometry to investigate oligomeric forms of their MBP-2C constructs and state that for the full length 2C protein "the high-mass peak closely corresponds to a hexamer". While it is true that the peak shown in Fig 2C aligns with the expected MW for an MBP-2C hexamer, the peak is very broad, indicative of the presence of other oligomeric states with lower and higher numbers of monomers. This should be commented on. Indeed, the finding seems to echo the early findings of Adams et al (ref 43) with poliovirus MBP-2C.

      Line 143 - for the reasons given above, this summary paragraph represents too strong a statement of what has been observed.

      Line 197 - I note that the authors did not test the membrane clustering capabilities of the 2C(41-329) construct. Although the 2C(deltaAH1) construct had already shown a significant loss of activity, the shorter construct could still have been a useful control. I don't think it is necessary for this experiment to be done, but if the authors have a rationale for not performing the experiment, perhaps they could include it in a revised manuscript.

      Line 223 - typo. I think you mean MBD.

      Line 215 - the authors observed that the presence of ssDNA reduced membrane clustering and conclude that "nucleic acid binding partially outcompetes membrane tethering activity". Two things: (1) although I agree is it likely that this effect is due to binding of DNA to 2C, binding has not been demonstrated experimentally so the authors should be more careful in how they describe their result; (2) there is no data presented to show that RNA binding reduces membrane tethering so at best I think the conclusion has to be that the data are consistent with the notion that DNA binding reduces membrane tethering. It would of course be interesting to see the effects of RNA and I'm curious to know why the assay was not performed.

      Line 237 - typo: by, not y

      Line 284 - the authors claim that 2C may only bind RNA after the N-terminus is liberated from 2B in infected cells, since cleavage of the MBP tag from their construct was needed for 2C to bind RNA in their in vitro assay. However, this does not automatically follow given the large structural differences between MBP and 2B and the fact that the authors have not tested the RNA binding capacity of a 2BC fusion protein. Their claim here is too strong and should be re-written.

      Line 293 - The authors speculate that RNA binding might cause a shift between the membrane clustering activities and the role of the protein in RNA replication. However, since they have not shown that RNA binding reduces membrane clustering, this is too speculative.

      Line 299-317 - within this discussion is the assumption that in their assay system enterovirus 2C adopts the ring-like hexameric structure typical of AAA+ ATPases. While I agree this may well be the case, it has not been demonstrated in this study so the authors should make clear they are making this assumption. The same applies to the legend of Fig 8.

      Line 302 - the authors claim to have shown that 2C is 'selective' for dsRNA. I think at best they have shown a preference for binding dsRNA over ssRNA.

      Line 313 - The sentence starting "A recent study..." needs a reference.

      Line 332 - the full sequence of the synthetic gene used in this study should be made available (e.g. as supplementary information or a deposited sequence with an accession number). This is a critical point before the paper can be published.

      Line 362 - the authors should describe the likely points of attachment of fluorophores and comment on how this labelling might affect 2C function.

      Line 372 - Is a single protein standard (BSA) sufficient to calibrate the SEC-MALS system?

      Significance

      As stated above this is an interesting study that presents findings from a novel assay. It will be of interest to picornavirologists and the wider community interested in the mechanisms of AAA+ ATPases.

      PeerReviewed
    3. EMBOpress 20 Jun 2024

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

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      Referee #3

      Evidence, reproducibility and clarity

      The manuscript provides insights into the role of the N-terminus in membrane binding and its importance in the various functions of 2C.

      Major issues

      Line 103-119. Is this novel? I thought people had done a lot of bioinformatic analysis of PV 2C (especially Wimmer) who also did mutational work to analyse the importance of various amino acids in the N-terminal helix. I feel like the paper in general, and this section in particular, underplays the large body of work that has been done on the amphipathic helix by various groups.

      Line 132. Did you validate your column with known MW standards? The peak for full length and deltaAH1 look fairly standard for 2C, in that you have a mixture of species. Not sure you can say it is a hexamer when it is such a broad peak. C doesn't really help you too much since the counts at 400 (pentamer) and 480 (hexamer) are almost the same with quite large error bars. Like most people that have worked with 2C I think the best you can say is that you are making some kind of oligomerized 2C that includes hexamer, pentamer, etc. Why no dimer for MBP-2C and MBP-2C(delta AH1) when compared to the other constructs?

      Line 143. Does your data show that there are two amphipathic helices? Bioinformatics suggests it but your experiments just show the importance of the two areas in oligomerization, not that it is forming two helices.

      Figure S2. Your preps are still relatively dirty, which isn't ideal for biochemical assays. Especially lane 3, where you are looking at 50-60% purity. I don't want you to re-run experiments but I think you need to comment on the purity of the protein you are working with. Also I don't like that you removed the top and bottom of the SDS-PAGE. How much protein never entered the gel. Is there a big fat band at 20 kDa? You need to have the full gel here. Did you measure 260 nm of the preps as well to see if you had bound RNA to the 2C?

      Lines 170. Wasn't this done in the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles"? I don't see it referenced. What is novel about the current work when compared to that paper? Any differences?

      I'm surprised by the lack of electron microscopy (negative stain mostly) of both the oligomerized 2C and the various liposomes. I know the Carlson group is a microscopy group so why the lack of validation using electron microscopy of the various DLS experiments? I know you did cryo-ET for one of the constructs but I think negative stain electron microscopy of other constructs would be useful.

      Figure 4C. What evidence is there that this is 2C apart from you added it to the liposomes? It also comes back to the relative impurity of your protein prep. Could this be E.coli contamination?

      Figure 8. Is this model supported by the data in this paper? Your cryo-ET says that 2C is there but that isn't supported by any other data. How is the dsRNA protected from the innate immune system in this model? is it just sat out in the cytosol? How is the nascent ssRNA packeged into the capsid? Is there competition between the dsRNA and capsid for 2C binding (which your model suggests)? I know it sounds like I am being overly critical of the model but in my opinion there are still too many unanswered questions in the field to come up with a half decent model.

      Minor issues

      Lines 43-45: I feel like you underplay the success of the poliovirus vaccination program. Approximately 30 of WPV1 in 2022 and the full eradication of WPV2 and 3. Vaccine derived polio is still an issue but even that is relatively low compared to where the world was in the 1950s.

      Line 66. I agree there are 11 individual proteins but I feel like this leaves out the fact that some of the uncleaved precursors appear to have some functions, for example 2BC.

      Line 56: LD needs to be defined.

      Line 75. I think you have misrepresented Xia et al here. They clearly say that in their study that they show helicase and chaperone activity. I never managed to repeat that work but you should still report what they claim. One major thing is that they used insect expressed protein, whereas most people (including myself and in the paper under review) use E.coli expressed protein. Do post translational modifications play an important role in function?

      Line 103. Need to make it clear here it is poliovirus 2C.

      Line 135. I assume you mean kDa instead of uM?

      Figure 3. What do you mean by "Only 2C"? Is that MBP-2C? Maybe I am reading the data wrong but adding TEV does nothing? How do you know TEV is removing the MBP? It looks like MBP-2C binds to the liposomes just the same as cleaved MBP-2C. I see in line 165 you acknowledge this. Could an alternative conclusion for line 168 be that MBP isn't being cleaved off but that AH2 is too small to be exposed in that construct? Did you do that construct without MBP being cleaved? I think you need to confirm that MBP is being cleaved off.

      Line 184. Is there a reason you use the 2019 paper as a reference instead of the far earlier Bienz et al papers? I'd suggest they are the seminal papers on 2C membrane association. Once again how is this work different from the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles" paper?

      Figure 5D. So only 1-3% of RNA is found in the upper fraction? Is that significant enough to say that dsRNA was recruited significantly more than ssRNA? How confident are you in your quantification of the starting amounts of RNA?

      Line 223. Any idea why the MBP needs to be cleaved off? Clearly the MDB is accessible or it would not bind to the liposomes.

      Line 237: missing "b" in "by"

      Figure 6. I don't fully understand the results here. Earlier you showed that the delta MBD didn't really bind SUV. So presumably it isn't really membrane bound. Why does it have similar activity to full-length MBP in your helicase assay if membrane is important? Did you do SUV and TEV protease only control?

      Line 257: "staring"?

      Line 336. Need to change the u to mu.

      Any discussion on your observation in Figure 1D that EV71 and CVB3 don't appear to have AH1 and AH2 or do you think that the domains are conserved across the different viruses?

      Table 1 (and possibly elsewhere): an apostrophe is not the prime symbol. 5' compared to 5′.

      Line 702 "and" should be "an".

      I couldn't open one of the movies (140844_0_supp_2820374_a2g272.avi).

      Significance

      Overall I liked the paper and is worth publishing. One of the issues in the 2C field is the difficulty in making pure 2C and carrying out in vitro assays that correlate with what is observed in the natural infection. I think this paper suffers from similar struggles with a 2C preparation that doesn't appear that pure. I think it also suffers from not having 2C from a wild-type infection. I don't think that it is feasible to get that kind of 2C but by once again using a recombinant protein from E.coli we are left with another manuscript that provides conflicting evidence of the functions of 2C without a definitive answer. The experiments are well done, although are missing some controls and the manuscript is laid out in a logical manner and is relatively easy to follow.

      PeerReviewed
    4. EMBOpress 20 Jun 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      The authors present an alternative assay system to investigate picornavirus 2C, a protein that is tricky to analyze biochemically in its full length form because of an amphipathic helix at the N-terminus. Poliovirus 2C is expressed with an N-terminal MBP tag, a 50kD protein that helps with solubility as is commonly used for 2C investigations. A difference here is that liposomes are included to mimic membranes for 2C attachment. The key findings are that 2C induces clustering of of liposomes, that double stranded RNA binding by 2C impacts this clustering effect and that a free N-terminus (after cleavage of MBP by TEV protease) is needed for RNA binding and an ATP independent (ie non helicase) RNA duplex separation activity.

      Major:

      In the floatation assays in figure 3 the authors use a system where MBP-2C is fluorophore-labeled with ATTO488 on exposed cysteines. Poliovirus and other enterovirus 2C has a very well characterized zinc finger domain that has cysteines coordinating a zinc ion. Mutation experiments previously showed that these cysteines are necessary for viral replication and 2C stability. Have the authors controlled for disruption of the zinc finger domain by the labelling of cysteines with ATT0488 and checked if the protein remains folded?

      In the analysis of the amphipathic helix, did the authors include membranes in their structural predictions o just the free helix? How does inclusion of membranes impact the predictions? In the predictions in Figure D, only 2 of 4 show a kink and there doesn't seem to be a correlation between those that predict a kink or not and whether the hydrophobic side is aligned in Figure S1.

      Based on previous structures of 2C from different viruses the N-terminal amphipathic helix containing region is predicted to localize on one face of the predicted hexametric structure tethering 2C to the membrane. How does the authors hypothesized model explain 2C dependent clustering? is there evidence that 2C hexamers can oligomerize further into dodecamers for example, maintaining separate faces to enable N-terminal interaction with different membranes? What is the distance between the liposomes in figure 4 at the points of density attributed to 2C? How does this compare to the size of 2C determined in previous structural studies? Is it consistent with one hexamer/2 hexamers sitting on top of one another?

      In the Discussion lines 278-285 the authors suggest that having MBP attached may reflect the polyprotein condition. Can they make a construct with MBP-2B2C to examine interaction with liposomes and assess 2C function?

      Discussion lines 293-296, the possibility of two different populations of 2C, binding RNA or membranes cannot be excluded, there is much more 2C around late in infection that present in early infection- the model in figure 8 doesn't acknowledge/capture this.

      Discussion lines 313-317, the authors don't reference a study where a mutant of foot-and-mouth disease virus 2C lacking the n-terminal amphipathic helix that could bind but not hydrolyze ATP, hexamerized in the presence of RNA that seems pertinent here (PMID: 20507978).

      Some evidence of MBP-2C cleavage by TEV in the different assays used should be presented as this is a major focus of discussion and currently no gels show TEV cleavage is happening.

      Significance

      The work presents an additional methodology to investigate a a protein that has previously been difficult to study. The authors acknowledge that there is still a lot of 2C biology that remains to be discovered.

      PeerReviewed
    5. EMBOpress 20 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      In this study by Shankar and colleagues, the authors aim to understand the structure and function of the enterovirus 2C protein, a putative viral helicase with AAA+ ATPase activity. Using poliovirus (as a model enterovirus) 2C, the author's propose the protein contains two amphipathic helices (AH1 and AH2) at the N-terminus that are divided by a conserved glycine. Using purified MBP-tagged 2C and N-terminal 2C truncations, their data suggests AH1 is primarily responsible for clustering at membranes, whilst AH2 is the main mediator of 2C oligmerisation and membrane binding. Furthermore, 2C was suggested to be able to recruit RNA to membranes, with a preference for dsRNA, and the author's data implies that the helicase activity of 2C is ATP-independent. Instead, the ATP activity appears to be required for 2C hexamer formation or chaperone activity. The manuscript is generally well written /presented and the author's present very interesting data which raises several questions, some of which require additional experimentation to help support the author's conclusions. Specific comments are as follows.

      Major Comments:

      1. The authors use four main constructs throughout the paper: full-length 2C, 2C with deletion of AH1 (ΔAH1), 2C with both AH1 and AH2 deleted (ΔMBP) and 2C with an extended N-terminal deletion. From this, the author's draw conclusions on the function of both AH1 and AH2. One of the author's main conclusions is that AH2 is the main mediator of 2C membrane association (e.g., in line 169). However, is it possible to conclude the relative importance of AH1 vs AH2 without testing a construct containing the deletion of AH2 only (ΔAH2)? This should be generated and used alongside this data to fully define the relative importance of AH1 and AH2 in these assay and remove the possibility that the deletion of AH1 changes the structure and/or function of AH2, which could also result in the observed differences.
      2. Previous structural predictions of 2C do not appear to have two separate AHs at the N-terminus. Are the AH1 and AH2 structures predicted to be formed in the context of the entire 2C protein, 2BC precursors and polyprotein? Are there structural approaches that could provide experimental evidence for two separate AH at the N-terminus?
      3. Why are the 2C dimers (lines 137-138) not apparent on the mass photometry data presented (figure 2)?
      4. It appeared that binding of ΔMBD-2C was better when POPS is in the membrane (line 174). What is the explanation for this and was this finding significant?
      5. From the author's data on lipid drop clustering they conclude ΔAH1 is more effective for clustering, however, the ΔAH1 construct produces pentamers not hexamers (from Figure 2). Is formation of hexamers related to or required for membrane clustering?
      6. The replicon data presented in Figure 7 should include a replication-defective control (e.g., polymerase mutant), in order to compare how defective in replication ΔAH1 and ΔMBP deletions are compared to a fully-defective construct. Likewise, deletion of ΔAH1 in this construct is likely to affect processing of the viral polyprotein where several previous studies with picornaviruses have demonstrated that the residues in the P2'-P4' positions can change cleavage efficiency (e.g., PMID: 2542331), or the structure of 2C, leading to the reduction of replication.
      7. How does the author's model of ATPase-independent helicase activity and an APT-dependent required RNA chaperone activity fit with 2 step model for RNA binding and ATPase activity suggested by Yeager et al (PMID: 36399514)? Optional major comments that would increase the significance of the work:
      8. The preference for dsRNA over ssRNA appears to be quite small (Figure 5d). In the context of a viral infection where ssRNA is likely to outnumber dsRNA at different times during infection is this preference physiologically relevant? In relation to this, what size stretch of dsRNA is required for preference, and could this correspond to cis-acting RNA structural elements, dsRNA as it escapes 3D polymerase or as part of the RF and RI forms (PMID: 9343205)? What is the proposed mechanism of how dsRNA outcompetes membrane tethering of 2C? OPTIONAL
      9. The author's study has been conducted in the absence of other viral non-structural proteins. What is the physiological importance of the observations, such as membrane interaction/clustering or RNA binding when presented in the context of the other replication machinery. OPTIONAL
      10. Do 2C monomers, dimers and hexamers have different functions in viral replication perhaps at different stages of replication and which of these forms are relevant during viral infection or can they all be detected during infection? Can any suggested separate functional arrangements be separated by genetic complementation experiments? OPTIONAL

      Minor comments:

      1. The author's appear to interchange between naming/nomenclature of the constructs which makes it confusing to follow (for example, ΔMBD is the same as 2C(41-329) likewise, 2C(Δ115) is sometimes called 2C(116-329)). It would be much easier to follow if the naming of constructs was consistent throughout (unless I am misunderstanding some subtlety in the difference between such constructs).
      2. The author's suggest a pentamer arrangement for the ΔAH1 construct, however in the mass photometry data (figure 2D), a hexamer is indicated with the arrow. It would be helpful to change the label to indicate the size of the pentamer where this is being generated, not the hexamer.
      3. In most figures, data for full-length 2C, ΔAH1 and ΔMBP is shown. However data for ΔMBP is missing in Figure 4. Using ΔMBP may demonstrate even lower clustering, hinting that AH2 is also involved in this process.
      4. I think it would be better for normalise the data in the flotation experiments such that the percentage of 2C in the upper faction is presented as relative to the amount of lipid in the upper fraction (presented in Figure S4).
      5. At several places (e.g., lines 232 and 272) the author's refer to "realistic systems". I think the term "physiologically relevant" might be more appropriate.
      6. Line 237: I think "y" is a typo and should read "by".

      Significance

      I have limited expertise with structural biology but specialise my research on positive-sense RNA virus replication, structure and function. This research is of interest to a broad audience of researchers investigating many positive-sense RNA viruses, which extends beyond the viral family studied here. The work utilises novel techniques to begin to understand the specific roles of 2C in poliovirus replication. The author's data add important incremental new insight into recent studies on viral helicase proteins as referenced in the study, however, a key limitation is understanding the importance/relevance of their observations during a viral infection.

      PeerReviewed
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    biorxiv.org/content/10.1101/2023.10.11.561830v3
  38. www.biorxiv.org www.biorxiv.org
    Global Release of Translational Repression Across Plasmodium’s Host-to-Vector Transmission Event
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    1. EMBOpress 20 Jun 2024

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      Reply to the reviewers

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

      This manuscript provides a detailed analysis of RNA and protein dynamics during transmission of the rodent malaria model P. yoelii from the mouse host to an in vitro ookinete culture setting (mimicking the mosquito midgut environment). This group and others have shown experimentally that a substantial number of mRNAs is stored in the female Plasmodium gametocyte, ready to be translated following initiation of ookinete development. The process is akin to maternal deposition of mRNA in oocytes of metazoans. With this manuscript the authors provide a significant contribution to the field of translational control in Plasmodium parasites as they explore the translational activation during the early hours of zygote-to-ookinete development. The paper presents RNAseq and mass-spec analyses of female gametocytes and for the first time for 6-hour zygotes (ie a fertilized female gamete); the zygote datasets are much improved and more comprehensive than the only other performed in 2008 in P. gallinaceum. Using comparative analyses of transcriptome and proteome data (including published datasets) the authors arrive at a list of 198 transcripts that are translationally repressed in the gametocyte and translated within 6 hours of fertilization in the zygote. Many of these mRNAs are known to be involved in zygote to ookinete transformation. BioID is finally used to explore changes in mRNP protein composition between the female gametocyte and the zygote.

      The paper is generally well written. The authors present a lot of data (also in comparison with published data). Sometimes perhaps the main message could be simplified / streamlined in section titles (Quantitative Proteomics by DIA-MS is not very informative. The outcome of the analysis would be more telling).

      Response: We have revised section headers to clarify the content.

      A considerable proportion of the DIA mass-spec proteomics results section is very technical. The paper describes a biological phenomenon rather than a technical mass-spec advance. Can these technical details be moved to the methods section?

      Response: As this is one of the first published instances of using DIA-MS to Plasmodium, we want to keep this information in the main text to help our community adopt these approaches. While these details are highly technical, they are also some of the major advances of this project.

      On the other hand, a bit more detail could be provided in the main text. For example, the age of the zygotes is never mentioned. This is important, please add this. The main manuscript text has 16 mentions of the word "many". As the authors are in possession of the data, please provide, if missing, (in parenthesis) the absolute numbers, maybe in an "x out y" format. Please clearly state the number of biological and/or technical replicates used for transcriptome and proteome analyses in the main text, figures and/or figure legends. How many protein coding genes are encoded in the P. yoelii genome?

      Response: Several of these requested details are noted in the materials and methods. We have added this information to the main manuscript now as well. We have also revised the manuscript to replace some instances of “many” with specific numbers unless it adversely impacted the flow of the sentence to do so.

      The authors claim that only zygotes (fertilized females) have surface-exposed Pys25 (a surface protein they use to affinity-purify zygotes) but not gametocytes. I could not find the experimental data for this in the paper. The cited reference #22 also does not appear to show this. In Figure 2C Pys25 is shown to be translated in gametocytes. In this context it may be important to note that in the related P. berghei the related protein P28 is expressed even in the absence of fertilization (Billker 2004; DOI: 10.1016/s0092-8674(04)00449-0). It may not be relevant whether translation requires fertilization, but the authors claim it affects trafficking of the Pys25 protein to the surface, so it needs to be shown. A reference to an infertile P. yoelii line would be great.

      Response: We have corrected the reference supporting the surface exposure of p25 on zygotes. The observation by Billker and colleagues about Pbs28 is also of interest, but outside of the scope of this study as we did not investigate the fertilization event itself here.

      It is highly commendable that all data is provided throughout the manuscript. For readability, may I suggest that the authors add labels to individual sheets within an excel file from A to Z, and do so also within the manuscript. That would really help; the most relevant data sets could then be identified quickly. For example, line 184 refers to 276 zygote proteins in which sheet of which table?

      Response: While this labeling system would also be effective, we have provided a README tab for our files that quickly directs the reader to the relevant tab (as we do for our previous publications).

      Section 176 onwards: here the authors combine P. falciparum and P. yoelii proteomics data. Please explain why you excluded any of the available P. berghei proteome data such as the male and female gametocyte proteome? The same question applies to 294 onwards.

      Response*: We compared our datasets with those of Lasonder et al. NAR 2016 because that study was also focused on translational repression of mRNAs and provided both RNA-seq and proteomic datasets of female gametocytes (although not of zygotes). *

      The comparative transcriptome-proteome analysis arrives at 198 translationally repressed mRNAs. Could the authors provide one or two alternatives using less stringent parameters? The list in P. falciparum and P. berghei is considerably larger (500+ and 700+).

      Response: We could have reduced the stringency of our thresholds to arrive at a far larger number, but prefer to retain higher confidence in those we are scoring as translationally repressed and then released for translation. We provide all of the pertinent data in the supplemental files if readers would like to adjust these thresholds to see which additional mRNAs may also be regulated.

      The turboID data is informative but somewhat speculative in regard to spatial rearrangements within these mRNPs. Figure 6 presents the RNA helicase to bind the 5' end of mRNAs that are associated with polyribosomes and I assume being translated. Is this association realistic? The RNA helicase DOZI homolog of yeast (Dhh1) is also involved in decapping. Response: We provide Figure 6 as our working model of how the reorganization of the DOZI/CITH/ALBA complex could occur based on available data from this study and others. Future studies are warranted to determine if DOZI remains associated with monosomes vs. polysomes, but current data indicate that DOZI can bind to eIF4E when translational repression is not imposed.

      Specific comments:

      title Is global the appropriate word? Some transcripts appear to be translated later.

      Response: We believe it does apply appropriately to these data.

      Line 30/32 Please re-phrase the sentence. There is: Cell Host Microbe 2012 Jul 19;12(1):9-19. doi: 10.1016/j.chom.2012.05.014.

      Response: We conclude that the sentence is correct as written, even in considering Sebastian et al. Cell Host & Microbe 2012.

      30 Perhaps add ookinete that establishes infection rather than the zygote. For a general readership, a brief description of the sexual life cycle might be useful

      Response: It is not possible to get into these nuances in the Abstract. This information is covered in the main text and the works that are cited.

      32 DOZI/CITH/ALBA complex would require some explanation for a more general reader

      Response: It is not possible to get into these nuances in the Abstract. This information is covered in the main text and the works that are cited.

      36-37 I believe zygotes were collected 6 hours after fertilization. Does that qualify as soon after fertilization? Motile ookinetes are generated within 20 hours and motility can be seen before that.

      Response: Yes, we think this qualifies as the process is not synchronous, but relies on when male gametes encounter and fuse with female gametes.

      37 Essential functions for what?

      Response: It is not possible to get into these nuances in the Abstract. This information is covered in the main text and the works that are cited.

      39 Is the spatial arrangement of this mRNP known?

      Response*: Some interactions of members of this complex were known (DOZI with eIF4E, ALBA4 with PABP1), but not the overall spatial arrangement. These findings are novel to this study. *

      40 Can you briefly allude to the "recent, paradigm-shifting models of translational control"

      Response: It is not possible to get into these nuances in the Abstract. This information is covered in the main text and the works that are cited.

      44 Products = mRNA

      Response: We have stated it as products because the maternal cell provides more than just mRNAs that are essential to further development post-fertilization.

      45 Oocyte in metazoans ?

      Response: Yes, this is the correct term. The context here is in higher eukaryotes.

      60/62 Please re-phrase the sentence. There is: Cell Host Microbe 2012 Jul 19;12(1):9-19. doi: 10.1016/j.chom.2012.05.014.

      Response: We conclude that the sentence is correct as written, even in considering Sebastian et al. Cell Host & Microbe 2012.

      81 PbDozi Plasmodium berghei DOZI

      Response: We have added this clarifying text here as suggested.

      84/85 Please rephrase and cite Nucleic Acids Res. 2008 Mar;36(4):1176-86. doi: 10.1093/nar/gkm1142. Epub 2007 Dec 23. and Cell Host Microbe 2012 Jul 19;12(1):9-19. doi: 10.1016/j.chom.2012.05.014.

      Response: As noted above for other comments, we hold that the current phrasing is accurate even when considering these important publications.

      88 Please define the timepoints throughout this manuscript. What age are the zygotes? How many hours post-induction? Please define the time for ookinete development somewhere in the introduction

      Response: The timepoint used for zygote collection is now included in the main text in addition to its previous inclusion in the Materials and Methods section. As we have not studied the ookinete stage here, we have opted to keep the introduction focused on the key details for this study.

      104 Please add the age (in hours) of these zygotes from the time of starting the in vitro cultures. From the methods section it looks like 6 hours.

      Response: The timepoint used for zygote collection is now included in the main text in addition to its previous inclusion in the Materials and Methods section.

      103/105 I can find no evidence for P25 (Pys25) expression relying on fertilization in the cited paper (22). The SOM has no reference to Pys25 either. Please show data or reference published data that there is no translation and trafficking of Pys25 in unfertilized female gametes, ie those that are placed in ookinete medium. In this respect it may be important to note that unfertilized Plasmodium berghei females placed in ookinete medium translate P28, the P25 paralog (https://www.sciencedirect.com/science/article/pii/S0092867404004490?via%3Dihub)

      Response: We have corrected the reference supporting the surface exposure of p25 on zygotes. The observation by Billker and colleagues about Pbs28 is also of interest, but outside of the scope of this study as we did not investigate the fertilization event itself here.

      104 What cell line was used for the zygotes?

      Response*: The PyApiAP2-O::GFP transgenic parasite line was used here. These details are included in the manuscript and supporting information. *

      114 The number of transcripts detected in gametocytes is quite small compared to the twice as large proteomics dataset. See for example also Lasonder 2016 for P. falciparum detected transcripts: 4477 different sense transcripts were identified, 98% of which were shared between MG and FG.

      Response: Yes, the number of mRNAs or proteins scored as detected differs based on thresholds applied. We prefer to err on the side of higher stringency as noted above.

      117 Does the 194 up-in-gametocytes dataset include the 81 not found in zygotes?

      Response: No, these 194 are detected in both datasets, but are more abundant in gametocytes than zygotes.

      117 Could you indicate some of the genes in the plot?

      Response: Several hits of special note are described in the text. We have opted to keep the figure clear and streamlined.

      Fig1 How were the upregulated transcripts identified? 1647 are shown to be specific to zygotes in 1B, yet only 685 are shown in 1C to be upregulated. Do the transcripts found exclusively in zygotes not count? Are these transcripts likely the result of de novo transcription? How old are these zygotes when the libraries are made?

      Response: The details of the RNA-seq processing are provided in the MakeFile, the supplementary tables, and the manuscript. The README tab provides descriptions of what processing occurred between sequential tabs. As noted above, zygotes were collected at 6 hours.

      132 Many? How many? Please provide a precise number.

      Response: These details are now in the revised manuscript.

      134 Please explain why p28 would be differentially abundant in the zygote rather than the female gametocyte. That would require de novo transcription of this gene. If there is experimental evidence for the de novo transcription of p28 and other translationally repressed transcripts in the zygote please cite the references. Can you name a few more examples here? P25 for example, ap2-o, or anything published and experimentally validated. What about AP2-o and AP2-Z? Both are known to be translationally repressed.

      Response: We state in the original manuscript that there is not a significantly different mRNA abundance of pys28.

      139 Please define how many members of the IMC?

      Response*: We have now replaced “many” with the number of IMC members we have detected, which is also shown in supporting tables. *

      156 Can you provide a number of how many parasites were used in total or per run. And how many biological and technical replicates were analysed?

      Response: These details are provided in the Materials and Methods.

      169 The number of proteins detected in the gametocyte sample is twice the size of transcripts. IS this to be expected?

      Response*: This reflects the sensitivity of the assays run for transcriptomics and proteomics. *

      170 How many samples were analyzed? One gametocyte and one zygote sample?

      Response: Yes, for the creation of the DIA-MS spectral library, a single biological replicate was used in addition to in silico library approaches. This information is provided in the next sentence.

      176 Why did you not include P. berghei in the meta-analysis?

      Response: We compared these results to all of the published Plasmodium proteomes in PlasmoDB.

      184 Please refer to an excel table here.

      Response: We have pointed to the relevant supporting files in this section.

      184 145 proteins: do you mean orthologs in general or orthologs with a gene/protein annotation other than unknown function?

      Response: We use the standard form of ortholog throughout the manuscript.

      190 142 proteins: do they all have orthologs in P. falciparum?

      Response: No, not all proteins in our dataset have unambiguous orthologues in P. falciparum, and this is accounted for in our data processing approaches.

      Figure 2C P25 is not exclusive to zygotes here and also found in the gametocyte sample.

      Response: That is correct. It is known that p25 is expressed in female gametocytes, but that the localization changes in the zygote.

      190 shortlist

      Response: The spelling of “short list” as two words is an appropriate American spelling of this term.

      219 onwards Does the list of 198 transcripts exclusively arise from your RNAseq and proteomics comparison? Or does it include falciparum data as outline in section 176 onwards, ie the list of 276 proteins that only are detected in zygotes?

      Response: Yes, this list of 198 mRNAs is derived from our datasets only using our defined thresholds. The details of this are provided in the manuscript.

      224 Early zygote? At 6 hours do the parasites not start to transform, elongate?

      Response: This process is not synchronous, as it is affected by the timing of gamete fusion.

      225 >5-fold. Is this an arbitrary decision?

      Response: This threshold has been used by our group and others in prior studies, and was partially informed by the behavior of previously characterized transcripts.

      227 1417 mRNAs: they are from which dataset?

      Response: These are from our datasets with P. yoelii, as described in the manuscript.

      228/229 Please explain why DOZI and CITH are in the list of 198 repressed transcripts? They are present in the gametocyte. Are they upregulated>5 fold?

      Response: Yes, they meet our criteria for this regulation, and in the manuscript we note that we believe that they are self-regulated and likely have continuing roles in early mosquito stage development.

      259 ... as they are already translated in the gametocyte?

      Response: Yes. Translational repression allows for the existence of some of the protein in the initial timepoint. This differs from translational silencing which does not.

      295 Is this from the 198 TR list S4?

      Response: No. Transcripts that remain repressed would not be in the list of 198, as the protein was not detected in zygotes.

      294 onwards How many putatively falciparum transcripts are there? How many were identified in P. berghei? How many are common to all? A Venn diagram perhaps to compare the different studies

      Response: There is substantial overlap between the species with respect to the presence of syntenic orthologues in this dataset. However, because we did not conduct experiments with P. falciparum or P. berghei here, we do not want to make claims that they are similarly regulated or potentially have a reader misinterpret a figure to that effect.

      301 How many transcripts were found associated with Plasmodium berghei DOZI and/or CITH in female gametocytes? How many of those were abundantly detected as protein in zygotes, or had no difference in protein abundance between gametocytes and zygotes, or even greater abundance in female gametocytes?

      Response: These details are now provided in the revised manuscript.

      303/305 Please indicate the numbers of translationally repressed transcripts identified for P. falciparum and berghei.

      Response: These data are provided in Supporting Information Table 4.

      317/319 Please add the promoter used for tid-GFP

      Response: We have now added this information to the Materials and Methods.

      320 Please elaborate on the spatial organization of the DCA complex.

      Response: This has not been previously characterized, and this entire section is dedicated to the experimental data and interpretations of how the DOZI/CITH/ALBA complex may be organized.

      321/322 Have precise binding sites of DOZI and ALBA4 really been shown experimentally in the cited papers? In relation to 5' and 3' ends of the mRNA? Please cite Braks et al. paper.

      Response: Yes. The association of DOZI with eIF4E and ALBA4 with PABP1 are established in the literature, in some cases by multiple independent laboratories. The Braks publication does not address the binding of these proteins, and thus is not cited.

      323 What is the first generation BioID enzyme? BirA*

      Response: Yes. The first generation enzyme is called BirA*

      323 Please cite relevant Kyle Roux and Alice Ting for the original enzymes

      Response: We have now added these citations to this sentence.

      327 Could you show images of ALBA4::TurboID::GFP, DOZI::TurboID::GFP and cytosolic (free) TurboID? Perhaps stained with fluorescently labelled streptavidin and / or against GFP? In the gametocyte and zygote samples?

      Response: We attempted to stain with monoclonal antibodies that are reactive against biotin and there was insufficient specificity, hence why such data is not included. We conclude that all of the other data that supports this approach suffices to demonstrate its rigor.

      331 What is the age of these zygotes? Where they affinity purified?

      Response: As throughout the manuscript, zygotes were collected at 6 hours. Details of experimental purifications are provided in the materials and methods.

      Fig S4 Please indicate whether ALBA4 and DOZI were tagged endogenously

      Response: Yes. The endogenous loci for both ALBA4 and DOZI were modified to include the C-terminal TurboID and GFP tags.

      421/430 Please add a few references here

      Response: We do not believe that specific references are warranted for these general statements.

      429 translational repression?

      Response: Yes. These statements set the stage for the use of translational repression.

      445 966 proteins in gallinaceum? The zygote cultures in that study were 2-3 hours. How old were the cultures in your study?

      Response: As throughout the manuscript, zygotes were collected at 6 hours.

      481 Please explain / cite why repression is energetically costly.

      Response: These details are provided in both the introduction and discussion sections. The energetic cost of translational repression is both the cost to produce the transcripts without immediately/fully utilizing it for translation, in addition to the energetic cost to impose the regulation.

      501 Please add the time-point of RNA and protein sampling. How many hours into ookinete development? What is the time from cardiac puncture through FACS sampling of gametocytes.

      Response: We have provided all of these details in the materials and methods for female gametocytes and zygotes. We did not look at ookinetes in this study.

      711/713 Do you have any images that show the successful purification of zygotes away from gametocytes? Secondly, please provide a reference for the statement that unfertilized female gametocyte do not express surface exposed Pys25.

      Response*: We do not have captured images of these zygotes, but confirmed them during collection using microscopy. The reference for surface exposure of Pbs25 is now provided earlier in the manuscript as well. *

      711/716 Were parasites lysed and mechanically homogenised?

      Response: We have provided all of these details in the materials and methods for female gametocytes and zygotes.

      Figure 6 What is the evidence that DOZI stays associated with mRNA that is being translated? Rather than mRNA that is being decapped. Please add the references that unequivocally show that DOZI and ALBA4 bind to opposite ends of repressed mRNAs.

      Response: This is our working model of these data. It is feasible that these complexes could form off of mRNA as well. Publications describing the interactions of DOZI with eIF4E and ALBA4 with PABP1 are provided in the manuscript. It is well established that eIF4E binds to the m7G cap of the 5’ end of mRNAs, and PABP1 binds to the poly(A) tail at the 3’ end of mRNAs.

      Reviewer #1 (Significance (Required)):

      The experiments in the manuscript are carefully conducted. Apart from a P. gallinaceum study from 2009 this is the first comprehensive analysis of the transcriptome and proteome of a Plasmodium zygote (developing ookinete) at 6 hours post-fertilization. The data are used to explore the temporal aspect of activation of translation during the first quarter of the 20-24 hour ookinete developmental period. The study will be of interest to the field, specifically those scientists working to understand translational control, ookinete development, and those developing intervention strategies to prevent mosquito infection and thus malaria transmission.

      Response: We appreciate Reviewer 1’s extensive feedback and positive remarks about the significance of our study. We have revised our manuscript to reflect this constructive feedback.

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

      Main findings

      Taking a multi-omic approach, the authors provide quantitative evidence for translation repression of ~200 mRNAs in Plasmodium yoelii female gametocytes. These mRNAs are then translated, and proteins detected by 6 hours after activating gametocytes. They accomplish this by performing a comparative global analysis of the transcriptome and proteome between female gametocytes and early zygotes that provides an intresting resource. The authors also use proximity labelling of the DOZI/CITH/ALBA4 repression complex, and these data suggest the complex may disassemble in the zygote or change its composition.

      Major points

      Line 181-184: The authors state that there is no evidence of how the DCA complex selects specific mRNAs for translation repression. While the exact mechanisms have not been fully elucidated, Braks et al (2008, doi:10.1093/nar/gkm1142) suggested a role of the untranslated regions (UTRs) in translation repression of transcripts in Plasmodium berghei female gametocytes. They identified a uridine-rich 47-base element in the 5'UTR and or 3'UTR that was associated with translationally repressed transcripts and validated it experimentally. Considering this finding, I would recommend an amendment of the statement and to include the earlier work. I would also like to see additional analysis to check if this U-rich motif or other motifs are associated with the translationally repressed transcripts identified in the current study. The current study should be better powered to conduct such an analysis.

      Response: We have now added a comment and citation in the revised text about this study in Lines 86-88. Understanding the full importance of this element is challenging, as the Plasmodium transcriptome is highly enriched in A’s and U’s due to the highly skewed A/T content of its genome. Perhaps for this reason, we did not see an association of this motif with the identified mRNAs.

      The authors used zygotes that expressed GFP tagged AP2-O, however, there is no explanation of the significance of using this line.

      Response: This line is described in the Materials and Methods and supporting information. It was used to provide further validation of the production of zygotes.

      Minor points

      In line 106-107, the authors refer to figure SI, this figure is about genomic locus and genotyping PCR for the PyApiAP2-O::GFP parasites but there is no intext description of why this specific line was used.

      Response: We have provided this information in the revised manuscript.

      Statement in line 122-124 "It is likely that....." should go into the discussion not results.

      Response: We have placed this single sentence immediately after presenting these data here to aid reader comprehension.

      Statement in line 171-175: "In addition to providing confirmatory...." Should be in the discussion not on the results.

      Response: We view this sentence as a concluding remark of this section of data that also places this information in context for the reader.

      In Fig. 4 A and B, could the colour scheme be changed so that the proteins that are not in both samples (and probably contain many unspecifically detected proteins) appear less prominent?

      Response: We appreciate this suggestion and have adjusted these plots accordingly in the revised manuscript.

      Reviewer #3 (Significance (Required)):

      Why is the paper interesting. Translation repression of mRNA at a global level in the female gametocytes has been studied previously in rodent malaria parasites investigated, but prior to the current study, the release of mRNA from translation repression in the mosquito stages has only been demonstrated for specific transcripts. By characterizing and quantitating changes in protein abundance between macrogamete and zygote, coupled with transcriptomic analysis, the current work broadens our understanding of zygotic translation activation that is key to successful malaria parasite transmission to the mosquito.

      This dataset provides a useful resource for the Plasmodium research community as it provides a more comprehensive view of how transcripts behave during the transitions from the mammalian host to the vector. It is one step in a broader endeavour towards finding genes crucial for parasite transmission that could be targeted for interventions.

      How translational repression and derepression is regulated remains unknown, although some of the molecular players have been identified. This paper shows proximity labelling and expansion microscopy data of the ribonuclear protein complex thought to mediate repression. Although the specific mechanistic insights provided by the experiments shown here remain relatively limited, the work demonstrates interesting new avenues for how translational derepression in Plasmodium can be studied.

      Response: We also appreciate Reviewer 3’s excellent feedback and positive remarks about the significance of our study. The revised manuscript addresses these comments, and we believe it is further strengthened because of it.

      PeerReviewed
    2. EMBOpress 20 Jun 2024

      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 #2

      Evidence, reproducibility and clarity

      Main findings

      Taking a multi-omic approach, the authors provide quantitative evidence for translation repression of ~200 mRNAs in Plasmodium yoelii female gametocytes. These mRNAs are then translated, and proteins detected by 6 hours after activating gametocytes. They accomplish this by performing a comparative global analysis of the transcriptome and proteome between female gametocytes and early zygotes that provides an intresting resource. The authors also use proximity labelling of the DOZI/CITH/ALBA4 repression complex, and these data suggest the complex may disassemble in the zygote or change its composition.

      Major points

      1. Line 181-184: The authors state that there is no evidence of how the DCA complex selects specific mRNAs for translation repression. While the exact mechanisms have not been fully elucidated, Braks et al (2008, doi:10.1093/nar/gkm1142) suggested a role of the untranslated regions (UTRs) in translation repression of transcripts in Plasmodium berghei female gametocytes. They identified a uridine-rich 47-base element in the 5'UTR and or 3'UTR that was associated with translationally repressed transcripts and validated it experimentally. Considering this finding, I would recommend an amendment of the statement and to include the earlier work. I would also like to see additional analysis to check if this U-rich motif or other motifs are associated with the translationally repressed transcripts identified in the current study. The current study should be better powered to conduct such an analysis.
      2. The authors used zygotes that expressed GFP tagged AP2-O, however, there is no explanation of the significance of using this line.

      Minor points

      In line 106-107, the authors refer to figure SI, this figure is about genomic locus and genotyping PCR for the PyApiAP2-O::GFP parasites but there is no intext description of why this specific line was used.<br /> Statement in line 122-124 "It is likely that....." should go into the discussion not results. Statement in line 171-175: "In addition to providing confirmatory...." Should be in the discussion not on the results. In Fig. 4 A and B, could the colour scheme be changed so that the proteins that are not in both samples (and probably contain many unspecifically detected proteins) appear less prominent?

      Significance

      Why is the paper interesting.

      Translation repression of mRNA at a global level in the female gametocytes has been studied previously in rodent malaria parasites investigated, but prior to the current study, the release of mRNA from translation repression in the mosquito stages has only been demonstrated for specific transcripts. By characterizing and quantitating changes in protein abundance between macrogamete and zygote, coupled with transcriptomic analysis, the current work broadens our understanding of zygotic translation activation that is key to successful malaria parasite transmission to the mosquito.

      This dataset provides a useful resource for the Plasmodium research community as it provides a more comprehensive view of how transcripts behave during the transitions from the mammalian host to the vector. It is one step in a broader endeavour towards finding genes crucial for parasite transmission that could be targeted for interventions.

      How translational repression and derepression is regulated remains unknown, although some of the molecular players have been identified. This paper shows proximity labelling and expansion microscopy data of the ribonuclear protein complex thought to mediate repression. Although the specific mechanistic insights provided by the experiments shown here remain relatively limited, the work demonstrates interesting new avenues for how translational derepression in Plasmodium can be studied.

      PeerReviewed
    3. EMBOpress 20 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript provides a detailed analysis of RNA and protein dynamics during transmission of the rodent malaria model P. yoelii from the mouse host to an in vitro ookinete culture setting (mimicking the mosquito midgut environment). This group and others have shown experimentally that a substantial number of mRNAs is stored in the female Plasmodium gametocyte, ready to be translated following initiation of ookinete development. The process is akin to maternal deposition of mRNA in oocytes of metazoans. With this manuscript the authors provide a significant contribution to the field of translational control in Plasmodium parasites as they explore the translational activation during the early hours of zygote-to-ookinete development. The paper presents RNAseq and mass-spec analyses of female gametocytes and for the first time for 6-hour zygotes (ie a fertilized female gamete); the zygote datasets are much improved and more comprehensive than the only other performed in 2008 in P. gallinaceum. Using comparative analyses of transcriptome and proteome data (including published datasets) the authors arrive at a list of 198 transcripts that are translationally repressed in the gametocyte and translated within 6 hours of fertilization in the zygote. Many of these mRNAs are known to be involved in zygote to ookinete transformation. BioID is finally used to explore changes in mRNP protein composition between the female gametocyte and the zygote.

      The paper is generally well written. The authors present a lot of data (also in comparison with published data). Sometimes perhaps the main message could be simplified / streamlined in section titles (Quantitative Proteomics by DIA-MS is not very informative. The outcome of the analysis would be more telling).

      A considerable proportion of the DIA mass-spec proteomics results section is very technical. The paper describes a biological phenomenon rather than a technical mass-spec advance. Can these technical details be moved to the methods section?

      On the other hand, a bit more detail could be provided in the main text. For example, the age of the zygotes is never mentioned. This is important, please add this. The main manuscript text has 16 mentions of the word "many". As the authors are in possession of the data, please provide, if missing, (in parenthesis) the absolute numbers, maybe in an "x out y" format. Please clearly state the number of biological and/or technical replicates used for transcriptome and proteome analyses in the main text, figures and/or figure legends. How many protein coding genes are encoded in the P. yoelii genome?

      The authors claim that only zygotes (fertilized females) have surface-exposed Pys25 (a surface protein they sue to affinity-purify zygotes) but not gametocytes. I could not find the experimental data for this in the paper. The cited reference #22 also does not appear to show this. In Figure 2C Pys25 is shown to be translated in gametocytes. In this context it may be important to note that in the related P. berghei the related protein P28 is expressed even in the absence of fertilization (Billker 2004; DOI: 10.1016/s0092-8674(04)00449-0). It may not be relevant whether translation requires fertilization, but the authors claim it affects trafficking of the Pys25 protein to the surface, so it needs to be shown. A reference to an infertile P. yoelii line would be great.

      It is highly commendable that all data is provided throughout the manuscript. For readability, may I suggest that the authors add labels to individual sheets within an excel file from A to Z, and do so also within the manuscript. That would really help; the most relevant data sets could then be identified quickly. For example, line 184 refers to 276 zygote proteins in which sheet of which table?

      Section 176 onwards: here the authors combine P. falciparum and P. yoelii proteomics data. Please explain why you excluded any of the available P. berghei proteome data such as the male and female gametocyte proteome? The same question applies to 294 onwards.

      The comparative transcriptome-proteome analysis arrives at 198 translationally repressed mRNAs. Could the authors provide one or two alternatives using less stringent parameters? The list in P. falciparum and P. berghei is considerably larger (500+ and 700+).

      The turboID data is informative but somewhat speculative in regard to spatial rearrangements within these mRNPs. Figure 6 presents the RNA helicase to bind the 5' end of mRNAs that are associated with polyribosomes and I assume being translated. Is this association realistic? The RNA helicase DOZI homolog of yeast (Dhh1) is also involved in decapping.

      Specific comments:

      title Is global the appropriate word? Some transcripts appear to be translated later.

      Line 30/32 Please re-phrase the sentence. There is: Cell Host Microbe 2012 Jul 19;12(1):9-19. doi: 10.1016/j.chom.2012.05.014.

      30 Perhaps add ookinete that establishes infection rather than the zygote. For a general readership, a brief description of the sexual life cycle might be useful

      32 DOZI/CITH/ALBA complex would require some explanation for a more general reader

      36-37 I believe zygotes were collected 6 hours after fertilization. Does that qualify as soon after fertilization? Motile ookinetes are generated within 20 hours and motility can be seen before that.

      37 Essential functions for what?

      39 Is the spatial arrangement of this mRNP known?

      40 Can you briefly allude to the "recent, paradigm-shifting models of translational control"

      44 Products = mRNA

      45 Oocyte in metazoans ?

      60/62 Please re-phrase the sentence. There is: Cell Host Microbe 2012 Jul 19;12(1):9-19. doi: 10.1016/j.chom.2012.05.014.

      81 PbDozi Plasmodium berghei DOZI

      84/85 Please rephrase and cite Nucleic Acids Res. 2008 Mar;36(4):1176-86. doi: 10.1093/nar/gkm1142. Epub 2007 Dec 23. and Cell Host Microbe 2012 Jul 19;12(1):9-19. doi: 10.1016/j.chom.2012.05.014.

      88 Please define the timepoints throughout this manuscript. What age are the zygotes? How many hours post-induction? Please define the time for ookinete development somewhere in the introduction

      104 Please add the age (in hours) of these zygotes from the time of starting the in vitro cultures. From the methods section it looks like 6 hours.

      103/105 I can find no evidence for P25 (Pys25) expression relying on fertilization in the cited paper (22). The SOM has no reference to Pys25 either. Please show data or reference published data that there is no translation and trafficking of Pys25 in unfertilized female gametes, ie those that are placed in ookinete medium. In this respect it may be important to note that unfertilized Plasmodium berghei females placed in ookinete medium translate P28, the P25 paralog (https://www.sciencedirect.com/science/article/pii/S0092867404004490?via%3Dihub)

      104 What cell line was used for the zygotes?

      114 The number of transcripts detected in gametocytes is quite small compared to the twice as large proteomics dataset. See for example also Lasonder 2016 for P. falciparum detected transcripts: 4477 different sense transcripts were identified, 98% of which were shared between MG and FG.

      117 Does the 194 up-in-gametocytes dataset include the 81 not found in zygotes?

      117 Could you indicate some of the genes in the plot?

      Fig1 How were the upregulated transcripts identified? 1647 are shown to be specific to zygotes in 1B, yet only 685 are shown in 1C to be upregulated. Do the transcripts found exclusively in zygotes not count? Are these transcripts likely the result of de novo transcription? How old are these zygotes when the libraries are made?

      132 Many? How many? Please provide a precise number.

      134 Please explain why p28 would be differentially abundant in the zygote rather than the female gametocyte. That would require de novo transcription of this gene. If there is experimental evidence for the de novo transcription of p28 and other translationally repressed transcripts in the zygote please cite the references. Can you name a few more examples here? P25 for example, ap2-o, or anything published and experimentally validated. What about AP2-o and AP2-Z? Both are known to be translationally repressed.

      139 Please define how many members of the IMC?

      156 Can you provide a number of how many parasites were used in total or per run. And how many biological and technical replicates were analysed?

      169 The number of proteins detected in the gametocyte sample is twice the size of transcripts. IS this to be expected?

      170 How many samples were analyzed? One gametocyte and one zygote sample?

      176 Why did you not include P. berghei in the meta-analysis?

      184 Please refer to an excel table here.

      184 145 proteins: do you mean orthologs in general or orthologs with a gene/protein annotation other than unknown function?

      190 142 proteins: do they all have orthologs in P. falciparum?

      Figure 2C P25 is not exclusive to zygotes here and also found in the gametocyte sample.

      190 shortlist

      219 onwards Does the list of 198 transcripts exclusively arise from your RNAseq and proteomics comparison? Or does it include falciparum data as outline in section 176 onwards, ie the list of 276 proteins that only are detected in zygotes?

      224 Early zygote? At 6 hours do the parasites not start to transform, elongate?

      225 >5-fold. Is this an arbitrary decision?

      227 1417 mRNAs: they are from which dataset?

      228/229 Please explain why DOZI and CITH are in the list of 198 repressed transcripts? They are present in the gametocyte. Are they upregulated>5 fold?

      259 ... as they are already translated in the gametocyte?

      295 Is this from the 198 TR list S4?

      294 onwards How many putatively falciparum transcripts are there? How many were identified in P. berghei? How many are common to all? A Venn diagram perhaps to compare the different studies

      301 How many transcripts were found associated with Plasmodium berghei DOZI and/or CITH in female gametocytes? How many of those were abundantly detected as protein in zygotes, or had no difference in protein abundance between gametocytes and zygotes, or even greater abundance in female gametocytes?

      303/305 Please indicate the numbers of translationally repressed transcripts identified for P. falciparum and berghei.

      317/319 Please add the promoter used for tid-GFP

      320 Please elaborate on the spatial organization of the DCA complex.

      321/322 Have precise binding sites of DOZI and ALBA4 really been shown experimentally in the cited papers? In relation to 5' and 3' ends of the mRNA? Please cite Braks et al. paper.

      323 What is the first generation BioID enzyme? BirA*

      323 Please cite relevant Kyle Roux and Alice Ting for the original enzymes

      327 Could you show images of ALBA4::TurboID::GFP, DOZI::TurboID::GFP and cytosolic (free) TurboID? Perhaps stained with fluorescently labelled streptavidin and / or against GFP? In the gametocyte and zygote samples?

      331 What is the age of these zygotes? Where they affinity purified?

      Fig S4 Please indicate whether ALBA4 and DOZI were tagged endogenously

      421/430 Please add a few references here

      429 translational repression?

      445 966 proteins in gallinaceum? The zygote cultures in that study were 2-3 hours. How old were the cultures in your study?

      481 Please explain / cite why repression is energetically costly.

      501 Please add the time-point of RNA and protein sampling. How many hours into ookinete development? What is the time from cardiac puncture through FACS sampling of gametocytes.

      711/713 Do you have any images that show the successful purification of zygotes away from gametocytes? Secondly, please provide a reference for the statement that unfertilized female gametocyte do not express surface exposed Pys25.

      711/716 Were parasites lysed and mechanically homogenised?

      Figure 6 What is the evidence that DOZI stays associated with mRNA that is being translated? Rather than mRNA that is being decapped. Please add the references that unequivocally show that DOZI and ALBA4 bind to opposite ends of repressed mRNAs.

      Significance

      The experiments in the manuscript are carefully conducted. Apart from a P. gallinaceum study from 2009 this is the first comprehensive analysis of the transcriptome and proteome of a Plasmodium zygote (developing ookinete) at 6 hours post-fertilization. The data are used to explore the temporal aspect of activation of translation during the first quarter of the 20-24 hour ookinete developmental period. The study will be of interest to the field, specifically those scientists working to understand translational control, ookinete development, and those developing intervention strategies to prevent mosquito infection and thus malaria transmission.

      PeerReviewed
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    Phosphorylation of Aly3 C-terminus impedes aberrant endocytosis of <I>S. pombe</I> hexose transporter Ght5
    4
    1. EMBOpress 20 Jun 2024

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      Reply to the reviewers

      1. General Statements [optional]

      We thank all the reviewers for their constructive and critical comments. We provide a point-by-point response to the reviewers' comments, as detailed below. By responding to them, we believe that our revised manuscript will significantly improve so that it will be of interest for researchers in the field of cell biology, signaling pathways, physiology and nutrition.

      Reply to the reviewers

      Reviewer #1 (Evidence, reproducibility and clarity):

      Summary: The manuscript by Yusuke Toyoda and co-workers describes that the phosphorylation of the a-arrestin Aly3 downstream of TORC2 and GAD8 (AKT) negatively regulates endocytosis of the hexose transporter Ght5 in S.pombe under glucose limiting growth conditions.

      To arrive at these conclusions, the researchers define a set of redundant c-terminal phosphorylation sites in Aly3 that are downstream by GAD8. Phosphorylation of these sites reduces Ght5 ubiquitination and endocytosis. For ubiquitination, Aly3 interacts with the ubiquitin ligases Pub1/3.

      We thank the reviewer for his/her time and reporting advantages and issues of this study.

      Major points:

      Figure 3B: it would be interesting to compare Aly3 migration pattern (and hence potential phosphorylation) under glucose replete or limiting growth conditions. Can the authors provide direct evidence that Aly3 phosphorylation changes in response to glucose availability? Also please explain the 'smear' in lanes aly3(4th Ala), aly3(4th Ala, A584S), aly3(4th Ala, A586T).

      While it is an interesting possibility that the Aly3 migration pattern changes in response to glucose concentrations in medium, we think that this is unlikely and that examining this possibility is beyond the scope of this study. Because a phospho-proteomics study reported by Dr. Paul Nurse's lab showed Tor1-dependent phosphorylation of Aly3 at S584 under high glucose (2%) conditions (Mak et al, EMBO J, 2021), the Aly3 phosphorylation (migration) pattern is likely to be constant regardless of glucose conditions. Glucose conditions affect the mRNA and protein levels of Ght5, but supposedly not its endocytosis to vacuoles (Saitoh et al, Mol Biol Cell, 2015; Toyoda et al, J Cell Sci, 2021).

      As for the smear in Aly3(4th A), Aly3(4th A;A584S), Aly3(4th A; A586T), we suspect that some posttranslational modification occurs on these mutant Aly3 proteins, but the identity of the modification is unclear. We did not mention the smear signals in the original manuscript, because the presence or absence of the smear did not necessarily correlate with cell proliferation in low glucose and thus vacuolar localization of Ght5, which is the main topic of this study. In the revised manuscript, we will mention this point more clearly.

      Figure 4: Ght5 localization should be analyzed + / - thiamine and in media with different glucose levels. Also, a co-localization with a vacuolar marker (FM4-64) would be nice (but not necessary). Ideally, the authors should add WB analysis of Ght5 turnover to complement the imaging data. Also, would it be possible to measure directly the effects on glucose uptake (using eg: 2-NBDG).

      In this revision, we plan to observe Ght5 localization under the conditions indicated by the reviewer (+/- thiamine and high/low glucose levels) to unambiguously show that the vacuolar localization of Ght5 occurs in a manner dependent solely on expression of the mutant Aly3 protein.

      We thank the reviewer for the suggestion of co-staining with FM4-64. Indeed, because we previously reported that the cytoplasmic Ght5 signals were surrounded by FM4-64 signals in the TORC2-deficient tor1Δ mutant cells (Toyoda et al, J Cell Sci, 2021), the cytoplasmic Ght5-GFP signals in Figure 4 are very likely to co-localize with vacuoles. We will modify the text to clarify this point.

      As suggested, we plan to add Western blot analysis of Ght5 turnover in Aly3-expressing cells, to complement the imaging data (Figure 4) in the revised manuscript. Persistent appearance of GFP in Western blot would be a good support for vacuolar transport of Ght5-GFP.

      While regulation of glucose uptake is an important issue, measurement of Ght5-dependent glucose uptake using 2-NBDG was very difficult in our hands. Another reviewer (Reviewer #2) also mentioned the difficulty of this measurement in the Referees cross-commenting section.

      Figure 5: Given the localization of Ght5 shown in Figure 4, I'm surprised that it is possible in to detect full length Ght5, and its ubiquitination in the phospho-mutants of Aly3. I expected that the majority of Ght5 would be constitutively degraded, and that one would need to prevent endocytosis and/or vacuolar degradation to detect full length Ght5 and ubiquitination. Please explain the discrepancy. Also it seems that the quantification in B was performed on a single experiment.

      As the aim of Figure 5 is to compare the ubiquitinated species of Ght5 among the samples expressing different species of Aly3, the loading amount of each sample was adjusted so that the abundance of immunoprecipitated Ght5 is same across them. Therefore, as the reviewer points out, before the adjustment, abundance of the full-length Ght5 might be different in these samples. In the revised manuscript, we will add explanation on this point; why the anti-GFP blot of Figure 5A has the similar intensities in those samples.

      In the revised manuscript, we will add two additional replicates of the same experiment as Figure 5 in Supplementary material to show reproducibility of the result.

      Figure 6: Which PPxY motif of Aly3 is used for interaction with Pub1/3 and does their interaction depend on (de)phosphorylation?

      In the revised manuscript, we will discuss that "both PY motifs of Aly3 might be required for full interaction with Pub1/3," by citing the following published knowledge:

      (a) Mutation of both PPxY motif of budding yeast Rod1 and Rog3 (Aly3 homologs) diminished their interaction with the ubiquitin ligase Rsp5 (Andoh et al, FEBS Lett, 2002).

      (b) Mutating either one of two PPxY motifs of budding yeast Cvs7/Art1 greatly decreased interaction with WW domain, and mutating both abolished the interaction (Lin et al, Cell, 2008).

      Our preliminary results indicated that Pub3 interacted with Aly3, Aly3(4th A) and phospho-mimetic Aly3(4th D), and thus suggested that the Aly3-Pub1/3 interaction does not depend on the phosphorylation status of Aly3. Consistently, budding yeast Rod1 reportedly interacts with Rsp5 regardless of its phosphorylation status (e.g. Becuwe et al, J Cell Biol, 2012). While we have partially mentioned this point in the original manuscript (L499-503), we will discuss this point more clearly in the revised manuscript.

      Reviewer #1 (Significance):

      The results are well presented and clear cut (with few exceptions, please see major points). They provide further evidence that metabolic cues instruct the phosphorylation of a-arrestins. Phosphorylation then negatively regulates a-arrestin function in selective endocytosis and is essential to adjust nutrient uptake across the plasma membrane to the given biological context.

      We thank the reviewer for finding significance of our study. We believe that adding new results of the requested experiments and responding to the raised comments will clarify the significance of our revised manuscript.

      Reviewer #2 (Evidence, reproducibility and clarity):

      **Summary / background. This paper focuses on the regulation of endocytosis of the hexose transporter, Ght5, in S. pombe by nutrient limitation through the arrestin-like protein Aly3. Ght5 is induced when glucose is limiting and is required for growth and proliferation in these conditions. ght5+ encodes the only high-affinity glc transporter from fission yeast. ght5+ is induced in low glucose conditions at the transcriptional level and is translocated to the plasma membrane to allow glc import. Ght5 is targeted to the vacuole in conditions of N limitation. Mutations in the TORC2 pathway lead to the same process, thus preventing growth on low glucose medium, as shown in the gad8ts mutant, mutated for the Gad8 kinase acting downstream of TORC2. Previously, the authors demonstrated that the vacuolar delivery of Ght5 in the gad8ts mutant is suppressed by mutation of the arrestin-like protein Aly3. Arrestin-like proteins are in charge of recognising and ubiquitinating plasma membrane proteins to direct their vacuolar targeting by the endocytosis pathway. This suggested that Aly3 is hyperactive in TORC2 mutants, and accordingly, Ght5 ubiquitination was increased in gad8ts.

      **Overall statement This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments below.

      We thank the reviewer for pointing both advantages and issues of our manuscript.

      We admit that phosphorylation of Aly3 was not experimentally shown in our manuscript, although its phosphorylation has already been shown in phospho-proteomic studies by other groups. For this issue, we plan to add an experiment and modify the text, as explained below.

      The other major issue raised by this reviewer is that detection of Ght5 ubiquitination by immunoprecipitation in a native condition cannot be conclusive. Although we noticed that many studies perform affinity purification after denaturing and precipitating proteins with TCA or acetone to detect ubiquitination of the affinity-purified protein (e.g. Lin et al, Cell, 2008), we disagree with this opinion of the reviewer #2. In a review article describing methods to study ubiquitination by immunoblotting (Emmerich and Cohen, Biochem Biophys Res Comm, 2015), affinity purification of the protein of interest in a native condition is mentioned as one major choice. Moreover, a denaturing condition was not applicable to detect ubiquitinated Ght5 because the Ght5 protein that is once denatured and precipitated with TCA cannot be re-solubilized for immune-purification and -blotting. As the reviewer points out, a pitfall of detection of ubiquitinated Ght5 in a native condition is the presence of co-immunoprecipitated proteins. In our previous study (Toyoda et al, J Cell Sci, 2021), we purified GFP-tagged Ght5 and showed that a 110 kDa band detected in an anti-Ub immunoblot was also recognized by an anti-GFP antibody, confirming that the detected 110 kDa band corresponded to an ubiquitinated species of Ght5, but not a co-immunoprecipitated protein. Similarly, in the revised manuscript, we will add a panel of high-contrast (over-exposed) anti-GFP immunoblot, in which the indicated 110 kDa band was clearly detected by an anti-GFP antibody, in Figure 5A.

      We appreciate these issues raised by the reviewer #2. By responding to them, we believe that conclusions of our study will be more rigorous and undoubtful in the revised manuscript.

      **Major statements and criticism.

      *Fig 1. Based on the hypothesis that TORC2-mediated phosphorylation regulate Ght5 endocytosis, the authors first considered a possible phosphorylation of Ght5. They mutagenised 11 **possible** phosphorylation sites on the Ct of Ght5, but none affected the growth on low glucose in the absence of thiamine, suggesting that they don't contribute to the observed TORC2-mediated regulation. However, I disagree with the statement that "phosphorylation of Ght5 is dispensable for cell proliferation in low glucose", given that the authors do not show 1- that Ght5 is phosphorylated and 2-that this is abolished by these mutations. They should either provide data on this or tone down and say that these residues are not involved in the regulation, without implying phosphorylation which is not proven.

      Although we did not experimentally test whether these 11 residues of Ght5 was phosphorylated in our hand, these residues have been shown to be phosphorylated in phospho-proteomics studies by other groups (Kettenbach et al, Mol Cell Proteomics, 2015; Swaffer et al, Cell Rep, 2018; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021). In the revised manuscript, we plan to be more precise by replacing this conclusion with the following statement: "11 Ser/Thr residues of Ght5, which are reportedly phosphorylated, are not essential for cell proliferation in low glucose."

      In the presence of Thiamine (Supp fig 1), it seems that the ST/A mutant grows better in low glucose, and this is not explained nor commented. Since the transporter is not expressed, could the authors provide an explanation to this? If the promoter is leaky and some ght5-ST/A is expressed, it may be more stable and allow better growth than the WT, which would tend to indicate that impairing phosphorylation prevents endocytosis (which is classical for many transporters, see the body of work on CK1-mediated phosphorylation of transporters). Have the authors tried to decrease glc concentration lower than 0.14% in the absence of thiamine to see if this also true when the transporters is strongly expressed? (OPTIONAL)

      Improved growth of Ght5(ST11A)-expressing cells in the presence of thiamine was mentioned in the legend of Supplementary Figure 1A. In the revised manuscript, we will mention this observation also in the main text for better description of the results.

      Adding thiamine to medium does not completely shut off transcription from the nmt1 promoter but allows some transcription, as previously reported (Maundrell, J Biol Chem, 1990; Forsburg, Nuc Acid Res, 1993). In the revised manuscript, we will mention this "leakiness" of the nmt1 promoter and, by citing the suggested studies, will discuss a possibility that the ST11A mutations might prevent endocytosis of Ght5 and consequently promote cell proliferation in low glucose conditions.

      We found that, in the absence of thiamine, cells expressing ght5+ and ght5(ST11A) proliferated to the comparable extent on medium containing 0.08% glucose. This result will be added to the revised manuscript.

      *Fig 2. The authors then follow the hypothesis that TORC2 exerts its Ght5-dependent regulation through the phosphorylation of Aly3. They mutagenised 18 **possible** phosphorylation sites on Aly3. This led to a strong defect in growth in low-glc medium. Mutation of the possible Gad8 site (S460) did not recapitulate this phenotype, suggesting that it is not sufficient, however, mutations of 4 ST residues in a CT cluster (582-586) mimicked the full 18ST/A mutation, suggesting these are the important residues for Ght5 endocytosis.

      We thank the reviewer for appreciating the results in Fig. 2. As we explain below, we plan to perform an additional experiment to show that the Aly3 C-terminus is phosphorylated. With this result, our model will gain another experimental support.

      *Fig 3A. Further dissection did not allow to pinpoint this regulation to a specific residue, beyond the dispensability of the T586 residue. Fig 3B. The authors look at the effects of mutation of Aly3 on these sites at the protein level. They had to develop an antibody because HA-epitope tagging did not lead to a functional protein (Supp fig 2). Whereas I agree that the mutations causing a phenotype lead to a change in the migration pattern, I disagree with the statement that "This observation indicated that slower migrating bands were phosphorylated species of Aly3" (p.9 l.271). First, lack of phosphorylation usually causes a slower mobility on gel, which is not clear to spot here. Second, a smear appears on top of the mutated proteins (eg. 4th Ala) which is possibly caused by another modification. There are many precedents in the literature about arrestins being ubiquitinated when they are not phosphorylated (see the work on Bul1, Rod1, Csr2 in baker's yeast from various labs). My gut feeling is that lack of phosphorylation unleashes Aly3 ubiquitination leading to change in pattern. All in all, it is impossible to state about the phosphorylation of a protein without addressing its phosphorylation properly by phosphatase treatment + change in migration, or MS/MS. Thus, whereas the data looks promising, this hypothesis that Aly3 is phosphorylated at the indicated sites is not properly demonstrated.

      We disagree with the reviewer's opinion that a lack of phosphorylation usually causes slower mobility on gel. There are many examples in which phosphorylation causes slower mobility on gel, including budding yeast Rod1 (Alvaro et al, Genetics, 2016), and mammalian TXNIP (Wu et al, Mol Cell, 2013). In the revised manuscript, we will cite these reports to support our interpretation that the slower migrating bands are likely phosphorylated species of Aly3 (L270-271).

      Smear-like signals in Aly3(4th Ala), Aly3(4th A;A584S) and Aly3(4th A;A586T) might result from some modification, but identity of the modification is unknown. As the reviewer #2 mentioned, phosphorylation on Aly3 might negatively regulate another modification. The precedent studies revealed that budding yeast Rod1 and Rog3 arrestins tend to be ubiquitinated in snf1/AMPK-deficient cells (Becuwe et al, J Cell Biol, 2012; O'Donnell et al, Mol Cell Biol, 2015), and that Bul1 arrestin is dephosphorylated and ubiquitinated in budding yeast cells deficient in Npr1 kinase (Merhi and Andre, Mol Cell Biol, 2012). Also, budding yeast Csr2 arrestin is deubiquitinated and phosphorylated upon glucose replenishment, while non-phosphorylated Csr2 is ubiquitinated and activated by Rsp5 (Hovsepian et al, J Cell Biol, 2012). While the smear-like signals are interesting, we noticed that the smear-like signals did not necessarily correlate with cell proliferation defects in low glucose. We therefore think that clarifying the identity of the smear-like signals is beyond the scope of this study. We will discuss the smear-like signals only briefly in the revised manuscript, and would address this issue in our future work, hopefully.

      While the 4 S/T residues at the C-terminus of Aly3 as well as the other 14 S/T residues have been already shown to be phosphorylated in the precedent studies (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021), we will confirm that the slower migrating Aly3 is indeed phosphorylated by phosphatase treatment in the revised manuscript. This planned experiment will further strengthen our study and support our conclusion and model.

      *Fig 4. The authors now look at the functional consequences of these mutations on ALy3 on Ght5 localisation. The data clearly shows that mutation of the 4 identified S/T residues (Aly3-4th A) causes aberrant localisation of the transporter to the vacuole, likely to cause the observed growth defect on low glucose. There is a nice correlation between the vacuolar localisation and growth in low-glucose for the various aly3 mutants. (A final proof could be to express this in the context of an endocytic mutant, which should restore membrane localisation and suppress the aly3-4thA phenotype - OPTIONAL). However, I still disagree with the statement that "These results indicate that phosphorylation of Aly3 at the C-terminal 582nd, 584th, and/or 585th serine residues is required for cell-surface localization of Ght5." given that phosphorylation was not properly demonstrated.

      While phosphorylation of the 582nd, 584th and/or 585th serine residues of Aly3 is not experimentally demonstrated in our hands, they have been shown to be phosphorylated in phospho-proteomics studies by other groups (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021). Among them, the 584th serine residue (S584) was reported to be phosphorylated in a TORC2-dependent manner (Mak et al, EMBO J, 2021), consistent with our model. To explicitly demonstrate that S584 is phosphorylated, we plan to make a strain expressing a mutant Aly3 protein in which all the possible phosphorylation sites except S584 are replaced with alanine, namely Aly3(ST17A;S584). Hopefully, we can properly show the phosphorylation of S584 by measuring the mobility of the Aly3(ST17A;S584) on gel with/without phosphatase treatment or gad8 mutation.

      We thank the reviewer for suggestion of the experiment using an endocytic mutant. Previously we reported that vacuolar localization of Ght5 in gad8 mutant cells was suppressed by mutations in not only aly3 but also genes encoding ESCRT complexes (Toyoda et al, J Cell Sci, 2021). We therefore think that in cells expressing Aly3(ST18A) or Aly3(4th Ala), Ght5 is subject to endocytosis and ensuing selective transport to vacuoles via endosome-localized ESCRT complexes. We will discuss this point in the revised manuscript.

      *Fig 5. Here, the authors question the role of Aly3 mutations on Ght5 ubiquitination. They immunoprecipitate Ght5 and address its ubiquitination status in various Aly3 mutants. The data is encouraging for a role in Aly3 phosphorylation (?) in the negative control of Ght5 ubiquitination. My main problem with this experiment is that it seems that Ght5 immunoprecipitations were made in non-denaturing conditions, which leads to the question of what is the anti-ubiquitin revealing here (Ght5 or a co-immunoprecipitated protein, for example Aly3 itself, or the Pub ligases, or an unknown protein). It seems that this protocol was previously used in their previous paper, but I stand by my conclusion that ubiquitination of a given protein can only be looked in denaturing conditions. The experiments should be repeated in buffers classical for the study of protein ubiquitination to be able to conclude unambiguously that we are looking at Ght5 ubiquitination itself, especially in the absence of a non-ubiquitinable form of Ght5 as a negative control. Could the authors comment on the fact that S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination?

      As mentioned above, immunoprecipitation of Ght5 in denaturating conditions is not feasible. Ght5 can be affinity-purified only in a non-denaturing condition. In addition, affinity purification in a native condition is considered as a major choice to examine its ubiquitination according to a literature by Emmerich and Cohen (Emmerich and Cohen, Biochem Biophys Res Comm, 2015). A drawback of native condition is, as the reviewer points out, that the affinity-purified fraction might include non-bait (non-Ght5) proteins. The 110 kDa band indicated by an arrow in Fig. 5A was confirmed to be Ght5, not a non-bait protein, as a band at the identical position was detected in the immunoblot with anti-GFP antibody. Because this band in the anti-GFP immunoblot was too faint to be visible in Fig. 5A of the original manuscript, we will add an additional panel showing the contrast-enhanced anti-GFP immunoblot in which the 110 kDa band is clearly visible.

