Biosensors and Directed Evolution

Diverse areas of biotechnology, including directed evolution, synthetic biology, and bioengineering, are impeded by a lack of general methods to link chemical and biochemical processes to defined genetic outputs. We are developing new classes of biosensors that “encode” specific chemical and biochemical events in defined RNAs for subsequent storage, analysis, or cellular control. This approach is powerful for several reasons: 1) nucleic acids can store large amounts of information, permitting the collection of highly multiplexed datasets, 2) nucleic acid analysis technologies are robust, cost-effective, and sensitive, permitting the detection of low levels of activities and providing a path toward clinical deployment, and 3) nucleic acid signals can be used to manipulate cell behavior, leading to a new approach to cell engineering.

Our group has developed proximity-dependent split RNA polymerase (RNAP)-based biosensors. We engineered previously-reported split RNAPs to be proximity dependent using rapid continuous evolution. The resultant evolved biosensors have a large dynamic range and can detect a multitude of input signals, including protein-protein interactions (PPIs), small molecules, and light. We have deployed the RNAP-based biosensors in mammalian synthetic biology applications including multidimensional PPI detection and CRISPR/Cas9 control. However, most importantly, our biosensors have opened up new opportunities for using powerful in vivo directed evolution systems, such as PACE, to solve problems in chemistry and biology. For example, we are developing new evolutionary tools to rapidly evolve protein interfaces, enzymes, and even peptide-based small molecule inhibitors.

Example publications: 

ACS Chem. Biol. 13, 431-437 (2018). link

J. Am. Chem. Soc. 139, 11964-11972 (2017). link

Nat. Chem. Biol. 13, 432-438 (2017). link

 J. Am. Chem. Soc. 136, 15996–15999 (2015). link