Strain level and comprehensive microbiome analysis in inflammatory bowel disease via multi-technology meta-analysis identifies key bacterial influencers of disease - Ravichandar, Jayamary Divya; Rutherford, Erica; Chow, Cheryl-Emiliane T.; Han, Andrew; Yamamoto, Mitsuko Lynn; Narayan, Nicole; Kaplan, Gilaad G.; Beck, Paul L.; Claesson, Marcus J.; Dabbagh, Karim; Iwai, Shoko; DeSantis, Todd Z. (Frontiers in Microbiology, 2022)
Objective Inflammatory bowel disease (IBD) is a heterogenous disease where the microbiome has been shown to play an important role. However, the precise homeostatic or pathological functions played by bacteria remain unclear. Most published studies report taxa-disease associations based on single-technology analysis of a single cohort, potentially biasing results to one clinical protocol, cohort and molecular analysis technology. To begin to address this key question, a precise identification of the bacteria implicated in IBD across cohorts is necessary. Methods We sought to take advantage of the numerous and diverse studies characterizing the microbiome in IBD to develop multi-technology meta-analysis (MTMA) as a platform for aggregation of independently-generated datasets, irrespective of DNA-profiling technique, in order to uncover the consistent microbial modulators of disease. We report the largest strain-level survey of IBD, integrating microbiome profiles from 3,407 samples from 21 datasets spanning 15 cohorts, three of which are presented for the first time in the current study, characterized using three DNA-profiling technologies. Results We identify several novel IBD associations with culturable strains that have so far remained elusive, including two genome-sequenced but uncharacterized Lachnospiraceae strains consistently decreased in both the gut luminal and mucosal contents of IBD patients, and demonstrate that these strains are correlated with inflammation related pathways that are known mechanisms targeted for treatment. Furthermore, comparative MTMA at the species versus strain-level demonstrates that strain-specificity, even within a species, is key to uncovering the potential involvement and roles played by microbes in disease. Conclusions We propose MTMA for uncovering experimentally-testable strain-disease associations that, as demonstrated here, are beneficial in discovering mechanisms underpinning microbiome impact on disease or novel targets for therapeutic interventions.