Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Yasuda, Shu, Okahashi, Nobuyuki, Tsugawa, Hiroshi, Ogata, Yusuke, Ikeda, Kazutaka, Suda, Wataru, Arai, Hiroyuki, Hattori, Masahira, Arita, Makoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721639/
https://www.ncbi.nlm.nih.gov/pubmed/33313490
http://dx.doi.org/10.1016/j.isci.2020.101841
_version_ 1783620064648364032
author Yasuda, Shu
Okahashi, Nobuyuki
Tsugawa, Hiroshi
Ogata, Yusuke
Ikeda, Kazutaka
Suda, Wataru
Arai, Hiroyuki
Hattori, Masahira
Arita, Makoto
author_facet Yasuda, Shu
Okahashi, Nobuyuki
Tsugawa, Hiroshi
Ogata, Yusuke
Ikeda, Kazutaka
Suda, Wataru
Arai, Hiroyuki
Hattori, Masahira
Arita, Makoto
author_sort Yasuda, Shu
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7721639
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-77216392020-12-11 Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses Yasuda, Shu Okahashi, Nobuyuki Tsugawa, Hiroshi Ogata, Yusuke Ikeda, Kazutaka Suda, Wataru Arai, Hiroyuki Hattori, Masahira Arita, Makoto iScience Article 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. Elsevier 2020-11-23 /pmc/articles/PMC7721639/ /pubmed/33313490 http://dx.doi.org/10.1016/j.isci.2020.101841 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yasuda, Shu
Okahashi, Nobuyuki
Tsugawa, Hiroshi
Ogata, Yusuke
Ikeda, Kazutaka
Suda, Wataru
Arai, Hiroyuki
Hattori, Masahira
Arita, Makoto
Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses
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 Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721639/
https://www.ncbi.nlm.nih.gov/pubmed/33313490
http://dx.doi.org/10.1016/j.isci.2020.101841
work_keys_str_mv AT yasudashu elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT okahashinobuyuki elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT tsugawahiroshi elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT ogatayusuke elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT ikedakazutaka elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT sudawataru elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT araihiroyuki elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT hattorimasahira elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses
AT aritamakoto elucidationofgutmicrobiotaassociatedlipidsusinglcmsmsand16srrnasequenceanalyses