(547h) Towards Multi-Tissue Type Metabolic Modeling of Maize

Zea Mays (commonly known as maize) is an important model C₄ plant due to its widespread use as a cereal and energy crop. In this talk we will highlight our progress to develop multi-tissue type metabolic model of Zea Mays metabolism assembled by integrating our earlier model iRS1563 with information from the KEGG, MaizeCyc, and MetaCrop databases. By including intracellular and intercellular transport and metabolic reactions, the model is tailored to describe functions of five major cell-types in maize: root, stalk, leaf, tassel and seed. Thus far, we complete reconstructing the leaf model, while development of rest of the cellular models is still in progress. The constructed leaf metabolic model contains GPR associations and elemental and charge balanced reaction entries while incorporating experimentally determined biomass composition, transcriptomic and proteomic data. The earlier iRS1563 metabolic model contained gaps in pathways (e.g. sterol biosynthesis, sphingolipid biosynthesis, ubiquinone biosynthesis and starch degradation), limited enzyme localization information, and an approximate representation of the PSI and PSII reactions. In addition to resolving shortcomings of the iRS1563 model, this second-generation leaf model includes detailed cell localization based on gene expression data and literature evidence. The model contains over 4,400 reactions involved in both primary and secondary metabolism. As many as 1000 reactions are unique to KEGG, 350 reactions are unique to MaizeCyc, and 40 reactions are unique to MetaCrop. The reactions are distributed in six organelles in the bundle sheath cell (i.e. the mitochondrion, plastid, thylakoid lumen, peroxisome, vacuole, and cytoplasm) and five organelles in the mesophyll cell (i.e. the mitochondrion, plastid, thylakoid lumen, vacuole, and cytoplasm). Using flux balance analysis, we simulated low-nitrogen and high-nitrogen supply conditions and analyzed metabolic flux changes. In addition, reactions underpinning nitrogen utilization efficiency were identified along with the effect of nitrogen supply to biomass yield