Gut microbial β-glucuronidases regulate host luminal proteases and are depleted in irritable bowel syndrome

Abstract

Intestinal proteases mediate digestion and immune signaling, while increased gut proteolytic activity disrupts the intestinal barrier and generates visceral hypersensitivity, which in common in irritable bowel syndrome (IBS). However, the mechanisms controlling protease function are unclear. Here we show that members of the gut microbiota suppress intestinal proteolytic activity through production of unconjugated bilirubin. This occurs via microbial β-glucuronidase-mediated conversion of bilirubin conjugates. Metagenomic analysis of fecal samples from patients with post-infection IBS (n=52) revealed an altered gut microbiota composition, in particular a reduction in Alistipes taxa, and high gut proteolytic activity driven by specific host serine proteases compared to controls. Germ-free mice showed 10-fold higher proteolytic activity compared with conventional mice. Colonization with microbiota from high proteolytic activity IBS patients failed to suppress proteolytic activity in germ-free mice, but suppression of proteolytic activity was achieved with colonization using microbiota from healthy donors. High proteolytic activity mice had higher intestinal permeability, a higher relative abundance of Bacteroides and a reduction in Alistipes taxa compared with low proteolytic activity mice. High proteolytic activity IBS patients had lower fecal β-glucuronidase activity and end-products of bilirubin deconjugation. Mice treated with unconjugated bilirubin and β-glucuronidase overexpressing E. coli , which significantly reduced proteolytic activity, while inhibitors of microbial β-glucuronidases increased proteolytic activity. Together, these data define a disease-relevant mechanism of host-microbial interaction that maintains protease homeostasis in the gut.

Benchmarking Differential Abundance Analysis Methods for Correlated Microbiome Sequencing Data

“…Differential abundance analysis is one of the most fundamental statistical tasks in microbiome data analysis. Given the rising popularity of complex study designs involving temporal 55 , spatial 56 , and repeated sampling 4 of the microbiome, statistical tools that could properly address the correlation structure in microbiome data are much needed. Although there are several tools for differential abundance analysis of correlated microbiome data (DAA-c) [26][27][28][29][36][37][38] , their performance has not been evaluated independently by a large-scale benchmarking study.…”

“…It is of great interest to study how the microbiome changes over time and its association with factors such as demographic and lifestyle characteristics, medical history, disease treatment, and various clinical outcomes. To answer these questions, longitudinal designs have been increasingly employed in microbiome studies 3,4 .…”

“…It is of great interest to study how the microbiome changes over time and its association with factors such as demographic and lifestyle characteristics, medical history, disease treatment, and various clinical outcomes. To answer these questions, longitudinal designs have been increasingly employed in microbiome studies 3,4 . Compared to case-control and cross-sectional microbiome studies, longitudinal studies, which repeatedly sample the microbiome over a course of time, provide unique opportunities to investigate the dynamics of the microbiome, decipher the species interaction network, and establish a potential causal relationship if the microbiome change precedes the phenotypic change 2 .…”

“…iHMP focuses on generating integrated longitudinal datasets and understanding how the microbiome impacts the disease course through a longitudinal view. Besides the longitudinal design, spatial and replicate sampling designs have also been frequently used in microbiome studies 2,4,6 . All these studies generate correlated microbiome data, where the microbiome composition profile derived from the same subject is more similar to each other than those derived from different subjects.…”

Understanding neuroimmune interactions in disorders of gut–brain interaction: from functional to immune-mediated disorders

“…87 88 Colonic infusion of faecal supernatant of patients with IBS in mice or application of biopsy supernatant on cell lines resulted in lower barrier function, indicating the involvement of luminal mediators. [90][91][92][93] The identity of these mediators is still unclear, but proteases, microbial products, food and bile acids are the main candidates (figure 4). Currently, most of the evidence supports a role for proteases.…”