Vacuolar H+-ATPase determines daughter cell fates through asymmetric segregation of the nucleosome remodeling and deacetylase complex

  1. Zhongyun Xie
  2. Yongping Chai
  3. Zhiwen Zhu
  4. Zijie Shen
  5. Zhengyang Guo
  6. Zhiguang Zhao
  7. Long Xiao
  8. Zhuo Du
  9. Guangshuo Ou
  10. Wei Li

  • Curated by eLife

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    The authors make the intriguing proposal that the NuRD complex in C. elegans, which has been linked to regulation of the cell death protein EGL-1 before, becomes asymmetrically distributed after cell division and that this asymmetry relies on V-ATPase activity. Whereas some disagreement remained between the reviewers' and the authors' interpretation, the final version incorporated alternative possibilities in the text, and with careful interpretation, the current manuscript's model is supported by solid data, and represents a valuable contribution to the field.

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Abstract

Asymmetric cell divisions (ACDs) generate two daughter cells with identical genetic information but distinct cell fates through epigenetic mechanisms. However, the process of partitioning different epigenetic information into daughter cells remains unclear. Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans . The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic daughter cells to survive. We identify the vacuolar H + –adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRD’s asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry. We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates.

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  1. Version published to 10.7554/elife.89032.4 on eLife
  2. Version published to 10.7554/elife.89032 on eLife
  3. Version published to 10.1101/2023.06.25.546476v4 on bioRxiv
  4. Version published to 10.7554/elife.89032.3 on eLife
  5. eLife

    Author response:

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

    Joint Public Review:

    Xie et al. propose that the asymmetric segregation of the NuRD complex is regulated in a V-ATPase-dependent manner, and plays a crucial role in determining the differential expression of the apoptosis activator egl-1 and thus critical for the life/death fate decision.

    Remaining concerns are the following:

    The authors should provide the point-by-point response to the following issues. In particular, authors should provide clear reasoning as to why they did not address some of the following comments in the previous revisions. The next response should be directly answering to the following concerns.

    (1) Discussion should be added regarding the criticism that NuRD asymmetric segregation is simply a result of daughter cell size asymmetry. It is perfectly fine that the NuRD asymmetry is due to the daughter cell size difference (still the nucleus within the bigger daughter would have more NuRD, which can determine the fate of daughter cells). Once the authors add this clarification, some criticisms about 'control' may become irrelevant.

    We thank the reviewer for this suggestion. We will add the following text in the revised discussion on page 14, line 26:

    “…We cannot rule out the possibility that NuRD asymmetric segregation results from daughter cell size asymmetry. According to this perspective, the nucleus in the larger daughter cell could possess more NuRD, potentially influencing the fate of the daughter cells. However, it is important to note that the nuclear protein histone or the MYST family histone acetyltransferase is equally segregated in daughter cells of different sizes.….”

    (2) ZEN-4 is a kinesin that predominantly associates with the midzone microtubules and a midbody during mitosis. Given that midbodies can be asymmetrically inherited during cell division, ZEN-4 is not a good control for monitoring the inheritance of cytoplasmic proteins during asymmetric cell division. Other control proteins, such as a transcriptional factor that predominantly localizes in the cytoplasm during mitosis and enters into nucleus during interphase, are needed to clarify the concern.

    We clarified the issue of ZEN-4 below:

    The critique assumes that "midbodies can be asymmetrically inherited during cell division." However, this assumption does not apply to our study of Q cell asymmetric divisions. In our earlier research, we demonstrated that midbodies in Q cells are released post-division and subsequently engulfed by surrounding epithelial cells (Chai et al., Journal of Cell Biology, 2012). Moreover, we have shown that midbodies from the first cell division in C. elegans embryos are also released and engulfed by the P1 cell (Ou et al., Cell Research, 2013). Therefore, the notion of midbody asymmetric inheritance is irrelevant to this manuscript. Additionally, our manuscript already presents the example of the MYST family histone acetyltransferase, illustrating a nuclear protein that predominantly localizes in the cytoplasm during mitosis and symmetrically enters the nucleus during interphase.

    As for pHluorin experiments, symmetric inheritance of GFP and mCherry is not an appropriate evidence to estimate the level of pHluorin during asymmmetric Q cell division. This issue remains unsolved.

    We acknowledge the limitation of pHluorin in measuring the pH level in a living cell. Future studies could be performed to measure the dynamics of pH levels when advanced tools are available.

    (3) Q-Q plot (quantile-quantile plot) in Figure S10 can be used for visually checking normality of the data, but it does not guarantee that the distribution of each sample is normal and has the standard deviation compared with the other samples. I recommend the authors to show the actual statistical comparison P-values for each case. The authors also need to show the number of replicate experiments for each figure panel.

    We thank the reviewer for pointing this out. We will provide P-values for each case and the number of replicate experiments in the revised Figure 5-figure supplement 1 ( corresponding to Figure S10) and the figure legend.

    The authors left inappropriate graphs in the revised manuscript. In Figure 3E, some error bars are disconnected and the other are stuck in the bars. In Figure S4C, LIN-53 in QR.a/p graph shows lines disconnected from error bars.

    We thank the reviewer for pointing this out. We will correct these error bars.

    I am bit confused with the error bars in Figure 2B. Each dot represents a fluorescent intensity ratio of either HDA-1 or LIN-53 between the two daughter cells in a single animal. Plots are shown with mean and SEM, but several samples (for example, the left end) exhibit the SEM error bar very close to a range of min and max. I might misunderstand this graph but am concerned that Figure 2B may contain some errors in representing these data sets. I would like to ask the authors to provide all values in a table format so that the reviewers could verify the statistical tests and graph representation.

    We thank the reviewer for pointing this out. We apologize for the typo in Figure 2B figure legend. We will correct SEM to SD.

    (4) The authors still do not provide evidence that the increase in sAnxV::GFP and Pegl-1gfp or the increase in H3K27ac at the egl-1 gene in hda-1(RNAi) and lin-53(RNAi) animals is not a consequence of global effects on development. Indeed, the images provided in Figure S7B demonstrate that there are global effects in these animals. no causal interactions have been demonstrated.

    We cannot exclude the global effects and have discussed this issue in our previous manuscript on page 9, line 26:

    “...Considering the pleiotropic phenotypes caused by loss of HDA-1, we cannot exclude the possibility that ectopic cell death might result from global changes in development, even though HDA-1 may directly contribute to the life-versus-death fate determination.”

    (5) Figure 4: Due to the lack of appropriate controls for the co-IP experiment (Fig. 4), I remain unconvinced of the claim that the NuRD complex and V-ATPase specifically interact. Concerning the co-IP, the authors now mention that the co-IP was performed three times: "Assay was performed using three biological replicates. Three independent biological replicates of the experiment were conducted with similar results." However, the authors did not use ACT-4::GFP or GFP alone as controls for their co-IP as previously suggested. This is critical considering that the evidence for a specific HDA-1::GFP - V-ATPase interaction is rather weak (compare interactions between HDA-1::GFP and V-ATPase subunits in Fig 4B with those of HDA-1::GFP and subunits of NuRD in Fig S8B).

    We conducted GFP pull-down experiments and MS spectrometric analysis for HDA-::GFP and ACT-4::GFP using identical protocols, yielding consistent results. We agree with the reviewer that in our Western blot, inclusion of ACT-4::GFP is a more effective negative control compared to empty beads.

    (6) Based on Fig 5E, it appears that Bafilomycin treatment causes pleiotropic effects on animals (see differences in HDA-1::GFP signal in the three rows). The authors now state: "Although BafA1-mediated disruption of lysosomal pH homeostasis is recognized to elicit a wide array of intracellular abnormalities, we found no evidence of such pleiotropic effects at the organismal level with the dosage and duration of treatment employed in this study". However, the 'evidence' mentioned is not shown. It is critical that the authors provide this evidence.

