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bioRxiv · 10.1101/2020.07.08.194159

Reference data based insights expand understanding of human metabolomes

Julia M Gauglitz·Wout Bittremieux·Candace L Williams·Kelly C Weldon·Morgan W Panitchpakdi·Francesca Di Ottavio·Christine M Aceves·Elizabeth Brown·Nicole C Sikora·Alan K. Jarmusch·Cameron Martino·Anupriya Tripathi·Erfan Sayyari·Justin Shaffer·Roxana Coras·Fernando Vargas·Lindsay DeRight Goldasich·Tara Schwartz·MacKenzie Bryant·Gregory Humphrey·Abigail J. Johnson·Katharina Spengler·Pedro Belda-Ferre·Edgar Diaz·Daniel McDonald·Qiyun Zhu·Dominic S. Nguyen·Emmanuel O. Elijah·Mingxun Wang·Clarisse Marotz·Kate E. Sprecher·Daniela Vargas-Robles·Dana Withrow·Gail Ackerm
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Abstract

The human metabolome has remained largely unknown, with most studies annotating [~]10% of features. In nucleic acid sequencing, annotating transcripts by source has proven essential for understanding gene function. Here we generalize this concept to stool, plasma, urine and other human metabolomes, discovering that food-based annotations increase the interpreted fraction of molecular features 7-fold, providing a general framework for expanding the interpretability of human metabolomic "dark matter."

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Julia M Gauglitz, Wout Bittremieux, Candace L Williams, Kelly C Weldon, Morgan W Panitchpakdi, Francesca Di Ottavio, Christine M Aceves, Elizabeth Brown, Nicole C Sikora, Alan K. Jarmusch, Cameron Martino, Anupriya Tripathi, Erfan Sayyari, Justin Shaffer, Roxana Coras, Fernando Vargas, Lindsay DeRight Goldasich, Tara Schwartz, MacKenzie Bryant, Gregory Humphrey, Abigail J. Johnson, Katharina Spengler, Pedro Belda-Ferre, Edgar Diaz, Daniel McDonald, Qiyun Zhu, Dominic S. Nguyen, Emmanuel O. Elijah, Mingxun Wang, Clarisse Marotz, Kate E. Sprecher, Daniela Vargas-Robles, Dana Withrow, Gail Ackerm. 2020-07-11. Reference data based insights expand understanding of human metabolomes. https://doi.org/10.1101/2020.07.08.194159

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