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An inter-laboratory comparison demonstrates that [1H]-NMR metabolite fingerprinting is a robust technique for collaborative plant metabolomic data collection
Authors:Jane L. Ward  John M. Baker  Sonia J. Miller  Catherine Deborde  Mickael Maucourt  Benoit Biais  Dominique Rolin  Annick Moing  Sofia Moco  Jacques Vervoort  Arjen Lommen  Hartmut Schäfer  Eberhard Humpfer  Michael H. Beale
Affiliation:1. The National Centre for Plant and Microbial Metabolomics, Rothamsted Research, West Common, Harpenden, Herts, AL5 2JQ, UK
2. INRA-UMR 619 Biologie du Fruit, Plateforme Métabolome-Fluxome du Centre de Génomique Fonctionnelle de Bordeaux, Centre INRA de Bordeaux, 33140, Villenave d’Ornon, France
3. Université de Bordeaux- UMR 619 Biologie du Fruit, Plateforme Métabolome-Fluxome du Centre de Génomique Fonctionnelle de Bordeaux, Centre INRA de Bordeaux, 33140, Villenave d’Ornon, France
4. Laboratory of Biochemistry, Wageningen University, 6703 HA, Wageningen, The Netherlands
5. Plant Research International, 6700 AA, Wageningen, The Netherlands
8. Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli-Strasse 16, 8093, Zurich, Switzerland
6. RIKILT - Institute of Food Safety, Wageningen, UR, P.O. Box 230, 6700 AE, Wageningen, The Netherlands
7. Bruker BioSpin GmbH, Silberstreifen 4, 76287, Rheinstetten, Germany
Abstract:In any metabolomics experiment, robustness and reproducibility of data collection is of vital importance. These become more important in collaborative studies where data is to be collected on multiple instruments. With minimisation of variance in sample preparation and instrument performance it is possible to elucidate even subtle differences in metabolite fingerprints due to genotype or biological treatment. In this paper we report on an inter laboratory comparison of plant derived samples by [1H]-NMR spectroscopy across five different sites and within those sites utilising instruments with different probes and magnetic field strengths of 9.4 T (400 MHz), 11.7 T (500 MHz) and 14.1 T (600 MHz). Whilst the focus of the study is on consistent data collection across laboratories, aspects of sample stability and the requirement for sample rotation within the NMR magnet are also discussed. Comparability of the datasets from participating laboratories was exceptionally good and the data were amenable to comparative analysis by multivariate statistics. Field strength differences can be adjusted for in the data pre-processing and multivariate analysis demonstrating that [1H]-NMR fingerprinting is the ideal technique for large scale plant metabolomics data collection requiring the participation of multiple laboratories.
Keywords:
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