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Referee #2

Evidence, reproducibility and clarity

In this manuscript, the authors explore the requirement for doublecortin kinase Zyg8 in C elegans oocytes. Oocytes build meiotic spindles in the absence of centrosomes, and therefore unique regulation occurs during this process. Therefore, how spindles are built and its later stability are an area of active investigation in the field. Using mutant alleles of Zyg8 and auxin-induced degron alleles, the authors demonstrate that this kinase is required to negatively regulate outward pole forces through BMK1 kinesin and that it has other functions to still explore. Overall, I find that this study takes an elegant genetic approach to tackling this important question in oocyte biology. I have some comments to consider for making the MS clear to a reader.

Major Comments:

1. Although I like the graphs describing the altered angles of the spindles, it falls short in fully assessing the phenotype in a meaningful statistical way. Could the authors also graph the data to show statistical significance in the angles between conditions? Perhaps by grouping them into angle ranges and performing an Anova test? This is important in Figure 2E where it is not obvious that there is a difference.

2. The authors do not discuss the significance of the altered spindle angles which I think is an interesting phenotype. Would this be a problem upon Anaphase onset? What is known about spindle angle and aneuploidy or cell viability? Has this phenotype been described before in oocytes or somatic cells? Does depletion of other kinesin motors cause this?

3. How is embryo spindle positioning determined? It is not clear from the images that there is a defect so I'm not sure what to look for. Is there a way to quantify this?

4. In Figure 1, it appears that there are 2 spindles. Are these MI and MII spindles or ectopic spindles? How do the authors know which one to measure?

5. The authors show depletion of Zyg8 by western (long) and loss of Gfp (long and short), but don't do so for the acute treatment. I'm guessing this is because the Gfp tag is taken by the spindle marker. The authors should either demonstrate or explain how they know that the acute depletion is effective in removing Zyg8 protein.

6. In video 2, the chromosome signal is dimmer in the auxin treatment compared to video 1. Why is this? Is it just an experimental artifact or is there something significant about this? If it is because of video choice, consider replacing this one.

7. Please consider color palette changes for color-blind readership.

Significance

The strengths of this manuscript include use of multiple genetic approaches to establish temporal requirements of ZYG8 and which pathway it is acting through. Additionally, the videos and images make the phenotypes clear to evaluate. A minor limitation is that we don't know if the ZYG8 and BMK1 genetic interaction is a direct phosphorylation or not.

This MS is an advancement to the field of spindle building and stability, and is particularly relevant to human oocyte quality and fertility. Previous work has shown that human oocyte spindles are highly unstable, but it is challenging to dissect genetic interactions and to conduct mechanistic studies in human oocytes. Therefore, the work here, although conducted in a nematode, can shed light on mechanism as to why human oocyte spindles are unstable and associated with high aneuploidy rates.

Based on my expertise in mammalian oocyte biology, I am confident that work presented here will be of high interest to people in the field of meiotic spindle building, aneuploidy and fertility. It also will have broader interest to folks in the areas of kinesin biology, general microtubule and spindle biology.

Reviewer #1 (Public Review):

Summary:

In this work, Odenwald and colleagues show that mutant biotin ligases used to perform proximity-dependent biotin identification (TurboID) can be used to amplify signal in fluorescence microscopy and to label phase-separated compartments that are refractory to many immunofluorescence approaches. Using the parasite Trypanosoma brucei, they show that fluorescent methods such as expansion microscopy and CLEM, which require bright signals for optimal detection, benefit from the elevated signal provided by TurboID fusion proteins when coupled with labeled streptavidin. Moreover, they show that phase-separated compartments, where many antibody epitopes are occluded due to limited diffusion and potential sequestration, are labeled reliably with biotin deposited by a TurboID fusion protein that localizes within the compartment. They show successful labeling of the nucleolus, likely phase-separated portions of the nuclear pore, and stress granules. Lastly, they use a panel of nuclear pore-TurboID fusion proteins to map the regions of the T. brucei nuclear pore that appear to be phase-separated by comparing antibody labeling of the protein, which is susceptible to blocking, to the degree of biotin deposition detected by streptavidin, which is not.

Strengths:

Overall, this study shows that TurboID labelling and fluorescent streptavidin can be used to boost signal compared to conventional immunofluorescence in a manner similar to tyramide amplification, but without having to use antibodies. TurboID could prove to be a viable general strategy for labeling phase-separated structures in cells, and perhaps as a means of identifying these structures, which could also be useful.

Weaknesses:

However, I think that this work would benefit from additional controls to address if the improved detection that is being observed is due to the increased affinity and smaller size of streptavidin/biotin compared to IgGs, or if it has to do with the increased amount of binding epitope (biotin) being deposited compared to the number of available antibody epitopes. I also think that using the biotinylation signal produced by the TurboID fusion to track the location of the fusion protein and/or binding partners in cells comes with significant caveats that are not well addressed here, mostly due to the inability to discern which proteins are contributing to the observed biotin signal.

To dissect the contributions of the TurboID fusion to elevating signal, anti-biotin antibodies could be used to determine if the abundance of the biotin being deposited by the TurboID is what is increasing detection, or if streptavidin is essential for this. Alternatively, HaloTag or CLIP tagging could be used to see if diffusion of a small molecule tag other than biotin can overcome the labeling issue in phase-separated compartments. There are Halo-biotin substrates available that would allow the conjugation of 1 biotin per fusion protein, which would allow the authors to dissect the relative contributions of the high affinity of streptavidin from the increased amount of biotin that the TurboID introduces.

The idea of using the biotin signal from the TurboID fusion as a means to track the changing localization of the fusion protein or the location of interacting partners is an attractive idea, but the lack of certainty about what proteins are carrying the biotin signal makes it very difficult to make clear statements. For example, in the case of TurboID-PABP2, the appearance of a biotin signal at the cell posterior is proposed to be ALPH1, part of the mRNA decapping complex. However, because we are tracking biotin localization and biotin is being deposited on a variety of proteins, it is not formally possible to say that the posterior signal is ALPH1 or any other part of the decapping complex. For example, the posterior labeling could represent a localization of PABP2 that is not seen without the additional signal intensity provided by the TurboID fusion. There are also many cytoskeletal components present at the cell posterior that could be being biotinylated, not just the decapping complex. Similar arguments can be made for the localization data pertaining to MLP2 and NUP65/75. I would argue that the TurboID labeling allows you to enhance signal on structures, such as the NUPs, and effectively label compartments, but you lack the capacity to know precisely which proteins are being labeled.

Reviewer #3 (Public Review):

Summary:

The authors aimed to investigate the effectiveness of streptavidin imaging as an alternative to traditional antibody labeling for visualizing proteins within cellular contexts. They sought to address challenges associated with antibody accessibility and inconsistent localization by comparing the performance of streptavidin imaging with a TurboID-HA tandem tag across various protein localization scenarios, including phase-separated regions. They aimed to assess the reliability, signal enhancement, and potential advantages of streptavidin imaging over antibody labeling techniques.

Overall, the study provides a convincing argument for the utility of streptavidin imaging in cellular protein visualization. By demonstrating the effectiveness of streptavidin imaging as an alternative to antibody labeling, the study offers a promising solution to issues of accessibility and localization variability. Furthermore, while streptavidin imaging shows significant advantages in signal enhancement and preservation of protein interactions, the authors must consider potential limitations and variations in its application. Factors such as the fact that tagging may sometimes impact protein function, background noise, non-specific binding, and the potential for off-target effects may impact the reliability and interpretation of results. Thus, careful validation and optimization of streptavidin imaging protocols are crucial to ensure reproducibility and accuracy across different experimental setups.

Strengths:

- Streptavidin imaging utilizes multiple biotinylation sites on both the target protein and adjacent proteins, resulting in a substantial signal boost. This enhancement is particularly beneficial for several applications with diluted antigens, such as expansion microscopy or correlative light and electron microscopy.

- This biotinylation process enables the identification and characterization of interacting proteins, allowing for a comprehensive understanding of protein-protein interactions within cellular contexts.

Weaknesses:

- One of the key advantages of antibodies is that they label native, endogenous proteins, i.e. without introducing any genetic modifications or exogenously expressed proteins. This is a major difference from the approach in this manuscript, and it is surprising that this limitation is not really mentioned, let alone expanded upon, anywhere in the manuscript. Tagging proteins often impacts their function (if not their localization), and this is also not discussed.

- Given that BioID proximity labeling encompasses not only the protein of interest but also its entire interacting partner history, ensuring accurate localization of the protein of interest poses a challenge.

- The title of the publication suggests that this imaging technique is widely applicable. However, the authors did not show the ability to track the localization of several distinct proteins on the same sample, which could be an additional factor demonstrating the outperformance of streptavidin imaging compared with antibody labeling. Similarly, the work focuses only on small 2D samples. It would have been interesting to be able to compare this with 3D samples (e.g. cells encapsulated in an extracellular matrix) or to tissues.

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Reply to the reviewers

The authors sincerely appreciate the editors’ and the reviewers’ dedication in providing constructive and insightful comments aimed at enhancing the quality of the manuscript. In response to the valuable feedback received, we have implemented significant revisions to the manuscript, including the addition of key experiments, reorganization of the figures as well as providing detailed point-to-point responses to address the reviewers’ concerns. With these changes, we are confident that we have effectively addressed the comments raised by all three reviewers and have strengthened the overall quality of the manuscript.

Below are the major improvements we have made in the revised manuscript:

1. Figure 4  new figure with polysome profiling assay to strengthen the link between translational regulation and mitochondrial defects.
2. Figure 7  added confocal images showing the transfer of mitochondria into recipient cells.
3. Figure S2  added RER data further supporting a shift of metabolism to favor fatty acid oxidation as shown by proteomics data.
4. Figure S4  added WB data showing that protein degradation was not affected, strengthening a protein synthesis defect due to Fam210a KO.
5. Figure S5B, S6C  added quantification to the staining and blots.

1. Point-by-point description of the revisions

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

In the manuscript entitled "FAM210A mediates an inter-organelle crosstalk essential for protein synthesis and muscle growth in mouse", Chen et al, found that knocking out of FAM210A specifically in muscle using Myl Cre resulted in abnormal mitochondria, hyperacetylation of cytosolic proteins, and translation defects. The manuscript uncovered the new functions of FAM210A in regulating metabolism and translation. I have the following the concerns about the manuscript.

Comments

One of the major phenotypes of FAM210A is the decrease of muscle mass after 6 weeks after birth. Is this phenotype caused by the accumulation of progressive loss of muscle mass from birth? Are the body weight and muscle mass reduced in FAM210A knocking out new-born mice? Is the muscle mass growth curve the same in FAM210A and WT mice from birth to 6 weeks after birth? These results will reveal more mechanism of FAM210A mediated muscle mass control. Answer: Indeed, the phenotype of the Fam210aMKO was caused by the progressive loss of muscle mass. The body weight of the mice was not different before 3-weeks of age (Figure 2B). We reasoned that myonuclei accretion occurred before Myl1Cre induced knockout of Fam210a, accounting for the relative normal muscle development and nuclei accretion prior to 21 days after birth (refer to Response Figure 2). However, due to the small muscle mass, it is hard to accurately evaluate whether the muscle mass in very young mice. Regardless, we believe that body weight and muscle weight closely mimic each other and exhibit similar slopes in WT and KO mice (Response Figure 1).

Beyond 21 days, muscle growth is mainly attributed to hypertrophy of myofibers, a process that relies on protein synthesis. Yet the Fam210aMKO myofibers has defects in protein synthesis, explaining why the muscles cannot gain weight after 3 weeks and started to lose weight. We have shown that at 4 weeks the TA muscle weight was 13 mg in Fam210aMKO compared to 25 mg in WT control. At 6-weeks, the TA weight in the Fam210aMKO mouse was 10 mg compared to 28 mg in the WT control. Furthermore, the TA weight of the Fam210aMKO mouse was 8.7 mg compared to 36mg in the WT control. These results provide compelling evidence that the Fam210aMKO muscles are progressively wasted.

Response Figure 1. Changes of body weights and TA muscle weights during postnatal growth. The muscle weights increased (in wildtype mice) or decreased (in KO mice) with body weights at similar trends.

Does the muscle mass continue to decrease after 8 weeks?

Answer: Based on the trend (see Response Figure 1), we believe the answer is “yes”. However, we were not allowed to monitor the Fam210aMKO mice after 8 weeks of age, as they were severely lethargic and can barely move, reaching the humane endpoint determined by the IACUC guidelines.

FAM210A knockout mice displayed high lethal rate. Is there any potential mechanism for the high lethality?

Answer: We performed extensive necropsy and could not identify a direct cause. The potential cause for the lethality could be the difficulty of breathing as the diaphragm muscle was very thin in the Fam210aMKO mouse compared to the WT control. Besides, the diminished muscle contraction force (Figure 3) might have prohibited normal activities (including eating), leading to exhaustive death.

In Figure 2, the muscle mass decreased significantly, while the fat mass only decreased slightly in FAM210A knockout mice. However, the ratio of the lean mass and fat mass to body mass did not change in FAM210A knockout mice compared to WT mice. How do the authors reconcile this?

Answer: Just to clarify, Figure 2D-E shows that fat mass was significantly reduced at 4-week old but not reduced at 6-week old. We interpret the significant reduction of the mass but not the ratio (to body weight) as the result of the concomitant reduction of the body weight in the Fam210aMKO mice.

Are there changes of the number of nuclei per myotube? Is the muscle atrophy in FAM210A knockout mice caused by the defects of fusion, or the degradation of protein, or both?

Answer: We thank the reviewer for this question. To answer this question, we isolated myofibers from WT and Fam210aMKO mouse at 4-week-old and quantify the myonuclei number. We did not observe a significant reduction of myonuclei number per myofiber in the Fam210aMKO mouse, suggesting that the myoblast fusion into myofibers was not affected in the Fam210aMKO model. (Response Figure 2)

Response Figure 2. DAPI staining and quantification in the single myofiber isolated from WT and Fam210aMKO mice.

The number of myonuclei in the WT and Fam210aMKO was not different, suggesting normal fusion of satellite cells in Fam210aMKO mice.

We also did western blot to check the atrophy related protein expression in WT and Fam210aMKO mouse at different ages. Interestingly, we did not observe a significant induction of these proteins (Atrogin-1, MuRF1) in the Fam210aMKOmuscle. Therefore, we conclude that the muscle atrophy was due to protein translation defects in the Fam210aMKO, independent of myoblast fusion and protein degradation (Figure S4C).

Are the growth curves of muscle mass growth in EDL and SOL the same in FAM210A knockout mice?

Answer: We thank the reviewer for the question. In the Myl1Cre mediated Fam210a KO model, Fam210a was deleted in both fast (EDL) and slow (SOL) muscles (see response to Reviewer 3, second point). We think that the “growth curve” of the EDL and SOL muscle should be same (stagnant and even reduced) upon Fam210a KO as the mouse grows from 4-week to 8-week.

The oxygen consumption and carbon dioxide production are higher in FAM210A knockout mice, suggesting a high metabolism rate. In contrast, the heat production of FAM210A knockout mice is lower, suggesting a low metabolism rate. Any explanation?

Answer: The VCO2 and VO2 values were normalized to the body weight, and the KO value appeared high because their body weights were much lower at the time of test. While for heat production (unit: Kcal/hr), body weight was not a factor in the calculation. The seemingly contradicting/surprising result that a weak KO mouse could have higher VCO2 and VO2could be recapitulated in other mouse models (for example PMID: 22307625).

Given the high glucose consumption in FAM210A, why is the clearance rate of blood glucose low?

Answer: We believe there is a misunderstanding here. A smaller AUC (as seen in the KO) suggest faster blood glucose clearance. The circulating glucose level after fasting is lower in the KO mice, which suggests that the Fam210aMKO mice were consuming more glucose compared to the WT mice. In the GTT test, the Fam210aMKO mice showed a lower AUC after the injection of glucose, implying that the Fam210aMKO mice cleared the injected glucose at a faster rate, probably due to a pseudo-fasting state which would promote the uptake of circulating glucose when available.

Are there any changes of the abilities for the FAM210A knockout mice in running endurance?

Answer: Indeed, the Fam210aMKO mice ran less distance, shorter time, and at a lower speed when tested on a treadmill endurance running program (Figure 3)

In page 5, the last sentence of the 2nd paragraph, the authors concluded "There results suggest that Fam210aMKO induces a metabolic switch to a more oxidative state." It is better to describe it as muscle metabolic since the whole-body metabolism has not been carefully examined.

Answer: We thank the reviewer for pointing this out, we will change the wording to better reflect the changes observed in the Fam210aMKO mouse regarding the metabolism.

In Fig. 6, what is the link between increased transcription level of Fgf21 and the elevated level of aberrant acetylation of proteins?

Answer: We thank the reviewer for this interesting question! However, we did not pursue a direct causal relationship between Fgf21 level and aberrant protein acetylation. In our model, we are proposing that mitochondrial defects in the Fam210aMKO model can trigger the integrated stress response which leads to a higher Fgf21 transcript level in the muscle. This is coinciding with the acetylation increase in the muscle due to the excessive production of acetyl-CoA. A potential relationship between Fgf21 and protein acetylation warrant examination in a future study.

After careful considerations on the mechanism proposed in the study, we decided to remove qPCR data showing the modest increase of Fgf21 mRNA level. The removal of this data will not change the conclusions we draw nor lessen the significance of the mitochondria transfer experiment.

Is there any link between the increased acetylation level of rebolsome proteins and the translation defects?

Answer: Indeed, there are ample studies showing that ribosomal proteins can be acetylated, and that the acetylation of ribosomal proteins can affect the protein synthesis process, for example in PMID: 35604121 and PMID: 37742082. Here in this paper, we showed by ribosome profiling assay that the muscle has defects in the polysome formation (at 4-week and 6-week), when the protein acetylation was significantly increased in the Fam210aMKO mice (Figure 4D-4G).

How do the abnormal mitochondria lead to increased protein acetylation? And how do these defects further cause translation problem?

Answer: As elaborated in the discussion, we propose that upon Fam210a KO in mature myofiber, the TCA cycle in the mitochondria was disrupted, blocking utilization of acetyl-CoA and resulting in the accumulation of acetyl-CoA in the muscle. The excess acetyl-CoA lead to increased protein acetylation in the cytosol. We identified that ribosomal proteins are hyperacetylated in the muscle. We also observed that the polysome formation in the muscle was impaired, which exacerbates the translation efficiency.

Consistently, when we treated C2C12 during in vitro culture with sodium acetate to mimic the increase of acetylation of proteins, we showed that excessive levels of acetyl-CoA can block the differentiation of C2C12 cells (Response Figure 3).

Response Figure 3. The effect of sodium acetate on the differentiation of C2C12 myoblasts.

The differentiation of C2C12 myoblasts into myotubes were probed by the protein abundance of Myog and MF20, which showed a decrease in the expression level when sodium acetate was added in increasing amounts.

The defects in translation will cause general problems besides mitochondria defects. Are there any phenotypes related to the overall translation inhibition observed? If not, why?

Answer: Just to clarify, our model suggests that mitochondrial defects in the Fam210a KO causes cytosolic translation defects, not the other way around. We showed by SUnSET experiment that the global translation was indeed reduced in the Fam210aMKO muscle at 4-week. We also observed that the p-S6 level which indicates the global protein translation was decreased. It is also true that the global translational arrest can exacerbate the mitochondrial defects and fewer mitochondrial proteins can be synthesized. This feed forward loop can explain the aggravating phenotype in the Fam210aMKO mouse as the mouse gets older.

Are the abnormal mitochondria, increased protein acetylation, and translation inhibition observed in 2-6 weeks old mice? When were these defects first found? Are they correlated with muscle atrophy?

Answer: At 2-week-old, the protein synthesis or degradation was not changed between WT and Fam210aMKO mice (Figure S4C). The mitochondria abnormality was first observed at 4 weeks of age, concomitant with the decrease of protein translation (decreased p-S6), polysome formation, and protein hyperacetylation. The acetylation increase was apparent at 6-week together with decreased p-S6 level, polysome assembly and mitochondrial defects. Decreased protein translation has been shown to cause muscle atrophy (PMID: 19046572).

Reviewer #1 (Significance (Required)):

This manuscript described many interesting phenotypes of Fam210a knockout mice. However, the links between these phenotypes are obscure. The logic of the manuscript will be greatly improved if the authors could provide explanations to logically link the phenotypes.

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

Summary: In this manuscript, Chen et al., investigate the functions of FAM210A in skeletal muscle physiology and metabolism. FAM210A is a mitochondria-localized protein in which mutations have been associated with sarcopenia and osteoporosis. Using publicly available gene expression datasets from human skeletal muscle biopsies the authors first demonstrate that the expression of FAM210 is reduced in muscle atrophy-associated diseases and increased in muscle hypertrophy conditions. Based on this, they show that a muscle specific Fam210a deletion leads to muscle atrophy/weakness, systemic metabolic defects, and premature lethality in mouse. Further examination of the knockout myofibers reveals impaired mitochondrial respiration and translation program. Additionally, the authors demonstrate that the flow of TCA cycle is disrupted in the FAM210A-deleted myofibers, which causes abnormal accumulation of acetyl-coA and hyperacetylation of a subset of proteins. The authors claim that Fam210a deletion in skeletal muscle induces the hyper-acetylation of several small ribosomal proteins that leads to ribosomal disassembly and translational deficiency. However, this conclusion is not supported by adequate experimentation and rigorous analysis of ribosomal proteins acetylation and ribosome assembly.

Major comments:

-In general, figure legends are lacking information regarding number of biological replicates used and details about statistical analysis. What does three * vs. one * mean in terms of p-value? Exact p-values should be indicated.

Answer: We thank the reviewer for pointing this out, we have added the information to the revised figure legends.

-The mechanistic studies linking muscle phenotypes with ribosomal protein hyperacetylation and mRNA translation defects are underdeveloped and not rigorously carried.

Answer: We agree with the reviewer and have added new data in the revised manuscript to strengthen this link. For example, we have now provided direct evidence on the defective polysome assembly in the Fam210a KO muscles (Figure 4D-4G), which should profoundly impact mRNA translation. In addition, other groups have also shown that ribosomal protein acetylation can impact mRNA translation and polysome formation (PMID: 35604121).

We also explored the effect of acetylation on differentiation (a process accompanied by extensive protein synthesis) related to our mouse model. We used sodium acetate to elevate acetylation during C2C12 differentiation. We found that increased acetylation indeed impaired the differentiation as can be seen by the reduced expression of MF20 (myosin protein) by WB and IF. The differentiation marker Myogenin was also reduced (Response Figure 3, 4).

Response Figure 4. Immunofluorescence staining of Myog and MF20 in the differentiated C2C12 myotubes treated with different amounts of sodium acetate.

The number of MF20 (green) positive myotubes and Myog (red) positive nuclei was significantly reduced in the cells treated with 15mM and 30mM sodium acetate.

-Fig S1: The validation WB of FAM210A KO is not the most convincing. Why are the FAM210A levels so low in TA compared to other tissues?

Answer: This is due to the insufficient proteins loaded as it was obvious from the Tubulin marker. We have replaced the WB blot with more convincing blots as requested (Figure S1C).

-Fig 2G: The authors state "Hematoxylin and eosin (H&E) staining did not reveal any obvious myofiber pathology in the Fam210a KO mice up to 8 weeks". However there seems to be a progressive increase in nuclei up to 8-weeks in the KO. What is the significance of this?

Answer: Thank you for pointing this out. We have now changed the wording and quantified the myonuclei number per myofiber. The increase of myonuclei in the H&E images is likely due to the smaller myofiber size in the Fam210aMKOmouse compared to the WT (Response Figure 5).

Response Figure 5. Quantification of the myonuclei number in the H&E images.

-IP-MS analysis for FAM210A interacting proteins requires validation with IP and reverse IP + WB experiment.

Answer: We did perform the co-IP with SUCLG2 and FAM210A antibodies to try to confirm the interaction. To be more specific, we transduced C2C12 myoblasts cells with an Fam210a overexpression virus and differentiated the cells for 3 days. The myotubes were used to test the interaction by pulling down Fam210a with a myc antibody (FAM210A has a myc tag) and blot with SUCLG2 antibody. Unfortunately, the results were not promising (Response Figure 6). We reasoned that the interaction might be indirect or too transient to be reliably detected.

Response Figure 6. co-IP of SUCLG2 and FAM210A.

• Figure 4A requires quantification of the SDH signals from multiple samples.

Answer: We thank the reviewer for this suggestion. We have added the quantification of the staining (Figure S5B).

• Figure 6F: To clearly demonstrate an increase in protein acetylation in the FAM210 MKO, the authors must provide quantification data generated with more then N=1. Please add the molecular weights markings on the side of the blots.

Answer: We thank the reviewer for this suggestion, we have provided the quantification of the Acetylated-lysine blots, and added the molecular weight markers (Figure 6F, Figure S6C).

• Figure 6H and S5: The mitochondria transfer experiment appears to be quite efficient compared to previously published studies. It would be important to control that the signal observed in the recipient cells is not due to the leakage of the MitoTracker dye from the donor mitochondria.

Answer: This is an interesting point though MitoTracker dye is not supposed to leak as it covalently binds to mitochondrial proteins. Even though the dye may leak to mark the endogenous mitochondrial, it does not affect our goal to demonstrate that transfer of Fam210aMKO mitochondria into healthy cells can induce protein hyperacetylation. Additional evidence argues against the leakiness of Mitotracker dye to subsequently mark other mitochondria in the recipient cells: 1) mtDNA and MitoTracker signal both increase linearly with the increasing amounts of mitochondria transferred (Figure S7A); 2) We have now also included confocal images to show the presence of both MitoTracker labeled and non-labeled mitochondria in the recipient cells. We reason that if MitoTracker leaks within a cell then it would have labeled all mitochondrial in that cell (Figure 7C).

• Figure 6J: The increase in Fgf21 is modest. Although the difference is statistically significant, is it biologically important?

Answer: We thank the reviewer for this question; indeed, the increase is modest. We think the reason of the modest increase compared to the drastic increase seen in vivo was because when we transplanted the WT and Fam210aMKOmitochondria to the recipient cell, the original mitochondria in the recipient were not depleted, which could explain the milder effect. However, we were able to show that the recipient cells readily increase the acetylation of proteins after receiving the Fam210aMKO mitochondria, recapitulating the phenotype we saw in the Fam210aMKO muscle.

After careful considerations on the mechanism proposed in the study, we decided to remove qPCR data showing the modest increase of Fgf21 mRNA level. The removal of this data will not change the conclusions we draw nor lessen the significance of the mitochondria transfer experiment.

• Figure 6C: How significant is the difference in acetylation of RPL30 in WT vs. KO. RPS13 was not found in the WT MS? Was this normalized to Input?

Answer: the MS was performed with same loading. The mass spectrometry results for protein identification after AcK-IP were from pooled samples from 3 independent replicates (as the KO muscles are very scarce). Therefore, there was not a significance test.

• Figure 7D: What are the MW of the bands shown on this blot? This experiment is by no means sufficient to demonstrate and confirm that ribosomal proteins are acetylated. An increase in RPL30 and RPS13 acetylation must be directly assessed.

Answer: We thank the reviewer for suggesting the more direct assays to look at RPL30 and RPS13 acetylation. We have shown that the ribosome fractions were indeed hyperacetylated in the Fam210aMKO mouse compared to the WT control (Figure S6D). We agree that this result cannot lead to the conclusion that the RPL30 and RPS13 are specifically hyperacetylated. Indeed, we have tried to use Acetylated lysine antibody pull down and RPS13/RPL30 blot to show the increase in the acetylated RPS13/RPL30 protein. However, we cannot show a robust increase in the acetylation, potentially due to the low number of acetylation sites on RPS13 and RPL30 protein. We therefore have reworded the conclusion in the revised manuscript to better reflect the results.

• Fig7E: This experiment is not properly executed and in its current state does not rigorously support that "hyper-acetylation of several small ribosomal proteins leads to ribosomal disassembly". A) UV profiles of the fractionation must be provided to assess the quality of the profile. B) Provide MW markers. Which band is RPL30? The Input and free fraction bands are not at the same size. RPL30 should at least be visible on the 60S and polysomes from the WT. C) These results do not match the acetylation MS data, which seem to show that the increase in acetylation is much greater for RPS13. However, RPS13 presence on polysomes (assuming they are polysomes) is not affected in the KO. D) This type of experiment must be done for three independent biological replicates, blots from single lanes must be quantified and normalized to total signal (from all the lanes) for the same antibody.

Answer: we appreciate the great advice on improving the experiment. As suggested, we have now added proper experimentation (UV profile, and better WB), with the help of Dr. Kotaro Fujii (included as co-author in the revised manuscript). The following results showed that in the 4-week sample, there was a decrease in the 80S monosome and polysome in the Fam210aMKO mice compared to the WT. The change was more drastic at 6-week (Figure 4D-4G). Similarly, due to the scarce amount of muscle in the KO mice, we need to pool samples from the 6-week-old mice for the experiment, and hope the reviewer can understand the situation. With the clear peaks shown in the UV profile as well as the WB results, we provide more convincing evidence that the polysome assembly was indeed impaired in the Fam210aMKO (Figure 4D-4G).

• Fig 7F: Global translation rates are assessed by puro incorporation at week 4, a time point when differences in protein acetylation were not observed. This does not support the hypothesis that increased acetylation of ribosomal proteins causes defect in protein translation. (Referencing the authors statement p.7 lines 321-24.).

Answer: We thank the reviewer for this question. When we quantified the protein acetylation increase in the muscle at 4-weeks, we showed that there was a significant increase. But like the reviewer said, the ribosomal fractions were not significantly acetylated by WB at 4-week. We reasoned that, at early stages (4-weeks), the ISR signaling can lead to the translational arrest, along with the polysome formation defects, leading to the decreased protein translation. These are included in the discussion.

• Other studies have implicated Fam210A in the regulation of mitochondrial protein synthesis through an interaction with EF-Tu. The authors also identified EF-Tu as an interactor in their LC-MS analysis (FigS4). A role for this interaction accounting for mitochondrial and translation defects seems to be underestimated and unexplored here.

Answer: We agree with this point and believe the cytoplasmic translation defects are in addition to the mitochondrial translational defects. We have shown that FAM210A KO leads to the decrease of the MTCO1 which is encoded by the mitochondrial genome. Besides, we also showed by mitochondrial proteomics that TUFM was reduced in the KO, which also contributed to translational arrest in the mitochondria (Figure 5J). To answer whether mitochondrial encoded proteins are decreased in upon Fam210a KO, we blotted the protein lysates at different stages with antibodies for a few mitochondrial encoded proteins and showed that they decreased with ages (Response Figure 7).

Response Figure 7. WB analysis and quantification of mitochondrial encoded proteins in WT and Fam210aMKO muscle at different ages.

The mitochondrial proteins were indeed decreased in Fam210aMKO starting from 6-weeks of age compared to the WT.

Minor comments:

-What is known about FAM210A, other studies assessing its role, and the rational for studying its function should be better introduced.

Answer: We thank the reviewer for the suggestion to have more information of FAM210A functions/mechanisms in the introduction. We have added more background to the introduction.

-In the discussion the authors states: "Moreover, when the proportion of ribosomal protein phosphorylation buildup in the Fam210aMKO, the assembly of the translational machinery is impaired therefore further dampen the cellular translation". Do they mean acetylation and not phosphorylation?

Answer: We are sorry about the typo and have changed it. We thank the reviewer for catching this.

• Please use the term "mRNA translation" or "protein synthesis" instead of "protein translation" in the text.

Answer: We thank the reviewer for the suggestion to properly refer to these processes. We have changed the terms in the manuscript.

-The methods section for RT-qPCR: It should ne M-MLV RT and not M-MLC. If the qPCR data was normalized with 18S, please provide the sequence of the primers in the table. Information on how primer efficiency was tested must be included in the method section.

Answer: We thank the reviewer for pointing this out. We have changed the texts. We also have provided 18S sequence and provide texts about how primer efficiency was tested.

Reviewer #2 (Significance (Required)):

General assessment: Previous genome-wide association studies have found that mutations in FAM210A were associated with sarcopenia and osteoporosis. Because FAM210A is not expressed in the bone and highly expressed in skeletal muscle, it suggests that FAM210A likely plays an important role in muscle, which could also affect bone regulation. The authors here provide further evidence of an important role for FAM210A in diseases affecting muscle function by demonstrating that the expression of FAM210A decreases with age and in patients affected by Pompe disease, Duchenne muscular dystrophy and hereditary recessive myopathy. FAM210A is a mitochondria-localized protein and given the crucial role of mitochondria in supporting muscle metabolism, elucidating the molecular function of FAM210A may provide important insights into diseases biology that could lead to the development of therapeutic approaches. Thus, a significant protein and regulatory pathway are explored in this study that can potentially impact human health. In this manuscript, the authors provide compelling evidence of the importance of Fam210a in muscle homeostasis with their newly generate mouse model. The experiments looking at muscle physiology, function and metabolism are well-executed and for the most part rigorous, which are the strengths of this manuscript. However, the conclusion that Fam210a deletion in skeletal muscle induces the hyper-acetylation of several small ribosomal proteins, which leads to ribosomal disassembly and translational deficiency is not supported by the data presented here. As noted in the comments above, these experiments need major improvement. Additionally, there are other concerns about general scientific rigor and conclusions inconsistent with the data presented as also noted in the comments section.

Advance: Although a previous study explored the role of FAM210A using a skeletal muscle-specific KO induced at postnatal 28 days under a HSA promoter, the model used by the authors here provide a cleaner approach and more insights into the molecular functions of FAM210A in muscle physiology. The findings that Fam210a MKO disrupts the flow of TCA cycle, which leads to an abnormal accumulation of acetyl-CoA is interesting and provide new conceptual advance on the roles of FAM210A in mitochondria function in muscle. Acetyl-CoA production is an important source of acetyl-group that can be transferred to proteins and regulate gene expression programs. Thus, this is an important finding. However, molecular mechanism by which FAM210A regulates this process through an interaction with SUCLG2 is not provided and the nature this interaction is superficially explored.

Audience: Findings from this manuscript are likely to interest both basic research and translational/clinical audiences as it explores the physiological and molecular function of a disease-linked protein. The findings are also likely to impact the fields of metabolism, mitochondria function and regulation of gene expression by protein acetylation (if concerns raised regarding these experiments are addressed).

The fields of expertise of this reviewer are protein and RNA modifications, ribosome biogenesis and mRNA translation.

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

The authors state that in their manuscript "the role of mitochondria in regulating cytosolic protein translation in skeletal muscle cells (myofibers)" has been explored (Line 19-20). As experimental model, they used mice expressing Cre recombinase under the control of the myosin light chain 1 promoter. The first conclusion was that "FAM210A is positively associated with muscle mass in mice and humans". The authors say that the presented data "reveal a novel crosstalk between the mitochondrion and ribosome mediated by FAM210A".

I recognize the potential of this work since the role of FAM210a has been more deeply investigated in skeletal muscle. In fact, the study by Tanaka et al, 2018 presented only a preliminary characterization of the role of FAM210a in muscle. However, I think that this work is not complete and each aspect that has been investigated is not well connected with each other. In particular, it is not clear whether the disrupted ribosomal assembly by hyperacetylation causes muscle atrophy or it is altered under catabolic states during atrophy (primary cause or consequence of?).

Answer: We thank the reviewer for recognizing the importance of the study that characterizes the effect of FAM210A in muscle mass maintenance. In this study, we have shown that polysome formation was impaired at 4-week and therefore the translational efficiency was reduced in the muscle. This translational decrease coincides with the acetylation increase. Moreover, we showed by mitochondrial transfer experiment that the mitochondria from the Fam210aMKO mice can carry the phenotype and lead to acetylation increase in the recipient cells. Since muscle protein synthesis defects have been known to lead to muscle dystrophy, and we have shown that in the Fam210aMKO model, protein synthesis was indeed defective while there was not an induction of atrophy. Therefore, we conclude that the in the KO model, the protein synthesis defects lead to muscle atrophy.

The other major point is represented by the fact that the Myl1-CRE expressing model provides selectivity in fast muscle fibers (see for example Barton PJR, Harris AJ, Buckingham M. Myosin light chain gene expression in developing and denervated fetal muscle in the mouse. Development. 1989;107: 819-824). Then the authors knocked out FAM210a only in fast fibers and they never take in consideration this key point! This is crucial since fast and slow muscles have different content of mitochondria with different size, shape, and metabolism! The muscle fibers can be classified based on the mitochondrial metabolism (see for example Chemello et al., 2019; PMID: 30917329).

Regarding this point, they simply wrote at Line 75-76 "using a skeletal muscle specific Myl1 (myosin, light polypeptide 1) driven Cre recombinase specifically expressed in post-differentiation myocytes and multinucleated myofibers,...". It would be more correct to write multinucleated type 2 myofibers showing the reduction of FAM210a in different fiber types.

I think that the authors must solve these aspect and then organize the findings accordingly. The data are in general interesting for broad type of audience.

Answer:

We appreciate the reviewer’s comment on the Myl1 knock-in Cre (Myl1Cre) model, which prompted us to more explicitly clarify some of the confusions around this model. We fully respect the validity of the 1989 study by Dr. Buckingham and other studies showing fast muscle specific expression of Myl1. However, we and others have shown that Myl1 not only mark the fast but also the slow myofibers (elaborated below). The discrepancy can be explained by the fact that using the Myl1Cre as a lineage marker is different from directly examining Myl1 expression at static timepoints by in situ hybridization (ISH). This is because Cre recombinase can accumulate and diffuse to all the myonuclei in a multinucleated myofiber, subsequently leading to deletion of LoxP-flanked DNA in all nuclei. Also, in the Cre/LoxP system, only a small amount of Cre recombinase is needed to induce the recombination of the target loxP sites and lead to gene KO. Another example of the discrepancy between the static mRNA pattern and the dynamic gene expression during development is the Hox gene expression. When the corresponding author (SK) of this manuscript was trained with Dr. Joshua R Sanes, he developed 3 Cre lines driven by three different Hox genes– that have been shown by ISH to be expressed in a specific rostral to caudal domain in the spinal cord during development. However, each of these Cre model ended up marking all the spinal cord without any domain specificity. In the case of Myl1Cre mouse model, we have previously published a paper on the lineage-tracing results using the Myl1Cre and showed that Myl1Cre marked all fast AND slow myofibers in mice (Wang et al, 2015, PMID: 25794679). In another lineage tracing study using nuclear GFP reporter, we report that Myl1Cre marks 96% nuclei in myofibers regardless of fiber types (Bi et al., 2016, PMID: 27644105), the remainder 4% non-marked nuclei potentially represent satellite cells. Other groups have also used the Myl1Cre model to induce KO in both fast and slow muscles (Pereira et al, 2020, PMID: 31916679). Therefore, we believe that the Myl1Cre mouse model allows us to efficiently knockout the Fam210a gene in both slow and fast muscle.

To directly confirm that Fam210a was efficiently knocked out in both slow and fast muscles using the Myl1Cre mouse model, we isolated different muscle groups (Soleus and diaphragm that contains a large fraction of slow myofibers, TA and EDL that contain predominantly fast myofibers) and checked the expression level and the KO efficiency of Fam210a by WB. We have shown that even in slow muscles like diaphragm and SOL, the KO was very efficient, as there were no visible FAM210A bands in the WB (Figure S1C).

In more detail:

The data must be analyzed and discussed based on the fact that FAM210a has been deleted specifically in fast fibers. First the authors must show the protein levels of FAM210a in both fast, slow and mixed fast-slow muscles. Then for example in Figure S1C EDL, GAS and SOL muscles must be included.

Answer: This is related to the misunderstanding of the Myl1Cre model. We understand the reviewer’s concern and therefore isolated proteins from different muscles in WT and Fam210aMKO mice at 4-weeks and checked the expression level of FAM210A. We have shown that regardless of fast or slow muscles, FAM210A was deleted.

The blot in general must be repeated since it has poor quality (continuum of FAM210a band in the samples).

Answer: We thank the reviewer for this suggestion and increase the data quality. We have changed the original blot with the following blots showing that FAM210A was not deleted in other non-muscle tissues (Figure S1C).

Please provide staining of TA, GAS and SOL muscles to show how Myl1CRE-directed deletion of FAM210a affect the different myofibers.

Answer: This point is also related to assumption that Myl1Cre only induce deletion in fast myofibers. We have done staining in both EDL and SOL muscle to show the relative changes in myofiber compositions. We found that the myofibers in EDL and SOL muscle have shifted to a more oxidative type upon Fam210a KO (Figure S3).

In Figure 2F where decreased TA muscle weight was showed in the Fam210aMKO mice, the authors must include also the other muscles (EDL, GAS and SOL).

Answer: We thank the reviewer for helping us be more rigorous on the phenotype examination. We understand that the reviewer initially raised this question because of the concern on Myl1Cre model. Now that we have shown the MylCremarks both the fast and slow muscles, we believe this question is no longer a concern. Besides, to indirectly answer the question, we would like for the reviewer to appreciate the size difference of the EDL as well as the SOL muscle in Figure S3 in the manuscript. As can be seen from the images, the size of the SOL muscles in the KO was significantly reduced compared to the WT, speaking in favor of the KO effect on slow muscles.

In general, since the HSA-CRE model is generally used for gene manipulation in skeletal muscles the authors must characterize their model considering that the myosin light chain 1 promoter Myl1-Cre is mainly active in postmitotic type II myofibers. The last model can also give advantage for mosaic gene manipulation in muscles with mixed fiber types.

Answer: We thank the reviewer for bringing this point up. We hope by the multiple lines of evidence that we provided in the previous questions, we can convince the reviewer that the KO model using the Myl1Cre does not lead to a mosaic gene manipulation in the muscle. On the contrary, the KO model is a homogeneous KO in both fast and slow muscles.

Line 118-119 Fam210a level is positively corelated with muscle mass, as it is reduced in muscle atrophy conditions and increased in muscle hypertrophy conditions. Fig 1: I don't like since there are many different models in which the muscle mass reduction is associated with different mechanisms. Then independently of mechanisms associated with changes in muscle mass Fam210a is always linked to? Which common mechanism can explain this?

Answer: We understand that the reviewer would like to pursue a conserved mechanism governing muscle mass maintenance, however, we by no means wanted to make a direct causal relationship between FAM210A level and different muscle disease/atrophy conditions. Indeed, the atrophic conditions presented have different mechanisms leading to muscle mass reduction, yet we wanted to present the possible connection that Fam210a level and muscle mass are co-regulated, and we later confirmed by KO mouse model that FAM210A KO indeed reduces muscle mass.

Line 144-146 Hematoxylin and eosin (H&E) staining did not reveal any obvious myofiber pathology in the Fam210aMKO mice up to 8 weeks (Figure 2G). I totally disagree! It seems that there is more inflammation upon deletion of Fam210aMKO. Please check it.

Answer: We thank the reviewer for pointing this out to help us more rigorously describe our results. We have changed the wording to better reflect the changes observed with H&E images.

Fig3E-L there is a huge difference between EDL and SOL. The authors can't avoid to discuss their data considering the real expression of CRE upon Myl promoter: specific deletion in fast fibers. I think that the data in FIGS3 are very important and must be linked to data in Fig3. Organize in a different way all the presented data to really describe what is happening upon deletion of Fam210a.

Again, the authors MUST organize better their data in the manuscript: to each paragraph must correspond data in the main figures. For example: at Line 189 Fam210aMKO mice exhibit systemic metabolic defects and at Line 208 Fam210aMKO increases oxidative myofibers and decreases glycolytic myofibers. These two paragraphs discuss data showed only in supplementary figures.

Answer: We thank the reviewer for this suggestion. As shown in the previous responses, the Myl1Cre indeed induce efficient deletion of Fam210a in slow muscles. Therefore, we did not consider this to be a myofiber-specific deletion model. We consider these two results as the effect of a mitochondrial protein (FAM210A) on the myofiber metabolism (independent of myofiber type specific deletion), and that the deletion of Fam210a results in mitochondrial stress, which can lead to myofiber switch (Figure S3).

Physical activity mast be monitored. Show respiratory exchange ratio (RER = VCO2/VO2) and discuss the results.

Answer: We thank the reviewer for this suggestion. By these results, we would like to demonstrate that muscle homeostasis is important for the systemic metabolism, disruption of muscle mass maintenance in the Fam210aMKO mice leads to defects in the whole-body metabolism. We have now included the RER results (Figure S2F, S2G). The results show that the Fam210aMKO mice had significantly lower RER (VCO2/VO2) value at daytime, indicating that the mice rely more on utilizing fat as the fuel source. This is consistent with the proteomics results (Figure 5K) that the Fam210aMKOmice have increased FAO pathway. Unfortunately, our metabolic chamber does not have the capacity to monitor activity. We instead include data on heat production (Figure S2E).

"Fam210aMKO increases oxidative myofibers and decreases glycolytic myofibers". The data mast be associated with the evaluation of the expression levels of FAM210 in different fiber type to really understand what is happening upon FAM210a loss.

Answer: We understand the reviewer’s concern on the different expression level of Fam210a as well as the KO efficiency using the Myl1Cre model. We have shown that Fam210a is knocked out in fast and slow muscles, therefore, we did not consider the effects on fast and slow myofibers separately.

As SDH activity in type 1 fibers is higher than type 2 the and since the authors are using a model in which Fam210a is deleted only in type 2 fiber they should understand what is happening: fiber 1

Answer: We agree with the reviewer that the SDH activity is different in different myofibers. We have shown by western blot that FAM210A was similarly KO in both fast and slow muscles. When we performed fiber type staining in EDL and SOL muscle, we saw that there was a shift towards the slower myofiber types both in the EDL and SOL muscle, due to mitochondrial defects.

Associate a cox assay with the sdh assay

Answer: We thank the reviewer for this suggestion. We have shown by SDH staining as well as seahorse experiments using isolated mitochondria that the complex II activity was impaired in the muscle. We understand the reviewer would like to see a COX assay to show the defects of the mitochondrial function. Though we were not able to perform the COX assay, we showed from other aspects that the mitochondrial function was impaired by running WB of the mitochondrial encoded proteins (ATP6, MTCO2, mtCYB) and showed these proteins were decreased with ages. Along with the morphological changes of the mitochondria shown by electron microscope (Figure 5 and Figure S5), we conclude that these changes must have impacted mitochondrial function.

Figure 4b blot tubulin and FAM210a look strange. Look especially at first and second and fourth form the left side.

Answer: We are sorry about the mistake in the images, we have changed the Tubulin blot in the Oxphos blots.

Figure 4B OXPHOS protein levels look similar between wt and KO. Include the quantification with the significance (min 3-5 mice per genotype).

Answer: we have quantified the change between WT and KO on different proteins (Reponse Figure 8).

Response Figure 8. Quantification of the OxPHOS proteins in WT and Fam210aMKO muscle at different ages.

Quantification of the blots showed that indeed the mitochondrial proteins were decreased in the Fam210aMKO. The change of mitochondrial encoded protein MTCO1 was earlier detected in the Fam210aMKO.

Provide TEM analysis for SOL muscle. I would understand whether mitochondria are differently affected in fast and slow muscles.

Answer: We understand the reviewer was originally concerned about the KO efficiency of Fam210a in fast and slow muscles, based on the assumption about the MylCre model. We have shown that the FAM210A protein was similarly depleted in both fast and slow muscles by western blot. In this case, we would speculate that the mitochondrial change in fast and slow muscles would be similar because the mitochondrial changes were due to the inherent defects in the mitochondria.

In all experiments must be clear which muscle type or types was/were used:

Line 268: "isolated from WT and Fam210aMKO muscles at 6 weeks of age".

Line 587 "Muscle lysate acetyl-CoA contents"

For Seahorse Mitochondrial Respiration Analysis at Line 599 "isolated mitochondria from muscle"

For TCA cycle metabolomics at Line 615 "muscle tissue was weighed and homogenized"

For SCS activity assay at Line 632 "mitochondria from muscles were isolated"

For LC-MS/MS at Line 647 "Mitochondria were purified from skeletal muscles and subjected to proteomics analysis".

For Ribosome isolation at Line 676 "Skeletal muscle from mice"

For Polysome profiling experiment at Line 696 "muscle tissues from mice were dissected"

It is important to know which muscles were used since confounding effects of the specific deletion of FAM210a in type 2 fibers must be identified and discussed.

Answer: We thank the reviewer for considering the different muscle groups in our mouse model. For experiments requiring a large amount of muscle tissue, such as ribosome isolation, mitochondrial isolation and polysome profiling, we used all the muscles from the mouse. For WB experiments, we used the TA muscle. We have included this information in the method section in the manuscript. Since we have shown that FAM210A was similarly depleted in different muscles (see previous responses), we think it is justified to pool muscles from the same mouse.

Line 296-297 The authors wrote "Consistently, the mRNA levels of Atf4, Fgf21 and the associated transcripts were highly induced in the Fam210aMKO 296 both in the 4-week and 6-week-old muscle samples". Is Fgf21 responsible for the reduction of body weight? (see for example PMID: 28552492, PMID: 28607005 and PMID: 33944779). Measure the circulating Fgf21 protein in Ko and wt mice.

Answer: We thank the reviewer for this great suggestion. Indeed, Fgf21 can potentially lead to body weight reduction, and this can explain the smaller body weight in our mouse model as well. However, we are more concerned about the muscle changes in our mouse model, therefore we did not further validate the changes of Fgf21 in the circulation.

After careful considerations on the mechanism proposed in the study, we decided to remove qPCR data showing the modest increase of Fgf21 mRNA level. The removal of this data will not change the conclusions we draw nor lessen the significance of the mitochondria transfer experiment.

Moreover the authors must check Opa1 total protein level and also the ratio between long and short isoforms. Is Fam210a interacting with Opa1?

Answer: We thank the reviewer for this interesting question. Another publication from our lab has shown that Fam210a can modulate the cleavage of OPA1 in brown adipose tissue and influence the cold-induced thermogenesis (PMID: 37816711). Indeed, OPA1 deletion in muscle can lead to muscle atrophy and postnatal death at about day 10 (PMID: 28552492) through the induction of UPR (ISR) and the induction of Fgf21. We did not check the interaction between FAM210A and OPA1 in the muscle context, and FAM210A was not found to be interacting with OPA1 in brown adipose tissue (PMID: 37816711). However, the focus of this study was the acetylation change and the FAM210A effect on muscle mass maintenance. Therefore, we did not pursue the OPA1 related mechanism in skeletal muscle.

The final part of the paper is really interesting but need to be discussed knowing exactly the used experimental model. Then check in which fiber types FAM210a is loss.

Answer: We thank the reviewer for the stringency on the model used. Indeed, the mitochondria can be different from different muscle groups. However, since the muscle isolated from WT and KO mice was properly controlled and therefore can balance the effects of different mitochondria. We have consistently observed the increased acetylation when mutant mitochondria were transferred.

Regarding the mitochondrial transplantation I'm surprise to see that it happens in the direction of unhealthy mitochondria to healthy cells. Are you able to rescue the phenotype of Fam210a KO cells with healthy mitochondria?

Answer: We thank the reviewer for bringing this interesting yet important question up! Our mitochondrial transfer results support a “gain-of-function” model where excessive Acetyl CoA produced by the Fam210a-KO mitochondrial induces hyperacetylation. Regarding the question to transfer healthy mitochondria to rescue the KO cells, we reason that even when we transfer the healthy mitochondria to the KO cells, the healthy mitochondria will not stop the mutant mitochondria from making excessive amounts of acetyl-CoA and thus protein acetylation. A clean transfer would require depletion of the mitochondria in the KO cells and concomitant restoring FAM210A level in the KO cells (as the lack of Fam210a gene in the KO cells will eventually convert the transferred mitochondrial into mutants with the normal turnover of FAM210A). This is technically highly challenging and nearly impossible to do. We hope that the reviewer can understand the difficulties.

Reviewer #3 (Significance (Required)):

In conclusion, the strength of the presented paper is the novelty: the authors explored the role of FAM210a in skeletal muscle. However, the major limitation is represented by the fact that they did not show in which fiber types Fam210a is knocked out. In fact, the used CRE recombinase expressing model is well-known to be specific for type 2 fibers. Then since mitochondria and metabolism are central in this manuscript and they are different in the fast and slow fiber types, the authors must dissect in details this point.

Moreover, there are many data but they are not linked each other and discussed properly. The paper must be completely re-organized.

This manuscript can be interesting for a broad type of audience.

I'm an expert on mitochondria, metabolism and skeletal muscle.

It is often a good idea to bookmark or tag pages that have dense presence of key words. It is the kind of para that you will have to go back often to.

Extended abstract and slides: https://github.com/filipbartek/wg5-vienna24/releases/tag/final

Author Response

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

eLife assessment

In this study, the authors develop a useful strategy for fluorophore-tagging endogenous proteins in human induced pluripotent stem cells (iPSCs) using a split mNeonGreen approach. Experimentally, the methods are solid, and the data presented support the author's conclusions. Overall, these methodologies should be useful to a wide audience of cell biologists who want to study protein localization and dynamics at endogenous levels in iPSCs.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors have applied an asymmetric split mNeonGreen2 (mNG2) system to human iPSCs. Integrating a constitutively expressed long fragment of mNG2 at the AAVS1 locus, allows other proteins to be tagged through the use of available ssODN donors. This removes the need to generate long AAV donors for tagging, thus greatly facilitating high-throughput tagging efforts. The authors then demonstrate the feasibility of the method by successfully tagging 9 markers expressed in iPSC at various, and one expressed upon endoderm differentiation. Several additional differentiation markers were also successfully tagged but not subsequently tested for expression/visibility. As one might expect for high-throughput tagging, a few proteins, while successfully tagged at the genomic level, failed to be visible. Finally, to demonstrate the utility of the tagged cells, the authors isolated clones with genes relevant to cytokinesis tagged, and together with an AI to enhance signal-to-noise ratios, monitored their localization over cell division.

Strengths:

Characterization of the mNG2 tagged parental iPSC line was well and carefully done including validation of a single integration, the presence of markers for continued pluripotency, selected offtarget analysis, and G-banding-based structural rearrangement detection.

The ability to tag proteins with simple ssODNs in iPSC capable of multi-lineage differentiation will undoubtedly be useful for localization tracking and reporter line generation.

Validation of clone genotypes was carefully performed and highlights the continued need for caution with regard to editing outcomes.

Weaknesses:

IF and flow cytometry figures lack quantification and information on replication. How consistent is the brightness and localization of the markers? How representative are the specific images? Stability is mentioned in the text but data on the stability of expression/brightness is not shown.

To address this comment, we have quantified the mean fluorescence intensity of the tagged cell populations in Fig. S3B-T. This data correlates well with the expected expression levels of each gene relative to the others (Fig. S3A), apart from CDH1 and RACGAP1, which are described in the discussion.

The images in Fig. 2 show tagged populations enriched by FACS so they are non-clonal and are representative of the diversity of the population of tagged cells.

The images shown in Fig. 3 are representative of the clonal tagged populations. The stability of the tag was not quantified directly. However, the fluorescence intensity was very stable across cells in clonal populations. Since these populations were recovered from a single cell and grown for several weeks, this low variability across cells in a population suggests that these tags are stable.

The localization of markers, while consistent with expectations, is not validated by a second technique such as antibody staining, and in many cases not even with Hoechst to show nuclear vs cytoplasmic.

We find that the localization of each protein is distinct and consistent with previous studies. To address this comment, we have added an overlay of the green fluorescence images with brightfield images to better show the location of the tagged protein relative to the nuclei and cytoplasm. We have also added references to other studies that showed the same localization patterns for these proteins in iPSCs and other relevant cell lines.

For the multi-germ layer differentiation validation, NCAM is also expressed by ectoderm, so isn't a good solo marker for mesoderm as it was used. Indeed, the kit used for the differentiation suggests Brachyury combined with either NCAM or CXCR4, not NCAM alone.

Since Brachyury is the most common mesodermal marker, we first tested differentiation using anti-Brachyury antibodies, but they did not work well for flow cytometry. We then switched to anti-NCAM antibodies. Since we used a kit for directed differentiation of iPSCs into the mesodermal lineage, NCAM staining should still report for successful differentiation. In the context of mixed differentiation experiments (embryoid body formation or teratoma assay), NCAM would not differentiate between ectoderm and mesoderm. The parental cells (201B7) have also been edited at the AAVS1 locus in multiple other studies, with no effect on their differentiation potential.

Only a single female parental line has been generated and characterized. It would have been useful to have several lines and both male and female to allow sex differences to be explored.

We agree that it would be interesting (and important) to study differences in protein localization between female and male cell types, and from different individuals with different genetic backgrounds. We see our tool as opening a door for cell biology to move away from randomly collected, transformed, differentiated cell types to more directed comparative studies of distinct normal cell types. Since few studies of cell biological processes have been done in normal cells, a first step is to understand how processes compare in an isogenic background, then future studies can reveal how they compare with other individuals and sexes. We hope that either our group or others will continue to build similar lines so that these studies can be done.

The AI-based signal-to-noise enhancement needs more details and testing. Such models can introduce strong assumptions and thus artefacts into the resolved data. Was the model trained on all markers or were multiple models trained on a single marker each? For example, if trained to enhance a single marker (or co-localized group of markers), it could introduce artefacts where it forces signal localization to those areas even for others. What happens if you feed in images with scrambled pixel locations, does it still say the structures are where the training data says they should be? What about markers with different localization from the training set? If you feed those in, does it force them to the location expected by the training data or does it retain their differential true localization and simply enhance the signal?

The image restoration neural network was used as in Weigert et al., 2018. The model was trained independently for each marker. Each trained model was used only on the corresponding marker and with the same imaging conditions as the training images. From visual inspection, the fluorescent signal in the restored images was consistent with the signal in the raw images, both for interphase and mitotic cells. We found very few artefacts of the restoration (small bright or dark areas) that were discarded. We did not try to restore scrambled images or images of mismatched markers.

Reviewer #2 (Public Review):

Summary:

The authors have generated human iPSC cells constitutively expressing the mNG21-10 and tested them by endogenous tagging multiple genes with mNG211 (several tagged iPS cell lines clones were isolated). With this tool, they have explored several weakly expressed cytokinesis genes and gained insights into how cytokinesis occurs.

Strengths:

Human iPSC cells are used.

Weaknesses:

i) The manuscript is extremely incremental, no improvements are present in the split-fluorescent (split-FP) protein variant used nor in the approach for endogenous tagging with split-FPs (both of them are already very well established and used in literature as well as in different cell types).

Although split fluorescent proteins and the endogenous tagging methodology had been developed previously, their use in human stem cells has not been explored. We argue that human iPSCs are a valuable model for cell biologists to study cellular processes in differentiating cells in an isogenic context for proper comparison. Many normal human cell types have not been studied at the cellular/subcellular level, and this tool will enable those studies. Importantly, other existing cell lines required transformation to persist in culture and represent a single, differentiated cell type that is not normal. Moreover, the protocols that we developed along with this methodology (e.g. workflows for iPSC clonal isolation that include automated colony screening and Nanopore sequencing) will be useful to other groups undertaking gene editing in human cells. Therefore, we argue that our work opens new doors for future cell biology studies.

ii) The fluorescence intensity of the split mNeonGreen appears rather low, for example in Figure 2C the H2BC11, ANLN, SOX2, and TUBB3 signals are very noisy (differences between the structures observed are almost absent). For low-expression targets, this is an important limitation. This is also stated by the authors but image restoration could not be the best solution since a lot of biologically relevant information will be lost anyway.

The split mNeonGreen tag is one of the brighter fluorescent proteins that is available. The low expression that the reviewer refers to for H2BC11, ANLN, TUBB3 and SOX2 is expected based on their predicted expression levels. Further, these images were taken with cells in dishes using lower resolution imaging and were not intended to be used for quantification. As shown in the images in Figures 3H, when using a different microscope with different optical settings and higher magnification, the localization is very clear and quantifiable without needing to use restoration (e.g., compare H2BC11 and ANLN). Using microscopes with high NA objectives, lasers and EMCCD or sCMOS cameras with high sensitivity can sufficiently detect levels of very weakly expressing proteins that can be quantified above background and compared across cells. It is worth noting that each tag may be studied in very different contexts. For example, ANLN will be useful for studies of cytokinesis, while the loss of SOX2 expression and gain of TUBB3 expression may be used to screen for differentiation rather than for localization per se. The reason for endogenous tagging is to study proteins at their native levels rather than using over-expression or fixation with antibodies where artefacts can be introduced. Endogenous tags tag will also enable studies of dynamic changes in localization during differentiation in an isogenic background as described previously.

Importantly, image restoration is not required to image any of these probes! We use it to demonstrate how a researcher can increase the temporal resolution of imaging weakly-expressed proteins for extended periods of time. This data can be used to compare patterns of localization and reveal how patterns change with time and during differentiation. Imaging with fewer timepoints and altered optical settings will still permit researchers to extract quantifiable information from the raw data without requiring image restoration.

iii) There is no comparison with other existing split-FP variants, methods, or imaging and it is unclear what the advantages of the system are.

We are not sure what the reviewer means by this comment. In the future, we plan to incorporate an additional split-FP variant (e.g., split sfCherry) in this iPSC line to enable the imaging of more than one protein in the same cell. However, the split mNeonGreen system is still amenable for use with dyes with different fluorescence spectra that can mark other cellular components, especially for imaging over shorter timespans. In addition to tagging efficiency, the main advantage of split FPs is its scale, as demonstrated by the OpenCell project by tagging 1,310 proteins endogenously (Cho et al., 2022). We developed protocols that facilitate the identification of edited cell lines with high throughput. We also used multiple imaging methods throughout the study that relied on the use of different microscopes and flow cytometry, demonstrating the flexibility of this tagging system. Even for more weakly expressing proteins, the probe could be sufficiently visualized by multiple systems. Such endogenous tags can be used for everything from simply knowing when cells have differentiated (e.g., loss of SOX2 expression, gain of differentiation markers), to studying biological processes over a range of timescales.

Reviewer #3 (Public Review):

The authors report on the engineering of an induced Pluripotent Stem Cell (iPSC) line that harbours a single copy of a split mNeonGreen, mNG2(1-10). This cell line is subsequently used to take endogenous protein with a smaller part of mNeonGreen, mNG2(11), enabling the complementation of mNG into a fluorescent protein that is then used to visualize the protein. The parental cell is validated and used to construct several iPSC lines with endogenously tagged proteins. These are used to visualize and quantify endogenous protein localisation during mitosis.

I see the advantage of tagging endogenous loci with small fragments, but the complementation strategy has disadvantages that deserve some attention. One potential issue is the level of the mNG2(1-10). Is it clear that the current level is saturating? Based on the data in Figure S3, the expression levels and fluorescence intensity levels show a similar dose-dependency which is reassuring, but not definitive proof that all the mNG2(11)-tagged protein is detected.

We have not quantified the levels of mNG21-10 expression directly. However, the increase in fluorescence observed with highly expressed proteins (e.g., ACTB) supports that mNG21-10 levels must be sufficiently high to permit differences among endogenous proteins with vastly different expression levels. To ensure high expression, we used a previously validated expression system comprised of the CAG promoter integrated at the AAVS1 locus, which has previously been used to provide high and stable transgene expression (e.g. Oceguera-Yanez et al., 2016). We acknowledge that it is difficult to confirm that all of the endogenous mNG211-tagged protein is ‘detectable’.

Do the authors see a difference in fluorescence intensity for homo- and heterozygous cell lines that have the same protein tagged with mNG2(11)? One would expect two-fold differences, or not?

To answer this question, we measured the fluorescence intensity of homozygous and heterozygous clones carrying smNG2-anillin and smNG2-RhoA. We found homozygous clones that were approximately twice as bright as the corresponding heterozygous clones (Fig. S4H and I). This suggests that the complementation between mNG21-10 and mNG211 occurs efficiently over a range of mNG211 expression, since anillin is expressed weakly and RhoA is expressed more strongly in iPSCs. However, we also observed some homozygous clones that were not brighter than the corresponding heterozygous clones, which could be due to undetected byproducts of CRISPR or clonal variation in protein expression.

Related to this, would it be favourable to have a homozygous line for expressing mNG2(1-10)?

Our heterozygous cell line leaves the other AAVS1 allele available for integrations of other transgenes for future experiments. While a homozygous line could express more mNG2(1-10), it does not seem to be rate-limiting even with a highly-expressed protein like beta-actin, and we are not sure that it is necessary. The value gained by having the free allele could outweigh the difference in mNG2(1-10) levels.

The complementation seems to work well for the proteins that are tested. Would this also work for secreted (or other organelle-resident) proteins, for which the mNG2(11) tag is localised in a membrane-enclosed compartment?

The interaction between the 1-10 and 11 fragments is strong and should be retained when proteins are secreted. It was recently shown that secreted proteins tagged with GFP11 can be detected when interacting with GFP1-10 in the extracellular space, albeit using over-expression (Minegishi et al., 2023). However, in our work, the mNG21-10 fragment is cytosolic and we have only explored proteins localized to the nucleus or the cytoplasm similar to Cho et al., (2022). By GO annotation, 75% of human proteins are present in the cytoplasm and/or nucleus, which still covers a wide range of proteins of interest. Future versions of our line could include incorporating organelle-targeting peptides to drive the large fragment to specific, non-cytosolic locations.

The authors present a technological advance and it would be great if others could benefit from this as well by having access to the cell lines.

As discussed below, some of the resources are already available, and we are working to make the mNG21-10 cell line available for distribution.

Recommendations for the authors:

Reviewer #2 (Recommendations For The Authors):

The manuscript is methodological, the main achievement is the generation of a stable iPSC with the split Neon system available for the scientific community. Although it is technically solid, the judgement of this reviewer is that the manuscript should be considered for a more specialised/methodological/resource-based journal.

Indeed, we have submitted this article under the “tools and resources” category of eLife, which publishes methodology-centered papers of high technical quality. We felt this was a good venue for the audience that it can reach compared to more specialized journals that may be more limited in scope. For example, our system will be a useful resource for cell biologists and they are more likely to see it in eLife compared to more specialized journals.

Reviewer #3 (Recommendations For The Authors):

(1) The authors present a technological advance and it would be great if others can benefit from this as well. Therefore access to the materials (and data) would be valuable (the authors do a great job by listing all the repair templates and primers).

We have added several pieces of data and information to the supplementary materials, as described below.

For instance:

What is the (complete/plasmid) sequence of the AAVS1-mNG2(1-10) repair plasmid? Will it be deposited at Addgene?

The plasmids used in this paper are now available on Addgene, along with their sequences [ID 206042 for pAAVS1-Puro-CAG-mNG2(1-10) and 206043 for pH2B-mNG2(11)].

The ImageJ code for the detection of colonies is interesting and potentially valuable. Will the code be shared (e.g. at Github, or as supplemental text)?

The ImageJ macro has been uploaded to the CMCI Github page (https://github.com/CMCI/colony_screening). The parameters are optimized to perform segmentation on images obtained using a Cytation5 microscope with our specific settings, but they can be tweaked for any other sets of images. The following text has been added to the methods section: “The code for this macro is available on Github (https://github.com/CMCI/colony_screening)”.

The cell line with the mNG2(1-10) as well as other cell lines can be of interest to others. Will the cell lines be made available? If so, can the authors indicate how?

We are in the process of depositing our cell line in a public repository. This process may take some time for quality control. For now, the cells can be made available by requesting them from the corresponding authors.

(2) How well does the ImageJ macro for detection of the colonies in the well work? Is there any comparison of analysis by a human vs. the macro?

In our most recent experiment, the colony screening macro correctly identified 99.5% of wells compared to manual annotation (83/84 positive wells and 108/108 negative wells). For each 96-well plate, imaging takes 25 minutes, and it takes 7 minutes for analysis. Despite a few false negatives, we expect this macro to be useful for large-scale experiments where multiple 96-well plates need to be screened, which would take hours manually.

(3) The CDH labeling was not readily detected by FACS, but was visible by microscopy. Is the labeling potentially disturbed by the procedure (low extracellular calcium + trypsin?) to prepare the cell for FACS?

It is not clear why the CDH labelling was not detected by FACS. As the reviewer suggests, there could be several reasons: E-cadherin could be broken down by the dissociation reagent (Accutase), or recycled into the cell following the loss of adhesion and the low extracellular calcium in PBS. However, the C-terminal intracellular tail of E-cadherin was tagged, which should not be affected by Accutase. Moreover, recycling into the cell should still result in a detectable fluorescent signal. Notably, the flow cytometry experiments were done as quickly as possible after dissociation to minimize the time that E-cadherin could be degraded or recycled. We also resuspended the cells in MTeSR Plus media instead of PBS, and compared cells grown on iMatrix511 to those grown on Matrigel in case differences in the extracellular matrix affected Ecadherin expression. Another possibility is that the microscopy used for detection of E-cadherin in cells involved using a sweptfield livescan confocal microscope with high NA objective, 100mW 488nm laser and an EMCCD camera with high sensitivity, and perhaps this combination permitted detection better than the detector on the BD FACSMelody used for FACs.

(4) The authors write that the "Tubulin was cytosolic during interphase" which is surprising (and see also figure 3H), as I was expecting it to be incorporated in microtubules. May this be an issue of insufficient resolution (if I'm right this was imaged with 20x, NA=0.35 and so the resolution could be improved by imaging at higher NA)?

Indeed, as the reviewer points out, our terminology (cytosol vs. microtubule) reflects the low resolution of the imaging for the cell populations in dishes and the individual alpha-tubulin monomers being labelled with the mNG211 tag, which are present as cytoplasmic monomers as well as polymers on microtubules. However, even in this image (Fig. 2C), the mitotic spindle microtubules are visible as they are so robust compared to the interphase microtubules. Notably, when we imaged cells from the cloned tagged cell line using a microscope designed for live imaging with a higher NA objective (see above), endogenous tagged TUBA1B was even more clearly visible in spindle microtubules, and was weakly observed in some microtubules in interphase cells, although they are slightly out of focus (Fig. 3H). If we had focused on a lower focal plane where the interphase cells are located and altered the optical settings, we would see more microtubules.

(5) It would be nice to have access to the Timelapse data as supplemental movies (.e.g from the experiments shown in Figure 4).

We have added the movies corresponding to the timeplase images as supplementary movies (Movies S1-6), with the raw and restored movies shown side-by-side.

(6) In Figure 3B, the order of the colors in the bar is reversed relative to the order of the legend. Would it be possible to use the same order? That makes it easier for me (as a colorblind person) to match the colors in the figure with that of the legend.

We have modified the legend in Fig 2B and 3B to be in the same order as the bars.

Reviewer #1 (Public Review):

Summary:

In this manuscript the authors have applied an asymmetric split mNeonGreen2 (mNG2) system to human iPSCs. By integrating a constitutively expressed long fragment of mNG2 at the AAVS1 locus, this allows other proteins to be tagged through the use of available ssODN donors. This removes the need to generate long AAV donors for tagging, thus greatly facilitating high-throughput tagging efforts. The authors then demonstrate the feasibility of the method by successfully tagging 9 markers expressed in iPSC at various, and one expressed upon endoderm differentiation. Several additional differentiation markers were also successfully tagged but not subsequently tested for expression/visibility. As one might expect for high-throughput tagging, a few proteins, while successfully tagged at the genomic level, failed to be visible. Finally, to demonstrate the utility of the tagged cells, the authors isolated clones with genes relevant to cytokinesis tagged, and together with an AI to enhance signal to noise ratios, monitored their localization over cell division.

Strengths

Reviewer Comment: Characterization of the mNG2 tagged parental iPSC line was well and carefully done including validation of a single integration, the presence of markers for continued pluripotency, selected off-target analysis and G-banding-based structural rearrangement detection.<br /> The ability to tag proteins with simple ssODNs in iPSC capable of multi-lineage differentiation will undoubtedly be useful for localization tracking and reporter line generation.<br /> Validation of clone genotypes was carefully performed and highlights the continued need for caution with regards to editing outcomes.

Weaknesses

Reviewer Comment: IF and flow cytometry figures lack quantification and information on replication. How consistent is the brightness and localization of the markers? How representative are the specific images? Stability is mentioned in the text but data on the stability of expression/brightness is not shown.

Author Response: To address this comment, we have quantified the mean fluorescence intensity of the tagged cell populations in Fig. S3B-T. This data correlates well with the expected expression levels of each gene relative to the others (Fig. S3A), apart from CDH1 and RACGAP1, which are described in the discussion.

Reviewer Reply: Great, thanks.

Reviewer Comment: The localization of markers, while consistent with expectations, is not validated by a second technique such as antibody staining, and in many cases not even with Hoechst to show nuclear vs cytoplasmic.

Author Response: We find that the localization of each protein is distinct and consistent with previous studies. To address this comment, we have added an overlay of the green fluorescence images with brightfield images to better show the location of the tagged protein relative to the nuclei and cytoplasm. We have also added references to other studies that showed the same localization patterns for these proteins in iPSCs and other relevant cell lines.

Reviewer Reply: There was no question that the localization fit with expectations, however, this still doesn't show that in the same cell the tag is in the same spot. It would have been fairly simple to do for at least a handful of markers, image, fix and stain to demonstrate unequivocally the tag and protein are co-localized. Of course, this isn't damning by any means, it just would have been nice.

Reviewer Comment: For the multi-germ layer differentiation validation, NCAM is also expressed by ectoderm, so isn't a good solo marker for mesoderm as it was used. Indeed, the kit used for the differentiation suggests Brachyury combined with either NCAM or CXCR4, not NCAM alone.

Author Response: Since Brachyury is the most common mesodermal marker, we first tested differentiation using anti-Brachyury antibodies, but they did not work well for flow cytometry. We then switched to anti-NCAM antibodies. Since we used a kit for directed differentiation of iPSCs into the mesodermal lineage, NCAM staining should still report for successful differentiation. In the context of mixed differentiation experiments (embryoid body formation or teratoma assay), NCAM would not differentiate between ectoderm and mesoderm. The parental cells (201B7) have also been edited at the AAVS1 locus in multiple other studies, with no effect on their differentiation potential.

Reviewer Reply: This is placing a lot of trust in the kit that it only makes what it says it makes. It could have been measured by options other than flow such as qPCR, Western blot, or imaging, but fine.

Reviewer Comment: Only a single female parental line has been generated and characterized. It would have been useful to have several lines and both male and female to allow sex differences to be explored.

Author Response: We agree that it would be interesting (and important) to study differences in protein localization between female and male cell types, and from different individuals with different genetic backgrounds. We see our tool as opening a door for cell biology to move away from randomly collected, transformed, differentiated cell types to more directed comparative studies of distinct normal cell types. Since few studies of cell biological processes have been done in normal cells, a first step is to understand how processes compare in an isogenic background, then future studies can reveal how they compare with other individuals and sexes. We hope that either our group or others will continue to build similar lines so that these studies can be done.

Reviewer Reply: Fair enough.

Reviewer Comment: The AI-based signal to noise enhancement needs more details and testing. Such models can introduce strong assumptions and thus artefacts into the resolved data. Was the model trained on all markers or were multiple models trained on a single marker each? For example, if trained to enhance a single marker (or co-localized group of markers), it could introduce artefacts where it forces signal localization to those areas even for others. What happens if you feed in images with scrambled pixel locations, does it still say the structures are where the training data says they should be? What about markers with different localization from the training set. If you feed those in, does it force them to the location expected by the training data or does it retain their differential true localization and simply enhance the signal?

Author Response: The image restoration neural network was used as in Weigert et al., 2018. The model was trained independently for each marker. Each trained model was used only on the corresponding marker and with the same imaging conditions as the training images. From visual inspection, the fluorescent signal in the restored images was consistent with the signal in the raw images, both for interphase and mitotic cells. We found very few artefacts of the restoration (small bright or dark areas) that were discarded. We did not try to restore scrambled images or images of mismatched markers.

Reviewer Reply: I understand. What I'm saying is that for the restoration technique to be useful you need to know that it won't introduce artefacts if you have an unexpected localization. Think of it this way, if you already know the localization, then there's no point measuring it. If you don't, or there's a possibility that it is somewhere unexpected, then you need to know with confidence that your algorithm will be able to accurately detect that unexpected localization. As such, it would be extremely important to validate that your restoration algorithm will not bias the results to the expected localization if the true localization is unexpected/not seen in the training dataset. It would have been extremely trivial to run this analysis and I do not feel this comment has been in any way adequately addressed.

Reviewer #3 (Public Review):

The authors report on the engineering of an induced Pluripotent Stem Cell (iPSC) line that harbours a single copy of a split mNeonGreen, mNG2(1-10). This cell line is subsequently used to take endogenous protein with a smaller part of mNeonGreen, mNG2(11), enabling complementation of mNG into a fluorescent protein that is then used to visualize the protein. The parental cell is validated and used to construct several iPSC line with endogenously tagged proteins. These are used to visualize and quantify endogenous protein localisation during mitosis.

I see the advantage of tagging endogenous loci with small fragments, but the complementation strategy has disadvantages that deserve some attention. One potential issue is the level of the mNG2(1-10). In addition, this may probably not work for organelle-resident proteins, where the mNG2(11) tag is localised in a membrane enclosed compartment.

Overall the tools and resources reported in this paper will be valuable for the community that aims to study proteins at endogenous levels.

Reviewer #1 (Public Review):

This is an interesting study investigating the mechanisms underlying membrane targeting of the NLRP3 inflammasome and reporting a key role for the palmitoylation-depalmitoylation cycle of cys130 in NRLP3. The authors identify ZDHHC3 and APT2 as the specific ZDHHC and APT/ABHD enzymes that are responsible for the s-acylation and de-acylation of NLRP3, respectively. They show that the levels of ZDHHC3 and APT2, both localized at the Golgi, control the level of palmitoylation of NLRP3. The S-acylation-mediated membrane targeting of NLRP3 cooperates with polybasic domain (PBD)-mediated PI4P-binding to target NLRP3 to the TGN under steady-state conditions and to the disassembled TGN induced by the NLRP3 activator nigericin.

However, the study has several weaknesses in its current form as outlined below.

(1) The novelty of the findings concerning cys130 palmitoylation in NLRP3 is unfortunately compromised by recent reports on the acylation of different cysteines in NLRP3 (PMID: 38092000), including palmitoylation of the very same cys130 in NLRP3 (Yu et al https://doi.org/10.1101/2023.11.07.566005), which was shown to be relevant for NLRP3 activation in cell and animal models. What remains novel and intriguing is the finding that NLRP3 activators induce an imbalance in the acylation-deacylation cycle by segregating NLRP3 in late Golgi/endosomes from de-acylating enzymes confined in the Golgi. The interesting hypothesis put forward by the authors is that the increased palmitoylation of cys130 would finally contribute to the activation of NLRP3. However, the authors should clarify the trafficking pathway of acylated-NLRP3. This pathway should, in principle, coincide with that of TGN46 which constitutively recycles from the TGN to the plasma membrane and is trapped in endosomes upon treatment with nigericin.

(2) To affect the S-acylation, the authors used 16 hrs treatment with 2-bromopalmitate (2-BP). In Figure 1f, it is quite clear that NLRP3 in 2-BP treated cells completely redistributed in spots dispersed throughout the cells upon nigericin treatment. What is the Golgi like in those cells? In other words, does 2-BP alter/affect Golgi morphology? What about PI4P levels after 2-BP treatment? These are important missing pieces of data since both the localization of many proteins and the activity of one key PI4K in the Golgi (i.e. PI4KIIalpha) are regulated by palmitoylation.

(3) The authors argue that the spots observed with NLRP-GFP result from non-specific effects mediated by the addition of the GFP tag to the NLRP3 protein. However, puncta are visible upon nigericin treatment, as a hallmark of endosomal activation. How do the authors reconcile these data? Along the same lines, the NLRP3-C130S mutant behaves similarly to wt NLRP3 upon 2-BP treatment (Figure 1h). Are those NLRP3-C130S puncta positive for endosomal markers? Are they still positive for TGN46? Are they positive for PI4P?

(4) The authors expressed the minimal NLRP3 region to identify the domain required for NLRP3 Golgi localization. These experiments were performed in control cells. It might be informative to perform the same experiments upon nigericin treatment to investigate the ability of NLRP3 to recognize activating signals. It has been reported that PI4P increases on Golgi and endosomes upon NG treatment. Hence, all the differences between the domains may be lost or preserved. In parallel, also the timing of such recruitment upon nigericin treatment (early or late event) may be informative for the dynamics of the process and of the contribution of the single protein domains.

(5) As noted above for the chemical inhibitors (1) the authors should check the impact of altering the balance between acyl transferase and de-acylases on the Golgi organization and PI4P levels. What is the effect of overexpressing PATs on Golgi functions?

zum vergleich wärs interessant, wie hart die in MINT fächern abkackt, also bei den exakten wissenschaften, wo man richtig und falsch exakt messen kann. bei den schwätzer-"wissenschaften" gehts den ganzen tag nur um hypothesen, die nie überprüft werden...

6:15 "born this way" versus "soziales konstrukt" ... nature versus nurture.<br /> siehe auch: calhoun experiments on overpopulation, universe 25, 1958<br /> bei übervölkerung sieht man in städten (in zentren) "dekadenz" und "sittenverfall" ...<br /> also aggression, homosexualität, kaputte familien (mütter lassen ihre kinder verhungern), ...<br /> und am rand der städte sieht man "the beautiful ones" (aussteiger, einsiedler, einzelgänger)<br /> die komplett alleine bleiben, und den ganzen tag ihr fell pflegen.<br /> (die beautiful ones sind die führer, avantgarde, pioniere, ... die einen neuen lebensraum suchen wollen,<br /> aber die am rand vom mauskäfig blockiert werden)

how to win friends and influence people summary

这为什么会造成信号的损失

Author Response

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

Public Comments

Reviewer 1

(1) Despite the well-established role of Netrin-1 and UNC5C axon guidance during embryonic commissural axons, it remains unclear which cell type(s) express Netrin-1 or UNC5C in the dopaminergic axons and their targets. For instance, the data in Figure 1F-G and Figure 2 are quite confusing. Does Netrin-1 or UNC5C express in all cell types or only dopamine-positive neurons in these two mouse models? It will also be important to provide quantitative assessments of UNC5C expression in dopaminergic axons at different ages.

Netrin-1 is a secreted protein and in this manuscript we did not examine what cell types express Netrin-1. This question is not the focus of the study and we consider it irrelevant to the main issue we are addressing, which is where in the forebrain regions we examined Netrin-1+ cells are present. As per the reviewer’s request we include below images showing Netrin-1 protein and Netrin-1 mRNA expression in the forebrain. In Figure 1 below, we show a high magnification immunofluorescent image of a coronal forebrain section showing Netrin-1 protein expression.

Author response image 1.

This confocal microscope image shows immunofluorescent staining for Netrin-1 (green) localized around cell nuclei (stained by DAPI in blue). This image was taken from a coronal section of the lateral septum of an adult male mouse. Scale bar = 20µm

In Figures 2 and 3 below we show low and high magnification images from an RNAscope experiment confirming that cells in the forebrain regions examined express Netrin-1 mRNA.

Author response image 2.

This confocal microscope image of a coronal brain section of the medial prefrontal cortex of an adult male mouse shows Netrin-1 mRNA expression (green) and cell nuclei (DAPI, blue). Brain regions are as follows: Cg1: Anterior cingulate cortex 1, DP: dorsopeduncular cortex, fmi: forceps minor of the corpus callosum, IL: Infralimbic Cortex, PrL: Prelimbic Cortex

Author response image 3.

