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NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows

INTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling. OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) an...

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Autores principales: Canlet, Cécile, Deborde, Catherine, Cahoreau, Edern, Da Costa, Grégory, Gautier, Roselyne, Jacob, Daniel, Jousse, Cyril, Lacaze, Mélia, Le Mao, Inès, Martineau, Estelle, Peyriga, Lindsay, Richard, Tristan, Silvestre, Virginie, Traïkia, Mounir, Moing, Annick, Giraudeau, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328857/
https://www.ncbi.nlm.nih.gov/pubmed/37418094
http://dx.doi.org/10.1007/s11306-023-02028-4
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author Canlet, Cécile
Deborde, Catherine
Cahoreau, Edern
Da Costa, Grégory
Gautier, Roselyne
Jacob, Daniel
Jousse, Cyril
Lacaze, Mélia
Le Mao, Inès
Martineau, Estelle
Peyriga, Lindsay
Richard, Tristan
Silvestre, Virginie
Traïkia, Mounir
Moing, Annick
Giraudeau, Patrick
author_facet Canlet, Cécile
Deborde, Catherine
Cahoreau, Edern
Da Costa, Grégory
Gautier, Roselyne
Jacob, Daniel
Jousse, Cyril
Lacaze, Mélia
Le Mao, Inès
Martineau, Estelle
Peyriga, Lindsay
Richard, Tristan
Silvestre, Virginie
Traïkia, Mounir
Moing, Annick
Giraudeau, Patrick
author_sort Canlet, Cécile
collection PubMed
description INTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling. OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision. METHODS: A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool. RESULTS: For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables. CONCLUSION: External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11306-023-02028-4.
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spelling pubmed-103288572023-07-09 NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows Canlet, Cécile Deborde, Catherine Cahoreau, Edern Da Costa, Grégory Gautier, Roselyne Jacob, Daniel Jousse, Cyril Lacaze, Mélia Le Mao, Inès Martineau, Estelle Peyriga, Lindsay Richard, Tristan Silvestre, Virginie Traïkia, Mounir Moing, Annick Giraudeau, Patrick Metabolomics Original Article INTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling. OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision. METHODS: A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool. RESULTS: For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables. CONCLUSION: External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11306-023-02028-4. Springer US 2023-07-07 2023 /pmc/articles/PMC10328857/ /pubmed/37418094 http://dx.doi.org/10.1007/s11306-023-02028-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Canlet, Cécile
Deborde, Catherine
Cahoreau, Edern
Da Costa, Grégory
Gautier, Roselyne
Jacob, Daniel
Jousse, Cyril
Lacaze, Mélia
Le Mao, Inès
Martineau, Estelle
Peyriga, Lindsay
Richard, Tristan
Silvestre, Virginie
Traïkia, Mounir
Moing, Annick
Giraudeau, Patrick
NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
title NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
title_full NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
title_fullStr NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
title_full_unstemmed NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
title_short NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
title_sort nmr metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328857/
https://www.ncbi.nlm.nih.gov/pubmed/37418094
http://dx.doi.org/10.1007/s11306-023-02028-4
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