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Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning
Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled...
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/PMC9323855/ https://www.ncbi.nlm.nih.gov/pubmed/35888789 http://dx.doi.org/10.3390/metabo12070665 |
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author | Magny, Romain Auzeil, Nicolas Lefrère, Bertrand Mégarbane, Bruno Houzé, Pascal Labat, Laurence |
author_facet | Magny, Romain Auzeil, Nicolas Lefrère, Bertrand Mégarbane, Bruno Houzé, Pascal Labat, Laurence |
author_sort | Magny, Romain |
collection | PubMed |
description | Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass spectrometry with data processing based on a molecular network to identify tramadol metabolites in urine and plasma in poisoned patients. The generated molecular network from liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes allowed for the identification of 25 tramadol metabolites in urine and plasma, including four methylated metabolites that have not been previously reported in humans or in vitro models. While positive ion mode is reliable for generating a network of tramadol metabolites displaying a dimethylamino radical in their structure, negative ion mode was useful to cluster phase II metabolites. In conclusion, the combined use of molecular networks in positive and negative ion modes is a suitable and robust tool to identify a broad range of metabolites in poisoned patients, as shown in a fatal tramadol-poisoned patient. |
format | Online Article Text |
id | pubmed-9323855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93238552022-07-27 Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning Magny, Romain Auzeil, Nicolas Lefrère, Bertrand Mégarbane, Bruno Houzé, Pascal Labat, Laurence Metabolites Article Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass spectrometry with data processing based on a molecular network to identify tramadol metabolites in urine and plasma in poisoned patients. The generated molecular network from liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes allowed for the identification of 25 tramadol metabolites in urine and plasma, including four methylated metabolites that have not been previously reported in humans or in vitro models. While positive ion mode is reliable for generating a network of tramadol metabolites displaying a dimethylamino radical in their structure, negative ion mode was useful to cluster phase II metabolites. In conclusion, the combined use of molecular networks in positive and negative ion modes is a suitable and robust tool to identify a broad range of metabolites in poisoned patients, as shown in a fatal tramadol-poisoned patient. MDPI 2022-07-19 /pmc/articles/PMC9323855/ /pubmed/35888789 http://dx.doi.org/10.3390/metabo12070665 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 Magny, Romain Auzeil, Nicolas Lefrère, Bertrand Mégarbane, Bruno Houzé, Pascal Labat, Laurence Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning |
title | Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning |
title_full | Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning |
title_fullStr | Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning |
title_full_unstemmed | Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning |
title_short | Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning |
title_sort | molecular network-based identification of tramadol metabolites in a fatal tramadol poisoning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323855/ https://www.ncbi.nlm.nih.gov/pubmed/35888789 http://dx.doi.org/10.3390/metabo12070665 |
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