A higher resolution image from the same sample as in Figure 2 shows Netrin-1 mRNA (green) and cell nuclei (DAPI; blue). DP = dorsopeduncular cortex

Regarding UNC5c, this receptor homologue is expressed by dopamine neurons in the rodent ventral tegmental area (Daubaras et al., 2014; Manitt et al., 2010; Phillips et al., 2022). This does not preclude UNC5c expression in other cell types. UNC5c receptors are ubiquitously expressed in the brain throughout development, performing many different developmental functions (Kim and Ackerman, 2011; Murcia-Belmonte et al., 2019; Srivatsa et al., 2014). In this study we are interested in UNC5c expression by dopamine neurons, and particularly by their axons projecting to the nucleus accumbens. We therefore used immunofluorescent staining in the nucleus accumbens, showing UNC5 expression in TH+ axons. This work adds to the study by Manitt et al., 2010, which examined UNC5 expression in the VTA. Manitt et al. used Western blotting to demonstrate that UNC5 expression in VTA dopamine neurons increases during adolescence, as can be seen in the following figure:

 References:

Daubaras M, Bo GD, Flores C. 2014. Target-dependent expression of the netrin-1 receptor, UNC5C, in projection neurons of the ventral tegmental area. Neuroscience 260:36–46. doi:10.1016/j.neuroscience.2013.12.007

Kim D, Ackerman SL. 2011. The UNC5C Netrin Receptor Regulates Dorsal Guidance of Mouse Hindbrain Axons. J Neurosci 31:2167–2179. doi:10.1523/jneurosci.5254-10.20110.2011

Manitt C, Labelle-Dumais C, Eng C, Grant A, Mimee A, Stroh T, Flores C. 2010. Peri-Pubertal Emergence of UNC-5 Homologue Expression by Dopamine Neurons in Rodents. PLoS ONE 5:e11463-14. doi:10.1371/journal.pone.0011463

Murcia-Belmonte V, Coca Y, Vegar C, Negueruela S, Romero C de J, Valiño AJ, Sala S, DaSilva R, Kania A, Borrell V, Martinez LM, Erskine L, Herrera E. 2019. A Retino-retinal Projection Guided by Unc5c Emerged in Species with Retinal Waves. Current Biology 29:1149-1160.e4. doi:10.1016/j.cub.2019.02.052

Phillips RA, Tuscher JJ, Black SL, Andraka E, Fitzgerald ND, Ianov L, Day JJ. 2022. An atlas of transcriptionally defined cell populations in the rat ventral tegmental area. Cell Reports 39:110616. doi:10.1016/j.celrep.2022.110616

Srivatsa S, Parthasarathy S, Britanova O, Bormuth I, Donahoo A-L, Ackerman SL, Richards LJ, Tarabykin V. 2014. Unc5C and DCC act downstream of Ctip2 and Satb2 and contribute to corpus callosum formation. Nat Commun 5:3708. doi:10.1038/ncomms4708

(2) Figure 1 used shRNA to knockdown Netrin-1 in the Septum and these mice were subjected to behavioral testing. These results, again, are not supported by any valid data that the knockdown approach actually worked in dopaminergic axons. It is also unclear whether knocking down Netrin-1 in the septum will re-route dopaminergic axons or lead to cell death in the dopaminergic neurons in the substantia nigra pars compacta?

First we want to clarify and emphasize, that our knockdown approach was not designed to knock down Netrin-1 in dopamine neurons or their axons. Our goal was to knock down Netrin-1 expression in cells expressing this guidance cue gene in the dorsal peduncular cortex.

We have previously established the efficacy of the shRNA Netrin-1 knockdown virus used in this experiment for reducing the expression of Netrin-1 (Cuesta et al., 2020). The shRNA reduces Netrin-1 levels in vitro and in vivo.

We agree that our experiments do not address the fate of the dopamine axons that are misrouted away from the medial prefrontal cortex. This research is ongoing, and we have now added a note regarding this to our manuscript.

Our current hypothesis, based on experiments being conducted as part of another line of research in the lab, is that these axons are rerouted to a different brain region which they then ectopically innervate. In these experiments we are finding that male mice exposed to tetrahydrocannabinol in adolescence show reduced dopamine innervation in the medial prefrontal cortex in adulthood but increased dopamine input in the orbitofrontal cortex. In addition, these mice show increased action impulsivity in the Go/No-Go task in adulthood (Capolicchio et al., Society for Neuroscience 2023 Abstracts)

References:

Capolicchio T., Hernandez, G., Dube, E., Estrada, K., Giroux, M., Flores, C. (2023) Divergent outcomes of delta 9 - tetrahydrocannabinol in adolescence on dopamine and cognitive development in male and female mice. Society for Neuroscience, Washington, DC, United States [abstract].

Cuesta S, Nouel D, Reynolds LM, Morgunova A, Torres-Berrío A, White A, Hernandez G, Cooper HM, Flores C. 2020. Dopamine Axon Targeting in the Nucleus Accumbens in Adolescence Requires Netrin-1. Frontiers Cell Dev Biology 8:487. doi:10.3389/fcell.2020.00487

(3) Another issue with Figure1J. It is unclear whether the viruses were injected into a WT mouse model or into a Cre-mouse model driven by a promoter specifically expresses in dorsal peduncular cortex? The authors should provide evidence that Netrin-1 mRNA and proteins are indeed significantly reduced. The authors should address the anatomic results of the area of virus diffusion to confirm the virus specifically infected the cells in dorsal peduncular cortex.

All the virus knockdown experiments were conducted in wild type mice, we added this information to Figure 1k.

The efficacy of the shRNA in knocking down Netrin-1 was demonstrated by Cuesta et al. (2020) both in vitro and in vivo, as we show in our response to the reviewer’s previous comment above.

We also now provide anatomical images demonstrating the localization of the injection and area of virus diffusion in the mouse forebrain. In Author response image 4 below the area of virus diffusion is visible as green fluorescent signal.

Author response image 4.

Fluorescent microscopy image of a mouse forebrain demonstrating the localization of the injection of a virus to knock down Netrin-1. The location of the virus is in green, while cell nuclei are in blue (DAPI). Abbreviations: DP: dorsopeduncular cortex IL: infralimbic cortex

References:

Cuesta S, Nouel D, Reynolds LM, Morgunova A, Torres-Berrío A, White A, Hernandez G, Cooper HM, Flores C. 2020. Dopamine Axon Targeting in the Nucleus Accumbens in Adolescence Requires Netrin-1. Frontiers Cell Dev Biology 8:487. doi:10.3389/fcell.2020.00487

(4) The authors need to provide information regarding the efficiency and duration of knocking down. For instance, in Figure 1K, the mice were tested after 53 days post injection, can the virus activity in the brain last for such a long time?

In our study we are interested in the role of Netrin-1 expression in the guidance of dopamine axons from the nucleus accumbens to the medial prefrontal cortex. The critical window for these axons leaving the nucleus accumbens and growing to the cortex is early adolescence (Reynolds et al., 2018b). This is why we injected the virus at the onset of adolescence, at postnatal day 21. As dopamine axons grow from the nucleus accumbens to the prefrontal cortex, they pass through the dorsal peduncular cortex. We disrupted Netrin-1 expression at this point along their route to determine whether it is the Netrin-1 present along their route that guides these axons to the prefrontal cortex. We hypothesized that the shRNA Netrin-1 virus would disrupt the growth of the dopamine axons, reducing the number of axons that reach the prefrontal cortex and therefore the number of axons that innervate this region in adulthood.

We conducted our behavioural tests during adulthood, after the critical window during which dopamine axon growth occurs, so as to observe the enduring behavioral consequences of this misrouting. This experimental approach is designed for the shRNa Netrin-1 virus to be expressed in cells in the dorsopeduncular cortex when the dopamine axons are growing, during adolescence.

 References:

Capolicchio T., Hernandez, G., Dube, E., Estrada, K., Giroux, M., Flores, C. (2023) Divergent outcomes of delta 9 - tetrahydrocannabinol in adolescence on dopamine and cognitive development in male and female mice. Society for Neuroscience, Washington, DC, United States [abstract].

Reynolds LM, Yetnikoff L, Pokinko M, Wodzinski M, Epelbaum JG, Lambert LC, Cossette M-P, Arvanitogiannis A, Flores C. 2018b. Early Adolescence is a Critical Period for the Maturation of Inhibitory Behavior. Cerebral cortex 29:3676–3686. doi:10.1093/cercor/bhy247

(5) In Figure 1N-Q, silencing Netrin-1 results in less DA axons targeting to infralimbic cortex, but why the Netrin-1 knocking down mice revealed the improved behavior?

This is indeed an intriguing finding, and we have now added a mention of it to our manuscript. We have demonstrated that misrouting dopamine axons away from the medial prefrontal cortex during adolescence alters behaviour, but why this improves their action impulsivity ability is something currently unknown to us. One potential answer is that the dopamine axons are misrouted to a different brain region that is also involved in controlling impulsive behaviour, perhaps the dorsal striatum (Kim and Im, 2019) or the orbital prefrontal cortex (Jonker et al., 2015).

We would also like to note that we are finding that other manipulations that appear to reroute dopamine axons to unintended targets can lead to reduced action impulsivity as measured using the Go No Go task. As we mentioned above, current experiments in the lab, which are part of a different line of research, are showing that male mice exposed to tetrahydrocannabinol in adolescence show reduced dopamine innervation in the medial prefrontal cortex in adulthood, but increased dopamine input in the orbitofrontal cortex. In addition, these mice show increased action impulsivity in the Go/No-Go task in adulthood (Capolicchio et al., Society for Neuroscience 2023 Abstracts)

References

Capolicchio T., Hernandez, G., Dube, E., Estrada, K., Giroux, M., Flores, C. (2023) Divergent outcomes of delta 9 - tetrahydrocannabinol in adolescence on dopamine and cognitive development in male and female mice. Society for Neuroscience, Washington, DC, United States [abstract].

Jonker FA, Jonker C, Scheltens P, Scherder EJA. 2015. The role of the orbitofrontal cortex in cognition and behavior. Rev Neurosci 26:1–11. doi:10.1515/revneuro2014-0043 Kim B, Im H. 2019. The role of the dorsal striatum in choice impulsivity. Ann N York Acad Sci 1451:92–111. doi:10.1111/nyas.13961

(6) What is the effect of knocking down UNC5C on dopamine axons guidance to the cortex?

We have found that mice that are heterozygous for a nonsense Unc5c mutation, and as a result have reduced levels of UNC5c protein, show reduced amphetamine-induced locomotion and stereotypy (Auger et al., 2013). In the same manuscript we show that this effect only emerges during adolescence, in concert with the growth of dopamine axons to the prefrontal cortex. This is indirect but strong evidence that UNC5c receptors are necessary for correct adolescent dopamine axon development.

References

Auger ML, Schmidt ERE, Manitt C, Dal-Bo G, Pasterkamp RJ, Flores C. 2013. unc5c haploinsufficient phenotype: striking similarities with the dcc haploinsufficiency model. European Journal of Neuroscience 38:2853–2863. doi:10.1111/ejn.12270

(7) In Figures 2-4, the authors only showed the amount of DA axons and UNC5C in NAcc. However, it remains unclear whether these experiments also impact the projections of dopaminergic axons to other brain regions, critical for the behavioral phenotypes. What about other brain regions such as prefrontal cortex? Do the projection of DA axons and UNC5c level in cortex have similar pattern to those in NAcc?

UNC5c receptors are expressed throughout development and are involved in many developmental processes (Kim and Ackerman, 2011; Murcia-Belmonte et al., 2019; Srivatsa et al., 2014). We cannot say whether the pattern we observe here is unique to the nucleus accumbens, but it is certainly not universal throughout the brain.

The brain region we focus on in our manuscript, in addition to the nucleus accumbens, is the medial prefrontal cortex. Close and thorough examination of the prefrontal cortices of adult mice revealed practically no UNC5c expression by dopamine axons. However, we did observe very rare cases of dopamine axons expressing UNC5c. It is not clear whether these rare cases are present before or during adolescence.

Below is a representative set of images of this observation, which is now also included as Supplementary Figure 4:

Author response image 5.

Expression of UNC5c protein in the medial prefrontal cortex of an adult male mouse. Low (A) and high (B) magnification images demonstrate that there is little UNC5c expression in dopamine axons in the medial prefrontal cortex. Here we identify dopamine axons by immunofluorescent staining for tyrosine hydroxylase (TH, see our response to comment #9 regarding the specificity of the TH antibody for dopamine axons in the prefrontal cortex). This figure is also included as Supplementary Figure 4 in the manuscript. Abbreviations: fmi: forceps minor of the corpus callosum, mPFC: medial prefrontal cortex.

References:

Kim D, Ackerman SL. 2011. The UNC5C Netrin Receptor Regulates Dorsal Guidance of Mouse Hindbrain Axons. J Neurosci 31:2167–2179. doi:10.1523/jneurosci.5254- 10.20110.2011

Murcia-Belmonte V, Coca Y, Vegar C, Negueruela S, Romero C de J, Valiño AJ, Sala S, DaSilva R, Kania A, Borrell V, Martinez LM, Erskine L, Herrera E. 2019. A Retino-retinal Projection Guided by Unc5c Emerged in Species with Retinal Waves. Current Biology 29:1149-1160.e4. doi:10.1016/j.cub.2019.02.052

Srivatsa S, Parthasarathy S, Britanova O, Bormuth I, Donahoo A-L, Ackerman SL, Richards LJ, Tarabykin V. 2014. Unc5C and DCC act downstream of Ctip2 and Satb2 and contribute to corpus callosum formation. Nat Commun 5:3708. doi:10.1038/ncomms4708

(8) Can overexpression of UNC5c or Netrin-1 in male winter hamsters mimic the observations in summer hamsters? Or overexpression of UNC5c in female summer hamsters to mimic the winter hamster? This would be helpful to confirm the causal role of UNC5C in guiding DA axons during adolescence.

This is an excellent question. We are very interested in both increasing and decreasing UNC5c expression in hamster dopamine axons to see if we can directly manipulate summer hamsters into winter hamsters and vice versa. We are currently exploring virus-based approaches to design these experiments and are excited for results in this area.

(9) The entire study relied on using tyrosine hydroxylase (TH) as a marker for dopaminergic axons. However, the expression of TH (either by IHC or IF) can be influenced by other environmental factors, that could alter the expression of TH at the cellular level.

This is an excellent point that we now carefully address in our methods by adding the following:

In this study we pay great attention to the morphology and localization of the fibres from which we quantify varicosities to avoid counting any fibres stained with TH antibodies that are not dopamine fibres. The fibres that we examine and that are labelled by the TH antibody show features indistinguishable from the classic features of cortical dopamine axons in rodents (Berger et al., 1974; 1983; Van Eden et al., 1987; Manitt et al., 2011), namely they are thin fibres with irregularly-spaced varicosities, are densely packed in the nucleus accumbens, sparsely present only in the deep layers of the prefrontal cortex, and are not regularly oriented in relation to the pial surface. This is in contrast to rodent norepinephrine fibres, which are smooth or beaded in appearance, relatively thick with regularly spaced varicosities, increase in density towards the shallow cortical layers, and are in large part oriented either parallel or perpendicular to the pial surface (Berger et al., 1974; Levitt and Moore, 1979; Berger et al., 1983; Miner et al., 2003). Furthermore, previous studies in rodents have noted that only norepinephrine cell bodies are detectable using immunofluorescence for TH, not norepinephrine processes (Pickel et al., 1975; Verney et al., 1982; Miner et al., 2003), and we did not observe any norepinephrine-like fibres.

Furthermore, we are not aware of any other processes in the forebrain that are known to be immunopositive for TH under any environmental conditions.

To reduce confusion, we have replaced the abbreviation for dopamine – DA – with TH in the relevant panels in Figures 1, 2, 3, and 4 to clarify exactly what is represented in these images. As can be seen in these images, fluorescent green labelling is present only in axons, which is to be expected of dopamine labelling in these forebrain regions.

References:

Berger B, Tassin JP, Blanc G, Moyne MA, Thierry AM (1974) Histochemical confirmation for dopaminergic innervation of the rat cerebral cortex after destruction of the noradrenergic ascending pathways. Brain Res 81:332–337.

Berger B, Verney C, Gay M, Vigny A (1983) Immunocytochemical Characterization of the Dopaminergic and Noradrenergic Innervation of the Rat Neocortex During Early Ontogeny. In: Proceedings of the 9th Meeting of the International Neurobiology Society, pp 263–267 Progress in Brain Research. Elsevier.

Levitt P, Moore RY (1979) Development of the noradrenergic innervation of neocortex. Brain Res 162:243–259.

Manitt C, Mimee A, Eng C, Pokinko M, Stroh T, Cooper HM, Kolb B, Flores C (2011) The Netrin Receptor DCC Is Required in the Pubertal Organization of Mesocortical Dopamine Circuitry. J Neurosci 31:8381–8394.

Miner LH, Schroeter S, Blakely RD, Sesack SR (2003) Ultrastructural localization of the norepinephrine transporter in superficial and deep layers of the rat prelimbic prefrontal cortex and its spatial relationship to probable dopamine terminals. J Comp Neurol 466:478–494.

Pickel VM, Joh TH, Field PM, Becker CG, Reis DJ (1975) Cellular localization of tyrosine hydroxylase by immunohistochemistry. J Histochem Cytochem 23:1–12.

Van Eden CG, Hoorneman EM, Buijs RM, Matthijssen MA, Geffard M, Uylings HBM (1987) Immunocytochemical localization of dopamine in the prefrontal cortex of the rat at the light and electron microscopical level. Neurosci 22:849–862.

Verney C, Berger B, Adrien J, Vigny A, Gay M (1982) Development of the dopaminergic innervation of the rat cerebral cortex. A light microscopic immunocytochemical study using anti-tyrosine hydroxylase antibodies. Dev Brain Res 5:41–52.

(10) Are Netrin-1/UNC5C the only signal guiding dopamine axon during adolescence? Are there other neuronal circuits involved in this process?

Our intention for this study was to examine the role of Netrin-1 and its receptor UNC5C specifically, but we do not suggest that they are the only molecules to play a role. The process of guiding growing dopamine axons during adolescence is likely complex and we expect other guidance mechanisms to also be involved. From our previous work we know that the Netrin-1 receptor DCC is critical in this process (Hoops and Flores, 2017; Reynolds et al., 2023). Several other molecules have been identified in Netrin-1/DCC signaling processes that control corpus callosum development and there is every possibility that the same or similar molecules may be important in guiding dopamine axons (Schlienger et al., 2023).

References:

Hoops D, Flores C. 2017. Making Dopamine Connections in Adolescence. Trends in Neurosciences 1–11. doi:10.1016/j.tins.2017.09.004

Reynolds LM, Hernandez G, MacGowan D, Popescu C, Nouel D, Cuesta S, Burke S, Savell KE, Zhao J, Restrepo-Lozano JM, Giroux M, Israel S, Orsini T, He S, Wodzinski M, Avramescu RG, Pokinko M, Epelbaum JG, Niu Z, Pantoja-Urbán AH, Trudeau L-É, Kolb B, Day JJ, Flores C. 2023. Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism in mice. Nat Commun 14:4035. doi:10.1038/s41467-023-39665-1

Schlienger S, Yam PT, Balekoglu N, Ducuing H, Michaud J-F, Makihara S, Kramer DK, Chen B, Fasano A, Berardelli A, Hamdan FF, Rouleau GA, Srour M, Charron F. 2023. Genetics of mirror movements identifies a multifunctional complex required for Netrin-1 guidance and lateralization of motor control. Sci Adv 9:eadd5501. doi:10.1126/sciadv.add5501

(11) Finally, despite the authors' claim that the dopaminergic axon project is sensitive to the duration of daylight in the hamster, they never provided definitive evidence to support this hypothesis.

By “definitive evidence” we think that the reviewer is requesting a single statistical model including measures from both the summer and winter groups. Such a model would provide a probability estimate of whether dopamine axon growth is sensitive to daylight duration. Therefore, we ran these models, one for male hamsters and one for female hamsters.

In both sexes we find a significant effect of daylength on dopamine innervation, interacting with age. Male age by daylength interaction: F = 6.383, p = 0.00242. Female age by daylength interaction: F = 21.872, p = 1.97 x 10-9. The full statistical analysis is available as a supplement to this letter (Response_Letter_Stats_Details.docx).

Reviewer 3

(1) Fig 1 A and B don't appear to be the same section level.

The reviewer is correct that Fig 1B is anterior to Fig 1A. We have changed Figure 1A to match the section level of Figure 1B.

(2) Fig 1C. It is not clear that these axons are crossing from the shell of the NAC.

We have added a dashed line to Figure 1C to highlight the boundary of the nucleus accumbens, which hopefully emphasizes that there are fibres crossing the boundary. We also include here an enlarged image of this panel:

Author response image 6.

An enlarged image of Figure1c in the manuscript. The nucleus accumbens (left of the dotted line) is densely packed with TH+ axons (in green). Some of these TH+ axons can be observed extending from the nucleus accumbens medially towards a region containing dorsally oriented TH+ fibres (white arrows).

(3) Fig 1. Measuring width of the bundle is an odd way to measure DA axon numbers. First the width could be changing during adult for various reasons including change in brain size. Second, I wouldn't consider these axons in a traditional bundle. Third, could DA axon counts be provided, rather than these proxy measures.

With regards to potential changes in brain size, we agree that this could have potentially explained the increased width of the dopamine axon pathway. That is why it was important for us to use stereology to measure the density of dopamine axons within the pathway. If the width increased but no new axons grew along the pathway, we would have seen a decrease in axon density from adolescence to adulthood. Instead, our results show that the density of axons remained constant.

We agree with the reviewer that the dopamine axons do not form a traditional “bundle”. Therefore, throughout the manuscript we now avoid using the term bundle.

Although we cannot count every single axon, an accurate estimate of this number can be obtained using stereology, an unbiassed method for efficiently quantifying large, irregularly distributed objects. We used stereology to count TH+ axons in an unbiased subset of the total area occupied by these axons. Unbiased stereology is the gold-standard technique for estimating populations of anatomical objects, such as axons, that are so numerous that it would be impractical or impossible to measure every single one. Here and elsewhere we generally provide results as densities and areas of occupancy (Reynolds et al., 2022). To avoid confusion, we now clarify that we are counting the width of the area that dopamine axons occupy (rather than the dopamine axon “bundle”).

References:

Reynolds LM, Pantoja-Urbán AH, MacGowan D, Manitt C, Nouel D, Flores C. 2022. Dopaminergic System Function and Dysfunction: Experimental Approaches. Neuromethods 31–63. doi:10.1007/978-1-0716-2799-0_2

(4) TH in the cortex could also be of noradrenergic origin. This needs to be ruled out to score DA axons

This is the same comment as Reviewer 1 #9. Please see our response below, which we have also added to our methods:

In this study we pay great attention to the morphology and localization of the fibres from which we quantify varicosities to avoid counting any fibres stained with TH antibodies that are not dopamine fibres. The fibres that we examine and that are labelled by the TH antibody show features indistinguishable from the classic features of cortical dopamine axons in rodents (Berger et al., 1974; 1983; Van Eden et al., 1987; Manitt et al., 2011), namely they are thin fibres with irregularly-spaced varicosities, are densely packed in the nucleus accumbens, sparsely present only in the deep layers of the prefrontal cortex, and are not regularly oriented in relation to the pial surface. This is in contrast to rodent norepinephrine fibres, which are smooth or beaded in appearance, relatively thick with regularly spaced varicosities, increase in density towards the shallow cortical layers, and are in large part oriented either parallel or perpendicular to the pial surface (Berger et al., 1974; Levitt and Moore, 1979; Berger et al., 1983; Miner et al., 2003). Furthermore, previous studies in rodents have noted that only norepinephrine cell bodies are detectable using immunofluorescence for TH, not norepinephrine processes (Pickel et al., 1975; Verney et al., 1982; Miner et al., 2003), and we did not observe any norepinephrine-like fibres.

References:

Berger B, Tassin JP, Blanc G, Moyne MA, Thierry AM (1974) Histochemical confirmation for dopaminergic innervation of the rat cerebral cortex after destruction of the noradrenergic ascending pathways. Brain Res 81:332–337.

Berger B, Verney C, Gay M, Vigny A (1983) Immunocytochemical Characterization of the Dopaminergic and Noradrenergic Innervation of the Rat Neocortex During Early Ontogeny. In: Proceedings of the 9th Meeting of the International Neurobiology Society, pp 263–267 Progress in Brain Research. Elsevier.

Levitt P, Moore RY (1979) Development of the noradrenergic innervation of neocortex. Brain Res 162:243–259.

Manitt C, Mimee A, Eng C, Pokinko M, Stroh T, Cooper HM, Kolb B, Flores C (2011) The Netrin Receptor DCC Is Required in the Pubertal Organization of Mesocortical Dopamine Circuitry. J Neurosci 31:8381–8394.

Miner LH, Schroeter S, Blakely RD, Sesack SR (2003) Ultrastructural localization of the norepinephrine transporter in superficial and deep layers of the rat prelimbic prefrontal cortex and its spatial relationship to probable dopamine terminals. J Comp Neurol 466:478–494.

Pickel VM, Joh TH, Field PM, Becker CG, Reis DJ (1975) Cellular localization of tyrosine hydroxylase by immunohistochemistry. J Histochem Cytochem 23:1–12.

Van Eden CG, Hoorneman EM, Buijs RM, Matthijssen MA, Geffard M, Uylings HBM (1987) Immunocytochemical localization of dopamine in the prefrontal cortex of the rat at the light and electron microscopical level. Neurosci 22:849–862.

Verney C, Berger B, Adrien J, Vigny A, Gay M (1982) Development of the dopaminergic innervation of the rat cerebral cortex. A light microscopic immunocytochemical study using anti-tyrosine hydroxylase antibodies. Dev Brain Res 5:41–52.

(5) Netrin staining should be provided with NeuN + DAPI; its not clear these are all cell bodies. An in situ of Netrin would help as well.

A similar comment was raised by Reviewer 1 in point #1. Please see below the immunofluorescent and RNA scope images showing expression of Netrin-1 protein and mRNA in the forebrain.

Author response image 7.

This confocal microscope image shows immunofluorescent staining for Netrin-1 (green) localized around cell nuclei (stained by DAPI in blue). This image was taken from a coronal section of the lateral septum of an adult male mouse. Scale bar = 20µm

Author response image 8.

This confocal microscope image of a coronal brain section of the medial prefrontal cortex of an adult male mouse shows Netrin-1 mRNA expression (green) and cell nuclei (DAPI, blue). RNAscope was used to generate this image. Brain regions are as follows: Cg1: Anterior cingulate cortex 1, DP: dorsopeduncular cortex, IL: Infralimbic Cortex, PrL: Prelimbic Cortex, fmi: forceps minor of the corpus callosum

Author response image 9.

A higher resolution image from the same sample as in Figure 2 shows Netrin-1 mRNA (green) and cell nuclei (DAPI; blue). DP = dorsopeduncular cortex

(6) The Netrin knockdown needs validation. How strong was the knockdown etc?

This comment was also raised by Reviewer 1 #1.

We have previously established the efficacy of the shRNA Netrin-1 knockdown virus used in this experiment for reducing the expression of Netrin-1 (Cuesta et al., 2020). The shRNA reduces Netrin-1 levels in vitro and in vivo.

References:

Cuesta S, Nouel D, Reynolds LM, Morgunova A, Torres-Berrío A, White A, Hernandez G, Cooper HM, Flores C. 2020. Dopamine Axon Targeting in the Nucleus Accumbens in Adolescence Requires Netrin-1. Frontiers Cell Dev Biology 8:487. doi:10.3389/fcell.2020.00487

(7) If the conclusion that knocking down Netrin in cortex decreases DA innervation of the IL, how can that be reconciled with Netrin-Unc repulsion.

This is an intriguing question and one that we are in the planning stages of addressing with new experiments.

Although we do not have a mechanistic answered for how a repulsive receptor helps guide these axons, we would like to note that previous indirect evidence from a study by our group also suggests that reducing UNC5c signaling in dopamine axons in adolescence increases dopamine innervation to the prefrontal cortex (Auger et al, 2013).

References

Auger ML, Schmidt ERE, Manitt C, Dal-Bo G, Pasterkamp RJ, Flores C. 2013. unc5c haploinsufficient phenotype: striking similarities with the dcc haploinsufficiency model. European Journal of Neuroscience 38:2853–2863. doi:10.1111/ejn.12270

(8) The behavioral phenotype in Fig 1 is interesting, but its not clear if its related to DA axons/signaling. IN general, no evidence in this paper is provided for the role of DA in the adolescent behaviors described.

We agree with the reviewer that the behaviours we describe in adult mice are complex and are likely to involve several neurotransmitter systems. However, there is ample evidence for the role of dopamine signaling in cognitive control behaviours (Bari and Robbins, 2013; Eagle et al., 2008; Ott et al., 2023) and our published work has shown that alterations in the growth of dopamine axons to the prefrontal cortex leads to changes in impulse control as measured via the Go/No-Go task in adulthood (Reynolds et al., 2023, 2018a; Vassilev et al., 2021).

The other adolescent behaviour we examined was risk-like taking behaviour in male and female hamsters (Figures 4 and 5), as a means of characterizing maturation in this behavior over time. We decided not to use the Go/No-Go task because as far as we know, this has never been employed in Siberian Hamsters and it will be difficult to implement. Instead, we chose the light/dark box paradigm, which requires no training and is ideal for charting behavioural changes over short time periods. Indeed, risk-like taking behavior in rodents and in humans changes from adolescence to adulthood paralleling changes in prefrontal cortex development, including the gradual input of dopamine axons to this region.

References:

Bari A, Robbins TW. 2013. Inhibition and impulsivity: Behavioral and neural basis of response control. Progress in neurobiology 108:44–79. doi:10.1016/j.pneurobio.2013.06.005

Eagle DM, Bari A, Robbins TW. 2008. The neuropsychopharmacology of action inhibition: cross-species translation of the stop-signal and go/no-go tasks. Psychopharmacology 199:439–456. doi:10.1007/s00213-008-1127-6

Ott T, Stein AM, Nieder A. 2023. Dopamine receptor activation regulates reward expectancy signals during cognitive control in primate prefrontal neurons. Nat Commun 14:7537. doi:10.1038/s41467-023-43271-6

Reynolds LM, Hernandez G, MacGowan D, Popescu C, Nouel D, Cuesta S, Burke S, Savell KE, Zhao J, Restrepo-Lozano JM, Giroux M, Israel S, Orsini T, He S, Wodzinski M, Avramescu RG, Pokinko M, Epelbaum JG, Niu Z, Pantoja-Urbán AH, Trudeau L-É, Kolb B, Day JJ, Flores C. 2023. Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism in mice. Nat Commun 14:4035. doi:10.1038/s41467-023-39665-1

Reynolds LM, Pokinko M, Torres-Berrío A, Cuesta S, Lambert LC, Pellitero EDC, Wodzinski M, Manitt C, Krimpenfort P, Kolb B, Flores C. 2018a. DCC Receptors Drive Prefrontal Cortex Maturation by Determining Dopamine Axon Targeting in Adolescence. Biological psychiatry 83:181–192. doi:10.1016/j.biopsych.2017.06.009

Vassilev P, Pantoja-Urban AH, Giroux M, Nouel D, Hernandez G, Orsini T, Flores C. 2021. Unique effects of social defeat stress in adolescent male mice on the Netrin-1/DCC pathway, prefrontal cortex dopamine and cognition (Social stress in adolescent vs. adult male mice). Eneuro ENEURO.0045-21.2021. doi:10.1523/eneuro.0045-21.2021

(9) Fig2 - boxes should be drawn on the NAc diagram to indicate sampled regions. Some quantification of Unc5c would be useful. Also, some validation of the Unc5c antibody would be nice.

The images presented were taken medial to the anterior commissure and we have edited Figure 2 to show this. However, we did not notice any intra-accumbens variation, including between the core and the shell. Therefore, the images are representative of what was observed throughout the entire nucleus accumbens.

To quantify UNC5c in the accumbens we conducted a Western blot experiment in male mice at different ages. A one-way ANOVA analyzing band intensity (relative to the 15-day-old average band intensity) as the response variable and age as the predictor variable showed a significant effect of age (F=5.615, p=0.01). Posthoc analysis revealed that 15-day-old mice have less UNC5c in the nucleus accumbens compared to 21- and 35-day-old mice.

Author response image 10.

The graph depicts the results of a Western blot experiment of UNC5c protein levels in the nucleus accumbens of male mice at postnatal days 15, 21 or 35 and reveals a significant increase in protein levels at the onset adolescence.

Our methods for this Western blot were as follows: Samples were prepared as previously (Torres-Berrío et al., 2017). Briefly, mice were sacrificed by live decapitation and brains were flash frozen in heptane on dry ice for 10 seconds. Frozen brains were mounted in a cryomicrotome and two 500um sections were collected for the nucleus accumbens, corresponding to plates 14 and 18 of the Paxinos mouse brain atlas. Two tissue core samples were collected per section, one for each side of the brain, using a 15-gauge tissue corer (Fine surgical tools Cat no. NC9128328) and ejected in a microtube on dry ice. The tissue samples were homogenized in 100ul of standard radioimmunoprecipitation assay buffer using a handheld electric tissue homogenizer. The samples were clarified by centrifugation at 4C at a speed of 15000g for 30 minutes. Protein concentration was quantified using a bicinchoninic acid assay kit (Pierce BCA protein assay kit, Cat no.PI23225) and denatured with standard Laemmli buffer for 5 minutes at 70C. 10ug of protein per sample was loaded and run by SDS-PAGE gel electrophoresis in a Mini-PROTEAN system (Bio-Rad) on an 8% acrylamide gel by stacking for 30 minutes at 60V and resolving for 1.5 hours at 130V. The proteins were transferred to a nitrocellulose membrane for 1 hour at 100V in standard transfer buffer on ice. The membranes were blocked using 5% bovine serum albumin dissolved in tris-buffered saline with Tween 20 and probed with primary (UNC5c, Abcam Cat. no ab302924) and HRP-conjugated secondary antibodies for 1 hour. a-tubulin was probed and used as loading control. The probed membranes were resolved using SuperSignal West Pico PLUS chemiluminescent substrate (ThermoFisher Cat no.34579) in a ChemiDoc MP Imaging system (Bio-Rad). Band intensity was quantified using the ChemiDoc software and all ages were normalized to the P15 age group average.

Validation of the UNC5c antibody was performed in the lab of Dr. Liu, from whom it was kindly provided. Briefly, in the validation study the authors showed that the anti-UNC5C antibody can detect endogenous UNC5C expression and the level of UNC5C is dramatically reduced after UNC5C knockdown. The antibody can also detect the tagged-UNC5C protein in several cell lines, which was confirmed by a tag antibody (Purohit et al., 2012; Shao et al., 2017).

References:

Purohit AA, Li W, Qu C, Dwyer T, Shao Q, Guan K-L, Liu G. 2012. Down Syndrome Cell Adhesion Molecule (DSCAM) Associates with Uncoordinated-5C (UNC5C) in Netrin-1mediated Growth Cone Collapse. The Journal of biological chemistry 287:27126–27138. doi:10.1074/jbc.m112.340174

Shao Q, Yang T, Huang H, Alarmanazi F, Liu G. 2017. Uncoupling of UNC5C with Polymerized TUBB3 in Microtubules Mediates Netrin-1 Repulsion. J Neurosci 37:5620–5633. doi:10.1523/jneurosci.2617-16.2017

(10) "In adolescence, dopamine neurons begin to express the repulsive Netrin-1 receptor UNC5C, and reduction in UNC5C expression appears to cause growth of mesolimbic dopamine axons to the prefrontal cortex".....This is confusing. Figure 2 shows a developmental increase in UNc5c not a decrease. So when is the "reduction in Unc5c expression" occurring?

We apologize for the mistake in this sentence. We have corrected the relevant passage in our manuscript as follows:

In adolescence, dopamine neurons begin to express the repulsive Netrin-1 receptor UNC5C, particularly when mesolimbic and mesocortical dopamine projections segregate in the nucleus accumbens (Manitt et al., 2010; Reynolds et al., 2018a). In contrast, dopamine axons in the prefrontal cortex do not express UNC5c except in very rare cases (Supplementary Figure 4). In adult male mice with Unc5c haploinsufficiency, there appears to be ectopic growth of mesolimbic dopamine axons to the prefrontal cortex (Auger et al., 2013). This miswiring is associated with alterations in prefrontal cortex-dependent behaviours (Auger et al., 2013).

References:

Auger ML, Schmidt ERE, Manitt C, Dal-Bo G, Pasterkamp RJ, Flores C. 2013. unc5c haploinsufficient phenotype: striking similarities with the dcc haploinsufficiency model. European Journal of Neuroscience 38:2853–2863. doi:10.1111/ejn.12270

Manitt C, Labelle-Dumais C, Eng C, Grant A, Mimee A, Stroh T, Flores C. 2010. Peri-Pubertal Emergence of UNC-5 Homologue Expression by Dopamine Neurons in Rodents. PLoS ONE 5:e11463-14. doi:10.1371/journal.pone.0011463

Reynolds LM, Pokinko M, Torres-Berrío A, Cuesta S, Lambert LC, Pellitero EDC, Wodzinski M, Manitt C, Krimpenfort P, Kolb B, Flores C. 2018a. DCC Receptors Drive Prefrontal Cortex Maturation by Determining Dopamine Axon Targeting in Adolescence. Biological psychiatry 83:181–192. doi:10.1016/j.biopsych.2017.06.009

(11) In Fig 3, a statistical comparison should be made between summer male and winter male, to justify the conclusions that the winter males have delayed DA innervation.

This analysis was also suggested by Reviewer 1, #11. Here is our response:

We analyzed the summer and winter data together in ANOVAs separately for males and females. In both sexes we find a significant effect of daylength on dopamine innervation, interacting with age. Male age by daylength interaction: F = 6.383, p = 0.00242. Female age by daylength interaction: F = 21.872, p = 1.97 x 10-9. The full statistical analysis is available as a supplement to this letter (Response_Letter_Stats_Details.docx).

(12) Should axon length also be measured here (Fig 3)? It is not clear why the authors have switched to varicosity density. Also, a box should be drawn in the NAC cartoon to indicate the region that was sampled.

It is untenable to quantify axon length in the prefrontal cortex as we cannot distinguish independent axons. Rather, they are “tangled”; they twist and turn in a multitude of directions as they make contact with various dendrites. Furthermore, they branch extensively. It would therefore be impossible to accurately quantify the number of axons. Using unbiased stereology to quantify varicosities is a valid, well-characterized and straightforward alternative (Reynolds et al., 2022).

References:

Reynolds LM, Pantoja-Urbán AH, MacGowan D, Manitt C, Nouel D, Flores C. 2022. Dopaminergic System Function and Dysfunction: Experimental Approaches. Neuromethods 31–63. doi:10.1007/978-1-0716-2799-0_2

(13) In Fig 3, Unc5c should be quantified to bolster the interesting finding that Unc5c expression dynamics are different between summer and winter hamsters. Unc5c mRNA experiments would also be important to see if similar changes are observed at the transcript level.

We agree that it would be very interesting to see how UNC5c mRNA and protein levels change over time in summer and winter hamsters, both in males, as the reviewer suggests here, and in females. We are working on conducting these experiments in hamsters as part of a broader expansion of our research in this area. These experiments will require a lengthy amount of time and at this point we feel that they are beyond the scope of this manuscript.

(14) Fig 4. The peak in exploratory behavior in winter females is counterintuitive and needs to be better discussed. IN general, the light dark behavior seems quite variable.

This is indeed a very interesting finding, which we have expanded upon in our manuscript as follows:

When raised under a winter-mimicking daylength, hamsters of either sex show a protracted peak in risk taking. In males, it is delayed beyond 80 days old, but the delay is substantially less in females. This is a counterintuitive finding considering that dopamine development in winter females appears to be accelerated. Our interpretation of this finding is that the timing of the risk-taking peak in females may reflect a balance between different adolescent developmental processes. The fact that dopamine axon growth is accelerated does not imply that all adolescent maturational processes are accelerated. Some may be delayed, for example those that induce axon pruning in the cortex. The timing of the risk-taking peak in winter female hamsters may therefore reflect the amalgamation of developmental processes that are advanced with those that are delayed – producing a behavioural effect that is timed somewhere in the middle. Disentangling the effects of different developmental processes on behaviour will require further experiments in hamsters, including the direct manipulation of dopamine activity in the nucleus accumbens and prefrontal cortex.

Full Reference List

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Bari A, Robbins TW. 2013. Inhibition and impulsivity: Behavioral and neural basis of response control. Progress in neurobiology 108:44–79. doi:10.1016/j.pneurobio.2013.06.005

Cuesta S, Nouel D, Reynolds LM, Morgunova A, Torres-Berrío A, White A, Hernandez G, Cooper HM, Flores C. 2020. Dopamine Axon Targeting in the Nucleus Accumbens in Adolescence Requires Netrin-1. Frontiers Cell Dev Biology 8:487. doi:10.3389/fcell.2020.00487

Daubaras M, Bo GD, Flores C. 2014. Target-dependent expression of the netrin-1 receptor, UNC5C, in projection neurons of the ventral tegmental area. Neuroscience 260:36–46. doi:10.1016/j.neuroscience.2013.12.007

Eagle DM, Bari A, Robbins TW. 2008. The neuropsychopharmacology of action inhibition: crossspecies translation of the stop-signal and go/no-go tasks. Psychopharmacology 199:439– 456. doi:10.1007/s00213-008-1127-6

Hoops D, Flores C. 2017. Making Dopamine Connections in Adolescence. Trends in Neurosciences 1–11. doi:10.1016/j.tins.2017.09.004

Jonker FA, Jonker C, Scheltens P, Scherder EJA. 2015. The role of the orbitofrontal cortex in cognition and behavior. Rev Neurosci 26:1–11. doi:10.1515/revneuro-2014-0043

Kim B, Im H. 2019. The role of the dorsal striatum in choice impulsivity. Ann N York Acad Sci 1451:92–111. doi:10.1111/nyas.13961

Kim D, Ackerman SL. 2011. The UNC5C Netrin Receptor Regulates Dorsal Guidance of Mouse Hindbrain Axons. J Neurosci 31:2167–2179. doi:10.1523/jneurosci.5254-10.2011

Manitt C, Labelle-Dumais C, Eng C, Grant A, Mimee A, Stroh T, Flores C. 2010. Peri-Pubertal Emergence of UNC-5 Homologue Expression by Dopamine Neurons in Rodents. PLoS ONE 5:e11463-14. doi:10.1371/journal.pone.0011463

Murcia-Belmonte V, Coca Y, Vegar C, Negueruela S, Romero C de J, Valiño AJ, Sala S, DaSilva R, Kania A, Borrell V, Martinez LM, Erskine L, Herrera E. 2019. A Retino-retinal Projection Guided by Unc5c Emerged in Species with Retinal Waves. Current Biology 29:1149-1160.e4. doi:10.1016/j.cub.2019.02.052

Ott T, Stein AM, Nieder A. 2023. Dopamine receptor activation regulates reward expectancy signals during cognitive control in primate prefrontal neurons. Nat Commun 14:7537. doi:10.1038/s41467-023-43271-6

Phillips RA, Tuscher JJ, Black SL, Andraka E, Fitzgerald ND, Ianov L, Day JJ. 2022. An atlas of transcriptionally defined cell populations in the rat ventral tegmental area. Cell Reports 39:110616. doi:10.1016/j.celrep.2022.110616

Purohit AA, Li W, Qu C, Dwyer T, Shao Q, Guan K-L, Liu G. 2012. Down Syndrome Cell Adhesion Molecule (DSCAM) Associates with Uncoordinated-5C (UNC5C) in Netrin-1-mediated Growth Cone Collapse. The Journal of biological chemistry 287:27126–27138. doi:10.1074/jbc.m112.340174

Reynolds LM, Hernandez G, MacGowan D, Popescu C, Nouel D, Cuesta S, Burke S, Savell KE, Zhao J, Restrepo-Lozano JM, Giroux M, Israel S, Orsini T, He S, Wodzinski M, Avramescu RG, Pokinko M, Epelbaum JG, Niu Z, Pantoja-Urbán AH, Trudeau L-É, Kolb B, Day JJ, Flores C. 2023. Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism in mice. Nat Commun 14:4035. doi:10.1038/s41467-023-39665-1

Reynolds LM, Pantoja-Urbán AH, MacGowan D, Manitt C, Nouel D, Flores C. 2022. Dopaminergic System Function and Dysfunction: Experimental Approaches. Neuromethods 31–63. doi:10.1007/978-1-0716-2799-0_2

Reynolds LM, Pokinko M, Torres-Berrío A, Cuesta S, Lambert LC, Pellitero EDC, Wodzinski M, Manitt C, Krimpenfort P, Kolb B, Flores C. 2018a. DCC Receptors Drive Prefrontal Cortex Maturation by Determining Dopamine Axon Targeting in Adolescence. Biological psychiatry 83:181–192. doi:10.1016/j.biopsych.2017.06.009

Reynolds LM, Yetnikoff L, Pokinko M, Wodzinski M, Epelbaum JG, Lambert LC, Cossette M-P, Arvanitogiannis A, Flores C. 2018b. Early Adolescence is a Critical Period for the Maturation of Inhibitory Behavior. Cerebral cortex 29:3676–3686. doi:10.1093/cercor/bhy247

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Vassilev P, Pantoja-Urban AH, Giroux M, Nouel D, Hernandez G, Orsini T, Flores C. 2021. Unique effects of social defeat stress in adolescent male mice on the Netrin-1/DCC pathway, prefrontal cortex dopamine and cognition (Social stress in adolescent vs. adult male mice). Eneuro ENEURO.0045-21.2021. doi:10.1523/eneuro.0045-21.2021

Private Comments

Reviewer #1

(12) The language should be improved. Some expression is confusing (line178-179). Also some spelling errors (eg. Figure 1M).

We have removed the word “Already” to make the sentence in lines 178-179 clearer, however we cannot find a spelling error in Figure 1M or its caption. We have further edited the manuscript for clarity and flow.

Reviewer #2

(1) The authors claim to have revealed how the 'timing of adolescence is programmed in the brain'. While their findings certainly shed light on molecular, circuit and behavioral processes that are unique to adolescence, their claim may be an overstatement. I suggest they refine this statement to discuss more specifically the processes they observed in the brain and animal behavior, rather than adolescence itself.

We agree with the reviewer and have revised the manuscript to specify that we are referring to the timing of specific developmental processes that occur in the adolescent brain, not adolescence overall.

(2) Along the same lines, the authors should also include a more substantiative discussion of how they selected their ages for investigation (for both mice and hamsters), For mice, their definition of adolescence (P21) is earlier than some (e.g. Spear L.P., Neurosci. and Beh. Reviews, 2000).

There are certainly differences of opinion between researchers as to the precise definition of adolescence and the period it encompasses. Spear, 2000, provides one excellent discussion of the challenges related to identifying adolescence across species. This work gives specific ages only for rats, not mice (as we use here), and characterizes post-natal days 28-42 as being the conservative age range of “peak” adolescence (page 419, paragraph 1). Immediately thereafter the review states that the full adolescent period is longer than this, and it could encompass post-natal days 20-55 (page 419, paragraph 2).

We have added the following statement to our methods:

There is no universally accepted way to define the precise onset of adolescence. Therefore, there is no clear-cut boundary to define adolescent onset in rodents (Spear, 2000). Puberty can be more sharply defined, and puberty and adolescence overlap in time, but the terms are not interchangeable. Puberty is the onset of sexual maturation, while adolescence is a more diffuse period marked by the gradual transition from a juvenile state to independence. We, and others, suggest that adolescence in rodents spans from weaning (postnatal day 21) until adulthood, which we take to start on postnatal day 60 (Reynolds and Flores, 2021). We refer to “early adolescence” as the first two weeks postweaning (postnatal days 21-34). These ranges encompass discrete DA developmental periods (Kalsbeek et al., 1988; Manitt et al., 2011; Reynolds et al., 2018a), vulnerability to drug effects on DA circuitry (Hammerslag and Gulley, 2014; Reynolds et al., 2018a), and distinct behavioral characteristics (Adriani and Laviola, 2004; Makinodan et al., 2012; Schneider, 2013; Wheeler et al., 2013).

References:

Adriani W, Laviola G. 2004. Windows of vulnerability to psychopathology and therapeutic strategy in the adolescent rodent model. Behav Pharmacol 15:341–352. doi:10.1097/00008877-200409000-00005

Hammerslag LR, Gulley JM. 2014. Age and sex differences in reward behavior in adolescent and adult rats. Dev Psychobiol 56:611–621. doi:10.1002/dev.21127

Hoops D, Flores C. 2017. Making Dopamine Connections in Adolescence. Trends in Neurosciences 1–11. doi:10.1016/j.tins.2017.09.004

Kalsbeek A, Voorn P, Buijs RM, Pool CW, Uylings HBM. 1988. Development of the Dopaminergic Innervation in the Prefrontal Cortex of the Rat. The Journal of Comparative Neurology 269:58–72. doi:10.1002/cne.902690105

Makinodan M, Rosen KM, Ito S, Corfas G. 2012. A critical period for social experiencedependent oligodendrocyte maturation and myelination. Science 337:1357–1360. doi:10.1126/science.1220845

Manitt C, Mimee A, Eng C, Pokinko M, Stroh T, Cooper HM, Kolb B, Flores C. 2011. The Netrin Receptor DCC Is Required in the Pubertal Organization of Mesocortical Dopamine Circuitry. J Neurosci 31:8381–8394. doi:10.1523/jneurosci.0606-11.2011

Reynolds LM, Flores C. 2021. Mesocorticolimbic Dopamine Pathways Across Adolescence: Diversity in Development. Front Neural Circuit 15:735625. doi:10.3389/fncir.2021.735625

Reynolds LM, Yetnikoff L, Pokinko M, Wodzinski M, Epelbaum JG, Lambert LC, Cossette MP, Arvanitogiannis A, Flores C. 2018. Early Adolescence is a Critical Period for the Maturation of Inhibitory Behavior. Cerebral cortex 29:3676–3686. doi:10.1093/cercor/bhy247

Schneider M. 2013. Adolescence as a vulnerable period to alter rodent behavior. Cell and tissue research 354:99–106. Doi:10.1007/s00441-013-1581-2

Spear LP. 2000. Neurobehavioral Changes in Adolescence. Current directions in psychological science 9:111–114. doi:10.1111/1467-8721.00072

Wheeler AL, Lerch JP, Chakravarty MM, Friedel M, Sled JG, Fletcher PJ, Josselyn SA, Frankland PW. 2013. Adolescent Cocaine Exposure Causes Enduring Macroscale Changes in Mouse Brain Structure. J Neurosci 33:1797–1803. doi:10.1523/jneurosci.3830-12.2013

(3) Figure 1 - the conclusions hinge on the Netrin-1 staining, as shown in panel G, but the cells are difficult to see. It would be helpful to provide clearer, more zoomed images so readers can better assess the staining. Since Netrin-1 expression reduces dramatically after P4 and they had to use antigen retrieval to see signal, it would be helpful to show some images from additional brain regions and ages to see if expression levels follow predicted patterns. For instance, based on the allen brain atlas, it seems that around P21, there should be high levels of Netrin-1 in the cerebellum, but low levels in the cortex. These would be nice controls to demonstrate the specificity and sensitivity of the antibody in older tissue.

We do not study the cerebellum and have never stained this region; doing so now would require generating additional tissue and we’re not sure it would add enough to the information provided to be worthwhile. Note that we have stained the forebrain for Netrin-1 previously, providing broad staining of many brain regions (Manitt et al., 2011)

References:

Manitt C, Mimee A, Eng C, Pokinko M, Stroh T, Cooper HM, Kolb B, Flores C. 2011. The Netrin Receptor DCC Is Required in the Pubertal Organization of Mesocortical Dopamine Circuitry. J Neurosci 31:8381–8394. doi:10.1523/jneurosci.0606-11.2011

(4) Figure 3 - Because mice tend to avoid brightly-lit spaces, the light/dark box is more commonly used as a measure of anxiety-like behavior than purely exploratory behavior (including in the paper they cited). It is important to address this possibility in their discussion of their findings. To bolster their conclusions about the coincidence of circuit and behavioral changes in adolescent hamsters, it would be useful to add an additional measure of exploratory behaviors (e.g. hole board).

Regarding the light/dark box test, this is an excellent point. We prefer the term “risk taking” to “anxiety-like” and now use the former term in our manuscript. Furthermore, our interest in the behaviour is purely to chart the development of adolescent behaviour across our treatment groups, not to study a particular emotional state. Regardless of the specific emotion or emotions governing the light/dark box behaviour, it is an ideal test for charting adolescent shifts in behaviour as it is well-characterized in this respect, as we discuss in our manuscript.

(5) Supplementary Figure 4,5 The authors defined puberty onset using uterine and testes weights in hamsters. While the weights appear to be different for summer and winter hamsters, there were no statistical comparison. Please add statistical analyses to bolster claims about puberty start times. Also, as many studies use vaginal opening to define puberty onset, it would be helpful to discuss how these measurements typically align and cite relevant literature that described use of uterine weights. Also, Supplementary Figures 4 and 5 were mis-cited as Supp. Fig. 2 in the text (e.g. line 317 and others).

These are great suggestions. We have added statistical analyses to Supplementary Figures 5 and 6 and provided Vaginal Opening data as Supplementary Figure 7. The statistical analyses confirm that all three characters are delayed in winter hamsters compared to summer hamsters.

We have also added the following references to the manuscript:

Darrow JM, Davis FC, Elliott JA, Stetson MH, Turek FW, Menaker M. 1980. Influence of Photoperiod on Reproductive Development in the Golden Hamster. Biol Reprod 22:443–450. doi:10.1095/biolreprod22.3.443

Ebling FJP. 1994. Photoperiodic Differences during Development in the Dwarf Hamsters Phodopus sungorus and Phodopus campbelli. Gen Comp Endocrinol 95:475–482. doi:10.1006/gcen.1994.1147

Timonin ME, Place NJ, Wanderi E, Wynne-Edwards KE. 2006. Phodopus campbelli detect reduced photoperiod during development but, unlike Phodopus sungorus, retain functional reproductive physiology. Reproduction 132:661–670. doi:10.1530/rep.1.00019

(6) The font in many figure panels is small and hard to read (e.g. 1A,D,E,H,I,L...). Please increase the size for legibility.

We have increased the font size of our figure text throughout the manuscript.

Reviewer #3

(15) Fig 1 C,D. Clarify the units of the y axis

We have now fixed this.

Full Reference List

Adriani W, Laviola G. 2004. Windows of vulnerability to psychopathology and therapeutic strategy in the adolescent rodent model. Behav Pharmacol 15:341–352. doi:10.1097/00008877-200409000-00005

Hammerslag LR, Gulley JM. 2014. Age and sex differences in reward behavior in adolescent and adult rats. Dev Psychobiol 56:611–621. doi:10.1002/dev.21127

Hoops D, Flores C. 2017. Making Dopamine Connections in Adolescence. Trends in Neurosciences 1–11. doi:10.1016/j.tins.2017.09.004

Kalsbeek A, Voorn P, Buijs RM, Pool CW, Uylings HBM. 1988. Development of the Dopaminergic Innervation in the Prefrontal Cortex of the Rat. The Journal of Comparative Neurology 269:58–72. doi:10.1002/cne.902690105

Makinodan M, Rosen KM, Ito S, Corfas G. 2012. A critical period for social experiencedependent oligodendrocyte maturation and myelination. Science 337:1357–1360. doi:10.1126/science.1220845

Manitt C, Mimee A, Eng C, Pokinko M, Stroh T, Cooper HM, Kolb B, Flores C. 2011. The Netrin Receptor DCC Is Required in the Pubertal Organization of Mesocortical Dopamine Circuitry. J Neurosci 31:8381–8394. doi:10.1523/jneurosci.0606-11.2011

Reynolds LM, Flores C. 2021. Mesocorticolimbic Dopamine Pathways Across Adolescence: Diversity in Development. Front Neural Circuit 15:735625. doi:10.3389/fncir.2021.735625 Reynolds LM, Yetnikoff L, Pokinko M, Wodzinski M, Epelbaum JG, Lambert LC, Cossette M-P, Arvanitogiannis A, Flores C. 2018. Early Adolescence is a Critical Period for the Maturation of Inhibitory Behavior. Cerebral cortex 29:3676–3686. doi:10.1093/cercor/bhy247

Schneider M. 2013. Adolescence as a vulnerable period to alter rodent behavior. Cell and tissue research 354:99–106. doi:10.1007/s00441-013-1581-2

Spear LP. 2000. Neurobehavioral Changes in Adolescence. Current directions in psychological science 9:111–114. doi:10.1111/1467-8721.00072

Wheeler AL, Lerch JP, Chakravarty MM, Friedel M, Sled JG, Fletcher PJ, Josselyn SA, Frankland PW. 2013. Adolescent Cocaine Exposure Causes Enduring Macroscale Changes in Mouse Brain Structure. J Neurosci 33:1797–1803. doi:10.1523/jneurosci.3830-12.2013

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Reply to the reviewers

We thank the reviewers for their valuable comments, which definitely make our story stronger.

2. Description of the planned revisions

Reviewer 1

Comments:

No data are shown from the genome-wide screening approach, including the common regulators of KRAS and HRAS. Information about how imaging data were processed and analysed is missing. A final table of 8 selected factors with phosphatase activity is presented without providing further insight about the selection criteria and other factors.

This information will be included in the revised manuscript. In the subsequent characterization via image-based quantification of GFP-KRAS membrane localization, a Manders´ coefficient was calculated. A respective chapter in the methods section on how this was done is missing.

This information will be provided in the revised manuscript. I would be happy to see the following analyses to strengthen the dataset:

• Reconstitution experiments and further validation to show that it is dependent on the enzymatic activity of MTMRs.

MTMR3 knockdown (KD) cells will be rescued with wildtype (WT) MTMR3 or the phosphatase mutant MTMR3 (C413S, PMID: 11676921). MTMR4 KD cells will be rescued with WT MTMR4 or the phosphatase mutant MTMR4 (C407S, PMID: 20736309). In these cells, the PM localization of KRAS and PtdSer will be examined by confocal and electron microscopy. - Additive effect upon depletion of multiple MTMRs? Are they functionally co-operative?

MTMR3 and 4 KD cells will be rescued with WT MTMR4 and 3, respectively, and the PM localization of KRAS and PtdSer will be examined by confocal and electron microscopy. - Signalling analysis is very limited (Fig. 5). Do the authors detect any defects in K-RAS driven downstream signaling in these cells upon depletion of MTMRs.

Human pancreatic ductal adenocarcinoma (PDAC) cell lines that harbor oncogenic mutant KRAS and their growth is KRAS signaling-dependent (MiaPaCa2 and AsPC1), and PDAC cell line harboring WT KRAS and their growth is KRAS signaling-independent (BxPC3) will be infected with lentivirus expressing shRNAs against MTMR 2, 3, 4 or 7. Their growth (proliferation assay) and KRAS signaling (e.g. phosphorylated ERK and Akt by immunoblot) will be measure. Reviewer 2

Major comments

The unbiased siRNA screen used to identify proteins that impact KRAS membrane localization was a very nice approach to identify MTMR proteins. Although there is a clear phenotype of KRAS mislocalization associated with knockdown of the various MTMR proteins, the data provided does not prove a causational role for the MTMR proteins in maintaining PtdSer content, nor KRAS localization, at the PM. The current data does not provide a mechanism by which MTMR proteins are influencing this process, but rather speculates using existing literature that it is the loss in MTMR 3-phosphotase activity that leads to decreased PtdSer in the membrane. There is a series of conversions and exchanges that act upon PI3P (the substrate of MTMR proteins) and PI to generate PtdSer in the PM; thus, it is a dynamic process that is influenced by a variety of different proteins and transporters [3, 4, 5, 6]. To prove their single-protein-driven hypothesis, the authors should clone and express a mutant MTMR protein construct that contains an inactive phosphatase catalytic domain, to prove that it is indeed MTMR's generation of PI (which is further converted into PI4P) in the membrane that is responsible for maintaining PtdSer content and KRAS localization. Without this, there is not enough evidence to support this claim.

MTMR3 knockdown (KD) cells will be rescued with wildtype (WT) MTMR3 or the phosphatase mutant MTMR3 (C413S, PMID: 11676921). MTMR4 KD cells will be rescued with WT MTMR4 or the phosphatase mutant MTMR4 (C407S, PMID: 20736309). In these cells, the PM localization of KRAS and PtdSer will be examined by confocal and electron microscopy. In addition, the authors speculate that ORP5 is a critical intermediate in this process, and that the loss in PI4P/ORP5 at the PM following MTMR knockdown is responsible for the decrease in PtdSer at the PM. The authors should knockdown ORP5 in MTMR-wildtype cells, since it is downstream of their proposed mechanism, and see whether this leads to comparable reductions in PtdSer levels and KRAS mislocalization at the PM. This would confirm ORP5 as having a major role in this setting and would support the initial mechanistic hypothesis. These experiments are imperative to forming an appropriate conclusion, especially since some of their current data contradicts their mechanistic hypothesis: the authors identify a decrease in whole cell PtdSer content, not just PM PtdSer content, when MTMR proteins are knocked down. Based on this result, one would predict that a secondary or supporting mechanism must exist that contributes to a reduction in whole cell PtdSer content, which likely contributes to its loss at the PM as well. The authors describe in line 360 how "previous work has shown that PM PI4P depletion indirectly blocks PtdSer synthase 1 and 2 activities," to explain this reduction in total cell levels of PtdSer. The authors should look at PtdSer synthase 1 and 2 activities in the presence of MTMR knockdown, as the loss in PtdSer at the PM may rely more heavily on synthase activity than ORP-dependent transfer of PtdSer.

Investigating the PM localization of KRAS and PtdSer after silencing ORP5 in MTMR WT mammalian cell lines has been published (PMID: 31451509 and 34903667). In these studies, silencing ORP5 1) reduces the levels of PtdSer and KRAS from the plasma membrane (PM), 2) reduces KRAS signal output, 3) blocks the growth of KRAS-dependent PDAC in vitro and in vivo. These studies have been appropriately cited in our manuscript in lines 82 and 277. Although the c. Elegans model that was used to investigate downstream let-60 (RAS ortholog) activity through a multi-vulva phenotype is quite intriguing, it is more critical to assess downstream RAS pathway activation, especially in the human colorectal adenocarcinoma or the human mammary gland ductal carcinoma cell lines. Not only would this line of questioning provide a higher significance and increase the clinical applicability of these findings, but it is also crucial to support the author's claim that MTMR knockdown can influence mutant KRAS activity. Although small changes in KRAS localization to the PM can have significant effects on downstream signaling, these effects need to be measured and confirmed in this setting. The authors should perform western blots to assess the activation of both the PI3K and MAPK pathway in the MTMR knockdown cell lines.

Human pancreatic ductal adenocarcinoma (PDAC) cell lines that harbor oncogenic mutant KRAS and their growth is KRAS signaling-dependent (MiaPaCa2 and AsPC1), and PDAC cell line harboring WT KRAS and their growth is KRAS signaling-independent (BxPC3) will be infected with lentivirus expressing shRNAs against MTMR 2, 3, 4 or 7. Their growth (proliferation assay) and KRAS signaling (e.g. phosphorylated ERK and Akt by immunoblot) will be measure. In addition to this, it might be important to know whether there are any changes in the levels of the KRAS protein itself, as recycling/transport pathways may be impacted by its lack of recruitment to the plasma membrane.

Total KRAS protein expression will be measured in MTMR KD cell lines. Finally, the authors show that proliferation is inhibited by MTMR knockdown as a readout of RAS activity. The authors should also assess the levels of cell death, as the inhibition of mutant KRAS in cancer cells would likely lead to cell death. The authors do not describe why reducing any one of the MTMR proteins alone is sufficient to deplete the PM of PtdSer. This sort of discussion is important for understanding compensatory or regulatory mechanisms in place between the MTMR proteins, as this may influence PtdSer levels at the PM. For example, it has been shown that MTMR2 can stabilize MTMR13 on membranes. Do the levels, stability, or localization of the other MTMR proteins change when one specific MTMR is knocked down? Is this why we see an effect on PtdSer in any one of the knockdowns? The authors should at the very least provide western blots for each of the MTMR proteins discussed in the presence of each individual MTMR knockdown.

MTMR3 knockdown (KD) cells will be rescued with WT MTMR3 or the phosphatase mutant MTMR3 (C413S, PMID: 11676921). MTMR4 KD cells will be rescued with WT MTMR4 or the phosphatase mutant MTMR4 (C407S, PMID: 20736309). In these cells, the PM localization of KRAS and PtdSer will be examined by confocal and electron microscopy. In addition, we will measure endogenous MTMR 2/3/4/7 proteins levels in the presence of each individual MTMR KD by immunoblotting. In addition to the above experiments, the MTMR hairpins should be expressed in a secondary or tertiary cell line to prove that these events are not specific to the current model used. Since their current human mammary gland ductal carcinoma cell line overexpresses a mutant KRAS-GFP construct, perhaps doing similar experiments in a cancer cell line that already expresses an endogenous mutant KRAS might provide a better model.

Human pancreatic ductal adenocarcinoma (PDAC) cell lines that harbor oncogenic mutant KRAS and their growth is KRAS signaling-dependent (MiaPaCa2 and AsPC1), and PDAC cell line harboring WT KRAS and their growth is KRAS signaling-independent (BxPC3) will be infected with lentivirus expressing shRNAs against MTMR 2, 3, 4 or 7. Their growth (proliferation assay) and KRAS signaling (e.g. phosphorylated ERK and Akt by immunoblot) will be measure. Although this protein would not include a GFP-tag, other ways of visualizing its localization at the PM (such as immunofluorescent staining) could be used to confirm its localization there.

The anti-KRAS antibody for IF has not been reported to my knowledge. In addition, the effects on downstream RAS signaling could be measured through western blot of PI3K and MAPK pathways.

Human pancreatic ductal adenocarcinoma (PDAC) cell lines that harbor oncogenic mutant KRAS and their growth is KRAS signaling-dependent (MiaPaCa2 and AsPC1), and PDAC cell line harboring WT KRAS and their growth is KRAS signaling-independent (BxPC3) will be infected with lentivirus expressing shRNAs against MTMR 2, 3, 4 or 7. Their growth (proliferation assay) and KRAS signaling (e.g. phosphorylated ERK and Akt by immunoblot) will be measure. Supplemental Figure 4 is incorrectly referred to in the text as Supplemental Figure 3 (line 257-258). The text reads, "Confocal microscopy further demonstrates that HRASG12V cellular localization is not disrupted after silencing MTMR 2/3/4/7 (Fig. S3)" but Figure S3 is an EM image of PM basal sheets from T47D cells expressing GFP-KRASG12V. Supplemental Figure 4 shows that mutant HRAS is unaffected by the various MTMR knockdowns.

They will be labeled correctly in the revised manuscript. Since the authors show decreased proliferation in mutant KRAS cells following MTMR knockdown, the authors should also investigate any changes to proliferation rates in mutant HRAS cell lines following MTMR knockdown. This data is necessary to prove that MTMR-driven changes in downstream RAS signaling are specific to mutant KRAS and not mutant HRAS.

Cell proliferation assay will be performed using MTMR 2/3/4/7-silenced T47D cell lines stably expressing oncogenic mutant HRAS (HRASG12V) to address this questions. It may also be important for the authors to also show any effects on wildtype RAS localization to the PM when MTMR-2,-3,-4, and -7 are knocked down, to show whether this is a oncoprotein-specific event.

Cells expressing the truncated mutant KRAS, which contains the minimal membrane anchor and does not have G-domain will be infected with lentivirus expressing shRNA against MTMR 2/3/4/7, and their localization will be examined. The representative images chosen for Figure 4 diminish the reliability of the data, as it is difficult to see a visible change in the PI3P probe between the control and MTMR knockdown cells in these images. Since the authors rely on the Mander's coefficient and the number of gold particles throughout much of the paper, having the same conclusion quantitatively but not qualitatively for these assays is confusing. Perhaps the authors should elaborate on whether MTMR knockdown has a stronger effect on PtSer and KRAS PM presence than PI3P PM presence.

We will include the discussion in the revised manuscript. They should also describe their method for identifying early endosomes, since they switch back and forth between describing the content of the PM and of early endosomes, such as in Figure 1 and Figure 4.

We will include the information in the revised manuscript. Minor comments:

An additional experiment that may add another layer of clinical applicability would be the use of an MTMR inhibitor in this cell line, to see whether similar effects can be achieved pharmacologically [7]. This would provoke other researchers to investigate MTMR inhibitors in vitro and in vivo to assess the effect on mutant KRAS cancers.

• This is an important point, but while vanadate, a general phospho-tyrosine phosphatase (PTP) inhibitor, has been reported to inhibit myotubulin, a family member of MTMR (PMID: 8995372 and 1943774), there are no commercially available MTMR-specific inhibitors. Using vanadate to inhibit MTMR proteins will produce non-specific effects by blocking other PTPs. The inclusion of cell lines that express KRAS proteins of different mutational statuses would be extremely interesting, as KRAS' orientation within the plasma membrane has been shown to be altered by these mutations. This fact should potentially be considered when choosing a secondary or tertiary cell line to do additional experiments in, but it is not necessary for the authors to elaborate on how MTMR proteins may impact different KRAS mutants for the scope of this project.

For the aforementioned experiments using human KRAS-dependent and -independent PDAC cell lines, we will use MiaPaCa2 (KRASG12C) and AsPC1 (KRASG12D). Reviewer #3

*Major comments: *

One of the two main manuscript claims indicates that KRAS12V "function" is impaired upon MTMR knockdown. While this is an obvious phenotype expected by mislocalizing KRAS from the inner PM it is not sufficiently demonstrated in the current version of the manuscript. Western blots of at least MAPK and PI3K signalling following MTMR knockdown in KRAS-dependent cell lines should be included. In addition to the T47D cells used in the manuscript, it would be ideal to include a KRAS-mutant cell line from tumour types where KRAS mutations are more frequent that in breast.

• Human pancreatic ductal adenocarcinoma (PDAC) cell lines that harbor oncogenic mutant KRAS and their growth is KRAS signaling-dependent (MiaPaCa2 and AsPC1), and PDAC cell line harboring WT KRAS and their growth is KRAS signaling-independent (BxPC3) will be infected with lentivirus expressing shRNAs against MTMR 2, 3, 4 or 7. Their growth (proliferation assay) and KRAS signaling (e.g. phosphorylated ERK and Akt by immunoblot) will be measure. Since the MTMR dependent phenotypes are mutant-KRAS specific it would be interesting to study the resulting phenotypes in HRAS-mutant cell line.

Cell proliferation assay will be performed using MTMR 2/3/4/7-silenced T47D cell lines stably expressing oncogenic mutant HRAS (HRASG12V) to address these questions.

**Referee cross-commenting**

After reading the reviews of my colleagues I think there is a clear agreement on the need to further substantiate that KRAS membrane mis-localization is indeed affecting oncogenic output. The use of other KRAS addicted and non-addicted models would further enhance this analysis.

Likewise, the other two reviewers request experimental evidences to validate the role of MTMR enzymatic activity in the process. This is a pertinent request that I failed to put forward. Suggestions include the use of reconstitution experiments catalytically dead mutants. Also, the use of MTMR small molecule inhibitors is proposed. If those exist with sufficient specificity this would indeed be appropriate to perform.

Experiments addressing these comments have been described above.

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

N/A

• *

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

*Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. *

Reviewer 2

R2 suggests to investigate PtdSer synthase 1 and 2 activities in presence of MTMR knockdown, as the loss in PtdSer at the PM may rely more heavily on synthase activity than ORP-dependent transfer of PtdSer.

Although it is intriguing to examine the effect of MTMR loss on the activities of PtdSer synthase 1 and 2, our lab does not have resources/techniques to carry out the experiment. * *

The results of this paper rely heavily on one experimental technique, which is calculating a Mander's coefficient and counting the co-localization of the probe of interest with the CellMask stain of the plasma membrane. How this coefficient is derived is explained in appropriate detail in the methods section of this manuscript; however, a secondary route of identifying these changes in membrane constituents would greatly enhance the paper's conclusions. This would eliminate any doubt surrounding the accuracy of the technique, since so much of the data relies on one experimental output.

In addition to Manders' coefficient for examining the colocalization of KRAS and LactC2 (the PtdSer probe) to propose KRAS/PS redistribution to endomembranes after MTMR loss. To complement this, we also performed quantitative EM to demonstrate the PM depletion of KRAS and PtdSer from the inner PM leaflet. We believe these two techniques would appropriate to investigate KRAS/PtdSer PM depletion and cellular re-distribution. * *

Reviewer 3

To further support the conclusions, oncogenic signalling should be studied in the C.elegans model by immunofluorescence of immunohistochemistry. Furthermore, although not strictly required to support the author's claims, it would be interesting to elucidate whether the inhibition of the multivulva phenotype upon MTMR knockdown in vivo results as a consequence of cell death.

Our collaborator for C. elegans study does not have resources to carry out the proposed IF and IHC experiment. Instead, we will measure KRAS signaling (e.g. phosphorylated ERK and Akt by immunoblot) and the growth of KRAS-dependent PDAC after MTMR loss. These experiments would be more clinically and physiologically relevant.

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Referee #2

Evidence, reproducibility and clarity

Summary:

Henkels et al. propose the role of myotubularin-related proteins in promoting KRAS4B localization to the plasma membrane. Their data shows that shRNA-mediated knockdown of myotubularin-related proteins -2, -3, -4, or -7 led to measurable changes in RAS localization and in plasma membrane (PM) content. More specifically, knockdown of any one of these MTMR proteins led to a decrease in PI4P levels in the PM, an increase in PI3P content in the PM, a decrease in phosphatidyl serine (PtdSer) in the PM/whole cell, and a decrease in mutant KRAS localization to the PM. Their data also shows a decreased presence of ORP5 at the PM, a protein which is responsible for the exchange of PI4P in the plasma membrane for PtdSer in the endoplasmic reticulum. These results are somewhat predictable and are supported by the existing literature, as MTMR proteins are known to exhibit 3-phosphotase activity towards PI3P to generate PI (a precursor to PI4P), PI4P is known to recruit ORP5, and ORP5 is known to contribute to PtdSer content in the membrane [1, 2]. Regardless, the authors find that the individual knockdown of MTMR proteins is sufficient to cause measurable changes in PM content and mislocalization of mutant KRAS4B. Thus, despite the fact that many proteins are involved in regulating PM content, such as PI4KA, PtdSer synthase 1 and 2, Nir2/3, and PITPs, Henkels et al. speculate that MTMR proteins are the primary regulators of PtdSer PM levels [3, 4, 5, 6]. The authors propose that the loss of function in any one of these MTMR proteins alone is sufficient to cause significant changes in PM content through an ORP5-dependent process, and that this ultimately leads to a decrease in mutant KRAS signaling.

Major comments:

The unbiased siRNA screen used to identify proteins that impact KRAS membrane localization was a very nice approach to identify MTMR proteins. Although there is a clear phenotype of KRAS mislocalization associated with knockdown of the various MTMR proteins, the data provided does not prove a causational role for the MTMR proteins in maintaining PtdSer content, nor KRAS localization, at the PM. The current data does not provide a mechanism by which MTMR proteins are influencing this process, but rather speculates using existing literature that it is the loss in MTMR 3-phosphotase activity that leads to decreased PtdSer in the membrane. There is a series of conversions and exchanges that act upon PI3P (the substrate of MTMR proteins) and PI to generate PtdSer in the PM; thus, it is a dynamic process that is influenced by a variety of different proteins and transporters [3, 4, 5, 6]. To prove their single-protein-driven hypothesis, the authors should clone and express a mutant MTMR protein construct that contains an inactive phosphatase catalytic domain, to prove that it is indeed MTMR's generation of PI (which is further converted into PI4P) in the membrane that is responsible for maintaining PtdSer content and KRAS localization. Without this, there is not enough evidence to support this claim. In addition, the authors speculate that ORP5 is a critical intermediate in this process, and that the loss in PI4P/ORP5 at the PM following MTMR knockdown is responsible for the decrease in PtdSer at the PM. The authors should knockdown ORP5 in MTMR-wildtype cells, since it is downstream of their proposed mechanism, and see whether this leads to comparable reductions in PtdSer levels and KRAS mislocalization at the PM. This would confirm ORP5 as having a major role in this setting and would support the initial mechanistic hypothesis. These experiments are imperative to forming an appropriate conclusion, especially since some of their current data contradicts their mechanistic hypothesis: the authors identify a decrease in whole cell PtdSer content, not just PM PtdSer content, when MTMR proteins are knocked down. Based on this result, one would predict that a secondary or supporting mechanism must exist that contributes to a reduction in whole cell PtdSer content, which likely contributes to its loss at the PM as well. The authors describe in line 360 how "previous work has shown that PM PI4P depletion indirectly blocks PtdSer synthase 1 and 2 activities," to explain this reduction in total cell levels of PtdSer. The authors should look at PtdSer synthase 1 and 2 activities in the presence of MTMR knockdown, as the loss in PtdSer at the PM may rely more heavily on synthase activity than ORP-dependent transfer of PtdSer. Although the c. Elegans model that was used to investigate downstream let-60 (RAS ortholog) activity through a multi-vulva phenotype is quite intriguing, it is more critical to assess downstream RAS pathway activation, especially in the human colorectal adenocarcinoma or the human mammary gland ductal carcinoma cell lines. Not only would this line of questioning provide a higher significance and increase the clinical applicability of these findings, but it is also crucial to support the author's claim that MTMR knockdown can influence mutant KRAS activity. Although small changes in KRAS localization to the PM can have significant effects on downstream signaling, these effects need to be measured and confirmed in this setting. The authors should perform western blots to assess the activation of both the PI3K and MAPK pathway in the MTMR knockdown cell lines. In addition to this, it might be important to know whether there are any changes in the levels of the KRAS protein itself, as recycling/transport pathways may be impacted by its lack of recruitment to the plasma membrane. Finally, the authors show that proliferation is inhibited by MTMR knockdown as a readout of RAS activity. The authors should also assess the levels of cell death, as the inhibition of mutant KRAS in cancer cells would likely lead to cell death. The authors do not describe why reducing any one of the MTMR proteins alone is sufficient to deplete the PM of PtdSer. This sort of discussion is important for understanding compensatory or regulatory mechanisms in place between the MTMR proteins, as this may influence PtdSer levels at the PM. For example, it has been shown that MTMR2 can stabilize MTMR13 on membranes. Do the levels, stability, or localization of the other MTMR proteins change when one specific MTMR is knocked down? Is this why we see an effect on PtdSer in any one of the knockdowns? The authors should at the very least provide western blots for each of the MTMR proteins discussed in the presence of each individual MTMR knockdown.<br /> In addition to the above experiments, the MTMR hairpins should be expressed in a secondary or tertiary cell line to prove that these events are not specific to the current model used. Since their current human mammary gland ductal carcinoma cell line overexpresses a mutant KRAS-GFP construct, perhaps doing similar experiments in a cancer cell line that already expresses an endogenous mutant KRAS might provide a better model. Although this protein would not include a GFP-tag, other ways of visualizing its localization at the PM (such as immunofluorescent staining) could be used to confirm its localization there. In addition, the effects on downstream RAS signaling could be measured through western blot of PI3K and MAPK pathways. Supplemental Figure 4 is incorrectly referred to in the text as Supplemental Figure 3 (line 257-258). The text reads, "Confocal microscopy further demonstrates that HRASG12V cellular localization is not disrupted after silencing MTMR 2/3/4/7 (Fig. S3)" but Figure S3 is an EM image of PM basal sheets from T47D cells expressing GFP-KRASG12V. Supplemental Figure 4 shows that mutant HRAS is unaffected by the various MTMR knockdowns. Since the authors show decreased proliferation in mutant KRAS cells following MTMR knockdown, the authors should also investigate any changes to proliferation rates in mutant HRAS cell lines following MTMR knockdown. This data is necessary to prove that MTMR-driven changes in downstream RAS signaling are specific to mutant KRAS and not mutant HRAS. It may also be important for the authors to also show any effects on wildtype RAS localization to the PM when MTMR-2,-3,-4, and -7 are knocked down, to show whether this is a oncoprotein-specific event. <br /> The representative images chosen for Figure 4 diminish the reliability of the data, as it is difficult to see a visible change in the PI3P probe between the control and MTMR knockdown cells in these images. Since the authors rely on the Mander's coefficient and the number of gold particles throughout much of the paper, having the same conclusion quantitatively but not qualitatively for these assays is confusing. Perhaps the authors should elaborate on whether MTMR knockdown has a stronger effect on PtSer and KRAS PM presence than PI3P PM presence. They should also describe their method for identifying early endosomes, since they switch back and forth between describing the content of the PM and of early endosomes, such as in Figure 1 and Figure 4.

Minor comments:

An additional experiment that may add another layer of clinical applicability would be the use of an MTMR inhibitor in this cell line, to see whether similar effects can be achieved pharmacologically [7]. This would provoke other researchers to investigate MTMR inhibitors in vitro and in vivo to assess the effect on mutant KRAS cancers.

The inclusion of cell lines that express KRAS proteins of different mutational statuses would be extremely interesting, as KRAS' orientation within the plasma membrane has been shown to be altered by these mutations. This fact should potentially be considered when choosing a secondary or tertiary cell line to do additional experiments in, but it is not necessary for the authors to elaborate on how MTMR proteins may impact different KRAS mutants for the scope of this project.

The results of this paper rely heavily on one experimental technique, which is calculating a Mander's coefficient and counting the co-localization of the probe of interest with the CellMask stain of the plasma membrane. How this coefficient is derived is explained in appropriate detail in the methods section of this manuscript; however, a secondary route of identifying these changes in membrane constituents would greatly enhance the paper's conclusions. This would eliminate any doubt surrounding the accuracy of the technique, since so much of the data relies on one experimental output.

References

1. Clague MJ, Lorenzo O. The myotubularin family of lipid phosphatases. Traffic. (12):1063-9 (2005).
2. Chung J, Torta F, Masai K, Lucast L, Czapla H, Tanner LB, Narayanaswamy P, Wenk MR, Nakatsu F, De Camilli P. PI4P/phosphatidylserine countertransport at ORP5- and ORP8-mediated ER-plasma membrane contacts. Science. 349(6246):428-32 (2015).
3. Kim YJ, Guzman-Hernandez ML, Wisniewski E, Balla T. Phosphatidylinositol-Phosphatidic Acid Exchange by Nir2 at ER-PM Contact Sites Maintains Phosphoinositide Signaling Competence. Dev Cell 33: 549-561 (2015).
4. Balla A, Balla T. Phosphatidylinositol 4-kinases: Old enzymes with emerging functions. Trends Cell Biol 16, 351-361 (2006).
5. Arikketh D, Nelson R, Vance JE. Defining the importance of phosphatidylserine synthase-1 (PSS1): unexpected viability of PSS1-deficient mice. J Biol Chem. 283(19):12888-97 (2008).
6. Cockcroft S. The diverse functions of phosphatidylinositol transfer proteins. Curr Top Microbiol Immunol. 362:185-208 (2012).
7. Taylor GS, Maehama T, Dixon JE. Myotubularin, a protein tyrosine phosphatase mutated in myotubular myopathy, dephosphorylates the lipid second messenger, phosphatidylinositol 3-phosphate. Proc Natl Acad Sci U S A. 1;97(16):8910-5 (2000).

Significance

The significance of this paper lies in providing the field with an additional regulator of KRAS localization at the PM, as this is localization is critical to KRAS function. Despite three decades worth of understanding and even successfully blocking KRAS membrane localization in vitro, no KRAS-membrane-localization inhibitors have been approved for the clinic. Thus, there is still room in the field for the development of a safe therapeutic target that can effectively block this process. There is a consensus in the literature that PtdSer is critical for KRAS anchoring to the membrane, and this paper describes how MTMR proteins may impact the supply of PtdSer to the PM. Since this work is done in a cancer background by utilizing a mutant KRAS construct (KRASG12V), this work would be interesting to many cancer researchers that are attempting to target mutant KRAS. This paper would also be interesting to researchers who investigate mechanisms of PM maintenance.

