Computational Approaches for Sequence Guided Metagenome Mining of Small Molecules in the Human Microbiome

Abstract

A quantitative analysis of small molecule biosynthesis in the human microbiome identifies disease-specific features

Changes in the composition of the human gut microbiome have been correlated with several human diseases, but the molecular details underlying these correlations remain largely unknown. Here, we devise a general approach for the identification of microbiome-derived small molecules that are enriched in specific diseases. By applying this approach to Inflammatory Bowel Diseases, we discover novel Clostridium-derived biosynthetic gene clusters of which are significantly and specifically enriched in the microbiome of Crohn's Disease (CD) patients, and expressed under disease conditions. Identifying disease-specific microbiome-derived small molecules will not only reveal mechanisms of disease elicitation and progression, but will also provide new venues for therapeutic intervention.

A metagenomic strategy for harnessing the chemical repertoire of the human microbiome

Remarkable progress has been made in determining the effects of the microbiome on human physiology and disease, but the underlying molecules and mechanisms governing these effects remain largely unexplored. Here, we develop a new computational algorithm to discover biologically active small molecules encoded directly in human microbiome-derived metagenomic sequencing data. We discover members of a clinically used class of molecules that were never reported before are widely encoded in the human microbiome. Our approach paves the way towards a systematic unveiling of the chemical repertoire encoded by the human microbiome, and provides a generalizable platform for discovering molecular mediators of microbiome-host interactions.