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Article Dans Une Revue Magnetic Resonance Année : 2022

Fine optimization of a dissolution dynamic nuclear polarization experimental setting for 13 C NMR of metabolic samples

Résumé

NMR-based analysis of metabolite mixtures provides crucial information on biological systems but mostly relies on 1D 1 H experiments for maximizing sensitivity. However, strong peak overlap of 1 H spectra often is a limitation for the analysis of inherently complex biological mixtures. Dissolution dynamic nuclear polarization (d-DNP) improves NMR sensitivity by several orders of magnitude, which enables 13 C NMR-based analysis of metabolites at natural abundance. We have recently demonstrated the successful introduction of d-DNP into a full untargeted metabolomics workflow applied to the study of plant metabolism. Here we describe the systematic optimization of d-DNP experimental settings for experiments at natural 13 C abundance and show how the resolution, sensitivity, and ultimately the number of detectable signals improve as a result. We have systematically optimized the parameters involved (in a semi-automated prototype d-DNP system, from sample preparation to signal detection, aiming at providing an optimization guide for potential users of such a system, who may not be experts in instrumental development). The optimization procedure makes it possible to detect previously inaccessible protonated 13 C signals of metabolites at natural abundance with at least 4 times improved line shape and a high repeatability compared to a previously reported d-DNP-enhanced untargeted metabolomic study. This extends the application scope of hyperpolarized 13 C NMR at natural abundance and paves the way to a more general use of DNP-hyperpolarized NMR in metabolomics studies.

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Dates et versions

hal-03828986 , version 1 (25-10-2022)

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Arnab Dey, Benoît Charrier, Karine Lemaitre, Victor Ribay, Dmitry Eshchenko, et al.. Fine optimization of a dissolution dynamic nuclear polarization experimental setting for 13 C NMR of metabolic samples. Magnetic Resonance, 2022, 3 (2), pp.183-202. ⟨10.5194/mr-3-183-2022⟩. ⟨hal-03828986⟩
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