Our lab studies RAS signaling in tumorigenesis. The authors are clear in their explanations of the mechanisms of PM maintenance and PM components relevant to this study.

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Reply to the reviewers

Manuscript number: RC-2023-01938R

Corresponding author(s): Ilan, Davis

1. General Statements

We thank all four reviewers for their helpful and constructive comments. We have gone through each and every comment and proposed how we would address each point raised by the reviewers. We are confident our proposed revisions are feasible within a reasonable and expected time frame. Some of the comments regarding minor typo/aesthetics and extra references have already been addressed in the transferred manuscript. The changes are highlighted in yellow in the transferred manuscript.

2. Description of the planned revisions

Reviewer #1 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Major points:

1. The presented work itself (Figures 1-4) does not need significant adjustments prior to publication, in my view, with only a few points to address. However, the work in Figure 5- doesn't really support the claims the authors make on its own, and would require some additional experiments or at the very least discussion of the caveats to its current form.

We thank the reviewer for these comments and will follow the reviewer’s suggestion by discussing the caveats regarding the interpretation of Figure 5. We will also add to the discussion to suggest future research approaches beyond the scope of this manuscript that would address the functional importance of localised mRNA translation. We will briefly mention in the discussion methods such as the quantification of the mRNA foci and the disruption of the mRNA localisation signals to disrupt localised translation and the use of techniques such as Sun-Tag (Tanenbaum et al, 2014) and FLARIM (Richer et al, 2021) to visualise local translation directly.

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Tanenbaum et al, 2014 DOI: 10.1016/j.cell.2014.09.039

Richer et al, 2021 DOI: 10.1101/2021.08.13.456301

* __ Localized glia transcripts, are they "glial/CNS/PNS" significant or are they similar to other known datasets of protrusion transcriptomes? The authors compared their 4801 "total" localized to a local transcriptome dataset from the Chekulaeva lab finding that a significant fraction are localized in both. As the authors note, this is in good agreement with a recent paper from the Talifarro lab showing conservation of localization of mRNAs across different cell types. What the authors haven't done here, is further test this by looking at other non-neuronal projection transcriptomic datasets (for example Mardakheh Developmental Cell 2015, among others). If the predicted glia-localized processes are similar to non-neuronal processes transcriptomes, this would further strengthen this claim and rule out some level of CNS/PNS derived linage driving the similarities between glia and neuronal localized transcripts. __*

This is a good point and we thank the review for pointing out this interesting cancer data set. We will do as the reviewer suggests and intersect our data with Mardakheh Dev Cell 2015 to test the further generality of localisation in neurons and glia, in other cell types. Specifically, we plan to intersect both glial (this study) and neuronal (von Kuegelgen & Chekulaeva, 2020) dataset with protrusive breast cancer cells (Mardakeh et al, 2015).

• *

von Kuegelgen & Chekulaeva, 2020 DOI: 10.1002/wrna.1590

Mardakeh et al, 2015 DOI: 10.1016/j.devcel.2015.10.005

* __ The presentation/discussion around Figure 3 is a bit weaker than other parts of the manuscript, and it doesn't really contribute to the story in its current form. Notably there is no discussion about the significance of glia in neurological disorders until the very end of the manuscript (page 21), meaning when its first brought up.. it just sits there as a one off side point. The authors might consider strengthening/tightening up the discussion here, if they really want to keep it as a solo main figure rather than integrating it somewhere else/putting it into supplemental. In my view, Figures 2 & 3 should be merged into something a bit more streamlined. __*

This is a good point. We plan to strengthen the presentation of Figure 3 and discussion of the significance of glia in neurological disorders by adding a description of the Figure in the Results section and highlighting the significance of glia in nervous system disorders in the Discussion section.

* __ Why aren't there more examples of different mRNAs in Figure 4? Seems a waste to kick them all to supplemental. __*

We agree that it could be helpful to show different expression patterns in the main figure. To address this point we will add Pdi (Fig. S4D), which shows mRNA expression in both the glia and the surrounding muscle cell. This pattern is in contrast to Gs2, which is highly specific to glial cells. We will also note that although pdi mRNA is present in both the glia and muscle, Pdi protein is only abundant in the glia, suggesting that translation of pdi mRNA to protein is regulated in a cell-specific manner.

The plasticity experiments, while creative, I think need to be approached far more cautiously in their interpretation. Given that the siRNAs will completely deplete these mRNAs- it really needs to be stressed any/all of the effects seen could just be the result of "defective" or "altered" states in this glial population- which has spill over effects on plasticity in at the NMJ. Without directly visualizing if these mRNAs are locally translated in these processes and assessing if their translation is modulated by their plasticity paradigm, all these experiments can say is that these RNAs are needed in glia to modulate ghost bouton formation in axons. This represents the weakest part of this manuscript, and the part that I feel does not actually backup the claims currently being made. Without any experiments to A. quantify how much of these transcripts are localized vs in the cell body of these glia, B. visualize/quantify the translation of these mRNAs during baseline and during plasticity; the authors cannot use these data to claim that localized mRNAs are required for synaptic plasticity.

We are grateful to the reviewer for pointing out that we were not precise enough in defining our interpretation of the structural plasticity assay. We did not intend to claim that our results show that local translation of these transcripts is necessary for plasticity, only that these transcripts are localized and are required in the glia for plasticity in the adjacent neuron (in which the transcript levels are not disrupted in the experiment). Definitively proving that these transcripts are required locally and translated in response to synaptic activity would require genetic/chemical perturbations and imaging assays that would require a year or more to complete, so are beyond the scope of this manuscript. To address this point, we will clarify that the results do not show that localized transcripts are required, only that the transcripts are required somewhere specifically in the glial cell (without affecting the neuron level), and we can indeed show in an independent experiment that there are localized transcripts.

Reviewer #2 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Major points:

1. * __ The authors analyse the 1700 shortlisted genes for Gene Ontology and associations with austism spectrum disorder, leading to interesting results. However, it is not clear to what extent the enrichments they observe are driven by their presumptive localization or if the associations are driven to a significant extent by the presence of these genes in the selected cell types in the Fly Cell Atlas. One way to address this would be to perform the GO and SFARI analysis on genes that are expressed in the same cells in the Fly Cell Atlas but were not shortlisted from the mammalian cell datasets - the results could then be compared to those obtained with the 1700 localized transcripts. __* This is a fair point raised by the reviewer as genes involved in neurological disease such as Autism Spectrum Disorder may be enriched in CNS/PNS cell types. We will follow the reviewer’s suggestion to perform GO and SFARI gene enrichment analysis in genes that were not shortlisted for presumptive glial localisation.

Although the authors attempt to justify its inclusion, I'm not convinced why it was important to use the whole cell transcriptome of perisynaptic Schwann cells as part of the selection process for localizing transcripts. Including this dataset may reduce the power of the pipeline by including mRNAs that are not localized to protrusions. How many of the shortlisted 1700 genes, and how many of the 11 glial localized mRNAs in Table 5, would be lost if the whole cell transcriptome were excluded. More generally, what is the distribution of the 11 validated localizing transcripts in each dataset in Table 4? This information might be valuable for determining which dataset(s), if any, has the best predictive power in this context.

We thank the reviewer for raising this point, which we will address with further analysis and adding to the discussion. We propose to address the criticism by running our analysis pipeline without the inclusion of the dataset using Perisynaptic Schwann Cells (PSCs) and then intersect with the PSCs-expressed genes, since their functional similarity with polarised Drosophila glial cells is highly relevant. We also agree with the reviewer that it would be a useful control for us to assess the ‘predictive power’ of each glial dataset by calculating their contribution to the shortlisted 1,700 glial localised transcripts and to the 11 experimentally validated transcripts via in situ hybridisation. To address this point, we plan to add this information in the revised manuscript.

* __ Did the authors check if any of the RNAi constructs are reducing levels of the target mRNA or protein? Doing so would strengthen the confidence in these important results significantly. In any case, the authors should also mention the caveat of potential off-target effects of RNAi. __*

We thank the reviewer for their useful comment and agree that the extent to which the RNAi expression reduces the levels of mRNA is not specifically known. We will add a FISH experiment on lac, pdi and gs2 RNAi showing very strong reduction in mRNA levels. We will also add an explanation of the caveats of the use of the RNAi system to the discussion.

Methods: what is the justification for assuming that if the RNAi cross caused embryonic or larval lethality then the 'next most suitable' RNAi line is reporting on a phenotype specific to the gene. If the authors want to claim the effect is associated with different degrees of knockdown they should show this experimentally. An alternative explanation is that the line used for phenotypic analysis in glia is associated with an off-target effect.

We thank the reviewer for this comment. We agree that off target effects cannot in principle be completely ruled out without considerable additional experimental analysis beyond the scope of this manuscript. To address the criticism we will remove the expression data of the lines that cause lethality and revise the discussion to explain that the level of knockdown in each line is unknown, and would require further experimental exploration.

Minor points:

1. It would be helpful to have in the Introduction (rather than the Results, as is currently the case) an operational definition of mRNA localization in the context of the study. And is it known whether or not localization in protrusions is the norm in mammalian glia or the Drosophila larval glia? I ask because it may be that almost all mRNAs diffuse into the protrusion, so this is not a selective process. One interesting approach to test this idea might be to test if the 1700 shortlisted transcripts have a significant underrepresentation of 'housekeeping' functions. We thank the reviewer for this excellent suggestion. To address the comment, we will move our explanation of the operational definition of mRNA localization to the Introduction. We will also perform enrichment analysis of housekeeping genes within 1,700 shortlisted transcripts compared to the transcriptome background, as the reviewer suggested.

Reviewer #3 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Major points:

1. The authors have pooled data from different studies across different type of glial cells performed from in vitro to in vivo. While pooling datasets may reveal common transcripts enriched in processes, this may not be the best approach considering these are completely different types of glial cells with distinct function in neuronal physiology. We thank the reviewer for highlighting the need for us to further justify why we pooled datasets. We will revise the manuscript to better emphasise that the overarching goal of our study was to try to discern a common set of localised transcripts shared between the cells. The problem with analysing and comparing individual data sets is that much of the variation may be due to differences in the methods used and amount of material, rather than differences in the type of cells used. We will revise the discussion to make this point and plan to explain that our approach corresponds well with a previous publication pooling localised mRNA datasets in neurons (von Kugelgen & Chekulaeva 2021).

von Kuegelgen & Chekulaeva, 2020 DOI: 10.1002/wrna.1590

It is important to note the limitations of the study. For example, DeSeq2 is biased for highly expressed transcripts. How robust was the prediction for low abundance transcripts?

The presented 1,700 transcripts were shortlisted based on their presence and expression level (TPM) in glial protrusions rather than their relative enrichment. Nevertheless, the reviewer makes a valid criticism of our use of DESeq2, where we compared enriched transcripts in glial and neuronal protrusions in Figure 1D. To address this point we will discuss this caveat in the relevant section.

The issue raised regarding low abundance transcript prediction raises an important question: does the likelihood of localisation to cell extremities correlate with mRNA abundance? We have already partially addressed this point, since our analysis of the fraction of localised transcripts per expression level quantiles shows only limited correlation. To address this comment, we will add these results in the revised manuscript as a supplementary figure.

The authors identify 1,700 transcripts that they classify as "predicted to be present" in the projections of the Drosophila PNS glia. This was based on the comparison to all the mammalian glial transcripts. Since the authors have access to a transcriptomic study from Perisynaptic Schwann cells (PSCs), the nonmyelinating glia associated with the NMJ isolated from mice; it would be more convincing to then validate the extent of overlap between Drosophila peripheral glial with the mammalian PSCs. This may reveal conserved features of localized transcripts in the PNS, particularly associated with the NMJ function.

Thank you for the valuable suggestion. A similar point was also raised by __[Reviewer #2 - Major point 2] __to re-run our pipeline excluding the PSCs dataset and intersect with the PSC transcriptome post-hoc. Please see the above section for our detailed response.

Fig 2: What is the extent of overlap between the translating fractions versus the localized fraction? It will be informative to perform the functional annotation of the translating glial transcripts as identified from Fig 1D.

This is an interesting question. To address this point, we plan to: (i) compare transcripts that are translated vs. localised in glial protrusions, and (ii) perform functional annotation enrichment analysis on the translated fraction of genes.

"We conclude predicted group of 1,700 are highly likely to be peripherally localized in Drosophila cytoplasmic glial projections". To validate their predictions, the authors test some of these candidates in only one glial cell type. It might be worthy to extend this for other differentially expressed genes localized in another glial type as well.

The presented in vivo analyses made use of the repo-GAL4 driver, which is active in all glial subtypes, including subperineurial, perineurial and wrapping glia that make distal projection to the larval neuromuscular junction. We agree that subtype-specific analysis would be highly informative, but we believe this is outside the scope of the current work where we aimed to identify conserved localised transcriptomes across all glial subtypes. Nevertheless, to address the comment, we plan to further clarify our use of pan-glial repo-GAL4 driver in the Results and Method section of the revised manuscript.

Figure 5: The authors perform KD of candidate transcripts to test the effect on synapse formation. However, these are KD with RNAi that spans across the entire cell. To make the claim about the importance of "target" RNA localization in glia stronger, ideally, they should disrupt the enrichment specifically in the glial protusions and test the impact on bouton formation. Do these three RNAs have any putative localization elements?

We agree with the review, that we would ideally test the effect of disruption of mRNA localization (and therefore localised translation). However, we feel these experiments are beyond the scope of this current study, as they will require a long road of defining localisation signals that are small enough to disrupt without affecting other functions. To address this comment we will revise the Discussion section to mention those difficulties explicitly, and clarify the limitations of the approach used in our study for greater transparency.

Reviewer #4 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Major points:

1. The authors use FISH to validate the glial expression of their target genes, though these experiments are not quantified, and no controls are shown. The authors should provide a supplemental figure with "no probe" controls, and/or validate the specificity of the probe via glial knockdown of the target gene (see point 2). Furthermore, these data should be quantified (e.g. number of puncta colocalized with NMJ glia membrans). Thank you for requesting further information regarding the YFP smFISH probes. We have validated the specificity and sensitivity of the YFP probe in our recent publication (Titlow et al, 2023, Figure 1 and S1). Specifically, we demonstrated the lack of YFP probe signal from wild-type untagged biosamples and showed colocalization of YFP spots with additional probes targeting the endogenous exon of the transcript. Nevertheless, we will address this comment by adding control image panels of smFISH in wild-type (OrR) neuromuscular junction preparations.

Titlow et al, 2023 DOI: 10.1083/jcb.202205129

For the most part, the authors only use one RNAi line for their functional studies, and they only show data for one line, even if multiple were used. To rule out potential false negatives, the authors should leverage their FISH probes to show the efficacy of their knockdowns in glia. This would serve the dual purpose of validating the new probes (see point 1).

Thank you for the suggestion. This point was also raised by [Reviewer #2 - Major point 3]. Please see above for our detailed response.

In Figure 5 E, given the severe reduction in size in the stimulated Pdi KD animals, the authors should show images of the unstimulated nerve as well. Do the nerve terminals actually shrink in size in these animals following stimulation, rather than expand? The NMJ looks substantially smaller than a normal L3 NMJ, though their quantification of neurite size in F suggests they're normal until stimulation.

We share the same interpretation of the data with the reviewer that the neurite area is reduced post-potassium stimulation in pdi knockdown animals. We will follow the reviewer’s suggestion and add an image showing unstimulated neuromuscular junctions.

Minor points:

The authors claim that there is an enrichment of ASD-related genes in their final list of ~1400 genes that are enriched in glial processes. It is well-appreciated that synaptically-localized mRNAs are generally linked to ASDs. Can the authors comment on whether the transcripts localized to glial processes are even more linked to ASDs and neurological disorders than transcripts known to be localized to neuronal processes?

This is an interesting point. To address the comment, we will add a comparison of the degree of enrichment of ASD-related genes in neurite vs. glial protrusions in the revised manuscript.

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

Reviewer #1

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1. The use of blue/green or blue/green/magenta is difficult to resolve in some places. Swapping blue for cyan would greatly aid in visualizing their data.
2. *

This comment is much appreciated. We have swapped blue for cyan in Figures 4 and S4. We have also changed Figure S1 to increase contrast and visibility as per reviewer’s comment.

Make the colouring/formatting of the tables more consistent, its distracting when its constantly changing (also there is no need for a blue background.. just use a basic white table).

This comment is much appreciated. We have applied a consistent colour palette to the Tables without background colourings and made the formatting uniform.

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Reviewer #2

• *

Introduction: 'Asymmetric mRNA localization is likely to be as important in glia, as it is in neurons,...'. Remove commas

Thank you for pointing this mistake out. We have made the corresponding edits.

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Reviewer #3

RNA localization in oligodendrocytes has been well studied and characterized. The authors should cite and discuss those papers (PMID: 18442491; PMID: 9281585).

We thank the reviewer for this useful suggestion. We have added these references to the paper.

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Reviewer #4

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• In Figure 5D, the authors should include a label to indicate that these images are from an unstimulated condition. We thank the reviewer for pointing this out. We have added the label as requested.

The authors are missing a number of key citations for studies that have explored the functional significance of mRNA trafficking in glia, and those that have validated activity-dependent translation:

- ____https://pubmed.ncbi.nlm.nih.gov/18490510____/

-____https://pubmed.ncbi.nlm.nih.gov/7691830____/

-____https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001053

-____https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450274____/

-_https://pubmed.ncbi.nlm.nih.gov/36261025_*/

*__

We thank the reviewer for the comment. We have added these references to the text.

• *

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

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

Learn more at Review Commons

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Reply to the reviewers

Dear Editor and Reviewers,

*We thank you for the thorough and detailed examination of our preprint and providing the very valuable comments that helped to even better present and interpret our data. *

*Thank you in particular for appreciating the extensive set of microscopic techniques that we have combined to study in a unique manner the characteristics and functionalities of FIT nuclear bodies in living plant cells. *

We prepared a revised preprint in which we address all reviewer comments. Our revision includes a NEW experiment (in four repetitions) that addresses one comment made by the reviewers with regard to the effects of the environmental FIT NB-inducing situation:

• NEW Supplemental Figures S6 and S7: Analysis of previously reported intron retention splicing variants of Fe deficiency genes FIT, BHLH039, IRT1, FRO2 in new gene expression experiments (Four independent repetitions of the experiments with three biological replicates of each sample – white/blue light treatment, sufficient and deficient iron supply). In the following, please find our detailed response to all reviewer comments.

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

We are looking forward to your response,

Sincerely

Petra Bauer and Ksenia Trofimov on behalf of all authors

Comments to the reviews:

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

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

Main comments:

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

Authors:

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

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

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

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

Authors:

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

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

Authors:

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

4) Direct conclusion in the manuscript:

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

Authors:

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

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

Authors:

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

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

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

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

Authors:

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

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

Authors:

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

Minor comments

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

Authors:

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

Line 106: What does IDR mean?

Authors:

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

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

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

Authors:

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

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

Line 188: Provide Figure ref.

Authors:

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

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

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

Authors:

We agree. We changed the text in two positions.

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

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

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

Authors:

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

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

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

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

Authors:

Please see the reformulated sentences and our response above.

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

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

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

Authors:

Thank you. We removed the conclusion.

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

Authors:

*This information is provided in the Supplemental Movie S1C. *

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

Authors:

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

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

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

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

Authors:

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

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

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

Authors:

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

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

Authors:

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

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

Authors:

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

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

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

Line 328: add the ref to figure, please.

Authors:

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

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

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

Authors:

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

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

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

Authors:

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

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

Authors:

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

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

Authors:

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

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

Authors:

We rephrased the sentence, line 387-388:

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

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

Authors:

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

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

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

Authors:

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

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

Authors:

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

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

Authors:

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

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

Authors:

*We shortened the discussion. *

**Referees cross-commenting**

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

Reviewer #1 (Significance (Required)):

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

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

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

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

Major points/comments:

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

Authors:

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

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

Authors:

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

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

Authors:

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

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

Authors:

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

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

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

Please comment and elaborate about this further.

Authors:

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

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

Authors:

Please see our response to your comment 4).

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

Authors:

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

Minor comments:

Line 75-76: Rephrase the sentence

Authors:

We rephrased the sentence, lines 73-74:

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

Line 119: Rephrase the sentence

Authors:

We rephrased the sentence, line 118-119:

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

Line 235-236: rephrase the sentence

Authors:

We rephrased the sentence, line 232-234:

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

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

Authors:

We corrected that, line 449-451:

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

**Referees cross-commenting**

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

Reviewer #2 (Significance (Required)):

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

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Reply to the reviewers

We thank all three reviewers for their positive comments on the value of our work and for and for their helpful suggestions.

*Reviewer #1 (Evidence, reproducibility and clarity:

This manuscript reports the development of a new bright fluorescent reporter that allows to label neighbouring cells. The system is based on upon secretion and uptake of s36GFP, a positively supercharged fluorescent protein. The authors also develop a Halo tag that will allow for straight forward colour exchange, as well as a customisable single plasmid construct with modular components.

There are some minor suggestions that the authors may want to consider: 1) The authors conclude that "PUFFIN labelling is transferred rapidly between cells within minutes". They report in their time lapse experiments (Figure 2A,C) that sGFP can be detected within neighbours of secretors after 30 minutes when the cells are plated in a 50:1 non-labelled/secretor cell ratio, whereas it can be detected after 15 minutes when the cells are plated in a 1:9 ratio. Is there any synergistic effect on the signal when the proportion of secretors is increased or is this difference just because there is more signal, making it easier to visualise. *

We have addressed this point with new experiments (new data shown in Figure 2E and Supp Figure S2A,B). This makes it clear that labelling can indeed be detected earlier when the proportion of secretors is higher. This is likely to be because higher secretor:acceptor ratios result in stronger labelling, which in turn makes it easier to detect labelled neighbours at very early time points - even within as early as 15 minutes. We also confirm that, even when secretors are very sparse (1:50 ratio), label becomes detectable in neighbours within 60 minutes.

1. *Is there any reason why the main Figure legends lack a title, but the supplementary figures have one? 2. In Figure 3, it may be helpful to label each option as A, B, C.. 3. In Figure 4E, the legends + JF646 and -JF646 may be switched around. Shouldn't the orange box should be (+) and the grey box should be (-)?

   *

We have modified / corrected the labelling as suggested and added titles to the main figure legends.

*Reviewer #1 (Significance):

This is a very valuable tool to address how cells change the behaviour of those in their environment. It will be very valuable for those interested in cell non-autonomous effects within a cell population or tissue. It will be especially valuable for live cell imaging; pulse chase experiments as well as omics approaches to understand cell behaviour in niches. *

We thank this reviewer for their positive comments on the value of our work.

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

The authors describe a new method, Positive Ultra-bright Fluorescent Fusion For Identifying Neighbours (PUFFFIN), to label with Fluorescent Proteins, neighboring cells. In brief, specific cells that express a nuclear mCherry are engineered to secrete a supercharged fluorescent protein (36GFP) fused to the ultra-bright green-fluorescent mNeonGreen (mNG) (s36GFP). Neighboring cells uptake s36GFP and can be easily visualized. The authors added the human serum albumin signal peptide which is efficiently cleaved to create s36GFP. The PUFFFIN system can also be customized for color-of-choice labelling using HaloTags. A shortcoming of the paper is that it is a method paper established in tissue culture cells with no biological applications. A test of the system in an in vivo model would improve the study. The authors should at least describe specific examples of how the method can be used to answer biological questions. *

We agree that the paper would be improved by demonstrating a biological application of our system. We are currently working on experiments to address a biological question, and will be submitting a revised manuscript containing these data.

*Reviewer #2 (Significance (Required)):

This straightforward and elegant approach is an improvement of current methods that are based on synthetic receptor-ligand interactions as it does not require genetic modification of both 'sender' cells and 'responding' cells. The approach should prove to be an effective and flexible tool for illuminating cellular neighborhoods. An interesting potential application of the method is to effectively deliver proteins fused to s36GFP.

A shortcoming of the paper is that it is a method paper established in tissue culture cells with no biological applications. A test of the system in an in vivo model would improve the study. The authors should at least describe specific examples of how the method can be used to answer biological questions.*

We thank this reviewer for their positive comments on the value of our work. We agree that the paper would be improved by demonstrating a biological application of our system. We are currently working on experiments to address a biological question, and will be submitting a revised manuscript containing these data

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

In this manuscript, the authors introduced a novel cell-neighbor-labeling system named PUFFFIN. PUFFFIN, as well as 'PUFFHalo', offers an elegantly simple method for distinguishing between secretors and receivers, providing users with a versatile tool to label proximate neighbors through the uptake of s36GFP, subsequently permitting their isolation via FACS for subsequent analysis. In addition, this system could be very useful considering of its customizability by exchanging elements, such as tissue-specific promotors, color-of-choice (HaloTag), and genes of interest to cater to the diverse requirements of secretors. Overall, this system is well-designed and characterized, and the claims in this study are mostly supported by the data. However, this neighbor-labeling approach is not efficiently used to obtain biological insights. The following comments are intended to enhance the overall quality of the study:

Major comments: *

1. * In Vidio1, it appears that certain nuclear mCherry+ cells did not secrete s36GFP-mNG during 19hrs recording window. However, in Figure1D and E, these GFP-mCherry+ cells were reported as having a 0% occurrence. This may be the result of either a delay in GFP secretion, or possible mCherry leakiness in unmodified cells. Please provide clarification. *

There is indeed one mCherry+ cell in video 1 that fails to generate s36GFP-mNG signal. This cell, unlike most other cells in the movie, fails to divide or actively migrate during the 19h recording period, but instead is being passively “pushed around” by surrounding cells, and therefore looks to us very much like a dead or dying cell (levels of cell death to tend to be slightly higher than usual during live imaging). We have looked through our other videos and identified only one other example of an mCherry+ GFP-negative cell: this cell is clearly dying because the nucleus disintegrates over the course of the movie.

We considered the possibility that some proportion of secretors may fail to generate signal even if they are healthy. We examined all our FACS analysis data. We detected at most 0.15% of such ‘failed secretors’, and most usually none. We conclude that any mCherry+ GFP- cells exist at extremely low frequencies and/or tend to be dying cells. Either way, they are very unlikely to interfere with interpretation of experimental data.

*Additionally, including representative images of the co-culture experiment in Figure 1.E would enhance the presentation of the data. *

These data have now been added to Supplemental Figure S1 C

*Since the authors mention that s36GFP-mNG labeling was not detectable beyond four cell diameters, it would be helpful to include statistical data regarding the average distances or cell layers that GFP can travel, thus describing the permeation and labeling limit of s36GFP-mNG, adjacent to Figure2C. *

We’ve now quantified the data and provide this information in a new panel (Figure 2D).

*Please comment on the application prospect of this system utilizing in vivo. In addition, comment should be made on the difference of PUFFFIN system and recent reported CILP (PNAS 2023). *

We have added discussion on prospects for using the system in vivo (new text lines 65-67). We have also described the CILP system in the revised introduction, explaining that it is an inducible version of the Cherry Niche system that we describe in our introduction (new text lines 291-294).

*Minor comments: 1. Please include the percentage of GFP+ and GFP- cells in Figure2.D, similar to what is provided in Figure S1.B. *

This is a great suggestion so we have decided to add this information to all flow cytometry histograms within the paper, Figure 2D.

*The '+' and '-' marks in Figure3.E appears to be mismatched with the results, please double-check and correct. *

This has now been corrected.

*I am curious about the interactions between secretors and 'receivers.' As the authors claim 'unbiased labeling' with this system, it's important to investigate whether the uptake abilities of receivers vary among different cell types. In other words, does the system exhibit cell-type preferences among receiver cells? This question could be optionally addressed through co-culture experiments involving secretors, receiver type A, and receiver type B. *

We will perform additional experiments to address the reviewer’s question by directly comparing labelling efficiency across different receiver cell-types.

Reviewer #3 (Significance (Required)):

*This study reported a simple and sensitive system for labeling neighboring cells in vitro, which can be customized by replacing exchangeable components for customized need. With promising application in vitro, this system could be further developed and tested in vivo. Fluorescent protein labeling in neighboring cells has been a topic of study recently, and this manuscript introduced a new tool that is added to such resources, offering a user-friendly and customizable alternative. Overall, this system will be of interest to researchers working on neighbor-cell labeling and study of cell-cell communications. *

We thank this reviewer for their positive comments on the value of our work.

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

This manuscript reports the development of a new bright fluorescent reporter that allows to label neighbouring cells. The system is based on upon secretion and uptake of s36GFP, a positively supercharged fluorescent protein. The authors also develop a Halo tag that will allow for straight forward colour exchange, as well as a customisable single plasmid construct with modular components.

There are some minor suggestions that the authors may want to consider: 1. The authors conclude that "PUFFIN labelling is transferred rapidly between cells within minutes". They report in their time lapse experiments (Figure 2A,C) that sGFP can be detected within neighbours of secretors after 30 minutes when the cells are plated in a 50:1 non-labelled/secretor cell ratio, whereas it can be detected after 15 minutes when the cells are plated in a 1:9 ratio. Is there any synergistic effect on the signal when the proportion of secretors is increased or is this difference just because there is more signal, making it easier to visualise. 2. Is there any reason why the main Figure legends lack a title, but the supplementary figures have one? 3. In Figure 3, it may be helpful to label each option as A, B, C.. 4. In Figure 4E, the legends + JF646 and -JF646 may be switched around. Shouldn't the orange box should be (+) and the grey box should be (-)?

Significance

This is a very valuable tool to address how cells change the behaviour of those in their environment. It will be very valuable for those interested in cell non-autonomous effects within a cell population or tissue. It will be especially valuable for live cell imaging; pulse chase experiments as well as omics approaches to understand cell behaviour in niches.

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

Reviewer #1

Evidence, reproducibility and clarity

In this manuscript, Hoskins et al describe analyses of the effects of sequence variation on RNA levels, protein levels, and ribosome loading for the COMT gene. They use multiple experimental approaches to assay these levels and report on how sequence differences affect expression. Overall, the paper is interesting in that it presents a very deep dive into the effects of sequence variation on gene expression, including in coding sequences. However, there are some issues with the polysome loading assay technique and there are substantial issues with the figure presentation, which is often confusing.

__Response: __Thanks for the positive assessment of our manuscript and the constructive feedback regarding the issues with the figure presentation. We have addressed all of these below and they have significantly improved the clarity.

• Major comments:*

• 1) Figures:*

• --Fig 1C needs a cartoon description to show where the UTRs are. Y-axis should say "Ribo-seq CPM"*

__Response: __Fig 1C now includes a schematic and the y-axis is updated. Locations of the uORFs are also now included in Fig 1A.

• --Sup Fig 1A confusing, what is "start" what is the point of this panel?*

__Response: __We apologize for the confusing labeling of the panels in Sup Fig 1. “Start” refers to the MB-COMT start codon. We removed this annotation as it is irrelevant to the figure. We included Supplementary Figure 1A to show RNA probing data for the entire transcript. Figure 1A and B only show the regions that encompass the variants assayed in our study.

• --Sup Fig 1B what is PCBP del?*

Response: “PCBP del” refers to deletion of PCBP1/PCBP2 RNA binding protein motifs. The legend now specifies this.

• --Sup Fig 1C what is "uORF B restore"? The description in the figure legend is not interpretable. Draw diagrams of the mutations that tell the reader what was assayed and why it was assayed. Why are there multiplication factors listed (e.g. 1.33X)? The data are depicted on a log scale, which makes it difficult to appreciate the fold-effects of the mutations (e.g. does uORFA mutation increase expression 1.5-fold?). Please calculate median expression values and report them on a bar graph or something like that so readers can interpret the results.*

Response: “uORF B restore” refers to restoration of the endogenous uORF B frame with a silent variant in the Flag tag of the transgene. The multiplication factors listed were the fold change in median fluorescence between each mutant and the template (wild-type) transgene. We retained the figures as they show the raw distribution of fluorescence in each cell line, but in response to the reviewer’s suggestion we included a new figure displaying the effects as a bar graph (Supplementary Figure 1E).

• --Fig 2A. It's hard to understand the cartoon diagram of the expression reporter construct. Why is +Dox shown here? Does that induce transcription?*

__Response: __The reviewer is correct. “+Dox” indicated addition of Doxycycline to induce transcription before the data collection step. We agree that there may have been too much detail in this diagram and have now removed this for simplicity and indicated this in the Methods section.

• --Fig 2B. What's on the x-axis? is it Log2(RNA/gDNA) from sequencing? is it Log2 or Log10 or Ln?*

__Response: __Variant effects in each figure were derived from ALDEx2 analysis, which reports effect size as the median standardized difference between groups. The effect size is not directly interpretable as a log fold change; it takes into account the difference between groups as well as the dispersion. This analysis strategy has been previously demonstrated for analysis of SELEX experiments (Fernandes et al. 2014), which are used to select small populations of cells with specific phenotypes.

ALDEx2 is a robust and principled choice for the analysis of count-compositional datasets, particularly after selection (e.g. sorted cell populations or low-input RNA fractions arising from polysome profiling). While we understand that this choice leads to less easily interpretable effect sizes, the mathematical advantages make ALDEx2 a more appropriate choice for this type of data. In the past, we had used other methods to analyze log frequencies (limma, a frequency based normalization-dependent analysis, as previously employed in Hoskins et al. 2023. Genome Biology) that directly reported fold changes. In our experience, the ALDEx2-derived effect sizes are well-correlated with those estimates (Pearson correlation 0.93 for variants significant at a FDR

• --Fig 2C. What's on the y-axis (same question). I think it's LogX(mutant/wt)RNA level?*

__Response: __For consistency with other figures, we replaced Figure 2C to report the effect size statistic as described above.

• --Fig 2D. What's on the y-axis now? Fold-difference (not log transformed)?*

__Response: __Please see our response above.

• --Fig 2E. The scale bar is flipped vs. normal convention. This is also log transformed, but it's not labeled. Please label as log(whatever) and put the negative values on the left side of the bar (red on the left, blue on the right).*

__Response: __Thanks for the suggestion, we have now updated the scale bar.

--Fig 2F y-axis should say Ribo-seq CPM.

__Response: __Done

• --Fig 3A - please separate the graphs more. Did you sort cells from ROI2 into populations, or just cells from ROI1?*

__Response: __Thanks for the suggestion, we now separate the graphs further. Cells were sorted for both ROI 1 and ROI 2 libraries.

• --Fig3C-F What's the "effect size" mean on these graphs?*

__Response: __Please see the response above regarding the effect size estimate from ALDEx2.

• --Fig3D It looks like the colors have switched for positive / negative "effects" on the heat map*

• compared to Figure 2E. Please define what "median effect" means and be consistent with*

• comparison to figure 2E.*

__Response: __We intentionally inverted colors for Figure 3. The rationale is that a variant causing low protein abundance corresponds to enrichment in P3 compared to gDNA, as opposed to depletion in P3. On the other hand, for effects on RNA abundance and ribosome load, a variant leading to low abundance for these measures is depleted.

• --Figure 4 what does effect size mean, what's the log-transformed scale (log2, 10, etc) same issues from earlier figures.*

__Response: __Please see response above.

• --Figure 5 "effect size"*

__Response: __The same definition of effect size was used with the exception that effect sizes are multiplied by -1 so that color schemes are consistent for deleterious effects.

• 2) "Codon stability" should always be "Codon Stability Coefficient", maybe use "CSC". Otherwise it's confusing.*

__Response: __Thanks for the suggestion. This has been updated throughout the manuscript.

3) Flow cytometry section talks about "RNA fluorescence", which is confusing. You need to explain that it's IRES-driven mCherry as a proxy for the level of RNA first. It would also help to state explicitly that you sorted the cells into four populations, and define them all first before describing the results.

__Response: __We apologize for the use of imprecise language with respect to this reporter. We revised the text to emphasize that mCherry is a proxy for RNA abundance and described the populations first as suggested.

4) What are DeMask scores? How are they related to conservation or amino acid properties? If you define these, you can help the reader interpret the result.

__Response: __Thanks for the suggestion. We now include a conceptual interpretation of the DeMask score in the relevant section. We also include a comparison to a recent large language model for variant effect prediction (ESM1b, Brandes et al. 2023) which is now reported in Supplementary Figure 5C.

5) There are several issues with the Polysome gradient fractionation. The gradients did not separate 40S, 60S, and monosomal fractions, so it's hard to tell how many ribosomes correspond to each peak on the gradient graph in Figure S5. This is probably because the authors used a 20-50% gradient instead of a lower percentage on top. More significantly, variations in the coding region of COMT are likely affecting the polysome association in ways the authors didn't consider. Nonsense codons will simply make the orf a lot shorter, hence fewer ribosomes. This may have nothing to do with NMD. Silent and missense variants may have unpredictable effects because they may make translation faster (fewer ribosomes) or slower (more ribosomes) on the reporter. This could lead to more ribosomes with less protein or fewer ribosomes with more protein. The reporter RNA also has an IRES loading mCherry on it, which probably helps blunt or dampen the effects of the COMT sequence variants on polysome location distribution. Overall, the design of the polysome assay is probably very limited in power to detect changes in ribosome loading (four fractions, limited separation by 20-50 gradient, IRES loading, etc). This is partially addressed in the limitations section, but these issues could be discussed in more detail.

__Response: __Given high polysomal association of endogenous COMT and our COMT transgene (Supplementary Figure 2B, Supplementary Figure 5B-C), we chose a 20-50% sucrose gradient to better resolve changes in ribosome load among heavy polysomes.

We thank the reviewer for offering another valid explanation regarding the depletion of nonsensense variants. We have now included a sentence in the discussion to indicate lower ribosome load for nonsense variants may be due to a shorter ORF as opposed to NMD. We further include the potential limitation of the assay due to the presence of the IRES-mCherry.

We agree that variants may have unpredictable effects due to effects on the dynamics of translation elongation. To address this potential limitation, we attempted to devise a selective ribosome profiling strategy by immunoprecipitating N-terminal Flag tagged peptides to enrich ribosomes translating COMT. However, we were unable to achieve significant enrichment, limiting our ability to measure variant effects on elongation in a high-throughput manner.

Significance

The study is novel in that it assays both 5' UTR and a wide range of protein coding sequence variants for effects on RNA and protein levels from a clinically important gene, COMT. The manuscript reports that most protein coding variants have modest effects on RNA levels, and that the minority of variants that do affect RNA levels are not predictable due to their affect on codon usage. The work also determines the distribution of effects of variants on protein levels, finding a variety of effects on expression. Interestingly, the authors found SNPs that affect ribosome loading generally affect RNA structure of the COMT coding region, rather than affecting codon usage.

This should appeal to many different communities of biologists - gene expression experts, geneticists, and clinical neurobiologists who focus on COMT. So there is a potential for fairly broad interest. The main limitations to the work are in a lack of clarity in the figures and perhaps in the underdeveloped nature of the discussion section. The discussion section reports new results (SNP associations that affect expression). These would make more sense in the results section, such that the discussion could do a better job relating the impact of sequence variants on expression levels to prior work to highlight the novelty.

__Response: __We thank reviewer #1 for their positive assessment of the broad significance of our study. We also thank them for constructive suggestions that led to increased clarity in the presentation. We have moved the analysis of gnomAD variants to the Results section and expanded the discussion.

Reviewer #2

Evidence, reproducibility and clarity

Summary:

Hoskins and colleagues expressed a reporter containing all silent, missense, and nonsense codons at 58 amino acid positions in the human COMT gene in HEK293T cells and measured levels of DNA, bulk RNA, and pooled polysomal mRNA. They included a C-terminal translational GFP fusion and a downstream transcriptional mCherry fusion in the reporter in order to also bin variants by their relative protein and mRNA levels by flow cytometry. They hypothesized that RNA structure, in-part by mediating uORF translation, influences COMT gene expression. The authors conclude by identifying previously-uncharacterized COMT variants that, in this reporter system, affect RNA abundance and ribosome load. We generally found the results of this paper convincing and clear. We do not have major comments, but have many minor comments that we hope the authors can address. These comments mostly deal with clarification on analysis metrics and giving recommendations on data presentation.

__Response: __Thanks for highlighting the strengths of our study and the constructive suggestions to improve the presentation.

Minor comments:

In Figure 2C, the vertical axis reads "Median between-group difference". How was this metric calculated and normalized? We also agree that nonsense mutations having consistently-detrimental effects on RNA abundance is reassuring, but recommend more explanation as to why the difference in the effects of silence and missense mutations between regions may be biologically relevant.

__Response: __Variant effects in each figure derive from ALDEx2 analysis, which reports effect size as the median standardized difference between groups. In particular, to avoid any distributional assumptions for standardization, ALDEx2 uses a permutation based non-parametric estimate of dispersion. The effect size is not directly interpretable as a log fold change; it takes into account the difference between groups as well as the max dispersion of the groups. We have now provided explicit references to the specific R functions that were used to calculate the effect size.

ALDEx2 is robust for analysis of count-compositional datasets, particularly after selection and bottlenecking (e.g. sorted cell populations or low-input RNA fractions arising from polysome profiling). While we have used other methods to analyze log frequencies (limma, a frequency based normalization-dependent analysis, as previously employed in Hoskins et al. 2023. Genome Biology), we opted for the less-interpretable but more robust ALDEx2 analysis to report variant effects between varying nucleic acid inputs.

We currently lack a mechanistic interpretation for the difference in RNA abundance effects between ROI 1 and 2. However, we observed consistent results using a different analysis framework, which makes use of variant frequencies (as in Hoskins et al. 2023 Genome Biology) instead of the centered log ratios used in ALDEx2 analysis, further supporting a biological difference between the two.

In Figure 3, we believe that the authors are claiming that lower RNA abundance causes lower protein abundance in some variants. However, this data only reports on protein abundance relative to transcript abundance, not absolute protein abundance. We think the claim should be revised to (1) clarify that the authors are measuring protein per mRNA, and (2) express that lower mRNA amounts are more likely to co-occur with lower protein amounts, but that this data does not support any causative model.

__Response: __Thanks for the suggestion. We have now included an explicit description of the experimental design in the results section and noted that we are unable to assign protein abundance effects to underlying RNA abundance effects. In the current setup, we did not sort cells based on the ratio of moxGFP/mCherry fluorescence (protein per mRNA), but rather we defined gates based on the 2D plot of moxGFP versus mCherry. This is explicitly marked in Figure 3A.

On page 9, the authors claim that their data supports a model that rs4633 increases RNA

abundance, leading to higher COMT expression. Can the authors rule out a model whereby rs4633 facilitates translation initiation, as suggested by Tsao et al. 2011, leading to both an increase in mRNA and protein abundance?

__Response: __Thanks for this question and opportunity to clarify. We have now added a sentence to the Discussion and included the following paragraph in the Supplementary Note:

“Importantly, our study does not rule out a model where rs4633 facilitates translation initiation. Nevertheless, our data suggest a potential concurrent mechanism where rs4633 leads to higher protein abundance in human cell lines and in an in vitro translation assay (Tsao et al. 2011) by increasing RNA abundance. We note that Tsao et al did not directly measure RNA abundance in their study. In Supplementary Figure 3A of Nackley et al 2006, the APS haplotype containing rs4633 C>T showed slightly higher total RNA abundance compared to the LPS haplotype (in our study, the wild-type template). However, this was not statistically significant and was only observed for the S-COMT isoform. It is possible that our observations are compatible with the conclusions in Tsao et al. 2011. For example, increased translation of rs4633 C>T may lead to stabilization of the RNA.”

The paper references "effect size" at multiple points (e.g. "polysome effect size") but we could not find this term explicitly defined (for example: for the polysome effect size, were RNA counts for each polysome fraction divided by the relative abundance of that RNA in total RNA?)

__Response: __We apologize for this confusion. Please see our response above. We have also stated the definition of effect size explicitly in the revised manuscript.

Could you elaborate on how you define "protein abundance and "effect size: in Figure 5G? How is enrichment in P3 or P1 calculated?

__Response: __Effect size is defined as described above. Enrichment in P3 or P1 is calculated with respect to the abundance in gDNA (unsorted cells).

Were 3396 variants considered for all readouts in this paper? How many of these variants were present in each ROI? It may be worth clarifying sample sizes.

__Response: __Thanks for the suggestion. The reviewer is correct: 3396 variants were present in all biological replicates and all readouts (after excluding polysome metafractions 1 and 2 and flow cytometry population 4). The Methods were updated to include all readouts that were dropped. The number of variants in each ROI are now included in this section of the main text.

How did Twist generate these mutagenized sequences? We assumed that they used error-prone PCR due to the mention of multiple nucleotide polymorphisms, but couldn't find an explicit answer.

__Response: __Twist generates these mutagenized inserts using degenerate primers. This allows all alternate codons to be assayed (all silent, missense changes). This is now noted in the Methods.

https://www.twistbioscience.com/resources/technical-note/solid-phase-dna-synthesis-allows-tight-control-combinatorial-library

In the methods, it may be worth elaborating on the composition of the HsCD00617865 plasmid. For example: this COMT reporter is under the control of a constitutively-expressed T7 promoter, correct?

__Response: __The HsCD00617865 plasmid was only used as a template for PCR amplification and generation of the transgene. The transgene is cloned into a vector containing attB sites for recombination into the landing pad cell line (Matreyek et al 2020). Transcription is induced by Doxycycline from the landing pad locus. Plasmid maps used for transfection into the landing pad line are now included in the GitHub repository.

In Supplementary Figures 4 and 5, it would be helpful to explicitly say that you are reporting Pearson correlations between biological replicates.

__Response: __Thanks for the suggestion. The legends have been updated accordingly.

"After summarizing biological replicates (N=4) for each readout...": how did the authors summarize biological replicates? Were counts averaged?

__Response: __Biological replicates were summarized using the median. This is now clarified in the Methods.

The authors used pairwise correlations between flow cytometry fractions, polysome fractions, and total RNA/gDNA as indications of data quality. Do the authors expect for these counts to be strongly correlated? We would not necessarily expect to see a strong correlation between ribosome load and RNA/gDNA.

__Response: __We used replicate correlation as an indicator of data quality. Our readouts of ribosome load reflect the abundance of a variant in a particular polysome fraction. Given that variants that are highly abundant in the RNA pool will on average be more highly represented in polysome fractions, we would expect a correlation between the abundance of a variant in total RNA and in polysome fractions.

The authors may need to check that their standard deviations on fold changes are properly reported.

__Response: __iIn the Figures and the main text, we specified the confidence intervals as calculated by ALDEx2 method instead of reporting standard deviations on fold changes,. Specifically, the confidence intervals were determined by Monte Carlo methods that produce a posterior probability distribution of the observed data given repeated sampling. Variants in which the confidence intervals do not cross 0 are considered true discoveries (section 5.4.1 of the ALDEx2 vignette on Bioconductor).

https://www.bioconductor.org/packages/devel/bioc/vignettes/ALDEx2/inst/doc/ALDEx2_vignette.html#541_The_effect_confidence_interval

We would expect standard deviation bounds to be symmetric for log fold changes, but not on unlogged fold changes - for example see page 8, for the sentence "our point estimate for nonsense variant effects on COMT RNA abundance was approximately a two-fold decrease relative to the gDNA frequency (fold change of 0.43 +/- 0.13; mean +/- standard deviation; Methods)."

__Response: __Thanks for the suggestion. To avoid any confusion about the symmetry, we replaced the +/- notation, and explicitly noted the mean and standard deviation. To help the reader gain an intuition of the magnitude of variant effects, we conducted a frequency based normalization-dependent analysis using limma (as previously employed in Hoskins et al. 2023. Genome Biology). We now report a fold change (unlogged) for RNA abundance compared to gDNA abundance. The point estimate is the mean and s.d. across all nonsense variants.

On page 10, the authors say that their data suggests that hydrophobicity in the early coding region of COMT may be important for COMT folding. If this is the case, would we expect to see this effect in flow cytometry data (which is affected by protein degradation) and not polysome profiling (which is unaffected by post-translational protein degradation)?

__Response: __We apologize as we are uncertain about the reviewer’s intended question. The section that refers to the importance of hydrophobicity indeed refers to the flow cytometry data. While there are specific instances in which the amino acid properties encoded by the mRNA influences translation dynamics, these are not universally true. Consequently, we did not expect these impacts to be observed at the level of polysome profiling.

We believe that we would have some trouble replicating the analysis from this paper from the raw data, given that the bulk of the analysis on GitHub is presented as a single R Markdown file, with references to local files to which we do not have access. We recommend that the authors add additional documentation to their repository to facilitate re-analysis.

__Response: __Thanks for the opportunity to address this issue of critical importance. To facilitate replication, we have now deposited all analysis files to Zenodo and refactored the code to enable replication by simply running a markdown file.

In Figure 1B, indicating that more signal indicates less structure (in the legend or the figure itself) may assist readers who are unfamiliar with DMS-seq.

__Response: __Thanks for the suggestion. This is now updated.

Figure 1C does a great job presenting evidence for the translation of uORFs, but does not seem to flow with the overall argument of the paper, so may fit better in the supplement.

__Response: __We considered this suggestion, and opted for keeping its placement as it gives evidence that our transgene is translated primarily as the MB-COMT isoform. This ensures that, for variants upstream of the S-COMT isoform, we can assay effects on ribosome load that are tied to mechanisms of translation elongation and codon stability.

We believe there is a typo in the Figure 1 legend that should read "K562" instead of "H562".

__Response: __Thank you, this was indeed a typo.

You also gated to separate into P1-P4, correct? Can you also show the bounds of that gating

strategy in Figure 3A?

__Response: __This has been updated. We also added the gating strategy in response to comments from reviewer #1.

We find Figure 3F very compelling. Do you have any theories as to why mutating I59-H66 to

nonpolar, uncharged residues leads to increased COMT expression?

__Response: __We do not have any theories for why this may be. However, we noted that with the exception of V63, residues I59-H66 are not evolutionarily constrained (based on DeMask entropy values). This suggests mutational tolerance for nonpolar, uncharged residues in this region (with the exception of V63 and H66; see Figure 3D).

There appears to be a non-negligible proportion of di- and tri- nucleotide polymorphisms in Supplementary Figure 4. Were these excluded in downstream analyses?

__Response: __These variants are expected from the Twist mutagenesis strategy and included in analysis. We believe they are at lower frequency compared to SNPs due to less favorable annealing of the degenerate primers.

A minor typo in the discussion reads "fluoresce".

__Response: __Done

Significance

Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

This work investigated the regulatory effects of thousands of coding variants in the COMT gene, focusing on two regions with clinical significance, by using high-throughput reporter assays. The results from this will be useful for clinical scientists interested in understanding the impacts of COMT mutations and be a useful framework for other systems/computational biologists to understand the impacts of coding mutations across different levels of regulatory function. Mutations in protein regions, if having a function, are classically known to interfere with protein function. There are fewer large-scale efforts to understand the impacts of coding mutations affecting expression through potentially changing of RNA structure or codon optimization - this work has contributed towards that frontier.

Place the work in the context of the existing literature (provide references, where appropriate). This is (as far as I am aware) the first paper that has integrated high-throughput screens massively parallel reporter assays from RNA degradation, ribosomal load, and flow cytometry. Previous papers have tended to measure on expression regulation on only one dimension (i.e. Greisemer et al. 2023 on RNA degradation, Sample et al. 2019 on ribosomal load, and de Boer at al. 2020 on protein expression).

__Response: __Thanks for highlighting the novelty of our approach compared to existing strategies in the literature.

State what audience might be interested in and influenced by the reported findings.

Clinicians/researchers interested in COMT, computational biologists, geneticists and potentially structural biologists interested in understanding the consequences of amino acid mutations on RNA/protein expression

__Response: __Thanks for noting the broad significance of our study.

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.

Genomics, Massively parallel reporter assays, High-throughput regulatory screens.

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

*This manuscript reports on transcript sequence variants that affect expression of the gene COMT. Targeted analysis of SNPs identifies 5' UTR variants that affect COMT, leading to the identification of translated uORFs. Common coding sequence SNPs do not affect COMT expression, however. Massively parallel analyses of mRNA abundance, protein abundance, and translation are combined to look more broadly at coding sequence variants. These analyses focus on regions of predicted structure in the COMT transcript. Both silent and missense mutations that increase mRNA abundance are identified. Protein abundance is then measured and many missense mutations are found to change protein levels. To address translation directly, analysis of polysome loading is performed and significant differences are identified, although technical challenges limit data quality in these experiments. These different experiments are then analyzed jointly to classify mutation effects and identify a class of silent mutations with expression effects, leading to a proposal that these act through structure. *

*The joint, integrative analysis of COMT variants through a range of methods allows clearer insights into interconnected post-transcriptional effects. The massively parallel experiments generate high-quality data, although targeted validation of key results would strengthen the work. The findings advance our understanding of silent variant effects, which remains an open question, and technical innovations could find broader applications. *

__Response: __Thanks for the positive assessment of the quality of the data generated and the potential for the broader application of the technical innovations.

*I do have concerns with the present version of this work. *

1. • There is no validation presented for high-throughput experimental data. I would say that validating the effects of M152T and V63V variants from Figure 2B would substantially strengthen the work and support key conclusions. * __Response: __Our experiments collectively enabled nearly 10,000 measurements of variant effect (summed over three layers of gene expression). The goal of our study was to identify broad mechanisms of variant effect. While we are excited about the specific variants uncovered, targeted experimental methods for validating changes to RNA abundance, such as RT-qPCR, are unlikely to be sufficiently sensitive. For example, RNA abundance effects in our study had a median effect size of 1.47 for variants up in RNA, and 0.4 for variants down in RNA. This likely corresponds to less than one Ct difference between the variant and the reference allele. Indeed, previous studies such as Findlay et al., 2018 Nature that reported similar effect sizes (FGF7 and FOS, respectively (Figure 4B).

Thus, for time and cost concerns, we respectfully suggest that targeted experiments involving V63V and M152T are beyond the scope of our study. Nevertheless, to further strengthen our conclusions, we have computationally confirmed our findings using a different analysis framework. We found 75/76 of the variants significant by ALDEx2 analysis were also significant by limma analysis (a frequency based normalization-dependent analysis, as previously employed in Hoskins et al. 2023. Genome Biology) using the same FDR (0.1).

• In the fluorescent reporter scheme, it seems that variants reducing mRNA abundance should be enriched in the "P2" gate region relative to "P1", as they would have lower mRNA abundance and correspondingly lower protein abundance. However, this analysis is not performed, and instead P1 and P3 are compared (Figure 3G), which would seem to focus on protein-level effects. *

__Response: __Our initial hesitation in comparing P2 to P1 is that the P2 population may be enriched for cells that underwent inefficient induction of transcription with Doxycycline. Hence technical factors as opposed to the effect of the variants may dominate this comparison. In response to the reviewer’s comments, we carried out the suggested analysis (new Supplementary Figure 5B). We found that variants that are down in RNA are enriched in P2 relative to P1 as expected. This is now noted in the Results section.

• In general the work classifies variants in several different ways and it would help to be a little clearer in naming these classes. For instance, in describing the FACS-based analysis of variant expression it is written, "protein fluorescence conditioned on RNA fluorescence" which is confusing at best-it's a fluorescence-based measurement that is used indirectly to measure COMT reporter abundance. *

__Response: __Thanks for the suggestion. We agree that our initial word-choice was imprecise. We rewrote this section to indicate mCherry fluorescence is an indirect proxy for RNA abundance.

• Likewise, the populations with shifted GFP/mCherry ratio in this assay are described as "uncorrelated" populations, which is opaque and somewhat inaccurate-there seems to be a correlation in this group but at a different ratio. *

__Response: __We have revised the language in the manuscript. We opted for “low or high RNA/protein abundance” to indicate the relationship between GFP and mCherry fluorescence in populations P3 and P4.

• In the same way, "deleterious variants" is used to describe protein abundance changes, but this term implies a fitness effect and is not very specific. *

__Response: __We apologize for the confusing word choice. We did away with this term in favor of “variants with low protein abundance”.

• In discussing the effects of missense COMT variants on protein levels, there is an implicit assumption that degradation of mis-folded protein (or perhaps properly-folded protein with excess hydrophobic exposure?) explains these effects. This is plausible, but it would help to lay out this reasoning more clearly. *

__Response: __Thanks for the suggestion. We have added a sentence at the end of the section that specifies this assumption and cites a recent study reporting that rare missense variants in COMT may be misfolded and degraded by the proteasome (Larsen et al. 2023).

• It is written that,"In line with codon stability as a predictor of translational efficiency (Presnyak et al., 2015), variants with low codon optimality were depleted from polysomes compared to variants with optimal codons". However, this mis-states the conclusions of the cited study, which notes, "Importantly, under normal conditions the ribosome occupancy of the HIS3 opt and non-opt constructs was determined to be similar (Fig. 6B)". *

__Response: __We apologize for mis-stating the conclusions of Presnyak et al. 2015. We have now revisited the relevant literature to more accurately place our conclusions in the context of literature. While Presnyak et al. and several other studies (Bazzini et al., 2016; Mauger et al., 2019) have clearly linked the association between codon choice and mRNA stability. We now reference Mauger et al. 2019 who used elegant experiments to demonstrate that mRNA secondary structure is a driver of increased protein production and synergizes with codon optimality (Figure 5B). Their results further support the role of codon optimality on RNA stability while providing evidence of additive impact on translation efficiency.

• It is written that, "One intriguing possibility is to develop multiplexed assays of variant effect on RNA folding, using mutational profiling RNA probing methods (Weng et al., 2020; Zubradt et al., 2017)." How would this differ from the "Mutate and Map" approach in doi://10.1038/nchem.1176 and subsequent work from the same group? *

__Response: __Thanks for pointing out the more recent work following the initial papers in 2010-2011. We have missed the work from the Das lab that extended the Mutate and Map approach to utilize mutational profiling (Cheng and Kladwang et al., 2017). We updated our Discussion to indicate that the proposed assay has been pioneered and is a viable approach for high-throughput determination of variant effects on RNA folding.

Because mutational profiling methods leverage reverse transcriptase readthrough and mismatch incorporation, they enable deeper and more uniform coverage of sequencing reads, particularly for longer transcripts. A key design principle of the proposed assay is to mutagenize only certain types of variants in the library such that they do not overlap RT mismatch signatures arising from the RNA probing reagent/RT enzyme. For example, readthrough of DMS base adducts largely generates A>N or C>N mismatches, so a variant library would be designed to only contain variants at G or T bases. This ensures variants in the library can be differentiated from signals of the RNA probing method.

***Referees cross-commenting** *

*I generally agree with the other reviewers and found that many small points on the figures were confusing, and in some cases the values being computed and displayed were under-specified. *

*I agree with Reviewer 1 that the polysome fractionation probably has limited power due to experimental design, and that the interpretation of changed ribosome loading is subtle. *

__Response: __In response to these helpful comments, we have clarified the points highlighted by the reviewers and expanded the limitations section related to the ribosome loading assay. Thanks for these constructive suggestions to strengthen our study.

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

*The joint, integrative analysis of COMT variants through a range of methods allows clearer insights into interconnected post-transcriptional effects. The massively parallel experiments generate high-quality data, although targeted validation of key results would strengthen the work. The findings advance our understanding of silent variant effects, which remains an open question, and technical innovations could find broader applications. *

__Response: __Thanks for pointing out the high-quality of the generated data and the broad significance of our study. The goal of our study was to identify broad mechanisms of variant effect instead of focusing on differential expression for any specific variants.

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

Learn more at Review Commons

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Reply to the reviewers

We thanks the reviewers for their critique of our report and our responses to all of their comments are given below.

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

Summary Toxoplasma gondii is an obligate intracellular parasite. Intracellular survival critical depends on secretory vesicles named dense granules. These vesicles are predicted to contain >100 different proteins that are released into PV, PV membrane and the host cell to control the parasites intracellular environment and host cell gene expression and immune response. How and where these vesicles are released from the parasite is a long-standing question in the field because T. gondii, and other apicomplexan parasites contained a complex pellicular cytoskeletal structure called the IMC which limits dense granule access to the plasma membrane. In this manuscript by Chelaghma, Ke and colleagues demonstrates for the first time that dense granules are secreted from the parasite at pore structures called the apical annuli. The authors used their previously generated HyperLOPIT data set and identified a plasma membrane protein that is specifically enriched at the apical annuli. Using BioID the authors then identify three SNARE proteins that also localize at the apical annuli. The localization of these proteins is determined using excellent super-resolution structured illumination microscopy. Conditional protein knockdowns for all four proteins were created and both proteomics and microscopy used to demonstrate a reduction in dense granule secretion in the absence of these proteins. Collectively, these data make new and substantial contributions to our understanding of mechanisms of dense granule secretion. Major comments: Overall, these data is convincing and well-described. The text is clear and well written. There are a few instances (see below) where the authors doesn't adequately describe the data or over state the strength of the results. These issues could all be addressed editorially or by process existing data.

Comment 1.1

The authors use proteomics and IFA to show that there is a reduction (rather than an inhibition of) in dense granule secretion. However, from the phase images in figure 5, the vacuoles of KD parasites look normal and so not have the phenotypes that one would expect after a significant reduction in dense granule secretion, such as the "bubble" phenotype described for GRA17 and GRA23 knockouts (Gold et al 2015; PMID: 25974303). Authors should describe their findings in the context of the expected phenotypes based on the published literature. The statement on line 369-371 is too strong and should imply a reduction rather than an inhibition of dense granule secretion.

Authors’ response: It is difficult to compare our results to individual dense granule protein mutants described in the literature because such phenotypes are the result of the loss of only a single protein being exported to the host, whereas we are observing the effects of the reduction of secretion of up to 120+ different proteins. Furthermore, we agree with this reviewer that none of the protein knockdowns appear to completely prevent dense granule secretion, which we implied by ‘inhibition’, and this could be either due to incomplete knockdown of each of these proteins with some residue function, or some redundancy where other proteins can contribute to secretion. We have changed the statement flagged by this reviewer to: ‘Depletion of all four of these proteins affects dense granule secretion*’ to avoid the interpretation of complete loss of function. We now further state that residual secretion may still occur and consider this in the light of possible reasons for this (Discussion, paragraph 4). In any case, none of these considerations change our conclusion that these proteins, at the site of the apical annuli, are implicated in dense granule secretion. *

__Comment 1.2 __

The more severe phenotype observed in the AAQa iKD and the additional localizations of AAQa and AAQc suggests an additional role for these protein in protein trafficking that is supported by the authors data. In both AAQa and AAQc there appears to be an accumulation of GRA1 in a post-Golgi compartment and is less vesicular in appearance than the phenotype observed in the AAQb iKD parasites. Additionally, I disagree with the authors assessment that KD of these proteins does not effect microneme localization. In both AAQa and AAQc there appears to be increased number of micronemes at the basal end of the parasites compared with controls. Although this is not a direct focus of the authors papers, a description of these findings should be included in the results and discussion sections.

Authors’ response: We have included a more complete discussion that considers the differences in phenotypes of the four mutants, including additional locations of two SNAREs, all of which is consistent with known SNARE biology (Discussion, fourth paragraph). These considerations, however, have no impact on our conclusions where all four proteins, including two that are exclusive to the apical annuli, have equivalent effects on dense granule exocytosis.

Concerning the effects on microneme and rhoptries of the different knockdowns, we have modified and limited our interpretation to overall IFA staining strength and protein organelle protein abundance by proteomics, where we see no differences. This addresses if there is a major post-Golgi trafficking defect that could affect biogenesis of all of micronemes, rhoptries and dense granules, for which we see no evidence. Whether there are subtle differences in the location of these organelles, which are known to show some variability, is beyond the scope or relevance to our central questions. Given that growth phenotypes are seen for all mutants, it is quite possible that secondary effects of retarded cells might present as some disorder within the cell, although we saw nothing conspicuous of this nature in many hundreds of examples observed.

__ Comment 1.3__

Presentation of the data in Figure 5. This figure contains images where the fluorescent dense granule signal is overlaid on phase images. However, in some cases (AAQb, AAQc, AAQa, GRA1 KD) the merged imaged looks like a straight merges of the two images, whereas in the rest of the images it looks like a thresholded fluorescent image is merge with phase. Authors need to process the images in consistent manner and provide a description of the image processing in the figure legend and materials and methods.

Authors’ response: Thank you for this suggestion, we have now processed all of these merges the same way (ImageJ -> merge channels -> Composite Sum). While the merges are only intended to aid in aligning the fluorescence signal with the phase image, we agree that it is better to present them the same way.

Minor comments:

Comment 1.4

The discussion is overly long and could be shorted in some places. Lines 373 and 388 in particularly don't seems directly relevant to the manuscript.

Authors’ response: The paragraph identified by this reviewer considers the LMBD protein that is the first, and currently only, trans plasma membrane protein specific to the apical annuli that implies that this structure is exposed to the exterior of the cell. It is, therefore, of considerable significance to how we interpret the function and behaviour of these annular structures. We believe that it is very relevant to our study to consider what else is known about these relatively mysterious, but widely conserved, eukaryotic proteins, which is the subject of this paragraph. The other reviewers highlight the relevance of LMBD3 to the interpretation of this structure. This reviewer hasn’t identified any further superfluous discussion elements, and we believe that the current length is not excessive and is justified.

Comment 1.5

Line 184 - Remove question mark from this sentence

Authors’ response: The question mark has been removed.

Comment 1.6

Line 321. Should read Figure 7A, not figure 6A.

Authors’ response: Thank you, corrected.

Comment 1.7

Line 139 - should read Figure 1B instead of 2C

Authors’ response: Thank you, corrected (although to 1C, which is in fact correct).

Comment 1.8

Figure 3- Column labels for early, mid, or late endodyogeny would help with the clarity of this figure, especially for readings who are unfamiliar with the field.

Authors’ response: We have labelled the figure as suggested.

Comment 1.9

Figure S2 - the letter n is missing from knockdown labels. And the number 3 from LMBD 3 is covering the word knockdown in the last panel.

Authors’ response: Thank you, corrected.

Reviewer #1 (Significance (Required)):

The manuscript provides, for the first time, insight into the mechanism of dense granule secretion in Toxoplasma and identifies the sites on parasite pellicle where these vesicles can traverse the IMC to reach the plasma membrane. This is a significant conceptual advance in our understanding of this cellular vital process, one that is required for T. gondii intracellular survival. This paper would have broad interest from other research groups studying parasitology, secretion and protein trafficking.

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

Summary: This manuscript reports on characterizing the function of the long-known apical annuli, which are pores embedded in the membrane skeleton of Toxoplasma gondii. Since their function has remained long elusive, this manuscript is a major breakthrough.

Comment 2.1

It is of note, however, that this breakthrough, using the same three SNAREs, was recently, in parallel, also reported by Fu et al in PLoS Pathogens (PMID 36972314), which work is cited here. The additional novelty here is the finding of LMDB3 in the plasma membrane at the site of the annuli. This is a widely conserved protein for which little function is known except roles in signaling, The connection between LMDB3 and the SNAREs is through BioID, but they are preys quite far down the list. Furthermore, the function of LMDB3 is not explored here. As such, the additional advance compared to the Fu et al report is limited. The function of the SNAREs in dense granule exocytosis is much more robustly done here through the proteomics data displaying an accumulation of DG proteins.

Authors’ response: While it is true that the discovery of the three SNAREs at the apical annuli was made and reported in parallel by Fu et al (2023), a major difference in their conclusions is that they suggest that dense granules are not secreted at this site (this reviewer has mistakenly thought that this was their conclusion — “In our experiments, none of the SNAREs were shown to be related to the exocytosis of GRAs. Therefore, the mechanism that mediates exocytosis of GRAs at the plasma membrane remains to be elucidated.” Fu et al (2023)*). The failure of Fu et al to detect this was almost certainly because they only tested for dense granule secretion defects by inducing depletion of the apical annuli SNAREs after the parasites had invaded the host cells. It is known that dense granule protein secretion happens rapidly in the initial moments after invasion, so apical annuli perturbation in their assay would have only occurred after these secretion events. We directly discuss this experimental difference in our revised discussion and how it accounts for their different conclusions (Discussion, fourth paragraph). We independently tested for this effect by quantitative proteomics which further supported our conclusions. *

As this reviewer indicates, we additionally discovered that a protein (LMBD3) also spans the plasma membrane at these structures, and this implicates signalling or events at the cell surface. We show that this protein is also required for normal dense granule secretion. While we have not identified an explicit mechanistic role for LMBD3 in this process, such insight is also lacking for all LMBD proteins, including those in humans where they are implicated in disease. While we continue to pursue this interesting question of LMBD3 function, we are by no means alone in cell biology for these answers to be outstanding still.

Comment 2.2

The presentation of the data is very clean and convincing, and the broader evolutionary context is well-presented as well. The discussion on whether maintaining the IMC during cell division is an innovation or ancestral is an open debate where the authors seem to come down on the side of innovation, but the evidence could go either way, so I would caution a bit more.

Authors’ response: We are puzzled by this reviewer’s comment because we do not make reference to the maintenance of the IMC during cell division in this evolutionary context — ancestral or a recent innovation. We describe the case of Toxoplasma and its close relatives maintaining the maternal IMC during division as ‘unusual’, not ancestral (second sentence of the last paragraph of the Discussion), and this is the only statement that we think might have elicited this query from the reviewer. But this does not imply what the ancestral state might have been which is not a subject of any of our considerations here.

Major comments: - Are the key conclusions convincing?

Comment 2.3

The identification of the three SNARE proteins through BioID is not very convincingly represented in Table S1. These SNAREs were not showing significant changes and were not detected universally across the three bio-reps, and thyn were also present in the controls. Although this does not diminish the message of the work, this appears to be quite Cherry-picked, while other top hits in the BioID were overlooked, e.g. Nd6 and Nd2 are right in the top ten, which have a demonstrated role in rhoptry exocytosis. This certainly piqued my interest, but is not even discussed.

*Authors’ response: We have used BioID as a protein discovery strategy, not to directly measure protein proximity for which it is an imperfect measure for many technical reasons. Accordingly, discovered ‘candidates’ for proteins that might occur at the annuli were all independently verified by protein reporter tagging. We focused our efforts on discovering apical annuli plasma membrane-tethered proteins and, therefore, parsed our BioID data for those shown previously to be in the plasma membrane by LOPIT spatial proteomics (Barylyuk et al, 2020). It is true that the SNARE proteins were not favoured over many other proteins in the BioID signal, but their verified location at these sites justified our pursuit of them as new apical annuli proteins. *

Other proteins, including the previously identified apical proteins Nd6 and Nd2 that are implicated in rhoptry secretion, similarly piqued our interest! But when we reporter-tagged them they were revealed as BioID false positives, consistent with published work on these proteins, and other ‘top hits’ included some other false positives. Table S1 is included as a further recourse for the field, but it only served as a first step in functional protein discovery in our study.

Comment 2.4

TgAAQa, TgAAQb and TgAAQc were recently also reported to localize to the annuli by Fu et al 2023 (PMID: 36972314; this report is even cited in this manuscript for Rab11a accumulation), who gave them different names: TgStx1, TgStx20, and TgStx21 (not in this order). I see no reason to adopt a new nomenclature here, which will be very confusing in the future literature. Please adopt the Stx names in this manuscript.

*Authors’ response: We agree that where there is precedent in naming it is better to use the earliest used names. Naming of proteins is also best done to reflect orthologues found between species so that consistent names indicate common functions. The naming system proposed by Fu et al for the Qa, Qb and Qc SNAREs unfortunately does not fulfil this second important criterion. They based their names on ‘Syntaxin’ which was first used for an animal SNARE of the nervous system that is almost exclusively used for Qa paralogues. Furthermore, in animals Stx1-4 are all vertebrate-specific Qa paralogues that have arisen only in this group. So, to name the Qa SNARE of Toxoplasma according to one of these animal-specific nerve proteins (Stx1) implies an evolutionary inheritance that is very unlikely (i.e., lateral gene transfer from an animal) and is unsupported by published phylogenies. Furthermore, Fu et al also give the Qb and Qc SNAREs the animal Qa name ‘syntaxin’, and arbitrarily number them Stx21 and Stx20. So, while they have named these proteins first, we think that the names given provide confusing and misleading labels for these proteins. *

We initially proposed a simpler system according to the location of the SNARE in Toxoplasma (AA = Apical Annuli) and the Q domain type (Qa, Qb, Qc), e.g., AAQa. But on reflection we propose using precedent and orthology and adopt the existing orthologue names as the most useful solution. Klinger et al (2022) have resolved the phylogeny of the three Toxoplasma SNAREs, and they group with strong phylogenetic support with known eukaryote-wide orthogroups with previous names: Qa=StxPM (Syntaxin Plasma Membrane); Qb=NPSN (Novel Plant ‘Syntaxin’); and Qc=Syp7 (a Qc SNARE family originally thought to be specific to plants). These SNARE types are all known to operate at the plasma membrane, and accordingly the names TgStxPM, TgNPSN, and TgSyp7 would indicate their orthology and similar functional location known in other eukaryotes. We have justified this preferred naming system in the text of our report (Discussion, third paragraph), but making it clear which Fu et al names correspond to these more universally consistent names so that these can be easily cross-referenced.

Comment 2.5

No knock-down of LMBD3 is pursued: how would this impact SNARE distribution and/or other annuli proteins? The fitness score is very severe, -4.07, so this is somewhat puzzling. Lower comment is related. This could provide tantalizing insights in the architecture of the annuli, and/or their function as a secretory conduit.

LMBD3 relative to the SNAREs is not explored: co-IPs or detergent extraction to see if they are all in a physically interacting complex. What keeps them together. Is LBCDR3 interfacing with any annuli proteins Cen2 is suggested through the image in Fig 2A, though there appears to be some separation in some images: AAP2, 3 and 5 were previously shown to have smaller diameters than Cen2 and therefore appear better positioned.

Authors’ response: LMBD3 knockdowns were pursued in so far as identifying that they also have a phenotype of reduced dense granule secretion as for the SNAREs, but it will indeed require further studies of this intriguing molecule to define its specific function. Our central questions of this study were what is the association of the apical annuli with respect to the IMC and plasma membrane, and what is the overall significance and function of these structures. These core questions have been answered in our study. The questions that this review raises here are further and logical questions specifically related to LMBD3 that we are now pursuing as an independent follow-on study.

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

Comment 2.6

The discussion on whether maintaining the IMC during cell division is an innovation or ancestral is an open debate where the authors seem to come down on the side of innovation, but the evidence could go either way, so I would caution a bit more.

Authors’ response: This comment (2.2) is already made and addressed above.

• 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.

Comment 2.7

The heavy focus on the LMBD3 in Fig 1 and the evolutionary discussion would warrant a more direct functional dissection. Either through an LMDB3 known-down, or its interface with the SNAREs or annuli more directly.

Authors’ response: This reviewer has not made it clear that further work on LMBD3 is necessary to support the conclusions of the paper or address the questions that we have asked, only that they would like to see more insight into LMBD3. We would also! But we do present knock-down studies and show that there are functional consequences for dense granule secretion. The question of if LMBD3 is involved in the maintenance of apical annuli structure and/or integrity is an interesting one, but a further question to those that we have presented in this first study. LMBD proteins have poorly characterised molecular functions throughout eukaryotes, and while we are also motivated to understand their role more, this has not proven a straightforward task in other systems also.

Comment 2.8

The claim that the annuli are the conduits though which the dense granules travel to get exocytosis is not directly supported by any of the experiments as it is solely based on co-localization studies, not even direct interactions.

Authors’ response: We agree that we have not directly observed dense granules in the act of secretion at the apical annuli. Dense granules are known to be very mobile in the cell and traffic dynamically on actin networks. So, they do not accumulate at any one site, and their fusion and exocytosis is likely a rapid, transient event. Multiple lines of evidence for them pausing and fusing with the plasma membrane, while indirect, independently support this conclusion:

• SNARE proteins restricted to the apical annuli in the plasma membrane are required for normal dense granule secretion
• When these SNAREs are depleted dense granule proteins accumulate in the parasite
• Rab11A is a further vesicle-tethering molecule that has been shown to be attached to dense granules and its mutation also leads to inhibition of dense granule proteins (Venugopal et al, 2020)
• When the apical annuli SNAREs are depleted Rab11A accumulates at the annuli (Fu et al, 2023) Collectively, we believe that the claim that the apical annuli are the sites of dense granule secretion is very strongly supported, particularly by the very molecules that would be required for vesicle docking and fusing at these sites, and is justified to be noted in the title. We have, however, made it clear in our report now that these data are indirect and that dense granules are yet to be captured in the act of secreting their contents at these sites (Discussion, paragraph five).

**Referees cross-commenting**

The consolidating themes I see (and value) in the reviews:

Comment 2.9

1. functional follow up of role of LMDB3 Authors’ response: This work is already part of a follow-up project.

Comment 2.10

adopt nomenclature of Fu et al, to avoid confusion in literature

Authors’ response: Please see our response to Comment 2.4

Comment 2.11

better integrate the findings in light of the Fu et al publication throughout this manuscript

*Authors’ response: We have further acknowledged and compared our findings to those of the parallel study of Fu et al with additional text in the discussion. *

Comment 2.12

no direct evidence of dense granules at annuli; attenuate the claims (in title etc), or include supportive data

Authors’ response: Please see our response to the equivalent Comment 2.8 above.

Reviewer #2 (Significance (Required)):

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

Comment 2.13

The presented manuscript reports on a novel protein, LMBD3, embedded in the plasma membrane of Toxoplasma gondii at the site of the apical annuli, which are pores across the inner membrane complex (IMC) skeleton. This provides a novel, putative connection between the cytoplasm and plasma membrane, although this is not directly explored here. Through LMDB3 proximity biotinylation, three SNAREs are identified that were recently reported to be involved in dense granule exocytosis, which is is confirmed here through robust proteomic experiments.

Authors’ response: This reviewer has made an error here in stating that the parallel study of Fu et al implicated the apical annuli SNAREs with dense granule exocytosis. See our response to Comment 2.1 where we describe why the experimental design used for Fu et al was unlikely to test this question effectively.

• Place the work in the context of the existing literature (provide references, where appropriate). The annuli were first reported in 2006, and understanding of their proteomic composition has expanded over the years, however, a function has remained long elusive. This report, together with another parallel performed work, now uses three SNAREs, named TgAAQa, TgAAQb and TgAAQc in this report but previously named TgStx1, TgStx20, and TgStx21 (not in this orthologous order), localizing to the annuli as tool to assign the function of the annuli to exocytosis of the dense granules during intracellular parasite multiplication. The evolutionary context and concepts of the new findings are very well-embedded in the existing literature and insights.

• State what audience might be interested in and influenced by the reported findings. The audience comprises people with a specific interest beyond apicomplexan biology, basically all Alveolates as they all share a similar membrane skeleton. Assigning a putative function to widely conserved LMBD3 will be of high interest to this completely different audience as well.

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

In the submitted work "Apical annuli are specialised sites of post-invasion secretion of dense granules in Toxoplasma", the authors explore the role of the apical annuli in T. gondii. They identify a number of proteins that localize to the membranes at the annuli, including SNARE proteins that are known players in vesicle fusion. They also shown that knockdown of several annuli localized proteins blocks replication and secretion of dense granule cargo into the parasitophorous vacuole. Overall, the work is well done and an important contribution to the field.

Major comments

Comment 3.1

1. In the title and throughout the manuscript the authors claim that the apical annuli are sites of dense granule secretion (e.g. "firmly implicating the apical annuli as the site of dense granule docking and membrane fusion." or "that the apical annuli are sites of vesicle fusion and exocytosis"). However, there does not appear to be direct evidence of the dense granules docking and fusing at these sites.

It would be ideal to see vesicles docked via EM at the annuli, either in wildtype or knockdown parasites. This may not be possible - if not, I recommend toning down the conclusions on docking (or "specialized sites of secretion" as this has not been shown) and instead stating that these structures play a critical role in dense granule secretion. Authors’ response: Please see our response to Comments 2.8 & 2.12, and we have toned down this conclusion as requested to make it clear that direct observations of dense granule fusion are yet to be made. Capturing the transient event of dense granule docking by EM would indeed be a very challenging ambition.

Comment 3.2

The authors should discuss earlier (in the results) the findings of Fu et al. which:

Authors’ response: The parallel study of Fu et al (2023) has indeed generated some similar data, but there are also multiple points of difference including their conclusions. We discuss all of these relevant points in the Discussion, and believe that it would make the Results narrative confusing to introduce this element of discussion there. Our study has not been performed in response to theirs, but rather was conducted in parallel.

• show the localization of some of the same SNAREs at the apical annuli. Fu et al also see localization to the plasma membrane separate from the annuli for some of these proteins. Do you see plasma membrane spots as well upon longer exposures? Can differences be explained by the position or type of tag used?

Authors’ response: Fu et al have indeed used different reporters and expressed the SNARE fusion proteins with different non-native promoters. They used a very bulky reporter which combined 12 HA tags as well as the large Auxin-Inducible Degron (AID), and together it is possible that they observe some mistargeting artefacts. For our location studies we used the small epitope 3xV5 only. We did not see the additional locations that they report, and this may be due to the larger modification that they made to these proteins.

• Fu et al also shows similar plaque defects in the knockdowns and loss of trafficking of plasma membrane proteins to the periphery. In general, the studies from this group are very complementary - they should be better acknowledged.

Authors’ response: We have included more frequent reference and comparison to the Fu et al study now in our Discussion.

• Fu et al see an invasion defect but no defect in GRA secretion - Do you see an invasion defect? These differences should be discussed

Authors’ response: See our response to Comments 2.1 & 2.13 regarding why the Fu et al could not detect the GRA secretion defect. We discuss this in our Discussion now (Discussion paragraph four). We also consider the Fu et al study of an invasion defect as flawed. Both our and their study show that depletion of apical annuli SNAREs has a strong replication phenotype of parasites within the host vacuole. Given induced SNARE depletion must occur during this growing stage of the parasites, to ask if apical annuli could be involved directly in invasion processes requires testing for invasion competence of already very sick cells. It is, therefore, not possible to control for secondary effects on invasion incompetence due to general cell malaise. Furthermore, Fu et al report on invasion efficiency using an assay that relies on SAG1 presentation on the cell surface. However, they conclude independently in their study that SAG1 delivery to the surface is inhibited in their SNARE knockdowns. This further confounds any attempt to reliable measure invasion and any role for these SNAREs in this process. Therefore, for biological as well as technical reasons, we have not tested for a possible role of annuli in invasion.

• It would be helpful for the field to use the same nomenclature whenever possible. Is it possible to use the naming described earlier?

Authors’ response: Please see our response to Comment 2.4.

Comment 3.3

Fig 1C - The authors use trypsin shaving to demonstrate plasma membrane localization of LMBD3. They are probably correct - but it is important to definitively distinguish between plasma membrane and IMC membrane localization. a. The western blot bands for GAP40 should be quantified. It appears that GAP40 is also reduced and it could be reduced to a similar extent as SAG1 without quantification. In addition, this protection from digestion could be confirmed with a second marker in the space between the PM and IMC membranes like GAP45 (whereas cytoplasmic/mito markers like profilin and Tom40 are likely further protected by the IMC membranes and are thus less relevant here).

Authors’ response: Quantitation of Western blots is notoriously inaccurate and, rather, we use it here as a qualitative indication of trypsin sensitivity of proteins in intact cells. The LMBD3 protein is completely transformed within the first time point (1 hour) to stable products of proteolysis of this polytopic membrane protein — presumably to those now protected within the cell. Known GPI-anchored surface protein SAG1 shows similar immediate sensitivity, although it is known that internalised SAG1 pools are constantly recycled to the surface and hence gradual elimination of the residual SAG1 band over 4 hours. The internal protein markers (GAP40, PRF, TOM40) show no discernible change in the first hour and little if any beyond that (within the variation common to Western blotting). GAP40 shares an equivalent polytopic membrane topology to LMBD3 except it occurs in the IMC membrane directly below the plasma membrane, so we think this is the more suitable control. Thus, this trypsin shaving experiment gives a binary output: sensitive or insensitive. This conclusion is further supported by the published spatial proteomics study (Barylyuk et al. 2020) which shows that LMBD3 segregates with other integral membrane proteins specific to the plasma membrane and not with the IMC proteins. Our super resolution imaging of LMBD3 relative to inner membrane complex markers (Centrin2, GAP45, IMC1) also show it as peripheral to them, further corroborating the plasma membrane location.

