Next-Generation Design of RNA Devices Incorporating Stochastic RNA Folding Kinetics and Ribosome Drafting

The performance of RNA devices (ribosome binding sites, riboswitches, ribozymes, and regulatory RNAs) are determined by their sequence-structure-function relationships. Existing models have largely focused on how the energetics of RNA folding shape this relationship, and often ignore the stochastic dynamics of RNA folding. We introduce and experimentally confirm a new mechanism, called Ribosome Drafting, that correctly predicts how slow-folding mRNAs can accelerate protein synthesis by over 1000-fold in bacteria. During cycles of translation, Ribosome Drafting emerges whenever successive ribosomes bind to a mRNA faster than the mRNA can refold, maintaining it in a non-equilibrium state. To explain this effect, we developed a non-equilibrium Markov model of Ribosome Drafting and utilized computational RNA design, kinetic TCSPC (time-correlated single photon counting), and expression measurements to successfully validate its quantitative predictions. To facilitate RNA device design, we introduce new foundational tools to program RNAs with desired folding pathways and rates. We also discuss how the stochastic dynamics of shape-changing RNA devices can be programmed to enhance their signal processing, memory, and actuating capabilities.