期刊
PHYTOCHEMICAL ANALYSIS
卷 22, 期 3, 页码 214-224出版社
WILEY
DOI: 10.1002/pca.1268
关键词
Metabonomics; Metabolic profiling; Maize; Partial Least Squares Discriminant Analysis; H-1 NMR Spectroscopy; salt stress
资金
- AstraZeneca
Introduction - High salinity, caused by either natural (e.g. climatic changes) or anthropic factors (e.g. agriculture), is a widespread environmental stressor that can affect development and growth of salt-sensitive plants, leading to water deficit, the inhibition of intake of essential ions and metabolic disorders. Objective - The application of an NMR-based metabolic profiling approach to the investigation of saline-induced stress in Maize plants is presented. Methodology - Zea Maize seedlings were grown in either 0, 50 or 150 mM saline solution. Plants were harvested after 2,4 and 6 days (n = 5 per class and time point) and H-1 NMR spectroscopy was performed separately on shoot and root extracts. Spectral data were analysed and interpreted using multivariate statistical analyses. Results - A distinct effect of time/growth was observed for the control group with relatively higher concentrations of acetoacetate at day 2 and increased levels of alanine at days 4 and 6 in root extracts, whereas concentration of alanine was positively correlated with the shoot extracts harvested at day 2 and trans-aconitic acid increased at days 4 and 6. A clear dose-dependent effect, superimposed on the growth effect, was observed for saline treated shoot and root extracts. This was correlated with increased levels of alanine, glutamate, asparagine, glycine-betaine and sucrose and decreased levels of malic acid, trans-aconitic acid and glucose in shoots. Correlation with salt-load shown in roots included elevated levels of alanine, gamma-amino-N-butyric acid, malic acid, succinate and sucrose and depleted levels of acetoacetate and glucose. Conclusions - The metabolic effect of high salinity was predominantly consistent with osmotic stress as reported for other plant species and was found to be stronger in the shoots than the roots. Using multivariate data analysis it is possible to investigate the effects of more than one environmental stressor simultaneously. Copyright (C) 2010 John Wiley & Sons, Ltd.
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