1. Is it possible to N-terminally tag LMBD3 and then examine plasma membrane localization by detection of the tag without permeabilization? (this would also confirm the proposed topology) Authors’ response: We have tried to N-terminally tag LMBD3 with an epitope reporter but this integration was not tolerated by the cell, presumable because it interferes with membrane insertion of this protein that is essential for cell viability. So, this experimental option is not available.

Comment 3.4

I think it is important to make clear for the reader what is happening here. The paper sounds as though the dense granules directly dock at the annuli for release. It also seems possible from this work and Fu et al that secretion at the annuli occurs via small vesicles that originate from the dense granules. Perhaps a diagram or model would help the reader here (and discuss why DGs or other vesicles are not routinely seen at the annuli if this is the critical portal - and perhaps why the organelles are not clustered in the apical end of the cell if this is where they are needed)

Authors’ response: This comment is related to that of review 2 (Comments 2.8/12), although we note again that Fu et al did not conclude that dense granules are exocytosed at this site. It is also unclear why this reviewer envisages that small vesicles arise from the dense granules, rather than the dense granule itself fusing at the annuli to the plasma membrane. Indeed, the occurrence of Rab11A on the dense granules, and the accumulation of this protein at the annuli with SNARE knockdown, supports that it is the dense granules that dock at this site. Why dense granules don’t otherwise cluster at their sites of secretion but are instead motile in the cell, their movement driven by Myosin F on actin filaments, is not known. Perhaps these otherwise bulky organelles would create too much cellular crowding that could interfere with other processes. We have addressed all of these points in additions to the discussion so that these interesting unknowns are transparent to the reader (Discussion paragraph 5).

Comment 3.5

Figure 5. The authors state the knockdown results in "strong phenotypes of reduced plaque development" - The plaque assays should be quantified.

• Are there no plaques or just very small ones here?

Authors’ response: The reviewer provides no rationale for this request or states what questions could be addressed by doing so. Indeed, none of our conclusions would be affected. We use the plaque assays to test whether each of the proteins tested are independently necessary for some facet of normal parasite growth where the result is binary — no difference in plaque size versus near or complete absence of plaque development. The interpretation of differing plaque sizes between different knockdown mutations is a very inexact science with assumptions of equal rates of protein depletion, sensitivity of relative protein abundance, modes of action of mutation, and kinetics of plaque growth very difficult to validate for meaningful comparisons to be made. Therefore, we don’t see any useful role for plaque quantification in the research questions that we’ve addressed or the conclusions that we present.

Comment 3.6

Figure 6 a. Fig 6A - The use of digitonin for semipermeabilization requires controls as there is typically a lot of variability across the monolayer. This is ideally done with something to show that the host plasma membrane has been permeabilized (e.g. host tubulin) and the PVM has not been permeabilized (e.g. SAG1). Otherwise, perhaps the authors could state what percent of cells showed the data like the representative images shown or describe further how selective permeabilization was assessed? (or wider fields with many cells and vacuoles?)

*Authors’ response: As requested, we have included a supplemental figure showing wider fields of view where multiple vacuoles are seen. These data show that the vacuoles are similarly stained with no evidence of variability of digitonin permeabilization. The reduction in GRA5 secretion shown by microscopy is further supported by this protein being quantified using proteomics as enriched in the parasites when the apical annuli proteins are depleted (Fig 7). *

Comment 3.7

1. Fig 6B - "the GRA signal seen within the parasite was increased compared to the control" This is not clear from the AAQb image shown as it appears more is also present in the vacuole (or perhaps residual body?) Can this be clarified? Authors’ response: Yes, in this image it appears that the ‘residual body’, which is also an integral internal compartment of the growing parasite rosette, is a site of dense granule accumulation. We have modified the text to make it clear that the observations of IFA images showing ‘apparent’ increase in dense granule staining were then directly tested by quantitative proteomics. These subsequent data (Fig 7) provided a clear measure of the increase in dense granule proteins in the parasites when apical annuli function was perturbed.

Minor comments

Comment 3.8

1. Line 215-217 The authors state that "Collectively these data imply that the apical annuli provide coordinated gaps in the IMC barrier that forms at the earliest point of IMC development and that they maintain access of the cytosol to these specialised locations in the plasma membrane."
2. However, their data shows that LMBD3 only recruits once daughters are emerging (not earliest point of IMC development). Please clarify? Is this just referring to Centrin2 or LMBD3 as well? Authors’ response: Yes, the other AAPs indicate that these structures form early, and they were mentioned as such in the sentences preceding this statement — hence ‘collectively’.

Comment 3.9

Fig 5. Regarding growth arrest. AAQa appears to show an arrest but is it possible the others just grow slower? Do they arrest later and hence fail to form a plaque? Is there incomplete knockdown which enables a few parasites to persist?

*Authors’ response: It is true that it is difficult to discern complete growth arrest from *

*very retarded growth. However, neither alternative would affect our conclusions where we use these phenotypes as an indication of apical annuli participating in process required for normal growth. All plaque assays show strong growth phenotypes. Nevertheless, we have removed the use of the term ‘growth arrest’ with respect to these phenotypes (including in the Abstract) and replaced it with growth impairment. *

Comment 3.10

Line 132, Fig 1 A-C. For clarity it may be better for the reader if LMBD3 is named earlier, or if Fig 1 refers to the gene ID for panels A-C before its named.

Authors’ response: This is a good idea and we have made this change, making note of the rationale for this name when we present the phylogeny.

Comment 3.11

Line 30 - "represent a second structure in the IMC specialised for protein secretion" this is confusing - do the authors mean in addition to the micronemes/rhoptries at the apical complex? Maybe "a second structure in the parasite" would be clearer

Authors’ response: To clarify we have reworded as follows: ‘The apical annuli, therefore, represent a second type of IMC-embedded structure to the apical complex that is specialised for protein secretion’

Comment 3.12

Line 440 - the author states that "these pre- and post-invasion secretion processes are also biochemically separated because both microneme and rhoptry secretion are SNARE-independent" Is this from the Cova and Dubios papers cited a line later? I took a quick scan of these papers and neither appear to show this? Cova claims still this is still unclear and Dubios says SNAREs are likely involved?

Authors’ response: While both microneme and rhoptry secretion use distinctive molecular machineries for controlling membrane fusion for exocytosis, it is true that it is not formally known that these processes completely lack SNARE involvement, and neither paper cited here can eliminate this possibility. We have therefore, removed this short part of the discussion where we consider that dense granules might be unique amongst these three compartments in relying on SNAREs.

Text editing

Comment 3.13

1. Line 94 - plasma membrane or cell surface. Clarify here - do you mean plasma membrane or under the membrane at the periphery? Authors’ response: We have modified as: ‘plasma membrane including the cell surface’.

Comment 3.14

Line 321 refers to Fig 6A but should say 7A. Panel 7B is never referenced in the text.

Authors’ response: Thank you, we have corrected this and only sited Fig7 because A and B are both relevant to the statement made in the text.

Comment 3.15

Line 347-242 and fig 4A - the discussion of Q-SNARES and diagram could use some references for the reader

Authors’ response: Thank you for this suggestion, we have acted on this request.

Comment 3.16

The methods says plaque assays were 7 days, fig 5 legend says 8 days

Authors’ response: Thank you, this is corrected as 8 days.

**Referees cross-commenting**

• I completely agree with Rev 2
• I also think examining invasion given Rev1 comment on the micronemes and the data from Fu et al would be worthwhile and straightforward to do

Authors’ response: Please see our response to Comment 3.2 where the validity of measuring invasion competence of poorly growing, and/or arrested, parasites is scientifically questionable. It would require controls of similarly unhealthy parasites where the apical annuli are unaffected, but it is difficult to imagine how one would deliver such a control.

Reviewer #3 (Significance (Required)):

This is an excellent study that assesses the role of apical annuli in parasite secretion. It is an important addition to the field (and outstanding imaging that provides a high level of detail to the study). The study could be improved by better integrating a recent similar study noted by the authors and in the review

Authors’ response: We have provided more direct discussion of the Fu et al paper in our Discussion section.

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 the submitted work "Apical annuli are specialised sites of post-invasion secretion of dense granules in Toxoplasma", the authors explore the role of the apical annuli in T. gondii. They identify a number of proteins that localize to the membranes at the annuli, including SNARE proteins that are known players in vesicle fusion. They also shown that knockdown of several annuli localized proteins blocks replication and secretion of dense granule cargo into the parasitophorous vacuole. Overall, the work is well done and an important contribution to the field.

Major comments

1. In the title and throughout the manuscript the authors claim that the apical annuli are sites of dense granule secretion (e.g. "firmly implicating the apical annuli as the site of dense granule docking and membrane fusion." or "that the apical annuli are sites of vesicle fusion and exocytosis"). However, there does not appear to be direct evidence of the dense granules docking and fusing at these sites.

It would be ideal to see vesicles docked via EM at the annuli, either in wildtype or knockdown parasites. This may not be possible - if not, I recommend toning down the conclusions on docking (or "specialized sites of secretion" as this has not been shown) and instead stating that these structures play a critical role in dense granule secretion.<br /> 2. The authors should discuss earlier (in the results) the findings of Fu et al. which: - show the localization of some of the same SNAREs at the apical annuli. Fu et al also see localization to the plasma membrane separate from the annuli for some of these proteins. Do you see plasma membrane spots as well upon longer exposures? Can differences be explained by the position or type of tag used? - Fu et al also shows similar plaque defects in the knockdowns and loss of trafficking of plasma membrane proteins to the periphery. In general, the studies from this group are very complementary - they should be better acknowledged. - Fu et al see an invasion defect but no defect in GRA secretion - Do you see an invasion defect? These differences should be discussed - It would be helpful for the field to use the same nomenclature whenever possible. Is it possible to use the naming described earlier? 3. Fig 1C - The authors use trypsin shaving to demonstrate plasma membrane localization of LMBD3. They are probably correct - but it is important to definitively distinguish between plasma membrane and IMC membrane localization. - a. The western blot bands for GAP40 should be quantified. It appears that GAP40 is also reduced and it could be reduced to a similar extent as SAG1 without quantification. In addition, this protection from digestion could be confirmed with a second marker in the space between the PM and IMC membranes like GAP45 (whereas cytoplasmic/mito markers like profilin and Tom40 are likely further protected by the IMC membranes and are thus less relevant here). - b. Is it possible to N-terminally tag LMBD3 and then examine plasma membrane localization by detection of the tag without permeabilization? (this would also confirm the proposed topology) 4. I think it is important to make clear for the reader what is happening here. The paper sounds as though the dense granules directly dock at the annuli for release. It also seems possible from this work and Fu et al that secretion at the annuli occurs via small vesicles that originate from the dense granules. Perhaps a diagram or model would help the reader here (and discuss why DGs or other vesicles are not routinely seen at the annuli if this is the critical portal - and perhaps why the organelles are not clustered in the apical end of the cell if this is where they are needed) 5. Figure 5. The authors state the knockdown results in "strong phenotypes of reduced plaque development" - The plaque assays should be quantified. - Are there no plaques or just very small ones here? 6. Figure 6

a. Fig 6A - The use of digitonin for semipermeabilization requires controls as there is typically a lot of variability across the monolayer. This is ideally done with something to show that the host plasma membrane has been permeabilized (e.g. host tubulin) and the PVM has not been permeabilized (e.g. SAG1). Otherwise, perhaps the authors could state what percent of cells showed the data like the representative images shown or describe further how selective permeabilization was assessed? (or wider fields with many cells and vacuoles?)

b. Fig 6B - "the GRA signal seen within the parasite was increased compared to the control" This is not clear from the AAQb image shown as it appears more is also present in the vacuole (or perhaps residual body?) Can this be clarified?

Minor comments

1. Line 215-217 The authors state that "Collectively these data imply that the apical annuli provide coordinated gaps in the IMC barrier that forms at the earliest point of IMC development and that they maintain access of the cytosol to these specialised locations in the plasma membrane."
2. However, their data shows that LMBD3 only recruits once daughters are emerging (not earliest point of IMC development). Please clarify? Is this just referring to Centrin2 or LMBD3 as well?
3. Fig 5. Regarding growth arrest. AAQa appears to show an arrest but is it possible the others just grow slower? Do they arrest later and hence fail to form a plaque? Is there incomplete knockdown which enables a few parasites to persist?
4. Line 132, Fig 1 A-C. For clarity it may be better for the reader if LMBD3 is named earlier, or if Fig 1 refers to the gene ID for panels A-C before its named.
5. Line 30 - "represent a second structure in the IMC specialised for protein secretion" this is confusing - do the authors mean in addition to the micronemes/rhoptries at the apical complex? Maybe "a second structure in the parasite" would be clearer
6. Line 440 - the author states that "these pre- and post-invasion secretion processes are also biochemically separated because both microneme and rhoptry secretion are SNARE-independent" Is this from the Cova and Dubios papers cited a line later? I took a quick scan of these papers and neither appear to show this? Cova claims still this is still unclear and Dubios says SNAREs are likely involved?

Text editing

1. Line 94 - plasma membrane or cell surface. Clarify here - do you mean plasma membrane or under the membrane at the periphery?
2. Line 321 refers to Fig 6A but should say 7A. Panel 7B is never referenced in the text.
3. Line 347-242 and fig 4A - the discussion of Q-SNARES and diagram could use some references for the reader
4. The methods says plaque assays were 7 days, fig 5 legend says 8 days

Referees cross-commenting

• I completely agree with Rev 2
• I also think examining invasion given Rev1 comment on the micronemes and the data from Fu et al would be worthwhile and straightforward to do

Significance

This is an excellent study that assesses the role of apical annuli in parasite secretion. It is an important addition to the field (and outstanding imaging that provides a high level of detail to the study). The study could be improved by better integrating a recent similar study noted by the authors and in the review

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

Learn more at Review Commons

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Reply to the reviewers

We have thoroughly revised the manuscript, taking into account all comments from all four reviewers. We have added new data (Supplemental Figure 2 and Supplemental Figure 4) in response to these comments.

Reviewer 1

The assessment of data reproducibility is currently uncertain due to the absence of replication and statistical analysis in the dataset. It is essential to provide explicit information regarding sample sizes or replicates for all data and figures, data should be presented as mean +/- SD/SEM, and the interpretation of results should be grounded in rigorous statistical analysis. The lack of experimental replicates and statistical analysis in most of the figures presented raises major concerns regarding the validity of the result.

We have now added error bars for the graphs in Figure 3D, E, F, G, H; Figure 4 D, F, G, H, I, J; Figure 5 B, C, D, E, F, G; and Figure 6B, C, D. All GTPase assays have repeated three times. The mean ± S.D. (n = 3) is plotted for each condition. For high-speed pelleting assays, all assays have been conducted three times, and a representative assay is shown.

Why was only one of the MiD proteins, specifically MiD49, studied, while MiD51 was not includedin the investigation?

This is an excellent point. In our previous work (doi:10.1101/2023.07.31.551267), we found that MiD49 and MiD51 were strikingly similar in their abilities to activate Drp1 after their own activation with fatty acyl-CoA. We feel that the demonstration here with MiD49 suggests that a similar effect would occur with MiD51. Due to time constraints for the lead author, preparing more MiD51 protein was out of the scope of what could be done. We now add a line in the Discussion that results for MiD51 may be different.

The author suggestion of Drp1 phosphorylation, based on the mobility of protein observed in SDS-PAGE gel (fig 4A, 5A, 6A), is not a sufficiently valid assessment. While western blot analysis is a valid method to assess Drp1 phosphorylation, it is essential to include replicates for semi-quantitation and demonstrate the reproducibility of the results. Moreover, it is recommended to incorporate Western blot analyses to provide additional support for the findings presented in Figures 5 and 6.

• We agree with the reviewer that additional information on the phosphorylation state of these proteins should be provided. We now include phospho-proteomic analysis for Erk2 phosphorylation of WT Drp1 and Drp1-S600D (Supplemental Table 1), showing that S579 is by far the predominant phosphorylation site. For WT Drp1, three lines of evidence now suggest efficient Erk2 phosphorylation of S579:
• Western blot using anti-phosphoS579
• Phosphoproteomic analysis
• Gel shift

For the Drp1-S600D phosphorylation, we have phosphoproteomic and gel shift analysis. For isoform 6, we regrettably only have gel shift. However, given the fact that the effect of Erk2 treatment on actin-stimulated GTPase activity mimics what we found for WT-Drp1 and for Drp1-phosphoS579/S600D, we think it is highly likely that the equivalent phosphorylation (S629 in this case) has been affected.

Data on phosphorylated peptides with replicates experiments should be presented.

We now present these data, which have been significantly expanded since the initial submission (new Supplemental Table 1). While non-phophorylated S579 is still detected in both the WT and S600D phosphorylation reactions, the phosphorylated peptide is 2.2 and 2.3-fold more abundant, respectively. Our conclusion is that Erk2 efficiently phosphorylates S579, although stoichiometric phosphorylation was not obtained here. We have added statements in the relevant sections of the Result, and in the Methods. We have also added Supplemental Table 1 to show the spectral counts obtained from phospho-proteomic analysis, and have deposited the raw data files with the PRIDE consortium (access information in the Methods).

Please provide additional context or specific details about the GFP-tagged Drp1 protein, such as the protein site where GFP was attached, as well as whether this tag could potentially impact the Drp1 GTPase activity and oligomerization. Figure 7C and D appear to suggest an increase in the GTPase activity of the GFP-Drp1 protein.

We have now added these details to the Methods section, and have also added the complete amino acid sequence for the final purified construct in Supplemental Figure 4. We have also added that a previous study (PMID: 32901052) found that inclusion of GFP strongly inhibited Drp1 GTPase activity. We do not observe this effect here or in a previous study (PMID: 27559132), and provide possible reasons for this difference in the Methods. The reviewer points out that the activity of GFP-Drp1 appears higher than that of un-tagged Drp1 (comparing 7C with 7D). We find that the GTPase activity of Drp1 alone varies between 1 and 2 uM/min/uM protein depending on the preparation. This variation occurs for both untagged and GFP-tagged Drp1. This difference in basal activity from prep-to-prep might relate to differences between protein preparations, or exact amount of time required to freeze the aliquots of purified protein (we freeze small aliquots ( An optional experiment that would significantly enhance the biological relevance of the findings presented in the current study is to assess the morphology of mitochondria in cells expressing the phospho-mimetic mutant Drp1 proteins. This experiment would provide valuable insights into the functional consequences of Drp1 S579 and S600 phosphorylation on mitochondrial structure and dynamics.

We fully agree that these would be valuable experiments. The issue is that a large number of experiments using phospho-mimetic mutants in cells have already been conducted, with varying results (Taguchi et al., 2007; Qi et al., 2011; Yu et al., 2011; Strack et al., 2013; Kashatus et al., 2015; Serasinghe et al., 2015; Xu et al., 2016; Brand et al., 2018; Han et al., 2020, Chang and Blackstone, 2007; Cribbs and Strack, 2007; Cereghetti et al., 2008; Wikstrom et al., 2013, Han et al., 2008，Wang et al., 2012 Jhun BS, Sheu, 2018, J Physiol). To conduct more targeted tests examining specific forms of Drp1 activation in cells (for example, through Mff, MiD proteins, actin, or cardiolipin) will require extensive work that is outside the scope here. Our feeling is that S579 phosphorylation is likely to recruit another molecule (probably a protein) that has an activating effect. We tried to test one possibility (NME3, mentioned in the Discussion) but failed to produce useable NME3 protein for these tests and, given time constraints for the lead author, could not address this further.

Provide reference for method on actin polymerization.

We have now added a reference in the ‘Actin preparation for biochemical assays’ section of the Methods (PMID 16472659).

Rectify the error in referencing figure 3 panels within the figure legends of Supplemental Fig S1.

Thank you, we have changed this.

The inclusion of full length isoform 6 is commendable. However, there is no mentioned of isoform6 in the method section.

Thank you for pointing this out. We have added description of the construct and referenced our previous paper that used it.

Since papers deposited in bioRxiv have not undergone peer review, reference #7 should not becited as references in scholarly work.

Reference 7 has so far been reviewed by a peer-review journal. e are addressing reviewers’ concerns and will re-submit soon. We do not know how to rectify the issue of referencing this work, because it describes an extensive amount of groundwork for the MiD proteins. Our hope is that this work will be in press by the time the work reviewed here is ready for publication.

Please provide details about the calculation of GTPase activity and the distinctions between the specific GTPase activity and total GTPase activity shown in figure 8D-F.

We now describe these calculations in the “GTPase assay” section of the Methods.

Reviewer 2

Overall, the experiments described here are carried out with rigor and the conclusions drawn are of significance to understanding how phosphorylation regulates Drp1 functions.

Thank you for these kind comments!

Phosphorylation of both the serine residues appears to elicit a common effect in that they inhibitDrp1's stimulated GTPase activity. This would suggest that phosphorylation affects Drp1's self-assembly as tightly packed helical scaffolds. Instead of sedimentation analysis, an EM analysis of helical scaffolds on cardiolipin-containing membrane nanotubes or in the presence of soluble adaptors causing Drp1 to form filaments would provide a direct readout for defects in self-assembly.

This is an excellent point, and we would love to conduct this work. Given our current EM infrastructure and expertise, these experiments would take extensive time for us to do. We do have a collaborator who could carry these out, but feel that the time it would take even for them to do this correctly is beyond that which we have (the lead author is transitioning to their next career phase). We have added the point that further EM studies of this type are necessary to test the effect on Drp1 assembly more directly.

I am not sure of the rationale for experiments reported in Fig. 7 and 8. If the idea was to test if hetero oligomerization with WT Drp1 rescues defects associated with phosphorylated Drp1 then this could be stated explicitly in the manuscript. GFP-Drp1 is used as a WT mimic but a previous report (PMID: 30531964) indicates that this construct is severely defective in stimulated GTPase assays, much like the K38A mutant. But the rationale of using these constructs is not quite apparent. Is the intention to test if defects seen in the phospho-mimetic mutants of Drp1 can be rescued by the presence of a 'seed' of WT Drp1. If so, then this could be stated explicitly in the manuscript. But regardless, I am not quite sure what this data set achieves in terms of addressing mechanism.

We apologize for not being clearer in our explanation of these experiments. Our goal was to test the effects of partial Drp1 phosphorylation on overall Drp1 activity, which likely mimics more accurately the cellular situation (wherein only a portion of the Drp1 population is likely to be phosphorylated even upon kinase activation). We now discuss these experiments in a clearer manner. For the GFP-Drp1, we do not observe the effect on GTPase activity shown in that previous manuscript by another laboratory, either here or in previous studies (eg, PMID: 27559132). In the Methods, we now provide a discussion of these differences and possible reasons for them, as well as providing the complete amino acid sequence of our GFP-fusion construct in Supplemental Figure 4.

Finally, it would have been nice to see if the phospho-mimetic mutants of Drp1 produce the same effects on mitochondrial structure as those reported earlier. Reanalyzing their effects in a cellular assay becomes important because it would consolidate this work for the readers to evaluate the'true' effects of phosphorylation on Drp1 functions. If the phospho-mimetic mutants fare in a manner like those previously reported, then it signifies that stimulation in GTPase activity is not a readout that directly correlates with Drp1 functions. If not, then the results presented here would establish a comprehensive analysis of in vitro biochemical activities and in vivo functions of the phospho-mimetic mutants.

We fully agree that these would be valuable experiments. The issue is that a large number of experiments using phospho-mimetic mutants in cells have already been conducted, with varying results (Taguchi et al., 2007; Qi et al., 2011; Yu et al., 2011; Strack et al., 2013; Kashatus et al., 2015; Serasinghe et al., 2015; Xu et al., 2016; Brand et al., 2018; Han et al., 2020, Chang and Blackstone, 2007; Cribbs and Strack, 2007; Cereghetti et al., 2008; Wikstrom et al., 2013, Han et al., 2008，Wang et al., 2012 Jhun BS, Sheu, 2018, J Physiol). To conduct more targeted tests examining specific forms of Drp1 activation in cells (for example, through Mff, MiD proteins, actin, or cardiolipin) will require extensive work that is outside the scope here. Our feeling is that S579 phosphorylation is likely to recruit another molecule (probably a protein) that has an activating effect. We tried to test one possibility (NME3, mentioned in the Discussion) but failed to produce useable NME3 protein for these tests and, given time constraints for the lead author, could not address this further.

Previous work reports that the effect of actin on the GTPase activity of Drp1 is biphasic but the binding to actin is not. This is quite confounding, and the authors could perhaps explain why this is the case.

The reviewer makes an excellent point, which we now explain further in the manuscript. We have also discussed this in doi:10.1101/2023.07.31.551267 (see Figure 2D in that work). Our interpretation is that it is the density of Drp1 bound to the actin that provides the activation, by positioning the GTPase domains in close proximity. As the amount of actin increases, the Drp1 becomes more dispersed on the filaments, and activation decreases. We observe the same effect for MiD49 and MiD51 oligomers (see the above-mentioned reference).

The manuscript cites PMID: 23798729 for expression analysis of slice variants but PMID:29853636 provides a more compressive analysis. The authors could cite this work.

Thank you for this reference. We were unaware of it, but are very glad to know of it now. We now include this reference. In particular, in the legend to Figure 1C (table of splice variants), we now state that this table is for human Drp1, and that additional splice variants have been identified for murine Drp1 (PMID 29853636).

Reviewer 3

The splendid results of the manuscript willbe interesting to the researchers in the related fields.

Thank you for this nice comment!

The manuscript provided well-organized biochemistry results for comparisons between phosphorylation of Drp1 S579 and S600. It is the reviewer's comments that the authors may include experiments that manipulate Drp1 phosphorylation at different amino acids in cells. Such experiments will provide strong support for this manuscript.

• We fully agree that these would be valuable experiments. The issue is that a large number of experiments using phospho-mimetic mutants in cells have already been conducted (Taguchi et al., 2007; Qi et al., 2011; Yu et al., 2011; Strack et al., 2013; Kashatus et al., 2015; Serasinghe et al., 2015; Xu et al., 2016; Brand et al., 2018; Han et al., 2020, Chang and Blackstone, 2007; Cribbs and Strack, 2007; Cereghetti et al., 2008; Wikstrom et al., 2013, Han et al., 2008，Wang et al., 2012 Jhun BS, Sheu, 2018, J Physiol). To conduct more targeted tests examining specific forms of Drp1 activation in cells (for example, through Mff, MiD proteins, actin, or cardiolipin) will require extensive work that is outside the scope here. Our feeling is that S579 phosphorylation is likely to recruit another molecule (probably a protein) that has an activating effect. We tried to test one possibility (NME3, mentioned in the Discussion) but failed to produce useable NME3 protein for these tests and, given time constraints for the lead author, could not address this further.

  The authors discussed the known factors that involved in Drp1 activation, such as its receptors, actin and cardiolipin. Recent JCB paper (J. Cell Biol. 2023 Vol. 222 No. 10 e202303147) indicates that intermembrane space protein Mdi1/Atg44 may play a role in coordinating mitochondria fission with Dnm1 (Drp1 in yeast cells). It will be valuable if the manuscript could also discuss the potential factor.

• Thank you for this comment. We now include Mdi1/Atg44 as a possible factor that might be influenced by Drp1 phosphorylation. Two points we would like to make here are: there doesn’t seem to be an Mdi1 homologue in mammals, so the equivalent factor must be identified before testing; and Mdi1 is an inter-membrane space protein, so any effect of Drp1 phosphorylation on coordinated functioning with Mdi1 would either require an intermediary factor or exposure of the IMS in some way.

  Keywords cannot represent the manuscript. It is recommended that the authors use other words to for the current manuscript.

We have removed K38A from this list. The other key words are not mentioned in the Abstract.

Reviewer 4

The authors showed that the binding of Drp1 to actin depends on salt concentrations (Fig. 2Band C). In the presence of 65 mM NaCl, the phosphomimetic mutants showed decreased binding to actin. The GTPase assay is performed with 65 mM KCl, in which actin did not stimulate GTP hydrolysis of the phosphomimetic mutants. In contrast, with 140 mM NaCl, the S579D Drp1 exhibits slightly enhanced actin binding compared to WT Drp1. Could the authors assess the actin-activated GTPase activity in the 140 mM salt condition to test if actin activates GTP hydrolysis ofS579D Drp1 more potently than WT?

This is a good point by the reviewer. However, with limited time for the first author, we chose to focus on the reviewer’s other comments (see below).

Both phosphomimetic mutants show reduced activation for GTP hydrolysis in the presence of cardiolipin, Mff, and MiD49. Is this because the mutants have a lower affinity for these interactors? Or do they bind with the same affinity but experience diminished activation? The data suggests the latter scenario, potentially resulting from decreased oligomerization properties. Can the authors provide more insights on this, for example, by measuring their interaction in the presence of GMP- PCP, which fully induces oligomerization in all three forms of Drp1?

• These are interesting ideas, and we conducted experiments similar to what the reviewer described: co-sedimentation experiments with combinations of Drp1 and Mff under three nucleotide states: no nucleotide, GMP-PCP, and GTP. We used Mff for these experiments because we have this protein in abundance, and have previously characterized this construct as a trimer in PMID 34347505. We use a high concentration of Mff (50 mM) versus Drp1 (1.3 mM) because of the relatively low affinity between the two proteins (shown in PMID 34347505). We find the following:
• In the absence of nucleotide, Mff does not cause an increase in pelletable Drp1 for any of the Drp1 constructs.
• In the GTP state, the presence of Mff greatly increases the amount of Drp1 in the pellet, suggestive of increased Drp1 oligomerization. This effect occurs for all Drp1 constructs (WT, S579D and S600D mutants), but the amounts of both Drp1 and Mff in the pellets are about 50% less for both mutants than for the WT construct. This result suggests a decrease in oligomerization for the mutants, but not necessarily a decrease in Mff binding.

I'm curious what happens to oligomerization if GTP is added instead of nonhydrolyzable GMP-PCP (Fig. 1D). Does this lead to higher oligomerization in the mutants compared to WT since the mutants seem to have lower GTPase activity? This might explain why phosphorylation increases mitochondrial localization of Drp1 in cells seen in some studies.

This is another interesting thought, and we describe the new experiments we conducted in the response to the previous comment. Essentially, while GTP does cause a slight increase in pelletable Drp1, the increase is somewhat similar for all constructs. As described in the last comment, the addition of Mff causes a substantial increase in pelletable Drp1 for both WT and the mutants. This result suggests that, while the basal oligomeric state of Drp1 (in the absence of nucleotide) is reduced for the mutants (our original analytical ultracentrifugation data), the mutants appear to be capable of responding to GTP and Mff in a similar manner to WT. We acknowledge that the assay used here (pelleting) lacks the precision required to draw detailed conclusions on oligomerization or interaction with Mff, and we try to reflect this in our discussion of the data. We do feel, however, that these data are useful to report, in guiding future study.

Please include the number of experimental repeats and error bars where applicable.

We have now added number of experimental repeats and error bars for the graphs in Figure 3D, E, F, G, H; Figure 4 D, F, G, H, I, J; Figure 5 B, C, D, E, F, G; and Figure 6B, C, D.

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Referee #1

Evidence, reproducibility and clarity

Summary

The present study aims to delineate the effect of S579 and S600 phosphorylation on Drp1 oligomerisation and GTPase activity. Using phospho-mimetic mutant Drp1 proteins, in conjunction with GTPase activity and phosphorylation assays, as well as size exclusion chromatography, the authors conclude that phosphorylation of residue S579 does not activate Drp1 directly. Notably, the authors did not perform cell-based assays to assess mitochondrial fission. The abstract concludes by stating, "our results suggest that nearest neighbour interactions within the Drp1 oligomer affect catalytic activity". However, this assertion appears to lack clarity and direct support from the presented results. Further clarification or evidence linking the observed data to this conclusion would enhance the overall comprehensibility and validity of the study's findings.

Major comments

• The assessment of data reproducibility is currently uncertain due to the absence of replication and statistical analysis in the dataset. It is essential to provide explicit information regarding sample sizes or replicates for all data and figures, data should be presented as mean +/- SD/SEM, and the interpretation of results should be grounded in rigorous statistical analysis. The lack of experimental replicates and statistical analysis in most of the figures presented raises major concerns regarding the validity of the result.
• Why was only one of the MiD proteins, specifically MiD49, studied, while MiD51 was not included in the investigation?
• The author suggestion of Drp1 phosphorylation, based on the mobility of protein observed in SDS-PAGE gel (fig 4A, 5A, 6A), is not a sufficiently valid assessment. While western blot analysis is a valid method to assess Drp1 phosphorylation, it is essential to include replicates for semi-quantitation and demonstrate the reproducibility of the results. Moreover, it is recommended to incorporate Western blot analyses to provide additional support for the findings presented in Figures 5 and 6.
• Data on phosphorylated peptides with replicates experiments should be presented.
• Please provide additional context or specific details about the GFP-tagged Drp1 protein, such as the protein site where GFP was attached, as well as whether this tag could potentially impact the Drp1 GTPase activity and oligomerisation. Figure 7C and D appear to suggest an increase in the GTPase activity of the GFP-Drp1 protein.
• An optional experiment that would significantly enhance the biological relevance of the findings presented in the current study is to assess the morphology of mitochondria in cells expressing the phospho-mimetic mutant Drp1 proteins. This experiment would provide valuable insights into the functional consequences of Drp1 S579 and S600 phosphorylation on mitochondrial structure and dynamics.

Minor comments

• Provide reference for method on actin polymerisation.
• Rectify the error in referencing figure 3 panels within the figure legends of Supplemental Fig S1.
• The inclusion of full length isoform 6 is commendable. However, there is no mentioned of isoform 6 in the method section.
• Since papers deposited in bioRxiv have not undergone peer review, reference #7 should not be cited as references in scholarly work.
• Please provide details about the calculation of GTPase activity and the distinctions between the specific GTPase activity and total GTPase activity shown in figure 8D-F.

Significance

The current investigation holds promise for advancing our understanding of the impact of post-translational modifications, specifically those occurring at the S579 and S600 sites, on Drp1 activity. Nevertheless, the absence of experimental replication and comprehensive statistical analysis introduces notable concerns regarding the credibility and replicability of the findings.

Audience: Basic research that focus on mitochondrial morphology and Drp1 biology.

I lack expertise in velocity analytical ultracentrifugation and, as a result, am unable to provide an assessment regarding the validity and accuracy of the assay.

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Reply to the reviewers

1. General Statements

We thank the reviewers for their time and both thoughtful and constructive comments. Their specific points are addressed below but a general point that we would like to comment on is that in the original version it appears we did not make our model clear enough. The dogma in the field is that Rab7 is recruited to endosomes from a cytosolic pool via exchange with Rab5 (mediated by Mon1/Ccz1). Our work instead indicates that the majority of Rab7 is delivered to Dictyostelium phagosomes by fusion with other endocytic compartments. It was not our intention to imply there was no canonical recruitment of Rab7 from a cytosolic pool, and indeed we provide data to show this happens at a low level and discuss this in the manuscript. Nonetheless, we clearly over-stated the exclusivity of Rab7 recruitment to phagosomes via fusion at several points and our original model cartoon, and have tried to better explain or more nuanced model with multiple routes for Rab7 acquisition in this revision, including a completely redrawn model figure (Fig. 7).

2. Description of the planned revisions

Reviewer 1:

1. The observation that macropinosomes undergo retrograde fusion with newly formed phagosomes to facilitate phagosome maturation is an interesting notion that challenges the traditional model. However, not all phagocytes exhibit a high level of macropinocytosis, and axenic Dictyostelium cells used in the study may be an exception. Thus, it remains unclear whether fusion with macropinosomes is universally required for phagosome maturation. WT Dictyostelium cells or axenic cells cultured under SorMC/Ka condition (Paschke et al., PLoS One, 2018) exhibit significantly reduced macropinocytosis. The authors could examine whether the accumulation of Rab7 and V-ATPase on large-sized phagosomes is delayed in these cells. These experiments may help broaden the applicability of the authors’ finding.

As our previous work (Buckley et al. PloS pathogens 2019) demonstrated that bacterially-grown PIKfyve mutants are also defective in bacterial killing and growth it is highly likely that cells also are defective in V-ATPase and Rab7 acquisition. However, we agree that formally testing this will further support our conclusions and improve the paper and should be quite straightforward.

We will therefore co-express GFP-V-ATPase and RFP-Rab7 in both Ax2 and non-axenic cells grown on bacteria and repeat our analysis of recruitment to phagosomes – with the caveat that non-axenic cells do not phagocytose large particles such as yeast (Bloomfield et al. eLife 2015), so the imaging and quantification will be more challenging in this case.

PIKfyve seems to play a specific role in the maturation of phagosomes but not macropinosomes. The differences may be driven by signaling from phagocytic receptors, as the author suggested. Alternatively, the large size of the yeast-containing phagosomes may require additional steps for efficient lysosomal delivery. The authors should consider examining whether PIKfyve is needed for the delivery of Rab7 and V-ATPase to phagosomes of comparable size to regular macropinosomes, such as those containing K. aerogenes or small beads. In addition, whether the process also involves fusion between phagosomes and macropinosomes should be verified.

Whilst it is possible that large size of yeast-containing phagosomes requires additional mechanisms to process them, our previous data demonstrate that PIKfyve is also required to kill much smaller bacteria such as Klebsiella and Legionella (Buckley et al. PloS pathogens 2019). Furthermore, in this paper we also showed that loss of PIKfyve disrupts phagosomal proteolysis using 3um beads, and showed that V-ATPase recruitment was reduced on purified phagosomes containing 1um beads. We therefore find consistent defects on phagosomes of different size, with different cargos. Nonetheless, the experiments above, observing V-ATPase and Rab7 in cells grown on bacteria should directly address this point.

As suggested, we will also perform a dextran pulse-chase prior to addition of bacteria to test if we can observe macropinocytic delivery to bacteria-containing phagosomes - perhaps using E. coli as their elongated shape may help phagosome visualisation.

In the previous study from the authors' group (Buckley et al., PLoS Pathog, 2019), it was shown that the accumulation of V-ATPase on phagosomes begins immediately after internalization in both PIKfyve mutant and WT, although V-ATPase accumulation reaches only half of the levels seen in WT. This partial accumulation of V-ATPase differs from the almost complete absence of Rab7 recruitment found in this study, which raises the question of whether there exists yet another population of fusogenic vesicles that are positive for V-ATPase but negative for Rab7. This could be checked by simultaneously examining the dynamics of V-ATPase and Rab7 during yeast phagocytosis in the PIKfyve mutant.

We agree with the referee that there are multiple pools of V-ATPase, and we show that there is both a very early PIKfyve-independent recruitment of both V-ATPase and Rab7 as well as a later and more substantial pool delivered in a PIKfyve-dependent manner. It is clear that V-ATPase and Rab7 do not always co-localise however - the clearest example being on the contractile vacuole, which has lots of V-ATPase but no Rab7 (the large bright magenta structure in Fig 2G.).

We suspect that the dramatically reduced, but not completely absent levels of both V-ATPase and Rab7 recruitment in the absence of PIKfyve are similar, but the challenges with imaging these very small low levels means we cannot formally exclude that there is a pool of V-ATPase vesicles that lack Rab7 which fuse to very early phagosomes. Nonetheless, as we will already be looking at V-ATPase and Rab7 in PIKfyve KO's in the experiments above will also attempt to unequivocally differentiate a pool of V-ATPase positive/Rab7 negative vesicles fusing with phagosomes.

Reviewer 2:

(1) The authors show that deletion of PIKfyve results "in an almost complete block in Rab7 delivery to phagosomes" (page 17) indicating that the delivery of Rab7 depends on fusion with Rab7-positive structures. This would suggest that the Rab7-GEF Mon1-Ccz1 is not localized to the membrane of the phagosomes. Could the authors test for the presence of Mon1-Ccz1 in either fluorescence microscopy experiments or on purified phagosomes to exclude the possibility of a "canonical" Rab7 recruitment by its GEF? If the GEF is found on phagosomal membranes it would indicate that a Rab-transition from Rab5 to Rab7 occurs on the phagosome during maturation, but on a low level. The later fusion event might be a homotypic fusion of two Rab7-positive compartments. The observed fusion events could still deliver the bulk of Rab7 and other endolysosomal proteins to the phagosome. If the Rab7-GEF is not found on phagosomes how do the authors envision that the organelle keeps its identity? Is it solely dependent on PI(3,5)P2? What is the fate of the Rab7-negative phagosome in ∆PIKfyve cells if Rab7 is not delivered to the membrane, is there degradation happening over longer periods of time?

This is an excellent suggestion, for which we thank the reviewer. Mon1 and Ccz1 are highly conserved, with clear Dictyostelium orthologues that have never been studied. Our model is that there is a small proportion of Rab7 driven by this canonical pathway so would expect Ccz1/Mon1 to coincide with loss of Rab5 and be unaffected by loss of PIKfyve - although subsequent Rab7 delivery would be lost. This is easy to test by cloning and expressing GFP-fusions of both Ccz1 and Mon1 and would be highly informative. Note we do not exclude canonical Rab7 recruitment in our model (see discussion), our data just indicate this has a minor contribution.

Reviewer 3:

The focus is on their manuscript is loading of Rab7 on phagosomes, but there's no indication about Rab7 activation (GTP-loading). Would the RILP-C33 probe work in Dictyostelium? If not possible, the activation state of Rab7 should still be discussed. Despite Rab7 on other organelles in PIKfyve-inhibited cells, is this active or not?

The GTP-loading status of Rab7 is a good question, although the general dogma is that membrane-localised Rabs are active. We will try the RILP-C33 probe in Dictystelium as suggested, but as these cells lack an endogenous RILP orthologue there is a high chance it will not work. Sadly, reliable tools to asses active Rab status are a general limitation for the field, so if the RILP-C33 probe does not work we will add this caveat to the discussion.

The authors need to better address the confusing kinetics of early Rab7 recruitment, followed by SnxA (Fig. 4G, same for VatM - Fig. 4I ) - which is counterintuitive if PIKfyve activity is required to recruit Rab7. How do the authors explain this? Are phagosomes prevented from acquiring Rab7 in PIKfyve deficient cells because of a defect on phagosomes or the endo-lysosomes loaded with Rab7 (but not active).

We believe this again relates to the over-simplification of our model. Our data indicate both PIKfyve dependent and independent Rab7 recruitment. In contrast to the abrupt recruitment of SnxA at ~120 seconds (Vines et al. JCB 2023), both Rab7 and VatM accumulate gradually over time starting from almost immediately following engulfment (Buckley et al. 2019, and Figure 2F). Our data indicate that the first stage of this is PIKfyve independent, and is responsible for ~10% of the total Rab7/V-ATPase accumulation by both the imaging in this paper, and Western blot for V-ATPase on purified phagosomes in Buckley et al. PLoS pathogens 2019. The arrival of some Rab7/V-ATPase prior to PI(3,5)P2 therefore supports our model where there are multiple sources of Rab7.

As the reviewer quite rightly points out, interpretation of the defects observed in the absence of PIKfyve becomes complex and we cannot completely differentiate between a defect on the phagosome, or the Rab7 compartments that fuse with them (or indeed both). In fact, we already note that small Rab7 compartments that we observe in wild-type cells are much more sparse in PIKfyve mutants. Therefore whilst the requirement for PI(3,5)P2 in the clustering and fusion of macropinosomes with phagosomes is clear, additional effects on the PI(3,5)P2-independent Rab7 compartments cannot be excluded.

The experiments above using the RILP-C33 active Rab7 biosensor as well as observation of the Mon1/Ccz complex should further clarify this, but we will also add further discussion of these points.

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

Reviewer 1:

Minor comments.

1. It is unclear how the experiment in Figure 3G was conducted. If microscopic analysis was involved, the corresponding images should be included.

We apologise that we overlooked this and have now added a full description in the materials and methods (P8 L16-21). Fluorescence measurements were performed using a plate reader, so there are no images.

Page 11-Line 2, the sentence "there was no obvious clustering around the nascent phagosome (Figure 2D)." It is Figure 2E, not Figure 2D.

Corrected.

There is an inconsistency regarding the description of fluorescent fusion proteins. For example, both GFP (RFP)-2xFyve and 2xFyve-GFP (RFP), as well as GFP-Rab5 and Rab5-GFP, were used. Typically, placing GFP (or RFP) before a gene suggests N-terminal tagging, while placing it after the gene implies C-terminal tagging. The authors should clarify the position of the fluorescent tag and ensure consistency in their descriptions.

We apologise for this oversight, and have been through and corrected all fusion protein references accordingly.

One of the videos was not referred in the manuscript or described in the Video legends. This video seems to correspond to Figure 5A, albeit with a different pseudo-color scheme.

This has been corrected. Video 7 does correspond to Fig 5A, and we have corrected the colour scheme to match and added references to the video in the text and figure legend.

Reviewer 2:

(2) In their abstract, the authors state that they "...delineate multiple subpopulations of Rab7-positive endosomes that fuse sequentially with phagosomes" (page 2, line 14,15). However, the data provides only evidence for V-ATPase or PI(3,5) P2-containing structures and the authors conclude to my understanding that macropinosomes are the main source for vesicular structures fusing with phagosomes. I would ask the authors to please be clear on the identity of the "Rab7-donor"-structures throughout the manuscript. Saying that they delineate multiple subpopulations of endosomes seems to be overstated.

We identify that macropinosomes are one source (subpopulation) of Rab7/PI(3,5)P2 vesicles but our data clearly show that they are the only source of Rab7 - there is clearly an additional early Rab positive / PI(3,5)P2-negative subpopulation of vesicles that cluster and fuse too at earlier stages. For example, in Figure 4F we co-express Rab7a/SnxA and show that whilst all the SnxA vesicles also contain Rab7 (and dextran), there is a clear separate population of small and early-fusing population of Rab7-containing vesicles that do not possess PI(3,5)P2. This is further validated in Figure 5B and C. To our mind this clearly demonstrates and defines different Rab7 endosomal populations, although we do not yet know the origins of the initial Rab7-positive/PI(3,5)P2 negative population - as discussed in our response to their point (3) below.

Minor points:

(1) The sentence "...which both deactivates and dissociates Rab5, and recruits and activates Rab7 on endosomes" is at least problematic as it suggests that Mon1-Ccz1 directly drives GTP-hydrolysis of Rab5 and dissociates it from the membrane. Indeed, Mon1-Ccz1 is shown to interfere with the positive feedback loop of the Rab5-GEF by interacting with Rabex (Poteryaev et al., 2010), so a rather indirect effect of Mon1-Ccz1. A GAP and the GDI are needed for Rab5 deactivation and dissociation from the membrane. How both are involved in the endosomal Rab-conversion is not clarified.

We have changed the text to better represent this complexity (P4 L4-6)

(2) Signals of RFP-labeled proteins are difficult to interpret throughout the experiments. What are the structures that show a strong accumulation of red signal in Fig. 1A,B, Fig 2G and Fig4A (20sec.) If these are fluorescently labeled proteins it would suggest that most of the proteins cluster/accumulate in the cell. Can the authors provide better images?

We appreciate that some of these reporters with multiple localisations can be difficult to interpret. This is major challenge for these sort of studies and main reason we use the large and easily-identified yeast containing phagosomes for quantification. In Fig. 1 the large structure is the large peri-nuclear cluster of Rab5 previously reported (Tu et al. JCB 2022). In Fig. 2G the bright structure is the recruitment of V-ATPase on the CV. Both these large structures easily distinguished from the phagosomal pool we are interested in. Whilst we would love to provide better images, this is simply not possible - both these other structures are unavoidable and we are already using some of the best microscopy methods available. We have however clarified the additional localisations seen in these images in the revised figure legends.

(3) On page 11 the authors state "...macropinosomes in ∆PIKfyve cells still appeared much larger. Quantification of their size and fluorescence intensity demonstrated that although macropinosomes started off the same size,...". This statement is not reflected in the data depicted in Fig. 3A,B. The size of the single labeled macropinosome appears to be larger in wildtype than in ∆PIKfyve cells from the beginning on. However, the quantification in Fig 3F is clear. So, are these bad examples in 3A,B, are they swapped or is this due to the additional expression of GFP-Rab7A? Could you please comment on the effect that the (over-)expression of GFP-tagged Rab-GTPases might have on the observations described in this paper in the discussion part?

As you can see from the error bars in Figure 3F, macropinosomes are extremely variable in size - ranging from ~0.2-5 microns in size in axenic Dicytostelium. The image in Figure 3B is therefore indicative of this heterogeneity, rather than being a "bad example". This is why we designed the experiment to quantify several hundred vesicles in order to make any conclusions - as well as doing it in the absence of any GFP-fusion expression.

Although we have not noticed any issues (enlarged vesicles are also clear in GFP-Rab7 expressing cells in Figure 1B), we do of course accept that GFP-Rab7 expression itself may have some detrimental effects on maturation and this is why we quantified macropinosome size in untransformed cells. We have clarified this in the results section (P12 L28).

(4) In Fig. 6E it is hard to distinguish if the dextran is accumulating inside the phagosome. I would suggest conducting a 3D reconstruction of these images to allow judging if macropinosomes fused with the phagosomes or if they cluster around the neck of the phagosome.

This would be nice, but not possible as these images are from single confocal sections, rather than a complete high-resolution Z-stack. We have however added an enlargement of both Figure 6D and E which we feel now more clearly shows the presence of dextran within the bounding PI(3)P membrane of the phagosome.

(5) In the discussion, the authors state that the small pool of "PIKfyve-independent Rab7" is "insufficient to for subsequent fusion with other Rab7A-positive compartments, further Rab7 enrichment, and lysosomal fusion." What is the rationale for this conclusion? Is it shown how many Rabs are necessary to induce a tethering and fusion event? It would be good to revise this part of the discussion also in respect of the first major point of my comments above.

Our data show that in the absence of PIKfyve, phagosomes still remove Rab5 and gain a small pool of Rab7 but progress no further. This is consistent with some block in the HOPS-mediated homotypic fusion of Rab7 compartments. However, we accept that this is not necessarily due to simply not having enough Rab's so have rephrased the discussion accordingly.

(6) The intention of the paragraph about phagosomal ion channels is for this reviewer somehow out of context. It is not clear to me how the authors relate this to their findings. It would be could to bring this into a broader context.

__ __We mention ion channels in the background as they represent the main class of PI(3,5)P2 effectors known so far. We feel this is important background context, even if our studies do not directly relate to this.

Reviewer 3:

Their disclosure and use of statistics is incomplete and/or inconsistent, and potentially wrong in some cases. For example, the authors disclose the number biological repeats in a few experiments (Fig. 3C, F) but not in the majority. Instead, they state the number of phagosomes without indicating biological repeats (eg. Fig. 2 and others). So, it is not possible to know if their data are reproducible. Despite not indicating independent experiments in some cases, they speak of SEM, which applies to mean of means from biological repeats. In other cases, none of this is disclosed (eg Fig. 3G). Often there is no indication of what statistical test was done OR if a statistical test was done (eg. Fig. 3G, Fig. 4, etc). I would recommend the authors review the excellent resource paper published in JCB on SuperPlots to better follow statistical expectations. This is essential to improve reproducibility and confidence in their observations.

We apologise if this was unclear for the referee, but we have tried to be clear in each case. The confusion likely lies in the definition of a biological repeat, which depends on the type of experiment. For quantification of phagocytic events over time, we feel it reasonable to take each individual event (each from an individual organism) as a biological repeat. This is because events are relatively rare and taken from multiple different movies, and it is not technically possible to film both mutants and controls simultaneously. In all these sort of experiments (e.g. Figure 2) we have shown standard deviation, which indicates the reproducibility between phagocytic events. We have clarified that these events are from movies obtained on at least 3 independent days in the methods.

In other cases, such as Figure 3C and F and Figures 5-6, we are able to take measurements across multiple cells simultaneously at each timepoint. It is therefore appropriate to average over multiple independent experimental repeats rather than individual cells. We have therefore used SEM in our analysis, and both the number of individual cells and independent repeats are stated on the graphs and legend. This was incomplete in a few cases but has now been clarified in all cases.

Regarding statistical tests, which ones were used now been clarified in each figure legend. Note that in Fig 3G, we do not apply any test as both lines essentially overlap and it is clear there would not be any convincing differences. In Figure 4, the graphs all compare co-expression of different reporters rather than different mutants or conditions and are from single events. We therefore feel statistical tests are unnecessary and inappropriate. Comparison of the same reporters between strains averaged across multiple events, with statistical analysis is shown in Fig 2 instead. All these points have now been added to the statistics section of the methods (P9 L1-6)

Minor Comments

It is interesting that 2FYVE-GFP stays on phagosomes for 50 min or more - this is distinct from macrophages. Please comment. Have the authors tried other PI(3)P probes to see if the same (PX-GFP).

We have not used other probes but we have no reason to believe 2xFYVE does not behave as predicted as it is the same probe used for most macrophage studies (FYVE domain from human Hrs), and gets removed from macropinosomes exactly as expected. We did not originally comment in this manuscript but PI3P dynamics are even more interesting as our previous data indicate that latex-bead containing phagosomes lose PI3P after 10 minutes (Buckley et al 2019, Figure 4F-G) This indicates phagosome maturation can be regulated by the cargo (under further investigation). Importantly however, both bead and yeast-containing phagosomes have comparable defects in the absence of PIKfyve. This is more fully discussed in our previous paper (Vines et al. JCB 2023) where we characterise PI(3)P and PI(3,5)P2 dynamics in more detail.

Fig. 7 model: the macropinosome in the diagram seems like a dead end as depicted - is there any arrow or change that could be added to show that it doesn't just sit there in the middle? Also, the light green on yellow hurts the eyes!

We apologise, there was actually supposed to be an arrow there but it was lost somewhere in the drafting process. The whole figure has now been updated to more clearly describe our full and more complex model.

Fig. 3F, could be converted to volume assuming macropinosomes are spheres.

This is true, however as these images are taken from single planes we cannot know where in the sphere the slices are and therefore what the maximum diameter would be. We therefore prefer to keep it as area so as not to confuse and over-interpret the data.

Pg. 10, line 10 - Vps34 is Class III PI3K, not Class II.

Corrected.

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

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

• *

Reviewer 2:

(3) ("OPTIONAL") Optionally, the authors could also try to clarify these structures' identity by including further colocalization studies with additional early and late endosomal marker proteins. Are they for example positive for early or late endosomal markers like EEA1, ESCRT or Retromer? How about organelle-specific SNAREs? This would give further insights into the character of the "Rab7-donor" structures and would allow to clarify if multiple subpopulations are contributing to phagosome maturation in a sequential order as stated in the abstract. As I am not an expert on Dictyostellium I can`t estimate the effort that would go into such an experimental setup. However, since the time scale of the events in the cell is nicely worked out in this study, these colocalization studies would not need to be conducted as live-cell microscopy experiments.

This is a sensible suggestion that would in theory help define these populations. However many of these markers are poorly defined with respect to phagosomes and/or Dictyostelium. Dictyostelium does not posses an EEA orthologue, but our data also indicate that these vesicles do not possess PI3P so cannot be canonical early endosomes. We have previously characterised WASH/retromer and whilst it is recruited to phagosomes at around the time of Rab5/7 transition Retromer appears to be recruited from the cytosol and drive recycling rather than being delivered on endosomes that fuse (see King et al. PNAS 2016). We have also previously looked at ESCRT (Lopez-Jimenez et al. PLoS Pathogens 2018) which also does not appear to have any recruitment to early phagosomes that would be consistent with a Rab7-sub-population. The SNAREs are yet to be studied in any detail, as they are often too divergent to assign a direct mammalian orthologue.

Therefore, whilst this is a sensible suggestion, and something we would like to follow up in the future, this is not straight-forward and we feel outside the scope of the current study. We have however included additional discussion of this in the revised manuscript (P20 L21-26).

Reviewer 3:

Major Comments:

1. Based on the current data, I am not entirely convinced that Rab7 is delivered mostly by fusion with other compartments. At least the data as provided cannot exclude other models. For example, Rab7-containing organelles that cluster with phagosomes may form contact sites that provide a local environment to load cytosolic Rab7. There's also a possibility that some of their Rab7 clusters are membrane sub-domains and not vesicles. Or perhaps, there is a first wave of cytosolic Rab7 recruitment, which then initiates fusion with Rab7 compartments, i.e., there is a two-phase Rab7 recruitment. While this last possibility is consistent with recruitment of Rab7 by fusion (the second phase), the authors present a model that is too simplistic and conclusive based on the data. The authors may be right, but they need to strengthen their evidence towards their claim. Maybe EM could help determine some of these issues. Perhaps better would be the use of FRAP, photo-activation, or optigenetics of Rab7. For example, if Rab7 is acquired on phagosomes after photobleaching clusters of Rab7, this would suggest a cytosolic Rab7 contribution, and if not, this would support their model. I recognize that these experiments are not necessarily trivial, but either the authors augment their data (as suggested or with other approaches) or significantly pare down their conclusions.

We agree with the Referee that we cannot completely exclude other models, and as we talk about in the discussion, we do not wish to do so. We apologise if the role of fusion was over-stated but the model we propose is as the referee suggests: there is likely an early first wave of canonical Rab7 recruitment from the cytosol that is independent of PIKfyve before the majority of Rab7 is subsequently delivered by fusion in a PIKfyve-dependent manner. Our data indicate that the second wave is both quantitively and functionally more significant (see functional data in Buckley et al. 2019).

We do however agree with the referee that we cannot formally exclude things such as contact-site mediated recruitment from the cytosol or sub-domains but not fusion however there is no data to support these either. In contrast, the hypothetical clustered Rab7 contacts/subdomains often (but not always) contain the transmembrane V-ATPase complex (Figure 2G) which must be delivered by fusion.

However we do not wish to over-simplify our conclusions and as we state in the discussion, we do think there is probably a small amount of Rab7 recruited from the cytosol by the canonical pathway. We accept that our cartoon in Figure 7 is over-focussed on fusion so we have substantially revised this, as well as the discussion to give a more balanced and complex view.

Regarding the proposed experiments, unfortunately, the imaging required to acquire these movies is already at the very limit of what is possible so we do not believe it would be technically feasible to employ methods such as FRAP and optogenetics on these relatively fast-moving phagosomes with the temporal resolution required. Furthermore, to differentiate recruitment from a cytosolic pool, every GFP-Rab7 cluster would need to be photobleached, which could not be reliably achieved.

However, this point will be largely addressed by the suggestion of Reviewer 2 to look at the Mon1/Ccz complex. The presence or absence of this will give strong evidence for canonical Rab5/7 transition and Rab7 recruitment from the cytosol which would significantly clarify our model and define the two different mechanisms of Rab7 recruitment to phagosomes.

Early macropinosomes fuse with early phagosomes more readily than 10-min old macropinosomes. Do 10-min old macropinosomes not fuse with older phagosomes? Is this not an issue of mismatched age?

This is an interesting point that we have clarified in the text. We agree with reviewer that it appears the ages of the macropinosomes and phagosomes must match but our data indicate this only occurs when both parties possess PI(3,5)P2 as macropinosome fusions appears to happen in a single burst at about 240 seconds (Figure 6F) rather than as a continuous process. We also do not start to see any fusion of these older macropinosomes when the phagosomes get past the initial first 10 minutes of maturation (Figure 6G).

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Referee #1

Evidence, reproducibility and clarity

PIKfyve/Fab1, a kinase responsible for phosphorylating PI3P to produce PI(3,5)P2, regulates phagosome maturation across various organisms. A previous work from the authors' group demonstrated that disrupting PIKfyve in Dictyostelium inhibits the delivery of V-ATPase and hydrolase, thus dramatically reducing the ability of cells to acidify newly formed phagosomes and digest their contents. The current manuscript further dissects the function of PIKfyve and PI(3,5)P2. Using live cell imaging, the authors show that nascent phagosomes acquire Rab7 by fusion with multiple populations of Rab7-positive vesicles, and the loss of PIKfyve abolishes this event. One of these fusogenic vesicle populations was identified as PI(3,5)P2-positive macropinosomes, which dock and fuse with phagosomes in a PIKfyve-dependent manner. Based on these findings, the authors propose that PIKfyve contributes to phagosome maturation by promoting heterotypic fusion between phagosomes and macropinosomes, which help deliver regulatory components necessary for phagosome acidification and digestion. This study provides fresh insights into the process of phagosome maturation. The work was well designed, performed and presented, and the manuscript is clearly written. However, there are several questions that should be addressed to strengthen the conclusions of the manuscript.

Major points:

1. The observation that macropinosomes undergo retrograde fusion with newly formed phagosomes to facilitate phagosome maturation is an interesting notion that challenges the traditional model. However, not all phagocytes exhibit a high level of macropinocytosis, and axenic Dictyostelium cells used in the study may be an exception. Thus, it remains unclear whether fusion with macropinosomes is universally required for phagosome maturation. WT Dictyostelium cells or axenic cells cultured under SorMC/Ka condition (Paschke et al., PLoS One, 2018) exhibit significantly reduced macropinocytosis. The authors could examine whether the accumulation of Rab7 and V-ATPase on large-sized phagosomes is delayed in these cells. These experiments may help broaden the applicability of the authors' finding.
2. PIKfyve seems to play a specific role in the maturation of phagosomes but not macropinosomes. The differences may be driven by signaling from phagocytic receptors, as the author suggested. Alternatively, the large size of the yeast-containing phagosomes may require additional steps for efficient lysosomal delivery. The authors should consider examining whether PIKfyve is needed for the delivery of Rab7 and V-ATPase to phagosomes of comparable size to regular macropinosomes, such as those containing K. aerogenes or small beads. In addition, whether the process also involves fusion between phagosomes and macropinosomes should be verified.
3. In the previous study from the authors' group (Buckley et al., PLoS Pathog, 2019), it was shown that the accumulation of V-ATPase on phagosomes begins immediately after internalization in both PIKfyve mutant and WT, although V-ATPase accumulation reaches only half of the levels seen in WT. This partial accumulation of V-ATPase differs from the almost complete absence of Rab7 recruitment found in this study, which raises the question of whether there exists yet another population of fusogenic vesicles that are positive for V-ATPase but negative for Rab7. This could be checked by simultaneously examining the dynamics of V-ATPase and Rab7 during yeast phagocytosis in the PIKfyve mutant.

Minor points:

1. It is unclear how the experiment in Figure 3G was conducted. If microscopic analysis was involved, the corresponding images should be included.
2. Page 11-Line 2, the sentence "there was no obvious clustering around the nascent phagosome (Figure 2D)." It is Figure 2E, not Figure 2D.
3. There is an inconsistency regarding the description of fluorescent fusion proteins. For example, both GFP (RFP)-2xFyve and 2xFyve-GFP (RFP), as well as GFP-Rab5 and Rab5-GFP, were used. Typically, placing GFP (or RFP) before a gene suggests N-terminal tagging, while placing it after the gene implies C-terminal tagging. The authors should clarify the position of the fluorescent tag and ensure consistency in their descriptions.
4. One of the videos was not referred in the manuscript or described in the Video legends. This video seems to correspond to Figure 5A, albeit with a different pseudo-color scheme.

Significance

Disruption of PIKfyve results in severe defects in phagosomal maturation across different organisms, but the underlying mechanism remains unclear. This study demonstrates that PIKfyve plays a specific role in phagosome maturation by promoting heterotypic fusion between macropinosomes and newly formed phagosomes. These fusion events provide a means for the rapid delivery of lysosomal components to early phagosomes. The study challenges the conventional model of phagosome maturation and provides novel insights into the complex dynamics involved. Nonetheless, further investigations are needed to elucidate the exact role of PIKfyve/PI(3,5)P2 in regulating vesicle fusion and to explore whether the proposed model can be applied to other endocytic pathways or cell types.

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Reply to the reviewers

Review Commons - Revision Plan

Manuscript number: RC-2023-02228

Corresponding author(s): Gatfield, David

1. General Statements

We are grateful to the three Reviewers for their detailed assessment of our manuscript and are delighted about their very constructive and positive evaluations, highlighting the study’s novelty and rigor.

Briefly, the main points raised by Reviewers 1 and 3 do not involve additional experiments and are mostly about rethinking manuscript structure (e.g. moving data/analyses to the supplement or removing them altogether, as they distract from the main thrust of the story) and making the text overall less dense and more readable.

Reviewer 3 also raises a number of additional interesting points that we should discuss in our manuscript, which would allow us placing our findings more effectively into the context of the existing literature.

All these points are very well taken and will be implemented (see below, under 2).

Reviewer 2 is overall also rather positive – speaking of “a very careful and detailed study that addresses an important issue” and the study being “really rigorous and the logic […] very well explained”; moreover, this Reviewer also shares the view of both other Reviewers that parts of the manuscript (i.e., in particular its beginning) should be shortened.

Importantly, this Reviewer remarks in addition under “Significance”: “Without additional mechanistic insights suggesting that there is something particular different about the regulation of these mRNAs the manuscript is not of extremely high significance.” – an important point of criticism that we wish to address in our revision, as detailed below.

2. Description of the planned revisions

In the following, we detail how we plan to address the points raised by the Reviewers. The order in which we treat the points follows their – in our view – relative importance according to the Reviewers’ feedback. In particular the first item below, under (A), is the main point of criticism that we feel we should address carefully for the future revised version.

(A) Major point raised by Reviewer 2: “However, the study falls short on addressing the mechanism of this regulation and if it is different of other feeding regulated mRNA oscillations. This diminishes the significance of the study unless additional mechanistic details are provided.” , which is cross-commented both by Reviewer 1: “More importantly, clues to the mechanism (e.g. iron, heme) regulating the rhythmic translation of IRP1 and IRP2 IRE-mRNAs in liver would increase the significance of the work.” as well as by Reviewer 3: “Reading the comment from Reviewer #2 over the lack of a mechanism to explain why only four transcripts with IREs amongst a larger pool are subject to circadian regulation by IRPs somehow reduces the significance of the study, one has to agree that a discovery - likely another component in the system - is wanting. I remain of the view that the present work exposes this "weakness" of the entire field in a global as opposed to a partial manner and in doing so, makes a significant contribution, especially by further sub-classifying the IRE-containing transcripts according to their responsiveness in the diurnal occupancy of their IREs.”

Our response and revision plan: Indeed, in the original version of our manuscript we established the link to feeding, yet we did not pinpoint the precise molecular cue that could underlie the rhythmic regulation observed on certain IRE-containing mRNAs. We did discuss the molecular candidates quite extensively in the Discussion section of the manuscript (Fe2+; oxygen; reactive oxygen species), and it remains quite obviously the main question whether the observed diurnal control could be mediated directly by changes in intracellular iron availability.

Of note, the preprint by Bennett et al., for which we cite the initial biorXiv version in our manuscript, was updated very recently (https://doi.org/10.1101/2023.05.07.539729 – see version submitted December 18, 2023). It now includes new data that analyses around-the-clock iron levels also in liver. Briefly, the preprint shows, first, that serum iron is rhythmic with a peak during the dark phase at ZT16 (Figure 1D in Bennett et al.) yet loses rhythmicity when feeding is restricted to the light phase (Bennett et al., Figure 2E), indicating both feeding-dependence and circadian gating. Moreover, liver total non-heme iron – quantified using a method that measures both ferrous Fe(II) and ferric Fe(III) – shows low-amplitude diurnal variations which, however, do not meet the threshold for rhythmicity significance (Bennett et al., Figure 3G). Still, the difference between timepoints ZT4 (lower iron; light phase) and ZT16 (higher iron; dark phase) is reported as significant, with a fold-change that is not very pronounced (not compatible with the observed direction of regulation of Tfrc mRNA, whose higher abundance in the dark phase would rather be in line with lower *cytoplasmic iron levels, as pointed out by the authors.

Thus, at first sight the analyses by Bennett et al. would appear to answer part of the Reviewer’s question and point towards other mechanisms of regulation than iron levels themselves. However, it should be pointed out that the particular methodology for iron measurements used by the authors includes the use of reducing reagents and hence quantifies the sum of Fe2+ and Fe3+ iron. Large amounts of iron are stored in the liver in the form of ferritin-bound Fe3+, yet the bioactive, low-complexity iron that is considered relevant for IRP regulation is in the Fe2+ form. Therefore, the question whether bioactive ferrous iron levels follow a daily rhythm, compatible with the observed IRP/IRE rhythms described in our manuscript, still remains an open question and warrants a dedicated set of experiments that we are proposing to conduct in response to the Reviewers’ comments.

Briefly, for the revision we propose to use liver pieces from the two relevant timepoints of our study (i.e., ZT5 and ZT12) and apply a method that allows the separate quantification of Fe2+ and Fe3+ (Abcam iron assay ab83366; this assay can be adapted to liver iron measurements, see e.g. PMID31610175, Fig. 4A). This experiment will provide novel and decisive data on the molecular mechanism that may regulate the IRP/IRE system in a rhythmic fashion and therefore add to the significance of our findings, as requested by the reviewers.

Moreover, we believe that the outcome of the experiment would be very interesting either way, i.e. if we find rhythms in Fe2+ that are compatible with rhythmic IRP/IRE regulation, we would be able to provide excellent evidence in term of likely molecular mechanism and rhythmicity cue. If, by contrast, we find that Fe2+ is not rhythmic, it will point towards a mechanism that is distinct from simple Fe2+ concentrations.

In the latter case, collecting additional evidence on relevant alternative molecular cues would be beyond our capabilities for this particular manuscript, as it would require quite sophisticated methodological setup and preparation. For example, one could imagine that measuring around-the-clock liver oxygen levels in vivo – another candidate cue – would be highly interesting, yet we would not be able to conduct these experiments in a reasonable time frame (to start with, we would first need to request ethics authorisation from the Swiss veterinary authorities, which would in itself take ca. 4-6 months before we could even start an experiment). Thus, in the case of non-rhythmic iron levels, we would leave the question of other responsible cues open, but still think that with a balanced discussion of the resulting hypotheses we could provide significant added value to our work.

(B) Major comment raised by Reviewer 1: “Alas2 is expressed mainly in erythroid cells and not liver, whereas Alas1 is ubiquitously expressed. Therefore, it is possible that Alas2 in this study may originate from red cells/reticulocytes in the liver, and not from hepatocytes.”

Our response and revision plan: We would like to thank the Reviewer for the comment that is indeed pertinent. It is well established that Alas1 is the main transcript encoding delta-aminolevulinate synthase activity in hepatocytes, and Alas2 is about 10-fold less abundant in total liver RNA-seq data (quantified form own RNA-seq data, not shown).

We are nevertheless relatively sure that the Alas2 signal comes from low expression in hepatocytes; the best argument in support of this hypothesis is the analysis of single-cell RNA-seq data, as shown in the following Revision Plan Figure 1, which we would be happy to include in a revised version of the manuscript if the reviewers wish:

(C) Minor comment raised by Reviewer 1: “The paper is dense and not easy to read. For example, the section on Tfrc regulation and NMD regulation is lengthy and perhaps not necessary for the paper and the section on "Previous observations in IRE-IRP regulation...." could be included in the discussion rather in than in the Results section. Some figures could be included in a supplement.” continued in Referee cross-commenting “I agree with Reviewer 2 that the first sections in the manuscript are lengthy and not needed.”; moreover, Reviewer 2: “Also, the manuscript first sections (which mainly describe negative results) seem too long and descriptive.”

Our response and revision plan: We shall reorganize the paper accordingly, with the aim of making it an easier, shorter, clearer read. Many thanks for the input.

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(D) Minor comment raised by Reviewer 1: “A description of the new anti-IREB2 antibody is needed. What IRP2 sequence was used to generate antibodies?”

Our response and revision plan: The following information will be included in the manuscript: “Rat monoclonal antibodies against ACO1/IRP1 and IREB2/IRP2 were generated at the Antibodies Core Facility of the DKFZ. Briefly, full-length murine ACO1/IRP1 and IREB2/IRP2 proteins, fused to a poly-histidine tag, were expressed in E. coli and purified on Ni-NTA columns using standard protocols. Purified His-tagged proteins were used to immunize rats and generate hybridomas. Hybridoma supernatants were first screened by ELISA against His-tagged ACO1/IRP1 and His-tagged IREB2/IRP2. As an additional control, supernatants were tested against full-length His-tagged murine ACO2 (mitochondrial aconitase), which shares 27 and 26% identity with ACO1/IRP1 and IREB2/IRP2, respectively. Supernatants reacting specifically with ACO1 or IREB2 were validated by western blotting using extracts from wild-type versus ACO1- or IREB2-null mice.”

(E) Minor comment raised by Reviewer 1: “A model summarizing the data would be useful.”

• *Our response and revision plan: Thank you for the suggestion – this will be done.

(F) “Optional” idea raised by Reviewer 3: “One nuance in the field of circadian biology is that a rhythm is deemed to be genuinely "circadian" when it continues in the absence of zeitgebers. In this sense, although all experiments are valuable, the "collapse" of the rhythm in the paradigms where dietary rhythms have been disrupted makes the phenomenology a candidate "epiphenomenon" rather than being closer related to the biological clock(s). Likewise, in the manuscript we never learn how the liver IRE-binding activity behaves in constant darkness.”

Our response and revision plan: This is an important aspect that we can clarify more specifically in our manuscript. It is true that constant (darkness) conditions are used to call a phenomenon circadian. We would nevertheless argue that for a rhythmic feature that is specifically found in liver, the constant darkness definition to distinguish circadian from non-circadian is not fully valid because even in constant darkness, the liver clocks are not in a free-running state but continue to be entrained by the SCN clock (it is only the latter that is free-running under these conditions).

In our manuscript, we actually suggest that the observed rhythms are not a core output of the circadian machinery (Fig. 6 of our manuscript), but indirectly engendered through feeding rhythms, which are coupled to sleep-wake cycles and thus connect in an indirect way to the central circadian clock activity in the SCN.

In wild-type mice we would therefore expect that irrespective of constant darkness or light-dark entrainment (and assuming ad libitum feeding), the hepatic rhythms of the relevant IRE-containing transcripts would persist in a similar fashion.

(G) “Optional” idea raised by Reviewer 3: “Where the authors mention in a parenthesis "moreover, there are documented links between iron and the circadian timekeeping mechanism itself", I invite them to take a closer look to the paper Konstantinos Mandilaras and I coauthored in 2012 "Genes for iron metabolism influence circadian rhythms in Drosophila melanogaster". In that work, we showed that RNA interference of genes that are required for iron sulfur cluster formation (including on IRP1) in the central clock neurons of the fly result in loss of the circadian rhythm when flies were kept at constant darkness (not so when they were kept under light:dark oscillation). So this point should probably remain open..”

Our response and revision plan: We would like to thank the Reviewer for pointing out this interesting connection that would fit well into the context of our manuscript. It should be cited in the context of our current Figure 3, where we measure in vivo and in tissue explants whether IRP-deficiency affects the clock itself.

To follow Reviewer 3’s idea, we have gone a little further in our analyses of around-the-clock expression data to see if any of the components of the Fe-S assembly machinery is rhythmic itself, which could have the potential to add novel information.

Briefly, we have used for this purpose our around-the-clock RNA-seq and ribo-seq data from PMID 26486724. In summary, we find that the expression at RNA and/or footprint level is non-rhythmic for the vast majority of genes involved in FeS biogenesis, assembly or transport, with the exception of low-amplitude rhythms for Glrx5 and Iba57 (Revision Plan Figure 2).

By contrast, all of the following other genes are non-rhythmic throughout (list of Fe-S-relevant genes from PMID34660592): Cytoplasmic/nuclear, all non-rhythmic: Cfd1=Nubp2, Nbp35=Nubp1 , Ciapin1, Ndor1, Iop1=Ciao3=Narfl, Ciao1, Ciao2b=Fam96b, Mms19, Ciao2a=Fam96a; mitochondrial, all non-rhythmic: Iscu, Nfs1, Isd11=Lyrm4, Acpm=Ndufab1, Fdx1, Fdx2=Fdx1l, Fxn, Hspa9 Hsc20=Hscb, Abcb7, Alr=Gfer, Isca1, Isca2, Nfu1

As these are mainly “negative results”, and as we are also unable to propose a solid possible mechanistic connection between the Glrx5 and/or Iba57 rhythms and the rest of the story of our manuscript, we do not intend to include such data in our manuscript, but are only putting it for the record into this rebuttal.

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

NONE

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

NONE – we think we can address all points as described above.

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Reply to the reviewers

We would like to thank our reviewers for their constructive criticism and for their appreciation and enthusiasm for our study. Some reviewers expressed opposing views, particularly when it came to the function and identity of the Cdt1-related protein in Toxoplasma gondii. To avoid redundancy in our response, we would like to make a brief statement. Toxoplasma gondii and other apicomplexan parasites utilize unique and highly unusual modes of cell division; numerous studies suggest that multiple phases can run concurrently in apicomplexan cell cycles. The best-known examples include the asynchronous S/M cycles in schizogony and concurrent mitosis and budding in Toxoplasma endodyogeny. These overlapping phases are not a feature exclusive to apicomplexans, since in budding yeast, cytokinesis initiates in G1 phase by marking the location of budding on the surface of the mother. Based on years of previous research and from our experience, we adjusted our approach by focusing on the processes that are associated with each cell cycle phase rather than on their temporal order. While the model of a conventional cell cycle guides our studies, we “follow the breadcrumbs” that we discover and the published studies to create a more accurate model of apicomplexan cell cycle instead of relying on the traditional cell cycle map employed by distantly related eukaryotes. Below are point-to-point responses to reviewers’ comments.

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

Summary: Hawkins et al. employ a reverse genetic approach to analyze the molecular function of the Toxoplasma gondii kinase Crk4 and the Toxoplasma gondii cyclin 4. The authors combine inducible depletion with imaging, (phospho-)proteomics, molecular modeling, and protein-protein interaction studies.

Major comments: - The major conclusion of the manuscript is that TgCrk4/TgCyc4 regulate entry into mitosis and that the primary role of TgCrk4 is to suppress DNA re-replication and chromosome re-duplication (lines 105-106). The authors also provide evidence that TgCrk4 interacts with TgCdt1, a DNA licensing factor ("TgCdt1" is missing in line 107). (had been corrected) By sequence homology, the authors found homologues of TgCrk4 only in apicomplexan parasites with binary division and concluded that the dominant division mode, presumably schizogony, is repressed in these organisms in favor of binary division. Indeed, internal budding and daughter cell formation is defective in the inducible depletion mutants of TgCrk4 and most experiments focus on this developmental stage. However, the analysis of preceding events, such as DNA replication is rather brief. If G2 is indeed regulated by TgCrk4/TgCyc4, one would assume that the parasites are post-S phase and the nucleus contains two copies of the genome, as indicated in Fig. 2C. The data shown in Fig. 3H and 7A, however, show that the TgCrk4 and TgCTD1 depletion induces a developmental arrest pre-S phase. This contradicts the main conclusions of the manuscript.

*We agree that the G2 location is odd for a conventional cell cycle model. Given the high possibility that cell cycle phases can overlap in apicomplexans, we determined the relative position of G2 phase in Toxoplasma endodyogeny by instead focusing solely on the processes that are attributed to a specific cell cycle phase (such as DNA replication for S phase, DNA re-replication for G2 phase, DNA segregation for mitosis). Our approach shows that Toxoplasma G2/M checkpoint operates upstream of SAC, which led to enrichment of parasites with replicated DNA (Fig. 3H and Fig. 7A), which places G2 at the end of S-phase. Our focus in the present study is on the G2 functions, the control of centrosome and chromosome reduplication, but we appreciate the suggestion to examine DNA replication in Toxoplasma, which could be investigated in future studies. *

Indeed, many data of this manuscript could support an alternative conclusion, i.e., that TgCrk4 regulates entry into S-phase (similar to Plasmodium falciparum Crk4: PMID: 28211852). This alternative conclusion is supported by the data showing that TgCyc4 is in the nucleus during S-phase (Fig. 1H) and that TgCrk4 interacts with TgCdt1, which has a well-known role in origin of replication licensing and loading of the MCM complex. MCM subunits were less phosphorylated in absence of TgCrk4, which could also suggest a role for TgCrk4 in S phase. Together, it seems more parsimonious to interpret the data as a DNA replication phenotype rather than a phenotype in G2.

*We understand some confusion from prior data, but PfCrk4 is not orthologous to TgCrk4 (Alvarez & Suvorova, 2017); The true TgCrk4 ortholog had not been found in Plasmodium genomes. Our understanding is that nuclear accumulation of TgCyc4 in S-phase activates TgCrk4, which leads to repression of the DNA reduplication. One of the possible mechanisms involves interfering with loading of the MCM complex on chromatin mediated by hyper-phosphorylated TgiRD1 (former TgCdt1), which has been reported in other eukaryotes. We also believe that increased MCM phosphorylation indicates entry into or active S-phase, while the reduced phosphorylation that was detected in Crk4-depleted cells supports a block at the end of S-phase (G2). *

• *

The currently provided data on the DNA content are, however, clearly insufficient to draw firm conclusions. The gating strategy (dotted lines in Figs. 3H, 7A) is unclear. Why are populations, e.g., not separated at the lowest part of the depression in the histogram, but shifted towards lower DNA content? This seems to overestimate the percentage of cells that have a higher DNA content and the statement in lines 269-271, i.e., that TgCrk4 deficient parasites break the "once and only once" rule, is not supported by data.

*We corrected the gating of the FACScan plots to separate G1, S, G2+M, and parasites with over-duplicated DNA. Please note that, in general, the cell cycle gating of FACScan data is relative and somewhat subjective when it comes to the gaussian curve. Independent of the chosen gates, our data show that removal of either TgCrk4 or TgiRD1 led to substantial decrease of the G1 population (reduction of 1N peak) accompanied by increase of parasites in the process of replication, completed replication (increase of 1.8 N peak), as well as undergoing DNA re-replication, which supports our claim in lines 269-271. In the case of TgiRD1, the number of parasites with re-duplicated DNA nearly doubled upon 8h of factor deficiency. *

• *

It is also unclear how may biological replicates are represented by these data (Figs. 3H, 7A), a critical wild type control at t = 4 h is missing, as well as a statistical analysis. Alternatively, the authors could use microscopy to quantify the DNA content of individual nuclei, which would yield a direct read out on whether a nucleus is in pre-S phase, S-phase or post-S phase. Defining the onset of S-phase indirectly by the number of centrosomes per cell seems imprecise, given the small size of the structure and the resolution of the microscope. Without solving these issues, the major conclusions and several minor statements throughout the manuscript are in question.

*Thank you for your point, we performed a minimum of three independent experiments to evaluate the DNA content of TgCrk4- or TgiRD1- (former TgCdt1) depleted tachyzoites and have now indicated this in the figure legends. The 0h time point is a “wild type” control, since the parasites that expressed factors were incubated without auxin (mock treated) for 4h. The DNA content of Toxoplasma has been thoroughly studied and we are thus confident our 0h data is a good representation of asynchronous healthy populations. Although the parental strain had been examined, due to the data density mentioned in the reviews, we included only relative results (control and two experimental points) for clarity. Our concern with using microscopy to analyze DNA content is that it can be highly subjective, hinging on the quality of staining and imaging, while flow cytometry produces more unbiased datasets. We have considered the concern that the start of centrosome duplication can be difficult to identify, but the centrin-positive centrosomes move apart by the middle of S-phase. The independent structures are then distinct and easy to resolve, providing a popular means of marking G1/S transition in Toxoplasma. *

• Lines 187-189: The mentioned checkpoint is unclear and so is the "specific cell cycle population". Fig. 2B analyses budding, but as the final step in the cell cycle, the knock down parasites may have arrested at various other stages of the cell cycle. In addition, it is unclear on which primary data Fig. 2B is based. It appears these may be at least partially shown in Fig. 3. If so, please reorganize as this is highly misleading.

