| Literature DB >> 35798960 |
Julia M Gauglitz1,2, Kiana A West1,2, Wout Bittremieux1,2, Candace L Williams3, Kelly C Weldon1,2,4, Morgan Panitchpakdi1,2, Francesca Di Ottavio1, Christine M Aceves1,2, Elizabeth Brown2,5, Nicole C Sikora1,2, Alan K Jarmusch1,2, Cameron Martino4,6,7, Anupriya Tripathi2,5,6, Michael J Meehan1,2, Kathleen Dorrestein1,2, Justin P Shaffer6, Roxana Coras8, Fernando Vargas1,2,5, Lindsay DeRight Goldasich6, Tara Schwartz6, MacKenzie Bryant6, Gregory Humphrey6, Abigail J Johnson9, Katharina Spengler1, Pedro Belda-Ferre4,6, Edgar Diaz6, Daniel McDonald6, Qiyun Zhu6, Emmanuel O Elijah1,2, Mingxun Wang1,2, Clarisse Marotz6, Kate E Sprecher10,11, Daniela Vargas-Robles12, Dana Withrow10, Gail Ackermann6, Lourdes Herrera13, Barry J Bradford14, Lucas Maciel Mauriz Marques15, Juliano Geraldo Amaral16, Rodrigo Moreira Silva17, Flavio Protasio Veras15, Thiago Mattar Cunha15, Rene Donizeti Ribeiro Oliveira18, Paulo Louzada-Junior18, Robert H Mills1,2,6,19, Paulina K Piotrowski20, Stephanie L Servetas20, Sandra M Da Silva20, Christina M Jones20, Nancy J Lin20, Katrice A Lippa20, Scott A Jackson20, Rima Kaddurah Daouk21,22,23, Douglas Galasko24, Parambir S Dulai25, Tatyana I Kalashnikova26, Curt Wittenberg26, Robert Terkeltaub8,27, Megan M Doty6,28, Jae H Kim29, Kyung E Rhee6, Julia Beauchamp-Walters30, Kenneth P Wright10, Maria Gloria Dominguez-Bello31, Mark Manary32, Michelli F Oliveira33, Brigid S Boland25, Norberto Peporine Lopes17, Monica Guma8, Austin D Swafford4, Rachel J Dutton5, Rob Knight34,35,36,37,38, Pieter C Dorrestein39,40,41,42,43.
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.Entities:
Year: 2022 PMID： 35798960 DOI： 10.1038/s41587-022-01368-1
Source DB: PubMed Journal: Nat Biotechnol ISSN： 1087-0156 Impact factor: 54.908