      As for the result that "S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination," we are afraid that the reviewer #2 misunderstood the labels of the samples. We apologize for confusing notational system of the sample name. Full description of samples is as follows; In Aly3(4th A), all of S582, S584, S585 and T586 are replaced with A; In Aly3(4th A;A584S), S582, S585 and T586 are replaced with A, whereas S584 remains intact; In Aly3(4th A;A584D), S582, S585 and T586 are replaced with A, and S584 is replaced with phospho-mimetic D. Because cells expressing Aly3(4th A;A584S) and Aly3(4th A;A584D) exhibited similarly low levels of Ght5 ubiquitination, we speculated that phosphorylation at S584 of Aly3 negatively regulates ubiquitination of Ght5.

      In the revised manuscript, we plan to add a table showing amino acid sequence of each species of Aly3 (just like Figure 3A) to avoid confusion.

      *Fig 6. The authors want to document the model whereby Aly3 may interact with some of the Nedd4 ligases (Pub1/2/3) to mediate its Ght5-ubiquitination function. They actually use the Aly3-4thA mutant, it should have been better with the WT protein. But the results indicate a clear interaction with at least Pub1 and Pub3. By the way, are the Pub1/2/3 fusions functional? Nedd4 proteins are notoriously affected in their function by C-terminal tagging and are usually tagged at their N-terminus (See Dunn et al. J Cell Biol 2004).

      We plan to test whether Pub1-myc is functional by comparing proliferation of the Pub1-myc-expressing strain and pub1Δ strain, as pub1Δ cells reportedly show proliferation defects at a high temperature (Tamai and Shimoda, J Cell Sci, 2002). As deletion of pub2 or pub3 reportedly exhibited no obvious defects (Tamai and Shimoda, J Cell Sci, 2002; Hayles et al, Open Biol, 2013), it is not easy to assess functionality of the myc-tagged genes.

      Please note that C-terminally tagged Pub1/2/3 proteins have been widely used in studies with fission yeast. Both Pub1-HA and non-tagged Pub1 were reported to be ubiquitinated (Nefsky and Beach, EMBO J, 1996; Strachan et al, J Cell Sci, 2023). Pub1-GFP, which complemented the high temperature sensitivity of pub1Δ, localized to cell surface and cytoplasmic bodies (Tamai and Shimoda, J Cell Sci, 2002). Pub2-GFP, overexpression of which arrested cell growth just like overexpression of non-tagged Pub2, localized to cell surface, and consistently Pub2-HA was detected in membrane-enriched pellet fractions after ultracentrifugation (Tamai and Shimoda, J Cell Sci, 2002). They also reported ubiquitin conjugation of the HECT domain of Pub2 fused with myc epitope at its C-terminus. Pub3-GFP localized to cell surface (Matsuyama et al, Nat Biotech, 2006).

      Regardless of functionality of the myc-tagged Pub1/2/3, we believe that results of this experiment (Figure 6) support our model, because the aim of this experiment, which is to identify the HECT-type and WW-domain containing ubiquitin ligase(s) that interact with Aly3, is irrelevant to functionality of the myc-tagged Pub proteins.

      *Fig 7. The authors want to provide genetic interaction between the Pub ligases and the growth defects in low glc due to alterations in Ght5 trafficking. It is unclear how the gad8ts pub1∆ mutant was generated since it doesn't seem to grow on regular glc concentration (Supp fig 5), could the authors provide some information about this? It is also not clear whether it can be stated thatches mutant is "more sensitive" to glc depletion because of the low level of growth to begin with (even at 3%). Altogether, the data show that deletion of pub3+ is able to suppress the growth defect of the gad8ts mutant on low glc medium, suggesting it is the relevant ligase for Ght5 endocytosis. This is confirmed by microscopy observations of Ght5 localisation. However, I would again tone down the main conclusion, which I feel is far-reaching: "Combined with physical interaction data, these results strongly suggest that Aly3 recruits Pub3, but not Pub2, for ubiquitination of Ght5." Work on Rsp5 in baker's yeast has shown that Rsp5 function goes beyond cargo ubiquitination, including ubiquitination of arrestins (which is often required for their function as mentioned in the introduction) or other endocytic proteins (epsins, amphyphysin etc). I agree that the data are compatible with this model but there are other possible explanations. Anything that would block endocytosis would supposedly suppress the gad8ts phenotype.

      gad8ts pub1Δ was produced at 26 {degree sign}C, a permissive temperature of the gad8ts mutant. While this is described in the Methods section of the original manuscript, we will mention this more clearly in the Results section of the revised manuscript.

      We did not conclude low glucose sensitivity of gad8ts pub1Δ cells in the indicated part (L376-377). Rather, we compared proliferation of gad8ts single mutant and pub1Δ single mutant cells in low glucose, and we found that the pub1Δ single mutant exhibited the higher sensitivity. In the revised manuscript we will correct the text to clarify that we compared proliferation of two single mutants (but not gad8ts pub1Δ mutant).

      We agree with the opinion that the recruited Pub3 may ubiquitinate proteins other than Ght5. In the revised manuscript, we will correct our conclusion of the Figure 7 experiment (L388-390), not to limit the possible ubiquitination target(s) to Ght5.

      In a genetic screen, we found that mutations in aly3+ and genes encoding ESCRT complexes suppressed low-glucose sensitivity and vacuolar transport of Ght5 of gad8ts mutant cells (Toyoda et al, J Cell Sci, 2021). This finding appears consistent with the reviewer's opinion that blocking endocytosis would supposedly suppress the gad8ts phenotype. We will mention this point in the revised manuscript.

      *Discussion Some analogy with the regulation of the Bul arrestins by TORC1/Npr1 and PP2A/Sit4 could be mentioned (Mehri et al. 2012), at the discretion of the authors. The possibility that phosphorylation may neutralise a basic patch on Aly3 Ct, possibly involved in electrostatic interactions with Ght5 is very interesting. Regarding the effect of the mutations on Aly3 localisation (p.15 l.498), did the authors tag Aly3 with GFP? There are examples where proteins tagged with HA are not functional whereas tagging with GFP does not alter their function (eg. Rod1, Laussel et al. 2022) - and here Supp Fig 2 only relates to HA-tagging. Proof of a change in Aly3 localisation upon mutation would definitely be a plus (OPTIONAL).

      We thank the reviewer for the suggestion of a reference. In the revised manuscript, we will cite the indicated report in the corresponding part for an additional support of TORC1-mediated control of Aly3 (de)phosphorylation.

      While examining localization of Aly3 by GFP-tagging is interesting, we do not believe that it is necessary in this study. We would like to produce Aly3-GFP and to examine its functionality and localization in our future study. We thank the reviewer's insightful suggestion.

      **Minor comments.

      *Introduction: - I believe the text corresponding to the work on TXNIP is incorrect (p.5 l.127). TXNIP is degraded after its phosphorylation, not "rectracted" from the surface.

      In the revised manuscript, we will correct the text accordingly.

      • For the sake of completion, the authors could add other references concerning the regulation of Rod1 in budding yeast such as Becuwe et al. 2012 J Cell Biol and O'Donnell et al. 2015 Mol Cell Biol, in addition to Llopis-Torregrosa et al. 2016.

      In the revised manuscript, we will add the suggested references and correct the text in the corresponding part of the Introduction (L123-138).

      • Other examples of the requirement for arrestin ubiquitination beyond Art1 (p.5 l.136-137) are listed in the ref cited: Kahlhofer et al. 2021.

      We will cite the indicated review to navigate readers for more examples of arrestin ubiquitination (and transporter ubiquitination).

      *Figures: In general, I think it would be clearer if the authors showed on the figures that the background strain in which the XXX gene is added (or its mutant forms) is a xxx∆ strain.

      We will modify the figures to clearly show the genetic background of the strains used.

      **Referees cross-commenting**

      Cross review of Reviewer 1 - *I don't believe that the authors "define a set of redundant c-terminal phosphorylation sites in Aly3", because phosphorylation is not proven. *I thinks the points raised for Fig 3B are valid but the authors should focus on making their story conclusive before expanding to other data (except for the explanation of the smear, see my review). Also, I don't think 2NBDG actually works to measure Glc uptake. * same for Fig 6 - not sure the interaction site mapping between Aly3 and Pubs would bring much value since there are more urgent things to do to make the story solid.

      As mentioned above, we will experimentally show phosphorylation of the Aly3 C-terminus in the revised manuscript. Such experiments would make our story more solid and conclusive. We truly appreciate the comments and suggestions.

      We agree with the comments on difficulty of measuring glucose uptake using 2-NBDG. In fact, we tried and failed measuring Ght5-mediated glucose uptake using 2-NBDG.

      Cros review of Reviewer 3 - we have many overlaps, so briefly : *I agree that the bibliography is incomplete (mentioned in my review) *I agree that there is no demonstration of the phospho-status of Aly3, and it is a problem *I agree that the results can be better quantified, esp. in the light of the points raised by this referee concerning the variability of expression of ST18A Other specific comments : *I agree that the statement that dephosphorylation activates alpha-arresting should be toned down - this was observed in several instances but there are examples of arrestin-mediated endocytosis which does not require their prior dephosphorylation. *I fully agree that efforts could be made regarding the classification/nomenclature of arrestins in S. pombe, this had escaped my attention

      As detailed in the individual point raised by the reviewers, we will add the suggested references and accordingly correct the text in the revised manuscript.

      In addition to experimentally showing Aly3 phosphorylation, we will quantify the immunoblot result.

      Our statement that dephosphorylation activates alpha-arrestins might be too generalized. We will mention reports in which arrestin-mediated endocytosis does not require prior dephosphorylation (e.g. O'Donnell et al, Mol Biol Cell, 2010; Gournas et al, Mol Biol Cell, 2017; Savocco et al, PLoS Biol, 2019), and modify the text precisely.

      Reviewer #2 (Significance):

      *strengths and limitations This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins in S. pombe. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand, including the discovery of Aly3 as the main arrestin for this regulation, and a signalling pathway (TORC2/Gad8) acting upstream. The main question is now to understand at the mechanistic level how TORC2 signaling impinges on the regulation of this arrestin.

      Overall, the authors nicely demonstrate that C-terminal Ser/Thr residues are crucial for the function of Aly3 in Ght5 endocytosis. They propose a model whereby Aly3 phosphorylation by an unknownn kinase inhibits its function on Ght5 ubiquitination, which would favour its endocytosis. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments above.

      *Advance

      This study, if completed carefully, would provide among the first examples of mapping of phosphorylation sites on arrestins, which are usually phosphorylated at many sites and are thus difficult to study. Few studies went down to this level in this respect (see Ivshov et al. eLife 2020). There are no changes in paradigms or new conceptual insights, but this work is a nice example of the conservation of these regulatory mechanisms.

      We appreciate that this study is highly evaluated by this reviewer. We understand the main problems raised by the reviewer, and as we detailed above, we plan to perform an experiment and make explanation to respond to the problems. With the raised issues answered, we believe that conclusions of the revised manuscript will be more rigorous.

      Our study reveals mechanisms regulating vacuolar transport of the Ght5 hexose transporter via the TORC2 pathway in fission yeast. The serine residues at the Aly3 C-terminus (582nd, 584th and 585th serine residues), which are probably phosphorylated in a manner dependent on the TORC2 pathway, are required for sustained Ght5 localization to cell surface and cellular adaptation to low glucose. To our knowledge, there is no such study, and thus we think that this study is novel. By responding to the reviewers' comments and adding new data as explained above, the revised manuscript will be able to present novelty of our study more clearly. Comparison of our study in fission yeast to related studies in other model organisms may reveal the conservation and diversity of these regulatory mechanisms.

      *Audience Should be of interest for people studying basic research in the field of cell biology, signalling pathways, transporter regulation by physiology. Reviewer background is on the regulation of transporter endocytosis by signalling pathways and arrestin-like proteins.

      Reviewer #3 (Evidence, reproducibility and clarity): (Authors' response in blue)

      In this manuscript, the authors work to address how phospho-regulation of a-arrestin Aly3 in S. pombe regulates the glucose transporter Ght5. The authors use a series of phospho-mutants in Aly3 and assess function of these mutants using growth assays and localization of Ght5. My main concerns with the manuscript are that 1) there is a lack of appreciation for the similar work that has been done in S. cerevisiae to define a-arrestin phospho-regulation, which is evidenced by the severe lack of referencing throughout the document, 2) the sites mutated on Aly3 are not demonstrated to change phospho-status of Aly3 and so all interpretations of these mutants need to be better contextualized and 3) almost none of the findings are quantified (imaging or immunoblots) making it difficult to assess the rigor of the outcomes. More detailed comments are provided below.

      We thank the reviewer for thorough reading of the manuscript and the detailed comments. As explained below, we will respond to the points raised by the reviewer and accordingly modify the manuscript.

      Minor Comments

      Immunoblotting or immunostaining to define the levels and localization of phospho-mutants - In Figure 1, an immunoblot or immunostaining to define the abundance/localization of WT Ght5 vs its ST11A mutant would be appreciated. It is very difficult to know if ST11A is as functional as WT or not without an assessment of the levels and localization of the WT and mutant proteins to accompany the spot assays. Perhaps a version of Ght5 that is a phospho-mimetic would be more useful here as well since that version should not be dephosphorylated and then presumably would be internalized and not allow for growth on low glucose medium.

      We plan to add fluorescence microscopy data of WT Ght5 and Ght5(ST11A) in the revised manuscript, to compare the localization and abundance of these two Ght5 species. In our preliminary observation, those of two Ght5 species seemed to be indistinguishable.

      We'd like to emphasize that the primary aim of this study is to reveal mechanisms regulating Ght5 localization and consequently ensuring cell proliferation in low glucose. While analyzing a phospho-mimetic Ght5 mutant (e.g. Ght5(ST11D)) is interesting in terms of understanding of the nature of Ght5, we believe that such an analysis is out of the scope on this study. As Ght5(ST11A)-expressing cells proliferated comparably to Ght5(WT)-expressing cells and WT and ST11A Ght5 indistinguishably localize on the cell surface, phosphorylation of the ST residues of Ght5 is not likely to be the primary mechanism regulating Ght5 localization and function. We would like to assess a phospho-mimetic Ght5 mutant protein in our future studies.

      For the Aly3 mutants where the abundance of Aly3 appears lower via immunoblotting (i.e., 4thA-A582S or S582A) how is the near perfect functional readout explained when the levels of the protein are much lower than WT? For the ST18A mutant, this is a particularly important point since the authors indicate on lines 194-197 that based on the functional data for ST18A, some of these ST residues are needed for phospho-regulation of Aly3. However, in Figure 3B the authors clearly show that there is very little ST18A protein in cells, and so these mutations have impacted Aly3 stability, which may or may not be linked to its phospho-status. The authors should be upfront about this finding on lines 194-197 and should not present this phospho-model as the only reason for why ST18A may not be functional. On lines 265-276 for the authors indicate that ST18A is expressed equivalently to WT Aly3, which is just not the case in Figure 3B. Perhaps quantification of replicate data would help clarify this issue. Further, if the authors wish to conclude that the upper MW bands in Figure 3B are due to phosphorylation, perhaps they should perform phosphatase treatments of their extracts to collapse these bands. However, most certainly the overall abundance of the single band for ST18A is reduced compared to the total bands of WT Aly3.

      We disagree with the opinion that the levels of the mutant Aly3 are much lower than WT. For semi-quantitative measurement of the protein abundance, 2-fold dilution series of the WT Aly3 sample were loaded in the leftmost 3 lanes of Figure 3B. Although the levels of Aly3(4th A;A582S), Aly3(S582A) and Aly3(ST18A) were lower than that of WT Aly3, those are 50% or more of the WT, judging from the intensities of the serially-diluted WT samples. To clearly show that the expression of these Aly3 proteins is within comparable levels, we plan to add a column chart of the quantified expression levels and to mention abundances of the Aly3 proteins more quantitatively in the revised text. We do not think that replicate data (of Western blots as in Figure 3B) helps clarify this issue, because nmt1 promoter-driven gene transcription is induced with a small variation (Forsburg, Nuc Acid Res, 1993). We will cite this report and mention this point in the revised text.

      We are afraid that this reviewer seems to consider that Aly3(ST18A) is not functional, but it is not a case and we do not intend to claim so. While deletion of aly3 did not interfere with cell proliferation in low glucose (see vector controls in Figures 2B, 2C and 3A, -Thiamine), expression of the ST18A mutant clearly hinders cell proliferation in low glucose, indicating that the ST18A performs dominant negative function to inhibit cell proliferation. That is, even though the expression level and/or stability of the ST18A is reduced, it is still sufficiently abundant to perform the dominant negative function. We propose the phospho-model not due to dysfunctionality of ST18A, but its dominant negative functionality. The 18 S/T residues of Aly3, which are shown to be phosphorylated in precedent phospho-proteomics studies, seem to be required to down-regulate Aly3's function to inhibit cell proliferation in low glucose. We apologize for this confusion, and we will modify the text and figures to clarify these points in the revised manuscripts.

      To obtain an experimental support for our description that the slower migrating bands in Figure 3B are due to phosphorylation, we plan to perform a phosphatase treatment experiment as suggested.

      Figure 2A - how do the phosphorylation sites identified in Aly3 compare to those identified in Rod1 from S. cerevisiae? See PMID 26920760 or SGD for more information. I am confused as to why the Aly3 protein has an arrowhead at the C-terminus. What does this denote?

      We will mention reported phosphorylation sites of Aly3 and budding yeast Rod1/Art4 in the revised manuscript, by referring to the indicated report and database. It should be noted that similarity between amino acid sequences of Aly3 and S. cerevisiae Rod1 is not so high and limited in Arrestin-N and -C domains. The C-terminal half of Aly3, in which most of the potential phosphorylation sites are found, is not similar to Rod1. Thus, these sites are unlikely to be conserved between them.

      An arrowhead indicates the direction of transcription (from N to C-terminus). We will describe it explicitly in the revised figure legend.

      Figure 2 - The WT and Aly3-ST18A are expressed in S. pombe from a non-endogenous locus under the control of the Nmt1 promoter. However, are these mutants present in cells that contain WT copies of Aly3 at other genomic loci? If so, this would surely muddy the interpretations of these data as a- and b-arrestins are capable of multimerizing and the effect of multimerization on their activities can vary.

      As mentioned in L188, an aly3 deletion mutant strain (aly3Δ) was used as a host, and thus all strains harboring an nmt1-driven aly3 gene lack the endogenous aly3 gene. We will add an illustration clearly showing that the host strain lacks the endogenous aly3+ gene and modify the legend of Figure 2.

      Functional readouts for Aly3 using Ght5 localization - The reduced surface levels of Ght5 does correspond to the spot assay growth in low glucose for the various Aly3 mutants used. However, it would be useful if these assays incorporated an endocytosis inhibitor to help prevent the activities of these Aly3 plasmids to see if the transporter is retained at the PM. At the end of these mutational analyses, the authors conclude that phosphorylation of Aly3 at any of 3 sites is required for Ght5 trafficking to the vacuole in low glucose, however no experiment is done to demonstrate that these sites are phosphorylated residues. A phosphatase assay would be useful to help demonstrate that the modifications in 3B really are phosphorylation and a quantification of the phosphorylated bands in these WBs would also be useful to solidify the statement made on lines 306-309.

      We thank the reviewer for suggestion of the experiment using an endocytosis inhibitor. Previously we reported that vacuolar localization of Ght5 in gad8ts mutant cells was suppressed by mutations in not only aly3 but also genes encoding ESCRT complexes (Toyoda et al, J Cell Sci, 2021). We therefore think that, in cells expressing Aly3(ST18A) or Aly3(4th Ala), Ght5 is subject to endocytosis and subsequent selective transport to vacuoles via ESCRT complexes. We will mention these previous findings in the revised manuscript.

      As mentioned in responses to the comments above and other reviewer's, we will perform a phosphatase treatment experiment and its quantification in the revised manuscript. Here, we'd like to emphasize that these 3 sites have been shown to be phosphorylated in phospho-proteomic studies by other researchers (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021), although we do not show it directly in this study.

      Phosphorylation assessments - in general, it would be good to not only build the non-phosphorylatable versions of Aly3 but also the phospho-mimetic forms.

      We produced a phospho-mimetic mutant Aly3 (i.e. Aly3(4th A;A584D)), and showed the result in Figure 5A; cells expressing Aly3(4th A;A584D) exhibited a low ubiquitination of Ght5, similarly to Aly3(WT)- and Aly3(4th A;A584S)-expressing cells. According to our experiences, replacing S/T with D/E does not necessarily mimic phosphorylation. Thus, we do not believe that systematic production of phospho-mimetic Aly3 mutants would help achieve the aim of this study.

      Pub1, 2, and 3 - It would be helpful if the authors indicated what genes Pubs 1-3 correspond to in S. cerevisiae, where Rsp5 is the predominant Ub ligase interacting with a-arrestins. Is there no ortholog of Rsp5 in S. pombe?

      Pub1, Pub2 and Pub3 are regarded as orthologs of budding yeast Rsp5, according to the fission yeast database PomBase. We will perform a homology search for these E3 proteins, and based on the result, we will add a description in the revised manuscript.

      Pub-Aly3 interactions - could the authors please comment on the reason why so very little Aly3 is copurified with Pub1 or Pub2? Can any clear conclusion be drawn about pub2 given how very little Pub2 is present in the IPs? Based on my understanding of these data I do not think that this can be cleanly interpreted. What is is the identity of the ~50kDa MW band in Figure 6 in the upper MYC detection panel?

      We do not have an accurate answer for the result that a small amount of Aly3 is copurified with Pub1 or Pub3. The Pub1/3-Aly3 interaction may be weak or transient. We will discuss this point in the revised manuscript.

      Regarding whether Aly3 interacts with Pub2, we agree with the reviewer. As described in the Results (L360-362), we could not conclude anything about Aly3-Pub2 interaction by this immunoprecipitation experiment alone. On the other hand, the genetic interaction experiment (Figure 7A) suggests that pub2+ is not involved in defects caused by the gad8ts mutation (while pub3+ and aly3+ are). By this experiment, we think that Pub2 is not a partner of Aly3.

      In the revised manuscript, we will describe that Pub2 is not a partner of Aly3 in a paragraph describing the Figure 7A experiment.

      Because the 50 kDa band found in the IP fraction of all the samples appears even in "beads only" (Figure 6), those are supposedly derived from mouse IgG dissociated from the beads used for immunoprecipitation. We will mention this in the legend of Figure 6.

      Phosphorylation and ubiquitination of a-arrestins - The paragraph from lines 123-138 is very superficial in addressing what is known about phosphorylation and ubiquitination of a-arrestins. The way this section is written, it feels misleading to the reader as it omits many of the details for regulation that would help place the current study in context. The discussion of Rod1 phosphorylation by AMPK for example, which is directly relevant to this study, is underdeveloped. I would recommend splitting this into two paragraphs and providing a more in depth, and accurate, view of the literature on this topic, with a focus on the regulation that is relevant for the ortholog of Aly3 in S. cerevisiae. For example, Rod1 phosphorylation by AMPK is greatly expanded upon in the following papers (PMID 22249293 and 25547292) and AMPK regulation of C-tail phosphorylation of a-arrestins is defined further in PMID 26920760. These references are each particularly important to compare with the current findings presented in this manuscript. Torc2 regulation ofa-arrestins is also reviewed in PMID 36149412 and references therein should be considered.

      Because the primary aim of this study is to reveal mechanisms regulating Ght5 localization in fission yeast, but not to dissect modification and regulation of α-arrestins, we decided not to get into the details of phosphorylation and ubiquitination of α-arrestins. Furthermore, although budding yeast Rod1 and Rog3 are found to be downstream of the TORC2-Ypk1 signaling in the context of internalization of the Ste2 pheromone receptor, it is not clear whether TORC2-Ypk1 signaling also regulate α-arrestin-mediated internalization of hexose transporters in budding yeast. For these reasons, we focused on limited literatures essential for interpretation of the results and omitted many references describing the details of α-arrestin regulation. However, as this reviewer commented, we realize that our decision makes the discussion superficial and misleading to the reader. We sincerely apologize for this inconvenience.

      In the revised manuscript, we will reorganize the paragraphs in the discussion and include the suggested references. Regarding budding yeast Rod1, we will cite the study reporting Ypk1-mediated phosphorylation on Rod1 in mating pheromone response via regulation of Ste2 endocytosis (Alvaro et al, Genetics, 2016). We will also mention other reports (Becuwe et al, J Cell Biol, 2012; O'Donnell et al, Mol Cell Biol, 2015) about AMPK-dependent phosphorylation of Rod1 in the corresponding part (e.g. L129-130). In addition, we will mention that Aly2, Rod1 and Rog3 α-arrestins were found downstream of the TORC2-Ypk1 signaling (Muir et al, eLife, 2014; Thorner, Biochem J, 2022).

      As a further detailed example, there is far more work done on ubiquitination of a-arrestins in S. cerevisiae than the single citation provided by the authors on line 137. The way this section is written it feels misleading. Considerable effort has been spent on defining how mono- and poly-ubiquitination regulate a-arrestins and the authors should consider the data provided in the following citations and revise the two sentences they provide in this introduction to better reflect the breadth of our understanding rather than simply indicate that the 'mechanisms that regulate functions of a-arrestisn are not fully understood'. (PMIDs 23824189; 22249293; 17028178; 28298493)

      Ubiquitination of α-arrestin itself is not the topic of this study, and physiological consequences of ubiquitination of Aly3 remain unknown. Because of these reasons, we did not describe the details of ubiquitination of α-arrestins in the original manuscript. However, we never intend to mislead the reader, and thus to avoid it, we will revise the indicated sentences and cite the suggested literatures (O'Donnell et al, J Biol Chem, 2013; Becuwe et al, J Cell Biol, 2012; Kee et al, J Biol Chem, 2006; Ho et al, Mol Biol Cell, 2017) in the revised manuscript.

      Context of the findings and lack of citations - The referencing in this manuscript is very poor as many of the key papers that report analogous findings in the budding yeast Saccharomyces cerevisiae are not cited. This oversight in citing the appropriate literature must be remedied before this manuscript can be considered further for publication. Examples of these omissions occur at the following places:

      We will modify the text and carefully cite more literatures describing analogous finding in budding yeast and other organisms in the revised manuscript. We appreciate the insightful suggestions by this reviewer. It should be noted, however, that it is not evident whether budding yeast Rod1 and Rog3 are orthologous to fission yeast Aly3. Although Rod1 and Aly3 share overlapping roles, amino acid sequence similarity of them is not high and limited only in domains which are generally conserved among α-arrestin-family proteins.

      Line 90 - The Puca and Brou citations is one example of this but the first examples come from Daniela Rotin's work looking at Rsp5 interactions in budding yeast, which is where the association between HECT-domain Ub ligases and a-arrestins is also documented by Scott Emr and Hugh Pelham's labs. Here are some PMID numbers to improve the citations of this section (PMID 17551511; 18976803; 19912579) and each of these references long predates the Puca and Brou publication.

      In the revised manuscript, we will improve the citations by including the suggested studies (Gupta et al, Mol Syst Biol, 2007; Lin et al, Cell, 2008; Nikko and Pelham, Traffic, 2009).

      Lines 123-126 - Phosphorylation can also increase vacuole-dependent degradation of alpha-arrestins as demonstrated in PMID 35454122. The interaction with 14-3-3 proteins that is driven by phosphorylation of a-arrestins was first demonstrated by the Leon group in PMID 22249293). Lines 129-132 - Here again the Leon reference that helps demonstrate the 14-3-3 inhibition of Rod1 is lacking (PMID 22249293).

      We will cite the suggested studies in description of these topics (Bowman et al, Biomolecules, 2022; Becuwe et al, J Cell Biol, 2012).

      Lines 130-132 - Please include references for the statement that dephosphorylation activates a-arrestin activity. There are no citations on this statement and there are many to choose from and I would urge the authors to cite the primary literature on these points.

      We will cite studies for the statement "Conversely, dephosphorylation is thought to activate α-arrestins and to promote selective endocytosis of transporter proteins" (L130-132).

      These are just a few examples from the Introduction, but the Discussion is similarly wrought with issues in referencing and framing the experimental results within the context of the larger field, including what is known about Rod1/Rog3 regulation in S. cerevisiae. For example, the Llopis-Torregrosa et al reference and statement on lines 508-510 is incorrect. There are other phosphorylation sites defined in the C-terminus of Rod1, as described in Alvaro et al. PMID: 26920760.

      We will carefully correct Discussion by citing the suggested references (e.g. Alvaro et al, Genetics, 2016) and framing the obtained results within the context of the larger field.

      Of note, a combination of α-arrestin, upstream kinase(s) and distinct phosphorylation sites appears to determine the target transporter (Kahlhofer et al, Biol Cell, 2021; Thorner, Biochem J, 2022), and it has not been explicitly proved that TORC2-Ypk1 signaling also regulate α-arrestin-mediated internalization of hexose transporters in budding yeast. For these reasons, we stated "S. cerevisiae Rod1 and Rog3 are phosphorylated solely by Snf1p/AMPK" in the context of internalization of hexose transporters. We will also discuss this point in the revised manuscript.

      Minor Comments Clarification needed - Lines 107-121 - The relationship between the S. pombe arrestins and those in other organisms is somewhat unclear. Frist, all the arrestins in humans and S. cerevisiae can be sorted into the alpha, beta and Vps26 classes. However, the authors indicate that the S. pombe genome has 11 arrestin-like proteins but only 4 of these are a-arrestins. What classes do the other 7 arrestins belong to? It would be appreciated if this point was clarified.

      To our knowledge, fission yeast arrestins are not well classified yet. We will perform a phylogenetic tree analysis to classify them, and modify the description of the indicated part accordingly. We will also cite our previous report (Toyoda et al, J Cell Sci, 2021), in which the overall protein structure and domains of 11 fission yeast arrestin-like proteins were reported.

      Next, for the 4 a-arrestins identified in S. pombe the authors indicate that Aly3 is the homolog of Rod1/Art4 and Rog3/Art7 from S. cerevisiae. What is the relationship of Rod1 in S. pombe to Rod1 in S. cerevisiae? Are these also homologs? You can see how the nomenclature is confusing and, given the functional overlap of S. cerevisiae Rod1/Rog3 proteins it is important to know if Aly3 is the only version of these a-arrestins or if there is an additional counterpart in S. pombe. This point becomes somewhat more confusing when on lines 134-136 the authors talk about Arn1/Any1 as an arrestin related protein in S. pombe yet this protein was not included on the list of a-arrestins in the preceding section. What class of arrestin is this protein?

      According to PomBase, both Aly3 and Rod1 are assigned as the orthologue of budding yeast Rod1 and Rog3. However, as mentioned in responses above, it is unclear whether Aly3 is really orthologous to budding yeast Rod1/Rod3. In the revised manuscript, we will perform a homology search for these 4 proteins, and add information on how much these arrestins share homology.

      Arn1/Any1 is regarded as a β-arrestin (Nakase et al, J Cell Sci, 2013). We will also mention this in the revised manuscript.

      Alpha-arrestin homology - On lines 127-129 the authors indicate that TXNIP is the mammalian homolog of Aly3. To my knowledge, there are no evolutionary analyses that can draw these lines of homology between the a-arrestins in humans and those in yeasts. It would be appreciated if the authors could cite the work that leads to this conclusion or revise the sentence to more accurately reflect what is known on this topic. It certainly appears that, given their functional overlap in regulating glucose transporters, Txnip and Rod1/Rog3 in humans and S. cerevisiae are functionally connected. I urge the authors to use more caution when describing this protein family.

      Among human α-arrestins, ARRDC2 (22%) but not TXNIP (20%) has the highest amino acid identity to Aly3 (Toyoda et al, J Cell Sci, 2021). However, as TXNIP has been reported to regulate endocytosis of hexose transporters, GLUT1 and 4 (Wu et al, Mol Cell, 2013; Waldhart et al, Cell Rep, 2017), we think that TXNIP and Aly3 share physiological roles. We will revise the sentence (L127-129) more accurately.

      Text editing - The text could use editing as there are awkward and grammatically incorrect sentences in several places. Here are a few examples to help the authors:

      Please note that the original manuscript is edited by a professional editor, who is a native English (American) speaker and has edited thousands of research papers, before initial submission. We will ask an editor to check the revised draft again before submission.

      Lines 57-60 - the protein is not expressed over the entire cell surface, but is localized to the entire cell surface.

      We will correct this wording.

      Lines 80-83 - this sentence is very confusing

      We will correct this part by changing the phrase "Unlike TORC1," into a clause.

      Line 86 - Is there more than one gene encoding Aly3 in S. pombe?

      No, there is only one gene encoding Aly3. We will correct this part so as to avoid being misunderstood.

      Line 88, 109, - these sentences need to start with a capitol so either capitalize the A in arrestin or write out Alpha with a capitol A.

      We will correct the sentence as suggested.

      Lines 145-148 - unclear as written

      We will clarify the meaning of the sentence by changing the voice.

      Line 224 - why are these amino acids being referred to as hydroxylated? Perhaps hydroxyl-containing amino acids or 18 amino acids with hydroxyl side chains would be better choices?

      We will correct the word as suggested.

      Line 300 - very confusing sentence structure

      We will correct this part by simplifying the structure of the sentence.

      And elsewhere....

      We will carefully check the revised text before submission.

      Reviewer #3 (Significance):

      The authors provide some information as to the residues needed in the Aly3 C-tail for Ght5 trafficking in S. Pombe. These results are not places in the context of similar phosphor-regulatory work done for a-arrestins in S. cerevisiae, and this is needed for appreciation of the significance of the study.

      Overall, it appears that the model put forth is very similar to the one already proposed in S. cerevisiae where phosphorylation impedes a-arrestin-mediated trafficking of glucose transporters. It is interesting to see this similarity hold in S. Pombe, but it does not dramatically alter our appreciation of a-arrestin biology.

      The significance of the findings are somewhat underscored by the fact that very little quantification of data are presented, making the rigor of the work difficult to assess.

      We thank the reviewer for careful reading and evaluation of our study. As the reviewer states, the results are not placed in the context of similar phospho-regulatory works done for α-arrestins in S. cerevisiae. This may partly come from the fact that it remains unclear whether internalization of hexose transporters is regulated by TORC2-dependent phosphorylation in S. cerevisiae. We believe that our study is novel and significant for this reason. By performing the additional experiments/quantification and revising the text as suggested by the reviewers, the manuscript will be further strengthened, and we will be able to clearly conclude that TORC2-dependent phosphorylation of Aly3 regulates localization of the Ght5 hexose transporter and cellular responses to glucose shortage stress.

      PeerReviewed
    2. EMBOpress 20 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, the authors work to address how phospho-regulation of a-arrestin Aly3 in S. pombe regulates the glucose transporter Ght5. The authors use a series of phospho-mutants in Aly3 and assess function of these mutants using growth assays and localization of Ght5. My main concerns with the manuscript are that 1) there is a lack of appreciation for the similar work that has been done in S. cerevisiae to define a-arrestin phospho-regulation, which is evidenced by the severe lack of referencing throughout the document, 2) the sites mutated on Aly3 are not demonstrated to change phospho-status of Aly3 and so all interpretations of these mutants need to be better contextualized and 3) almost none of the findings are quantified (imaging or immunoblots) making it difficult to assess the rigor of the outcomes. More detailed comments are provided below.

      Minor Comments

      Immunoblotting or immunostaining to define the levels and localization of phospho-mutants - In Figure 1, an immunoblot or immunostaining to define the abundance/localization of WT Ght5 vs its ST11A mutant would be appreciated. It is very difficult to know if ST11A is as functional as WT or not without an assessment of the levels and localization of the WT and mutant proteins to accompany the spot assays. Perhaps a version of Ght5 that is a phospho-mimetic would be more useful here as well since that version should not be dephosphorylated and then presumably would be internalized and not allow for growth on low glucose medium.

      For the Aly3 mutants where the abundance of Aly3 appears lower via immunoblotting (i.e., 4thA-A582S or S582A) how is the near perfect functional readout explained when the levels of the protein are much lower than WT? For the ST18A mutant, this is a particularly important point since the authors indicate on lines 194-197 that based on the functional data for ST18A, some of these ST residues are needed for phospho-regulation of Aly3. However, in Figure 3B the authors clearly show that there is very little ST18A protein in cells, and so these mutations have impacted Aly3 stability, which may or may not be linked to its phospho-status. The authors should be upfront about this finding on lines 194-197 and should not present this phospho-model as the only reason for why ST18A may not be functional. On lines 265-276 for the authors indicate that ST18A is expressed equivalently to WT Aly3, which is just not the case in Figure 3B. Perhaps quantification of replicate data would help clarify this issue. Further, if the authors wish to conclude that the upper MW bands in Figure 3B are due to phosphorylation, perhaps they should perform phosphatase treatments of their extracts to collapse these bands. However, most certainly the overall abundance of the single band for ST18A is reduced compared to the total bands of WT Aly3.

      Figure 2A - how do the phosphorylation sites identified in Aly3 compare to those identified in Rod1 from S. cerevisiae? See PMID 26920760 or SGD for more information. I am confused as to why the Aly3 protein has an arrowhead at the C-terminus. What does this denote?

      Figure 2 - The WT and Aly3-ST18A are expressed in S. pombe from a non-endogenous locus under the control of the Nmt1 promoter. However, are these mutants present in cells that contain WT copies of Aly3 at other genomic loci? If so, this would surely muddy the interpretations of these data as - and -arrestins are capable of multimerizing and the effect of multimerization on their activities can vary.

      Functional readouts for Aly3 using Ght5 localization - The reduced surface levels of Ght5 does correspond to the spot assay growth in low glucose for the various Aly3 mutants used. However, it would be useful if these assays incorporated an endocytosis inhibitor to help prevent the activities of these Aly3 plasmids to see if the transporter is retained at the PM. At the end of these mutational analyses, the authors conclude that phosphorylation of Aly3 at any of 3 sites is required for Ght5 trafficking to the vacuole in low glucose, however no experiment is done to demonstrate that these sites are phosphorylated residues. A phosphatase assay would be useful to help demonstrate that the modifications in 3B really are phosphorylation and a quantification of the phosphorylated bands in these WBs would also be useful to solidify the statement made on lines 306-309.

      Phosphorylation assessments - in general, it would be good to not only build the non-phosphorylatable versions of Aly3 but also the phospho-mimetic forms.

      Pub1, 2, and 3 - It would be helpful if the authors indicated what genes Pubs 1-3 correspond to in S. cerevisiae, where Rsp5 is the predominant Ub ligase interacting with -arrestins. Is there no ortholog of Rsp5 in S. pombe?

      Pub-Aly3 interactions - could the authors please comment on the reason why so very little Aly3 is copurified with Pub1 or Pub2? Can any clear conclusion be drawn about pub2 given how very little Pub2 is present in the IPs? Based on my understanding of these data I do not think that this can be cleanly interpreted. What is is the identity of the ~50kDa MW band in Figure 6 in the upper MYC detection panel?

      Phosphorylation and ubiquitination of -arrestins - The paragraph from lines 123-138 is very superficial in addressing what is known about phosphorylation and ubiquitination of a-arrestins. The way this section is written, it feels misleading to the reader as it omits many of the details for regulation that would help place the current study in context. The discussion of Rod1 phosphorylation by AMPK for example, which is directly relevant to this study, is underdeveloped. I would recommend splitting this into two paragraphs and providing a more in depth, and accurate, view of the literature on this topic, with a focus on the regulation that is relevant for the ortholog of Aly3 in S. cerevisiae. For example, Rod1 phosphorylation by AMPK is greatly expanded upon in the following papers (PMID 22249293 and 25547292) and AMPK regulation of C-tail phosphorylation of -arrestins is defined further in PMID 26920760. These references are each particularly important to compare with the current findings presented in this manuscript. Torc2 regulation of-arrestins is also reviewed in PMID 36149412 and references therein should be considered. As a further detailed example, there is far more work done on ubiquitination of -arrestins in S. cerevisiae than the single citation provided by the authors on line 137. The way this section is written it feels misleading. Considerable effort has been spent on defining how mono- and poly-ubiquitination regulate -arrestins and the authors should consider the data provided in the following citations and revise the two sentences they provide in this introduction to better reflect the breadth of our understanding rather than simply indicate that the 'mechanisms that regulate functions of -arrestisn are not fully understood'. (PMIDs 23824189; 22249293; 17028178; 28298493)

      Context of the findings and lack of citations - The referencing in this manuscript is very poor as many of the key papers that report analogous findings in the budding yeast Saccharomyces cerevisiae are not cited. This oversight in citing the appropriate literature must be remedied before this manuscript can be considered further for publication. Examples of these omissions occur at the following places:

      Line 90 - The Puca and Brou citations is one example of this but the first examples come from Daniela Rotin's work looking at Rsp5 interactions in budding yeast, which is where the association between HECT-domain Ub ligases and -arrestins is also documented by Scott Emr and Hugh Pelham's labs. Here are some PMID numbers to improve the citations of this section (PMID 17551511; 18976803; 19912579) and each of these references long predates the Puca and Brou publication.

      Lines 123-126 - Phosphorylation can also increase vacuole-dependent degradation of alpha-arrestins as demonstrated in PMID 35454122. The interaction with 14-3-3 proteins that is driven by phosphorylation of -arrestins was first demonstrated by the Leon group in PMID 22249293).

      Lines 129-132 - Here again the Leon reference that helps demonstrate the 14-3-3 inhibition of Rod1 is lacking (PMID 22249293).

      Lines 130-132 - Please include references for the statement that dephosphorylation activates -arrestin activity. There are no citations on this statement and there are many to choose from and I would urge the authors to cite the primary literature on these points.

      These are just a few examples from the Introduction, but the Discussion is similarly wrought with issues in referencing and framing the experimental results within the context of the larger field, including what is known about Rod1/Rog3 regulation in S. cerevisiae. For example, the Llopis-Torregrosa et al reference and statement on lines 508-510 is incorrect. There are other phosphorylation sites defined in the C-terminus of Rod1, as described in Alvaro et al. PMID: 26920760.

      Minor Comments

      Clarification needed - Lines 107-121 - The relationship between the S. pombe arrestins and those in other organisms is somewhat unclear. Frist, all the arrestins in humans and S. cerevisiae can be sorted into the alpha, beta and Vps26 classes. However, the authors indicate that the S. pombe genome has 11 arrestin-like proteins but only 4 of these are -arrestins. What classes do the other 7 arrestins belong to? It would be appreciated if this point was clarified. Next, for the 4 -arrestins identified in S. pombe the authors indicate that Aly3 is the homolog of Rod1/Art4 and Rog3/Art7 from S. cerevisiae. What is the relationship of Rod1 in S. pombe to Rod1 in S. cerevisiae? Are these also homologs? You can see how the nomenclature is confusing and, given the functional overlap of S. cerevisiae Rod1/Rog3 proteins it is important to know if Aly3 is the only version of these -arrestins or if there is an additional counterpart in S. pombe.

      This point becomes somewhat more confusing when on lines 134-136 the authors talk about Arn1/Any1 as an arrestin related protein in S. pombe yet this protein was not included on the list of -arrestins in the preceding section. What class of arrestin is this protein?

      Alpha-arrestin homology - On lines 127-129 the authors indicate that TXNIP is the mammalian homolog of Aly3. To my knowledge, there are no evolutionary analyses that can draw these lines of homology between the -arrestins in humans and those in yeasts. It would be appreciated if the authors could cite the work that leads to this conclusion or revise the sentence to more accurately reflect what is known on this topic. It certainly appears that, given their functional overlap in regulating glucose transporters, Txnip and Rod1/Rog3 in humans and S. cerevisiae are functionally connected. I urge the authors to use more caution when describing this protein family.

      Text editing - The text could use editing as there are awkward and grammatically incorrect sentences in several places. Here are a few examples to help the authors:

      Lines 57-60 - the protein is not expressed over the entire cell surface, but is localized to the entire cell surface.

      Lines 80-83 - this sentence is very confusing

      Line 86 - Is there more than one gene encoding Aly3 in S. pombe?

      Line 88, 109, - these sentences need to start with a capitol so either capitalize the A in arrestin or write out Alpha with a capitol A.

      Lines 145-148 - unclear as written

      Line 224 - why are these amino acids being referred to as hydroxylated? Perhaps hydroxyl-containing amino acids or 18 amino acids with hydroxyl side chains would be better choices?

      Line 300 - very confusing sentence structure

      And elsewhere....

      Significance

      The authors provide some information as to the residues needed in the Aly3 C-tail for Ght5 trafficking in S. Pombe. These results are not places in the context of similar phosphor-regulatory work done for a-arrestins in S. cerevisiae, and this is needed for appreciation of the significance of the study.

      Overall, it appears that the model put forth is very similar to the one already proposed in S. cerevisiae where phosphorylation impedes a-arrestin-mediated trafficking of glucose transporters. It is interesting to see this similarity hold in S. Pombe, but it does not dramatically alter our appreciation of a-arrestin biology.

      The significance of the findings are somewhat underscored by the fact that very little quantification of data are presented, making the rigor of the work difficult to assess.

      PeerReviewed
    3. EMBOpress 20 Jun 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary/background.

      This paper focuses on the regulation of endocytosis of the hexose transporter, Ght5, in S. pombe by nutrient limitation through the arrestin-like protein Aly3. Ght5 is induced when glucose is limiting and is required for growth and proliferation in these conditions. ght5+ encodes the only high-affinity glc transporter from fission yeast. ght5+ is induced in low glucose conditions at the transcriptional level and is translocated to the plasma membrane to allow glc import. Ght5 is targeted to the vacuole in conditions of N limitation. Mutations in the TORC2 pathway lead to the same process, thus preventing growth on low glucose medium, as shown in the gad8ts mutant, mutated for the Gad8 kinase acting downstream of TORC2. Previously, the authors demonstrated that the vacuolar delivery of Ght5 in the gad8ts mutant is suppressed by mutation of the arrestin-like protein Aly3. Arrestin-like proteins are in charge of recognising and ubiquitinating plasma membrane proteins to direct their vacuolar targeting by the endocytosis pathway. This suggested that Aly3 is hyperactive in TORC2 mutants, and accordingly, Ght5 ubiquitination was increased in gad8ts.

      Overall statement

      This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments below.

      Major statements and criticism.

      • Fig 1. Based on the hypothesis that TORC2-mediated phosphorylation regulate Ght5 endocytosis, the authors first considered a possible phosphorylation of Ght5. They mutagenised 11 possible phosphorylation sites on the Ct of Ght5, but none affected the growth on low glucose in the absence of thiamine, suggesting that they don't contribute to the observed TORC2-mediated regulation. However, I disagree with the statement that "phosphorylation of Ght5 is dispensable for cell proliferation in low glucose", given that the authors do not show 1- that Ght5 is phosphorylated and 2-that this is abolished by these mutations. They should either provide data on this or tone down and say that these residues are not involved in the regulation, without implying phosphorylation which is not proven. In the presence of Thiamine (Supp fig 1), it seems that the ST/A mutant grows better in low glucose, and this is not explained nor commented. Since the transporter is not expressed, could the authors provide an explanation to this? If the promoter is leaky and some ght5-ST/A is expressed, it may be more stable and allow better growth than the WT, which would tend to indicate that impairing phosphorylation prevents endocytosis (which is classical for many transporters, see the body of work on CK1-mediated phosphorylation of transporters). Have the authors tried to decrease glc concentration lower than 0.14% in the absence of thiamine to see if this also true when the transporters is strongly expressed? (OPTIONAL)
      • Fig 2. The authors then follow the hypothesis that TORC2 exerts its Ght5-dependent regulation through the phosphorylation of Aly3. They mutagenised 18 possible phosphorylation sites on Aly3. This led to a strong defect in growth in low-glc medium. Mutation of the possible Gad8 site (S460) did not recapitulate this phenotype, suggesting that it is not sufficient, however, mutations of 4 ST residues in a CT cluster (582-586) mimicked the full 18ST/A mutation, suggesting these are the important residues for Ght5 endocytosis.
      • Fig 3A. Further dissection did not allow to pinpoint this regulation to a specific residue, beyond the dispensability of the T586 residue. Fig 3B. The authors look at the effects of mutation of Aly3 on these sites at the protein level. They had to develop an antibody because HA-epitope tagging did not lead to a functional protein (Supp fig 2). Whereas I agree that the mutations causing a phenotype lead to a change in the migration pattern, I disagree with the statement that "This observation indicated that slower migrating bands were phosphorylated species of Aly3" (p.9 l.271). First, lack of phosphorylation usually causes a slower mobility on gel, which is not clear to spot here. Second, a smear appears on top of the mutated proteins (eg. 4th Ala) which is possibly caused by another modification. There are many precedents in the literature about arrestins being ubiquitinated when they are not phosphorylated (see the work on Bul1, Rod1, Csr2 in baker's yeast from various labs). My gut feeling is that lack of phosphorylation unleashes Aly3 ubiquitination leading to change in pattern. All in all, it is impossible to state about the phosphorylation of a protein without addressing its phosphorylation properly by phosphatase treatment + change in migration, or MS/MS. Thus, whereas the data looks promising, this hypothesis that Aly3 is phosphorylated at the indicated sites is not properly demonstrated.
      • Fig 4. The authors now look at the functional consequences of these mutations on ALy3 on Ght5 localisation. The data clearly shows that mutation of the 4 identified S/T residues (Aly3-4th A) causes aberrant localisation of the transporter to the vacuole, likely to cause the observed growth defect on low glucose. There is a nice correlation between the vacuolar localisation and growth in low-glucose for the various aly3 mutants. (A final proof could be to express this in the context of an endocytic mutant, which should restore membrane localisation and suppress the aly3-4thA phenotype - OPTIONAL). However, I still disagree with the statement that "These results indicate that phosphorylation of Aly3 at the C-terminal 582nd, 584th, and/or 585th serine residues is required for cell-surface localization of Ght5." given that phosphorylation was not properly demonstrated.
      • Fig 5. Here, the authors question the role of Aly3 mutations on Ght5 ubiquitination. They immunoprecipitate Ght5 and address its ubiquitination status in various Aly3 mutants. The data is encouraging for a role in Aly3 phosphorylation (?) in the negative control of Ght5 ubiquitination. My main problem with this experiment is that it seems that Ght5 immunoprecipitations were made in non-denaturing conditions, which leads to the question of what is the anti-ubiquitin revealing here (Ght5 or a co-immunoprecipitated protein, for example Aly3 itself, or the Pub ligases, or an unknown protein). It seems that this protocol was previously used in their previous paper, but I stand by my conclusion that ubiquitination of a given protein can only be looked in denaturing conditions. The experiments should be repeated in buffers classical for the study of protein ubiquitination to be able to conclude unambiguously that we are looking at Ght5 ubiquitination itself, especially in the absence of a non-ubiquitinable form of Ght5 as a negative control. Could the authors comment on the fact that S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination?
      • Fig 6. The authors want to document the model whereby Aly3 may interact with some of the Nedd4 ligases (Pub1/2/3) to mediate its Ght5-ubiquitination function. They actually use the Aly3-4thA mutant, it should have been better with the WT protein. But the results indicate a clear interaction with at least Pub1 and Pub3. By the way, are the Pub1/2/3 fusions functional? Nedd4 proteins are notoriously affected in their function by C-terminal tagging and are usually tagged at their N-terminus (See Dunn et al. J Cell Biol 2004).
      • Fig 7. The authors want to provide genetic interaction between the Pub ligases and the growth defects in low glc due to alterations in Ght5 trafficking. It is unclear how the gad8ts pub1∆ mutant was generated since it doesn't seem to grow on regular glc concentration (Supp fig 5), could the authors provide some information about this? It is also not clear whether it can be stated thatches mutant is "more sensitive" to glc depletion because of the low level of growth to begin with (even at 3%). Altogether, the data show that deletion of pub3+ is able to suppress the growth defect of the gad8ts mutant on low glc medium, suggesting it is the relevant ligase for Ght5 endocytosis. This is confirmed by microscopy observations of Ght5 localisation. However, I would again tone down the main conclusion, which I feel is far-reaching: "Combined with physical interaction data, these results strongly suggest that Aly3 recruits Pub3, but not Pub2, for ubiquitination of Ght5." Work on Rsp5 in baker's yeast has shown that Rsp5 function goes beyond cargo ubiquitination, including ubiquitination of arrestins (which is often required for their function as mentioned in the introduction) or other endocytic proteins (epsins, amphyphysin etc). I agree that the data are compatible with this model but there are other possible explanations. Anything that would block endocytosis would supposedly suppress the gad8ts phenotype.

      Discussion

      Some analogy with the regulation of the Bul arrestins by TORC1/Npr1 and PP2A/Sit4 could be mentioned (Mehri et al. 2012), at the discretion of the authors. The possibility that phosphorylation may neutralise a basic patch on Aly3 Ct, possibly involved in electrostatic interactions with Ght5 is very interesting. Regarding the effect of the mutations on Aly3 localisation (p.15 l.498), did the authors tag Aly3 with GFP? There are examples where proteins tagged with HA are not functional whereas tagging with GFP does not alter their function (eg. Rod1, Laussel et al. 2022) - and here Supp Fig 2 only relates to HA-tagging. Proof of a change in Aly3 localisation upon mutation would definitely be a plus (OPTIONAL).

      Minor comments.

      Introduction:

      • I believe the text corresponding to the work on TXNIP is incorrect (p.5 l.127). TXNIP is degraded after its phosphorylation, not "rectracted" from the surface.
      • For the sake of completion, the authors could add other references concerning the regulation of Rod1 in budding yeast such as Becuwe et al. 2012 J Cell Biol and O'Donnell et al. 2015 Mol Cell Biol, in addition to Llopis-Torregrosa et al. 2016.
      • Other examples of the requirement for arrestin ubiquitination beyond Art1 (p.5 l.136-137) are listed in the ref cited: Kahlhofer et al. 2021.

      Figures: In general, I think it would be clearer if the authors showed on the figures that the background strain in which the XXX gene is added (or its mutant forms) is a xxx∆ strain.

      Referees cross-commenting

      Cross review of Reviewer 1

      • I don't believe that the authors "define a set of redundant c-terminal phosphorylation sites in Aly3", because phosphorylation is not proven.
      • I thinks the points raised for Fig 3B are valid but the authors should focus on making their story conclusive before expanding to other data (except for the explanation of the smear, see my review). Also, I don't think 2NBDG actually works to measure Glc uptake.
      • same for Fig 6 - not sure the interaction site mapping between Aly3 and Pubs would bring much value since there are more urgent things to do to make the story solid.

      Cros review of Reviewer 3 - we have many overlaps, so briefly :

      • I agree that the bibliography is incomplete (mentioned in my review)
      • I agree that there is no demonstration of the phospho-status of Aly3, and it is a problem
      • I agree that the results can be better quantified, esp. in the light of the points raised by this referee concerning the variability of expression of ST18A

      Other specific comments :

      • I agree that the statement that dephosphorylation activates alpha-arresting should be toned down - this was observed in several instances but there are examples of arrestin-mediated endocytosis which does not require their prior dephosphorylation.
      • I fully agree that efforts could be made regarding the classification/nomenclature of arrestins in S. pombe, this had escaped my attention

      Significance

      strengths and limitations

      This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins in S. pombe. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand, including the discovery of Aly3 as the main arrestin for this regulation, and a signalling pathway (TORC2/Gad8) acting upstream. The main question is now to understand at the mechanistic level how TORC2 signaling impinges on the regulation of this arrestin.

      Overall, the authors nicely demonstrate that C-terminal Ser/Thr residues are crucial for the function of Aly3 in Ght5 endocytosis. They propose a model whereby Aly3 phosphorylation by an unknownn kinase inhibits its function on Ght5 ubiquitination, which would favour its endocytosis. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments above.

      Advance

      This study, if completed carefully, would provide among the first examples of mapping of phosphorylation sites on arrestins, which are usually phosphorylated at many sites and are thus difficult to study. Few studies went down to this level in this respect (see Ivshov et al. eLife 2020). There are no changes in paradigms or new conceptual insights, but this work is a nice example of the conservation of these regulatory mechanisms.

      Audience

      Should be of interest for people studying basic research in the field of cell biology, signalling pathways, transporter regulation by physiology. Reviewer background is on the regulation of transporter endocytosis by signalling pathways and arrestin-like proteins.

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    4. EMBOpress 20 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary: The manuscript by Yusuke Toyoda and co-workers describes that the phosphorylation of the a-arrestin Aly3 downstream of TORC2 and GAD8 (AKT) negatively regulates endocytosis of the hexose transporter Ght5 in S.pombe under glucose limiting growth conditions.

      To arrive at these conclusions, the researchers define a set of redundant c-terminal phosphorylation sites in Aly3 that are downstream by GAD8. Phosphorylation of these sites reduces Ght5 ubiquitination and endocytosis. For ubiquitination, Aly3 interacts with the ubiquitin ligases Pub1/3.

      Major points:

      Figure 3B: it would be interesting to compare Aly3 migration pattern (and hence potential phosphorylation) under glucose replete or limiting growth conditions. Can the authors provide direct evidence that Aly3 phosphorylation changes in response to glucose availability? Also please explain the 'smear' in lanes aly3(4th Ala), aly3(4th Ala, A584S), aly3(4th Ala, A586T).

      Figure 4: Ght5 localization should be analyzed + / - thiamine and in media with different glucose levels. Also, a co-localization with a vacuolar marker (FM4-64) would be nice (but not necessary). Ideally, the authors should add WB analysis of Ght5 turnover to complement the imaging data. Also, would it be possible to measure directly the effects on glucose uptake (using eg: 2-NBDG).

      Figure 5: Given the localization of Ght5 shown in Figure 4, I'm surprised that it is possible in to detect full length Ght5, and its ubiquitination in the phospho-mutants of Aly3. I expected that the majority of Ght5 would be constitutively degraded, and that one would need to prevent endocytosis and/or vacuolar degradation to detect full length Ght5 and ubiquitination. Please explain the discrepancy. Also it seems that the quantification in B was performed on a single experiment.

      Figure 6: Which PPxY motif of Aly3 is used for interaction with Pub1/3 and does their interaction depend on (de)phosphorylation?

      Significance

      The results are well presented and clear cut (with few exceptions, please see major points). They provide further evidence that metabolic cues instruct the phosphorylation of a-arrestins. Phosphorylation then negatively regulates a-arrestin function in selective endocytosis and is essential to adjust nutrient uptake across the plasma membrane to the given biological context.

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    TPR is required for cytoplasmic chromatin fragment formation during senescence
    4
    1. EMBOpress 18 Jun 2024

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      Reply to the reviewers

      Reviewer #1

      i) "Enhancers dependent on TPR during senescence are enriched for binding sites of inflammatory transcription factors". *Proximity to genes does not confirm an enhancer role for that gene, although Tasdemir et al., 2016 suggested this. At that time, HI-C and Hi-CHiP techniques were not well-established. Nowadays, without combining HI-C and H3K27ac ChIP, Hi-ChIP alone cannot definitively identify actual enhancer regions. If we repeatedly use the Tasdemir et al., 2016 map, we risk incorrect mapping of enhancers of SASP. The authors should either use other public Hi-C databases to map the enhancer of SASP or temper their conclusions about enhancers. Otherwise, this could set a precedent for the SASP enhancer region that might not be entirely accurate. *

      The enhancer mapping for SASP is outdated, as advancements in Hi-C have significantly developed this area. Therefore, the claimed enhancers of SASP may not be accurate.

      __Response: __We agree with the reviewer that enhancers are not easy to define, or to pair with their target gene(s). Indeed, we would argue that even combined HI-C and H3K27ac does not define enhancers or enhancer-gene pairs and that the gold-standard evidence for an enhancer is genetics – does its deletion/mutation abrogate gene activation. We would also point out that we did not actually use the Tasdemir data to call enhancers. In response to the reviewer’s comment, we will temper our terminology and now refer to our inter-and intra-genic ATAC-seq peaks only as “putative enhancers”.

      ii) “Many of these include putative enhancers located close to key SASP genes, such as IL1B and IL8 (Figure 1D).” I have the same concern as mentioned above (i). However, I am interested in knowing the other key SASP genes where DNA is accessible near the genes. A supplementary table listing key SASP genes along with their distances to the TSS and affected by TPR knock-down would be helpful.

      __Response: __We thank the reviewer for this suggestion. We will provide tables listing the TPR dependent, senescent specific ATAC-seq peaks that are close to genes associated with the ‘positive regulation of inflammatory response’, ‘cytokine activity’ and ‘cytokine receptor binding’ gene ontology terms which were significant in the GREAT analysis, and which includes many SASP genes. We will also provide distances of these regions from the associated genes.

      iii) "As we previously reported, knockdown of TPR (siTPR) in RAS cells blocks SAHF formation, but it also results in reduced nuclear localisation (decreased nucleocytoplasmic ratio) of NF-κB, consistent with decreased NF-κB activation (Figure 2A and B, Figure S2A)." TPR is required for CCF, SASP, and SAHF. The relationship between CCF and SASP is well established, but the relationship between SAHF and CCF/SASP remains elusive. Both SAHF and CCF are enriched with heterochromatin markers, suggesting that CCF might originate from SAHF. However, this has not been confirmed. Do the authors think that SAHF is a prerequisite for CCF in the OIS model, or is it an independent event?

      Response: __We agree with the reviewer that CCFs likely originate from SAHF. Whilst we cannot definitively prove thisin our ER-Ras OIS model, in the revised manuscript we intend to further investigate the relationship between SAHF and CCF by knocking down HMGA1 during RAS-induced senescence. Like TPR, HMGA1 depletion is known to lead to loss of SAHF (Narita et al., Cell, 2006) but, unlike TPR, HMGA1 is a chromatin protein enriched on heterochromatin itself. We will assess whether loss of HMGA1 also abrogates CCF formation.__

      iv) The authors suggested that "it is plausible that the decrease in CCFs produced during the early phases of OIS upon TPR knockdown may be caused by an increase in the stability of the nuclear periphery due to the heterochromatin that remains there when SAHF are not formed." I do not completely agree with this explanation because CCF starts forming at day 3-4 but culminates at later time points. According to Figure 5A, only 5-6% of cells are positive for CCFs on day 5. What happens on day 8? By day 8, the percentage of CCF-positive cells could be 20-25%, or the number of CCFs per cell might be 0.2-0.3. If TPR is not required for CCF formation at this stage, then linking CCF to SASP at day 8 becomes critical. This suggests that another mechanism might be driving SASP expression and that TPR could be regulating downstream signaling of CCF. It is possible that changes in nuclear pore density affect the localization of cGAS from the nucleus to the cytoplasm.

      Response: __In our hands and using this IMR90 ER-RAS system, CCF formation decreases later in senescence (d8 - only 2% of cells) hence our focus on early timepoints after oncogenic RAS activation. At later timepoints, cGAS activation is also mediated by retrotransposons (de Cecco et al., Nature, 2019; Liu et al., Cell, 2023), as well as leakage of mitochondrial DNA (Victorelli et al., Nature, 2023; Chen et al., Nat. Comms, 2024), and so it is difficult to disentangle the net contribution of these three inputs.__

      v) Additionally, the authors did not address what happens in the later stages of CCF formation in the absence of TPR. If TPR is not required for CCF formation at later stages, it fails to explain the downstream processes at these time points adequately. This suggests that TPR may also have another mechanism of SASP regulation independent of CCF formation.

      __Response: __In our cellular system CCFs precede the SASP - CCFs are already present at day 3 but SASP factors are not secreted until day 5. However, CCFs are not necessarily required for maintenance of the SASP. Once initiated the SASP is maintained by cytokine feedback loops.

      …………

      Reviewer #2:

      1. The claim that TPR knockdown does not affect NFkappaB nuclear translocation indeed stands, but it would be nice if the authors also compared data across conditions in Fig. 2F, i.e. siCTRL+Ras CM versus siTPR+Ras CM in RAS cells and provided a p-value as it seems to me that there is some dampening of translocation intensity, which is clearly not the case for STOP cells. The authors focus on this for d3 and d5, but it seems to be also the case for later time points.

      __Response: __As basal NF-κB translocation is lower in RAS cells on TPR knockdown, we would expect a dampening in NF-κB translocation between siCTRL+RAS CM and siTPR+Ras CM regardless of whether there is a transportation defect. Consistent with this, the p-value for this comparison is significant, but we did not show it because it is not important in considering whether NF-κB nuclear translocation is impeded by TPR knockdown, which is the focus here. We will add a table with median nuclear:cytoplasmic NF-κB ratios and 95% confidence intervals to make the changes in basal level (treatment with STOP CM) clearer.

      Also, a comment based on literature or from the authors previous work on TPR, on the extent to which the structural integrity of the nuclear basket is at all affected upon TPR depletion would be helpful for data interpretation.

      __Response: __In the revised manuscript we will refer to the literature showing that TPR is the final component added to the nuclear pore and that its absence does not affect localisation of NUP153 to the nuclear basket (Hase and Cordes., Mol. Biol. Cell 2003; Aksenova et al., Nat Comms, 2020).

      Magnification of representative cells per each condition in Fig. 2E would be welcome.

      __Response: __We will provide a revised figure 2E with the magnifications as requested.

      Regarding the data in Figs 3 and S3: I am a bit confused about how the obviously decreased NFkappaB nuclear signal (e.g., in Fig. 3D) does not translate into a skewed N/C ratio (e.g., in Fig. 3C)? The western blots indicate that overall NFkappaB levels remain essentially unchanged? Am I missing something?

      Response: __As stated in the Methods section, we used a 50-pixel expansion of the detected nuclear area as our cytoplasmic area in the analysis (see image below). This was because we found detecting and segmenting the whole cytoplasmic area in the NF-κB channel to be unreliable. At day 3 and 5, the decrease in NF-κB nuclear signal in RAS cells on TPR knockdown was accompanied by a decrease in signal in the portion of the cytoplasm closest to the nucleus. This led to no change in the nuclear:cytoplasmic ratio. We believe the redistribution of NF-κB closer to the nucleus in the RAS siCTRL sample indicates early activation and will make this clearer in the revised text. We will also quantify the NF-κB western blots (see point 5), to help clarification of this issue.____ __

      Also, along these lines, d8 western blots seem to portray an overall drop in NFkappaB levels. Is this indeed so? Can the authors maybe quantify their blots' replicates and provide a box plot and statistical testing?

      Response: __We will provide quantification for the NF-κB western blots, though box plots would not be appropriate as we only have two replicates.__

      Regarding the ATAC-seq data from d3, I think it could be mined a bit more. For example, compare to d8 (which the authors have apparently done, but don't present in detail) and discuss which are these early regions that also become accessible by d3 and what kind of genes and motifs are associated with them. Moreover, the focus in Fig. S3E is on ATAC sites shared with d8; how about d3-specific ones? How many of these are there (if any) and how might they be affected?

      __Response: __As shown in Table S2, TPR knockdown did not cause any changes in chromatin accessibility at day 3, so there are no day 3 specific TPR dependent peaks. We will edit the text to make this clearer. We will carry out motif analysis and GREAT analysis on the day 3 peaks that become accessible in RAS cells but are not accessible in STOP (RAS-specific peaks).

      I trust that the authors quantified their STING blots for the conclusions they present, but since it is difficult to assess these confidently by eye, again, some quantification plots would be welcome in Figs 4C,D and S4D,E.

      __Response: __We will provide quantification for the STING western blots.

      As controls for Fig. 5, it would be interesting to see if active histone readouts also mark CCFs in this system.

      __Response: __Ivanov et al., J. Cell Biol., 2013 showed the absence of H3K9 acetylation from chromatin in CCFs. Further exploration of the types of chromatin/sequences in CCFs is outside the scope of our current manuscript.

      *The POM121 channel in Fig. 5C appears to have some small signal foci in the cytoplasm; could these be small CCFs? More generally, the authors focus on these large blobs that only appear in

      __Response: __The small signal foci the reviewer is highlighting are background from the POM121 antibody staining rather than CCFs – they do not show DAPI staining, and similar foci are evident in non-senescent cells where CCFs are generally not present. Our unpublished data (see response to Reviewer 1, point iv) from day 8 cells shows that only ~2% of senescent cells are positive for CCF regardless of TPR knockdown, which is a similar number to that observed in non-senescent cells at earlier timepoints. Thus, in our hands CCF formation occurs earlier, triggering the SASP, rather than at day 8 when the SASP is already established and reinforced through positive feedback cytokine signalling.

      I wonder if there is a simple experiment the authors could do to test if this mechanism is only linked to senescence, specifically oncogene-induced senescence? I don't think this is needed to support the conclusions drawn here, but it could significantly broaden the scope of their discovery of, for example, this was true in other senescence models or during proinflammatory activation in general?

      __Response: __These are interesting suggestions, but setting up, characterising and quantifying other senescence models will take a substantial amount of time that would be outside the scope of our current manuscript.

      ………….

      Reviewer #3

      1. The study uses a single cell strain IMR90 undergoing a single form of senescence, induced by activated Ras. To show the generalizability of the finding, the authors are advised to inhibit TPR in other forms of senescence in addition to IMR90. For example, IR or etoposide induces greater amount of CCF than in OIS of IMR90. BJ, MEFs, and ARPE-19 senescence also show prominent CCF.

      __Response: __These are interesting suggestions, but as we responded to reviewer 2, setting up, characterising and quantifying other senescence models will take a substantial amount of time that would be outside the scope of our current manuscript.

      To convincing show the CCF pathway is involved, the authors need to measure the activity of cGAS-STING pathway. Including cGAMP ELISA will be informative.

      __Response: __We thank the reviewer for this suggestion, and we will try to include this assay in our revised manuscript.

      The authors used conditioned media to show that TPR KD does not directly affect NFkB nuclear translocation. While this is helpful, conditions other than senescence will be more direct. For example, TNFa treatment or poly I:C transfection induces efficient NFkB nuclear translocation in IMR90 cells.

      __Response: __This experiment (Fig. 2EF) was designed to simply show that knocking down TPR does not impair the ability of activated NFkB to enter the nucleus, it is not about senescence per se. Indeed, this is why we included the addition of SASP (RAS) conditioned media to non-senescence STOP cells in Fig. 2. We do not think investigating other methods of activating NFkB would add more to the question of whether TPR loss abrogates NFkB nuclear import.

      Fig. 4C and Fig. S4D are identical.

      Response: Though these STING immunoblots look similar; in fact they are not identical. Below we attach the raw original image in which both biological replicates (Fig 4C and S4D) for Day 3 were run on the same gel as proof of this claim.

      Figure legend for Fig. S4F is mislabeled.

      __Response: __We will correct this.

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    2. EMBOpress 18 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Bartlett et al reported that knockdown of TPR inhibits CCF and NFkB during oncogene-induced senescence in IMR90 cells. The manuscript is well-written, and the results are clear and convincing. I have the following suggestions.

      1. The study uses a single cell strain IMR90 undergoing a single form of senescence, induced by activated Ras. To show the generalizability of the finding, the authors are advised to inhibit TPR in other forms of senescence in addition to IMR90. For example, IR or etoposide induces greater amount of CCF than in OIS of IMR90. BJ, MEFs, and ARPE-19 senescence also show prominent CCF.
      2. To convincing show the CCF pathway is involved, the authors need to measure the activity of cGAS-STING pathway. Including cGAMP ELISA will be informative.
      3. The authors used conditioned media to show that TPR KD does not directly affect NFkB nuclear translocation. While this is helpful, conditions other than senescence will be more direct. For example, TNFa treatment or poly I:C transfection induces efficient NFkB nuclear translocation in IMR90 cells.

      Minor:

      1. Fig. 4C and Fig. S4D are identical.
      2. Figure legend for Fig. S4F is mislabeled.

      Significance

      This study builds on the group's prior publication that knockdown of TPR inhibits SAHF and SASP. The current study finds that the underlying mechanism is via CCF-STING-NFkB pathway. Overall, the study broadens our understanding of CCF and SASP in senescence, and will be of general interest to the senescence field.

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    3. EMBOpress 18 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript by Bartlett et al. revisits the role of the nuclear pore component, TPR, in OIS to uncover its contribution to NFkappaB activation magnitude via the control of chromatin fragment release from the senescent nucleus. The flow of the manuscript is very good and the conclusions are supported by clear experimental evidence. This is an overall mature manuscript, and I offer below some comments that might help the authors streamline their message even more:

      • The claim that TPR knockdown does not affect NFkappaB nuclear translocation indeed stands, but it would be nice if the authors also compared data across conditions in Fig. 2F, i.e. siCTRL+Ras CM versus siTPR+Ras CM in RAS cells and provided a p-value as it seems to me that there is some dampening of translocation intensity, which is clearly not the case for STOP cells. The authors focus on this for d3 and d5, but it seems to be also the case for later time points.
      • Also, a comment based on literature or from the authors previous work on TPR, on the extent to which the structural integrity of the nuclear basket is at all affected upon TPR depletion would be helpful for data interpretation.
      • Magnification of representative cells per each condition in Fig. 2E would be welcome.
      • Regarding the data in Figs 3 and S3: I am a bit confused about how the obviously decreased NFkappaB nuclear signal (e.g., in Fig. 3D) does not translate into a skewed N/C ratio (e.g., in Fig. 3C)? The western blots indicate that overall NFkappaB levels remain essentially unchanged? Am I missing something?
      • Also, along these lines, d8 western blots seem to portray an overall drop in NFkappaB levels. Is this indeed so? Can the authors maybe quantify their blots' replicates and provide a box plot and statistical testing?
      • Regarding the ATAC-seq data from d3, I think it could be mined a bit more. For example, compare to d8 (which the authors have apparently done, but don't present in detail) and discuss which are these early regions that also become accessible by d3 and what kind of genes and motifs are associated with them. Moreover, the focus in Fig. S3E is on ATAC sites shared with d8; how about d3-specific ones? How many of these are there (if any) and how might they be affected?
      • I trust that the authors quantified their STING blots for the conclusions they present, but since it is difficult to assess these confidently by eye, again, some quantification plots would be welcome in Figs 4C,D and S4D,E.
      • As controls for Fig. 5, it would be interesting to see if active histone readouts also mark CCFs in this system.
      • The POM121 channel in Fig. 5C appears to have some small signal foci in the cytoplasm; could these be small CCFs? More generally, the authors focus on these large blobs that only appear in <6% of cells in d3 and d5. Does this increase by d8? What is the effect of TPR knockdown on CCF numbers at that later time point?
      • I wonder if there is a simple experiment the authors could do to test if this mechanism is only linked to senescence, specifically oncogene-induced senescence? I don't think this is needed to support the conclusions drawn here, but it could significantly broaden the scope of their discovery of, for example, this was true in other senescence models or during proinflammatory activation in general?