*“A checkpoint” in the indicated lines refers to G2/M and SAC, which are regulated by TgCrk4 and TgCrk6, respectively. We refer to “specific cell cycle population” since each transgenic parasite that is subject to G2/M or SAC arrest can allow us to isolate very different cell cycle stages. TgCrk6-dependent arrest had been confirmed by the presence of unresolved centrocone (not shown but was previously reported in Hawkins et al., 2022), while we thoroughly examined the novel TgCrk4-dependent block by focusing on many parameters, such as joint centrosomes, single-bud assembly, or unresolved apicoplast. Fig. 2 and Fig. S2 summarize our rigorous quantifications of these phenotypes. For convenience, we used budding efficiency as a readout to compare arrest and release of G2/M and SAC, which was incorporated in Fig. 2B. Table S4 contains the primary data used in all figures in the manuscript, including Fig. 2B. *

• Line 246-254: It is unclear how many biological replicates were performed and how many cells were analyzed to conclude that TgCrk4 deficient parasites cannot form a bipolar spindle (Fig. 2H, S3B). This, together with the possibility that the developmental arrest occurs pre-S phase (Fig. 3H), does not support the statement, that the G2/M transition is regulated by the novel TgCrk4-TgCyc4 complex.

We have indicated our replicates in the M&M. As addressed for Fig. 3H above, these IFA experiments were performed in at least three independent experiments.

* * Minor comments: - Throughout the manuscript, please reorganize and present the figures in order of appearance in the text. Also, Fig. 1G summarizes data that are only presented in Fig. 1H. Please reorder. Similarly, Fig. 2C appears to summarize data that are only presented later.

*Thank you for the suggestion, however we must abide by the standards of the publishers. The order of the figures must be maintained, but there is a substantial degree of freedom in organizing panels within figures. Fig. 1G summarizes data shown in Fig. 1F, H, while Fig. 2C summarizes many panels including preceding Fig. 2B and Fig. S2. Most of our schematics are placed at the top of figures to provide guidance for the relevant experiments. *

• Why was only the "G1" timepoint quantified in Fig. 1H? Do the other images shown in F and H represent the majority of cells analyzed?

*You are correct, we indicated the percentage of factor-positive parasites only when the factor emerges during a specific cell cycle phase. For example, the TgCyc4-positive parasites with 1 centrin dot were quantified to show that TgCyc4 emerges in the middle of G1 phase. The lack of a number indicates that the image represents all the parasites progressing through this phase; we have added this explanation to the figure legends. *

• Several micrographs lack scale bars (Fig. 1B, D; 2E, F, H, I; 6D; 7F, H and S2G, S3A, B; S5A, B, D).

*Thank you, we have added the scale bars to indicated images.

*

• Lines 83-85 and 93-95: Recently several publications investigated the cell cycle of the apicomplexan parasite Plasmodium and data are accumulating, showing that there may be a gap between the last S phase and segmentation (e.g., PMID: 35731838; PMID: 35353560), which may be interpreted as a G2 phase. Thus, these statements could be revised to reflect the current literature.

*The studies mentioned provide very valuable insights into S-phase dynamics; the gap that was detected between S-phase and segmentation includes mitotic events such as prophase, metaphase, and anaphase prior to telophase (karyokinesis to segmentation). However, studies using means like stage-specific markers could help resolve the composition and order of events in the apicomplexan cell cycle. We used processes specific to G2 (repression of DNA and centrosome reduplication) and identified TgCrk4/TgCyc4 as the first G2 markers in apicomplexans. *

• Fig. 4 shows the effect on protein abundance and phosphorylation upon TgCrk4 depletion. Fig. 4B seems somewhat redundant as a more detailed analysis with two timepoints is shown in the rest of the figure.

*Fig. 4B is provided in contrast to the plot in Fig. 4A. It demonstrates that TgCrk4 depletion results in a far more pronounced effect on global phosphorylation rather than on proteolysis. While Fig. 4B highlights the checkpoint arrest, panels C and D are dedicated to the search for TgCrk4 substrates: the phospho-sites that immediately lost intensity of phosphorylation and remained low during the 4h block. *

*

*

• Lines 146-148: This statement is confusing in light of the expression data in Fig.1 F and H. If they stabilize each other, how is TgCrk4 stabilized in G1, when TgCyc4 is absent?

We believe that multiple mechanisms contribute to the stability and function of TgCrk4. We tested one and found that depleting the cyclin partner led to reduced expression of TgCrk4, and were able to conclude that the complex is stable when both subunits are expressed. Please note that we probed the mixed cell cycle populations by WB, and our proteomics data show that TgCrk4 interacts with many partners (Fig. 1E). Thus, it is likely that G1 stability may have been mediated by other partners, or by a higher transcription/translation rate, which could be evaluated in further experiments that focus on the regulation of TgCrk4/TgCyc4 complex.

• *

• Fig. 2D, and G: Please provide representative images of what has been quantified, as E/F and H/I are apparently UxEM images.

The corresponding images are included in Fig. S2.

• Line 236-243: This statement seems to be based on a single IFA shown in Fig. 2K. If so, the manuscript would benefit from clearly stating that this is a singular observation.

*Thank you, we have provided clarification as described in previous points. *

*

*

• Lines 301-304: In the cited publication, the TgOTUD3A knockout could not be complemented, which raises the possibility that other factors are involved. Thus, this statement would benefit from revision.

*The lack of TgOTUD3A KO complementation is an example of the unappreciated complexity of apicomplexan cell cycle regulation by controlled proteolysis. We highlighted the similarity of TgCrk4 and TgOTUD3A deficiencies, which indirectly confirms their partnerships in the G2 network. Fig. 8A shows that, in addition to TgOTUD3A, the G2 network contains numerous factors. *

*

*

• Lines 421-422: PfCdt1 was annotated in PlasmoDB some time ago and this statement needs to be revised.

*Please see our response to comments made by Reviewer 2. Briefly, we agree with Reviewer 2 comment that TgCdt1 does not function as conventional DNA replication licensing factor CDT1. Therefore, we named TGME49_247040 TgiRD1 – inhibitor of DNA and centrosome ReDuplication 1. *

• *

• Lines 448-450 and Fig. 6F: Are these data from a single biological replicate and how many cells were analyzed for the different time points? Given the insufficient data on the DNA content, the paper would benefit form more conservative conclusions on the role of TgCdt1. The numbers of biological replicates were added throughout the text, also please refer to our response to Reviewer 2 and the comment above.

Reviewer #1 (Significance (Required)):

• This manuscript investigates the role of TgCrk3, TgCyc4 and TgCdt1s and provides a large amount of data.
• These data will contribute to our understanding of the unusual division modes of Apicomplexa, a field of research that recently gained momentum.
• These data will be interesting to the community of cell and molecular biologist, which work on the fundamental biology of eukaryotic microorganisms.
• My field of expertise is the cell biology of Apicomplexa.

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

Summary: In this Manuscript, Hawkins et. al. describe advances in the apicomplexan parasite cell cycle, which is reminiscent but distinct from mammalian cell cycle regulation. These differences include a presumed lack of G2 phase and the ability to replicate in either a multinuclear (schizogony) or binary (endodyogeny) manner. Using Toxoplasma gondii (TG) as a model, the authors seek to expand the current understanding of how these highly variable parasitic cell cycles are regulated by describing a previously unreported G2 phase. Building on the authors earlier work, this manuscript defines the function of TgCrk4 and identifies a novel binding partner, TgCyc4. Crk4 and Cyc4 control a G2/M checkpoint by regulating centrosome duplication and separation.

The authors also identify 247040, a protein with previously no known function, as a binding partner and substrate of TgCrk4/TgCyc4 and several replication fork proteins such as MCM and PCNA. Results indicate that the protein negatively regulates replication and centrosome duplication. The authors propose to rename this protein TgCDT1 despite "low sequence similarity" and having a completely opposite function to eukaryotic CDT1. Using Swiss-Prot modeling the authors claim 247040 bears a "partial resemblance" to mammalian CDT1. Indeed, both of these proteins show high intrinsic disorder and have 2 folded domains. While 247040, like hCDT1, does contain cyclin interacting motifs (Cy), a collection degrons (not all shared with other CDT1 orthologs), and an NLS, the list of nuclear cell cycle proteins that also contain Cy and degron motifs would be very long. Further, 247040 is regulated in an opposite manner to all other CDT1 orthologs because it is absent in TG G1 and present in TG S phase; eukaryotic CDT1 is either degraded or relocalized to the cytoplasm in S phase, and evidence for degradation via APC/C is minimal. Crucially, loss of 247040 resulted in inappropriate replication ("re-replication"), whereas all other eukaryotic CDT1 orthologs are essential for replication. Re-replication in eukaryotic cells can be caused by excess or hyper-active CDT1, not by loss of CDT1 activity as shown here for 247040. Clearly 247040 is a negative regulator of DNA replication, and as such, is not a candidate for the TgCDT1 ortholog. If anything, it is functionally analogous to metazoan geminin, the negative regulator of metazoan CDT1; of note, geminin also has centrosome-related phenotypes. We cannot support naming 247040 TgCDT1 because it will cause confusion in the field.

Aside from this major issue, the study is well-executed, rigorous, quantitative, and thorough; it has many strengths from the unbiased interaction screens. The authors' sequence analysis also suggests broader possibilities for cyclin structures than had previously been appreciated. We appreciate the legend in Figure 2 to the organism-specific terminology.

Major comments: The spatiotemporal dynamics of 247040, its role in repressing TG DNA replication, lack of PIP motif and winged helix domain indicate that some other nomenclature, other than TgCdt1 will be a better name for this protein of previous unknown function.

We would like to thank Reviewer 2 for this highly insightful comment. We agree that TGME49_247040 functions as a CDT1 inhibitor rather than as CDT1 itself, so conserving the name would produce confusion in the cell cycle field. Based on TGME49_247040 protein function we decided to name this factor TgiRD1 – inhibitor of DNA and centrosome ReDuplication 1. We revisited our data, looked deeper into the protein structure, and adjusted our conclusions. Our new Figure S5 shows differences in the predicted folding of HsCDT1 and TgiRD1. We could not ignore the fact that TgiRD1 is phylogenetically related to CDT1 in ancestral branches and metazoans (Fig. 6B), but we identified substantial differences that may indicate a selective loss (or inheritance) of protein features. For example, TgiRD1 does not interact with ORCs that are critical for the licensing step, but TgiRD1 retained an MCM binding domain (winged helix-turn-helix) that plays a role in licensing and firing. Rather than CRL4Cdt2 degrons, TgiRD1 contains APC/C degrons that would be activated late in mitosis (similar to regulation of Geminin). Together with the lack of DNA licensing control in G1 and its opposing expression profile, we concluded that TgiRD1 represents a Cdt1-related protein that controls DNA and centrosome reduplication in S and G2 phases.

Minor comments:

1. For clarity, please include the number of replicates in the figure legends where appropriate. We added the requested information.

For microscopy/imaging, how were representative cells/images chosen? The representative images constituted the most common phenotype of the feature we aimed to highlight, and most are accompanied by quantifications.

In addition to the ELM analysis, the authors could also employ fold recognition software (such as Promal) to analyze 247040 structural models to show similarity to known protein structures.

We use a variety of folding prediction software, including AlphaFold2, PyMol, and template-based SWISS-PRO module to examine protein structures in our study, indicated in the text and figure legends. Our new TgiRD1 (former TgCdt1) analysis is based on an AlphaFold2 prediction (Fig. S5). All the software we used is listed in the M&M section.

Line 107: missing words "TgCdt1"

*We corrected the sentence.

*

Line 141: the interpretation that the C terminus is "unstable" is misleading if it is simply that the protein cannot tolerate a fusion to the C-terminus.

*We successfully incorporated a tag at the C-terminus (confirmed by sequencing across the recombinant gene) but could not detect protein expression. If our protein could not tolerate a recombinant tag, the transgenic parasites would not survive because TgCyc4 is essential protein. Therefore, since the parasites survived, we concluded that the lack of TgCyc4-AID-HA expression was due to native truncation at the C-tail (instability). *

Line 221: word choice "reminisced" We have changed the wording.

Line 348 refers to Orc4 expression in Figure 4A, but the data point is not labelled. Fig. 4A references GO group (DNA replication/licensing factors), and the raw data is included in Table S6, which is now indicated in the text.

Lines 407-8 and 510-11: Reference Fig 1E We added the reference.

Line 408: please define what is meant by "dominant interactor" We meant that TgiRD1 is the most prominent interactor of TgCrk4 and TgCyc4. To clarify the confusion, we changed the wording to “primary interactor”.

Reviewer #2 (Significance (Required)):

This manuscript makes great strides in defining apicomplexan cell cycle control and genome replication. These strides include defining a previously unrecognized G2/M checkpoint controlled by TgCrk4 and the novel TgCyc4. Further, the authors identify a binding partner and substrate of the novel Crk4/Cyc4 kinase complex, 247040 that acts as a repressor of replication.

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

Summary The present study Hawkins et al have described the important role of Cyclin-CDK complex in an apicomplexan parasite Toxoplasma(Tg) which exhibit binary mode of cell division like many other eukaryotes. In the apicomplexan field it is generally shown that G2 phase of cel cycle is either absent or has very little role. The authors here demonstrate that the combination of Tg CRK4 and Tg Cyclin4 works during the G2 phase of cell cycle such as chromosome rereplication and centrosome reduplication. In order to show the function of Cyclin-CRK function they used Auxin degradation system to down regulate or deplete the protein and study parasite growth during cell cycle as well as they used tagged parasite to identify the protein complex with these two molecules. In the study they showed that these two molecules Cyc4 and cRK4 formed the complex in protein pulldown method and show identical function in the cell cycle. In addition to thiese two proteins they also found another interacting partner Cdt1 that was further analysed to be involved in controlling Chromosome rereplication and centrosome. So overall the study is nicely performed and three molecules of Cyclin4-CRk4-Cdt1 and their role is illustrated in the binary mode of cell division in Toxoplasma.

Comments 1.Though no new experiments need to be performed but it will be good if some details are given as to which stage of tachyzoite cycle the protein complex were performed and if there is difference in the various phases of cell cycle especially the s phase and the M phase. Are these period changed. Since G2 is suppose to be absent in many apicomplexan do the authors suggest that G2 phase is only coupled to binary mode of cell division. Please discuss how it is then linked to the other part of cell cycle.

*You are correct, we propose that the presence of G2 phase is linked to binary division in apicomplexans and our hypothesis is supported by the overall evolution of the cell cycle (see Discussion section). We also entertained the hypothesis that G2 operates in multinuclear division since all apicomplexans encode TgiRD1 orthologs (please, see the Discussion section). For the first time, we identified the major functions of G2 functions (repression of the DNA and centrosome reduplication) in the apicomplexan cell cycle. However, given the unresolved organization of the Toxoplasma (or any apicomplexan) cell cycle, it is currently impossible to define the boundaries of G2. According to our study, TgCrk4 and TgCyc4 control G2/M transition or the end of G2 phase, and we still lack markers of G2 entry. In our comparative synchronization study (Fig 2), we uncovered the temporal link between G2/M and SAC regulatory points, which is discussed in the results section. *

Ganter et al have studied CRK4 in Plasmodium previously and they do find in their phosphoproteome study the similar association with the DNA replication machinery with CRK4 but no cyclin was identified in their study. In the cyclin study by Roques et al it has been shown that no cell cycle cyclins are found in Apicomplexan so can the author discuss more how these complex can be different in two apicomplexan species. They describe that Crk4 is novel cell cycle kinase though this has been studied earlier. Authors have almost not discussed these previous finding with respect to their in this study.

*We would like to clarify this confusion. We have not discussed Ganter et al. studies because PfCRK4 is not orthologous to TgCrk4, but rather it is related to TgCrk6. Unfortunately, the Plasmodium and Toxoplasma Crk nomenclature was published almost concurrently. Our previous (Alvarez & Suvorova, 2017) and current study show that Plasmodium and other apicomplexans that divide by multinuclear division do not encode TgCrk4 orthologs (and/or TgCyc4). Additionally, the mentioned studies by Roques and Ganter were released prior to newer genome annotations that include additional cyclin-domain proteins, including 10 Toxoplasma cyclins (5 new) that we categorized in our recent publication (Hawkins et al., 2022). Although the newly annotated cyclins are not related to conventional cell cycle cyclins, we had proven empirically that TgCyc1 together with TgCrk6 controls SAC, and now, the specific interaction of TgCyc4 with TgCrk4 controls G2 processes. Lastly, we call TgCrk4 “a novel” kinase only in the meaning that it is a novel cyclin-dependent kinase that is not related to known CDKs in other eukaryotes. The identification of TgCrk4 in our previous study (Alvarez & Suvorova, 2017) is described in the Introduction section and at the opening of the Results. *

The manuscript is too dense, in terms of both figures and text. At times loses the focus and hence can be organised with most important finding in the figure and text. Especially Fig2, Fig4 and Fig7. Fig5 does not give too much in terms of the real finding an in fact take away from the focus. Some parts of these figures can be simplified or moved to supplementary. Some of the figures in Fig2 and 7 are missing the scale bars.

We respectfully disagree with some conclusions made by the Reviewer. Our study contains ample material that is intended to guide the reader through the complexity of the Toxoplasma cell cycle and the intricate structures contained in the parasite. We have also introduced a few novel approaches that require additional schematics and dedicated discussions.

• Fig 2*. The G2/M block, as well as the G2 phase, had never been detected in apicomplexans. We created a new approach to determine the timing of the G2/M checkpoint, which involves comparison to a known cell cycle block. Panels A, B, and C provide visuals and summarize our findings. The main events are highlighted with arrows (Panel C), while graphs (panel B) show differences in responses. The rest of the figure is devoted to quantification of the primary events caused by TgCrk4 deficiency, since the G2 block had never been examined. While the U-ExM images of the entire vacuole (2-4 parasites) may seem overwhelming, they represent that the deficiency is consistent. *
• Fig 7* is devoted to the major Crk4/Cyc4 interactor TgiRD1 (former TgCdt1). This is one of the first mechanistic studies of central cell cycle regulators in Toxoplasma. This Cdt1-related protein was examined at the molecular level to support the main claims of its control of G2 Nevertheless, we moved two panels from Fig. 7 into the supplement. *
• 4* is organized as follows. Top row: panels A, B visualize the G2/M checkpoint block at the protein level. Middle row: panels C, D, and E represent the workflow to find TgCrk4 substrates. Bottom row: panels F, G highlight TgCrk4 substrates of interest that are discussed in the paper. *
• 5* is an in-depth analysis of the central cell cycle regulators across Apicomplexa phylum, a key figure of the study. Its comparative nature supports our main message: binary division is regulated by TgCrk4/TgCyc4, which are only expressed in a subgroup of apicomplexans that divide in a binary mode. *

May be bit more discussion of ORC in relation to their Cyclin-CRK complex as they did find upregulation of the ORC in their genome profiling. So may be instead of CDT1 these are more important in the licencing of DNA replication.

*Our choice to focus on Cdt1-related protein was driven by the fact this protein is a major component of the TgCrk4/TgCyc4 complex, while the ORCs act downstream (as TgCrk4 substrates). Shifting focus to ORCs opens an entire new project, which will be explored in the future. *

5 The model in Fig8B does not take Cyc4 into consideration and I feel is bit oversimplified as there are many factors that may be responsible for centrosome non separation. The S and G2 are no separated in the Cell cycle as given in this Fig.

Referring to comment 3, we focused on empirically supported, central findings and created the first model of centrosome cycle regulation in T. gondii. We intentionally drew focus to TgCrk4, which was extensively studied, while TgCyc4 received less attention due to difficulties in modulating its expression. We have used transcriptional downregulation to evaluate TgCyc4 (tet-OFF model), which is unfavorable for cell cycle studies because it exceeds the duration of the cell cycle. The unclear cell cycle borders are addressed in the introduction to this response. Briefly, the organization of apicomplexan cell cycle is currently unclear, thus most of the schematics are approximate.

It is not clear from the data with CDt1 if this linking the inner and outer centrocone or its down regulation breaks the bipartite centrosome. May be some reflection it will be useful.

*Our model suggests that both TgCrk4 and TgiRD1 (former TgCdt1) affect only the inner core of the centrosome, which we propose is comprised of two types of linkers. The arrows in Fig. 8 point specifically to the linkers whose stability depends on the expression of TgCrk4 or TgiRD1. *

Minor comments

I what is SAINT analysis as it is not described in methods.

*We added the description of our SAINT analysis to M&M.

*

How was budding quantified

*We supplemented the figure legend with the required information. *

Western blot can have predicted size

*Due to density of the figures, we did not supply the predicted MW of the proteins when they display the proper PAGE motility. *

what does red star mean in Blot 1C

*We added the description to the figure legend.

*

What does the number in Fig1H means please explain in the legends and same for Fig6F. In fig 1, removing the inhibition for 5 hours led to very less budding, but in fig 3, removing inhibition showed increased budding (50% in 2 hours). Please explain

*Please see our response to the reviewer 1 minor comment regarding Fig. 1H and 6F. *

*We presume that there is some confusion regarding figure numbers. Perhaps the Reviewer refers to Fig. 2B. Indeed, the 4h block at G2/M led to reduced budding (Fig. 2B), while release from the block for 2 hours (Fig. 3C, post-recovery) allows parasites to continue cell cycle progression and reach the next stage –budding. The numbers over the Fig. 3A, B, and C panels are from the plots in Fig. 2B to help give a comprehensive representation of the analyzed timepoint. *

Fig2 has no scale bars -please add- this figure is too dense. May be fig2A, B,C can be in supplementary, legend in the figure can be in the figure legend.

Please see our response to comment 3. We have included scale bars.

Also this figure2 H and I in not quoted in line 231. Also this figure2 has no panel J but goes directly from I to K

*The alphabetical order was corrected, and the reference added. *

Fig3 the FigG can be more relevant in the Figure 8 while describing about the Crk4 and Cyc4 and CDt1 in binary mode of cell division. Also please define what stars mean either in legend or methods section in terms of significance.

*Thank you for the suggestion. The Fig. 3G schematics summarize the overall findings of the Figure and acts as an intermediate conclusion in this study. We added the meaning of the stars in the M&M section. *

Line 107 the sentence is incomplete

We have corrected the sentence.

Line 217 may be the figure could be referred as then it is not cleat about the description.

Due to the density of the figures and well-established dynamics of the centrocone and basal rings, we included the reference to a publication rather than as a figure panel.

**Referees cross-commenting**

The study is quite rigrous and with analyses of CRK4-CYC4 and CDT. However it will be better if authors please revisit their conclusions on G2 phase of cell cycle in Toxoplasma based on their findings. The study will have important bearing on the community studying apicomplexan parasites and DNA replication as well as who work on eukaryotic cell cycle.

Reviewer #3 (Significance (Required)):

Significance In the manuscript by Hawkins etal have illustrated that in the apicomplexan parasite that have binary mode of cell division present a Cyclin-Crk complex with detailed analysis of Tg Crk4-Cyc4 that are novel in these group pf parasite infect humans and animal alike like malaria parasite and ones affecting cattle and chicken. So these finding are novel as very little is known about this interaction. The significant finding is to show how the G2 phase of cell cycle may be regulated in these parasites and how DNA licencing factor Cdt1 is highly divergent but part of this CRK-Cyclin complex.

So though it discusses more on the Toxoplasma but it may be of interest to the scientist working on eukaryotes with divergent mode of cell cycle.

General Assessment - The findings are novel but the manuscript is too dense and at time loses the focus. May be both text and Figures could be made less dense so that important finding are revealed in better way.

Advance - It does give important insight into the cell cycle in apicomplexan parasite and how even though there are no cell cycle cyclin in Apicomplexa. The findings here suggest how different complexes can substitute for the function. It does extend the knowledge in the field of Cell division in divergent parasites both in terms of mechanistic, functional and technical way.

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Reply to the reviewers

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

1. In this manuscript, Imoto et al. analyze the specific role of the Dynamin1 splice variant Dyn1xA in so-called ultrafast endocytosis, an important mechanism of synaptic vesicle recycling at synapses. In a previous publication (Imoto et al. Neuron 2022), some of the authors had shown that Dyn1xA, and not the other splice variant Dyn1xB, is essential for ultrafast endocytosis. Moreover, Dyn1xA forms clusters around the active zone for exocytosis and interacts with Syndapin 1 in a phosphorylation dependent manner. However, it was unclear which molecular interactions underlie the specific role of Dyn1xA. Here, the authors provide convincing evidence with pull down assays and CSP that Dyn1xA PRR interacts with EndophilinA1/2 with two binding sites. The first binding site lies in the part common to xA and xB, was previously characterized. The second site was previously uncharacterized, is specific for Dyn1xA, and is regulated by phosphorylation (phosphobox 2). The location of these splice variants and mutated forms at presynaptic sites correlate with the prediction made by the biochemical assays. Finally, the authors perform rescue experiments ('flash and freeze' and VGLUT1-pHluorin imaging experiments) to show that Dyn1xA-EndophilinA1/2 binding is important for ultrafast endocytosis. I find the results interesting, providing an important step in the understanding of the interplay between dynamin and the endocytic proteins interacting with it (endophilin, syndapin, amphiphysin) in the context of synaptic vesicle recycling. The manuscript is clearly written and for the most part the data supports the authors' conclusions (see specific comments below). However, there are some issues which need to be clarified before this manuscript is fully suitable for publication.

We thank the reviewer for noting the importance of our study. Indeed, our previous study has raised the question as to why only the Dyn1xA splice variant mediates ultrafast endocytosis, and our current manuscript now resolves this issue.

Introduction: the dynx1B Calcineurin binding motif is written PxIxIT consensus but actual sequence is PRITISDP. Is this a typo?

The sequence is correct. One thing we failed to mention is that the last amino acid in this motif can be either threonine or serine for calcineurin binding, as we demonstrated previously [Jing, et al., 2011 JBC; PMC3162388]. We have amended the text as follows.

1. calcineurin-binding motif (PxIxI[T/S]) 19.

Figure 1: the difference between the constructs used in panels C and D is not clear. In D, is it a truncation without residues 796 and 845? If so, it should be labelled clearly in the Western blots. In Panel E, Dyn1xA 746-798 should be labeled Dyn1x 746-798 because it is common to both splice variants.

We thank the reviewer for pointing this out. Both C and D used the full-length PRRs of Dyn1xA-746 to 864 and xB-746 to 851. To make the labeling clear, we changed Dyn1xA PRR to “Dyn1xA PRR (746-864)” and Dyn1xB PRR to “Dyn1xB PRR 746-851” in Figure 1. In the main text, we made the following changes.

1. 4: “To identify the potential isoform-selective binding partners, the full-length PRRs of Dyn1xA746-864 and xB746-851 (hereafter, Dyn1xA-PRR and Dyn1xB-PRR, respectively).”

Figure 1: For amphiphysin binding the authors write that "No difference in binding to Amphiphysin 1 was observed among these peptides (Figure1D-F)." They should write that Dyn1x 746-798 does not bind Amphiphysin1 SH3 domain, confirming the specificity of binding to the 833-838 motif.

We edited the sentence as suggested.

1. “Dyn1x 746-798 does not bind Amphiphysin1 SH3 domain (Figure 1G), confirming the specificity of binding to the 833-838 motif as reported in previous studies 29,30. (Figure 1D-F).”

Figure S2. The panels are way too small to see the shifts and the labelling. Please provide bigger panels

As suggested, we have now provided bigger panels in Figure S2, and amended the text and Figure legend accordingly.

We also removed Figure S2B as it was not referred to in the text in any way. (It was the reverse experiment – HSQCs of 15N-labelled SH3 titrated with unlabelled dynamin).l

Figure 2 panel B. There is a typo in the connecting line between the sequence and the CSP peaks. It is 846 instead of 864 (after 839).

Corrected.

Figure 3 panel E. In the text, the authors write that "Western blotting of the bound proteins from the R838A pull-down experiment showed that R838A almost abolished both Endophilin and Amphiphysin binding in xA806-864 (Figure 3D), and reduced Endophilin binding to xA-PRR (Figure 3E)." I think they should write "only slightly reduced Endophilin binding..." it is more faithful to the result and consistent with the conclusion that Endophilin A1 has two binding sites on Dyn1xA PRR.

We have now provided quantitative data for R838A and R846A (Fig. 3F and G). Endophilin binding is significantly reduced with R846A.

It is unclear why the R846A mutant affects binding of Dyn1xA 806-864 but not Dyn1xA-PRR-.

The reviewer asks why the R846A mutant affects binding of Dyn1xA 806-864, but not so much of Dyn1xA-PRR. The explanation is simply that there are two endophilin binding sites in Dyn1xA-PRR. The first is not present in the xA806-864 peptide, while both are present in Dyn1xA-PRR (the full length tail). When doing pull-down experiments, the binding tends to saturate – even when the second site is blocked by R846A. The first site is still able to bind, and the binding appears as normal. The same applies to the R838A mutant.

Moreover, it affects binding to endophilin as well as amphiphysin, and therefore it is not specific. It is thus not correct to write that "R846 is the only residue found to specifically regulate the Dyn1 interaction with Endophilin as a part of an SDE". In the Discussion (page 11), the authors refer to the R846A mutation as specifically affecting Endophilin binding. This should be toned down, as it also affects Amphiphysin binding. For this important point, the data on quantification of Endophilin binding should be presented.

The reviewer’s concern is about our claims of specificity of Endophilin A binding in Dyn1xA R846 mutation experiments. The reviewer is correct, and we have now defined specific parameters for those claims. Specifically, we have added new quantitative data from the Western blots in Fig 3E (full-length Dyn1aX-PRR) as Fig 3F-G. We used full-length Dyn1aX-PRR rather than the xA806-864 peptide because the subsequent transfection experiments use full length Dyn1xA. In the new figures 3F and 3G, we quantified Endophilin A, Amphiphysin and Syndapin1 amounts from the multiple Western blots such as Figure 3E (now n=14, 6 experiments, each in with 2-4 replicates for Dyn1xA PRR). R846A mutated in Dyn1xA-PRR significantly reduces the binding to Endophilin A, but it does not significantly affect the binding to Amphiphysin 1and Syndapin1 (Fig 3G). Therefore, this particular Dyn1xA-PRR mutation specifically affects Endophilin A binding, in the context of the full-length tail Dyn1aX-PRR. To make these results clear, we modified the text as below.

P7. “R838A and R846A caused smaller reductions in Endophilin binding compared to wild-type Dyn1xA-PRR, (Figure 3E, 3F, R838A, median 68.5 ; Figure 3G, R846A, median 59.3 % : R838A reduced the Dyn1/Amphiphysin interaction (Figure 3E, 3F, median 14.2 % binding compared to wild-type Dyn1xA-PRR). By contrast, R846A did not affect Amphiphysin and Syndapin binding to Dyn1xA-PRR (Figure 3E, 3G). Therefore, R846, being part of an SDE, is the only residue we found to specifically regulate the Dyn1 interaction with Endophilin in the context of the full length tail (DynxA-PRR)”.

Additionally, the reviewer notes that “the authors refer to the R846A mutation as specifically affecting Endophilin binding. This should be toned down, as it also affects Amphiphysin binding.” In the light of the above data and new quantitative analysis (Fig 3F-G), we have clarified the conclusion. However, to be clear that this statement is only correct in the context of the full-length DynxA-PRR, we amended texts as follows:

P7. “By contrast, R846A did not affect Amphiphysin and Syndapin binding to Dyn1xA-PRR (Figure 3E, 3G). Therefore, R846, being part of an SDE, is the only residue we found to specifically regulate the Dyn1 interaction with Endophilin in the context of the full length tail (DynxA-PRR)”.

New legends for Figure 3F and G have now been added as follows.

“(F) The binding of Endophilin A, and Amphiphysin 1 and Syndapin1 to Dyn1xA-PRR (wild type) or R838A mutant quantified from Western blots in (E). n=14 (6 experiments with 2-4 replicates in each). Median and 95% confidential intervals are shown. Kruskal-Wallis with Dunn’s multiple comparisons test (**p (G) The binding of Endophilin A, and Amphiphysin 1 and Syndapin1 to Dyn1xA-PRR (wild type) or R846A mutant quantified from Western blots in (E). n=14 (6 experiments with 2-4 replicates in each). Median and 95% confidential intervals are shown. Kruskal-Wallis with Dunn’s multiple comparisons test was applied (*p

Figure 3F-G (which are now 3H and 3I in the revised text): what do the star symbols represent in the graphs? I guess the abscissa represents retention time. Please write it clearly instead of a second ordinate for molecular mass, which does not make much sense if this reflects the estimate for the 3 conditions.

The “stars” are crosses (x) and represent individual data points. The figure legends have been updated for clarity. The reviewer is correct that the X-axis is retention time (min). The second Y-axis is needed to define the points in the curve marked with crosses (x’s). The legends for Figure 3H and I are now changed as follows.

“(H) SEC-MALS profiles for Dyn1xA alone (in green), Endophilin A SH3 alone (in red) and the complex of the two (in black) are plotted. The x-axis shows retention time. The left axis is the corresponding UV absorbance (280 nm) signals in solid lines, and the right axis shows the molar mass of each peak in crosses. The molecular weight of the complex was determined and tabulated in comparison with the predicted molecular weight. x represent individual data points.

(I) SEC-MALS profiles for a high concentration of Dyn1xA-PRR/Endophilin A SH3 complex (0.5 mg) (in dark blue) and a low concentration of Dyn1xA-PRR/endophilin A SH3 complex (0.167 mg) (in blue). The x-axis shows retention time. The left axis is the corresponding UV absorbance (280 nm) signals in solid lines, and the right axis shows the molar mass of each peak in crosses. The molecular weight of the complex was determined and tabulated in the table. x represent individual data points.”

Figure 4: The statement that "By contrast [to Dyn1xA], Endophilin A1 or A2 formed multiple clusters (1-5 clusters)" is not at all clear on the presented pictures. The authors should provide views of portions of axons with several varicosities, for the reader to appreciate the cases where there are more EndoA clusters than Dyn1 clusters.

In the revised Figure S4, we added additional STED images for a region of axons with more EndoA1/2 clusters than Dyn1xA clusters. The locations of Dyn1xA and EndoA1/2 clusters are annotated in each image based on the local maximum of intensity, which is determined using our custom Matlab analysis scripts (Imoto, et al., Neuron 2022; for the description of the methods, please refer to the Point #14 below). We also added Figure S3 to describe our analysis pipelines. In the Dyn1xA channel, outer contour indicates 50% of local maxima (boundary of Dyn1xA cluster) while inner contour indicates 70% of local maxima of the clusters. In the EndoA1/2 channel, local maxima of the clusters are indicated as points. To reflect these changes, we modified text as below.

P 9. “By contrast, Endophilin A1 or A2 formed multiple clusters (1-5 clusters) (Figure S4)”

The legends for Figure S4 are now as follows.

“Figure S4. Additional STED images for Figure 4.

(A) The top image shows an axon containing multiple boutons. Signals show overexpression of GFP-tagged Dyn1xA (Dyn1xA) and mCherry-tagged Endophilin A1 (EndoA1). The bottom images show magnifications of four boutons in the top image. Red hot look-up table (LUT) images on the right side of Dyn1xA and EndoA1 images are enhanced contrast images. Outer and inner contours represent 50% and 70% of local maxima of the Dyn1xA, respectively. Black circles represent local maxima of Endophilin A1. In these boutons, multiple EndophilinA1 puncta are present.

(B) The top image shows an axon congaing multiple boutons. Signals show overexpression of mCherry-tagged Dyn1xA (Dyn1xA) and GFP-tagged Endophilin A1 (EndoA1). The bottom images show magnifications of four boutons in the top image. Red hot LUT images on the right side of Dyn1xA and EndoA2 images are enhanced contrast images. Outer and inner contours represent 50% and 70% of local maxima of the Dyn1xA, respectively. Black circles represent local maxima of Endophilin A2. In these boutons, multiple EndophilinA2 puncta are present.

(C) STED micrographs of the same synapses as in Figure 4E with an active zone marker Bassoon (magenta) visualized by antibody staining. GFP-tagged Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A (green) are additionally stained with GFP-antibodies. Local maxima of Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A signals and minimum distance to the active zone boundary are indicated by dark blue lines.”

Moreover, overexpression of EndophilinA1/2-mCherry is not sufficient to assess its localization. Please consider either immunofluorescence or genome editing (e.g. Orange or TKIT techniques).

We agree with the reviewer that overexpression obscures the endogenous localization of proteins. To address this point in our previous publication, we titrated the amount of plasmids for Dyn1xA-GFP and transfected neurons just for 20 hours – this protocol allowed us to uncover the endogenous localization of Dyn1xA despite the fact that it was overexpressed in wild-type neurons (Imoto, et al., 2022). We also confirmed this localization by ORANGE-based CRISPR knock-in of GFP-tag in the endogenous locus of Dyn1 just after the exon 23 and confirm the true endogenous localization of Dyn1xA (Imoto, et al., 2022). Similar approaches were taken by the Chapman lab to localize Synaptotagmin-1 and Synaptobrevin 2 in axons (Watson et al, 2023, eLife, PMID: 36729040). We did not emphasize this in the first submission, but we took the same approach for the EndoA1/2 localization. This does not mean that they also unmask the endogenous localization, and the reviewer is correct that additional evidence would strengthen the data here. Thus, as suggested, we have looked at the endogenous EndophilinA1 localization by antibody staining. As the reviewer is likely aware, EndophilinA1 also localizes to other places including dendrites and postsynaptic terminals, making it difficult to analyze the data. However, we observe colocalization of Dyn1xA with endogenous EndoA1. Thus, we believe that our major conclusion here drawn based on EndoA1/2-mCherry overexpression is valid (Reviewer’s Figure 1). Since the Endophilin signals in neighboring processes obscures its localization in synapses-of-interest, repeating this localization experiments with ORANGE-based knock-in would be ideal. However, with the lead author starting his own group and many validations needed to confirm the knock-in results, this experiment would require us at least 4-6 months, and thus, it is beyond the scope of our current study. We will follow up on this localization in the near future, but given that endophilin is required for ultrafast endocytosis (Watanabe, et al., Neuron 2018, PMID: 29953872) and these proteins need to be in condensates at the endocytic sites for accelerating the kinetics of endocytosis (Imoto, et al., Neuron 2022, PMID: 35809574), we are confident that endogenous

EndoA1/2 are localized with Dyn1xA.

The analysis of the confocal microscopy data is not explained. How is the number of clusters determined? How far apart are they? Confocal microscopy may not have the resolution to distinguish clusters within a synapse.

We apologize for the insufficient description of the method. We had provided a more thorough description of the methods in our previous publication (Imoto, et al., Neuron 2022, PMID: 35809574). To make this more automated, we improved our custom Matlab scripts. Please note that all the analysis for the cluster location is performed on STED images, not on normal confocal images. To determine the cluster, first, presynaptic regions (based on Bassoon signals or Dyn1xA signals within boutons) in each STED image are cropped with 900 by 900 nm (regions-of-interest) ROIs. Then, our Matlab scripts calculate the local maxima of fluorescence intensity within the ROIs. To determine the distance between the active zone and the Dyn1xA or EndoA1/2 clusters, the Matlab scripts perform the same local maxima calculations in both channels and make contours at 50% intensity of the local maxima. The minimum distance reflects the shortest distance between the active zone and Dyn1xA/EndoA1/2 contours. To make these points clearer, we modified the main text and the Methods section. In addition, we have added workflow of these analysis as Figure S3.

P9. Main. “Signals of these proteins are acquired by STED microscopy and analyzed by custom MATLAB scripts, similarly to our previous work23.”

P20. Methods. “All the cluster distance measurements are performed on STED images. For the measurements, a custom MATLAB code package23 was modified using GPT-4 (OpenAI) to perform semi-automated image segmentation and analysis of the endocytic protein distribution relative to the active zone marked by Bassoon or relative to Dyn1xA cluster in STED images. First, the STED images were blurred with a Gaussian filter with radius of 1.2 pixels to reduce the Poisson noise and then deconvoluted twice using the built-in deconvblind function: the initial point spread function (PSF) input is measured from the unspecific antibodies in the STED images. The second PSF (enhanced PSF) input is chosen as the returned PSF from the initial run of blind deconvolution62. The enhanced PSF was used to deconvolute the STED images to be analyzed. Each time, 10 iterations were performed. All presynaptic boutons in each deconvoluted image were selected within 3030-pixel (0.81 mm2) ROIs based on the varicosity shape and bassoon or Dyn1xA signals. The boundary of active zone or Dyn1xA puncta was identified as the contour that represents half of the intensity of each local maxima in the Bassoon channel. The Dyn1xA clusters and Endophilin A clusters were picked by calculating pixels of local maxima. The distances between the Dyn1xA cluster and active zone boundary or Endophilin A clusters were automatically calculated correspondingly. For the distance measurement, MATLAB distance2curve function (John D'Errico 2024, MATLAB Central File Exchange) first calculated the distance between the local maxima pixel and all the points on the contour of the active zone or Dyn1xA cluster boundary. Next, the shortest distance was selected as the minimum distance. Signals over crossing the ROIs and the Bassoon signals outside of the transfected neurons were excluded from the analysis. The MATLAB scripts are available by request.”

In the legend of Figure S3,

“Protein localization in presynapses is determined by semi-automated MATLAB scripts (see Methods).

(A) Series of deconvoluted STED images are segmented to obtain 50-100 presynapse ROIs in each condition.

(B) Two representations of the MATLAB analysis interface are shown. The first channel (ch1, green) is processed to identify the pixels of local maxima within this channel. The second channel (ch2, magenta) is normally an active zone protein, Bassoon. Active zone boundary is determined by the contour generated at 50% intensity of the local maxima of ch2. The contours outside of the transfected neurons are manually selected on the interface and excluded from the analysis. Minimum distances from each pixel of the local maxima in ch1 to the contour in ch2 are calculated and shown in the composite image. The plot “Distance distribution” shows all the minimum distance identified in this presynapses ROI (unit of the y axis is nanometer). The plot “Accumulated distance distribution” shows the accumulated distance distribution from the initial to the current presynapses ROI. The plot “Histogram of total intensity” shows the intensity counts around individual local maxima pixels in ch1.”

For the STED microscopy, a representation of the processed image (after deconvolution) and the localization of the peaks would be important to assess the measurement of distances. If Dyn1xA S851/857D is more diffuse, are there still peaks to measure for every synapse?

We thank the reviewer for bringing up this important question. In Figure S4C, we have added the position of the local maxima of wild-type and mutant Dyn1xA shown in the main Figure 4E. As the reviewer pointed out, when a protein is more diffuse, it is difficult to find the peak intensity by STED. However, since these proteins are still found at a higher density within a very confined space of a presynapse and synapses are packed with organelles like synaptic vesicles and macromolecules, signals from even diffuse proteins can be detected as clusters, and local maxima can be detected in these images.

To illustrate this point better, we added Reviewer’s Figure 2 below. In this experiment, we transfected neurons with a typical amount of plasmids (2.0 µg/well) or ~10x lower amount (0.25 µg/well). When the density of cytosolic proteins is high (Reviewer’s Figure 2A), the depletion laser has to be strong enough to induce sufficient stimulated emission and resolve protein localization. Insufficient power would produce low resolution images, leading to inappropriate detection of the local maxima (Reviewer’s Figure 1A). Thus, we set our excitation and depletion laser powers to resolve the protein localization to ~40-80 nm at presynapses. Furthermore, to avoid mislocalization of proteins due to the overexpression, we use 0.25-0.5 ug/well (in 12-well plate) of plasmid DNA for transfection, which is around 10 times lower than the amount used in the typical lipofectamine neuronal transfection protocol (Imoto, et al., Neuron 2022). We also change the medium around 20 hours after the transfection instead of the typical 48 hours (Imoto, et al., Neuron 2022). With these modifications and settings, we can obtain the location of the local maxima of the diffuse signals (Reviewer’s Figure 1B and Figure 4E and Figure S4). We modified the Method section to make these points clearer.

P 17, “Briefly, plasmids were mixed well with 2 µl Lipofectamine in 100 µl Neurobasal media and incubated for 20 min. For Dyn1xA and Endophilin A expressions, 0.5 µg of constructs were used to reduce the overexpression artifacts23. The plasmid mixture was added to each well with 1 ml of fresh Neurobasal media supplemented with 2 mM GlutaMax and 2% B27. After 4 hours, the medium was replaced with the pre-warmed conditioned media. To prevent too much expression of proteins, neurons were transfected for less than 20 hours and fixed for imaging.”

P 20, “Quality of the STED images are examined by comparing the confocal and STED images and measuring the size of signals at synapses and PSF (non-specific signals from antibodies).”

Legends for Figure S4C,

“(C) STED micrographs of the synapses shown in Figure 4F with an active zone marker Bassoon (magenta). GFP-tagged Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A are visualized by antibody staining of GFP (green). Local maxima of Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A signals and minimum distance to the active zone boundary are overlaid.”

Figures 5 and 6: No specific comment. The data and its analysis are very nice and elegant. The comment on the lack of rescue of Dyn1xA on endosome maturation may be a bit overstated, because many "controls" (shRNA control Figure S5 or Dyn3 KO in Imoto et al. 2022) have a significant number of endosomes 10 s after stimulation.

We thank the reviewer for noting the strength of our data and pointing out this issue on endosomal resolution. In particular, the reviewer is concerned about our interpretation of the ferritin positive endosomes present at 10 s in time-resolved electron microscopy experiments. Indeed, the number of ferritin positive endosomes in Dyn1 KO, Dyn1xA OEx neurons (0.1/profile) is similar to the control conditions: scramble shRNA control (0.1/profile, Figure S5) and Dyn3KO neurons (0.2/profile) in our previous study (Imoto et al. 2022). Although we do not consider Dyn3 KO as a control, given the presence of abnormal endosomal structures, we agree with the reviewer that scramble shRNA control in Figure S5 does indicate that some ferritin-positive endosomes even at 10 s after stimulation. We would like to note that this result is in stark contrast to our previous studies where we observed the number of ferritin positive endosomes returning to the basal level in both wild-type neurons and many scramble shRNA controls (Watanabe et al. 2014, 2018, Imoto et al 2022). Thus, the majority of the data we have indicate that the number of ferritin positive endosomes returns to basal level by 10 s, suggesting that endosomes are typically resolved into synaptic vesicles by this time. However, given that we do not know the nature of the inconsistency here and we cannot exclude the possibility of overexpression artifact of Dyn1xA as an alternative, we changed the following lines.

P. 10, “Interestingly, the number of ferritin-positive endosomes did not return to the baseline (Figure 5E, F) as in previous studies3,35,36, suggesting that Dyn1xA may not fully rescue the knockout phenotypes or that overexpression of Dyn1xA causes abnormal endosomal morphology.”

By the way, why did the authors use Dyn1 KO in this study, and not Dyn1,3 DKO as in Imoto et al. 2022?

This is simply because Dyn3KO displayed an endosomal defect in our previous study (Imoto et al 2022), and we wanted to focus on endocytic phenotypes of Dyn1 KO and mutant rescues in this study.

In the Discussion, the authors present the binding sites (for endophilin and amphiphysin SH3 domains) as independent. However, these proteins form dimers or even multimers as they cluster around the neck of a forming vesicle. Even though they provide evidence in vitro (Figure 3) that in these conditions of high concentration one dyn1xA-PRR binds one SH3 domain, in cells multiple binding sites on the PRR to these proteins may involve avidity effects, as discussed for example in Rosendale et al. 2019 doi 10.1038/s41467-019-12434-9. For example, the high affinity binding of Dyn1-PRR to amphiphysin cannot be explained only by the sequence 830-838.

The reviewer suggests “In the Discussion, the authors present the binding sites (for endophilin and amphiphysin SH3 domains) as independent.” However, we do not claim these interactions are functionally independent, except in the context of in vitro experiments where they are sequence-independent.

They also suggest “However, these proteins form dimers or even multimers as they cluster around the neck of a forming vesicle”. However we do not agree with this in the context of our Discussion, because the evidence of multimers and clustering is convincing but is entirely in vitro data.

Thirdly they comment that “For example, the high affinity binding of Dyn1-PRR to amphiphysin cannot be explained only by the sequence 830-838.” We fully agree with the statement and felt we had addressed this in the manuscript. To explain, it’s important to point out our relatively new concept here and previously reported by us (Lin Luo et al 2016, PMID: 26893375) of the existence and importance of SDE and LDE for SH3 domains (Endophilin here, syndapin in our previous report). These elements act at a distance from the so-called core PxxP motifs and they provide much higher affinity and specificity than the core region alone. We had further mentioned this in the p11 discussion “Although this is a previously characterized binding site for Amphiphysin and is also present in Dyn1xB-PRR, the extended C-terminal tail of Dyn1xA contains short and long distance elements (SDE and LDE) essential for Endophilin binding, making it higher affinity for Endophilin.” Because the NMR identified F862 as a chemical shift for dynamin, we performed a pulldown with this mutant in the xA746-798 construct (which only contains the higher affinity site) and found that indeed “.F862A reduced Endophilin binding 29% (pOverall, the reviewer correctly points out that “multiple binding sites on the PRR to these proteins may involve avidity effects*” could play a role in vivo. We agree that avidity is an additional possibility, not examined in our study. Therefore, as suggested, we added the following sentence to the discussion on the SDE and LDE impacts.

P. 11. “Our pull-down results showed that R846A abolished endophilin binding to xA806-864 (which contains only the second and higher affinity binding site and the associated SDE (A839) and LDE (F862)) and reduced about 40% of endophilin binding to the Dyn1xA-PRR (which contains both binding sites) without affecting its interaction with Amphiphysin, providing important partner specificity, although we cannot exclude the possibility that avidity effects may additionally come in play in vivo 42

Reviewer #1 (Significance (Required)):

This study provides a significant advance on the mechanisms of dynamin recruitment to endocytic zones in presynaptic terminals. The work adds a significant step by experienced labs (Robinson, Watanabe) who have provided important insight in the mechanisms by many publications in the last years.

We thank the reviewer for the careful read of our manuscript and positive outlook of our work.

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

1. This is a compelling study that reports a key discovery to understand the molecular mechanism of ultrafast endocytosis. The authors demonstrate that the Dynamin splice version 1xA (Dynamin 1xA) uniquely binds Endophilin A, in contrast to Dynamin splice version 1xB (Dynamin 1xB) that does not bind Endophilin A and it is not required for ultrafast endocytosis. In addition, the Endophilin A binding occurs in a dephosphorylation-regulated manner. The study is carefully carried out and it is based on high quality data obtained by means of advanced biochemical methodologies, state-of-art flash-freezing electron microscopy analysis, superresolution microscopy and dynamic imaging of exo-and endocytosis in neuronal cultures. The results convincingly support the conclusions.

We thank the reviewer for supporting the conclusions of our study.

1. Although additional experiments are not essential to support the claims of the paper there is room, however, for improvement within the pHluorin experiments. These experiments, that are clearly informative and consistent with the rest of experimental data, do not apply the useful approach to separate endo- from exocytosis. The use of bafilomycin or folimycin to block the vesicular proton pump allows the unmasking the endocytosis that is occurring during the stimulus, that should correspond to ultrafast endocytosis. It would be very elegant to demonstrate that such a component, as expected according to the electron microscopy data, requires the binding of Endophilin A to Dynamin 1xA. If the authors have the pHluorin experiments running, the suggested experiments are very much doable because the reagents and the methodology is already in place and the new data could be generated in around six weeks.

We thank the reviewer for the suggestion. The reviewer is concerned that vGlut1 pHluorin experiment in Figure 6 may not correspond to ultrafast endocytosis. We agree that bafilomycin/folimycin treatment will reveal the amount of endocytosis that takes place while neurons are stimulated. However, we are not certain that endocytosis during this phase would fully correspond to ultrafast endocytosis because reacidification of endocytosed vesicles typically takes 3-4 s (Atluri and Ryan, 2006, PMID: 16495458; although see https://elifesciences.org/articles/36097) and thus, the nature of endocytosis cannot be fully determined by this assay. To claim that endocytosis measured by pHluorin assay during stimulation all correspond to ultrafast endocytosis, we would need to perform very careful work to track single pHluorin molecules at the ultrastructural level and corelate their internalization to pHluorin signals. Perhaps, a rapid acid quench technique used by the Haucke group would also be appropriate to estimate the amount of ultrafast endocytosis (Soykan et al. 2017 PMID: 28231467), but we are not set up to perform such experiments here. Also, our lead author, Yuuta Imoto, is leaving the lab to start up his own group, and it will take us months rather than weeks to get the requested experiments done. Since the point of this experiment was to test whether the interaction of Dyn1xA and EndoA is essential for protein retrieval regardless of the actual mechanisms and the reviewer acknowledges that this point is sufficiently supported by the experiments, we will set this experiment as the priority for the next paper.

Instead of the bafilomycin or rapid acid quenching experiments, we have now added data from vglut1-pHluorin experiment with a single action potential. With a single action potential, all synaptic vesicle recycling is mediated by ultrafast endocytosis in these neurons (Watanabe et al, 2013 PMID: 24305055; Watanabe et al. 2014, PMID: 25296249). Our electron microscopy experiments in Figure 5 is also performed with a single action potential. As with 10 action potentials, 20 Hz experiments, re-acidification of vglut1-pHluorin is blocked when Dyn1 and EndophilinA1 interaction is disrupted (Figure 6 F-I). We added a description of this result as below.

P 11. “Similar defects were observed when the experiments were repeated with a single action potential – synaptic vesicle recycling is mediated by ultrafast endocytosis with this stimulation paradigm25 (S851/857 recovery is 73.3% above the baseline; R846A, recovery is 30.0% above the baseline) (Figure S9 A-D). Together, these results suggest that the 20 amino acid extension of Dyn1xA is important for recycling of synaptic vesicle proteins mediated by specific phosphorylation and Endophilin binding sites within the extension.”

The methods are carefully explained. Some of the experiments are only replicated in two cultures and the authors should justify the reasons to convince the audience that the approaches used have enough low variability for not increasing the n number. The pHluorin experiments, however, are performed only in a single culture; they should replicate these experiments in at least 3 different cultures (three different mice).

The reviewer is correct. The variability is very low in our ultrastructural studies and STED imaging, and thus, in all our previous publications, two independent cultures are used. We do agree that in the ideal case, we would like to have three independent cultures, but given the nature of ultrastructural studies (control, mutants, and multiple time points), triplicating the data would add another year to our work. We are currently developing AI-based segmentation analysis, and once this pipeline is established, we will be able to increase N. However, please note that for these experiments, we examine around 200 synapses from each condition in electron microscopy studies (Table S2)– these numbers are far more than the gold standard in the field. Likewise, 50-100 synapses are examined for STED experiments (Table S2). To examine variability of our analysis results, we compared a significance between the dataset using cumulative curves and Kolmogorov–Smirnov test (Figure S11). As shown in the summarized data and p value in each condition, there are no significant difference between the datasets.

For pHluorin analysis, the reviewer is correct. We repeated the experiments twice to increase the N after the initial submission. The data are consistent, and the conclusions are not changed by the additional experiments (Figure 6 and Figure S9). We also changed the Statistical analysis section in Methods as below.

P. 19. “All electron microscopy data are pooled from multiple experiments after examined on a per-experiment basis (with all freezing on the same day); none of the pooled data show significant deviation from each replicate (Table S2).”

p 19, “All fluorescence microscopy data were first examined on a per-experiment basis. For Figure 4, the data were pooled; none of the pooled data show significant deviation from each replicate (Figure S11 and Table S2). Sample sizes were 2 independent cultures, at least 50-100 synapses from 4 different neurons in each condition..”

Legends for Figure S11

Figure S11. Data variability in Figure 4.

Cumulative curves are made from each dataset of (A) distance of Endophilin A1 puncta from the edge of Dyn1xA puncta, (B) distance of Endophilin A2 puncta from the edge of Dyn1xA puncta, distance distribution of Dyn1xA from active zone edge in (C) neurons expressing wild-type Dyn1xA-GFP, (D) Dyn1xA-S851/857-GFP and (E) Dyn1xA-R846-GFP. n > 4 coverslips from 2 independent cultures. Kolmogorov–Smirnov (KS) test, p values are indicated in each plot.

Minor comments: 4. Prior studies referenced appropriately and the text and figures are clear and accurate.

We thank the reviewer for the careful read of our manuscript.

The authors should discuss about the mediators (enzymes) responsible for dephosphorylation of phosphor-box 2 that is key for the Dynamin 1xa-Endophilin A interaction.

We thank the reviewer for the suggestion. We added a discussion on a potential mediator, Dyrk1, as below.

P. 12. ”What are the kinases that regulate Dyn1? The phosphorylation of phosphobox-1 is mediated by Glycogen synthase kinase-3 beta (GSK3ß) and Cyclin-dependent kinase 5 (CDK5)17, while phosphobox-2 is likely phosphorylated by Trisomy 21-linked dual-specificity tyrosine phosphorylation-regulated kinase 1A (Mnb/Dyrk1)44,45 since Ser851 in phosphobox-2 is shown to be phosphorylated by Mnb/Dyrk1 in vitro32. Furthermore, overexpression of Mnb/Dyrk1 in cultured hippocampal neurons causes slowing down the retrieval of a synaptic vesicle protein vGlut146. Consistently, our data showed that phosphomimetic mutations in phosphobox-2 results disruption of Dyn1xA localization, perturbation of ultrafast endocytosis, and slower kinetics of vGlut1 retrieval. However, how these kinases interplay to regulate the interaction of Dyn1xA, Syndapin1 and Endophilin A1 for ultrafast endocytosis is unknown.”

It would be very helpful to include a final cartoon depicting the key protein-protein interactions regulated by dephosphorylation (activity) and the sequence of molecular events that leads to ultrafast endocytosis

As suggested, we made a model figure, (new Figure 7) showing how Dyn1xA and its interaction with EndoA and Syndapin1 increases the kinetics of endocytosis at synapses. Regarding the sequence of molecular events, we think that there are already dephosphorylated fraction of Dyn1xA molecules sitting on the endocytic zone at the resting state and they mediate ultrafast endocytosis. However, it is equally possible that activity-dependent dephosphorylation of Dyn1xA also may play a role (Jing et al. 2011, PMID: 21730063). However, we have no evidence about the sequence of activity dependent modulation of Dyn1xA and its binding partners during ultrafast endocytosis yet. This is much beyond what we have reported in this work and therefore, excluded from the model figure. We added the following to the end of the discussion:

p13, “Nonetheless, these results suggest that Dyn1xA long C-terminal extension allows multivalent interaction with endocytic proteins and that the high affinity interaction with Endophilin A1 permits phospho-regulation of their interaction and defines its function at synapses (Figure S7)”.

Figure legend Figure 7,

“Figure 7. Schematics depicting how specific isoforms Dyn1xA and Endophilin A mediate ultrafast endocytosis.

A splice variant of dynamin 1, Dyn1xA, but not other isoforms/variants can mediate ultrafast endocytosis. (A) Dyn1xA has 20 amino acid extension which introduces a new high affinity Endophilin A1 binding site. Three amino acids, R846 at the splice site boundary, S851 and S857, act as long-distance element which can enhance affinity of proline rich motifs (PRM) to SH3 motif from outside of the PRM core sequence PxxP. (B) At a resting state, Dyn1xA accumulates at endocytic zone with SH3 containing BAR protein Syndapin 123 and Endophilin A1/2. When phosphobox-1 (Syndapin1 binding) and phosphobox-2 (Endophilin A1/2 binding, around S851/S857) within Dyn1xA PRD are phosphorylated, these proteins are diffuse within the cytoplasm. A dephosphorylated fraction of Dyn1xA molecules can interact with these BAR domain proteins. Loss of interactions including Dyn1xA-R846A or -S851/857D mutations, disrupts endocytic zone pre-accumulations. Consequently, ultrafast endocytosis fails.”

Reviewer #2 (Significance (Required)):

This is a remarkable and important advance in the field of endocytosis. The study reports a key discovery to understand the molecular mechanism of ultrafast endocytosis. Scientist interested in synaptic function and the general audience of cell biologist interested in membrane trafficking will very much value this study. The mechanism reported will potentially be included in textbooks in the near future.

My field of expertise includes molecular mechanisms of presynaptic function and membrane trafficking.

I have not enough experience to evaluate the quality of the NMR experiments, however, I do not have any problem at all with, in my opinion, elegant results reported.

We thank the reviewer for the positive outlook of our manuscript.

Reviewer #1 (Public Review):

Summary:

Hippo pathway activity is required for pancreas morphogenesis, but its role in endocrine pancreas function remains elusive. The author aims to study the function of the TEAD1 gene in b-cells.

Strengths:

The authors generated TEAD1 conditional knockout animals by crossing the TEAD1f/f mice with three Cre strains (RIP-Cre, Ins1-Cre, and MIP-CreERT). In all of them, the KO animals showed progressive loss of insulin secretion with normal beta cell mass. Further characterization of the animals indicated glucose-induced insulin secretion defect and increased beta cell proliferation rate. RNA-Seq and ChIP-Seq experiments identified Pdx1, MafA, and Glut2, etc. as direct targets of TEAD1, which might be responsible for the insulin secretion defect in the animals. Of interest, the authors also uncovered the cell cycle-related gene p16 as a direct target of TEAD1. Reduction of p16 is likely to drive the beta cell proliferation in the TEAD1 knockout model. Thus, they proposed that TEAD1 is a regulator of the proliferative quiescence process in beta cells. Overall, the evidence provided by the authors is highly relevant and supports their conclusion.

Weaknesses:

(1) The authors don't explicitly mention that some results appeared in a previous publication (https://doi.org/10.1093/nar/gkac1063) from them.

(2) The authors begin their story by introducing TEAD1 as part of the Hippo pathway. They showed Taz expression data in Figure 1. Did they do any experiments to detect Taz in their TEAD1 model? Did the authors detect any expression changes in CTGF following TEAD1 knockout? I could not see this changed. The phenotype characterization data presented here contrasts with what has been shown in TAZ b-cell knockout mice (https://doi.org/10.1101/2022.05.31.494216). Based on the data presented here, Hippo is not involved, which should at least be discussed in length.

(3) Figure 1B - TAZ staining looks different in the three-month age group.

(4) TEAD ChIP-seq data doesn't look very convincing to me. It's hard to tell whether those highlighted regions in Figures 3A and 5J were signals or background noise. Although the authors also performed ChIP-qPCR in MIN6, it's unclear whether these binding events occur in vivo. The analysis of ChIP-seq dataset is limited as well. How many peaks called? What proportion of differentially expressed genes are bound by TEAD1? Was TEAD1 also detectable at NGN3 and NEUROD1 gene regions? If acquiring enough cells is not possible, the authors could try CUT&RUN or CUT&Tag to improve the data quality.

(5) The authors should perform RNA-seq or gene expression studies in MIP-CreERT to confirm, which could help narrow down the actual targets of TEAD1 as well.

(6) Figure 6 - the experiment lacks a control: Ezh2 beta cell KO. In addition to p16, Ezh2, and PRC2 have other targets in beta-cells, the authors could not rule out the contribution of those to the phenotype, so the implication of this experiment is vague.

Reviewer #1 (Public Review):

Summary:

Ewing sarcoma is an aggressive pediatric cancer driven by the EWS-FLI oncogene. Ewing sarcoma cells are addicted to this chimeric transcription factor, which represents a strong therapeutic vulnerability. Unfortunately, targeting EWS-FLI has proven to be very difficult, and a better understanding of how this chimeric transcription factor works is critical to achieving this goal. Towards this perspective, the group had previously identified a DBD-𝛼4 helix (DBD) in FLI that appears to be necessary to mediate EWS-FLI transcriptomic activity. Here, the authors used multi-omic approaches, including CUT&tag, RNAseq, and MicroC to investigate the impact of this DBD domain. Importantly, these experiments were performed in the A673 Ewing sarcoma model where endogenous EWS-FLI was silenced, and EWS-FLI-DBD proficient or deficient isoforms were re-expressed (isogenic context). They found that the DBD domain is key to mediating EWS-FLI cis activity (at msat) and to generating the formation of specific TADs. Furthermore, cells expressing DBD-deficient EWS-FLI display very poor colony-forming capacity, highlighting that targeting this domain may lead to therapeutic perspectives.

Strengths:

The group has strong expertise in Ewing sarcoma genetics and epigenetics and also in using and analyzing this model (Theisen et al., 2019; Boone et al., 2021; Showpnil et al., 2022).

They aim at better understanding how EWS-FLI mediated its oncogenic activity, which is critical to eventually identifying novel therapies against this aggressive cancer.

They use the most recent state-of-the-art omics methods to investigate transcriptome, epigenetics, and genome conformation methods. In particular, Micro-C enables achieving up to 1kb resolved 3D chromatin structures, making it possible to investigate a large number of TADs and sub-TADs structures where EWS-FLI1 mediates its oncogenic activity.

They performed all their experiments in an Ewing sarcoma genetic background (A673 cells) which circumvents bias from previously reported approaches when working in non-orthologous cell models using similar approaches.

Weaknesses:

The main weakness comes from the poor reproducibility of Micro-C data. Indeed, it appears that the distances/clustering observed between replicates are typically similar or even larger than between biological conditions. For instance, in Figure 1B, I do not see any clustering when considering DBD1, DBD2, DBD+1, DBD+2.

Lanes 80-83: "KD replicates clustered together with DBD replicate 1 on both axes and with DBD replicate 2 on the y-axis. DBD+ replicates, on the other hand, clustered away from both KD and DBD replicates. These observations suggest that the global chromatin structure of DBD replicates is more similar to KD than DBD+ replicates."

When replacing DBD replicate 1 with DBD replicate 2, their statement would not be true anymore.

Additional replicates to clarify this aspect seem absolutely necessary since those data are paving the way for the entire manuscript.

Similarly:<br /> - In Figure 1C, how would the result look when comparing DBD2/KD2/DBD+2? Same when comparing DBD 1 with KD1 and DBD+1. Would the difference go in the same direction?<br /> - Figure 1D-E. How would these plots look like when comparing each replicate to each other's? How much difference would be observed when comparing, for instance, DBD1/DBD2 ? or DBD1/DBD+1?<br /> - Figure 2: again, how would these analyses look like when performing the analysis with only DBD1/DBD+1/KD1 or DBD2/DBD+2/KD?

Another major question is the stability of EWS-FLI DBD vs EWS-FLI DBD+ proteins. Indeed, it seems that they have more FLAG (i.e., EWS-FLI) peaks in the DBD+ condition compared to the DBD condition (Figure 2B). In the WB, FLAG intensities seem also higher (2/3 replicates) in DBD+ condition compared to the DBD condition (Figure S1B).

Would it be possible that DBD+ is just more expressed or more stable than DBD? The higher stability of the re-expressed DBD+ could also partially explain their results independently of the 3D conformational change. In other words, can they exclude that DBD+ and DBD binding are not related to their respective protein stability or their global re-expression levels?

Surprisingly, WB FLI bands in DBD+ conditions are systematically (3/3 replicates) fainter than in DBD conditions (Figure S1B). How do the authors explain these opposite results between FLI and FALG in the WB?

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Reply to the reviewers

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

Summary Maintenance of the histone H3 variant CENP-A at centromeres is necessary for proper kinetochore assembly and correct chromosome segregation. The Mis18 complex recruits the CENP-A chaperone HJURP to centromeres to facilitate CENP-A replenishment. Here the authors characterise the Mis18 complex using hybrid structural biology, and determine complex interface separation-of-function mutants.

Major Comments The SAXS and EM data on the full-length Mis18 components must be included in the main Figures, either as an additional figure or by merging/rearranging the existing figures. The authors discuss these results in three whole paragraphs, which are a very important part of the paper.

We thank the reviewer for this constructive suggestion. We have now included an additional figure (new Fig. 2, attached below), that highlights the fit of the integrative model against the SAXS and EM data.

Could the authors also compare the theoretical SAXS scattering curves generated by their final model(s) with the experimental SAXS curves? This would provide some additional evidence for the overall shape of their complex model beyond the consistency with the Dmax/Rg.

We acknowledge the importance of this suggestion. We have now compared the theoretical SAXS scattering curve of the Mis18a/b core complex (named Mis18a/b DN), which lacks the flexible elements (disordered regions and the helical region flexibility connected to the Yippee domains). The theoretically calculated SAXS scattering curve of the model matches nicely with the experimental data with c2 value of 1.36. This data is now included in new Fig. 2 (Fig. 2f) and is referenced on page 9 line 21.

Minor Comments

While the introduction is clearly written, an additional cartoon schematic, representing the system/question would be helpful to a non-specialist reader to interpret the context of the study.

We have now included a cartoon in the revised Fig. 1 to support the introduction on centromere maintenance and the central role of the Mis18a/b/BP1 complex in this process. Please find the new Fig. 1 below.

No doubt the authors had a reason for choosing their figure allocation, but I wonder if more material couldn't be brought from the supplementary into the main figures?

As addressed in our response to one of the major comments, we have now moved key CLMS, SAXS and EM data from the supplemental figure into the main figure, new Fig. 2.

Page 6 "Mis18-alpha possesses an additional alpha-helical domain" - please make it clear in addition to what (I assume it's in addition to Mis18-beta).

Apologies for the lack of clarity. We have now rephrased this sentence to highlight that this difference is in comparison with Mis18b on page 6 line 15.

Page 7 - Report the RMSD of the Pombe vs. Human Mis18-alpha yipee structures?

The S. pombe Mis18 Yippee structure superposes on to the Human Mis18a Yippee domain with an RMSD of 0.92 angstroms with is now mentioned on page 7 line 9.

Page 7 - "We generated high-confidence structural models...." is there a metric for the confidence as reported by RaptorX? Perhaps includinging the PAE plots in the supplementary for the AlphaFold generated models would be useful?

We thank the reviewer for the valid suggestion. We have now included the PAE plot corresponding to the AlphaFold model in the supplementary Fig. S1d and reference on page 7 line 18. RaptorX ranks models based on estimated error. We have now included this information in the new figure legend for Supplementary Fig. S1.

Figure 1 - Perhaps label figure 1b as being experimentally determined, with the R values (as for Figure 1d), and 1c being a predicted model.

We have included Rfree and Rwork values for the Mis18a Yippee homo dimer structure and labelled Mis18a/b Yippee hetero-dimer as the predicted model in Fig. 1c and 1d.

Page 8 "This observation is consistent with the theoretically calculated pI of the Mis18alpha helix" This is a circular argument, of course this region has a low pI due to the amino acid composition. Please remove this statement.

We have now removed this statement as suggested.

Page 8 "...reveals tight hydrophobic interactions" these are presumably shown in Figure 1d rather than in the referenced 1e.

We apologise for the oversight. We have now referred to the correct figure (Fig. 1f in the revised Fig. 1).

Page 8 - The authors should briefly somewhere discuss why there is a difference between their results and those in Pan et al 2009. As I understand it, the Pan et al paper was based in part on modelling with CLMS data as restraints.

We thank the reviewer for this suggestion. According to Pan et al., 2009, the model shown by them was generated using CCBuilder, and their CLMS data could not differentiate the two models with the 2nd Mis18a C-terminal helix in either parallel or anti-parallel orientation. We now briefly discuss this on page 8 and line 22 as follows: "Although the Pan et al., 2019 model presented the 2nd Mis18a in a parallel orientation, they did not rule out the possibility of this assembling in an anti-parallel orientation within the Mis18a/b C-terminal helical assembly (Pan et al., 2019)."

Figure 1 - The labelling of the residues for Mis18-alpha in Figure 1d is problematic, they are black on dark purple (might be my printer/screen/eyes) suggest amending.

We have now rearranged the label positions to overcome this issue. For clarity, the labels that could not be moved appropriately are shown in white.

Figure S3a - Do the authors have some data to show the mass of the cross-linked complex that was loaded onto grids is consistent with what is expected?

Unfortunately, the amount of material that we recover after performing GraFix is not sufficient enough to determine the molecular weight of the crosslinked sample by techniques such as SEC-MALS. However, GraFix fractions were analysed by SDS PAGE, and fractions that ran around the expected molecular weight were selected for EM analysis. We have now included the corresponding SDS-PAGE showing the migration of the crosslinked sample analysed by EM (Supplementary Fig. S3a).

Figure S3b - scale bar

Revised Fig. 2d now includes the scale bar shown.

Figure S3c - Could the authors show or explain the differences between these different 3D reconstructions?

The models mainly differ in the relative orientations of the bulkier structural features that are referred to as 'ear' and 'mouth' pieces of a telephone handset. This has been mentioned in the text, but we note that the figure is not referenced right next to this statement. We have now amended this (Page 9 line 19), and to make it clear, we have also highlighted the difference using an arrowhead in Fig. 2e and S3b. The different orientations are also stated in the corresponding figure legends.

Page 9 - The use of "AFM" for AlphaFoldMultimer" is a little confusing since AFM is the established acronym for Atomic Force Microscopy. Perhaps AF2M?

We have now replaced AFM with AF2M on page 9 to avoid confusion.

Figure S4a - Control missing for Mis18-alpha wild-type

Apology for the confusion, this control is present in Fig. 4a. We have now stated this in the figure legend of S4a for clarity.

Figure S4 d and e - The contrast between the bands and the background is very bad (at least in my copy).

We have now adjusted the contrast of the blots in Fig. S4d and S4e response to this comment.

Page 13 "Our structural analysis suggests that two Mis18BP1 fragments.....". How did you arrive at this conclusion? Is this based on the AlphaFold/RaptorX model? What additional evidence do you have that the positioning of the Mis18BP1 is correct? Does the CLMS data support this?

We confirm that this statement is based on AlphaFold model. We have now explicitly highlighted this on page 14, line 5. As noted in the same paragraph (page 14, line 19), this model agrees with the contacts suggested by the cross-linking mass spectrometry data presented here.

Figure 4a - Would the authors like to consider using a different colour for Mis18BP1? The contrast is not great, especially in the electrostatic surface inset.

In response to this suggestion, the Mis18BP1 helix is now shown in grey in the inset of Fig. 5a.

Reviewer #1 (Significance (Required)):

General Assessment The paper is extremely clearly written. Likewise the figures are beautifully presented and the data extremely clean and fully supportive of the authors conclusions. Indeed it is seldom that one sees the depth of the structural approaches (X-ray, CLMS, EM, SAXS) in one paper which is a huge strength of the manuscript. In addition the translation of this data into very clean cell biological experiments, makes the paper truly outstanding.

Advance The authors provide the first model of the Mis18 complex, with extensive evidence to back up this model. The authors provide additional evidence as to how the deposition/renewal of CENP-A might be mediated by the Mis18 complex. The advance comes from both the level of clarity, detail, and scope achieved in this paper.

Audience This will likely be of great interest to anyone with an interest in chromosome biology, plus be of interest to structural biologists as an outstanding example of hybrid structural biology.

Expertise I am a biochemist with a background in structural biology with some familiarity with centromere biology

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

Summary: The manuscript "structural basis for Mis18 complex assembly: implications for centromere maintenance" by Thamkachy and colleagues describes a study that uses structural analysis to test essential candidate residues in Mis18 complex components in CENP-A loading. For chromosomes to faithfully segregate during cell division, CENP-A levels must be maintained at the centromere. How CENP-A levels are maintained is therefore important to understand at the mechanistic level. The Mis18 complex has been found to be important, but how exactly the various Mis18 complex components interact and how they regulate new CENP-A loading remains not fully understood. This study set out to characterize the critical residues using X-ray crystallography, negative staining EM, SEC analysis, molecular modeling (Raptorx, AlphaFold2, and AlphaFold-multimer) to identify the residues of Mis18a and Mis18b that are critical for the formation of the Mis18a/b hetero-hexamer and which residues are important for Mis18a and Mis18BP1 interactions. A complex beta-sheet interface dictates the Mis18a and Mis18b interactions. Mutating the Mis18a residues that are important for the Mis18a/b interactions resulted in impaired pull-down of Mis18b and reduced centromeric levels of mutated Mis18a. The functional consequences of mutating residues that impair Mis18a/b interactions is that with reduced centomeric levels of Mis18a, also impaired new CENP-A loading. Interestingly, mutated Mis18b did not impact centromeric Mis18a levels and only modestly impaired new CENP-A loading. These data were interpreted that Mis18a is critical for new CENP-A loading, whereas Mis18b might be involved in finetuning how much new CENP-A is loaded. Overall, it is a very well described and well written study with exciting data.

Major comments:

• Overall, the structural data and the IF data support the importance of Mis18a residues 103-105 are critical for centromeric localization and new CENP-A loading, whereas Mis18b residues L199 and I203 are critical for centromeric localization, but only very modestly impair centromeric Mis18a localization and new CENP-A loading. In the discussion the authors argue that the N-terminal helical region of Mis18a mediate HJURP binding. This latter is postulated based on published work, but not tested in this work. This should be clarified as such.

We thank the reviewer for this comment. Our very recent study aimed at understanding the licencing role of Plk1, independent of the work reported here, serendipitously has now validated this suggestion and demonstrates that a Plk1-mediated phosphorylation cascade activates the Mis18a/b complex via a conformational switch of the N-terminal helical region of Mis18a, which facilitates a robust HJURP-Mis18a/b interaction (Parashara et al. bioRxiv 2024). An independent study from the Musacchio lab (Conti et al. bioRxiv, 2024) also reports similar findings, mutually strengthening our independent conclusions. Overall, these studies highlight the importance of the critical structural insights into the Mis18 complex this study reports. We now explicitly discuss the validation of our original hypothesis by citing our recent work along with that of the Musacchio lab. The corresponding section of the last paragraph now reads as follows (page 17 line 10): "Previously published work identified amino acid sequence similarity between the N-terminal region of Mis18a and R1 and R2 repeats of the HJURP that mediates Mis18a/b interaction (Pan et al., 2019). Deletion of the Mis18a N-terminal region enhanced HJURP interaction with the Mis18 complex (Pan et al., 2019). Here, we show that the N-terminal helical region of Mis18a makes extensive contact with the C-terminal helices of Mis18a and Mis18b, which had previously been shown to mediate HJURP binding by Pan et al., 2019. Collectively these observations suggest that the N-terminal region of Mis18a might directly interfere with HJURP - Mis18 complex interaction. Two independent recent studies (Parashara et al., 2024, Conti et al., 2024) reveal that this is indeed the case and a Plk1-mediated phosphorylation cascade involving several phosphorylation and binding events of the Mis18 complex subunits relieve the intramolecular interactions between the Mis18a N-terminal helical region and the HJURP binding surface of the Mis18a/b C-terminal helical bundle. This facilitates robust HJURP-Mis18a/b interaction in vitroand efficient HJURP centromere recruitment and CENP-A loading in cells. Overall, these studies also highlight the importance of the critical structural insights into the Mis18 complex we report here."

• Overall, the authors clearly describe their data and methodology and use adequate statistical analyses. The structural data of the Mis18a/b complex being a hetero-hexamer is convincing, but the validation in vivo is missing. As structural experiment are not performed under physiological conditions, it is important to establish the stoichiometry in vivo to further support the totality of the findings of the structural experiments and modeling. The data for the hierarchical assembly of Mis18a and Mis18b at the centromere and its importance in new CENP-A loading is convincing. An additional open question is whether "old" centromeric CENP-A or HJURP:new CENP-A complex is needed to recruit Mis18a to the centromere and whether the identified residues have a role in Mis18a centromeric localization. These data would provide a solid link between the Mis18 complex and how it is directly linked to new CENP-A loading.

We agree that establishing the stoichiometry of Mis18 subunits of the Mis18 complex in vivo would be insightful. However, considering that the Mis18 complex assembles in a specific window of the cell cycle (late Mitosis and early G1), we think characterising the stoichiometry in cells is extremely difficult and technically challenging. However, consistent with our structural model, several lines of independent evidence (Pan et al., 2017 and Spiller et al., 2017) using different biophysical methods (Analytical Ultra Centrifugation (Pan et al., 2017), SEC-MALS (Spiller et al., 2017)) showed that recombinantly purified Mis18 complex (irrespective of the expression host, from both E. Coli or insect cells) is a hetero-octamer made of a hetero-hexameric Mis18a/b (4 Mis18a and 2 Mis18 b) complex bound to two copies of Mis18BP1. These observations suggested that hetero-hexamerisation of the Mis18a/b complex may be needed to bind and dimerise Mis18BP1 in cells. Previously published cellular studies support the in vivo requirement of the hetero-octameric Mis18 assembly as: (i) Perturbing the hetero-hexamerisation of the Mis18a/b complex (by introducing mutations at the Mis18a/b Yippee dimerisation interface, which while did not disrupt Mis18a/b complex formation, perturbed its hetero-hexamerisation and resulted in a hetero-trimeric Mis18a/b complex made of 2 Mis18aand 1 Mis18b) abolished Mis18BP1 binding in vitro and in cells, consequently abolished CENP-A deposition (Spiller et al., 2017) and (ii) artificial dimerisation of Mis18BP1, by expressing Mis18BP1 as a GST-tagged protein, enhanced the centromere localisation of Mis18BP1 highlighting the requirement of Mis18a/b hexameric assembly mediated dimerization of Mis18BP1 in cells (Pan et al., 2017). While these studies highlighted the importance of maintaining the right stoichiometry (hetero-octamer of 4 Mis18a, 2 Mis18b and 2 Mis18BP1), lack of structural information on how this essential biological assembly is established remained a major knowledge gap. Our work presented here fills this critical knowledge gap by showing that a segment of Mis18BP1 (aa 20-51) also binds at the Yippee dimerisation interface. To highlight this, we have included the following statements in the introduction on page 5 and 20 "Perturbing the Yippee domain-mediated hexameric assembly of Mis18a/b (that resulted in a Mis18a/b hetero-trimer, 2 Mis18a and 1 Mis18b) abolished its ability to bind Mis18BP1 in vitro and in cells (Spiller et al., 2017), emphasising the requirement of maintaining correct stoichiometry of Mis18a/b subunits. Consistent with this, artificial dimerisation of Mis18BP1, by expressing Mis18BP1 as a GST-tagged protein, enhanced the centromere localisation of Mis18BP1 (Pan et al., 2017)." and in the Results section on page 14 line 12: "Mis18BP120-51 contains two short b strands that interact at Mis18a/b Yippee interface extending the six-stranded-b sheets of both Mis18a and Mis18b Yippee domains. This provides the structural rationale for why Yippee domains-mediated Mis18a/b hetero-hexamerisation is crucial for Mis18BP1 binding (Spiller et al., 2017)."

