Research articleMorphological and metabolic responses to salt stress of rice (Oryza sativa L.) cultivars which differ in salinity tolerance
Graphical abstract
Introduction
Salinity is regarded as a major environmental constraint to crop productivity worldwide (Zhu, 2001). More than 6% of the world land area are either salinity or sodicity affected (FAO, 2008). Due to the human activities and natural causes, soil salinization is increasing. A saline soil is defined to have an electrical conductivity of the saturated paste extract above 4 dS/m (~40 mM NaCl) (Chinnusamy et al., 2005). The high concentration of salt in the soil makes it harder for roots to uptake water and nutrients, therefore inducing ion imbalances and water stress in plants (Hasegawa et al., 2000). Following a consequence of these primary effects, the secondary stresses, such as metabolic damage, growth arrest, and even death, can occur. For example, osmotic stress leads to cell dehydration and a subsequent decrease in shoot and root growth. The high accumulation of Na+ in the leaf blades has been shown to be negatively correlated with plant growth in wheat (Triticum aestivum) (Munns et al., 2000), rice (Oryza sativa L.) (Zhu et al., 2001; Platten et al., 2013) and barley (Hordeum vulgare L.) (Garthwaite et al., 2005).
Metabolite changes are indicators of cellular regulatory processes. The osmotic adjustment in rice can be achieved by synthesis of compatible solutes, such as proline, glycine, GABA and sucrose (Ma et al., 2018; Banerjee et al., 2019; Gayen et al., 2019). Prolonged salt stress in wheat has showed progressive accumulation of sugars to avoid osmotic stress (Guo et al., 2015). Furthermore, cereals with different sensitivity to salt show different metabolite changes. For example, salt stress increased the levels of hexose phosphates and tricarboxylic acid (TCA) cycle intermediates in the salt tolerant barley (Sahara) while these solutes remained unchanged in the sensitive barley (Clipper) (Widodo et al., 2009). The metabolic pathways changes in cereals differing in salinity resistance may provide fundamental information to breed for tolerant cultivars.
Rice is the staple food for nearly half of the world's population. More than 50% of rice is produced and consumed in Asia (GRiSP, 2013). Compared with other crops, such as wheat and barley, rice is the most sensitive crop to salt stress (Munns and Tester, 2008). Rice grain yield can be reduced significantly by the addition of 50 mM NaCl (Yeo and Flowers, 1986), while barley, for instance, can withstand up to 450 mM NaCl (Garthwaite et al., 2005). Among the predominant abiotic stresses, such as drought and cold, salinity tolerance remains the main goal to breed stress-tolerant rice cultivars in order to assure food security (Jini and Joseph, 2017; Reddy et al., 2017).
Nipponbare, a japonica salt sensitive genotype has been used as a model rice cultivar in a variety of abiotic and biotic stress studies (Ahn et al., 2010; Wang et al., 2012). Dendang and Fatmawati are two indica genotypes with relatively high salt tolerance (Barus and Rauf, 2013). In general, indica rice has a higher level of salinity tolerance when compared with japonica (Lee et al., 2003). To our knowledge, there are no reports defining differences in metabolic responses to different salt treatments of these relatively high tolerant rice cultivars (Dendang and Fatmawati).
The growth stages, organ types and cultivars are important factors to select against the sensitivity of rice to salt. Many researchers have shown that salinity influences rice growth throughout its life cycle from germination to maturity, but the most sensitive growth stage is shown to be the seedling stage (Lutts et al., 1995; Khan et al., 1997; Nam, 2018). In this study, we investigated the salt stress response in the leaves and roots of three rice cultivars (Dendang, Fatmawati and Nipponbare) at seedling stage (four-leaf stage) at the metabolic level in order to understand their physiological responses of salt stress. Metabolic profiling may allow an initial functional insight into the metabolic pathways of tolerance acquisition without prior knowledge of genetic variation between these cultivars.
Section snippets
Chemicals and reagents
Sugars and organic acids standards, internal standards (ISTD) and the derivatization reagent, methoxyamine hydrochloride (Meox), used for Gas chromatography-mass spectrometry (GC-MS) were acquired from Sigma Aldrich (Castle Hill, NSW, Australis). N,O-Bis (trimethylsilyl) trifluoroacetamide with 1% trimethylsilyl chloride (BSTFA + 1% TMCS) was from Thermo Scientific (Bellefonte, USA). All solvents used were High performance liquid chromatography (HPLC)-grade purchased from Merck (Australia).
Plant materials and stress treatment
The
Morphological responses to salt stress
The three rice cultivars with different tolerance to salt (Dendang, Fatmawati, and Nipponbare) were evaluated for growth parameters after the time-series salt treatment. There were no obvious symptoms at the beginning of salt stress, but the reduction in shoot and root growth, and faster senescence of leaves occurred as exposure time increased. Rice plants began to develop leaf symptoms such as yellowing and necrotic lesions of old leaf tips after 3–4 days of exposure. After 2 weeks of stress,
Shoot length and root fresh weight in Nipponbare were affected by salt stress
Under salinity, the three cultivars performed differently during the 14 days of treatment. Compared with Nipponbare, Dendang and Fatmawati were less affected as indicated by a smaller reduction in shoot length, root length and root fresh weight. As morphological parameters are used for screening salt tolerant cultivars (Munns, 2002; Shahzad et al., 2012; Yildirim et al., 2015), our results demonstrate that Dendang and Fatmawati showed higher salt tolerance than Nipponbare.
The shoot and root
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Author contributions
Ute Roessner and Jing Chang developed the experiment. Siria Natera and Ute Roessner provided assistance with metabolite analysis. Jing Chang and Ute Roessner analysed data. Jing Chang drafted the manuscript which has been revised and reviewed by all other authors. Bo Eng Cheong provided advice and suggestions on plant growth and data analysis.
Acknowledgment
Jing Chang thanks for the support of the University of Chinese Academy of Sciences (UCAS, UCAS[2015]37) Joint PhD Training Program and the University of Melbourne Study Abroad Scholarship Program. Metabolite analysis was carried out at Metabolomics Australia (School of BioSciences, University of Melbourne, Australia), which is a National Collaborative Research Infrastructure Strategy initiative under Bioplatforms Australia Pty Ltd (http://www.bioplatforms.com/). The work was funded through an
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