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Appl. Environ. Microbiol. doi:10.1128/AEM.02750-07
Copyright (c) 2008, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.

Functional Genomics for Pathway Optimization: Application to Isoprenoid Production

Department of Chemical Engineering, University of California, Berkeley, CA 94720-1462; Department of Bioengineering, University of California, Berkeley, CA 94720-1762; Synthetic Biology Department, Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720

^* To whom correspondence should be addressed. Email: keasling{at}berkeley.edu.

	Abstract

Producing complex chemicals using synthetic metabolic pathways in microbial hosts can have many advantages over chemical synthesis but is often complicated by deleterious interactions between pathway intermediates and the host-cell metabolism. With the maturation of functional genomic analysis it is now technically feasible to identify modes of toxicity associated with the accumulation of foreign molecules in the engineered bacterium. Previously, Escherichia coli was engineered to produce large quantities of isoprenoids by creating a mevalonate-based isopentenyl pyrophosphate biosynthetic pathway (Martin et al. 2003. Nat. Biotechnol. 21:796). The engineered E. coli produced high levels of isoprenoids, but further optimization lead to an imbalance in carbon flux and the accumulation of the pathway intermediate 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA), which proved to be cytotoxic to E. coli. Using both DNA microarray analysis and metabolite profiling we have studied E. coli strains inhibited by the intracellular accumulation of HMG-CoA. Our results indicate that HMG-CoA inhibits fatty acid biosynthesis in the microbial host leading to a generalized membrane stress. The cytotoxic effects of HMG-CoA accumulation can be counteracted by the addition of palmitic acid (16:0) and, to a lesser extent, oleic acid (cis-⁹-18:1) in the growth medium. This work demonstrates the utility of using transcriptomic and metabolomic methods to optimize synthetic biological systems.