    We thank the Reviewer for pointing out this issue. We only checked the viability of the L1 larvae and morphology of animals at the organismal level with the BafA1 dosage and duration of treatment and did not notice any death of the animals and apparent abnormality in morphology (N > 20 for each treatment). However, as the reviewer pointed out, there can be some abnormalities at the cellular level. We thus revised this above description as the following, on page 11, line 27:

    “…Although BafA1-mediated disruption of lysosomal pH homeostasis is recognized to elicit a wide array of intracellular abnormalities, we did not observe any larval deaths and apparent abnormality in morphology at the organismal level (N > 20 for each treatment) at the dose and duration of treatment employed in this study...”

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

    eLife assessment

    The authors propose that the asymmetric segregation of the NuRD complex in C. elegans is regulated in a V-ATPase-dependent manner, that this plays a crucial role in determining the differential expression of the apoptosis activator egl-1, and that it is therefore critical for the life/death fate decision in this species. If proven, the proposed model of the V-ATPase-NuRD-EGL-1-Apoptosis cascade would shed light onto the mechanisms underlying the regulation of apoptosis fate during asymmetric cell division, and stimulate further investigation into the intricate interplay between V-ATPase, NuRD, and epigenetic modifications. However, the strength of evidence for this is currently incomplete.

    Public Review:

    Xie et al. propose that the asymmetric segregation of the NuRD complex is regulated in a V-ATPase-dependent manner, and plays a crucial role in determining the differential expression of the apoptosis activator egl-1 and thus critical for the life/death fate decision.

    While the model is very intriguing, the reviewers raised concerns regarding the rigor of the method. One issue is with statistics (either insufficient information or inadequate use of statistics), and second is the concern that the asymmetry observed may be caused by one cell dying (resulting in protein degradation, RNA degradation etc). We recommend that the authors address these issues.

    We extend our sincere thanks to the Editors and Reviewers for their insightful comments on this study.

    Major #1:

    There are still many misleading statements/conclusions that are not rigorously tested or that are logically flawed. These issues must be thoroughly addressed for this manuscript to be solid.

    (1) Asymmetry detected by scRNA seq vs. imaging may not represent the same phenomenon, thus should not be discussed as two supporting pieces of evidence for the authors' model, and importantly each method has its own flaw. First, for scRNA seq, when cells become already egl-1 positive, those cells may be already dying, and thus NuRD complex's transcripts' asymmetry may not have any significance. The data presented in FigS1D, E show that there are lots of genes (6487 out of 8624) that are decreased in dying cells. Thus, it is not convincing to claim that NuRD asymmetry is regulated by differential RNA amount.

    We agree with the reviewer's comment. Indeed, scRNA-seq reveals phenomena different from those observed in protein imaging, and NuRD asymmetry may not be regulated by differential RNA levels. Seven years ago, when we started this project, NuRD asymmetry during asymmetric neuroblast division was unknown. We first found NuRD mRNA asymmetry using scRNA-seq and then NuRD protein asymmetry using fluorescence imaging. We have documented the whole process of discovering NuRD asymmetry, although the asymmetry of NuRD complex transcripts does not necessarily imply protein asymmetry. We have revised statements related to "NuRD asymmetry being regulated by differential RNA amounts" and discussed this issue in the revised manuscript on page 14, line 2:

    " The transcript asymmetry detected by scRNA-seq may not correspond to the protein asymmetry detected by microscopic imaging. Our scRNA-seq data shows that 6487 out of 8624 genes were not detected in egl-1-positive cells, the putative apoptotic cells. Cells that are egl-1 positive may be undergoing apoptosis, rendering the asymmetry of NuRD complex transcripts insignificant in inferring protein asymmetry. Thus, the observed transcript asymmetry of the NuRD subunits between live and dead cells may be coincidental with NuRD protein asymmetry during asymmetric neuroblast division, rather than serving as a regulatory mechanism."

    (2) Regarding NuRD protein's asymmetry, there are still multiple issues. Most likely explanation of their asymmetry is purely daughter size asymmetry. Because one cell is much bigger than the other (3 times larger), NuRD components, which are not chromatin associated, would be inherited to the bigger cell 3 times more than the smaller daughter. Then, upon nuclear envelope reformation, NuRD components will enter the nucleus, and there will be 3 times more NuRD components in the bigger daughter cell. It is possible that this is actually the underling mechanism to regulate gene expression differentially, but this possibility is not properly acknowledged. Currently, the authors use chromatin associated protein (Mys-1) as 'symmetric control', but this is not necessarily a fair comparison. For NuRD asymmetry to be meaningful, an example of protein is needed that is non-chromatin associated in mitosis, distributed to daughter cells proportional to daughter cell size, and re-enter nucleus after nuclear envelope formation to show symmetric distribution. And if daughter size asymmetry is the cause of NuRD asymmetry, other lineages that do not undergo apoptosis but exhibit daughter size asymmetry would also show NuRD asymmetry. The authors should comment on this (if such examples exist, it is fine in that in those cell types, NuRD asymmetry may be used for differential gene expression, not necessarily to induce cell death, but such comparison provides the explanation for NuRD asymmetry, and puts the authors finding in a better context).

    For more than one decade, we have meticulously explored the relationship between protein asymmetry and cell size asymmetry during ACDs of Q cells. A notable example of even protein distribution is the cytokinetic kinesin ZEN-4, as documented in our 2012 publication in the Journal of Cell Biology (Chai et al., JCB, 2012). This study, primarily focusing on the fate of the midbody post-cell division, also showcased the dynamics of GFP-tagged ZEN-4 during ACDs of QR.a cells in movie S1. Intriguingly, beyond its role in the cytokinetic ring, we observed a uniform dispersal of ZEN-4 throughout the cytoplasm. Remarkably, following cell division, ZEN-4 transitions evenly into the nuclei of the daughter cells, a phenomenon with implications yet to be fully understood. One hypothesis is that ZEN-4's nuclear localization may prevent the formation of ectopic microtubule bundles in the cytosol during interphase. Below, we present a snapshot from our original movie, clearly showing the symmetrical distribution of ZEN-4 into the nuclei of the two daughter cells.

    (3) For the analysis of protein asymmetry between two daughters in Fig S4C, the method of calibration is unclear, making it difficult to interpret the results.

    In Figure S4C, we quantified the relative total fluorescence of the Q cell, with the quantification method illustrated in Figure S4A. To further clarify our quantification approach, we have updated Figure S4A and the "Live-Cell Imaging and Quantification" section in the Materials and Methods:

    “…To determine the ratios of fluorescence intensities in the posterior to anterior half (P/A) of Q.a lineages or A/P of Q.p lineages, the cell in the mean intensity projection was divided into posterior and anterior halves. ImageJ software was used to measure the mean fluorescence intensities of two halves with background subtraction. The slide background's mean fluorescence intensity was measured in a region devoid of worm bodies. The background-subtracted mean fluorescence intensities of the two halves were divided to calculate the ratio. The same procedure was used to determine the fluorescence intensity ratios between two daughter cells. Total fluorescence intensity was the sum of the posterior and anterior fluorescence intensities or the sum of fluorescence intensities from two daughter cells (Figure S4A). …”

    (4) As for pHluorin experiments, the authors were asked to test the changes in fluorescence observed are due to changes in pH or changes in the amount of pHluorin protein. They need to add a ratio-metric method in this manuscript. A brief mention to Page 12 line 12 is insufficient to clarify this issue.

