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A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids
Short Chain Fatty Acids (SCFAs) are produced by the gut microbiota and are present in varying concentrations in the intestinal lumen, in feces but also in the circulatory system. By interacting with different cell types in the body, they have a great impact on host metabolism and their exact quantif...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8875994/ https://www.ncbi.nlm.nih.gov/pubmed/35208244 http://dx.doi.org/10.3390/metabo12020170 |
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author | Rohde, Julia K. Fuh, Marceline M. Evangelakos, Ioannis Pauly, Mira J. Schaltenberg, Nicola Siracusa, Francesco Gagliani, Nicola Tödter, Klaus Heeren, Joerg Worthmann, Anna |
author_facet | Rohde, Julia K. Fuh, Marceline M. Evangelakos, Ioannis Pauly, Mira J. Schaltenberg, Nicola Siracusa, Francesco Gagliani, Nicola Tödter, Klaus Heeren, Joerg Worthmann, Anna |
author_sort | Rohde, Julia K. |
collection | PubMed |
description | Short Chain Fatty Acids (SCFAs) are produced by the gut microbiota and are present in varying concentrations in the intestinal lumen, in feces but also in the circulatory system. By interacting with different cell types in the body, they have a great impact on host metabolism and their exact quantification is indispensable. Here, we present a derivatization-free method for the gas chromatography mass spectrometry (GC-MS) based quantification of SCFAs in plasma, feces, cecum, liver and adipose tissue. SCFAs were extracted using ethanol and concentrated by alkaline vacuum centrifugation. To allow volatility for separation by GC, samples were acidified with succinic acid. Analytes were detected in selected ion monitoring (SIM) mode and quantified using deuterated internal standards and external calibration curves. Method validation rendered excellent linearity (R(2) > 0.99 for most analytes), good recovery rates (95–117%), and good reproducibility (RSD: 1–4.5%). Matrix effects were ruled out in plasma, feces, cecum, liver and fat tissues where most abundant SCFAs were detected and accurately quantified. Finally, applicability of the method was assessed using samples derived from conventionally raised versus germ-free mice or mice treated with antibiotics. Altogether, a reliable, fast, derivatization-free GC-MS method for the quantification of SCFAs in different biological matrices was developed allowing for the study of the (patho)physiological role of SCFAs in metabolic health. |
format | Online Article Text |
id | pubmed-8875994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88759942022-02-26 A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids Rohde, Julia K. Fuh, Marceline M. Evangelakos, Ioannis Pauly, Mira J. Schaltenberg, Nicola Siracusa, Francesco Gagliani, Nicola Tödter, Klaus Heeren, Joerg Worthmann, Anna Metabolites Article Short Chain Fatty Acids (SCFAs) are produced by the gut microbiota and are present in varying concentrations in the intestinal lumen, in feces but also in the circulatory system. By interacting with different cell types in the body, they have a great impact on host metabolism and their exact quantification is indispensable. Here, we present a derivatization-free method for the gas chromatography mass spectrometry (GC-MS) based quantification of SCFAs in plasma, feces, cecum, liver and adipose tissue. SCFAs were extracted using ethanol and concentrated by alkaline vacuum centrifugation. To allow volatility for separation by GC, samples were acidified with succinic acid. Analytes were detected in selected ion monitoring (SIM) mode and quantified using deuterated internal standards and external calibration curves. Method validation rendered excellent linearity (R(2) > 0.99 for most analytes), good recovery rates (95–117%), and good reproducibility (RSD: 1–4.5%). Matrix effects were ruled out in plasma, feces, cecum, liver and fat tissues where most abundant SCFAs were detected and accurately quantified. Finally, applicability of the method was assessed using samples derived from conventionally raised versus germ-free mice or mice treated with antibiotics. Altogether, a reliable, fast, derivatization-free GC-MS method for the quantification of SCFAs in different biological matrices was developed allowing for the study of the (patho)physiological role of SCFAs in metabolic health. MDPI 2022-02-11 /pmc/articles/PMC8875994/ /pubmed/35208244 http://dx.doi.org/10.3390/metabo12020170 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rohde, Julia K. Fuh, Marceline M. Evangelakos, Ioannis Pauly, Mira J. Schaltenberg, Nicola Siracusa, Francesco Gagliani, Nicola Tödter, Klaus Heeren, Joerg Worthmann, Anna A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids |
title | A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids |
title_full | A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids |
title_fullStr | A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids |
title_full_unstemmed | A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids |
title_short | A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids |
title_sort | gas chromatography mass spectrometry-based method for the quantification of short chain fatty acids |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8875994/ https://www.ncbi.nlm.nih.gov/pubmed/35208244 http://dx.doi.org/10.3390/metabo12020170 |
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