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微生物组-代谢物关联驱动多年冻土解冻梯度上的温室气体动态。

Microbiome-metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient.

机构信息

Department of Environmental Science, The University of Arizona, Tucson, AZ, USA.

Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, USA.

出版信息

Nat Microbiol. 2024 Nov;9(11):2892-2908. doi: 10.1038/s41564-024-01800-z. Epub 2024 Oct 1.

DOI:10.1038/s41564-024-01800-z
PMID:39354152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11522005/
Abstract

Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This contradicts common assumptions in trait-based microbial models and highlights the limitations of measuring microbial community-level data alone. Furthermore, feature-scale analysis revealed connections between microbial taxa, metabolites and observed CO and CH porewater variations. Our study showcases insights gained by using feature-level data and microorganism-metabolite interactions to better understand metabolic processes that drive greenhouse gas emissions during ecosystem changes.

摘要

微生物组和代谢物之间的相互作用在环境中起着至关重要的作用，但这些相互作用如何在生态系统变化过程中驱动温室气体排放尚不清楚。在这里，我们使用基于群落组装理论的原则，通过配对的基因组解析宏基因组学和高分辨率傅里叶变换离子回旋共振质谱分析了瑞典 Stordalen 湿地的永冻层解冻梯度，以测试微生物和代谢物是否对变化的驱动因素表现出一致的响应。我们的分析揭示了推断的微生物与代谢物组装过程之间的分歧，这表明它们对相同的选择压力有不同的反应。这与基于特征的微生物模型中的常见假设相矛盾，突出了仅测量微生物群落水平数据的局限性。此外，特征尺度分析揭示了微生物分类群、代谢物和观察到的 CO 和 CH 孔隙水变化之间的联系。我们的研究展示了通过使用特征级数据和微生物-代谢物相互作用来更好地理解在生态系统变化过程中驱动温室气体排放的代谢过程所获得的见解。

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本文引用的文献

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