SBIR Phase I: Programmable Intracellular Sensors for Direct In Vivo Screening of Target Molecule Production in Yeast

Period of Performance: 12/15/2016 - 05/31/2017


Phase 1 SBIR

Recipient Firm

Enevolv, Inc.
83 Cambridge Pkwy W806 Array
Cambridge, MA 02142
Firm POC, Principal Investigator


The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a tool to allow for more rapid screening of engineered yeast strains for the production of desirable biochemical compounds. Industries such as specialty chemicals, food, energy, personal care, and pharmaceuticals are increasingly using engineered microorganisms, especially yeast, for biochemical production. A key challenge in strain engineering is screening. In order to find the optimal genetic changes that direct a strain to produce the target molecule efficiently, companies have to build and screen large numbers of strains. Current best practices using automation allow companies to screen strains at a cost of approximately $1-5 per strain with a throughput of hundreds to a thousand strains per day. The proposed yeast sensors enable ultra high-throughput screening of yeast strains, allowing the measurement of tens of millions of strains per day at a cost below $0.00002 per strain. This technology will not only substantially improve the economics and success rate of strain engineering projects, but it will allow the exploration of much more complex design spaces and enable otherwise intractable projects. This SBIR Phase I project proposes to create a platform for the rapid engineering of designer biosensors in yeast that are capable of sensing and responding to any desired molecule. Cells have evolved a large number of sensory proteins that allow them to dynamically interact with their environment. The proposed technology is to re-engineer these natural biosensors to sense and respond to chemicals of commercial or scientific interest. The proposed approach computationally models the interaction of each sensor and target molecule, predicting protein mutations that improve binding to the desired molecule. It is possible to then rapidly construct and test vast numbers of these predicted sensors, identifying those with the requisite sensing and response characteristics in yeast. The resulting sensors will allow the rapid engineering of yeast strains by altering yeast cell behavior in response to the target chemical, making them powerful tools that have broad applications in strain engineering, diagnostics, and synthetic biology.