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Optimizing 1D 1H-NMR profiling of plant samples for high throughput analysis: extract preparation, standardization, automation and spectra processing

hal.structure.identifierBiologie du fruit et pathologie [BFP]
hal.structure.identifierMetaboHUB-Bordeaux
dc.contributor.authorDEBORDE, Catherine
hal.structure.identifierBiologie des Plantes et Innovation - UR UPJV 3900 [BIOPI]
dc.contributor.authorFONTAINE, Jean-Xavier
hal.structure.identifierBiologie du fruit et pathologie [BFP]
hal.structure.identifierMetaboHUB-Bordeaux
dc.contributor.authorJACOB, Daniel
hal.structure.identifierJEOL (U.K.) Ltd. [JEOL UK]
dc.contributor.authorBOTANA, Adolfo
hal.structure.identifierUnité de recherche Mycologie et Sécurité des Aliments [MycSA]
dc.contributor.authorNICAISE, Valerie
hal.structure.identifierUnité de recherche Mycologie et Sécurité des Aliments [MycSA]
dc.contributor.authorRICHARD-FORGET, Florence
hal.structure.identifierBiologie des Plantes et Innovation - UR UPJV 3900 [BIOPI]
dc.contributor.authorLECOMTE, Sylvain
hal.structure.identifierBiologie des Plantes et Innovation - UR UPJV 3900 [BIOPI]
dc.contributor.authorDECOURTIL, Cédric
hal.structure.identifierBiologie des Plantes et Innovation - UR UPJV 3900 [BIOPI]
dc.contributor.authorHAMADE, Kamar
hal.structure.identifierBiologie des Plantes et Innovation - UR UPJV 3900 [BIOPI]
dc.contributor.authorMESNARD, François
hal.structure.identifierBiologie du fruit et pathologie [BFP]
hal.structure.identifierMetaboHUB-Bordeaux
dc.contributor.authorMOING, Annick
hal.structure.identifierBiologie des Plantes et Innovation - UR UPJV 3900 [BIOPI]
dc.contributor.authorMOLINIÉ, Roland
dc.date.issued2019
dc.identifier.issn1573-3882
dc.description.abstractEn<strong>Introduction</strong> Proton nuclear magnetic resonance spectroscopy (H-1-NMR)-based metabolomic profiling has a range of applications in plant sciences. <strong>Objectives</strong> The aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances. <strong>Methods</strong> An automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed H-1-NMR spectroscopy in three different sites on the wheat sample set utilizing instruments from two manufacturers with different probes and magnetic field strengths. The three collections of spectra were processed separately with the NMRProcFlow web tool using intelligent bucketing, and the resulting buckets were subjected to multivariate analysis. <strong>Results</strong> Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600MHz and from the wheat sample set recorded at the three sites (400, 500 and 600MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups. <strong>Conclusion</strong> Standardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.
dc.description.sponsorshipDéveloppement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation - ANR-11-INBS-0010
dc.language.isoen
dc.publisherSpringer Verlag
dc.subjectMetabolomics
dc.subjectNMR acquisition
dc.subject.enNMR spectra processing
dc.subject.enSample preparation
dc.title.enOptimizing 1D 1H-NMR profiling of plant samples for high throughput analysis: extract preparation, standardization, automation and spectra processing
dc.typeArticle de revue
dc.identifier.doi10.1007/s11306-019-1488-3
dc.subject.halSciences du Vivant [q-bio]/Biologie végétale
bordeaux.journalMetabolomics
bordeaux.page1-12
bordeaux.volume15
bordeaux.issue3
bordeaux.peerReviewedoui
hal.identifierhal-02622523
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02622523v1
bordeaux.COinSctx_ver=Z39.88-2004&amp;rft_val_fmt=info:ofi/fmt:kev:mtx:journal&amp;rft.jtitle=Metabolomics&amp;rft.date=2019&amp;rft.volume=15&amp;rft.issue=3&amp;rft.spage=1-12&amp;rft.epage=1-12&amp;rft.eissn=1573-3882&amp;rft.issn=1573-3882&amp;rft.au=DEBORDE,%20Catherine&amp;FONTAINE,%20Jean-Xavier&amp;JACOB,%20Daniel&amp;BOTANA,%20Adolfo&amp;NICAISE,%20Valerie&amp;rft.genre=article


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