In silico modeling and evaluation of Gordonia alkanivorans for biodesulfurization

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Abstract
The genus Gordonia is well known for its catabolic diversity and ability to transform several compounds including the various recalcitrant polyaromatic sulfur heterocycles (PASHs) found in the fossil fuels. In fact, some strains offer the unique ability to desulfurize even benzothiophene (BT) and other thiophenic compounds, which most of the commonly studied rhodococci strains cannot. In this work, we present the first genome scale metabolic model for G. alkanivorans, a desulfurizing strain, to enable a holistic study of its metabolism and comparison with R. erythropolis. Our model consists of 881 unique metabolites and 922 reactions associated with 568 ORFs/genes and 544 unique enzymes. It successfully predicts the growth rates from experimental studies and quantitatively elucidates the pathways for the desulfurization of the commonly studied sulfur compounds, namely dibenzothiophene (DBT) and benzothiophene (BT). Using our model, we identify the minimal media for G. alkanivorans, and show the significant effect of carbon sources on desulfurization with ethanol as the best source. Our model shows that the sulfur-containing amino acids such as cysteine and methionine decrease desulfurization activity, and G. alkanivorans prefers BT over DBT as a sulfur source. It also suggests that this preference may be driven by the lower NADH requirements for BT metabolism rather than the higher affinity of the transport system for BT. Our in silico comparison of R. erythropolis and G. alkanivorans suggests the latter to be a better desulfurizing strain due to its versatility for both BT and DBT, higher desulfurization activity, and higher growth rate.

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