(598e) Computational Modeling of Aspergillus Metabolism for Metabolic Engineering Purposes

Aspergillus niger are widely used as attractive industrial fermentation hosts to produce therapeutics, value-added fungal secondary metabolites as well as expression platform for eukaryotic proteins since it offer unique advantages of accessible genetic manipulation and valuable repertoire for muti-purpose production machineries.

However, a principal drawback is low yield of compound of interest and suitable fermentation protocols of specific strains. To overcome limitations of maximizing production titer of compound of interest while sustaining cell biomass growth, rational reconfiguring and redirection of cellular complex metabolic network flux has been made to compound of interest by exhaustively exploring combinations of genetic modifications by considering multiple gene targets. In this study, we combine flux balance analysis and elementary mode analysis to develop an optimization framework for evolving metabolic networks to identify feasible gene knockouts and overexpression targets, furthermore, and to validate computational results experimentally in related engineered Aspergillus niger strains.