    We appreciate the concerns about potential changes in pH or pHluorin protein levels. While we cannot completely dismiss the impact of changes in the amount of pHluorin protein, it appears improbable that the asymmetry of pHluorin fluorescence is attributed to an asymmetric amount of pHluorin protein. This inference is supported by the observation that other fluorescent proteins, such as GFP or mCherry, did not exhibit any asymmetry during ACDs of Q cells. An example of GFP alone during the ACD of QL.p is illustrated in figure 5A from Ou and Vale, JCB, 2009. The fluorescence intensities in the large QL.pa cell and the small QL.aa are indistinguishable.

    Major #2:

    Some issues surrounding statistics must be resolved.

    (1) Fig. 1FG, 2D, 3BDEG, 5BD and 6B used either one-sample t-test or unpaired two-tailed parametric t-test for statistical comparison. These t-tests require a verification of each sample fitting to a normal distribution. The authors need to describe a statistical test used to verify a normal distribution of each sample.

    (2) Fig. 2D, 3D, and 3G have very small sample size (N=3-4, N=6, N=3, respectively), it is possible that a normal distribution cannot be verified. How can the authors justify the use of one-sample t-test and unpaired parametric t-test ?

    (3) Statistical comparison in Fig. 2D and Fig. 6B should be re-assessed. For Fig. 2D, the authors need to compare the intensity ratio of HDA-1/LIN53 between sister cells dying within 35 min and those over 400 min. For Fig. 6B, they need to compare the intensity ratio of VHA-17 between DMSO- and BafA1- treated cells at the same time point after anaphase.

    We appreciate the reviewer's advice on the statistical analysis of our data. In response, we performed normality tests on the datasets presented in Figures 1F, 1G, 3B, 5B, 5D, and 6B, all of which passed the tests (as demonstrated in Figure S10). We also acknowledge the reviewer's comment on the inadequate sample sizes in Figures 2D, 3D, 3E, and 3G for fitting a normal distribution. Therefore, we have revised our statistical analysis methods for these figures and updated both the figures and their legends. The revised statistical results support the primary conclusions of this study.

    In response to the reviewer's observation regarding the small sample size in Figure 2D , which precluded normality verification, and the suggestion to compare sister cells that die within 35 minutes to those surviving over 400 minutes, we adapted our approach. We implemented the Kruskal-Wallis test to evaluate the differences among the groups. To assess the specific differences between each group and the 400 min MSpppaap group, we conducted the Dunn’s multiple comparisons test. The revised Figure 2D illustrates the updated statistical significance.

    For Figure 3D, due to the small sample size precluding normality verification, we applied the Wilcoxon test with 1 as the theoretical median. The revised Figure 3D illustrates the updated statistical significance.

    For Figure 3E, where the sample size also hindered normality verification, we conducted the Kruskal-Wallis test to evaluate the overall effect. Additionally, Dunn’s multiple comparisons test was utilized to examine the differences between groups. The revised Figure 3E illustrates the updated statistical significance.

    For Figure 3G, the reviewer pointed out the small sample size and the limited statistical power due to having only three data points per group. To address this, we revised the figure to visually present each data point, aiming to more clearly illustrate the variation trends.

    For Figure 6B, following the reviewer's suggestion, we compared the DMSO group directly with the Baf A1 group, updating Figure 6B to reflect this comparison as advised.

    These adjustments have been made to ensure the statistical analyses are robust and appropriate given the sample sizes and to align with the reviewer's recommendations, enhancing the clarity and accuracy of our findings.

    Recommendations for the authors:

    We recommend using grey scale (instead of 'heatmap' representation) to show the protein distribution of interest. Heatmap does not help at all, because 'total protein amount per cell' (instead of signal intensity on each pixel) is what matters in the context of this paper. Heatmap presentation does not allow readers to integrate signal intensity with their eyes.

    We thank the editor for pointing this out. We have changed heatmaps to inverted fluorescence images in grey scale.

  6. eLife

    eLife assessment

    The authors make the intriguing proposal that the NuRD complex in C. elegans, which has been linked to regulation of the cell death protein EGL-1 before, becomes asymmetrically distributed after cell division and that this asymmetry relies on V-ATPase activity. Whereas some disagreement remained between the reviewers' and the authors' interpretation, the final version incorporated alternative possibilities in the text, and with careful interpretation, the current manuscript's model is supported by solid data, and represents a valuable contribution to the field.

  7. eLife

    Joint Public Review:

    Xie et al. propose that the asymmetric segregation of the NuRD complex is regulated in a V-ATPase-dependent manner, and plays a crucial role in determining the differential expression of the apoptosis activator egl-1 and thus critical for the life/death fate decision.

    Remaining concerns are the following:

    The authors should provide the point-by-point response to the following issues. In particular, authors should provide clear reasoning as to why they did not address some of the following comments in the previous revisions. The next response should be directly answering to the following concerns.

    (1) Discussion should be added regarding the criticism that NuRD asymmetric segregation is simply a result of daughter cell size asymmetry. It is perfectly fine that the NuRD asymmetry is due to the daughter cell size difference (still the nucleus within the bigger daughter would have more NuRD, which can determine the fate of daughter cells). Once the authors add this clarification, some criticisms about 'control' may become irrelevant.

    (2) ZEN-4 is a kinesin that predominantly associates with the midzone microtubules and a midbody during mitosis. Given that midbodies can be asymmetrically inherited during cell division, ZEN-4 is not a good control for monitoring the inheritance of cytoplasmic proteins during asymmetric cell division. Other control proteins, such as a transcriptional factor that predominantly localizes in the cytoplasm during mitosis and enters into nucleus during interphase, are needed to clarify the concern.

    As for pHluorin experiments, symmetric inheritance of GFP and mCherry is not an appropriate evidence to estimate the level of pHluorin during asymmmetric Q cell division. This issue remains unsolved.

    (3) Q-Q plot (quantile-quantile plot) in Figure S10 can be used for visually checking normality of the data, but it does not guarantee that the distribution of each sample is normal and has the standard deviation compared with the other samples. I recommend the authors to show the actual statistical comparison P-values for each case. The authors also need to show the number of replicate experiments for each figure panel.

    The authors left inappropriate graphs in the revised manuscript. In Figure 3E, some error bars are disconnected and the other are stuck in the bars. In Figure S4C, LIN-53 in QR.a/p graph shows lines disconnected from error bars.

    I am bit confused with the error bars in Figure 2B. Each dot represents a fluorescent intensity ratio of either HDA-1 or LIN-53 between the two daughter cells in a single animal. Plots are shown with mean and SEM, but several samples (for example, the left end) exhibit the SEM error bar very close to a range of min and max. I might misunderstand this graph but am concerned that Figure 2B may contain some errors in representing these data sets. I would like to ask the authors to provide all values in a table format so that the reviewers could verify the statistical tests and graph representation.

    (4) The authors still do not provide evidence that the increase in sAnxV::GFP and Pegl-1gfp or the increase in H3K27ac at the egl-1 gene in hda-1(RNAi) and lin-53(RNAi) animals is not a consequence of global effects on development. Indeed, the images provided in Figure S7B demonstrate that there are global effects in these animals. no causal interactions have been demonstrated.

    (5) Figure 4: Due to the lack of appropriate controls for the co-IP experiment (Fig. 4), I remain unconvinced of the claim that the NuRD complex and V-ATPase specifically interact. Concerning the co-IP, the authors now mention that the co-IP was performed three times: "Assay was performed using three biological replicates. Three independent biological replicates of the experiment were conducted with similar results." However, the authors did not use ACT-4::GFP or GFP alone as controls for their co-IP as previously suggested. This is critical considering that the evidence for a specific HDA-1::GFP - V-ATPase interaction is rather weak (compare interactions between HDA-1::GFP and V-ATPase subunits in Fig 4B with those of HDA-1::GFP and subunits of NuRD in Fig S8B).

