Lysine acetylation (Kac), an abundant post-translational modification (PTM) in prokaryotes, regulates various microbial metabolic pathways. However, no studies have examined protein Kac at the microbiome level, and it remains unknown whether Kac level is altered in patient microbiomes. Herein, we use a peptide immuno-affinity enrichment strategy coupled with mass spectrometry to characterize protein Kac in the microbiome, which successfully identifies 35,200 Kac peptides from microbial or human proteins in gut microbiome samples. We demonstrate that Kac is widely distributed in gut microbial metabolic pathways, including anaerobic fermentation to generate short-chain fatty acids. Applying to the analyses of microbiomes of patients with Crohn’s disease identifies 52 host and 136 microbial protein Kac sites that are differentially abundant in disease versus controls. This microbiome-wide acetylomic approach aids in advancing functional microbiome research.
The intestinal microbiome is emerging as an important organ within the human body that actively interacts with its host to influence human health. Dysbiosis of the intestinal microbiota has been reported to be associated with a myriad of diseases, including obesity, diabetes, Crohn’s disease (CD), cancer, and cardiovascular diseases. In the past few years, meta-omic approaches, including metagenomics, metatranscriptomics, and metaproteomics, have been applied to study the alterations of the microbiome composition and functions in patients with these diseases. However, very little is known of the regulatory processes in the microbiome, such as post-translational modifications (PTMs) that are known to regulate the activity of proteins. In fact, there are currently neither published studies on the global and deep characterization of PTMs in the human microbiome nor published techniques for efficient PTM profiling at the metaproteome level.
Acetylation is an important PTM in both Eukaryotes and Prokaryotes. In particular, lysine (Nε) acetylation (Kac) has been shown to be involved in the regulation of various biological processes, including transcription and metabolism. Compared with other PTMs that are commonly implicated in regulation of metabolic processes, such as phosphorylation, acetylation demonstrated higher levels in microorganisms. In bacteria, up to 40% of proteins can be acetylated, due to the presence of both enzymatic and nonenzymatic acetylation mechanisms. Protein Kac has been characterized in several single bacterial species, including Escherichia coli, Bacillus subtilis, Salmonella enterica, and Mycobacterium tuberculosis, and widely implicated in various microbial processes, including chemotaxis, nutrient metabolism, stress response, and virulence. In E. coli, the enzymatic activities in acetate metabolism were regulated by acetylation. On the other hand, metabolic intermediates of acetate metabolism, such as acetylphosphate and acetyl-CoA, can non-enzymatically acetylate metabolic enzymes or provide acetyl donor for enzymatic lysine acetylation. Therefore, microorganisms may evolve elegant mechanisms in regulating cellular metabolism through acetylation.
One of the most important metabolic functions of the gut microbiome is fermentation of indigestible dietary fibers to generate short-chain fatty acids (SCFAs). SCFAs can nourish the intestinal cells, maintain the acidic intestinal environment, and thereby protecting the intestinal barrier function. Accumulating evidence suggests that intestinal SCFAs and SCFA-producing bacteria at least partially mediate the complex host–microbiome interactions that underlie the development of many diseases, such as CD. Given the potential role of Kac in regulating SCFA metabolism, the study of Kac in human gut microbiome may aid in better understanding the role of gut microbiome in CD.
In this study, we first establish experimental and bioinformatic workflows for characterization of microbiome Kac. Briefly, an immuno-affinity-based approach is used for the enrichment of Kac peptides from the microbiome protein digests; the eluted peptides are analyzed with Orbitrap-based mass spectrometer (MS); and the MS data are then processed using an integrated metaproteomics/lysine acetylomics bioinformatic workflow that is developed in this study. In total, 35,200 Kac peptides corresponding to 31,821 Kac sites are identified from either human or microbial proteins. This study is a global characterization of Kac proteins in human microbiomes and achieves the highest number of site identifications in lysine acetylomic studies. We further apply the approach to study alterations of Kac in intestinal microbiomes of children with new-onset CD, which demonstrates the upregulation of Kac in host proteins, such as immune-related proteins, and downregulation of Kac in microbial proteins from the Firmicutes species that are known SCFA producers. This study provides an efficient workflow for studying lysine acetylome in the microbiomes, and our results provide additional information on the intestinal dysbiosis in pediatric CD.
Integrated gut metaproteomic/lysine acetylomic workflow
In this study, the proteolytic peptides generated from each microbiome sample were aliquoted for both metaproteomics and lysine acetylomics analysis. Kac peptides from the first aliquot were enriched using a seven-plex anti-Kac peptide antibody cocktail; the second aliquot was directly analyzed for metaproteome profiling. An integrative metaproteomics/lysine acetylomics data-processing workflow was then developed based on our previously established MetaPro-IQ workflow and MetaLab software tool. We, and others, have previously shown that the Integrated Gene Catalog (IGC) database performed similarly to the matched metagenome database for metaproteomic identification. Therefore, in this study, we used the IGC database for the identification of both metaproteomic and lysine acetylomic data sets. Briefly, each of the raw files was first searched against the IGC protein database using MetaLab; the parameters were as default, except that lysine acetylation (m/z 42.010565, HCO) was added as an additional variable modification. The sample-specific databases for both aliquots of all samples were then combined and concatenated with a human protein database for peptide/protein identification and quantification of both data sets.
Senior Scientist, CHEO Research Institute