Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses

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...

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Main Authors: Shu Yasuda, Nobuyuki Okahashi, Hiroshi Tsugawa, Yusuke Ogata, Kazutaka Ikeda, Wataru Suda, Hiroyuki Arai, Masahira Hattori, Makoto Arita
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:iScience
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Online Access:http://www.sciencedirect.com/science/article/pii/S2589004220310385
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author Shu Yasuda
Nobuyuki Okahashi
Hiroshi Tsugawa
Yusuke Ogata
Kazutaka Ikeda
Wataru Suda
Hiroyuki Arai
Masahira Hattori
Makoto Arita
author_facet Shu Yasuda
Nobuyuki Okahashi
Hiroshi Tsugawa
Yusuke Ogata
Kazutaka Ikeda
Wataru Suda
Hiroyuki Arai
Masahira Hattori
Makoto Arita
author_sort Shu Yasuda
collection DOAJ
description 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.
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spelling doaj.art-69fab6c217dc4271b87603e74769e5af2022-12-21T22:33:26ZengElsevieriScience2589-00422020-12-012312101841Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence AnalysesShu Yasuda0Nobuyuki Okahashi1Hiroshi Tsugawa2Yusuke Ogata3Kazutaka Ikeda4Wataru Suda5Hiroyuki Arai6Masahira Hattori7Makoto Arita8RIKEN 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, JapanRIKEN 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, JapanRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; RIKEN Center for Sustainable Resource Science, Yokohama 230-0045, JapanRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, JapanRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Clinical Omics Unit, Kazusa DNA Research Institute, Kisarazu, Chiba, JapanRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, JapanDepartment of Health Chemistry, Graduate School of Pharmaceutical Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0033, JapanRIKEN 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, JapanRIKEN 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 authorSummary: 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.http://www.sciencedirect.com/science/article/pii/S2589004220310385MicrobiomeOmicsLipidomics
spellingShingle Shu Yasuda
Nobuyuki Okahashi
Hiroshi Tsugawa
Yusuke Ogata
Kazutaka Ikeda
Wataru Suda
Hiroyuki Arai
Masahira Hattori
Makoto Arita
Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
iScience
Microbiome
Omics
Lipidomics
title Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
title_full Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
title_fullStr Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
title_full_unstemmed Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
title_short Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
title_sort elucidation of gut microbiota associated lipids using lc ms ms and 16s rrna sequence analyses
topic Microbiome
Omics
Lipidomics
url http://www.sciencedirect.com/science/article/pii/S2589004220310385
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