Genome-scale Metabolic Flux Analyses in Plant Systems

Abstract

Plants are essential for human life, food and as sustainable chemical feedstocks. Optimizing their growth and productivity is a major biotechnological goal. In this study, we apply systems engineering methods to perform a cost/benefit analysis for leaf biomass synthesis in poplar, and starch and zein protein synthesis in maize. Toward this, we used flux balance analysis (FBA) and flux variability analysis (FVA) via the COBRA toolbox on MATLAB. Our results provide metabolic justifications for field observations and point to reaction bottlenecks that could be relieved by synthetic biology. In poplar, FVA showed that glutamine uses an optimal combination of carbon assimilation (RuBisCO) cost and photon cost. Furthermore, we expanded on a previous one amino acid (AA)-model to a two-AA FBA model, which showed that best for leaf biomass is optimized with one nitrogen-rich and one nitrogen-lean AA. In maize, serine was the optimal AA for starch and zein protein synthesis.