A semi-tryptic peptide centric metaproteomic mining approach and its potential utility in capturing signatures of gut microbial proteolysis

Abstract

Abstract Background Proteolysis regulation allows gut microbes to respond rapidly to dynamic intestinal environments by fast degradation of misfolded proteins and activation of regulatory proteins. However, alterations of gut microbial proteolytic signatures under complex disease status such as inflammatory bowel disease (IBD, including Crohn’s disease (CD) and ulcerative colitis (UC)), have not been investigated. Metaproteomics holds the potential to investigate gut microbial proteolysis because semi-tryptic peptides mainly derive from endogenous proteolysis. Results We have developed a semi-tryptic peptide centric metaproteomic mining approach to obtain a snapshot of human gut microbial proteolysis signatures. This approach employed a comprehensive meta-database, two-step multiengine database search, and datasets with high-resolution fragmentation spectra to increase the confidence of semi-tryptic peptide identification. The approach was validated by discovering altered proteolysis signatures of Escherichia coli heat shock response. Utilizing two published large-scale metaproteomics datasets containing 623 metaproteomes from 447 fecal and 176 mucosal luminal interface (MLI) samples from IBD patients and healthy individuals, we obtain potential signatures of altered gut microbial proteolysis at taxonomic, functional, and cleavage site motif levels. The functional alterations mainly involved microbial carbohydrate transport and metabolism, oxidative stress, cell motility, protein synthesis, and maturation. Altered microbial proteolysis signatures of CD and UC mainly occurred in terminal ileum and descending colon, respectively. Microbial proteolysis patterns exhibited low correlations with β-diversity and moderate correlations with microbial protease and chaperones levels, respectively. Human protease inhibitors and immunoglobulins were mainly negatively associated with microbial proteolysis patterns, probably because of the inhibitory effects of these host factors on gut microbial proteolysis events. Conclusions This semi-tryptic peptide centric mining strategy offers a label-free approach to discover signatures of in vivo gut microbial proteolysis events if experimental conditions are well controlled. It can also capture in vitro proteolysis signatures to facilitate the evaluation and optimization of experimental conditions. Our findings highlight the complex and diverse proteolytic events of gut microbiome, providing a unique layer of information beyond taxonomic and proteomic abundance.