      I typically disclose my identity to the authors: A. Papantonis

      Significance

      This is a very clearly written and well-controlled study that addresses a gap in knowledge from the previous work on TPR in senescence. It also brings about a perhaps unexpected effect of a nuclear pore component on NFkappaB signaling that might not necessarily be senescence-specific. As such, I think that the study would be of interest to both the senescence community and to researchers studying inflammatory responses, especially those driven by TNFalpha or IL1A/B.

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    4. EMBOpress 18 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      DNA damage triggers senescence, inducing chromatin reorganization and SASP activation. The authors previously demonstrated that the TPR nucleoprotein at nuclear pores is crucial for both SAHF formation and SASP activation during senescence. Here they also showed that TPR is required for the formation of cytoplasmic chromatin fragments (CCF), which activate cGAS-STING-TBK1-NF-kB signaling to express SASP. While the mechanistic regulation of CCF formation by TPR remains unclear, their study provides compelling evidence of downstream processes involving CCF. This study offers new insights into CCF formation, suggesting a promising direction for further research. I endorse the manuscript; however, there are several concerns that need addressing before acceptance.

      i) "Enhancers dependent on TPR during senescence are enriched for binding sites of inflammatory transcription factors".

      Proximity to genes does not confirm an enhancer role for that gene, although Tasdemir et al., 2016 suggested this. At that time, HI-C and Hi-CHiP techniques were not well-established. Nowadays, without combining HI-C and H3K27ac ChIP, Hi-ChIP alone cannot definitively identify actual enhancer regions. If we repeatedly use the Tasdemir et al., 2016 map, we risk incorrect mapping of enhancers of SASP. The authors should either use other public Hi-C databases to map the enhancer of SASP or temper their conclusions about enhancers. Otherwise, this could set a precedent for the SASP enhancer region that might not be entirely accurate.

      ii) Many of these include putative enhancers located close to key SASP genes, such as IL1B and IL8 (Figure 1D).

      I have the same concern as mentioned earlier about enhancers. However, I am interested in knowing the other key SASP genes where DNA is accessible near the genes. A supplementary table listing key SASP genes along with their distances to the TSS and affected by TPR knock-down would be helpful.

      iii) "As we previously reported, knockdown of TPR (siTPR) in RAS cells blocks SAHF formation, but it also results in reduced nuclear localisation (decreased nucleocytoplasmic ratio) of NF-κB, consistent with decreased NF-κB activation (Figure 2A and B, Figure S2A)." TPR is required for CCF, SASP, and SAHF. The relationship between CCF and SASP is well established, but the relationship between SAHF and CCF/SASP remains elusive. Both SAHF and CCF are enriched with heterochromatin markers, suggesting that CCF might originate from SAHF. However, this has not been confirmed. Do the authors think that SAHF is a prerequisite for CCF in the OIS model, or is it an independent event?

      iv) The authors suggested that "it is plausible that the decrease in CCFs produced during the early phases of OIS upon TPR knockdown may be caused by an increase in the stability of the nuclear periphery due to the heterochromatin that remains there when SAHF are not formed." I do not completely agree with this explanation because CCF starts forming at day 3-4 but culminates at later time points. According to Figure 5A, only 5-6% of cells are positive for CCFs on day 5. What happens on day 8? By day 8, the percentage of CCF-positive cells could be 20-25%, or the number of CCFs per cell might be 0.2-0.3. If TPR is not required for CCF formation at this stage, then linking CCF to SASP at day 8 becomes critical. This suggests that another mechanism might be driving SASP expression and that TPR could be regulating downstream signaling of CCF. It is possible that changes in nuclear pore density affect the localization of cGAS from the nucleus to the cytoplasm.

      Significance

      The authors previously demonstrated that the TPR nucleoprotein at nuclear pores is crucial for both SAHF formation and SASP activation during senescence. Here they also showed that TPR is required for the formation of cytoplasmic chromatin fragments (CCF), which activate cGAS-STING-TBK1-NF-kB signaling to express SASP. While the mechanistic regulation of CCF formation by TPR remains unclear, their study provides compelling evidence of downstream processes involving CCF. This study offers new insights into CCF formation, suggesting a promising direction for further research.

      However, there are some limitations to this study. The enhancer mapping for SASP is outdated, as advancements in Hi-C have significantly developed this area. Therefore, the claimed enhancers of SASP may not be accurate. Additionally, the authors did not address what happens in the later stages of CCF formation in the absence of TPR. If TPR is not required for CCF formation at later stages, it fails to explain the downstream processes at these time points adequately. This suggests that TPR may also have another mechanism of SASP regulation independent of CCF formation.

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    Symmetry breaking and fate divergence during lateral inhibition in Drosophila
    4
    1. EMBOpress 18 Jun 2024

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      Reply to the reviewers

      *Reviewer #1 *

      1. The authors conclude that RFP-Ac expression is restricted to emerging SOPs and surroundings cells at 18h APF, indicating that Ac is activated later than Sc. Can the authors provide images for RFP-Ac expression at 10h and 16h APF similar to GFP-Sc as shown in their figures. Do the SOPs that contain high levels of both Ac and Sc (as some SOPs have Sc expression but not Ac) undergo fate divergence and SB faster than the SOPs containing higher levels of only Sc?

      We are now showing the expression pattern of GFP-SC and RFP-Ac/GFP-Ac in fixed samples stained also for E-cad at 13h, 16h and 18h APF (Fig 1I-K' and Fig S1E-G'). Ac and Sc were found to be activated around the same time. However, Ac appeared to accumulate at lower levels than Sc prior to SOP selection in the central domain of the ADHN (Fig 1J-K'). We also confirmed that Ac was more strongly expressed in SOPs. Additionally, SOPs appeared to accumulate both Ac and Sc, i.e. SOPs with high levels of GFP-Sc also showed a strong RFP-Ac signal (Fig S1H-H'). Finally, since RFP-Ac was not detectable in living pupae, possibly due to the rapid turn-over of Ac and the slow maturation of RFP, we could not study more precisely the relative dynamics of Ac and Sc. For the same reason, we could not address whether the rate of fate divergence (measured using GFP-Sc) varied with the level of Ac.

      2. It would be interesting to see the spatial and temporal dynamics of Ac and Sc in Notch mutants or even Notch dynamics in Sc and Ac mutants to better understand the progression fate divergence and its effect on lateral inhibition in real time.

      Following the reviewer's suggestion, we examined the expression pattern of NRE-deGFP, a Notch activity reporter, in ac sc double mutant pupae at 16h and 24h APF (Fig S3A-D). This showed that the initial pattern of NRE-deGFP at 16h APF (signal detected in posterior ADHN cells as well as in the ADHN) did not depend on Ac and Sc. By contrast, the second phase of NRE-deGFP expression (in cells of the proneural ADHN domain, around emerging SOPs) was found to depend on the activity of Ac and Sc. Thus, strong Notch activation observed in cells surrounding emerging SOPs was found to depend on the activity of Ac-Sc, presumably because Ac and Sc are required for SOP specification and SOPs produce Delta, serving as the local source to activate Notch (see also our response to reviewer 3, point #6). Thus, since NRE-deGFP was not up-regulated in the proneural ADHN domain of sc10-1 ac3 mutant pupae, a quantitative analysis of the dynamics of NRE-deGFP may not be informative.

      The reviewer also suggested us to study the dynamics of GFP-Sc in Notch mutants. One can easily predict that most Notch mutant cells would accumulate GFP-Sc, as observed in the notum (PMID: 28386027). Therefore, analysis of fate symmetry breaking is unlikely to be useful in that context. Likewise, a FDI analysis would not be relevant. From a technical point of view, live imaging of GFP-Sc would have to be performed in Notch mutant clones. This is because RNAi against Notch (strong 10xUAS-Notch hp2 construct, PMID: 19487563) driven by escargot-Gal4 to knock down Notch in larval histoblasts only led to a partial loss of Notch function (our unpublished data). Generation of Notch mutant clones in the abdomen would require constructing appropriate GFP-Sc Notch FRT recombinant chromosome as well as generating a new FRT GFP-Sc chromosome with an infrared marker (not currently available) to compare the relative dynamics of GFP-Sc in wild-type and mutant cells. In sum, this proposed experiment would take a significant amount of time and is unlikely to shed new light. Given that this experiment is not essential to support the claims of the paper and that it is not clear to us what would be learnt from this experiment, we opted for not performing this experiment.

      Minor comments * 1. In figure 1F and F', the authors mention GFP-Sc is not expressed prior to 14h, however, there is still GFP signal detected in their imaging. Can the authors comment what would be the cause of this GFP signal or was it due to non-specific background signal during their imaging analysis?*

      We thank the referee for raising this issue. Yes, a strong autofluorescence signal was detected prior to the onset of GFP-Sc expression. We provide below the results of our analysis of the autofluorescence signal (Fig R1) relative to the nuclear signal (Fig R2), and how normalization of the signal was used to measure the specific GFP-Sc signal.

      Analysis of the autofluorescence signal over time

      To estimate the autofluorescence signal, we measured the average intensity of the signal acquired in the GFP channel for each frame and plotted these values over time. The results are shown in Fig R1 below:

      *Fig R1: temporal profile of the autofluorescence signal *

      Each measurement corresponds to the average intensity measured in the GFP channel over the entire field at each z-section and for each time point. Mean and SD values of measured are shown over time in black and grey, respectively. Time is in frame number (dt is 2.5 min). The data shown above corresponds to movie 1 (see also Fig 2).

      This plot indicates that the autofluorescence signal was progressively bleached. We therefore excluded from our analysis the first 50 time points when the autofluorescence signal was initially strong. No nuclear GFP-Sc signal was detectable in these first 50 frames in the cells of the central area of the ADHN which are studied here (see Fig 2A', t=1:12, time frame #29).

      While revising the manuscript, we realized that t=0 corresponded to two distinct time points in the first version of our manuscript: it corresponded to the onset of imaging in Fig 2A-D', and to t=2:08 (time frame #51) in all other figures showing data following removal of the first 50 time points. We have now fixed this issue and are presenting all data with t=0 corresponding to the onset of imaging.

      Analysis of the nuclear fluorescence signal over time

      To detect the nuclear GFP-Sc signal, we measured the average intensity of the signal acquired in the GFP channel (raw intensity values corresponding to the sum of the GFP-Sc and autofluorescence signals) in segmented nuclei (in 3D, within the entire z-stack). These values were plotted over time (pink curve in Fig R2 below; the autofluorescence is plotted in black, as in Fig R1, for the sake of comparison). This showed that the intensity of the signal measured in nuclei was initially identical to the mean intensity measured across the entire field of view, indicative of autofluorescence only. A specific increase in signal intensity in nuclei (relative to the entire field of view) was detectable after 2h of imaging (time frame 48 in Fig R1; dt is 2.5 min). Importantly, mean intensity values of the autofluorescence signal appeared to be approximately 10-fold stronger than the mean intensity associated with the nuclear GFP-Sc signal.

      Fig R2: temporal profile of the GFP-Sc signal

      *The plot in pink corresponds to the average intensity in the GFP channel (raw intensity values corresponding to the GFP-Sc and/or autofluorescence signals) per nucleus (within the entire z-stack) for each time point. Mean and SD values measured in each nucleus are shown over time (in pink; these data correspond to movie 1; shown also in Fig 3). This plot (pink) should be compared with the plot shown in Fig R1 (also in black in Fig R2). The intensity difference between the pink and black curves was attributed to the specific GFP-Sc signal. *

      Signal normalization and analysis of the GFP-Sc signal

      In our study, we normalized the GFP-Sc signal by dividing the averaged value measured in each single nucleus (data corresponding to the pink curve in Fig R2) by the mean value of the signal measured at the same time point in the same channel in the entire image stack (data corresponding to the black curve in Fig R1/R2). Given the low intensity of the GFP-Sc signal, and the small number of pixels corresponding to Scute-expressing nuclei over the entire field of view, this value should closely reflect the autofluorescence noise. Thus, the background autofluorescence signal should be close to 1. This was experimentally verified by measuring the normalized intensity values of the PDHN nuclei that did not express Scute: a mean intensity value of 0.96 +/- 0.10 was measured (at time frame #51; see Fig R1 below). In contrast, the normalized GFP-Sc values measured several hours before SB were found to be close to 1.1 (see Fig 3D). Whether these values reflect very low levels of nuclear GFP-Sc that cannot be detected visually or result from imperfect normalization of the signal remain unclear. Given the intensity and non-uniformity of the autofluorescence signal, we cannot exclude the latter. For this reason, we chose to not over-interpret the initial low intensity values of GFP-Sc.

      In the materials and methods, the authors mention that prior to imaging the larvae and pupae are grown at 18, 21 or 25{degree sign}C. Is there a reason why the larvae and pupae are grown at different temperatures for different experiments? Can the authors specify (i.e. in the figure legends) in which experiments different temperatures were used?

      Larvae and pupae were grown at different temperatures for convenience, i.e. to adapt the time interval between staging at 0h APF and mounting for live imaging. Indeed, it is much easier to obtain 10-14h APF pupae by collecting staged pupae at 0h APF the day before and incubating them overnight at lower temperature to slow-down development. However, all live imaging experiments were performed at 23-25{degree sign}C, and we have no reason to think that this prior incubation would affect the process studied here.

      The citations need to have a better format as they show up as each citation within a single bracket which makes it a little hard to read when multiple references are cited in a single sentence. fixed

      In the abstract, the sentence 'Unexpectedly, we observed at low frequency (10%) pairs of cells that are in direct contact at the time of SB'. SB should be replaced with "Symmetry breaking", as it appeared for the first time in the manuscript and should be written out in full. fixed

      Throughout the manuscript there are instances where the abbreviations are written in full with the abbreviation in brackets after they have already been introduced in the introduction which can be changed to just the abbreviation itself. fixed

      In the discussion on page 11, 'our observation...', our needs to be changed to Our. fixed

      7. It would be nice to have arrow heads or dotted lines around the cells or areas on interest in both, all the figures and movies, so that it will be easier to follow the results. The videos have a lot of background due to fragmented apoptotic nuclei, etc. as mentioned by the authors, hence arrow heads or dotted lines would bring viewers focus on the areas of interest.

      fixed (see for instance Fig 1D, Fig 2A, Fig 5B, Fig 7A, Fig S3D, etc...)

      8. It would be helpful to have anterior - posterior axis (i.e. with an arrow) shown on top of all the figures.

      In our earlier version, we indicated that 'In this and all other figures, dorsal is up and anterior is left' in the legend of Fig 1B. We have now moved this sentence at the end of Fig 1 to have it more apparent. Additionally, the AP axis is now clearly indicated in Fig 1C. We believe that it is not necessary to repeat this orientation in all figures.

      Scale bars are missing in all figures, videos, and figure legends. Added

      Only movies 1 and 3 are referenced in the text. All movies are now referenced in the text

      Keeping the colors in the movies and figures consistent and same would be helpful. For example, Movie 2 Histone3.3-mIFP marker is in blue but in figure 3 it is in magenta. fixed (H3.3-mIFP in magenta in this movie, now numbered 3)

      As mentioned above, it would be helpful if the authors have arrow heads or dotted lines around the cells or areas of interest in both the figures and movies for better representation of their data. For example, movie 1 shows a larger area of imaging than shown in figure 2A, which makes it hard to follow the cells of interest in the movie.

      An additional movie corresponding to the SOP shown in Fig 2A is now provided (new movie 2).

      --

      Reviewer #2

      1. Despite "symmetry breaking" being the main focus of the paper, in the Introduction, the authors do not explain what this term means and do not provide any description of this process. This is a critical point that makes understanding of the goals of the paper difficult. Therefore, the authors are encouraged to provide more information and a clear description of this term/phenomenon. We thank the reviewer for this suggestion, we are now stating in the introduction what symmetry breaking means in the context of lateral inhibition: 'To describe and study the process of SOP selection, we studied fate SB. The latter refers to the transition point when one cell, the future SOP, starts to stably accumulate a higher level of GFP-Sc relative to its immediate neighbors.'

      The role of Achaete in the story is not clear. Even though both factors are required for SOP determination, the authors mainly focus on Scute, so it is not very clear what the role of Achaete in this process is, if there is any. As shown in the paper, Achaete is expressed later when heterogeneity is promoting cell fate divergence. Is Achaete maybe contributing to cell heterogeneity/ cell fate divergence?

      We thank the reviewer for raising this point. We now show in Fig S1A-D that abdominal bristles develop in a protein null allele of sc (scM6 ) as well as in an ac mutant corresponding to a 45 kb deletion that removes ac but not sc (PMID: 16216235)). Together with our analysis of sc10-1 ac3 __mutant flies, we can now conclude that __Sc and Ac act redundantly for SOP specification in the pupal abdomen. We have also further studied the expression of Ac relative to Sc and E(spl)HLH-m3 (see our response above to point #1 of reviewer 1). We fully agree with the reviewer that cell-to-cell variations in Ac expression might contribute to proneural heterogeneity and SB. This is now briefly discussed.

      Minor points: * * 1. Symmetry Breaking (SB) should be abbreviated in the Abstract. The authors initially use the full term without abbreviation, and only on page 5, the abbreviation is finally defined; however, it should be introduced much earlier.

      fixed

      The second-to-last sentence in the abstract, "These lateral inhibition defects were correlated via cellular rearrangements," is unclear regarding what defects the authors are referring to.

      This sentence was rewritten: 'Live imaging showed that these patterning defects were corrected via cellular rearrangements associated with global tissue fluidity, not via cell fate change.'

      For clarity, being more specific in the text in regards to description of the figure panels would be beneficial (e.g. page 3 Fig 1C-E); referring to C-E together makes it hard to understand what does each panel shows.

      fixed

      In many instances, the movies are not properly referenced (e.g. on page 5, third row simply states "movies"), making it difficult to discern which movie should be checked. On page 8, when authors refer to movie 3, they likely meant movie 5.

      fixed

      Figure S1 requires some corrections.

      We thank the reviewer for helping us improve the presentation of our results.

      The authors use the short name "scute" initially and then switch to the shortened version "sc'.

      fixed

      Additionally, the nlsRFP (blue) is difficult to see; adjusting the levels or changing colors/showing separate channels may improve visibility.

      The authors mention clone borders, but none are shown. It would greatly help to outline the borders in all figures.

      The ubiquitous nlsRFP marker is now shown in magenta in Fig S1I that now shows only 2 channels to outline the ADHN (white dotted line) and the clones (yellow dotted lines).

      We also outlined the clone borders in Fig 4C,C'.

      Genotypes of the samples should be indicated, and clarification is needed regarding what "n" represents (number of cells, clones, or flies).

      The genotype studied in Fig S1 and Fig 4 (which is the only complex genotype studied here) is now indicated in the Methods section. We have clarified what the different 'n' meant, in Fig 4 (see text) and elsewhere (see legend of Fig S2 for instance).

      What do the arrows in the panel B show?

      Thanks for pointing this out. The arrows in Fig S1I' indicate Cut/Hnt-positive cells (SOPs) within the clones (as now explained in the legend).

      It is also recommended to display important channels as separate black and white images.

      Separate channels are now shown in Fig S1 and S3.

      Additionally, the use of RNAi against GFP instead of RNAi against scute should be justified; using RNAi GFP as the genotype on the graph could be interpreted as a control genotype rather than downregulation of scute.

      A RNAi construct against GFP was used because this construct was known to very efficient and specific. Indeed, a strong knock-down of GFP-Sc was obtained by this approach (see Fig 4C'). We did not test sc RNAi constructs in the context of GFP-Sc. To avoid confusion, we are now indicating Sc downregulation (gfp RNAi) in Fig 4C'.

      In the Figure 2 Legend, the authors use "std" as an abbreviation to define standard deviation. Typically, this is abbreviated as SD.

      fixed

      In Figure 4E, the authors do not explain on why there are points on the x-axis that correspond to a decimal number of cells.

      Since heterogeneity was calculated over a 20 min interval, we likewise calculated the number of neighbors over the same time interval. Thus, the number of neighbors for each SOP corresponds to an averaged value calculated over this time interval. This is now explained in the legend.

      --

      Reviewer #3

      1. First and foremost, the authors should state in the first paragraph of the Results that scGFP is a CRISPR knockin and thus it's the only source of Sc protein in the animals imaged (this is stated only in the Methods section). Thanks for this comment, we agree that this is one of the strengths of our work that we should emphasize. We now state in the results section: 'GFP-Sc is produced from the endogenous locus such that all Sc molecules produced in these pupae are GFP-tagged'

      The magnitude of the Sc increase should be commented on. Based on the intensity and FDI plots in Fig. 3B-E, an increase of 15-17% in the amount of Sc is suggested (the FDI plateaus at 0.08, which gives 1.08/0.92 = 1.17x the level of Sc in the SOP vs the surrounding cells). However, in the stills shown in Fig. 2BCD and in Fig. 3A, the intensity differential between SOPs and neighbors seems at least 100% (ie at least double the intensity, which would yield an FDI of >1/3 =0.33). Why is this high contrast never seen in the quantitative measurements?

      Thanks for asking about the fold change of GFP-Sc levels in SOPs, from SB to its plateau. This fold change can be seen in Fig 3D: the normalized value of GFP-Sc is 1.12 at SB, and 1.26 three hours after SB (when the FDI plateaus), indicative of a 2.2x fold increase of GFP-Sc in SOPs (0.26/0.12= 2.2, following background subtraction; see our detailed response to reviewer #1, minor point 1, about background signal analysis and normalization of the signal). This fold-change value is now indicated in the legend of Fig 3D. Obviously, this fold-change value is highly sensitive to signal normalization. Since the autofluorescence signal was stronger than the GFP-Sc signal (see Fig R2 above) and varied over time (due to bleaching; see Figs R1 and R2 above), we feel that this fold-change value should be taken with a grain of salt.

      From Fig. 2A-D it appears that the ScGFP fluorescence intensity is at the same level or weaker than nearby autofluorescence. Please state (1) how you confirmed that the histoblast nest has lower autofluorescence than the larval epidermis and (2) how you corrected for histoblast nest autofluorescence in your quantifications.

      As detailed above (our response to reviewer #1, minor point 1), the specific GFP-Sc signal is ten-times lower than the autofluorescence signal. We did not compare the autofluorescence signal produce by larval and imaginal cells (but note that larval epidermal cells had a stronger autofluorescence signal; see the yellow dots in Fig 2A). Normalization of the signal to correct for autofluorescence was explained in the Methods (and is also detailed above in our response to reviewer #1, minor point 1).

      The paradoxical result of Fig. S1B should be discussed. On the one hand it is stated that "Ac and Sc specify the fate of the Sensory Organ Precursor cells (SOPs)" (p.2) and on the other S1B shows SOP specification in the absence of Sc. Are the SOPs shown in Fig S1B rare exceptions? Do the authors believe that these rare exceptions are there because of inefficient RNAi (since in comparison with S1A, in the null condition almost no SOPs should be formed)? Or they are the SOPs in RNAi clones as rare as the occasional bristles in S1A?

      We do not see the result of Fig S1B as paradoxical but interpreted this result assuming that Ac and Sc were redundant for SOP determination. We now provide clear genetic evidence in support of this view (see our response above to reviewer #2, point 2). Otherwise, we found that RNAi is efficient (see loss of the GFP signal in clone in Fig. 4C'). In adult males, the density of bristles appeared to be quite normal over clonal patches of gfp RNAi cells (not shown), consistent with Ac being redundant with Sc

      One figure that is not straightforward to interpret is Fig. 4E. It plots ScGFP heterogeneity vs. number of RNAi neighbors. Each point in the plot must be an individual SOP (165 total). Therefore, its neighbors (the x-axis) should take integral (not decimal) values. How can a single SOP have a decimal number of RNAi neighbors, especially since heterogeneity was sampled over a 10min time-window, when not much cell rearrangement can take place? Please explain.

      Since heterogeneity was calculated over a 20 min interval, we likewise calculated the number of neighbors over the same time interval. Thus, the number of neighbors for each SOP corresponds to an averaged value calculated over this time interval. This is now explained in the legend: 'Note that the number of neighbors was likewise calculated over this time interval, and the resulting number of neighbors may not take an integral value.'

      I found the discussion of the Notch reporter dynamics (Fig. 7) confusing in several places. * * (6a) Whereas it's clear that there is plenty of Notch signaling going on before SBN, the authors repeatedly imply that Notch signaling starts after SBN. For example, in the Results (p.9) they state "Thus, this quantitative approach failed to detect a phase of reciprocal Notch signaling during which proneural cluster cells would both send and receive a Delta-Notch signal prior to SOP emergence." The fact that the NRE-deGFP gave a robust signal before the start of the movies clearly means that mutual inhibition was going on for quite some time before SB. In fact, an FDI of 0 for >4h prior to SBN (Fig. 7G) means exactly this: that the level of Notch response among the cluster cells is equivalent ("mutual inhibition" lasts for at least 4h before SBN). (6b) In the first paragraph of this section (p.8) they comment that the pre-existence of Notch signaling is unexpected - why? I interpret it to simply be mutual inhibition (see above). Then they go on to quantitate the average Notch response intensity over the entire posterior ADHN (please define the borders the "posterior" ADHN). I question the informational value of this analysis (averaging over a large region), when Notch signaling is known to have intense local cell-to-cell variability (also evident in the stills shown in Fig. 7A,B,C).

      We apologize for not describing well enough the data shown in Fig 7E, and for not explaining clearly our interpretation of the NRE-deGFP signal.

      While the observation of a strong NRE-deGFP signal indeed indicates that Notch signaling had been active prior to the time of observation (in this sense, Notch is indeed active long before SBN), this does not necessarily imply that Notch is still active at that time. This is because the deGFP protein produced by the NRE-deGFP reporter is stable relative to the time scale of the studied process. Its measured half-life in S2 cells cultured at 25{degree sign}C is 2h (PMID: 31140975). Based on this data, the NRE-deGFP signal is likely to remain detectable several hours after Notch signaling has been switched off. If the rate of production of deGFP is lower than its rate of degradation, then the NRE-deGFP signal is expected to progressively decay over time. We believe that this is what we observed in our movies: while a strong signal was detected over the posterior half of the ADHN at 14-15h APF, this signal decreased over time (Fig 7D). To interpret the temporal dynamics of NRE-deGFP signal in terms of instantaneous Notch activity, we examined the Rate of Change (ROC): an increase of the NRE-deGFP signal over time (positive ROC) would indicate that Notch activity is increasing (more precisely, the production rate of deGFP is higher than its rate of degradation), whereas a decrease (negative ROC) indicates that Notch becomes less active (or inactive if the rate of decrease approximates the decay rate of the deGFP protein). Our data shown in Fig 7D showed that the NRE-deGFP signal (measured in the area indicated with a dotted line in Fig 7A,B; this area was defined by the initial pattern of NRE-deGFP) decreased over time (negative ROC) between t=1 and t=6.5h. We therefore conclude that Notch signaling is decreasing to reach a minimum at t=~3.5h, indicating that the level of Notch activity is at its lowest around the time of SB. At this minimum, the decay rate corresponds to a protein half-life of 4.4h, which is not so different from the measured half-time of deGFP in S2 cells (particularly if one assumes a 1.4x difference between the decay rates measured at 22 and 25{degree sign}C, based on the known temperature-dependent speed of development). This is why we conclude that Notch signaling is very low at this stage. Additionally, no NRE-deGFP signal was detected before t=4:30h (movie 7) in the initially NRE-deGFP negative cells (located anterior to the area indicated with a dotted line in Fig 7A). This indicated that Notch was activated late in this area. Together, our observations are not consistent with the view that Notch mediates a strong mutual inhibition signal over a prolonged time interval prior to SB.

      To further study the pattern of Notch activity, we have monitored over time the accumulation pattern of GFP-tagged E(spl)m3-HLH (GFP-m3) (PMID: 31375669) in fixed sample (Fig S3F-G'). This confirmed that Notch was active in posterior ADHN cells and in the PDHN prior to 14h APF, i.e. prior to the onset of Ac and Sc, and that Notch activation extended to the central ADHN domain at 17-18h APF (Fig S3E-E' and G-G', and Fig 7I-I''), coinciding with SOP emergence.

      Otherwise, the reviewer is correct when stating that a FDI value close to 0 indicates that the level of measured fluorescence among the different cells of the considered cluster is similar. Such a FDI value would be measured if cells did not express NRE-deGFP or had decreasing but similar levels of NRE-deGFP. This FDI value does not, per se, imply that Notch is active.

      And then they move on to a (much more informative) cell-by-cell analysis, without even changing paragraphs, making it hard for the reader to follow. (6c) The conclusion at the end of the second paragraph (p. 9) "It also showed that SB was detected soon after the onset of Notch-mediated inhibitory signaling." is nowhere supported by data. If I understand well, SB refers to Sc and "the onset of Notch-mediated inhibitory signaling" refers to SBN (which is the onset of ASYMMETRY in Notch signaling, not the onset of Notch signaling, which has been going on for hours earlier). I don't see any data comparing SB with SBN. In fact, this is an important question to address (see below - comment 10).

      We apologize for the lack of clarity in our writing, we meant: "It also showed that SBN was detected soon after the onset of Notch-mediated inhibitory signaling."

      Yes, SBN refers to the onset of asymmetry in Notch signaling, as measured using NRE-deGFP. As explained above (but see also our response to point #7 below), our data do not provide evidence for a detectable Notch signal prior to SBN.

      We agree that comparing SB and SBN would be nice. Unfortunately, our current tools do not permit a detailed comparison (see our detailed response below, point #10).

      Mutual inhibition amongst neighboring cells has been proposed to involve (besides mutual Notch signaling) an increase in Sc levels in 2-3 cells in a cluster before the singularization of a single SOP. The authors seem rather biased against such a transient Sc hike based on their results in Fig. 2D, where the neighboring cells stay at rather constant basal Sc levels for several hours, while the Sc SB event happens. However, looking at an individual SOP in Fig. 2B, I do detect a mild hike in the pink curve right around SB in the blue curve. Could the average result from 160 SOPs (in Fig 2D) simply blur such transient Sc hikes, if they happen with different kinetics for different SOPs? Couldn't the 10% of SOP twins (shown in Fig. 6) represent a special case of this transient "subcluster" Sc hike? I would appreciate some discussion on this point. [Whether Sc is transiently upregulated or not, however, does not change my firm conclusion - from the data presented - that Notch-mediated mutual inhibition has been going on long before SBN.]

      First, our data are consistent with the notion that a few proneural cells progressively accumulate higher level of Scute prior to SB (as proposed above). Indeed, the moderate increase in both GFP-Sc levels and coefficient of variation values (GFP-Sc heterogeneity) seen prior to SB correspond to what the reviewer has in mind (higher levels of GFP-Sc in a few proneural cluster cells). We also appreciate the reviewer's comment about the plot shown in Fig 2D. However, we strongly feel that our quantitative analysis of a large dataset is a strength. Thus, we do not find useful to discretize a continuous process by introducing the notion of 'subclusters' of 2-3 cells. Likewise, we believe that it is more informative to focus our analysis on the entire dataset using average and SD values and do not wish to base our interpretation of the process based on selected tracks (the one shown in Fig 2B only served as an illustration of how we performed our analysis and has no interpretation value).

      The reviewer also states that "mutual inhibition amongst neighboring cells has been proposed to involve an increase in Sc levels in 2-3 cells in a cluster before the singularization of a single SOP". Since there is no published description of the pattern of accumulation of Scute in abdominal histoblats (to our best knowledge), we hypothesize that this statement applies to the proneural clusters in the developing wing disc. This is because the accumulation pattern of Sc has been studied in detail in that context by the Modollel and Carroll labs (PMID: 2044965, PMID: 2044964). However, their description of the accumulation pattern of Scute (in fixed samples, using anti-Sc antibodies) did not refer to sub-clusters of 2-3 cells. We would appreciate if the reviewer could direct us to the relevant published observation.

      Finally, we are not sure to follow the reviewer when she/he firmly concluded from our data that Notch-mediated mutual inhibition has been going on long before SBN. Instead, our data clearly showed that the ADHN region that produced SOPs exhibited two distinct NRE-deGFP patterns, with Notch signaling being active prior to imaging (i.e. prior to 14h APF) and decreasing to reach a minimum of Notch activation around 17h APF (i.e. around the time of SB, as determined by GFP-Sc imaging) in the posterior area of the ADHN.

      Thus, our data do not show that mutual inhibition does not take place in this tissue but rather imply that the phase of mutual inhibition (or competition) must be relatively short, or transient, and that competition amongst proneural cluster cells operate at low Notch and Sc levels (probably contrary to what many people have in mind).

      Some minor points: * * 8. Please change Cad-GFP to Ecad-GFP or shg-GFP, as Cad misdirects to caudal.

      Thanks, changed into Ecad-GFP and Ecad-mKate

      What is c in "(x,y,z,c,t) movies"? (a fifth independent variable?)

      c stands for channel. This is relatively standard nomenclature.

      The authors show that Sc displays a SB event leading to FDI of 0.08 and the Notch reporter displays another SB (SBN) leading to a much more pronounced FDI of -0.2. Are these two events (the hike of Sc levels and the plummeting of Notch signal) contemporaneous or does one precede the other? Having both tagged with GFP makes it impossible to image simultaneously, but the authors could register each reporter's dynamics relative to the time of SOP division (as done in Fig. 5C) to get a sense of their relative order.

      We do agree with the reviewer that it would be nice to be able to align in time these two data sets. Unfortunately, the temporal correlation between SB and the SOP division is too variable (4.7 +/- 1.1) to confidently align these two datasets using this event as a time reference. New tools are needed (see our response to point #11 below).

      Where in the above timeline is the SOP fate definitively adopted? neur-nlsGFP, Ac-RFP, m3Cherry and Sens detection in Figs. 1 and 7 give us a rough idea that these other markers appear around the time of Sc FDI peaking, around 3h after the initial SB. But this is not presented in an organized fashion - the reader collects this information sporadically. A reanalysis of the already existing data attempting to place these various markers in an integrated timeline would be of great importance in understanding the details of this cell fate specification process. Which is the earliest SB event? sc, neur or Notch? How long does it take from that early SB until definitive SOP markers (Sens) first appear?

      We agree with the reviewer, it would be interesting to extend the approach reported here for Scute to characterize SB and rate of FDI for other key factors governing the selection of SOPs. As pointed out by the reviewer (point #10 above), it would also be important to register in time these various events. Unfortunately, the maturation time of RFP, mCherry, FP670, etc... appeared to be too slow relative to the rapid turnover of the Ac, Sc and E(spl)-HLH factors prevented us from performing two-color imaging. Hence, current tools do not permit to determine which is the earliest SB event.

      More genetic perturbations could be performed to solidify the model of cell-cell communication during lateral inhibition. Two obvious ones come to mind: (a) How would the Sc-GFP dynamics change in a Notch-RNAi background? (b) How would the NRE-deGFP dynamics change in a sc-RNAi background?

      See our detailed response to reviewer #1, major point #2.

      PeerReviewed
    2. EMBOpress 18 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Phan et al present their work on the dynamics of Sc accumulation and Notch signaling in the dorsal abdomen of Drosophila. They use live imaging to provide more detailed knowledge on a well-studied phenomenon of lateral inhibition, where proneural proteins (like Sc) promote a certain fate (like SOP) in groups of equivalent cells. The selection of individual SOPs among these equivalent cells depends on Delta-Notch signaling, which allows neighboring cells to communicate. Cells that accumulate higher levels of Sc acquire an increased ability to inhibit their neighbors and will ultimately become SOPs. This paradigm seems to be used time and again in arthropods and vertebrates alike and its central importance is witnessed by the fact that it has been under intense study over the last 3 decades. The present manuscript adds the temporal dimension to one instance that deploys this proneural-Notch interplay. The authors show that the timecourse from equivalence to singularized SOPs takes 3-8 hours (from 13 to 21 h APF) and is visible as an increase in Sc-GFP levels in one cell of the cluster. They calculated precisely the onset of this increase (which they term "symmetry breaking") and showed that Sc levels plateau approx. 3 h later, although some SOPs are faster than others in reaching that plateau. Sc increase is accompanied by Notch reporter decrease. The apical area of the cells does not seem to bias the level of Notch signaling/ Sc accumulation. What does seem to speed up the process is pre-existing heterogeneity in Sc (and Notch?) levels. Interestingly, when this process of lateral inhibition fails to singularize a single cell (resulting in two adjacent cells with high Sc levels), these two cells move apart by cellular rearrangements. During the 3h that the SOP upregulates its Sc levels after SB, its neighboring cells stay at relatively constant baseline Sc levels and only afterwards do they start reducing their own Sc-GFP. The authors have taken the trouble to collect live data for >100 SOPs in different experimental settings, so there is no doubt about their reproducibility and statistical robustness. In general, the figures are clear and self-explanatory. I found it hard to follow the text, however, and I have some suggestions for its improvement.

      1. First and foremost, the authors should state in the first paragraph of the Results that scGFP is a CRISPR knockin and thus it's the only source of Sc protein in the animals imaged (this is stated only in the Methods section).
      2. The magnitude of the Sc increase should be commented on. Based on the intensity and FDI plots in Fig. 3B-E, an increase of 15-17% in the amount of Sc is suggested (the FDI plateaus at 0.08, which gives 1.08/0.92 = 1.17x the level of Sc in the SOP vs the surrounding cells). However, in the stills shown in Fig. 2BCD and in Fig. 3A, the intensity differential between SOPs and neighbors seems at least 100% (ie at least double the intensity, which would yield an FDI of >1/3 =0.33). Why is this high contrast never seen in the quantitative measurements?
      3. From Fig. 2A-D it appears that the ScGFP fluorescence intensity is at the same level or weaker than nearby autofluorescence. Please state (1) how you confirmed that the histoblast nest has lower autofluorescence than the larval epidermis and (2) how you corrected for histoblast nest autofluorescence in your quantifications.
      4. The paradoxical result of Fig. S1B should be discussed. On the one hand it is stated that "Ac and Sc specify the fate of the Sensory Organ Precursor cells (SOPs)" (p.2) and on the other S1B shows SOP specification in the absence of Sc. Are the SOPs shown in Fig S1B rare exceptions? Do the authors believe that these rare exceptions are there because of inefficient RNAi (since in comparison with S1A, in the null condition almost no SOPs should be formed)? Or they are the SOPs in RNAi clones as rare as the occasional bristles in S1A?
      5. One figure that is not straightforward to interpret is Fig. 4E. It plots ScGFP heterogeneity vs. number of RNAi neighbors. Each point in the plot must be an individual SOP (165 total). Therefore, its neighbors (the x-axis) should take integral (not decimal) values. How can a single SOP have a decimal number of RNAi neighbors, especially since heterogeneity was sampled over a 10min time-window, when not much cell rearrangement can take place? Please explain.
      6. I found the discussion of the Notch reporter dynamics (Fig. 7) confusing in several places. (6a) Whereas it's clear that there is plenty of Notch signaling going on before SBN, the authors repeatedly imply that Notch signaling starts after SBN. For example, in the Results (p.9) they state "Thus, this quantitative approach failed to detect a phase of reciprocal Notch signaling during which proneural cluster cells would both send and receive a Delta-Notch signal prior to SOP emergence." The fact that the NRE-deGFP gave a robust signal before the start of the movies clearly means that mutual inhibition was going on for quite some time before SB. In fact, an FDI of 0 for >4h prior to SBN (Fig. 7G) means exactly this: that the level of Notch response among the cluster cells is equivalent ("mutual inhibition" lasts for at least 4h before SBN). (6b) In the first paragraph of this section (p.8) they comment that the pre-existence of Notch signaling is unexpected - why? I interpret it to simply be mutual inhibition (see above). Then they go on to quantitate the average Notch response intensity over the entire posterior ADHN (please define the borders the "posterior" ADHN). I question the informational value of this analysis (averaging over a large region), when Notch signaling is known to have intense local cell-to-cell variability (also evident in the stills shown in Fig. 7A,B,C). And then they move on to a (much more informative) cell-by-cell analysis, without even changing paragraphs, making it hard for the reader to follow. (6c) The conclusion at the end of the second paragraph (p. 9) "It also showed that SB was detected soon after the onset of Notch-mediated inhibitory signaling." is nowhere supported by data. If I understand well, SB refers to Sc and "the onset of Notch-mediated inhibitory signaling" refers to SBN (which is the onset of ASYMMETRY in Notch signaling, not the onset of Notch signaling, which has been going on for hours earlier). I don't see any data comparing SB with SBN. In fact, this is an important question to address (see below - comment 10).
      7. Mutual inhibition amongst neighboring cells has been proposed to involve (besides mutual Notch signaling) an increase in Sc levels in 2-3 cells in a cluster before the singularization of a single SOP. The authors seem rather biased against such a transient Sc hike based on their results in Fig. 2D, where the neighboring cells stay at rather constant basal Sc levels for several hours, while the Sc SB event happens. However, looking at an individual SOP in Fig. 2B, I do detect a mild hike in the pink curve right around SB in the blue curve. Could the average result from 160 SOPs (in Fig 2D) simply blur such transient Sc hikes, if they happen with different kinetics for different SOPs? Couldn't the 10% of SOP twins (shown in Fig. 6) represent a special case of this transient "subcluster" Sc hike? I would appreciate some discussion on this point. [Whether Sc is transiently upregulated or not, however, does not change my firm conclusion - from the data presented - that Notch-mediated mutual inhibition has been going on long before SBN.] Some minor points:
      8. Please change Cad-GFP to Ecad-GFP or shg-GFP, as Cad misdirects to caudal.
      9. What is c in "(x,y,z,c,t) movies"? (a fifth independent variable?)

      Significance

      The mechanism of proneural-Notch interplay is evolutionarily conserved, so this study of its temporal dynamics is valuable and will interest a broad audience in the field of animal developmental biology. The rich data collected by the authors should contain enough information to make a big contribution to the field, but the presentation in the manuscript stops a little short of that. The fact that Sc expression is highly dynamic was already known - now we have quantitative measurements of this variability. Same holds for Notch signaling. The authors should try to integrate their data better to make a complete timeline of events that leads to SOP specification, using the panoply of fluorescent markers at their disposal.

      1. The authors show that Sc displays a SB event leading to FDI of 0.08 and the Notch reporter displays another SB (SBN) leading to a much more pronounced FDI of -0.2. Are these two events (the hike of Sc levels and the plummeting of Notch signal) contemporaneous or does one precede the other? Having both tagged with GFP makes it impossible to image simultaneously, but the authors could register each reporter's dynamics relative to the time of SOP division (as done in Fig. 5C) to get a sense of their relative order.
      2. Where in the above timeline is the SOP fate definitively adopted? neur-nlsGFP, Ac-RFP, m3Cherry and Sens detection in Figs. 1 and 7 give us a rough idea that these other markers appear around the time of Sc FDI peaking, around 3h after the initial SB. But this is not presented in an organized fashion - the reader collects this information sporadically. A reanalysis of the already existing data attempting to place these various markers in an integrated timeline would be of great importance in understanding the details of this cell fate specification process. Which is the earliest SB event? sc, neur or Notch? How long does it take from that early SB until definitive SOP markers (Sens) first appear?
      3. More genetic perturbations could be performed to solidify the model of cell-cell communication during lateral inhibition. Two obvious ones come to mind: (a) How would the Sc-GFP dynamics change in a Notch-RNAi background? (b) How would the NRE-deGFP dynamics change in a sc-RNAi background?
      PeerReviewed
    3. EMBOpress 18 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Understanding cell fate is crucial for various biological processes, including development, tissue regeneration, and disease progression. In this manuscript, colleagues in the team of François Schweisguth provide high-quality live cell observations demonstrating how SOP (Sensory Organ Precursor) cells are determined from a cluster of proneuronal cells via symmetry breaking (SB), which is key in the process of lateral inhibition. Although the process of lateral inhibition has been proposed long ago, no studies have been conducted to demonstrate it using live imaging. Using Drosophila abdominal epidermis as a model, the authors showed how the levels of the main neuronal determinants are expressed during SOP cell determination. The team uses a tagged version of one of the cell fate determinants, Scute, to follow the dynamics of this process, which is then further supported by genetic experiments showing that cell-to-cell variations in Scute expression levels promote fate divergence and patterning. This paper provides a new perspective on how dynamic expression of proneural factors determines cell fate acquisition from the equivalent population of cells. The data is presented very clearly, and the methods are adequately detailed, with suitable experiments and statistical analysis, as well as convincing key conclusions.

      Major points:

      1. Despite "symmetry breaking" being the main focus of the paper, in the Introduction, the authors do not explain what this term means and do not provide any description of this process. This is a critical point that makes understanding of the goals of the paper difficult. Therefore, the authors are encouraged to provide more information and a clear description of this term/phenomenon.
      2. The role of Achaete in the story is not clear. Even though both factors are required for SOP determination, the authors mainly focus on Scute, so it is not very clear what the role of Achaete in this process is, if there is any. As shown in the paper, Achaete is expressed later when heterogeneity is promoting cell fate divergence. Is Achaete maybe contributing to cell heterogeneity/ cell fate divergence? Minor points:
      3. Symmetry Breaking (SB) should be abbreviated in the Abstract. The authors initially use the full term without abbreviation, and only on page 5, the abbreviation is finally defined; however, it should be introduced much earlier.
      4. The second-to-last sentence in the abstract, "These lateral inhibition defects were correlated via cellular rearrangements," is unclear regarding what defects the authors are referring to.
      5. For clarity, being more specific in the text in regards to description of the figure panels would be beneficial (e.g. page 3 Fig 1C-E); referring to C-E together makes it hard to understand what does each panel shows.
      6. In many instances, the movies are not properly referenced (e.g. on page 5, third row simply states "movies"), making it difficult to discern which movie should be checked. On page 8, when authors refer to movie 3, they likely meant movie 5.
      7. Figure S1 requires some corrections. The authors use the short name "scute" initially and then switch to the shortened version "sc'. Additionally, the nlsRFP (blue) is difficult to see; adjusting the levels or changing colors/showing separate channels may improve visibility. The authors mention clone borders, but none are shown. It would greatly help to outline the borders in all figures. Genotypes of the samples should be indicated, and clarification is needed regarding what "n" represents (number of cells, clones, or flies). What do the arrows in the panel B show? It is also recommended to display important channels as separate black and white images. Additionally, the use of RNAi against GFP instead of RNAi against scute should be justified; using RNAi GFP as the genotype on the graph could be interpreted as a control genotype rather than downregulation of scute.
      8. In the Figure 2 Legend, the authors use "std" as an abbreviation to define standard deviation. Typically, this is abbreviated as SD.
      9. In Figure 4E, the authors do not explain on why there are points on the x-axis that correspond to a decimal number of cells.

      Reviewer Cross-Commenting

      I fully agree with the comments provided by the other reviewers, most of which were complementary and overlapping with mine. Their comments are well-reasoned and highlight certain aspects that I overlooked. I agree that conducting additional genetic analyses would enhance our understanding of the progression fate divergence and its impact on lateral inhibition in real-time. Specifically, exploring the spatial and temporal dynamics of Ac and Sc in Notch mutants, as well as Notch dynamics in Sc and Ac mutants, could strengthen the proposed model of cell-cell communication during lateral inhibition.

      Significance

      Understanding cell fate is crucial for various biological processes, including development, tissue regeneration, and disease progression. In this manuscript, colleagues in the team of François Schweisguth provide high-quality live cell observations demonstrating how SOP (Sensory Organ Precursor) cells are determined from a cluster of proneuronal cells via symmetry breaking (SB), which is key in the process of lateral inhibition. Although the process of lateral inhibition has been proposed long ago, no studies have been conducted to demonstrate it using live imaging. Using Drosophila abdominal epidermis as a model, the authors showed how the levels of the main neuronal determinants are expressed during SOP cell determination. The team uses a tagged version of one of the cell fate determinants, Scute, to follow the dynamics of this process, which is then further supported by genetic experiments showing that cell-to-cell variations in Scute expression levels promote fate divergence and patterning. This paper provides a new perspective on how dynamic expression of proneural factors determines cell fate acquisition from the equivalent population of cells. The data is presented very clearly, and the methods are adequately detailed, with suitable experiments and statistical analysis, as well as convincing key conclusions.

      PeerReviewed
    4. EMBOpress 18 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      In this manuscript, the authors addressed when and how fate symmetry breaking occurs during lateral inhibition using live imaging of Drosophila pupal abdomen as a model system. Using quantitative live imaging of a GFP tagged version of the proneural gene scute (sc), the authors demonstrated that GFP-Sc expression appears first along the posterior margin of the anterior dorsal histoblast nest (ADHN) and later in the central region of ADHN, suggesting that posterior cues regulate early proneural expression in this region, which is consistent with previous findings. By tracking the temporal expression of GFP-Sc in the sensory organ precursor cells (SOPs), the authors further showed that SOPs emerge within a 2 hour time frame around 17h APF in the ADHN. Moreover, the presumptive SOP and its surrounding histoblasts showed a weak and slowly increasing GFP-Sc signal until the presumptive SOP showed a rapid increase in GFP-Sc accumulation, whereas GFP-Sc levels remained relatively constant in non-selected histoblasts. Interestingly, using symmetry breaking as a reference point, the authors found that the onset of fate divergence took place at low levels of Sc, soon after the onset of proneural gene expression and was not preceded by a prolonged phase of Sc accumulation. The authors also demonstrated that lateral inhibition in the pupal abdomen failed to single out SOPs in around 10% of the cell clusters that are in direct contact with each other during symmetry breaking and that pattern refinement involving cellular rearrangements were required to correct these defects. By manipulating the heterogeneity of Sc in genetically mosaic pupae, the authors successfully showed that increasing the heterogeneity of Sc positively correlated with an increased rate of fate divergence, suggesting that cell-to-cell variations in Sc levels promote fate divergence during lateral inhibition. Although earlier modelling suggested that differences in apical cell area may serve as a possible source of bias for Notch-based decisions, the authors found no significant difference in the apical area of the presumptive SOP compared to the mean area of its neighbouring cells, suggesting that apical cell shape does not bias Notch-mediated cell fate decisions in this developmental context. Finally, examination of Notch activity dynamics using a destabilized GFP expressed downstream of a Notch-Responsive Element as well as analysing the expression of the E(spl)m3 Notch target gene, the authors demonstrate that Notch activity was minimal around the time of SOP emergence as E(spl)m3 was detected after the onset of Sc expression but not prior to SOP emergence, indicating that SOP selection in the abdominal epidermis took place at low levels of Notch signalling.

      Major comments:

      • Are the key conclusions convincing?

      Yes, the key conclusions are convincing with quantitative live imaging and proper explanations on how the analyses were carried out. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      No.

      • Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
      • The authors conclude that RFP-Ac expression is restricted to emerging SOPs and surroundings cells at 18h APF, indicating that Ac is activated later than Sc. Can the authors provide images for RFP-Ac expression at 10h and 16h APF similar to GFP-Sc as shown in their figures. Do the SOPs that contain high levels of both Ac and Sc (as some SOPs have Sc expression but not Ac) undergo fate divergence and SB faster than the SOPs containing higher levels of only Sc?
      • It would be interesting to see the spatial and temporal dynamics of Ac and Sc in Notch mutants or even Notch dynamics in Sc and Ac mutants to better understand the progression fate divergence and its effect on lateral inhibition in real time.
      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3-4 months to complete the experiments. - Are the data and the methods presented in such a way that they can be reproduced?

      Yes. - Are the experiments adequately replicated and statistical analysis adequate?

      The experiments are straight forward and were performed with a good number of n values for their live imaging and supported by quantifications.

      Minor comments:

      • Specific experimental issues that are easily addressable.
      • In figure 1F and F', the authors mention GFP-Sc is not expressed prior to 14h, however, there is still GFP signal detected in their imaging. Can the authors comment what would be the cause of this GFP signal or was it due to non-specific background signal during their imaging analysis?
      • In the materials and methods, the authors mention that prior to imaging the larvae and pupae are grown at 18, 21 or 25C. Is there a reason why the larvae and pupae are grown at different temperatures for different experiments? Can the authors specify (i.e. in the figure legends) in which experiments different temperatures were used?
      • The citations need to have a better format as they show up as each citation within a single bracket which makes it a little hard to read when multiple references are cited in a single sentence.
      • In the abstract, the sentence 'Unexpectedly, we observed at low frequency (10%) pairs of cells that are in direct contact at the time of SB'. SB should be replaced with "Symmetry breaking", as it appeared for the first time in the manuscript and should be written out in full.
      • Throughout the manuscript there are instances where the abbreviations are written in full with the abbreviation in brackets after they have already been introduced in the introduction which can be changed to just the abbreviation itself.
      • In the discussion on page 11, 'our observation...', our needs to be changed to Our.
      • Are prior studies referenced appropriately?

      Yes. - Are the text and figures clear and accurate? 1. It would be nice to have arrow heads or dotted lines around the cells or areas on interest in both, all the figures and movies, so that it will be easier to follow the results. The videos have a lot of background due to fragmented apoptotic nuclei, etc. as mentioned by the authors, hence arrow heads or dotted lines would bring viewers focus on the areas of interest. 2. It would be helpful to have anterior - posterior axis (i.e. with an arrow) shown on top of all the figures. 3. Scale bars are missing in all figures, videos, and figure legends. 4. Only movies 1 and 3 are referenced in the text. 5. Keeping the colors in the movies and figures consistent and same would be helpful. For example, Movie 2 Histone3.3-mIFP marker is in blue but in figure 3 it is in magenta. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      As mentioned above, it would be helpful if the authors have arrow heads or dotted lines around the cells or areas of interest in both the figures and movies for better representation of their data. For example, movie 1 shows a larger area of imaging than shown in figure 2A, which makes it hard to follow the cells of interest in the movie.

      Significance

      Since the dynamics of fate acquisition has mostly been studied in fixed samples in Drosophila, this is an interesting study to understand the spatial and temporal dynamics of Notch signalling as well as proneural activity during lateral inhibition using Drosophila pupal abdomen as a model. Using quantitative live imaging the authors provide key evidence on how and when SB occurs during lateral inhibition, providing experimental support for the intracellular feedback model. Most importantly, they show that fate selection occurred early and was not preceded by a detectable phase of mutual inhibition, but instead, the initial bias in Sc expression and heterogeneity might play a significant role in in SB.

      • Place the work in the context of the existing literature (provide references, where appropriate).

      So far, most work in this field has focused on the dynamics of fate acquisition using fixed samples and mathematical remodelling, with some live imaging analysis (Skeath and Carol, 1991; Collier et al, 1996; Castro et al, 2005; Corson et al, 2017; Couturier et al, 2019; Troost et al, 2023). Here, considering previous literature, the authors move one step forward, using quantitative live imaging of proneural factors Scute to determine fate SB and monitor fate divergence during lateral inhibition. This study though not entirely conceptually novel provides important new insights into SB and fate divergence in the pupal abdomen, wherein symmetry breaking occurred at low Sc levels and that fate divergence was not preceded by a prolonged phase of low or intermediate level of Sc accumulation. Furthermore, the relative size of the apical area did not influence this fate choice but cell-to-cell variations in Sc levels promoted fate divergence, thereby providing experimental support for the intercellular negative feedback loop model. - State what audience might be interested in and influenced by the reported findings.

      Developmental and cell biologists. - Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

      Stem cells, developmental biology.

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    biorxiv.org/content/10.1101/2024.03.11.583933v1
  42. www.biorxiv.org www.biorxiv.org
    Targeting the ER stress sensor IRE1 protects the liver from fibrosis through the downregulation of the proteostasis factor P4HB/PDIA1
    3
    1. EMBOpress 17 Jun 2024

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      Reply to the reviewers

      Response to reviewers

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    2. EMBOpress 17 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript by Hazari et al reports on an important new function of the UPR IRE1 in liver fibrosis. The results are clearly and logically described. It shows that the genetic ablation of IRE1 in mice prevents liver fibrosis through retention of collagen in the ER and its degradation hence preventing secretion and accumulation in liver parenchyma. This effect was reversed was P4HB (a multifunctional enzyme that belongs to the protein disulfide isomerase) showing that IRE1 control P4HB.

      As such the paper is both scientifically and medically relevant.

      There is in my opinion a conceptual issue the paper does not directly address nor resolve.

      A clear functional distinction between IRE1 and XBP1 is not made nor attempted. This comes across as an unresolved issue. In the Introduction the authors cite ref 29 that provided evidence for a role of RIDD in alleviating hepatic cytotoxicity. The paper is based on chronic liver toxicity by CCL4 to identify the protective role of IRE1 and acute CCL4 toxicity to identify P4HB. IRE1 KO demonstrates that IRE1 controls collagen metabolism (degradation vs. secretion). However, many considerations involve XBP1 (see Fig. 8 as a example). Yet the paper concludes by saying "we propose that pharmacological inhibition of IRE1 activation..." Granted that IRE1 inhibition would definitely cause an attenuation of XBP1 splicing, I see a clear distinction between IRE1 and XBP1 still necessary to back the conclusion that inhibition of IRE1 and not XBP1 is the therapeutic modality one should develop.

      It is clear that IRE1 controls XBP1, but it also controls RIDD. Both independently control the fate of multiple downstream genes and also miRNAs in the case of RIDD. Because RIDD may offer some advantages in attenuating liver pathology, forfeiting some benefits IRE1 can offer via RIDD in order to blunt XBP1 may not be the optimal solution. Therefore, I suggest to complement the present study with experiments that target XBP1 specifically bypassing IRE1. Experiments of deletion (siRNA or Cre) as well as specific activation of XBP1 for which there exist commercially available molecules (e.g., IAX4 is a direct activator of XBP1 without UPR that also does not induce XBP1s-independent IRE1 signaling such as RIDD or JNK phosphorylation) will permit to better differentiate the role of XBP1 from IRE1 in P4HB regulation and collagen degradation vs. secretion in hepatic stellate cells and deposition in liver.

      Throughout the paper the authors refer to XBP1 and even center the Discussion on XBP1 more than on IRE1. Since determining the precise mechanism in this particular instance is critical to future treatments to prevent liver fibrosis these additional experiments should be performed.

      Minor point

      Fig. 4D. The label must have been erroneously copied and pasted. There is not way to distinguish what is different in lane 1-2 from lane 3-4. The legend is not helpful.

      Fig. S4B. Same problem.

      Significance

      This is an excellent paper with profound new medical implications with conceptual advances for the treatment of NASH.

      The limitations have been underscored in comments to authors.

      The audience remains specialized for the time being.

      PeerReviewed
    3. EMBOpress 17 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      The current study aimed to investigate the possible contribution of the unfolded protein response (UPR), the main adaptive pathway that monitors and adjusts the protein production capacity at the endoplasmic reticulum (ER), to collagen biogenesis and liver disease. The authors targeted the ER sensor, inositol requiring transmembrane kinase/endoribonuclease 1 alpha (IRE1), using the IRE1Lox/Lox, Mx1Cre/- mouse strain where Cre is induced with 3 poly I:C injections. After confirmation of depleting IRE1 in the liver, they challenged mice with a high dose of carbon tetrachloride (CCl4). Phenotype analysis revealed the deleterious role of IRE1 in the liver in acute liver damage. Then, the authors determined the biological consequence of IRE1 deletion on the progression of experimental liver fibrosis. Consistently, IRE1 plays a promotive role in the CCl4-induced liver fibrosis mouse model since the results suggest that IRE1 knockout mice have reduced collagen deposition and AST/ALT activity (two major liver damage enzymes). To determine the potential mechanisms underlying the protective effects of IRE1 deficiency, the authors did mass spectrometry-based quantitative proteomics of liver samples from the experimental mice. Through bioinformatic analysis, they determined that protein and mRNA expression levels of P4HB decreased in IRE1 deficiency mice. Besides, in vitro and ex vivo studies suggested that IRE1 deficiency downregulated collagen generation. They further investigated the impact of IRE1 deficiency in liver steatosis in a mouse model fed a high-fat diet (HFD). Similarly, IRE1 deficiency suppressed liver steatosis and fibrosis in this mouse model. To clarify how IRE1 modulates collagen expression, the authors generated IRE1 knockout cell (KO) lines. They found that IRE1 KO cells may cause misfolding and intracellular accumulation of collagen inside the cells, reducing its secretion. Finally, they suggested the correlation of IRE1 associated gene (XBP1) and PH4B but not PH4A1 in human patients with non-alcoholic steatohepatitis (NASH). Overall, the current study may provide a potential molecular linkage between IRE1 and collagen in chronic liver disease progression. However, the inconsistent data presentation, poor data quality, and lack of suitable animal models make the current manuscript's impact on the field of chronic liver disease low.

      Major concern:

      1. The authors suggested that P450 levels are not changed in the liver samples of IRE1 KO mice compared to the wildtype (WT) ones. It has been demonstrated that IRE1 activation reduced P450 expression levels (PMID: 22291093). Can the authors explain the inconsistent findings?
      2. Why did the authors challenge mice with CCl4 for 12 weeks? The CCl4-induced liver fibrosis model would have a severe fibrotic liver phenotype at 8 weeks. Did the author check if IRE1 deficient mice have less liver injury than wildtype (WT) mice at early time points? Also, could you check the liver fibrosis phenotype using another typical liver fibrosis mouse model? The HFD-feeding mouse model would induce liver fibrosis after challenging mice for 50 weeks (PMID: 37270060).
      3. What are the mouse numbers, age, and sex in the CCl4 studies? In Fig. 2, several figures have inconsistent mouse numbers for the data presentation.
      4. There are many downregulated and upregulated target genes. What is the rationale for focusing on downregulated P4HB in IRE1 deficient mice, given that IRE1 has an RNase domain functioning in posttranscriptional regulation? In this case, how does IRE1 depletion upregulate P4HB?
      5. The author suggested that TGFb1 would promote collagen generation, but targeting IRE1 would reduce P4HB and the TGFb1-mediated collagen generation. The Fig. 4D does not support the statement. However, the authors' data demonstrated that TGFb1 cannot promote IRE1 and P4HB expression (Fig. 4G). If TGFb1 cannot promote collagen generation through activating IRE1 and P4HB, how can targeting IRE1 reduce TGFb1-induced collagen (Fig. 4H)?
      6. The authors stated that hepatic Ern1 deficiency suppresses the progression of liver steatosis. In fact, it has been reproducibly demonstrated that hepatic IRE1 deletion promotes hepatic steatosis progression (PMID: 21407177 and PMID: 29764990), contradicting the authors' findings. Besides, the authors did not deplete IRE1 specifically in the liver. Therefore, they made a misleading conclusion without solid evidence. The authors basically depleted IRE1 in the whole body of these experimental mice upon poly I:C injection. The authors must not conclude that hepatic Ern1 deficiency suppresses the progression of liver steatosis without considering the contributions of other organs in the phenotypes that you observed. Also, the HFD-treated mice would develop liver fibrosis 50 weeks post-feeding (PMID: 37270060). It is unclear what other treatments the authors used to accelerate the fibrotic liver phenotype, as shown in Fig. 5D. The authors should show body weight and liver weight over body weight in the result section. Besides, hepatic cholesterol, serum triglyceride, and cholesterol need to be measured in these mice to clarify how deleting IRE1 in the whole body can suppress hepatic steatosis, but liver-specific deletion of IRE1 promotes fatty liver. Without clarifying this issue, it is unclear how hepatic IRE1 deficiency can reduce steatosis and liver fibrosis.
      7. The authors suggested that ablation of IRE1 expression increased the levels of intracellular GFP-collagen as compared with control cells (Fig. 6C). How did the authors quantify the results? It is not clear if KO really increased the intracellular collagen levels. As the authors showed in Fig. 6C, WT-NT, and WT-GFP-collagen-untreated have no overlap of green fluorescence. However, KO-NT and KO-GFP-collagen-untreated still have an overlap of green fluorescence, indicating that some cells are not GFP-positive. In this case, how could authors conclude that IRE1-KO cells have a more than 2-fold increase of green fluorescence change compared to WT? Besides, Fig. 6F suggested that secreted collagens increased in KO cells, contradicting the authors' previous data in Fig. 2, 4, and 5. Why did you use U2OS, Hepa1-6, and Huh7 in these studies? Should the collagen be secreted by hepatic stellate cells?
      8. In Fig. 7, the authors suggested that IRE1 KO promotes the levels of collagen inside cells using the whole cell lysate. Interestingly, they indicated that IRE1 deficiency suppressed TGFb1-induced collagen production using whole cell lysates (Fig. 4D). It is really confusing if IRE1 KO promotes or suppresses collagen production or secretion. Also, Fig. 7C did not support that IRE1-KO reduced collagen secretion. Besides, what cells did the authors use for these studies? Are they hepatic stellate cells?
      9. It is interesting to see the positive correlation between XBP1 and P4HB mRNA expression. However, it is still unclear if IRE1 deficiency could downregulate P4HB mRNA expression, given its RNase function. Thus, it would be essential to determine how IRE1 regulates P4HB expression before analyzing the correlation using human datasets. Besides, Fig. 8D did not suggest that XBP1 expression levels are really correlated with chronic liver disease progression, given that its correlation scores with AST and ALT are 0 and -0.01, respectively.

      Significance

      The current study aimed to investigate the possible contribution of the unfolded protein response (UPR), the main adaptive pathway that monitors and adjusts the protein production capacity at the endoplasmic reticulum (ER), to collagen biogenesis and liver disease. The authors targeted the ER sensor, inositol requiring transmembrane kinase/endoribonuclease 1 alpha (IRE1), using the IRE1Lox/Lox, Mx1Cre/- mouse strain where Cre is induced with 3 poly I:C injections. After confirmation of depleting IRE1 in the liver, they challenged mice with a high dose of carbon tetrachloride (CCl4). Phenotype analysis revealed the deleterious role of IRE1 in the liver in acute liver damage. Then, the authors determined the biological consequence of IRE1 deletion on the progression of experimental liver fibrosis. Consistently, IRE1 plays a promotive role in the CCl4-induced liver fibrosis mouse model since the results suggest that IRE1 knockout mice have reduced collagen deposition and AST/ALT activity (two major liver damage enzymes). To determine the potential mechanisms underlying the protective effects of IRE1 deficiency, the authors did mass spectrometry-based quantitative proteomics of liver samples from the experimental mice. Through bioinformatic analysis, they determined that protein and mRNA expression levels of P4HB decreased in IRE1 deficiency mice. Besides, in vitro and ex vivo studies suggested that IRE1 deficiency downregulated collagen. They further investigated the impact of IRE1 deficiency in liver steatosis in a mouse model fed a high-fat diet (HFD). Similarly, IRE1 deficiency suppressed liver steatosis and fibrosis in this mouse model. To clarify how IRE1 modulates collagen expression, the authors generated IRE1 knockout cell (KO) lines. They found that IRE1 KO cells may cause misfolding and intracellular accumulation of collagen inside the cells, reducing its secretion. Finally, they suggested the correlation of IRE1 associated gene (XBP1) and PH4B but not PH4A1 in human patients with non-alcoholic steatohepatitis (NASH). Overall, the current study may provide a potential molecular linkage between IRE1 and collagen in chronic liver disease progression. However, the inconsistent data presentation, poor data quality, and lack of suitable animal models make the current manuscript's impact on the field of chronic liver disease low.

      Major concern:

      1. The authors suggested that P450 levels are not changed in the liver samples of IRE1 KO mice compared to the wildtype (WT) ones. It has been demonstrated that IRE1 activation reduced P450 expression levels (PMID: 22291093). Can the authors explain the inconsistent findings?
      2. Why did the authors challenge mice with CCl4 for 12 weeks? The CCl4-induced liver fibrosis model would have a severe fibrotic liver phenotype post the 8-week CCl4 challenge. Did the author check if IRE1 deficient mice have less liver injury than wildtype (WT) mice at early time points? Also, could you check the liver fibrosis phenotype using another typical liver fibrosis mouse model? The HFD-feeding mouse model would induce liver fibrosis after challenging mice for 50 weeks (PMID: 37270060).
      3. What are the mouse numbers, age, and sex in the CCl4 studies? In Fig. 2, several figures have inconsistent mouse numbers for the data presentation.
      4. There are many downregulated and upregulated target genes. What is the rationale for focusing on downregulated P4HB in IRE1 deficient mice, given that IRE1 has an RNase domain functioning in posttranscriptional regulation? In this case, how does IRE1 depletion upregulate P4HB mRNA expression?
      5. The author suggested that TGFb1 would promote collagen generation, but targeting IRE1 would reduce P4HB and the TGFb1-mediated collagen generation. The Fig. 4D does not support the statement. However, the authors' data demonstrated that TGFb1 cannot promote IRE1 and P4HB expression (Fig. 4G). If TGFb1 cannot promote collagen generation through activating IRE1 and P4HB, how can targeting IRE1 reduce TGFb1-induced collagen (Fig. 4H)?
      6. The authors stated that hepatic Ern1 deficiency suppresses the progression of liver steatosis. In fact, it has been reproducibly demonstrated that hepatic IRE1 deletion promotes hepatic steatosis progression (PMID: 21407177 and PMID: 29764990), contradicting the authors' findings. Besides, the authors did not deplete IRE1 specifically in the liver. Therefore, they made a misleading conclusion without solid evidence. The authors basically depleted IRE1 in the whole body of these experimental mice upon poly I:C injection. The authors must not conclude that hepatic Ern1 deficiency suppresses the progression of liver steatosis without considering the contributions of other organs in the phenotypes that they observed. Also, the HFD-treated mice would develop liver fibrosis 50 weeks post-feeding (PMID: 37270060). It is unclear what other treatments the authors used to accelerate the fibrotic liver phenotype, as shown in Fig. 5D. The authors should show body weight and liver weight over body weight in the result section. Besides, hepatic cholesterol, serum triglyceride, and cholesterol need to be measured in these mice to clarify how deleting IRE1 in the whole body can suppress hepatic steatosis, but liver-specific deletion of IRE1 promotes fatty liver. Without clarifying this issue, it is unclear how hepatic IRE1 deficiency can reduce steatosis and liver fibrosis.
      7. The authors suggested that ablation of IRE1 expression increased the levels of intracellular GFP-collagen as compared with control cells (Fig. 6C). How did the authors quantify the results? It is not clear if KO really increased the intracellular collagen levels. As the authors showed in Fig. 6C, WT-NT and WT-GFP-collagen-untreated have no overlap of green fluorescence. However, KO-NT and KO-GFP-collagen-untreated still have an overlap of green fluorescence, indicating that some cells are not GFP-positive. In this case, how could authors conclude that IRE1-KO cells have a more than 2-fold increase of green fluorescence change compared to WT? Besides, Fig. 6F suggested that secreted collagens increased in KO cells, contradicting the authors' previous data in Fig. 2, 4, and 5. Why did you use U2OS, Hepa1-6, and Huh7 in these studies? Should the collagen be secreted by hepatic stellate cells?
      8. In Fig. 7, the authors suggested that IRE1 KO promotes the levels of collagen inside cells using the whole cell lysate. Interestingly, they indicated that IRE1 deficiency suppressed TGFb1-induced collagen production using whole cell lysates (Fig. 4D). It is really confusing if IRE1 KO promotes or suppresses collagen production or secretion. Also, Fig. 7C did not support that IRE1-KO reduced collagen secretion. Besides, what cells did the authors use for these studies? Are they hepatic stellate cells?
      9. It is interesting to see the positive correlation between XBP1 and P4HB mRNA expression. However, it is still unclear if IRE1 deficiency could downregulate P4HB mRNA expression, given its RNase function. Thus, it would be essential to determine how IRE1 regulates P4HB expression before analyzing the correlation using human datasets. Besides, Fig. 8D did not suggest that XBP1 expression levels are correlated with chronic liver disease progression, given that its correlation scores with AST and ALT are 0 and -0.01, respectively.
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    BMP antagonist CHRDL2 enhances the cancer stem cell phenotype and increases chemotherapy resistance in Colorectal Cancer
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    1. EMBOpress 17 Jun 2024

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      Reply to the reviewers

      We thank the reviewers for taking the time to read and comprehensively evaluate our manuscript. We are pleased that, overall, they recognize the quality of our data and that it supports our conclusions. We are grateful for their comments, insights and advice and have revised the manuscript accordingly as described in the point-by-point response below. We believe that the revised manuscript is substantially improved by some experimental additions, additional replicates, improved analysis and increased clarity. Some key enhancements are as follows:

      Previously we had found increased expression of the WNT pathway following CHRDL2 treatment, using RNA seq. We have now demonstrated this experimentally using the cellular levels and localisation of β-catenin. Previously we had shown that overexpression of CHRDL2 increased resistance to common chemotherapy treatments, as well as irradiation in colorectal cell lines. We have now shown that cells surviving treatment show a further reduction SMAD1/5/8 phosphorylation indicating a selection for CHRLD2 high cells during the treatment. We have also demonstrated a decrease in chemotherapy sensitivity in intestinal organoids treated with secreted forms of CHRDL2.

      1. Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      Reviewer #1

      __Evidence, reproducibility and clarity __

      Clarkson and Lewis present data suggesting that overexpression of Chordin like 2 (CHRDL2) can affect colorectal cancer cell responses to chemotherapy agents, possibly by modulating stem-cell like pathways. I have the following comments:

      1. Fig. 1J-it is standard to show the images of cell migration-this is important here, given the modest effect of CHRDL2 overexpression here.

      We have now included 3 replicate control and CHRDL2 overexpressing cell images in this figure panel to support the quantification in the graph.