    (6) Based on Fig 5E, it appears that Bafilomycin treatment causes pleiotropic effects on animals (see differences in HDA-1::GFP signal in the three rows). The authors now state: "Although BafA1-mediated disruption of lysosomal pH homeostasis is recognized to elicit a wide array of intracellular abnormalities, we found no evidence of such pleiotropic effects at the organismal level with the dosage and duration of treatment employed in this study". However, the 'evidence' mentioned is not shown. It is critical that the authors provide this evidence.

  8. Version published to 10.1101/2023.06.25.546476v3 on bioRxiv
  9. Version published to 10.7554/elife.89032.2 on eLife
  10. eLife

    Author Response

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

    Public Reviews:

    Throughout the study, there is insufficient information about how experiments were performed and how often (imaging, pull-downs etc), how data was acquired, modified and analysed (especially imaging data, see below), how statistical analyses were done and what is presented in the figures (single planes or maximum intensity projections etc). This makes it difficult to evaluate the data and results.

    We have incorporated additional experimental details to the Materials and Methods section: "Recent advancements in optical and camera technologies permit the acquisition of Z-stacks without perturbing Q cell division or overall animal development. Z-stack images were acquired over a range of -1.6 to +1.6 μm from the focal plane, at intervals of 0.8 μm. The field-of-view spanned 160 μm × 160 μm, and the laser power, as measured at the optical fiber, was approximately 1 mW. ImageJ software (http://rsbweb.nih.gov/ij/) was used to perform image analysis and measurement. Image stacks were z-projected using the average projection for quantification and using the maximum projection for visual display. "

    The majority of our experimental procedures adhere to methodologies delineated in our prior publications and other scientific literature. We were pioneers in the development of fluorescence time-lapse live microscopy techniques for capturing Q cell migration and asymmetric division (Ou and Vale, Journal of Cell Biology, 2009; Ou et al., Science, 2010; Chai et al., Nature Protocols, 2012). Our innovative imaging protocol uncovered a novel mode of polarized, non-muscle myosin-II-dependent asymmetric cell division (Ou et al., Science, 2010). Subsequently, we unveiled another previously uncharacterized mechanism of asymmetric cell division dependent on polarized actin polymerization (Chai et al., Cell Discovery, 2022). In the present study, we have significantly refined our imaging and quantification protocols. Different from the single-focal-plane imaging employed in our earlier study by Ou et al. 2009, advancements in optical technologies and camera resolution now enable us to undertake time-lapse imaging across multiple focal planes and track signal differences between the anterior and posterior segments of dividing cells.

    There is insufficient information about tools and reporters used. This is misleading and impacts the conclusions that can be made from the results presented. To give an example, in Figure 1D-F, the authors present data that HDA-1::GFP and LIN-53::mNeonGreen (both components of the nucleosome remodeling and deacetylation complex) but not the histone acetyltransferase MYS-1::GFP are 'asymmetrically segregated' during QR.a division. However, the authors do not mention that HDA-1::GFP and LIN-53::mNeonGreen are expressed at endogenous levels (they are CRISPR alleles) whereas MYS-1::GFP is overexpressed (integration of a multi-copy extrachromosomal array). The difference in 'segregation' could therefore be a consequence of different levels of expression rather than different modes of segregation ('asymmetric' versus 'symmetric').

    Figure S2 shows overexpressed HDA-1, LIN-53 and CHD-3 are also asymmetrically segregated during ACD of QR.a, which indicates that different levels of expression do not affect the modes of segregation, at least for the NuRD subunits. In the main text, however, we presented the asymmetric segregation of HDA-1::GFP and LIN-53::mNeonGreen using their CRISPR KI alleles.

    There is insufficient information about the phenotypes of the animals used (RNAi knock-downs of hda-1, lin-53 RNAi, pig-1 etc). Again this is misleading and impacts the conclusions that can be made. To give some examples,

    1. In Figure 3A-G, control RNAi embryos are compared to hda-1 RNAi and lin-53 RNAi embryos. What the authors do not mention is that hda-1 RNAi and lin-53 RNAi embryos have severe developmental defects and essentially cannot be compared to control RNAi embryos. The differences between the embryos can be seen in Figure S7B where bright-field images of control RNAi, hda-1 RNAi and lin-53 RNAi embryos are shown. At the 350 min time point, a normal embryo is visible for the control, a 'ball of cells' embryo for hda-1 RNAi and an embryo that seems to have arrested at an earlier developmental stage (and therefore have much larger cells) for lin-53 RNAi. Because of these pleiotropic phenotypes, it is unclear whether differences seen for example in sAnxV::GFP positive cells (Figure 3A) are the result of a direct effect of hda-1(RNAi) on cell death or whether they are the result of global changes in development and cell fate induced by hda-1(RNAi). hda-1(RNAi) and lin-53(RNAi) embryos are also used for the data shown in Figures S6 and S7, raising the same concerns;

    In the submitted manuscript, we mentioned that hda-1 RNAi and lin-53 RNAi caused embryonic lethality and that we could track some of the apoptotic events in hda-1 RNAi embryos arrested between the late gastrulation stage and bean stage. We agree with the reviewers that because of the pleiotropic phenotypes, we cannot distinguish whether sAnxV::GFP positive cells (Figure 3A) are the result of a direct effect of hda-1 (RNAi) on cell death or whether they are the result of global changes in development and cell fate induced by hda-1 (RNAi). We added the sentence to page 9 line 26: “Considering the pleiotropic phenotypes caused by loss of HDA-1, we cannot exclude the possibility that ectopic cell death might result from global changes in development, even though HDA-1 may directly contribute to the life-versus-death fate determination.”

    1. The authors do not mention what the impact of Baf A1 treatment is on animals; however, the images provided in Figure 5E indicate that Baf A1 treatment causes pleiotropic effects in L1 larvae.

    We have carefully checked the BafA1 treated animals, but have not been able to detect any visible defect in Baf A1 treated animals under a 25× dissection microscope at the given dosage and duration of treatment. We also searched for the published images or literature and did not find pleiotropic effects on the animal level at this dosage and duration; however, we agree with the reviewers that perturbation of pH homeostasis in lysosomes by BafA1 will certainly generate pleiotropic cellular defects. We discussed the issue below:

    "Although BafA1-mediated disruption of lysosomal pH homeostasis is recognized to elicit a wide array of intracellular abnormalities, we found no evidence of such pleiotropic effects at the organismal level with the dosage and duration of treatment employed in this study."

    There is a lack of adequate controls. Because of this, some of the data presented must be considered as preliminary. To give some examples:

    1. Controls are lacking for the data shown in Figure 3D-G (i.e. genes other than egl-1). Since hda-1 RNAi has a pleiotropic effect and most likely affects H3K27 acetylation genome-wide, this is critical. Based on what is shown, it is unclear whether the results presented are specific to egl-1 or not;

    In figure 3F, we added F23B12.1 and sru-43 as the controls of egl-1. We added “while the H3K27ac level of genes adjacent to egl-1 showed no significant changes” to Page 10 line 22 in the revised text.

    1. The co-IP and mass spec data shown in Figure 4A, C and Figure S8 also lack a critical control, which is GFP only. Because of this, it is unclear whether subunits of the V-ATPase bind to HDA-1 or GFP. The co-IP and mass spec data forms the basis of Figures 5 and 6 as well as Figure S9. Data presented in these figures therefore has to be considered preliminary as well.

