Many pharmaceuticals we use today originate from plant secondary metabolites and are usually produced by extraction from natural sources. To solve the supply constraints encountered when using plant extracts, significant progress has been made in cloning the biosynthetic pathways into microorganisms to produce these compounds through fermentative processes.
We have developed and implemented a constrained-based modeling approach termed Cipher of Evolutionary Design (CiED) to investigate the impact of gene deletions and other network modifications on the metabolite profile of microorganisms. By incorporating constraint-based modeling into an evolutionary algorithm we have created a computational platform where, like other evolutionary algorithms, the process of natural selection is used to find optimal phenotypes for the production of end products, such as recombinant natural products, while maintaining high levels of cellular biomass. Here we report the use of CiED to investigate the metabolic potential of Escherichia coli to channel carbon towards malonyl-CoA in an effort to generate recombinant strains with elevated flavonoid production capacity. Flavonoids, along with several of their substituted unnatural analogues, have potential therapeutic value in the treatment of various chronic diseases such as cancer, obesity, type II diabetes, and heart disease. As a result, the specific flavanone production from our optimally engineered strains was increased by over 660% for naringenin (15 to 100 mg/L/OD) and by over 420% for eriodictyol (13 to 55 mg/L/OD). These efforts demonstrate the utility of an evolutionary model based solely on stoichiometry in predicting improved microbial phenotypes for natural product production.