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Updated: Jul 29, 2025

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Published on: July 11, 2014
Comparison between 5 extractions methods in either plasma or serum to determine the optimal extraction and matrix
Maryne Lepoittevin1, Quentin Blancart-Remaury2, Thomas Kerforne1,3
1Inserm Unit IRMETIST, UMR U1313, University of Poitiers, Faculty of Medicine and Pharmacy, 86073, Poitiers, France.
Background:
Although metabolomics continues to expand in many domains of research, methodological issues such as sample type, extraction and analytical protocols have not been standardized, impeding proper comparison between studies and future research.
Methods:
In the present study, five solvent-based and solid-phase extraction methods were investigated in both plasma and serum. All these extracts were analyzed using four liquid chromatography coupled with high resolution mass spectrometry (LC-MS) protocols, either in reversed or normal-phase and with both types of ionization. The performances of each method were compared according to putative metabolite coverage, method repeatability and also extraction parameters such as overlap, linearity and matrix effect; in both untargeted (global) and targeted approaches using fifty standard spiked analytes.
Results:
Our results verified the broad specificity and outstanding accuracy of solvent precipitation, namely methanol and methanol/acetonitrile. We also reveal high orthogonality between methanol-based methods and SPE, providing the possibility of increased metabolome coverage, however we highlight that such potential benefits must be weighed against time constrains, sample consumption and the risk of low reproducibility of SPE method. Furthermore, we highlighted the careful consideration about matrix choice. Plasma showed the most suitable in this metabolomics approach combined with methanol-based methods.
Conclusions:
Our work proposes to facilitate rational design of protocols towards standardization of these approaches to improve the impact of metabolomics research.
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