Regarding the question "whether 'old' centromeric CENP-A or HJURP:new CENP-A complex is needed to recruit Mis18a centromere localisation and whether identified residues have a role in Mis18a centromere localisation": According to the published literature, the Mis18 complex associates with centromeres through interaction with CCAN components CENP-C and CENP-I (Shono et al., 2015, Dambacher et al., 2012, Moree et al., 2011, Hoffmann et al., 2020). Considering CCAN assembles on CENP-A nucleosomes, and HJURP:new CENP-A centromere recruitment depends on the Mis18 complex, it will be reasonable to argue that the 'old' centromeric CENP-A contributes to the centromere localisation of the Mis18 complex. Amongst the components of the Mis18 complex, Mis18BP1 and Mis18bhave previously been suggested to interact with CENP-C. Within the Mis18 complex, we (Spiller et al., 2017) and others (Pan et al., 2017) have shown that Mis18a can directly interact with Mis18BP1, but it does so more efficiently when Mis18a hetero-oligomerises with Mis18b via their Yippee domains. Here, our structural analysis mapped the interaction interfaces and showed that Mis18a residues E103, D104 and T105 contribute to Mis18BP1 binding, as mutating these residues abolishes centromere localisation of Mis18a (Fig. 5c and 5d). To accentuate our findings, we have now included the following paragraph in the discussion section (page 17 line 26): "One of the key outstanding questions in the field is how does the Mis18 complex associate with the centromere. Previous studies identified CCAN subunits CENP-C and CENP-I as major players mediating the centromere localisation of the Mis18 complex mainly via Mis18BP1 (Shono et al., 2015, Dambacher et al., 2012, Moree et al., 2011), although Mis18b subunit has also been suggested to interact with CENP-C (Stellfox et al., 2016). Within the Mis18 complex, we and others have shown that the Mis18a/b Yippee hetero-dimers can directly interact with Mis18BP1. Here our structural analysis allowed us to map the interaction interface mediating Mis18a/b-Mis18BP1 binding. Perturbing this interface on Mis18a completely abolished Mis18a centromere localisation and reduced Mis18BP1 centromere levels. These observations show that Mis18a associates with the centromere mainly via Mis18BP1, and assembly of the Mis18 complex itself is crucial for its efficient centromere association, as previously suggested. Future work aimed at characterising the intermolecular contact points between the subunits of the Mis18 complex, centromeric chromatin and CCAN components and understanding if the Mis18 complex undergoes any conformational and/or compositional variations upon centromere association and/or during CENP-A deposition process, will be crucial to delineate the mechanisms underpinning the centromere maintenance."

Minor comments:

• The bar graphs shown ideally also show the individual data points for the authros to appreciate the spread of the data. These figures can be replicated in the Supplemental to avoid making the main figures look too busy.

We thank the reviewers for this suggestion. Reviewer #3 made a similar comment and suggested we use Superplot, which allows visualisation of individual data points of independent experiments. We have now revised all bar graphs using Superplot to address both reviewers' suggestions.

Reviewer #2 (Significance (Required)):

• This study uses a broad range of structural techniques, including molecular modeling which were subsequently validated by in vitro pull-down assays, co-IP, and IF. This combination of these techniques is important because many structural techniques cannot be performed under physiological conditions. Validating the main findings of the structural results by IF and co-IP is therefore critical.
• This work greatly advances our structural understanding how Mis18a, Mis18b, and Mis18BP1 form the Mis18 complex and how the critical residues in especially Mis18a help the Mis18 complex localize to the centromere and influence new CENP-A loading. This study also provides the first strong evidence in hierarchical assembly of the Mis18 complex.
• How centromere identity is maintained is a critical question in chromosome biology and genome integrity. The Mis18 complex has been identified as an important complex in the process. Several structural and mutational studies (all adequately cited in this manuscript) have tried to address which residues guide the assembly and functional regions of the Mis18 complex. This work builds and expands our understanding how especially Mis18a holds a pivotal role in both Mis18 complex formation and its impact on maintaining centromeric CENP-A levels.
• This work will be of interest to the chromosome field in general and anyone studying the mechanism of cell division.
• Chromatin, centromere, CENP-A, cell division. This reviewer has limited expertise in structural biology.

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

Centromere identity is defined by CENP-A loading to specific sites on genomic DNA. CENP-A loading is known to rely on the Mis18 complex, and several regulators are known; yet how the Mis18 complex achieves this complex process has remained puzzle. By elucidating the structural basis of Mis18 complex assembly using integrative structural approaches the authors show that multiple homo and heterodimeric interfaces of Mis18alpha, beta and Mis18BP1 are involved in centromere maintenance. The authors show that Mis18alpha can associate with centromeres and deposit CENP-A independent of Mis18 β. Mis18α functions in CENP-A deposition at centromeres independent of Mis18β. Mis18β is required for maintaining a specific level of CENP-A occupancy at centromeres. Thus, using structure-guided and separation-of-function mutants the study reveals how Mis18 complex ensures centromere maintenance. Major comments: This is an excellent study on centromere inheritance, combining structural and cell biology techniques. The comments here primarily refer to Cell biology aspect of the work.

Figures show that new CENP-A deposits in Mis18βL199D/I203D mutants, but the level was reduced moderately. Based on this observation, the authors make a strong conclusion that Mis18β licenses the optimal levels of CENP-A at centromeres. Mis18α may be essential for both CENP-A incorporation and depositing a specific amount of CENP-A, as Mis18α and CENP-A levels are both reduced in Mis18βL199D/I203D mutants which failed to form the triple helical assembly with Mis18α as shown in Figure 3B and 3C. The authors may want to qualify some of these claims as preliminary or speculative.

We thank the reviewer for this suggestion. We agree that although the reduction in CENP-A levels upon replacing WT Mis18b with Mis18b L199D/I203D is more prominent than the reduction in centromere localised Mis18a, one cannot completely rule out the contribution of reduced Mis18a on CENP-A loading. This also raises an interesting possibility where Mis18b ensures the correct amount of CENP-A deposition by facilitating the optimal level of Mis18a at centromeres. We now explicitly discuss this in the discussion as follows (page 16 line 26): "Whilst proteins involved in CENP-A loading have been well established, the mechanism by which the correct levels of CENP-A are controlled is yet to be thoroughly explored and characterised. The data presented here suggest that Mis18b mainly contributes to the quantitative control of centromere maintenance - by ensuring the right amounts of CENP-A deposition at centromeres - and maybe one of several proteins that control CENP-A levels. We also note that the Mis18b mutant, which cannot interact with Mis18a, moderately reduced Mis18a levels at centromeres, and hence, it is possible that Mis18b ensures the correct level of CENP-A deposition by facilitating optimal Mis18a centromere recruitment. Future studies will focus on dissecting the mechanisms underlying the Mis18b-mediated control of CENP-A loading amounts along with any other mechanisms involved."

This work and others show that phosphorylation of Mis18BP1 by CDK1 can interfere with complex function (Spiller et al., 2017, Pan et al., 2017). Does the structure provide any insight into PLK1-mediated phosphorylation surfaces for activation of the complex? If yes, a brief discussion would help to link CDK1 and PLK1 mediated opposing actions will strengthen the work.

As described in our response to the first major comment of Reviewer 2, our very recent study aimed at understanding the licencing role of Plk1, independent of the work reported here, identified and evaluated the functional contribution of Plk1 phosphorylation on the subunits of the Mis18 complex (Parashara et al., bioRxiv 2024). Serendipitously, this recent work has now validated our hypothesis proposed based on the structural characterisation reported here and demonstrates that a Plk1-mediated phosphorylation cascade activates the Mis18a/b complex via a conformational switch of the N-terminal helical region of Mis18a which facilitates a robust HJURP-Mis18a/b interaction (Parashara et al. bioRxiv 2024). An independent study from the Musacchio lab (Conti et al., bioRxiv 2024) also reports similar findings, mutually strengthening our independent conclusions. Overall, these studies highlight the importance of the critical structural insights into the Mis18 complex this study reports. We now explicitly discuss the validation of our original hypothesis by citing our recent work along with that of the Musacchio lab. The corresponding section of the last paragraph now reads as follows (page 17 line 10): "Previously published work identified amino acid sequence similarity between the N-terminal region of Mis18a and R1 and R2 repeats of the HJURP that mediates Mis18a/binteraction (Pan et al., 2019). Deletion of the Mis18a N-terminal region enhanced HJURP interaction with the Mis18 complex (Pan et al., 2019). Here, we show that the N-terminal helical region of Mis18a makes extensive contact with the C-terminal helices of Mis18a and Mis18b, which had previously been shown to mediate HJURP binding by Pan et al., 2019. Collectively these observations suggest that the N-terminal region of Mis18a might directly interfere with HJURP - Mis18 complex interaction. Two independent recent studies (Parashara et al., 2024, Conti et al., 2024) reveal that this is indeed the case and a Plk1-mediated phosphorylation cascade involving several phosphorylation and binding events of the Mis18 complex subunits relieve the intramolecular interactions between the Mis18a N-terminal helical region and the HJURP binding surface of the Mis18a/b C-terminal helical bundle. This facilitates robust HJURP-Mis18a/b interaction in vitro and efficient HJURP centromere recruitment and CENP-A loading in cells. Overall, these studies also highlight the importance of the critical structural insights into the Mis18 complex we report here."

I am happy with the way cell biology data and the methods are presented so that they can be reproduced. The experiments are adequately replicated and the statistical analysis adequate. It will help to include sample size of cells or centromeres used for building the graphs.

We have now included this information in figure legends of Fig. 3a, 3c, 4b, 4c, 5b, 5c and 5d.

This is a strong interdisciplinary study using a variety of in vitro and in vivo techniques. Can the authors discuss if they expect chromatin associated Mis18 complex to host a similar structure as the soluble one? In other words, are they able to comment on any key differences between chromatin and non-chromatin associated Mis18 complexes.

We thank the reviewer for the suggestion. We agree that one cannot rule out the possibility of the Mis18 complex undergoing compositional and/or conformational variations during the processes of CENP-A loading at centromeres. We now explicitly discuss this possibility in the last paragraph of the discussion section (page 18 line 10): "Future work aimed at characterising the intermolecular contact points between the subunits of the Mis18 complex, centromeric chromatin and CCAN components and understanding if the Mis18 complex undergoes any conformational and/or compositional variations upon centromere association and/or during CENP-A deposition process, will be crucial to delineate the mechanisms underpinning the centromere maintenance."

Minor comments: -

In cell biology experiments, fluorescence intensities could be presented as a superplot for added value across cells and repeats (instead of bar graphs). More on superplot:https://doi.org/10.1083/jcb.202001064.

We thank the reviewers for this kind suggestion. We have now included graphs made using 'superplot' as suggested.

In general, ACA levels do not appear to change significantly between WT and mutant expressing cells although new CENP-A loading is significantly absent in the presence of a few mutants - please comment if ACA used here can recognise CENP-A. Would this mean that old CENP-A remains normally?

We thank the reviewer for this comment. While new CENP-A incorporated at centromeres is selectively labelled using the SNAP-tag, the ACA antibody used in these experiments can recognise CENP-A, CENP-B and CENP-C, with CENP-B being the primary target (Kallenberg, Clinical Rheumatology,1990). We would also like to note that ACA has commonly been used to locate the centromere in CENP-A loading assays where new CENP-A levels are assessed via selective labelling (e.g. McKinley 2014).

It is unclear whether any of the mutant acted in a dominant negative fashion in the presence of endogenous Mis18 proteins. It would have been useful to test this particularly in the context of mis18alpha mutants that seem to fully abolish new CENP-A recruitment.

As Mis18 subunits oligomerise (homo and hetero), we thought expressing these mutants in the presence of endogenous proteins might interfere with endogenous protein in a heterogenous manner and might make the interpretation difficult. Hence, we did not test this. Instead, as described in the manuscript we have tested these mutants in siRNA rescue experiments (Fig. 3, 4 and 5).

In figure 3a, GFP panel (input lane, 1) is shown to mark a band corresponding to GFP. Is this expected? Please comment.

Yes, as a control, an empty vector was transfected to express just GFP along with Mis18a-mCherry. These were used to show that there was no unspecific interaction between the beads used for IP or Mis18a-mCherry and GFP tag, and that any interaction seen was due to Mis18b. A similar control was used in S4b, where mCherry was expressed along with Mis18b-GFP. We have now clarified this in the corresponding legends of Fig. 4a and S4b.

Would be useful to have the scale for the cropped images presented as insets. Figure 4B should read YFP and not YPF.

We apologise for this typographical error. We have now corrected this.

The authors may want to explain whether the tag differences matter for their study (Case in point: His-SUMO-Mis18a191-233 WT and mutant His-MBP-Mis18b188-229 proteins).

The MBP tag was chosen to perform amylose pull-down assays, whereas the SUMO tag was chosen to increase the protein size. This is crucial as the C-terminal fragments of Mis18a and Mis18b are less than 50 amino acids long and are not easy to visualise by the band intensity in the Coomassie-stained SDS PAGE gels.

Reviewer #3 (Significance (Required)):

This work elucidates the structural basis of Mis18 complex assembly and the intermolecular interfaces essential for Mis18 functions. This is a significant advance in the field as it helps researchers in the field better understand CENP-A deposition and mechanism underpinning the maintenance of centromere identity. This is a broad area of research benefitting those studying cell division, genome stability, centromere identity and epigenetics might all be interested in and influenced by these findings. Novelty and strength lies in combining structural and cell biology work. Strengths of the work are structural details of the Mis18 complex. Minor weakness is the link between Mis18 structure and Centromere inheritance is limited to one immunostaining assay (I have mentioned this as a minor comment because addressing this may not be within the scope of this manuscript and is likely to require a repeat of a vast majority of the work with additional reagents which may not directly add value to the current manuscript).

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Referee #3

Evidence, reproducibility and clarity

Centromere identity is defined by CENP-A loading to specific sites on genomic DNA. CENP-A loading is known to rely on the Mis18 complex, and several regulators are known; yet how the Mis18 complex achieves this complex process has remained puzzle. By elucidating the structural basis of Mis18 complex assembly using integrative structural approaches the authors show that multiple homo and heterodimeric interfaces of Mis18alpha, beta and Mis18BP1 are involved in centromere maintenance. The authors show that Mis18alpha can associate with centromeres and deposit CENP-A independent of Mis18 β. Mis18α functions in CENP-A deposition at centromeres independent of Mis18β. Mis18β is required for maintaining a specific level of CENP-A occupancy at centromeres. Thus, using structure-guided and separation-of-function mutants the study reveals how Mis18 complex ensures centromere maintenance.

Major comments:

This is an excellent study on centromere inheritance, combining structural and cell biology techniques. The comments here primarily refer to Cell biology aspect of the work.

1. Figures show that new CENP-A deposits in Mis18βL199D/I203D mutants, but the level was reduced moderately. Based on this observation, the authors make a strong conclusion that Mis18β licenses the optimal levels of CENP-A at centromeres. Mis18α may be essential for both CENP-A incorporation and depositing a specific amount of CENP-A, as Mis18α and CENP-A levels are both reduced in Mis18βL199D/I203D mutants which failed to form the triple helical assembly with Mis18α as shown in Figure 3B and 3C. The authors may want to qualify some of these claims as preliminary or speculative.
2. This work and others show that phosphorylation of Mis18BP1 by CDK1 can interfere with complex function (Spiller et al., 2017, Pan et al., 2017). Does the structure provide any insight into PLK1-mediated phosphorylation surfaces for activation of the complex? If yes, a brief discussion would help to link CDK1 and PLK1 mediated opposing actions will strengthen the work.
3. I am happy with the way cell biology data and the methods are presented so that they can be reproduced. The experiments are adequately replicated and the statistical analysis adequate. It will help to include sample size of cells or centromeres used for building the graphs.
4. This is a strong interdisciplinary study using a variety of in vitro and in vivo techniques. Can the authors discuss if they expect chromatin associated Mis18 complex to host a similar structure as the soluble one? In other words, are they able to comment on any key differences between chromatin and non-chromatin associated Mis18 complexes.

Minor comments:

In cell biology experiments, fluorescence intensities could be presented as a superplot for added value across cells and repeats (instead of bar graphs). More on superplot: https://doi.org/10.1083/jcb.202001064. In general, ACA levels do not appear to change significantly between WT and mutant expressing cells although new CENP-A loading is significantly absent in the presence of a few mutants - please comment if ACA used here can recognise CENP-A. Would this mean that old CENP-A remains normally?

It is unclear whether any of the mutant acted in a dominant negative fashion in the presence of endogenous Mis18 proteins. It would have been useful to test this particularly in the context of mis18alpha mutants that seem to fully abolish new CENP-A recruitment.

In figure 3a, GFP panel (input lane, 1) is shown to mark a band corresponding to GFP. Is this expected? Please comment. Would be useful to have the scale for the cropped images presented as insets.

Figure 4B should read YFP and not YPF.

The authors may want to explain whether the tag differences matter for their study (Case in point: His-SUMO-Mis18a191-233 WT and mutant His-MBP-Mis18b188-229 proteins).

Significance

This work elucidates the structural basis of Mis18 complex assembly and the intermolecular interfaces essential for Mis18 functions. This is a significant advance in the field as it helps researchers in the field better understand CENP-A deposition and mechanism underpinning the maintenance of centromere identity. This is a broad area of research benefitting those studying cell division, genome stability, centromere identity and epigenetics might all be interested in and influenced by these findings. Novelty and strength lies in combining structural and cell biology work.

Strengths of the work are structural details of the Mis18 complex. Minor weakness is the link between Mis18 structure and Centromere inheritance is limited to one immunostaining assay (I have mentioned this as a minor comment because addressing this may not be within the scope of this manuscript and is likely to require a repeat of a vast majority of the work with additional reagents which may not directly add value to the current manuscript).

DOI: 10.1038/s44319-024-00074-0

Resource: RRID:Addgene_108077

Curator: @olekpark

SciCrunch record: RRID:Addgene_108077

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What is this?

DOI: 10.1038/s44319-024-00074-0

Resource: RRID:Addgene_108078

Curator: @olekpark

SciCrunch record: RRID:Addgene_108078

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What is this?

Author Response

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

We appreciate the insightful feedback provided by the editors and reviewers who have recognized the novelty of our study. We have mapped the spatial distribution of six endogenous somatic histone H1 variants within the nuclei of several human cell lines using specific antibodies, which strongly suggest functional differences between variants. We are submitting a revised version of the manuscript to accommodate the reviewers comments and recommendations.

Reviewer #1 (Recommendations For The Authors):

Minor Comments:

(1) In Figure 1C, since H1.4 is uniformly distributed among the four sections (A1-A4), its levels are not expected to be significant among the four sections as depicted. Even the violin plots shown do not seem to be significantly different from each other. This requires an explanation.

We agree with this reviewer that significant differences of H1.4 abundance within areas A1 to A4 seem to not exist, either looking at the images or the data violin plots, as discussed in the manuscript. Nonetheless, statistical testing gave this as significant, due to small differences and the elevated sample N of the analysis. It is clear that H1.4 does not show a relevant peripheral enrichment as shown for the other variants.

(2) At the end, it would be better to include a figure panel depicting chart/table/pictorial representation, depicting the summary of the work done with respect to all the histone variants, as there are several histone H1 variants studied under different conditions and contexts.

A table summarizing the location and characteristics of the different H1 variants has been included in the manuscript (Figure 6).

Reviewer #2 (Recommendations For The Authors):

(1) The authors may consider adding controls for the specificity of the antibodies used for the studies. While the antibodies used here are commercial, it does not guarantee the quality for immunofluorescence, especially considering their unreliability in the past. The authors may consider including peptide/ recombinant protein-based adsorption controls in addition to knockdown or knockout controls. Having these data will strengthen the exciting observations presented in this MS and significantly increase the impact of the presented findings.

We totally agree with the reviewers that the use of commercially available antibodies does not guarantee their quality and specificity. As this issue was crucial for our studies, we extensively assayed performance and specificity of the antibodies, using different approaches. The validations were shown in our previous publications where these antibodies where successfully used for ChIP-seq (Serna-Pujol et al. 2022 NAR 50:3892; Salinas-Pena et al. 2024 NAR doi 10.1093/nar/gkae014). In summary, performance of H1.0 (05-629l, Millipore), H1.2 (ab4086, abcam), H1.4 (702876; Invitrogen), H1.5 (711912, Invitrogen) and H1X (ab31972; abcam) antibodies was tested by Western-Blot, ChIP and proteomic analyses (all the results are included in Supplem. Figure 1 in Serna-Pujol et al. 2022 NAR 50:3892). Concretely, we tested specificity using inducible KDs for the depletion of each of the somatic H1 variants in T47D. We also checked that the antibodies did not recognize additional H1 variants using recombinant proteins or cell lines naturally lacking some of the variants. All the experiments confirmed that antibodies were variant-specific. In addition, when the corresponding epitope was absent, the antibodies did not gain new cross-reactivity with other variants. More recently, validation of the specificicity of the H1.3 antibody (ab203948) was performed following the same experimental approaches described for the rest of antibodies (Supplem. Figure 1 in Salinas-Pena et al. 2024 NAR doi 10.1093/nar/gkae014).

(2) Histone H1 is overexpressed in several cancers. While the authors do not use an overexpression strategy, the cells used in this study are all cancer cell lines. The study would benefit greatly if some of the findings- primarily regarding the spatial distribution of the H1 were to reproduce in non-tumorigenic, diploid cells.

We have also studied and discussed the spatial distribution of H1 variants in nontumorogenic cell lines 293T and IMR-90, and we have added this in the revised manuscript (Figure 5D and Figure 5-figure supplement 3). The nuclear radiality of H1.4 in 293T cells is also shown (Figure 5-figure supplement 4A).

Reviewer #3 (Recommendations For The Authors):

This is an interesting paper that provides convincing evidence of distinct distributions to individual histone H1 variants. There are several aspects of the study that leave me unconvinced that the study accurately captures histone H1 variant distributions.

(1) Antibody accessibility: (see PMID: 32505195). One means to address this is to express a fluorescent protein-tagged version of histone H1 and demonstrate that the antibody can detect that tagged version of histone H1 independent of its location in the nucleus. In general, these FP-tagged H1s show a much more even distribution than what is observed here. Of course, that could reflect artifacts related to the fusion or the expression of the exogenous construct. However, even if all of the above are true, this will test the ability of the antibodies to recognize their epitopes in different chromatin environments. The fluorescent protein tag enables unambiguous knowledge of the presence or absence of the H1 histone.

We have used cells expressing HA-tagged H1.0 variant and performed immunofluorescence with HA and H1.0 antibody to investigate co-localization, to test whether an H1 antibodiy recognize all the tagged protein in different chromatin environments or irrespective of its location in the nucleus. A very high correlation between the two antibodies has been found (Figure 1-figure supplement 1B).

(2) At high concentrations, the fluorescence signal intensity can be quenched. For example, this is common with high-affinity histone H3 serine 10 phosphorylation antibodies in late interphase/prophase nuclei. The artifact can be minimized by serial dilution of the antibody and identifying the minimum usable concentration for immunofluorescence. While I am not certain that this is taking place here, the rate and manner that the intensity drops off from the periphery in the peripheral H1 variant distribution are very similar in appearance. There are biological explanations related to constraints on diffusion that one could imagine also explaining the data so I'm not stating that this must be an artefact. However, I am concerned that it might be. An improved staining may reveal the same result but more convincingly.

We have performed immunofluorescence with serial dilutions of the H1.3 antibody to show that peripheral distribution was not due to fluorescence signal intensity quenching (Figure 1figure supplement 1A).

(3) Histone H1 is highly mobile and there is some concern that they could reorganize during the relatively long period of time that it takes to fully fix the cells for both ChIP and immunofluorescence. This should be acknowledged in the manuscript.

We have added this reviewer’ concern in the Discussion section.

(4) The paper would benefit from a more rigorous quantification of histone H1 subtypes. Mass spectrometry would be ideal but more classical techniques such as 2D AU-SDS PAGE, HPLC, etc...would be an improvement over immunoblotting. The authors did not explain the quantification of the immunoblots and the assignment of relative contributions of H1 subtypes to the individual coommassie bands in the Image J section of methods, which is referred to as the method of quantification in the immunoblotting methods.

We have further explained how the relative quantification of H1 variants in different cell lines was performed (Methods section). We agree that more sophisticated mass spectrometrybased quantification is desirable and we are collaborating to do this using internal H1 peptide controls (Parallel Reaction Monitoring), but this is out of the scope of this manuscript as the observed patterns of distribution of H1 variants do not depend on mild differences in variants abundance. Only the absence of H1.3 and H1.5 in some cell lines alters the distribution of other variants.

Additional author responses to the Public Review comments made by some Reviewer:

(1) Respect to the functional significance of the results presented here, we want to stress that as a consequence of the differential distribution and abundance of H1 variants among cell types, depletion of different variants has different consequences. For example, H1.2 depletion but not others has a great impact on chromatin compaction. Besides, cell lines lacking H1.3/H1.5 expression present a basal up-regulation of some Interferon stimulated genes (ISGs) and particular repetive elements, as it was previously described upon induced depletion of H1.2/H1.4 in a breast cancer cell line or in pancreatic adenocarcinomas with lower levels of replication-dependent H1 variants (Izquierdo et al. 2017 NAR 45:11622). So, our results reinforce the existing link between H1 content and immune signature. We have added this data in the revised manuscript (Figure 5-figure supplement 5).

Moreover, we also analyzed the chromatin structural changes upon combined depletion of H1.2 and H1.4. Combined H1.2/H1.4 depletion triggers a global chromatin decompaction, which supports previous observations from ATAC-Seq and Hi-C experiments in these cells (Izquierdo et al. 2017 NAR 45:11622; Serna-Pujol et al. 2022 NAR 50:3892). Although H1 content is more compromised in these cells (30% total H1 reduction) compared to single H1 KDs, the phenotype observed could not be recapitulated when other H1 KD combinations, in which total H1 content was reduced similarly, were investigated (Izquierdo et al. 2017 NAR 45:11622), supporting that the deleterious defects were due to the non-redundant role of H1.2 and H1.4 proteins. Indeed, this manuscript supports this notion, as H1.2 and H1.4 show a different genomewide and nuclear distribution.

(2) Our immunofluorescence data, together with ChIP-seq data, do not discard binding of H1 variants to a great variety of chromatin, but show enrichment or preferential binding to certain regions or chromatin types. Our data on the interphase nuclei does not suggest at all any type of quenching or saturation. Obviously, detection with antibodies depends on epitope accessibility, just like all immunofluorescence data ever published, and we have acknowledged that post-translational modifications of H1 may occlude antibody accessibility as some phospho-H1 antibodies give distribution patterns different than total/unmodified H1 antibodies. Thus, we cannot exclude that specific modified-H1s exhibit particular distribution patterns that are not being recapitulated in our data. This represents another layer of complexity in H1 diversity and we agree that exploration of the repertoire of H1 PTMs and their functional roles are an interesting matter of study that needs to be addressed. Still, our data is highly relevant as it demonstrates for the first time the unique distribution patterns of H1 variants among multiple cell lines and it does not use overexpression of tagged H1 variants that in our experience may produce mislocalization of H1s.

(3) We do have investigated co-localization of H1 variants with HP1alpha protein and we have added this data in the revised version of this manuscript (Figure 1-figure supplement 1C-D).

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Referee #2

Evidence, reproducibility and clarity

Mitochondrial carrier homolog 2 (MTCH2, SLC25A50) loss induces alterations in mitochondrial dynamics and energy utilization. However, the molecular mechanisms underlying these changes are still unknown. The study employs temporal metabolomic and lipidomic analyses, uncovering heightened catabolism, increased lipid storage, and disrupted adipogenesis in MTCH2 KO cells. The manuscript provides a comprehensive metabolic profile, revealing ATP demand increase, oxidized cellular environment, and adaptive changes in MTCH2 KO cells. Notably, in line with the fundamental role of fatty acid biosynthesis and anabolism in adipogenesis, the authors demonstrates that MTCH2 loss inhibits adipocyte differentiation. This work offers novel insights into the broader metabolic consequences of MTCH2 depletion.

Major comments:

• The key conclusions of the paper align with the conducted experiments, but a few additional experiments are necessary to state some claims and provide more robust conclusions.

• The paper could benefit from the inclusion of specific experiments, particularly those that address the following aspects:

• Validate MTCH2 ablation in HeLa and NIH3T3L1 through sequencing of clonal lines, Western blot analysis to confirm the absence of the protein, and real-time PCR to assess whether the mechanism involves mRNA decay.

• Provide a more detailed rationale for their temporal metabolomics approach, elucidating the choice of the media and the timepoints of cell collection. The method involves an initial culture of the cells in DMEM medium, followed by a switch to complete medium (CM) for overnight cell growth, and subsequent refreshment with CM for different timepoints before the metabolomics analyses. Authors should articulate the reasoning for opting for CM. Furthermore, authors should explicitly explain the rationale behind selecting specific timepoints for cell collection after the addition of the fresh medium.
• In Figure 1, authors conclude that MTCH2 ablation stimulates oxidative metabolism and ATP production to fulfill increased cellular ATP demands. However, this conclusion is based only on metabolomic analyses of the ADP/ATP ratio. To comprehensively assess the impact on cellular respiration, the authors should monitor the Oxygen Consumption Rate (OCR) and report the Respiratory Control Ratio (RCR).
• NAD+/NADH ratio: authors should measure NADH levels in both mitochondria and cytosol. This can be accomplished through NADH autofluorescence (recommended) or commercially available kits. This additional analysis would contribute to a more comprehensive interpretation of the observed changes in oxidative metabolism. They should also include measurement of mitochondrial membrane potential using TMRM. Suggested experiment: measuring NADH autofluorescence. The autofluorescence of mitochondrial NADH can be distinguished from cytosolic NADH by optimizing substrate consumption followed by the complete inhibition of electron feeding to the ETC. The redox state of NADH reflects the equilibrium between mitochondrial ETC activity and the rate of substrate supply. After acquiring basal autofluorescence levels through live imaging, max signal is obtained by stimulating maximal respiration (FCCP), and min signal is obtained by inhibiting respiration (NaCN or Rot+AA). Subsequently, "NADH redox indexes" are generated by expressing the basal NADH levels as a percentage of the difference between the oxidized and reduced signals. Furthermore, by examining the fluorescence signal increase after NaCN addition, the rate of NADH production can be monitored. This rate serves as a proxy of TCA efficiency.
• Authors observe a reduction in the levels of various amino acids and TCA cycle intermediates, indicative of an increased flux through the TCA cycle. This proposition could be further supported by measuring the kinetics of NADH autofluorescence. Additionally, a decrease in metabolites associated with the urea cycle, such as citrulline and ornithine, is observed, yet this observation remains uncommented and warrants discussion. Intriguingly, an elevation in Branched-Chain Amino Acids (BCAAs) and unsaturated acyl carnitines is noted, leading to the hypothesis of an increased transport and breakdown of fatty acids in the mitochondria to meet the heightened cellular demand for ATP in MTCH2 KO cells. To substantiate this, and to quantitatively measure mitochondrial fuel utilization in live cells, authors shall perform a Mitofuel Flex Test by measuring the Oxygen Consumption Rate (OCR) in cells treated with inhibitors of each mitochondrial oxidative pathway including etomoxir. This approach would enable the measurement of the dependency, capacity, and flexibility of cells concerning the pathway of interest in meeting ATP demand. It is also recommended to perform MitoStress test in cells supplemented with only one of the carbon sources (such as Glucose, Glutamine, Long chain and Short Chain Fatty acids).
• In Fig 3, a reduction in membrane lipids, free fatty acids, and non-esterified fatty acids is observed, while there is an increase in esterified fatty acids, storage lipids like Triacylglycerols (TAG) and Cholesterol Esters (CE), and lipid droplet number and size. Notably, these lipid droplets are positioned closer to mitochondria in MKO cells. The authors propose that MKO results in enhanced transfer and metabolism of lipid moieties at the mitochondria to generate ATP. To provide insights into the molecular mechanisms underlying the observed lipid changes in MTCH2 KO cells, the following experiments are recommended: Employ Western blot and real-time PCR to measure the levels of enzymes crucial in TAG and CE formation and accumulation (e.g., Long-chain acyl-CoA synthetase (Acsl), Stearoyl-CoA desaturase (SCD) or others). Evaluate the enzymatic activity of these identified enzymes to understand their functional role in lipid metabolism in MTCH2 KO cells.
• The suggested experiments are realistic in terms of time and resources, ensuring practical feasibility.
• The data and methods are presented in a clear and reproducible manner.
• The experiments appear adequately replicated, and the statistical analysis seems OK.

Minor comments:

• There are no specific experimental issues that require addressing.
• Prior studies are appropriately referenced
• In general, both the text and figures are clear and accurate. The significant alteration of metabolites found in their metabolomic dataset should be plotted using the online tool MetaboAnalyst to analyze metabolic pathways and generate better visualizations.
• Overall, the presentation is satisfactory with only minor language adjustments recommended. A minor suggestion for improvement involves refining the language used in the text. Instead of consistently using the term "produce energy," please use "conversion of energy".

Significance

General Assessment: The study, through the integration of metabolomic and lipidomic data in MTCH2 KO cells, provide a comprehensive overview of the metabolic rewiring of these cells. This metabolic change is particularly interesting in the context of adipogenesis, offering valuable insights into the interconnectedness of a mitochondrial solute carrier, cellular metabolism and adipogenesis.

Comparison and Advance: The current study significantly advances our understanding of the mitochondrial carrier homolog 2 (MTCH2) by uncovering its intricate roles in metabolism, and adipogenesis. While prior research identified MTCH2 as a regulator of apoptosis and mitochondrial dynamics, the present study expands our knowledge by elucidating its involvement in cellular metabolism and adipocyte differentiation. The major advance lies in the detailed exploration of MTCH2's impact on cellular metabolism through temporal metabolomic and lipidomic analyses. The study reveals that MTCH2 deletion leads to heightened ATP demand, an oxidized cellular environment, and alterations in lipid, amino acid, and carbohydrate metabolism. Additionally, the adaptive response in MTCH2 knockout cells involves a strategic decrease in membrane lipids and an increase in storage lipids. Furthermore, the study unveils a novel connection between the imbalance in energy metabolism triggered by MTCH2 deletion and the inhibition of adipocyte differentiation-a process that demands substantial energy and reductive biosynthetic activities. This mechanistic insight provides a conceptual advance, indicating how MTCH2, beyond its known role in apoptosis and mitochondrial dynamics, plays a pivotal role in orchestrating cellular metabolism and adipogenesis. Importantly, this work aligns with prior observations that hinted at MTCH2's involvement in fatty acid synthesis, storage, and use through his identified interactome. In summary, the study advances our knowledge of MTCH2 by providing a more comprehensive understanding of its roles in cellular metabolism and adipocyte differentiation, shedding new light on its multifaceted functions beyond its originally identified roles.

Audience: This research will appeal to a broad audience, ranging from specialists in cellular metabolism to those with a general interest in mitochondrial dynamics and biochemistry.

this glossary entry should not tag "the" and should come under "u"

This glossary entry should tag: true nature of things

this glossary entry should not tag "the" and should come under "h": holy life

eLife assessment

This study presents two valuable new mouse models that individually tag proteins from the SMAD family to identify distinct roles during early pregnancy. Convincing evidence is provided that SMAD1 and SMAD5 target many of the same genomic regions as each other and the progesterone receptor. Given the broad effect of these signaling pathways in multiple systems, these new tools will most likely interest readers across biological disciplines.

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Reply to the reviewers

Manuscript number: RC-2023-02232

Corresponding author(s): Shinji, Saiki and Nobutaka, Hattori

1. General Statements [optional]

Thank you for the review of our paper entitled “Identification of novel autophagy inducers by accelerating lysosomal clustering against Parkinson's disease” (RC-2023-02232). We have carefully read the critiques and planed experiments. Below we include point-by-point responses to the questions raised by the reviewers. We have also carried out some experiments and highlighted the revised sentences in the transferred manuscript in red. The numbers of pages and lines are indicated based on the MS Word transferred manuscript. We believe this revision plans appropriately addresses the issues raised by Reviewers. Finally, all the authors would like to thank again the Editor and Reviewers for improving our manuscript by providing their invaluable comments and suggestions.

Point-by-point description of the revisions

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

The manuscript by Date et al employed a cell model by stably expressing LGP120-mCherry and GFP-gamma-tubulin to carry out high-content screening in search of chemical compounds that enhance lysosomal clustering and autophagy. They found 6 clinically approved drugs categorized as topoisomerase II inhibitors and the benzimidazole class. They further validated these compounds by a set of well-designed experiments including autophagy flux assays and mTOR dependence. In the mechanistic study, they demonstrated the compounds induce lysosomal clustering in a JIP4-TRPML1-dependent manner. In a PD cell model, one of the compounds albendazole exhibited the effect on boosting the degradation of insoluble alpha-synuclein. The study is of interest, and the cell model and the approach generated by the authors would be transferable for future studies of other high-content imaging screening. Most of the data is clear and convincing.

Major comment

1) In addition to its role in facilitating a-syn turnover by autophagy, Is the chemical protective against a-syn toxicity?

RESPONSE:

As suggested by the Reviewer, we examined the cytotoxicity of aSyn aggregates in SH-SY5Y cells overexpressing aSyn-GFP by LDH assay. As shown in the revised version of Fig. 1, aSyn aggregates induced by introducing aSyn fibrils into SH-SY5Y cells overexpressing aSyn-GFP did not exhibit any cytotoxicity. In addition, we observed no significant change in cell death after 8 hours of treatment with albendazole compared with DMSO.

Previous studies have reported that induced pluripotent stem cells (iPSCs) derived from patients with PD with a triplication of the human SNCA genomic locus exhibited reduced capacity for differentiation into dopaminergic or GABAergic neurons, decreased neurite outgrowth, and lower neuronal activity compared with control cultures, albeit without showing cytotoxicity (Cell Death and Disease 6: e1994, Oliveira et al., 2015). Given this context, we were thus unable to conduct the suggested assessment due to technical limitations. Therefore, we consider the evaluation of the recovery of aSyn toxicity by drug treatment challenging in this cellular model using fibril aSyn.

__Revised Fig 1. __

SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril for 48 h and treated with the indicated albendazole concentrations for 8 h. The cytotoxicity was measured by using Cytotoxicity LDH Assay Kit-WST kit.

2) Please elaborate why albendazole does not change the levels of soluble a-syn, but those of insoluble, as shown Fig 8D.

RESPONSE:

The unchanged aSyn-GFP levels in the soluble fraction (Fig. 8D) are likely due to the abundance of soluble aSyn-GFP. To evaluate the autophagic degradation of aSyn monomers, we used SH-SY5Y cells stably expressing aSyn-Halo and measured aSyn degradation by quantifying cleaved Halo. As shown in the revised version of Fig. 2, albendazole treatment induced a higher cleavage rate of Halo than DMSO treatment for 8 h, suggesting that albendazole degrades both aSyn monomers and aSyn aggregates. We have added the data in Fig. S7A, and the description of these experiments in the Results section (page 10, lines 359 to 364).

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__Revised Fig. 2. __

SH-SY5Y cells expressing aSyn-Halo were labeled for 20 min with 100 nM of tetramethylrhodamine-conjugated ligand in a nutrient-rich medium. After washing with phosphate-buffered saline and incubating in normal medium for 30 min, the cells were treated with 10 µM albendazole for 8 h. The experiments were performed in triplicate. Cell lysates were separated by electrophoresis and analyzed by in-gel fluorescence detection (left). The HaloTMR band intensity was normalized by the sum of the band intensities of HaloTMR-aSyn and HaloTMR. The vertical axis of the graph represents the intensity multiplied by 100. Mean values of data from five or three experiments are shown. The graph data are expressed as mean ± standard deviation. ****P 

3) Fig 6A shows that some of the compounds (Teniposide, Amsacrine) affect the levels of JIP4. Can albendazole also reduce JIP4 levels. It might be interesting to test this, as JIP4 is important for lysosomal clustering.

RESPONSE:

As the Reviewer pointed out, JIP4 is essential for lysosome accumulation. However, our data showed decreased JIP4 levels with the addition of lysosomal-clustering compounds. We hypothesized that this response was caused by the autophagy-induced degradation of JIP4. The decrease in JIP4 levels was detected by western blot after 4 h of treatment with 10 μM of teniposide. Moreover, the decrease in JIP4 levels induced by teniposide was suppressed by co-treatment with bafilomycin A1, indicating that JIP4 was degraded by teniposide-induced autophagy, as shown in the revised version of Fig. 3. We have added the data in Fig. S6 and the related description of these experiments in the Results section (page 8, lines 289 to 293).

__Revised Fig 3. __

SH-SY5Y cells were treated with 10 µM teniposide and with or without 30 nM bafilomycin A1 for 4 h. Cell lysates were immunoblotted with anti-JIP4 and actin antibodies.

Minor comments: The writing is good generally. Please tide up the text in a few occasions to make the expressions more formal.

RESPONSE: We have revised our manuscript to adopt a more formal tone.

Reviewer #1 (Significance (Required)):

Significance: The study generated a new approach for high-throughput screening of compounds to enhance lysosomal clustering. Audience: Basic and clinical research Expertise: Programmed cell death, neurodegenerative diseases

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

In this study, the authors focused on lysosome positioning and autophagy activity to search for novel agents effective against Parkinson's disease. As a result, several compounds were successively identified, including Topoisomerase inhibitors and Benzimidazole. Authors showed that these agents regulate lysosomal positioning through different pathways but commonly require JIP4 to regulate lysosomal positioning and subsequent autophagy. They also showed that albendazole treatment promoted the degradation of insoluble ubiquitinated proteins and αSyn in cultured cells.

Major Comments.

1) Two compounds, for instance teniposide and albendazole both requires JIP4 and/or TRPML1 to regulate lysosomal positioning and autophagy but their action seems different. What is the actual mechanism by which these compounds require JIP4/TRPML1. How inhibition of Topoisomerase leads to increase of JIP4 phosphorylation? Do teniposide and albendazole both affect calcium release from TRPML1?

RESPONSE:

We previously reported that acrolein/H2O2 accelerates lysosomal retrograde trafficking by TRPML1 and phosphorylated JIP4. Mechanistically, JIP4 was phosphorylated by CaMK2G activated by Ca2+ released from TRPML1 (EMBO J 41: e111476, Sasazawa et al., 2022). TRPML1 acts as a reactive oxygen species (ROS) sensor in lysosomes (Nat Commun 7: 12109, Zhang et al., 2016). We concluded that acrolein induces ROS production, which then activates TRPML1. (EMBO J 41: e111476, Sasazawa et al., 2022). Therefore, topoisomerase inhibitors (topo-i) may induce ROS and stimulate TRPML1. We examined intracellular ROS levels in response to topo-i. As shown in revised Fig. 4A, the topo-i teniposide, etoposide, and amsacrine significantly increased ROS levels. Moreover, N-acetyl-L-cysteine, an ROS scavenger, partially attenuated lysosomal clustering induced by topo-i (revised Fig. 4B). In addition, Ca2+ imaging showed that teniposide, but not albendazole, upregulates Ca2+ flux (revised Fig. 4C). Based on the activity of CaMK2G siRNA as shown in Fig. 5D, 5E, and S5, topo-i may activate TRPML1 in a ROS-dependent manner and increase PI(3,5)P2 binding with TRPML1 (Nat Commun 1, 38, Dong et al., 2010). Consecutive Ca2+ release via TRPML1 activated CaMK2G and is followed by enhanced lysosomal transport toward the MTOC via JIP4 phosphorylation.

We have added the revised Fig.4A and 4B data in Fig. S8A and S8B, and the related description of these experiments in the Discussion section (page 11, lines 401 to 409). We have also added the data in revised Fig. 4C to Fig. S6 and the related description of these experiments in the Results section (page 7, lines 266 to 267).

Conversely, we showed that benzimidazoles, including albendazole, induce lysosomal clustering mediated by JIP4, TRPML1, ALG2, and Rab7. Moreover, benzimidazoles showed lysosomal clustering activity within a narrow concentration range, as shown in Fig. S7D. Benzimidazoles inhibit tubulin polymerization (Int J Paras 18:885–936. Lacey et al., 1988). We hypothesized that the effect of tubulin polymerization induced by benzimidazole plays a key role in the induction of lysosomal clustering as described in the Discussion section. To clarify this, we observed the behavior of tubulin filaments in response to various albendazole concentrations under confocal microscopy. As shown in revised Fig. 4D, conditions where albendazole was administered to induce lysosomal clustering, tubulin filaments were observed only near the MTOC, and the filaments in the cell periphery were disassembled. In contrast, when exposed to higher albendazole concentrations, tubulin filaments throughout the cell were disassembled, resulting in the inhibition of lysosomal clustering This would explain why benzimidazole exerts lysosomal clustering activity within a narrow concentration range. Under JIP4, TRPML1, ALG2 and Rab7 silencing, lysosomes may fail to interact with microtubules, resulting in the inhibition of lysosomal clustering. We postulated that albendazole-induced lysosomal clustering is not mediated by factors activated by specific stimuli in lysosomal transport but, rather, is induced by spatially constraining conventional lysosomal transport mediated by various adaptors (i.e., JIP4, TRPML1, ALG2, and Rab7) through tubulin disassembly. We have added the data in Fig. S9C and the related description of these experiments in the Discussion section (page 12, lines 428 to 436).

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__Revised Fig. 4. __

1. SH-SY5Y cells were treated with the indicated compounds (10 µM) for 4 h. The amount of intracellular reactive oxygen species (ROS) is examined by ROS Assay Kit -Highly Sensitive DCFH-DA (Dojindo) and the normalized pixels above threshold as measured using an INCellAnalyzer 2200 and ImageJ.
2. SH-SY5Y cell lines were pretreated with 0.1 mM N-acetyl-L-cysteine (NAC) for 24 h and then treated with the indicated compound (10 µM) for an additional 4 Cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies. Lysosomal distribution was examined using an INCellAnalyzer 2200 and quantified using ImageJ software.
3. SH-SY5Y cells were treated with teniposide, amsacrine, etoposide, albendazole (1, 5, 10 µM), oxibendazole (0.1, 0.5, and 1 µM), or and mebendazole (0.5,1, and 5 µM) for 4 h, and stained with Fluo4-AM for 30 min. The fluorescence intensity was measured using a plate reader.
4. SH-SY5Y cells were treated with albendazole (10 and 100 µM) or nocodazole (0.5 and 10 µM) for 4 h. Cells were fixed and stained with LAMP1 (red) and a-tubulin (green) antibodies.

   2) The authors should clarify the functional advantage of these drugs identified in this study as drugs for Parkinson's disease by comparing with known autophagy inducers such as Torin1 or rapamycin.　

RESPONSE:

To evaluate the functional advantage of lysosome-clustering compounds over Torin1, we evaluated the degradation activity of insoluble aSyn induced by the addition of aSyn fibrils to aSyn-GFP cells. Torin1 induced the degradation of insoluble aSyn by autophagy, as shown in revised Fig. 5A. However, the degradation activity of albendazole was more vigorous, as shown in revised Fig. 5B. In contrast, we observed that Torin1 exhibited more autophagic induction activity than albendazole, as assessed using Halo-LC3. Similar results were obtained with teniposide (revised Fig. 5C). These results suggest that albendazole, with its ability to concentrate lysosomes around the degradation substrate, facilitates more effective degradation of insoluble aSyn than Torin1. This presents a significant advantage in the development of therapeutics for Parkinson's Disease. Moreover, Torin1 acts on the upstream signals of autophagy by inhibiting mTORC1, potentially impacting diverse cellular responses. Conversely, compounds that induce lysosomal clustering target the final step of autophagic degradation, which may have fewer side effects. We have added the description of these experiments in the Results section (page 10, lines 366 to 380) and the Discussion section (page 11 lines 410 to 412) and presented the data in Fig. S7B–S7E and Fig. 6D.

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__Revised Fig. 5. __

1. SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000. After 48 h, the transfection reagent was washed out, and the SH-SY5Y cells were treated with 100 nM Torin1 with or without 100 nM bafilomycin A1 for 8 h (B). Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble), then subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting with the indicated antibody(left). The amount of insoluble aSyn was quantified using Image J software (C).
2. SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000. After 48 h, and washing out the transfection reagent, SH-SY5Y cells were treated with albendazole (10μM) with or without 100 nM Torin1 for 8 h. Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble), then subjected to SDS-PAGE and immunoblotting with the indicated antibody (left). The amount of insoluble aSyn was quantified using Image J software.
3. SH-SY5Y cells stably expressing Halo-LC3 were labeled for 20 min with 100 nM TMR-conjugated ligand in a nutrient-rich medium. After washing with PBS and incubating the cells in normal medium for 30 min, cells were treated with DMSO, teniposide (10 μM), albendazole (10 µM), and/or Torin1 (100 nM) for 8 h. Cell lysates were immunoblotted with the indicated antibody and analyzed by in-gel fluorescence detection (left). The HaloTMR band intensity was normalized by the sum of the band intensities of HaloTMR-LC3B and HaloTMR (right).

   3) Related to the previous question, in Fig.6A and B additional data comparing novel compounds with established autophagy inducers, such as torin1 and rapamycin, should be included and discussed.

RESPONSE:

As indicated in a previous response, we evaluated the autophagic induction activity of Torin1, and the results have been added to Fig. 6D. In addition, co-treatment with Torin1 and teniposide or albendazole induced autophagy more effectively than Torin1 treatment alone, without affecting mTOR inhibition activity (revised Fig. 4C). These findings indicate that the induction of autophagy by lysosomal clustering compounds is not caused by autophagosome formation but by the formation of autolysosomes. We have added a description of these experiments in the Results section (page 9, lines 316 to 322) and have added the data in Fig. 6D.

4) The authors should examined whether increased degradation of insoluble proteins and αSyn are dependent on JIP4. 　

RESPONSE:

As the Reviewer suggested, we have examined whether lysosomal accumulation through the JIP4-TRPML1 pathway is crucial for the degradation of aSyn aggregates. We evaluated the degradation activity of insoluble aSyn induced by the addition of aSyn fibrils to aSyn-GFP cells when JIP4, TMEM55B, or TRPML1 were knocked down. Interestingly, the insoluble fraction assay showed that JIP4 and TRPML1 knockdown regulated the decrease of aSyn-GFP and p-aSyn levels in the insoluble fraction for both DMSO and albendazole treatments. The results were particularly more pronounced with TRPML1 knockdown. However, the knockdown of TMEM55B did not produce such findings (revised Fig. 6). These data suggest that lysosomal clustering via the JIP4–TRPML1 pathway plays a significant role in aSyn degradation. We have added a relevant description in the Results section (page 10, lines 373 to 380) and have added the data in Fig. S7F and S7G.

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__Revised Fig. 6. __

SH-SY5Y cells over-expressing aSyn-GFP were transfected with the indicated siRNAs for 24 h and then transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000 for 48 h. After washing out the transfection reagent, the SH-SY5Y cells were treated with dimethyl sulfoxide or albendazole (10 μM) for 8 h. Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble) and subjected to SDS-PAGE and immunoblotting with the indicated antibody. The bar graph presents the ratio of the insoluble aSyn-GFP to the soluble GAPDH or insoluble p-aSyn to the soluble GAPDH of the intensity of the data in panel F. Data are expressed as mean ± standard deviation.

5) Authors only utilized. SH-SY5Y cells in this study. It is important to examine whether these compounds also regulate lysosomal positioning and autophagy in other cell lines.

RESPONSE:

As per the Reviewer’s suggestion, we evaluated the lysosomal-clustering activity induced by topo-i and benzimidazole in human adenocarcinoma HeLa cells. As shown in revised Fig. 7A and 7B compounds do not induce lysosomal clustering or autophagy in HeLa cells. Furthermore, in the case of benzimidazole, they transport lysosomes to the cell periphery. Previously, we found that oxidative stress accumulates lysosomes in a neuroblastoma-specific manner through the TRPML1–phosphoJIP4-dependent mechanism (EMBO J 41: e111476, Sasazawa et al., 2022). Since we have demonstrated that topo-i-mediated lysosomal trafficking is dependent on the TRPML1–phosphorylated JIP4 complex, we hypothesized that several molecules involved in lysosomal trafficking are absent in HeLa cells.

In contrast, we showed that albendazole-induced lysosomal clustering is due to tubulin depolymerization. Therefore, we examined the relationships between tubulin depolymerization and lysosomal clustering induced by albendazole in HeLa cells and found that albendazole did not induce lysosomal clustering but rather inhibited it at higher concentrations (revised Fig. 7B). Interestingly, similar to SH-SY5Y cells, a low albendazole concentration (10 μM) induced tubulin depolymerization only at the cell periphery, whereas a high concentration (100 μM) depolymerized the entire cell (revised Fig. 7C). However, unlike SH-SY5Y cells, no characteristic accumulation of tubulin filaments was observed near the MTOC under low albendazole concentration (10 µM); instead, they were arranged around the nucleus. Concurrently, lysosomes were around these dispersed tubulin filaments. Therefore, the differences in the effects of benzimidazole in HeLa and SH-SY5Y cells lies in the dose-dependent effects on the state of tubulin filaments. We have added a relevant description in the Discussions section (page 12, lines 419 to 422, and 437 to 453).

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__Revised Fig. 7. __

HeLa cells were treated with teniposide (10 μM), amsacrine (10 μM), etoposide (10 μM), albendazole (10 μM), oxibendazole (1 μM), or mebendazole (5 μM). Images were captured using an INCellAnalyzer2200. INCellAnalyzer2200 images were analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± standard deviation (SD). ****P HeLa cells were treated with teniposide (10 μM), amsacrine (10 μM), etoposide (10 μM), albendazole (10 μM), oxibendazole (1 μM), or mebendazole (5 μM) for 4 h. Cell lysates were immunoblotted with the indicated antibodies. The amount of LC3II was estimated using Image J software (bottom panel). HeLa cells were treated with albendazole at specified concentrations (in µM). After treatment, cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies, followed by imaging with an INCellAnalyzer2200. INCellAnalyzer2200 images were processed and analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± SD. *P  HeLa cells were treated with albendazole (10 and 25 µM) for 4 h. Cells were fixed and stained with LAMP1 (red) and a-tubulin (green) antibodies.

6) The authors conclude that the six compounds do not mediate mTOR signaling in Fig. 3, but should more carefully describe in the manuscript why they performed this experiment and what the results mean for.

RESPONSE:　

As per the Reviewer’s advice, we have changed the description in the manuscript as follows:

Previous studies have shown that lysosomal retrograde transport regulates autophagic flux by facilitating autophagosome formation by suppressing mTORC1 and expediting fusion between autophagosomes and lysosomes (Kimura et al, 2008; Korolchuk et al, 2011). Conversely, we recent found that acrolein/H2O2 induces lysosomal clustering in an mTOR-independent manner (Sasazawa et al., 2022). In this study, we aimed to identify pharmacologic agents that act downstream rather than upstream in the autophagy pathway, with the goal of minimizing side effects. Therefore, we evaluated the effects of the compounds on the mTOR pathway. As shown in Fig. 3, these compounds induced lysosomal clustering without affecting mTOR activity, indicating their potential as promising candidates for PD therapy. We have added the description of these experiments in the Results section (page 6, lines 202 to 208 and line 217).

Minor comments. 1) The name of the compound should be written in the red point of Fig.2A.

RESPONSE:

We have included the names of the six compounds identified and are listed in Fig. 2A.

2) Regarding images of Fig.2B, the magnified images and quantitative data should be added.

RESPONSE:

We have included magnified images, as well as the quantitative results of lysosome clustering analysis using INCellAnalyzer2200 in Fig. 2B.

3) The results of Fig.2C need to be explained more carefully. A quantitative data is missing.

RESPONSE:

We have included the quantitative results of western blot in Fig. 2B.

4) Fig.S2, which compares autophagy activity with conventional agents, should be quantified and added to the Fig.3.

RESPONSE:

We have presented the results of RFP/GFP quantification performed by FACS analysis using SH-SY5Y cells stably expressing RFP-GFP-LC3 in Fig. S2, which is equivalent to the quantification of the data in the Fig. S2 image. These data are now presented as Fig. S2B. Since Fig. 3 focuses on mTOR signaling, we preferred to retain the figure number.

5) In the statistical analysis of Fig.4B, the clustering value was increased by siRILP, which should be briefly described in the manuscript.

RESPONSE:

On the contrary, the enhancement of lysosomal retrograde transport in RILP knockdown cells in Fig. 4B suggests the potential involvement of RILP in anterograde transport. However, to the best of our knowledge, no reports have investigated this matter. We presume that negative feedback mechanisms may be present. We have added this description to the Results section (page 7 lines 238 to 241).

6) In Fig.4A and B, it is possible that the knockdown efficiency of siRILP and siTMEM55B was not sufficient to observe the effect on lysosomes, and this concern should be described in the manuscript.

RESPONSE:

We established starvation conditions, which induce TMEM55B-dependent lysosomal retrograde transport, as a positive control and evaluated the lysosomal induction activity of compounds when TMEM55B was knocked down. As shown below, lysosome accumulation was suppressed only when subjected to starvation treatment, indicating sufficient knockdown efficiency of TMEM55B. These compounds induced lysosomal clustering independently of TMEM55B, unlike under starvation conditions. We have added a description of these experiments in the Results section and presented the data in Fig. S4A (page 7, lines 232 to 237).

On the other hand, we were unable to establish a positive control for RILP knockdown experiments because conditions that regulate RILP-dependent lysosomal distribution dependent are not understood. While we cannot completely rule out the possibility of insufficient knockdown efficiency, considering that RILP knockdown appears to paradoxically enhance lysosomal induction, as mentioned above, it is reasonable to assume that the knockdown effect has occurred.

__Revised Fig. 8. __

SH-SY5Y cells were transfected with TMEM55B siRNA for 48 h and then treated with teniposide (10 μM), albendazole (10 μM), or starvation medium for 4 h. Cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies. Images were captured using an INCellAnalyzer2200. INCellAnalyzer2200 images were analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± standard deviation (SD). ****P

7) The authors should add the results of the WB experiment showing the amount of JIP4 protein in Fig.5G.　

RESPONSE:

We have added western blot data that introduce flag-JIP4 into JIP4KO SH-SY5Y cells, which are presented in Fig. 5G.

8) In Fig.5F, images of JIP4KO cells that do not express FLAG-JIP4 should be added as controls, and further quantification should be done on cells in all three conditions.

RESPONSE:

We have added immunofluorescence data that do not express flag-JIP4 in Fig. 5F, which had been obtained simultaneously during the acquisition of other images. Furthermore, we quantified lysosomal distribution, which is shown in Fig. 5E. Using ImageJ, we automatically delineated approximately 70% of the cell area toward the cell center and designated the region excluded from this area as the cellular peripheral region (revised Fig. 9A). Subsequently, we quantified the proportion of lysosomes contained within that region in cells expressing flag-JIP4 (revised Fig. 9B). We have added this experimental data in Fig. 5E.

A B

__Revised Fig. 9. __

1. Approximately 70% of the cell area toward the cell center was automatically delineated using ImageJ, with the region excluded from this defined as the cellular peripheral region.
2. JIP4 KO cells were transfected with flag-tagged JIP4 (wild-type and T217A) for 24 h and treated with teniposide (10 μM) for 4 h. Cell lysates underwent SDS-PAGE and were immunoblotted with anti-JIP4 and anti-actin The graph displays the percentage of cells with peripheral lysosomes. Data are expressed as mean ± standard deviation. *P 20).

   9) In Fig.6A, the total amount of JIP4 seems to change in some agent treatments, which needs to be explained.

RESPONSE:

As per our response to Reviewer 1, we evaluated the decrease in JIP4 expression by WB after 4 h of treatment with 10 μM teniposide. The teniposide-induced decrease of JIP4 was suppressed by bafilomycinA1 co-treatment, indicating that JIP4 was degraded by teniposide-induced autophagy (revised Fig. 3). We have added the data in Fig. S6, and the related description of these experiments have been added to the Results section (page 8, lines 289 to 293).

10) In Fig.7C and D, the effect of drug treatment on the amount of ubiquitinated proteins should also be checked.

RESPONSE:

We have included ubiquitin protein blots in Fig. 7C and 7D.

11) In Fig.8B, it is described that lysosomes are more localized in αSyn by drug treatment, but more convincing images and quantitative data are needed.

RESPONSE:

. The colocalization of LAMP2 and aSyn-GFP aggregates was assessed by measuring the fluorescence values of lysosomes in contact within the aSyn-GFP aggregation area using ImageJ. We have added this quantified data in Fig. 8D.

Reviewer #2 (Significance (Required)): Although the reviewer appreciates the discovery of novel drugs to induce autophagy through regulating lysosomal positioning, the detailed action of these compounds and their superiority in the field are not clear.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)):____ __ In this manuscript, Date et al. sought to identify compounds that promote protein aggregates clearance - in particular those formed by mutant alpha synuclein. Briefly the authors screened a library of clinically approved compounds for inducers of lysosomal clustering followed by a secondary screen for autophagy inducers. By this two-step procedure, the authors identified three topoisomerase inhibitors and three anthelmintics as hits. Next, the authors unveiled that lysosomal clustering induced by these compounds is independent of mTORC1 but requires TRPML1 and JIP4. Moreover, the topoisomerase inhibitors hits involved phosphorylation of JIP4 while the anthelmintics additionally required Rab7 and ALG2. Intriguingly, the authors found that lysosomal clustering was prerequisite to autophagy induction. Focusing on the class of anthelmintics (i.e. albendazole) the authors showed that these induce autophagy to degrade aggregates formed upon proteasome inhibition. Lastly, the authors demonstrated that albendazole also led to increased degradation of αSyn aggregates through autophagy induction.

Major points 1) Most importantly, the authors need to tone down the significance of their findings throughout the manuscript. For examples, they should restrain from using "nullified" when it is really reduced only by 10-25 %.

RESPONSE:　

We have changed the description in the manuscript according to the Reviewer’s suggestion.

2) The authors claim that the topoisomerase inhibitors led to JIP4 phosphorylation while Figure 5C actually shows the opposite (partially reduced phosphorylation compared to DMSO treatment) and the Jak3 inhibitor has no obvious effect. The authors should quantify the phostag results.

RESPONSE:

We agree with the Reviewer that the Phos-tag PAGE results of JIP4 in Fig. 5C is complicated, and the bands were not clear. We have replaced these with more robust data (Fig. 5C).

3) Figure 6A/B: Why do all compounds except Mebendazole affect the abundance of JIP4?

RESPONSE:

As per our response to Reviewer 1, we evaluated the decrease in JIP4 expression by WB after 4 h of treatment with 10 μM teniposide. The teniposide-induced decrease of JIP4 was suppressed by bafilomycinA1 co-treatment, indicating that JIP4 was degraded by teniposide-induced autophagy (revised Fig. 3). We have added the data in Fig. S6, and the related description of these experiments have been added to the Results section (page 8, lines 289 to 293).

4) Figure 7C: The blot is not convincing. The authors should quantify this effect.

RESPONSE:

We evaluated and confirmed the degradation of p62 by albendazole, as shown in Fig. 7C.

Reviewer #3 (Significance (Required)):

Overall, the work of Date and colleague highlights the role of lysosomal clustering in clearing protein aggregates. Importantly, the identified classes of compounds might open new avenues for rationalizing treatment strategies for neurodegenerative diseases. However, several critical points remain.

• *

Reviewer #2 (Public Review):

The following submission titled "Xanthomonas citri subsp. citri type III effector PthA4 directs the dynamical expression of a putative citrus carbohydrate-binding gene for canker formation" by Chen et al. provides evidence that PthA4 binds to PCs9g12620 to downregulate expression potentially for citrus canker disease development. They tackle a relevant, complicated problem about the timing and regulation of an S gene expression and its relationship to disease development. Most often research stops at an S gene that is upregulated. This study aims to define the complexity of TAL effector family proteins beyond their standard activation role. Cs9g12620 encodes a putative carbohydrate-binding protein, and downregulation of this occurs via PthA4-CsLOB1 direct interaction. Silencing of Cs9g12620 leads to reduced virulence of X. citri, highlighting its importance as an S gene target from PthA4-mediated CsLOB1 induction. The authors also hypothesize that PthA4 represses the expression of Cs9g12620, and it seems to depend not on DNA binding by PthA4 but rather CsLOB1 interaction. This provides an interesting mode of action for a TAL effector, which typically is described as a transcription factor. An overall curiosity is that TAL effectors like PthA4 induce gene expression for virulence activity, but the authors do not probe this question with artificial TAL effectors or PthA4 variants to define the domains required for this activity. These tools, which are widely used in TAL effector research, could help determine what domain is responsible for this repression and if it is unique to PthA4 or a general TAL phenomenon. Work is further needed to also demonstrate the repressive role of PthA4 over time because it is not explicitly clear that the time-related suppression is directly attributed to the PthA4-CsLOB1 interactions.

(1) The authors show that both WT but not WT expressing AvrXa7 induce Cs9g12620 and CsLOB1. They performed an adjacent supportive experiment comparing a Tn5-disrupted pthA4 to WT and saw a similar induction. Do the authors have a southern blot or genome sequence to show this is the true mutation? Have the authors complemented the Tn5 strain with pthA4 and an artificial TAL effector?

(2) Figure 2 and "The expression of Cs9g12620 depends on pthA4 during Xcc infection" section: Overall I cannot determine the biological importance as written in the text about examining an ortholog of Cs9g12620 that is not expressed. The title of Figure 2 is: "Cs9g12620 and Cs9g12650 show different profiles of expression owing to the genetic variation in promoter." What is the biological importance of showing that there is promoter variation when the RNA-seq pointed to this target? This is unclear. Now, an interesting experiment would be to create an artificial TAL that activates the expression of Cs9g12650, which was, yes, not expressed in Nicotiana, but this wasn't examined in citrus and could be with an artificial TAL effector. Moreover, if this is about how something is not expressed, this seems out of place in the story before we arrive at the repression aspect of the narrative. Is the lack of expression a typical state of this gene family and do TAL effectors induce this for virulence? Is it also possible that RT alone isn't sensitive enough to detect relevant Cs9g12650 expression? Could the authors rather build on their RNAseq data or maybe use qPCR, a more sensitive approach, to see if this gene is expressed. Overall, this seems like a non-issue still because it isn't clear why this is important to support their narrative. Finally "2 μg of total RNA extracted" seems to be an extremely high input for RT. In summary here, it would be nice to see the hypothesis they tested and how it supports their overall aim because this is unclear.

(3) Figure 3C: The authors should include a 35S::GUS + 35S::pthA4 control. This control is missing to show that the suppression is not due to overexpressing the two proteins simultaneously.

(4) Figure 3E&G are just the same but rotated. Please include a separate replicate as this would be more beneficial to examine. With this and concerns on some of the reporting, the raw data and images should be included as supplemental for each replicate and detailed as if they are a regular figure.

(5) Figure 3G: What is low and high? There are quantifiable values (e.g. RLU) here that correspond to the intensity of the figure legend. There should be a water/buffer infiltrated control.

(6) Figure 3F: The Y1H data demonstrate that PCs9g12620 is bound by PthA4. The second panel for the gel mobility shift is however lacking a complementary treatment with PCs9g12620 WT. These gel mobility shift assays are always relative to something, and there is no comparison here unfortunately to other treatments. An example to follow as a model for formatting and experimental design could include as seen in Figure 5 by Duan et al. MPP (DOI:10.1111/mpp.12667). These should be performed as a single experiment not separated by panel D. A GST-Tag only should always be an additional control.

(7) Figure 4: CsLOB1 activates Cs9g12620. Figure 4C: A reasonable control would be to include 35S::GUS and 35S::PthA4.

(8) Figure 5F: The purpose of this experiment to show the multiplication over time and increase is not clear. It would be expected to see an increase in growth over time during susceptibility; so why was this documented?

(9) Figure 5: Cs9g12620 expression decreases along with expansion and pectin esterase expression. How do we know that this is not a general downregulation of gene expression more broadly due to cell death or tissue deformation at 10 dpi? To test if this is also PthA4-specific, an experiment needed would be to test a specific pthA4 mutant rather than the TAL effectorless strain, which is already pretty weak a pathogen and does not trigger expression of any tested genes to wild-type levels to see if this is a general trend or specific to PthA4 activity. Finally, why are the color bars switched for time points 5 & 10 dpi for the effectorless strain? This is the finding that led them to suggest the repression. According to the rest of the figure, the gray and black are typically 5 and 10 dpi, respectively, but they seem to be switched to fit the narrative.

(10) Figure 6 nicely documents the interaction between PthA4 and CsLOB1, but why did the authors not take the additional step to define what domains are required for PthA4 interaction? This is an important curiosity of what mediates this interaction. Was it the repeats or C- or N-terminus? Is this general to TAL effectors or precise to PthA4? This seems like the crux of the story especially since there is a TAL effector binding cited in the promoter.

(11) Figure 7: RNAi-mediated silencing of Cs9g12620 demonstrates that this gene is a susceptibility target for X. citri as seen by colonization (E). First, the symptoms are not quite clear in A, and the morphological changes are unclear. Are there additional images for these to showcase the difference reproducibly? They hypothesize that there is complexity in Cs9g12620 expression during infection as proposed in Figure 8. It seems pretty important to perturb this in the opposite direction with artificial TAL effectors that either target a) Cs9g12620 for induction and b) CsLOB1 in a 049E background. One would hypothesize that this would not allow for the CsLOB1 interaction because they demonstrate this is PthA4-specific and therefore Cs9g12620 expression would not decrease while CsLOB1 is induced.

(12) Figure 8: It is unclear if this is an appropriate model. The impact of CsLOB1-PthA4 interaction is depicted as a late phenomenon based on Cs9g12620 expression. However, it is not clear from their data that the CsLOB1-PthA4 interaction does not happen at the early stages of infection. This is not defined by their experiments proposed. As mentioned above, an overall concern is that the authors do not test variants of PthA4 or domains that could examine specifically what permits this suppression. Is this a general TAL effector structure-mediated phenomenon or is it something unique about PthA4 in this family? Does it require both DNA binding and interaction with CsLOB1?

Reviewer #2 (Public Review):

Diaphorina citri is the primary vector of Candidatus Liberibacter asiaticus (CLas), but the mechanism of how D. citri maintains a balance between lipid metabolism and increased fecundity after infection with CLas remains unknown. In their study, Li et al. presented convincing methodology and data to demonstrate that CLas exploits AKH/AKHR-miR-34-JH signaling to enhance D. citri lipid metabolism and fecundity, while simultaneously promoting CLas replication. These findings are both novel and valuable, not only have theoretical implications for expanding our understanding of the interaction between insect vectors and pathogenic microorganisms but also provide new targets for controlling D. citri and HLB in practical implications. The conclusions of this paper are mostly well supported by data, but some aspects of phrasing and data analysis need to be further clarified and extended.

Key Considerations:

There are specific instances where additional information would enhance comprehension of the results and their interpretation.

There seem to be two inconsistencies related to some results depicted in Figures 1, 2, 3 and 5.

Firstly, Figure 1 shows the effect on CLas infection (CLas+) compared to the control (CLas-), where results show an increase of TAG, Glycogen, lipid droplet size, oviposition period, and fecundity. In Figures 2, 3, and 5, the authors establish the involvement of the genes DcAKH, DcAKHR, and miR34 in this process, by showing that by preventing the function of these three factors the effects of CLas+ are lost. However, while Figure 1 shows the increase of TAG and lipid droplet size in CLas+, Figures 2, 3, and 5 do not show a significant elevation in TAG when comparing CLas- and CLas+.

Secondly, in addition to the absence of statistical difference in TAG and lipid droplet size observed in Figure 1, Figures 2, 3, and 5 show an increase in TAG and lipid droplet size after dsDcAKH (Figure 2), dsDcAKHR (Figure 3) and agomiR34 (Figure 5) treatments. Considering that AKH, AKHR, and miR34 are important factors to CLas-induce increase in TAG and lipid droplet size, one might expect a reduction in TAG and lipid droplet size when CLas+ insects are silenced for these factors, contrary to the observed results.

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Referee #3

Evidence, reproducibility and clarity

Summary:

In this manuscript the authors are interested in understanding how fission yeast respond to a Nitrogen Signaling Factor (NSF) that has previously been shown to allow Leucine auxotrophs to grow in the presence of Leucine when Nitrogen Catabolite Repression (NCR) is triggered by the presence of a high quality Nitrogen source such as Ammonium Chloride (NH4Cl).

The authors begin with a screen to identify genes that affect the ability of wild type cells grown near cells with leucine auxotrophy to enhance or abolish NCR phenotype. They screened the non-essential gene deletion library which they manipulate so that it only contains a leucine auxotrophy (unlike the original gene deletion library which contains additional auxotrophies). They identify 137 genes whose deletion allows growth of Leu auxotrophs in the presence of Leucine and Ammonia without the presence of WT cells. These genes are required for NCR. They further identify 203 genes which do not bypass NCR even in the presence of wild type cells, and are thus important for bypassing NCR in the presence of WT cells.

They then conduct a second screen to identify which of these genes are important for bypassing NCR in response to the Synthetic NSF, 10(R)-hydroxy-8(Z)-octadecenoic acid, by looking for genes which grow in the presence of leucine when ammonia is not present, but do not grow in the presence of leucine when ammonia is present, even when NSF is added. This second screen identifies 117 strains carrying deletions in a gene set enriched for genes related to cellular respiration and mitochondria. They then show that the NSF bypass of NCR is linked to respiration by showing that it is abolished in the presence of the respiration inhibitor Antimycin A, that growth in low levels of glucose can bypass NCR in the absence of NSF< and that cells supplemented with NSF have a higher oxygen consumption rate.

To gain insight into how the cell responds to NSF, the authors then gather RNA expression data from cells grown in high ammonium concentrations following treatment with NSF relative to a negative control treated only with Methanol (the vehicle into which NSF is dissolved). They argue that the gene expression pattern resembles gene expression data from cells undergoing respiration in glycerol relative to cells undergoing fermentation in glucose. They show that the upregulated genes relate to trehalose synthesis, detoxification of Reactive Oxygen Species, and cellular fusion and the downregulated genes are related to cellular adhesion and flocculation.

They validate their RNA-seq measurements by showing that the two most highly induced and two most highly repressed genes respond to NSF addition in a dose dependent manner and do not respond oleic acid which is chemically similar to NSF. The most highly responsive gene they identify is an uncharacterized gene, SPBPB2B2.01, which they suggest naming "NSF-responsive amino acid transporter 1" (nrt1). They also show that the nrt1 response is dependent on the culture density, and that the response is present (though the magnitude varies) in YES and in EMM under varying nitrogen concentrations, and that yfp driven by the nrt1 promoter is induced by NSF.

The authors then investigate the 8 transcription factors that were present in their list of genes required for NSF-mediated adapted growth. They note that Hsr1 was the only one of these transcription factors, indeed the only gene, that was a hit in their screen for NSF-mediated adapted growth and whose expression was induced upon NSF treatment. To see if the activity of the other transcription factors changed in response to NSF treatment, the authors then gathered ChIP-seq data using 6 of these transcription factors as targets for IP. They saw that for Hsr1 and Php3, targets that had increased RNA-seq expression showed an increase in promoter occupancy while for Hsr1, Php3, Adn2, and Atf1, genes that had decreased RNA-seq expression showed a decrease in promoter activity.

Finally the authors attempt to identify the mode of action of NSF by generating a functionalized NSF with an alkyne tag (AlkNSF) which they then use as a probe to identify NSF binding partners. They first show that AlkNSF does allow bypass of NCR, although at 30-fold higher concentration. Also AlkNSF induces nrt1 expression in a dose dependent manner, although the expression saturates at a lower level and requires a much higher concentration for induction. They then look for proteins that co-purify with AlkNSF compared to a control that was pre-incubated with NSF which was expected to compete off AlkNSF. The only significant protein they saw was Ayr1, which was not identified in their screen and which did not abrogate NSF bypass of NCR when deleted independantly. They saw that Ayr1 deletion actually increases the response of nrt1 and mei2 targets to NSF, and speculate that Ayr1 metabolises NSF and reduces the cell's ability to respond to NSF to bypass NCR.

They then repeat the affinity purification / mass spec protocol in an Ayr1 delete cells to identify other interaction partners, this time incubating with a higher concentration of NSF, and also comparing to an experiment using Alkeyne Oleic Acid as a control for non-specific binding. The top two specific hits from this assay are Hmt2 and Gst3. NSF was still able to rescue NCR in gst3 deletes, indicating that it was not relevant for the phenotype. Cells lacking hmt2 did not grow in EMM, but did grow in YES when not supplemented with ammonium and when supplemented with ammonium did not grow, and addition of NSF did not rescue growth. They also see that nrt1 and mei2 gene induction in response to NSF is abolished when hmt2 is deleted. They then argue that hmt2, a sulfide:quinone oxidoreductase localized in the inner membrane of mitochondria is a direct target of NSF that triggers a switch to respiratory metabolism and allows bypass of NCR.

Below are comments that I think ought to be addressed prior to publication (Major comments)

1. In line 70, the authors state that "S. pombe cells rely on their own BCAA synthesis to sustain growth" when grown alongside Leucine when ammonium is supplied in the media. If prototrophs can inhibit NCR via NSFs in neighboring auxotrophic cells on the same plate, couldn't they also inhibit NCR within their own colony? How do we know that prototrophic cells grown in high quality nitrogen sources along with, say leucine, are not taking up leucine? The fact that leucine auxotrophs cannot grow in high quality nitrogen sources when leucine is present does not imply that wild type cells must use be synthesizing BCAAs rather than importing them. In a recent paper (Kamrad et al Nat. Microbiol. 2023, https://www.nature.com/articles/s41564-022-01304-8), it was shown that S. cerevisiae cells grown in lysine and in high concentrations of ammonium uptake lysine rather than synthesize it as lysine concentrations in the media are increased. I am aware via unpublished results that this is the case for Leucine as well. I would be surprised if the same isn't true in S. pombe. The authors should caveat or remove this assertion.
2. It is important for the authors to put their observation linking respiration to rescue from NCR in context with findings from a closely related study (Chiu et al 2022) which included some authors from this manuscript and which the authors cite. In that paper, it was shown that the siderefore ferrichrome can also rescue NCR in fission yeast. That paper stated "It is likely that ferrichrome increased mitochondrial activity, which enabled efficient utilization of glucose downstream of the glycolytic pathway" based on experiments in different concentrations of glucose. This evidence seems to support the link between respiration and rescue from NCR proposed by the authors of this manuscript. The authors should acknowledge this closely related and earlier work as it strengthen's the case they are trying to make. They could even test if ferrichrome addition makes cells sensitive to antimycin A (as in fig 1E), but that extra experiment would be optional in my opinion.
3. In figure 1B for the second screen I do not understand what the photos represent. For the photos, two rows are meant to have no NH4 and also no NSF and the label on that image makes no mention of Leucine supplementation. In the diagram there are two rows that have NH4 and leucine and one row that has no NH4 but does have leucine. I assume the diagram is correct and the labels on the images are incorrect.
4. It would be important for the authors to put their observation linking respiration to rescue from NCR in context with findings from Chiu et al 2022 which the authors cite. In that paper, it was shown that the siderefore Ferrichrome can also rescue NCR in fission yeast which the authors site which found that a siderephore rescues NCR. Also the authors of that paper stated "It is likely that ferrichrome increased mitochondrial activity, which enabled efficient utilization of glucose downstream of the glycolytic pathway." based on experiments in different concentrations of glucose. This evidence seems to support the link between respiration and rescue from NCR proposed by the authors of this manuscript.
5. In line 133. The authors state that the 29 mutants that didn't grow under Leucine supplementation either without NH4CL or with NH4Cl whether or not NSF was present were "related to EMM Growth, leucine uptake, or utilization of ammonium as the sole nitrogen source." The first two make sense, but I can't see why a a strain with deletion of a gene related to utilization of ammonium as a sole nitrogen source wouldn't grow when supplemented with leucine. In fact for all the leucine auxotrophs in the screen, if one was to try to grow them with ammonium as the sole nitrogen source they would not grow, so it isn't clear that this screen can identify genes responsible for utilization of ammonium as a sole nitrogen source. The authors should clarify or remove this point.
6. 203 strains are important for avoidance of NCR (because in the presence of Ammonium and Leucine, as well as a WT strain, they cannot grow). Of these 57 strains can't grow in the presence of a WT strain but they can grow in the presence of NSF. The authors conclude in line 138 that these strains are "likely to respond to a transmissible signal that is different from NSF". This is confusing because deletion of these genes still does allow cells to respond to NSF, however when these cells are growing in the presence of wild type cells (which in their model are releasing NSF), the cells don't grow. I am confused about the nature of the transmissible signal that the authors suggest. It would appear that when these genes are deleted and grown next to a wild type cell which sends the alternative signal and the NSF, the other transmissible signal would inhibits the ability of NSF to release NCR (as NSF can still rescue the gene). It is not clear how the other transmissible signal would work when the gene is present as it is clearly not necessary to rescue growth.

A simpler explanation might be that there was contamination in the second screen, or that there was a threshold effect - perhaps in the first screen the strains grew just below a threshold and in the second screen it grew just above that level.

The authors should clarify their interpretation for these strains, and acknowledge any alternative technical explanations.<br /> 7. The authors' efforts to removed confounding effects that might stem from additional auxotrophic alleles made the screen more convincing. However, Fig 1E, 1F, 5B, and 5E were done with EMM+Leu+Ade+Ura, while the initial strain was just done in the presence of additional Leucine. It is unclear why this was done from the text and captions, but I assume it was because they used a strain that was ade- and ura- in addition to being leu-. Given that they had strains without these additional mutations, this seems like a strange choice. The authors should acknowledge that there are possible confounding effects of adding adenine and uracil to the media, and, if they did have additional metabolic deletions, acknowledge that that could possibly be confounding.<br /> 8. Fig 1E, it appears that cells can grow without NSF in the presence of ammonium and additional amino acids after 10 days (although NSF is required for growth at 5 days). This is not a problem for the screen as that was taken at 5-6 days, but it appears as though NSF does not rescue growth so much as speed it up. The authors should acknowledge this when describing the phenotype. It also argues for a quantitative time course growth experiment to compare growth over the course of 10 days with and without NSF, although this would not be necessary to the paper's main argument.<br /> 9. In line 191 and 192, the authors suggest that the "downregulation of flocculation/adhesion related genes by NSF could serve to avoid undesirable mating during growth". If this is the case, I don't understand why mating genes and cellular fusion genes would be upregulated. What do the authors mean by undesirable mating? Wouldn't flocculation increase desirable mating as well? If all mating is undesirable, wouldn't upregulation of mating and cellular fusion genes be detrimental? 10. The authors mention that trehalose is an antioxidant, for which they reference Malecki 2019, however that paper shows no direct evidence of trehalose functioning as an antioxidant under respiratory conditions. It only shows that some trehalose synthesis genes are upregulated when cells are grown under glucose. The authors should identify primary literature to back this statement up, or soften the wording. Also trehalose is known to be a storage metabolite (which is mentioned in Malicki et al 2019, but not in this manuscript). In fact work in budding yeast has show that trehalose can be a shared metabolite that can be produced by respiring cells and used as a fermentable carbon source in communities of budding yeast cells that consist of fermenting and non-fermenting cells (Varahan et al, eLife 2019 https://doi.org/10.7554/eLife.46735). It seems that this role should be considered as an alternative explanation for the induction of trehalose in respiratory cells.<br /> 11. Line 208: The stimulatory effect of NSF on NRT1 decreased with cell density, thus cell density is likely to be an important factor in terms of gene expression. The methods section, text and figure captions do not mention the density at which cells were inoculated/harvested for RNA-seq and other experiments. If that density was more than OD 0.1, then this would be inconsistent with the measurements from Fig 3. Also in fig 3D, The culture density is not mentioned in the figure or the caption, even though the text suggests that for that experiment cells were grown at low density (Lines 212-213). The authors should provide information on density for their experiments in order for them to be reproducible, as they show it is a key factor. 12. In suggesting a name for NRT1 (NSF-responsive amino acid transporter 1), the authors assume that the gene has a role in amino acid transmembrane transport, but they have no experiments showing this phenotype. They mention that it is Inferred from homology with other amino acid transporters. I presume this name has already been approved by Pombase and is not provisional, but it seems that including phenotypes inferred from homology, rather than from experiments is unwise. Do the authors have any other direct evidence that this is a bona fide Amino Acid Transporter? Perhaps a name like "NSF-responsive gene" would be more appropriate.

