<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Freire-Zapata V</submitter><funding>NSF | Directorate for Biological Sciences (BIO)</funding><funding>DOE | SC | Biological and Environmental Research</funding><funding>DOE | SC | Biological and Environmental Research (BER)</funding><funding>NSF | Directorate for Biological Sciences</funding><pagination>2892-2908</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11522005</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>9(11)</volume><pubmed_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 mod</pubmed_abstract><journal>Nature microbiology</journal><pubmed_title>Microbiome-metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient.</pubmed_title><pmcid>PMC11522005</pmcid><funding_grant_id>2022070</funding_grant_id><funding_grant_id>DE-SC0021349</funding_grant_id><pubmed_authors>Ibba M</pubmed_authors><pubmed_authors>Saleska SR</pubmed_authors><pubmed_authors>EMERGE 2012 Field Team</pubmed_authors><pubmed_authors>Fahnestock MF</pubmed_authors><pubmed_authors>Holland-Moritz H</pubmed_authors><pubmed_authors>Tfaily MM</pubmed_authors><pubmed_authors>Wilson RM</pubmed_authors><pubmed_authors>Cronin DR</pubmed_authors><pubmed_authors>Hodgkins SB</pubmed_authors><pubmed_authors>Varner RK</pubmed_authors><pubmed_authors>Aroney S</pubmed_authors><pubmed_authors>Mondav R</pubmed_authors><pubmed_authors>Ernakovich JG</pubmed_authors><pubmed_authors>EMERGE Biology Integration Coordinators</pubmed_authors><pubmed_authors>Smith DA</pubmed_authors><pubmed_authors>Ferriere R</pubmed_authors><pubmed_authors>Zayed AA</pubmed_authors><pubmed_authors>Woodcroft BJ</pubmed_authors><pubmed_authors>Bagby SC</pubmed_authors><pubmed_authors>Freire-Zapata V</pubmed_authors><pubmed_authors>Rich VI</pubmed_authors><pubmed_authors>E Cross J</pubmed_authors><pubmed_authors>Sullivan MB</pubmed_authors><pubmed_authors>Stegen JC</pubmed_authors></additional><is_claimable>false</is_claimable><name>Microbiome-metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient.</name><description>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 mod</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Nov</publication><modification>2026-06-02T06:17:28.366Z</modification><creation>2025-04-04T09:58:50.02Z</creation></dates><accession>S-EPMC11522005</accession><cross_references><pubmed>39354152</pubmed><doi>10.1038/s41564-024-01800-z</doi></cross_references></HashMap>