تنش های محیطی در علوم زراعی (Mar 2023)

Metabolic analysis of rice (Oryza sativa L.) seedlings under high salinity stress using GC-MS method and principal component analysis (PCA)

  • Mojdeh Akbarzadeh Lelekami,
  • Mohammad Hadi Pahlevani,
  • Khalil Zaynali Nezhad,
  • Keyvan Mahdavi Mashaki,
  • Andreas P.M. Weber,
  • Dominik Brilhaus

DOI
https://doi.org/10.22077/escs.2021.4349.2011
Journal volume & issue
Vol. 16, no. 1
pp. 71 – 81

Abstract

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IntroductionSalinity as one of the major abiotic stresses influences plant growth and development. Rice with a salt tolerance threshold of 3 ds/m is regarded as a very sensitive crop, especially at seedling stage. Metabolite profiling is conducted by instruments such as GC-MS (Gas chromatography–mass spectrometry) and permits the study of plant responses to environmental stresses at the molecular level. The present study assessed the primary metabolite profiles related to high salinity stress in sensitive (IR28) and tolerant (CSR28) genotypes of rice seedlings in shoots and roots after 6h and 54 h salinity exposure.Material and methodsThe seeds of two rice (Oryza sativa L. ssp. Indica) genotypes with different salinity tolerance were obtained from International Rice Research Institute (IRRI) in Philippines. The plants were grown hydroponically in the greenhouse of Heinrich-Heine-University (HHU), Düsseldorf, Germany. The two-week old seedlings were exposed to 150 mM (15 ds/m) NaCl salinity. The topmost parts of the plants were harvested (in five replications of 10 seedlings each) at 6h and 54h post-treatment. Metabolite extraction was performed by GC-MS method. The experiment was conducted as factorial in a completely randomized design (CRD) and significance level was tested using ANOVA in SAS v9.2 software. R software was used for Principal Component Analysis (PCA) using metabolite z-score data Results and discussionGC-MS analysis identified 37 primary metabolites including 18 amino acids (AAs), five sugars and sugar alcohols and 14 organic acids (OAs) in roots and shoots of the CSR28 and IR28 genotypes at 6h and 54h post-salt exposure. In response to salinity, amino acids and sugars accumulated and organic acids depleted in both genotypes. Long-term stress revealed pronounced differences between the two genotypes. The major osmolyte proline indicated maximum response to salinity in CSR28 shoots, while the stress marker GABA accumulated more in IR28 shoots. Under high salinity the osmoprotectants raffinose and myo-inositol increased in CSR28 roots. Principal Component Analysis (PCA) revealed amino acid accumulations in the long-term exposure of salt stress in roots are main contributors to differentiate the genotypes for salt tolerance.ConclusionsBased on GC-MS analysis, 83.3% increase in amino acids and 61.8% decrease in organic acids were observed in response to salinity, indicating an increase in osmotic adjustment mechanisms and a decrease in photosynthetic reactions in the genotypes, respectively. The PCA demonstrated that amino acids play the most important role in separating the samples under salinity stress and control conditions in both organs. Further, the genotypes were differentiated due to metabolic changes in roots in response to salinity particularly in the long-term stress. Proline which is one of the most important osmolytes involved in abiotic stresses was significantly higher in the shoots of CSR28 under the long-term salinity compared to that of IR28. On the other hand, GABA which is a stress marker accumulated more in the shoots of the sensitive genotype. Some metabolites such as aspartate myo-inositol, citrate, glycerate, isocitrate and shikimate were specifically accumulated in roots. Finally, proline, GABA, etc. can be used as biomarkers for selecting salt tolerant lines. The present study highlights the contribution of metabolic adaptation to salinity tolerance.AcknowledgementsWe appreciate the International Rice Research Institute (IRRI) for providing the seeds. We also acknowledge the excellent technical assistance of Gorgan University of Agricultural Sciences and Natural Resources (GAU), Gorgan, Iran and Heinrich-Heine-University (HHU), Düsseldorf, Germany.

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