Design and Characterization of E. coli Transcriptional Factors for Use as Biosensors in Synthetic Biology

Biosensors are detection tools which use a biological recognition element to provide selective and quantitative information about changes in the availability of a specific input signal. Metabolite-sensing bacterial transcriptional factors (TFs) are a class of biosensors which interact with small molecule ligands (input signal) and lead to subsequent changes in a target gene expression. These bacterial TF-based biosensors are widely used in high-throughput screening (HTS) or selection, and in dynamic gene regulation for bacterial and mammalian host systems. Repurposing of the naturally existing bacterial transcription factor proteins as biosensors typically requires protein engineering to capture/retain the desirable biosensing properties. In this thesis, I first describe the combined use of computational and evolutionary protein design to isolate AraC-based biosensors with enhanced specificity towards orsellinic acid (OA), as compared to their triacetic acid lactone (TAL)-specific parent (AraC-TAL14). Variant AraC-OA7, isolated after one round of directed evolution, showed 10-fold increase in OA specificity and retained a low background expression level, comparable to that of wild-type AraC. Further directed evolution led to variant AraC-OA8, with 15-fold increased OA specificity compared to AraC-TAL14, still retaining low background. AraC-OA8 has potential utility as biosensor for improving OA biosynthesis through engineering of related biosynthesis pathways. I next describe the design of a salicylate (SA)-inducible, “SAON” gene expression system for regulating transgene expression in human Jurkat cell lines. The SAON system, comprising a modified MarR protein from E. coli along with a MarR-regulated promoter, initially demonstrated a 1.5-fold increase in reporter protein (EGFP) expression in engineered Jurkat cells, when induced with SA. Fusion of the MarR protein with a nuclear-tagged maltose binding protein further led to a total of 2.1-fold increase in EGFP expression in presence of SA. Further optimization of this SAON system to reduce background (leaky) expression will enable its use for tight and inducible gene regulation in engineered Jurkat cell lines. Overall, the bacterial TF-based biosensors described in this work will enable researchers to gain desirable control over gene expression for varied synthetic biology applications.