Analytical approaches

Metabolomic untargeted approach aims to gather information on as many metabolites as possible in biological systems by considering all information present in the datasets. This approach is essential to pinpoint modifications of metabolic pathways associated to nutritional, disease or environmental status, and discover potential new biomarkers. Metabolic profiles are determined using LC/QToF, or/and GC/QToF, or/and NMR. After statistical analyses, biomarkers are identified using LC/HRMS. 

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Metabolomic targeted approach: based on GC/MS, LC/MS or NMR, this approach is used to quantify selected small molecules from a biological source, and to elucidate metabolite accumulation patterns. 

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Fluxomic approach: This is a metabolism dynamic approach aiming to identify pathways and metabolic networks, and to measure metabolic fluxes in vivo. It consists in measurements of isotopic enrichments, using GC/MS and/or GC/C/IRMS, of amino acids and fatty acids, which allows calculation of their metabolic rates in vivo, after infusion of these isotopes.

 

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Data science for metabolomics

Untargeted metabolomics approaches generate massive and complex data that need dedicated analyses to extract the biologically meaningful information. Then, one of the most challenging steps is data annotation and integration. Our team gathers a full complementary expertise dedicated to data management, processing and analysis activities dispatched between statistics, bioinformatics and biological computing: tools and workflow for data analysis, and scientific information systems and databases.

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Mapping research group

The objective of this scientific component is to bring metabolomics into systems biology, first by the development of methods and tools to increase knowledge extraction from metabolomics data, and second by the development of modeling approaches to reveal determinants and modulators of metabolic changes for a better understanding of the role of nutrition on health. The Mapping research group proposes and coordinates proof of concept research projects within multidisciplinary consortia, aiming to position metabolomics in the field of systems epidemiology and precision medicine.

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