Strain level and comprehensive microbiome analysis in inflammatory bowel disease via multi-technology meta-analysis identifies key bacterial influencers of disease
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Date
2022
Authors
Ravichandar, Jayamary Divya
Rutherford, Erica
Chow, Cheryl-Emiliane T.
Han, Andrew
Yamamoto, Mitsuko Lynn
Narayan, Nicole R.
Kaplan, Gilaad G.
Beck, Paul L.
Claesson, Marcus J.
Dabbagh, Karim
Journal Title
Journal ISSN
Volume Title
Publisher
Frontiers Media S.A.
Published Version
Abstract
Inflammatory bowel disease (IBD) is a heterogenous disease in which 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, precise identification of the bacteria implicated in IBD across cohorts is necessary.
We sought to take advantage of the numerous and diverse studies characterizing the microbiome in IBD to develop a 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, mapping all nucleotide data against known, culturable strain reference data.
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 patients with IBD, 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 reveals that not all significant strain associations resulted in a corresponding species-level significance and conversely significant species associations are not always re-captured at the strain level.
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.
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Keywords
Meta-analysis , Gut microbiome , Inflammatory bowel disease , Metagenomics , 16S rRNA , Strain
Citation
Ravichandar, J. D., Rutherford, E., Chow, C-E T., Han, A., Yamamoto, M. L., Narayan, N. R., Kaplan, G. G., Beck, P. L.; Claesson, M. J., Dabbagh, K., Iwai, S. and DeSantis, T. Z. (2022) 'Strain level and comprehensive microbiome analysis in inflammatory bowel disease via multi-technology meta-analysis identifies key bacterial influencers of disease', Frontiers In Microbiology, 13, (20pp). doi: 10.3389/fmicb.2022.961020