(175ai) Computational Analysis of Xylitol Production in Candida Tropicalis

Xylitol is a polyalcohol that has sweetening properties equal to sucrose but with a lower caloric content. The implementation of xylitol can reduce the risk of dental caries and its use is recommended for people with diabetes [1,2]. Although most xylitol is produced chemically, based on the catalytic reduction of pure xylose at high pressure and temperature using a nickel catalyst, this process demands costs in the catalysis and purification processes. The biotechnological reduction of xylose to xylitol offers a potentially better alternative both at the energy level and at the cost of the process. This reduction is made using from microorganisms, among which some yeasts stand out, especially those belonging to the genus Candida sp. These yeasts are able to use xylose as a carbon source and large accumulation xylitol [3].

In recent decades, several metabolic engineering strategies have been explored to modify the key enzymes and thereby increase the production of xylitol. Among the most used strategies can be enunciated the isolation of new xylitol reductases, increasing the productivity of xylitol by directed evolution and the development of theoretical studies, such as genome-scale metabolic reconstructions (GEMs), allowing to understand molecular aspects of different metabolic processes [4], [5]. Therefore, this work aims to perform a genome-scale metabolic reconstruction of a strain of Candida tropicalis producing xylitol to be further analyzed, in order to predict different phenotypic states of said yeast, and give improvements in performance and productivity xylitol. The genomic scale metabolic reconstruction was developed from the reference genome of the strain Candida tropicalis MYA3404 and from the genome annotation of the strain Candida tropicalis 116-5, through Merlin, which allows to obtain in a semi-automated way the reactions, metabolites and enzymes associated with genes found in the annotation. This reconstruction includes 1922 genes, 1738 metabolites and 2735 reactions, of which 273 are transporters. Further, reactions were added to the model for gap filling purposes. The addition was made simulating the production of each of the biomass precursors, verifying the connectivity of the reactions involved for the production of each one. This reconstruction makes it possible to elucidate the compounds and reactions that are essential for its growth, as well as to evaluate the metabolic mechanisms it exerts for the production of compounds of industrial interest such as xylitol. Finally, these data are compared with experimental data obtained from bioreactor assays.

References:

[1] Werpy, T. and Petezrsen, G. (2004) Top Value Added Chemicals from Biomass Volume I—Results of Screening for Potential Candidates from Sugars and Synthesis Gas Energy Efficiency and Renewable Energy.

[2] Venkateswar Rao, L., Goli, J. K., Gentela, J. and Koti, S. (2015) “Bioconversion of lignocellulosic biomass to xylitol: An overview”, Bioresource Technology.

[3] Prakasham, R. S., Sreenivas-Rao, R. and Hobbs, P. (2009) “Current trends in biotechnological production of xylitol and future prospects”, Current Trends in Biotechnology and Pharmacy, 3, pp. 8–36.

[4] Oberhardt, M. A. Palsson, B. O, Papin, J. A. (2009) “Applications of genome-scale metabolic reconstructions”, Mol Syst Biol, 5, 320.

[5] Zhang, F., Qiao, D., Xu, H., Liao, C., Li, S. and Cao, Y. (2009) “Cloning, expression, and characterization of xylose reductase with higher activity from Candida tropicalis”, Journal of Microbiology.