Rational Design of Large Crispr/dCas9 Transcriptional Logic Circuits in Eukaryotic Cells

Natural cells perform incredible feats of computation through a beautiful orchestra of inter-connected and interacting molecules. A grand challenge in synthetic biology is to emulate the complexities of natural cellular systems to create new sophisticated cellular behaviors through the introduction of synthetic molecular functions. The creation of new molecular functions that are orthogonal, inter-connectable, and scalable is essential for engineering complex molecular networks. However, many natural molecular functions often exhibit unpredictable behaviors when used outside of their natural genetic context, impeding the engineering of grand molecular networks in vivo. To address these issues, we engineered a set of un-natural transcriptional components in S. cervisiae that can be interconnected and assembled into large genetic circuits. Our system is comprised of a large set of orthogonal synthetic transcriptional CRISPR/dCas9 ‘NOR’ gates. We leveraged a RNA-guided synthetic chromatin remodeler, a dCas9-mxi1 fusion, to substantially improve dCas9 guided transcriptional repression and used computer-aided design to create a set of orthogonally interacting guide-RNAs and promoter components. Since all of the components are orthogonal to the native S. cervisiae host, our transcriptional system exhibits exceptional predictability and scalability with minimal cell loading. We demonstrate the power of our synthetic NOR gates by assembling them into large circuits that perform basic combinatorial computation (NOT, OR, AND, NAND, XOR, XNOR functions) and long delay cascading circuits (up to seven interconnected NOR gates). Complementing this system, we also constructed a biochemical model that predicts synthetic network behavior through global parameter optimization and Monte Carlo simulation. The model allows for predictable forward-engineering of synthetic gene circuits through dynamic behavior prediction and examination of parameter sensitivity estimation. Our approach has enabled the construction of among the largest eukaryotic gene circuits to date. We envision future iterations of the system will form the basis for large, synthetic, decision-making systems in living cells.