Automated design of synthetic ribosome binding sites to control protein expression

• Published in: Nature biotechnology Vol. 27; no. 10; pp. 946 - 950
• Main Authors: Voigt, Christopher A, Salis, Howard M, Mirsky, Ethan A
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01-10-2009; Nature Publishing Group
• Subjects: Agriculture; Algorithms; Binding Sites; Bioinformatics; Biological and medical sciences; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Biomedicine; Biotechnology; Cloning, Molecular - methods; Design; DNA, Recombinant - genetics; E coli; Escherichia coli; Escherichia coli - genetics; Escherichia coli Proteins - genetics; Escherichia coli Proteins - metabolism; Fundamental and applied biological sciences. Psychology; Gene expression; Genetic Engineering - methods; letter; Life Sciences; Microbiology; Optimization; Physiological aspects; Protein binding; Protein Biosynthesis; Proteins; Reproducibility of Results; Ribosomal Proteins - genetics; Ribosomal Proteins - metabolism; Ribosomes; Ribosomes - genetics; RNA, Messenger - genetics; RNA, Messenger - metabolism; Structure; Thermodynamics; United States; Design; Regulation(control); Binding site; Ribosome; Gene expression; Protein
• ISSN: 1087-0156; 1546-1696
• DOI: 10.1038/nbt.1568

Microbial engineering often requires fine control over protein expression-for example, to connect genetic circuits or control flux through a metabolic pathway. To circumvent the need for trial and error optimization, we developed a predictive method for designing synthetic ribosome binding sites, enabling a rational control over the protein expression level. Experimental validation of >100 predictions in Escherichia coli showed that the method is accurate to within a factor of 2.3 over a range of 100,000-fold. The design method also correctly predicted that reusing identical ribosome binding site sequences in different genetic contexts can result in different protein expression levels. We demonstrate the method's utility by rationally optimizing protein expression to connect a genetic sensor to a synthetic circuit. The proposed forward engineering approach should accelerate the construction and systematic optimization of large genetic systems.