1. Enhancing untargeted metabolomics using metadata-based source annotation
- Author
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Gauglitz, Julia M, West, Kiana A, Bittremieux, Wout, Williams, Candace L, Weldon, Kelly C, Panitchpakdi, Morgan, Di Ottavio, Francesca, Aceves, Christine M, Brown, Elizabeth, Sikora, Nicole C, Jarmusch, Alan K, Martino, Cameron, Tripathi, Anupriya, Meehan, Michael J, Dorrestein, Kathleen, Shaffer, Justin P, Coras, Roxana, Vargas, Fernando, Goldasich, Lindsay DeRight, Schwartz, Tara, Bryant, MacKenzie, Humphrey, Gregory, Johnson, Abigail J, Spengler, Katharina, Belda-Ferre, Pedro, Diaz, Edgar, McDonald, Daniel, Zhu, Qiyun, Elijah, Emmanuel O, Wang, Mingxun, Marotz, Clarisse, Sprecher, Kate E, Vargas-Robles, Daniela, Withrow, Dana, Ackermann, Gail, Herrera, Lourdes, Bradford, Barry J, Marques, Lucas Maciel Mauriz, Amaral, Juliano Geraldo, Silva, Rodrigo Moreira, Veras, Flavio Protasio, Cunha, Thiago Mattar, Oliveira, Rene Donizeti Ribeiro, Louzada-Junior, Paulo, Mills, Robert H, Piotrowski, Paulina K, Servetas, Stephanie L, Da Silva, Sandra M, Jones, Christina M, Lin, Nancy J, Lippa, Katrice A, Jackson, Scott A, Daouk, Rima Kaddurah, Galasko, Douglas, Dulai, Parambir S, Kalashnikova, Tatyana I, Wittenberg, Curt, Terkeltaub, Robert, Doty, Megan M, Kim, Jae H, Rhee, Kyung E, Beauchamp-Walters, Julia, Wright, Kenneth P, Dominguez-Bello, Maria Gloria, Manary, Mark, Oliveira, Michelli F, Boland, Brigid S, Lopes, Norberto Peporine, Guma, Monica, Swafford, Austin D, Dutton, Rachel J, Knight, Rob, and Dorrestein, Pieter C
- Subjects
Medical Biochemistry and Metabolomics ,Analytical Chemistry ,Biomedical and Clinical Sciences ,Chemical Sciences ,2.1 Biological and endogenous factors ,Humans ,Tandem Mass Spectrometry ,Metadata ,Metabolomics - 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.
- Published
- 2022