(353b) Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription-Translation (TX-TL) Systems | AIChE

(353b) Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription-Translation (TX-TL) Systems

Authors 

Takahashi, M. K. - Presenter, Cornell University
Hayes, C. A., California Institute of Technology
Sun, Z. Z., California Institute of Technology
Kim, J., Korea Advanced Institute of Science and Technology
Singhal, V., California Institute of Technology
Spring, K. J., University of Texas Medical School at Houston
Al-Khabouri, S., Universitex de Montreal
Fall, C. P., University of Illinois
Noireaux, V., University of Minnesota
Murray, R. M., California Institute of Technology
Lucks, J. B., Cornell University

The ability to engineer synthetic genetic networks using RNA regulators has solidified them as powerful components of the synthetic biology toolbox. A potential strength of RNA regulators is that they have fast degradation rates compared to proteins, and may be able to propagate signals through networks on the timescale of RNA degradation. However, a current bottleneck to understanding signal propagation through genetic networks is the slow design-build-test cycle of evaluating them in vivo. In this work we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA transcriptional networks. The flexibility of the TX-TL system allowed us to design an experiment to measure the response time of a two-stage RNA transcription cascade, which we found to be approximately 10 minutes, or about 5 minutes per step of the cascade. We then show that this response time can be adjusted by regulator threshold tuning, which we achieved using tandem RNA regulators in front of target genes. This allowed us to prototype a new RNA network, an RNA single input module (RNA SIM), which was predicted to sequentially activate the expression of two different genes. Finally, we show that the RNA SIM functions as designed in vivo. This work lays the foundation for using TX-TL as a tool for RNA circuit prototyping. We conclude with thoughts on what needs to be done to quantitatively translate TX-TL circuit characterization into predictions for in vivo circuit function.