Related to this, it appears that the expression level of Nrt1 may be very low (see Fig S2B in which the scale of the RNA-seq track is very small [-1,1] and the amount of expression is very small even when NSF is added). Looking at Fig 2A, the total transcript abundance did not appear to be very low in terms of counts per million (over 100) is this a discrepancy in fig S2B? Perhaps the large fold change is the result of counts very close to zero in the control condition? Also in Fig 3 the nrt1 expression levels did not appear to be especially low and they appeared repeatable. Is the RNA-seq data shown in fig S2B for nrt1 a fluke or am I misinterpreting it? <br /> 13. To show that their Chip-seq worked, the authors showed specific examples of Chip-seq reads for target genes Line 240, "Previously determined target genes of these TFs were significantly enriched in our data set, demonstrating that the experiment has worked (Figure S2A)." Is the significance here, the threshold from fig S2B? If so that threshold should be clearly stated here in the text. If it is the fact that asn1 shows up as "Fil1 bound" is strange as there are no genes that had significant changes in ChIP-seq signals for fig S2B. If there is another threshold the authors should describe it. While some of the examples they showed were convincing (e.g. php3-flag for the php3 regulated gene gln1 and the increased reads for srw1 for the reb1 target srw1), there were some targets that didn't seem to be especially enriched for their designated transcription factor. For example, the gene trx1 which was identified as an Hsr1 binding target had some binding from Hsr1, but more from Php3 and equivalent amounts for many of the other transcription factors. A clear description of how genes are chosen to be significant in the text, alongside references/selection criteria the authors used to select the specific genes shown should be provided to improve reproducability. <br /> 14. In lines 244-246 the authors state that "These differences in TF occupancy were positively correlated with target gene expression changes. That is, individual genes that were upregulated by NSF tended to be more strongly bound by the TFs, whereas downregulated genes were less occupied by the respective TFs (Figure 4A)." This is far from a general trend. The trend is not there for reb1 and fil1. In fact fil1 looks to the eye like it shows a decrease in occupancy for genes with increased expression, and I worry that the authors did a one sided test for significance that would have missed this, although the variability of the genes that don't change in this case is very high, so there could be no significant effect. The authors elaborate on some of the detail in following statements, but they should soften or remove this statement.

Related to this, in line 254, the authors state: "These results imply that NSF exposure rewires the recipient cell's transcriptional program, for which the TFs Atf1, Adn2, Adn3, Fil1, Hsr1, Php3, Php5, and Reb1 are indispensable (Table S3)." While I am convinced from the RNA-seq evidence and some of the chip-seq evidence that NSF exposure rewires cell's transcriptional program, I am not convinced that the 8 transcription factors they mention are indespensable for rewiring the transcriptional program. While they may be indespensible for the phenotype itself, Reb1, and Fil1 show no no siginificant enrichment in occupancy of upregulated or downregulated targets (Fig 4A) and, along with Atf1, Reb1, and Fil1, have very few genes in which ocupancy is changed significantly (Fig S2B), while no chip-seq experiments were shown for Php5 and Adn3.

The more specific summary of the data (Lines 250-253) from Fig S2B describing how hsr1 and adn2 have the strongest effects of the transcription factors required for NSF-mediated NCR bypass is a much stronger message for this section. 15. In line 335, the authors state that "in contrast to other communication systems, NSF does not induce noticeable changes in S. pombe's morphology", referring to changins in mating, filamentation, and bacterial biofilm formation. However they do show very clearly that NSF does cause a large decrease in expression in flocculation/adhesion genes. The fact that they do not see a change in morphology is likely due to the fact that the lab strain in the conditions used for this assay do not flocculate. We have recently identified conditions and strains which do exhibit flocculation in this preprint [https://www.biorxiv.org/content/10.1101/2023.12.15.571870v2]. It is likely that if they had a strain and conditions that did flocculate addition of NSF would break up flocculation and thus change the morphology based on their evidence. The authors should remove or caveat this point.<br /> 16. Line 270 Fig 5B: The concentration of NH4Cl listed in the text (374mM) does not match the concentration shown on the figure (748mM). I assume this is a typo but it should be corrected prior to publication.

Also I have several minor comments to help improve the manuscript.

m1: Lines 66-70- state that "uptake of the branched-chain amino acids (BCAA) isoleucine (Ile), leucine (Leu), and valine (Val) is suppressed in the presence of high-quality nitrogen sources such as ammonium or glutamate, because the expression of transporters or permeases that are needed for the uptake of poorer nitrogen sources are down regulated (Zhang et al, 2018)." This reference is for S. cerevisiae and is a review. The authors should cite original results in S. pombe if possible, and if that is not available, alert the reader that this result is from a different species.

m2: It is unclear from the methods section how the images taken for the screens were analyzed. Were they analayzed and scored by hand, or using custom image analysis software. Either way, when publishing the authors should publish the scores for each deletion mutant in their screen. If there was custom image analysis, the authors should mention in their methods the cutoffs which they used to score growth, and consider plotting the data as a supplement so readers can get a sense of how sensitive the screen was.

m3: The authors identify 137 mutants that did not require NSF signaling to bypass NCR and claimed these genes were required for NCR. It would be helpful and give more confidence in this screen to demonstrate the extent to which the genes identified in this study overlap with any previous genes required for NCR, and whether there was any GO-term enrichment in this set.

m4: It would be interesting if the authors could speculate a bit in their discussion on why mitochondrial respiration counteracts NCR. Is there something about cells undergoing respiration that would make it easier for them to use BCAAs than to produce them, or conversely something about fermenting cells that makes it easier for them to produce BCAAs rather than importing them?

m5: It is unclear why Figure 1F has 'MP biomedicals TM' listed in the figure. It doesn't seem to be listed in the caption or the methods. Is this different media than in other experiments? If so, the authors should add that information to the methods or the caption.

m6: In Line 160, positively influenced is strange wording, do the authors mean "induced"?

m7: In the section on gene expression change upon exposure to NSF, the authors use a + after each gene name. My understanding is that that notation is meant to refer to strains with the wild type genotype of that gene, and not the gene itself. Shouldn't the gene be italicised in lower case to represent the gene? See: Lera-Ramirez et al 2023 https://doi.org/10.1093/genetics/iyad143.

m8: In Fig 2A, genes are displayed on a plot that depicts level vs log2FC, but a comparison between the fold change and p-value would be more useful, and I believe DESeq2 should provide an adjusted p-value for these genes. A related issue is that it appears as though there were no biological replicates, though there was data gathered at different time points. In these genome wide experiments, replicates can give confidence to data and help distinguish true change from intrinsic variability of expression in specific genes. Though the authors did qPCR to validate specific results, it would have improved the quality of their systems-level data to have replicates for these and other key experiments (Chip-seq, affinity purification and even the screen).

m9: Supp Fig S1: To show that similar gene expression profiles exist for other time points, it would be more convincing to show Log fold change 2h vs 4h and 2h vs 6h and show correlation, or else to make a heat map with all genes to see that genes that go up in one condition go up in the other conditions. It is not clear if the red and blue colors are defined for the 2h dataset and then mapped onto the 4 and 6h dataset, or if they are independently assigned for each plot.

m10: Mbx2 is a key transcription factor related to flocculation and adhesion genes, and its expression is correlated with expression of its targets. If this transcription factor's expression levels decreased in response to NSF, that might strengthen and help explain the decrease in expression the authors observe in flocculation/adhesion genes when cells encounter NSF. If it it does not change, it might also be interesting for readers interested in these phenotypes.

m11: In Fig 3D, The notation for the Ammonium concentrations for EMM and YES are inconcistent (+ vs parentheses), also the units (mM from the caption) are not on the figure, but the abbreviation "N" is which is confusing and inconsistent with the other plots in which NH4CL is not abbreviated. Additionally, the caption lists additional nutrients in the media for the EMM conditions (Leu, Ade, Ura) which ought to also be listed.

m12: In lines 233-235, the authors say "One possibility is that they remain bound to their target genes but become activated or deactivated by NSF directly, or posttranslational modification, such as phosphorylation in the case of Atf1". I don't think the authors intend this, but this sentence could be taken to mean that Atf1 has been shown to be phorphorylated by NSF in the reference they site. I think the authors should clarify, i.e. by saying "..such as phophorylation which is known to regulate activity of Aft1 in response to oxidative and osmotic stress [Lawrence et al 2009]".

m13: In Fig 4B and Fig S2A, there are grey and colored tracks for the chip-seq (- and + NSF), but they are very difficult to see. If grey is in front it is hard to tell how close the colored peak wehn the colored peak is lower. For example, grey is in front for pex7 while color is in front for yhb1. Could the authors add some transparancy so that the data for both conditions could be seen at once? Also there is little information on the control. My assumption for the input(ChIP) sample was that it was cross-linked and sonicated but not immunoprecipitated, but it is not clear what conditions it was in. I would assume it was done without NSF treatment in WT cells, but those details should be added in the caption or methods. In particular, in the input there is a large spike for Gsf2. Do the authors have any explanation for this and does it have anything to do with that gene's NSF responsiveness?

m14: The authors might consider putting something like Fig S2B (or even a corresponding volcano plot) as a main figure for Fig 4 in addition to the other two panels, as the individual examples from fig 4B are nice to see, but do not give a broad overview of the data.

m15: In line 348, the wording "Would score" might be better replaced by "would be identified."

Significance

Assessment:

In general I find the authors arguments compelling and their experiments convincing. The initial and follow on screens were well designed and the authors linked respiration and the action of NSF in a convincing way. The analysis of RNA-seq data was also convincing, especially regarding the decreased expression of flocculation and adhesion genes, and the follow up of specific targets gives confidence in the data (though see Major point 12 below regarding the naming and expression levels of nsf1). The identification of hmt2 as a functional target of NSF was compelling and rigorous, and the authors offer an interesting hypothesis to connect this to respiration that could form the basis of future studies.

At times I thought that some of the interpretation of the results was hard to follow, poorly worded, or off the mark (see comments below). The presentation of the CHiP seq data also felt incomplete, though the influence of Hsr1 and Adn2 on expression of NSF1 targets was convincing. The genome wide assays (RNA-seq, CHiP seq, screen and pull-down/mass spec) could have done with replicates which would have improved statistics and reliability of the results presented for those experiments, although for key messages, the authors followed up with convincing targeted experiments.

The study represents an advance on recent work in NCR in fission yeast in linking this with the broad metabolic switch between fermentation and respiration, and in that sense makes this of interest to a broader swathe of the microbiology community, outside those interested in metabolic regulation in microbes. In addition to being of interest to applied researchers interested in producing metabolites with yeast and other microbes, the link to cell signaling and, via flocculation and adhesion genes, to microbial multicellular-like phenotypes would make this work of interest to those interested in microbial communities.

Reviewer #2 (Public Review):

Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.

(1) The conclusions of the paper are mostly supported by the data although some clarification is warranted concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3, and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. Since lysines are important for the GAG-binding properties of CCL5, knowledge of the number and location of the Cy-3 labels on CCL5 is important information for the interpretation of the experimental results with the fluorescently labeled CCL5. Was the His-tag attached to the N- or C-terminus of CCL5? Indicate this for each individual experiment and consider/discuss also potential effects of the modifications on CCL5 in the results and discussion sections.

(2) In general, the authors appear to use high concentrations of CCL5 in their experiments. The reason for this is not clear. Is it because of the effects of the labels on the activity of the protein? In most biological tests (e.g. chemotaxis assays), unmodified CCL5 is active already at low nM concentrations.

(3) For the statistical analyses of the results, the authors use t-tests. Was it confirmed that data follow a normal distribution prior to using the t-test? If not a non-parametric test should be used and it may affect the conclusions of some experiments.

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

Manuscript number: RC-2023-02270

Corresponding author(s): Usha Vijayraghavan

General Statements

We thank all three Reviewers for their thorough assessment of our manuscript and their constructive feedback and comments.

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

We are encouraged by the very positive comments made on the significance of our study that it provides convincing insights on alternative modes of nuclear positioning and division which is an important question in cell biology. We also took all possible suggestions to improve the interpretation of our results, have also added some newer data to address the constructive points raised by the reviewer.

Major comments:

1. A) I am concerned about the lethal phenotype caused by slu7 deprivation. Slu7 deficiency causes defective nuclear positioning at the bud in late G2. This phenotype per se should not cause defective mitosis, so slu7 deficiency may also be interfering with other aspects of mitosis which might indeed impinge on cell viability.

Response: Our data indeed show Slu7 knockdown has severe growth defect when grown on non-permissive media (YPD) where a two-fold difference in O.D. was seen by 12 hours (Supplementary figure 2.B).

We agree with the reviewer that defective mitosis, arises from several aspects of cell cycle including those in mitosis. The data we present show G2 arrest, small-budded cells with unsegregated nuclei and large-budded cells with segregated nuclei, all which do not progress through cell cycle phases and contribute to the severe growth defect. Further, GO enrichment analysis of deregulated pathways on knockdown of Slu7 support the above findings as various cell cycle related pathways are abnormal in their expression levels. In this study, we have focused on an in depth analysis of the role of Slu7 in a particular window and uncover how it controls nuclear position for progress G2-M phase cell cycle progression. The likely targets and mechanisms by which Slu7 regulates other phases of the cell cycle which needs similar other deeper investigations in future. Our detailed analysis of nuclear movement in Slu7 knockdown cells grown in YPD for 12 hours showed no nuclear movement (Supplementary figure 3B) which is the terminal phenotype. To examine events that lead to nuclear mispositioning phenotype we investigated the dividing slu7kd cells grown in non-permissive media for only 6 hours; under these conditions Slu7 protein is still detected at lower amount (Supplementary figure 1D). From the studies of nuclear position, mitotic spindle position and dynein distribution in mother and daughter cell, we propose that in the dividing cells, the nucleus does not experience enough force to move inside the daughter bud during mitosis. Further, we delineate the role of Slu7 in the splicing of transcripts for PAC1 encoding a protein whose homolog in S. cerevisiae has a proven role in nuclear migration. In live imaging of slu7kd cells that show nuclear segregation at the start of live imaging, new bud was not formed till the end of 60 minutes, implying that are arrested after transition to mitosis. We could speculate a role for Slu7 through regulation of genes involved in mitotic exit or cytokinesis.

1. B) Supp. Fig4 shows defective mitosis in TBZ, so TBZ may be exacerbating defective mitosis of slu7-deficient cells.

__Response: __Studies with yeast and mammalian model systems have revealed that the mobility and repair of damaged DNA are compromised upon disruption of microtubules (Wu et al, 2008; Chung et al, 2015; Lottersberger et al, 2015; Lawrimore et al, 2017; Oshidari et al, 2018; Laflamme et al, 2019). These data point to reasons why the mutants in DNA damage checkpoint genes are sensitive to TBZ. In this context, we observed that CnSlu7 knockdown is also sensitive to MMS stress (shown below). In addition, recent work on human Slu7 in Hela cell lines has elucidated the its role in the maintenance of genome integrity by preventing the formation of R-loops (Jiménez et al, 2019). We suggest that TBZ may exacerbate the defective mitosis of Slu7 depleted cells, however, whether it is particular only to mitosis or to the other cellular processes where the microtubules are involved needs further investigation.

Throughout the figures it can be observed uneven chromosome/nuclear segregation in cells deprived of slu7, however, these mitotic defects have not been mentioned or explored in depth. From Supp Figure 3C it can be inferred that CENP-A segregation is uneven. Is this correct? Is CENP-A-GFP segregation normal?

__Response: __ It should be noted that in Cryptococcus, the kinetochore remains unclustered during the early phase of cell cycle, cluster to a single punctum at the end of G2 phase and then de-cluster at the end of mitosis. Since this is a highly dynamic process, its technically challenging to measure the intensity CENP-A in mother and daughter cell. In the fixed cell imaging or live imaging data, there are no appreciable differences in intensity of the GFP signal of the tagged proteins (H4 and CENPA). The uneven chromosome/nuclear segregation observed in certain panels images presented are due to technical issues in that particular stack while generating the montage. This has been re-examined and we infer that there are no major differences in the signals from GFP-H4 and GFP - CENPA through mitosis.

Additionally, taking the cue from the reviewer’s comment, we examined the likelihood of improper chromosome segregation by evaluating if there are any appreciable cell populations that are aneuploid. We revisited our flow cytometry data, we found no significant difference in the population of aneuploid cells between the knockdown strain and wildtype strain grown in non-permissive condition for 12 hours. This data was assessed again in new experiments where we also analyzed by flow cytometry the ipl1 mutant where aneuploidy is reported (Varshney et al, 2019). It has been reported in Cryptococcus neoformans that aneuploid cells are resistance to anti-fungal drug fluconazole. Preliminary experiments showed that slu7kd cells were sensitive to fluconazole and in this assay were similar to wildtype cells. Hence, we speculate that chromosome segregation is normal in Slu7 depleted cells.

If chromosome segregation is altered upon slu7 deprivation, this might also explain the drop in cell viability and slow growth rates of this condition.

__Response: __ From live microscopy imaging and flow cytometry data, we believe that the chromosome segregation is normal in Slu7 depleted cells. Dilution spotting in permissive media after growth in non-permissive media revealed that slu7kd cells resumed growth without losing viability, indicating the arrest phenotype associated with the depletion of Slu7 is largely reversible and does not cause chromosome mis-segregation (figure is now added to manuscript as supplementary figure 2D). Prolonged arrest at various cell cycle phase might lead to cell death and hence drop in cell viability.

The manuscript will improve if authors analyse chromosome segregation for example, by showing time-lapse images of chromosome dynamics during mitosis.

__Response: __Chromosome dynamics during the mitotic phase is given below. We observe that the chromosome segregation is equal in both mother and daughter bud. The uneven chromosome/nuclear segregation observed in certain panels images presented in original manuscript were due to technical issues while generating the montage.

The authors perform an RNA seq comparing wild-type cells with slu7 deficiency and detect changes in gene expression, however, they do not explore from this data the percentage of un-spliced introns genome-wide which might be very informative, even more than changes in gene expression, which many of them, might be an indirect consequence of Slu7 deficiency. Authors should re-analyze the RNA seq data looking for unprocessed mRNAs and provide information about the overall impact of slu7 in intron processing.

__Response: __ A very detailed bioinformatic analysis of the impact on slu7 on global transcriptome and splice pattern, is an ongoing study in the laboratory. The findings are indeed giving good leads which are being validated by further experiments using mini-gene exon-intron constructs. These studies are extensive and form a future manuscript identifying and characterizing intronic features which predispose an intron towards Slu7 dependency. Therefore, it falls outside the scope for this study on the cell biological role of Slu7 on mitosis, specifically nuclear position to ensure faithful mitotic segregation.

Minor comments:

__ __1. "Previous studies of slu7 mutants in S. cerevisiae and the conditional knockdown of its S. pombe homolog". Consider replacing homolog with Ortholog.

Response: The suggestion is well taken, and the word “homolog” has been replaced with word “ortholog”.

1. A) Taking these results together, we conclude that the inability of the conditional mutant to grow in the non-permissive media is due to impaired progression through the G2-M phase of the cell cycle. Is the G2/M delay the cause of the slow growth phenotype of the Slu7 deficiency?

Response: From the live microscopy, we note that even when the budding index for mitosis has been reached the nucleus in slu7kd cells is still in the mother cell and spends more time here rather than reaching the bud or bud neck. We present G2/M delay as ONE of the reasons for the slow growth of Slu7 depleted cells. Although we have showed that Slu7 depletion does not activate MAD2 dependent Spindle Assembly Checkpoint, we have not investigated the activation of other cell cycle checkpoints such as G2 DNA damage checkpoint. These are potential new leads as we infer from our RNA seq datasets that CHK1, TEL1, BDR1 and RAD51 show increased expression in Slu7 knockdown condition when compared to wildtype. It is therefore reasonable to conclude that Slu7 might play a role at various cell cycle phases through direct or indirect effect on genes involved in these phases. Delayed positioning of the nucleus during G2/M is one of the major effects that is investigated in depth in this study.

1. B) If so, growth defects of slu7 deficiency could be suppressed by ectopic expression of G2/M activators.

Response: We have not tested this possibility, but we predict that expression of G2/M activators would at best offer only partial rescue the growth defect of Slu7 depleted cells since multiple pathways are adversely affected in cells depleted of Slu7.

In this line of investigation, we have tested the consequences of PAC1 overexpression, as PAC1 expression levels and splicing are affected by loss of Slu7. We report a partial rescue of nuclear position defect during mitosis, yet these cells were arrested at cytokinesis. Further, the unavailability of an array of suitable auxotrophic (or other) markers in this model system makes it technically challenging to do rescue experiments by overexpression of multiple candidate downstream genes.

Supp Figure 3C, remove the drawing on the right. Adjust times relative to panels.

Response: The drawing has been removed and the time points have been adjusted.

1. Tracking the nucleus in wild-type cells with a small bud showed that the nucleus moved into the daughter bud, divided into two, and one-half migrated to the mother bud (Supplementary Figure 3B, top row).

Please replace the sentence: "one-half" with "one of the daughter nuclei". Additionally, as this nuclear positioning occurring during late mitosis is due to spindle elongation, I would not use the term migrated but "positioned" or "moved". Nuclear movement into the bud, which is referred to as "moved", can indeed be named "migrated".

Response: The word “migrated” in the above sentence has been replaced with the word “moved”.

1. Indicates in Figure 2B the marker used (GFP-H4), as in Fig Supp 3B.

Response: The marker has been indicated in the figure.

1. Nuclear division initiates in the bud, and one of the divided nuclei with segregated chromosomes migrates back to the mother cell (Figure 2B, top panel, wildtype, quantified in Figure 2C grey bar).

As mentioned before, I would not name this, nuclear migration as it is the result of spindle elongation, and it can be confusing or misleading for non-expert readers.

Response: The word “migrate” in the above sentence has been replaced with the word “move”.

1. These two conclusions should be revised and described in temporal/sequential order.
2. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration and division.
3. Together, these results confirmed that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear migration during the G2 to mitotic transition in Cryptococcus neoformans.

Response: We thank the reviewer for bringing out the clarity in the concluding statements. These has now been revised to read as follows:

“Together, these results confirm that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear movement during the G2 to mitotic transition in Cryptococcus neoformans. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration, and division.”

1. In slu7d cells, in cells with small buds, numerous cMTs were nucleated from the MTOCs, and as the cell cycle progressed, they organized to form the unipolar mitotic spindle (Figure 3A, slu7kd GFP-TUB1 panel, time point 55 mins).

Please, revise whether the term unipolar mitotic spindle is correct here.

Response: The word unipolar has been removed.

1. I suggest including page and line numbers in the manuscript to facilitate revision.

Response: We regret missing out this formatting guideline. The Page and line numbers have provided.

Reviewer #2

We are thankful by the very positive comments on the significance of our work, its novelty and findings being of broad interest to microbiology; splicing; cell cycle and cell division communities. We respond to all comments raised below.

1. The authors test the Mad2-dependent spindle assembly checkpoint and show that it is not relevant for slu7-depletion. This is as expected if the defect is in nuclear positioning. They could test other checkpoint pathways that would monitor nuclear positioning in budding yeasts. Perhaps they have considered this: Bub2, Bfa1, Tem1, Lte1 mutants? I don't think this experiment is essential for publication, but it could strongly support their model.

Response: We appreciate the comment on other checkpoints operating during mitosis. However, we have not done these experiments to examine role of components that arrest mitosis (Bub2, Tem1 etc.) in response to spindle or kinetochore damage. We hope the reviewer appreciates that this line of work would require the generation of bub2Δ strain and extensive characterization for their role in checkpoint in Cryptococcus before it can be brought into strains compromised for Slu7.

__ Minor comments:__ 1. in Figure 3, Dyn1-GFP is imaged and in many of the cells in which Slu7 is depleted, nothing (or very little) can be seen. It is later argued that this is an indirect effect, due to defects in Pac1 and associated functions. Have the authors attempted a Dynein western blot (the 3xGFP tag should be quite sensitive)? It would be good to demonstrate that the Dynein motor complex hasn't simply fallen apart and Dynein been degraded in the slu7-depletion.

Response: A study in S. cerevisiae has reported the dynein expression does not change in pac1Δ cells (Lee et al., 2003). Since the molecular weight of CnnDYN1 along with the tag is 630kDa, we did attempt the very challenging experiment of western blot to check for the expression levels this very large protein in wildtype and slu7kd cells. Based on the reviewer’s suggestion, we have attempted dot blot of protein lysates from wild type and from slu7kd cells probed with anti GFP antibody for estimating DYN-GFP levels. Untagged WT H99 strain was used as negative control. The same blot was stripped and re-probed for PSTAIRE which served as a loading control. This experiment revealed that dynein levels are same in both wildtype and slu7kd cells.

in Figure 7: have any intronless genes been tested for rescue of the post-mitotic delay/arrest? This is not necessary for publication, but if any have been tested already, they could be listed here.

Response: We have not tested intronless genes for their role in the rescue of post mitotic delay/arrest. From the RNA seq data, we observed that most of the genes involved in mitotic exit network (MEN) and cytokinesis were highly expressed in slu7kd cells as compared to the wildtype indicating and indirect role for Slu7 in their expression level. So, we had validated three candidates MOB2, CDC12 and DBF2 by qRT PCR (Supplementary 7.D) and found they were upregulated in slu7kd cells and hence speculate that deregulation of these transcript could contribute to the post mitotic arrest in slu7kd.

In SFig2C legend make it clear that these cells are HU arrested at time zero. Are the cells in glucose or galactose during HU treatment.?

Response: We regret the lack of clarity in the legend and the required details have been added. The cells were initially grown in non-permissive media for 2 hours to deplete Slu7 and then HU was added to the non-permissive media and the cell were allowed to grow for 4 hours.

in SFig4, the TBZ sensitivity isn't very convincing as the slu7kd strain is struggling to grow at all on YPD.

Response: We agree with the reviewer comment on the growth of slu7kd cells on media YPD containing TBZ. TBZ may exacerbate the defective mitosis of Slu7 depleted cells, however whether it pertains only to mitosis or any cellular processes where microtubules are involved requires further investigation.

In SFig5 legend the volcano plot needs to be better explained. What are the dashed lines etc. ?

Response: We regret missing these details on the volcano plot which has now been added to the legend.

__Reviewer #3 __

We appreciate the views that our work provides strong evidence to support out conclusions that Cryptococcus neoformans Slu7 controls mitotic progression by efficient splicing of cell cycle regulators and cytoskeletal elements. We have taken all comments of the reviewer into account to revise our manuscript with additional data, and by improving the presentation. The key additional data are summarized below.

Major comments:

1) The authors claimed that CnSlu7 is the most divergent among the fungal homologs and closer to its human counterpart (Fig. 1A, Supplementary Fig 1A). -Just based on the phylogenetic tree including limited members, as in Supplementary Fig. 1, it cannot be concluded that CnSlu7 is closer to its human counterpart since the basidiomycete yeast such as C. neoformans itself is more closely positions to humans compared to the ascomycete yeasts S. cerevisiae and Sch. pombe in phylogenetic tree analysis. It is strongly recommended to include other fungal species from the Basidiomycota, such as Ustilago maydis, in phylogenetic analysis in Supplementary Fig. 1. - Conservation analysis among diverse eukaryotes is more meaningful data that the conservation withing the fungi group, so that it is recommended that the data of Fig. 1 A would be replaced with the revised Supplementary Fig 1. -The analysis data on amino acid identities among Slu7 homologues should be presented to support the claim.

Response: We agree with the reviewer that our data would be better served by an improved analysis of the phylogenetic relationship between various Slu7 homologs. We have therefore reconstructed the phylogenetic tree by including other fungal groups. This is presented here and also in the revised manuscript Supplementary Figure 1A. These data too, show that Cryptococcus (deneoformans and neoformans) Slu7 is the most diverged among its homologs from various fungal species with its closest homologs being other pathogens Puccinia graminis and Ustilago maydis.

2) Despite that CnSlu7 is the main key subject, the comparative analysis of CnSlu7 to the previously reported Slu7 homologues, in the aspect of functional domain organization, is not provided in the present manuscript. - It was reported that Slu7 contains the four motifs that control its cellular localization and canonical function as a splicing factor, such as a nuclear location signal, a zinc knuckle motif, four stretches of leucine repeats and a lysine-rich domain. Notably, human Slu7 protein is 204 amino acids longer than S. cerevisiae homolog with only 24% identity in the zinc knuckle motif (Molecular Biology of the Cell Vol. 15, 3782-3795). Thus, it is strongly recommended to provide additional information on the conserved and diverged features of CnSlu7 compared to other Slu7 homologs as a part of revised Figure.

Response: The multiple sequence alignment of Cryptococcus neoformans Slu7 with its fungal and higher eukaryote homologs such as human Slu7 and plant Slu7 proteins revealed that only the CCHC zinc finger motif is highly conserved. We do not detect conservation in the nuclear localization signal, stretch of leucine repeats and lysine rich domain except for leucine 3 stretch near the C terminal. This additional information is presented in revised Figure 1A.

3) The manuscript clearly demonstrated that one of key targets of Slu7-mediated splicing is PAC1 in C. neoformans. Considering, Pac1 is also conserved from S. cerevisiae to human, it could be speculated that the defect of Slu7 can affect nuclear migration in other fungal species and human cells by inefficient splicing of PAC1, despite striking differences in their nuclear position during cell division. Please discuss this possibility or provide the qRT-PCR analysis data of PAC1 homologs in the available fungal Slu7 mutant strains.

Response: Cell cycle arrest phenotypes of splicing factor mutants (studied largely in budding and fission yeast) results from inefficient pre-mRNA splicing of cell cycle-related genes. Slu7 is a well characterized second step splicing factor in S. cerevisiae where in vitro splicing assays with ACT1 minigene transcripts with a modified single intron showed ScSlu7 is dispensable for splicing when the branchpoint to 3'SS distance is less than seven nucleotides in the mini transcript (Brys and Schwer, 1996). In fission yeast we reported the effects of metabolic depletion of Slu7, which is an essential gene (Banerjee et al., 2013) and showed unexpectedly that in addition to BrP to 3'SS distance new intronic features contributors of dependency of fission yeast intron containing transcripts on Slu7 functions. The work also showed in multi-intronic transcripts its role is intron-specific and thus the candidate gene/ transcript is likely to be to dependent on Slu7 by virtue of the intronic features and not its biological function. In this study a splicing dependent role of CnSlu7 in cell cycle progression is investigated where based on a strong nuclear mis-positioning phenotype we narrowed on PAC1 transcripts as one of targets. We show PAC1, encoding a cytoskeletal factor, has introns dependent on CnSlu7 for efficient splicing and show partial rescue of nuclear position in strain complemented with expression of an intronless PAC1 gene. In this scenario, while it is likely that in other species where PAC1 exon-introns nucleotide sequences are similar to that in Cryptococcus a role for Slu7 may be predicted, for validation by other experimentalists.

Interestingly, PAC1 in S. cerevisiae is an intronless gene and its homolog is not annotated in S. pombe. In human cell lines, knockdown of Slu7 by siRNA resulted in metaphase arrest by inefficient splicing of soronin – which is crucial in sister chromatid cohesion and correct spindle assembly, according to recent research in human cell lines (Jiménez et al., 2019).

Hence the roles of splicing factor in cell cycle is through splicing of targets involved in cell cycle wherein the targets regulated by splicing factor may or may not be conserved in other species.

Minor comments:

General points 1) Provide information on the marker sizes in the data of qRT-PCR analysis presented in Figures 5 and 6, and Supplementary Fig 2A.

Response: We regret the omission of this technical data and have corrected the same by providing the marker sizes in all the figures.

2) Please unify the format of gene names. Some genes were written with superscript of "+", such as CLN1+ and PAC1+ in Fig. 4. What does "+" mean in the gene names?

Response: We have taken the suggestion to carefully review the nomenclature of genes and their expressed transcripts as is typical for Cryptococcus neoformans. To depict the wildtype form of transcript we had used +. Thus CLN1+ was used to denote Cyclin 1 cellular transcript from expressed from its own locus without any modification of promoter or the intronic features.

3) Supplementary Figure 1 C: Please correct "Slu7KD" 6 hrs YPD to "slu7kd" 6 hrs YPD.

Response: This error has been corrected.

4) Supplementary Figure 2A: What do "mRNA" and "No RT29X/", respectively, indicate?

Response: The mRNA indicates the spliced form across any intron after intron is spliced out, so denotes exon-exon sequences in the mRNA. The reactions marked as “No RT 29 X” denote semi- quantitative PCR performed on DNase treated RNA sample, without reverse transcription to generate the cDNA. These reactions were done to confirm that there is no genomic DNA present in the RNA sample used for reverse transcription reaction of the cellular transcripts. Some of these details are now included in the Supp Fig 2A legend.

5) Supplementary Figure 4C: Please provide brief explanation in the text on why the authors employed mad2Δ slu7kd cells.

Response: In Page 8, line 6, we had provided the rationale for generating and studying mad2Δ slu7kd strain. This is recapitulated below:

“To investigate whether Slu7 knockdown triggers the activation of spindle assembly checkpoint (SAC), we generated a strain with conditional slu7kd in cells with mad2Δ allele and the GFP-H4 nuclear marker.”

6) Supplementary Figure 6D legend: Please correct the description of "slu7kd SH:Slu7 FL" from "expressing intronless PAC1" to "expressing full length of SLU7".

Response: The error in the legend is regretted and this has been corrected.

7) Supplementary Figure 7D: The authors confirmed that MOB2, CDC12, and DFB1 were expressed at higher levels in slu7kd when compared to wildtype. Please briefly explain in the text why the expression level of these genes in slu7kd was mentioned.

Response: slu7kd cells expressing intronless Pac1 arrest post nuclear division. Revisiting our transcriptomic data, we found that genes involved in mitosis exit network and cytokinesis, such as DFB1, MOB2, CDC12, BUD4, and CHS2, were deregulated in slu7kd when compared to wildtype. We confirmed the same by performing qRT PCRs for three candidates, MOB2, DBF1 and CDC12 and that these transcript were expressed at high levels in knockdown when compared to wildtype.

8) The species name should be written as abbreviation after the first mention. For example, please correct Cryptococcus neoformans to C. neoformans throughout manuscript.

Response: The suggestion is well taken, and the required edits have been made throughout the text.

9) Please unify the format of paper titles listed in References.

Response: This formatting error is regretted and corrected to have all references in a single format.

10) No page information for Hoffmann et al (2010) in References.

Response: This omission is corrected.

11) Update the information on the published journal of Chatterjee et al. (2021) in References.

Response: This omission is regretted and is now corrected.

12) Information on the authors, title, published journal and pages should be provided for the papers (Yadav and Sanyal, 2018; Sridhar et al., 2021) in Supplementary Table 1, which were not included in the main Reference list.

Response: The references are now added to the main list.

References used for addressing the reviewer’s comments:

1. Chung DKC, Chan JNY, Strecker J, Zhang W, Ebrahimi-Ardebili S, Lu T, Abraham KJ, Durocher D, Mekhail K (2015) Perinuclear tethers license telomeric DSBs for a broad kinesin- and NPC-dependent DNA repair process. Nat Commun doi:10.1038/NCOMMS8742.
2. Jiménez M, Urtasun R, Elizalde M, Azkona M, Latasa MU, Uriarte I, Arechederra M, Alignani D, Bárcena-Varela M, Alvarez-Sola G et al (2019) Splicing events in the control of genome integrity: Role of SLU7 and truncated SRSF3 proteins. Nucleic Acids Res 47: 3450–3466. doi:10.1093/nar/gkz014.
3. Laflamme G, Sim S, Leary A, Pascariu M, Vogel J, D’Amours D (2019) Interphase Microtubules Safeguard Mitotic Progression by Suppressing an Aurora B-Dependent Arrest Induced by DNA Replication Stress. Cell Rep 26: 2875-2889.e3. doi:10.1016/J.CELREP.2019.02.051.
4. Lawrimore J, Barry TM, Barry RM, York AC, Friedman B, Cook DM, Akialis K, Tyler J, Vasquez P, Yeh E et al (2017) Microtubule dynamics drive enhanced chromatin motion and mobilize telomeres in response to DNA damage. Mol Biol Cell 28: 1701–1711. doi:10.1091/MBC.E16-12-0846.
5. Lee WL, Oberle JR, Cooper JA (2003) The role of the lissencephaly protein Pac1 during nuclear migration in budding yeast. J Cell Biol. doi:10.1083/jcb.200209022.
6. Lottersberger F, Karssemeijer RA, Dimitrova N, De Lange T (2015) 53BP1 and the LINC Complex Promote Microtubule-Dependent DSB Mobility and DNA Repair. Cell 163: 880–893. doi:10.1016/J.CELL.2015.09.057.
7. Oshidari R, Strecker J, Chung DKC, Abraham KJ, Chan JNY, Damaren CJ, Mekhail K (2018) Nuclear microtubule filaments mediate non-linear directional motion of chromatin and promote DNA repair. Nat Commun doi:10.1038/S41467-018-05009-7.
8. Varshney N, Som S, Chatterjee S, Sridhar S, Bhattacharyya D, Paul R, Sanyal K (2019) Spatio-temporal regulation of nuclear division by Aurora B kinase Ipl1 in Cryptococcus neoformans. PLoS Genet doi:10.1371/journal.pgen.1007959.
9. Wu G, Zhou L, Khidr L, Guo XE, Kim W, Lee YM, Krasieva T, Chen PL (2008) A novel role of the chromokinesin Kif4A in DNA damage response. Cell Cycle 7: 2013–2020. doi:10.4161/CC.7.13.6130.

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Referee #2

Evidence, reproducibility and clarity

Summary:

This manuscript reports the effects of depleting the Slu7 splicing factor in Cryptococcus neoformans. Mitotic defects are apparent, in particular in positioning the nucleus with cells struggling to get this into the bud (daughter) before chromosome segregation. The manuscript is well written, logically presented and the data of high quality. I suggest minor modifications and a few additional experiments that could be attempted.

Major comments:

• Are the key conclusions convincing? Yes. Splicing is clearly perturbed. Pac1 is likely to be one of the targets, as expression of an intronless minigene rescues the spindle positioning defect in the slu7 depleted cells. Importantly, other defects are still apparent (late mitotic delay/block) and so growth is not rescued. This is not surprising, as the expression of hundreds of genes are affected by Slu7-depletion.
• the authors test the Mad2-dependent spindle assembly checkpoint, and show that it is not relevant for the slu7-depletion. This is as expected if the defect is in nuclear positioning. They could test other checkpoint pathways that would monitor nuclear positioning in budding yeasts. Perhaps they have considered this: Bub2, Bfa1, Tem1, Lte1 mutants? I don't think this experiment is essential for publication, but it could strongly support their model.
• 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? Yes.

Minor comments:

• in Figure 3, Dyn1-GFP is imaged and in many of the cells in which Slu7 is depleted, nothing (or very little) can be seen. It is later argued that this is an indirect effect, due to defects in Pac1 and associated functions. Have the authors attempted a Dynein western blot (the 3xGFP tag should be quite sensitive)? It would be good to demonstrate that the Dynein motor complex hasn't simply fallen apart and Dynein been degraded in the slu7-depletion.
• in Figure 7: have any intronless genes been tested for rescue of the post-mitotic delay/arrest? This is not necessary for publication, but if any have been tested already they could be listed here.
• In SFig2C legend make it clear that these cells are HU arrested at time zero. Are the cells in glucose or galactose during HU treatment.?
• in SFig4, the TBZ sensitivity isn't very convincing as the slu7kd strain is struggling to grow at all on YPD. In SFig5 legend the volcano plot needs to be better explained. What are the dashed lines etc. ?
• Are prior studies referenced appropriately? Yes
• Are the text and figures clear and accurate? Yes
• Do you have suggestions that would help the authors improve the presentation of their data and conclusions? A few are listed above.

Significance

This manuscript will be of broad interest to the microbiology; splicing; cell cycle and cell division communities. The links between splicing and cell division is a novel area of research in Cryptococcus.

I am an expert in mitotic regulation in yeast. Not a splicing expert.

Author Response

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

We wish to thank the reviewers for their helpful insightful comments. Their concerns were mainly related to the interpretation of the data, help in clarifying our statements and improving our discussion.

Reviewer #1 (Recommendations For The Authors):

This is a very interesting study It involves the utilization of hippocampal neuronal cultures from syntaxin 1 knock-out mice. These cultures serve as a platform for monitoring changes in synaptic transmission through electrophysiological recording of postsynaptic currents, upon lentiviral infection with various isoforms, chimeras, and point mutations of syntaxins.

The authors observe the following:

(1) Syntaxin2 restores neuronal viability and can partially rescue Ca2+-evoked release in syntaxin1 knock-out neurons that it is much slower (cumulative charge transfer differences) and with a clearly smaller RRP than when rescued with syntaxin1. In contrast, syntaxin2-mediated rescue leads to a high increase in spontaneous release (Figure 1). Convincingly, the authors conclude that syntaxin 1 is optimized for fast phasic release and for clamping of spontaneous release, in comparison with syntaxin2.

(2) The replacement of the SNARE domain (or its C-terminal part) of syntaxin1 by the SNARE domain of syntaxin2 (or its C-terminal part) rescues the fast kinetics, but not the amplitude, of Ca2+-evoked release. This is associated with a decrease in the size of the RRP and an increase in spontaneous release. The probability of vesicular release (PVR) is a little bit increased, which is intriguing because a little decrease would be expected instead according to the reduced RRP, indicating that an enhancement of Ca2-dependent fusion is occurring at the same time by unknown mechanisms as the authors properly point out. The replacement of the Analogous experiments in which the SNARE domain of syntaxin1 is replaced into syntaxin2, reveals the exitance of differential regulatory elements outside the SNARE domain.

(3) Different constructs of syntaxin 1 and syntaxin 2 display different expression levels. On the other hand, the expression levels of Munc-18 are associated with the characteristics of the transfected specific syntaxin construct. In any case, the electrophysiological phenotypes cannot be consistently explained by changes in Munc-18.

(4) Mutations in several residues of the outer surface of the C-terminal half of the syntaxin1 SNARE domain lead to alterations in the RRP and the frequency of spontaneous release, but the changes cannot attributed to a change in the net surface charge, because the alterations occur even in paired mutations in which electrical neutrality is conserved.

Comments:

(1) This is a comment regarding the interpretation of the results. In general, the decrease in the RRP size is associated with the increased frequency of spontaneous release due to unclamping. The authors claim that both phenomena seem to be independent of each other. In any case, how can the authors discard the possibility that the unclamping of spontaneous release leads to a decrease in the RRP size?

The main argument against the reduction of the RRP being caused by the observed increase in the mEPSC frequency is based on kinetics of refilling and depletion. The average time a vesicle fuses spontaneously after it becomes primed is 500 – 1000 seconds (spontaneous vesicle release rate – STX1 Figure 1, Figure 2 and Figure 3). The time it takes to refill the RRP after depletion is in the order of 3 seconds (Rosenmund and Stevens, 1996). Therefore, the refilling of the RRP is more than 100 times faster. Even when the spontaneous release would increase 5 fold, this would lead to less than 5 % of the steady state depletion of the RRP.

(2) The authors have analyzed the kinetics of mEPSCs and found differences (Fig2-Supp. Fig1; Fig2-Supp. Fig1). It would be interesting and pertinent to discuss these data in the context of potential phenotypes in the fusion pore kinetics involving syntaxin1 and syntaxin2 and their SNARE domains. Indeed, the figure will improve by including averaged traces of mEPSCs.

We thank the reviewer for the idea. Upon closer examination of the changes in mEPSC rise time and mEPSC decay time we noticed a minor slowing in the mEPSC rise time from 0.443ms (SEM0.0067) of STX1A to 0.535ms (SEM0.0151) for STX1A-2(SNARE) or 0.507ms (SEM0.01251) for STX1A-2(Cter), while the mEPSC half widths did not change significantly. It is possible that the measured change is related to the detection algorithm as mEPSC detection at elevated frequencies becomes more difficult due to increased overlap of event, and we therefore prefer to refrain from making any mechanistic claims.

Minor comments:

(1) Fig2 J; Fig 3 J. It is difficult to distinguish between different colors and implementing a legend within the graph will be very helpful.

(2) Fig3 H. Please change the color of the box plot for Stx1 A to improve the contrast with the individual data points.

(3) Page 6. Line 225. "Figure 2D and E" should be corrected to "Figure 2C and D"

(1) Colors were changed for clearer visualization. (2) Unfortunately, changing the color did not improve the contrast with the individual plots. However, the numerical data is all included in the data sheets of the corresponding figure. (3) The mistake was corrected.

Reviewer #2 (Recommendations For The Authors):

Line 135-136: Are cited numbers cited in the text mean and SEM? Please indicate.

Line 139 and Figure 1G: The difference between purple and blue was very hard to see on my hard copy.

Line 152: Reference to Figure 1L should probably be 1K.

Line 183: Reference to Figure 2C should probably be Figure 2F.

Line 225: Reference to Figure 2D and 2E should probably be 2C and 2D.

Line 239: Reference to Figure 3I should probably be 3H.

All typos were addressed and colors were changed for better visualization.

Line 210-211: Sentence ("One of the benefits..") is hard to understand.

Thank you for noticing this mistake, agreeably the the sentence did not add any important or new information and so it was deleted. Additionally, the message of the mentioned sentence was already clearly stated in lines 209-211.

Figure 4E-H misses data for STX2, for the figure to be arranged like Figure 5.

Given that STX1 is the endogenous syntaxin in hippocampal neurons, we use it at a control for all the analysis done in STX2 and STX2-chimera experimental groups, thus it is included in Figure 3 and 5.

It appears that the authors do not present or discuss the Western Blot in Fig. 4D. Are the quantitative results of the Western Blot consistent with or different from the quantification of the immunostainings (Fig. 4B-C)? A similar question for Figure 5D, which also seems not to be presented.

In terms of quantification, we have relied mainly on the ICC experiments because they test also for putative impairments in transport to the presynaptic compartment. Our WB data are overall consistent with the results, but were not used to quantitate expression of our syntaxin chimeras and mutations in the STX1-null hippocampal neuron model.

Figure 6F-G: The normalization of spontaneous vesicular release rates is not clear, because the vesicular release rates already contain a normalization (mEPSC rate divided by RRP size). Is a further normalization of the STX1A condition informative? The authors should consider presenting the release rates themselves. In any case, the normalization should be presented/explained, at least in the legends.

The reviewer is in principle correct. Due to the large number of experimental groups we had to perform recordings from multiple cultures, where not all experimental groups were present, while the WT STX1 was present as a consistent control. The reduce culture to culture variability, additional normalization to the WT control group was performed. However, we also included the raw data numerical values in the data-source sheets (Normalized and absolute), which produce a similar overall outcome.

References to Figure 7 subpanels (A, B, and C) are missing.

Thank you for the comment. We have integrated all panels into one for better representation and understanding since they are representative of one another.

Lines 330-339 and Figure 7 in Discussion: the authors discuss that adding the non-cognate STX2 SNARE-domain to syntaxin-1 might destabilize the primed state and decrease the fusion energy barrier (as indicated in Figure 7C). What is the evidence that the decrease in RRP size is not caused solely by the depletion of the pool due to the increased spontaneous fusion?

Please see the comments to major point 2 of reviewer 1.

Statistics: Missing is the number of observations (n) for all data. Even if all data points are displayed, this should be stated.

N numbers are included in the data sheets attached to each figure.

The statement (start of Discussion,) that the SNARE-domain of STX1 'plays a minimal role in the regulation for Ca2+-evoked release' is somewhat puzzling, since without the SNARE-domain in STX1 there would be no Ca2+-evoked release. I guess these statements (similar statements are found elsewhere) are due to the interesting finding that STX2 leads to a decrease in release kinetics, compared to STX1, and this is not (entirely) due to differences in the SNARE-domain. I would suggest rephrasing the finding in terms of release kinetics. Also, the statement in the last sentence of the Abstract is not clear.

Thank you for pointing this out and we agree that our experiments showed strong impact of the syntaxin isoform exchange on release kinetics and overall release output. A similar comment came also from reviewer #3 and so, we have addressed both comments as one.

Our confusing statement resulted from the order of the presented results and our summarizing remarks for each section. Our statement reflected our finding that mutating residues in the C-terminal part of the STX1 SNARE motif affected only spontaneous release and RRP size but not release efficacy. We now state (pg. 6 lines 231-233) that the data observed from the comparison of “the results obtained from the Ca2+-evoked release between STX1 and STX2 support major regulatory differences of the domains outside of the SNARE domain between isoforms”.

We have changed the abstract pg. 2 lines 55-56

We have changed the introduction pg. 3 lines 102-105 for a better contextualization.

We have changed the start of the discussion pg. 9 lines 250-252 for better contextualization.

Reviewer #3 (Recommendations For The Authors):

In this manuscript, Salazar-Lázaro et al. presented interesting data that C-terminal half of the Syx1 SNARE domain is responsible for clamping of spontaneous release, stabilizing RRP, and also Ca2+-evoked release. The authors routinely utilized the chimeric approach to replace the SNARE domain of Syx1 with its paralogue Syx2 and analyzed the neuronal activity through electrophysiology. The data are straightforward and fruitful. The conclusions are partly reasonable. One obvious drawback is that they did not explore the underlying mechanism. I think it is easy for the authors to carry out some simple assays to verify their hypothesis for the mechanism, instead of just talking about it in the discussion section. In all, I appreciate the data presented in the manuscript. If the authors could supply more data on the mechanisms, this would be important research in the field. Some critical comments are listed below:

We thank the reviewer for his/her comments and suggestions.

Major comments:

(1) In pg.3, lines 102-104, the authors stated that 'We found that the C-terminal half of the SNARE domain of STX1.. ..while it is minimally involved in the regulation of Ca2+-evoked release.' But in pg.5, lines 174-176, they wrote that 'Replacement of the full-SNARE domain (STX1A-2(SNARE)) or the C-terminal half (STX1A-2(Cter)) of the SNARE domain of STX1A with the same domain from STX2 resulted in a reduction in the EPSC amplitude (Figure 2B).' and in pg.5-6, lines 197-199, they wrote that 'Taken together our results suggest that the C-terminal half of the SNARE domain of STX1A is involved in the regulation of the efficacy of Ca2+-evoked release, the formation of the RRP and in the clamping of spontaneous release.' It puzzles me a lot as to what the authors are really trying to express for the relationship between C-half of the SNARE complex and Ca2+-evoked release (i.e., minimally involved or significantly participate in the process?). Please clarify and reorganize the contexts.

Please see our reply to the last comment of reviewer 2.

(2) Figure 1-figure supplement 1, the authors should analyze Syx1/VGlut1 level additionally. And, if possible, compare the difference between Syx1/VGlut1 and Syx2/VGlut1.

The levels of STX1/VGlut1 and STX2/VGlut1 were analyzed in detail in Figures 4 and 5.

The direct comparison between the expression levels of these two proteins is not possible since affinities of the antibodies to the target proteins are different and can induce potential biases. While this could be overcome by the use of a FLAG-tag to the syntaxin proteins, we have not utilized this approach in this publication. We in addition inferred sufficient and comparable expression of both syntaxins from their ability to rescue some of syntaxin1 loss of function phenotypes.

(3) Figure 2D only analyzed the EPSC half-width, could the author alternatively analyze the rise/decay time? Also, in Figure 3-figure supplement 1, does it refer to the kinetic parameters of Syx2-1A in Figure 3? It is very confused.

We have changed the text accordingly and each parameter is referenced to its corresponding figure for clarity. As for the decay and rise time of STX1 and STX1-chimeras, they are in Figure 2-figure supplement 1A and B.

(4) On pg.4, lines 151-152, 'Finally, no change was observed in the paired-pulse ratio (PPR) between STX1A and STX2 groups (Figure 1L).' does not contain any explanations and comments for this observation in the texts.

The small EPSC amplitudes and altered kinetics on the STX2 constricts (Figure 1 and Figure 3) have made it more difficult to quantitate paired pulse experiments. Therefore, we preferred not to overinterpret these measurements. The findings that the paired pulse data were not significantly different, fit with the vesicular release probability measurements which showed no major changes. We have made our statement on this basis.

(5) On pg.6, lines 235-236, the authors wrote that 'Additionally, we found that only STX2-1A(SNARE) and STX2-1A(Cter) could rescue the RRP to around double of what we measured from STX2 and STX2-1A(Nter) (figure 3F)'. However, in Figure 3F, the authors indicated 'n.s.' (p>0.05) for the differences between STX2 and STX2-1A(SNARE)/STX2-1A(Cter). It is perplexing how the authors interpret their data. Definitely, the p-value could not be arbitrarily used as a criterion of difference. An easier way is that indicating the exact p-values for each comparison (indicate in figure legends or list in tables).

We apologize for any confusion, and hope the modification gives more clarity in our interpretation. The calculated p-values are included in attached data source tables and hope this will provide clarity to our comparative analysis. We have changed the text in pg 7 lines 238-241 and are cautious to overinterpret these results and rely more on the data observed in STX1A-chimeras, which show significant changes in the RRP.

(6) I noticed that the authors preferred using 'xx% increase/decrease' or 'xx-fold increase/decrease' to interpret their inter-group data. I would doubt whether the interpretations are appropriate. First, it seems that most of the individual scatters from one set were not subject to Gaussian distribution; also, the authors utilized non-parameter tests to compare the differences. Second, the authors did not explicitly indicate the method to calculate the % or fold, e.g., by comparing mean value or median. I think it is a bad choice to use the median to calculate fold changes; meanwhile, the mean value would also be biased, given the fact that the data were not Gaussian-distributed. The authors should be cautious in interpreting their data.

We thank the reviewer for pointing the inaccuracy of our descriptions and have included the parameter used to calculated the percentage and fold increase/decrease in the materials and methods section. Specifically, the mean. Our intention is to plainly state the amount of change seen in a parameter based on the observed changes in the mean value. We agree with the reviewer that interpreting this could be problematic if we are speculating possible mechanisms. Further test should be conducted as to state whether similar increase/decrease changes in a parameter are due to the disturbance of the same mechanisms or different. E.g., we discussed whether the regulation of SYT1 might be or not be the mechanism affected in some of the chimeras that show an increase in the spontaneous release rate, for the release rate observed in some is massively higher than that seen in SYT1-KO (Bouazza-Arostegui et al., 2022). It is tempting to speculate that it could be due to other mechanisms based on the differences in the changes. For this reason, we have given an array of possible mechanisms affected when we manipulate the SNARE domain of STX1.

(7) The authors routinely analyzed the levels of Munc18-1 in neuronal lysates by WB and Munc18-1/VGlut1 by immunofluorescence in various Syx1 mutants. However, in my view, these assays were slightly indirect. It is evident that the SNARE domain of Syx1 participates in the binding to Munc18-1 according to the atomic structures (pdb entries: 3C98 and 7UDB). Meanwhile, Han et al. reported that K46E mutation (located in domain 1 of Munc18-1) strongly impairs Syx1 expression, Syx1-interaction, vesicle docking and secretion (Han et al., 2011, PMID: 21900502). Intriguingly, the residue K46 of Munc18-1, which is close to D231/R232 of Syx1, may have potential electrostatic contacts to D231 and R232 of Syx1. This is reminiscent of the possibility that Syx1D231/R232 and some Syx1-2 chimeras lost their normal function through their defective binding to Munc18-1.nmb, To better understand the underlying mechanism, the authors may need to carry out in vivo and/or in vitro binding analysis between syntaxin mutants/chimeras and Munc18-1. They also need to conduct more discussions about the issue.

We express our gratitude for the identification of a previously overlooked aspect in our investigation of the interplay between Munc18-1 and STX1. In response, we have incorporated additional discourse on this matter in pg11 lines 419-431.

Additionally, we appreciate the thoughtful suggestion regarding additional experiments to further explore the molecular relationship between Munc18-1 and STX1. We agree that co-immunoprecipitation experiments (either by using an antibody against Munc18-1 or STX1 and STX2) would offer greater insight into whether the binding of these proteins is affected in the isoform or the mutants. Notably, we performed immunoprecipitation experiments by using neuronal lysates of the corresponding groups and using STX1A and STX2 antibodies for the pull-downs. However, we were unable to co-IP Munc18-1 when doing so. Changing the conditions of the experiment did not yield better results and so these experiments remained inconclusive for the moment. For this reason, we included it as an open question and a potential concluding hypothesis of the molecular mechanism. However, Shi et al., 2021, have performed co-IP assays using Munc18-1-wt and a mutant form which affects the binding to the C-terminal half of the SNARE domain of STX, and STX1-wt and a STX mutants targeting some of our residues of interest and showed a decrease in the pulled-down levels of Munc18-1 using HeLa cells. We have made sure to mention the conclusion of this important publication in our discussion.

(8) The third possible mechanism (i.e., interaction with Syt1) proposed by the authors seems more reasonable. However, the discussions raised by the authors were not enough. For instance, plenty of literature has indicated that Syt1 may participate in synaptic vesicle priming through stabilizing partially or fully assembled SNARE complex (Li et al., 2017, PMID: 28860966; Bacaj et al., 2015, PMID: 26437117; Mohrmann et al., 2013, PMID: 24005294; Wang et al., 2011; PMID: 22184197; Liu et al., 2009, PMID: 19515907); complexins are also SNARE binding modules that regulate synaptic exocytosis. Lack of complexins could lead to unclasping of spontaneous fusion of synaptic vesicles, though it causes severe Ca2+-triggered release at the same time (Maximov et al., 2009, PMID: 19164751). Meanwhile, different domains of complexin may accomplish different steps of SV fusion, early research had indicated that the C-terminal sequence of complexin is selectively required for clamping of spontaneous fusion and priming but not for Ca2+-triggered release (Kaeser-Woo et al., 2012, PMID: 22357870). Likewise, if possible, the authors may need to carry out in vivo and/or in vitro binding analysis to confirm their hypothesis.

The exploration of complexin´s involvement was limited in our study primarily due to our methodological focus on comprehending molecular mechanisms concerning the sequence disparities between STX1 and STX2. Our laboratory has studied the role of Complexin extensively, and we certainly have had a possible involvement in mind. However, since the sites identified on syntaxin are either conserved between STX1 and STX2 or not close to the central or accessory helical domains of complexin, we did not perform experiments to test putative interactions, and we refrained from discussing complexin in this paper.

(9) Lastly, I would suspect that whether the defects of Syx2 and Syx1 chimeras were caused by the SNARE complex itself, from another point of view that is different from the hypothesis raised by the authors. Changing the outward residues (or we say the solvent-accessible residues) of the SNARE complex may affect the stability, assembly kinetics, and energetics (Wang and Ma, 2022, PMID: 35810329; Zorman et al., 2014, PMID: 25180101), especially for the C-terminal halves. Is this another possible mechanism through which the C-terminus of Syx1 might contribute to SV priming and clamping of spontaneous release? The authors should at least conduct some discussions about the point.

Thank you for this suggestion. We indeed assumed that since the hydrophobic layers of the SNARE domains that form the hydrophobic pocket of STX2 and STX1 are mainly conserved, that the intrinsic stability of the SNARE complex is largely unchanged. Additionally, Li et al., (2022) PMID: 35810329 examined the stability of the alfa-helix structure of the SNARE domain of SNAP25. And while they found no changes in the stability and formation of the alfa-helix when mutating outwards-facing residues for methodological purposes (bimane-tryptophan quenching), their study did not selectively explore the effect of mutations of outer-surface residues on the stability of the alfa-helix.

Zorman et al., (2014) PMID: 25180101, as noted by the reviewer, observed that changes in the sequence of the SNARE domain (by using SNARE proteins from different trafficking systems (neuron, GLUT4, yeast…) correlated with changes in the step-wise SNARE complex assembly. However, they also did not selectively mutate the outer solvent-accessible residues, hindering conclusive speculations in the contribution of said residues on the kinetics and energetics of assembly and intrinsic stability of the SNARE complex.

Upon petition of the reviewer, we have added this paragraph to discuss an additional mechanism:

“As a final remark, it is possible that the changes in the spontaneous release rate and the priming stability may stem from a reduced stability of the SNARE complex itself through putative interactions between outer surface residues. Studies of the kinetics of assembly of the SNARE complex which mutate solvent-accessible residues in the C-terminal half of the SNARE domain of SYB2 have shown reduction in the stability of the SNARE complex assembly and are correlated with impaired fusion (Jiao et al., 2018). However, STX1 mutations of outward residues were inconclusive and were always accompanied by hydrophobic layer mutations (Jiao et al., 2018), which affect the assembly kinetics and energetics of the SNARE complex (Ma et al., 2015). Single molecule optical-tweezer studies have focused on the impact of regulatory molecules on the stability of assembly such as Munc18-1 (Ma et al., 2015; Jiao et al., 2018) and complexin (Hao et al., 2023), or on the intrinsic stability of the hydrophobic layers in the step-wise assembly of the SNARE complex (Gao et al., 2012; Ma et al., 2015; Zhang et al., 2017). Although the conserved hydrophobic layers in the SNARE domains of STX1A and STX2 (Figure 1) suggest unchanged zippering and intrinsic stability of the complex, further studies addressing the contribution of surface residues on the stability of the alfa-helix structure of the SNARE domain of STX1 (Li et al., 2022) or the stability of the SNARE complex should be conducted.”

Minor comments:

(1) In pg.6, line 236, 'figure 3F', the initial 'f' should be uppercased.

(3) On pg.11, line 396, the section title 'The interaction of the C-terminus of de SNARE domain of STX1A with Munc18-1 in the stabilization of the primed pool of vesicles.' The word 'de' is confusing, please check.

(4) In pg.12, line 446, the section title, should 'though' be 'through'?

These comments have been acknowledged and changed. Thank you

(2) In pg.7, line 239, '..had an increased PVR (Figure 3G), no change in the release rate (Figure 3I)', should Figure 3I be Figure 3H? and line 240, 'and an increase in short-term depression during 10Hz train stimulation (Figure 3I)', should Figure 3I be Figure 3J? If so, Figure 3I will not be cited in the texts and lack adequate interpretations. Please check.

We apologize for the oversight in not referencing this specific subpanel of the figure and have incorporated the reference in the text. Additionally, our interpretation of this data is connected to the mechanisms that govern efficacy of Ca2+-evoked response, and its dependence on the integrity of the entire-SNARE domain. We wish to highlight the modifications made to the discussion on the regulation of the Ca2+-evoked response based on previous reviewer comment #1, and a similar comment from reviewer #2 (as stated previously).

Author Response

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

eLife assessment

This study presents a useful characterization of the biochemical consequences of a disease-associated point mutation in a nonmuscle actin. The study uses solid and well-characterized in vitro assays to explore function. In some cases the statistical analyses are inadequate and several important in vitro assays are not employed.

Public Reviews:

Reviewer #1 (Public Review):

Strengths:

The authors first perform several important controls to show that the expressed mutant actin is properly folded, and then show that the Arp2/3 complex behaves similarly with WT and mutant actin via a TIRF microscopy assay as well as a bulk pyrene-actin assay. A TIRF assay showed a small but significant reduction in the rate of elongation of the mutant actin suggesting only a mild polymerization defect.

Based on in silico analysis of the close location of the actin point mutation and bound cofilin, cofilin was chosen for further investigation. Faster de novo nucleation by cofilin was observed with mutant actin. In contrast, the mutant actin was more slowly severed. Both effects favor the retention of filamentous mutant actin. In solution, the effect of cofilin concentration and pH was assessed for both WT and mutant actin filaments, with a more limited repertoire of conditions in a TIRF assay that directly showed slower severing of mutant actin.

Lastly, the mutated residue in actin is predicted to interact with the cardiomyopathy loop in myosin and thus a standard in vitro motility assay with immobilized motors was used to show that non-muscle myosin 2A moved mutant actin more slowly, explained in part by a reduced affinity for the filament deduced from transient kinetic assays. By the same motility assay, myosin 5A also showed impaired interaction with the mutant filaments.

The Discussion is interesting and concludes that the mutant actin will co-exist with WT actin in filaments, and will contribute to altered actin dynamics and poor interaction with relevant myosin motors in the cellular context. While not an exhaustive list of possible defects, this is a solid start to understanding how this mutation might trigger a disease phenotype.

We thank the reviewer for the positive evaluation of our work.

Weaknesses:

• Potential assembly defects of the mutant actin could be more thoroughly investigated if the same experiment shown in Fig. 2 was repeated as a function of actin concentration, which would allow the rate of disassembly and the critical concentration to also be determined.

The polymerization rate of individual filaments observed in TIRFM experiments showed only minor changes, as did the bulk-polymerization rate of 2 µM actin in pyrene-actin based experiments. Therefore, we decided not to perform additional pyrene-actin based experiments, in which we titrate the actin concentration, as we expect only very small changes to the critical concentration. Instead, we focused on the disturbed interaction with ABPs, as we assume these defects to be more relevant in an in vivo context. Using pyrene-based bulkexperiments, we did determine the rate of dilution-induced depolymerization of mutant filaments and compare them with the values determined for wt (Figure 5A, Table 1).

• The more direct TIRF assay for cofilin severing was only performed at high cofilin concentration (100 nM). Lower concentrations of cofilin would also be informative, as well as directly examining by the TIRF assay the effect of cofilin on filaments composed of a 50:50 mixture of WT:mutant actin, the more relevant case for the cell.

The TIRF assay for cofilin severing was performed initially over the cofilin concentration range from 20 to 250 nM. The results obtained in the presence of 100 nM cofilin allow a particularly informative depiction of the differences observed with mutant and WT actin. This applies to the image series showing the changes in filament length, cofilin clusters, and filament number as well as to the graphs showing time dependent changes in the number of filaments and total actin fluorescence. We have not included the results for a 50:50 mixture of WT:mutant actin because its attenuating effect is documented in several other experiments in the manuscript.

• The more appropriate assay to determine the effect of the actin point mutation on class 5 myosin would be the inverted assay where myosin walks along single actin filaments adhered to a coverslip. This would allow an evaluation of class 5 myosin processivity on WT versus mutant actin that more closely reflects how Myo5 acts in cells, instead of the ensemble assay used appropriately for myosin 2.

Our results with Myo5A show a less productive interaction with mutant actin filaments as indicated by a 1.7-fold reduction in the average sliding velocity and an increase in the optimal Myo5A-HMM surface density from 770 to 3100 molecules per µm2. These results indicate a reduction in binding affinity and coupling efficiency, with a likely impact on processivity. We expect only a small incremental gain in knowledge about the extent of changes by performing additional experiments with an inverted assay geometry, given that under physiological conditions the motor properties of Myo5A and other cytoskeletal myosins are modulated by other factors such as the presence of tropomyosin isoforms and other actin binding proteins.

Reviewer #2 (Public Review):

Greve et al. investigated the effects of a disease-associated gamma-actin mutation (E334Q) on actin filament polymerization, association of selected actin-binding proteins, and myosin activity. Recombinant wildtype and mutant proteins expressed in sf9 cells were found to be folded and stable, and the presence of the mutation altered a number of activities. Given the location of the mutation, it is not surprising that there are changes in polymerization and interactions with actin binding proteins. Nevertheless, it is important to quantify the effects of the mutation to better understand disease etiology.

We thank the reviewer for the positive evaluation of our work.

Some weaknesses were identified in the paper as discussed below.

• Throughout the paper, the authors report average values and the standard-error-of-the-mean (SEM) for groups of three experiments. Reporting the SEM is not appropriate or useful for so few points, as it does not reflect the distribution of the data points. When only three points are available, it would be better to just show the three different points. Otherwise, plot the average and the range of the three points.

We have gone through the manuscript carefully to correct any errors in the statistics, as explained below.

Figure 1B, 5B, 5C, 5D, 8D, 9B, and 8 – figure supplement 2 all show the mean ± SD, as also correctly reported for Figure 8E and 8F in the figure legend. The statement, that these figures show the mean ± SEM was inaccurate. We corrected this mistake for all the listed figures. Furthermore, we now give the exact N for every experiment in the figure legend.

Figure 2C, 2E, 2F, 4B, 5A, 6B-E showed the mean ± SEM. As suggested by the reviewer, we corrected the figures to show the mean ± SD.

We still refer to the mean ± SEM in Figure 2B, where elongation rates for more than 100 filaments were recorded, and in Figure 8B, where sliding velocities for several thousand actin filaments were measured.

• The description and characterization of the recombinant actin is incomplete. Please show gels of purified proteins. This is especially important with this preparation since the chymotrypsin step could result in internally cleaved proteins and altered properties, as shown by Ceron et al (2022). The authors should also comment on N-terminal acetylation of actin.

We added an additional figure showing the purification strategy for the recombinant cytoskeletal γ –actin WT and p.E334Q protein with exemplary SDS-gels from different stages of purification (Figure 1 – figure supplement 1).

In a previous paper, we reported the mass spectrometric analysis of the post-translational modifications of recombinant human β- and γ-cytoskeletal actin produced in Sf-9 cells. (Müller et al., 2013, Plos One). Recombinant actin showing complete N-terminal processing resulting in cleavage of the initial methionine and acetylation of the following aspartate (β-actin) or glutamate (γ-actin) is the predominant species in the analyzed preparations (> 95 %). While the recombinant actin in the 2013 study was produced tag-free and purified by affinity chromatography using the column-immobilized actin-binding domain of gelsolin (G4-G6), we have no reason to assume that the purification strategy using the actin-thymosin-β4 changes the efficiency of the N-terminal processing in Sf-9 cells. This is supported by our, yet unpublished, mass-spectrometric studies on recombinant human α-cardiac actin purified using the actin- thymosin-β4 fusion construct, which revealed actin species with an acetylated aspartate-3. This N-terminal modification of α-cardiac actin is catalyzed by the same actinspecific acetyltransferase (NAA80) as the acetylation of asparate-2 or glutamate-2 in cytoskeletal actin isoforms (Varland et al., 2019, Trends in Biochemical Sciences). Furthermore, additional studies that used the actin-thymosin-β4 fusion construct for the production of recombinant human cytoskeletal actin isoforms in Pichia pastoris reported robust N-terminal acetylation, when the actin was co-produced with NAA80 (In contrast to Sf-9 cells, NAA80 is not endogenously expressed in Pichia pastoris) (Hatano et al., 2020, Journal of Cell Science).

We therefore, added the following statement to the manuscript:

“Purification of the fusion protein by immobilized metal affinity chromatography, followed by chymotrypsin–mediated cleavage of C–terminal linker and tag sequences, results in homogeneous protein without non–native residues and native N-terminal processing, which includes cleavage of the initial methionine and acetylation of the following glutamate. “

• The authors do not use the best technique to assess actin polymerization parameters. Although the TIRF assay is excellent for some measurements, it is not as good as the standard pyrene-actin assays that provide critical concentration, nucleation, and polymerization parameters. The authors use pyrene-actin in other parts of the paper, so it is not clear why they don't do the assays that are the standard in the actin field.

The polymerization rate of individual filaments observed in TIRFM experiments showed only minor changes, as did the bulk-polymerization rate of 2 µM actin in pyrene-actin based experiments. Therefore, we decided not to perform additional pyrene-actin based experiments, in which we titrate the actin concentration, as we expect only very small changes to the critical concentration. Instead, we focused on the disturbed interaction with ABPs, as we assume these defects to be more relevant in an in vivo context. Using pyrene-based bulkexperiments, we did determine the rate of dilution-induced depolymerization of mutant filaments and compare them with the values determined for WT (Figure 5A, Table 1).

• The authors' data suggest that, while the binding of cofilin-1 to both the WT and mutant actins remains similar, the major defect of the E334Q actin is that it is not as readily severed/disassembled by cofilin. What is missing is a direct measurement of the severing rate (number of breaks per second) as measured in TIRF.

The severing rate as measured in TIRF is dependent on a number of parameters in a nonlinear manner. Therefore, we opted to show the combination of images directly showing the progress of the reaction and graphs summarizing the concomitant changes in cofilin clusters, actin filaments, actin-related fluorescence intensity and cofilin-related fluorescence intensity.

• Figure 4 shows that the E334Q mutation increases rather than decreases the number of filaments that spontaneously assemble in the TIRF assay, but it is unclear how reduced severing would lead to increased filament numbers, rather, the opposite would be expected. A more straightforward approach would be to perform experiments where severing leads to more nuclei and therefore enhances the net bulk assembly rate.

Figure 4 shows polymerization experiments that were started from ATP-G-actin in the presence of cofilin-1. These experiments show clearly that, especially at the higher cofilin-1 concentration (100 nM), the filament number is strongly increased in experiments performed with mutant actin. Inspection of the corresponding videos of these TIRFM experiments suggest that the increased number of filaments must result from an increased number of de novo nucleation events and not primarily from a mutation-induced change in severing susceptibility. The observation of a cofilin-stimulated increase in the de novo nucleation efficiency of actin was initially described by Andrianantoandro & Pollard (2006, Molecular Cell) using TIRFMbased experiments and is thought to arise from the stabilization of thermodynamically unfavorable actin dimers and trimers by cofilin. While the exact role of this cofilin-mediated effect in vivo is not completely clear, it is thought to contribute to cofilin-meditated actin dynamics synergistically with cofilin-mediated severing. It is therefore necessary, to clearly distinguish between the two effects of cofilin in vitro: stimulation of de novo nucleation and stimulation of filament disassembly. Our data indicated that the E334Q mutation affects these two effects differentially, as we state in the abstract and in the discussion.

Abstract: “E334Q differentially affects cofilin-mediated actin dynamics by increasing the rate of cofilin-mediated de novo nucleation of actin filaments and decreasing the efficiency of cofilin-mediated filament severing.”

Discussion: “Cofilin-mediated severing and nucleation were previously proposed to synergistically contribute to global actin turnover in cells (Andrianantoandro & Pollard, 2006; Du & Frieden, 1998). Our results show that the mutation affects these different cofilin functions in actin dynamics in opposite ways. Cofilin-mediated filament nucleation is more efficient for p.E334Q monomers, while cofilin-mediated severing of filaments containing p.E334Q is significantly reduced. The interaction of both actin monomers and actin filaments with ADF/cofilin proteins involves several distinct overlapping reactions. In the case of actin filaments, cofilin binding is followed by structural modification of the filament, severing and depolymerizing the filament (De La Cruz & Sept, 2010). Cofilin binding to monomeric actin is followed by the closure of the nucleotide cleft and the formation of stabilized “long-pitch” actin dimers, which stimulate nucleation (Andrianantoandro & Pollard, 2006)”.

We interpret the reviewer's suggestion to mean that additional pyrene-actin-based bulk polymerization experiments should be performed to investigate the bulk-polymerization rate of ATP-G-actin in the presence of cofilin-1. In our understanding, these experiment would not provide additional value as 1) An observed increase of the bulk-polymerization rate cannot be directly correlated to a change of the efficiency of de novo nucleation or severing and 2) the effect of the mutation on cofilin-mediated filament disassembly was extensively analyzed in other experiments starting from preformed actin filaments. Moreover, our results are consistent with in silico modelling and normal mode analysis of the WT and mutant actin-cofilin complex.

• Figure 5 A: in the pyrene disassembly assay, where actin is diluted below its critical concentration, cofilin enhances the rate of depolymerization by generating more free ends. The E334Q mutation leads to decreased cofilin-induced severing and therefore lower depolymerization. While these data seem convincing, it would be better to present them as an XY plot and fit the data to lines for comparison of the slopes.

We now present the data as suggested by the reviewer. Furthermore, we determined the apparent second-order rate constant for cofilin-induced F-actin depolymerization (kc) to quantify the observed differences between WT, mutant and heterofilaments, as suggested by the reviewer.

The paragraph describing these results was changed accordingly:

“The observed rate constant values are linearly dependent on the concentration of cofilin–1 in the range 0–40 nM, with the slope corresponding to the apparent second– order rate constant (kC) for the cofilin-1 induced depolymerization of F–actin. In experiments performed with p.E334Q filaments, the value obtained for kC was 4.2-fold lower (0.81 × 10-4 ± 0.08 × 10-4 nM-1 s-1) compared to experiments with WT filaments (3.42 × 10-4 ± 0.22 × 10-4 nM-1 s-1). When heterofilaments were used, the effect of the mutation was reduced to a 2.2-fold difference compared to WT filaments (1.54 × 10-4 ± 0.11 × 10-4 nM-1 s-1).”

• Figure 5 B and C: the cosedimentation data do not seem to help elucidate the underlying mechanism. While the authors report statistical significance, differences are small, especially for gel densitometry measurements where the error is high, which suggests that there may be little biological significance. Importantly, example gels from these experiments should be shown, if not the complete set included in the supplement. In B, the higher cofilin concentrations would be expected to stabilize the filaments and thus the curve should be Ushaped.

We do not completely agree with the reviewer on this point. We think the co-sedimentation experiments are useful, as they show that cofilin-1 efficiently binds to mutant filaments, but is less efficient in stimulating disassembly in these endpoint-experiments. This information is not provided by the analysis of the effect of cofilin-1 on the bulk-depolymerization rate and adds to our understanding of the defect of the actin-cofilin interaction for the mutant.

While we agree with the reviewer on the point that co-sedimentation experiments must be repeated several times to produce reliable data, we cannot fully grasp the reasoning behind the statement “While the authors report statistical significance, differences are small, especially for gel densitometry measurements where the error is high, which suggests that there may be little biological significance.”. We interpret this statement as advice to be cautious when extrapolating the observed perturbances of cofilin-mediated actin dynamics in vitro to the in vivo context. We think we are cautious about this throughout the manuscript.

The author expects a U-shape curve, as high cofilin concentrations are reported to stabilize actin filaments by completely decorating the filament before severing-prone boundaries between cofilin-decorated and undecorated regions are generated. We have also performed these experiment with cytoskeletal β-actin and human cofilin-1 and never observed this U shape. This indicates that significant filament disassembly also happens at high cofilin concentrations, most likely directly after mixing of F-actin and cofilin. We cannot rule out that the incubation time plays an important role and that the U-shape only appears after longer incubation times. We also want to direct the reviewer to the publication “A Mechanism for Actin Filament Severing by Malaria Parasite Actin Depolymerizing Factor 1 via a Low Affinity Binding Interface” (Wong et al. 2013, JBC) in which comparable co-sedimentation experiments were performed (Figure 5E-G) with rabbit skeletal α-actin and human cofilin-1 and also no Ushaped curves were observed, even at higher molar excess of cofilin-1 compared to our experiments and with longer incubation times (1 hour vs. 10 minutes).

We now included an exemplary gel showing co-sedimentation experiments performed with WT, mutant actin and different concentrations of cofilin at pH 7.8 in the manuscript (Figure 5 – figure supplement 2)

• Figure 5 D: these data show that the binding of cofilin to WT and E334Q actin is approximately the same, with the mutant binding slightly more weakly. It would be clearer if the two plots were normalized to their respective plateaus since the difference in arbitrary units distracts from the conclusion of the figure. If the difference in the plateaus is meaningful, please explain.

As suggested by the reviewer, we normalized the data for a better understanding of the message conveyed.

• Figure 6: It is assumed that the authors are trying to show in this figure that cofilin binds both actins approximately the same but does not sever as readily for E334Q actin. The numerous parameters measured do not directly address what the authors are actually trying to show, which presumably is that the rate of severing is lower for E334Q than WT. It is therefore puzzling why no measurement of severing events per second per micron of actin in TIRF is made, which would give a more precise account of the underlying mechanism.

The severing rate as measured in TIRF is dependent on a number of parameters in a nonlinear manner. Therefore, we opted to show the combination of images directly showing the progress of the reaction and graphs summarizing the concomitant changes in cofilin clusters, actin filaments, actin-related fluorescence intensity and cofilin-related fluorescence intensity.

• Actin-activated steady-state ATPase data of the NM2A with mutant and WT actin would have been extremely useful and informative. The authors show the ability to make these types of measurements in the paper (NADH assay), and it is surprising that they are not included for assessing the myosin activity. It may be because of limited actin quantities. If this is the case, it should be indicated.

Indeed, the measurement of the steady-state actin-activated ATPase with recombinant cytoskeletal actin is very material-intensive and therefore costly, as a complete titration of actin is required for the generation of meaningful data. Since the vast majority of our assays involving a myosin family member were performed with NM2A-HMM, we decided to perform a full actin titration of the steady-state actin-activated ATPase of NM2A-HMM with WT and mutant filaments. The results of these experiments are now shown in Figure 8C. The panel showing the results used for determining the dissociation rate constants (k-A) for the interaction of NM2C-2R with p.E334Q or WT γ –actin in the absence of nucleotide was moved to the supplement (Figure 8 – figure supplement 2).

We added the following paragraph to the Material and Methods section concerning the Steady-State ATPase assay:

“For measurements of the basal and actin–activated NM2A–HMM ATPase, 0.5 µM MLCKtreated HMM was used. Phalloidin–stabilized WT or mutant F-actin was added over the range of 0–25 µM. The change in absorbance at 340 nm due to oxidation of NADH was recorded in a Multiskan FC Microplate Photometer (Thermo Fisher Scientific, Waltham, MA, USA). The data were fitted to the Michaelis-Menten equation to obtain values for the actin concentration at half-maximal activation of ATP-turnover (Kapp) and for the maximum ATP-turnover at saturated actin concentration (kcat).”

Furthermore, we added a description of the results of the experiments to the Results section of the manuscript:

“Using a NADH-coupled enzymatic assay, we determined the ability of p.E334Q and WT filaments to activate the ATPase of NM2A-HMM over the range of 0-25 µM F-actin (Figure 8C). While we observed no significant difference in Kapp, indicated by the actin concentration at half-maximal activation, in experiments with p.E334Q filaments (2.89 ± 0.49 µM) and WT filaments (3.20 ± 0.74 µM), we observed a 28% slower maximal ATP turnover at saturating actin concentration (kcat) with p.E334Q filaments (0.076 ± 0.005 s-1 vs. 0.097 ± 0.002 s-1).”

• (line 310) The authors state that they "noticed increased rapid dissociation and association events for E334Q filaments" in the motility assay. This observation motivates the authors to assess actin affinities of NM2A-HMM. Although differences in rigor and AM.ADP affinities are found between mutant and WT actins, the actin attachment lifetimes (many minutes) are unlikely to be related to the rapid association and dissociation event seen in the motility assay. Rather, this jiggling is more likely to be related to a lower duty ratio of the myosins, which appears to be the conclusion reached for the myosin-V data. These points should be clarified in the text.

We changed the text in accordance with the reviewer’ suggestion. It reads now: Cytoskeletal –actin filaments move with an average sliding velocity of 195.3 ± 5.0 nm s–1 on lawns of surface immobilized NM2A–HMM molecules (Figure 8A, B). For NM2A-HMM densities below about 10,000 molecules per μm2, the average sliding speed for cytoskeletal actin filaments drops steeply (Hundt et al, 2016). Filaments formed by p.E334Q actin move 5fold slower, resulting in an observed average sliding velocity of 39.1 ± 3.2 nm/s. Filaments copolymerized from a 1:1 mixture of WT and p.E334Q actin move with an average sliding velocity of 131.2 ± 10 nm s–1 (Figure 8A, B). When equal densities of surface-attached WT and mutant filaments were used, we observed that the number of rapid dissociation and association events increased markedly for p.E334Q filaments (Figure 8 – video supplement 7– 9).

Using a NADH-coupled enzymatic assay, we determined the ability of p.E334Q and WT filaments to activate the ATPase of NM2A-HMM over the range of 0-25 µM F-actin (Figure 8C). While we observed no significant difference in Kapp, indicated by the actin concentration at halfmaximal activation, in experiments with p.E334Q filaments (2.89 ± 0.49 µM) and WT filaments (3.20 ± 0.74 µM), we observed a 28% slower maximal ATP turnover at saturating actin concentration (kcat) with p.E334Q filaments (0.076 ± 0.005 s-1 vs. 0.097 ± 0.002 s-1). To investigate the impact of the mutation on actomyosin–affinity using transient–kinetic approaches, we determined the dissociation rate constants using a single–headed NM2A–2R construct (Figure 8D). …..

