Metabolite discovery through global annotation of untargeted metabolomics data

Abstract A primary goal of metabolomics is to identify all biologically important metabolites. One powerful approach is liquid chromatography-high resolution mass spectrometry (LC-MS), yet most LC-MS peaks remain unidentified. Here, we present a global network optimization approach, NetID, to annota...

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Veröffentlicht in:bioRxiv
Hauptverfasser: Chen, Li, Lu, Wenyun, Wang, Lin, Xing, Xi, Teng, Xin, Zeng, Xianfeng, Dmuscarella, Antonio, Shen, Yihui, Cowan, Alexis, Mcreynolds, Melanie R, Kennedy, Brandon, Lato, Ashley M, Campagna, Shawn R, Singh, Mona, Rabinowitz, Joshua
Format: Paper
Sprache:Englisch
Veröffentlicht: Cold Spring Harbor Cold Spring Harbor Laboratory Press 06.01.2021
Cold Spring Harbor Laboratory
Ausgabe:1.2
Schlagworte:
Bioinformatics
Liquid chromatography
Mass spectroscopy
Metabolites
Metabolomics
Optimization
Taurine
Thiamine
ISSN:2692-8205, 2692-8205
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Zusammenfassung:Abstract A primary goal of metabolomics is to identify all biologically important metabolites. One powerful approach is liquid chromatography-high resolution mass spectrometry (LC-MS), yet most LC-MS peaks remain unidentified. Here, we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. We consider all experimentally observed ion peaks together, and assign annotations to all of them simultaneously so as to maximize a score that considers properties of peaks (known masses, retention times, MS/MS fragmentation patterns) as well network constraints that arise based on mass difference between peaks. Global optimization results in accurate peak assignment and trackable peak-peak relationships. Applying this approach to yeast and mouse data, we identify a half-dozen novel metabolites, including thiamine and taurine derivatives. Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to annotate untargeted metabolomics data, revealing novel metabolites. Competing Interest Statement The authors have declared no competing interest.
Bibliographie:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
Competing Interest Statement: The authors have declared no competing interest.
ISSN:2692-8205
2692-8205
DOI:10.1101/2021.01.06.425569