Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences.

ABSTRACT: Microbial community metabolomics, particularly in the human gut, are beginning to provide a new route to identify functions and ecology disrupted in disease. However, these data can be costly and difficult to obtain at scale, while amplicon or shotgun metagenomic sequencing data are readily available for populations of many thousands. Here, we describe a computational approach to predict potentially unobserved metabolites in new microbial communities, given a model trained on paired metabolomes and metagenomes from the environment of interest. Focusing on two independent human gut microbiome datasets, we demonstrate that our framework successfully recovers community metabolic trends for more than 50% of associated metabolites. Similar accuracy is maintained using amplicon profiles of coral

SUBMITTER: Mallick H 

PROVIDER: S-EPMC6637180 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature