Reconstruction of a genome-scale metabolic network of Rhodococcus erythropolis for desulfurization studies

Abstract

The remarkable catabolic diversity of Rhodococcus erythropolis makes it an interesting organism for bioremediation and fuel desulfurization. However, a model that can describe and explain the combined influence of various intracellular metabolic activities on its desulfurizing capabilities is missing from the literature. Such a model can greatly aid the development of R. erythropolis as an effective desulfurizing biocatalyst. This work reports the reconstruction of the first genome-scale metabolic model for R. erythropolis using the available genomic, experimental, and biochemical information. We have validated our in silico model by successfully predicting cell growth results and explaining several experimental observations in the literature on biodesulfurization using dibenzothiophene. We report several in silico experiments and flux balance analyses to propose minimal media, determine gene and reaction essentiality, and compare effectiveness of carbon, nitrogen, and sulfur sources. We demonstrate the usefulness of our model by studying a few in silico mutants of R. erythropolis for improved biodesulfurization, and comparing the desulfurization abilities of R. erythropolis with an in silico mutant of E. coli.