Engineering Escherichia coli for production of functionalized terpenoids using plant P450s

Production of artemisinin by genetically-modified microbes

Artemisinin, an endoperoxidized sesquiterpene originally extracted from the medicinal plant Artemisia annua L., is a potent malaria-killing agent. Due to the urgent demand and short supply of this new antimalarial drug, engineering enhanced production of artemisinin by genetically-modified or transgenic microbes is currently being explored. Cloning and expression of the artemisinin biosynthetic genes in Saccharomyces cerevisiae and Escherichia coli have led to large-scale microbial production of the artemisinin precursors such as amorpha-4,11-diene and artemisinic acid. Although reconstruction of the complete biosynthetic pathway toward artemisinin in transgenic yeast and bacteria has not been achieved, artemisinic acid available from these transgenic microbes facilitates the subsequent partial synthesis of artemisinin by either chemical or biotransformational process, thereby providing an attractive strategy alternative to the direct extraction of artemisinin from A.annua L. In this review, we update the current trends and summarize the future prospects on genetic engineering of the microorganisms capable of accumulating artemisinin precursors through heterologous and functional expression of the artemisinin biosynthetic genes.

Stochastic reaction-diffusion simulation of enzyme compartmentalization reveals improved catalytic efficiency for a synthetic metabolic pathway

We have demonstrated the accuracy of a spatial stochastic model of Escherichia coli central carbon metabolism using the next subvolume method (NSM), an efficient implementation of the Gillespie direct method of stochastic simulation. Using this model, we demonstrate that compartmentalization of the enzymes comprising an engineered pathway for biosynthesis of R-1,2-propanediol leads to improved kinetic properties for the pathway enzymes, especially when substrate diffusivities are low. Our results suggest that enzyme compartmentalization is a powerful approach for improving the catalytic turnover of a channeled carbon substrate and should be particularly useful when applied to synthetic metabolic pathways that suffer from poor translation efficiency, are present in highly variable copy numbers, and have low turnover for new substrates. Furthermore, this approach represents a generic modeling framework for simultaneously analyzing spatial and stochastic events in cellular metabolism and should enable quantitative evaluation of the effect of enzyme compartmentalization on virtually any recombinant pathway.