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Semi-targeted metabolomic approaches to validate potential markers of health for micronutrients: analytical perspectives
Authors:Marie-Laure Bayle  Suzan Wopereis  Jildau Bouwman  Ben van Ommen  Augustin Scalbert  Estelle Pujos-Guillot
Institution:1. Platform of Metabolism Exploration, Human Nutrition Department, UMR 1019, INRA, 63122, Saint-Gen??s-Champanelle, France
2. Department of Biosciences, TNO-Quality of Life, P.O. Box 360, 4700 AJ, Zeist, The Netherlands
3. Micronutrients, Metabolism and Health, Human Nutrition Department, UMR 1019, INRA, 63122, Saint-Gen??s-Champanelle, France
4. Nutrition and Metabolism Section, Biomarkers Group, International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69372, Lyon Cedex 08, France
Abstract:Recommended dietary allowances for micronutrients fluctuate noticeably within European Union countries. The Network of Excellence EURRECA (EURopean micronutrient RECommendations Aligned) aims at harmonising micronutrient intake recommendations through population groups. The lack of proper markers of status for some micronutrients limits progress in this area: metabolomics could help identifying such new markers. We developed an original metabolomic strategy in order to monitor the largest fraction of a list of >270 metabolites known to be influenced by the micronutrients of interest. To improve the coverage of these metabolites in plasma, a multi platform approach was performed using both liquid and gas chromatography coupled to mass spectrometry. A sample preparation protocol based on a three-step plasma fractionation has been set up, using both liquid and solid phase extractions. Four fractions were obtained containing respectively polar metabolites, neutral lipids, free fatty acids and polar lipids. Recoveries were determined using spiked plasma samples, and the advantages and drawbacks of the fractionation method compared to a commonly used single preparation step method were investigated in terms of metabolites detection and robustness. Fractionation improved coverage of the endogenous metabolome more than twice in terms of extracted features, allowing to identify 90?metabolites.
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