Genomic structure predicts metabolite dynamics in microbial communities
ORAL
Abstract
The metabolic activities of microbial communities play a defining role in the evolution and persistence of life on Earth, driving redox reactions that give rise to global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes, including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolite dynamics from genomes remains elusive. Here we show, for the process of denitrification, that metabolite dynamics of a community are predictable from the genes each member of the community possesses. A simple linear regression reveals a sparse and generalizable mapping from gene content to metabolite dynamics for genomically-diverse bacteria. A consumer-resource model correctly predicts community metabolite dynamics from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community function, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.
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Publication: https://www.biorxiv.org/content/10.1101/2020.09.29.315713v2
Presenters
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Karna Gowda
University of Chicago
Authors
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Karna Gowda
University of Chicago
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Derek J Ping
University of Illinois at Urbana-Champaign
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Madhav Mani
Northwestern University
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Seppe Kuehn
University of Chicago