      Fig. 2A-the very small error bars for most of the data on the curves suggests these are n=1 experiments with multiple technical replicates to generate the error bars. Please clarify. The legend says n=3 with ANOVA analysis but no significance detected. Please clarify.

      All experiments in this figure were done with 5 technical replicates per experiment, this was replicated at least three times to give n=3 biological replicates. The error bars represent the standard error of the mean of these 3 biological replicates as stated in the legend. Some data points showed very little data variation, hence the small error bars. Raw data is available if requested.

      1. Fig. 2B-given the overlapping error bars here, how can there be a pWe have removed this representation of the data as it combined many different experiments with variable cell types and chemotherapeutics and it was difficult to carry out meaningful statistics. An overview of the data can be better seen in table form as shown in the revised figure 2B.

      Fig. 2G-did the authors try to estimate the concentration of CHRDL2 in the conditioned medium? Which cell line was used to generate this CM?

      Conditioned media was harvested from the matching transgenic cell lines with inducible CHRDL2. eg RKO cells were treated with media collected from doxycycline induced transgenic RKO cells whereas CaCO2 cells were treated with media from CaCO2 cells. The concentration of doxycycline was represented by ++ for 10ug/ml, the same notation we have used for directly induced cells treated with 10ug/ml dox.

      We did not try to quantify the absolute concentration of CHRDL2 but we have shown the relative amount on a Western blot normalised with a ponceau stain (quantification now included in supplementary figure 1).

      We have clarified our description of this experiment, inserting the following statement, "Conditioned media was harvested from corresponding cell lines with the inducible CHRDL2 transgene and the parental control cells. Induction of CHRDL2 to generate conditioned media was carried out using the same concentration and duration of doxycycline treatment as the cells in figure 2A. "

      Fig. 5-what is the potential mechanism for gene expression changes in response to CHRDL2 overexpression? Is it all due to BMP inhibition? More mechanistic detail would be welcome here.

      We have suggested other pathways involved in these functional effects based on our RNA seq data but at the moment it is not possible to say whether any changes are independent of BMP signaling. CHRDL2 is relatively understudied and as yet there is not much literature supporting BMP independent actions of CHRDL2. However, we have added some discussion and reference to an article suggesting interactions between CHRLD2 and YAP (Wang et al., 2022) including the following statement on page 17: "While the changes in BMP and WNT signaling shown in our GSEA analysis suggest that the effects of CHRDL2 in our system work directly through inhibition of BMP, it is not possible to rule out that some pathways are affected by BMP independent actions of CHRLD2. Indeed, Wang et al, suggest that CHRDL2 can directly alter phosphorylation and activity of YAP in gastric cancer cell lines, which merits further exploration (Wang et al., 2022)"

      Significance

      Unclear whether genetically engineered inducible overexpression has any real physiological significance but we all use cell models so this is OK.

      Reviewer #2

      __Evidence, reproducibility and clarity __

      Summary: In the manuscript entitled "BMP antagonist CHRDL2 enhances the cancer stem-cell phenotype and increases chemotherapy resistance in Colorectal Cancer" the authors demonstrated that Chordin-like 2 (CHDRL2), a secreted BMP antagonist, promotes a chemo-resistant colorectal cancer stem cell phenotype through the inhibition of BMP signaling. The authors took advantage of both 2D engineered colorectal cancer (CRC) cells and healthy murine 3D organoid systems. Specifically, the authors showed a decreased proliferation rate and reduced clonogenic capability upon overexpression of CHRDL2 in established human colon cancer cell lines. Subsequently, they identified a chemo-resistant phenotype upon standard therapies (5FU, Oxaliplatin and Irinotecan) in CHDRL2 overexpressing cells by performing MTS assay. The authors showed that this chemo-resistant phenotype is associated with ATM and RAD21 activation, supporting an induction of DNA damage signaling pathway. Of note, the authors assessed that the exposure of 3D murine organoid to CHRDL2 resulted in a stem-like phenotype induction accompanied by a reduction of the differentiated counterpart. From RNA-seq data analysis emerged the upregulation of genes associated to stemness and DNA repair pathways in CHRDL2 overexpressing cells.

      Major comments: 1. In the first paragraph of the result section authors assessed that "Colorectal adenocarcinoma cell lines were deliberately chosen to encompass a range of CHRDL2 expression levels and genetic mutations", without showing qRT-PCR or WB data on the differential expression levels of CHRDL2 in a panel of immortalized CRC cell lines. Authors should include these data to better support their choice.

      *We have now included some qRT-PCR in supplementary figure 1 alongside a table of some of the key driver mutations in each cell line. Western blotting of these cells shows only a very low concentration of CHRDL2 protein. As shown in figure 1B in the control columns, no significant protein expression is observed in any line. *

      In Figure 1F, authors described a reduction of cell proliferation in CRC cell lines expressing high levels of CHRDL2 only under low glucose conditions. Why did the authors perform the assay under these conditions? They should better argue this aspect and validated the role of CHRDL2 in metabolism rewiring by performing additional in vitro assays.

      We have removed this aspect of the paper as it does not add significantly to our overall conclusions and we can clearly see the effects of CHRDL2 overexpression under standard growth conditions (Figure 1G).

      The authors should evaluate the role of CHRDL2 in promoting a stem-like phenotype in human colon cancer stem cells freshly isolated from patients and characterized.

      We would very much like to do experiments such as this but it is beyond the scope of this study and will be included in upcoming grant proposals.

      In order to confirm the data obtained on 3D murine organoids system obtained from normal Intestinal Stem Cells, authors should investigate the stemness induction, driven by CHRDL2, also in human intestinal organoids.

      Experiments using human intestinal organoids are currently planned and ethical approval applications and grant proposals are underway for future experiments of this nature.

      The authors should evaluate the oncogenic role of CHRDL2, through the maintenance of stemness, by performing orthotopic or subcutaneous experiments in vivo model.

      Similarly, this is not possible for this manuscript but is planned for the future alongside a transgenic mouse model of inducible CHRDL2 overexpression in the intestine.

      BMPs proteins are part of a very broad protein family. In the introduction section, authors should indicate the specific BMP protein on which CHRDL2 exerts its inhibitory function. Moreover, they should have assessed BMP protein levels in CACO2, LS180, COLO320 and RKO cell lines.

      We have clarified the interactions between CHRDL2 and specific BMPs in the introduction. We have not specifically assessed the BMP protein levels in our cells however we have now included an analysis of expression data from the Cancer Cell Line Encyclopedia in supplementary figure 1 C.

      In first panel, the authors should quantify the secreted levels of CHRDL2 in the media of overexpressing CHRDL2 cell lines.

      We have done this using the ponceau staining as a loading control and the results are displayed (supplementary figure 1).

      In Figure 2D the authors should use the appropriate controls and describe this with more details in results section.

      In this figure we have used Hoechst staining followed by FACs analysis to identify the cell cycle profile of our CHRDL2 treated cells. We have improved the description of this in the methods section. Appropriate controls for staining, both negative and positive, are used when setting up the analysis for this experiment. The cell cycle profile is calculated using the Novocyte in house software. We have now included the histogram plots in the main figure to clarify these data in figure 2D.

      In Figure 3A, the authors should have performed the assay by choosing IC50.

      *We attempted these experiments with the IC50 levels, however the high amount of cell death and frequency of apoptotic cells meant that clear images were difficult to obtain. We therefore reduced the concentrations and still had very measurable effects. *

      In Supplementary Fig. 4A-B. the results are unclear. The control cell lines are already chemo resistant.

      Again, we used IC25 levels of the drugs so that our cells were damaged but still live throughout the experiment. This has been explained on page 10.

      The authors should review and add statistical analysis in both main and supplementary figures.

      *We have now added additional details about statistical analysis throughout the figures, legend and main text, showing all significance levels as well as non-significance for each data set. * Minor comments: 1. The quality of immunofluorescence and WB images should be implemented, and in the immunofluorescence panels scale bars should be added.

      We have added or improved scale bars on each immunofluorescence image. Western blot images have been improved.

      In the graphical abstract authors reported that CHRDL2 overexpression increase WNT and EMT pathways, without performing any specific assay to demonstrate this. Authors should correct and graphically improve the graphical abstract.

      *This is a good point and we have now carried out Beta-catenin immunofluorescence as a measure of WNT signaling on both our cancer cell lines - showing an increase in nuclear beta-catenin (figure 1J and K), and our organoids - showing an increase in overall levels and cytoplasmic staining (Figure 4 F). In terms of EMT markers we have carried out immunofluorescence on IQGAP1 (Figure 1K). IQGAP1 is significantly upregulated in CHRDL2 cells, reflecting its role in reduced cell adhesion and increased migration. This correlates with our data showing increased cellular migration as well as the increase in EMT related transcription in our RNAseq data. *

      The term "significantly" in the discussion section is inappropriately referred to data showed in the histogram in Figure 1J. Moreover, in Figure 1Jthe authors should delete from the y-axis the term "corrected".

      We have changed significantly to substantially

      The term "significant" in discussion is inappropriately referred to BMI1 expression level if compared to the histogram in Figure 4G.

      We have changed significantly to "a trend to increase"

      In Figure 2C the authors should add the unit of measurement (fold over control) in the table.

      We have done this

      In Figure 4E the authors should add the figure legend reporting OLFM4 protein.

      We have done this

      The authors should include few sentences summarizing the findings at the end of each paragraph.

      We have added short summaries at the start or end of each section to improve the flow of the results section.

      Significance

      General assessment: Overall, the work is aimed to elucidate the role of CHRDL2 already considered a poor prognosis biomarker involved in the promotion of CRC (PMID: 28009989), in promoting stem-like properties. The authors elucidated new additional insights into the molecular mechanisms regulating stemness phenotype induced by the BMP antagonist CHRDL2 in CRC. The authors include in the study a large amount of data, which only partially support their hypothesis. However, this manuscript lacks organization and coherence, making it challenging to follow and read. Numerous concerns need to be addressed, along with some sentences to rephrase in the result and discussion sections.

      Advance: The manuscript reported some functional insights on the role of CHRDL2 in colorectal cancer, but additional data should be added to support authors 'conclusions.

      Audience: The manuscript is suggested for basic research scientists.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)):____ __ Summary BMP antagonist CHRDL2 enhances the cancer stem-cell phenotype and increases chemotherapy resistance in Colorectal Cancer Eloise Clarkson et al. The manuscript explored the function of CHRDL2, a BMP antagonist, on colorectal cancer (CRC). The authors found that CHRDL2 overexpression can enhance the survival of CRC cells during chemotherapy and irradiation treatment with elevated levels of stem-cell markers and reduced differentiation. Further RNA-seq analysis revealed that CHRDL2 increased the expression of stem-cell markers, WNT signaling and other well-established cancer-associated pathways. Overall, the manuscript is well-written and presented. I have some suggestions:

      Major points:

      1. The authors assert BMP antagonism was demonstrated by assessing levels of phosphorylated SMAD1/5 (Figure 1G). However, the immunoblotting assay only depicted P-SMAD 1/5 levels and B-ACTIN as internal control. It's suggested to include total-SMAD1/5 immunoblotting as an internal control to further support the claim of BMP antagonism.

      The reviewer is correct that this is the best control. Western blotting has now been performed with total SMAD1 protein expression used as an internal control and this is shown in Figure 1D and Supplementary figure 1F

      The authors argue that CHRDL2 overexpression reduced the proliferation of CRC cell lines, as evidenced by cell proliferation assays. However, from Figure 1E, the reduction in proliferation appears insignificant. It would be beneficial to perform one-way ANOVA tests on each time point for CHRDL2+ and CHRDL2++ with Control in Figure 1E to ascertain significance.

      *We now have repeated this experiment to reduce variability and have also provided two-way ANOVA analysis between Control and CHRDL2+ and Control and CHRDL2++. One-way ANOVA at timepoint 96hr also provided with details in the figure legend. *

      The findings indicating that overexpressing CHRDL2 can confer resistance to chemotherapy in CRC cells (Figure 2A-C) are noteworthy. To deepen the understanding of BMP signaling in cancer stemness and the molecular underpinning of CHRDL2 antagonism, additional western blot assays on P-SMAD1/5 with CHRDL2 overexpression and drug treatment are recommended.

      *Western blotting of P-SMAD1/5 upon cells treated with IC50 5FU has now been performed in figure 2C (in the same experiment as the revised panels in figure 1D). The data suggest that CHRDL2 overexpressing cells able to survive chemotherapy have higher levels of P-SMAD1/5 reduction compared to that of untreated cells, strongly suggesting that chemotherapy treatment acts to select the cells with the highest CHRDL2 expression. We thank reviewer 3 for this suggested experiment and have included further discussion on this on page 9. *

      The assertion that extrinsic CHRDL2 addition diminishes differentiation and enhances stem-cell numbers in an intestinal organoid model is intriguing. As BMP signaling inhibition contributes to intestinal cell stemness, incorporating additional layers for BMP antagonism of CHRDL2 on intestinal organoids through immunoblotting or real-time quantitative PCR for treated organoids would augment the conclusions.

      As stated in the response to reviewer 2, we have investigated Beta-catenin in our organoids following CHRDL2 treatment using immunofluorescence and find that the levels are increased with the staining shifting from the membrane to the cytoplasm and nucleus (Figure 4F).

      The authors claim CHRDL2 overexpression can decrease BMP signaling based on GSEA analysis (Figure 5E). However, the GSEA results did not demonstrate the downregulation of BMP signaling. Reanalysis of this GSEA analysis is warranted.

      *We agree with this point and have changed the description of this result since the gene set covers both positive and negative regulators of the BMP pathway. We cannot conclusively say from this RNAseq data set that BMP signaling is "downregulated", however since SMAD phosphorylation is increased and nuclear beta-catenin is increased, overall we suggest that the changes we see are likely to represent the effects of decreased BMP signaling along with increased WNT signaling. *

      Minor Points:

      6.Provide the threshold/cutoff values chosen for differential expressed genes (DEGs) in CHRDL2+ and CHRDL2++ RNA-seq compared with control cells. Explain the minimal overlap between CHRDL2 LOW and CHRDL2 HIGH DEGs. Consider presenting all DEGs in CHRDL2 LOW and CHRDL2 HIGH compared with control cells in one gene expression heatmap for better visualization.

      We have now provided the cutoff values for the DEGs in the legend for figure 5 (PThe minimal overlap of DEGs in the low and high expressing cells is an interesting point. We hypothesize that this may be related to the different effects of intermediate vs high levels of WNT signaling that occurs in colon cancer cells, frequently discussed in the literature as the "Just right hypothesis" (Lamlum et al. 1999, Albuquerque et al., 2002, Lewis et al., 2010). However, we haven't included this in the discussion as it merits further exploration. However, we have mainly focused on specific genes that are modified in both data sets, which are more likely to be the direct result of CHRDL2 modification. *

      After DEGs analysis, perform Gene Ontology (GO) analysis on these DEGs to further investigate possible gene functions rather than selectively discussing some genes, enhancing understanding of CHRDL2 functions in CRC cells.

      We have carried out this analysis using a variety of tools and have now included a Gene Ontology Panther analysis as supplementary figure 7. We have included a comment on this in the text on page 14 saying "Gene ontology analysis supports these findings with enrichment in biological processes such as cellular adhesion, apoptosis and differentiation. "

      Conduct similar experiments in both 2D culture and organoid systems, if feasible, to provide more comprehensive insights into CHRDL2's oncogenic roles in CRC tumor progression.

      *We have now performed chemotherapy treatment on our organoid systems, and have found that organoids with extrinsic CHRDL2 addition have a higher survival rate after chemotherapy compared to a control (Figure 4H and I). *

      Label significance (*, **, ***, and n.s.) for every CRC cell line treated with CHRDL2 in Figure 2D, 2F, 2J, 4G, 5D, and 5F.

      We have done this

      Label the antibodies with different colors used for immunofluorescence in the figure text in Figure 4E.

      We have done this

      * * Include replicate dots for the Control group in the bar plots in Figure 1F and 2B.

      We have done this

      * * Add scale bars in Figure 3A and correct similar issues in other figures if applicable.

      We have done this

      * *13.Correct grammar and punctuation mistakes throughout the manuscript. For example:

      We have done this and further proofread our revised manuscript

      Page 7: "As seen in Figure 1J, CHRDL2 overexpression significantly increased the number of migrated cells (P *We have now added additional details about statistical analysis throughout the figures, legend and main text, showing all significance levels as well as non-significance for each data set. * Reviewer #3 (Significance (Required)):

      The current study presents compelling evidence demonstrating that BMP signaling antagonist CHRDL2 enhances colon stem cell survival in colorectal cancer cell lines and organoid models. Further validation through CRC mouse models could offer invaluable insights into the clinical relevance and therapeutic implications of CHRDL2 in colorectal cancer.

      PeerReviewed
    2. EMBOpress 17 Jun 2024

      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 #3

      Evidence, reproducibility and clarity

      Summary

      BMP antagonist CHRDL2 enhances the cancer stem-cell phenotype and increases chemotherapy resistance in Colorectal Cancer Eloise Clarkson et al. The manuscript explored the function of CHRDL2, a BMP antagonist, on colorectal cancer (CRC). The authors found that CHRDL2 overexpression can enhance the survival of CRC cells during chemotherapy and irradiation treatment with elevated levels of stem-cell markers and reduced differentiation. Further RNA-seq analysis revealed that CHRDL2 increased the expression of stem-cell markers, WNT signaling and other well-established cancer-associated pathways. Overall, the manuscript is well-written and presented. I have some suggestions:

      Major points:

      1. The authors assert BMP antagonism was demonstrated by assessing levels of phosphorylated SMAD1/5 (Figure 1G). However, the immunoblotting assay only depicted P-SMAD 1/5 levels and B-ACTIN as internal control. It's suggested to include total-SMAD1/5 immunoblotting as an internal control to further support the claim of BMP antagonism.
      2. The authors argue that CHRDL2 overexpression reduced the proliferation of CRC cell lines, as evidenced by cell proliferation assays. However, from Figure 1E, the reduction in proliferation appears insignificant. It would be beneficial to perform one-way ANOVA tests on each time point for CHRDL2+ and CHRDL2++ with Control in Figure 1E to ascertain significance.
      3. The findings indicating that overexpressing CHRDL2 can confer resistance to chemotherapy in CRC cells (Figure 2A-C) are noteworthy. To deepen the understanding of BMP signaling in cancer stemness and the molecular underpinning of CHRDL2 antagonism, additional western blot assays on P-SMAD1/5 with CHRDL2 overexpression and drug treatment are recommended.
      4. The assertion that extrinsic CHRDL2 addition diminishes differentiation and enhances stem-cell numbers in an intestinal organoid model is intriguing. As BMP signaling inhibition contributes to intestinal cell stemness, incorporating additional layers for BMP antagonism of CHRDL2 on intestinal organoids through immunoblotting or real-time quantitative PCR for treated organoids would augment the conclusions.
      5. The authors claim CHRDL2 overexpression can decrease BMP signaling based on GSEA analysis (Figure 5E). However, the GSEA results did not demonstrate the downregulation of BMP signaling. Reanalysis of this GSEA analysis is warranted.

      Minor Points:

      6.Provide the threshold/cutoff values chosen for differential expressed genes (DEGs) in CHRDL2+ and CHRDL2++ RNA-seq compared with control cells. Explain the minimal overlap between CHRDL2 LOW and CHRDL2 HIGH DEGs. Consider presenting all DEGs in CHRDL2 LOW and CHRDL2 HIGH compared with control cells in one gene expression heatmap for better visualization. 7. After DEGs analysis, perform Gene Ontology (GO) analysis on these DEGs to further investigate possible gene functions rather than selectively discussing some genes, enhancing understanding of CHRDL2 functions in CRC cells. 8. Conduct similar experiments in both 2D culture and organoid systems, if feasible, to provide more comprehensive insights into CHRDL2's oncogenic roles in CRC tumor progression. 9. Label significance (, , **, and n.s.) for every CRC cell line treated with CHRDL2 in Figure 2D, 2F, 2J, 4G, 5D, and 5F. 10. Label the antibodies with different colors used for immunofluorescence in the figure text in Figure 4E. 11. Include replicate dots for the Control group in the bar plots in Figure 1F and 2B. 12. Add scale bars in Figure 3A and correct similar issues in other figures if applicable. 13.Correct grammar and punctuation mistakes throughout the manuscript. For example:

      Page 7: "As seen in Figure 1J, CHRDL2 overexpression significantly increased the number of migrated cells (P

      Page 7: "As seen in Figure 1J, CHRDL2 overexpression significantly increased the number of migrated cells (P

      Page 7: "As seen in Figure 1J, CHRDL2 overexpression significantly increased the number of migrated cells (P < 0.0449)," suggesting increased migratory ability, a hallmark of cancer stem cells."

      Page 8: "CHRDL2 overexpression resulted in an approximate twofold increase in IC50 values compared to control cells (P < 0.001)."

      Page 10: "As seen in Figure 4B, upon the" should be corrected to "Figure 4B."

      1. Specify the statistical methods or estimates used for determining statistical significance.

      Significance

      The current study presents compelling evidence demonstrating that BMP signaling antagonist CHRDL2 enhances colon stem cell survival in colorectal cancer cell lines and organoid models. Further validation through CRC mouse models could offer invaluable insights into the clinical relevance and therapeutic implications of CHRDL2 in colorectal cancer.

      PeerReviewed
    3. EMBOpress 17 Jun 2024

      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 #2

      Evidence, reproducibility and clarity

      Summary:

      In the manuscript entitled "BMP antagonist CHRDL2 enhances the cancer stem-cell phenotype and increases chemotherapy resistance in Colorectal Cancer" the authors demonstrated that Chordin-like 2 (CHDRL2), a secreted BMP antagonist, promotes a chemo-resistant colorectal cancer stem cell phenotype through the inhibition of BMP signaling. The authors took advantage of both 2D engineered colorectal cancer (CRC) cells and healthy murine 3D organoid systems. Specifically, the authors showed a decreased proliferation rate and reduced clonogenic capability upon overexpression of CHRDL2 in established human colon cancer cell lines. Subsequently, they identified a chemo-resistant phenotype upon standard therapies (5FU, Oxaliplatin and Irinotecan) in CHDRL2 overexpressing cells by performing MTS assay. The authors showed that this chemo-resistant phenotype is associated with ATM and RAD21 activation, supporting an induction of DNA damage signaling pathway. Of note, the authors assessed that the exposure of 3D murine organoid to CHRDL2 resulted in a stem-like phenotype induction accompanied by a reduction of the differentiated counterpart. From RNA-seq data analysis emerged the upregulation of genes associated to stemness and DNA repair pathways in CHRDL2 overexpressing cells.

      Major comments:

      1. In the first paragraph of the result section authors assessed that "Colorectal adenocarcinoma cell lines were deliberately chosen to encompass a range of CHRDL2 expression levels and genetic mutations", without showing qRT-PCR or WB data on the differential expression levels of CHRDL2 in a panel of immortalized CRC cell lines. Authors should include these data to better support their choice.
      2. In Figure 1F, authors described a reduction of cell proliferation in CRC cell lines expressing high levels of CHRDL2 only under low glucose conditions. Why did the authors perform the assay under these conditions? They should better argue this aspect and validated the role of CHRDL2 in metabolism rewiring by performing additional in vitro assays.
      3. The authors should evaluate the role of CHRDL2 in promoting a stem-like phenotype in human colon cancer stem cells freshly isolated from patients and characterized.
      4. In order to confirm the data obtained on 3D murine organoids system obtained from normal Intestinal Stem Cells, authors should investigate the stemness induction, driven by CHRDL2, also in human intestinal organoids.
      5. The authors should evaluate the oncogenic role of CHRDL2, through the maintenance of stemness, by performing orthotopic or subcutaneous experiments in vivo model.
      6. BMPs proteins are part of a very broad protein family. In the introduction section, authors should indicate the specific BMP protein on which CHRDL2 exerts its inhibitory function. Moreover, they should have assessed BMP protein levels in CACO2, LS180, COLO320 and RKO cell lines.
      7. In first panel, the authors should quantify the secreted levels of CHRDL2 in the media of overexpressing CHRDL2 cell lines.
      8. In Figure 2D the authors should use the appropriate controls and describe this with more details in results section.
      9. In Figure 3A, the authors should have performed the assay by choosing IC50.
      10. In Supplementary Fig. 4A-B. the results are unclear. The control cell lines are already chemoresistant.
      11. The authors should review and add statistical analysis in both main and supplementary figures.

      Minor comments:

      1. The quality of immunofluorescence and WB images should be implemented, and in the immunofluorescence panels scale bars should be added.
      2. In the graphical abstract authors reported that CHRDL2 overexpression increase WNT and EMT pathways, without performing any specific assay to demonstrate this. Authors should correct and graphically improve the graphical abstract.
      3. The term "significantly" in the discussion section is inappropriately referred to data showed in the histogram in Figure 1J. Moreover, in Figure 1Jthe authors should delete from the y-axis the term "corrected".
      4. The term "significant" in discussion is inappropriately referred to BMI1 expression level if compared to the histogram in Figure 4G.
      5. In Figure 2C the authors should add the unit of measurement (fold over control) in the table.
      6. In Figure 4E the authors should add the figure legend reporting OLFM4 protein.
      7. The authors should include few sentences summarizing the findings at the end of each paragraph.

      Significance

      General assessment:

      Overall, the work is aimed to elucidate the role of CHRDL2 already considered a poor prognosis biomarker involved in the promotion of CRC (PMID: 28009989), in promoting stem-like properties. The authors elucidated new additional insights into the molecular mechanisms regulating stemness phenotype induced by the BMP antagonist CHRDL2 in CRC. The authors include in the study a large amount of data, which only partially support their hypothesis. However, this manuscript lacks organization and coherence, making it challenging to follow and read. Numerous concerns need to be addressed, along with some sentences to rephrase in the result and discussion sections.

      Advance: The manuscript reported some functional insights on the role of CHRDL2 in colorectal cancer, but additional data should be added to support authors 'conclusions.

      Audience: The manuscript is suggested for basic research scientists.

      PeerReviewed
    4. EMBOpress 17 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Clarkson and Lewis present data suggesting that overexpression of Chordin like 2 (CHRDL2) can affect colorectal cancer cell responses to chemotherapy agents, possibly by modulating stem-cell like pathways. I have the following comments:

      1. Fig. 1J-it is standard to show the images of cell migration-this is important here, given the modest effect of CHRDL2 overexpression here.
      2. Fig. 2A-the very small error bars for most of the data on the curves suggests these are n=1 experiments with multiple technical replicates to generate the error bars. Please clarify. The legend says n=3 with ANOVA analysis but no significance detected. Please clarify.
      3. Fig. 2B-given the overlapping error bars here, how can there be a p<0.01 between the groups?
      4. Fig. 2G-did the authors try to estimate the concentration of CHRDL2 in the conditioned medium? Which cell line was used to generate this CM?
      5. Fig. 5-what is the potential mechanism for gene expression changes in response to CHRDL2 overexpression? Is it all due to BMP inhibition? More mechanistic detail would be welcome here.

      Significance

      Unclear whether genetically engineered inducible overexpression has any real physiological significance but we all use cell models so this is OK.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.01.23.576664v2
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    The specific AMPK activator A-769662 ameliorates pathological phenotypes following mitochondrial DNA depletion
    4
    1. EMBOpress 17 Jun 2024

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      Reply to the reviewers

      The authors do not wish to provide a response at this time.

      PeerReviewed
    2. EMBOpress 17 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      The authors investigate the role of the AMP-activated protein kinase (AMPK) in mitochondrial dysfunction. Using HEK293T cells as model system they induce expression of either the wild-type or a dominant-negative variant of the mitochondrial DNA polymerase, which results in depletion of mtDNA and a decreased mitochondrial membrane potential. Using different time points of Pol induction they correlate the mitochondrial defects with activation of AMPK and make the interesting observation that only the mitochondrial associated fraction of AMPK becomes activated at an early stage of mitochondrial dysfunction. The authors then apply a known AMP activator (A-769662) and assess its impact on mtDNA levels and respiratory chain subunit steady state levels. Finally, they compare the findings using the HEK cells with patient derived fibroblasts, which show the same response to the activator.

      Regarding the so far provided data I have the following concerns:

      • I do not agree with the statement that the mechanisms in the HEK and patient cells are different. First of all, there is no analysis of the mechanism in the HEK cells nor the patient fibroblasts. Secondly, the control cell line (Pol WT overexpression) is also showing a decrease in mitochondrial membrane potential, but no change in mtDNA - which is fully reflecting the observation of the patient cells.
      • Figure 1H-J: the authors claim that CIV activity is decreasing. However, CIV is virtually absent in these samples and therefore the statement that CIV activity is decreased is not correct.
      • It is not clear why the authors used the dominant negative D1135A variant in the HEK system and not the most common dominant patient mutations (of which they in the end use the patient fibroblasts).
      • Supplemental Figure S1A/B: Which time point of induction is shown here?
      • The rho zero cell line and the control UV treatment are not described in the materials and methods section.

      Significance

      The observation that mitochondrial-associated AMPK reacts much earlier than the global AMPK pool to the mitochondrial dysfunction is interesting. The other observations described in the manuscript were rather to be expected given previous publications. Overall, the study primarily provides descriptive findings, which, in my view, seem preliminary at this stage and requires significant revisions for it to be truly valuable to the scientific community.

      At least some molecular insight into the regulation of the different cellular AMPK pools or detailed analysis on how the activator impacts on mtDNA or the general mechanism that results in stabilization of the mitochondrial membrane potential are necessary to provide sufficient novel findings for publication. This additional analysis would be necessary to strengthen the study's conclusions and broaden its relevance to a larger readership.

      PeerReviewed
    3. EMBOpress 17 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The authors aimed to investigate the functional consequences of AMPK agonist, A-769662, in improving the cellular energetic response to mitochondrial DNA depletion. AMP kinase plays a crucial role in switching the metabolic programming in the cells upon energetic stresses. It drives the activation of transcription factors of the mitochondrial genome as well as nuclear genes important for mitochondrial biogenesis (Herzig and Shaw., 2018, Bonekamp et al., 2021). Previous studies have shown that triggering the AMPK cascade has positive outcomes in mitochondrial disease models (Peralta et a., 2016, Moore et al., 2020). However, the mechanistic basis of their impact on mitochondrial function, especially mtDNA is not known.

      Brief Summary:

      In this study, the authors characterize the dynamics of mitochondrial dysfunction in response to severe mtDNA depletion, using a cell model and report that A-769662, a non-AMP mimetic AMPK agonist maintains cellular energy homeostasis by stimulating the AMPK cascade to restore membrane potential in mtDNA depleted cells. The positive effect was observed only in patient-derived, mtDNA-depleted cells and absent in control cells, suggesting that A-769662 mediates mitochondrial activity and cellular function via partially different mechanisms.

      Major Results:

      • The authors used a previously established inducible cell line to transiently express a dominant negative mutant of the mitochondrial DNA polymerase, Poly, as a model system for mtDNA depletion. Compared to the wildtype cells, mtDNA copy number, membrane potential, assembly and levels of respiratory chain complexes I, III and IV were severely reduced in the PolyD1135A cells (Figure 1A-K).
      • The authors checked the relative ratio of AMP/ADP and ATP in the PolyD1135A cells and found that ADP levels were elevated, as expected (Figure 2A). Consequently, the levels of phosphorylated AMPK in/at (?) the mitochondria were also increased, in good correlation with the depletion of mtDNA levels and respiratory complexes after 3 days of induction (Figure 2B-E). Activation of the pAMPK pathway was further confirmed by the increased levels of AMPK substrate ACC. However, metabolite levels and cell cycle profiles are mildly altered in the PolyD1135A cells, suggesting that the activation of mitochondrial AMPK is an early response to mtDNA dysfunction.
      • Chemical activation of AMPK by agonist A-769662 had a sustained positive effect on the membrane potential in both induced and uninduced cells. This was specific to AMPK signalling as evidenced by no change in membrane potential in cells transfected with AMPK siRNA (Figure 3A-C). However, the A-769662 treatment was insufficient to rescue the proliferation defects in the PolyD1135A mutant cells (Figure 3D), suggesting that the growth defect is independent of AMPK activation.
      • A-769662 treatment for 48 or 72h in PolyD1135A improved mtDNA copy number and respiratory complex subunit expression, while having no effect on control cells (Figure 4A-G). Upon A-769662 treatment, patient-derived mutant cell lines showed no change in mtDNA levels (Figure 4H). Interestingly, membrane potential was enhanced in both control and patient cell lines (Figure 4I), suggesting an overall activation of mitochondrial function and not a specific response to restoring mtDNA.

      Taken together the manuscript by Carvalho et al., proposes a stimulatory effect of AMP agonist, A-769662 on mtDNA depletion. However, since the model is not consistent in different model systems, the authors should provide stronger evidence for the utility of A-769662 as a therapeutic possibility for mtDNA disorders. Moreover, some mechanistical molecular insights into these largely descriptive results must be presented in a revised version. What drives AMPK localization to mitochondria? Is this kinase imported? Is it just attached? What regulates the distribution of AMPK between their different locations?

      Significance

      Major points:

      • The effect of A-769662 on mtDNA levels in the FlipIn-TRex cell line, harboring a severe mutation and clinically-relevant patient-derived cell lines are not comparable (Figure4A and 4H), suggesting that the amelioration of mitochondrial defect is probably dependent on the extent of mtDNA damage. The FlipIn system shows a loss of almost 85% of mtDNA on day 3 of induction (Figure 1A) whereas the patient-derived cells retain almost 60% of the mtDNA (Figure 4H). The authors argue that the two systems are not comparable. A good control would be to check an inducible FlipIn-TRex cell line with the same patient-derived mutations or alter the induction system, with a shorter induction time or reduced concentration of doxycycline, to have comparable levels of mtDNA depletion.
      • A more thorough investigation of A-769662 in different cell models of mtDNA dysfunction, possibly different disease-specific mutations in Poly, or cell types which contain AMPK complexes with -subunits (irresponsive to A-769662 stimulation) will be needed to claim its therapeutic merit.
      • To substantiate the claim that the downstream effect of A-769662 treatment is dependent on the metabolic context of the cell, it would be necessary to test the levels of crucial metabolites like mtDNA transcripts, ATP, NADH, in addition to dNTPs tested in the study. It would also help to compare the levels of these metabolites in of PolyD1135A cells, grown in galactose medium.
      • In Figure 2C, TFAM is nearly absent in the mitochondrial fraction of PolyD1135A cells, since Poly dysfunction triggers a reduced expression of the transcription machinery. Considering the mtDNA level upregulation is mild after if A-769662 treatment (about 8%, Figure 4A), it would be worthwhile to check if A-769662 could alter transcript levels of mtDNA and/or expression of mitochondrial transcription factors TFAM and TF2B.

      Minor points:

      • The data from Figure 1 conclusively show defects in mtDNA. It would be necessary to compare OCR, ROS and cellular ATP levels to demonstrate the extent of mitochondrial dysfunction in this model due to mtDNA depletion.
      • To further delineate the differences in mitochondrial bioenergetics in PolyD1135A , cells should be grown in galactose media and probed for respiratory fitness.
      • The study uses 100uM of A-769662 in the cell assays (Figures 3 and 4) and 200uM to test the activation of AMPK substrate ACC (Figure S2A-C). The authors should explain if a dose-dependent study was performed and how the concentration of A-769662 to be used was determined.

      A-769662 is a known AMPK activator with possible therapeutic effects in metabolic disorders, type II diabetes (Cool et al., 2006, Görransson et al., 2007): However, due to the wide range of effects it may have, it would be necessary to get to the molecular basis of how A-769662 targets mtDNA depletion. This study is a nice starting point to further probe into the benefits of A-769662, however it is not (yet) conclusive and definitely needs the clarification of the underlying molecular mechanisms.

      PeerReviewed
    4. EMBOpress 17 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript by Carvalho and colleagues addresses how an increase in AMPK signaling, triggered by the agonist A769662, contributes to ameliorate cellular phenotypes caused by mtDNA depletion. The authors build on previously established cellular models of mtDNA depletion, and use subcellular fractions in an attempt to distinguish pools of AMPK associated with different organelles. The data is very clearly presented, and the western blot data shown is of high quality. The authors also use cells from two patients with mtDNA depletion, in which they stimulate AMPK using A769662. The overall conclusion is that AMPK stimulation in the cell models with mtDNA depletion is advantageous to minimize the disease-related phenotypes.

      There is one fundamental weakness: there are several intracellular AMPK pools described, the major ones being in the cytoplasm, or associated with mitochondria, or with lysosomes, or in the nucleus. However, and importantly, while the authors convincingly show that there is no cytoplasm in their mitochondrial fractions, they do not control for the presence of lysosomal proteins. For the conclusions to be valid, it is absolutely essential to distinguish the effects of mitochondria-associated AMPK from lysosome-associated AMPK, because they may have different effectors and because they are activated by different mechanisms. Furthermore, the authors do not show what happens to AMPK in the patient cells, and this would be very informative. Finally, it would be important to put these findings in the context of other studies on AMPK signaling in response to other mitochondrial perturbations and that find AMPK to be down-regulated in chronic mitochondrial respiratory chain deficiency, as well as to more carefully reference the different intracellular AMPK pools. These studies might help to strengthen the discussion, given that the authors find AMPK signaling to be increased but show that increasing it pharmacologically has benefits - is A769662 activating different pools of AMPK?

      Significance

      The manuscript addresses an important question: how does the metabolic hub AMPK contribute to the phenotypes observed in chronic mitochondrial malfunction. Most of the studies on AMPK and mitochondrial malfunction focus on acute effects, which are not a model for mitochondrial diseases. Therefore, focusing on chronic effects is important to understand the long term consequences on AMPK signaling and its downstream signaling. Furthermore, if AMPK reactivation is beneficial (as this study proposes and other studies have also shown in other models of chronic mitochondrial malfunction), then this can become a new important therapeutic strategy.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.03.14.584413v2
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    In-silico docking with serine protease inhibitors (SERPINs) identifies alternate protease targets with significance for SARS-CoV-2
    3
    1. EMBOpress 14 Jun 2024

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      Reply to the reviewers

      1. General Statements

      *We thank the reviewers for the overwhelmingly positive feedback on our initial submission. *

      • *

      Reviewer 1: “Overall this is a very simple, although extensive and excellent, study analyzing a wide range of data form (sic) patients with bronchoalveolar lavage and epithelial cell samples, human epithelial cell cultures after infection with a range of respiratory viruses as well as the development of a 3D in silico analysis of potential protease and serpin interactions.”

      Reviewer 2: “Overall, this paper will be interesting to a specialized audience that is interested in SERPIN function. The SERPIN expression data during viral infection, discovery of CTSL as a target of PAI-1, and evidence that PAI-1 can inhibit SARS-CoV-2 replication, will move that field forward.”

      No new experiments were requested, but some were either suggested or explicitly marked optional. We thus focused the initial 4-week-revision on performing new experiments aimed to enhance our study’s significance and impact by validating the heart of our study: the data from the in-silico docking screen.

      Reviewer 1: “Further analysis of the detected proteases that are reported here to bind to PAI-1 would be of great interest.”

      Reviewer 2: “It is exciting that they predicted CTSL as a target of PAI-1, but it is not obvious that this is a generalizable approach without further hypothesis testing.”

      • *

      Thus, we performed additional protease activity assays to validate SERPIN-protease pairs from the in-silico-screen. The results elevate our study above the proof-of-principle state. Beyond their described roles in infectious disease, the two SERPINs that are now tested in more detail (SERPINB2, plasminogen activator inhibitor 2 and SERPINE1, plasminogen activator inhibitor 1) also play critical roles in cancer, neurodegeneration, aging, and cardiovascular disease. (Bouton et al., EMBO Mol Med 2023 Vol. 15 No. 6; Zhang et al., EMBO Mol Med 2023 Vol. 15 No. 9; Bode et al., EMBO Journal 1986 Vol. 5 No. 10; Uhl et al., EMBO Mol Med 2021 Vol. 13 No. 6). Given these multifaceted roles, we anticipate that our discovery of new SERPIN-protease binders and non-binders will advance various areas of human disease driven by SERPIN biology.

      2. Description of the planned revisions

      *We believe that the planned revisions outlined below can be finalized within 1-2 months. *

      • *

      Reviewer 1: “Further analysis of the detected proteases that are reported here to bind to PAI-1 would be of great interest.”

      *At the time of the 30-day revision, recombinant SERPINB1 (LEI) and SERPING1 (C1-INH) were still backordered with an estimated shipping date the week of resubmission. Once delivered, we will perform protease activity assays with LEI or C1-INH and uPA, TMPRSS2, Cathepsin L, and Cathepsin B to bring up the number of validated SERPIN:protease interactions from 8 to 16. *

      Reviewer 2, major points:

      9) Further, to strengthen the conclusions of this data the authors should include additional controls. One would be to use trixplanin as they did in previous panels to show that PAI-1 is necessary. Further, if the authors generate mutant PAI-1 that is unable to inhibit TMPRSS2 (see comment 11 below), they could also use this as a control to show the necessity of functional PAI-1.

      *We agree that these optional experiments would increase rigor. We generated plasmids containing mutated PAI-1 that we can use in spike cleavage assays as suggested and can perform this experiment. *

      *We can unfortunately not use triplaxinin on cells, as our preliminary data show that it is quite cytotoxic at the concentrations required to inhibit PAI-1. *

      10) For Figures 4I-J, is it possible to also blot for S1 cleavage? If possible, this optional data would be helpful to understand whether the entire cleavage process is disrupted or only S2 to S2' especially given that visually it appears as if the full length is more depleted in the condition with PAI-1 suggesting that it is cleaving spike better into S1 and S2. Could also suggest that the dynamics of cleavage are shifted rather than impaired?

      *S1 cleavage is shown indirectly in (now) Figure 5f,g – the main product of S1 cleavage is the fragment annotated as S2. Due to high levels of endogenous furin in BHK cells, this cleavage always occurs in this experimental setting. It is true that we have not shown the effects of PAI-1 inhibits on S1 cleavage– we can include that control in the above optional experiment (point 9). We do not expect PAI-1 to have an effect on S1 cleavage, as it is well-established that it does not inhibit furin. *

      • *

      Reviewer 2, minor points

      7) As a supplemental figure, can the authors show a complex blot (similar to Figure 4F) for CTSB to show that is does not complex with PAI-1.

      *Purified active CTSB is not commercially available, but we can attempt to perform gel shift analysis on the samples from the in vitro protease assay. Due to the presence of proteinaceous substrate in these samples, we have previously observed lot of background on the gel, but we can attempt it and include it in a revised manuscript if reviewer/editor find it useful. *

      *

      • *

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

      Reviewer 1:

      Summary:

      The authors do not reference the prior work which has examined cross class serpins, viral and mammalian, - this should be noted as alternative protease targets are known.

      *Thank you – please see our response in point 1 below. *

      • *

      The bronchiolar lavage analysis is excellent but cannot differentiate epithelial cell and associated immune cells and their roles in the response.

      We apologize for not making this clear – scRNAseq can indeed differentiate between different cell types using cell-type specific expression markers for each individual cell. This is how we were able to retrieve expression data specific for individual cell types. The reviewer is correct in that an expression analysis cannot show the role of individual cell types in the antiviral response. However, as epithelial cells are the primary cell type infected by SARS-CoV-2 gene expression patterns in these epithelial cells may show us cell-intrinsic effectors that are upregulated in response to viral infection. We now revised language in this paragraph to make this clearer (lines 156-162).

      • *

      PAI-1 does not seem to be present in the bronchoalveolar lavage samples.

      We do not know if PAI-1 is present, as we did not analyze protein levels in these samples. The gene expression data suggests that SERPINE1, the gene encoding PAI-1, is expressed at low levels in the epithelial cell subset at baseline, and expressed at slightly higher levels in individuals with severe COVID-19 (Figure 1c). This is consistent with previously published data on SERPINE1 gene expression upon viral infection (Dittmann et al., Cell, 2015).

      • *

      Further discussion of prior work with cross class serpins and also the limitations of the in-silico analyses and the lavage specimens should be provided.

      Prior work evidencing other cross class serpin protease targets as well as limitations related to the analyses as discussed in the critiques above should be noted and the abstract and title could better describe and define the studies as performed.

      *Thank you for raising these important points. For cross-class SERPINs, please see our response to point 1. The limitations of in silico analyses are discussed in-depth in a paragraph of the discussion (lines 608-631). We also discuss discrepancies observed between SERPIN expression in lavage specimens and in HAEC – please advise whether this is sufficient or needs bolstering (lines 546-564). We revised both title and abstract to better describe and define the studies as performed. *

      • *

      These correlations between changes in serpin and protease expression with viral infections and potential new interactions for serpins with previously non identified proteases is of clear interest. This shows an excellent correlation but as with big data sets this does not provide a true cause and effect - rather providing new potential directions for analysis of these interactions in viral infections in lung epithelium and this is valuable as a basis for ongoing studies.

      *We are in agreement with the lack of cause and effect –to our knowledge, we make no such claim from the gene expression data. We state that we used the expression data to guide the selection of SERPINs for our in-silico screen (lines 317-319). We then validated select data from our in-silico screen in vitro, which provides true cause and effect (Figures 4 and 5). *

      • *

      Major points:

      • Cross class serpin interactions are known and have been reported for at least two viral serpins Serp-1 and CrmA - both of which bind cysteine proteases as well as serine proteases as well as the mammalian SCCA serpins. *Thank you for bringing these two examples to our attention – we added them to the discussion (lines 648-652). We now also emphasized throughout the manuscript that the novelty of our findings is in PAI-1 cross-class inhibition, specifically, which has not been previously reported despite PAI-1 being an extremely well-studied SERPIN. *

      *We also would like to mention that in our opinion the scientific advance provided by our in-silico screen is not limited to the identification of new PAI-1 targets, but also provides a birds-eye view on SERPIN selectivity in a specific proteolytic landscape. For example, to our knowledge, it was unknown that SERPINB1 is promiscuous and that SERPINC1 is more selective, which our docking predicted. It was unknown that most TMPRSSs are unlikely SERPIN targets and that those that are SERPIN targets need to be in their active state to bind. The unsupervised clustering in Figure 4b (both on the SERPIN and on the protease side) predicts such unrecognized patterns in SERPIN selectivity. *

      • *

      • The protease targets are reported to vary when interacting with glycosaminoglycans such as heparan sulfate - PAI-1 inhibits thrombin in the presence of heparin - thus while a canonical serpin suicide inhibition is considered specific - it can vary. This is noted in the discussion Yes, we agree (lines 608-610).

      • What is the potential impact of the noted interactions of PAI-1 with other proteases such as cathepsin - PAI-1 is considered to have predominately extracellular functions, but prior work indicates internalization of PAI-1 when bound to the uPA/uPAR complex with alterations in intra cellular activation This is correct and PAI-1 internalization is cited and mentioned in discussion (lines 620-624). We now also added data on SARS-CoV-2 variant Omicron BA.1, which predominantly uses CTSL for maturation, and we show is also inhibited by PAI-1 (new Figure 5).

      • *

      • This is supported by basic in vivo and in vitro serpin and protease interactions that are demonstrated confirming in silico analyses, eg. gel shift analyses or even Mass spectrometry analysis particularly for PAI-1 Yes, this is the data shown in Figure 4. We now also added protease activity assays for other SERPIN-protease pairs, thereby elevating our study above the proof-of-principle state. *This was also a suggestion raised by reviewer 2. *

      • *

      • Per the authors "To date, three SERPINs have been studied in the context of innate antiviral defense: PAI- 1 (encoded by SERPINE1) against influenza viruses encoding hemagglutinin H1 and SARS-CoV-2, by impeding the proteolytic maturation of H1 or spike, respectively19,20; alpha-1-antitrypsin (encoded by SERPINA1) and antithrombin (encoded by SERPINC1) against SARS-CoV-2, likely through the inhibition of TMPRSS2, by reducing maturation of spike, although direct inhibition of TMPRSS2 by either SERPIN was not shown". This is partially complete however other serpins such as C1Inh and one virus derived serpin that have been analyzed for efficacy in treating SARS Thank you for mentioning this, we added the information to the introduction *(lines 106-111). *

      • *

      • While TMPRSS2 is indeed a serine protease - Beneficial effects of some serpins may be due to modulation of the immune response as opposed to selective anti-viral responses. The immune / cytokine storm and coagulopathies (with clotting and even hemorrhage) seen in the excess inflammatory response that causes respiratory vascular leak and severe viral sepsis. PAI-1 targets tPA and uPA - uPA has marked proinflammatory actions when bound to the uPA receptor (uPAR) and can activate growth factors and MMPs which can enhance immune cell invasion - PAI-1 binds to the uPA / uPAR complex which can thus also alter inflammatory cell responses and cell activation when internalized. Thank you for bringing up this point. The role of SERPINs in inflammation and anti-viral immune responses is indeed well-established. While our study focuses on cell-intrinsic antiviral roles of SERPINs by shutting down pro-viral proteases, which is much less established, we now added this to the results section for clarification (line 153-156).

      • The RCL does in general incorporate P4 to P4' but can vary from this specific P4 to P4' sequence *Yes, we agree. *

      • *

      • How accurately does in silico protease serpin analysis predict real interactions? - this should be discussed as HADDOCK may have some limitations - This is outside my field of expertise We added an in-depth paragraph on how HADDOCK operates to the results section to help readers not familiar with the technique (lines 248-290). We discuss the limitations of HADDOCK in depth in the discussion section *(lines 608-631)– please advise whether this needs additional information. *

      *We argue that, with the limitations stated in the discussion, our in-silico method predicts interactions well, as shown by the correct prediction of known binders and non-binders, as well as of new binders (PAI-1 to *active* TMPRSS2 and CTSL) and a new non-binder (CTSB). *

      *As with any screening method, results require validation via another method, which we performed for select SERPINs and proteases. In fact, the revised manuscript now features in vitro validation of 8 SERPIN-protease pairs (Figure 4a, b), with 8 additional planned (see “planned revisions” section). *

      • *

      • The data from a published study examining bronchoalveolar lavage fluid single cell transcriptional analysis from patients with and without COVID - mild and severe - and with comparison to patients without COVID does demonstrate altered protease and serpin activity - but does not indicate specific interactions *We agree with this statement partially. We disagree in that the data does not demonstrate altered protease and SERPIN activity; it instead demonstrates changes in gene expression levels. We agree in that this does indeed not indicate specific interactions. *

      • What is the significance for changes in gene expression in epithelial cells versus macrophage T and B cells looks - This looks like a small change like a small change in the mean values Figure 1b *We performed additional statistical analyses on the Figure 1 data – please refer to Reviewer 2 point 1. *

      • *

      • Of interest - is the brocholaveolar lavage fluid likely to contain both epithelial cells as well as immune response macrophage, T cells and NK cells etc - one assumes single cells were identified and isolated- Is this defined? Apologies if this was unclear. Yes, the BALF contains all of these cell types. We now added some sentences to the results section explaining scRNAseq and analyses in more detail *(lines 147-162). *

      • *

      • The known previously reported target proteases for PAI-1 should be noted Agreed; it is noted in the results section where we first speak about PAI-1 target specificity (line 379-382).

      SERPINE1 is not noted in figure 1 - this is PAI-1 - but is seen in the HAEC infection model data

      SERPINE1 is indeed not significantly upregulated in Figure 1, but is significantly upregulated in HAEC upon infection with Reovirus and parainfluenzavirus 3, and upon IFN stimulation (new Supplemental Tables S1 and S2). The possible reasons for discrepancies between the BALF and HAEC data are discussed in lines 546-564.

      • “To overcome this limitation, we developed a computational method to predict 3D interactions between SERPINs and proteases, simulating the binding process depicted in Supplemental Figure 1a. Specifically, we employed High Ambiguity Driven protein- protein Docking (HADDOCK), a tool that predicts complex structures, integrating experimental and computational data35,36." This analysis looks to be extensive however this is a correlation - not a true analysis of cause and effect. We agree on the first point – to our knowledge, our study provides the most extensive SERPIN target discovery process (testing 480 SERPIN-protease interactions). We disagree on the point that our results provide a mere correlation. If you will, we performed a computer-modeled interaction experiment that yields predicted binding energies between each SERPIN with each tested protease. We added a paragraph on how HADDOCK operates to the results section to help readers unfamiliar with the technique. As with any screening method, results need to be validated with another method, which we did for select SERPINs and proteases (Figure 4a, b). This does however have the potential to identify significant interactions We certainly agree on this point. * In future it might be of interest to assess PAI-1 given to infected cultures to assess viral replication and titers or perhaps examine a knock out cell model? We did exactly the former in Figure 4 (now 5). *

      • *

      • As PAI-1 was identified as having new cathepsin protease binding in addition to TMPRSS2 - the authors did demonstrate inhibition of the new targets on fluorometric analysis and also demonstrated interaction by gel shift - This is excellent *Thank you. *

      • *

      • The title and the abstract could be better written and more clearly indicate the extent of the analyses performed and the discovery of alternate protease targets for PAI-1 We modified both title and abstract.

      • *

      • Was the SARS CoV2 lung epithelial cell culture analysis performed in BSL3? Yes. All SARS-CoV-2 infection experiments were performed in a BSL3 environment. We added this information throughout the Methods section, and also generated a new Methods section on Biohazards (lines 779-797).

      __Minor critiques __

      1) Results section heading "SERPINs are differentially expressed individuals with COVID-19 and in response to respiratory virus infection in a model of the human airway epithelium." The word in needs to be inserted between expressed and individuals *Thank you for catching this – we fixed the sentence (lines 128-129). *

      *

      • *

      Reviewer 2:

      Major points:

      1) The rigor of the results presented in Figure 1 are unclear. For the COVID-19 analyses (Figure 1), only one dataset is used, and no statistical analyses are performed to determine to what degree any of the changes they observe are significant relative to variation in the dataset. This makes it difficult to determine how much can be extrapolated from these data.

      We agree that performing statistics on the BALF dataset would be ideal. However, the BALF contains only two non-infected individuals (intubated gun-shot victims), limiting our possibilities for statistical analysis.

      *For Figure 1b, we overcame this limitation by adding statistical analysis of upregulated expression values between cell types (i.e. by analyzing differences of upregulation of given SERPIN in epithelial cells compared to macrophages; Supplemental Table S1). We also performed statistical analysis on upregulation for individual SERPINs compared to housekeeping gene B2M (Supplemental Table S1). This revealed that SERPINs statistically significantly upregulated in severe COVID-19 in most cell types, including epithelial cells, in which SERPIN function has not been broadly studied. Upregulation was not statistically significant in mild COVID-19 samples, likely due to the n=3 (as compared to n=6 in the severe COVID-19 group). *

      *As for analysis of Figure 1c, we could theoretically perform analysis of differential levels between mild and severe COVID-19, but this is not the question we are trying to answer. The question is whether epithelial cells express SERPINs and proteases, and whether there is an upregulation of either in infected individuals. We now state the limitation of lacking statistical power in the figure legend and the text (lines 176-177). *

      2) Similarly, the qPCR data presented in Figure 2 are presented with no statistical analyses. Results should not only be presented with fold change but also p-values that are adjusted for multiple testing.

      *We now present p-values in Supplemental Table S2. Of note, data obtained with the experimental system of polarized airway epithelial cultures, differentiated over several weeks, tends to be noisier than that obtained with cell lines. Despite this, a number of SERPINs reach statistical significance. *

      • *

      3) How is the dotted line drawn in Figure 3C and D? It would appear there is very little in terms of HADDOCK score to distinguish a predicted "binder" from "non-binder". Also, they later show that CTSB is non inhibited, and yet in Figure 3C it is below the dotted line. Can the authors more clearly delineate how one might use their dataset shown in Figure 3B to accurately predict targets of SERPINs?

      This is a valid point. We added a more in-depth description to the results section on how we define “binders” and “non-binders” *(lines 324-331 and Figure 3 legend). We added raw data graph with the thresholds in Supplemental Figure 3d. We further added and defined a threshold line to the PAI-1:CTSs graph (Figure 3c). It is now evident that CTSL, A, F, K score as high-confidence “binders”, while CTSB and others do not. We also added the normalization process and the visual assessment of top-scoring complexes to the in silico docking screen schematic in Figure 3a and the respective figure legend to guide readers. *

      4) Based on this, it would be preferable for the authors to tone down their claims about the broad applicability of this approach to predict SERPIN-protease interactions. It is true that they have used it to accurately predict PAI-1-CTSL interactions, but to make such a broad claim about the generalizable nature of this approach would require testing several more SERPIN-protease pairs (both binders and non-binders) to clearly define the scores and parameters that can used to robustly predict interactions.

      We thank the reviewer for this criticism. We now address this in the text as outlined in our response to point 3 above. As with any screening method, the results require to be validated via an alternative approach, which we did in the initial submission for TMPRSS2 and CTSL as binders and CTSB as a non-binder. The revised manuscript now features additional in vitro validation of binders and non-binders for a total of 8 SERPIN-protease combinations (Figure 4a, b), which were all correctly predicted by our in-silico method. Two more SERPINs will be added in the final revision (see “planned revisions” section). Our study provides ample data for future studies validating additional predicted pairs and characterizing their biological function, in infectious disease and beyond.

      5) In Figure 3D, the authors mutate all eight modeled RCL residues to alanine to create a LOF mutant that has a higher HADDOCK score. Single residue mutations would be more convincing for their model, and would be more informative in terms of their predicted models of interactions.

      *We now performed the docking with the single mutant, please see new Figure 3c. *

      • *

      7) Further, in Figure 4G lanes 2-4, the PAI-1 band at ~38kDa is not present. Can the authors explain this?

      *This is likely because CTSL digests PAI-1 working at its optimum pH (aka “the protease wins”). We removed the panel from the manuscript. *

      9) In Figure 4I, the authors claim that the addition of PAI-1 is inhibiting cleavage of the SARS-CoV-2 spike protein (S2) based on densitometry quantifications. However, it is unclear how the authors are normalizing their data, nor whether the experiments (and therefore quantification) are from a single experiment or multiple replicates. Could the authors explain the quantification further and provide replicate information (including statistical support) if those experiments were performed?

      Thank you for pointing this out. An explanation has now been added to the Figure 5 legend.

      __Minor comments: __

      1) The authors speculate about SERPINA1 regulation during viral infection, suggesting an active process of "viral evasion". However, it would appear that even upon interferon treatment in Figure 2C, SERPINA1 expression is decreased. Based on that, the authors should soften their claims about the cause of downregulation of SERPINA1.

      Thank you for pointing this out – we softened the language on this point (*lines 225-228). *

      2) In Figure 2C, do the authors have an explanation or hypothesis for why SERPINE1 is less upregulated at 72hrs when compared to 24hr infection of SARS-CoV-2?

      *We can only speculate on this point. It is possible that one or several of the SARS-CoV-2 accessory proteins modulate SERPINE1 expression in a time-dependent manner. *

      3) Can the authors demonstrate how the docking structure of the TMPRSS2 zymogen differs from the active version (especially zooming in on the interface of PAI-1 and the protease)? This could be supplemental data but can the authors show a panel like that in Figure 3F to show how the interface between PAI-1 and TMPRSS2 zymogen looks. Does the inactive TMPRSS2 not interface well with the RCL? Or what is leading to the decreased HADDOCK score?

      We added an extensive paragraph on how HADDOCK operates to the results section to introduce how the HADDOCK score is calculated *(lines 248-290). We also added a visual of the top-scoring docking complex of PAI-1 and the TMPRSS2 zymogen (Figure 3d) to illustrate the differences in binding. *

      4) In methods, uPA fluorometric protease assay information is missing. Please add this information.

      Thank you for catching this – we added the information (line 890).

      5) It is a bit confusing that Figure 4K is the quantification of assays shown in Figure 4A-C, rather than quantification of any of the intervening figure panels. It might be clearer to move this quantification next to 4A-C so that it is clearer.

      *Thank you for the suggestion – Figure 4 has been restructured. *

      6) In Figure 4H, the authors show that addition of recombinant PAI-1 decreases the number of SARS-CoV-2 nucleoprotein positive cells. Have the authors examined whether this decreases the viral titers as well?

      *Yes, this is now part of the (new) Figure 5. *

      8) In the text, the authors suggest that PAI-1 inhibition of CTSL is surprising/novel. The authors should reconsider phrasing this since there are several other SERPINs that have been shown to inhibit other cathepsins, making this appear less surprising than the authors are suggesting.

      *Thank you for pointing this out. We have now clarified throughout the manuscript that while other SERPINs indeed are known to inhibit cathepsins, this had not been previously shown for the extremely well-studied SERPIN PAI-1 with over 15,000 pubmed entries. We also added the implications of this PAI-1-specific finding to the discussion section. *

      __Significance: __

      The claim of novelty about TMPRSS2 is confusing. In their previous paper (reference 19) they show that PAI-1 inhibits TMPRSS2 activity. These data are clearly shown in Figure 4C & 4D of that paper and are summarized in their sentence in the discussion: "Here, we find three new PAI-1 protease targets: human tryptase (tryptase Clara; club cell secretory protein), HAT, and TMPRSS2 ...". In this current paper, although they characterize the PAI-1-TMPRSS2 interaction in more detail than in their previous paper, they have truly only discovered one new target for PAI-1, which is CTSL.

      Thank you for pointing this out – we softened language on the novelty of TMPRSS2 as a PAI-1 target *throughout the manuscript. We further clarify that the novelty is that TMPRSS2 has to be in its active form to be inhibited by PAI-1, which was previously unknown (lines 392, 432). The revised manuscript now also provides validation of total 8 predicted binders and non-binders for 2 (Figure 4 b,c), with 8 more pending (see “planned revisions” section). As those two (future four) SERPINs have various roles in cancer, cardiovascular disease, neurodegeneration, and immunity, our findings have impact beyond their antiviral potential, thereby increasing the overall significance of the manuscript. *

      • *

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

      Reviewer 1 major point:

      The more common names for the SERPINS as detected in COVID alveolar lavage samples would be helpful in figure 1 - and specifically labelling PAI-1 as this is a focus for this study - together with the known SERPIN nomenclature or under abbreviations - For example SERPINB2 is PAI-2 and SERPING1 is C1INH and SERPINA1 is alpha 1 antitrypsin *Thank you for this suggestion. We tried to keep the SERPIN nomenclature consistent throughout the manuscript, in that the SERPIN genes are referred to by their gene name (i.e., SERPINE1), while the proteins are referred to by their protein name (i.e., PAI-1). Editor and/or Reviewer 1, please advise whether this is acceptable or should be changed. We also added the protein corresponding names in the figure legend. *

      Why does supplemental figure 2 show SERPINB1 and not PAI-1. *We performed this computer-modeled experiment (docking SERPINs to known binders and known non-binders) for each SERPIN tested in the study. This was needed to obtain thresholds to define likely binders and likely non-binders. We chose to show SERPINB1 in this supplemental figure because it is well-described with regards to binders and non-binders (the latter, as “negative result”, is not always published for a given SERPIN). We also did not want to narrow the study immediately to PAI-1, as we believe our screen is a generalizable method and our findings are valid beyond PAI-1. We can easily show any other SERPIN here - editor and/or Reviewer 1, please advise. *

      Reviewer 2 major point:

      6) Figures 4F and 4G are rather confusing. First, in Figure 4F, amount of PAI-1 in lane 1 is not the same as in the lanes with CTSL. The biggest concern with this is that there is a second, higher MW band that is present in lane 1 (also in Figure 4G lane 1) that runs near the band in lanes 2&3 that is marked as the PAI-1-CTSL complex. Although it does appear that the band in lane 1 and lanes 2&3 are slightly different sizes, it is hard to say that conclusively when the amounts of PAI-1 are different. Can the authors repeat this assay to load consistent amounts PAI-1 across all conditions and even potentially separate the top bands to more convincingly show that the band in lanes 2&3 is not in the PAI-1 alone control?

      *The upper band is an impurity that disappears upon addition of a protease to the reaction. We confirmed that this band is neither PAI-1 nor CTSL via western blot with PAI-1- or CTSL-specific antibodies. Should reviewer 2 and/or the editor feel that we should repeat the experiment with more loading in the first lane, we can certainly do so. Please advise. *

      8) The authors show that exogenous PAI-1 can inhibit SARS-CoV-2 in a multicycle infection in Figure 4H. However, this could be acting at multiple points during the viral infection cycle. A clearer virology experiment to support their model would be to perform single-cycle infections to show that the virus fails to productively infect the cell. For instance, have the authors attempted a high MOI, single-cycle infection to see whether they can detect uncleaved spike protein to show inhibition of cleavage? Or show that no early products of viral infection are produced? While this type of experiment is optional in that it is not required to support the claim that PAI-1 inhibits multicycle SARS-CoV-2 infection, it would support the conclusion that PAI-1 is inhibiting viral entry.

      *We agree with the reviewer. We did expand on the virology by using now two strains of SARS-CoV-2 with different proteolytic needs, ancestral WA-1 and Omicron BA.1. We also performed titer analysis (all in Figure 5). *

      *However, the other suggested experiments would represent a substantial amount of work in a BSL3 environment. We thus would prefer not do these experiments (as the reviewer states, it is optional), and instead tone down the manuscript to make clear we make no claims on viral entry. *

      • *

      Reviewer 2 minor point:

      11) One (optional) way to extend these data and support their molecular model would be to mutate residues in PAI-1 that they predict are important for protease inhibition. As their source of PAI-1 currently is commercial, this would require purification of WT and variant PAI-1, which is clearly an undertaking. However, these data would strongly support their modeling and the importance of these residues in engaging with the proteases and springing the mousetrap for their in-vitro/in-vivo experiments (as suggested by data shown in Figure 3F and explained in text). Further, the authors can use these mutants to do some of the functional experiments in Figure 4 as a negative control, and potentially even separate the role of PAI-1 in inhibition of CTSL and TMPRSS2 in terms of SARS-CoV-2 inhibition.

      *We agree that these (optional) experiments would be beautiful and are indeed part of future studies on the subject. We feel that they exceed the scope of this current manuscript. *

      PeerReviewed
    2. EMBOpress 14 Jun 2024

      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 #2

      Evidence, reproducibility and clarity

      Summary:

      Rodriguez Galvan et al. use a combined computational and functional approach to identify a novel target for the protease inhibitor, PAI-1 (SERPINE1), and show that exogenous PAI-1 can inhibit SARS-CoV-2 replication. They first use a COVID-19 dataset to identify SERPINs that are differentially expression in individuals with mild and severe COVID-19. They further use experimental infections of a model of human airway epithelium to identify SERPINs that are upregulated in response to several viruses, as well as treatment with interferon. Using this panel of SERPINs and a panel of host proteases, they use computational docking to predict SERPINs that may inhibit human proteases that may be relevant for viral infection. Using these predictions, they show that PAI-1 inhibits TMPRSS2 (previously shown) and CTSL (newly shown in this study), two proteases with relevance for SARS-CoV-2 infection. They finally show that extracellular addition of PAI-1 inhibits multicycle replication of SARS-CoV-2.

      Major comments:

      1) The rigor of the results presented in Figure 1 are unclear. For the COVID-19 analyses (Figure 1), only one dataset is used, and no statistical analyses are performed to determine to what degree any of the changes they observe are significant relative to variation in the dataset. This makes it difficult to determine how much can be extrapolated from these data. 2) Similarly, the qPCR data presented in Figure 2 are presented with no statistical analyses. Results should not only be presented with fold change but also p-values that are adjusted for multiple testing. 3) How is the dotted line drawn in Figure 3C and D? It would appear there is very little in terms of HADDOCK score to distinguish a predicted "binder" from "non-binder". Also, they later show that CTSB is non inhibited, and yet in Figure 3C it is below the dotted line. Can the authors more clearly delineate how one might use their dataset shown in Figure 3B to accurately predict targets of SERPINs? 4) Based on this, it would be preferable for the authors to tone down their claims about the broad applicability of this approach to predict SERPIN-protease interactions. It is true that they have used it to accurately predict PAI-1-CTSL interactions, but to make such a broad claim about the generalizable nature of this approach would require testing several more SERPIN-protease pairs (both binders and non-binders) to clearly define the scores and parameters that can used to robustly predict interactions. 5) In Figure 3D, the authors mutate all eight modeled RCL residues to alanine to create a LOF mutant that has a higher HADDOCK score. Single residue mutations would be more convincing for their model, and would be more informative in terms of their predicted models of interactions. 6) Figures 4F and 4G are rather confusing. First, in Figure 4F, amount of PAI-1 in lane 1 is not the same as in the lanes with CTSL. The biggest concern with this is that there is a second, higher MW band that is present in lane 1 (also in Figure 4G lane 1) that runs near the band in lanes 2&3 that is marked as the PAI-1-CTSL complex. Although it does appear that the band in lane 1 and lanes 2&3 are slightly different sizes, it is hard to say that conclusively when the amounts of PAI-1 are different. Can the authors repeat this assay to load consistent amounts PAI-1 across all conditions and even potentially separate the top bands to more convincingly show that the band in lanes 2&3 is not in the PAI-1 alone control? 7) Further, in Figure 4G lanes 2-4, the PAI-1 band at ~38kDa is not present. Can the authors explain this? 8) The authors show that exogenous PAI-1 can inhibit SARS-CoV-2 in a multicycle infection in Figure 4H. However, this could be acting at multiple points during the viral infection cycle. A clearer virology experiment to support their model would be to perform single-cycle infections to show that the virus fails to productively infect the cell. For instance, have the authors attempted a high MOI, single-cycle infection to see whether they can detect uncleaved spike protein to show inhibition of cleavage? Or show that no early products of viral infection are produced? While this type of experiment is optional in that it is not required to support the claim that PAI-1 inhibits multicycle SARS-CoV-2 infection, it would support the conclusion that PAI-1 is inhibiting viral entry. 9) In Figure 4I, the authors claim that the addition of PAI-1 is inhibiting cleavage of the SARS-CoV-2 spike protein (S2) based on densitometry quantifications. However, it is unclear how the authors are normalizing their data, nor whether the experiments (and therefore quantification) are from a single experiment or multiple replicates. Could the authors explain the quantification further and provide replicate information (including statistical support) if those experiments were performed? Further, to strengthen the conclusions of this data the authors should include additional controls. One would be to use trixplanin as they did in previous panels to show that PAI-1 is necessary. Further, if the authors generate mutant PAI-1 that is unable to inhibit TMPRSS2 (see comment 11 below), they could also use this as a control to show the necessity of functional PAI-1. 10) For Figures 4I-J, is it possible to also blot for S1 cleavage? If possible, this optional data would be helpful to understand whether the entire cleavage process is disrupted or only S2 to S2' especially given that visually it appears as if the full length is more depleted in the condition with PAI-1 suggesting that it is cleaving spike better into S1 and S2. Could also suggest that the dynamics of cleavage are shifted rather than impaired? 11) One (optional) way to extend these data and support their molecular model would be to mutate residues in PAI-1 that they predict are important for protease inhibition. As their source of PAI-1 currently is commercial, this would require purification of WT and variant PAI-1, which is clearly an undertaking. However, these data would strongly support their modeling and the importance of these residues in engaging with the proteases and springing the mousetrap for their in-vitro/in-vivo experiments (as suggested by data shown in Figure 3F and explained in text). Further, the authors can use these mutants to do some of the functional experiments in Figure 4 as a negative control, and potentially even separate the role of PAI-1 in inhibition of CTSL and TMPRSS2 in terms of SARS-CoV-2 inhibition.

      Minor comments:

      1) The authors speculate about SERPINA1 regulation during viral infection, suggesting an active process of "viral evasion". However, it would appear that even upon interferon treatment in Figure 2C, SERPINA1 expression is decreased. Based on that, the authors should soften their claims about the cause of downregulation of SERPINA1. 2) In Figure 2C, do the authors have an explanation or hypothesis for why SERPINE1 is less upregulated at 72hrs when compared to 24hr infection of SARS-CoV-2? 3) Can the authors demonstrate how the docking structure of the TMPRSS2 zymogen differs from the active version (especially zooming in on the interface of PAI-1 and the protease)? This could be supplemental data but can the authors show a panel like that in Figure 3F to show how the interface between PAI-1 and TMPRSS2 zymogen looks. Does the inactive TMPRSS2 not interface well with the RCL? Or what is leading to the decreased HADDOCK score? 4) In methods, uPA fluorometric protease assay information is missing. Please add this information. 5) It is a bit confusing that Figure 4K is the quantification of assays shown in Figure 4A-C, rather than quantification of any of the intervening figure panels. It might be clearer to move this quantification next to 4A-C so that it is clearer. 6) In Figure 4H, the authors show that addition of recombinant PAI-1 decreases the number of SARS-CoV-2 nucleoprotein positive cells. Have the authors examined whether this decreases the viral titers as well? 7) As a supplemental figure, can the authors show a complex blot (similar to Figure 4F) for CTSB to show that is does not complex with PAI-1. 8) In the text, the authors suggest that PAI-1 inhibition of CTSL is surprising/novel. The authors should reconsider phrasing this since there are several other SERPINs that have been shown to inhibit other cathepsins, making this appear less surprising than the authors are suggesting.

      Significance

      Assessment and impact:

      This paper brings attention to the potential role of SERPINs in viral pathogenesis. The datasets shown in Figure 1 and 2, with the statistical caveats described above, are interesting demonstrations of the regulation of SERPINS during viral infection. In particular, the comparison of different viruses, and viruses compared to interferon alone, in Figure 2B is intriguing. These data are the strongest points of the paper.

      The impact of the computational modeling is difficult to assess. While they have used this dataset to predict one novel interaction (CTSL) with PAI-1, the generalizable nature of this approach to broadly predict SERPIN-protease interactions is unclear since they have not tested or validated any other SERPIN-protease pairs. One major concern is the one raised in Major comments 3&4 above, which is that the score difference between a "non-binder" (CTSB) and a "binder" (uPa) is very small. It is exciting that they predicted CTSL as a target of PAI-1, but it is not obvious that this is a generalizable approach without further hypothesis testing.

