Efficient biosynthesis of L-tyrosine from glucose is necessary to make biological production economically viable. To this end, we designed and constructed a modular biosynthetic pathway for L-tyrosine production in E. coli MG1655 by encoding the enzymes for converting erythrose-4-phosphate (E4P) and phosphoenolpyruvate (PEP) to L-tyrosine on two plasmids. Rational engineering to improve L-tyrosine production and to identify pathway bottlenecks was directed by targeted proteomics and metabolite profiling. The bottlenecks in the pathway were relieved by modifications in plasmid copy numbers, promoter strength, gene codon usage, and the placement of genes in operons. One major bottleneck was due to the bifunctional activities of quinate/ shikimate dehydrogenase (YdiB), which caused accumulation of the intermediates dehydroquinate (DHQ) and dehydroshikimate (DHS) and the side product quinate; this bottleneck was relieved by replacing YdiB with its paralog AroE, resulting in the production of over 700 mg/liter of shikimate. Another bottleneck in shikimate production, due to low expression of the dehydroquinate synthase (AroB), was alleviated by optimizing the first 15 codons of the gene. Shikimate conversion to L-tyrosine was improved by replacing the shikimate kinase AroK with its isozyme, AroL, which effectively consumed all intermediates formed in the first half of the pathway. Guided by the protein and metabolite measurements, the best producer, consisting of two medium-copy-number, dual-operon plasmids, was optimized to produce >2 g/liter L-tyrosine at 80% of the theoretical yield. This work demonstrates the utility of targeted proteomics and metabolite profiling in pathway construction and optimization, which should be applicable to other metabolic pathways.

The models and simulation tools available to design functionally complex synthetic biological devices are very limited. We formulated a design-driven approach that used mechanistic modeling and kinetic RNA folding simulations to engineer RNA-regulated genetic devices that control gene expression. Ribozyme and metabolite-controlled, aptazyme-regulated expression devices with quantitatively predictable functions were assembled from components characterized in vitro, in vivo, and in silico. The models and design strategy were verified by constructing 28 Escherichia coli expression devices that gave excellent quantitative agreement between the predicted and measured gene expression levels (r = 0.94). These technologies were applied to engineer RNA-regulated controls in metabolic pathways. More broadly, we provide a framework for studying RNA functions and illustrate the potential for the use of biochemical and biophysical modeling to develop biological design methods.