(599bq) Pathway Optimization Techniques for the Production of Free Fatty Acids and Flavonoids in Escherichia coli

The importance of developing alternative and sustainable methods for the production of both high value and commodity chemicals cannot be understated. Much research has attempted to answer this growing need by using metabolic engineering techniques to develop microbes suited to manufacture a wide variety of industrially significant products.

When a functional pathway is first developed for a new organism the resulting titers and efficiency are very low, resulting in a non-feasible industrial replacement for the naturally derived source. These downfalls are inherit to all metabolic engineering projects and facilitate the need for pathway optimization to develop microbial production methods for biofuels and chemicals that are competitive with current production methods. Many factors play a role in the efficiency of a metabolic pathway including enzyme kinetics, thermodynamics and co-factor requirements as well as pathway regulatory and feedback mechanisms. Many of the details needed to rationally design a perfectly optimized system are simply not known, or well-understood, making complete rational design currently impossible. Understanding the points at which pathway flux can be modulated is an important first step toward optimizing any given pathway.

A variety of pathway optimization techniques will be used to improve the production of chemicals derived from acetyl-CoA and malonyl-CoA in Escherichia coli. First, we will demonstrate how gene copy number and synthetic gene scaffolds were used to optimize the production of flavonoids. Second, we will optimize fatty acid production by tailoring gene expression at the individual gene level using a set of three compatible vectors with different expression levels. Third, we will demonstrate the use of a T7 promoter library to increase the production of chemicals derived from recombinant pathways. Each method presented here has been tailored to the specific pathway to be balanced. The pros and cons of each method will be presented such that an appropriate pathway optimization strategy can be implemented for a wide variety of microbial pathways.