Preprints
https://doi.org/10.5194/mr-2022-14
https://doi.org/10.5194/mr-2022-14
 
15 Jul 2022
15 Jul 2022
Status: this preprint is currently under review for the journal MR.

Fine optimization of a dissolution-DNP experimental setting for 13C NMR of metabolic samples

Arnab Dey1, Benoît Charrier1, Karine Lemaître1, Victor Ribay1, Dmitry Eshchenko2, Marc Schnell2, Roberto Melzi3, Quentin Stern5, Samuel F. Cousin6, James G. Kempf4, Sami Jannin5, Jean-Nicolas Dumez1, and Patrick Giraudeau1 Arnab Dey et al.
  • 1Nantes Université, CNRS, CEISAM UMR 6230, F-44000 Nantes, France
  • 2Bruker Biospin, Industriestrasse 26, 8117 Fällanden, Switzerland
  • 3Bruker Biospin, Viale V. Lancetti 43, 20158 Milano, Italy
  • 4Bruker Biospin, 15 Fortune Dr., Billerica, MA 01821 USA
  • 5Université de Lyon, CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, Centre de RMN à Très Hauts Champs (CRMN), UMR5082, F-69100 Villeurbanne, France
  • 6Aix Marseille Univ., CNRS, ICR, 13397, Marseille, France

Abstract. NMR based analysis of metabolite mixture provides crucial information on biological systems but mostly rely on 1D 1H experiments for maximizing sensitivity. However, strong peak overlap of 1H 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 13C 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 13C 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 system who may not be experts in instrumental development). The optimization procedure makes it possible to detect previously inaccessible protonated-13C 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 13C NMR at natural abundance and paves the way to a more general use of DNP-hyperpolarised NMR in metabolomics studies.

Arnab Dey et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on mr-2022-14', Anonymous Referee #1, 20 Jul 2022
  • RC2: 'Comment on mr-2022-14', Benno Meier, 26 Jul 2022
    • EC1: 'Reply on RC2', Geoffrey Bodenhausen, 26 Jul 2022
    • EC2: 'Reply on RC2', Geoffrey Bodenhausen, 26 Jul 2022

Arnab Dey et al.

Data sets

Fine optimization of a dissolution-DNP experimental setting for 13C NMR of metabolic samples Arnab Dey; Benoît Charrier; Karine Lemaitre; Victor Ribay; Dmitry Eshchenko; Marc Schnell; Roberto Melzi; Quentin Stern; Samuel F. Cousin; James G. Kempf; Sami Jannin; Jean-Nicolas Dumez; Patrick Giraudeau https://doi.org/10.5281/zenodo.6810794

Arnab Dey et al.

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Short summary
Nuclear Magnetic Resonance (NMR) is a great tool for analytical chemistry, but it is not the most sensitive one. This work aims to develop a sensitive and repeatable workflow for the analysis of complex samples by hyperpolarized carbon-13 NMR. Through systematic and careful optimization of experimental parameters, we were able to achieve unprecedented sensitivity for the analysis of naturally abundant metabolite mixtures while maintaining the precision required for metabolomic studies.