Probabilistic Design of RNA Based Genetic Components: Next Generation Rgr Devices

The current disconnect between designing biological systems and realizing their construction within biological chassis necessitates multiple iterations within the design-build-test engineering framework. It has been demonstrated that by considering genetic components at the level of RNA in terms of structure and free energy it is possible to predict integrated part performance. Recently, Cas9 proteins have been repurposed and extended to be modular transcriptional regulators. To construct genetic networks based on the Cas9 platform it is necessary to both robustly and efficiently express guide RNA (gRNA) and have that gRNA function in an orthogonal and predictable manner. Previous work has efficiently expressed gRNA from robust and well characterized pol II promoters by flanking gRNA with self-cleaving ribozymes (RGRs).  Our work will demonstrate how probabilistic non-comparative RNA structure prediction methods as well as kinetic based RNA folding-path simulations can inform the design and implementation of the original RGR framework as well as develop more sophisticated expression devices. Finally, the aforementioned tools are used to develop rules for the predictable and orthogonal implementation of Cas9 based genetic systems.