Flux-based analysis of sulfur metabolism in desulfurizing strains of Rhodococcus erythropolis

Abstract

Rhodococcus erythropolis has been studied widely for potential applications in biodesulfurization. Previous works have been largely experimental with an emphasis on the characterization and genetic engineering of desulfurizing strains for improved biocatalysis. A systems modeling approach that can complement these experimental efforts by providing useful insights into the complex interactions of desulfurization reactions with various other metabolic activities is absent in the literature. In this work, we report the first attempt at reconstructing a flux-based model to analyze sulfur utilization by R. erythropolis. The model includes the 4S pathway for dibenzothiophene (DBT) desulfurization. It predicts closely the growth rates reported by two independent experimental studies, and gives a clear and comprehensive picture of the pathways that assimilate the sulfur from DBT into biomass. In addition, it successfully elucidates that sulfate promotes higher cell growth than DBT and its presence in the medium reduces DBT desulfurization rates. A study using eight carbon sources suggests that ethanol and lactate yield higher cell growth and desulfurization rates than citrate, fructose, glucose, gluconate, glutamate, and glycerol.

Transcriptome of the quorum-sensing signal-degrading Rhodococcus erythropolis responds differentially to virulent and avirulent Pectobacterium atrosepticum

“…Additional genes which exhibit a lower expression level were expected to be also involved in multiplication of R. erythropolis on potato tuber slices. A major characteristic of R. erythropolis species is their capability to assimilate a wide variety of carbon and sulfur sources from natural and xenobiotic compounds (de Carvalho and da Fonseca, 2005; Urai et al, 2007;Aggarwal et al, 2011). This metabolic versatility would contribute to the distribution of R. erythropolis in a wide variety of environments such as oceans and soils, including those polluted by fuels and pesticides.…”

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

“…A few examples of organisms that were studied within the last year using Pathway Tools include Bacillus acidocaldarius, B. circulans, B. filicolonicus, B. laterosporus, B. licheniformis and B. stearothermophilus (17), Clostridium difficile (18), C. thermocellum (19), Corynebacterium pseudotuberculosis (20), Ignicoccus hospitalis and Nanoarchaeum equitans (21), Mycobacterium species (22,23), Rhizobium etli CFN42 (24), Rhodococcus erythropolis (25), R. opacus PD630 (26), S. cerevisiae and Pichia pastoris (27), Serratia symbiotica (28), Shewanella species (29), Vibrio vulnificus (30), Xanthomonas axonopodi s (31) and X. citri (32). Pathway Tools can also generate PGDBs from metagenomic data sets (33).…”

In silico modeling and evaluation of Gordonia alkanivorans for biodesulfurization

“…Nevertheless, they provide an effective framework for studying genotype-phenotype relationships, interactions among various metabolic activities, and internal flux distributions associated with various metabolic activities under given environmental conditions. Such constraint-based genome-scale metabolic (GSM) models have been reconstructed and analyzed widely for several industrially important bacterial strains such as Escherichia coli, 17,18 R. erythropolis, 19,20 Saccharomyces cerevisae, 21,22 and Zymomonas mobilis, 23 and even mammalian cells such as mouse hydridoma. 24,25 Once constructed, these models can be very useful in exploring the possible states and properties of the metabolic network of an organism.…”