Multiscale Metabolic Modeling of C4 Plants: Connecting Nonlinear Genome-Scale Models to Leaf-Scale Metabolism in Developing Maize Leaves

摘要: C4 plants, such as maize, concentrate carbon dioxide in a specialized compartment surrounding the veins of their leaves to improve efficiency assimilation. Nonlinear relationships between and oxygen levels reaction rates are key physiology but cannot be handled with standard techniques constraint-based metabolic modeling. We demonstrate that incorporating these constraints on solving resulting nonlinear optimization problem yields realistic predictions response systems environmental biochemical perturbations. Using new genome-scale reconstruction maize metabolism, we build an 18000-reaction, nonlinearly constrained model describing mesophyll bundle sheath cells 15 segments developing leaf, interacting via metabolite exchange, use RNA-seq enzyme activity measurements predict spatial variation state by novel method optimizes correlation fluxes expression data. Though correlations known weak general, suggest developmental gradients may particularly suited inference from data, our predicts achieve high successfully capture experimentally observed base-to-tip transition carbon-importing tissue carbon-exporting tissue, include nonzero growth rate, contrast prior results similar methods other systems.