    In the co-IP and mass spec shown in Figure 4A, we used ACT-4::GFP as the negative control, which can preclude V-ATPase subunits that bind to GFP. In Figure 4C, we used anti-V1A (V-ATPase V1 domain A subunit) antibody to confirm the interaction between V1A and HDA-1. In Figure S8B, we also used ACT-4::GFP as a control, showing other NuRD subunits bind to HDA-1 rather than GFP.

    Inappropriate methods are used. For this reason, some of the data again must be considered preliminary. To give some examples:

    1. In Figure 5A, B, the authors used super-ecliptic pHluorin to look at changes in pH in the daughter cells. However, the authors used quenching of super-ecliptic pHluorin fluorescence rather than a ratio-metric method to 'measure' changes in pH. Because of this, it is unclear whether the changes in fluorescence observed are due to changes in pH or changes in the amount of pHluorin protein. Figure 5A, B forms the basis for the experiments presented in the remaining parts of Figure 5 as well as in Figure 6 and Figure S9;

    Bafilomycin A1 inhibits the activity of V-ATPase, presumably preventing the pumping of protons into the apoptotic daughter cell. It is more likely that the apoptotic daughter cell becomes less acidic and more neutral after the treatment of Baf1A, although we cannot exclude the possibility that the changes in fluorescence could be due to changes in the amount of pHluorin protein. A ratio-metric method to measure changes in pH will be further used to distinguish the two possibilities.

    We added “although we cannot exclude the possibility that the changes in fluorescence could be due to changes in the amount of pHluorin protein.” to Page 12 line 12 in the revised text.

    1. The authors' description of how some images were modified before quantitative analysis raises concerns. The figures of concern are particularly Figure 1 and Figure S4, where background subtraction with denoising and deconvolution was used. Background subtraction, with denoising and deconvolution is an image manipulation that enhances the contrast between background and what looks like foreground. Therefore, background subtraction should be applied primarily in experiments involving image segmentation not fluorescence intensity measurement. Not being provided any information by the authors about the kind of subtraction that was made, this processing could lead to an uneven subtraction across the image, which can easily lead to artefacts. Since the fluorescence intensity in the smaller daughter cell is lower, and thus closer to background, the algorithm the authors used may have misinterpreted the grey value information in the smaller daughter cell pixels. This could have led to an asymmetric subtraction of background in the two daughter cells, leading to a stronger subtraction in the smaller daughter cell. Ultimately, their processing could have artificially increased the intensity asymmetry between the two daughter cells in all their results.

    As mentioned earlier, the imaging and quantification methods of this manuscript have been routinely used in our previous publications or studies from many other labs (Gräbnitz F, et al., Cell Rep. 2023; Herrero E, et al., Genetics. 2020; Roubinet C, et al., Curr Biol. 2021). Background subtraction is a standard procedure to quantify cellular fluorescence intensities. The fluorescence intensity of the slide background was measured from a region without worm bodies, of the same size as the region of interest. We have added how we measured the background to page 19 Line 24: “The fluorescence intensity of the slide background was measured from a region without worm bodies, of the same size as the region of interest.”

    The imaging data is of low quality (for example Figures 1, 2, 5, 6; Figures S2, S3, S5, S6, S9). Since much of the study and the findings are based on imaging, this is a major concern. Critical parameters are not mentioned (number of sections in z-stack, size of the field-of-view, laser power used etc), which makes it difficult to understand what was done and what one is looking at.

    Fluorescence images of neuroblast asymmetric cell division in developing C. elegans larvae has historically presented considerable challenges. Our recent methodological advancements have facilitated live imaging in this intricate system with improved resolution. In the revised manuscript, we have elucidated the specific z-stack parameters, field-of-view dimensions, and laser power settings employed: "Z-stack images were acquired over a range of -1.6 to +1.6 μm from the focal plane, at intervals of 0.8 μm. The field-of-view spaned 160 μm × 160 μm, and the laser power, as measured at the optical fiber, was approximately 1 mW."

    To give some specific examples,

    1. The images shown in Figure 2B are of very low quality with severe background from neighbouring cells. In addition, the outline of the cells (plasma membrane) or the nuclei of the daughter cells is unknown. Based on this it is not clear how the authors could have measured 'Fluorescence intensity ratio between sister nuclei' in an accurate and unbiased way (what is clear from these images is that there is an increase in HDA-1::GFP signal in ALL surviving daughters (asymmetric and symmetric divisions) post cytokinesis but not in the daughter cell that is about to die (asymmetric and unequal division));

    We employed live-cell imaging in conjunction with automated cell lineage tracing algorithms (Du et al., Cell, 2014) to scrutinize NuRD asymmetry in embryos from the two- or four-cell stage up to the 350-cell stage. This sophisticated approach was initially pioneered by Dr. Zhirong Bao at Sloan Kettering and subsequently refined by Dr. Zhuo Du during Dr. Du's postdoctoral training in Dr. Bao's laboratory. This advanced imaging pipeline enables the scientific community to quantify cellular fluorescence intensity in an automated fashion, thereby substantially mitigating manual intervention and bias.

    1. The images in Figure 6A and Figure S9A on VHA-17 segregation and its colocalization to ER and lysosome segregation during QR.a division are of very low quality and it is unclear to the reviewer how such images were used to obtain the quantitative data shown.

    In some cases, there is a discrepancy between what is shown in figures and what the authors state in the text. To give some examples:

    1. On page 7, the authors state "..., we found that nuclear HDA-1 or LIN-53 asymmetry gradually increased from 1.1-fold at the onset of anaphase to 1.5 or 1.8-fold at cytokinesis, respectively (Figure 1D-E)." Looking at the images for HDA-1 and LIN-53 in Figure 1D, the increase in the ratio mainly occurs between 4 min and 6 min, which is post cytokinesis and NOT prior to cytokinesis;

    Thank the reviewer for pointing out this. The nuclear HDA-1 or LIN-53 asymmetry increased to 1.5 or 1.8-fold 6 min after the onset of anaphase, when QR.a just completes cytokinesis. Therefore, We change the sentence “we found that nuclear HDA-1 or LIN-53 asymmetry gradually increased from 1.1-fold at the onset of anaphase to 1.5 or 1.8-fold at cytokinesis, respectively (Figure 1D-E).” to “we found that nuclear HDA-1 or LIN-53 asymmetry gradually increased from 1.1-fold at the onset of anaphase to 1.5 or 1.8-fold upon the completion of cytokinesis, respectively (Figure 1D-E).”

    However, nuclear HDA-1 or LIN-53 asymmetry initiates prior to cytokinesis. We started to see the nuclear HDA-1 or LIN-53 asymmetry (1.4 fold for HDA-1 and 1.2 fold for LIN-53 ) 2 min after the onset of anaphase (Figure 1D).

    1. These images (Figure 1D) also show that there is an increase in the HDA-1 and LIN-53 signals in the larger daughter cells (QR.ap), which suggests that the increase in ratios (Figure 1E) is the result of increased HDA-1 and LIN-53 synthesis post cytokinesis. However, on top of page 8, the authors state "The total fluorescence of HDA-1, LIN-53 and MYS-1 remained constant during ACDs, suggesting that protein redistribution may establish NuRD asymmetry (Figure S4C)." In Figure S4C, the authors present straight lines for 'relative total fluorescence' for imaging (probably z-stacks) that was done every min over the course of 7 min. If there was no increase in material as the authors claim, they should have seen significant photobleaching over the course of the 7 min and therefore reduced level of 'relative total fluorescence' over time. How the data presented in Figure S4C was generated is therefore unclear. (Despite the fact that the authors claim that the asymmetry seen is not due to new synthesis in the larger daughter cell post cytokinesis, it would be more consistent with the first experiment presented in this study (Figure S1) that shows that there is more hda-1 mRNA in egl-1(-) cells compared to egl-1(+) cells);

    Regarding the concern of photo-bleaching, we have meticulously calibrated our imaging system over the past several years. Rigorous controls, qualification, and analyses were scrupulously undertaken during the development of our fluorescence time-lapse imaging system for the investigation of Q cell dynamics, initially established by Dr. Guangshuo Ou in Ron Vale's laboratory—a renowned hub for avant-garde imaging techniques (Ou & Vale, Journal of Cell Biology, 2009; Ou et al., Science, 2010). Remarkably, no discernible photobleaching was observed even during two to three-hour imaging.