      The claim of novelty about TMPRSS2 is confusing. In their previous paper (reference 19) they show that PAI-1 inhibits TMPRSS2 activity. These data are clearly shown in Figure 4C & 4D of that paper and are summarized in their sentence in the discussion: "Here, we find three new PAI-1 protease targets: human tryptase (tryptase Clara; club cell secretory protein), HAT, and TMPRSS2 ...". In this current paper, although they characterize the PAI-1-TMPRSS2 interaction in more detail than in their previous paper, they have truly only discovered one new target for PAI-1, which is CTSL.

      Finally, the data on SARS-CoV-2 are intriguing and contribute to an emerging field on antiviral SERPINs. This reveals an additional virus that is inhibited by PAI-1, to add to their previous discoveries (reference 19) of influenza virus and Sendai virus inhibition by PAI-1. Future virology experiments, and experiments with mutants that ideally separate the ability of PAI-1 to inhibit TMPRSS2 versus CTSL, will further reveal the step of viral replication that is inhibited, and reveal the contribution of inhibition of TMPRSS2, CTSL, or any other PAI-1 targets, on SARS-CoV-2 replication.

      Audience: Overall, this paper will be interesting to a specialized audience that is interested in SERPIN function. The SERPIN expression data during viral infection, discovery of CTSL as a target of PAI-1, and evidence that PAI-1 can inhibit SARS-CoV-2 replication, will move that field forward.

      Field of expertise: Biochemistry, host-virus interactions

      PeerReviewed
    3. EMBOpress 14 Jun 2024

      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

      Title - In-silico docking platform with serine protease inhibitor (SERPIN) structures identifies host cysteine protease targets with significance for SARS-CoV-2

      Authors - Joaquín J Rodriguez Galvan, Maren de Vries, Shiraz Belblidia, Ashley Fisher, Rachel A Prescott, Keaton M Crosse, Walter F. Mangel, Ralf Duerr, Meike Dittmann

      Summary

      The finding that PAI-1 has cross class serpin functions is of definite interest given the roles of PAI-1 in regulation of physiological processes as well as in driving pathology. PAI-1 is generally considered to be a key regulator of thrombolysis and thus an effect on other pathways and even intracellular pathways is of interest. Examining airway epithelial proteases and serpins is of definite interest in respiratory viral infections. Broadening the targets for serpins is also of very definite interest. This study ranges from an overview of prior published work on bronchoalveolar lavage samples and serpin expression, a tissue culture analysis of lung epithelial cells and expression of proteases and serpins is assessed. In addition selective changes in serpin expression and protease targets are assessed by in silico analysis as well as proof of concept via Western blot and fluorometric analysis. This is an extensive study and of definite interest.

      There are some limitations as with any study, albeit the study overall is excellent. The authors do not reference the prior work which has examined cross class serpins, viral and mammalian, - this should be noted as alternative protease targets are known. They do mention the modulation of protease targets by glycosaminoglycans in the discussion. Further, serpins are inhibitors, thus while the RCL provides a target for a protease, but the response may not be fully selective in vivo as the protease has to be present and active to complete the serpin protease interaction. The bronchiolar lavage analysis is excellent but cannot differentiate epithelial cell and associated immune cells and their roles in the response. PAI-1 does not seem to be present in the bronchoalveolar lavage samoles. Further discussion of prior work with cross class serpins and also the limitations of the in silico analyses and the lavage specimens should be provided. Further analysis of the detected proteases that are reported here to bind to PAI-1 would be of great interest. The data from the bronchoalveolar lavage is published.

      Overall this is a very simple, although extensive and excellent, study analyzing a wide range of data form patients with bronchoalveolar lavage and epithelial cell samples, human epithelial cell cultures after infection with a range of respiratory viruses as well as the development of a 3D in silico analysis of potential protease and serpin interactions. These correlations between changes in serpin and protease expression with viral infections and potential new interactions for serpins with previously non identified proteases is of clear interest. This shows an excellent correlation but as with big data sets this does not provide a true cause and effect - rather providing new potential directions for analysis of these interactions in viral infections in lung epithelium and this is valuable as a basis for ongoing studies. Prior work evidencing other cross class serpin protease targets as well as limitations related to the analyses as discussed in the critiques above should be noted and the abstract and title could better describe and define the studies as performed.

      Critique

      Major

      1. Cross class serpin interactions are known and have been reported for at least two viral serpins Serp-1 and CrmA - both of which bind cysteine proteases as well as serine proteases as well as the mammalian SCCA serpins
      2. The protease targets are reported to vary when interacting with glycosaminoglycans such as heparan sulfate - PAI-1 inhibits thrombin in the presence of heparin - thus while a canonical serpin suicide inhibition is considered specific - it can vary. This is noted in the discussion
      3. What is the potential impact of the noted interactions of PAI-1 with other proteases such as cathepsin - PAI-1 is considered to have predominately extracellular functions, but prior work indicates internalization of PAI-1 when bound to the uPA/uPAR complex with alterations in intra cellular activation
      4. This is supported by basic in vivo and in vitro serpin and protease interactions that are demonstrated confirming in silico analyses, eg. gel shift analyses or even Mass spectrometry analysis particularly for PAI-1
      5. Per the authors "To date, three SERPINs have been studied in the context of innate antiviral defense: PAI- 1 (encoded by SERPINE1) against influenza viruses encoding hemagglutinin H1 and SARS-CoV-2, by impeding the proteolytic maturation of H1 or spike, respectively19,20; alpha-1-antitrypsin (encoded by SERPINA1) and antithrombin (encoded by SERPINC1) against SARS-CoV-2, likely through the inhibition of TMPRSS2, by reducing maturation of spike, although direct inhibition of TMPRSS2 by either SERPIN was not shown". This is partially complete however other serpins such as C1Inh and one virus derived serpin that have been analyzed for efficacy in treating SARS
      6. While TMPRSS2 is indeed a serine protease - Beneficial effects of some serpins may be due to modulation of the immune response as opposed to selective anti-viral responses. The immune / cytokine storm and coagulopathies (with clotting and even hemorrhage) seen in the excess inflammatory response that causes respiratory vascular leak and severe viral sepsis. PAI-1 targets tPA and uPA - uPA has marked proinflammatory actions when bound to the uPA receptor (uPAR) and can activate growth factors and MMPs which can enhance immune cell invasion - PAI-1 binds to the uPA / uPAR complex which can thus also alter inflammatory cell responses and cell activation when internalized.
      7. The RCL does in general incorporate P4 to P4' but can vary from this specific P4 to P4' sequence
      8. How accurately does in silico protease serpin analysis predict real interactions? - this should be discussed as HADDOCK may have some limitations - This is outside my field of expertise
      9. The data from a published study examining bronchoalveolar lavage fluid single cell transcriptional analysis from patients with and without COVID - mild and severe - and with comparison to patients without COVID does demonstrate altered protease and serpin activity - but does not indicate specific interactions
      10. What is the significance for changes in gene expression in epithelial cells versus macrophage T and B cells looks - This looks like a small change like a small change in the mean values Figure 1b
      11. The more common names for the SERPINS as detected in COVID alveolar lavage samples would be helpful in figure 1 - and specifically labelling PAI-1 as this is a focus for this study - together with the known SERPIN nomenclature or under abbreviations - For example SERPINB2 is PAI-2 and SERPING1 is C1INH and SERPINA1 is alpha 1 antitrypsin
      12. Of interest - is the brocholaveolar lavage fluid likely to contain both epithelial cells as well as immune response macrophage, T cells and NK cells etc - one assumes single cells were identified and isolated- Is this defined?
      13. The known previously reported target proteases for PAI-1 should be noted
      14. SERPINE1 is not noted in figure 1 - this is PAI-1 - but is seen in the HAEC infection model data
      15. "To overcome this limitation, we developed a computational method to predict 3D interactions between SERPINs and proteases, simulating the binding process depicted in Supplemental Figure 1a. Specifically, we employed High Ambiguity Driven protein- protein Docking (HADDOCK), a tool that predicts complex structures, integrating experimental and computational data35,36." This analysis looks to be extensive however this is a correlation - not a true analysis of cause and effect This does however have the potential to identify significant interactions - In future it might be of interest to assess PAI-1 given to infected cultures to assess viral replication and titers or perhaps examine a knock out cell model?
      16. Why does supplemental figure 2 show SERPINB1 and not PAI-1
      17. As PAI-1 was identified as having new cathepsin protease binding in addition to TMPRSS2 - the authors did demonstrate inhibition of the new targets on fluorometric analysis and also demonstrated interaction by gel shift - This is excellent
      18. The title and the abstract could be better written and more clearly indicate the extent of the analyses performed and the discovery of alternate protease targets for PAI-1
      19. Was the SARS CoV2 lung epithelial cell culture analysis performed in BSL3?

      Minor critiques

      1. Results section heading "SERPINs are differentially expressed individuals with COVID-19 and in response to respiratory virus infection in a model of the human airway epithelium." The word in needs to be inserted between expressed and individuals

      Significance

      Overall this is a very simple, although extensive and excellent, study analyzing a wide range of data form patients with bronchoalveolar lavage and epithelial cell samples, human epithelial cell cultures after infection with a range of respiratory viruses as well as the development of a 3D in silico analysis of potential protease and serpin interactions. These correlations between changes in serpin and protease expression with viral infections and potential new interactions for serpins with previously non identified proteases is of clear interest. This shows an excellent correlation but as with big data sets this does not provide a true cause and effect - rather providing new potential directions for analysis of these interactions in viral infections in lung epithelium and this is valuable as a basis for ongoing studies. Prior work evidencing other cross class serpin protease targets as well as limitations related to the analyses as discussed in the critiques above should be noted and the abstract and title could better describe and define the studies as performed.

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    biorxiv.org/content/10.1101/2022.11.18.517133v2
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    The whole blood microbiome of Indonesians reveals translocated and pathogenic microbiota
    3
    1. EMBOpress 14 Jun 2024

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      Reply to the reviewers

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

      Summary: Authors performed a metatranscriptomic analysis from publicly-available datasets of whole blood from 3 places in Indonesia. Their goal was to explore which pathogens were present on the blood of those 117 healthy individuals. It was interesting that reads from Flaviviridae and Plasmodium were detected in asymptomatic subjects.

      Major comments: 1) How did the authors assess and correct batch-effects between different datasets?

      Our response: We have sequencing batch information for the Indonesian dataset and saw no clear clustering based on batches in the first 8 PCs. We recognize that sampling variations may exist between islands, though the taxa matrix we acquired from the unmapped reads are very scarce that such variations did not have a strong enough effect to introduce batch effects in our microbiome analyses, and that the signals were driven by pathogenic reads. For our comparative analyses between datasets, we made sure that all three datasets shared similar processing (collected using Tempus Blood RNA Tubes and went through globin depletion method) and have trimmed both Indonesian and Malian reads to match the length of the UK reads (75BP).

      2) Did the RNA-seq capture poly-A mRNAs? If so... these reads that did not map the human genome were captured because of internal priming. Can they find internal poly A sequences in the genome of Flaviviridae and Plasmodium pathogens? I would like to know that to understand the source of the reads and which other pathogens may be missing (due to the lack of internal priming).

      __Our response: __No, our dataset did not capture poly-A mRNAs. We performed ribosomal RNA (rRNA) and globin mRNA depletion.

      3) Principal coordinates analysis (PCoA) is often utilized in metagenomics analysis. Although they are equivalent, is there a reason for using PCA?

      Our response: Since we used CLR transformation, the resulting matrix lies in Euclidian space. PCA is just a form of PCoA in Euclidian space.

      Minor comments: 1) "Indonesia is a country with large numbers of endemic and emerging infectious diseases [16], making it a crucially important location to monitor and understand the effects of pathogens on human hosts." Is there any epidemiological data that shows differences in infectious diseases across these 3 places? Can the authors provide a map and better explanation about the importance in comparing these 3 areas?

      __Our response: __We have added references to malaria infection being more prevalent in the eastern side of Indonesia in the discussion section.

      2) Why is it so hard to try to identify (only for Flaviviridae reads) reads that map to very relevant viruses, such as Zika, Dengue, and Yellow Fever? Why did the authors state that they "were unable to refine this assignment further" if this is one of the most interesting finding?

      __Our response: __Our reanalysis showed a small percentage of the Flaviviridae reads to be assigned to the Pegivirus genus. As more diverse microbial genomes are added to reference databases and identical regions become more common between them, it becomes harder for the classifer to further define reads to species level (https://link.springer.com/article/10.1186/s13059-018-1554-6). Flaviviridae has distinct species spread across six different genera (https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=11050). In comparison, despite Plasmodiidae having more species recorded compared to Flaviviridae, an overwhelming majority of the species is part of the Plasmodium genus, hence we were able to refine them down to species-level (https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=1639119).

      3) Is the script available at https://gitlab.unimelb.edu.au/igr-lab/Epi_Study ? This reviewer could not access it. __Our response: __We thank Reviewer 1 for pointing this out and have amended the link, now accessible here: https://gitlab.svi.edu.au/muhamad.fachrul/indo_blood_microbiome

      Reviewer #1 (Significance (Required)):

      Interesting paper that enable to extract additional knowledge from whole blood RNA-seq data. There are already several papers that do this and I think authors could go one step forward (for instance, PCR validation of additional individuals). I don't think this can be used for surveillance if it cannot identify species, it is more expensive than running targeted assays, and that may be many false negative pathogens in the samples.

      __Our response: __We thank Reviewer 1 for their comments. We have updated our manuscript to reflect our updated analyses which minimizes false positive taxa and the project’s significance not as a mainline surveillance tool, but a retrospective one.

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

      Summary:

      Bobowik and colleagues perform a computational analysis of whole blood RNA-seq datasets from healthy individuals of three different regions of Indonesia. Their goal is to identify infecting pathogens and other microbes and correlate their abundances to host gene expression patterns or health characteristics in these populations. They find a broad range of bacterial, viral and microeukaryote taxa. When comparing the three Indonesian populations, they find that the Korowai population is the most diverse and different from the other two, possibly driven by the higher prevalence and abundance of Plasmodium (Apicomplexa) in this population.

      Then, the authors conduct a statistical decomposition of human gene expression in these samples in independent factors using ICA, and correlate each of these factors to the abundances of the microbial taxa detected. This analysis allows researchers to associate specific patterns of gene expression, such as immune-related pathways, to the presence of members of the Apicomplexa and Kitrinoviricota phyla.

      Lastly, the authors use previously published data from other two cohorts (from Mali and the UK) to contextualize their blood microbiome findings. They find microbial reads in all datasets. The Mali cohort is characterized by a large abundance of archaea, not found in the other two populations, while the UK cohort has the lower diversity. Altogether, the authors propose the use of RNA-seq data from human whole blood as a way to study the blood microbiome and establish potential associations between blood resident microbes and host gene expression

      Major comments:

      1) The methodology to filter and remove reads from potential contaminants needs to be more stringent to ensure the results do not contain spurious contaminants and that the conclusions are correct. It has been described that genomic databases are heavily contaminated with human sequences (Steinegger and Salzberg, 2020), and in this manuscript, even after a two-pass alignment with STAR, reads mapping to helminths also corresponded to the human genome. Additionally, ad-hoc removal of specific taxa (Metazoa and Viridiplantae) was only performed after suspicion of contamination. However, this ad-hoc removal cannot be performed with microbial (bacterial, viral, etc.) contaminants as there is a risk of removing actual bacteria from the samples. But it has been confirmed that many microbial assemblies also suffer from human contamination. Possible actions to take are the following: a.Perform the human mapping with more lenient parameters to avoid human reads to map to other (likely contaminated) genomes in genome databases. b.Remove common contaminants that have been documented, for instance in blood (Chrisman et al., 2022). c.Run a tool to detect contaminated contigs in the database used to map reads to microbes and remove these problematic contigs from further analysis.

      Our response: We thank Reviewer 2 for the suggestions, especially to address contaminants. We have reanalyzed our data which resulted in much fewer taxa yet still retained the main pathogenic findings.

      2) In line with the above, removing singletons (as I have understood these are taxa that are represented by a single read), is a way to minimize the risk of contamination. To take advantage of the functional profiling of RNA-seq, a measure to ensure that microbes found in blood are active would be to include in the analysis only taxa for which expression of more than a few genes is detected. This type of filtering has been previously applied in studies where very low microbial loads are expected (Lloréns-Rico et al., 2021). In this study, it has only been applied to the specific case of the archaeal taxon Methanocaldococcaceae. However, I would expect cleaner results if applied consistently to all taxa detected.

      __Our response: __We have reanalyzed the data and applied this to all taxa detected.

      3) The specificity of Methanocaldococcaceae in the samples from Mali is very striking. I am highly suspicious that this only occurs due to a batch effect, even though the authors were highly selective in their cohorts to avoid these. In fact, I extracted the genes spanning the regions highlighted in Supplementary Figure 9 of the Methanocaldococcus jannaschii genome. A BLAST search of these sequences returned, among Methanocaldococcus hits, hits from the ERCC synthetic spike-in sequences, used as internal controls in many RNA-seq experiments. ERCC synthetic spike-in hits appeared for all 4 regions in the genome of M. jannaschii highlighted in this figure. In the original publications of this dataset, there is no reference to the use of these ERCC controls, but given the observed matches, I suggest the authors to perform an extra step in their filtering pipeline to remove all reads mapping to these ERCC standards in all their three cohorts to prevent these sort of batch effects.

      __Our response: __We thank Reviewer 2 for pointing this out. Our reanalysis, which now used proper 2-pass mapping and further downstream classification with both pairs of the reads, no longer detected any archaea.

      4) I am puzzled by the inconsistencies shown between forward and reverse reads when mapping paired-end data. I expect these inconsistencies at lower taxonomic ranks (species or genus level) due to incomplete genomes, but not at higher taxonomic ranks. I wonder if, by performing more stringent filtering of contaminants as suggested above, the consistency between forward and reverse reads increases and both mates can be used, making the mapping more reliable.

      __Our response: __We have reanalyzed the data using both pairs of the reads for classification, resulting in less detected taxa. We believe the new results are more robust as it no longer includes taxa that are not typically found in humans (such as the archae Methanocaldococcus and other environmental bacteria).

      In summary, my main concerns regarding this manuscript involve the possibility that contaminants in the sequencing data may be the cause of some of the results presented, and I tried to propose ways of dealing with these contaminants. While some of the results may not be affected by detection of contaminants (i.e. the association between Apicomplexa and some ICs), others such as the diversity measures or the comparison across cohorts may be severely affected. I will consider these results highly preliminary until a more thorough and stringent approach for contaminant removal is applied.

      Our response: We thank Reviewer 2 for the suggestions and have updated our manuscript with results updated analyses that are more stringent towards contaminants, as can be seen from our updated findings.

      Minor comments:

      1) I would appreciate some of the analyses done at lower taxonomic levels if the sparsity of the data allows it, after removing contaminants. Given that the CLR transformation does not allow for zeros, other alternatives such as GMPR (Chen et al., 2018) or adding a pseudocount would allow these analyses?

      __Our response: __After our reanalysis, we ended up with even sparser data and therefore could not perform the analyses at lower taxonomic levels.

      2) In the PCA shown in figure 1, does the number of microbial reads detected correlate with any of the first two components?

      __Our response: __Yes Plamosdiidae correlates well with PCs 1 and 2 (0.66 & 0.73) and Flaviviridae correlates very strongly with PC1 (0.917). We have added this detail in the results section.

      3) In Figure 1C, the x axis is wrongly named PC2.

      __Our response: __We thank Reviewer 2 for pointing this out and have amended this detail.

      4) There is a typo in the legend of Figure 1A ("showeing")

      __Our response: __We thank Reviewer 2 for pointing this out and have amended this detail.

      5) In the alpha diversity estimates comparison across the three different cohorts, after subsampling each population to achieve similar sample size in each cohort, it is stated that "after subsampling, each population had similar diversity estimates". However, the numbers shown afterwards corresponding to the mean values of alpha diversity, without confidence intervals or a boxplot/violin plot together with an accompanying statistical test, are not enough to assess similarity. I would appreciate a figure (similar to Figure 3E and F) or a test accompanying these mean values.

      __Our response: __We thank Reviewer 2 for pointing this out and have amended this detail.

      6) In the volcano plots (Figure 3A, B and others throughout the manuscript) it would help the reader to add lines for the thresholds chosen for the effect size and -log10(p-value) to separate significant results.

      __Our response: __We thank Reviewer 2 for pointing this out and have amended this detail.

      7) In Figure 3E and F, I would appreciate having bars for the statistically significant comparisons.

      __Our response: __We thank Reviewer 2 for pointing this out and have amended this detail.

      PeerReviewed
    2. EMBOpress 14 Jun 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      Bobowik and colleagues perform a computational analysis of whole blood RNA-seq datasets from healthy individuals of three different regions of Indonesia. Their goal is to identify infecting pathogens and other microbes and correlate their abundances to host gene expression patterns or health characteristics in these populations. They find a broad range of bacterial, viral and microeukaryote taxa. When comparing the three Indonesian populations, they find that the Korowai population is the most diverse and different from the other two, possibly driven by the higher prevalence and abundance of Plasmodium (Apicomplexa) in this population.

      Then, the authors conduct a statistical decomposition of human gene expression in these samples in independent factors using ICA, and correlate each of these factors to the abundances of the microbial taxa detected. This analysis allows researchers to associate specific patterns of gene expression, such as immune-related pathways, to the presence of members of the Apicomplexa and Kitrinoviricota phyla.

      Lastly, the authors use previously published data from other two cohorts (from Mali and the UK) to contextualize their blood microbiome findings. They find microbial reads in all datasets. The Mali cohort is characterized by a large abundance of archaea, not found in the other two populations, while the UK cohort has the lower diversity. Altogether, the authors propose the use of RNA-seq data from human whole blood as a way to study the blood microbiome and establish potential associations between blood resident microbes and host gene expression

      Major comments:

      1. The methodology to filter and remove reads from potential contaminants needs to be more stringent to ensure the results do not contain spurious contaminants and that the conclusions are correct. It has been described that genomic databases are heavily contaminated with human sequences (Steinegger and Salzberg, 2020), and in this manuscript, even after a two-pass alignment with STAR, reads mapping to helminths also corresponded to the human genome. Additionally, ad-hoc removal of specific taxa (Metazoa and Viridiplantae) was only performed after suspicion of contamination. However, this ad-hoc removal cannot be performed with microbial (bacterial, viral, etc.) contaminants as there is a risk of removing actual bacteria from the samples. But it has been confirmed that many microbial assemblies also suffer from human contamination. Possible actions to take are the following:
        • a.Perform the human mapping with more lenient parameters to avoid human reads to map to other (likely contaminated) genomes in genome databases.
        • b.Remove common contaminants that have been documented, for instance in blood (Chrisman et al., 2022).
        • c.Run a tool to detect contaminated contigs in the database used to map reads to microbes and remove these problematic contigs from further analysis.
      2. In line with the above, removing singletons (as I have understood these are taxa that are represented by a single read), is a way to minimize the risk of contamination. To take advantage of the functional profiling of RNA-seq, a measure to ensure that microbes found in blood are active would be to include in the analysis only taxa for which expression of more than a few genes is detected. This type of filtering has been previously applied in studies where very low microbial loads are expected (Lloréns-Rico et al., 2021). In this study, it has only been applied to the specific case of the archaeal taxon Methanocaldococcaceae. However, I would expect cleaner results if applied consistently to all taxa detected.
      3. The specificity of Methanocaldococcaceae in the samples from Mali is very striking. I am highly suspicious that this only occurs due to a batch effect, even though the authors were highly selective in their cohorts to avoid these. In fact, I extracted the genes spanning the regions highlighted in Supplementary Figure 9 of the Methanocaldococcus jannaschii genome. A BLAST search of these sequences returned, among Methanocaldococcus hits, hits from the ERCC synthetic spike-in sequences, used as internal controls in many RNA-seq experiments. ERCC synthetic spike-in hits appeared for all 4 regions in the genome of M. jannaschii highlighted in this figure. In the original publications of this dataset, there is no reference to the use of these ERCC controls, but given the observed matches, I suggest the authors to perform an extra step in their filtering pipeline to remove all reads mapping to these ERCC standards in all their three cohorts to prevent these sort of batch effects.
      4. I am puzzled by the inconsistencies shown between forward and reverse reads when mapping paired-end data. I expect these inconsistencies at lower taxonomic ranks (species or genus level) due to incomplete genomes, but not at higher taxonomic ranks. I wonder if, by performing more stringent filtering of contaminants as suggested above, the consistency between forward and reverse reads increases and both mates can be used, making the mapping more reliable.

      In summary, my main concerns regarding this manuscript involve the possibility that contaminants in the sequencing data may be the cause of some of the results presented, and I tried to propose ways of dealing with these contaminants. While some of the results may not be affected by detection of contaminants (i.e. the association between Apicomplexa and some ICs), others such as the diversity measures or the comparison across cohorts may be severely affected. I will consider these results highly preliminary until a more thorough and stringent approach for contaminant removal is applied.

      Minor comments:

      1. I would appreciate some of the analyses done at lower taxonomic levels if the sparsity of the data allows it, after removing contaminants. Given that the CLR transformation does not allow for zeros, other alternatives such as GMPR (Chen et al., 2018) or adding a pseudocount would allow these analyses?
      2. In the PCA shown in figure 1, does the number of microbial reads detected correlate with any of the first two components?
      3. In Figure 1C, the x axis is wrongly named PC2.
      4. There is a typo in the legend of Figure 1A ("showeing")
      5. In the alpha diversity estimates comparison across the three different cohorts, after subsampling each population to achieve similar sample size in each cohort, it is stated that "after subsampling, each population had similar diversity estimates". However, the numbers shown afterwards corresponding to the mean values of alpha diversity, without confidence intervals or a boxplot/violin plot together with an accompanying statistical test, are not enough to assess similarity. I would appreciate a figure (similar to Figure 3E and F) or a test accompanying these mean values.
      6. In the volcano plots (Figure 3A, B and others throughout the manuscript) it would help the reader to add lines for the thresholds chosen for the effect size and -log10(p-value) to separate significant results.
      7. In Figure 3E and F, I would appreciate having bars for the statistically significant comparisons.

      References:

      Chen, L., Reeve, J., Zhang, L., Huang, S., Wang, X., and Chen, J. (2018). GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data. PeerJ 6, e4600. https://doi.org/10.7717/peerj.4600.

      Chrisman, B., He, C., Jung, J.-Y., Stockham, N., Paskov, K., Washington, P., and Wall, D.P. (2022). The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families. Sci Rep 12, 9863. https://doi.org/10.1038/s41598-022-13269-z.

      Lloréns-Rico, V., Gregory, A.C., Van Weyenbergh, J., Jansen, S., Van Buyten, T., Qian, J., Braz, M., Menezes, S.M., Van Mol, P., Vanderbeke, L., et al. (2021). Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host. Nat Commun 12, 6243. https://doi.org/10.1038/s41467-021-26500-8.

      Steinegger, M., and Salzberg, S.L. (2020). Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank. Genome Biol 21, 115. https://doi.org/10.1186/s13059-020-02023-1.

      Significance

      The research reported in this manuscript may have both technical and clinical significance, once the concerns raised above are adequately addressed. At the technical level, once contamination can be ruled out or securely minimized, this work can provide guidelines for microbial identification from whole blood RNA-seq data, applicable to both prospective studies as well as to retrospective studies using previously generated datasets. From this perspective, this work would add to the existing body of bioinformatics pipelines aimed at detecting microbes from host RNA-seq data (Simon et al., 2018). From a clinical perspective, it can provide an additional means of pathogen and disease surveillance without the need of microbial culturing or pathogen-specific tests. However, the requirement of blood samples may still hamper use in rural or underdeveloped areas. Lastly, another advantage is the possibility to directly link microbial abundances to gene expression patterns in the host.

      Field of expertise: bacterial transcriptomics, metatranscriptomics, low-biomass microbiome analyses.

      Limitations in my expertise: I cannot evaluate the clinical implications of the associations between host gene expression patterns and microbial abundances. Also, I am not familiar with the ICA methodology.

      Reference:

      Simon, L.M., Karg, S., Westermann, A.J., Engel, M., Elbehery, A.H.A., Hense, B., Heinig, M., Deng, L., and Theis, F.J. (2018). MetaMap: an atlas of metatranscriptomic reads in human disease-related RNA-seq data. GigaScience 7, giy070. https://doi.org/10.1093/gigascience/giy070.

      PeerReviewed
    3. EMBOpress 14 Jun 2024

      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

      Summary:

      Authors performed a metatranscriptomic analysis from publicly-available datasets of whole blood from 3 places in Indonesia. Their goal was to explore which pathogens were present on the blood of those 117 healthy individuals. It was interesting that reads from Flaviviridae and Plasmodium were detected in asymptomatic subjects.

      Major comments:

      1. How did the authors assess and correct batch-effects between different datasets?
      2. Did the RNA-seq capture poly-A mRNAs? If so... these reads that did not map the human genome were captured because of internal priming. Can they find internal poly A sequences in the genome of Flaviviridae and Plasmodium pathogens? I would like to know that to understand the source of the reads and which other pathogens may be missing (due to the lack of internal priming).
      3. Principal coordinates analysis (PCoA) is often utilized in metagenomics analysis. Although they are equivalent, is there a reason for using PCA?

      Minor comments:

      1. "Indonesia is a country with large numbers of endemic and emerging infectious diseases [16], making it a crucially important location to monitor and understand the effects of pathogens on human hosts." Is there any epidemiological data that shows differences in infectious diseases across these 3 places? Can the authors provide a map and better explanation about the importance in comparing these 3 areas?
      2. Why is it so hard to try to identify (only for Flaviviridae reads) reads that map to very relevant viruses, such as Zika, Dengue, and Yellow Fever? Why did the authors state that they "were unable to refine this assignment further" if this is one of the most interesting finding?
      3. Is the script available at https://gitlab.unimelb.edu.au/igr-lab/Epi_Study ? This reviewer could not access it.

      Significance

      Interesting paper that enable to extract additional knowledge from whole blood RNA-seq data. There are already several papers that do this and I think authors could go one step forward (for instance, PCR validation of additional individuals). I don't think this can be used for surveillance if it cannot identify species, it is more expensive than running targeted assays, and that may be many false negative pathogens in the samples.

      PeerReviewed
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    Mining the heparinome for cryptic antimicrobial peptides that selectively kill gram-negative bacteria
    4
    1. EMBOpress 13 Jun 2024

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      Response to Reviewer 1

      __Glycosaminoglycan (GAG)-binding proteins regulating essential processes such as cell growth and migration are essential for cell homeostasis. It is reported that the GAG has the ability to bind to Herpin sulfate. As both GAGs and the LPS lipid A disaccharide core of gram-negative bacteria contain negatively charged disaccharide units, the researchers proposed that heparin-binding peptides might have cryptic antimicrobial peptide motifs. To prove the hypothesis, they have synthesized five candidates [HBP1-5], which showed a binding affinity towards heparin and LPS binding. By using various methods, they showed that these molecules have antimicrobial activity. The key finding in this study is the finding of the CPC domain, where C is a cationic amino acid and P is a polar amino acid. __

      Major comments

      1. __ Even though the Authors propose here that CPC' clip motif is needed for antimicrobial activity. However, various studies have demonstrated that the mere presence of cationic amino or hydrophobic amino acids does not give the activity, the location of these amino acids at the strategic position is critically needed. The major issue in this work, the authors have not presented, whether there was a single CPC motif or multiple in the 5 peptides they have synthesized. Further, they need to demonstrate how are the charged and hydrophobic amino acids distributed in the peptides. these things will clearly explain the difference in the activity as well spectrum of the peptides. The authors should make an extra figure or add information highlighting this unique characteristic for better understanding to the reader.__

      We thank the reviewer for his/her comments and suggestions. We concur that the distribution of amino acids is crucial for the antimicrobial activity of the peptides and their ability to bind heparin. We also agree with the suggestion of illustrating the location of the CPC' motifs of HBPs in the context of the parental proteins and have accordingly done so in the new Supplementary Figure 1. In all cases, only one CPC' motif was identified in the antimicrobial region, as highlighted in the figure, and the inter-residue distances measured are consistent with the CPC' motif definition. Thus, we demonstrate that a CPC' motif exists in all five HBPs, which explains how they recognize and bind heparin.

      To illustrate the distribution of charged and hydrophobic amino acids in HBPs, we have also prepared new Supplementary Figure 2, displaying electrostatic potentials in the predicted HBP structures, and showing how the distribution of charged residues creates hydrophobic and cationic patches on the surface of the peptides. Our analysis reveals cationic patches to be surrounded by hydrophobic residues, which may explain the ability of the peptides to disrupt membranes and exert antimicrobial activity.

      __ It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study.__

      We thank the reviewer for his/her comment on the observation of antimicrobial activity in peptides derived from heparin-binding proteins. Indeed, a few such studies have appeared in the literature, some with moderate success [1]. It is possible that a lack of understanding on how to identify heparin-binding regions in proteins and AMPs underlies their relative paucity. In this context, we believe our results will spur further efforts, specifically by providing a rationale on how to identify CPC' motifs hence heparin-binding regions in protein sequences.

      Regarding the suggestion of assessing the in vivo efficacy of HBPs, we would agree that it would be helpful for better understanding their potential therapeutic applications. However, we feel that such experiments are beyond the scope of our manuscript, which offers ample, compelling in vitro and in silico evidence of how heparin-binding proteins can be a source of AMPs. We have done this by showing that CPC' motifs embedded in such proteins can be unveiled, accurately defined in structural terms, and experimentally shown to possess antimicrobial activity. Furthermore, we have shown that heparin binding correlates with LPS binding, allowing us to propose a mechanistic explanation for how heparin binding can be related to antimicrobial activity.

      Translating these results to animal models is possibly premature at this stage as, from a classical medicinal chemistry perspective, it would require previous structural elaboration in terms of, e.g., optimized serum half-life or serum protein binding, both of which can modulate activity in in vivo studies regardless of heparin affinity or bactericidal activity per se. Ongoing work in our laboratories is focused in these directions and will be reported in due time.

      *Referees cross-commenting**

      Minor comments

      1. __ The presence of Cryptic antimicrobial domain in various heparin-binding proteins like laminin isoforms, von Willebrand factor, vitronectin, protein C inhibitor, matrix glycoproteins thrombospondin, proline arginine-rich end leucine-rich repeat protein and fibronectin, have been reported previous. It is not clear why the authors did not refer to that work. The authors should refer to the works. (same as reviewer 3)__

      We were aware of other prior studies on heparin-binding proteins and did indeed cite some of them, though not exhaustively for conciseness' sake. However, as encouraged by reviewers 1 and 3 we have cited the following studies:

      Malmström E, Mörgelin M, Malmsten M, Johansson L, Norrby-Teglund A, Shannon O, Schmidtchen A, Meijers JC, Herwald H. Protein C inhibitor--a novel antimicrobial agent. PLoS Pathog. 2009 Dec;5(12):e1000698. doi: 10.1371/journal.ppat.1000698. Epub 2009 Dec 18. PMID: 20019810; PMCID: PMC2788422.

      Ishihara, J., Ishihara, A., Fukunaga, K. et al. Laminin heparin-binding peptides bind to several growth factors and enhance diabetic wound healing. Nat Commun 9, 2163 (2018). https://doi.org/10.1038/s41467-018-04525-w

      Chillakuri Chandramouli R, Jones Céline and Mardon Helen J(2010), Heparin binding domain in vitronectin is required for oligomerization and thus enhances integrin mediated cell adhesion and spreading, FEBS Letters, 584, doi: 10.1016/j.febslet.2010.06.023

      Papareddy P, Kasetty G, Kalle M, Bhongir RK, Mörgelin M, Schmidtchen A, Malmsten M. NLF20: an antimicrobial peptide with therapeutic potential against invasive Pseudomonas aeruginosa infection. J Antimicrob Chemother. 2016 Jan;71(1):170-80. doi: 10.1093/jac/dkv322. Epub 2015 Oct 26. PMID: 26503666.

      All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So, this is unique and a novelty in the study.

      We thank the reviewers for these observations. Indeed, our quest to unveil CPC' motifs in antimicrobial regions of heparin-binding proteins is the key point of our investigation, and what distinguishes it from previous studies on consensus motifs such as XBBBXXBX or XBBXBX. We believe our definition of CPC' motifs in simple, structure-based, and experimentally verifiable terms is not only a significant departure but also a step forward from earlier views, highlighting the importance of a structural perspective in defining heparin-binding regions. In point of fact, we show that our peptides, even without consensus Cardin-Weintraub motifs, bind heparin with high affinity. The presence of the CPC' motif is crucial for such binding, as well as for LPS binding, and the new experiments performed at editor/reviewer's request, where the CPC motif in HBP5 is abolished, with predictable impact, fully support our view, see new section "Insights into the CPC' motif of HBP-5 and its implication on the antibacterial mechanism" and new Table 3 in the revised manuscript.

      __ Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heprin, the authors did not show any data or draw the conclusions related to the CPC domain when it comes to differences in the activity. this is the weakness of the manuscript. (same as reviewer 2)__

      We welcome the reviewer's observation. To address it, we made and tested three HBP-5 mutants aimed at showing how alterations in the CPC' motif might influence interaction with heparin and LPS, as well as antimicrobial properties. The first two mutants involved replacing positively charged R10 and R14 residues with glutamine, similar in size and polarity but uncharged. As shown in the new section "Insights into the CPC' motif of HBP-5 and its implication on the antibacterial mechanism" and on the new Table 3 of the revised manuscript, the changes reduced heparin binding, i.e., shorter retention times on affinity chromatography, as well as LPS binding, i.e., a decrease in EC50 in the cadaverine assay (Table 3). The modifications had a lesser impact on antimicrobial activity, most likely due to the low resolution of MIC assays.

      In a further step to assess the effect of the CPC' motif on antimicrobial activity, we deleted it in full by replacing residues H9, R10 and R14 of HBP-5 by alanine. As expected, this DCPC' peptide showed a sharp reduction in both heparin and LPS binding (Table 3) and, most importantly, a significant and asymmetric change in antimicrobial activity, with substantial impact on Gram-negatives yet practically no effect on Gram-positives, suggesting that LPS plays a key role in this selective response. Altogether, these observations align with our hypothesis that heparin-binding proteins might exploit their intrinsic affinity for heparin as an opportunity to developing antimicrobial properties by leveraging structural similarities between glycosaminoglycans and LPS.

      __ It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin (sic) binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study. (Same as reviewer 2)__

      We would kindly direct attention to #2 in the response to reviewer 1 above.

      __ There are more than 20 different AMP databases or prediction software. however, not all of them are 100 % current, their success rate varies from 30-50% only. It needs to be investigated if adding this search in the hit peptides might increase the success rate of the extra in silico-based AMPs prediction software.__

      If we understand the question correctly, the reviewer wonders whether including a CPC' motif predictor would increase the accuracy of AMP search algorithms. In our view, this strategy has two main limitations to be considered: (i) locating a CPC' motif in a peptide sequence typically requires a known 3D structure. Unfortunately, this is not always the case, and for proteins lacking reliable 3D data it can be a challenging and resource-intensive process; (ii) while CPC' motifs may predispose proteins to evolve antimicrobial properties, it is unclear if this is a required feature for all AMPs. Imposing the presence of a CPC' motif may not be applicable to all AMPs, although it might help identifying peptides with specific activity against gram-negative strains.

      In summary, while the query of including a CPC' motif search tool in AMP predictors is intriguing and worthy of exploration for its potential bearing on antimicrobial research, it is technically complicated and beyond the scope of our manuscript.

      __Reviewer #1 (Significance (Required)): __

      __All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So this is unique and a novelty in the study. __

      Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heparin, the authors did not show any data or draw conclusions related to the CPC domain when it comes to differences in the activity. This is the weakness of the manuscript.

      We would direct reviewer's attention to #1 in the Referee's cross-commenting section above.

      Response to Reviewer 2

      This is a very nice paper by the Andreu and Torrent groups that report the antimicrobial and heparin-binding of several encrypted peptides. Overall, this study presents an intriguing exploration into the potential dual functionality of glycosaminoglycan (GAG)-binding proteins, specifically heparin-binding proteins (HBPs), in recognizing lipopolysaccharide (LPS) and exhibiting antimicrobial properties. The findings, particularly the identification and characterization of novel encrypted peptides, such as HBP-5, are promising and contribute to our understanding of the intricate interplay between GAG-binding proteins and immunity. The data provided and methodology are thorough and well described. In sum, this is a very nice work. Please see below my minor comments.

      Minor comments:

      1. __ Fig. 1 legend does not show antimicrobial activity. Please remove from the figure legend title.__

      As pointed out by the reviewer, the legend was incorrect and has been corrected accordingly and now reads "Figure 1. Structural and bioinformatics analysis of HBPs".

      __ Discussion section: the authors should expand this section a bit to discuss recent work in the encrypted/cryptic peptide area. There are some recent relevant papers published in the past 3 years that should be discussed.__

      We agree with the reviewer's suggestion to expand the discussion section to address recent work in the field of encrypted/cryptic peptides. We have carefully reviewed the recent literature and added several references in this topic:

      Torres MDT, Melo MCR, Flowers L, Crescenzi O, Notomista E, de la Fuente-Nunez C. Mining for encrypted peptide antibiotics in the human proteome. Nat Biomed Eng. 2022 Jan;6(1):67-75. doi: 10.1038/s41551-021-00801-1. Epub 2021 Nov 4. Erratum in: Nat Biomed Eng. 2022 Dec;6(12):1451. PMID: 34737399.

      • *

      Santos MFDS, Freitas CS, Verissimo da Costa GC, Pereira PR, Paschoalin VMF. Identification of Antibacterial Peptide Candidates Encrypted in Stress-Related and Metabolic Saccharomyces cerevisiae Proteins. Pharmaceuticals (Basel). 2022 Jan 28;15(2):163. doi: 10.3390/ph15020163. PMID: 35215278; PMCID: PMC8877035.

      • *

      Boaro A, Ageitos L, Torres MT, Blasco EB, Oztekin S, de la Fuente-Nunez C. Structure-function-guided design of synthetic peptides with anti-infective activity derived from wasp venom. Cell Rep Phys Sci. 2023 Jul 19;4(7):101459. doi: 10.1016/j.xcrp.2023.101459. PMID: 38239869; PMCID: PMC10795512.

      __ References provided are a bit outdated and do not accurately reflect the latest in the field (see comment above).__

      We thank the reviewer for this comment. Older references were updated as suggested.

      __ Gram should be capitalized throughout the text.__

      Gram has been capitalized as suggested by the reviewer.

      __ Can the authors comment on the potential translatability of HBP-5? Please also comment on the potential advantages of having peptides that 1) bind to heparin; and 2) kill bacteria.__

      We appreciate the reviewer's interest in the potential of HBP-5. Indeed, we believe it has promise for clinical applications due to its unique attributes, but further studies, including in vivo experiments and pharmacokinetic assessments, are needed to fully evaluate its potential. The advantages of peptides that bind to heparin and kill bacteria include targeted delivery or localization of therapeutic agents, enhanced efficacy, and minimized off-target effects. HBP-5's ability to perturb outer membrane LPS, a crucial aspect of its antibacterial activity, makes it a promising approach to combat Gram-negative bacterial infections, which are often challenging to treat. By disrupting the outer membrane integrity, HBP-5 may also enhance the susceptibility of Gram-negative bacteria to other antimicrobial agents or host immune responses, underscoring its translational potential for treating bacterial infections.

      __ More details on the computational tools and methods used to mine the peptides are needed.__

      We have updated the Methods section to provide more details on the computational tools used for defining AMPs. Briefly, from the library of heparin-binding proteins obtained from previous studies [2] and AMP scanning for all these proteins was performed using the AMPA tool. The predicted antibacterial segments were located in the 3D structure of their respective proteins. Then, the CPC' motifs were searched in each segment following the criteria previously reported in [3, 4]. The motif involves two cationic residues (Arg or Lys) and a polar residue (preferentially Asn, Gln, Thr, Tyr or Ser), with fairly conserved distances between the carbons and the side chain center of gravity, defining a clip-like structure where heparin would be lodged. This structural motif is highly conserved and can be found in many proteins with reported heparin binding capacity. Finally, for all these regions, docking with a heparin disaccharide was performed using AutoDock Vina to evaluate the potential binding energy.

      Response to Reviewer 3

      __Summary: This manuscript has identified and investigated antimicrobial peptides from GAG binding proteins. Authors hypothesized that due to physiochemical similarity between GAG and LPS, fragments of GAG binding proteins might exert antimicrobial activity particularly against G- bacteria. Authors have identified few such AMPs that demonstrate LPS binding and displayed antibacterial activity. They have also solved NMR structure of the potent peptide and mode of action. __

      Major comments: AMPs are promising molecules that can serve as lead for the development of therapeutics against MDR bacteria. In particular, currently therapeutic options to treat MDR Gram negative pathogens are limited. The current study is interesting and provides new non-toxic AMPs. Conclusions drawn from the works are largely valid. However, authors should address following comments:

      1. __ The design and characterization of the peptide YI12WF is not described. Previous studies had shown design of β-boomerang peptides (Bhattacharjya and coworkers) that target LPS.__

      We thank the reviewer for this comment. YI12WF (YVLWKRKRFIFI-amide) has been previously reported [4, 5] and shown to bind LPS with high affinity. YI12WF also contains a CPC' motif that, if deleted, reduces heparin binding [4]. References have been added in the text.

      __ Mutations or substitution of the key residues peptide 5 might improve the novelty of the work.__

      We thank the reviewer for this comment and agree that targeted substitutions in HBP-5 might shed light on the importance of the CPC' motif. As this point was also raised by reviewer 1, we would direct the reviewer's attention to #2 in the *Referees cross-commenting** section above.

      __ How these peptides disrupt LPS permeability is not investigated. As LPS is the major target.__

      We thank the reviewer for this suggestion and have accordingly evaluated the outer membrane (OM) permeability of the peptides by the 1-N-phenyl-naphthylamine (NPN) assay, a widely used method to assess OM integrity in Gram-negative bacteria. NPN is typically unable to cross the intact outer membrane; however, when the membrane is damaged or disrupted, it can penetrate and interact with lipids and proteins inside the cell, leading to an increase in fluorescence which is directly correlated with the degree of OM permeability and serves as an indicator of membrane damage.

      Our results, illustrated in the new Figure 2D, show that all peptides are able to disrupt the OM of Gram-negative bacteria comparably to the LL-37 positive control, except for HBP2. Notably, HBP-5 exhibits the highest activity against OM, consistent with findings elsewhere in the manuscript and altogether confirming the ability of HBPs to bind to and disrupt the LPS structure.

      __ Are the D-enantiomers of the peptides active against bacteria?__

      We tested the antibacterial activity of the D-enantiomer of HBP5 (dHBP-and 5) and found it to be even higher than that of all-L HBP-5 against both Gram-negative and -positive bacteria, probably due to increased proteolytic stability as found in many AMP studies [6, 7]. As for LPS and heparin affinity, L- and D-HBP-5 behaved similarly (Table R1). As expected, the CD signatures of L- and D-HBP-5 were mirror images (Figure R1). These results suggest that the conformation of the CPC' motif is preserved in dHBP5, in tune with all previous results.

      Antibacterial Activity

      ID

      E. Coli

      P. Aeruginosa

      A. Baumannii

      S. Aureus

      E. Faecium

      L. monocytognes

      HPB-5

      0.4

      0.8

      0.2

      6.3

      25

      1.6

      dHBP-5

      0.1

      0.2

      0.2

      1.6

      0.4

      0.2

      Binding Affinity

      LPS (EC50, µM)

      Heparin (% Elution buffer)

      HPB-5

      0.9 {plus minus} 0.7

      98.0

      dHBP-5

      1.1 {plus minus} 0.8

      97.2

      Table R1. Antimicrobial activity of HBP-5 and dHBP-5

      Figure R1. CD spectra of HBP-5 (red line) and dHBP-5 (green line) in LPS (left panel) and heparin (right panel).

      __ 3D structure of peptide 5 is solved in DPC micelle which is a mimic for eukaryotic cells. Authors should attempt to determine structure in LPS as shown in several recent studies with potent AMPs thanatin, MSI etc.__

      We appreciate the suggestion and have indeed attempted to obtain NMR spectra of HBP-5 in LPS micelles. However, we've been hindered by peptide precipitation and, despite considerable efforts, have not been able to obtain satisfactory results thus far. In contrast, we have succeeded in obtaining CD spectra of HBP5 in LPS micelles, showing an a-helix conformation similar to the one in SDS micelles, hence suggesting similar conformation in both environments.

      Minor comments: There are examples of AMPs derived from human proteins. Authors should highlight such works.

      Other studies have been cited according to the reviewers' comments:

      Malmström E, Mörgelin M, Malmsten M, Johansson L, Norrby-Teglund A, Shannon O, Schmidtchen A, Meijers JC, Herwald H. Protein C inhibitor--a novel antimicrobial agent. PLoS Pathog. 2009 Dec;5(12):e1000698. doi: 10.1371/journal.ppat.1000698. Epub 2009 Dec 18. PMID: 20019810; PMCID: PMC2788422.

      Ishihara, J., Ishihara, A., Fukunaga, K. et al. Laminin heparin-binding peptides bind to several growth factors and enhance diabetic wound healing. Nat Commun 9, 2163 (2018). https://doi.org/10.1038/s41467-018-04525-w

      Chillakuri Chandramouli R, Jones Céline and Mardon Helen J(2010), Heparin binding domain in vitronectin is required for oligomerization and thus enhances integrin mediated cell adhesion and spreading, FEBS Letters, 584, doi: 10.1016/j.febslet.2010.06.023

      Papareddy P, Kasetty G, Kalle M, Bhongir RK, Mörgelin M, Schmidtchen A, Malmsten M. NLF20: an antimicrobial peptide with therapeutic potential against invasive Pseudomonas aeruginosa infection. J Antimicrob Chemother. 2016 Jan;71(1):170-80. doi: 10.1093/jac/dkv322. Epub 2015 Oct 26. PMID: 26503666.

      References

      1. Papareddy, P., et al., An antimicrobial helix A-derived peptide of heparin cofactor II blocks endotoxin responses in vivo. Biochimica et Biophysica Acta (BBA) - Biomembranes, 2014. 1838(5): p. 1225-1234.
      2. Ori, A., M.C. Wilkinson, and D.G. Fernig, A systems biology approach for the investigation of the heparin/heparan sulfate interactome. J Biol Chem, 2011. 286(22): p. 19892-904.
      3. Torrent, M., et al., The "CPC Clip Motif": A Conserved Structural Signature for Heparin-Binding Proteins.PLOS ONE, 2012. 7(8): p. e42692.
      4. Pulido, D., et al., Structural similarities in the CPC clip motif explain peptide-binding promiscuity between glycosaminoglycans and lipopolysaccharides. J R Soc Interface, 2017. 14(136).
      5. Bhunia, A., et al., Designed beta-boomerang antiendotoxic and antimicrobial peptides: structures and activities in lipopolysaccharide. J Biol Chem, 2009. 284(33): p. 21991-22004.
      6. Varponi, I., et al., Fighting Pseudomonas aeruginosa Infections: Antibacterial and Antibiofilm Activity of D-Q53 CecB, a Synthetic Analog of a Silkworm Natural Cecropin B Variant. Int J Mol Sci, 2023. 24(15).
      7. Chen, Y., et al., Comparison of Biophysical and Biologic Properties of α-Helical Enantiomeric Antimicrobial Peptides. Chemical Biology & Drug Design, 2006. 67(2): p. 162-173.
      PeerReviewed
    2. EMBOpress 13 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Summary: This manuscript has identified and investigated antimicrobial peptides from GAG binding proteins. Authors hypothesized that due to physiochemical similarity between GAG and LPS, fragments of GAG binding proteins might exert antimicrobial activity particularly against G- bacteria. Authors have identified few such AMPs that demonstrate LPS binding and displayed antibacterial activity. They have also solved NMR structure of the potent peptide and mode of action.

      Major comments: AMPs are promising molecules that can serve as lead for the development of therapeutics against MDR bacteria. In particular, currently therapeutic options to treat MDR Gram negative pathogens are limited. The current study is interesting and provides new non-toxic AMPs. Conclusions drawn from the works are largely valid. However, authors should address following comments

      1. The design and characterization of the peptide YI12WF is not described. Previous studies had shown design of b-boomerang peptides (Bhattacharjya and coworkers) that target LPS.
      2. Mutations or substitution of the key residues peptide 5 might improve the novelty of the work.
      3. How these peptides disrupt LPS permeability is not investigated. As LPS is the major target.
      4. Are the D-enantiomers of the peptides active against bacteria?
      5. 3-D structure of peptide 5 is solved in DPC micelle which is a mimic for eukaryotic cells. Authors should attempt to determine structure in LPS as shown in several recent studies with potent AMPs thanatin, MSI etc,

      Minor comments: There are examples of AMPs derived from human proteins. Authors should highlight such works.

      Significance

      The work described in the manuscript is novel and hold promises to develop antimicrobials in future.

      PeerReviewed
    3. EMBOpress 13 Jun 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      This is a very nice paper by the Andreu and Torrent groups that report the antimicrobial and heparin-binding of several encrypted peptides. Overall, this study presents an intriguing exploration into the potential dual functionality of glycosaminoglycan (GAG)-binding proteins, specifically heparin-binding proteins (HBPs), in recognizing lipopolysaccharide (LPS) and exhibiting antimicrobial properties. The findings, particularly the identification and characterization of novel encrypted peptides, such as HBP-5, are promising and contribute to our understanding of the intricate interplay between GAG-binding proteins and immunity. The data provided and methodology are thorough and well described. In sum, this is a very nice work. Please see below my minor comments.

      Minor comments:

      • Fig. 1 legend does not show antimicrobial activity. Please remove from the figure legend title.
      • Discussion section: the authors should expand this section a bit to discuss recent work in the encrypted/cryptic peptide area. There are some recent relevant papers published in the past 3 years that should be discussed.
      • References provided are a bit outdated and do not accurately reflect the latest in the field (see comment above).
      • Gram should be capitalized throughout the text.
      • Can the authors comment on the potential translatability of HBP-5? Please also comment on the potential advantages of having peptides that 1) bind to heparin; and 2) kill bacteria.
      • More details on the computational tools and methods used to mine the peptides are needed.

      Significance

      The data provided and methodology are thorough and well described. In sum, this is a very nice work.

      PeerReviewed
    4. EMBOpress 13 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Glycosaminoglycan (GAG)-binding proteins regulating essential processes such as cell growth and migration are essential for cell homeostasis. It is reported that the GAG has the ability to bind to Herpin sulfate. As both GAGs and the LPS lipid A disaccharide core of gram-negative bacteria contain negatively charged disaccharide units, the researchers proposed that heparin-binding peptides might have cryptic antimicrobial peptide motifs. To prove the hypothesis, they have synthesized five candidates [HBP1-5], which showed a binding affinity towards heparin and LPS binding. By using various methods, they showed that these molecules have antimicrobial activity. The key finding in this study is the finding of the CPC domain, where C is a cationic amino acid and P is a polar amino acid.

      Major comments

      1. Even though the Authors propose here that CPC' clip motif is needed for antimicrobial activity. However, various studies have demonstrated that the mere presence of cationic amino or hydrophobic amino acids does not give the activity, the location of these amino acids at the strategic position is critically needed. The major issue in this work, the authors have not presented, whether there was a single CPC motif or multiple in the 5 peptides they have synthesised. Further, they need to demonstrate how are the charged and hydrophobic amino acids distributed in the peptides. these things will clearly explain the difference in the activity as well spectrum of the peptides. The authors should make an extra figure or add information highlighting this unique characteristic for better understanding to the reader.
      2. It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study.

      Minor comments

      1. The presence of Cryptic antimicrobial domain in various heparin-binding proteins like laminin isoforms, von Willebrand factor, vitronectin, pro-tein C inhibitor, matrix glycoproteins thrombospondin, proline arginine-rich end leucine-rich repeat protein and fibronectin, have been reported previous. It is not clear why the authors did not refer to that work. the authors should refer to the works.

      Referees cross-commenting

      Minor comments

      1. The presence of Cryptic antimicrobial domain in various heparin-binding proteins like laminin isoforms, von Willebrand factor, vitronectin, pro-tein C inhibitor, matrix glycoproteins thrombospondin, proline arginine-rich end leucine-rich repeat protein and fibronectin, have been reported previous. It is not clear why the authors did not refer to that work. the authors should refer to the works. (same as reviewer 3)

      All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So this is unique and a novelty in the study.

      Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heprin, the authors did not show any data or draw the conclusions related to the CPC domain when it comes to differences in the activity. this is the weakness of the manuscript. (same as reviwer 2) 2. It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study.(Same as reviewer 2)

      Significance

      All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So this is unique and a novelty in the study.

      Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heprin, the authors did not show any data or draw the conclusions related to the CPC domain when it comes to differences in the activity. this is the weakness of the manuscript.

      There are more than 20 different AMP databases or prediction software. however, not all of them are 100 % current, their success rate varies from 30-50% only. It needs to be investigated if adding this search in the hit peptides might increase the success rate of the extra in silico-based AMPs prediction software

      PeerReviewed
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    O-GlcNAcylation of the intellectual disability protein DDX3X exerts proteostatic cell cycle control
    4
    1. EMBOpress 11 Jun 2024

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      Reply to the reviewers

      Reviewer 1:

      Although HEK cells are effective for studying molecular mechanisms and post-translational modifications through siRNA and variant overexpression manipulations, they lack functional relevance in a neuronal context. Consequently, the connection between molecular findings and observed phenotypes in mice is tenuous. It is suggested that the authors attempt to replicate these results (Figures 4 and 5) using a neuronal differentiation model employing ESCs or iPSCs.

      We have previously attempted to generate DDX3XSer584Ala knock-in ESCs via CRISPR-Cas9 because, as the reviewer points out, this would facilitate investigating the role of DDX3X O-GlcNAcylation in a neuronal differentiation model. However, clones derived after puromycin selection stop proliferating and perish during clonal outgrowth - we will include a statement to this effect in the revised manuscript. A similar phenomenon has been reported previously in Neuro2a cells by Lennox et al. (2020), who reported that installation of DDX3X patient variants is potentially toxic in certain cell lines. Therefore, the HEK293 KD/overexpression approach, also used for the study of clinically relevant DDX3X variants in other studies, while sub-optimal, is the best possible currently accessible model.

      While employing variant overexpression following siRNA-mediated reduction of the endogenous protein is a direct method to illustrate the effects of mutated DDX3X variants, the authors stress a connection between this regulatory mechanism and neurodevelopmental defects. Therefore, it would be justifiable for the authors to create cell lines by editing the endogenous DDX3X gene and demonstrate the effects of O-GlcNAc, disruption of DDX3X target levels, and cell cycle regulation. Combining these approaches (from points 1 and 2), the authors could generate iPSC/ESC lines containing the DDX3X mutations and examine their effects within a neuronal differentiation context. Such an approach would significantly enhance the impact of this study.

      As mentioned above for point 1, we have previously tried to edit the endogenous DDX3X gene with a Ser584Ala point mutation for this purpose. However, after trying this approach in both ESCs and HEK293T cells, we consistently observed stalled proliferation and cell death during clonal outgrowth. Therefore, as desirable as this experiment is, we are limited to siRNA-mediated reduction of DDX3X and rescue via over-expression, as also extensively used in other studies.

      Given the points raised by reviewers 1 and 3 about the appropriateness of model system and the links drawn between DDX3X O-GlcNAcylation and neurodevelopmental defects, we will revise the manuscript to highlight the correlative nature of this link. In addition we will add further data from OGT-CDG mouse models that strengthens this possible link (see response to point 4 by reviewer 1).

      The finding of diminished DDX3X levels in OGT mutant mice and the consequent reduction in O-GlcNAc represents a pivotal connection to the observed neurodevelopmental defects in OGT-CDG. However, this aspect of the research remains somewhat unclear, as it has not been definitively demonstrated that O-GlcNAc levels of DDX3X in OGT mutant mice are indeed decreased. Without this confirmation, the causal relationship between OGT malfunction, O-GlcNAc, and reduced DDX3X levels cannot be firmly established. There is a possibility of indirect effects, and merely observing correlation does not suffice to draw the robust conclusions presented in this paper. To address the uncertainty surrounding Figure 6D, attributed to the antibody's declared lack of specificity, the authors should conduct additional experiments.

      The aim of this study is not to confirm whether there is a causal link between OGT catalytic deficiency and DDX3X, but rather to report the function of DDX3X O-GlcNAcylation and propose a possible link between OGT catalytic deficiency, DDX3X loss of activity, and neurodevelopmental defects. However, we do agree that further investigation is required to determine whether there is a correlative link between OGT catalytic deficiency and DDX3X levels (and O-GlcNAcylation) in the mouse brain. Towards this end, we will repeat the immunoprecipitation of DDX3X from mouse brain lysate of wild type and OGT-CDG mice and blot for O-GlcNAc using different pan-specific O-GlcNAc antibodies/ far western techniques (CTD110.6, GST-CpOGAD298N). We will also incorporate an internal negative control (competition with free GlcNAc) to verify the specificity of the O-GlcNAc signals.

      The study places significant emphasis on this phenotype and seeks to elucidate it, at least partially, through the O-GlcNAcylation of DDX3X. However, a precise description or depiction of this phenotype is absent. Understanding the phenotype of the OGT-CDG mice necessitates consulting existing literature. The authors ought to contemplate providing brain sections with relevant staining to (i) showcase the microcephaly phenotype and (ii) bolster their assertion regarding the dysregulated cell cycle by utilising appropriate marker stainings for the progenitor cells during embryonic development.

      We have recently published a manuscript reporting a mouse model of OGT-CDG (OGTC921Y). OGTC921Y mice display microcephaly as determined by brain weight and skull length. An additional mouse model of the N648Y OGT-CDG variant also displays microcephaly (Authier et al., 2024 reports the C921Y mouse; the N648Y mice line is on BioRxiv: https://doi.org/10.1101/2023.08.23.554427 and subject to peer review elsewhere). As part of the revisions for this manuscript, we will report a micro CT-based analysis of reduced skull/brain volume that supports the microcephaly phenotype. O-GlcNAc, OGT, OGA, DDX3X and cyclin E1 western blots for three brain regions from these mouse models will also be provided. Furthermore, we will include NeuN staining of cortical brain sections to establish whether cortical density is reduced in OGTN648Y mouse brains. The proposed staining of progenitor cells during embryonic corticogenesis is a very good suggestion for future investigation, but is a time-consuming experiment (est. 1 year) that falls beyond the scope of this study and would delay sharing of our current findings.

      The proposed staining of progenitor cells during embryonic corticogenesis is a time consuming experiment (est. 1 year) that falls beyond the scope of this study.

      Reviewer 2:

      Figure 6 D - text last paragraph on page 16, and in supplement where you use RL2 - You need to do the control to show that RL2 staining goes away in the presence of free GlcNAc or when you galactosylate the protein. This control would indicate that you are detecting the sugar, not the protein backbone.

      We agree with the reviewer that an internal negative control will help validate the specificity of the RL2 signal. We will repeat the immunoprecipitation/ O-GlcNAc western blot with a free GlcNAc control.

      • Reviewer 3:*

      Lack of Appropriate Model System: Although the authors initially address the role of O-GlcNAcylation (OGT/OGA) and DDX3X in cerebral development, given that mutations in these enzymes are causative for neurological malformations and disabilities, the experiments addressing the consequences of DDX3X or OGT silencing are predominantly performed in HEK293T cells rather than a nervous system model. This limits the relevance of the findings.

      As discussed above (see Reviewer 1, points 1 and 2), we have previously tried to generate ESC knock-ins of the DDX3XSer584Alain ESCs to establish a neuronal differentiation model. However, clones perish during outgrowth, and thus these experiments are not possible. We have however performed preliminary biochemical analysis of DDX3X levels in the brains of OGT-CDG mice. It is important to emphasise that whether there is a causal link between OGT catalytic deficiency, DDX3X and cerebral development, lies beyond the remit of this manuscript. This manuscript aims to highlight DDX3X loss of activity as a candidate conveyor of neurodevelopmental defects in the mouse brain.

      Inconclusive Cell Cycle Analysis: The authors' analysis regarding cell cycle characterization is not sufficiently conclusive. First, they need to accurately define the link between DDX3X and cyclin E1. The study they refer to (Lai et al., 2010) is rather superficial, and requires a more in-depth analysis, in order to appreciate the existing link between the two given molecules. Indeed, the current experiments do not clarify whether cells are stuck in G1 due to cyclin E1 downregulation or if cyclin E1 is downregulated because cells are blocked in G1. A suggested approach would be to perform rescue experiments with cyclin E1 overexpression, by using Quantitative Image-Based Cytometry (QIBC) or flow cytometry (EdU incorporation + Hoecsht staining) to monitor cell cycle changes and define the interplay between these molecules mechanistically. However, this alone cannot exclude the presence of alternative substrates of DDX3X regulation influencing cell cycle phase transition. A more holistic approach, such as an interactome analysis through mass spectrometry, may be helpful. Additionally, mild mitotic stress often results in cell cycle arrest in the subsequent G0/G1 phase, which can resemble the G1/S transition impairment described by the authors. Consequently, the statement "Here we identify Ser584 O-GlcNAcylation of DDX3X (...) as a key regulator of G1/S transition" is not well-supported (to do so, the authors should define the temporal pattern of such post-translational modification). It would also be interesting to determine whether the reduction in cell viability is due to a simple slowdown of the cell cycle or apoptotic induction.

      We agree that performing cyclin E1 over-expression could provide mechanistic insights into the link between DDX3X, cyclin E1, and the cell cycle. We will therefore repeat the cell cycle analysis by flow cytometry shown in Fig. 5B with the addition of cyclin E1 over-expression in cells co-transfected with siRNA against DDX3X and siRNA-resistant DDX3XSer584Ala, to investigate whether cyclin E1 rescues the observed accumulation of cells in G1.

      We acknowledge the reviewer's point that quiescence (G0 entry) and G1/S stalling can provide similar cell cycle profiles to that observed in Fig. 5B. We will therefore re-write the necessary sections of the manuscript to emphasise that we cannot be certain whether the observed cell cycle defects resulting from loss of DDX3X Ser584 O-GlcNAcylation stem from G1/S phase stalling or mitotic stress followed by quiescence.

      Regarding the possibility that our observed reductions in the number of viable cells stems from stalled cell cycle progress or apoptosis, we will knock-down DDX3X and blot for cleaved caspase-3 as a marker for apoptosis to investigate the latter.

      The proposed interactome analysis of DDX3X is a tangential experiment. Given that DDX3X regulates cell cycle progression through its RNA helicase and transcriptional co-regulator functions, interactome analysis would not provide direct (or indeed, useful) readouts of how loss of DDX3X Ser584 O-GlcNAcylation affects cell cycle progression (i.e. it is possible there are significant effects on DDX3X activity without affecting the interactome).

      Weak Correlative Link: While the link between OGT/OGA and the cell cycle is well-established (seereviewSaunders et al., 2023) due to the multitude of targets subjected to this post-translational regulation, the correlative link between DDX3X mutations and cell cycle effects is further weakened by the fact that cyclin E1 knockout mice are indistinguishable from their wild-type littermates.

      DDX3X controls the transcription and translation of hundreds of genes, not just cyclin E1. For example, DDX3X controls Klf4 transcription which, in certain cell lines, regulates S-phase entry (Canizarro et al., FEBS Lett. 2018). Thus, it is possible for one candidate conveyor of the observed cell cycle defects to not produce significant phenotypes in a KO mouse. In the interests of emphasising this point, we will add a discussion point regarding the multiple pathways through which loss of DDX3X O-GlcNAcylation may affect the cell cycle in the discussion.

      Throughout the text, the authors refer to figures out of alphanumerical order, making the reading experience extremely difficult. To enhance readability, it is essential to present figures in a logical, sequential manner. Additionally, for further comments I would suggest to implement the text with line numbers.

      We will correct the text to ensure all figures are referenced and presented in a sequential manner, and line numbers will be added.

      PeerReviewed
    2. EMBOpress 11 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      In the manuscript, Mitchell et al. explore the interplay between O-GlcNAcylation and the cell cycle, with a particular focus on how DDX3X, an RNA helicase of the DEAD box family, influences the G1/S phase transition. The authors begin with a bioinformatics strategy to identify patterns of correlation between cell cycle regulators and the enzymes OGT and OGA in a dataset of temporal transcriptomics of the human prefrontal cortex. They then narrow their analysis to DDX3X, due to its strong potential correlation with the cell cycle and its candidacy as a substrate for O-GlcNAcylation. Subsequently, the authors biochemically investigate how O-GlcNAcylation regulates DDX3X. Finally, given that DDX3X has been previously shown to regulate cyclin E1, the authors assess the effect of DDX3X depletion on the cell cycle in vitro.

      Major comments:

      Despite the authors' interesting identification of a novel substrate for O-GlcNAcylation, most conclusions drawn from the study are correlative. The manuscript suffers from three major drawbacks:

      1. Lack of Appropriate Model System: Although the authors initially address the role of O-GlcNAcylation (OGT/OGA) and DDX3X in cerebral development, given that mutations in these enzymes are causative for neurological malformations and disabilities, the experiments addressing the consequences of DDX3X or OGT silencing are predominantly performed in HEK293T cells rather than a nervous system model. This limits the relevance of the findings.
      2. Inconclusive Cell Cycle Analysis: The authors' analysis regarding cell cycle characterization is not sufficiently conclusive. First, they need to accurately define the link between DDX3X and cyclin E1. The study they refer to (Lai et al., 2010) is rather superficial, and requires a more in-depth analysis, in order to appreciate the existing link between the two given molecules. Indeed, the current experiments do not clarify whether cells are stuck in G1 due to cyclin E1 downregulation or if cyclin E1 is downregulated because cells are blocked in G1. A suggested approach would be to perform rescue experiments with cyclin E1 overexpression, by using Quantitative Image-Based Cytometry (QIBC) or flow cytometry (EdU incorporation + Hoecsht staining) to monitor cell cycle changes and define the interplay between these molecules mechanistically. However, this alone cannot exclude the presence of alternative substrates of DDX3X regulation influencing cell cycle phase transition. A more holistic approach, such as an interactome analysis through mass spectrometry, may be helpful. Additionally, mild mitotic stress often results in cell cycle arrest in the subsequent G0/G1 phase, which can resemble the G1/S transition impairment described by the authors. Consequently, the statement "Here we identify Ser584 O-GlcNAcylation of DDX3X (...) as a key regulator of G1/S transition" is not well-supported (to do so, the authors should define the temporal pattern of such post-translational modification). It would also be interesting to determine whether the reduction in cell viability is due to a simple slowdown of the cell cycle or apoptotic induction.
      3. Weak Correlative Link: While the link between OGT/OGA and the cell cycle is well-established (see review Saunders et al., 2023) due to the multitude of targets subjected to this post-translational regulation, the correlative link between DDX3X mutations and cell cycle effects is further weakened by the fact that cyclin E1 knockout mice are indistinguishable from their wild-type littermates.

      Minor comments:

      Throughout the text, the authors refer to figures out of alphanumerical order, making the reading experience extremely difficult. To enhance readability, it is essential to present figures in a logical, sequential manner. Additionally, for further comments I would suggest to implement the text with line numbers.

      Significance

      Overall, the major novelty of the manuscript is the interesting link between DDX3X, its O-GlcNAcylation, and cell cycle regulation. However, this section requires the most intense revision to ensure robustness and clarity of the findings.

      PeerReviewed
    3. EMBOpress 11 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Missense mutations in OGT are causative in X-linked intellectual disability disorders, termed OGT-CDG. This paper identifies O-GlcNAcylation (OGN) at Ser584 of DDX3X, a known intellectual disability and microcephaly associated protein, as a regulator of G1/S transition, inhibiting the proteasome degradation of DDX3X. This OGN site controls the degradation of DDX3X. Lack of OGN at Ser 584 results in more rapid degradation of the protein, which affects the cell cycle. The study shows that dysregulation of DDX3X-dependent translation and concomitant impairments in cortical neurogenesis as a pathway disrupted in OGT-CDG. Overall, a well written paper. The data support the author's conclusions.

      Figure 6 D - text last paragraph on page 16, and in supplement where you use RL2 - You need to do the control to show that RL2 staining goes away in the presence of free GlcNAc or when you galactosylate the protein. This control would indicate that you are detecting the sugar, not the protein backbone.

      Significance

      This well prepared paper is highly significant. 1) It provides mechanistic insights into a cause of human intellectual disability; 2) It helps elucidate the role of O-GlcNAcylation in nutrient regulation of the cell cycle. 3) It provides more data on the roles of DDX3X.

      The paper is of significant general interest.

      PeerReviewed
    4. EMBOpress 11 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      O-GlcNAcylation is a post-translational modification and plays a crucial role in neurodevelopment. Variants of O-GlcNAc transferase (OGT) are linked to OGT Congenital Disorder of Glycosylation (OGT-CDG), a syndrome causing intellectual disability. Microcephaly in OGT-CDG patients suggests the involvement of cell cycle dysregulation and abnormal neurogenesis. Mitchell et al. identify Ser584 O-GlcNAcylation of DDX3X, a protein associated with intellectual disability and microcephaly, as a regulator of G1/S-phase transition. They show that this PTM of DDX3X stabilises and prevents the targeting of DDX3X to the proteasome and therefore its degradation. Reduced DDX3X levels in an OGT-CDG mouse model and decreased expression of DDX3X-target gene cyclin E1 suggest impaired cell cycle control and cortical neurogenesis as pathways affected in OGT-CDG.

      This study introduces DDX3X as a novel target for O-GlcNAcylation, which enhances its stability and ensures proper regulation of the cell cycle, particularly through its target cyclin E1. While the findings regarding DDX3X O-GlcNAcylation and the identification of the modified residue are compelling, addressing several issues regarding the link between O-GlcNAc of DDX3X-cell cycle regulation and neurodevelopmental impact would enhance the study's robustness.

