A searchable metadata network graph for microbiome metabolomics.
| Title: | A searchable metadata network graph for microbiome metabolomics. |
|---|---|
| Authors: | Charron-Lamoureux V; Xing S; Patan A; Walker C; Monter RA; Abiead YE; Zhao HN; Patel L; Weng Y; Gonzalez A; Ackermann G; Deleray V; Gandhi V; Mohanty I; Caraballo-Rodriguez AM; Kvitne KE; Zuffa S; Norman A; Martin A; Chin L; Paz-Gonzalez R; Sala-Climent M; Suryawinata N; Zemlin J; Gouda H; Hu Z; Norton G; Rajkumar P; Molina AJ; Bergstrom J; Pinner M; Giddings S; Aron AT; Liang L; Dahesh S; Lamichhane S; Reilly ER; Nizet V; Skrip A; Lukowski AL; Shore SFH; Ghoshal S; Engevik MA; Horvath TD; Renwick S; Agongo J; Marco ML; Mazmanian SK; Wang M; Yang H; McDonald D; Guma M; Stegmann E; Hernandez Perez N; Stincone P; Kemen E; Pakkir Shah AK; Bode L; Petras D; Siegel D; Raffatellu M; Patterson AD; Devkota S; Jinich A; Knight R; Zengler K; Dorrestein PC |
| Source: | BioRxiv : the preprint server for biology [bioRxiv] 2026 Feb 05. Date of Electronic Publication: 2026 Feb 05. |
| Publication Type: | Journal Article; Preprint |
| Language: | English |
| Journal Info: | Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| Abstract: | Establishing the biological context of microbial metabolites remains a major challenge. We present microbiomeMASST, a metadata-driven network graph that maps metabolites across 467 available datasets with 144,424 mass spectrometry files from humans, animals, and microbial culture systems. MicrobiomeMASST integrates monocultures, synthetic communities, and host-associated samples across multiple body sites and plants. MS/MS spectra can be queried to trace occurrence across hosts, experimental conditions, and interventions, enabling cross-study integration. We demonstrate this framework by contextualizing microbial-conjugated bile acids and interrogating microbiome-mediated drug metabolism. Screening gut bacteria revealed deprolylation of the angiotensin-converting enzyme (ACE) inhibitor prodrug enalapril. Using microbiomeMASST, we traced this metabolite across human cohorts, microbial isolates, environmental samples, and in Gorilla gorilla . Structural modeling and enzymatic assays showed that microbial deprolylation abolishes ACE inhibition, thereby inactivating its therapeutic effect. Together, microbiomeMASST links MS/MS spectra to biological context, converting isolated observations into an interpretable microbiome map for cross-study analysis. |
| Grant Information: | K99 ES037746 United States ES NIEHS NIH HHS; R35 ES035027 United States ES NIEHS NIH HHS |
| Entry Date(s): | Date Created: 20260212 Date Completed: 20260212 Latest Revision: 20260401 |
| Update Code: | 20260401 |
| PubMed Central ID: | PMC12889665 |
| DOI: | 10.64898/2026.02.04.703849 |
| PMID: | 41676651 |
| Database: | MEDLINE |
Journal Article; Preprint