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

Nat Commun 2019 07 17;10(1):3136. Epub 2019 Jul 17.

Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.

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-associated, murine gut, and human vaginal microbiomes. We also provide an expected performance score to guide application of the model in new samples. Our results thus demonstrate that this 'predictive metabolomic' approach can aid in experimental design and provide useful insights into the thousands of community profiles for which only metagenomes are currently available.

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Source
http://www.nature.com/articles/s41467-019-10927-1
Publisher Site
http://dx.doi.org/10.1038/s41467-019-10927-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637180PMC
July 2019
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