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Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses

We describe a protocol for identifying bacteria-derived lipid metabolites produced in the guts using antibiotic-treated mice, liquid chromatography tandem mass spectrometry-based lipidomics, and feature-based molecular spectrum networking (FBMN). Untargeted lipidomics using the MS-DIAL 4 program pro...

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Detalles Bibliográficos
Autores principales: Okahashi, Nobuyuki, Ueda, Masahiro, Yasuda, Shu, Tsugawa, Hiroshi, Arita, Makoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091925/
https://www.ncbi.nlm.nih.gov/pubmed/33997812
http://dx.doi.org/10.1016/j.xpro.2021.100492
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author Okahashi, Nobuyuki
Ueda, Masahiro
Yasuda, Shu
Tsugawa, Hiroshi
Arita, Makoto
author_facet Okahashi, Nobuyuki
Ueda, Masahiro
Yasuda, Shu
Tsugawa, Hiroshi
Arita, Makoto
author_sort Okahashi, Nobuyuki
collection PubMed
description We describe a protocol for identifying bacteria-derived lipid metabolites produced in the guts using antibiotic-treated mice, liquid chromatography tandem mass spectrometry-based lipidomics, and feature-based molecular spectrum networking (FBMN). Untargeted lipidomics using the MS-DIAL 4 program provides information on known and unknown complex lipid molecules. The FBMN technique clusters similar MS2 spectra, facilitating the identification of bacterial lipids. Targeted analysis was used as a complementary method to cover oxylipins. Here, we provide details for targeted and untargeted analyses. For complete details on the use and execution of this protocol, please refer to Yasuda et al. (2020).
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spelling pubmed-80919252021-05-13 Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses Okahashi, Nobuyuki Ueda, Masahiro Yasuda, Shu Tsugawa, Hiroshi Arita, Makoto STAR Protoc Protocol We describe a protocol for identifying bacteria-derived lipid metabolites produced in the guts using antibiotic-treated mice, liquid chromatography tandem mass spectrometry-based lipidomics, and feature-based molecular spectrum networking (FBMN). Untargeted lipidomics using the MS-DIAL 4 program provides information on known and unknown complex lipid molecules. The FBMN technique clusters similar MS2 spectra, facilitating the identification of bacterial lipids. Targeted analysis was used as a complementary method to cover oxylipins. Here, we provide details for targeted and untargeted analyses. For complete details on the use and execution of this protocol, please refer to Yasuda et al. (2020). Elsevier 2021-04-21 /pmc/articles/PMC8091925/ /pubmed/33997812 http://dx.doi.org/10.1016/j.xpro.2021.100492 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Okahashi, Nobuyuki
Ueda, Masahiro
Yasuda, Shu
Tsugawa, Hiroshi
Arita, Makoto
Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses
title Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses
title_full Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses
title_fullStr Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses
title_full_unstemmed Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses
title_short Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses
title_sort global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by lc-ms/ms-based analyses
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091925/
https://www.ncbi.nlm.nih.gov/pubmed/33997812
http://dx.doi.org/10.1016/j.xpro.2021.100492
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