Vacuolar H+-ATPase Determines Daughter Cell Fates through Asymmetric Segregation of the Nucleosome Remodeling and Deacetylase Complex

  1. Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua University, Beijing, China
  2. State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; Beijing 100101, China; University of Chinese Academy of Sciences; Beijing 100049, China
  3. School of Medicine, Tsinghua University; Beijing, China

Peer review process

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.

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Editors

  • Reviewing Editor
    Yukiko Yamashita
    Whitehead Institute/MIT, Cambridge, United States of America
  • Senior Editor
    Kevin Struhl
    Harvard Medical School, Boston, United States of America

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.

  1. Howard Hughes Medical Institute
  2. Wellcome Trust
  3. Max-Planck-Gesellschaft
  4. Knut and Alice Wallenberg Foundation