학술논문

Enhancing untargeted metabolomics using metadata-based source annotation
Document Type
article
Author
Gauglitz, Julia MWest, Kiana ABittremieux, WoutWilliams, Candace LWeldon, Kelly CPanitchpakdi, MorganDi Ottavio, FrancescaAceves, Christine MBrown, ElizabethSikora, Nicole CJarmusch, Alan KMartino, CameronTripathi, AnupriyaMeehan, Michael JDorrestein, KathleenShaffer, Justin PCoras, RoxanaVargas, FernandoGoldasich, Lindsay DeRightSchwartz, TaraBryant, MacKenzieHumphrey, GregoryJohnson, Abigail JSpengler, KatharinaBelda-Ferre, PedroDiaz, EdgarMcDonald, DanielZhu, QiyunElijah, Emmanuel OWang, MingxunMarotz, ClarisseSprecher, Kate EVargas-Robles, DanielaWithrow, DanaAckermann, GailHerrera, LourdesBradford, Barry JMarques, Lucas Maciel MaurizAmaral, Juliano GeraldoSilva, Rodrigo MoreiraVeras, Flavio ProtasioCunha, Thiago MattarOliveira, Rene Donizeti RibeiroLouzada-Junior, PauloMills, Robert HPiotrowski, Paulina KServetas, Stephanie LDa Silva, Sandra MJones, Christina MLin, Nancy JLippa, Katrice AJackson, Scott ADaouk, Rima KaddurahGalasko, DouglasDulai, Parambir SKalashnikova, Tatyana IWittenberg, CurtTerkeltaub, RobertDoty, Megan MKim, Jae HRhee, Kyung EBeauchamp-Walters, JuliaWright, Kenneth PDominguez-Bello, Maria GloriaManary, MarkOliveira, Michelli FBoland, Brigid SLopes, Norberto PeporineGuma, MonicaSwafford, Austin DDutton, Rachel JKnight, RobDorrestein, Pieter C
Source
Nature Biotechnology. 40(12)
Subject
Medical Biochemistry and Metabolomics
Analytical Chemistry
Biomedical and Clinical Sciences
Chemical Sciences
Neurodegenerative
Neurosciences
Nutrition
Multiple Sclerosis
Brain Disorders
Humans
Tandem Mass Spectrometry
Metadata
Metabolomics
Language
Abstract
Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.