Optimizing 1D
Arabidopsis
Automation
Flax
High-Throughput Screening Assays
/ methods
Magnetic Resonance Imaging
/ methods
Magnetic Resonance Spectroscopy
/ methods
Metabolomics
/ methods
Plant Extracts
/ isolation & purification
Plant Leaves
/ chemistry
Proton Magnetic Resonance Spectroscopy
/ methods
Reference Standards
Specimen Handling
/ methods
Triticum
Metabolomics
NMR acquisition
NMR spectra processing
Sample preparation
Journal
Metabolomics : Official journal of the Metabolomic Society
ISSN: 1573-3890
Titre abrégé: Metabolomics
Pays: United States
ID NLM: 101274889
Informations de publication
Date de publication:
26 02 2019
26 02 2019
Historique:
received:
28
09
2018
accepted:
07
02
2019
entrez:
5
3
2019
pubmed:
5
3
2019
medline:
9
4
2020
Statut:
epublish
Résumé
Proton nuclear magnetic resonance spectroscopy ( 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. 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 Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) 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. 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.
Identifiants
pubmed: 30830443
doi: 10.1007/s11306-019-1488-3
pii: 10.1007/s11306-019-1488-3
pmc: PMC6394467
doi:
Substances chimiques
Plant Extracts
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
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