    We agree that protein turnover, involving both degradation and synthesis, may occur. However, NuRD asymmetric distribution occurred within several minutes after metaphase and QR.a completes cytokinesis ~6min after the onset of anaphase, while GFP protein translation and maturation require ~ 30 min in Q neuroblast (Ou & Vale, Journal of Cell Biology, 2009). Even if hda-1::gfp mRNA is translated during cell division, the nascent GFP-tagged protein will mature long after the completion of cytokinesis. Consequently, we postulate that the influence of newly synthesized GFP-tagged protein during Q cell division is negligible for quantification purposes. It is plausible that the asymmetry in HAD-1 protein distribution is independent of hda-1 mRNA asymmetry.

    1. On page 12, the authors state "..., in Baf A1-treated animals, QRaa inherited similar levels of HDA-1::GFP as its sister cell,...". However, looking at the image provided in Figure 5E (0 min), there seems to be a similar ratio of HDA-1::GFP between the daughter cells in DMSO and Baf A1-treated animals.

    We have adjusted the images in Figure 5E to show the asymmetry in DMSO-treated control animals. We acknowledge variations among animals. Our quantifications from more than 10 animals show the HDA-1 asymmetry in DMSO-treated animals in Figure 5B.

    Recommendations for the authors:

    Conclusion 1

    "Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans" (Abstract)

    Results described on pages 6-9 ("NuRD asymmetric segregation during neuroblast ACDs" and "NuRD asymmetric segregation in embryonic cell lineages") and data shown in Figure S1, Figure 1, Figures S2, S3, S4, S5, Figure 2.

    Conclusion 1 is not supported by the results as numerous concerns exist about the data in many of these figures (see above, major weaknesses). A more likely explanation for the authors' observations is that there is synthesis of NuRD post cytokinesis and that asymmetries in the amounts of NuRD observed in the two daughter cells is a consequence of their different cell sizes (QR.ap is 3x as large as QR.aa). This is supported by the finding that the loss of pig-1, which causes 'equal' division resulting in two daughter cells of similar sizes, abolishes the differences in NuRD seen between the daughter cells.

    As discussed earlier, GFP protein translation and maturation require ~ 30 min in Q neuroblast (Ou & Vale, Journal of Cell Biology, 2009). Even if there is the synthesis of NuRD post cytokinesis, the nascent GFP-tagged protein will not mature within our imaging timeframe, Therefore, NuRD asymmetry is unlikely to be a result of the synthesis of NuRD post cytokinesis. In addition, We found that MYS-1::GFP was symmetrically segregated into the small apoptotic daughter cells and big surviving daughter cells, suggesting NuRD asymmetry may be irrelevant to cell size asymmetry.

    Interestingly, despite the fact that the loss of pig-1 causes 100% of the divisions to be equal by size and symmetric with respect to NuRD amounts, it only causes about 30% of QR.aa cells to inappropriately survive. This demonstrates that there is a correlation between NuRD asymmetry and daughter cell size asymmetry but NOT between NuRD asymmetry and cell death. This also demonstrates that loss of 'NuRD asymmetry' and presence of NuRD in the daughter that should die is NOT sufficient to block its death.

    Cordes et al. 2006 (DOI: 10.1242/dev.02447) reported that in pig-1 loss-of-function mutants, <40% of Q.p lineages produce extra neurons because Q.pp cells inappropriately survive. Noticeably, only 30% and 5% Q.p lineages produce extra neurons in ced-3 and egl-1 loss of function single mutant, respectively. pig-1 ced-3 double mutant or pig-1 egl-1 double mutants show a dramatically stronger phenotype than either single mutant, resulting in about 80% of Q.p lineages producing extra neurons. These results suggest that pig-1 functions in parallel to the EGL-1-CED-9-CED-4-CED-3 cell death pathway to promote Q cell apoptosis.

    We agree with the reviewer that “loss of 'NuRD asymmetry' and presence of NuRD in the daughter that should die is NOT sufficient to block its death” in pig-1 loss-of-function mutants. However, these results do not rule out the correlation between NuRD asymmetry and cell death. In the pig-1 mutant, the concentration of NuRD in Q.pp might not be high enough to completely block the death pathway. Alternatively, NuRD may be one but not the only factor blocking the cell death pathway.

    Lastly, it is imperative to underscore that cellular aberrations observed during early developmental stages frequently undergo compensatory correction during subsequent developmental stages or even initial aging stages. For example, in certain cell migration mutants exhibiting early migration defects, the initial penetrance exceeds 80%; however, the penetrance is mitigated to a mere 30% in adults. Such observations have been corroborated in our prior publications focusing on cell migration dynamics (Wang et al., PNAS, 2013; Zhu et al., Dev Cell, 2016). This appears to be a pervasive phenomenon, echoed by several laboratories specializing in neural development. Sengupta and Blacque’s labs has reported that early aging can ameliorate ciliary phenotypes in C. elegans mutants with compromised intraflagellar transport mechanisms. Accordingly, late developmental stages may act as a compensatory buffer for antecedent developmental abnormalities.

    Conclusion 2

    "The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic cells to survive." (Abstract) Results described on pages 8-10 ("Loss of the deacetylation activity of NuRD causes ectopic apoptosis" and "NuRD RNAi upregulates the egl-1 expression by increasing its H3K27 aceylation") and data shown in Figure S6, Figure 3, Figure S7 and data shown in Figure 5.

    Because of the various concerns raised above (major weaknesses) about the data presented in Figure S6, Figure 3, Figure S7 (pleiotropic phenotypes of hda-1 and lin-53 RNAi animals, lack of controls etc), there is no evidence that NuRD has a specific and/or direct effect on egl-1 expression in cells programmed to die or that loss of NuRD causes ectopic egl-1-dependent cell death. The claim that "ectopic gain of NuRD enables apoptotic cells to survive." is based on Figure 5E, where the authors show that Baf A1 treatment causes symmetric NuRD segregation in 11/12 animals and that QR.aa survives in 11/12 animals. However, those data are unconvincing. As mentioned above (major weaknesses), from the low-quality images provided, it is not clear whether there is 'symmetric NuRD segregation' in Baf A1 treated animals, and the conditions of the animals are a concern because of pleiotropic effects of blocking V-ATPase. (I am not convinced I am actually looking at the same region of an L1 larvae in the three animals because the HDA-1::GFP signal seems inconsistent across them.) One process that is affected by a block of V-ATPase is engulfment. The fact that the authors observe that 130 min post-cytokinesis, QR.aa still persists in Baf A1 treated animals could therefore be the result of a delay in engulfment rather than a block in cell death. In addition, the claim that ectopic gain of NuRD enables apoptotic cells to survive contradicts their findings on loss of pig-1 described about ('Conclusion 1').

    We acknowledge the limitations of our imaging system; however, as we pointed out earlier that we developed imaging methods and kept improving them. We have tried our best to obtain images from developing C. elegans larvae. On the other hand, we showed that hda-1 RNAi and lin-53 RNAi increase the expression of a subset of genes, including egl-1, either directly or indirectly (Fig. 3C). Figure 3B shows the ectopic cell death caused by loss of NuRD is dependent on EGL-1-CED-9-CED-4-CED-3 pathway. While we cannot exclude several other possibilities while addressing such a complex problem in such a challenging model system, these results provide some evidence supporting that our claim can be one of the possibilities.

