4.8 Article

Genomic structure predicts metabolite dynamics in microbial communities

期刊

CELL
卷 185, 期 3, 页码 530-+

出版社

CELL PRESS
DOI: 10.1016/j.cell.2021.12.036

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资金

  1. National Science Foundation Division of Emerging Frontiers [EF 2025293, EF 2025521]
  2. National Science Foundation Physics Frontiers Center Program [PHY 0822613, PHY 1430124]
  3. James S. McDonnell Foundation [220020499]
  4. Simons Foundation Investigator Award [597491]

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The metabolic activities of microbial communities are crucial for the evolution and persistence of life on Earth. This study shows that the dynamics of metabolites in a community can be predicted based on the genes possessed by each member of the community, providing insights into how genome evolution impacts metabolism.
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 metabolite dynamics, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.

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