Enhancing untargeted metabolomics using metadata-based source annotation

Authors: GAUGLITZ, JULIA - University Of California, San Diego; WEST, KIANA - University Of California, San Diego; BITTREMIEUX, WOUT - University Of California, San Diego; WILLIAMS, CANDACE - San Diego Zoo; WELDON, KELLY - University Of California, San Diego; PANITCHPAKDI, MORGAN - University Of California, San Diego; DI OTTAVIO, FRANCESCA - University Of California, San Diego; ACEVES, CHRISTINE - University Of California, San Diego; BROWN, ELIZABETH - University Of California, San Diego; SIKORA, NICOLE - University Of California, San Diego; JARMUSCH, ALAN - University Of California, San Diego; MARTINO, CAMERON - University Of California, San Diego; TRIPATHI, ANUPRIYA - University Of California, San Diego; MEEHAN, MICHAEL - University Of California, San Diego; DORRESTEIN, KATHLEEN - University Of California, San Diego; SHAFFER, JUSTIN - University Of California, San Diego; CORAS, ROXANA - University Of California, San Diego; VARGAS, FERNANDO - University Of California, San Diego; DERIGHT GOLDASICH, LINDSAY - University Of California, San Diego; SCHWARTZ, TARA - University Of California, San Diego; BRYANT, MACKENZIE - University Of California, San Diego; HUMPHREY, GREGORY - University Of California, San Diego; JOHNSON, ABIGAIL - University Of Minnesota; SPENGLER, KATHARINA - University Of California, San Diego; BELDA-FERRE, PEDRO - University Of California, San Diego; DIAZ, EDGAR - University Of California, San Diego; MCDONALD, DANIEL - University Of California, San Diego; ZHU, QIYUN - University Of California, San Diego; ELIJAH, EMMANUEL - University Of California, San Diego; WANG, MINGXUN - University Of California, San Diego; MAROTZ, CLARISSE - University Of California, San Diego; SPRECHER, KATE - University Of Colorado; VARGAS-ROBLES, DANIELA - Amazonic Center For Research And Control Of Tropical Diseases (CAICET); WITHROW, DANA - University Of Colorado; ACKERMAN, GAIL - University Of California, San Diego; HERRERA, LOURDES - Billings Clinic; BRADFORD, BARRY - Michigan State University; MAURIZ MARQUES, LUCAS - Universidad De Sao Paulo; GERALDO AMARAL, JULIANO - Federal University Of Bahia (UFBA); MOREIRA SILVA, RODRIGO - Universidad De Sao Paulo; PROTASIO VERAS, FLAVIO - Universidad De Sao Paulo; MATTAR CUNHA, THIAGO - Universidad De Sao Paulo; DONIZETI RIBIERO OL, RENE - Universidad De Sao Paulo; LOUZADA-JUNIOR, PAULO - Universidad De Sao Paulo; MILLS, ROBERT - University Of California, San Diego; PIOTROWSKI, PAULINA - National Institute Of Standards And Technology; SERVETAS, STEPHANIE - National Institute Of Standards And Technology; DA SILVA, SANDRA - National Institute Of Standards And Technology; JONES, CHRISTINA - National Institute Of Standards And Technology; LIN, NANCY - National Institute Of Standards And Technology; LIPPA, KATRICE - National Institute Of Standards And Technology; JACKSON, SCOTT - National Institute Of Standards And Technology; KADDURAH DAOUK, RIMA - Duke University School Of Medicine; GALASKO, DOUGLAS - University Of California, San Diego; DULAI, PARAMBIR - University Of California, San Diego; KALASHNIKOVA, TATYANA - Scripps Institute; WITTENBERG, CURT - Scripps Institute; TERKELTAUB, ROBERT - University Of California, San Diego; DOTY, MEGAN - University Of California, San Diego; KIM, JAE - University Of Cincinnati; RHEE, KYUNG - University Of California, San Diego; BEAUCHAMP-WALTERS, JULIA - University Of California, San Diego; WRIGHT, KENNETH - University Of Colorado; DOMINGUEZ-BELLO, MARIA - Rutgers University; MANARY, MARK - Children'S Nutrition Research Center (CNRC); OLIVEIRA, MICHELLI - University Of California, San Diego; BOLAND, BRIGID - University Of California, San Diego; PEPORINE LOPES, NORBERTO - Universidad De Sao Paulo; GUMA, MONICA - University Of California, San Diego; SWAFFORD, AUSTIN - University Of California, San Diego; DUTTON, RACHEL - University Of California, San Diego; KNIGHT, ROB - University Of California, San Diego; DORREISTEIN, PIETER - University Of California, San Diego

Submitted to: Nature Biotechnology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/20/2022
Publication Date: 7/7/2022
Citation: Gauglitz, J.M., West, K.A., Bittremieux, W., Williams, C.L., Weldon, K.C., Panitchpakdi, M., Di Ottavio, F., Aceves, C.M., Brown, E., Sikora, N.C., Jarmusch, A.K., Martino, C., Tripathi, A., Meehan, M.J., Dorrestein, K., Shaffer, J.P., Coras, R., Vargas, F., Deright Goldasich, L., Schwartz, T., Bryant, M., Humphrey, G., Johnson, A.J., Spengler, K., Belda-Ferre, P., Diaz, E., McDonald, D., Zhu, Q., Elijah, E., Wang, M., Marotz, C., Sprecher, K.E., Vargas-Robles, D., Withrow, D., Ackerman, G., Herrera, L., Bradford, B., Mauriz Marques, L., Geraldo Amaral, J., Moreira Silva, R., Protasio Veras, F., Mattar Cunha, T., Donizeti Ribiero Ol, R., Louzada-Junior, P., Mills, R.H., Piotrowski, P.K., Servetas, S.L., Da Silva, S.M., Jones, C.M., Lin, N.J., Lippa, K.A., Jackson, S.A., Kaddurah Daouk, R., Galasko, D., Dulai, P.S., Kalashnikova, T., Wittenberg, C., Terkeltaub, R., Doty, M.M., Kim, J.H., Rhee, K.E., Beauchamp-Walters, J., Wright, K.P., Dominguez-Bello, M.G., Manary, M., Oliveira, M.F., Boland, B.S., Peporine Lopes, N., Guma, M., Swafford, A.D., Dutton, R.J., Knight, R., Dorreistein, P.C. 2022. Enhancing untargeted metabolomics using metadata-based source annotation. Nature Biotechnology. 40.1774–1779. https://doi.org/10.1038/s41587-022-01368-1.
DOI: https://doi.org/10.1038/s41587-022-01368-1

Interpretive Summary: The study of small molecule metabolites in material taken from the human body is important for understanding diet and nutritional intake, exposure risks, medication use, consumption of illegal substances, environmental allergens, pollution studies, microbiome investigations, food ingredients/contamination, forensics, and personal care product tracing to inform of potential exposures and health effects. We introduced reference data driven (RDD) inquiry, which uses a reference library of both known and unknown molecules, to compare with the previous methods of human untargeted metabolomic studies. RDD analysis increases the scope of metabolomic studies, yielding a more effective tool for metabolite analysis.

Technical 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.