    Conclusion(s) 3

    "We identified the vacuolar H+-adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRD's asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry" (Abstract)

    Results described on pages 10-13 ("V-ATPase regulates asymmetric segregation of NuRD during somatic ACDs") and data shown in Figures 4, 5, 6, Figures S8, S9.

    As outlined above (major weaknesses), the evidence that HDA-1 interacts with the V-ATPase complex is preliminary (no GFP control), and I consider the imaging data showing that V-ATPase asymmetrically segregates very low quality and unconvincing (Figure 6). The data on pH changes are also preliminary as the experiment was not done the way it should have (quenching rather than ratiometric). Finally, there are concerns about the results that apparently demonstrate that inhibiting V-ATPase activity disrupts pH asymmetry and NuRD asymmetry (impact of Baf A1 treatment).

    As discussed earlier, Bafilomycin A1 inhibits the activity of V-ATPase, presumably preventing the pumping of protons into apoptotic daughter cells. It is more likely that the apoptotic daughter cell becomes less acidic and more neutral after the treatment of Baf1A, although we cannot exclude the possibility that the changes in fluorescence could be due to changes in the amount of pHluorin protein. A ratio-metric method to measure changes in pH will be further used to distinguish the two possibilities.

    We added “although we cannot exclude the possibility that the changes in fluorescence could be due to changes in the amount of pHluorin protein.” to Page 12 line 12 in the revised text.

    Conclusion 4

    "We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates." (Abstract) Discussion and model Figure 6C.

    I consider the model premature and not based on any convincing data. In addition, the role of V-ATPase and acidification does not make sense. V-ATPase is involved in the acidification of the lysosomal system (lumen), and it is thought that cytosolic acidification in apoptotic cells is caused by lysosomal leakage. This is not consistent with the authors' model.

    This manuscript lacks a section describing details of statistical analyses and the rationale for the chosen test, sample sizes, exclusion criteria, and replication details. Although the sample size is relatively smaller (less than 30), the authors used "unpaired t-test" for most of the tests. They should describe which type of t-test they used (parametric or non-parametric test). They also should provide replication details for non-statistical data set, for example Fig 3F and Fig 4C.

    We used the Unpaired two-tailed parametric t-test. We have now added the information for statistic tests in the revised methods and figure legends.

  11. eLife

    eLife assessment

    The authors propose that the asymmetric segregation of the NuRD complex in C. elegans is regulated in a V-ATPase-dependent manner, that this plays a crucial role in determining the differential expression of the apoptosis activator egl-1, and that it is therefore critical for the life/death fate decision in this species. If proven, the proposed model of the V-ATPase-NuRD-EGL-1-Apoptosis cascade would shed light onto the mechanisms underlying the regulation of apoptosis fate during asymmetric cell division, and stimulate further investigation into the intricate interplay between V-ATPase, NuRD, and epigenetic modifications. However, the strength of evidence for this is currently incomplete.

  12. eLife

    Joint Public Review:

    Xie et al. propose that the asymmetric segregation of the NuRD complex is regulated in a V-ATPase-dependent manner, and plays a crucial role in determining the differential expression of the apoptosis activator egl-1 and thus critical for the life/death fate decision.

    While the model is very intriguing, the reviewers raised concerns regarding the rigor of the method. One issue is with statistics (either insufficient information or inadequate use of statistics), and second is the concern that the asymmetry observed may be caused by one cell dying (resulting in protein degradation, RNA degradation etc). We recommend that the authors address these issues.

    Major #1:

    There are still many misleading statements/conclusions that are not rigorously tested or that are logically flawed. These issues must be thoroughly addressed for this manuscript to be solid.

    1. Asymmetry detected by scRNA seq vs. imaging may not represent the same phenomenon, thus should not be discussed as two supporting pieces of evidence for the authors' model, and importantly each method has its own flaw. First, for scRNA seq, when cells become already egl-1 positive, those cells may be already dying, and thus NuRD complex's transcripts' asymmetry may not have any significance. The data presented in FigS1D, E show that there are lots of genes (6487 out of 8624) that are decreased in dying cells. Thus, it is not convincing to claim that NuRD asymmetry is regulated by differential RNA amount.

    2. Regarding NuRD protein's asymmetry, there are still multiple issues. Most likely explanation of their asymmetry is purely daughter size asymmetry. Because one cell is much bigger than the other (3 times larger), NuRD components, which are not chromatin associated, would be inherited to the bigger cell 3 times more than the smaller daughter. Then, upon nuclear envelope reformation, NuRD components will enter the nucleus, and there will be 3 times more NuRD components in the bigger daughter cell. It is possible that this is actually the underling mechanism to regulate gene expression differentially, but this possibility is not properly acknowledged. Currently, the authors use chromatin associated protein (Mys-1) as 'symmetric control', but this is not necessarily a fair comparison. For NuRD asymmetry to be meaningful, an example of protein is needed that is non-chromatin associated in mitosis, distributed to daughter cells proportional to daughter cell size, and re-enter nucleus after nuclear envelope formation to show symmetric distribution. And if daughter size asymmetry is the cause of NuRD asymmetry, other lineages that do not undergo apoptosis but exhibit daughter size asymmetry would also show NuRD asymmetry. The authors should comment on this (if such examples exist, it is fine in that in those cell types, NuRD asymmetry may be used for differential gene expression, not necessarily to induce cell death, but such comparison provides the explanation for NuRD asymmetry, and puts the authors finding in a better context).

    3. For the analysis of protein asymmetry between two daughters in Fig S4C, the method of calibration is unclear, making it difficult to interpret the results.

    4. As for pHluorin experiments, the authors were asked to test the changes in fluorescence observed are due to changes in pH or changes in the amount of pHluorin protein. They need to add a ratio-metric method in this manuscript. A brief mention to Page 12 line 12 is insufficient to clarify this issue.

    Major #2:

    Some issues surrounding statistics must be resolved.

    1. Fig. 1FG, 2D, 3BDEG, 5BD and 6B used either one-sample t-test or unpaired two-tailed parametric t-test for statistical comparison. These t-tests require a verification of each sample fitting to a normal distribution. The authors need to describe a statistical test used to verify a normal distribution of each sample.

    2. Fig. 2D, 3D, and 3G have very small sample size (N=3-4, N=6, N=3, respectively), it is possible that a normal distribution cannot be verified. How can the authors justify the use of one-sample t-test and unpaired parametric t-test ?

    3. Statistical comparison in Fig. 2D and Fig. 6B should be re-assessed. For Fig. 2D, the authors need to compare the intensity ratio of HDA-1/LIN53 between sister cells dying within 35 min and those over 400 min. For Fig. 6B, they need to compare the intensity ratio of VHA-17 between DMSO- and BafA1- treated cells at the same time point after anaphase.

  13. Version published to 10.1101/2023.06.25.546476v2 on bioRxiv
  14. Version published to 10.7554/elife.89032.1 on eLife
  15. eLife

    eLife assessment

    The authors propose that the asymmetric segregation of the NuRD complex in C. elegans is regulated in a V-ATPase-dependent manner, that this plays a crucial role in determining the differential expression of the apoptosis activator egl-1 and that it is therefore critical for the life/death fate decision in this species. The proposed model is interesting and the work could be important if proven correct. However, the current evidence is inadequate to support the major claims.

