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Hoffmann, M.A.* ; Nothias, L.F.* ; Ludwig, M.* ; Fleischauer, M.* ; Gentry, E.C.* ; Witting, M. ; Dorrestein, P.C.* ; Dührkop, K.* ; Böcker, S.*

High-confidence structural annotation of metabolites absent from spectral libraries.

Nat. Biotechnol. 40, 411–421 (2021)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but, typically, only a small fraction of spectra can be matched. Previous in silico methods search in structure databases but cannot distinguish between correct and incorrect annotations. Here we introduce the COSMIC workflow that combines in silico structure database generation and annotation with a confidence score consisting of kernel density P value estimation and a support vector machine with enforced directionality of features. On diverse datasets, COSMIC annotates a substantial number of hits at low false discovery rates and outperforms spectral library search. To demonstrate that COSMIC can annotate structures never reported before, we annotated 12 natural bile acids. The annotation of nine structures was confirmed by manual evaluation and two structures using synthetic standards. In human samples, we annotated and manually validated 315 molecular structures currently absent from the Human Metabolome Database. Application of COSMIC to data from 17,400 metabolomics experiments led to 1,715 high-confidence structural annotations that were absent from spectral libraries.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Molecular-structure Databases; Tandem Mass-spectra; High-fat Diet; Peptide Identification; Metabolomics Data; Ms/ms Spectra; Proteomics; Acid; Discovery; Fragmentation
Sprache englisch
Veröffentlichungsjahr 2021
HGF-Berichtsjahr 2021
ISSN (print) / ISBN 1087-0156
e-ISSN 1546-1696
Zeitschrift Nature Biotechnology
Quellenangaben Band: 40, Heft: 3, Seiten: 411–421 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Verlagsort New York, NY
Begutachtungsstatus Peer reviewed
Institut(e) CF Metabolomics & Proteomics (CF-MPC)
POF Topic(s) 30203 - Molecular Targets and Therapies
30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505700-001
A-630710-001
Förderungen NIGMS NIH HHS
NCI NIH HHS
U.S. Department of Health & Human Services | National Institutes of Health (NIH)
Gordon and Betty Moore Foundation (Gordon E. and Betty I. Moore Foundation)
DOI 10.1038/s41587-021-01045-9
WOS ID WOS:000769954200024
WOS ID WOS:000707299300001
Scopus ID 85117243101
PubMed ID 34650271
Erfassungsdatum 2021-12-02
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