Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
Shu Yasuda,
Nobuyuki Okahashi,
Hiroshi Tsugawa,
Yusuke Ogata,
Kazutaka Ikeda,
Wataru Suda,
Hiroyuki Arai,
Masahira Hattori,
Makoto Arita
Affiliations
Shu Yasuda
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Health Chemistry, Graduate School of Pharmaceutical Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
Nobuyuki Okahashi
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan
Hiroshi Tsugawa
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; RIKEN Center for Sustainable Resource Science, Yokohama 230-0045, Japan
Yusuke Ogata
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
Kazutaka Ikeda
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Clinical Omics Unit, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
Wataru Suda
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
Hiroyuki Arai
Department of Health Chemistry, Graduate School of Pharmaceutical Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
Masahira Hattori
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan
Makoto Arita
RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Division of Physiological Chemistry and Metabolism, Graduate School of Pharmaceutical Sciences, Keio University, Minato-ku, Tokyo 105-8512, Japan; Graduate School of Medical Life Science, Yokohama City University, Tsurumi, Yokohama 230-0045, Japan; Corresponding author
Summary: Host-microbiota interactions create a unique metabolic milieu that modulates intestinal environments. Integration of 16S ribosomal RNA (rRNA) sequences and mass spectrometry (MS)-based lipidomics has a great potential to reveal the relationship between bacterial composition and the complex metabolic network in the gut. In this study, we conducted untargeted lipidomics followed by a feature-based molecular MS/MS spectral networking to characterize gut bacteria-dependent lipid subclasses in mice. An estimated 24.8% of lipid molecules in feces were microbiota-dependent, as judged by > 10-fold decrease in antibiotic-treated mice. Among these, there was a series of unique and microbiota-related lipid structures, including acyl alpha-hydroxyl fatty acid (AAHFA) that was newly identified in this study. Based on the integrated analysis of 985 lipid profiles and 16S rRNA sequence data providing 2,494 operational taxonomic units, we could successfully predict the bacterial species responsible for the biosynthesis of these unique lipids, including AAHFA.
