Genomic structure predicts metabolite dynamics in microbial communities
Genomic structure predicts metabolite dynamics in microbial communities
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DOI：
10.1016/j.cell.2021.12.036
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发表时间：
2022-02-03
期刊：
影响因子：
64.5
通讯作者：
Kuehn, Seppe
中科院分区：
文献类型：
--
作者：
Gowda, Karna;Ping, Derek;Kuehn, Seppe
微生物群落的代谢活动在地球上生命的进化和持久性中起着决定性的作用，推动氧化还原反应，从而产生全球生物地球化学循环。群落代谢是由基因表达、生态相互作用和环境因素等一系列过程组成的。在野生群落中，基因含量与环境背景相关，但从基因组预测代谢动力学仍然是难以捉摸的。在这里，我们表明，反硝化的过程中，代谢动力学的社区是可预测的基因，社区的每个成员拥有。一个简单的线性回归揭示了一个稀疏的和概括的映射基因组不同的细菌从基因含量代谢动力学。消费者资源模型正确预测社区代谢动力学从单菌株表型。我们的研究结果表明，代谢基因的保守影响可以预测社区代谢动力学，使代谢动力学预测从宏基因组，设计简化社区，并发现基因组进化如何影响代谢。
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.