Metabolomics for rice blast resistance
Authors: Deepak V Pawar1, Mahesh Mahajan1, Rakesh Kumar Prajapat1, Kishor U Tribhuvan1
1ICAR-NRCPB, I.A.R.I, New Delhi-12
Rice (Oryza sativa L.) is the most important staple crop, feeding more than half of the world's population. Maintaining stable rice production is extremely important to feed the constantly growing human population. However, rice production is challenged with many biotic and abiotic stresses. Among them, rice blast, caused by the filamentous ascomycete fungus Magnaporthe oryzae, is one of the most devastating and destructive diseases of rice worldwide
According to the genetic performance and the sensitivity to environmental conditions, plant disease resistance can be divided into qualitative disease resistance and quantitative disease resistance. Qualitative disease resistance, also known as isolate specific disease resistance or vertical resistance is controlled by one or a few major genes. The qualitative resistance, because of monogenic inheritance, has been successfully transferred to elite cultivars to develop resistance. Quantitative resistance is also referred to as partial resistance, multi-gene resistance, field resistance or horizontal resistance, controlled by a number of minor genes. The quantitative resistance is generally considered to be durable, non-race-specific, and effective against multiple pathogens. Although many quantitative trait loci (QTLs) associated with quantitative resistance have been identified for blast resistance in rice (Ballini et al., 2008), because of its complex polygenic inheritance quantitative stress responses remain largely unexplored in plant breeding. Recent advances in metabolomics offer opportunities to overcome the hurdle of polygenic inheritance and identify candidate genes for the disease resistance. By examining the metabolic profiles and their dynamic changes before and after the pathogen invasion can help in detection of array of metabolites that can be correlated with biotic stress resistance.
Metabolites play central role in the plant-microbe interaction. After the attack by the pathogen, the plant's primary as well as secondary metabolic pathways are activated to produce more energy and secondary metabolites having antimicrobial activity, to prevent pathogen invasion and spread. Apart from this pathogen can also interfere with the normal metabolism of plants to accomplish their nutritional needs and produce some pathogenic biochemical factors like toxins and extracellular polysaccharides (EPSs), having pathogenicity to the host plant. Metabolomics is the systematic study of the unique chemical fingerprints that specific cellular processes leave behind. Following discovery, resistance-related (RR) metabolites can be mapped in their metabolic pathways, to better understand their regulation, and the corresponding genes can be identified in biological databases. The use of metabolomics to understand plant biological functions, plant breeding, and to study host-pathogen interaction has been well documented. In parallel, proteomics has been widely used to study host-pathogen interactions.
Hamzehzarghani et al. (2005) and Swarbrick et al. (2006) analyzed the nontarget metabolomic profile of resistant and susceptible cultivar of cereal crops and obtained several metabolite biomarkers associated with disease resistance. Allwood et al. (2006) elucidated the key metabolite changes occurring during interactions of M. grisea with an alternate host Brachypodium distachyon susceptible and resistant accessions. Phosphatidyl glycerol (PG) phospholipids were suppressed during both resistant and susceptible responses while different phosphatidic acid phospholipids either increased or reduced during resistance or during disease development. Parker et al. (2009) studied the changes of metabolomic profiles of rice (Oryza sativa), barley (Hordeum vulgare), and model grass species brachypodium (Brachypodium distachyon) before and after the inoculation of rice Magnaporthe grisea. GC-tof-MS profiling and further accurate mass approaches based on LC-FT-ICR-MS, various disease-associated metabolites have been identified in leaves of these three different hosts. Magnaporthe grisea adopted a similar strategy of "interference" to the metabolomic profiles of these three species. These preliminary studies prove that metabolomics is a very effective way for the study of plant-microbe interaction. Kushalappa and Gunnaiah, 2013 have reviewed the conceptual background to the plant-pathogen relationship and proposed ten heuristic steps streamlining the application of metabolo-proteomics to improve plant resistance to biotic stress.
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About Author / Additional Info:
I am PhD research scholar, pursuing PhD at IARI, New Delhi in the discipline of Molecular Biology and Biotechnology. I am working on blast disease resistance in O. sativa