An in silico Flux Analysis of Rice Metabolism during Anoxia and Drought Stress Using Central Metabolic Model of Rice

Abiotic and biotic stresses affect about 50% of the global rice production each year. Among them, flooding and drought stresses are the major factors.  Despite many researches, our understanding of the mechanism that operates under such stress conditions is still very limited and that highlights the need for further research. In recent years, systems biology approaches provide tools to develop mathematical models that can simulate biochemical processes for understanding the metabolic changes that happens during such stress conditions. In the current work, we used such approaches to reconstruct the central metabolic model of rice to understand the mechanism of rice germination under anoxia and the photorespiratory pathway that increases under drought stress. The simulation was performed for both conditions using Flux Balance Analysis. We also analyzed and identified the key regulatory reactions that could be involved in the unique anoxic germination of rice seeds by combining in silico metabolic model with gene expression data. The patterns of cis-regulatory information content of those transcriptionally regulated genes were further analyzed to find the potential transcription factors that could be involved in the regulation of metabolism under anoxia. Similarly, simulation was performed for the photorespiratory pathway in rice leaves.  Essential genes of the pathway were identified through single gene deletion analysis and pair of lethal genes was identified by synthetic lethality screening. The information derived from the current in silico analysis for both anoxic and photorespiratory metabolism of rice can potentially guide for developing new targets to engineer crop productivity strategies.