(590e) In Silico Metabolic Model of Rhodococcus Erythropolis to Study and Improve Desulfurization | AIChE

(590e) In Silico Metabolic Model of Rhodococcus Erythropolis to Study and Improve Desulfurization

Authors 

Aggarwal, S. - Presenter, National University of Singapore

In silico Metabolic Model of Rhodococcus erythropolis to Study and Improve Desulfurization

Shilpi Aggarwal1, I A Karimi1, Dong-Yup Lee1,2

1Dept of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576

2Bioprocessing Technology Institute, 20 Biopolis Way, #06-01, Centros, Singapore 138668

The increasingly stringent rules for ultra-low-sulfur fuels have inspired efforts to improve existing desulfurization techniques and develop new, efficient, and more economical methods. Hydrodesulfurization, the prevalent method for desulfurization, is a chemical process that is energy-intensive, expensive, and incapable of desulfurizing certain recalcitrant sulfur compounds such as benzothiophene, dibenzothiophene (DBT), and their derivatives present in fossil fuels [1]. Studies aimed at evolving new methods of desulfurization have recognized biodesulfurization as a potential alternative.

Biodesulfurization involves the use of either enzymes or whole cells for reducing sulfur content of the fossil fuels. It is advantageous, as it can proceed under ambient conditions, does not involve the loss of calorific value [2], and is relatively economical. Rhodococcus erythropolis IGTS8 was isolated as the first microorganism that can specifically desulfurize polyaromatic sulfur heterocycles (PASHs) such as DBT and its derivatives via the 4S pathway. Over the last two decades, several strains of Rhodococcus have been studied for their desulfurization ability [2]. The desulfurization rates obtained in a biodesulfurization process using naturally occurring bacterial cultures are too low for commercialization [3]. Despite numerous efforts for increased specific desulfurization activity with various manipulations at the genetic level, desirable desulfurization rates are yet to be attained.

The complex interactions among the various metabolic pathways and associated reactions largely determine the metabolic fluxes [4] within an organism and hence its cellular activities and phenotypes (here, desulfurization activity). However, most studies have targeted the 4S pathway exclusively, and a holistic systems study of various intracellular activities has not been reported. Therefore, it is critical to study the desulfurizing characteristics of R. erythropolis by considering its interactions and dependence on the other parts of its metabolism.

This work represents the very first stoichiometric model of R. erythropolis to study its intracellular metabolic processing of various sulfur compounds. It consists of the sulfur metabolic pathway along with the other biochemical pathways such as central metabolism, amino acids biosynthetic pathways, etc. It describes the dependence of the flux through sulfur metabolism on factors such as the supply of reducing equivalents and demand for sulfur containing precursor metabolites. It has been successfully validated using the experimental data available in literature. The model predicts biomass growth close to the experimental values with the measured DBT uptake rates [5] used as inputs. Moreover, it shows the effects of alternate sulfur sources (i.e., sulfate and DBT) on the growth rates which are in close agreement with the experimental observations [6, 7]. Based on the model findings, we have been able to propose an alternate hypothesis for the effect of sulfate on desulfurizing activity. Successful predictions on the suitability of carbon sources [8] by the model have led us to determine the effectiveness of additional carbon sources and other medium components for achieving higher in silico desulfurizing activity and growth of this biocatalyst. The determination and comparison of the fluxes through other host functions provide insights into the relative influence of the various enzymatic activities on the extent of desulfurization exhibited by R. erythropolis. The analysis of the metabolic network has also enabled us to identify the various metabolic engineering approaches such as gene(s) knockouts, over expression of certain gene(s), etc. that may be instrumental in enhancing the desulfurization activity of R. erythropolis effectively.

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