Manually curated genome-scale reconstruction of the metabolic network of Bacillus megaterium DSM319

Abstract

AbstractBacillus megateriumis a microorganism widely used in industrial biotechnology for production of enzymes and recombinant proteins, as well as in bioleaching processes. Precise understanding of its metabolism is essential for designing engineering strategies to further optimizeB.megateriumfor biotechnology applications. Here, we present a genome-scale metabolic model forB.megateriumDSM319,iJA1121, which is a result of a metabolic network reconciliation process. The model includes 1709 reactions, 1349 metabolites, and 1121 genes. Based on multiple-genome alignments and available genome-scale metabolic models for otherBacillusspecies, we constructed a draft network using an automated approach followed by manual curation. The refinements were performed using a gap-filling process. Constraint-based modeling was used to scrutinize network features. Phenotyping assays were performed in order to validate the growth behavior of the model using different substrates. To verify the model accuracy, experimental data reported in the literature (growth behavior patterns, metabolite production capabilities, metabolic flux analysis using13C glucose and formaldehyde inhibitory effect) were confronted with model predictions. This indicated a very good agreement betweenin silicoresults and experimental data. For example, ourin silicostudy of fatty acid biosynthesis and lipid accumulation inB.megateriumhighlighted the importance of adopting appropriate carbon sources for fermentation purposes. We conclude that the genome-scale metabolic modeliJA1121 represents a useful tool for systems analysis and furthers our understanding of the metabolism ofB.megaterium.