Metabolic network reconstruction of Manihot esculenta Crantz (2017)
The global harvested area of cassava (Manihot esculenta Crantz) is 19.6 (2011) million hectares. Cassava grows throughout the tropic and it is cultivated by small-scale farmers in areas where soils are poor and rainfall is low. It has one of the biggest harvested area increase among the world's food crops (44 %) in the last two decades. Herein, we generate a compartmentalized genome-scale model for cassava, which takes into account the gene- protein-reaction (GPR) relationships. The stoichiometric values of each reaction were assigned according with Metanetx annotation. The Gibbs free changes of reactions (ArG') was used to predict reaction directionality. Compartmentalization was carried out using a multiple gene-location prediction analysis followed by a cluster analysis. To assay the network gaps, gapfin/gapfill algorithm were used, along with topological metrics. The model was assayed using flux balance analysis (FBA). Optimization was carried out using biomass production as the objective function. In total, 8526 genes, 5253 metabolites and 4636 reactions associated to primary and secondary metabolism were identified. All reactions were localized into five different compartments (i.e., cytoplasm, mitochondrion, plastid, vacuole and extracellular). The FBA under normal and modified condition (i.g., deletions of biomass components) identified that the hemicellulose is a major biomass contributor in cassava. In addition, the importance of cyanogenic compound conversion reactions in connection with biomass production was evidenced, potentially through the release of beta- D-glucose and D-glucose. This model is the first cassava metabolic model and the first model among the Euphorbiaceae family. In addition, we present an gene sequence-based method for the compartmentalization of metabolic models based on genomic data.