A genome-scale metabolic reconstruction provides insight into the metabolism of the thermophilic bacteriumRhodothermus marinus

Abstract

The thermophilic bacterium Rhodothermus marinus has mainly been studied for its thermostable enzymes. More recently, the potential of using the species as a cell factory and in biorefinery platforms has been explored, due to the elevated growth temperature, native production of compounds such as carotenoids and EPSs, the ability to grow on a wide range of carbon sources including polysaccharides, and available genetic tools. A comprehensive understanding of the metabolism of production organisms is crucial. Here, we report a genome-scale metabolic model of R. marinus DSM 4252T. Moreover, the genome of the genetically amenable R. marinus ISCaR-493 was sequenced and the analysis of the core genome indicated that the model could be used for both strains. Bioreactor growth data was obtained, used for constraining the model and the predicted and experimental growth rates were compared. The model correctly predicted the growth rates of both strains. During the reconstruction process, different aspects of the R. marinus metabolism were reviewed and subsequently, both cell densities and carotenoid production were investigated for strain ISCaR-493 under different growth conditions. Additionally, the dxs gene, which was not found in the R. marinus genomes, from Thermus thermophilus was cloned on a shuttle vector into strain ISCaR-493 resulting in a higher yield of carotenoids.

Medium development and production of carotenoids and exopolysaccharides by the extremophile Rhodothermus marinus DSM16675 in glucose-based defined media

“…The subsequent growth rates and glucose uptake rates were determined and an increased concentration of any of these components resulted in complete consumption of glucose (5 g/L) and better growth compared to the original medium. A genome-scale metabolic model of R. marinus [ 18 ] was used to estimate the required concentration of the main medium components for optimized growth and to facilitate interpretation of the results obtained here. The model was used to predict the growth rates, using default model constraints, and the resulting fluxes of the three metabolites: phosphate, sulfate and ammonium were compared to the in vivo data obtained here.…”