      Major points requiring attention:

      1. Although HEK cells are effective for studying molecular mechanisms and post-translational modifications through siRNA and variant overexpression manipulations, they lack functional relevance in a neuronal context. Consequently, the connection between molecular findings and observed phenotypes in mice is tenuous. It is suggested that the authors attempt to replicate these results (Figures 4 and 5) using a neuronal differentiation model employing ESCs or iPSCs.
      2. While employing variant overexpression following siRNA-mediated reduction of the endogenous protein is a direct method to illustrate the effects of mutated DDX3X variants, the authors stress a connection between this regulatory mechanism and neurodevelopmental defects. Therefore, it would be justifiable for the authors to create cell lines by editing the endogenous DDX3X gene and demonstrate the effects of O-GlcNAc, disruption of DDX3X target levels, and cell cycle regulation. Combining these approaches (from points 1 and 2), the authors could generate iPSC/ESC lines containing the DDX3X mutations and examine their effects within a neuronal differentiation context. Such an approach would significantly enhance the impact of this study.
      3. The finding of diminished DDX3X levels in OGT mutant mice and the consequent reduction in O-GlcNAc represents a pivotal connection to the observed neurodevelopmental defects in OGT-CDG. However, this aspect of the research remains somewhat unclear, as it has not been definitively demonstrated that O-GlcNAc levels of DDX3X in OGT mutant mice are indeed decreased. Without this confirmation, the causal relationship between OGT malfunction, O-GlcNAc, and reduced DDX3X levels cannot be firmly established. There is a possibility of indirect effects, and merely observing correlation does not suffice to draw the robust conclusions presented in this paper. To address the uncertainty surrounding Figure 6D, attributed to the antibody's declared lack of specificity, the authors should conduct additional experiments.
      4. The study places significant emphasis on this phenotype and seeks to elucidate it, at least partially, through the O-GlcNAcylation of DDX3X. However, a precise description or depiction of this phenotype is absent. Understanding the phenotype of the OGT-CDG mice necessitates consulting existing literature. The authors ought to contemplate providing brain sections with relevant staining to (i) showcase the microcephaly phenotype and (ii) bolster their assertion regarding the dysregulated cell cycle by utilising appropriate marker stainings for the progenitor cells during embryonic development.

      Minor issue:

      Consider replacing in cellulo with in vitro

      Significance

      The study provides an in-depth biochemical analysis of the O-GlcNAcylation of DDX3X, identifying it as a novel target. However, limitations stem from the absence of a robust causal connection between OGT-DDX3X and neurodevelopmental effects, as well as the utilization of HEK cells rather than a neuronal model. Moreover, the study would gain from exploring endogenous proteins instead of solely relying on siRNA and OE methods to investigate the cellular and functional impacts of DDX3X O-GlcNAcylation. Overall, the study provides a mechanistic advance regarding O-GlcNAc PTM and the targets of OGT. This work could be of interest to audiences interested in neurodevelopment, as well as PTM of non-histone proteins.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.02.28.582457v1
  49. www.biorxiv.org www.biorxiv.org
    Autism candidate gene rbm-26 (RBM26/27) regulates MALS-1 to protect against mitochondrial dysfunction and axon degeneration during neurodevelopment.
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    1. EMBOpress 10 Jun 2024

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      Reply to the reviewers

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

      This manuscript uses C. elegans as a model to interrogate the effects of autism-associated variants of previously unknown function in the RNA-binding protein RBM-26/RBM27.

      Despite its potential impact, there are several concerns related to the technical rigor and specificity of the observed effects.

      Major concerns: 1. The effects on PLM are interesting, but why was this neuron selected for study? Was this a lucky guess or are other axons also affected? It is important to clarify whether the effects of RBM-26 are specific to this neuron or act pleiotropically across many or all neurons. According to CeNGEN, rbm-26 is strongly expressed in the well-characterized neurons ASE, PVD, and HSN. Are there morphological defects in these neurons, or others? As a note, there are also functional assays for these neurons (salt sensing, touch response, and egg laying, respectively).

      We have added new data to the supplemental materials showing that loss of rbm-26 function also causes the beading phenotype in the axons and dendrites of the PVD neuron (Figure S4 and lines 196-199). We have focused on the PLM neuron because our preliminary studies indicated that it had a higher penetrance of axon defects relative to the PVD neuron. Moreover, we observed expression of endogenously tagged RBM-26 in the PLM neuron (Figure 3A-C and lines 210-215).

      Similarly, the choice of the MALSU homolog seemed like a shot in the dark. It is ranked 46th (out of 63 genes) for fold-enrichment following RBM-26 pull-down, and 9th for p-value. Were any of the mRNAs with greater fold-enrichment or smaller p-values examined further? It is important to determine whether many or all of these interacting genes are overexpressed in the absence of RBM-26 and whether they are also required for the phenotypic effects of RBM-26 mutants, or if the MALSU homolog is special.

      We have clarified our reasoning for selecting the MALS-1 ortholog of MALSU1 for further study (see lines 283-284 and Table S2). Amongst binding partners with human orthologs, MALS-1 was by far the top ranked candidate. The adjusted p-value for MALS-1 was 0.0008. The next smallest adjusted p-value was two orders of magnitude larger (0.028 for dpy-4). Moreover, the log2fold fold enrichment for MALS-1 was 1.98, about the same as the largest (ACADS with 2.13). Nonetheless, we agree that some of the other interactors may also be of interest and have thus included them in the supplemental table S2. Although these other potential binding partners are outside the scope of this study, we expect that future studies by ourselves or others may focus on the roles of these other binding partners.

      In addition to the specificity controls mentioned above, positive and negative controls are needed throughout the results. While each of these may be relatively minor by itself, as a group they raise questions about the technical rigor of the study. Briefly these include: Fig 1C. Missing loading controls and negative control (rbm-26 null allele). Additional exposures should be included to show whether RBM-26(P80L) protein or the lower band for RBM-26(L13V) are present at all, relative to the null allele.

      We have added no-stain loading controls to figure 1C. We have also switched to using ECL detection, which is much more sensitive and reveals faint bands for RBM-26(P80L) and additional faint bands for RBM-26(L13V). In addition, we have included a longer exposure for the blot (Figure S1). We are unable to test the null, as we can only produce a limited number of small maternally rescued progeny, thereby precluding western blot analysis.

      Fig 2. Controls to distinguish overextension of PLM axon from posterior mispositioning of ALM cell body are needed. Quantification of PLM axon lengths in microns (or normalized to body size) with standard deviation, not error of proportion, should be shown. Measurement of "beading phenotype" should be more rigorous, see for example the approach in Rawson et al. Curr. Biol. 2017 https://doi.org/10.1016/j.cub.2014.02.025 . The developmental stage examined, and the reason for choosing that stage, should be described for this and all figures.

      We have added new data that shows PLM axon length relative to body length for each of the RBM-26 mutants (Figure S2 and lines 183-185). These results indicate that the PLM axon has a larger axon length to body length ration, suggesting that the PLM/ALM overlap phenotype is a result of PLM axon overextension. For most experiments, we retain penetrance, as this has been standard practice in the field and allows for a much larger sample size (see examples listed below). We have also added examples of how the beading phenotype was measured (Figure S3). Moreover, we have now analyzed this phenotype and others at multiple developmental stages (Figures 2D-H and Table S1). In general, we have conducted experiments at the L3 stage because the rbm-26(null) mutants don't survive past this stage. However, for many of our experiments we have also included additional stages as well. We have added this explanation to the methods section of phenotype analysis and also at various locations throughout the text. We have also labeled all graphs to clearly indicate the developmental stages and included.

      10.1038/s41467-019-12804-3 Article by laboratory of Brock Grill

      10.1371/journal.pgen.1002513 Article by laboratory of Ian Chin-Sang

      doi.org/10.1073/pnas.1410263111 Article by laboratory of Chun-Liang Pan

      10.1016/j.neuron.2007.07.009 Article by laboratory of Yishi Jin

      doi.org/10.1523/JNEUROSCI.5536-07.2008 Article by laboratory of William Wadsworth

      Fig 3. Controls without auxin and with neuronal TIR1 expression alone should be included. Controls demonstrating successful RBM-26 depletion, in larvae as well as in embryos at the time of PLM extension, should be included (weak embryonic depletion might explain why the overextension phenotype is only 14% instead of 40% as in the null). According to CeNGEN, rbm-26 expression in PLM is barely detected, thus depletion with a PLM-specific TIR1 should also be tested. To confirm the authors' identification of the cell marked "N" as the PLM cell body, co-expression of rbm-26 and a PLM-specific marker should be added. Rescue of the rbm-26 mutants with neuronal (and PLM-only) expression should be included to test sufficiency in PLM, and as a further control for potential artifacts of the AID system.

      We have added new data showing that an endogenously tagged RBM-26::Scarlet protein is expressed in the PLM neuron (Figure 3A-C). Moreover, we have added rescue experiments, showing that a Pmec-7::rbm-26::scarlet transgene can rescue the beading phenotype and the PLM/ALM overlap phenotype (Figure 3 F-G). We have also added controls without auxin (Figure S7) __and without the rbm-26::scarlet::aid gene (Figure S8). We have added a new figure showing auxin-mediated depletion of RBM-26::Scarlet::AID in the PLM neuron (Figure S10)__. We examined auxin-mediated depletion at the L3 stage for consistency with our auxin-mediated phenotypic experiments. Moreover, these were done at the L3 stage for consistency with other experiments that included the rbm-26(null) mutants, which don't survive past this stage.

      In general, auxin-mediated knockdown tends to be hypomorphic in neurons. This is likely due to the fact that the neuronal TIR1 driver is expressed at much lower levels relative to the other drivers. In addition, the lower penetrance observed in auxin-mediated PLM/ALM overlap phenotype could reflect the fact that this phenotype resolves by the L4 stage in the hypomorphic mutants. For example, in P80L mutants at the L3 stage we see only about a 20% penetrance of the PLM/ALM overlap phenotype (relative to about 15% in auxin-mediated knockdown).

      Fig 4. More rigorous quantification of the distribution of mitochondria along the axon should be included, not only total number, and it should be clarified what region of the axon the images are taken from. Including the AID-depletion strain with and without auxin would further add to the sense of rigor. For the mitoTimer experiments, why is RBM-26(L13V) not included and why do wild-type values differ ~5-fold between experiments (despite error bars being almost non-existent)? A more rigorous approach to standardizing imaging conditions may be needed. Positive controls using compounds that affect oxidation should be included. Measurements of individual mitochondria with standard deviations should be shown, rather than aggregate averages with error of proportion.

      We have changed our methodology for measuring mitochondria, so that we now report the density of mitochondria in the axon (number per 100µm), (Figure 4E-F). We agree that this method is much better than counting the total number of mitochondria per axon, as it corrects for differences in body length and axon length). We also now include data for the whole axon (Figure 4E), proximal axon (Figure 4G), and distal axon (Figure 4H). These data suggest that the mitochondrial density defects occur in the proximal axon but not in the distal axon. Using the null allele, we have also examined the timing of mitochondria defects in the axon and report that the defects begin in the L1 stage and continue throughout larval development (Figure 4F). Individual datapoints have been added for all graphs in Figure 4.

      For the mitoTimer experiments (Figure 5), we have added data for L13V and have added the individual datapoints to the graph. In the prior version, the values did not differ 5-fold between experiments with the same stage, rather the different graphs were from different stages (as noted in the figure legends/main text) and the L4 stage has much more oxidation than the L2 stage. To clear this up, we have added labels to the graphs to indicate the stages for each experiment. We have also added new data, so that we now show results for the L2, L3, and L4 stages for all three rbm-26 mutants (see Figure 5C-E). We didn't test the L1 stage because the signal was not sufficient for accurate quantitation.

      Fig 5. Additional positive and negative controls should be added, including additional rbm-26 alleles, the AID-tagged strain with and without auxin, and a rescued mutant.

      The old Figure 5 has become Figure 6 in the new version. We have added the rbm-26(L13V) allele to each experiment, (Figure 6B-D). We have also added the loading controls for the western blot along with quantification for 3 biological replicates of the western blot analysis (Figure 6D). We agree that these additions significantly strengthen the data because they show that two independent alleles of rbm-26 cause very substantial increase in the expression of mals-1 at both the mRNA and protein levels. We did not do these experiments with the rescuing transgene or with the AID-tagged strain because these experiments are done on whole worm lysates, whereas the AID-tagged and rescuing transgene are neuron-specific.

      Fig 6. Controls showing whether the Scarlet-tagged protein is functional are needed, to rule out dominant negative or toxicity-related effects.

      This is Figure 7 in the new version. For this experiment, we are showing that overexpression of MALS-1 does cause defects. The idea is that excessive amounts of MALS-1 causes deleterious effects to the mitochondria. In fact, these defects could be considered as dominant negative or toxic. We considered the possibility of crossing the Pmec-7::mals-1::scarlet transgene with rbm-26; mals-1 double mutants. However, this does not seem workable, because the single copy Pmec-7::mals-1::scarlet transgene produces the phenotypes at penetrances that are similar to what we observe in rbm-26; mals-1 double mutants. We concede that the results of the overexpression experiments in Figure 7 are limited when considered in isolation. However, we think that they are meaningful when considered in combination with the results on the mals-1;rbm-26 double mutants in Figure 8.

      Fig 8. Controls for other mitochondrial components need to be included. It is important to determine if the decrease in ribosomes is specific or reflects a general decrease in mitochondria. If there are fewer mitochondria as suggested in Fig. 4, then of course mitochondrial ribosomal protein levels are also reduced. Additional rbm-26 alleles should be included here as well. Is this effect dependent on the MALSU homolog?

      This is Figure 8D-E in the new version. We have added new data showing that the decrease in MRPL-58 expression that is caused by the rbm-26(P80L) mutation is dependent on MALS-1. We concede that these experiments cannot be used to determine anything about the mitoribosomes per se, but rather serve as an alternative way of testing the effect of rbm-26 on mitochondria. We have revised the text accordingly (lines 355-357). Given these limitations we have elected not to try additional mitochondrial markers and have also not included additional rbm-26 alleles for this experiment.

      Finally the authors should address concerns about image manipulation, which amplify the concerns about technical rigor outlined above. The image in Fig. 2A appears to have a black box placed over the lower-right portion of the field to hide some features. Black boxes also appear to have been placed over the tops of images in Fig. 4B and 4D and at the left of Fig. 6A, 6B, and 6C. While these manipulations probably do not affect the conclusions, they further undermine confidence in data integrity and experimental rigor.

      We have corrected all of these image processing errors. The box in 2A was for the purpose of squaring off a corner that was clipped during image rotation. The boxes in Figures 4 and 6 (of the prior version) were added to give space for labels (without obscuring image features). We have now used alternative methods to accomplish the same goals. For example, in Figures 4-D we have placed the labels outside of the images.

      Minor points. 1. C. elegans nomenclature conventions should be followed: - C. elegans gene names have three or four letters, thus the MALSU homolog cannot be named "malsu-1". Please have new gene names approved by WormBase BEFORE submitting for publication http://tazendra.caltech.edu/~azurebrd/cgi-bin/forms/gene_name.cgi

      We have changed malsu-1 to mals-1. In addition, both mals-1 and mrpl-58 have now been approved by wormbase and will be listed on the website upon its next update.

      • If two sequential CRISPR edits are made on the same gene then they should be listed as a compound allele, such as rbm-26(cue22cue25)

      We have updated our gene names to reflect this convention.

      • Genes on the same chromosome should not be separated with a semicolon, for example rbm-26(cue40) K12H4.2(syb6330)

      We have updated our gene names to reflect this convention.

      Describing the defects as "neurodevelopmental" is misleading in the case of axon beading or degeneration. Similarly, there is no evidence for an "axon targeting" defect as stated in the abstract.

      We have revised such that instead of referring to degeneration phenotypes as neurodevelopmental, we now refer to axon degeneration phenotypes that occur during development. For example, in the abstract we now say, "These observations reveal a mechanism that regulates expression of a mitoribosomal assembly factor to protect against axon degeneration during neurodevelopment.

      Regarding targeting defects, this was meant to refer to the misplacement of the PLM axon tip (which contains electrical synapses). However, our subsequent analysis has revealed that these defects are transient in P80L and L13V mutants, as they resolve by the L4 stage. The rbm-26 null axon development defects do not resolve, though these mutant die prior to the L4 stage. Given these findings, we have decided not to use the term of targeting defects. Instead, we now refer to this as an axon tiling defect or PLM/ALM overlap phenotype.

      In Fig. 5A, the symbol that appears to correspond to F59C6.15 (lowest p-value) is a different size than the others and is colored as ncRNA, whereas WormBase annotates this gene as snoRNA.

      This error has been corrected.

      In the Introduction, the last sentences of the first two paragraphs should be varied ("However, little is known about the [...] mechanisms that protect [...] during neurodevelopment.")

      This has been done.

      Why is RBM-26 protein running as a doublet at both sizes?

      We have improved our western blotting methodology by using 12% gel, allowing for better resolution. We have also switched from colorimetric detection to ECL detection, allowing for greater sensitivity. In our new blots, we identify 6 different RBM-26 protein bands. We don't know the reason for these bands, but speculate that they are the result of post-translational processing (148-150).

      When showing the RBM-26 expression pattern (Fig. 3) please include a lower-magnification image of the entire animal.

      This has been done (Figure S6)

      It is confusing to refer to the RNA IP experiments as an "unbiased screen", which in C. elegans typically refers to a genetic screen.

      We now refer to this as a "biochemical screen".

      The relationship between axon overextension, beading, and mitochondrial localization is not clear. What causal connection between these is being proposed? The causal connections between these phenotypes, if any, should be clarified experimentally. For example, if the axon extension defects develop before mitochondrial localization defects, then it is unlikely that mitochondrial defects cause axon overextension.

      We have added new data showing that the reduction in mitochondrial density within the axon begins during the L1 stage and increases throughout larval development (Figure 4F). We have also added additional data showing that the increase in mitochondrial oxidation is weak in the L2 stage and surges in the L3 stage (Figure 5C-E), coincident with the beginning of the axon degeneration phenotypes. We propose (lines 383-391) that a low level of mitochondrial defects is present in L1 larvae, giving rise to the axon tiling defects. In the L3 stage there is a surge in excessive mitochondrial oxidation, giving rise to the axon degeneration phenotypes. We have added a new section to the discussion that addresses the relationship between defects in axon development and axon degeneration (lines 375-405).

      Please explain how to interpret the difference in axon beading in the two deletion alleles of the MALSU homolog (axon beading defects in tm12122 but not in syb6330). Is syb6330 not a null allele? Or are the defects in tm12122 due to other mutations in this strain background?

      One likely reason for this difference is that tm12122 is predicted to cause a partial deletion of the mals-1 coding sequence, whereas the syb6330 is a full deletion. Thus, the tm12122 could be acting as a dominant negative. In fact, prior work on the MALSU1 ortholog has indicated that this protein is subject to interference by a dominant negative construct (see Rorbach et al, Nucleic Acids Res 2012). Nonetheless, we cannot rule out the possibility of a linked second mutation in tm12122. However, since we have found similar phenotypes and genetic interactions with both alleles, we can conclude that these phenotypes and interactions are due to loss of MALS-1, rather than a second mutation.

      Are mitochondria reduced in number or mislocalized? If they are reduced in number, is this due to altered balance of fission/fusion?

      We have adjusted our methods for quantifying mitochondria and have also analyzed the proximal vs distal axon (Figure 4). We find that the density of mitochondria is decreased in the proximal axon, but not in the distal axon. We speculate that this might reflect a higher demand on mitochondria in the proximal axon, due to a higher amount of trafficking activity in the proximal axon (lines 255-257). We propose that the loss of RBM-26 causes dysfunction in mitochondria. Since fission and fusion are mechanisms that can help to repair damaged mitochondria, it is likely that they would be involved in the phenotypes that we observe.

      In Fig. 3A-D, please keep the labels in the same position in all panels and do not alter brightness settings between single-color and merged panels.

      These images have been moved to the supplemental data section (Figure S5). We have adjusted the labels as suggested. We have not changed the brightness settings, as they were already the same in all panels. However, the blue signal in the merged panel does obscure some of the red signal, giving an appearance of an alteration in color balance.

      The claim that rbm-26 acts cell-autonomously requires PLM-specific depletion and rescue experiments.

      We have added new data indicating that a Pmec-7::rbm-26::scarlet transgene can rescue the beading phenotype (Figure 3F-G).

      **Referees cross-commenting** I appreciate the use of the consultation session to resolve differences between reviewers, but in this case I fully agree with the content and tone of all the comments from the other reviewer -- I think our remarks are very well aligned!

      Reviewer #1 (Significance (Required)):

      The study engineers autism-associated variants in conserved residues of RBM27 into the C. elegans homolog RBM-26 and identifies neuronal phenotypes potentially relevant to autism and a potential molecular mechanism involving regulation of mitochondrial ribosome assembly.

      The key claims of the study are 1} that autism-associated variants in RBM-26 decrease its protein expression; 2} that impaired RBM-26 function leads to a variety of defects in development and maintenance of a single neuron called PLM, including altered axonal localization of mitochondria; 3} that RBM-26 normally binds the mRNA for the C. elegans homolog of MALSU, a mitochondrial ribosomal assembly factor; 4} that loss of RBM-26 leads to overexpression of the MALSU homolog; and 5} that MALSU is required for some of the deleterious effects on the PLM neuron seen in RBM-26 mutants.

      This study will be of interest to the autism research community because it bolsters the idea that variants in RBM27 are likely to disrupt gene function and to affect neuronal health. It will also be of interest to the broader cell biology community because it suggests an interesting potential nucleus-to-mitochondria signaling mechanism, in which a nuclear RNA-binding protein might regulate assembly of mitochondrial ribosomes.

      My field of expertise is developmental biology in C. elegans.

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

      Summary In this manuscript, the authors studied an ASD-associated gene, rbm-26 in neuronal morphology using the touch receptor neuron PLM in C. elegans, and found that loss-of-function rbp-27 causes overextension and the formation of bulb-like structures in the axon. Using UV-crosslinking RNA immunoprecipitation and RNA-Seq, they identify malsu-1 as a target of rbm-26. Genetic analyses suggest malsu-1 likely functions downstream of rbm-26 in controlling the PLM morphology. Major comments:

      • The authors describe RBM27 is associated with ASD and ID while they only cite SFARI paper that describes a weak association of RBM27 to ASD. The appropriate referenced that show link between RBM27 and ID should be provided. The link with ID was an error. We had meant to say "ASD or other neurodevelopmental disorders." This has been corrected.

      • SFARI database only has three (P79L, R190Q, G348D) mutations listed as ASD-associated. Where are other mutations L13V and R455H, particularly L13V that the authors used to generate the C. elegans mutant come from? Are they associated with intellectual disabilities? The others came from the devovo-DB. We have added a reference for this database and have also added the primary source references for each of the five de novo variants (see line 121).

      • The authors should be very careful when describing 'gene X causes Y diseases'. Many (if not all) of the examples described in this manuscript are disease-associated genes without validation to be causal genes. We have revised accordingly. For example on lines 433-435, we now say," For example, mutations in the EXOSC3, EXOSC8 and EXOSC9 are thought to cause syndromes that include defects in brain development such as hypoplasia of the cerebellum and the corpus callosum". We have decided to use the phrase "thought to cause" because three of the five referenced articles on these genes use titles that indicate causation.

      • The authors refer PLM axon beading and overextension phenotypes to 'axon degeneration and targeting defects'. The authors must provide additional evidence of axon degeneration (see below). Also the term 'targeting defects' is misleading as the authors did not examine if overextension of the PLM axon causes targeting defects. At least they should examine some synaptic markers. To provide more evidence of degeneration we have analyzed several additional phenotypes at multiple developmental stages (Figure 2 and Table S1). Regarding targeting defects, this was meant to refer to the misplacement of the PLM axon tip (which contains electrical synapses). However, our subsequent analysis has revealed that these defects are transient in P80L and L13V mutants, as they resolve by the L4 stage. The rbm-26 null axon development defects do not resolve, though these mutant die prior to the L4 stage. Given these findings, we have decided not to use the term of targeting defects. Instead, we now refer to this as an axon tiling defect or PLM/ALM overlap phenotype.

      • Neuronal phenotypes (axon overextension and beading) should be examined at different developmental timepoints (larval, young adult, and aged animals) to test if these phenotypes are indeed degenerative instead of developmental defects. We have included new data to observe all of these phenotypes at multiple developmental time points (Figure 2 and Table S1).

      • The authors use the blebbing (beading) phenotype in the axon as the sole evidence of neurodegenerative properties of the PLM neuron. A more thorough analysis of this phenotype as done by others (Pan PNAS 2006) must be provided to support the authors' claim that this phenotype represents neurodegeneration. We have included new data on multiple degenerative phenotypes in axons including: blebbing, beading, waviness and breaks (Table S1).

      • The number of beads per axon should be quantified to better represent the severity of rbm-26 mutant. Individual samples should be plotted in the quantification instead of showing the percentage of animals. We have added data on the density of beads in rbm-26(null), rbm-26(P80L), and rbm-26(L13V) mutants (Figure S3). For most experiments we have decided to use penetrance to measure axon degeneration because this is a standard in the field and allows for a larger sample size. For examples please see:

      10.1523/JNEUROSCI.1494-11.2012 (Toth et al, 2012)

      https://doi.org/10.1016/j.cub.2014.02.025 (Rawson et al, 2014)

      10.1073/pnas.1011711108 (Pan et al, 2012)

      https://doi.org/10.7554/eLife.80856 (Czech et al, 2023)

      https://doi.org/10.1016/j.celrep.2016.01.050 (Nichols et al, 2016)

      • Based on the single gel image in Fig. 1C with no loading control, the P80L mutant appears to have no protein expression. How is the P80L viable while the null mutant is lethal? The authors should quantify the protein expression levels from multiple blots with proper loading controls. If P80L mutation is introduced into RBM-26::mScarlet strain can it cause depletion of the signal in vivo? We have added new data showing that the RBM-26::Scarlet signal is diminished by the P80L mutation in vivo (Figure 1E-F). We have also added quantification from 3 biological replicate blots (Figure 1D). Finally, we have improved the sensitivity of our blots by using ECL detection and also show various exposures to highlight the fainter bands (Figures 1C and S1). Therefore, we are now able to detect low level expression of RBM-26(P80L) mutant protein. It is likely that the low level of RBM-26(P80L) and RBM-26(L13V) seen on western blots is sufficient to prevent the lethal phenotype.

      • 'Moreover, loss of either the SPTBN1 or ADD1 genes causes a neurodevelopmental syndrome that includes autism and ADHD' References are missing, and as described above, be extra careful when indicating causality. Very few genes are known to cause ASD and ADHD. We have added the citations for this work (line 81). We also note that the titles for both of the cited articles indicate causation. To be on the safe side we have revised this line to say, "Moreover, loss of either the SPTBN1 or ADD1 genes are thought to cause a neurodevelopmental syndrome that includes autism and ADHD"

      • Fig. 3E F, the authors should use the strains that express TIR1 specifically in the touch receptor neurons to argue cell autonomous function of RBM-26. Alternatively, the authors may conduct PLM neuron-specific rescue experiments to test the sufficiency. We have added new data indicating that a Pmec-7::rbm-26::scarlet transgene can rescue the beading phenotype and the PLM/ALM overlap phenotype (see Figure 3F-G).

      • 'Loss of RBM-26 causes mitochondria dysfunction in axons.' The authors did not examine mitochondria function in axons. They only examined the number of mitochondria, and ROS production in the soma. The authors should provide additional evidence to support the idea that elevated ROS production in the soma is due to mitochondrial dysfunction in axons. Also, the authors should use both P80L and L13V for this experiment, and indicate individual datapoint as dots. Here, they quantified at the L4 stage, which the authors should justify. We have added the L13V data to this experiment and now show the individual data points. In addition, we have now conducted this analysis at the L2, L3 and L4 stages (Figure 5C-E). We have also revised the text to indicate that loss of rbm-26 function causes mitochondrial dysfunction in the cell body which could potentially cause a reduction of mitochondria in the axon (see lines 100-101 and 268-270). We speculate that mitochondria in the axon are also dysfunctional. However, the mitoTimer signal is not bright enough in axons to allow for quantification.

      • Figure 5B and C: the authors should also use L13V to quantify malsu-1 mRNA and protein level, and include quantifications in panel C (from multiple blots). This is Figure 6 in the new version. We have added new data for expression of mals-1 mRNA and protein in rbm-26(L13V) mutants (Figure 6B-D). We have also included quantifications from 3 biological replicates (Figure 6D).

      • In the rbm-26 mutant, the number of mitochondria is reduced, while the amount of MALSU-1 protein is increased. If MALSU-1 is specifically localized at mitochondria in wild type, where does the excessive MALSU-1 go in the rbm-26 mutants? Quantification of MALSU-1 signal intensity should be provided. Our Pmec-7::mals-1::scarlet transgene uses the tbb-2 3'UTR and causes an overexpression phenotype. To address the question posed by the reviewer, we would need to express MALS-1 at endogenous levels. Given that endogenous levels of MALS-1 are very low, it is unlikely that we would be able to visualize its expression. Nonetheless, as a way to address this question we have attempted to create a single copy Pmec-7::mals-1::scarlet transgene that utilizes the mals-1 endogenous 3'UTR. We have tried multiple approaches for generating this construct, but all have failed, likely due to sequence complexities within the mals-1 3'UTR. While we cannot say where the extra MALS-1 protein goes, we think that it is likely overloaded into the remaining mitochondria and could also be in the cytosol as well.

      • Figure 7C: malsu-1 knockout mutants exhibit PLM overextension phenotype, which is not consistent with their model. The authors should discuss this in detail. We have added a paragraph to the discussion explaining that mitochondria function could be disrupted by either MALS-1 overexpression or by MALS-1 loss of function (lines 471-480).

      • 'To validate these findings, we also repeated these experiments with an independent allele of malsu-1, malsu-1(tm12122) and found similar results (Fig. 7A-C).' The malsu-1(tm12122) exhibits beading phenotype and more severe overextension phenotype which the authors must describe and discuss more carefully. One likely reason for this difference is that tm12122 is predicted to cause a partial deletion of the mals-1 coding sequence, whereas the syb6330 is a full deletion. Thus, the tm12122 could be acting as a dominant negative. In fact, prior work on the MALSU1 ortholog has indicated that this protein is subject to interference by a dominant negative construct (see Rorbach et al, Nucleic Acids Res 2012). Nonetheless, we cannot rule out the possibility of a linked second mutation in tm12122. However, since we have found similar phenotypes and genetic interactions with both alleles, we can conclude that these phenotypes and interactions are due to loss of MALS-1, rather than a second mutation (albeit at a slightly different penetrance). We have added these considerations to the results section (lines 342-244).

      • Figure 8: The authors should include data from L13V, malsu-1 and rbm-26; malsu-1 mutants. Quantification from multiple blots should be provided. This is Figure 8D in the new version. We have added the malsu-1 and rbm-26;malsu-1 double mutants to this experiment. We have also added quantification from multiple biological replicate blots. As pointed out by the other reviewer, we think that this experiment does not give specific information about mitoribosomes, but is an alternative approach to looking at the reduction in mitochondria. Given this limitation and considering that we have added L13V data to the mitochondria experiment in Figure 8B, we have elected not to add additional data on L13V to the western blot experiment in Figure 8D

      Minor comments: • 'Consistent with a role for mitochondria in neurodevelopmental disorders, some of these disorders include a neurodegenerative phenotype.' Why is it consistent to have neurodegenerative phenotypes if mitochondria is associated with neurodevelopmental disorders? A better explanation would help.

      We have changed this sentence to, "Some neurodevelopmental syndromes feature neurodegenerative phenotypes that occur during neuronal development."

      • L13V is generally more severe in axon overextension phenotype than P80L while protein level is more abundant. The authors should discuss about this. We have also added a time course for the PLM/ALM overlap phenotype mutants (Figure 2D). This new data shows that the PLM/ALM overlap is quite similar overall between the P80L and L13V mutants. Both of these mutations cause an increase in PLM/ALM overlap in early larval development that is resolved by the L4 stage. The P80L phenotype resolves slightly sooner for reasons that are unknown. This could reflect differences in expression within the PLM that are not reflected in the whole worm lysate. This could also be due to a slight difference in the genetic background or other stochastic factors. The key point is that these two independent alleles cause similar phenotype overall, indicating that this phenotype is the result of loss in RBM-26 function.

      • Fig. 2E, F: 'Beading refers to focal enlargement or bubble-like lesions which were at least twice the diameter of the axon in size.' How are the diameters of axons measured? A more detailed quantification method, and examples of measurement should be provided. We have added example measurements to the supplemental section (Figure S3). Additional detail on the measurements are in the Methods section (lines 517-518).

      • Figure 3: The authors should also include low-magnification images to show where RBM-26 is expressed. The current image does now allow identifying cells. The transgene that labels the nuclei of hypodermis should be indicated in the manuscript. Specifically, the expression of the RBM-26 in the PLM should be shown. We have added a low magnification image (Figure S6) and have also added images of endogenously tagged RBM-26:Scarlet in the PLM (Figure 3A-C). The transgenic label for the hypodermis has been added to the legend of Figure S5.

      • Figure 3: 'Tissue specific degradation of RBM-26::SCARLET::AID was achieved due to cell-type specific TIR-1 driver lines (see methods for details).' This information is not provided in the method section. This information has been added to methods section, "Auxin proteindegredation"

      • Fig. 4 E. Values from individual samples should be indicated as dots. Representative images of P80L and L13V should be included. Conduct quantifications at adult stage as the authors use in other quantifications, or justify use of specific developmental stage (L3) they used. Figure 4 has become Figures 4 and 5 in the revised version. We have updated the graphs to include dots for individual data points. We have added quantifications of the mitoTImer experiments for the L2, L3 and L4 stages (Figure 5C-E). We note that our other experiments were done at the L1, L2, L3 and L4 and adult stages. The mitoTimer signal is not sufficient at the L1 stage for quantification. At the adult stage, the red signal becomes saturated. We have added representative images for mitoTimer in P80L and L13V mutants (Figure S9).

      • The genes malsu-1 and mrpl-58 are not listed on wormbase. If the authors would like to designate names to these gene, they should clearly indicate that along with the sequence name. We have changed malsu-1 to mals-1. In addition, both mals-1 and mrpl-58 have now been approved by wormbase and will be listed on the website upon its next update.

      • The authors found that MRPL-58 amount is reduced in rbm-26 mutants (which require additional verifications). This can be explained by the fact that axonal mitochondria number is reduced in the rbm-26 mutants. How did the authors confirm that the reduction in MRPL-58 level is due to the disruption of mitoribosome assembly? This is Figure 8D-E in the new version. We have added new data showing that the decrease in MRPL-58 expression that is caused by the rbm-26(P80L) mutation is dependent on MALS-1. We concede that these experiments cannot be used to determine anything about the mitoribosomes per se, but rather serve as an alternative way of testing the effect of rbm-26 on mitochondria. We have revised the text accordingly (lines 355-357).

      • 'MALSU-1 is a mitoribosomal assembly factor that functions as part of the MALSU1:LOR8F8:mtACP anti-association module [37-39].' I don't think these are known for C. elegans MALSU-1. We have revised to, "MALS-1 is an ortholog of the MALSU1 mitoribosomal assembly factor that functions as part of the MALSU1:LOR8F8:mtACP anti-association module"

      • 'Moreover, our results also suggest that disruption of this process can give rise to neurodevelopmental disorders.' I feel this is a quite a bit of stretch.

      This has been replaced with, "Therefore, we speculate that human RBM26/27 could function with the RNA exosome complex to protect against neurodevelopmental defects and axon degeneration in infants." (lines 371-373)

      **Referees cross-commenting** Yes, many of our comments overlap, and I fully agree with all comments from the other reviewer too. Reviewer #2 (Significance (Required)):

      I found the manuscript interesting particularly the use of innovative techniques in identifying the target of RBM-26, The genetic analyses of rbm-26 and malsu-1 generally support the authors main conclusions that rbm-26 inhibits malsu-1 and be of potential interest to basic neuroscientists and cell biologists. However, the current manuscript looked premature which made my reading experience less pleasant. The phenotypic analyses is superficial compared to works similar to this work, which are insufficient to support the authors' claim of 'axon degeneration and targeting defects'. A number of issues listed above should be addressed before this manuscript is published. The reviewer's expertise: neurodevelopment in model organisms.

      PeerReviewed
    2. EMBOpress 10 Jun 2024

      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 #2

      Evidence, reproducibility and clarity

      Summary

      In this manuscript, the authors studied an ASD-associated gene, rbm-26 in neuronal morphology using the touch receptor neuron PLM in C. elegans, and found that loss-of-function rbp-27 causes overextension and the formation of bulb-like structures in the axon. Using UV-crosslinking RNA immunoprecipitation and RNA-Seq, they identify malsu-1 as a target of rbm-26. Genetic analyses suggest malsu-1 likely functions downstream of rbm-26 in controlling the PLM morphology.

      Major comments:

      • The authors describe RBM27 is associated with ASD and ID while they only cite SFARI paper that describes a weak association of RBM27 to ASD. The appropriate referenced that show link between RBM27 and ID should be provided.
      • SFARI database only has three (P79L, R190Q, G348D) mutations listed as ASD-associated. Where are other mutations L13V and R455H, particularly L13V that the authors used to generate the C. elegans mutant come from? Are they associated with intellectual disabilities?
      • The authors should be very careful when describing 'gene X causes Y diseases'. Many (if not all) of the examples described in this manuscript are disease-associated genes without validation to be causal genes.
      • The authors refer PLM axon beading and overextension phenotypes to 'axon degeneration and targeting defects'. The authors must provide additional evidence of axon degeneration (see below). Also the term 'targeting defects' is misleading as the authors did not examine if overextension of the PLM axon causes targeting defects. At least they should examine some synaptic markers.
      • Neuronal phenotypes (axon overextension and beading) should be examined at different developmental timepoints (larval, young adult, and aged animals) to test if these phenotypes are indeed degenerative instead of developmental defects.
      • The authors use the blebbing (beading) phenotype in the axon as the sole evidence of neurodegenerative properties of the PLM neuron. A more thorough analysis of this phenotype as done by others (Pan PNAS 2006) must be provided to support the authors' claim that this phenotype represents neurodegeneration.
      • The number of beads per axon should be quantified to better represent the severity of rbm-26 mutant. Individual samples should be plotted in the quantification instead of showing the percentage of animals.
      • Based on the single gel image in Fig. 1C with no loading control, the P80L mutant appears to have no protein expression. How is the P80L viable while the null mutant is lethal? The authors should quantify the protein expression levels from multiple blots with proper loading controls. If P80L mutation is introduced into RBM-26::mScarlet strain can it cause depletion of the signal in vivo?
      • 'Moreover, loss of either the SPTBN1 or ADD1 genes causes a neurodevelopmental syndrome that includes autism and ADHD' References are missing, and as described above, be extra careful when indicating causality. Very few genes are known to cause ASD and ADHD.
      • Fig. 3E F, the authors should use the strains that express TIR1 specifically in the touch receptor neurons to argue cell autonomous function of RBM-26. Alternatively, the authors may conduct PLM neuron-specific rescue experiments to test the sufficiency.
      • 'Loss of RBM-26 causes mitochondria dysfunction in axons.' The authors did not examine mitochondria function in axons. They only examined the number of mitochondria, and ROS production in the soma. The authors should provide additional evidence to support the idea that elevated ROS production in the soma is due to mitochondrial dysfunction in axons. Also, the authors should use both P80L and L13V for this experiment, and indicate individual datapoint as dots. Here, they quantified at the L4 stage, which the authors should justify.
      • Figure 5B and C: the authors should also use L13V to quantify malsu-1 mRNA and protein level, and include quantifications in panel C (from multiple blots).
      • In the rbm-26 mutant, the number of mitochondria is reduced, while the amount of MALSU-1 protein is increased. If MALSU-1 is specifically localized at mitochondria in wild type, where does the excessive MALSU-1 go in the rbm-26 mutants? Quantification of MALSU-1 signal intensity should be provided.
      • Figure 7C: malsu-1 knockout mutants exhibit PLM overextension phenotype, which is not consistent with their model. The authors should discuss this in detail.
      • 'To validate these findings, we also repeated these experiments with an independent allele of malsu-1, malsu-1(tm12122) and found similar results (Fig. 7A-C).' The malsu-1(tm12122) exhibits beading phenotype and more severe overextension phenotype which the authors must describe and discuss more carefully.
      • Figure 8: The authors should include data from L13V, malsu-1 and rbm-26; malsu-1 mutants. Quantification from multiple blots should be provided.

      Minor comments:

      • 'Consistent with a role for mitochondria in neurodevelopmental disorders, some of these disorders include a neurodegenerative phenotype.' Why is it consistent to have neurodegenerative phenotypes if mitochondria is associated with neurodevelopmental disorders? A better explanation would help.
      • L13V is generally more severe in axon overextension phenotype than P80L while protein level is more abundant. The authors should discuss about this.
      • Fig. 2E, F: 'Beading refers to focal enlargement or bubble-like lesions which were at least twice the diameter of the axon in size.' How are the diameters of axons measured? A more detailed quantification method, and examples of measurement should be provided.
      • Figure 3: The authors should also include low-magnification images to show where RBM-26 is expressed. The current image does now allow identifying cells. The transgene that labels the nuclei of hypodermis should be indicated in the manuscript. Specifically, the expression of the RBM-26 in the PLM should be shown.
      • Figure 3: 'Tissue specific degradation of RBM-26::SCARLET::AID was achieved due to cell-type specific TIR-1 driver lines (see methods for details).' This information is not provided in the method section.
      • Fig. 4 E. Values from individual samples should be indicated as dots. Representative images of P80L and L13V should be included. Conduct quantifications at adult stage as the authors use in other quantifications, or justify use of specific developmental stage (L3) they used.
      • The genes malsu-1 and mrpl-58 are not listed on wormbase. If the authors would like to designate names to these gene, they should clearly indicate that along with the sequence name.
      • The authors found that MRPL-58 amount is reduced in rbm-26 mutants (which require additional verifications). This can be explained by the fact that axonal mitochondria number is reduced in the rbm-26 mutants. How did the authors confirm that the reduction in MRPL-58 level is due to the disruption of mitoribosome assembly?
      • 'MALSU-1 is a mitoribosomal assembly factor that functions as part of the MALSU1:LOR8F8:mtACP anti-association module [37-39].' I don't think these are known for C. elegans MALSU-1.
      • 'Moreover, our results also suggest that disruption of this process can give rise to neurodevelopmental disorders.' I feel this is a quite a bit of stretch.

      Referees cross-commenting Yes, many of our comments overlap, and I fully agree with all comments from the other reviewer too.

      Significance

      I found the manuscript interesting particularly the use of innovative techniques in identifying the target of RBM-26, The genetic analyses of rbm-26 and malsu-1 generally support the authors main conclusions that rbm-26 inhibits malsu-1 and be of potential interest to basic neuroscientists and cell biologists. However, the current manuscript looked premature which made my reading experience less pleasant. The phenotypic analyses is superficial compared to works similar to this work, which are insufficient to support the authors' claim of 'axon degeneration and targeting defects'. A number of issues listed above should be addressed before this manuscript is published.

      The reviewer's expertise: neurodevelopment in model organisms.

      PeerReviewed
    3. EMBOpress 10 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript uses C. elegans as a model to interrogate the effects of autism-associated variants of previously unknown function in the RNA-binding protein RBM-26/RBM27.

      Despite its potential impact, there are several concerns related to the technical rigor and specificity of the observed effects.

      Major concerns:

      1. The effects on PLM are interesting, but why was this neuron selected for study? Was this a lucky guess or are other axons also affected? It is important to clarify whether the effects of RBM-26 are specific to this neuron or act pleiotropically across many or all neurons. According to CeNGEN, rbm-26 is strongly expressed in the well-characterized neurons ASE, PVD, and HSN. Are there morphological defects in these neurons, or others? As a note, there are also functional assays for these neurons (salt sensing, touch response, and egg laying, respectively).
      2. Similarly, the choice of the MALSU homolog seemed like a shot in the dark. It is ranked 46th (out of 63 genes) for fold-enrichment following RBM-26 pull-down, and 9th for p-value. Were any of the mRNAs with greater fold-enrichment or smaller p-values examined further? It is important to determine whether many or all of these interacting genes are overexpressed in the absence of RBM-26 and whether they are also required for the phenotypic effects of RBM-26 mutants, or if the MALSU homolog is special.
      3. In addition to the specificity controls mentioned above, positive and negative controls are needed throughout the results. While each of these may be relatively minor by itself, as a group they raise questions about the technical rigor of the study. Briefly these include:

      Fig 1C. Missing loading controls and negative control (rbm-26 null allele). Additional exposures should be included to show whether RBM-26(P80L) protein or the lower band for RBM-26(L13V) are present at all, relative to the null allele.

      Fig 2. Controls to distinguish overextension of PLM axon from posterior mispositioning of ALM cell body are needed. Quantification of PLM axon lengths in microns (or normalized to body size) with standard deviation, not error of proportion, should be shown. Measurement of "beading phenotype" should be more rigorous, see for example the approach in Rawson et al. Curr. Biol. 2017 https://doi.org/10.1016/j.cub.2014.02.025 . The developmental stage examined, and the reason for choosing that stage, should be described for this and all figures.

      Fig 3. Controls without auxin and with neuronal TIR1 expression alone should be included. Controls demonstrating successful RBM-26 depletion, in larvae as well as in embryos at the time of PLM extension, should be included (weak embryonic depletion might explain why the overextension phenotype is only 14% instead of 40% as in the null). According to CeNGEN, rbm-26 expression in PLM is barely detected, thus depletion with a PLM-specific TIR1 should also be tested. To confirm the authors' identification of the cell marked "N" as the PLM cell body, co-expression of rbm-26 and a PLM-specific marker should be added. Rescue of the rbm-26 mutants with neuronal (and PLM-only) expression should be included to test sufficiency in PLM, and as a further control for potential artifacts of the AID system.

      Fig 4. More rigorous quantification of the distribution of mitochondria along the axon should be included, not only total number, and it should be clarified what region of the axon the images are taken from. Including the AID-depletion strain with and without auxin would further add to the sense of rigor. For the mitoTimer experiments, why is RBM-26(L13V) not included and why do wild-type values differ ~5-fold between experiments (despite error bars being almost non-existent)? A more rigorous approach to standardizing imaging conditions may be needed. Positive controls using compounds that affect oxidation should be included. Measurements of individual mitochondria with standard deviations should be shown, rather than aggregate averages with error of proportion.

      Fig 5. Additional positive and negative controls should be added, including additional rbm-26 alleles, the AID-tagged strain with and without auxin, and a rescued mutant.

      Fig 6. Controls showing whether the Scarlet-tagged protein is functional are needed, to rule out dominant negative or toxicity-related effects.

      Fig 8. Controls for other mitochondrial components need to be included. It is important to determine if the decrease in ribosomes is specific or reflects a general decrease in mitochondria. If there are fewer mitochondria as suggested in Fig. 4, then of course mitochondrial ribosomal protein levels are also reduced. Additional rbm-26 alleles should be included here as well. Is this effect dependent on the MALSU homolog? 4. Finally the authors should address concerns about image manipulation, which amplify the concerns about technical rigor outlined above. The image in Fig. 2A appears to have a black box placed over the lower-right portion of the field to hide some features. Black boxes also appear to have been placed over the tops of images in Fig. 4B and 4D and at the left of Fig. 6A, 6B, and 6C. While these manipulations probably do not affect the conclusions, they further undermine confidence in data integrity and experimental rigor.

      Minor points.

      1. C. elegans nomenclature conventions should be followed:
        • C. elegans gene names have three or four letters, thus the MALSU homolog cannot be named "malsu-1". Please have new gene names approved by WormBase BEFORE submitting for publication http://tazendra.caltech.edu/~azurebrd/cgi-bin/forms/gene_name.cgi
        • If two sequential CRISPR edits are made on the same gene then they should be listed as a compound allele, such as rbm-26(cue22cue25)
        • Genes on the same chromosome should not be separated with a semicolon, for example rbm-26(cue40) K12H4.2(syb6330)
      2. Describing the defects as "neurodevelopmental" is misleading in the case of axon beading or degeneration. Similarly, there is no evidence for an "axon targeting" defect as stated in the abstract.
      3. In Fig. 5A, the symbol that appears to correspond to F59C6.15 (lowest p-value) is a different size than the others and is colored as ncRNA, whereas WormBase annotates this gene as snoRNA.
      4. In the Introduction, the last sentences of the first two paragraphs should be varied ("However, little is known about the [...] mechanisms that protect [...] during neurodevelopment.")
      5. Why is RBM-26 protein running as a doublet at both sizes?
      6. When showing the RBM-26 expression pattern (Fig. 3) please include a lower-magnification image of the entire animal.
      7. It is confusing to refer to the RNA IP experiments as an "unbiased screen", which in C. elegans typically refers to a genetic screen.
      8. The relationship between axon overextension, beading, and mitochondrial localization is not clear. What causal connection between these is being proposed? The causal connections between these phenotypes, if any, should be clarified experimentally. For example, if the axon extension defects develop before mitochondrial localization defects, then it is unlikely that mitochondrial defects cause axon overextension.
      9. Please explain how to interpret the difference in axon beading in the two deletion alleles of the MALSU homolog (axon beading defects in tm12122 but not in syb6330). Is syb6330 not a null allele? Or are the defects in tm12122 due to other mutations in this strain background?
      10. Are mitochondria reduced in number or mislocalized? If they are reduced in number, is this due to altered balance of fission/fusion?
      11. In Fig. 3A-D, please keep the labels in the same position in all panels and do not alter brightness settings between single-color and merged panels.
      12. The claim that rbm-26 acts cell-autonomously requires PLM-specific depletion and rescue experiments.

      Referees cross-commenting I appreciate the use of the consultation session to resolve differences between reviewers, but in this case I fully agree with the content and tone of all the comments from the other reviewer -- I think our remarks are very well aligned!

      Significance

      The study engineers autism-associated variants in conserved residues of RBM27 into the C. elegans homolog RBM-26 and identifies neuronal phenotypes potentially relevant to autism and a potential molecular mechanism involving regulation of mitochondrial ribosome assembly.

      The key claims of the study are 1} that autism-associated variants in RBM-26 decrease its protein expression; 2} that impaired RBM-26 function leads to a variety of defects in development and maintenance of a single neuron called PLM, including altered axonal localization of mitochondria; 3} that RBM-26 normally binds the mRNA for the C. elegans homolog of MALSU, a mitochondrial ribosomal assembly factor; 4} that loss of RBM-26 leads to overexpression of the MALSU homolog; and 5} that MALSU is required for some of the deleterious effects on the PLM neuron seen in RBM-26 mutants.

      This study will be of interest to the autism research community because it bolsters the idea that variants in RBM27 are likely to disrupt gene function and to affect neuronal health. It will also be of interest to the broader cell biology community because it suggests an interesting potential nucleus-to-mitochondria signaling mechanism, in which a nuclear RNA-binding protein might regulate assembly of mitochondrial ribosomes.

      My field of expertise is developmental biology in C. elegans.

      PeerReviewed
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    The Sfp1 transcription factor integrates inputs from the TORC1 and PKA pathways
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    1. EMBOpress 08 Jun 2024

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      Reviewer 1

      The paper is overall convincing. However, a little more attention to data presentation and possibly the addition of at least another technique (see below) would greatly strengthen the findings.

      As we hope to demonstrate below, we have taken steps to improve our manuscript on both fronts (data presentation and experimental evidence).

      The absence of statistics catches immediately the eye. I am sure that the shown differences are statistically significant (thanks to the number of analyzed cells), but reporting the result of some statistical test would help the reader in identify the relevant data in a plot. This is somehow necessary considering that sometimes in the text something is deemed to be "significant" or "not significant", and I felt that I really needed that when looking at the plot in Fig. 3D.

      To facilitate the interpretation of figures that contain data from multiple strains (such as the one mentioned by the reviewer), we have carried out a nonparametric single-step multiple comparison test (Games-Howell) to identify mutants whose means differ significantly from each other. To avoid overcrowding the figures, we have graphically summarized the p-values of all pairwise comparisons in a small matrix within the corresponding panel, and provided 99% confidence intervals and p-values of all differences in the Supplement.

      Related to the previous point: for every N/C distribution analysis, a number of analyzed cells is reported. By the way it is written, it seems that the replication relies solely by the cells in that specific population, i.e.: each cell is treated as a replicate. At least I could not find if that is not the case in the legends or in the methods. I wonder what the results would be (and their significance) if each replicate would be a new assay on another population.

      Cell populations exhibit significant variability in their phenotypic characteristics. Consequently, the quantification of a specific feature (e.g., the Sfp1 nuclear/cytoplasmic ratio) across a sample of cells from a given population results in a distribution rather than a single fixed value. For each quantification, we report the number of cells that were used to construct the corresponding distribution, i.e. the sample size. To compare samples from different populations (e.g., different Sfp1 mutant strains), we run them in parallel during microscopy experiments and compare their means, as described above. Throughout our study, we have tried to ensure that we quantify a sufficiently large number of cells to overcome cell-to-cell variability and enhance the reliability of our results.

      In this context, the question of the reviewer is not entirely clear to us, as individual measurements of a sample are not replicates. However, one can replicate the entire experiment on a different day by re-growing the different strains, running microscopy, quantifying the new movies etc. In this sense, the experiments shown in the manuscript consist of single replicates, i.e. experiments that were carried out on the same day, with all the relevant mutants and controls quantified together. However, we have monitored many of our mutants multiple times over the course of our work. For example, Fig. 1 below shows replicates of the Sfp1 N/C ratio distributions at steady-state in the analog-sensitive (A) and wild-type (B) background, which were quantified several times across various experiments. While day-to-day variability in the empirical distributions of the same mutant exists to a small extent, it is quite small.

      The scale of x axes in N/C ratio plots. Besides not being consistent throughout the figures, it originates from 1, visually enhancing the differences.

      We believe the reviewer was referring to the y-axes, as the x-axes represent time. Summarizing the N/C ratio dynamics of different Sfp1 mutants has been challenging. First, the average N/C ratios at steady-state vary considerably across different mutants, as shown in the panels that summarize steady-state N/C ratios. To compare the magnitude and features of their responses, normalization is necessary. We chose to normalize the time series of each mutant to have a mean of 1 prior to the onset of a perturbation. This allows the normalized time series to represent the percentage-wise changes in the Sfp1 N/C ratio upon perturbation.

      Using a common y-axis scale for all plots of N/C ratio dynamics not ideal, as some responses are subtler than others. Additionally, we do not believe that N/C dynamics across different figures need to (or should) be compared to each other. However, within a figure, panels that require comparison are placed in the same row and share the same y-axis scale. We believe that this approach optimizes data visualization and facilitates important visual comparisons.

      Related to the previous point: it is evident from the plots that the N/C ratio is always positive, even in the most deficient of the analyzed mutants. This implies that a relevant fraction of Sfp1 is still nuclear. I thus wonder what the impact of these mutations would be on the actual function of Sfp1. For this reason, I feel that qPCR evaluation of transcripts of Sfp1 target genes is particularly needed. Since lack of Sfp1 is known to yield some of the smallest cells possible, it would also be cool to have an estimate of the size of mutants where Sfp1 is less nuclear. These analyses could confer phenotypical relevance to the data, but would also help in assessing a currently unexplored possibility, that phosphorylation events by PKA influence Sfp1 function besides its localization, i.e.: the still somehow nuclear fraction is not as functional as wt Sfp1 in promoting transcription.

      It is indeed the case that the recorded N/C ratios are larger than 1 in all strains that we have monitored. We have never observed an N/C ratio smaller than 1 using widefield microscopy for two main reasons: first, out-of-focus light from the cytosol above and below the nucleus is added to the nuclear signal, causing the nuclear signal to always be non-zero, even for predominantly cytosolic proteins. Second, both in- and out of focus vacuoles are devoid of the fluorescent protein fusions that we quantify, which reduces the average brightness of the cytosol. For these reasons, even when a protein is largely cytosolic, the average N/C ratio over a cell population is no lower than around 1.5. Keeping these points in mind, one can observe that our most delocalized Sfp1 mutants have an N/C ratio that is around 1.6-1.7, which is very close to the lower limit. This means that these Sfp1 mutants are largely cytosolic, and the nuclear fraction (if non-zero) is quite small.

      We agree that assessing the phenotypic relevance of Sfp1 mutations is of interest. However, this was impossible with our original strains, as we introduced each Sfp1 mutant as an extra copy in the HO locus while leaving the endogenous Sfp1 locus intact. This was done in order to avoid any phenotypic changes that might result from changes in Sfp1 activity.

      To address the suggestion of the reviewer, we therefore deleted the endogenous Sfp1 copy in strains carrying sfp1PKA2A, sfp1PKA2D and sfp113A, leaving only the mutated Sfp1 copy at the HO locus. Surprisingly, the growth rate and drug sensitivity (determined by halo assays) of these single-copy mutants did not differ much in comparison to the mutants carrying the functional Sfp1 copy and from the wild-type (Supp. Figs. 4J and 7). This observation aligns with findings for the single-copy sfp1-1 mutant in [Lempiäinen et al. 2009], which corresponds to sfp1TOR7A in our work. [Lempiäinen et al. 2009] had suggested that Sch9 compensates for the loss of Sfp1 activity via a feedback mechanism, which could explain our results as well. If this is the case, acute depletion of wild-type Sfp1 could unveil transient changes in cell growth, before the compensatory effect of Sch9 was established. Unfortunately, we were unable to efficiently degrade wild-type Sfp1 carrying a C-terminal auxin-inducible degron. Instead, we followed the same approach with [Lempiäinen et al. 2009] and deleted SCH9.

      As we describe in the last section of Results, the difference was dramatic for sfp113A __mutants, which were extremely slow-growing in the absence of Sch9 (doubling time was around 4 hours, but it was hard to estimate because we could not grow the cells consistently). Interestingly, SCH9 deletion had a negative impact on sfp1__PKA2D __but not sfp1__PKA2A __cells (__Supp. Fig. 7). Overall, these results demonstrate that Sch9 can compensate for loss of Sfp1 activity, which makes it challenging to study the impact of Sfp1 mutations on cellular phenotypes.

      To further understand to what extent Sch9 compensates for loss of Sfp1 phosphorylation, we carried out RNA-seq on WT and cells carrying a single copy of sfp113A (with the endogenous SFP1 copy removed). Despite the fact that sfp113A __grow as well as WT, RNA-seq picked up several differentially expressed genes related to amino acid biosynthesis. This surprising finding is presented in the last section of Results, and in __Supplementary Figures 8, 9 and 10. We explore the relevance of these results and their connection with past literature on Sfp1 and Sch9 in the Discussion section.

      I found some typos here and there, and it would greatly help to report them if in the manuscript line numbers were included.

      We apologize for the typos. We have tried to eliminate them, and we have also added line numbers to the manuscript.

      Reviewer 2

      There is no biochemical evidence presented that the putative PKA sites (S105 and S136) are genuinely phosphorylated by PKA. The fact that they match the PKA consensus motif, alone, does not guarantee this. In order to claim that they are looking at the effect of PKA by mutagenizing these residues, the authors have to demonstrate the PKA-dependency of S105 and S136 phosphorylation by, for example, mass spec experiments or western blotting with phospho-specific antibodies (Cell Signaling Technology #9624 for example). Also, does the band-shift caused by PKA inhibition (Fig 3C) is canceled by the S105A/S136A mutation?

      We took several actions to demonstrate that the putative PKA sites are indeed phosphorylated by PKA. We first tried to detect Sfp1 phosphorylation using the antibody mentioned by the reviewer, but failed as the sensitivity of this antibody appears to be quite low. On the other hand, mass spectrometry did not produce the right fragments to detect the sites of interest. We therefore resorted to an in vitro kinase assay using [γ-32P]ATP together with purified PKA and Sfp1. Unfortunately, bacterial overexpression of MBP-tagged Tpk1, Tpk2 and Tpk3 (the catalytic subunits of PKA) was quite challenging and we were unable to produce soluble protein. We therefore resorted to commercially available bovine PKA (bPKA, PKA catalytic subunit, Sigma-Aldrich 539576), which shows high homology to the yeast Tpk kinases [Toda et al. 1987]. Moreover 87% of bPKA substrates have been shown to also be Tpk1 substrates [Ptacek et al. 2005], and bPKA has been used to identify new Tpk substrates in budding yeast [Budovskaya et al. 2005__]. As we show in the revised manuscript, bovine PKA does phosphorylate Sfp1. Moreover, phosphorylation is reduced by 50% in the double S105A, S136A mutant (Fig.1F), and becomes undetectable in the 13A mutant__ (Supp Fig. 6). Together with the rapid response of Sfp1 localization to acute PKA inhibition which we had already reported, we believe that these results provide strong evidence that Sfp1 is a direct PKA substrate, and that the two phosphosites that we identified are functional.

      As the above in vivo experiments do not exclude S105/S136 phosphorylation by other kinases downstream of PKA, in order to claim the direct phosphorylation, the authors need in vitro PKA kinase assay. These biochemical experiments are not trivial, but I think absolutely necessary for this story.

      One cannot exclude that S105/S136 are also phosphorylated by other kinases of the AGC family (note that [Lempiäinen et al. 2009] has already excluded Sch9). However, as we hope to have shown, PKA indeed phosphorylates Sfp1. Examining if other kinases besides PKA and TORC1 target Sfp1 is a very interesting question that should be addressed in future work.

      The authors only look at the localization of Sfp1. To assess its functionality and so physiological impact, it would be informative to measure the mRNA level of target ribosomal genes in various Sfp1 mutants they created.

      As we described in our response to Reviewer 1 above, we did perform RNA-seq on WT and cells carrying a single copy of sfp113A. We observed a notable absence of differentially expressed ribosomal genes and ribosome-related categories in the GO analysis (Supp. Figs. 8, 9 and 10). Together with our observations on SCH9 deletion (Supp. Fig. 7), these results suggest that Sch9 can largely compensate for the loss of Sfp1 activity. On the other hand, the emergence of differentially expressed amino acid biosynthesis genes is a finding that merits further investigation, as it connects with previous observations made with Sch9 deletion mutants and the [ISP+] prion form of Sfp1 (cf. Discussion).

      In the experiments using analog-sensitive PKA (Fig 1D and E for example), they directly compare wildtype-PKA versus analog sensitive-PKA, or with 1-NM-PP1 versus without 1-NM-PP1. This makes interpretation difficult, particularly because 1-NM-PP1 itself has a significant impact even in the wild PKA strain. The real question is the difference between wild-type Sfp1 versus mutant Sfp1. In the current form, they compare Fig 1D versus 1E, these two do not look like a single, side-by-side experiment. They should compare wild-type Sfp1 versus mutant Sfp1 side-by-side.

      Figure 1D shows that 1-NM-PP1 has a transient off-target effect on Sfp1 localization in WT cells, which could also affect Sfp1 mutants. This observation prompted us to use wild-type PKA as a control when testing the effect of 1-NM-PP1 on sfp1PKA2D in cells carrying PKAas (Figure 1E). As Fig. 1E shows, the effect of 1-NM-PP1 on sfp1PKA2D localization in PKAas cells is quite similar to the off-target effect in cells carrying sfp1__PKA2D __and wild-type PKA. This behavior of sfp1__PKA2D __is clearly different from the response of wild-type Sfp1 to PKAas inhibition, which results in sustained delocalization. We have made the latter observation repeatedly, both in this study and our previously published work [Guerra et al. 2021].

      In Figure 3, the argument around the additive effects of PKA and TORC1 is confusing. The authors say they are additive referring Figure 3E, but say they are not additive referring Figure 3B. Which is true? In fact, Figure 3B appears to show an additive effect as well.

      We did not use the word "additive" in the text, because we find it difficult to interpret. Instead, we state that PKA and TORC1 appear to control Sfp1 phosphorylation independently of each other. PKA and TORC1 phosphorylation converges to the same response, affecting Sfp1 localization. It appears that loss of either kinase delocalizes Sfp1, while loss of both kinases may only have a small additional effect.

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    2. EMBOpress 08 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      The authors investigated how Sfp1, a transcription factor for ribosomal genes, integrates signals from TORC1 and PKA pathways. They did so by analyzing the nuclear localization of the GFP-tagged Sfp1 variants harboring unphosphorylatable or phosphomimetic mutations on either TORC1 target sites, putative PKA target sites, or a combination of both. This approach was complemented by examining the effect of pharmacological inhibition of either pathway on Sfp1 localization. The obtained results support that TORC1 and PKA independently promote nuclear localization of Snf1, provided that the putative PKA sites are genuinely PKA sites (see Major point). In course of their investigation, the authors made two novel findings about the regulatory mechanism of Sfp1 localization. First, they identified the 98-106aa region as a nuclear export signal (NES). Because this region overlaps with a putative PKA site, it is conceivable that PKA regulates Sfp1 localization via altering the functionality of NES. In addition, they found that the nuclear localization of Snf1 requires its C-terminal zinc fingers, although this domain appears to work independently from TORC1- and PKA-dependent regulations.

      Major points:

      1. There is no biochemical evidence presented that the putative PKA sites (S105 and S136) are genuinely phosphorylated by PKA. The fact that they match the PKA consensus motif, alone, does not guarantee this. In order to claim that they are looking at the effect of PKA by mutagenizing these residues, the authors have to demonstrate the PKA-dependency of S105 and S136 phosphorylation by, for example, mass spec experiments or western blotting with phospho-specific antibodies (Cell Signaling Technology #9624 for example). Also, does the band-shift caused by PKA inhibition (Fig 3C) is canceled by the S105A/S136A mutation?
      2. As the above in vivo experiments do not exclude S105/S136 phosphorylation by other kinases downstream of PKA, in order to claim the direct phosphorylation, the authors need in vitro PKA kinase assay. These biochemical experiments are not trivial, but I think absolutely necessary for this story.

      Minor points:

      1. The authors only look at the localization of Sfp1. To assess its functionality and so physiological impact, it would be informative to measure the mRNA level of target ribosomal genes in various Sfp1 mutants they created.
      2. In the experiments using analog-sensitive PKA (Fig 1D and E for example), they directly compare wildtype-PKA versus analog sensitive-PKA, or with 1-NM-PP1 versus without 1-NM-PP1. This makes interpretation difficult, particularly because 1-NM-PP1 itself has a significant impact even in the wild PKA strain. The real question is the difference between wild-type Sfp1 versus mutant Sfp1. In the current form, they compare Fig 1D versus 1E, these two do not look like a single, side-by-side experiment. They should compare wild-type Sfp1 versus mutant Sfp1 side-by-side.
      3. In Figure 3, the argument around the additive effects of PKA and TORC1 is confusing. The authors say they are additive referring Figure 3E, but say they are not additive referring Figure 3B. Which is true? In fact, Figure 3B appears to show an additive effect as well.

      Significance

      TORC1 and PKA are major pro-growth signaling pathways widely conserved in eukaryotes, that often converge on the same target proteins. How the information from the two pathways is integrated is an interesting question, which the authors directly and meticulously address here with yeast Sfp1 as an example. Provided that they can demonstrate that the putative PKA sites are the real ones (this is really important- TORC1 sites are already known, what is new here is PKA sites), their data and conclusion should be of interest to the signal transduction field.

      Their additional discovery of NES and the role of zinc fingers in Sfp1 localization should be of interest to those working on Sfp1, or transcriptional regulation of ribosomal genes in general.

      My area of expertise: yeast TOR

      PeerReviewed
    3. EMBOpress 08 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      In this paper, Vuillemenot and Milias-Argeitis investigate in budding yeast the role of Protein Kinase A (PKA) in regulating through phosphorylation the subcellular localization of the transcription factor Sfp1, known for controlling transcription of RP genes. Sfp1 is very well known for being regulated by another signaling pathway, centered on the kinase TORC1. Thus, regulation of Sfp1 by PKA raises the intriguing possibility of a downstream crosstalk between the two pathways. Indeed, the authors find that Sfp1 is regulated by PKA independently from TORC1. In the study, the authors employ mainly single-cell microscopy to monitor the nucleo/cytosolic localization of Sfp1 mutants, an experimental set-up they established in a previous paper, with some contribution by PhosTag bandshift assays.

      Major comments:

      The paper is overall convincing. However, a little more attention to data presentation and possibly the addition of at least another technique (see below) would greatly strengthen the findings. Summarizing my major concerns: - The absence of statistics catches immediately the eye. I am sure that the shown differences are statistically significant (thanks to the number of analyzed cells), but reporting the result of some statistical test would help the reader in identify the relevant data in a plot. This is somehow necessary considering that sometimes in the text something is deemed to be "significant" or "not significant", and I felt that I really needed that when looking at the blot in Fig. 3D. - Related to the previous point: for every N/C distribution analysis, a number of analyzed cells is reported. By the way it is written, it seems that the replication relies solely by the cells in that specific population, i.e.: each cell is treated as a replicate. At least I could not find if that is not the case in the legends or in the methods. I wonder what the results would be (and their significance) if each replicate would be a new assay on another population. - The scale of x axes in N/C ratio plots. Besides not being consistent throughout the figures, it originates from 1, visually enhancing the differences. - Related to the previous point: it is evident from the plots that the N/C ratio is always positive, even in the most deficient of the analyzed mutants. This implies that a relevant fraction of Sfp1 is still nuclear. I thus wonder what the impact of these mutations would be on the actual function of Sfp1. For this reason, I feel that qPCR evaluation of transcripts of Sfp1 target genes is particularly needed. Since lack of Sfp1 is known to yield some of the smallest cells possible, it would also be cool to have an estimate of the size of mutants where Sfp1 is less nuclear. These analyses could confer phenotypical relevance to the data, but would also help in assessing a currently unexplored possibility, that phosphorylation events by PKA influence Sfp1 function besides its localization, i.e.: the still somehow nuclear fraction is not as functional as wt Sfp1 in promoting transcription.

      Minor comments:

      Experimental issues and suggestions on data presentation are reported in the major comments section, since I felt those were major issues.

      Just a side remark: I found some typos here and there, and it would greatly help to report them if in the manuscript line numbers were included.

      Significance

      The finding that both PKA and TORC1 impinge on Sfp1, and therefore presumably on protein synthesis, is a valuable conceptual addition to the field of cell signaling. The audience potentially interested by the findings of the study include not only yeast cell biologists, but also computational biologists interested in modeling crucial cellular processes. One example is the regulation of cell size, where TORC1, PKA and Sfp1 are already know to play a role, but were potentially missing a crosstalk link.

      As requested by Review Commons, I specify that my expertise is on TORC1/AMPK/PKA pathways, on their crosstalk and their regulation by metabolic intermediates.

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    Nucleocytoplasmic transport senses mechanics independently of cell density in cell monolayers
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    1. EMBOpress 07 Jun 2024

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      Reply to the reviewers

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

      The nucleus is recognised as a core component of mechanotransduction with many mechano-sensitive proteins shuttling between the nucleus and cytoplasm in response to mechanical stimuli. In this work, Granero-Moya et al characterise a live florescent marker of nucleocytoplasmic transport (NCT) and how it responds to a variety of cues. This work follows on from the authors previous study (Andreu 2022) where they examined the response of passive and active NCT to mechanical signalling using a series of artificial constructs. One of these constructs (here named Sencyt) showed a differential localisation depending on substrate stiffness, accumulating in the nucleus on stiffer substrates (which the authors previously showed was due to differences in mechano-sensitivity of passive versus facilitated NCT). Here the authors use Sencyt as a tool to probe how different cues affect NCT and thus nuclear force-sensing in two different cell lines (one epithelial, one mesenchymal). *

      They have established a 3D image segmentation pipeline to measure both the nuclear/cytoplasmic ratio of Sencyt and 3D nuclear shape parameters. As a proof-of -principle, they show that hypoosmotic shock (which inflates the nucleus and would be expected to increase nuclear tension) and hyper-osmotic shock (which shrinks and deforms the nucleus) alter Sencyt nuclear-cytoplasmic ration as expected. They then show that inhibiting acto-myosin, which would be expected to block force transduction to the nucleus, reduces NCT, although interestingly this is without any changes to nuclear morphology. They then examine how cell density affects NCT and show that Sencyt localisation correlates only weakly with density but much more strongly with nuclear deformation (especially as measured by solidity). This is surprising considering that mechano-sensitive transcription factors such as YAP have been shown to exit the nucleus at high cell densities. Therefore, the authors directly compare Sencyt and Yap nucleo/cytoplasmic localisation and show that Sencyt behaves differently to YAP with YAP localisation correlating strongly with cell density. This reveals an added layer of complexity in YAP regulation beyond pure changes to NCT.* Major points *

      The data presented throughout this work are high quality and rigorous. The controls used are appropriate (including the use of a freely diffusing mCherry to illustrate the specificity of the Sencyt probe in osmotic shock experiments - figure S2). Experiments are properly replicated and the statistical analysis is appropriate. The data are beautifully presented in figures and the manuscript is well written and very clear. Overall this is a high quality work.

      We thank the reviewer for the positive assessment of the manuscript.

      * The discussion is careful and the conclusions are supported by the data. My only small concern is that the authors place too much emphasis on how this work is in 'multicellular systems' as opposed to their previous work in single cells (for example "Here, we demonstrate that mechanics also plays a role in multicellular systems, in response to both hypo and hyper-osmotic shocks, and to cell contractility. L212). Cell density is only controlled in figures 3 and 4 and in some of the earlier experiments, cells look quite sparse (eg Figure 2). It's also debatable how far a monolayer of cancer cells, which lack contact inhibition of growth, is a multicellular system. Furthermore, the authors don't specifically look at cell/cell adhesion or observe major differences between the epithelial or mesenchymal lines. For this reason, the authors should tone down this discussion before publication. *

      • *

      We agree with the reviewer that properly assessing cell-cell adhesion is important in the context of the work. To this end, we have stained for E-cadherin in both cell lines. As expected and as described previously, the results confirm that MCF7 cells do have clear cadherin-mediated cell-cell adhesions, with a cadherin staining localized specifically in cell-cell junctions. Also as expected, C26 cells show much lower cadherin expression, without a clear pattern. Further confirming this difference, MCF7 cells show clearly distinct actin organizations in their apical and basal sides, whereas C26 cells do not. Thus, we believe that the two cell models do represent a reasonable assessment of epithelial versus mesenchymal phenotypes, in a multicellular context. The data are presented in new supplementary fig. 1, and discussed in page 3 of the manuscript (first paragraph). We have also included a paragraph in the discussion to comment on the differences between cell types (page 7, 2nd paragraph).

