The recent advances of modern high-throughput genomic technologies have resulted in a large number of fully sequenced microbial organisms. The construction of these comprehensive metabolic models serves many purposes including encapsulating all the data and allowing for in silco experiments to be performed that can drive experimental work and aid in strain development and optimization. The creation of a full metabolic reconstruction requires a significant amount of manual work; an automated procedure for rapidly developing metabolic models would be extremely valuable for the biotechnology field. We intend to use our recently developed automated metabolic model construction system and apply this to build a complete predictive model of Pichia pastoris for use in recombinant protein production. We will perform dedicated experiments to complete and validate the in silico metabolic model of Pichia pastoris and use this model to develop metabolic intervention strategies and optimize the process feed strategy to increase production of a protein of interest to the DOD. This combined computational and experimental methodology takes advantage of the simulation and predictive powers of the complete genome-scale metabolic model to drive experimentation and create rational-based metabolic intervention changes and process development changes.
Keywords: Computational Biology, Metabolism, Microbial Systems, Bioinformatics, Protein Production.
