Application of constraint-based methods in Staphylococcus aureus metabolic network

With the remarkable advances in reconstruction of genome-scale metabolic networks, computational methods are increasingly important in investigation of these networks. Since they only need a few available kinetic parameters, constraint-based modeling methods have attracted so much attention in recent years. With the important aid by COBRA Toolbox, Staphylococcus aureus metabolic network (S. aureus_iSB619 model) which contains 619 genes, 571 metabolites and 640 metabolic reactions is studied in the present paper. We investigated (mainly under glucose minimal media condition) the optimal flux distributions, optimal growth rates, dynamic growth, robustness analysis (to PGK and MDH reactions), gene deletion and uniform random sampling (all allowed flux distributions) of the model. The study provided a constraint-based modeling framework of Staphylococcus aureus, and the results could be used in its metabolic engineering and industry microbial research.