      * Optional experimental suggestions: For me, the most compelling finding is that nuclear deformation has a greater correlation with NCT than cell density and that this is different from the behaviour of YAP. To cement the importance of nuclear deformation, the authors could induce deformation in single cells, for example by culture on very thin micropatterned lines and assess the localisation of Sencyt and YAP. It would also be interesting to assess the role of force transduction in this context or in different densities by removing actin, which affects NCT without inducing nuclear shape changes. These functional experiments would allow the authors to draw stronger conclusions about the role of nuclear shape and deformation but they aren't necessary for publication. *

      • *

      This is a very interesting suggestion. Following the reviewer's advice, we have now carried out experiments in which we have seeded cells on micropatterns of different sizes, and measured both sencyt and YAP ratios. In C26 cells, we have found as expected that increasing spreading leads to progressive nuclear deformation (as measured through nuclear solidity) and progressive increase in both sencyt and YAP ratios. Interestingly, cell spreading in MCF7 did not affect nuclear solidity, sencyt ratios, or YAP ratios. This further confirms the relationship between nuclear deformation and nucleocytoplasmic transport, and shows as well that different cell lines have different sensitivities. The lack of response of MCF7 cells is consistent with the lower sencyt response, and lower sencyt/nuclear shape correlation measured in fig. 4. It suggests that MCF7 cells may have mechanisms to shield the nucleus from deformation, something which we have reported in a different context (Kechagia et al., Nat. Mater. 2023). The new results are reported in new fig. 3, and supplementary fig. 8, and discussed in pages 5 (1st paragraph) and 6 (1st paragraph) of the manuscript results.

      • *

      Minor points

      * - I'd like to see better examples of 3D reconstructions of nuclei (ie fig 1C but bigger) in different conditions. This is especially important in figure 3 where it would be helpful to see examples of nuclei with high or low solidity. The differences in oblateness are clear to see from the images in 3a and 3f but solidity could be better illustrated. *

      • *

      We have now added 3D reconstructions as requested, which illustrate the nuclear shape changes that take place. This is shown in figs. 1, 4 (which corresponds to figure 3 in the previous version of the manuscript), s3, and s7.

      *

      • Where Sencyt index is plotted, it would be clearer to add labels to at least figure 1 which indicate whether it is more cytoplasmic or nuclear. *
      • *

      We have done this as requested in figure 1.

      * Reviewer #1 (Significance (Required)): *

      * In this work, Granero-Moya et al characterise a new tool for measuring NCT and show that it is mechanically regulated. Given the importance of NCT in mechano-transduction, this tool will be a great asset to the mechano-biology community and will likely be adopted by multiple groups in the future. The findings about the effects of cell density on NCT and differences from YAP are interesting but could be further fleshed out. This work is likely to be of greatest interest to a specialised audience working in the fields of mechano-biology and nuclear transport. *

      • *

      We thank the reviewer for the positive assessment.

      * *

      • *

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

      * The study conducted by Granero Moya and colleagues describes the application of a synthetic protein which is observed to enter the nucleus in response to mechanical strains, rather than being influenced by cell density. However, the novelty of this work is minimal since the conceptual framework and the utilization of this identical or similar tool have been previously reported by the same team in earlier publications. *

      • *

      We respectfully disagree with the assessment of the reviewer. Please see below for a detailed response regarding novelty.

      • *

      *In their experiments, they employ this GFP-based sensor, referred to as Sencyt, in cells subjected to osmotic shocks. These shocks are highly stressful and impact a range of cellular processes, including stress response pathways MAPK and others; Osmoregulatory pathways; cell cycle regulations, autophagy and death pathway; ion channel regulations and others. The second findings are on cells treated with a combo of drugs affecting the actin cytoskeleton. The justification for using a combination of two specific drugs remains unclear, as the study does not adequately explain the rationale behind this choice. Additionally, there is a lack of information regarding the full range of targets these drugs affect. This raises questions about the comprehensiveness and applicability of the findings, as understanding the complete scope of the drugs' targets is crucial for interpreting the results within a minimal frame of physiological context. *

      • *

      The two drugs used are paranitroblebbistatin (a photostable version of blebbistatin) and Ck666. We apologize for not explaining in more detail the action of these drugs, both of which have been characterized and used extensively in the literature. Paranitroblebbistatin binds to myosin, preventing its ATPase activity and therefore impairing actomyosin contractility (https://doi.org/10.1002/anie.201403540). It acts on different myosin isoforms, including non-muscle myosin II, the main type of myosin responsible for actomyosin contractility in non-muscle cells. CK666 binds to and inhibits arp2/3, a protein responsible for nucleating branched actin (https://doi.org/10.1016/j.chembiol.2013.03.019). This impairs lamellipodial formation and therefore cell spreading (see for instance https://doi.org/10.1371/journal.pone.0100943).

      The rationale for using both drugs in combination was explained in page 4 of the manuscript. In our previous work, we determined that myosin inhibition with blebbistatin is not sufficient to inhibit nuclear mechanotransduction. Indeed, in an epithelial context, we observed that due to reduced contractility, blebbistatin-treated epithelial cells in fact spread more on their substrate. This leads to more deformed (flattened) nuclei, leading to the counterintuitive result that YAP nuclear localization increases rather than decreases. If cell spreading is impaired by interfering with branched actin nucleation, then this spreading is prevented, and the combination of drugs leads to reduced nuclear deformation, and reduced YAP nuclear localization (see supplementary fig. 7 in Kechagia et al, Nat. Mater. 2023, https://doi.org/10.1038/s41563-023-01657-3). Similar results had been published previously by the group of Clare Waterman (https://doi.org/10.1074/jbc.M115.708313).

      Thus, the combination of drugs was designed to ensure that we were impairing nuclear mechanotransduction. Of course, we agree with the reviewer that all perturbations have potential side effects. Osmotic shocks will affect a range of cellular processes (as mentioned in the discussion of the manuscript), and any drug treatment can potentially have off-target effects. However, the fact that two orthogonal perturbations with different potential side effects (osmotic shocks versus actomyosin-targeting drugs) lead to the same effects in sencyt strongly suggests that the effect is mediated by mechanics, and not other factors. To reinforce this, we have now added an additional mechanical manipulation: seeding cells on micropatterned islands of different sizes. As spreading increases, cells are known to increase actomyosin contractility, and nuclear deformation (https://doi.org/10.1529/biophysj.107.116863, https://doi.org/10.1073/pnas.0235407100, https://www.nature.com/articles/ncomms1668, https://doi.org/10.1073/pnas.1902035116). As expected, nuclear solidity, sencyt ratios, and Yap ratios all increased with cell spreading. Interestingly, this occurred only for C26 and not MCF7 cells, where no changes were measured in solidity, sencyt, or YAP. The lack of response of MCF7 cells is consistent with the lower sencyt response, and lower sencyt/nuclear shape correlation measured in fig. 4. It suggests that MCF7 cells may have mechanisms to shield the nucleus from deformation, something which we have reported in a different context (Kechagia et al., Nat. Mater. 2023).

      The new results are shown in figs. 3 and s8. We have also expanded the explanation of drug treatments in page 4 (3rd paragraph).

      * The novelty is on the specificity of this synthetic fusion protein for these manipulations and not on cell density. Yet, the reasons behind this selective response remain unexplained, potentially attributable to the unique characteristics or sensitivity thresholds of their synthetic probe. As comparison, YAP localization and this is sensitive to both inputs, but this is also already published (fig4). The focus is anyway on Sencyt for which they offer simple observations and quantifications. *

      • *

      The main novelty of the work lies in the characterization of the role of nucleocytoplasmic transport in mechanotransduction, in the context of multicellular systems. We and others had shown that nucleocytoplasmic transport responds to mechanical force in the context of single cells (see for instance Andreu et al. 2022 from our group, but also https://doi.org/10.1126/science.abd9776 from the Martin Beck group). However, to what extent this applies to multicellular systems was unknown. It is true that in multicellular systems, the response of YAP and other mechanosensitive transcription factors has been characterized (such as in our Elosegui-Artola 2017 paper, mostly done at the single cell level but including one figure panel on epithelial cell monolayers). The reviewer argues here and in the consultation comments with other reviewers (see below) that this demonstrated the role of nucleocytoplasmic transport in multicellular systems. However, we respectfully disagree. As also noted by reviewer 3 in the consultation, the response of YAP, and of any transcription factor, may include effects on nucleocytoplasmic transport, but will also likely include effects caused by the complex biochemical signalling pathways that regulate them. Disentangling such effects requires a sensor that only responds to nucleocytoplasmic transport, and this is precisely what Sencyt provides.

      The reviewer also states that our manuscript does not explain why sencyt responds to mechanics and not cell density. We disagree: sencyt responds to mechanics for the reasons explained in our previous work (Andreu et al., Nat. Cell Biol. 2022), and there is no reason to expect a specific response to cell density. In this regard, we don't think there are any sensitivity thresholds to detect cell density, as the probe is not designed to sense this parameter in the first place. The fact that YAP responds to both mechanics and cell density shows that the response to density cannot be merely explained by mechanics, and is rather due to signalling through other means. Of course, we agree that we do not explain the mechanism by which YAP senses cell density, but we think this lies clearly out of the scope of our manuscript.

      In terms of novelty, our work also characterizes a tool to assess nucleocytoplasmic transport live in cells. We agree with the reviewer that the specific construct had been reported in our previous paper, but it had not been characterized in detail. This is done here, enabling its use by the community as a tool to measure nucleocytoplasmic transport in any context, be it related to mechanics or not.

      • *

      When reviewing the figures presented, I find it challenging to detected marked differences, despite their quantitative data suggesting otherwise.

      • *

      We assume here that the reviewer refers to differences in sencyt nuclear localization, that is, the sencyt index. We have now checked the example images showing changes in sencyt index, in figures 1 and 2. In figure 1, the example cells under hypo-osmotic shocks increase their sencyt index from 1.2 to 1.45 (C26). In figure 1, the example cells under hyper-osmotic shocks decrease their sencyt index from 0.9 to 0.3 (MCF7) and from 1.4 to 0.5 (C26). In figure 2, the example cells increase their sencyt index upon drug washout from 0.2 to 1.4 (MCF7) and from 0 to 0.9 (C26). Of course, these individual values don't reflect exactly average values, but they do reflect the reported average trends and their magnitudes faithfully. Here we note that even though sencyt changes with the different treatments, it is always more nuclear than cytosolic (sencyt index >0, as it has an NLS). Thus, to the naked eye, sencyt always seems to show a "bright" nucleus, and it is hard to intuitively see changes in its localization. Further, we also note that osmotic shocks lead to overall changes in fluorescence levels due to volume changes (as GFP molecules get diluted or concentrated in hypo or hyper osmotic shocks, respectively). This does not affect ratiometric quantifications as assessed with our mcherry control, but means that changes in ratios are hard to see by eye. To help in this visualization, we have now changed the images from green to grayscale, which is better perceived by the human eye. We have also specified the issue of fluorescence intensity changes in the legend of the figure.

      In addition to this, we have seen that there is indeed a case in which examples were not following average trends. In the case of hypo-osmotic shocks in figure 1, example MCF7 cells were barely changing their sencyt index with treatment. We apologize for choosing this non-representative image for the figure, we have now changed the figure to show more representative cells.

      • Furthermore, the study attempts to correlate the behavior of Sencyt with the nuclear geometric parameter of solidity, a connection that seems to lack a clear basis in cell biology and could potentially lead to misconceptions. *
      • *

      Mechanical effects on nucleocytoplasmic transport are mediated by mechanical tension application to nuclear pores, which are embedded in the nuclear membrane (nuclear envelope). Whereas nuclear envelope tension is very challenging to measure directly, it can be indirectly related to nuclear shape. Indeed, a tense membrane will tend to even out membrane irregularities and appear rounded, whereas a membrane under low tension will tend to show wrinkles. Nuclear solidity is a geometric parameter that compares actual nuclear volume to the volume of the convex hull (intuitively, the volume of the smallest wrinkle-free object containing all of the nucleus). Thus, it is the geometric parameter that best reflects the presence of wrinkles, folds or irregularities, and as such the one that should best correlate to membrane tension. Of course, this correlation is not perfect, and there could be many situations in which changes in membrane tension may not directly affect nuclear solidity. But we do believe that solidity is the geometrical parameter that should best reflect membrane tension, and this is why we focus on it. Consistent with our hypothesis, solidity is the geometrical parameter that best correlates with sencyt. To further clarify this, we now explain this rationale in detail in page 4 of the manuscript (1st paragraph).

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

      * In sum, I think the MS is of interest for a very specialistic audience. There are no clear interpretations. The work is done in one or two cellular model systems in vitro; and the general significance of these observations is of very limited impact and no novelty. *

      We strongly disagree. The study is done on two cellular models, one with epithelial and the other with mesenchymal phenotype, and thus highly relevant for multicellular systems. Following suggestions by reviewers 1 and 2, we have now characterized the epithelial/mesenchymal behaviour of the cell types in detail (see supp. fig. 1). The results are novel in that they demonstrate the role of nucleocytoplasmic transport in multicellular systems, something which as argued above had not been done before. The difference with YAP, and the disentanglement between transport and signalling, is also novel. Finally, we believe the manuscript will be impactful because of this novelty, but also because of the availability of sencyt as a tool for the community. In fact, since placing this manuscript in biorxiv, we have received many requests (directly and through addgene) to share sencyt, which is currently being used in several labs across the world.

      • *

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

      • *

      In this very well-written manuscript, Pere Roca-Cusachs and colleagues investigated the response of nucleocytoplasmic transport (NCT) to mechanical stress and tested whether this response is similar in epithelial and mesenchymal cells using a combination of quantitative approaches. This study builds upon their earlier findings, which elegantly demonstrated that NCT is sensitive to mechanical forces transmitted to the nuclear membrane. Using a similar approach to their recent work, they quantitatively analyzed NCT and compared the two cell types using various treatments that impact nuclear membrane tension. The study is straightforward and experimentally sound, with an adequate number of replicates and independent experiments. While one might consider the limitations given their previous work, none have demonstrated that NCT is mechanosensitive in epithelial cells. Additionally, they provide a simple approach to measure NCT, which should be of interest in the field. However, it is unclear how the authors defined the epithelial phenotype in this work and whether they solely based this characterization on the tissue/cell's origin. Epithelia can be defined ultrastructurally with reference to their apico-basal polarity and specific cell-cell junctions (Alberts et al., 1994; Davies and Garrods, 1997). Changing cell density should affect cell/cell adhesion, but the authors provide no evidence that the cells tested in the study are attached to their neighbors on all sides and form an epithelium. While I recognize that the objective of this study is not to mimic the in vivo behavior of epithelial tissue, the authors should at least ensure that cells form a monolayer by quantitatively assessing cell-cell junctions (or they should adjust their conclusions adequately). This control is specifically important for Figure 3 and 4, whose objective is to test the impact of cell/cell contacts. But it would also be important to provide this essential control for Figure 1 and 2, as it is unclear from the images provided if MCF7 cells are forming an epithelium (and form cell/cell junctions).

      • *

      We thank the reviewer for the positive assessment of our work. We fully agree with the reviewer that properly assessing cell-cell adhesion is important in the context of the work. To this end, we have stained for E-cadherin in both cell lines. As expected and as described previously, the results confirm that MCF7 cells do have clear cadherin-mediated cell-cell adhesions, with a cadherin staining localized specifically in cell-cell junctions. Also as expected, C26 cells show much lower cadherin expression, without a clear pattern. Further confirming this difference, MCF7 cells (but not C26 cells) show a clear apico-basal polarization, with distinct actin organizations in their apical and basal sides. Thus, we believe that the two cell models do represent a reasonable assessment of epithelial versus mesenchymal phenotypes, in a multicellular context. The data are presented in new supplementary fig. 1. We have also included a paragraph in the discussion to comment on the differences between cell types (page 7, 2nd paragraph).

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

      • *

      The mechanosensitivity of NCT is an important question central to many aspects of cell biology. One might consider the impact of the proposed work limited, given their previous research. However, none have demonstrated that NCT is mechanosensitive in epithelial cells, making it a crucial question that needs to be addressed. Additionally, they provide a simple approach to measure NCT, which should be of interest to a broad audience.

      We thank again the reviewer for this positive assessment.

      • *

      *Referees cross-commenting *

      * Here comments from all 3 reviewers are reported *

      * Reviewer 1: *

      * I disagree with R2's comment that there is 'no novelty' here. Although this work is going to be of greater interest to a specialised rather than general audience, it characterises in depth a simple tool to measure NCT which will be useful for mechanobiology field. Also, using 'two cellular model systems in vitro' is very standard in the field when assessing subcellular processes like NCT. Using this approach in vivo would be very interesting but challenging and would be an entirely different study . *

      • *

      *I agree with R2's comments that the authors should better justify their combination of two actin inhibitors and R3s point on better assessing cell/cell junctions. *

      • *

      We thank the reviewer for these comments. Both issues have been addressed, as described in the response to reviewers above.

      * Reviewer 2 *

      * About Reviewer 3's comments, I believe it's a stretch to highlight the strength and novelty based on "NCT's mechanosensitivity in epithelial cells has not been demonstrated,". There are thousands of papers on the Hippo pathway, that is known to be mechanosensitive, on the regulation of YAP, that enters in the nucleus in Hippo inhibited conditions and exits to the cytoplasm in Hippo induced cells, including downstream of mechanical signals. The phenomenon of nuclear-cytoplasmic shuttling being a common event from neurons to endothelial and multiple types of epithelial, immune, and fibroblast cells is already established through NCT of this and other endogenous proteins. This is simply an accepted fact. Then, The Nature cell Biology 2022 was offering a very general claim. No warning that conclusions could have been cell type specific. In the Artola 2017 Cell paper they also showed NCT in mammary epithelial cells. We should definitively conclude that NCT's mechanosensitivity in epithelial cells has been well demonstrated. *

      • *

      We disagree with this assessment, for the same reasons also exposed by reviewer 3 below. Previous work on YAP and other transcription factors cannot be seen as a demonstration of the role of nucleocytoplasmic transport per se. The localization of any transcription factor is highly regulated by complex signalling pathways, and can be affected by many factors. One of them is nucleocytoplasmic transport, but signalling events (for instance through phosphorylation) could change localization by promoting binding to cytosolic or nuclear binding partners, by promoting protein degradation, by masking nuclear localization signals, and others. To isolate the role of nucleocytoplasmic transport, a probe sensitive only to this factor should be designed. This is exactly what sencyt provides. In fact, this has allowed us to answer an important open question: is the sensitivity of YAP to cell density mediated by mechanics and nucleocytoplasmic transport, or is it mediated by some other factor? Our results suggest that some other factor, likely mediated by the Hippo pathway and not necessarily mechanotransduction, explains this sensing of cell density. This is a novel finding, which was not provided in either our Elosegui-Artola 2017 paper or our Andreu 2022 paper.

      * About Reviewer 1: I find it challenging to grasp the point made in the comment. On novelty, in their previous study in NBC 2022 Syncet was already shown to undergo NCT. The reviewer states that the study presents "a simple tool to measure nuclear-cytoplasmic transport (NCT) beneficial for the mechanobiology field, and evidence that this demonstrates a novel layer of regulation in hippo signaling (also because this is observational and not a mechanistic study). The tool in question is far from simple. Its application requires transfection into cell cultures, conducting live imaging, etc. If one aims to measure NCT of endogenous proteins, straightforward immunofluorescence or live imaging of endogenous proteins (like GFP-tagged YAP, Twist, Smads, etc.) using the same experimental setup should suffice to demonstrate relevance, without necessitating any additional experiments. What then, is the unique benefit of this proposed tool? Given it's an artificial construct combining NLS-GFP with a bacterial protein, questions arise about the effects of the forced nuclear localization signal (NLS) or the bacterial component. It is an empirical artificial construct and there is no mechanism to explain its behavior.The comparison of Syncet with YAP seems to me questionable and of limited utility. *

      As also noted by reviewer 3 below, the use of genetically encoded fluorescent sensors that require transfection is by now absolutely standard in biology, and cannot be considered to be "far from simple". And as stated above, imaging of endogenous transcription factors (which also requires transfection if it is done live) does not isolate the role of nucleocytoplasmic transport. We also disagree that "there is no mechanism to explain its behaviour". Sencyt was developed in our previous andreu et al 2022 paper, where the mechanism is explained in detail.

      • *

      *It's unsurprising that an artificial construct only mirrors some aspects of what is considered a genuine mechanosensitive protein. The utility of a synthetic tool lies in its ability to replicate actual phenomena, not in what it fails to do. In comparison to their NBC 2022 study, this manuscript focuses on what their reporter fails to detect. *

      We disagree that a synthetic tool is only useful if it replicates the behaviour of endogenous proteins. A synthetic tool, precisely due to its engineered, artificial nature, can be made to respond only to specific factors (in this case, nucleocytoplasmic transport). This can then be used to disentangle the role of such specific factors, as done here.

      The osmotic shock was the assay in their 2017 Cell paper. Here they demonstrate that a combination of Blebbistatin+CK (an unclear choice of drugs) is ineffective, as is cell density. Are there other specific peculiarities associated with this construct?

      Here, we note that our osmotic shock experiments in our 2017 paper were done for YAP (not nucleocytoplasmic transport in general). Regarding the choice of drugs, please refer to our answer to the reviewer comments above for a full explanation. Also, we want to clarify that this combination is not ineffective, as it leads to clear changes in sencyt. * *

      * My other concern is on the minor quantitative changes reported, which seem inconsistent with the provided representative images, where significant differences are difficult to appreciate. For instance, the claim that the transfected sensor differs from an endogenous NCT protein, YAP, after cell density treatment, is hard to detect in their images. In Figure 4, comparing YAP and Syncet in C26 cells, YAP appears uniformly nuclear at high cell density, potentially more nuclear than the synthetic sensor, which is not coherent with their claim.*

      • *

      Regarding the concern of the minor changes seen in images, please refer to our full response to the reviewer comments above. Regarding the comparison between sencyt and YAP, we want to clarify that in our manuscript we do not compare the absolute values of nuclear localization between YAP and sencyt. As the reviewer notes, these are two different proteins, so which one is more nuclear does not really provide useful information. So whether YAP is more or less nuclear than sencyt is unrelated to (not incoherent with) our claim. What we state in figure 4 is that YAP responds to cell density, whereas sencyt does not. This is clear from the quantifications and also from the images.

      • *
      • From the Hippo perspective, there is really an unusual amount of nuclear YAP left in their cells. This should be almost completely cytoplasmic from prior contact inhibition studies in the Hippo field. Syncet could be simply less sensitive than YAP in these borderline conditions. Although there's a more noticeable cytoplasmic noise in dense cells with YAP compared to Syncet, this could be attributed to several factors, including differences in protein degradation rates, which I suspect to be quicker for a synthetic protein. From a technical perspective it is complex to get strong conclusions after comparing something so unrelated with each other. One is a live GFP detection and the other is a staining by immunofluorescence. the nature of the background is also different and so conclusions from comparisons between unrelated systems is not justified. *
      • *

      In conditions of high density, average YAP ratios are close to one (zero in logarithmic scale, as reported in the figures) for MCF10A cells, so there is no nuclear localization. This is similar to what we and others have previously reported in similar conditions (Elosegui Artola et al 2017, Kechagia et al. 2023, for example). In C26 cells, YAP levels at high density are a bit higher. This is likely due to their mesenchymal nature, and therefore diminished cell-cell contact inhibition (as assessed in detail in this revision). This in fact further suggests that the response of YAP to cell-cell contacts is different from a mere mechanical factor, supporting our hypothesis. Regarding the issue of noise, background noise is removed from quantifications, and potential noise coming from non-specificities or autofluorescence is also cancelled by the fact that we compute fluorescence ratios between nucleus and cytoplasm (and not absolute values). Thus, we don't think noise is an issue. Further, we note again that we do not directly compare values between sencyt and yap.

      * This suggests caution on what is heralded as the main claim here put forward. *

      * Reviewer 1: *

      *I do have some sympathy with R2s comments in the consultation. I agree that showing that NCT is mechanosensitive in an epithelium is not new. I also agree that sometimes it is difficult to see the quantitative differences by eye. This second point could be addressed by including more details of the segmentation and analysis in the supplemental material (along with some example images). *

      • *

      We thank the reviewer for the suggestions. Regarding the novelty, please see above for a detailed discussion, and also the comments of reviewer 3 below (previous work studied not NCT but transcription factors, affected by many parameters). Regarding quantitative differences, we have now addressed this issue by showing images in grayscale rather than green, and also by replacing one example cell in figure 1 which indeed did not reflect the average measured trends. We now also show examples of 3D rendered images of the nuclei in different conditions. We have also gone through the methods and clarified in detail how ratios are calculated, the segmentation procedure is also explained in detail.

      * Regarding novelty, I would be interested to know if R2 thinks that there are experiments that the authors could do to improve the work. Or do they need to simply tone down their claims? It's perfectly acceptable to publish a well characterised tool with a series of observations and it's beneficial to the community to do so.*

      • Reviewer 3 *

      * Thanks to Reviewers #1 and #2 for using this consultation option; I truly appreciate their feedback on my comments and find it extremely valuable. I agree with Reviewer #1 that the method proposed here is relatively simple. Transfecting cells and conducting live fluorescent imaging can hardly be considered difficult. I believe the construct used/designed by the authors is the main advantage as it provides a specific way to quantitatively assess NCT and not limit the analysis to a single nuclear protein (such as YAP). Reviewer #2 suggests using immunofluorescence staining of YAP or live imaging of fusion fluorescent protein (following transfection) to analyze NCT, but this approach would yield a readout not only based on NCT but also on the many other interacting partners/mechanisms that regulate the candidate localization, resulting in an unspecific readout (and similar transfection/live imaging set-up). *

      • *

      We thank the reviewer for this comment, we fully agree and have elaborated on this in our responses above.

      * Regarding the impact of the study, I agree that it is certainly not as impactful as previous publications on this topic. Although I find reviewer#2 argument on Yap irrelevant, as YAP is not the main focus of this paper. Some experiments have been done with cells of epithelial origin, but NCT mechanosensitivity has not been clearly tested in epithelial monolayer, which is the main claim of the proposed study here. The 2017 Cell paper focused on YAP transport into the nucleus (and not NCT in general) and they showed a correlation between YAP nuclear localization and traction force in MCF10A. I am not sure if one would say that "NCT mechanosensitivity has been well demonstrated in epithelial cells" based on this single panel. The impact of the proposed study is certainly not outstanding but offering a thorough analysis in epithelial cells (as monolayers and not as individual cells) and presenting a well-defined experimental approach should be of interest in the field. I agree with comments from reviewer#2 that some reported effects in graph are unclear on main images. More experimental details should hopefully clarify this aspect.*

      • *

      We fully agree with the reviewer. Regarding quantitative differences, we have now addressed this issue by showing images in grayscale rather than green, and also by replacing one example cell in figure 1 which indeed did not reflect the average measured trends.

      PeerReviewed
    2. EMBOpress 07 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      In this very well-written manuscript, Pere Rochas-Cusachs and colleagues investigated the response of nucleocytoplasmic transport (NCT) to mechanical stress and tested whether this response is similar in epithelial and mesenchymal cells using a combination of quantitative approaches. This study builds upon their earlier findings, which elegantly demonstrated that NCT is sensitive to mechanical forces transmitted to the nuclear membrane. Using a similar approach to their recent work, they quantitatively analyzed NCT and compared the two cell types using various treatments that impact nuclear membrane tension. The study is straightforward and experimentally sound, with an adequate number of replicates and independent experiments. While one might consider the limitations given their previous work, none have demonstrated that NCT is mechanosensitive in epithelial cells. Additionally, they provide a simple approach to measure NCT, which should be of interest in the field. However, it is unclear how the authors defined the epithelial phenotype in this work and whether they solely based this characterization on the tissue/cell's origin. Epithelia can be defined ultrastructurally with reference to their apico-basal polarity and specific cell-cell junctions (Alberts et al., 1994; Davies and Garrods, 1997). Changing cell density should affect cell/cell adhesion, but the authors provide no evidence that the cells tested in the study are attached to their neighbors on all sides and form an epithelium. While I recognize that the objective of this study is not to mimic the in vivo behavior of epithelial tissue, the authors should at least ensure that cells form a monolayer by quantitatively assessing cell-cell junctions (or they should adjust their conclusions adequately). This control is specifically important for Figure 3 and 4, whose objective is to test the impact of cell/cell contacts. But it would also be important to provide this essential control for Figure 1 and 2, as it is unclear from the images provided if MCF7 cells are forming an epithelium (and form cell/cell junctions).

      Significance

      The mechanosensitivity of NCT is an important question central to many aspects of cell biology. One might consider the impact of the proposed work limited, given their previous research. However, none have demonstrated that NCT is mechanosensitive in epithelial cells, making it a crucial question that needs to be addressed. Additionally, they provide a simple approach to measure NCT, which should be of interest to a broad audience.

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    3. EMBOpress 07 Jun 2024

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      Referee #2

      Evidence, reproducibility and clarity

      The study conducted by Granero Moya and colleagues describes the application of a synthetic protein which is observed to enter the nucleus in response to mechanical strains, rather than being influenced by cell density. However, the novelty of this work is minimal since the conceptual framework and the utilization of this identical or similar tool have been previously reported by the same team in earlier publications. In their experiments, they employ this GFP-based sensor, referred to as Sencyt, in cells subjected to osmotic shocks. These shocks are highly stressful and impact a range of cellular processes, including stress response pathways MAPK and others; Osmoregulatory pathways; cell cycle regulations, autophagy and death pathway; ion channel regulations and others. The second findings are on cells treated with a combo of drugs affecting the actin cytoskeleton. The justification for using a combination of two specific drugs remains unclear, as the study does not adequately explain the rationale behind this choice. Additionally, there is a lack of information regarding the full range of targets these drugs affect. This raises questions about the comprehensiveness and applicability of the findings, as understanding the complete scope of the drugs' targets is crucial for interpreting the results within a minimal frame of physiological context.

      The novelty is on the specificity of this synthetic fusion protein for these manipulations and not on cell density. Yet, the reasons behind this selective response remain unexplained, potentially attributable to the unique characteristics or sensitivity thresholds of their synthetic probe. As comparison, YAP localization and this is sensitive to both inputs, but this is also already published (fig4). The focus is anyway on Sencyt for which they offer simple observations and quantifications. When reviewing the figures presented, I find it challenging to detected marked differences, despite their quantitative data suggesting otherwise. Furthermore, the study attempts to correlate the behavior of Sencyt with the nuclear geometric parameter of solidity, a connection that seems to lack a clear basis in cell biology and could potentially lead to misconceptions.

      Significance

      In sum, I think the MS is of interest for a very specialistic audience. There are no clear interpretations. The work is done in one or two cellular model systems in vitro; and the general significance of these observations is of very limited impact and no novelty.

      PeerReviewed
    4. EMBOpress 07 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      The nucleus is recognised as a core component of mechanotransduction with many mechano-sensitive proteins shuttling between the nucleus and cytoplasm in response to mechanical stimuli. In this work, Granero-Moya et al characterise a live florescent marker of nucleocytoplasmic transport (NCT) and how it responds to a variety of cues. This work follows on from the authors previous study (Andreu 2022) where they examined the response of passive and active NCT to mechanical signalling using a series of artificial constructs. One of these constructs (here named Sencyt) showed a differential localisation depending on substrate stiffness, accumulating in the nucleus on stiffer substrates (which the authors previously showed was due to differences in mechano-sensitivity of passive versus facilitated NCT). Here the authors use Sencyt as a tool to probe how different cues affect NCT and thus nuclear force-sensing in two different cell lines (one epithelial, one mesenchymal).

      They have established a 3D image segmentation pipeline to measure both the nuclear/cytoplasmic ration of Sencyt and 3D nuclear shape parameters. As a proof-of -principle, they show that hypoosmotic shock (which inflates the nucleus and would be expected to increase nuclear tension) and hyper-osmotic shock (which shrinks and deforms the nucleus) alter Sencyt nuclear-cytoplasmic ration as expected. They then show that inhibiting acto-myosin, which would be expected to block force transduction to the nucleus, reduces NCT, although interestingly this is without any changes to nuclear morphology. They then examine how cell density affects NCT and show that Sencyt localisation correlates only weakly with density but much more strongly with nuclear deformation (especially as measured by solidity). This is surprising considering that mechano-sensitive transcription factors such as YAP have been shown to exit the nucleus at high cell densities. Therefore, the authors directly compare Sencyt and Yap nucleo/cytoplasmic localisation and show that Sencyt behaves differently to YAP with YAP localisation correlating strongly with cell density. This reveals an added layer of complexity in YAP regulation beyond pure changes to NCT.

      Major points

      The data presented throughout this work are high quality and rigorous. The controls used are appropriate (including the use of a freely diffusing mCherry to illustrate the specificity of the Sencyt probe in osmotic shock experiments - figure S2). Experiments are properly replicated and the statistical analysis is appropriate. The data are beautifully presented in figures and the manuscript is well written and very clear. Overall this is a high quality work.

      The discussion is careful and the conclusions are supported by the data. My only small concern is that the authors place too much emphasis on how this work is in 'multicellular systems' as opposed to their previous work in single cells (for example "Here, we demonstrate that mechanics also plays a role in multicellular systems, in response to both hypo and hyper-osmotic shocks, and to cell contractility. L212). Cell density is only controlled in figures 3 and 4 and in some of the earlier experiments, cells look quite sparse (eg Figure 2). It's also debatable how far a monolayer of cancer cells, which lack contact inhibition of growth, is a multicellular system. Furthermore, the authors don't specifically look at cell/cell adhesion or observe major differences between the epithelial or mesenchymal lines. For this reason, the authors should tone down this discussion before publication.

      Optional experimental suggestions: For me, the most compelling finding is that nuclear deformation has a greater correlation with NCT than cell density and that this is different from the behaviour of YAP. To cement the importance of nuclear deformation, the authors could induce deformation in single cells, for example by culture on very thin micropatterned lines and assess the localisation of Sencyt and YAP. It would also be interesting to assess the role of force transduction in this context or in different densities by removing actin, which affects NCT without inducing nuclear shape changes. These functional experiments would allow the authors to draw stronger conclusions about the role of nuclear shape and deformation but they aren't necessary for publication.

      Minor points

      • I'd like to see better examples of 3D reconstructions of nuclei (ie fig 1C but bigger) in different conditions. This is especially important in figure 3 where it would be helpful to see examples of nuclei with high or low solidity. The differences in oblateness are clear to see from the images in 3a and 3f but solidity could be better illustrated.
      • Where Sencyt index is plotted, it would be clearer to add labels to at least figure 1 indicting which indicate whether it is more cytoplasmic or nuclear.

      Referees cross-commenting

      Here comments from all 3 reviewers are reported

      Reviewer 1:

      I disagree with R2's comment that there is 'no novelty' here. Although this work is going to be of greater interest to a specialised rather than general audience, it characterises in depth a simple tool to measure NCT which will be useful for mechanobiology field. Also, using 'two cellular model systems in vitro' is very standard in the field when assessing subcellular processes like NCT. Using this approach in vivo would be very interesting but challenging and would be an entirely different study .

      I agree with R2's comments that the authors should better justify their combination of two actin inhibitors and R3s point on better assessing cell/cell junctions.

      Reviewer 2

      About Reviewer 3's comments, I believe it's a stretch to highlight the strength and novelty based on "NCT's mechanosensitivity in epithelial cells has not been demonstrated,". There are thousands of papers on the Hippo pathway, that is known to be mechanosensitive, on the regulation of YAP, that enters in the nucleus in Hippo inhibited conditions and exits to the cytoplasm in Hippo induced cells, including downstream of mechanical signals. The phenomenon of nuclear-cytoplasmic shuttling being a common event from neurons to endothelial and multiple types of epithelial, immune, and fibroblast cells is already established through NCT of this and other endogenous proteins. This is simply an accepted fact. Then, The Nature cell Biology 2022 was offering a very general claim. No warning that conclusions could have been cell type specific. In the Artola 2017 Cell paper they also showed NCT in mammary epithelial cells. We should definitively conclude that NCT's mechanosensitivity in epithelial cells has been well demonstrated.

      About Reviewer 1: I find it challenging to grasp the point made in the comment. On novelty, in their previous study in NBC 2022 Syncet was already shown to undergo NCT. The reviewer states that the study presents "a simple tool to measure nuclear-cytoplasmic transport (NCT) beneficial for the mechanobiology field, and evidence that this demonstrates a novel layer of regulation in hippo signaling (also because this is observational and not a mechanistic study). The tool in question is far from simple. Its application requires transfection into cell cultures, conducting live imaging, etc. If one aims to measure NCT of endogenous proteins, straightforward immunofluorescence or live imaging of endogenous proteins (like GFP-tagged YAP, Twist, Smads, etc.) using the same experimental setup should suffice to demonstrate relevance, without necessitating any additional experiments. What then, is the unique benefit of this proposed tool? Given it's an artificial construct combining NLS-GFP with a bacterial protein, questions arise about the effects of the forced nuclear localization signal (NLS) or the bacterial component. It is an empirical artificial construct and there is no mechanism to explain its behavior. The comparison of Syncet with YAP seems to me questionable and of limited utility. It's unsurprising that an artificial construct only mirrors some aspects of what is considered a genuine mechanosensitive protein. The utility of a synthetic tool lies in its ability to replicate actual phenomena, not in what it fails to do. In comparison to their NBC 2022 study, this manuscript focuses on what their reporter fails to detect. The osmotic shock was the assay in their 2017 Cell paper. Here they demonstrate that a combination of Blebbistatin+CK (an unclear choice of drugs) is ineffective, as is cell density. Are there other specific peculiarities associated with this construct?

      My other concern is on the minor quantitative changes reported, which seem inconsistent with the provided representative images, where significant differences are difficult to appreciate. For instance, the claim that the transfected sensor differs from an endogenous NCT protein, YAP, after cell density treatment, is hard to detect in their images. In Figure 4, comparing YAP and Syncet in C26 cells, YAP appears uniformly nuclear at high cell density, potentially more nuclear than the synthetic sensor, which is not coherent with their claim. From the Hippo perspective, there is really an unusual amount of nuclear YAP left in their cells. This should be almost completely cytoplasmic from prior contact inhibition studies in the Hippo field. Syncet could be simply less sensitive than YAP in these borderline conditions. Although there's a more noticeable cytoplasmic noise in dense cells with YAP compared to Syncet, this could be attributed to several factors, including differences in protein degradation rates, which I suspect to be quicker for a synthetic protein. From a technical perspective it is complex to get strong conclusions after comparing something so unrelated with each other. One is a live GFP detection and the other is a staining by immunofluorescence. the nature of the background is also different and so conclusions from comparisons between unrelated systems is not justified. This suggests caution on what is heralded as the main claim here put forward.

      Reviewer 1: I do have some sympathy with R2s comments in the consultation. I agree that showing that NCT is mechanosensitive in an epithelium is not new. I also agree that sometimes it is difficult to see the quantitative differences by eye. This second point could be addressed by including more details of the segmentation and analysis in the supplemental material (along with some example images).

      Regarding novelty, I would be interested to know if R2 thinks that there are experiments that the authors could do to improve the work. Or do they need to simply tone down their claims? It's perfectly acceptable to publish a well characterised tool with a series of observations and it's beneficial to the community to do so.

      Reviewer 3

      Thanks to Reviewers #1 and #2 for using this consultation option; I truly appreciate their feedback on my comments and find it extremely valuable. I agree with Reviewer #1 that the method proposed here is relatively simple. Transfecting cells and conducting live fluorescent imaging can hardly be considered difficult. I believe the construct used/designed by the authors is the main advantage as it provides a specific way to quantitatively assess NCT and not limit the analysis to a single nuclear protein (such as YAP). Reviewer #2 suggests using immunofluorescence staining of YAP or live imaging of fusion fluorescent protein (following transfection) to analyze NCT, but this approach would yield a readout not only based on NCT but also on the many other interacting partners/mechanisms that regulate the candidate localization, resulting in an unspecific readout (and similar transfection/live imaging set-up). Regarding the impact of the study, I agree that it is certainly not as impactful as previous publications on this topic. Although I find reviewer#2 argument on Yap irrelevant, as YAP is not the main focus of this paper. Some experiments have been done with cells of epithelial origin, but NCT mechanosensitivity has not been clearly tested in epithelial monolayer, which is the main claim of the proposed study here. The 2017 Cell paper focused on YAP transport into the nucleus (and not NCT in general) and they showed a correlation between YAP nuclear localization and traction force in MCF10A. I am not sure if one would say that "NCT mechanosensitivity has been well demonstrated in epithelial cells" based on this single panel. The impact of the proposed study is certainly not outstanding but offering a thorough analysis in epithelial cells (as monolayers and not as individual cells) and presenting a well-defined experimental approach should be of interest in the field. I agree with comments from reviewer#2 that some reported effects in graph are unclear on main images. More experimental details should hopefully clarify this aspect.

      Significance

      In this work, Granero-Moya et al characterise a new tool for measuring NCT and show that it is mechanically regulated. Given the importance of NCT in mechano-transduction, this tool will be a great asset to the mechano-biology community and will likely be adopted by multiple groups in the future. The findings about the effects of cell density on NCT and differences from YAP are interesting but could be further fleshed out. This work is likely to be of greatest interest to a specialised audience working in the fields of mechano-biology and nuclear transport.

      PeerReviewed
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    biorxiv.org/content/10.1101/2024.01.11.575167v1
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    Amalgam plays a dual role in controlling the number of leg muscle progenitors and regulating their interactions with developing tendon
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    1. EMBOpress 06 Jun 2024

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      Reply to the reviewers

      Reply to reviewers

      First, we would like to extend our gratitude to all reviewers for their supportive and enthusiastic feedback, which acknowledges our study as an interesting, well-executed, and well-documented contribution to the field. We are also pleased that the novelty and significance of our work have been recognized and appreciated.

      As highlighted by reviewers 2, 3, and 4, our research represents a substantial advancement in understanding the mechanisms that coordinate the development of different cell types. Our findings have broader implications for developmental biology. We also thank the reviewers for their valuable insights, which have significantly improved the overall readability of our manuscript. We have carefully considered all minor corrections and text modifications they had suggested and made amendments accordingly.

      The reviewers proposed several complementary experiments to enhance and clarify our points. We have conducted most of these experiments, with one exception (detailed below), and incorporated the corresponding results into this revised version of the manuscript.

      Additionally, reviewers agreed that higher resolution images depicting the interactions between tendon and myoblast membranes would strengthen our manuscript. In response, we are pleased to present new high-resolution images of Ama::EGFP localization with respect to tendon and muscle cells, obtained using Zeiss Airyscan technology. We also provide new images using newly generated flies that allow simultaneous observation of both myoblast and tendon membranes.

      We believe these modifications substantially enhance the quality and interest of our results, as already highlighted by the reviewers.

      __Referees cross-commenting: __

      All reviewers agreed* that "this is an interesting study that is well done and well documented. I agree with reviewer 1 that the study would further benefit from better imaging of the cellular extensions of tendons and myoblasts to see how both cell types interact." *

      Reply: We agree with this point. To address it, we analyzed leg discs from Sr-Gal4>UAS-myrGFP line (labelling tendon membranes) crossed with a newly generated line R32D05::CD4TdTomato (myoblast specific expression of membrane tagged Tomato protein). Using confocal Zeiss Airy Scan technology, we generated high resolution images for which both tendon cell extensions and myoblast membranes are simultaneously visualized. These images are included in the new Figure 2 (O, P and O', P'). To be noticed: as we also provide new high resolution images of Ama::EGFP and Nrt localizations (Fig. 2 M, N and M', N'), we removed images of zoom in of 5h APF leg disc.

      REVIEWER 1

      Moucaud et al carried out single cell sequencing on myoblasts from the developing drosophila leg muscles, focusing on gene expressions overlapping with tendon and muscle cells. This study proposes that neuronal cell adhesion molecules Ama and Nrt interact in myoblast and tendon adhesion to support tendon and in proliferation of muscle progenitors. This study traces Ama and Nrt expression with various drosophila mutant strains and provides evidence to support its claims using single cell sequencing, immuno-fluoresence and in situ hybridisation. *The authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of their functions in muscle and muscle and tendon formation. *

      • The authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of their functions in muscle and muscle and tendon formation. *

      __ Reply:__ We are grateful to the Reviewer 1 for his/her supportive comments on the quality of our work.

      Page 2 "cell types*..." might be worth including other cell types such as vascular/endothelial if listing all cell types in the limb, as the sentence is suggesting. *

      __ Reply__: "blood vessels" have been added as components of the limb musculoskeletal system.

      Reviewer's comment: The authors discuss the interactions between the myoblasts and tendon cells but do not show any cellular resolution of the interaction between the cells and the secreted adhesion proteins. It would enhance the manuscript if the authors could show high resolution images of these cellular interactions with the secreted protein in vivo.

      __ Reply__: see reply to referees cross-commenting about newly generated high-resolution images shown in Fig. 2.

      Lots of examples of definite article (the) missing throughout the text.

      Reply: The text has been edited and missing articles added

      Second line of Abstract does not flow: Ama encodes secreted proteins to "Ama encodes a secreted protein"

      __ Reply__ the correction has been made accordingly

      2nd para Intro- this para is essentially discussing vertebrate limb muscle/tendon precursors, although includes a non-vertebrate citation. It could be helpful to (briefly) compare/contrast the non-vertebrate vs vertebrate literature on this topic.

      __ Reply__: Indeed, this paragraph is primarily focused on the development of the musculoskeletal system in vertebrates. The comparison (from a molecular standpoint) with the muscle system of the Drosophila leg appears in the following paragraph. For clarity, we have included a brief, more general description (end of second paragraph) about the muscle/tendon system in Drosophila to highlight certain divergences between vertebrate and invertebrate systems and to introduce the subsequent paragraph.

      "in limb of chick embryo add "the limb"

      __ Reply:__ the correction has been made accordingly

      p6 because these two antibodies were raised in rabbit, as the Twist antibody, needs some additional explanatory text.

      __ Reply__: We have modified the text to give a more accurate explanation: "Because these two antibodies were raised in rabbit, as was the Twist antibody, we could not use this latter to visualize the myoblasts"

      P9 discussion creeping into results section-with some speculation on Ama forming homophilic adhesions which has not been experimentally tested.

      __ Reply:__ Because we chose to submit this work as a short format paper, Results and Discussion sections are indeed combined. However, we agree that homophilic adhesion properties of Ama have been shown only in cell culture and not tested in physiological context. To clarify this point, we have modified the corresponding part of the text and only suggest that Ama could directly bind to membranes through its putative GPI modification as proposed by Seeger et al.

      Ama depletion affects both viability and the proliferation rate of leg disc myoblasts (in a Nrt-independent way) Does it have similar role in tendon precursors? Could the authors provide any evidence of apoptosis given proposed role of Ama in glial cells?

      __ Reply: __As asked by Reviewer 1, we have tested these two points and included the results in suppl figure 3 (A-C). As expected, the proliferation rate of tendon cells is not affected as we have previously showed that tendon cells are post-mitotic cells (Laurichesse et al. 2021). Moreover, we now show that Ama depletion does not lead to apoptosis of tendon cells. See Supp. Figure 3 (A-C), the main text has also been modified accordingly.

      REVIEWER 2:

      In this well-written, comprehensive, and interesting manuscript, the authors study the molecular circuitry that supports the coordinated activity of tendon cells and myoblasts during development. As the authors themselves point out in the introduction, the assembly of tissues within the musculoskeletal system provides a particularly attractive system in which to study how different cell types coordinate their behaviours to form higher-order structures. Using single-cell transcriptomics, the authors first identify the cell adhesion molecule Ama and transmembrane protein Nrt as enriched in Drosophila myoblasts and tendon cells. Their transcriptomic data suggest that Nrt is specifically expressed in the tendon cells while Ama is expressed in both. They support these data with a variety of in situ, antibody, and endogenous stainings. Using a series of genetic manipulations, they then convincingly show that Ama controls the total number of myoblasts during the larval stages: Ama knockdown is associated with both decreased proliferation and increased apoptosis of myoblasts. Ama's role in regulating myoblast number is shown to be independent of Nrt and likely under the control of the FGF/RTK pathway. Finally, the authors show that the loss of either Nrt or Ama activity is associated with a loss of adhesion between myoblasts and tendon cells and with the stunted growth of the long tendon. Thus, their data point to Ama playing dual roles in muscle development by regulating both myoblast number and cell adhesion.

      * I very much enjoyed reading the paper, which I think makes an important contribution to our understanding of both the developing musculature and inter-cell-type coordination during development more broadly. I have only a handful of grammatical errors to point out.*

      __Reply: __We appreciate these enthusiastic and supportive comments, and we would like to thank the Reviewer for highlighting the broader contribution of our work to the understanding of the mechanisms of coordination between different cell types.

      *- Grammar: 'This prompted us to use Drosophila model to search' should read 'This prompted us to use the Drosophila model to search' - Grammar: '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama) as candidates...' should read '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama), as candidates...' - Grammar: 'As tendon precursors in leg disc' should read 'As tendon precursors in the leg disc'. - Grammar : '...we performed a series of in situ hybridization...' should read '...we performed a series of in situ hybridizations...' - Grammar: 'Because these two antibodies were raised in rabbit, as the Twist antibody' should read 'Because these two antibodies were raised in rabbit, as was the Twist antibody' - Grammar: 'Statistical analysis reveals an increase myoblast total number when overexpressing an activated ERK' should read 'Statistical analysis reveals an increase in the total number of myoblasts when overexpressing an activated ERK' - Grammar: The following section header needs rephrasing: 'Ama, potential downstream effector of FGF pathway in the regulation of myoblast number'. Maybe 'Ama is a potential downstream effector of the FGF pathway in the regulation of myoblast number' or Ama: a potential downstream effector of the FGF pathway in the regulation of myoblast number. - Grammar: 'whereas its reduction (UAS-StyRNAi) lead to more myoblasts' should read 'whereas its reduction (UAS-StyRNAi) leads to more myoblasts' - For clarity 'The expression of the constitutively active form of ERK could rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020)' might read better as 'Previous work has shown that the expression of the constitutively active form of ERK can rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020). Therefore, we tried...' - Grammar: 'showed a significant higher number of myoblasts compared' should read 'showed a significantly higher number of myoblasts compared' - Grammar: 'Another, not exclusive, possibility' should read Another, non-mutually exclusive, possibility'. - Grammar: 'We measured the length of the tilt relatively to the length' should read '. We measured the length of the tilt relative to the length' *

      Reply: All the modifications suggested above by Reviewer 2 are now included in the text.

      REVIEWER 3:

      *Myoblast and tendon precursors stem from different developmental origins. Hence, they need to find each other to build a functional muscle-skeleton. How they do so is an exciting biological problem, not only for this reviewer who is working on Drosophila muscle development, too. As we currently understand little about how myoblasts communicate with tendons during development, I find this manuscript a generally interesting contribution unravelling a new mechanism of cell-cell communication between these two cell types. It proposes a role for 2 interesting proteins that are little studied. Furthermore, Drosophila leg muscle-tendon development is complex and results in an intricate final architecture. Thus, a better understanding of its molecular mechanisms of development is exciting to this reviewer and to the muscle and tendon fields. *

      Reply: We express our gratitude to Reviewer 3 for his/her keen interest in our work and for emphasizing its significance within the field of developmental biology.

      *While some Ama mRNA expression in myoblasts was confirmed with in situ hybridisation, it was also shown that Ama mRNA is expressed in other sources including tendon precursors. As the interesting AmaGFP protein overlapping with the developing tendon cells is found at some distance from the myoblasts, the source for this Ama protein population is not entirely clear. To identify if it is secreted from myoblasts I suggest to stain for Ama-GFP in the muscle-specific Ama knock-down discs at 5h APF. This could use the late knock-down condition. *

      __ Reply:__ In Suppl Fig.2 in a close-up view of the femur region, we show that at 5h APF Ama is transcribed in addition to myoblasts also in the developing tilt tendon. This tendon associated Ama expression is specific as it is detected after myoblast specific Ama knockdown. Thus, at 5h APF, the Ama-GFP signal detected at the interface of muscle and tendon precursors could in part correspond to Ama secreted by the tilt tendon cells. However, we also observed clear Ama-GFP signal at the interface of myoblasts and tendon precursors at 0h APF when Ama is not yet transcriptionally activated in tilt tendon precursors (not shown). Thus, we are confident that the myoblasts are the main source of secreted Ama protein that ensure close proximity of myoblast and tendon precursor cells. A view supported by the loss of myoblast-tendon cell proximity in myoblast-specific Ama knockdown. However, to clarify this point, we immunostained myoblast-specific Ama knock-down discs for the Ama protein in at 5h APF as suggested. As stated in the text, we were concerned that GFP tag could influence the life-time of the Ama protein, as GFP itself is pretty stable. This is why we used anti-Ama antibody kindly provided by Dr. Silman to determine whether myoblast-specific Ama knockdown (using R32D05-Gal4 driver) would completely abolish Ama protein at 5h APF. We indeed observed a strong reduction of Ama protein at this stage indicating that the contribution of Ama protein from tendon cells is minimal (but cannot be completely excluded), with myoblasts remaining the major source at this stage. This new result is now presented in Suppl Fig. 2M-P. This result is also in accordance with our new result showing that tendon-specific AmaKD has no effect on tendon growth (see reply to the comment below regarding tendon length). In light of this new result, we have modified the text accordingly in the corresponding paragraph (p5-6).

      Generally, it might be useful to move the part of Figure 2 that shows the Ama-GFP Nrt co-staining to the later part in the text that addresses the interaction of both cell types and keep the autonomous Ama role in muscle for the start of paper only.

      __ Reply: __We have indeed debated extensively about this possibility before submitting this work. While such a presentation would have some logical coherence, it also has the disadvantage of having to resume, at least partially, the expression of Ama, leading to certain redundancies. Additionally, we chose to begin with a comparison of the new myoblast transcriptomic data with pre-established tendon data to highlight the presence of ligand-receptor pairs. In this context, it seemed to us more pertinent to present the expression patterns of Ama and Nrt together in the initial figures.

      To quantify the interaction of the myoblast cell membranes and the tendon cells better it would be useful to combine sr>CAAXmCherry with a myoblast membrane maker (possibly Him-CD8-GFP or use R15B03-Gal4 with R79D08-lexA). This could also improve the "mean distance" measurements. As currently presented, it is not so clear how the mean distance was measured. It could be helpful to indicate some examples in zoom-in vies on Figure 5. Does a distance of 4 µm in wild type mean that the myoblast is not touching the tendon precursors, or is only the myoblast nucleus that is Twi positive at this distance?

      __ Reply: We are grateful to this reviewer for its relevant suggestion. Thus, as stated above (referees cross-commenting), we provide new high-resolution images with labelled membranes of both tendon cells and myoblasts (fig 2 O-P). As shown here, myoblast membranes are very closed to each other, and nuclei occupy an important part of myoblast volumes. So, we found more accurate to use the myoblast nucleus (stained with Twist antibody) to detect individual myoblasts using Imaris Spot function rather than myoblast membranes. We also believe that the distances between the center of myoblast nuclei and the tendon surface are representative of the distance between these two cell types as nucleus myoblast occupies most of the cell volume. We addressed this point in the new Suppl. Fig.5. __Regarding the distance of 4____ µm: As mentioned in the original text, the 4 µm distance represents the average distance between myoblasts and the tendon surface in wild type discs. We do not perceive this distance as indicative of a threshold distinguishing myoblasts that interact physically with tendons from those that do not. We rather use this mean distance to quantify the distribution of myoblasts around the tendon and their dispersion/mis-distribution in Ama and Nrt knockdown leg discs. To clarify this point, we have modified the corresponding paragraph: "This result indicates that AmaKD leads to myoblasts mis-distribution around the tilt, suggesting that the reduction of Ama level could affect myoblast-tendon adhesion".

      For a better understanding of how the mean distance was measured, we added a new Supplementary Figure 5 (rather than a zoom-in in the main figure as suggested by this reviewer), with a corresponding description of how this distance was measured in addition to the explanations in the material and method section.

      Is the tendon elongation phenotype seen after Ama RNAi in muscle and in Nrt mutants due to the fact that myoblasts are further away from tendons or is it an Ama/Nrt role that is autonomous to tendons? This could be tested by assaying tendon elongation after tendon-specific Ama knock-down as shown in Figure S2.

      __ Reply: __As asked by this reviewer, we have performed this experiment using Sr-Gal4 driver to induce tendon-specific Ama knockdown and assessed tendon elongation using R79D08-lexA>lexAop-GFP marker. Overall statistical analysis is now included in Fig 5F and G graphs. This analysis shows that tendon-specific Ama knockdown does not affect tendon elongation. This is in concordance with the fact that Ama knockdown in myoblasts leads to tendon defects similar to that of Nrt loss of function in tendon clearly indicating that the observed phenotypes are due to Ama's role in myoblasts. This does not exclude an additional subsequent Ama function in growing tendon precursors in later development.

      Minor : Is Figure 2Q a zoom-in from Figure 2P? If yes, it would be helpful to indicate the rough position of it in the lower magnification image.

      Reply: Figure 2Q was not a zoom-in from Figure 2P in the previous version of the paper. As stated above Fig. 2 has now been modified.

      Minor page 6 - w[1118] is with small "w".

      Reply: modifications have been made accordingly in main and figure texts.

      REVIEWER 4:

      *The manuscript is well-organized, with clear descriptions of methods and results. The use of transcriptomic datasets and gene expression analyses provides insights into the molecular mechanisms underlying the interaction between muscle and tendon precursors. *

      *The immunostaining and in situ hybridization experiments well illustrate the expression patterns of Ama and Nrt in muscle and tendon cells during leg disc development in Drosophila. *

      *The functional analyses, including knockdown experiments, support the conclusion that Ama plays a crucial role in maintaining the pool of leg muscle precursor cells and coordinating tendon and muscle precursor growth. *

      The manuscript significantly enhances our understanding of cell-cell interactions in the musculoskeletal system of Drosophila. The findings have broader implications for the field of developmental biology. In general, this manuscript provides valuable insights into the molecular processes governing leg muscle and tendon development.

      Reply: We are indebted to Reviewer 4 for highlighting that our manuscript is well-organized and well-illustrated. We are also grateful to Reviewer 4 for highlighting the valuable insights of our work.

      some aspects in the manuscript, for example how Ama regulates myoblast number and its interaction with the FGFR pathway, could be further explored or clarified.

      __ Reply:__ Regarding Ama's contribution for maintaining the myoblast pool through its interaction with the FGF pathway, we demonstrate here that, contrary to what has been proposed for glial cells, Ama acts downstream of this pathway, although we emphasize that there is a synergistic effect with the MAPK pathway inhibitor, Sprouty. These findings thus reveal complex and variable regulatory mechanisms between Ama and the FGF pathway that would require specific investigation, the entirety of which appears challenging to integrate into this same publication.

      the organization of the abstract could be improved to provide a clearer and more comprehensive overview of the study. The abstract currently lacks a structured presentation of essential components such as methods, results, and conclusions. It would greatly benefit from a more systematic arrangement.

      __ Reply:__ We have made modifications to propose a more structured abstract.

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      Referee #4

      Evidence, reproducibility and clarity

      The manuscript by Moucaud et al. titled "Amalgam plays a dual role in controlling the number of leg muscle progenitors and regulating their interactions with developing tendon" presents a comprehensive investigation of cell-cell interaction between skeletal muscle and tendon precursor cells. The authors use the Drosophila leg development model to findr candidates involved in early interactions between muscle and tendon precursors. The manuscript focuses on the role of Amalgam (Ama) and Neurotactin (Nrt) in these two cell populations communication during musculoskeletal system development .

      The results demonstrate that Ama and Nrt are selectively expressed in skeletal muscle and tendon precursors, respectively. Moreover, Ama and Nrt are required to keep myogenic and tendom precursors closely associated, thus is essential for leg muscles development. Furthermore, Ama plays also important role in maintaining the pool of leg muscle precursor cells. Additionally, the expression patterns of Ama and Nrt suggest a potential dual role for Ama, not only in interacting with Nrt but also in a Nrt-independent manner. Summarizing, the study shows the importance of specific bi-directional communication between different cell populations in the formation of functional organs in suggests that Ama and Nrt plays key role during musculoskeletal system development.

      The manuscript is well-organized, with clear descriptions of methods and results. The use of transcriptomic datasets and gene expression analyses provides insights into the molecular mechanisms underlying the interaction between muscle and tendon precursors. The immunostaining and in situ hybridization experiments well illustrate the expression patterns of Ama and Nrt in muscle and tendon cells during leg disc development in Drosophila. The functional analyses, including knockdown experiments, support the conclusion that Ama plays a crucial role in maintaining the pool of leg muscle precursor cells and coordinating tendon and muscle precursor growth. Additionally, the authors explore the potential link between Ama and the FGFR pathway, suggesting that Ama may act downstream of the pathway.

      However, some aspects in the manuscript, for example how Ama regulates myoblast number and its interaction with the FGFR pathway, could be further explored or clarified. Moreover, the organization of the abstract could be improved to provide a clearer and more comprehensive overview of the study. The abstract currently lacks a structured presentation of essential components such as methods, results, and conclusions. It would greatly benefit from a more systematic arrangement.

      Significance

      The manuscript significantly enhances our understanding of cell-cell interactions in the musculoskeletal system of Drosophila. The findings have broader implications for the field of developmental biology. In general, this manuscript provides valuable insights into the molecular processes governing leg muscle and tendon development.

      PeerReviewed
    3. EMBOpress 06 Jun 2024

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      Referee #3

      Evidence, reproducibility and clarity

      This manuscript is investigating mechanisms how muscle and tendon development is properly coordinated. By using differential expression analysis of developing Drosophila legs, the authors find that Amalgam (Ama) is expressed in the developing leg myoblasts and Neurotactin (Nrt) is expressed in one class of tendon precursors, the tilt in the dorsal femur. Using a new Ama-GFP knock-in line, Ama protein was found in the proximity to the developing tendons at 5h APF, when myoblasts and tendons likely interact.

      Using myoblast specific knock-down of Ama, the authors find that Ama acts autonomously in the leg myoblasts to promote their proliferation and survival. A similar function for Ama had been described for flight muscle myoblasts in larval wing discs (Zappa et al. 2020). In leg myoblasts ama likely acts downstream of FGF signalling in the myoblasts to promote their proliferation.

      As Ama and Nrt were proposed as a ligand-receptor pair promoting adhesion, the authors knocked-down Ama later during myoblast development, after they have proliferated, and tested where these myoblasts are positioned. They find that Ama knock-down myoblasts stay at a larger distance from tendons compared to wild type; the same was found in Nrt mutants. Thus, the authors propose that Ama protein secreted from myoblasts acts via the membrane-bound Nrt protein on the tendon precursors to coordinate muscle-tendon adhesion and proper positioning.

      1. While some Ama mRNA expression in myoblasts was confirmed with in situ hybridisation, it was also shown that Ama mRNA is expressed in other sources including tendon precursors. As the interesting AmaGFP protein overlapping with the developing tendon cells is found at some distance from the myoblasts, the source for this Ama protein population is not entirely clear. To identify if it is secreted from myoblasts I suggest to stain for Ama-GFP in the muscle-specific Ama knock-down discs at 5h APF. This could use the late knock-down condition. Generally, it might be useful to move the part of Figure 2 that shows the Ama-GFP Nrt co-staining to the later part in the text that addresses the interaction of both cell types and keep the autonomous Ama role in muscle for the start of paper only.
      2. To quantify the interaction of the myoblast cell membranes and the tendon cells better it would be useful to combine sr>CAAXmCherry with a myoblast membrane maker (possibly Him-CD8-GFP or use R15B03-Gal4 with R79D08-lexA). This could also improve the "mean distance" measurements. As currently presented, it is not so clear how the mean distance was measured. It could be helpful to indicate some examples in zoom-in vies on Figure 5. Does a distance of 4 µm in wild type mean that the myoblast is not touching the tendon precursors, or is only the myoblast nucleus that is Twi positive at this distance?
      3. Is the tendon elongation phenotype seen after Ama RNAi in muscle and in Nrt mutants due to the fact that myoblasts are further away from tendons or is it an Ama/Nrt role that is autonomous to tendons? This could be tested by assaying tendon elongation after tendon-specific Ama knock-down as shown in Figure S2.

      Minor:

      1. Is Figure 2Q a zoom-in from Figure 2P? If yes, it would be helpful to indicate the rough position of it in the lower magnification image.
      2. page 6 - w[1118] is with small "w".

      Referees cross-commenting

      All reviewer agree that this is an interesting study that is well done and well documented. I agree with reviewer 1 that the study would further benefit from better imaging of the cellular extensions of tendons and myoblasts to see how both cell types interact.

      Significance

      Myoblast and tendon precursors stem from different developmental origins. Hence, they need to find each other to build a functional muscle-skeleton. How they do so is an exciting biological problem, not only for this reviewer who is working on Drosophila muscle development, too.

      As we currently understand little about how myoblasts communicate with tendons during development, I find this manuscript a generally interesting contribution unravelling a new mechanism of cell-cell communication between these two cell types. It proposes a role for 2 interesting proteins that are little studied. Furthermore, Drosophila leg muscle-tendon development is complex and results in an intricate final architecture. Thus, a better understanding of its molecular mechanisms of development is exciting to this reviewer and to the muscle and tendon fields.

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      Referee #2

      Evidence, reproducibility and clarity

      In this well-written, comprehensive, and interesting manuscript, the authors study the molecular circuitry that supports the coordinated activity of tendon cells and myoblasts during development. As the authors themselves point out in the introduction, the assembly of tissues within the musculoskeletal system provides a particularly attractive system in which to study how different cell types coordinate their behaviours to form higher-order structures. Using single-cell transcriptomics, the authors first identify the cell adhesion molecule Ama and transmembrane protein Nrt as enriched in Drosophila myoblasts and tendon cells. Their transcriptomic data suggest that Nrt is specifically expressed in the tendon cells while Ama is expressed in both. They support these data with a variety of in situ, antibody, and endogenous stainings. Using a series of genetic manipulations, they then convincingly show that Ama controls the total number of myoblasts during the larval stages: Ama knockdown is associated with both decreased proliferation and increased apoptosis of myoblasts. Ama's role in regulating myoblast number is shown to be independent of Nrt and likely under the control of the FGF/RTK pathway. Finally, the authors show that the loss of either Nrt or Ama activity is associated with a loss of adhesion between myoblasts and tendon cells and with the stunted growth of the long tendon. Thus, their data point to Ama playing dual roles in muscle development by regulating both myoblast number and cell adhesion.

      I very much enjoyed reading the paper, which I think makes an important contribution to our understanding of both the developing musculature and inter-cell-type coordination during development more broadly. I have only a handful of grammatical errors to point out.

      Grammar: 'This prompted us to use Drosophila model to search' should read 'This prompted us to use the Drosophila model to search'

      Grammar: '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama) as candidates...' should read '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama), as candidates...'

      Grammar: 'As tendon precursors in leg disc' should read 'As tendon precursors in the leg disc'.

      Grammar : '...we performed a series of in situ hybridization...' should read '...we performed a series of in situ hybridizations...'

      Grammar: 'Because these two antibodies were raised in rabbit, as the Twist antibody' should read 'Because these two antibodies were raised in rabbit, as was the Twist antibody'

      Grammar: 'Statistical analysis reveals an increase myoblast total number when overexpressing an activated ERK' should read 'Statistical analysis reveals an increase in the total number of myoblasts when overexpressing an activated ERK'

      Grammar: The following section header needs rephrasing: 'Ama, potential downstream effector of FGF pathway in the regulation of myoblast number'. Maybe 'Ama is a potential downstream effector of the FGF pathway in the regulation of myoblast number' or Ama: a potential downstream effector of the FGF pathway in the regulation of myoblast number.

      Grammar: 'whereas its reduction (UAS-StyRNAi) lead to more myoblasts' should read 'whereas its reduction (UAS-StyRNAi) leads to more myoblasts'

      For clarity 'The expression of the constitutively active form of ERK could rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020)' might read better as 'Previous work has shown that the expression of the constitutively active form of ERK can rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020). Therefore, we tried...'

      Grammar: 'showed a significant higher number of myoblasts compared' should read 'showed a significantly higher number of myoblasts compared'

      Grammar: 'Another, not exclusive, possibility' should read Another, non-mutually exclusive, possibility'.

      Grammar: 'We measured the length of the tilt relatively to the length' should read '. We measured the length of the tilt relative to the length'

      Significance

      I very much enjoyed reading the paper, which I think makes an important contribution to our understanding of both the developing musculature and inter-cell-type coordination during development more broadly

      PeerReviewed
    5. EMBOpress 06 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Moucaud et al carried out single cell sequencing on myoblasts from the developing drosophila leg muscles, focusing on gene expressions overlapping with tendon and muscle cells. This study proposes that neuronal cell adhesion molecules Ama and Nrt interact in myoblast and tendon adhesion to support tendon and in proliferation of muscle progenitors. This study traces Ama and Nrt expression with various drosophila mutant strains and provides evidence to support its claims using single cell sequencing, immuno-fluoresence and in situ hybridisation.

      Minor comments:

      Page 2 "cell types..." might be worth including other cell types such as vascular/endothelial if listing all cell types in the limb, as the sentence is suggesting.

      The authors discuss the interactions between the myoblasts and tendon cells but do not show any cellular resolution of the interaction between the cells and the secreted adhesion proteins. It would enhance the manuscript if the authors could show high resolution images of these cellular interactions with the secreted protein in vivo.

      Minor typographical

      Lots of examples of definite article (the) missing throughout the text

      Second line fo Abstract does not flow Ama encodes secreted proteins to "Ama encodes a secreted protein"

      2nd para Intro- this para is essentially discussing vertebrate limb muscle/tendon precursors, although includes a non-vertebrate citation. It could be helpful to (briefly) compare/contrast the non-vertebrate vs vertebrate literature on this topic.

      in limb of chick embryo add "the limb"

      p6 because these two antibodies were raised in rabbit, as the Twist antibody, needs some additional explanatory text

      p8 or FGF receptor add "the"

      P9 discussion creeping into results section-with some speculation on Ama forming homophilic adhesions which has not been experimentally tested.

      Significance

      Thge authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of theri functions in muscle and muscle and tendon formation.

      Ama depletion affects both viability and the proliferation rate of leg disc myoblasts (in a Nrt-independent way)

      Does it have similar role in tendon precursors?

      Could the authors provide any evidence of apoptosis given proposed role of Ama in glial cells?

      PeerReviewed
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    Structural analysis of SALL4 zinc-finger domain reveals a link between AT-rich DNA binding and Okihiro syndrome
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    Prion diseases disrupt the glutamate/glutamine metabolism in skeletal muscle
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      Reply to the reviewers

      We thank the referees for their insightful comments and constructive feedback, which have undoubtedly strengthened our manuscript.

      Reviewer #1 Comment:

      Absence of evidence demonstrating the presence of prions or prion-seeding activity in extraneural tissues.

      Response: Our study focuses on all pathophysiological alterations brought about by prion infections in extraneural organs, be they caused directly by prion infections of said organs or through indirect mechanisms. Nevertheless, we share the reviewer's curiosity about a possible correlation between these changes and the presence of prion-seeding activity. We propose to include additional data demonstrating prion presence and seeding activity in skeletal muscle at various timepoints. This will be achieved by employing proteinase K digestion followed by Western blot (PK-WB) and real-time quaking-induced conversion (RT-QuIC) assays to provide a robust correlation with our transcriptomic analyses and Glul upregulation.

      Revision: We have conducted preliminary experiments using PK-WB and RT-QuIC assays. These experiments were performed on terminal-stage prion-infected samples and related controls. If prion presence is detected at this stage, we plan to extend the analysis to earlier stages, specifically at 16 weeks post-inoculation (wpi) and 8 wpi, to track the progression of prion-seeding activity over time.

      Western blot analysis was performed on skeletal muscle homogenates at the terminal stage of prion disease in mice infected with three prion strains (RML6, ME7, and 22L) and related NBH control. Control samples include CNS brain homogenates, showing prion presence (PrPSc) in RML6 but not in NBH. Neither skeletal muscles from NBH nor from prion-infected samples show detectable prions, indicating that PK-WB may lack the sensitivity to detect prions in skeletal muscle or that prion levels are below detection thresholds (Revision Figure 1A) for this specific technique.

      Next, we performed RT-QuIC assays on muscle homogenates using different protocols, including sodium phosphotungstic acid (NaPTA) enrichment (Revision Figure 1B). NaPTA binds and precipitates PrPSc in the presence of MgCl2, removing contaminants and concentrating PrPSc. For this protocol, 100 µg of muscle homogenates were treated with benzonase to degrade DNA contaminants. Then, 4% NaPTA and 170 mM MgCl2 were added, resulting in a final NaPTA concentration of 0.3%. The samples were incubated at 37{degree sign}C while shaking at 1500 rpm for 2 hours, followed by centrifugation at 15,000 g for 30 minutes to precipitate PrPSc. The resulting pellets were used to seed RT-QuIC reactions. Each biological replicate was run in quadruplicate, and replicates were considered positive only if at least 3 out of 4 technical replicates showed detection. Results indicated no amplification for NBH samples. For RML6 skeletal muscles, 2 out of 3 biological replicates were positive. For ME7, 0 out of 4 biological replicates were positive. For 22L, 1 out of 3 biological replicates was positive.

      Using the same protocol without NaPTA (Revision Figure 1C), two positive samples were observed in the NBH condition, suggesting that NaPTA is useful for specific prion enrichment.

