Peer review of: Widespread protein lysine acetylation in gut microbiome and its alterations in patients with (2020)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
This paper is novel for presenting a large-scale look at human intestinal microbiome (in situ colonic 
mucosal wash) protein modification (K-Ac), which is an important frontier issue in microbiome 
ecology. The data is analyzed to describe microbial composition and taxon-associated gene state in 
this microbiome compartment for a set of control adults, and in a comparison of pediatric 
endoscopic patients nominally Crohn's disease or control. The technical pipeline is state of art, and 
overall it provides a number of interesting observations. 
 
There are a few limitations of this study. 
 
Major 
1. The paper implies that Kac-modification is highlighting representation of organisms and their 
functions that cannot be observed by straight metaproteomics. However, it is possible that these 
features are concordant with whole metaproteomics, with just additional incremental change when 
the Kac subset is assessed. That is, the Kac changes are mainly reflecting simply the underlying 
shift in the microbiome composition and function, rather than something special about the Kac 
subset. This possibility is supported by the observation that many of the same differential 
organisms and genes reported in the literature by metagenomics and metatranscriptomics in the 
normal microbiome, or in healthy vs. IBD, are also reported here using the Kac subset. 
This really should be addressed and clarified, to provide context on what is being gained by Kac 
analysis. (a) A way to analytically do this is to provide description and comparisons first using the 
all-peptide metaproteomics data for taxon and gene representation. This analysis would provide 
context for the present dataset. (b) And/or, in the discussion the authors could systemically 
tabulate the Kac subset findings compare for how these compare to the metaproteomics (or 
metagenomics and metatranscriptomics )literature for controls and disease/healthy comparisons. 
As presented, it is possible that the differential Kac features may simply can't tell whether Kac 
fraction is telling us 
 
 
Technical 
2. The statistics are can be better presented. The paper presents many types of data processing 
and statistical methods, but these aren't justified (why the particular method is most suitable or 
even appropriate?): paired T-test (line 184 for F/B ratio- is this normally distributed data?), 
hypergeometric test (line 191, for COG distribution among Kac vs. unmodified data); PLS-DA (line 
227, for patient/control comparisons. And in some cases, the particular analytic question and how 
it was analyzed was unclear (e.g., Mann-Whitney in line 292, referring to a list of features and 
hence uncertain comparisons of microbial taxa, gene sets, and subject subsets). A section in 
methods or supplemental information can be used to provide rationale/justification for the 
analytics, and more clarity where needed in the results-findings regarding statistics used. 
 
3. Down-regulated genes in CD (p. 10, para. starting with 238). It refers to "upregulated" genes, 
but it seems that these should be termed "down-regulated" 
 
 
 
Reviewer #2: 
Remarks to the Author: 
This manuscript outlines a detailed study of the level and nature of protein lysine acetylation in the 
human microbiome. The authors utilize an anti-acetyl-lysine (Kac) antibody enrichment strategy 
and tandem mass spectrometry approach to identify 35,200 Kac peptides corresponding to 31,821 
Kac sites from the microbial or host 27 proteins in human gut microbiome samples. They conduct 
a detailed functional analysis on the protein types, and then apply this approach to the analysis of 

Editorial Note: Parts of this Peer Review File have been redacted as indicated to maintain patient confidentiality. pediatric Crohn’s 31 disease (CD) patient microbiome, where they identified 52 host and 136 
microbial protein Kac sites that 32 were differentially abundant in CD versus controls. 
 
In general, this manuscript is well-written and logically designed. The technical approach is sound 
and systematic. However, there are some fairly serious issues that reduce enthusiasm, as listed 
below: 
 
1. The title strongly suggests that this manuscript is primarily a “methods paper,” as there is really 
no description of why acetylation could be important in disease? While this is okay, the authors 
might consider revising to better define a “science message” if one is available. 
 
2. Abstract (line 25) and Introduction - of all the possible PTMs, why focus on acetylation? The 
rationale is very weak and vague, which diminishes the overall impact of the study. Are there 
expectations that more or less acetylation is associated with disease somehow? 
 
3. Line 98 – the authors should discuss the rationale for using the integrated gut microbial gene 
catalog vs. a matched assembled metagenome of the exact samples should be discussed and 
defended. How do the authors know that the gene catalog adequately reflects the exact nature 
and identify of the microbiota in their patients, especially the diseased cohort? 
 
4. Line 114 – the observation of only 6 Kac peptides common in the enrichment compared to the 
117 observed in the metaproteome is confusing and concerning. This issue is revisited on line 363, 
where the authors suggest that Kac peptides in the unenriched samples are likely false 
identifications. This is confusing and raises serious concerns with respect to false positive control in 
the other samples, and whether many of those might be false as well? 
 
