Abstract
Bacillus megaterium is 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 optimize B. megaterium for biotechnology applications. Here, we present a genome-scale metabolic model for B. megaterium DSM319, 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 other Bacillus species, 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 using 13C glucose and formaldehyde inhibitory effect) were confronted with model predictions. This indicated a very good agreement between in silico results and experimental data. For example, our in silico study of fatty acid biosynthesis and lipid accumulation in B. megaterium highlighted the importance of adopting appropriate carbon sources for fermentation purposes. We conclude that the genome-scale metabolic model iJA1121 represents a useful tool for systems analysis and furthers our understanding of the metabolism of B. megaterium.
Highlights
In recent decades, research on Bacillus megaterium has gained momentum due to its versatile metabolic capabilities and physical properties favorable to biotechnology applications
Further investigation of the growth behavior of B. megaterium mutants was carried out by applying the results reported by Wang et al.[16] to the analysis of MS941 and WH320 strains under high cell density conditions
It was assumed that glucose is taken up by B. megaterium directly, as isotopic measurements could not identify which glucose uptake pathway was active[47]
Summary
Research on Bacillus megaterium has gained momentum due to its versatile metabolic capabilities and physical properties favorable to biotechnology applications This bacterium had already been commonly used in biochemical studies before the extensive popularity of Bacillus subtilis[1,2]. GEM-based predictions can be used for amelioration of culture medium composition, by identifying key metabolites that need to be added to increase the growth rate. They can be used for predicting metabolite production fluxes[26] and defining gene deletion strategies for metabolic engineering[27]. Model predictions were in agreement with the growth simulation results from Biolog phenotyping assays, as well as with several experimental data-sets reported in the literature
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