生物
代谢物
代谢组学
计算生物学
背景(考古学)
基因
生物地球化学循环
基因组
基因组学
进化生物学
生态学
遗传学
生物信息学
生物化学
古生物学
作者
Karna Gowda,Derek Ping,Madhav Mani,Seppe Kuehn
出处
期刊:Cell
[Elsevier]
日期:2022-02-01
卷期号:185 (3): 530-546.e25
被引量:75
标识
DOI:10.1016/j.cell.2021.12.036
摘要
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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