Titre
From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data.
Type
synthèse (review)
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Ivanisevic, J.
Co-dernière auteure/Co-dernier auteur
Want, E.J.
Co-dernière auteure/Co-dernier auteur
Liens vers les personnes
Liens vers les unités
ISSN
2218-1989
Statut éditorial
Publié
Date de publication
2019-12-17
Volume
9
Numéro
12
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: epublish
Publication Status: epublish
Résumé
Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.
PID Serval
serval:BIB_E8044FA17AB4
PMID
Open Access
Oui
Date de création
2020-01-03T15:09:41.715Z
Date de création dans IRIS
2025-05-21T07:07:46Z
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Nom
31861212_BIB_E8044FA17AB4.pdf
Version du manuscrit
published
Licence
https://creativecommons.org/licenses/by/4.0
Taille
3.15 MB
Format
Adobe PDF
PID Serval
serval:BIB_E8044FA17AB4.P001
URN
urn:nbn:ch:serval-BIB_E8044FA17AB41
Somme de contrôle
(MD5):652fc3fccb126ba01a66096945e86b52