@article{a26b75647d66481ba015c4eaf699dc71,
title = "Characterization of TMAO productivity from carnitine challenge facilitates personalized nutrition and microbiome signatures discovery",
abstract = "The capability of gut microbiota in degrading foods and drugs administered orally can result in diversified efficacies and toxicity interpersonally and cause significant impact on human health. Production of atherogenic trimethylamine N-oxide (TMAO) from carnitine is a gut microbiota-directed pathway and varies widely among individuals. Here, we demonstrated a personalized TMAO formation and carnitine bioavailability from carnitine supplements by differentiating individual TMAO productivities with a recently developed oral carnitine challenge test (OCCT). By exploring gut microbiome in subjects characterized by TMAO producer phenotypes, we identified 39 operational taxonomy units that were highly correlated to TMAO productivity, including Emergencia timonensis, which has been recently discovered to convert γ-butyrobetaine to TMA in vitro. A microbiome-based random forest classifier was therefore constructed to predict the TMAO producer phenotype (AUROC = 0.81) which was then validated with an external cohort (AUROC = 0.80). A novel bacterium called Ihubacter massiliensis was also discovered to be a key microbe for TMA/TMAO production by using an OCCT-based humanized gnotobiotic mice model. Simply combining the presence of E. timonensis and I. massiliensis could account for 43% of high TMAO producers with 97% specificity. Collectively, this human gut microbiota phenotype-directed approach offers potential for developing precision medicine and provides insights into translational research. [MediaObject not available: see fulltext.]",
keywords = "Cardiovascular disease, Emergencia timonensis, Gut microbiome, Ihubacter massiliensis, Machine learning, Oral carnitine challenge test, Personalized nutrition, Trimethylamine N-oxide",
author = "Wu, {Wei Kai} and Suraphan Panyod and Liu, {Po Yu} and Chen, {Chieh Chang} and Kao, {Hsien Li} and Chuang, {Hsiao Li} and Chen, {Ying Hsien} and Zou, {Hsin Bai} and Kuo, {Han Chun} and Kuo, {Ching Hua} and Liao, {Ben Yang} and Chiu, {Tina H.T.} and Chung, {Ching Hu} and Lin, {Angela Yu Chen} and Lee, {Yi Chia} and Tang, {Sen Lin} and Wang, {Jin Town} and Wu, {Yu Wei} and Hsu, {Cheng Chih} and Sheen, {Lee Yan} and Orekhov, {Alexander N.} and Wu, {Ming Shiang}",
note = "Funding Information: The research was supported by the Ministry of Science and Technology (Taiwan) (108-2314-B-002-032, 106-2314-B-002 -039 -MY3 and 108-2321-B-002 -035, 106-2319-B-492-001, 109-2327-B-002 -005, 109-2314-B-002 -103 -MY3, 109-2314-B-002 -064 -MY3), Program for Translational Innovation of Biopharmaceutical Development-Technology Supporting Platform Axis (AS-KPQ-106-TSPA) and Russian Science Foundation (Grant # 19-15-00010). Funding Information: We would like to acknowledge the service provided by the Medical Microbiota Center of the First Core Laboratory, National Taiwan University College of Medicine. We thank the Humanized Mouse Platform: Patient Derived Tumor, Gut Microbiota Transplantation and Gene Modification Service at the National Core Facility for Biopharmaceuticals, National Laboratory Animal Center, Taiwan for providing the germ-free mouse facilities. We thank Animal Resource Center, National Taiwan University for providing space and equipment for our animal studies.?We thank to Brain KN Tsai and Richie Wang from Delta Electronics, Inc. for validating the work of machine learning model. We thank the laboratory assistance from Yu-Ting Yang, Ying-Tzu Li, Chang-Hao Lai, and Pei-Lin Wang.?We thank Liver Disease Prevention & Treatment Research Foundation, Taiwan for supporting this program. Publisher Copyright: {\textcopyright} 2020, The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = dec,
doi = "10.1186/s40168-020-00912-y",
language = "English",
volume = "8",
journal = "Microbiome",
issn = "2049-2618",
publisher = "BioMed Central",
number = "1",
}