  16. eLife

    Joint Public Review:

    Throughout the study, there is insufficient information about how experiments were performed and how often (imaging, pull-downs etc), how data was acquired, modified and analysed (especially imaging data, see below), how statistical analyses were done and what is presented in the figures (single planes or maximum intensity projections etc). This makes it difficult to evaluate the data and results.

    There is insufficient information about tools and reporters used. This is misleading and impacts the conclusions that can be made from the results presented. To give an example, in Figure 1D-F, the authors present data that HDA-1::GFP and LIN-53::mNeonGreen (both components of the nucleosome remodeling and deacetylation complex) but not the histone acetyltransferase MYS-1::GFP are 'asymmetrically segregated' during QR.a division. However, the authors do not mention that HDA-1::GFP and LIN-53::mNeonGreen are expressed at endogenous levels (they are CRISPR alleles) whereas MYS-1::GFP is overexpressed (integration of a multi-copy extrachromosomal array). The difference in 'segregation' could therefore be a consequence of different levels of expression rather than different modes of segregation ('asymmetric' versus 'symmetric').

    There is insufficient information about the phenotypes of the animals used (RNAi knock-downs of hda-1, lin-53 RNAi, pig-1 etc). Again this is misleading and impacts the conclusions that can be made. To give some examples, (1) in Figure 3A-G, control RNAi embryos are compared to hda-1 RNAi and lin-53 RNAi embryos. What the authors do not mention is that hda-1 RNAi and lin-53 RNAi embryos have severe developmental defects and essentially cannot be compared to control RNAi embryos. The differences between the embryos can be seen in Figure S7B where bright-field images of control RNAi, hda-1 RNAi and lin-53 RNAi embryos are shown. At the 350 min time point, a normal embryo is visible for the control, a 'ball of cells' embryo for hda-1 RNAi and an embryo that seems to have arrested at an earlier developmental stage (and therefore have much larger cells) for lin-53 RNAi. Because of these pleiotropic phenotypes, it is unclear whether differences seen for example in sAnxV::GFP positive cells (Figure 3A) are the result of a direct effect of hda-1(RNAi) on cell death or whether they are the result of global changes in development and cell fate induced by hda-1(RNAi). hda-1(RNAi) and lin-53(RNAi) embryos are also used for the data shown in Figures S6 and S7, raising the same concerns; (2) the authors do not mention what the impact of Baf A1 treatment is on animals; however, the images provided in Figure 5E indicate that Baf A1 treatment causes pleiotropic effects in L1 larvae.

    There is a lack of adequate controls. Because of this, some of the data presented must be considered as preliminary. To give some examples: (1) controls are lacking for the data shown in Figure 3D-G (i.e. genes other than egl-1). Since hda-1 RNAi has a pleiotropic effect and most likely affects H3K27 acetylation genome-wide, this is critical. Based on what is shown, it is unclear whether the results presented are specific to egl-1 or not; (2) the co-IP and mass spec data shown in Figure 4A, C and Figure S8 also lack a critical control, which is GFP only. Because of this, it is unclear whether subunits of the V-ATPase bind to HDA-1 or GFP. The co-IP and mass spec data forms the basis of Figures 5 and 6 as well as Figure S9. Data presented in these figures therefore has to be considered preliminary as well.

    Inappropriate methods are used. For this reason, some of the data again must be considered preliminary. To give some examples: (1) in Figure 5A, B, the authors used super-ecliptic pHluorin to look at changes in pH in the daughter cells. However, the authors used quenching of super-ecliptic pHluorin fluorescence rather than a ratio-metric method to 'measure' changes in pH. Because of this, it is unclear whether the changes in fluorescence observed are due to changes in pH or changes in the amount of pHluorin protein. Figure 5A, B forms the basis for the experiments presented in the remaining parts of Figure 5 as well as in Figure 6 and Figure S9; (2) the authors' description of how some images were modified before quantitative analysis raises concerns. The figures of concern are particularly Figure 1 and Figure S4, where background subtraction with denoising and deconvolution was used. Background subtraction, with denoising and deconvolution is an image manipulation that enhances the contrast between background and what looks like foreground. Therefore, background subtraction should be applied primarily in experiments involving image segmentation not fluorescence intensity measurement. Not being provided any information by the authors about the kind of subtraction that was made, this processing could lead to an uneven subtraction across the image, which can easily lead to artefacts. Since the fluorescence intensity in the smaller daughter cell is lower, and thus closer to background, the algorithm the authors used may have misinterpreted the grey value information in the smaller daughter cell pixels. This could have led to an asymmetric subtraction of background in the two daughter cells, leading to a stronger subtraction in the smaller daughter cell. Ultimately, their processing could have artificially increased the intensity asymmetry between the two daughter cells in all their results.

    The imaging data is of low quality (for example Figures 1, 2, 5, 6; Figures S2, S3, S5, S6, S9). Since much of the study and the findings are based on imaging, this is a major concern. Critical parameters are not mentioned (number of sections in z-stack, size of the field-of-view, laser power used etc), which makes it difficult to understand what was done and what one is looking at. To give some specific examples, (1) the images shown in Figure 2B are of very low quality with severe background from neighbouring cells. In addition, the outline of the cells (plasma membrane) or the nuclei of the daughter cells is unknown. Based on this it is not clear how the authors could have measured 'Fluorescence intensity ratio between sister nuclei' in an accurate and unbiased way (what is clear from these images is that there is an increase in HDA-1::GFP signal in ALL surviving daughters (asymmetric and symmetric divisions) post cytokinesis but not in the daughter cell that is about to die (asymmetric and unequal division); (2) the images in Figure 6A and Figure S9A on VHA-17 segregation and its colocalization to ER and lysosome segregation during QR.a division are of very low quality and it is unclear to the reviewer how such images were used to obtain the quantitative data shown.

    In some cases, there is a discrepancy between what is shown in figures and what the authors state in the text. To give some examples: (1) on page 7, the authors state "..., we found that nuclear HDA-1 or LIN-53 asymmetry gradually increased from 1.1-fold at the onset of anaphase to 1.5 or 1.8-fold at cytokinesis, respectively (Figure 1D-E)." Looking at the images for HDA-1 and LIN-53 in Figure 1D, the increase in the ratio mainly occurs between 4 min and 6 min, which is post cytokinesis and NOT prior to cytokinesis; (2) these images (Figure 1D) also show that there is an increase in the HDA-1 and LIN-53 signals in the larger daughter cells (QR.ap), which suggests that the increase in ratios (Figure 1E) is the result of increased HDA-1 and LIN-53 synthesis post cytokinesis. However, on top of page 8, the authors state "The total fluorescence of HDA-1, LIN-53 and MYS-1 remained constant during ACDs, suggesting that protein redistribution may establish NuRD asymmetry (Figure S4C)." In Figure S4C, the authors present straight lines for 'relative total fluorescence' for imaging (probably z-stacks) that was done every min over the course of 7 min. If there was no increase in material as the authors claim, they should have seen significant photobleaching over the course of the 7 min and therefore reduced level of 'relative total fluorescence' over time. How the data presented in Figure S4C was generated is therefore unclear. (Despite the fact that the authors claim that the asymmetry seen is not due to new synthesis in the larger daughter cell post cytokinesis, it would be more consistent with the first experiment presented in this study (Figure S1) that shows that there is more hda-1 mRNA in egl-1(-) cells compared to egl-1(+) cells); (3) On page 12, the authors state "..., in Baf A1-treated animals, QRaa inherited similar levels of HDA-1::GFP as its sister cell,...". However, looking at the image provided in Figure 5E (0 min), there seems to be a similar ratio of HDA-1::GFP between the daughter cells in DMSO and Baf A1-treated animals.

  17. Version published to 10.1101/2023.06.25.546476v1 on bioRxiv