• (line 327) The authors report that the 1/K1 value is unchanged. There are no descriptions of this experiment in the paper. I am assuming the authors measured the ATP-induced dissociation of actomyosin and determined ATP affinity (K1) from this experiment. If this is the case, they should describe the experiment and show the data, provide a second-order rate constate for ATP binding, and report the max rate of dissociation (k2). This is a kinetic experiment done frequently by this group, so the absence of these details is surprising.

In the previous version of the manuscript, the method used to determine 1/K1 (ATP-induced dissociation of the actomyosin complex) was described in the Material and Methods paragraph “Transient kinetic analysis of the actomyosin complex” and the values obtained for 1/K1 were given in Table 1. We now included the experimental data as an additional figure in the manuscript (Figure 8 – figure supplement 3). Furthermore, we also give the maximal dissociation rate k+2 and the apparent second-order rate constant for ATP-binding (K1k+2) for the WT and mutant actomyosin complex in Table 1. Therefore, we changed the paragraph in the Results section concerning this experiment to:

“The apparent ATP–affinity (1/K1), the maximal dissociation rate of NM2A from F-actin in the presence of ATP (k+2), and the apparent second-order rate constant of ATP binding (K1k+2) showed no significant differences for complexes formed between NM2A and WT or p.E334Q filaments (Table 1, Figure 8 – figure supplement 3).”

and the section in the Material and Methods to:

“The apparent ATP–affinity of the actomyosin complex was determined by mixing the apyrase–treated, pyrene–labeled, phalloidin–stabilized actomyosin complex with increasing concentrations of ATP at the stopped–flow system. Fitting an exponential function to the individual transients yields the ATP–dependent dissociation rate of NM2A–2R from F–actin (kobs). The kobs–values were plotted against the corresponding ATP concentrations and a hyperbola was fitted to the data. The fit yields the apparent ATP–affinity (1/K1) of the actomyosin complex and the maximal dissociation rate k+2.

The apparent second–order rate constant for ATP binding (K1k+2) was determined by applying a linear fit to the data obtained at low ATP concentrations (0 – 25 µM).”

For a better understanding of the numerous rate and equilibrium constants, we have now included a figure showing the kinetic reaction scheme of the myosin ATPase cycle (Figure 8 – figure supplement 1).

Recommendations for the authors:

Reviewer #1:

• The subdomains of actin are mislabeled in Fig. 1A.

The labeling of the subdomains has been corrected.

• Additional experimental data addressing the 3 weaknesses noted in the public review would be informative but are not essential in my opinion. Examining the effect of cofilin on severing by the TIRF assay in more detail and using a processivity assay for myosin V (immobilized actin) would be the two aspects I would most value.

The TIRF assay for cofilin severing was performed initially over the cofilin concentration range from 20 to 250 nM. The results obtained in the presence of 100 nM cofilin allow a particularly informative depiction of the differences observed with mutant and WT actin. This applies to the image series showing the changes in filament length, cofilin clusters, and filament number as well as to the graphs showing time dependent changes in the number of filaments and total actin fluorescence. We have not included the results for a 50:50 mixture of WT:mutant actin because its attenuating effect is documented in several other experiments in the manuscript.

Our results with Myo5A show a less productive interaction with mutant actin filaments as indicated by a 1.7-fold reduction in the average sliding velocity and an increase in the optimal Myo5A-HMM surface density from 770 to 3100 molecules per µm2. These results indicate a reduction in binding affinity and coupling efficiency, with a likely impact on processivity. Given that Myo5A is only one of many cytoskeletal myosin motors and that the motor properties of all myosins are modulated by the presence of tropomyosin isoforms and other actin binding proteins, we expect only a small incremental gain in knowledge by performing additional experiments with an inverted assay geometry.

Reviewer #2:

• The authors should address the concerns regarding the statistical methodologies.

We have gone through the manuscript carefully to correct any errors in the statistics, as explained below.

Figure 1B, 5B, 5C, 5D, 8D, 9B, and 8 – figure supplement 2 all show the mean ± SD, as also correctly reported for Figure 8E and 8F in the figure legend. The statement, that these figures show the mean ± SEM was wrong and we corrected this mistake for all the listed figures. Furthermore, we now give the exact N for every experiment in the figure legend.

Figure 2C, 2E, 2F, 4B, 5A, 6B-E indeed showed the mean ± SEM. As the reviewer rightly points out, this is not the appropriate way to deal with such sample sizes. We therefore corrected the figures to show the mean ± SD.

We still refer to the mean ± SEM in Figure 2B, where elongation rates for more than 100 filaments were recorded, and in Figure 8B, where sliding velocities for several thousand actin filaments were measured.

• The authors should present the actin titration of the steady state ATPase activity for at least one of the myosins, or preferably all of them.

An actin titration of the steady state ATPase activity of NM-2A has been included in the revised version of the manuscript (Fig 8C).

• The authors should consider the use of pyrene-actin in measuring the assembly/disassembly of actin.

Values for the rate of actin assembly/disassembly measured with pyrene-actin are given in Table 1. Based on the small changes observed, we did not determine the critical actin concentration for the mutant construct.

Reviewer #1 (Public Review):

Summary: Nuclear depletion and cytoplasmic mislocalization/aggregation of the DNA and RNA binding protein TDP-43 are pathological hallmarks of multiple neurodegenerative diseases. Prior work has demonstrated that depletion of TDP-43 from the nucleus leads to alterations in transcription and splicing. Conversely, cytoplasmic mislocalization/aggregation can contribute to toxicity by impairing mRNA transport and translation as well as miRNA dysregulation. However, to date, models of TDP-43 proteinopathy rely on artificial knockdown- or overexpression-based systems to evaluate either nuclear loss or cytoplasmic gain of function events independently. Few model systems authentically reproduce both nuclear depletion and cytoplasmic miscloalization/aggreagtion events. In this manuscript, the authors generate novel iPSC-based reagents to manipulate the localization of endogenous TDP-43. This is a valuable resource for the field to study pathological consequences of TDP-43 proteinopathy in a more endogenous and authentic setting. However, in the current manuscript, there are a number of weaknesses that should be addressed to further validate the ability of this model to replicate human disease pathology and demonstrate utility for future studies.

Strengths: The primary strength of this paper is the development of a novel in vitro tool.

Weaknesses: There are a number of weaknesses detailed below that should be addressed to thoroughly validate these new reagents as more authentic models of TDP-43 proteinopathy and demonstrate their utility for future investigations.

(1) The authors should include images of their engineered TDP-43-GFP iPSC line to demonstrate TDP-43 localization without the addition of any nanobodies (perhaps immediately prior to addition of nanobodies). Additionally, it is unclear whether simply adding a GFP tag to endogenous TDP-43 impact its normal function (nuclear-cytoplasmic shuttling, regulation of transcription and splicing, mRNA transport etc).

(2) Can the authors explain why there is a significant discrepancy in time points selected for nanobody transduction and immunostaining or cell lysis throughout Figure 1 and 2? This makes interpretation and overall assessment of the model challenging.

(3) The authors should further characterize their TDP-43 puncta. TDP-43 immunostaining is typically punctate so it is unclear if the puncta observed are physiologic or pathologic based on the analyses carried out in the current version of this manuscript. Additionally, do these puncta co-localize with stress granule markers or RNA transport granule markers? Are these puncta phosphorylated (which may be more reminiscent of end-stage pathologic observations in humans)?

(4) The authors should include multiple time points in their evaluation of TDP-43 loss of function events and aggregation. Does loss of function get worse over time? Is there a time course by which RNA misprocessing events emerge or does everything happen all at once? Does aggregation get worse over time? Do these neurons die at any point as a result of TDP-43 proteinopathy?

(5) Can the authors please comment on whether or not their model is "tunable"? In real human disease, not every neuron displays complete nuclear depletion of TDP-43. Instead there is often a gradient of neurons with differing magnitudes of nuclear TDP-43 loss. Additionally, very few neurons (5-10%) harbor cytoplasmic TDP-43 aggregates at end-stage disease. These are all important considerations when developing a novel authentic and endogenous model of TDP-43 proteinopathy which the current manuscript fails to address.

Reviewer #2 (Public Review):

Summary:<br /> TDP-43 mislocalization occurs in nearly all of ALS, roughly half of FTD, and as a co-pathology in roughly half of AD cases. Both gain-of-function and loss-of-function mechanisms associated with this mislocalization likely contribute to disease pathogeneisis.

Here, the authors describe a new method to induce TDP-43 mislocalization in cellular models. They endogenously-tagged TDP-43 with a C-terminal GFP tag in human iPSCs. They then expressed an intrabody - fused with a nuclear export signal (NES) - that targeted GFP to the cytosol. Expression of this intrabody-NES in human iPSC-derived neurons induced nuclear depletion of homozygous TDP-43-GFP, caused its mislocalization to the cytosol, and at least in some cells appeared to cause cytosolic aggregates. This mislocalization was accompanied by induction of cryptic exons in well characterized transcripts known to be regulated by TDP-43, a hallmark of functional TDP-43 loss and consistent with pathological nuclear TDP-43 depletion. Interestingly, in heterozygous TDP-43-GFP neurons, expression of intrabody-NES appeared to also induce the mislocalization of untagged TDP-43 in roughly half of the neurons, suggesting that this system can also be used to study effects on untagged endogenous TDP-43 as well as TDP-43-GFP fusion protein.

Strengths:<br /> A clearer understanding of how TDP-43 mislocalization alters cellular function, as well as pathways that mitigate clearance of TDP-43 aggregates, is critical. But modeling TDP-43 mislocalization in disease-relevant cellular systems has proven to be challenging. High levels of overexpression of TDP-43 lacking an NES can drive endogenous TDP-43 mislocalization, but such overexpression has direct and artificial consequences on certain cellular features (e.g. altered exon skipping) not seen in diseased patients. Toxic small molecules such as MG132 and arsenite can induce TDP-43 mislocalization, but co-induce myriad additional cellular dysfunctions unrelated to TDP-43 or ALS. TDP-43 binding oligonucleotides can cause cytosolic mislocalization as well. Each system has pros and cons, and additional ways to induce TDP-43 mislocalization would be useful for the field. The method described in this manuscript could provide researchers with a powerful way to study the combined biology of cytosolic TDP-43 mislocalization and nuclear TDP-43 depletion, with additional temporal control that is lacking in current method. Indeed, the authors see some evidence of differences in RNA splicing caused by pure TDP-43 depletion versus their induced mislocalization model. Finally, their method may be especially useful in determining how TDP-43 aggregates are cleared by cells, potentially revealing new biological pathways that could be therapeutically targeted.

Weaknesses:<br /> The method and supporting data have limitations in its current form, outlined below, and in its current form the findings are rather preliminary.

• Tagging of TDP-43 with a bulky GFP tag may alter its normal physiological functions, for example phase separation properties and functions within complex ribonucleoprotein complexes. In addition, alternative isoforms of TDP-43 (e.g. "short" TDP-43, would not be GFP tagged and therefore these species would not be directly manipulatable or visualizable with the tools currently employed in the manuscript.<br /> • The data regarding potential mislocalization of endogenous TDP-43 in the heterozygous TDP-43-GFP lines is especially intriguing and important, yet very little characterization was done. Does untagged TDP-43 co-aggregate with the tagged TDP-43? Is localization of TDP-43 immunostaining the same as the GFP signal in these cells?<br /> • The experiments in which dox was used to induce the nanobody-NES, then dox withdrawn to study potential longer-lasting or self-perpetuating inductions of aggregation is potentially interesting. However, the nanobody was only measured at the RNA level. We know that protein half lives can be very long in neurons, and therefore residual nanobody could be present at these delayed time points. The key measurement to make would be at the protein level of the nanobody if any conclusions are be made from this experiment.<br /> • Potential differences in splicing and microRNAs between TDP-43 knockdown and TDP-43 mislocalization are potentially interesting. However, different patterns of dysregulated RNA splicing can occur at different levels of TDP-knockdown, thus it is difficult to asses whether the changes observed in this paper are due to mislocalization per se, or rather just reflect differences in nuclear TDP-43 abundance.

Author Response

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

eLife assessment

This important study combines a range of advanced ultrastructural imaging approaches to define the unusual endosomal system of African trypanosomes. Compelling images show that instead of a distinct set of compartments, the endosome of these protists comprises a continuous system of membranes with functionally distinct subdomains as defined by canonical markers of early, late and recycling endosomes. The findings suggest that the endocytic system of bloodstream stages has evolved to facilitate the extraordinarily high rates of membrane turnover needed to remove immune complexes and survive in the blood, which is of interest to anyone studying infectious diseases.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

Bloodstream stages of the parasitic protist, Trypanosoma brucei, exhibit very high rates of constitutive endocytosis, which is needed to recycle the surface coat of Variant Surface Glycoproteins (VSGs) and remove surface immune complexes. While many studies have shown that the endo-lysosomal systems of T. brucei BF stages contain canonical domains, as defined by classical Rab markers, it has remained unclear whether these protists have evolved additional adaptations/mechanisms for sustaining these very high rates of membrane transport and protein sorting. The authors have addressed this question by reconstructing the 3D ultrastructure and functional domains of the T. brucei BF endosome membrane system using advanced electron tomography and super-resolution microscopy approaches. Their studies reveal that, unusually, the BF endosome network comprises a continuous system of cisternae and tubules that contain overlapping functional subdomains. It is proposed that a continuous membrane system allows higher rates of protein cargo segregation, sorting and recycling than can otherwise occur when transport between compartments is mediated by membrane vesicles or other fusion events.

Strengths:

The study is a technical tour-de-force using a combination of electron tomography, super-resolution/expansion microscopy, immune-EM of cryo-sections to define the 3D structures and connectivity of different endocytic compartments. The images are very clear and generally support the central conclusion that functionally distinct endocytic domains occur within a dynamic and continuous endosome network in BF stages.

Weaknesses:

The authors suggest that this dynamic endocytic network may also fulfil many of the functions of the Golgi TGN and that the latter may be absent in these stages. Although plausible, this comment needs further experimental support. For example, have the authors attempted to localize canonical makers of the TGN (e.g. GRIP proteins) in T. brucei BF and/or shown that exocytic carriers bud directly from the endosomes?

We agree with the criticism and have shortened the discussion accordingly and clearly marked it as speculation. However, we do not want to completely abandon our hypothesis.

The paragraph now reads:

Lines 740 – 751:

“Interestingly, we did not find any structural evidence of vesicular retrograde transport to the Golgi. Instead, the endosomal ‘highways’ extended throughout the posterior volume of the trypanosomes approaching the trans-Golgi interface. It is highly plausible that this region represents the convergence point where endocytic and biosynthetic membrane trafficking pathways merge. A comparable merging of endocytic and biosynthetic functions has been described for the TGN in plants. Different marker proteins for early and recycling endosomes were shown to be associated and/ or partially colocalized with the TGN suggesting its function in both secretory and endocytic pathways (reviewed in Minamino and Ueda, 2019). As we could not find structural evidence for the existence of a TGN we tentatively propose that trypanosomes may have shifted the central orchestrating function of the TGN as a sorting hub at the crossroads of biosynthetic and recycling pathways to the endosome. Although this is a speculative scenario, it is experimentally testable.”

Furthermore, we removed the lines 51 - 52, which included the suggestion of the TGN as a master regulator, from the abstract.

Reviewer #2 (Public Review):

The authors suggest that the African trypanosome endomembrane system has unusual organisation, in that the entire system is a single reticulated structure. It is not clear if this is thought to extend to the lysosome or MVB. There is also a suggestion that this unusual morphology serves as a trans-(post)Golgi network rather than the more canonical arrangement.

The work is based around very high-quality light and electron microscopy, as well as utilising several marker proteins, Rab5A, 11 and 7. These are deemed as markers for early endosomes, recycling endosomes and late or pre-lysosomes. The images are mostly of high quality but some inconsistencies in the interpretation, appearance of structures and some rather sweeping assumptions make this less easy to accept. Two perhaps major issues are claims to label the entire endosomal apparatus with a single marker protein, which is hard to accept as certainly this reviewer does not really even know where the limits to the endosomal network reside and where these interface with other structures. There are several additional compartments that have been defined by Rob proteins as well, and which are not even mentioned. Overall I am unconvinced that the authors have demonstrated the main things they claim.<br /> The endomembrane system in bloodstream form T. brucei is clearly delimited. Compared to mammalian cells it is tidy and confined to the posterior part of the spindleshaped cell. The endoplasmic reticulum is linked to one side of the longitudinal cell axis, marked by the attached flagellum, while the mitochondrion locates to the opposite side. Glycosomes are easily identifiable as spheres, as are acidocalcisomes, which are smaller than glycosomes and – in electron micrographs – are characterized by high electron density. All these organelles extend beyond the nucleus, which is not the case for the endosomal compartment, the lysosome and the Golgi. The vesicles found in the posterior half of the trypanosome cell are quantitatively identifiable as COP1, CCVI or CCVII vesicles, or exocytic carriers. The lysosome has a higher degree of morphological plasticity, but this is not topic of the present work. Thus, the endomembrane system in T. brucei is comparatively well structured and delimited, which is why we have chosen trypanosomes as cell biological model.

We have published EP1::GFP as marker for the endosome system and flagellar pocket back in 2004. We have defined the fluid phase volume of the trypanosome endosome in papers published between 2002 and 2007. This work was not intended to represent the entirety of RAB proteins. We were only interested in 3 canonical markers for endosome subtypes. We do not claim anything that is not experimentally tested, we have clearly labelled our hypotheses as such, and we do not make sweeping assumptions.

The approaches taken are state-of-the-art but not novel, and because of the difficulty in fully addressing the central tenet, I am not sure how much of an impact this will have beyond the trypanosome field. For certain this is limited to workers in the direct area and is not a generalisable finding.

To the best of our knowledge, there is no published research that has employed 3D Tokuyasu or expansion microscopy (ExM) to label endosomes. The key takeaway from our study, which is the concept that "endosomes are continuous in trypanosomes" certainly is novel. We are not aware of any other report that has demonstrated this aspect.

The doubts formulated by the reviewer regarding the impact of our work beyond the field of trypanosomes are not timely. Indeed, our results, and those of others, show that the conclusions drawn from work with just a few model organisms is not generalisable. We are finally on the verge of a new cell biology that considers the plethora of evolutionary solutions beyond ophistokonts. We believe that this message should be widely acknowledged and considered. And we are certainly not the only ones who are convinced that the term "general relevance" is unscientific and should no longer be used in biology.

Reviewer #3 (Public Review):

Summary:

As clearly highlighted by the authors, a key plank in the ability of trypanosomes to evade the mammalian host’s immune system is its high rate of endocytosis. This rapid turnover of its surface enables the trypanosome to ‘clean’ its surface removing antibodies and other immune effectors that are subsequently degraded. The high rate of endocytosis is likely reflected in the organisati’n and layout of the endosomal system in these parasites. Here, Link et al., sought to address this question using a range of light and three-dimensional electron microscopy approaches to define the endosomal organisation in this parasite.

Before this study, the vast majority of our information about the make-up of the trypanosome endosomal system was from thin-section electron microscopy and immunofluorescence studies, which did not provide the necessary resolution and 3D information to address this issue. Therefore, it was not known how the different structures observed by EM were related. Link et al., have taken advantage of the advances in technology and used an impressive combination of approaches at the LM and EM level to study the endosomal system in these parasites. This innovative combination has now shown the interconnected-ness of this network and demonstrated that there are no ‘classical’ compartments within the endosomal system, with instead different regions of the network enriched in different protein markers (Rab5a, Rab7, Rab11).

Strengths:

This is a generally well-written and clear manuscript, with the data well-presented supporting the majority of the conclusions of the authors. The authors use an impressive range of approaches to address the organisation of the endosomal system and the development of these methods for use in trypanosomes will be of use to the wider parasitology community.

I appreciate their inclusion of how they used a range of different light microscopy approaches even though for instance the dSTORM approach did not turn out to be as effective as hoped. The authors have clearly demonstrated that trypanosomes have a large interconnected endosomal network, without defined compartments and instead show enrichment for specific Rabs within this network.

Weaknesses:

My concerns are:

i) There is no evidence for functional compartmentalisation. The classical markers of different endosomal compartments do not fully overlap but there is no evidence to show a region enriched in one or other of these proteins has that specific function. The authors should temper their conclusions about this point.

The reviewer is right in stating that Rab-presence does not necessarily mean Rabfunction. However, this assumption is as old as the Rab literature. That is why we have focused on the 3 most prominent endosomal marker proteins. We report that for endosome function you do not necessarily need separate membrane compartments. This is backed by our experiments.

ii) The quality of the electron microscopy work is very high but there is a general lack of numbers. For example, how many tomograms were examined? How often were fenestrated sheets seen? Can the authors provide more information about how frequent these observations were?

The fenestrated sheets can be seen in the majority of the 37 tomograms recorded of the posterior volume of the parasites. Furthermore, we have randomly generated several hundred tiled (= very large) electron micrographs of bloodstream form trypanosomes for unbiased analyses of endomembranes. In these 2D-datasets the “footprint” of the fenestrated flat and circular cisternae is frequently detectable in the posterior cell area.

We now have included the corresponding numbers in all EM figure legends.

iii) The EM work always focussed on cells which had been processed before fixing. Now, I understand this was important to enable tracers to be used. However, given the dynamic nature of the system these processing steps and feeding experiments may have affected the endosomal organisation. Given their knowledge of the system now, the authors should fix some cells directly in culture to observe whether the organisation of the endosome aligns with their conclusions here.

This is a valid criticism; however, it is the cell culture that provides an artificial environment. As for a possible effect of cell harvesting by centrifugation on the integrity and functionality of the endosome system, we consider this very unlikely for one simple reason. The mechanical forces acting in and on the parasites as they circulate in the extremely crowded and confined environment of the mammalian bloodstream are obviously much higher than the centrifugal forces involved in cell preparation. This becomes particularly clear when one considers that the mass of the particle to be centrifuged determines the actual force exerted by the g-forces. Nevertheless, the proposed experiment is a good control, although much more complex than proposed, since tomography is a challenging technique. We have performed the suggested experiment and acquired tomograms of unprocessed cells. The corresponding data is now included as supplementary movie 2, 3 and 4. We refer to it in lines 202 – 206: To investigate potential impacts of processing steps (cargo uptake, centrifugation, washing) on endosomal organization, we directly fixed cells in the cell culture flask, embedded them in Epon, and conducted tomography. The resulting tomograms revealed endosomal organization consistent with that observed in cells fixed after processing (see Supplementary movie 2, 3, and 4).

We furthermore thank the reviewer for the experiment suggestion in the acknowledgments.

iv) The discussion needs to be revamped. At the moment it is just another run through of the results and does not take an overview of the results presenting an integrated view. Moreover, it contains reference to data that was not presented in the results.

We have improved the discussion accordingly.

Recommendations for the authors:

The reviewers concurred about the high calibre of the work and the importance of the findings.

They raised some issues and made some suggestions to improve the paper without additional experiments - key issues include

(1) Better referencing of the trypanosome endocytosis/ lysosomal trafficking literature.

The literature, especially the experimental and quantitative work, is very limited. We now provide a more complete set of references. However, we would like to mention that we had cited a recent review that critically references the trypanosome literature with emphasis on the extensive work done with mammalian cells and yeast.

(2) Moving the dSTORM data that detracts from otherwise strong data in a supplementary figure.

We have done this.

(3) Removal of the conclusion that the continuous endosome fulfils the functions of TGN, without further evidence.

As stated above, this was not a conclusion in our paper, but rather a speculation, which we have now more clearly marked as such. Lines 740 to 751 now read:

“Interestingly, we did not find any structural evidence of vesicular retrograde transport to the Golgi. Instead, the endosomal ‘highways’ extended throughout the posterior volume of the trypanosomes approaching the trans-Golgi interface. It is highly plausible that this region represents the convergence point where endocytic and biosynthetic membrane trafficking pathways merge. A comparable merging of endocytic and biosynthetic functions was already described for the TGN in plants. Different marker proteins for early and recycling endosomes were shown to be associated and/ or partially colocalized with the TGN suggesting its function in both secretory and endocytic pathways (reviewed in Minamino and Ueda, 2019). As we could not find structural evidence for the existence of a TGN we tentatively propose that trypanosomes may have shifted the central orchestrating function of the TGN as a sorting hub at the crossroads of biosynthetic and recycling pathways to the endosome. Although this is a speculative scenario, it is experimentally testable.”

(4) Broader discussion linking their findings to other examples of organelle maturation in eukaryotes (e.g cisternal maturation of the Golgi)

We have improved the discussion accordingly.

Reviewer #1 (Recommendations For The Authors):

What are the multi-vesicular vesicles that surround the marked endosomal compartments in Fig 1. Do they become labelled with fluid phase markers with longer incubations (e.g late endosome/ lysosomal)?

The function of MVBs in trypanosomes is still far from being clear. They are filled with fluid phase cargo, especially ferritin, but are devoid of VSG. Hence it is likely that MVBs are part of the lysosomal compartment. In fact, this part of the endomembrane system is highly dynamic. MVBs can be physically connected to the lysosome or can form elongated structures. The surprising dynamics of the trypanosome lysosome will be published elsewhere.

Figure 2. The compartments labelled with EP1::Halo are very poorly defined due to the low levels of expression of the reporter protein and/or sensitivity of detection of the Halo tag. Based on these images, it would be hard to conclude whether the endosome network is continuous or not. In this respect, it is unclear why the authors didn't use EP1-GFP for these analyses? Given the other data that provides more compelling evidence for a single continuous compartment, I would suggest removing Fig 2A.

We have used EP1::GFP to label the entire endosome system (Engstler and Boshart, 2004). Unfortunately, GFP is not suited for dSTORM imaging. By creating the EP1::Halo cell line, we were able to utilize the most prominent dSTORM fluorescent dye, Alexa 647. This was not primarily done to generate super resolution images, but rather to measure the dynamics of the GPI-anchored, luminal protein EP with single molecule precision. The results from this study will be published separately. But we agree with the reviewer and have relocated the dSTORM data to the supplementary material.

The observation that Rab5a/7 can be detected in the lumen of lysosome is interesting. Mechanistically, this presumably occurs by invagination of the limiting membrane of the lysosome. Is there any evidence that similar invagination of cytoplasmic markers occurs throughout or in subdomains of the endocytic network (possibly indicative of a 'late endosome' domain)?

So far, we have not observed this. The structure of the lysosome and the membrane influx from the endosome are currently being investigated.

The authors note that continuity of functionally distinct membrane compartments in the secretory/endocytic pathways has been reported in other protists (e.g T. cruzi). A particular example that could be noted is the endo-lysosomal system of Dictyostelium discoideum which mediates the continuous degradation and eventual expulsion of undigested material.

We tried to include this in the discussion but ultimately decided against it because the Dictyostelium system cannot be easily compared to the trypanosome endosome.

Reviewer #2 (Recommendations For The Authors):

Abstract

Not sure that 'common' is the correct term here. Frequent, near-universal..... it would be true that endocytosis is common across most eukaryotes.

We have changed the sentence to “common process observed in most eukaryotes” (line 33).

Immune evasion - the parasite does not escape the immune system, but does successfully avoid its impact, at least at the population level.

We have replaced the word “escape” with “evasion” (line 35).

The third sentence needs to follow on correctly from the second. Also, more than Igs are internalised and potentially part of immune evasion, such as C3, Factor H, ApoL1 etcetera.

We believe that there may be a misunderstanding here. The process of endocytic uptake and lysosomal degradation has so far only been demonstrated in the context of VSGbound antibodies, which is why we only refer to this. Of course, the immune system comprises a wide range of proteins and effector molecules, all of which could be involved in immune evasion.

I do not follow the logic that the high flux through the endocytic system in trypanosomes precludes distinct compartmentalisation - one could imagine a system where a lot of steps become optimised for example. This idea needs expanding on if it is correct.

Membrane transport by vesicle transfer between several separate membrane compartments would be slower than the measured rate of membrane flux.

Again I am not sure 'efficient' on line 40. It is fast, but how do you measure efficiency? Speed and efficiency are not the same thing.

We have replaced the word “efficient” with “fast” (line 42).

The basis for suggesting endosomes as a TGN is unclear. Given that there are AP complexes, retromer, exocyst and other factors that are part of the TGN or at least post-G differentiation of pathways in canonical systems, this seems a step too far. There really is no evidence in the rest of the MS that seems to support this.

Yes, we agree and have clarified the discussion accordingly. We have not completely removed the discussion on the TGN but have labelled it more clearly as speculation.

I am aware I am being pedantic here, but overall the abstract seems to provide an impression of greater novelty than may be the case and makes several very bold claims that I cannot see as fully valid.

We are not aware of any claim in the summary that we have not substantiated with experiments, or any hypothesis that we have not explained.

Moreover, the concept of fused or multifunctional endosomes (or even other endomembrane compartments) is old, and has been demonstrated in metazoan cells and yeast. The concept of rigid (in terms of composition) compartments really has been rejected by most folks with maturation, recycling and domain structures already well-established models and concepts.

We agree that the (transient) presence of multiple Rab proteins decorating endosomes has been demonstrated in various cell types. This finding formed the basis for the endosomal maturation model in mammals and yeast, which has replaced the previous rigid compartment model.

However, we do not appreciate attempts to question the originality of our study by claiming that similar observations have been made in metazoans or yeast. This is simply wrong. There are no reports of a functionally structured, continuous, single and large endosome in any other system. The only membrane system that might be similar was described in the American parasite Trypanosoma cruzi, however, without the use of endosome markers or any functional analysis. We refer to this study in the discussion.

In summary, the maturation model falls short in explaining the intricacies of the membrane system we have uncovered in trypanosomes. Therefore, one plausible interpretation of our data is that the overall architecture of the trypanosome endosomes represents an adaptation that enables the remarkable speed of plasma membrane recycling observed in these parasites. In our view, both our findings and their interpretation are novel and worth reporting. Again, modern cell biology should recognize that evolution has developed many solutions for similar processes in cells, about whose diversity we have learned almost nothing because of our reductionist view. A remarkable example of this are the Picozoa, tiny bipartite eukaryotes that pack the entire nutritional apparatus into one pouch and the main organelles with the locomotor system into the other. Another one is the “extreme” cell biology of many protozoan parasites such as Giardia, Toxpoplasma or Trypanosoma.

Higher plants have been well characterised, especially at the level of Rab/Arf proteins and adaptins.

We now mention plant endosomes in our brief discussion of the trypanosome TGN. Lines 744 – 747:

“A comparable merging of endocytic and biosynthetic functions was already described for the TGN in plants. Different marker proteins for early and recycling endosomes were shown to be associated and/ or partially colocalized with the TGN suggesting its function in both secretory and endocytic pathways (reviewed in Minamino and Ueda, 2019).”

The level of self-citing in the introduction is irritating and unscholarly. I have no qualms with crediting the authors with their own excellent contributions, but work from Dacks, Bangs, Field and others seems to be selectively ignored, with an awkward use of the authors' own publications. Diversity between organisms for example has been a mainstay of the Dacks lab output, Rab proteins and others from Field and work on exocytosis and late endosomal systems from Bangs. These efforts and contributions surely deserve some recognition?

This is an original article and not a review. For a comprehensive overview the reviewer might read our recent overview article on exo- and endocytic pathways in trypanosomes, in which we have extensively cited the work of Mark Field, Jay Bangs and Joel Dacks. In the present manuscript, we have cited all papers that touch on our results or are otherwise important for a thorough understanding of our hypotheses. We do not believe that this approach is unscientific, but rather improves the readability of the manuscript. Nevertheless, we have now cited additional work.

For the uninitiated, the posterior/anterior axis of the trypanosome cell as well as any other specific features should be defined.

In lines 102 - 110 we wrote:

“This process of antibody clearance is driven by hydrodynamic drag forces resulting from the continuous directional movement of trypanosomes (Engstler et al., 2007). The VSG-antibody complexes on the cell surface are dragged against the swimming direction of the parasite and accumulate at the posterior pole of the cell. This region harbours an invagination in the plasma membrane known as the flagellar pocket (FP) (Gull, 2003; Overath et al., 1997). The FP, which marks the origin of the single attached flagellum, is the exclusive site for endo- and exocytosis in trypanosomes (Gull, 2003; Overath et al., 1997). Consequently, the accumulation of VSG-antibody complexes occurs precisely in the area of bulk membrane uptake.”

We think this sufficiently introduces the cell body axes.

I don't understand the comment concerning microtubule association. In mammalian cells, such association is well established, but compartments still do not display precise positioning. This likely then has nothing to do with the microtubule association differences.

We have clarified this in the text (lines 192 – 199). There is no report of cytoplasmic microtubules in trypanosomes. All microtubules appear to be either subpellicular or within the flagellum. To maintain the structure and position of the endosomal apparatus, they should be associated either with subpellicular microtubules, as is the case with the endoplasmic reticulum, or with the more enigmatic actomyosin system of the parasites. We have been working on the latter possibility and intend to publish a follow-up paper to the present manuscript.

The inability to move past the nucleus is a poor explanation. These compartments are dynamic. Even the nucleus does interesting things in trypanosomes and squeezes past structures during development in the tsetse fly.

The distance between the nucleus and the microtubule cytoskeleton remains relatively constant even in parasites that squeeze through microfluidic channels. This is not unexpected as the nucleus can be highly deformed. A structure the size of the endosome will not be able to physically pass behind the nucleus without losing its integrity. In fact, the recycling apparatus is never found in the anterior part of the trypanosome, most probably because the flagellar pocket is located at the posterior cell pole.

L253 What is the evidence that EP1 labels the entire FP and endosomes? This may be extensive, but this claim requires rather more evidence. This is again suggested at l263. Again, please forgive me for being pedantic, but this is an overstatement unless supported by evidence that would be incredibly difficult to obtain. This is even sort of acknowledged on l271 in the context of non-uniform labelling. This comes again in l336.

The evidence that EP1 labels the entire FP and endosomes is presented here: Engstler and Boshart, 2004; 10.1101/gad.323404).

Perhaps I should refrain from comments on the dangers of expansion microscopy, or asking what has actually been gained here. Oddly, the conclusion on l290 is a fair statement that I am happy with.

An in-depth discussion regarding the advantages and disadvantages of expansion microscopy is beyond the manuscript's intended scope. Our approach involved utilizing various imaging techniques to confirm the validity of our findings. We appreciate that our concluding sentence is pleasing.

F2 - The data in panel A seem quite poor to me. I also do not really understand why the DAPI stain in the first and second columns fails to coincide or why the kinetoplast is so diffuse in the second row. The labelling for EP1 presents as very small puncta, and hence is not evidence for a continuum. What is the arrow in A IV top? The data in panel B are certainly more in line with prior art, albeit that there is considerable heterogeneity in the labelling and of the FP for example. Again, I cannot really see this as evidence for continuity. There are gaps.... Albeit I accept that labelling of such structures is unlikely to ever be homogenous.

We agree that the dSTORM data represents the least robust aspect of the findings we have presented, and we concur with relocating it to the supplementary material.

F3 - Rather apparent, and specifically for Rab7, that there is differential representation - for example, Cell 4 presents a single Rab7 structure while the remaining examples demonstrate more extensive labelling. Again, I am content that these are highly dynamic strictures but this needs to be addressed at some level and commented upon. If the claim is for continuity, the dynamics observed here suggest the usual; some level of obvious overlap of organellar markers, but the representation in F3 is clever but not sure what I am looking at. Moreover, the title of the figure is nothing new. What is also a bit odd is that the extent of the Rab7 signal, and to some extent the other two Rabs used, is rather variable, which makes this unclear to me as to what is being detected. Given that the Rab proteins may be defining microdomains or regions, I would also expect a region of unique straining as well as the common areas. This needs to at least be discussed.

The differences in the representation result from the dynamics of the labelled structures. Therefore, we have selected different cells to provide examples of what the labelling can look like. We now mention this in the results section.

The overlap of the different Rab signals was perhaps to be expected, but we now have demonstrated it experimentally. Importantly, we performed a rigorous quantification by calculating the volume overlaps and the Pearson correlation coefficients.

In previous studies the data were presented as maximal intensity projections, which inherently lack the complete 3D information.

We found that Rab proteins define microdomains and that there are regions of unique staining as well as common areas, as shown in Figure 3. The volumes do not completely overlap. This is now more clearly stated in lines 315 – 319:

“These objects showed areas of unique staining as well as partially overlapping regions. The pairwise colocalization of different endosomal markers is shown in Figure 3 A, XI - XIII and 3 B. The different cells in Figure 3 B were selected to represent the dynamic nature of the labelled structures. Consequently, the selected cells provide a variety of examples of how the labelling can appear.”

This had already been stated in lines 331 – 336:

“In summary, the quantitative colocalization analyses revealed that on the one hand, the endosomal system features a high degree of connectivity, with considerable overlap of endosomal marker regions, and on the other hand, TbRab5A, TbRab7, and TbRab11 also demarcate separated regions in that system. These results can be interpreted as evidence of a continuous endosomal membrane system harbouring functional subdomains, with a limited amount of potentially separated early, late or recycling endosomes.”

F4-6 - Fabulous images. But a couple of issues here; first, as the authors point out, there is distance between the gold and the antigen. So, this of course also works in the z-plane as well as the x/y-planes and some of the gold may well be associated with membraneous figures that are out of the plane, which would indicate an absence of colinearity on one specific membrane. Secondly, in several instances, we have Rab7 essentially mixed with Rab11 or Rab5 positive membrane. While data are data and should be accepted, this is difficult to reconcile when, at least to some level, Rab7 is a marker for a late-endosomal structure and where the presence of degradative activity could reside. As division of function is, I assume, the major reason for intracellular compartmentalisation, such a level of admixture is hard to rationalise. A continuum is one thing but the data here seem to be suggesting something else, i.e. almost complete admixture.

We are grateful for the positive feedback regarding the image quality. It is true that the "linkage error," representing the distance between the gold and the antigen, also functions to some extent in the z-axis. However, it's important to note that the zdimension of the section in these Figures is 55 nm. Nevertheless, it's interesting to observe that membranes, which may not be visible within the section itself but likely the corresponding Rab antigen, is discernible in Figure 4C (indicated by arrows).

We have clarified this in lines 397 – 400:

“Consequently, gold particles located further away may represent cytoplasmic TbRab proteins or, as the “linkage error” can also occur in the z-plane, correspond to membranes that are not visible within the 55 nm thickness of the cryosection (Figure 4, panel C, arrows). “

The coexistence of different Rabs is most likely concentrated in regions where transitions between different functions are likely. Our focus was primarily on imaging membranes labelled with two markers. We wanted to show that the prevailing model of separate compartments in the trypanosome literature is not correct.

F7 - Not sure what this adds beyond what was published by Grunfelder.

First, this figure is an important control that links our results to published work (Grünfelder et al. (2003)). Second, we include double staining of cargo with Rab5, Rab7, and Rab11, whereas Grünfelder focused only on Rab11. Therefore, our data is original and of such high quality that it warrants a main figure.

F8 - and l583. This is odd as the claim is 'proof' which in science is a hard thing to claim (and this is definitely not at a six sigma level of certainty, as used by the physics community). However, I am seeing structures in the tomograms which are not contiguous - there are gaps here between the individual features (Green in the figure).

We have replaced the term "proof". It is important to note that the structures in individual tomograms cannot all be completely continuous because the sections are limited to a thickness of 250 nm. Therefore, it is likely that they have more connectivity above and below the imaged section. Nevertheless, we believe that the quality of the tomograms is satisfactory, considering that 3D Tokuyasu is a very demanding technique and the production of serial Tokuyasu tomograms is not feasible in practice.

Discussion - Too long and the self-citing of four papers from the corresponding author to the exclusion of much prior work is again noted, with concerns about this as described above. Moreover, at least four additional Rab proteins are known associated with the trypanosome endosomal system, 4, 5B, 21 and 28. These have been completely ignored.

We have outlined our position on referencing in original articles above. We also explained why we focused on the key marker proteins associated with early (Rab5), late (Rab7) and recycling endosomes (Rab11). We did not ignore the other Rabs, we just did not include them in the present study.

Overall this is disappointing. I had expected a more robust analysis, with a clearer discussion and placement in context. I am not fully convinced that what we have here is as extreme as claimed, or that we have a substantial advance. There is nothing here that is mechanistic or the identification of a new set of gene products, process or function.

We do not think that this is constructive feedback.

This MS suggests that the endosomal system of African trypanosomes is a continuum of membrane structures rather than representing a set of distinct compartments. A combination of light and electron microscopy methods are used in support. The basic contention is very challenging to prove, and I'm not convinced that this has been. Furthermore, I am also unclear as to the significance of such an organisation; this seems not really addressed.

We acknowledge and respect varying viewpoints, but we hold a differing perspective in this matter. We are convinced that the data decisively supports our interpretation. May future work support or refute our hypothesis.

Reviewer #3 (Recommendations For The Authors):

Line 81 - delete 's

Done.

Generally, the introduction was very well written and clearly summarised our current understanding but the paragraph beginning line 134 felt out of place and repeated some of the work mentioned earlier.

We have removed this paragraph.

For the EM analysis throughout quantification would be useful as highlighted in the public review. How many tomograms were examined, and how often were types of structures seen? I understand the sample size is often small but this would help the reader appreciate the diversity of structures seen.

We have included the numbers.

Following on from this how were the cells chosen for tomogram analysis? For example, the dividing cell in 1D has palisades associating with the new pocket - is this commonly seen? Does this reflect something happening in dividing cells. This point about endosomal division was picked up in the discussion but there was little about in the main results.

This issue is undoubtedly inherent to the method itself, and we have made efforts to mitigate it by generating a series of tomograms recorded randomly. We have refrained from delving deeper into the intricacies of the cell cycle in this manuscript, as we believe that it warrants a separate paper.

As the authors prosecute, the co-localisation analysis highlights the variable nature of the endosome and the overlap of different markers. When looking at the LM analysis, I was struck by the variability in the size and number of labelled structures in the different cells. For example, in 3A Rab7 is 2 blobs but in 3B Cell 1 it is 4/5 blobs. Is this just a reflection of the increase in the endosome during the cell cycle?

The variability in representation is a direct consequence of the dynamic nature of the labelled structures. For this reason, we deliberately selected different cells to represent examples of how the labelling can look like. We have decided not to mention the dynamics of the endosome during the cell cycle. This will be the subject of a further report.

Moreover, Rab 11 looks to be the marker covering the greatest volume of the endosomal system - is this true? I think there's more analysis of this data that could be done to try and get more information about the relative volumes etc of the different markers that haven't been drawn out. The focus here is on the co-localisation.

Precisely because we recognize the importance of this point, we intend to turn our attention to the cell cycle in a separate publication.

I appreciate that it is an awful lot of work to perform the immuno-EM and the data is of good quality but in the text, there could be a greater effort to tie this to the LM data. For example, from the Rab11 staining in LM you would expect this marker to be the most extensive across the networks - is this reflected in the EM?

For the immuno-EM there were no numbers, the authors had measured the position of the gold but what was the proportion of gold that was in/near membranes for each marker? This would help the reader understand both the number of particles seen and the enrichment of the different regions.

Our original intent was to perform a thorough quantification (using stereology) of the immuno-EM data. However, we later realized that the necessary random imaging approach is not suitable for Tokuyasu sections of trypanosomes. In short, the cells are too far apart, and the cell sections are only occasionally cut so that the endosomal membranes are sufficiently visible. Nevertheless, we continue to strive to generate more quantitative data using conventional immuno-EM.

The innovative combination of Tokuyasu tomograms with immuno-EM was great. I noted though that there was a lack of fenestration in these models. Does this reflect the angle of the model or the processing of these samples?

We are grateful to the referee, as we have asked ourselves the same question. However, we do not attribute the apparent lack of fenestration to the viewing angle, since we did not find fenestration in any of the Tokuyasu tomograms. Our suspicion is more directed towards a methodological problem. In the Tokuyasu workflow, all structures are mainly fixed with aldehydes. As a result, lipids are only effectively fixed through their association with membrane proteins. We suggest that the fenestration may not be visible because the corresponding lipids may have been lost due to incomplete fixation.

We now clearly state this in the lines 563 – 568.

“Interestingly, these tomograms did not exhibit the fenestration pattern identified in conventional electron tomography. We suspect that this is due to methodological reasons. The Tokuyasu procedure uses only aldehydes to fix all structures. Consequently, effective fixation of lipids occurs only through their association with membrane proteins. Thus, the lack of visible fenestration is likely due to possible loss of lipids during incomplete fixation.”

The discussion needs to be reworked. Throughout it contains references to results not in the main results section such as supplementary movie 2 (line 735). The explicit references to the data and figures felt odd and more suited to the results rather than the discussion. Currently, each result is discussed individually in turn and more effort needs to be made to integrate the results from this analysis here but also with previous work and the data from other organisms, which at the moment sits in a standalone section at the end of the discussion.

We have improved the discussion and removed the previous supplementary movies 2 and 3. Supplementary movie 1 is now mentioned in the results section.

Line 693 - There was an interesting point about dividing cells describing the maintenance of endosomes next to the old pocket. Does that mean there was no endosome by the new pocket and if so where is this data in the manuscript? This point relates back to my question about how cells were chosen for analysis - how many dividing cells were examined by tomography?

The fate of endosomes during the cell cycle is not the subject of this paper. In this manuscript we only show only one dividing cell using tomography. An in-depth analysis focusing on what happens during the cell cycle will be published separately.

Line 729 - I'm unclear how this represents a polarization of function in the flagellar pocket. The pocket I presume is included within the endosomal system for this analysis but there was no specific mention of it in the results and no marker of each position to help define any specialisation. From the results, I thought the focus was on endosomal co-localisation of the different markers. If the authors are thinking about specialisation of the pocket this paper from Mark Field shows there is evidence for the exocyst to be distributed over the entire surface of the pocket, which is relevant to the discussion here. Boehm, C.M. et al. (2017) The trypanosome exocyst: a conserved structure revealing a new role in endocytosis. PLoS Pathog. 13, e1006063

We have formulated our statement more cautiously. However, we are convinced that membrane exchange cannot physically work without functional polarization of the pocket. We know that Rab11, for example, is not evenly distributed on the pocket. By the way, in Boehm et al. (2017) the exocyst is not shown to cover the entire pocket (as shown in Supplementary Video 1).

We now refer to Boehm et al. (Lines 700 – 703):

“Boehm et al (2017) report that in the flagellar pocket endocytic and exocytic sites are in close proximity but do not overlap. We further suggest that the fusion of EXCs with the flagellar pocket membrane and clathrin-mediated endocytosis take place on different sites of the pocket. This disparity explains the lower colocalization between TbRab11 and TbRab5A.”

Line 735 - link to data not previously mentioned I think. When I looked at this data I couldn't find a key to explain what all the different colours related to.

We have removed the previous supplementary movies 2 and 3. We now reference supplementary movie 1 in the results section.

Put the description of the example BEFORE the example.

In general: Let's introduce the example before the actual example.

Then, any special observations come after the example.

See, e.g., the rust book that follows this style: https://doc.rust-lang.org/book/ch04-02-references-and-borrowing.html

Here is how you would define and use a calculate_length function that has a reference to an object as a parameter instead of taking ownership of the value:

EXAMPLE

First, notice that ...

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

Learn more at Review Commons

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Reply to the reviewers

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

Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, γ1. In complex with γ1, Slo1 adopts an open state that closely resembles previous open state structures. Of γ1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how γ1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses.

While this report provides a first glimpse of how γ1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how γ1 can regulate Slo1 channels.

We thank the reviewer for their honest judgment. We agree that validating the structure by biochemical and/or functional data would have significantly strengthened the manuscript. However, we are convinced that our structural data alone already provides significant novel understanding of the assembly of the Slo1-γ1 complex and regulation of Slo1 by γ1. Thus, we feel that publication of this manuscript is justified by the high importance of Slo channels and our data will have an impact in the field.

__Major comments: __ 1. The authors propose several models for how γ1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by γ1.

We agree with the reviewer that experimental validation of this hypothesis would have been an asset. Nevertheless, we think that our structural data in context of previous functional data e.g. from Li et al. 2015,2016) and also in comparison with the other two manuscripts on the same topic which have been published while this manuscript was under review, allows us to draw conclusions about the mechanism of γ1-mediated activation of Slo1. We have now, however, toned down some of the earlier statements and changed parts of our interpretations in light of the novel findings by Yamanouchi et al. and Kallure et al.

The authors analysis of the extracellular domain of γ1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both γ and b subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.

We completely agree with the reviewer that a thorough analysis of the extracellular domain is important and thank the reviewer for their valuable suggestions. We had attempted such analysis already from the beginning, but were not successful. More specifically, we have attempted reconstructions with lower symmetry (C2 and C1) from the beginning or by symmetry relaxation after initial C4 reconstruction. Also, we tested different masking and signal subtraction strategies in combination with different global and local refinements, as well as symmetry expansion and 3D classification. Unfortunately, none of these strategies led to a better resolved LRR module.

We now think that in comparison with Kallure et al. and Yamanouchi et al., the ice in our sample was thinner, which allowed us to reach higher resolution in the core particle (Slo1 and γ1 TM helix), but at the cost of the γ1 LRRs being denatured or at least distorted by the air-water interface.

The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different γ1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.

We thank the reviewer for pointing this out, and while the values for clashscores and rotamers were not outside the range of values typically found in many other cryo-EM structures, we agree that there was still some room for improvement. We have worked on this and could lower the values to a clashscore of 7.0 and 1.8 % rotamer outliers.

The difference in Q-score is also something not too uncommon since, while the map is indeed C4-symmetric, during model refinement the NCS restraints are not completely preventing small deviations between the protomers. We have now also successfully attempted to minimize these differences further.

Reviewer #1 (Significance (Required)):

The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.

We thank the reviewer for this honest statement, but respectfully disagree. While additional functional analyses would have certainly boosted the impact, we are certain that our structural data and their interpretation will be very valuable for the field, because they provide (as stated by Reviewer 3) new insights into the regulation of Slo channel activity by the γ subunits and suggest (as stated by reviewer 2) a novel mechanism of activation of voltage-gated ion channels..

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

Summary This study presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit. Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.

__Major comments __ The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like

"a possible mechanism... might be... which would make... more likely".

"... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..."

"... might play an important role... does not allow a certain conclusion..."

We completely agree with the reviewer that the paper would have been much stronger if we would have been able to perform biochemical or functional assays testing mutations in the binding interface. However, this would have unfortunately been beyond the scope of the project. We are nevertheless confident that our structural data will be of value for the field, also in context of the two structure-function papers that have been published since which confirm and validate our data and provide the link to function.

__Minor comments which could be confidently addressed __ The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty. is incremental or significant.

We have adjusted the introduction to explicitly mention previously published structural data on the Slo channels.

References 10 and 42 (eLife) lacj some details.

We have adjusted said references accordingly.

__Reviewer #2 (Significance (Required)): ______

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Significance general assessment As it turns out, at least two papers in exactly the same field just appeared: -one in Molecular Cell by a Japanese group, which is much more developed and contains functional tests and structure-function relationships, in addition to beautiful structures (available on-line early December) https://www.sciencedirect.com/science/article/pii/S1097276523009218

-one in biorxiv, deposited yesterday https://www.biorxiv.org/content/biorxiv/early/2023/12/20/2023.12.20.572542.full.pdf

Advances wrt known results See above. As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.

We agree with the reviewer that in light of the other two publications which both were published a while after we deposited our preprint on biorxiv and while the manuscript was under review, the uniqueness of our data is somewhat lowered. However, since our data is overall in large agreement with these two other publications, but we report a structure at significantly higher resolution and from a different species (indeed the first Slo1 structure from rabbit, a model organism of BK channel characterization in the last decades), we are confident that our data are still very valuable for the field and qualify for publication in one of the affiliate journals of Review Commons. After all, the fact that three papers reporting very similar data were published within a few weeks (plus another preprint reporting structures of a Slo channel, but unrelated to γ subunits) illustrates the importance for understanding the regulation of this essential ion channel and the impact of all structural data enhancing this understanding, and independent confirmation by three different labs is something very valuable to the community.

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

"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."

1. In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.

We have adjusted the coloring of calcium ions Fig. 1D to increase their visibility.

It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.

We have arrived at these concentrations of the respective viruses by empirically testing ranges between 3 % and 15 %. We have now added a sentence to the manuscript to explain this.

Is there any rationale behind initially purifying using strep affinity followed by His affinity?

The idea behind using a dual-affinity protocol is to ensure that all purified complexes contain at least one copy of Slo1 and one copy of γ1. Using the Strep tag first allows to remove most contaminants already in the first step, due to its higher specificity compared to the His tag. We have added a sentence to the methods section to explain this.

Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"

We exclusively observe complexes with four γ1 subunits. This is also in agreement with the other two recent publications reporting Slo1-γ1 complex structures, but could in principle be an artifact of artificial overexpression. Also when we refine the particles in C1, we retain C4 symmetry and do not observe any classes with C2 or C1 symmetry.

The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?

The large number of particles is not strictly necessary, i.e. we could obtain similar quality by using fewer particles. In the end, we have now further classified down to ~827k particles, which very slightly improved the resolution and quality of the map.

Authros mentioned that F273 of γ1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.

F273 forms (slightly distorted) T stacking interactions with F164 in S2 and F187 in S3. We now changed the sentence in the manuscript to mention the residues that line the hydrophobic pocket to make it more clear which elements contribute to the interaction with F273.

The authors propose that the disulfide bond between the γ subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"

We have run all our SDS-PAGE experiments under reducing conditions, thus destroying any disulfide bridges that might have been present in the complex. We have now, however obtained a slightly better defined reconstruction (as pointed out in our answer to point 5 raised by this reviewer) where we do not see as clear continuous density anymore between the two cysteine side chains. Thus, we have removed the cystine bond from the final model and have adjusted text and figures accordingly. We still think that it might be more than coincidence that those two side chains come into such close proximity, though, and still discuss the possibility of a cystine bridge in the manuscript.

Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.

We have expanded our description of the proposed repulsive effect of the positive charges in the manuscript and in addition also discuss the additional role of the charges in stabilizing the Ca2+-bound conformation of the gating ring as proposed by Yamanouchi et al.

Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.

We agree with the reviewer that this is an interesting question which we have also thought about and one which should be tested, but as the reviewer already mentioned, this would go beyond the present study and should be subject to an independent follow-up investigation.

Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"

Given the high resolution of our structure, we observe a number of ordered lipid and detergent molecules, most of which were located at similar positions as in previous structures of Slo channels. Besides those molecules clustering in the deep cleft between neighboring voltage-sensor domains, we also observe lipid densities close to the binding site of γ1 on the distal side of the VSD. However, as their relevance for γ1 binding is unclear, we don’t discuss them in the manuscript. In general, of course, we agree with the reviewer that lipids can have a large impact on the function of membrane proteins.

It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.

As shown by Kallure et al., substituting P270 in the kink by serine (the native residue at this position in γ3) strongly diminished the ability of γ1 to associate with Slo1 in vitro, demonstrating the importance of the kink and providing a rationale for the observed differences in the potency of the TM helices of γ1 and γ3 in Slo1 activation.

It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.

We absolutely agree with the reviewer that functional insights on the relevance of the kink would be very valuable, but we think that the available experimental data together with the natural sequence differences in γ1-γ4 and the correlation with their physiological activity are very clear indications that the kink is relevant. However, future follow-up studies that prove this beyond any doubt would be valuable.

Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.

This is, to the best of our knowledge, not known. The only existing data that suggests co-presence of beta and gamma subunits on Slo1, reported in Gonzalez-Perez et al., 2015, stems from electrophysiological experiments and does not reveal anything about hierarchy and temporal order of binding events.

Reviewer #3 (Significance (Required)):

The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.

We thank the reviewer for this positive assessment of the data and agree that our structural data, also when regarded together with the complementary manuscripts by Kallure et al. and Yamanouchi et al., provides significant new insight into the assembly and activity of γ subunits.

You need role when there is not a built in tag for the behaviour you would like to have

That's easily done.

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Author Response

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

Public Reviews:

Reviewer #1 (Public Review):

The authors of this study seek to visualize NS1 purified from dengue virus infected cells. They infect vero cells with DV2-WT and DV2 NS1-T164S (a mutant virus previously characterized by the authors). The authors utilize an anti-NS1 antibody to immunoprecipitate NS1 from cell supernatants and then elute the antibody/NS1 complex with acid. The authors evaluate the eluted NS1 by SDS-PAGE, Native Page, mass spec, negative-stain EM, and eventually Cryo-EM. SDS-PAGE, mas spec, and native page reveal a >250 Kd species containing both NS1 and the proteinaceous component of HDL (ApoA1). The authors produce evidence to suggest that this population is predominantly NS1 in complex with ApoA1. This contrasts with recombinantly produced NS1 (obtained from a collaborator) which did not appear to be in complex with or contain ApoA1 (Figure 1C). The authors then visualize their NS1 stock in complex with their monoclonal antibody by CryoEM. For NS1-WT, the major species visualized by the authors was a ternary complex of an HDL particle in complex with an NS1 dimer bound to their mAB. For their mutant NS1-T164S, they find similar structures, but in contrast to NS1-WT, they visualize free NS1 dimers in complex with 2 Fabs (similar to what's been reported previously) as one of the major species. This highlights that different NS1 species have markedly divergent structural dynamics. It's important to note that the electron density maps for their structures do appear to be a bit overfitted since there are many regions with electron density that do not have a predicted fit and their HDL structure does not appear to have any predicted secondary structure for ApoA1. The authors then map the interaction between NS1 and ApoA1 using cross-linking mass spectrometry revealing numerous NS1-ApoA1 contact sites in the beta-roll and wing domain. The authors find that NS1 isolated from DENV infected mice is also present as a >250 kD species containing ApoA1. They further determine that immunoprecipitation of ApoA1 out of the sera from a single dengue patient correlates with levels of NS1 (presumably COIPed by ApoA1) in a dose-dependent manner.

In the end, the authors make some useful observations for the NS1 field (mostly confirmatory) providing additional insight into the propensity of NS1 to interact with HDL and ApoA1. The study does not provide any functional assays to demonstrate activity of their proteins or conduct mutagenesis (or any other assays) to support their interaction predications. The authors assertion that higher-order NS1 exists primarily as a NS1 dimer in complex with HDL is not well supported as their purification methodology of NS1 likely introduces bias as to what NS1 complexes are isolated. While their results clearly reveal NS1 in complex with ApoA1, the lack of other NS1 homo-oligomers may be explained by how they purify NS1 from virally infected supernatant. Because NS1 produced during viral infection is not tagged, the authors use an anti-NS1 monoclonal antibody to purify NS1. This introduces a source of bias since only NS1 oligomers with their mAb epitope exposed will be purified. Further, the use of acid to elute NS1 may denature or alter NS1 structure and the authors do not include controls to test functionality of their NS1 stocks (capacity to trigger endothelial dysfunction or immune cell activation). The acid elution may force NS1 homo-oligomers into dimers which then reassociate with ApoA1 in a manner that is not reflective of native conditions. Conducting CryoEM of NS1 stocks only in the presence of full-length mAbs or Fabs also severely biases what species of NS1 is visualized since any NS1 oligomers without the B-ladder domain exposed will not be visualized. If the residues obscured by their mAb are involved in formation of higher-order oligomers then this antibody would functionally inhibit these species from forming. The absence of critical controls, use of one mAb, and acid elution for protein purification severely limits the interpretation of these data and do not paint a clear picture of if NS1 produced during infection is structurally distinct from recombinant NS1. Certainly there is novelty in purifying NS1 from virally infected cells, but without using a few different NS1 antibodies to purify NS1 stocks (or better yet a polyclonal population of antibodies) it's unclear if the results of the authors are simply a consequence of the mAb they selected.

Data produced from numerous labs studying structure and function of flavivirus NS1 proteins provide diverse lines of evidence that the oligomeric state of NS1 is dynamic and can shift depending on context and environment. This means that the methodology used for NS1 production and purification will strongly impact the results of a study. The data in this manuscript certainly capture one of these dynamic states and overall support the general model of a dynamic NS1 oligomer that can associate with both host proteins as well as itself but the assertions of this manuscript are overall too strong given their data, as there is little evidence in this manuscript, and none available in the large body of existing literature, to support that NS1 exists only as a dimer associated with ApoA1. More likely the results of this paper are a result of their NS1 purification methodology.

Suggestions for the Authors:

Major:

(1) Because of the methodology used for NS1 purification, it is not clear from the data provided if NS1 from viral infection differs from recombinant NS1. Isolating NS1 from viral infection using a polyclonal antibody population would be better to answer their questions. On this point, Vero cells are also not the best candidate for their NS1 production given these cells do not come from a human. A more relevant cell line like U937-DC-SIGN would be preferable.

We performed an optimization of sNS1 secretion from DENV infection in different cell lines (Author response image 1 below) to identify the best cell line candidate to obtain relatively high yield of sNS1 for the study. As shown in Author response image 1, the levels of sNS1 in the tested human cell lines Huh7 and HEK 293T were at least 3-5 fold lower than in Vero cells. Although using a monocytic cell line expressing DC-SIGN as suggested by the reviewer would be ideal, in our experience the low infectivity of DENV in monocytic cell lines will not yield sufficient amount of sNS1 needed for structural analysis. For these practical reasons we decided to use the closely related non-human primate cell line Vero for sNS1 production supported by our optimization data.

Author response image 1.

sNS1 secretion in different mammalian and mosquito cell lines after DENV2 infection. The NS1 secretion level is measured using PlateliaTM Dengue NS1 Ag ELISA kit (Bio-Rad) on day 3 (left) and day 5 (right) post infection respectively.

(2) The authors need to support their interaction predictions and models via orthogonal assays like mutagenesis followed by HDL/ApoA1 complexing and even NS1 functional assays. The authors should be able to mutate NS1 at regions predicted to be critical for ApoA1/HDL interaction. This is critical to support the central conclusions of this manuscript.

In our previous publication (Chan et al., 2019 Sci Transl Med), we used similarly purified sNS1 (immunoaffinity purification followed by acid elution) from infected culture supernatants from both DENV2 wild-type and T164S mutant (both also studied in the present work) to carry out stimulation assay on human PBMCs as described by other leading laboratories investigating NS1 (Modhiran et al., 2015 Sci Transl Med). For reader convenience we have extracted the data from our published paper and present it as Author response image 2 below.

Author response image 2.

(A) IL6 and (B) TNFa concentrations measured in the supernatants of human PBMCs incubated with either 1µg/ml or 10µg/ml of the BHK-21 immunoaffinity-purified WT and TS mutant sNS1 for 24 hours. Data is adapted from Chan et al., 2019.

Incubation of immunoaffinity-purified sNS1 (WT and TS) with human PBMCs from 3 independent human donors triggered the production of proinflammatory cytokines IL6 and TNF in a concentration dependent manner (Author response image 2), consistent with the published data by Modhiran et al., 2015 Sci Transl Med. Interestingly the TS mutant derived sNS1 induced a higher proinflammatory cytokines production than WT virus derived sNS1 that appears to correlate with the more lethal and severe disease phenotype in mice as also reported in our previous work (Chan et al., 2019). Additionally, the functionality of our immune-affinity purified infection derived sNS1 (isNA1) is now further supported by our preliminary results on the NS1 induced endothelial cell permeability assay using the purified WT and mutant isNS1 (Author response image 3). As shown in Author response image 3, both the isNS1wt and isNS1ts mutant reduced the relative transendothelial resistance from 0 to 9 h post-treatment, with the peak resistance reduction observed at 6 h post-treatment, suggesting that the purified isNS1 induced endothelial dysfunction as reported in Puerta-Guardo et al., 2019, Cell Rep.) It is noteworthy that the isNS1 in our study behaves similarly as the commercial recombinant sNS1 (rsNS1 purchased from the same source used in study by Puerta-Guardo et al., 2019) in inducing endothelial hyperpermeability. Collectively our previous published and current data suggest that the purified isNS1 (as a complex with ApoA1) has a pathogenic role in disease pathogenesis that is also supported in a recent publication by Benfrid et al., EMBO 2022). The acid elution has not affected the functionality of NS1.

Author response image 3.

Functional assessment of isNS1wt and isNS1ts on vascular permeability in vitro. A trans-endothelial permeabilty assay via measurement of the transendothelial electrical resistance (TEER) on human umbilical vascular endothelial cells (hUVEC) was performed, as described previously (Puerta-Guardo et al., 2019, Cell Rep). Ovalbumin serves as the negative control, while TNF-α and rsNS1 serves as the positive controls.

We agree with reviewer about the suggested mutagnesis study. We will perform site-directed mutagenesis at selected residues and further structural and functional analyses and report the results in a follow-up study.

(3) The authors need to show that the NS1 stocks produced using acid elution are functional compared to standard recombinantly produced NS1. Do acidic conditions impact structure/function of NS1?

We are providing the same response to comments 1 & 2 above. We would like to reiterate that we have previously used sNS1 from immunoaffinity purification followed by acid elution to test its function in stimulating PBMCs to produce pro-inflammatory cytokines (Chan et al., 2019; Author response image 2). Similar to Modhiran et al. (2015) and Benfrid et al. (2022), the sNS1 that we extracted using acid elution are capable of activating PBMCs to produce pro-inflammatory cytokines. We have now further demonstrated the ability of both WT and TS isNS1 in inducing endothelial permeability in vitro in hUVECs, using the TEER assay (Author response image 3). Based on the data presented in the rebuttal figures as well as our previous publication we do not think that the acid elution has a significant impact on function of isNS1.

We performed affinity purification to enrich the complex for better imaging and analysis (Supp Fig. 1b) since the crude supernatant contains serum proteins and serum-free infections also do not provide sufficient isNS1. The major complex observed in negative stain is 1:1 (also under acidic conditions which implies that the complex are stable and intact). We agree that it is possible that other oligomers can form but we have observed only a small population (74 out of 3433 particles, 2.15%; 24 micrographs) of HDL:sNS1 complex at 1:2 ratio as shown in the Author response image 4 below and in the manuscript (p. 4 lines 114-117, Supp Fig. 1c). Other NS1 dimer:HDL ratios including 2:1 and 3:1 have been reported by Benfrid et al., 2022 by spiking healthy sera with recombinant sNS1 and subsequent re-affinity purification. However, this method used an approximately 8-fold higher sNS1 concentration (400 ug/mL) than the maximum clinically reported concentration (50 ug/mL) (Young et al., 2000; Alcon et al., 2002; Libraty et al., 2002). In our hands, the sNS1 concentration in the concentrated media from in vitro infection was quantified as 30 ug/mL which is more physiologically relevant.

We conclude that the integrity of the HDL of the complex is not lost during sample preparation, as we are able to observe the complex under the negative staining EM as well as infer from XL-MS. Our rebuttal data and our previous studies with our acid-eluted isNS1 from immunoaffinity purification clearly show that our protein is functional and biologically relevant.

Author response image 4.

(A) Representative negative stain micrograph of sNS1wt (B) Representative 2D averages of negative stained isNS1wt. Red arrows indicating the characteristic wing-like protrusions of NS1 inserted in HDL. (C) Data adapted from Figure 2 in Benfrid et al. (2022).

(4) Overall, the data obtained from the mutant NS1 (contrasted to WT NS1) reveals how dynamic the oligomeric state of NS1 proteins are but the authors do not provide any insight into how/why this is, some additional lines of evidence using either structural studies or mutagenesis to compare WT and their mutant and even NS1 from a different serotype of DENV would help the field to understand the dynamic nature of NS1.

The T164S mutation in DENV2 NS1 was proposed as the residue associated with disease severity in 1997 Cuban dengue epidemic (Halsted SB. “Intraepidemic increases in dengue disease severity: applying lessons on surveillance and transmission”. Whitehorn, J., Farrar. J., Eds., Clinical Insights in Dengue: Transmission, Diagnosis & Surveillance. The Future Medicine (2014), pp. 83-101). Our previous manuscript examined this mutation by engineering it into a less virulent clade 2 DENV isolated in Singapore and showed that sNS1 production was higher without any change in viral RNA replication. Transcript profiling of mutant compared to WT virus showed that genes that are usually induced during vascular leakage were upregulated for the mutant. We also showed that infection of interferon deficient AG129 mice with the mutant virus resulted in disease severity, increased complement protein expression in the liver, tissue inflammation and greater mortality compared to WT virus infected mice. The lipid profiling in our study (Chan et al., 2019) suggested small differences with WT but was overall similar to HDL as described by Gutsche et al. (2011). We were intrigued by our functional results and wanted to explore more deeply the impact of the mutation on sNS1 structure which at that stage was widely believed to be a trimer of NS1 dimers with a central channel (~ X Å) stuffed with lipid as established in several seminal publications (Flamand et al., 1999; Gutsche et al., 2011; Muller et al., 2012). In fact “This Week in Virology” netcast (https://www.microbe.tv/twiv/twiv-725/) discussed two back-to-back publications in Science (Modhiran et al., 371(6625)190-194; Biering et al., Science 371(6625):194-200)) which showed that therapeutic antibodies can ameliorate the NS1 induced pathogenesis and expert discussants posed questions that also pointed to the need for more accurate definition of the molecular composition and architecture of the circulating NS1 complex during virus infection to get a clearer handle on its pathogenic mechanism. Our current studies and also the recent high resolution cryoEM structures (Shu et al., 2022) do not support the notion of a central channel “stuffed with lipid”. Even in the rare instances where trimer of dimers are shown, the narrow channel in the center could only accommodate one molecule of lipoid molecule no bigger than a typical triglyceride molecule. This hexamer model cannot explain the lipid proeotmics data in the literature.

In our study we observed predominantly 1:1 NS1 dimer to HDL (~30 μg/mL) mirroring maximum clinically reported concentration of sNS1 in the sera of DENV patients (40-50 μg/mL) as we highlighted in our main text (P. 18, lines 461-471). What is often quoted (also see later) is the recent study of Flamand & co-workers which show 1-3 NS1 dimers per HDL (Benfrid et al, 2022) by spiking rsNS1 (400 μg/mL) with HDL. This should not be confused with the previous models which suggested a lipid filled central channel holding together the hexamer. The use of physiologically relevant concentrations is important for these studies as we have highlighted in our main text (P. 18, lines 461-471).

Our interpretation for the mutant (isNS1ts) is that it is possible that the hydrophilic serine at residue 164 located in the greasy finger loop may weaken the isNS1ts binding to HDL hence the observation of free sNS1 dimers in our immunoaffinity purified (acid eluted sample). The disease severity and increased complement protein expression in AG129 mice liver can be ascribed to weakly bound mutant NS1 with fast on/off rate with HDL being transported to the liver where specific receptors bind to free sNS1 and interact with effector proteins such as complement to drive inflammation and associated pathology. Our indirect support for this is that the XL-MS analysis of purified isNS1ts identified only 7 isNS1ts:ApoA1 crosslinks while 25 isNS1wt:ApoA1 crosslinks were identified from purified isNS1wt (refer to Fig. 4 and Supp. Fig. 8).

Taken together, the cryoEM and XL-MS analysis of purified isNS1ts suggest that isNS1ts has weaker affinity for HDL compared to isNS1wt. We welcome constructive discussion on our interpretation that we and others will hopefully obtain more data to support or deny our proposed explanation. Our focus has been to compare WT with mutant sNS1 from DENV2 and we agree that it will be useful to study other serotypes.

Reviewer #2:

CryoEM:

Some of the neg-stain 2D class averages for sNS1 in Fig S1 clearly show 1 or 2 NS1 dimers on the surface of a spherical object, presumably HDL, and indicate the possibility of high-quality cryoEM results. However, the cryoEM results are disappointing. The cryo 2D class averages and refined EM map in Fig S4 are of poor quality, indicating sub-optimal grid preparation or some other sample problem. Some of the FSC curves (2 in Fig S7 and 1 in Fig S6) have extremely peculiar shapes, suggesting something amiss in the map refinement. The sharp drop in the "corrected" FSC curves in Figs S5c and S6c (upper) indicate severe problems. The stated resolutions (3.42 & 3.82 Å) for the sNS1ts-Fab56.2 are wildly incompatible with the images of the refined maps in Figs 3 & S7. At those resolutions, clear secondary structural elements should be visible throughout the map. From the 2D averages and 3D maps shown in the figures this does not seem to be the case. Local resolution maps should be shown for each structure.

The same sample is used for negative staining and the cryoEM results presented. The cryoEM 2D class averages are similar to the negative stain ones, with many spherical-like densities with no discernible features, presumably HDL only or the NS1 features are averaged out. The key difference lies in the 2D class averages where the NS1 could be seen. The side views of NS1 (wing-like protrusion) are more obvious in the negative stain while the top views of NS1 (cross shaped-like protrusion) are more obvious under cryoEM. HDL particles are inherently heterogeneous and known to range from 70-120 Å, this has been highlighted in the main text (p. 8, lines 203 and 228). This helps to explain why the reviewer may find the cryoEM result disappointing. The sample is inherently challenging to resolve structurally as it is (not that the sample is of poor quality). In terms of grid preparation, Supp Fig 4b shows a representative motion-corrected micrograph of the isNS1ts sample whereby individual particles can be discerned and evenly distributed across the grid at high density.

We acknowledge that most of the dips in the FSC curves (Fig S5-7) are irregular and affect the accuracy of the stated resolutions, particularly for the HDL-isNS1ts-Fab56.2 and isNS1ts-Fab56.2 maps for which the local resolution maps are shown (Fig S7d-e). Probable reasons affecting the FSC curves include (1) the heterogeneous nature of HDL, (2) preferred orientation issue (p 7, lines 198 -200), and (3) the data quality is intrinsically less ideal for high resolution single particle analysis. Optimizing of the dynamic masking such that the mask is not sharper than the resolution of the map for the near (default = 3 angstroms) and far (12 angstroms) parameters during data processing, ranging from 6 - 12 and 14 - 20 respectively, did not help to improve the FSC curves. To report a more accurate global resolution, we have revised the figures S5-7 with new FSC curve plots generated using the remote 3DFSC processing server.

Regardless, the overall architecture and the relative arrangement of NS1 dimer, Fab, and HDL are clearly visible and identifiable in the map. These results agree well with our biochemical data and mass-spec data.

The samples were clearly challenging for cryoEM, leading to poor quality maps that were difficult to interpret. None of the figures are convincing that NS1, Ab56.2 or Fab56.2 are correctly fit into EM maps. There is no indication of ApoA1 helices. Details of the fit of models to density for key regions of the higher-resolution EM maps should be shown and the models should be deposited in the PDB. An example of modeling difficulty is clear in the sNS1ts dimer with bound Fab56.2 (figs 3c & S7e). For this complex, the orientation of the Fab56.2 relative to the sNS1ts dimer in this submission (Fig 3c) is substantially different than in the bioRxiv preprint (Fig 3c). Regions of empty density in Fig 3c also illustrate the challenge of building a model into this map.

We acknowledge the modelling challenge posed by low resolution maps in general, such as the handedness of the Fab molecule as pointed out by the reviewer (which is why others have developed the use of anti-fab nanobody to aid in structure determination among other methods). The change in orientation of the Fab56.2 relative to the sNS1ts dimer was informed by the HDX-MS results which was not done at the point of bioRxiv preprint mentioned. With regards to indication of ApoA1 helices, this is expected given the heterogeneous nature of HDL. To the best of our knowledge, engineered apoA1 helices were also not reported in many cryoEM structures of membrane proteins solved in membrane scaffold protein (MSP) nanodiscs. This is despite nanodiscs, comprised of engineered apoA1 helices, having well-defined size classifications.

Regions of weak density in Fig 3c is expected due to the preferred orientation issue acknowledged in the results section of the main text (p. 9, line 245). The cryoEM density maps have been deposited in the Electron Microscopy Data Bank (EMDB) under accession codes EMD-36483 (isNS1ts:Fab56.2) and EMD-36480 (Fab56.2:isNS1ts:HDL). The protein model files for isNS1ts:Fab56.2 and Fab56.2:isNS1ts:HDL model are available upon request. Crosslinking MS raw files and the search results can be downloaded from https://repository.jpostdb.org/preview/14869768463bf85b347ac2 with the access code: 3827. The HDX-MS data is deposited to the ProteomeXchange consortium via PRIDE partner repository51 with the dataset identifier PXD042235.

Mass spec:

Crosslinking-mass spec was used to detect contacts between NS1 and ApoA1, providing strong validation of the sNS1-HDL association. As the crosslinks were detected in a bulk sample, they show that NS1 is near ApoA1 in many/most HDL particles, but they do not indicate a specific protein-protein complex. Thus, the data do not support the model of an NS1-ApoA1 complex in Fig 4d. Further, a specific NS1-ApoA1 interaction should have evidence in the EM maps (helical density for ApoA1), but none is shown or mentioned. If such exists, it could perhaps be visualized after focused refinement of the map for sNS1ts-HDL with Fab56.2 (Fig S7d). The finding that sNS1-ApoA1 crosslinks involved residues on the hydrophobic surface of the NS1 dimer confirms previous data that this NS1 surface engages with membranes and lipids.

We thank the reviewer for the comment. The XL-MS is a method to identify the protein-protein interactions by proximity within the spacer arm length of the crosslinker. The crosslinking MS data do support the NS1-ApoA1 complex model obtained by cryo-EM because the identified crosslinks that are superimposed on the EM map are within the cut-off distance of 30 Å. We agree that the XL-MS data do not dictate the specific interactions between specific residues of NS1-ApoA1 in the EM model. We also do not claim that specific residue of NS1 in beta roll or wing domain is interacting with specific residue of ApoA1 in H4 and H5 domain. We claim that beta roll and wing domain regions of NS1 are interacting with ApoA1 in HDL indicating the proximity nature of NS1-ApoA1 interactions as warranted by the XL-MS data.

As explained in the previous response on the lack of indication of ApoA1 helical density, this is expected given the heterogeneous nature of HDL. It is typical to see lipid membranes as unstructured and of lower density than the structured protein. In our study, local refinement was performed on either the global map (presented in Fig S7d) or focused on the NS1-Fab region only. Both yielded similar maps as illustrated in the real space slices shown in Author response image 5. The mask and map overlay is depicted in similar orientations to the real space slices, and at different contour thresholds at 0.05 (Author response image 5e) and 0.135 (Author response image 5f). While the overall map is of poor resolution and directional anisotropy evident, there is clear signal differences in the low density region (i.e. the HDL sphere) indicative of NS1 interaction with ApoA1 in HDL, extending from the NS1 wing to the base of the HDL sphere.

Author response image 5.

Real Space Slices of map and mask used during Local Refinement for overall structure (a-b) and focused mask on NS1 region (c-d). The corresponding map (grey) contoured at 0.05 (e) and 0.135 (f) in similar orientations as shown for the real space slices of map and masks. The focused mask of NS1 used is colored in semi-transparent yellow. Real Space Slices of map and mask are generated during data processing in Cryosparc 4.0 and the map figures were prepared using ChimeraX.

Sample quality:

The paper lacks any validation that the purified sNS1 retains established functions, for example the ability to enhance virus infectivity or to promote endothelial dysfunction.

Please see detailed response for question 2 in Reviewer #1’s comments. In essence, we have showed that both isNS1wt and isNS1ts are capable of inducing endothelial permeability in an in vitro TEER assay (Rebuttal Fig 3) and also in our previous study that quantified inflammation in human PBMC’s (Rebuttal Fig 2).

Peculiarities include the gel filtration profiles (Fig 2a), which indicate identical elution volumes (apparent MWs) for sNS1wt-HDL bound to Ab562 (~150 kDa) and to the ~3X smaller Fab56.2 (~50 kDa). There should also be some indication of sNS1wt-HDL pairs crosslinked by the full-length Ab, as can be seen in the raw cryoEM micrograph (Fig S5b).

Obtaining high quality structures is often more demanding of sample integrity than are activity assays. Given the low quality of the cryoEM maps, it's possible that the acidification step in immunoaffinity purification damaged the HDL complex. No validation of HDL integrity, for example with acid-treated HDL, is reported.

Please see detailed response for question 3 in Reviewer #1’s comments.

Acid treatment is perhaps discounted by a statement (line 464) that another group also used immunoaffinity purification in a recent study (ref 20) reporting sNS1 bound to HDL. However the statement is incorrect; the cited study used affinity purification via a strep-tag on recombinant sNS1.

We thank the Reviewer for pointing this out and have rewritten this paragraph instead (p 18, line 445-455). We also expanded our discussion to highlight our prior functional studies showing that acid-eluted isNS1 proteins do induce endothelial hyperpermeability (p 18-19, line 470-476).

Discussion:

The Discussion reflects a view that the NS1 secreted from virus-infected cells is a 1:1 sNS1dimer:HDL complex with the specific NS1-ApoA1 contacts detected by crosslinking mass spec. This is inconsistent with both the neg-stain 2D class average with 2 sNS1 dimers on an HDL (Fig S1c) and with the recent study of Flamand & co-workers showing 1-3 NS1 dimers per HDL (ref 20). It is also ignores the propensity of NS1 to associate with membranes and lipids. It is far more likely that NS1 association with HDL is driven by these hydrophobic interactions than by specific protein-protein contacts. A lengthy Discussion section (lines 461-522) includes several chemically dubious or inconsistent statements, all based on the assumption that specific ApoA1 contacts are essential to NS1 association with HDL and that sNS1 oligomers higher than the dimer necessarily involve ApoA1 interaction, conclusions that are not established by the data in this paper.

We thank the Reviewer and have revised our discussion to cover available structural and functional data to draw conclusions that invariably also need further validation by others. One point that is repeatedly brought up by Reviewer 1 & 2 is the quality and functionality of our sample. Our conclusion now reiterates this point based on our own published data (Chan et al., 2019) and also the TEER assay data provided as Author response image 3.

Reviewer #1 (Recommendations For The Authors):

Minor:

(1) Fig. S3B, should the label for lane 4 be isNS1? In figure 1C you do not see ApoA1 for rsNS1 but for S3B you do? Which is correct?

This has been corrected in the Fig. S3B, the label for lane 4 has been corrected to isNS1 and lane 1 to rsNS1, where no ApoA1 band (25 kDa) is found.

(2) Line 436, is this the correct reference? Reference 43?

This has been corrected in the main text. (p 20, Line 507; Lee et al., 2020, J Exp Med).

Reviewer #2 (Recommendations For The Authors):

The cryoEM data analysis is incompletely described. The process (software, etc) leading to each refined EM map should be stated, including the use of reference structures in any step. These details are not in the Methods or in Figs S4-7, as claimed in the Methods. The use of DeepEMhancer (which refinements?) with the lack of defined secondary structural features in the maps and without any validation (or discussion of what was used as "ground truth") is concerning. At the least, the authors should show pre- and post-DeepEMhancer maps in the supplemental figures.

The data processing steps in the Methods section have been described with improved clarity. DeepEMhancer is a deep learning solution for cryo-EM volume post-processing to reduce noise levels and obtain more detailed versions of the experimental maps (Sanchez-Garcia, et al., 2021). DeepEMhancer was only used to sharpen the maps and reduce the noise for classes 1 and 2 of isNS1wt in complex with Ab56.2 for visualization purpose only and not for any refinements. To avoid any confusion, the use of DeepEMhancer has been removed from the supp text and figures.

Line 83 - "cryoEM structures...recently reported" isn't ref 17

This reference has been corrected in to Shu et al. (2022) in p 3, line 83.

Fig. S3 - mis-labeled gel lanes

This has been corrected in the Fig. S3B, the label for lane 4 has been corrected to isNS1 and lane 1 to rsNS1.

Fig S6c caption - "Representative 2D classes of each 3D classes, white bar 100 Å. Refined 3D map for classes 1 and 2 coloured by local resolution". The first sentence is unclear, and there is no white scale bar and no heat map.

Fig S6c caption has been corrected to “Representative 3D classes contoured at 0.06 and its particle distribution as labelled and coloured in cyan. Scale bar of 100 Å as shown. Refined 3D maps and their respective FSC resolution charts and posterior precision directional distribution as generated in crysosparc4.0”.