Rational Design and Characterization of Synthetic Promoters for Artificial Network Engineering

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Drew Michael, Michael Brent

Center for Genome Sciences and Systems Biology, United States

One of the primary challenges in synthetic transcriptional network engineering is the difficulty in choosing the correct system components to achieve the desired system behavior. Every modifiable aspect of the system, from promoters and ORFs to protein degrons and transcriptional terminators has the potential to impact the performance of the final network. The requirement to select system components with variable quantitative characteristics creates a multi-dimensional space of possible choices, of which only a sub-set of possible network configurations are likely to produce the desired outcome. In synthetic networks of limited size, it is possible to search through component combinations to find a working configuration, but as a system grows in size, this search process becomes prohibitively expensive. As a result, synthetic networks have averaged less than 6 promoters per system. As a proof of principle, we have developed a modular promoter assembly and characterization process that allows the rational assembly and characterization of synthetic promoter libraries containing non-native transcription factor binding sites. Using this technique, we have assembled a library of promoters with binding sites for two non-yeast transcription factors. The assembled promoters were integrated into the yeast genome and regulatory factors with binding sites in each promoter were titrated into the cell via drug inducible promoters. Synthetic promoter output across a range of input transcription factor concentrations was then measured by the Quantigene platform. Preliminary results indicate that the titration system accurately captures the full dynamic range of the interaction between the titrated factor and the target promoter. The application of this transcription factor titration system will enable the accurate parameterization of transcription factors whose activity cannot be directly controlled by small molecules, expanding the space of well characterized components for future synthetic network engineering.