Genome-Scale Metabolic Model Reconstruction of Rice and its Bacterial Blight Pathogen Xanthomonas oryzae pv. oryzae

Rice has played a major role in the lives of people in South-east Asia as well as in the whole world. Although the production of rice is increasing, still it is not achieving the target to meet the demand of the growing population due to different biotic and abiotic stress conditions. The success of rice production depends on the control of different stresses that could prevent loss in rice productivity. Several efforts have been going on to understand the complexity of the system. One potential way to solve this problem is through system biology approach with the help of mathematical model. To achieve this, we have developed a central metabolic model of rice. This model can predict the classical fermentative and photorespiratory pathways that operate during flooding and drought conditions, respectively. Since this model lacks the involvement of hormones and other secondary metabolic pathways, we aimed to expand it to a “Genome-Scale Metabolic Model” (GSMM).  To accomplish this, we have reconstructed a draft version of GSMM of rice consisting of 1440 reactions and 807 unique metabolites localized across six different cellular compartments. Currently, the model is being analyzed for dead-ends and network gaps. Once it is ready, we hope to predict and simulate different metabolic pathways associated with abiotic and biotic stress conditions using the newly reconstructed GSMM. In addition, we have also reconstructed a GSMM of Xanthomonas oryzae to integrate with rice GSMM to analyze the interactions between rice and its pathogen for the leaf blight disease.