5. Line 117 – it seems a bit surprising that 80% of all protein groups have acetylation – was this 
expected? In light of the point above, this raises issue about false positives here again? 
 
6. Line 156 – Do the authors suspect that the highest number of acetylation sites simply reflect 
the fact that Firmicutes and Bacteroidetes are simply the most abundant? In that case, acetylation 
might not be related to microbiome condition. 
 
7. Line 216 – is there a basis to expect protein acetylation to be important in CD patients? Why 
this particular focus group? What will the “differences” mean? Line 383 provides some speculation, 
but even this linkage is quite vague and suspect. 
 
8. The general outcome of this work is a broad and descriptive summary of protein acetylation, but 
delivers minimal biological value about what these differences mean? 
 
9. Line 417 – One of the most concerning and unsettling aspects of this study is the sample 
cohort. The number of patients are low but not unacceptable for such a study. The most serious 
concern is that protein acetylation is known to be dynamic and thus temporal aspects are critical 
here. The use of only one sample per patient makes this study without context – how do the 
authors know that collection of samples from the same patients at another time-point wouldn’t 
produce dramatically different results. This could be especially true in the diseased patients. This 
study would have been more meaningful if the authors had conducted multiple time-point 
measurements on a more limited number of the samples. 
 
 
 
Reviewer #3: 
Remarks to the Author: 
In this manuscript, Zhang and colleagues have performed a characterization of the acetylation 
sites present in metaproteomic samples, including changes occurring in IBD patients. They have 

identified on the order of 30,000 acetylation sites in bacterial proteins, which they have mapped to 
bacterial taxonomic diversity and protein functional annotations. As expected, most acetylation 
maps to proteins that relate to translation and metabolism. Interestingly, by performing also a 
separate proteomic analysis the authors could determinate the ratio of acetylated vs. non-modified 
peptides for different taxonomic groups. Finally, they analysed a small number of IBD patients and 
controls and performed a proof-of-principle analysis of how acetylation changes in the microbial 
samples of these patients. I think the number of samples is too low but serves as a useful test 
case application. The large number of acetylation sites identified in the study serves as potential 
exciting resource to study protein regulation by acetylation. However, the authors don’t really 
make an effort of exploring this resource. The taxonomic differences in ratio of proteome 
acetylation is an interesting aspect that is mentioned mostly in discussion but it seems to be the 
most interesting result of the manuscript and could be better analysed. As it currently stands, the 
manuscript is mostly a quick description of acetylation patterns and does not go very far in novel 
discoveries. 
 
Major concerns 
 
The authors have identified what it is likely to be the largest collection of microbial acetylation 
sites to date. However, very little is done with this resource beyond a brief description of the 
taxonomic diversity and biological processes connected with these peptides. Understanding how 
most of the acetylation regulates protein activity is an important open question and this resource 
could be a fantastic opportunity to study this problem. The authors should provide some examples 
of how this could be achieved to motivate others to explore this great resource they have 
generated. For acetylated sites that match proteins that exist across many bacterial genomes the 
authors could align the protein sequences and map the acetylation sites to the alignment in order 
to study regions that are often acetylated across a large number of proteomes/species. For a 
number of these, there will be structural models that can serve as homology templates to study 
the structural impact of mapped acetylation sites. Since many of these will be in metabolic 
enzymes there should be many enzymes that are present in many different species and a number 
of structural models available to represent these enzymes. For example, the authors could ask if 
acetylation sites are often near catalytic residues for example. 
 
In my opinion, the most interesting aspect of the results presented were the potential differences 
in ratio of acetylated vs non-modified peptides along the taxonomic diversity studied. The authors 
speculated that this differences in ratios could be due to metabolic differences with some species 
being known producers of acetate. Acetate can be converted to acetyl-phosphate in some species 
which can in turn directly chemically acetylate proteins (Weinert et al. Mol Cell 2013). The authors 
could try to further analyse this association using isolate genomes or very complete metagenomic 
assembled genomes. Can the authors find a relationship between the enzymes encoded in the 
genomes of some of the taxonomic groups and their ratios of acetylated vs non-modified peptides 
? 
 
Minor 
The authors need to make available in supplementary material the list of identified peptides with 
MS relevant associated statistics in a way that can facilitate their further analysis. 
 
The motif analysis of acetylated peptides could be relegated to supplementary information or 
shown briefly as an additional panel in Figure 1. 
 
The IBD results serve as an interesting proof-of-principle but the sample sizes are not large 
enough to identify variations that may still be meaningful. This should be addressed in the 
discussion. Figure 6 could as well be moved to supplementary and significant differences indicated 
in Figure 5.