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Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms
Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a uniqu...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305469/ https://www.ncbi.nlm.nih.gov/pubmed/34299389 http://dx.doi.org/10.3390/molecules26144111 |
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author | Martias, Cécile Baroukh, Nadine Mavel, Sylvie Blasco, Hélène Lefèvre, Antoine Roch, Léa Montigny, Frédéric Gatien, Julie Schibler, Laurent Dufour-Rainfray, Diane Nadal-Desbarats, Lydie Emond, Patrick |
author_facet | Martias, Cécile Baroukh, Nadine Mavel, Sylvie Blasco, Hélène Lefèvre, Antoine Roch, Léa Montigny, Frédéric Gatien, Julie Schibler, Laurent Dufour-Rainfray, Diane Nadal-Desbarats, Lydie Emond, Patrick |
author_sort | Martias, Cécile |
collection | PubMed |
description | Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms ((1)H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map. |
format | Online Article Text |
id | pubmed-8305469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83054692021-07-25 Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms Martias, Cécile Baroukh, Nadine Mavel, Sylvie Blasco, Hélène Lefèvre, Antoine Roch, Léa Montigny, Frédéric Gatien, Julie Schibler, Laurent Dufour-Rainfray, Diane Nadal-Desbarats, Lydie Emond, Patrick Molecules Article Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms ((1)H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map. MDPI 2021-07-06 /pmc/articles/PMC8305469/ /pubmed/34299389 http://dx.doi.org/10.3390/molecules26144111 Text en © 2021 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 Martias, Cécile Baroukh, Nadine Mavel, Sylvie Blasco, Hélène Lefèvre, Antoine Roch, Léa Montigny, Frédéric Gatien, Julie Schibler, Laurent Dufour-Rainfray, Diane Nadal-Desbarats, Lydie Emond, Patrick Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms |
title | Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms |
title_full | Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms |
title_fullStr | Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms |
title_full_unstemmed | Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms |
title_short | Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms |
title_sort | optimization of sample preparation for metabolomics exploration of urine, feces, blood and saliva in humans using combined nmr and uhplc-hrms platforms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305469/ https://www.ncbi.nlm.nih.gov/pubmed/34299389 http://dx.doi.org/10.3390/molecules26144111 |
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