Ulcerative colitis (UC) is driven by disruptions in host-microbiota homeostasis, however current treatments exclusively target host inflammatory pathways. To understand how host-microbiota interactions become disrupted in UC, we collected and analyzed six fecal or serum based –omic datasets (metaproteomic, metabolomic, metagenomic, metapeptidomic, and amplicon sequencing profiles of fecal samples and proteomic profiles of serum samples) from 40 UC patients at a single inflammatory bowel disease centre, as well as various clinical, endoscopic, and histologic measures of disease activity. A validation cohort of 210 samples (73 UC, 117 Crohn’s disease (CD), 20 healthy controls) was collected and analyzed separately and independently. Data integration across both cohorts showed that a subset of the clinically active UC patients had an over-abundance of proteases that originated from the bacterium, Bacteroides vulgatus . To test whether B. vulgatus proteases contribute to UC disease activity, we first profiled B. vulgatus proteases found in patients and bacterial cultures. Use of a broad-spectrum protease inhibitor improved B. vulgatus -induced barrier dysfunction in vitro , and prevented colitis in B. vulgatus monocolonized, IL-10 deficient mice. Furthermore, transplantation of feces from UC patients with a high abundance of B. vulgatus proteases into germ-free mice induced colitis dependent on protease activity. These results, stemming from a multi-omics approach, improve understanding of functional microbiota alterations that drive UC and provides a resource for identifying other pathways that could be inhibited as a strategy to treat this disease.

Background Studies of the cystic fibrosis (CF) lung microbiome have consistently shown that lung function decline is associated with decreased microbial diversity due to the dominance of opportunistic pathogens. However, how this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood. Methods Here we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry to determine their interrelationships and associations with clinical measures of disease severity. Results The CF metabolome was found to exist in two states: one from patients with more severe disease that had higher molecular diversity and more Pseudomonas aeruginosa and the other from patients with better lung function having lower metabolite diversity and fewer pathogenic bacteria. The two molecular states were differentiated by the abundance and diversity of peptides and amino acids. Patients with severe disease and more pathogenic bacteria had higher levels of peptides. Analysis of the carboxyl terminal residues of these peptides indicated that neutrophil elastase and cathepsin G were responsible for their generation, and accordingly, these patients had higher levels of proteolytic activity from these enzymes in their sputum. The CF pathogen Pseudomonas aeruginosa was correlated with the abundance of amino acids and is known to primarily feed on them in the lung. Conclusions In cases of severe CF lung disease, proteolysis by host enzymes creates an amino acid-rich environment that P. aeruginosa comes to dominate, which may contribute to the pathogen’s persistence by providing its preferred carbon source. Electronic supplementary material The online version of this article (10.1186/s40168-019-0636-3) contains supplementary material, which is available to authorized users.

A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn’s disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual’s fecal microbiome associated with clinical consequences.