      Similarly, we combined NaPTA and sarkosyl in our further trial. 10% weight/volume muscle homogenates in 1x PBS containing 2% sarkosyl were centrifuged at 80 g for 1 minute, and the supernatant (500 µl) was collected. If still dirty, further centrifugation at 2700 g for 5 minutes was performed. Then, 500 µl PBS containing 2% sarkosyl was added and incubated for 10 minutes at 37{degree sign}C. Benzonase and MgCl2 (final concentrations 50 U/ml and 1 mM, respectively) were added and incubated for 30 minutes at 37{degree sign}C with shaking at 1500 rpm. NaPTA was added to a final concentration of 0.3% and incubated for 30 minutes at 37{degree sign}C with shaking. Samples were centrifuged at 15,000 g for 30 minutes and resuspended in 20 µl of 0.1% sarkosyl-containing PBS condition (Revision Figure 1D). Using this protocol, we also detected signals in the NBH control.

      These results indicate ongoing challenges in optimizing prion extraction from skeletal muscle. Unlike brain tissue, where prion levels are significantly higher, skeletal muscle presents difficulties due to lower prion concentrations. In brain samples, dilutions still result in positive signals only from prion-enriched conditions. However, for skeletal muscle, prion extraction is not as straightforward, highlighting the need for further refinement of the protocol to achieve reliable detection and differentiation between prion-infected and control samples.

      Inclusion of prion strain with limited extraneural replication. Reliance on three prion strains limits the relevance. Inclusion of a strain with limited extraneural replication is suggested.

      Response: To address this limitation, we propose a comprehensive discussion on the systemic nature of prion diseases, emphasizing the need for future research to explore potential strains with restricted replication patterns.

      Revision: There is a significant interest in prion deposits in skeletal muscles as potential sources of prion spreading. The consumption of beef products from cattle infected with bovine spongiform encephalopathy (BSE) prions caused new variant Creutzfeldt-Jakob disease, raising early concerns about the transmission of prions from cervids to humans (1-3). This remains a hot topic in the field (4-7), underscoring the importance of our longitudinal transcriptomic analysis in different extraneural organs. However, prion strains with restricted extraneural replication which we could use as control have not been described in mice used as prion animal models. According to our knowledge and the existing literature, there is no documentation of any mouse-adapted prion strains that are unable to propagate prions outside the central nervous system (CNS). Although this does not apply to our study, it is important to note that hamster-derived prion strains such as HY and DY exhibit different replication patterns. Hamsters infected with HY TME prions show detectable infectivity and/or PrPSc in the CNS, lymphoreticular system, skeletal muscle, nasal secretions, and blood (8-11). Conversely, prion infectivity and/or PrPSc in DY TME-infected hamsters is restricted to the CNS (12-14).

      In mice, the situation is quite different, and there are no prion strains with restricted extraneural replication. Instead, studies have focused on models where prion protein (PrPC) is absent in all tissues except skeletal muscle, which is essentially the opposite of the condition requested by the reviewer. For instance, research has demonstrated that prion levels in skeletal muscles are 5-10% of those observed in the brain (1). Here, transgenic mice (Tg(α-actin-MoPrP)6906/Prnp0/0) expressing PrPC only in skeletal muscles (and barely detectable in the CNS) were created. After intramuscular prion injection, these mice showed that skeletal muscles could propagate prions (1). Additionally, another study found that prions were not detectable in skeletal muscle at early stages (32 and 60 days post intracerebral prion inoculation) unless experimental autoimmune myositis was induced, which increased prion spread to skeletal muscle (15).

      This comprehensive discussion underscores the absence of a mouse model prion strain with limited extraneural replication, highlighting a gap in current research that our study aims to address indirectly through our systemic approach.

      Clarification on statistical methods. Lack of details on statistical tests used for comparing GLUL levels in Figures 3 and 4.

      Response: We clarified the statistical tests used, specifying whether they are parametric or non-parametric, and provide a rationale for the chosen methods. It is important to note that GLUL upregulation is significant, as evident from Figure 4. At 8 wpi, the fold change for RML6 is above 3, for ME7 is above 1.5, and for 22L is above 2. The fold change in later timepoints is increasingly larger.

      Revision: For Figure 3E, normalized raw counts for the GLUL gene in control and sCJD patients were analyzed using the DESeq2 package, with related false discovery rate (FDR) calculations. DESeq2 is appropriate for RNA-seq data as it models count data using a negative binomial distribution, suitable for overdispersed count data commonly found in RNA-seq experiments. The normalization and FDR calculation ensure that the comparisons between control and sCJD patients are statistically robust.

      In Figure 3G, Western blot densitometry data were analyzed using the Mann-Whitney U test, resulting in a p-value of 0.01072. The Mann-Whitney U test is a non-parametric test that does not assume normal distribution, making it suitable for small sample sizes and non-normally distributed data, which is often the case in Western blot densitometry. For statistical analyses in Figure 4A, Mann-Whitney U test was used. In Figure 4C, we applied the t-test (as the standard deviations were consistent) with Bonferroni correction to account for multiple comparisons. The t-test is a parametric test suitable for normally distributed data, and the Bonferroni correction adjusts for the increased risk of Type I errors when multiple comparisons are made, ensuring the results are not due to chance. Additionally, we used one-way ANOVA corrected with Kruskal-Wallis, a non-parametric method, to confirm our findings (Revision Figure 2). The results from both statistical tests were in strong agreement, validating our analysis.

      In Supplementary Figure 6, the Mann-Whitney U test was used due to its non-parametric nature, which is suitable for data that do not assume a normal distribution. This test was chosen to provide a robust analysis of the data, which did not fit the assumptions required for parametric tests.

      These methods were selected based on the data distribution and the need for accurate statistical analysis to validate the significance of our findings. The choice of DESeq2 for RNA-seq data, Mann-Whitney U for non-normally distributed data, and t-tests with Bonferroni correction for normally distributed data ensures that our analyses are appropriately tailored to the characteristics of the data, providing reliable and valid results.

      Details on CJD cases analyzed. Information regarding the types of CJD analyzed is missing.

      Response: We ensured that details on the types of CJD cases analyzed, including genotype, strain type, and age, are clearly presented in the main text and supplementary materials.

      Revision: A comprehensive description of the sCJD cases, including genotype, strain type, and age, was accessible in Supplementary Table 5 (and here, in Revision Figure 3). This table also provides the reasons why some biosamples were excluded from the final bulk RNA sequencing and downstream analysis.

      Recent publications on prion seeding activity. Mention recent publications showing prion seeding activity in extraneural tissues.

      Response: We will update the Introduction section to include references to recent studies demonstrating prion seeding activity in extraneural tissues of sCJD and vCJD patients using RT-QuIC or PMCA assays.

      Revision: We will discuss and cite additional papers on this topic, highlighting the growing body of evidence for prion seeding activity in extraneural tissues. These references will provide a comprehensive background on the detection and significance of prion seeding in peripheral tissues, thereby strengthening the context and relevance of our study.

      Reviewer #2 Comment:

      The RNA sequencing of human skeletal muscle samples identified only one common gene between human and mouse conditions. There is concern that this gene may be a bystander result of terminal disease stage pathophysiology in both animals and human.

      Response: We strengthened the evidence supporting GLUL as early and altered gene by including additional timepoint analyses and showing its presence at earlier disease stages.

      Revision: The upregulation of GLUL cannot be attributed to a bystander effect result of terminal disease stage pathophysiology, as it is consistently upregulated across all analyzed timepoints. We performed weighted gene co-expression network analysis (WGCNA) grouped by disease stages and GLUL belongs to the orange module (upregulated genes throughout all timestages in both main (Figure 2A - original manuscript) and validation (Figure 3A - original manuscript) cohort). We also included a comparison of GLUL expression between RML6 and NBH. As shown in the figure (Revision Figure 4), GLUL is upregulated at all individual timepoints. This finding is corroborated at both the transcriptional and protein levels, including other prion strains (Figure 4 - original manuscript) from a further animal cohort for RML6 condition. This consistent upregulation across various stages supports GLUL as a robust altered genes and possible biomarker for prion disease progression.

      Cautious interpretation of GLUL dysregulation specificity. The claim that GLUL dysregulation is specific to prion diseases should be mentioned more cautiously due to the small sample number of other neurodegenerative diseases (NDs). The finding would be stronger if a meta-analysis of possible available data from human ND cohorts could be examined.

      Response: We will rephrase our conclusion to acknowledge the sample size limitation and suggest further studies for confirmation. However, due to the poor sample availability of skeletal muscles biopsis from other NDs, related metadata are complicated to be found.

      Revision: Modify the discussion section to reflect a more cautious interpretation, emphasizing the need for larger cohort studies to confirm GLUL specificity.

      Post-transcriptional modifications of GLUL. Explore the possibility of GLUL being modified through RNA editing affecting its expression.

      Response: We investigated the potential post-transcriptional modifications of GLUL, such as RNA editing, and their impact on its expression and function.

      Revision: We will add a paragraph named "Lack of post-transcriptional changes in extra-neural organs of prion-inoculated mice".

      Results: We calculated the genome-wide adenosine-to-inosine editing index (AEI) to measure global RNA editing levels (16), the preferential site of RNA editing in mammals. Blood global editing levels rose steadily during aging but were independent of prion inoculation (Revision Figure 5A). No AEI differences were seen in muscle or spleen (Revision Figure 5B and C). To determine recoding of individual transcripts, we aligned our sequencing results to previously published high-confidence AEI recoding sites (17). We found Flnb and Copa in the spleen and Cog3 in blood to be significantly recoded (Revision Figure 5D). However, Glul did not show significant recoding.

      Alternative splicing can give rise to disease-associated differentially used transcripts (18). In contrast to our previous results in the brain (19), the present alternative splicing analyses in extraneural organs showed only minor alterations (Revision Figure 5E). Necap2, Myl6 and Srsf5 transcripts were alternatively spliced across multiple organs and prion incubation times (Revision Table 1). Only in two out of a total of 21 splice variants differential transcript usage was accompanied by differential gene expression: upregulation of Myl6 in blood at 4 wpi and downregulation of Ms4a6c in blood at 14 wpi.

      Discussion: Except for Flnb, Copa and Cog3, we were unable to find evidence for broad dysregulation of posttranscriptional RNA editing, in contrast a recent report (20) but in line with our previous findings (19). Furthermore, splicing analysis suggests that alternative splicing was largely unlinked from gene expression changes.

      Method: Adenosine-to-inosine editing index (AEI) was calculated as previously published (16). Herein, raw fastq reads were uniquely aligned to a murine mm10 reference genome using STAR v2.7.3 with the filter outFilterMultimapNmax=1. RNAEditingIndexer (https://github.com/a2iEditing/RNAEditingIndexer) was used to calculate per-sample AEI.

      We identified gene-specific RNA editing based on a recently published list of high-confidence targets of Adar (17)as follows. RediToolsKnown.py from REDItools (21) was applied on uniquely aligned samples as mentioned above. This yielded per-site lists of A-to-I editing on which we applied the following thresholds: (a) a minimum of 3 alternative reads per site per sample (b) a minimal editing frequency of 1 % per site (c) criteria a) and b) are fulfilled in at least floor(2/3 * n) biological replicates, n is total number of biological replicates per group (d) transcripts of site present in at least 2 biological control replicates. Multiple testing of sites passing above-mentioned thresholds was performed using REDIT (https://github.com/gxiaolab/REDITs) and adjusted for false discovery rate (FDR) according to Benjamini-Hochberg, we considered sites with an FDR For alternative splicing, SGSeq R package (22) was employed to find splicing events characterized by two or more splice variants. Exons and splice junction predictions were obtained from BAM filesPrediction of exons and splice junctions was first made for each sample individually. Then the predictions for all samples were merged and we obtained a common set of transcript features. Overlapping exons were disjoint into non-overlapping exon bins and a genome-wide splice graph was compiled based on splice junctions and exon bins. A single value for each variant was produced by adding up the 5' and 3' counts, or, if these represented the same transcript features, by considering the unique value. These counts were then fed to DEXSeq (23). We analyzed differential usage of variants across a single event, in-stead of quantifying differential usage of exons across a single gene. We retained only variants with at least five counts in at least three samples (of any condition). After filtering, the events associated with a single variant were discarded. Differential analysis was then performed implementing a sam-ple+exon+condition:exon model in DEXSeq. Differentially expressed isoforms were defined as isoforms changing with FDR < 0.05. In the case of differentially used splice variants in muscle on 12 wpi, this dataset was considered as an outlier and hence excluded due to excessively reported splice variants (1,788 events compared to 5 or less on all other time-points and extraneural organs).

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      Referee #2

      Evidence, reproducibility and clarity

      Summary: The authors present a comprehensive transcriptomic analysis of different organ tissue samples (blood, spleen and muscle) from established prion models RML6, or 22L, or ME7 strain mouse-adapted scrapie, at a significant number of timepoints recapitulating early, asymptomatic preclinical, clinical and terminal stages of disease. The transcriptome profile of each tissue at each progression stage is a very useful information, on disease relevant transcriptional changes of variable significance. Eigengene networks were constructed to study the relationships between 39 modules only 2 were significant (orange and dark green) in skeletal muscle from all 3 tissues examined. The authors support they reveal a higher order organization of the late-stage disease transcriptome and provide insights into the modular architecture of gene expression during disease progression (early, presymptomatic and symptomatic) followed by 20 gene hub identification. In the context of network analysis, a high preservation with a Z-summary statistic > 1.96 suggests that the module's connectivity pattern is significantly preserved across different networks of the module's structure as RML6 disease progresses and it is not random compared to control.

      The RNA sequencing of human skeletal muscle samples further validated and only 1 common gene between human and mouse condition confirmed by immunoblotting. The GLUL gene was further investigated in terms of gene and protein expression in various mouse disease models along with human skeletal muscle CJD autopsy material. Their findings did not correlate between human and all mice models completely. The increase in GLUL expression is accompanied by changes in glutamate/glutamine metabolism and reduced glutamate levels in CJD skeletal muscle. These alterations were only specific to prion diseases, as they were not confirmed in other neurodegenerative conditions such as amyotrophic lateral sclerosis, Alzheimer's disease, or dementia with Lewy bodies. The authors propose GLUL dysregulation as a potential novel biomarker for prion disease progression, during the preclinical stages with potentially useful efficacy for monitoring of therapies.

      Comments

      • The RNA sequencing of human skeletal muscle samples identified only 1 common gene between human and mouse condition confirmed by immunoblotting at the terminal stage of the disease. How can they conclude that this specific gene is not a bystander result of the known pathophysiology at the terminal disease stage? The mouse data are not solidly consistent with the biomarker expression.
      • The claim that GLUL dysregulation with a result in glutamate/glutamine metabolism is only specific to prion progression only eventhough interesting should be mentioned with a more cautious way as the sample number of other NDs is small. The finding would be significantly stronger if metanalysis of possible available data of human ND cohorts could be examined.
      • Post-transcriptional modifications have been described as potential contributors to prion pathogenesis therefore, the authors should also explore the possibility of GLUL being modified through RNA editing affecting its expression.
      • The experiments are well designed and executed and the analysis methods are explained in detail. The figures are elegantly presented with adequate information.

      Significance

      The authors present a very well designed and comprehensive transcriptomic analysis of several tissue organs related to prion disease progression and validation data from multiple mouse models as well as human CJD skleletal muscle tissue.

      They provide a strong and logic experimental strategy with adequate validation comparing multiple strains with disease onset differences and human tissue. The result was to identify GLUL as a potential biomarker of prion specific disease progression without any overlap with other NDs sharing pathophysiology.

      The finding is interesting to the field but most importantly the established transcriptome profiles available will by of great use for future use from relevant basic research and also translational studies.

      The presented study is an important addition to the field without any other comparable datasets regarding skeletal muscle analysis in CJD.

      Any novel biomarker for progression of prion disease is extremely important and its potential link with pathogenesis would be of paramount importance.

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    3. EMBOpress 04 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript by Caredio et al is a follow-up of their previous work (Sorce et al,PloS Pathogens 2020), wherein they conducted genome-wide transcriptomic analyses on the brains of prion-infected mice throughout the course of the experimental disease. In the present study, the authors extended their analysis to extraneural tissues of prion-infected mice, including hindlimb skeletal muscles, spleen and blood. Their key findings indicate upregulation of the glutamate-ammonia ligase (GLUL) gene in the skeletal muscle, a pattern also observed across different mouse prion strains and notably in human cases of sporadic CJD, albeit in a relatively small cohort.

      A major limitation of the manuscript is the absence of evidence demonstrating the presence of prions or prion-seeding activity, and the lack of correlation with transcriptomic analyses, in any of the extraneural tissues and different timepoints. This omission is surprising given its inclusion in their initial publication in PloS Pathogens. Particularly concerning are the mouse experiments, where intracerebral inoculations were performed, suggesting potential presence of prions in terminal nerve endings and then muscles only at late stage of the disease, due to anterograde axonal transport. The reliance on three prion strains (22L, ME7, and RML) that replicate extraneurally limits the relevance of the study. Including at least one strain with limited or no capacity for extraneural replication could help distinguish whether observed transcriptomic alterations are directly linked to prion replication or are indirect consequences, particularly within the brain. This would also have prevented a significant misinterpretation in the discussion section. The authors delve into the alterations observed in the spleens of affected mice at the terminal disease stage. They attribute these alterations to the consequence of intracerebral inoculation, suggesting a delayed accumulation of prions in lymphatic tissues compared to oral or intraperitoneal inoculation routes. However, considering the high volume and dose inoculated (30 µL 10%), there is likely spillover from the brain, resulting in an intravenous-like inoculation concurrent with the intracerebral infection. Consequently, prion replication occurs rapidly in the lymphoid tissue. Given this, the tardy transcriptomic alterations observed in the spleens become even more surprising.

      Information regarding the statistical tests used to compare GLUL levels in Figures 3 and 4, and whether these tests are parametric or not, is missing. Given the relatively low differences observed and the substantial SEM, clarification on statistical methods is imperative for interpreting the results accurately.

      Providing details on the types of CJD analyzed, such as genotype, strain type, and age, would enhance the manuscript's comprehensiveness. While this information may be available in supplementary Table 8, we had no access to it.

      Minor point: in the introduction, it may be worth mentioning recent publications showing presence of prion seeding activity in many extraneural tissues from humans infected with sporadic CJD and or vCJD, using RT-QuIC or PMCA assays.

      Significance

      Given the aforementioned concerns, the correlates between prion replication and the GLUL/glutamate-glutamine metabolism alterations are thus highly uncertain. This limits the general significance of the study.

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    Trim66 paternal deficiency causes intrauterine overgrowth
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    The concerted action of SEPT9 and EPLIN modulates the adhesion and migration of human fibroblasts
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    Alstr&#x00F6;m syndrome proteins regulate centriolar cartwheel assembly by enabling Plk4-Ana2 amplification loop in Drosophila
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      Referee #3

      Evidence, reproducibility and clarity

      Brunet and colleagues utilized expansion microscopy to identify the distinct localizations of Alms1a and Alms1b at the centrosome in transgenic flies expressing Alms1a-Tomato or Alms1b-GFP-6Myc. Their imaging results are of exceptional quality and include insightful observations and discussion. However, these experiments were exclusively conducted in the transgenic flies, and no evidence has been provided for the expression of endogenous Alms1b proteins. Moreover, the defect in centriole duplication was observed only when Alms1 was depleted via RNA interference, not through gene knockout. Although some discussion is provided to address this discrepancy, the evidence remains unconvincing. More robust evidence is necessary to support their findings.

      Major comments

      1. One of the primary observations is the defect in centriole duplication in the absence of Alms1. This finding was only observed with RNAi and not with gene knockout. The authors performed the RNAi experiments in Alms1-deleted cells (Alms1del3) and did not observe the defects in centriole duplication. Therefore, authors concluded that acute loss of Alms1 is responsible for centriole duplication in germline stem cells. However, it is still difficult for me to reach that conclusion with only this evidence.

      A. Could the authors provide the western blot and staining results of Alms1a and Alms1b proteins after RNAi and gene knockout?

      B. The most reliable and widely accepted method to determine the specificity of RNAi (whether it is an off-target effect or not) is through genetic rescue experiments. Could the authors provide rescue data? It would be great if the authors could show the rescue of centriolar signals of Plk4, Sas-6, and Ana2, in addition to centriole duplication.

      C. The authors failed to discriminate which gene is crucial for centriole duplication in GSGs due to the sequence similarity. Linked to the above point, could the authors show the rescue results with either or both Alms1a and/or Alms1b genes? If only one gene can rescue the centriole duplication defects, it would clarify the specific functions of Alms1a and Alms1b in this process.

      D. (Optional) Considering the results in the manuscript, the authors appear to have good techniques in genetic manipulation in flies. If so, generating transgenic flies of Alms1a and Alms1b tagged with a degron (e.g., dTAG or destabilization domain [DD]) to observe centriole duplication defects upon rapid protein degradation might be feasible to support their observations. 2. There were no results with endogenous Alms1a and Alms1b in the manuscript. Could the authors provide immunostaining results for endogenous Alms1a and Alms1b? If expansion microscopy is not available due to antibody specificity issues, standard confocal imaging would be sufficient. 3. In figure 3C and D, the authors noted measurements from 7 to 8 testes per group. It would be helpful to also know how many centrosomes were measured, as done in Figure 4C.

      Minor comments

      1. In figure S1, the orientation of the gene is not consistent between endogenous and transgenic Alms1. Could the authors make it consistent for readers to intuitively recognize it? Additionally, the promoter used for transgenic gene expression is not specified. Please provide this information as well.
      2. On page 5, the statement '~, whereas Alms1b is associated with post-duplication maturation of the centriole." needs revision. The authors observed strong Alms1b-GFP signals in the centrioles at the end of the SC stage or during meiotic division but did no observe any defects in centriole maturation at the current stages. Furthermore, Alms1b was not detected from rapidly duplicating centrioles in syncytial embryos and dividing neuroblasts (Page 6), making it making it hard to understand that that Alms1b has a role in post-duplication centriole maturation.
      3. In figure S2, the centrosome drawings are unclear (initially thought to be 'v' marks). Could a centrosome drawing be added to the legend for clarity?

      Significance

      ALMS1 is a well-known protein which is important for cilia formation in human cells. Recent research by Chen and Yamashita (eLife, 2020) highlighted its significance in centrosome duplication in Drosophila's germ line stem cells (GSGs). Brunet and colleagues' findings align with these previous studies but go further by elucidating the localization of Alms1a as a centriolar and pericentriolar material protein, and Alms1b solely as a centriolar protein, using expansion microscopy. Moreover, their research suggests that only acute, not chronic, loss of Alms1 leads to defects in centriole duplication, proposing that cells may develop compensatory mechanisms for Alms1 loss in GSGs.

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      Referee #2

      Evidence, reproducibility and clarity

      The study takes a look at the role of Alms1a and b in centriole formation in Drosophila tissues using genetics and microscopy approaches. Alsm1a RNAi was previously shown to lead to loss of centrioles on the male germ line, but the molecular mechanism of how Alsm1a provides this function is not known. This is what this manuscript addresses.

      The general proposal of this manuscript is that Alsm1a is a key regulator of centriole formation in Drosophila tissues (embryos, male germ line and neuroblasts analysed). Alms1a is an inner PCM protein and functions downstream of PLK4 to drive procentriole formation.

      This is an interesting advance in understanding of centriole formation in flies. The authors managed to pull of beautiful expansion microscopy and produced images of centrioles both by immunofluorescence and electron microscopy. The data quality is very high, the quantifications lack a little behind in places. The manuscript would benefit from thinking about structure and presentation. The proposal that chronic loss of Alms1a (mutants) is well tolerated while acute (RNAi) is not is a bit puzzling. It is not impossible, but RNAi is not that acute either. It would be important to clarify this. To make sure there is no glitch in the tools, the newly generated alms1 deletions should be better characterised to clarify whether a compensatory mechanism exists, that upon chronic depletion rescues all phenotypes described by RNAi. There are also ways to test whether the Alsm1a fluorescent transgene introduce confounding effects, which if tested would be an improvement (see below). The genetic and immunofluorescence analysis got the authors quite far, the manuscript lacks biochemical analysis to strengthen the proposed molecular mechanism and clarify whether key and easy to predict interactions of Alms1 actually do occur. This would be a big plus but is not limiting. There are also inconsistencies that need clarification, for instance the title of figure 6 is that Alms1 proteins act downstream of Plk4, yet the model in the discussion proposes that Alsm1 stabilises Plk4 which does not fit and hinges on quantification of Plk4 levels that is perhaps currently not robust enough. The statement that Alms1 is required for PLK4 activity is too strong based on the data provided or provide data on PLK4 activity. The attempt to check what is going on in other systems is appreciated, in RPE cells Alms1 comes in only after 120nm elongation. Some of the quantifications could be done more robustly, using ratiometric analsysis rather than directly comparing intensity levels. Referencing in the manuscript and discussion should be improved.

      Specific points

      1. Provide a thorough characterisation of the alsm1 deletions generated using qPCR to measure RNA levels in the flies. Provide whether the alleles are viable and fertile and clarify all genotypes in the manuscript. Can the mutants suppress the Plk4-ND overexpression effect?
      2. BamGal4 alms1a RNAi, SCs loose centrioles, those that keep centrioles, have Alms1a, but fail to initiate procentriole formation. To strengthen this view please provide nos-Gal4 alms1a RNAi, Alms1a-Tomatoe data showing that now Alms1a-Tomato is not present accept on the mother centrosomes in GCS, ruling out anything unpredicted happens by introducing the Alsm1a-Tomatoe.
      3. Quantifications, measure fluorescence ratios (e.g. Figure 3 C,D quantify the ratio of Asl/PlP to Bld10, similarly for PLK4-ND in the relevant figure).
      4. A model for Alms1a in the style of Figur5A would be great.
      5. What happens to Alsm1a upon Plk4 inhibition? Experiments like this could strengthen the validity of the hierarchy of events proposed.

      Other comments

      The organisation and presentation should be improved. The figures reorganised to group what belongs together, I would suggest moving human RPE cell analysis to supplementary data and bring the beautiful EM of BamGal4-Alms1 RNAi, Alsm1a-Tomatoe into the main manuscript.

      In the deletions asterless levels are reduced in SC but not in the testis tip, why is that?

      Conclusion: "while Alms1b is only detected on mature centrioles as it is absent from rapidly duplicating centrioles of syncytial embryos or from duplicating centrioles of dividing neuroblasts." Perhaps add, Alms1b when expressed.

      BamGal4 alms1a RNAi, SCs loose centrioles, those that keep centrioles, have Alms1a, but fail to initiate procentriole formation. To strengthen this view please provide nos-Gal4 alms1a RNAi, Alms1a-Tomatoe data showing that now Alms1a-Tomato is not present accept on the mother centrosomes in GCS.

      The idea to compare nos-gal4 and bam-gal4 driving Alms1a RNAi is good. Providing a scheme of when these are expressed in the male germ line will help illustrate the experimental strategy. BamGal4 Alsm1a RNAi leads to loss of centrioles in SCs

      Alms1b (CG12184) is according to published RNAseq data not expressed in neuroblasts, so it makes sense they do not observe (Knoblich lab data), which could be cited here: "in agreement with RNA-seq data showing low expression of alms1b in neurons and glial cells (Li et al., 2022)."

      Fig S5 what cells were analysed by TEM?

      Fig S6 monochrome images confirm what is what.

      Figure 4 A for clarity it would be helpful to provide landmarks, marker for stem cells (Vasa) or the Hub to be able to understand what we are looking at. Same for Fig 4E, Mira or Dpn? The DAPI staining does not allow in the images provided to identify NBs.

      Figure 5 For the fluorescence profile plots it would be nice to see the average plus the standard deviation of the signal in the quantifications.

      Figure 6 D is not convincing, how were the dots visible chosen for the quantification?

      Figure 1C. Quantification of protein levels is not provided (is this because the expanded ultrastructural approach is not linear precluding quantification?)

      Figure 2 B radial dimensions, it would be great to show the sample average and standard deviation.

      I don't find figure S2 helpful

      Significance

      Understanding the process of centriole duplication is an important topic that should be relevant to a broader cell biological community especially since the proteins of interest have disease relevance.. This study provides new insights into how Plk4 dependent centriole duplication takes place in Drosophila.

      The manuscript is strong on the microscopic images both immune fluorescence and TEM. The function of Alms proteins is dissected genetically no biochemical analysis is provided, which is a limitation. Another limitation currently is the uncertainty about the discrepancy between the RNAi and the mutant results. If the mutants are confirmed and technical issues can be ruled out the finding that a compensatory mechanism exists that suppresses chronic loss of Alms1 proteins could bar very interesting.

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      Referee #1

      Evidence, reproducibility and clarity

      Much is known about the centriole duplication machinery and the centriole duplication cycle thanks to key screens performed in C.elegans in the past 20-25 years and subsequent work in Drosophila or human cells. It has been proposed that the core duplication machinery consists of 5 proteins implicating Cep192-PLK4-SAS6-SAS5 and SAS4, with specific variations according to the model system or cell line studied. Recently, a role for ALM proteins in the duplication of centrioles in the Drosophila male germ line has been reported, but in this study the mechanism involved has not been identified or described.

      In the Brunet study, the authors show a role for Alm proteins in centriole duplication in different tissues in flies- showing that these proteins have more a ubiquitous role in centriole duplication rather than a restricted role in the male germ line as initially described. This is already accounting for the novelty of this paper. However, this study goes well beyond previous studies as it proposes two very novel concepts. The first one is that Alm proteins can stabilize PLK4, the sole kinase implicated in centriole duplication, and so be responsible for maintaining kinase activity during a time window where daughter centrioles are generated. This is extremely interesting and makes a lot of sense and the data is very convincing. The second novel concept is that loss of Alm can have different consequences according to the- I do not even know how to call it- loss condition- leading to Alm deficiency. While I think this is quite novel, interesting and maybe even real, I think the authors conclude very strongly on the differences between a gene knock out or gene knock down conditions. I think that they may want to tune down their conclusions related to this part, as many more data would be required to conclude in this way.

      In other words, I think the paper is of high interest to a broad field of cell biology with interests in centrosome, cilia and the regulation of centriole duplication.

      Major points:

      1. I did not find a rescue experiment of the Alm deletions with the Alm transgenes.
      2. If I understood the authors correctly, Alm def compensate for centrosome duplication by a yet unknown process, while Gal4-induced depletions do not. First, calling Gal4- induce RNAi- acute depletion is not correct. This is certainly not acute and so another designation has to be found. Acute is something like a degron such as Auxin or dTag where the protein is degraded in a very acute manner. RNAi targets the mRNA, so if the protein is already made, it will not suffer from the RNAi treatment. Second, are the authors sure that either their crispr strategy did not generate any other knock out- hence the essentiality of rescuing these mutations. Or alternatively, are they sure about their RNAi conditions? So can they add the RNAi conditions on the background of their deficiency and see that nothing changes? Third if depletion through RNAi indeed leads to a more evident role of Alm proteins, one is expected to see this over time. Can they do a clone-using an FRT site recombined with their Alm mutation, so that the initial cell divisions does not contain Alm, and so it is expected to fail duplication, which may be overcome with time? So a large clone might have progeny with cells with centrosomes (the young ones) and without (the older ones). Can they show that RNAi depletion in cells that will generate sensory cilia- these are not assembled? Because I am assuming that the mutants are not uncoordinated...
      3. If they think that Almdef flies compensate for Alm loss - can they analyse levels of PLK4, SAS6, Ana2 and SAS4 in the mother centrioles?

      Minor points

      1. Some figures (the majority) lack scale bars.
      2. I do not think that one can consider centrioles that are not in rosettes to be made de novo. They might just have disengaged. The "novo" centriole should be removed. Actually, PLK4 ND generates extra centrosomes, this is sufficient.

      Significance

      The article by Brunet and colleagues investigates the role of ALMs proteins in centriole duplication. Centrioles are the core constituents of centrosomes and as such contribute to microtubule nucleation. Centrioles can behave as basal bodies, providing essential function sin cilia assembly and function.

      Here the authors have use Drosophila to characterize the role of Alm proteins. They show that 2 isoforms with distinct behaviour are expressed with different localizations. Further, through the assessment of different tissues and loss-of-function conditions, they propose a role for Alm proteins in centriole duplication.

      Overall the paper is very well written and easy to follow.

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    The role of Med15 sequence features in transcription factor interactions
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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, the authors performed extensive genetic analyses in yeast on the functions of Med15 regions under multiple stress conditions, linking cell growth phenotypes, gene expression and protein-protein interaction. Med15 is an activator-contacting subunit of the Mediator complex and the functions of yeast Med15 have been extensively studied. In particular, the authors attempted to understand the roles of a poly-Q region (Q1), its length and composition in stress response phenotypes, Med15-mediated gene expression, and interaction with transcription factor Msn2. Results from this work are consistent with several previous studies and revealed some new insights. The authors concluded that robust Med15 activities required the Q1 tract and the length of Q1 tract modulates activity in a context-dependent manner. While the study is well executed and the conclusions are generally sound, several concerns listed below should be addressed and some clarifications should be made.

      Major comments:

      1. Abstract, "We also observed that distinct glutamine tracts and Med15 phosphorylation affected the activities of the KIX domain". Fig. 1 shows the effects of KIXQ2Q3 deletion and p7 phosphor-dead mutant under Acetic acid and Ketoconazole treatment, but does not demonstrate that these domains or phosphorylation affects KIX domain activities.
      2. Is it known that Med15 is dephosphorylated under stress conditions other than osmotic challenge? Another explanation for D7P/D30P mutant results (Fig. 1B) might be that Med15 phosphorylation in unstressed cells is important for certain types of stress response (acetic acid and Keto). In contrast, the observation that D7P has no effects on osmotic stress (Fig. 1B) might suggest that phosphor-Med15 is dispensable for function. Some explanations on how to ascertain the roles of Med15 phosphorylation would be needed.
      3. Fig. 4, what is the rationale of analyzing basal expression rather than activated expression of Gcn4 and Msn2 dependent genes? Gal4 and Hap5 dependent genes could be measured as well, in order to complete the gene expression-phenotype correlation that the authors strive to make in this paper.
      4. Fig. 4, Error bars should be provided on gene expression analysis. Gcn4 and Msn2 target genes should be highlighted separately to facilitate comparisons.
      5. Results from Fig. 4 and 5 indicate that Spacer-Q1 and 12PQ-Q1, being the strongest interactors to Msn2, actually reduced HSP12 expression (a known Msn2 target gene). Some explanations would be needed. Page 12 Discussion paragraph 2 "Q1 substitutions that interfered with coiled-coil propensity had no effect on TF activity" would need to be revised and to include some discussions on this result.
      6. Fig. 5C, additional explanation is needed on how interaction rank is determined and how error bars are obtained.
      7. The idea that Q1 provides a molecular hinge to facilitate intramolecular interactions is interesting, but sounds like a possible scenario without further evidence. Are there any published structural studies on Med15/Mediator complex that might support this idea?

      Minor comments:

      1. SC-HLUM and SC-HLMU is used interchangeably in the legend and text. Please keep consistent. Explanations for these acronyms are not found in the Methods.
      2. Fig. 2, 3. AcOH should be Acetic acid, to be consistent with Fig. 1.
      3. Fig. 3B, error bars should be provided for growth measurements.

      Significance

      This work provided a detailed analysis on the roles of a specific poly-glutamine region in yeast Med15 functions and regulation. One conceptual advance of this work is that the structural flexibility rather than the sequence itself of Q1 tract proves to be critical for Med15 function. The ability to correlate Med15-Msn2 interaction with gene expression analysis demonstrated some technical novelty, given the power of genetic manipulation in yeast.

      Med15 is a key Mediator subunit contacting several sequence-specific transcription activators. Its interaction with a number of transcription activators in yeast such as Gcn4 and Gal4, was previously studied as referenced in this manuscript. This manuscript first provided a quite comprehensive genetic mutational analysis and confirmed several findings in previous studies. The identification of critical Med15 regions for acetic acid response (and Hap5-dependent gene activation) and the analysis of Msn2-Med15 interactions appear to be novel. Researchers interested in eukaryotic transcriptional regulation would benefit from reading this study.

      Field of expertise of this reviewer: mechanisms of transcriptional regulation, genetics, nuclear organization and function

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      Evidence, reproducibility and clarity

      Summary:

      The Mediator complex, a multicomponent complex, regulates the interaction between transcription factors and RNA polymerase II using protein interactions. In particular, Intrinsically Disordered Regions (IDRs) with in Med15. Copper and Frassler made extensive mutations to the three IDRs that are characterized with high glutamate content (poly-Q), the KIX domain which interacts with transcription factors and the MAD which interacts with the rest of the Mediator complex. The three poly-Q repeats are adjacent to Activator Binding Domains (ABD). The impact of mutant Med15 was measured with growth assays, co-IPs with a transcription factor, and transcriptional activation of a reporter during different stresses. Med15 is particular important in stress responsive transcription rather than basal transcription because in yeast it is nonessential. It can be repress and activation translation of genes. Using a series of internal deletions and substitutions impact of the mutations was tested on by measuring growth of strains, expression of Med15 regulated genes, and interaction with Msn2, a transcription factor that regulates to various stresses. This work adds to the body of research confirming that multiple weak/ transient interaction domains regulate Med15 function.

      Major comments:

      1. Without knowing the protein levels of the different mutants, it is difficult to contribute deletions of different regions with phenotypes measured. Various internal deletions decrease Med15 protein levels (Jedidi et al. 2010) while other affect the integrity of the Mediator complex. This study did not measure mRNA or protein levels of their mutants. However, (Jedidi et al. 2010) used Myc-tagged Med15 which affects regulation of Med15 via SNF1 (Gallagher et al. 2020). In another study, Med15 was N-terminally tagged and protein levels of some deletions increased (Herbig et al. 2010). It's unknown if other tags such as HA, TAP or FLAG affect Med15 regulation via SNF1. This study used untagged Med15 expressed from the native promoter which avoids these complications. It's also unknown if the differences in Med15 deletions are from reduced transcription, translation, or protein stability. There are commercial antibody that may work (https://www.genetex.com/Product/Detail/Gal-11-S-cerevisiae-antibody/GTX64110). There are several commercial antibodies to human Med15 but the cross reactivity has not been tested.
      2. Quantification with ImageJ on spot assays is difficult because once growth has maxed out on the dense spots there is no resolution. Using more dilute spots is challenging because colony size is affected by the nearby colonies. The error bars are the mutants are large. Can quantitative growth curves be carried out in flasks or an automatic plate reader for better quantification?

      Minor comments:

      1. Why were the stress conditions chosen in figure 1B? These are only a subset of conditions that the med15 deletion is sensitive to. Aside from acetic acid the phenotypic profile of each deletion is similar. The bigger the deletion, the more severe the growth defect. The keto plate appears under loaded by comparing the number of colonies in the third dilution on the keto plate and the fourth spot on the YPD plate in the BY4742 (MED15 wild-type strain). Does keto lyse cells? Or was there that much variation between mutants? Perhaps the dose of keto needs to be calibrated. In figure 2B it looks like wildtype growth in keto was 70% of untreated growth.
      2. Figures 1C and 1D are not discussed in the results. The authors should remind what the hGR assay measures when discussing the results. How is it different from the GAL4 transcriptional reporter?
      3. In the D to A mutants some appear to be required for acetic acid tolerance. What was the pH of the media?
      4. The labels between Figure 1 and 2 are inconsistent. 90 mM acetic versus 80mM AcOH, YPGal versus YPGalactose, SD+LKHU versus SD+KLUH. The mutants on 0.97M NaCl at 37oC from figure 2A grew more than 0.9M NaCl at 38oC. Also, in the text it says 37 oC.
      5. Is the MED15 strain BY4742? In Figure 1 was it also transformed the pRS315? How was the plasmid maintained on the plates, specifically YPD?
      6. Genes such as GAL and URA3 should in italics.
      7. In the split Ub assays, was wildtype Msn2 and Med15 also present?
      8. There is inconsistently naming of media in Media and Phenotype Testing section. The media is called synthetic complete media is labeled SC-URA or SC-LEU and at times in Results its called SD+K or SC-HULM. Is SC with all amino acids and SD without any amino acids?
      9. The plasmid names in the supplemental table don't match the ones labeled in the figures.
      10. Why was ALG9 used for normalization of qRT PCR?
      11. The background of the strains is confusing. There appears to be two different med15 knockouts OY320 and JF1368. Which ones were used in which experiments? Some of the trains have a trp1 auxotrophic which affects stress response on it's own (González et al. 2008; Schroeder and Ikui 2019).

      Significance

      • General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? Extensive mutational analysis of Med15.
      • Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...). This work confirms numerous other studies on the contribution of various Med15 domains on function.
      • Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? Incorporation of human domain substitutions could influence how people outside the field would interpret how Med15 interacts with transcription factors.
      • Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Expert in using yeast genetics and natural genetic variation to address underlying mechanisms of stress response to environmental toxins with a particular focus on transcription factors and TORC1.
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    4. EMBOpress 03 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      Major Comments

      The authors show that the amino acid content and length of Q1 affects transcription activity in a media-dependent way in a construct that includes Q1-ABD1 and a tailing Q/N rich region (Q1R). Briefly, different media conditions used as proxies for specific target TF activities varied in their sensitivity to the Q1 sequence content. However, the reason for this variation between target TF activities is not addressed, so the observations seem more anecdotal than insightful. One test performed suggests some of the Q1 sequence dependence may be due to changes in AD-ABD interactions, but this interesting possibility is not investigated further.

      A split-ubiquitin two-hybrid assay, meant to detect interactions between Msn2 TAD and Med15-Q1R, showed clear Q1 sequence/composition-dependence when changed from polyQ tracts. In particular, replacement with leucine-rich tracts (12L and RvHs) significantly reduced interactions (as inferred from growth requirements in Fig 5B). Q1 consisting of just 10 spacer residues, 0 to 24 Q residues, or PQ repeats all had quite similar results suggesting retention of some Msn2 and Med15 interactions. Replacement with a helix-forming sequence from NAB3 gave intermediate results. Again, no explanation was offered for the observation but it seems probable that the NAB3 Q1 system is no longer reporting on Msn2 Med15 interactions.

      The manuscript presents extensive assays, but a lack of consistency in conditions and constructs tested makes comparing different assays difficult. In particular, it would be valuable to have NAB3-Q1, FrHs-Q1, and RvHS-Q1 tested under conditions of high salt as that is indicated to be the Msn2 target condition (e.g. an additional result that would be presented in Fig 3B); this would be valuable to compare to the two-hybrid results. The relationship between Q1 polyQ length and Msn2 TAD-Med15 ABD1 binding is not clear from this assay as all had similar growth on the plates. A possible explanation for the inferred reduction in TAD-ABD1 binding in the leucine rich Q1 constructs is that this highly hydrophobic linker itself binds to ABD1 and is therefore self-inhibitory. There is also the unexplored/not discussed possibility that NAB3, 12L, and RvHs have off-target interactions that disrupt the TAD-ABD1 interactions.

      The framing of the study and the title of the manuscript strongly suggest that there might be a relationship between coiled-coil formation and transcription activity. This is the basis for selection of many of the Q1 sequences tested, with the premise of either increasing or disrupting coiled-coil structure. These 'propensities' are quantified in Supp Fig 1; however, a significant limitation of this interpretation is that these propensities are bulk properties that presume formation of homo-dimers or homo-trimers, a situation that is not shown to be relevant for Med15 at a promoter. This means that Q1 is potentially only one of the multiple partners required for coiled-coil formation. So even if a tested sequence has high coiled-coil propensity, that may not be the case in the actual biological systems at play here. Another consideration to be entertained is how different solvent conditions (different media) may affect coiled-coil propensity. An unanswered question is whether Q1 may form coiled-coil structure either with other regions of Med15 and/or with other Mediator subunits or even other co-factors entirely. This is a question implied by the title of this paper, but the data presented address neither intra- nor inter-molecular interactions of the polyQ regions (the two-hybrid study is designed to probe the ABD-AD interactions).

      A final proposed hypothesis was that Q1 acts as a hinge in a way analogous to what was reported for the huntingtin protein (ref 7). This is an attractive model but remains untested in this work. In particular, the Med15-Q1R construct used does not have multiple ABDs that would potentially be brought in close contact, so the results here cannot be interpreted as analogous to the huntingtin hinge model. Minor Comments:

      Please explain the choice of the 10-residue spacer instead of a 12-residue spacer.

      Page 14: "We observed that Q1 substitutions with increased coiled-coil propensity (Supplementary Figure 1) diminished TF activity while Q1 substitutions that interfered with coiled-coil propensity had no effect on TF activity (Fig. 3, 4), suggesting that the flexibility of the sequence is an important feature." There was no demonstration that those sequences in this context form CCs. There's no evidence of what is actually being modulated whether it's length, flexibility, or ability to interact with other regions of Med15 or even with other co-factors.

      Page 15: "We confirmed that Msn2-dependent activities of Med15 are encoded by the region containing the Q1 tract and ABD1 (aa 116-277) and found that the KIX domain alone could also mediate an interaction with Msn2 (Fig. 5). This contrasts with the Gcn4- or Gal4-dependent growth or stress responses which are the result of additive interactions with Med15 that are characterized by weak, highly dispersed, multivalent interfaces. While it is not yet entirely clear if the interaction with Msn2 is similarly multivalent, we have shown that either the KIX domain alone or the Q1R region alone of Med15 was sufficient with no evidence of additivity." These statements are unsupported. While Gcn4 and Gal4 transcription activity has been shown to depend on multiple AD-ABD interactions, none of the data reported here shows that Msn2 does not (as is stated here, which undermines the "contrasts" argument. Further, based on the assays presented in Figure 1B, Msn2, Gal4, and Gcn4 behave similarly for the various Med15 constructs.

      Page 16: "In all instances TF activity was reduced in the absence of the Med15 Q1 tract." This seems false based on the data presented. Met10 activity appears to have increased in Figure 4A.

      Page 16: Reference to Figure 2C and Figure 2B are mislabeled. Should be Figure 2D and 2C, respectively.

      Page 17: "The fact that residues at Q1 were not functionally constrained to be glutamine residues suggests the Q1 tract is not an interaction motif participating directly in protein-protein interactions." This is completely unsupported. There are no data presented that address interactions between Q1 and anything else.

      Figure 2: Not clear which assays were at 30{degree sign}C vs 22{degree sign}C as they are not labeled in the figure. In Figure 2A, the label med15 should be med15Δ.

      Figure 4: Interpretation of these results seems limited by only reporting YPD media conditions. May be helpful to include the conditions reported in Figure 1.

      Figure 6: It is not clear what some elements of this figure are meant to represent. Is saw tooth always polyQ? or Is ABD1 always blue and ABD2 is always red. What then are the loops? The general premise of this figure does not seem to be supported by the actual experiments performed.

      Supp Figure 3: "K is the Med15 fragment encompassing the KIX domain, aa 1-277." This aa range is KQ in the main text. Either the residue range is wrong, or the label is wrong.

      Significance

      This manuscript addresses an interesting topic. There appears to be a disconnect between the stated motivation and what was actually done. The large array of assays and conditions are difficult to compare, leaving the reader with a feeling that the authors have catalogued a lot of possibilities but that no generalizable or unifying insights are at hand. The attempt to present a model (Figure 6) is difficult to parse and is not directly supported by the data presented. Addressing the issues raised here could result in a work that is useful to the specific field of Med15 structure and function but of limited use at the moment to a wider audience.

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    Recruitment of the m6A/Am demethylase FTO to target RNAs by the telomeric zinc finger protein ZBTB48
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    1. EMBOpress 01 Jun 2024

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      The authors do not wish to provide a response at this time

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      Referee #2

      Evidence, reproducibility and clarity

      In the manuscript by Nabeel-Shah et al. the authors identify ZBTB48 as a novel interactor of FTO. They show that ZBTB48 helps recruiting FTO to mRNA as well as the noncoding RNA Terra. Their results further suggest that this recruitment is required for FTO to demethylated m6A and m6Am RNA modification in target RNAs. This affects cellular rates of RNA turnover. Furthermore, the mechanism is involved in repressing colorectal cancer cell growth.

      Overall, the authors present a new role of ZBTB48 in m6A and m6Am mediated RNA metabolism. They also suggest a nice model of ZBTB48 action, via the recruitment of the demethylase FTO. These findings will be of interest for the general RNA community and might be also relevant for cancer treatment. However, I have some concerns about the quality and analysis of the obtained data, especially the iCLIP and miCLIP experiments. The concerns are detailed below and should be addressed before publication.

      Major concerns:

      1. Figure 1B) I think that the results shown in the autoradiograph are not very convincing and suggest that the purification of ZBTB48 is not very clean. The radioactive signal covers the lane from 50 kDa to 200 kDa. The ZBTB48 alone is running around 80 kDa. If the purification is specific most of the signal should be above 80 kDa. Maybe it helps to also use higher RNAse concentrations: Having very short RNA pieces will allow to evaluate specificity of the purification, since protein-RNA complexes will just a bit above the size of the protein. This also applies to Figures S1E,F.

      This concern could also apply to the generated iCLIP libraries and indicates that at least part of the obtained reads does not originate from ZBTB48 crosslinked RNA. The validation of protein-RNA interactions with RIP shown in Figure S2E supports the quality of the iCLIP data. Here some control RNAs should be analyzed to show that the RIP is not unspecifically enriching any RNA. 2. Regarding the co-occurrence of m6A sites as well as FTO and ZBTB48 binding sites shown in Figures 2B, C, F and G. The CLIP signal is a lot affected by crosslinking bias and read mappability. Therefore, to make these results more convincing it would be important to include additional iCLIP datasets (published other RBPs) for comparison. 3. Regarding Figure 2D and related analyses: I very much like this experiment and the results obtained here! I just wondered where the remaining reads go in the ZBTB48 knockdown. The introns? Maybe this becomes clearer in the meta profile representation used in Figure 1F.

      For me the changes in the 5' UTR look most dramatic. Maybe this means that ZBTB48 is most important for recruitment of FTO to m6Am sites. Therefore, I think it would be good to differentiate the analyses in the remainder of the manuscript for m6A and m6Am sites. I first step would be to treat sites in the 5'UTR separate from the CDS and 3'UTR sites in the following analysis. 4. I have some concerns about the analysis of the miCLIP data. In Figure 3A antibody crosslinking in all conditions appears similar. Yet in panel B there seems less signal for FTO and ZBTB48 overexpression in all areas. Have there been more reads generated for the GFP control? Where is the rest of the reads going? I think it would be required here to identify peaks that significantly change between the conditions. Then ask do those peaks coincide with DRACH and were are they located. Also, in the Genome browser pictures the signal is going down at all locations. Why is that? Usually, miCLIP generates a lot of background peaks. These should be unchanged. 5. I am a bit confused by the author's interpretation of the results shown in Figure 5E. For me this plot shows that target transcripts are less downregulated and less upregulated than non-targets? Basically they are less regulated overall. In this context I also think that the representation in of the mean in figure 5E and F is misleading. Data distribution should be visible as violin or boxplot.

      Minor points:

      Figure 1D) I think the legend in the panel is confusing and does not add information. Especially since its in a different order than the categories on the y-Axis.

      Figure S2D) I wondered if the authors controlled for mappability of reads when picking random sites. How do the authors account for that in iCLIP there will be less reads in introns compared to exons?

      5E,F boxplots would be more suitable than barplots.xx

      Figure 2I: Please do not use "+ve"

      Figures with Microscopy pictures of cells have no scale bars or way too small.

      The model that is shown in figure 7 is somehow misleading as it shows FTO binding only to ZBTB48 and not to the RNA.

      Significance

      Overall, the authors present a new role of ZBTB48 in m6A and m6Am mediated RNA metabolism. They also suggest a nice model of ZBTB48 action, via the recruitment of the demethylase FTO. These findings will be of interest for the general RNA community and might be also relevant for cancer treatment. However, I have some concerns about the quality and analysis of the obtained data, especially the iCLIP and miCLIP experiments. The concerns are detailed below and should be addressed before publication.

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    3. EMBOpress 01 Jun 2024

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      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript, Nabeel-Shah et al. identified that the telomeric zinc finger protein ZBTB48 help recruit FTO onto target RNA, including mRNAs and the telomere-associated regulatory RNA TERRA, to achieve cellular RNA m6A/m6Am demethylation, thereby regulating cell biology such as tumour growth studied in this study. The biochemistry and molecular biology experiments were done in HEK293 cells, and the cell models for tumour growth was done in HCT116 cells. However, I have identified both major and minor concerns that, when addressed, could further strengthen the findings and enhance the impact on the field.

      Major concerns

      1. Regarding the ZBTB48/FTO targets and m6A/m6Am level that are regulated by ZBTB48/FTO axis. Wei et al Molecular Cell 2018 (PMID: 30197295) (Figure 1B) quantified the m6A/m6Am levels upon knockdown of FTO in HeLa, HEK293, and 3T3-L1 cells, and found that the m6A/m6Am levels are generally mildly (10-20%) yet significantly upregulated on poly(A)+ RNAs. Here shown in the Figure 4A in this manuscript, the authors show that (1) siFTO and siZBTB48 led to ~2-3 fold upregulation of m6A and m6Am levels using total RNAs (dominant by rRNA in the population), and (2) that the m6A and m6Am levels are similar between siFTO and siZBTB48. Regarding (1), can the authors explain the discrepancy? This point is also relevant to the m6AIP-qRT-PCR results in this manuscript. Regarding (2), does this result suggest that ZBTB48 helps FTO to demethylate nearly all its targets, rather than a subset?
      2. Considering the significance of how FTO achieves target specificity, can the author anticipate the extent of applicability of the proposed model? Does the interaction between ZBTB48 and FTO also exist in various human and mouse cell lines? If confirmed, this discovery would hold substantial value for the field. This interaction at least needs to be confirmed in HCT116 cells used for tumour growth model in this study.

      Minor concerns.

      1. The authors realised that knockdown of ZBTB48 does not change FTO levels, whereas overexpression of ZBTB48 leads to elevated FTO. It is unclear about the rationale behind overexpression studies?
      2. Considering the multifunctional nature of ZBTB48, it's important to disentangle transcriptional and post-transcriptional roles of ZBTB48 to draw conclusions. I appreciate the analysis conducted in this manuscript. Is it possible to overexpress an DNA-binding mutant of ZBTB48 or RNA-binding mutant of ZBTB48 proteins?
      3. In Fig 2B, the innet panel does not match the metagene profile regarding the difference.
      4. In Fig 5H, there is a lack of experiments for comparison, i.e. siFTO and o/e FTO.
      5. Page 3, "Genome-wide studies" should be "Transcriptome-wide studies".

      Significance

      Strengths: The biochemistry and molecular biology experiments are comprehensive and well designed. The analysis is robust, and the conclusions generally align with the presented data.

      Limitations: Cell line-specific and/or species-specific interaction?

      Advance: filling a gap in our knowledge of how FTO achieves target specificity.

      Audience: Basica research in the field of RNA modifications and RNA Biology.

      My expertise: Bioinformatics, gene regulation by RNA m6A modification

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    DNA binding site II is required for RAD51 recombinogenic activity in Arabidopsis thaliana
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    Identification of new drugs to counteract anti-spike IgG-induced hyperinflammation in severe COVID-19
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    Mapping protein-metabolite interactions in E. coli by integrating chromatographic techniques and co-fractionation mass spectrometry.
    4
    1. EMBOpress 30 May 2024

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      'The authors do not wish to provide a response at this time.'

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      Referee #3

      Evidence, reproducibility and clarity

      The authors expand upon a previous method (PROMIS) that was developed to detect metabolite-protein interactions from cell extracts through co-elution of proteins and metabolites in size exclusion chromatography. Here, the authors use ion exchange chromatography. By comparing PROMIS and IEX datasets, the authors increase the confidence of detected interactions being true hits. The addition of IEX data significantly improves the power of the method to identify previously known/predicted protein-metabolite interactions. The authors also purify two proteins identified by the method and experimentally validates their novel interactions with dipeptide metabolites.

      In general the paper is well written and provides a clear assessment of the two methods. The validation of two interactions is welcomed.

      There are some issues that could be addressed with better clarification:

      • While the two datasets for omniTICC appear to show good overlap, the two PROMIS replicates appear to have very little. Due to this low overlap, one of the metabolite interactions chosen for validation (dipeptide) was chosen by manually lowering the correlation cutoff of PROMIS as well as relying on two previous PROMIS datasets. Authors could comment on possible reasons for this low overlap.
      • Experimentally validating the effect of Val-Leu on the enzyme activity of FabF would be a very good addition, but is not crucial to the paper.

      Minor:

      Line 173: In STITCH the authors find 1012 known or predicted interactions, while their method finds 92 of these interactions. Authors could comment on limitation of the unbiased method which may lead to missing these interactions (for example, sensitivity of MS detection of low abundance metabolites).

      Minor: - Authors could comment on what are some drawbacks to using docking to estimate binding sites. Computational screening could be a powerful way to prioritize hits for validation, so could be worth a more detailed discussion here. - In figure 2 the color labelling of the experiments could be presented more clearly. - Authors could add in the text or methods how they calculate the Pearson correlation coefficient they use for determining significance. Overall the methods are well presented and the technical approach is very well described and impressive. In general the authors present the statistics such as likelihood over chance detection, in a way that helps to evaluate the accuracy of the separate and combined CF approaches.

      Some comments:

      • The PROMIS method and the omniTICC method are performed only in duplicate, where the two PROMIS experiments also differ in proteomics workflow. Could that be why the overlap between PROMIS experiments is so poor? Why not perform the experiments in biological triplicates?
      • Authors correct for poor replicate overlap by lowering the requirements of one subset of metabolites. What's the argument for not doing this with all metabolite subsets? Would this interaction have been discovered just by using PROMIS in three different experiments (i.e. more biological replicates)? The benefit of adding the IEX analysis is clouded by the poor overlap of PROMIS data
      • Line 353 - It would also be good to elaborate as to why other methods would be likely to miss this interaction. Is it because the authors method does not require the users to choose specific metabolites or proteins to focus on beforehand?
      • Authors could comment on whether any of the high confidence interactions were also been observed in different IP experiments with E. coli (such the Lip-SMAP method reported by Piazza et al., 2018).
      • Authors could comment on other ways to identify the potential binding site. For example, limited proteolysis of the protein in presence of metabolite has been used previously
      • There is massive interconnectivity between NMPs and ribosomal proteins. It would be good to comment on this. Do the authors believe these are true interactions? Could there be another reason for this cluster? Do the STITCH interactions also show that these proteins interact with so many NMPs?
      • Line 157 - The authors state that "isopropylmalate co-eluate with tens of proteins". This feels like a bit of an understatement if the actual numbers are: 92, 119, 303, 287

      Minor:

      • How did the number 1479 proteins come about? Are those detected in all 4 datasets? What about those detected in only some datasets? This information could be more clear

      Significance

      General assessment

      The paper is a welcome comparison of using two co-elution MS methods for identifying protein-metabolite interactions. It is clear that these types of interactions are important for modulating protein activity but are not well studied. The paper provides a clear workflow for both the experimental and data analysis portions of interaction proteomics. The relatively low number of validated hits could limit its significance outside the specialised field.

      Advance.

      The paper makes a conceptual advance in interaction proteomics. It is perhaps not unexpected that combining two different interaction proteomics methods gives more accurate target identification than a single method alone. The paper also strengthens the evidence that dipeptides play a role in regulation that may be conserved in bacteria and plants.

      Audience.

      The audience for this paper is likely researchers that are actively involved in the field of interaction proteomics. The link between dipeptides and feedback regulation has been developed by the group over a few papers, and this report provides further evidence. The paper also shows that a weak kinetic effect in vitro can actually lead to a significant effect in vivo, which is a very interesting finding that is a good point of reference for future in vitro validation efforts. Often the effect of metabolites in vitro is weak, which could lead to the (possibly false) conclusion that it is not relevant in vivo (see e.g. weak effects of metabolites on enzyme activity in vitro in a recent LiP-SMap paper (https://doi.org/10.1038/s42003-023-05318-8)

      Reviewer background:

      Reviewers are active in the field of interaction proteomics and have previously used the Lip-SMAP method as well as thermal proteome shift method.

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    3. EMBOpress 30 May 2024

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      Referee #2

      Evidence, reproducibility and clarity

      In this work, Wagner et al aimed to comprehensively map protein-metabolite interaction in E. coli. They do so by extending a previously developed SEC-based co-elution method with an IEX-based co-elution method. The results is a more extensive and robust protein-metabolite network. As a validation, selected predicted protein-metabolite interactions are confirmed at the level of binding, as well as enzyme kinetics and even phenotype.

      The key conclusions of the paper are mostly convincing, even more so because the authors provide a critical evaluation of the method. My only concern is that the results from the PROMIS replicates seem to be quite different (e.g. Fig 1h and Suppl Fig 1a). One wonders whether, given this apparent variation, two replicates are sufficient to define the protein-metabolite interactions with great confidence.

      The author took care to make all data (proteomics & metabolomics) publicly available and the methods are clearly described.

      The manuscript is well-written and the figures are clear, although Fig 1 would benefit from and explanation of the color coding in the legend. Personally, I feel that less emphasis on lumichrome would help focus the conclusion section.

      Significance

      This work is of high significance because it describes a method to comprehensively map protein-metabolite interaction that could relatively easily be applied to any organism. The work is of high quality and similar to work by for example Link et al (https://doi.org/10.1038/nbt.2489) or Piazza et al (https://doi.org/10.1016/j.cell.2017.12.006), but technically less challenging which increases its potential impact.

      Beyond these technical advances, global studies like these are a great resource for anyone working on the functional characterization of proteins. Often, a (predicted) protein-metabolite interaction can be a crucial lead to find the function of a protein.

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    4. EMBOpress 30 May 2024

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      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript, the authors demonstrate a strategy for uncovering metabolite-protein interactions, rooted in the concept of identifying co-fractionating metabolites and proteins through independent analyses of each fraction using untargeted proteomics and metabolomics. This approach is applied to E. coli protein lysates.

      The same research group has previously advocated for utilizing the simultaneous elution of metabolites and proteins as an indication of interactions, as seen in Luzarowski et al. (2019) and Veyel et al. (2017), where metabolite-protein interactions in yeast and plants were investigated, respectively. Here, a variation of the original proposed method (PROMIS) is introduced, involving an additional chromatography separation (ion exchange) alongside the original size exclusion separation proposed in PROMIS. By incorporating an extra dimension to reduce sample complexity, both experimental and data analysis efforts are effectively doubled, entailing the processing of 48 additional fractions for proteomic and metabolomic analyses, in addition to the 40 already included in the original PROMIS protocol.

      While previous studies have demonstrated the isolation of small molecule-protein complexes following ion-exchange based separation (Chan et al., 2012), the method described here does not introduce any fundamentally new concepts. However, it remains to be determined whether the addition of an extra separation dimension genuinely aids in accurately classifying new interactions. Although coincidental co-elution effects may be mitigated, there is a risk of disrupting genuine complexes through excessive handling of lysates.

      In my view, there are several points that require clarification:

      1. Line 138: There's an assumption that the metabolite profile will alter in IEX upon binding to proteins. While this might occur, it's not definite. Additionally, it's unclear why peaks associated with protein binding could also increase in intensity, and how this signifies a binding event.
      2. Lines 147-154: The most crucial dataset in this paper isn't adequately delineated here. We learn that by combining SEC and IEX, 1479 proteins and 58 metabolites are identified, but what about when only one separation method is employed? What advantages does using IEX provide?
      3. Line 170: Similar to point 2 regarding PMI.
      4. Line 174: To gauge whether the proposed strategy aids in accurately classifying new interactions, the authors examined if their predicted interactions also appear in the STITCH database. Out of the 994 PMI in the network, 92 were found in STITCH. I'm uncertain if STITCH is the most suitable metric for this assessment, given it likely hasn't been updated since 2016. How does this PROMIS-IEX protocol mirror known interactions in E. coli's central carbon metabolism, for instance, such as those detailed in this publication: doi: 10.15252/msb.20199008?
      5. Certain details of Figure 1 are challenging to grasp and inadequately explained in the figure legend. What do the colours of the heatmap in 1d represent?
      6. In Figure 1h, the proteins co-eluting with 2-isopropylmalic acid in the four separations decrease to 5 from tens of proteins, with only one known interactor of 2-isopropylmalic acid (LeuA) among them. Is this outcome favourable or unfavourable? Are the other four proteins false positives?
      7. Figure 2b: Why is this expected to work particularly well for NMPs? Is there a specific biological rationale behind it?

      Furthermore, among the classified interactions, two were corroborated through microscale thermophoresis and protein docking. One involved the enzyme FabF and the dipeptide Val-Leu. The decision to delve deeper into this pair likely stemmed from the prior focus on dipeptide-protein interactions, extensively discussed in Luzarowski et al.'s 2019 manuscript. The second interaction pertained to lumicrome and PyrE.

      Significance

      To summarise, this paper advocates for heightening the complexity of experimental and computational analyses in studying metabolite-protein interactions through co-fractionation techniques. While it's anticipated that increased separation would enhance results, I remain unconvinced that the data presented conclusively demonstrates this. Overall, I believe the proposed method possesses only a modest level of originality and novelty, as outlined at the beginning of my review. Nonetheless, the substantial experimental effort and data generation warrant publication following additional meticulous quality control evaluation.

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    The role of Med15 sequence features in transcription factor interactions
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    1. EMBOpress 30 May 2024

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    2. EMBOpress 30 May 2024

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, the authors performed extensive genetic analyses in yeast on the functions of Med15 regions under multiple stress conditions, linking cell growth phenotypes, gene expression and protein-protein interaction. Med15 is an activator-contacting subunit of the Mediator complex and the functions of yeast Med15 have been extensively studied. In particular, the authors attempted to understand the roles of a poly-Q region (Q1), its length and composition in stress response phenotypes, Med15-mediated gene expression, and interaction with transcription factor Msn2. Results from this work are consistent with several previous studies and revealed some new insights. The authors concluded that robust Med15 activities required the Q1 tract and the length of Q1 tract modulates activity in a context-dependent manner. While the study is well executed and the conclusions are generally sound, several concerns listed below should be addressed and some clarifications should be made.

      Major comments:

      1. Abstract, "We also observed that distinct glutamine tracts and Med15 phosphorylation affected the activities of the KIX domain". Fig. 1 shows the effects of KIXQ2Q3 deletion and p7 phosphor-dead mutant under Acetic acid and Ketoconazole treatment, but does not demonstrate that these domains or phosphorylation affects KIX domain activities.
      2. Is it known that Med15 is dephosphorylated under stress conditions other than osmotic challenge? Another explanation for D7P/D30P mutant results (Fig. 1B) might be that Med15 phosphorylation in unstressed cells is important for certain types of stress response (acetic acid and Keto). In contrast, the observation that D7P has no effects on osmotic stress (Fig. 1B) might suggest that phosphor-Med15 is dispensable for function. Some explanations on how to ascertain the roles of Med15 phosphorylation would be needed.
      3. Fig. 4, what is the rationale of analyzing basal expression rather than activated expression of Gcn4 and Msn2 dependent genes? Gal4 and Hap5 dependent genes could be measured as well, in order to complete the gene expression-phenotype correlation that the authors strive to make in this paper.
      4. Fig. 4, Error bars should be provided on gene expression analysis. Gcn4 and Msn2 target genes should be highlighted separately to facilitate comparisons.
      5. Results from Fig. 4 and 5 indicate that Spacer-Q1 and 12PQ-Q1, being the strongest interactors to Msn2, actually reduced HSP12 expression (a known Msn2 target gene). Some explanations would be needed. Page 12 Discussion paragraph 2 "Q1 substitutions that interfered with coiled-coil propensity had no effect on TF activity" would need to be revised and to include some discussions on this result.
      6. Fig. 5C, additional explanation is needed on how interaction rank is determined and how error bars are obtained.
      7. The idea that Q1 provides a molecular hinge to facilitate intramolecular interactions is interesting, but sounds like a possible scenario without further evidence. Are there any published structural studies on Med15/Mediator complex that might support this idea?

      Minor comments:

      1. SC-HLUM and SC-HLMU is used interchangeably in the legend and text. Please keep consistent. Explanations for these acronyms are not found in the Methods.
      2. Fig. 2, 3. AcOH should be Acetic acid, to be consistent with Fig. 1.
      3. Fig. 3B, error bars should be provided for growth measurements.

      Significance

      This work provided a detailed analysis on the roles of a specific poly-glutamine region in yeast Med15 functions and regulation. One conceptual advance of this work is that the structural flexibility rather than the sequence itself of Q1 tract proves to be critical for Med15 function. The ability to correlate Med15-Msn2 interaction with gene expression analysis demonstrated some technical novelty, given the power of genetic manipulation in yeast.

      Med15 is a key Mediator subunit contacting several sequence-specific transcription activators. Its interaction with a number of transcription activators in yeast such as Gcn4 and Gal4, was previously studied as referenced in this manuscript. This manuscript first provided a quite comprehensive genetic mutational analysis and confirmed several findings in previous studies. The identification of critical Med15 regions for acetic acid response (and Hap5-dependent gene activation) and the analysis of Msn2-Med15 interactions appear to be novel. Researchers interested in eukaryotic transcriptional regulation would benefit from reading this study.

      Field of expertise of this reviewer: mechanisms of transcriptional regulation, genetics, nuclear organization and function

      PeerReviewed
    3. EMBOpress 30 May 2024

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      The Mediator complex, a multicomponent complex, regulates the interaction between transcription factors and RNA polymerase II using protein interactions. In particular, Intrinsically Disordered Regions (IDRs) with in Med15. Copper and Frassler made extensive mutations to the three IDRs that are characterized with high glutamate content (poly-Q), the KIX domain which interacts with transcription factors and the MAD which interacts with the rest of the Mediator complex. The three poly-Q repeats are adjacent to Activator Binding Domains (ABD). The impact of mutant Med15 was measured with growth assays, co-IPs with a transcription factor, and transcriptional activation of a reporter during different stresses. Med15 is particular important in stress responsive transcription rather than basal transcription because in yeast it is nonessential. It can be repress and activation translation of genes. Using a series of internal deletions and substitutions impact of the mutations was tested on by measuring growth of strains, expression of Med15 regulated genes, and interaction with Msn2, a transcription factor that regulates to various stresses. This work adds to the body of research confirming that multiple weak/ transient interaction domains regulate Med15 function.

      Major comments:

      1. Without knowing the protein levels of the different mutants, it is difficult to contribute deletions of different regions with phenotypes measured. Various internal deletions decrease Med15 protein levels (Jedidi et al. 2010) while other affect the integrity of the Mediator complex. This study did not measure mRNA or protein levels of their mutants. However, (Jedidi et al. 2010) used Myc-tagged Med15 which affects regulation of Med15 via SNF1 (Gallagher et al. 2020). In another study, Med15 was N-terminally tagged and protein levels of some deletions increased (Herbig et al. 2010). It's unknown if other tags such as HA, TAP or FLAG affect Med15 regulation via SNF1. This study used untagged Med15 expressed from the native promoter which avoids these complications. It's also unknown if the differences in Med15 deletions are from reduced transcription, translation, or protein stability. There are commercial antibody that may work (https://www.genetex.com/Product/Detail/Gal-11-S-cerevisiae-antibody/GTX64110). There are several commercial antibodies to human Med15 but the cross reactivity has not been tested.
      2. Quantification with ImageJ on spot assays is difficult because once growth has maxed out on the dense spots there is no resolution. Using more dilute spots is challenging because colony size is affected by the nearby colonies. The error bars are the mutants are large. Can quantitative growth curves be carried out in flasks or an automatic plate reader for better quantification?

      Minor comments:

      1. Why were the stress conditions chosen in figure 1B? These are only a subset of conditions that the med15 deletion is sensitive to. Aside from acetic acid the phenotypic profile of each deletion is similar. The bigger the deletion, the more severe the growth defect. The keto plate appears under loaded by comparing the number of colonies in the third dilution on the keto plate and the fourth spot on the YPD plate in the BY4742 (MED15 wild-type strain). Does keto lyse cells? Or was there that much variation between mutants? Perhaps the dose of keto needs to be calibrated. In figure 2B it looks like wildtype growth in keto was 70% of untreated growth.
      2. Figures 1C and 1D are not discussed in the results. The authors should remind what the hGR assay measures when discussing the results. How is it different from the GAL4 transcriptional reporter?
      3. In the D to A mutants some appear to be required for acetic acid tolerance. What was the pH of the media?
      4. The labels between Figure 1 and 2 are inconsistent. 90 mM acetic versus 80mM AcOH, YPGal versus YPGalactose, SD+LKHU versus SD+KLUH. The mutants on 0.97M NaCl at 37oC from figure 2A grew more than 0.9M NaCl at 38oC. Also, in the text it says 37 oC.
      5. Is the MED15 strain BY4742? In Figure 1 was it also transformed the pRS315? How was the plasmid maintained on the plates, specifically YPD?
      6. Genes such as GAL and URA3 should in italics.
      7. In the split Ub assays, was wildtype Msn2 and Med15 also present?
      8. There is inconsistently naming of media in Media and Phenotype Testing section. The media is called synthetic complete media is labeled SC-URA or SC-LEU and at times in Results its called SD+K or SC-HULM. Is SC with all amino acids and SD without any amino acids?
      9. The plasmid names in the supplemental table don't match the ones labeled in the figures.
      10. Why was ALG9 used for normalization of qRT PCR?
      11. The background of the strains is confusing. There appears to be two different med15 knockouts OY320 and JF1368. Which ones were used in which experiments? Some of the trains have a trp1 auxotrophic which affects stress response on it's own (González et al. 2008; Schroeder and Ikui 2019).

      Significance

      • General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? Extensive mutational analysis of Med15.
      • Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...). This work confirms numerous other studies on the contribution of various Med15 domains on function.
      • Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? Incorporation of human domain substitutions could influence how people outside the field would interpret how Med15 interacts with transcription factors.
      • Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Expert in using yeast genetics and natural genetic variation to address underlying mechanisms of stress response to environmental toxins with a particular focus on transcription factors and TORC1.
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    biorxiv.org/content/10.1101/2024.05.04.592524v1