NMR Techniques Coupled with Multivariate Statistical Analysis: Tools to Analyse Oryza sativa Metabolic Content under Stress Conditions |
| |
| Authors: | E Fumagalli E Baldoni P Abbruscato P Piffanelli A Genga R Lamanna & R Consonni |
| |
| Institution: | Istituto per lo Studio delle Macromolecole, CNR v. Bassini 15, Milan, Italy;
Istituto di Biologia e Biotecnologia Agraria, CNR v. Bassini 15, Milan, Italy;
Parco Tecnologico Padano via Einstein, Lodi, Italy;
BIOTEC-AGRO ENEA C.R. Trisaia, Rotondella (Mt), Italy |
| |
| Abstract: | Rice ( Oryza sativa L.) is one of the most important crops in the world and its growth is influenced by several environmental stresses, such as drought and high salinity. In our study, we first investigated the metabolic profile in shoots and roots of two rice cultivars (Arborio and Nipponbare) through 1H-high-resolution magic angle spinning (HR MAS) and liquid-state nuclear magnetic resonance (NMR) experiments. Drought and salt stress experiments on shoot and root growth showed Arborio seedlings to be more sensitive than those of Nipponbare to these abiotic stresses. Moreover, the metabolic content of the same samples was analysed by liquid-state NMR coupled with multivariate statistical analysis. Principal component analysis highlighted a significant accumulation of amino acids and sugars in shoots and roots under stress conditions and the existence of clear differences between the two analysed rice cultivars. In particular, Arborio seedlings accumulated a higher concentration of amino acids and sugars than Nipponbare seedlings. Furthermore, we also obtained preliminary data about metabolic changes in rice following infection with the fungus Magnaporthe grisea . This study proves that NMR technique coupled with multivariate statistical analysis is a powerful tool to assess a possible correlation between differences in metabolic profile and in tolerance/sensitivity phenotype in rice cultivars. |
| |
| Keywords: | crop/stress physiology drought stress nuclear magnetic resonance Oryza sativa principal components analysis salinity stress |
|
|
