(646b) De Novo Design of Heat-Repressible RNA Thermosensors in E. coli

Authors: 
Hoynes-O'Connor, A., Washington University in St. Louis
Moon, T. S., Washington University in St. Louis
Kirchner, L., Washington University in St. Louis
Hinman, K., Washington University in St. Louis

Inducible gene expression systems are powerful tools for optimizing metabolic pathways or generating logical behavior in an organism. However, in most systems, chemical inducers must be added exogenously, leading to extra costs and potential barriers to scale-up. Expression systems that are induced by environmental changes avoid the need for costly chemical additions and allow bacteria to respond directly to growth conditions. The overall goal of this research is to develop small, synthetic, heat-repressible RNA thermosensors. These thermosensors are located in the 5' UTR upstream of the Shine-Dalgarno site, where they contain a cleavage site for ribonuclease E, an enzyme native to Escherichia coli that binds at the cleavage site and degrades the mRNA. At low temperatures, the recognition site is sequestered in a stem-loop structure, turning on gene expression. At high temperatures, the stem-loop unfolds and exposes the recognition site, and thus the mRNA is degraded, turning off gene expression. Synthetic heat-repressible RNA thermosensors were designed and tested in vivo by varying length, number of recognition sites, size of the loop, and predicted melting temperature of the stem. The RNA thermosensors worked as expected, with high expression levels at low temperatures. Several experiments were performed to support the hypothesized mechanism, and to demonstrate that these thermosensors respond exclusively to temperature. Furthermore, these thermosensors were shown to function in a multi-input genetic circuit. Finally, design guidelines are presented, based on the behavior of the 24 designed thermosensors. These heat-repressible thermosensors are small, do not require expression of protein regulators, and can function independently of expensive chemical inducers. In addition, they are relatively simple to design and can be implemented in the optimization of a range of metabolic processes.