Peer review of: Identifying proteins bound to native mitotic ESC chromosomes reveals chromatin repressors are i (2020)


RR2
 REVIEWERS' COMMENTS:
Reviewer #1 (Remarks to the Author):
Reviewer #2 (Remarks to the Author):
  The authors have addressed the most important concerns I had raised. The paper is now
 substantially improved and, in my opinion, should be published
  After reviewing the revised manuscript, we find that the authors have extensively revised the
 manuscript to address the major concerns we have raised in the initial review.
 1. To our concern that their multistage isolation process might drastically change the composition
 of mitotic chromosomes, they provided a comparison (reviewer fig only) to two other similar
 studies, stating that majority of proteins enriched are shared. Further they validated their results
 They also did an ATAC-seq showing that accessibility is maintained. Furthermore, they performed
 mitotic chromosome isolation x-lined with DSG and followed by MS and no significant differences
 are detected between their native and DGS-xlink proteome (reviewer fig only – for reviewer #1).
 These new experiments have satisfied our initial concern.
 by performing live imaging of 4 proteins from their data set (however Esrrb was done previously).
 2. Furthermore, the authors repeated the measurements of chromosomes and centromeres using
 FISH and chromosome spreading and got similar results, although centromere size seems to be
 more controlled than average chromosome size (Fig 2D). They also provide explanation for their
 “puffy/blobby” look of chromosomes stating that a) immobilization of native chromosome might
 cause that look b) providing cryo-ET and super-resolution optical microscopy image which shows
 quite blobby look.
 3. They added the missing reference to Ohta 2010 study. They also provided us the figure where
 they compare localisation of detected proteins and saying that >80% of their enriched proteins are
 annotated as the nuclear, whereas Ohta et al., had only ~40% of nuclear proteins. This suggest
 that they are getting more pure chromosomes then previous studies.
 4. They revised the manuscript by downplaying bookmarking by TFs and more focusing on
 maintaining the chromatin condensation and discussing the possibility of maintaining tx programs
 by repression.
 Taken together, the authors addressed our comments in a satisfactory way.
Reviewer #3 (Remarks to the Author):
  The authors have done a remarkable job addressing reviewer comments. I have no more
 comments except two very minor ones:
 1) The comparison of the author's data to previously published datasets shown in the rebuttal
 should be added to the supplemental materials.
 2) The different arrest times to obtain mitotic chromosomes for different cell types remains a
 confounding factor in chromosome size estimates and this should be mentioned as a caveat.

 Reviewer #4 (Remarks to the Author):
 I would like to thank the authors for theirs efforts on improving the manuscript based on reviewer
 comments. Originally, I had an impression that the manuscript is not focused on mitotic
 bookmarking as also stated by the authors in the rebuttal letter: „We did not intend to convey a
 singular focus on mitotic bookmarking and have edited the revised text accordingly (see revised
 introduction).“However, it seems that mitotic bookmarking is a very important finding of the
 study: „It is probably not that productive to discuss the advances made in our study versus the
 Ohta 2010 paper, but one major consideration is that we define the mitotic proteome of mouse
 ESCs, a widely used and fundamental tool for studies of stem cells and differentiation.“
 I am not convinced whether the permutation based FDR test used in this study is suitable to define
 „mitotic proteome“. Typically it is used to compare similar states and not very different states as
 mitotic proteome vs total proteome. In the figure S1C it is clear that mitotic proteome is different
 compared to total proteome, but defining a criteria which protein is significantly enriched/depleted
 and in turn is part of the mitotic proteome is not trivial in this experimental setup. I would suggest
 to avoid strong statements on the definition of "mitotic proteome" since it requires statistically
 more robust analysis and experimental set up combination.
 Regarding the comment on the MaxLFQ algorithm:“ The MaxLFQ algorithm exploits a proportion of
 the proteome which remains unchanged between samples for normalisation. However, this
 proportion does not have to encompass the majority of protein hits. The original publication
 introducing the MaxLFQ algorithm (Cox et al.,2014, Mol Cell Proteomics, 13, 2513) used ‘spike in’
 experiments to show the validity of the computational approach. In Fig 3a, a 1:1 mix of
 E.coli:H.sapiens was compared to a 3:1 mix (i.e. all proteins change in abundance). Mean protein
 ratios remained accurate in the MaxLFQ approach even in this scenario.“
 I would like to refer to the same publication (Cox et al., 2014, Mol Cell Proteomics, 13, 2513)and
 quote the authors suggesting that in 3:1 mix the situation is that not all proteins are changing, but
 based on their estimate only 31% are changing. „MaxLFQhas the prerequisite that a majority
 population of proteins exists that is not changing between the samples. How big this population
 needs to be and what the consequences are if the changing population becomes comparable in
 size to the non-changing one can be seen in the benchmark dataset itself, in which the changing
 (E. coli) population comprised 31% of the proteins measured in total. MaxLFQ still operated well
 under these circumstances.“
 It is surprising that only 11 proteins were specific to mitotic proteome. I would have expected
 many more chromatin specific proteins to be identified after removing large fraction of a
 „background“ proteome as also mentioned by the authors in the rebuttal letter: „purifying mitotic
 chromosomes may minimize ‘contamination‘“.
 Regarding the figure S1D, I would recommend to use the full protein list for hierarchical clustering
 instead of only comparing enriched and depleted protein datasets. I believe that most of the
 information is lost using this pre-filtering step.
 I find the comparisons (bar plot and venn diagram) between Gino et. al and this study informative
 and would suggest to add this to supplementary material. However, the four volcano plots
 provided in the rebuttal letter lack the description.