A split-range acquisition method for the non-targeted metabolomic profiling of human plasma with hydrophilic interaction chromatography - high-resolution mass spectrometry.


Journal

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
ISSN: 1873-376X
Titre abrégé: J Chromatogr B Analyt Technol Biomed Life Sci
Pays: Netherlands
ID NLM: 101139554

Informations de publication

Date de publication:
01 Oct 2019
Historique:
received: 24 05 2019
revised: 07 08 2019
accepted: 27 08 2019
pubmed: 4 9 2019
medline: 6 2 2020
entrez: 4 9 2019
Statut: ppublish

Résumé

Untargeted metabolomics of human plasma with mass spectrometry is of particular interest in medical research to explore pathophysiology, find disease biomarkers or for the understanding of the response to pharmacotherapy. Since analytical performances may be impacted by the laboratory environment and the acquisition method settings, the objectives of this study were to assess the role of interfering compounds and to propose an acquisition method to maximize the metabolome coverage for human plasma metabolomic analysis. Human plasma samples were processed with liquid/liquid extraction then analysed with HILIC-high resolution mass spectrometry. A method with a single m/z range was compared to four methods with different split acquisition ranges and four sets of ionization source parameters were compared. The data were analysed with the R software and on the Worklow4Metabolomics online platform. The major interfering compounds were identified in blank samples where they accounted for up to 86% of the signal intensity. Splitting the acquisition range into 3 m/z ranges improved the number of detected features, the number of features with proposed annotation in the Human Metabolome Database, as well as signal intensity throughout the whole m/z range. The method performing best was the one using three m/z ranges of approximatively the same extent. Ionization source parameters also strongly affected the number of detected features. Splitting the acquisition range into 3 m/z ranges with optimized ionization source parameters allows a comprehensive analysis of the human plasma metabolome with perspectives for applications to pathophysiological studies.

Identifiants

pubmed: 31479891
pii: S1570-0232(19)30831-1
doi: 10.1016/j.jchromb.2019.121780
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

121780

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Fanta Fall (F)

INSERM U1173, Plateforme de Spectrométrie de Masse, UFR Simone Veil - Santé, Université Versailles - Saint Quentin en Yvelines, Université Paris Saclay, Montigny le Bretonneux, France.

Natacha Lenuzza (N)

CEA, LIST, Laboratory for Data Sciences and Decision, MetaboHUB-Paris, Gif-sur-Yvette, France.

Elodie Lamy (E)

INSERM U1173, Plateforme de Spectrométrie de Masse, UFR Simone Veil - Santé, Université Versailles - Saint Quentin en Yvelines, Université Paris Saclay, Montigny le Bretonneux, France.

Marion Brollo (M)

UPRES EA220, Université Versailles - Saint Quentin en Yvelines, Université Paris Saclay, Suresnes, France.

Emmanuel Naline (E)

UPRES EA220, Université Versailles - Saint Quentin en Yvelines, Université Paris Saclay, Suresnes, France; Département des Maladies des Voies Respiratoires, Hôpital Foch, Suresnes, France.

Philippe Devillier (P)

UPRES EA220, Université Versailles - Saint Quentin en Yvelines, Université Paris Saclay, Suresnes, France; Département des Maladies des Voies Respiratoires, Hôpital Foch, Suresnes, France.

Etienne Thévenot (E)

CEA, LIST, Laboratory for Data Sciences and Decision, MetaboHUB-Paris, Gif-sur-Yvette, France.

Stanislas Grassin-Delyle (S)

INSERM U1173, Plateforme de Spectrométrie de Masse, UFR Simone Veil - Santé, Université Versailles - Saint Quentin en Yvelines, Université Paris Saclay, Montigny le Bretonneux, France; Département des Maladies des Voies Respiratoires, Hôpital Foch, Suresnes, France. Electronic address: stanislas.grassin-delyle@uvsq.fr.

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Classifications MeSH