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

Information

  • NSF Award
  • 1648176
Owner
  • Award Id
    1648176
  • Award Effective Date
    12/15/2016 - 8 years ago
  • Award Expiration Date
    5/31/2017 - 7 years ago
  • Award Amount
    $ 225,000.00
  • Award Instrument
    Standard Grant

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

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. <br/><br/>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.

  • Program Officer
    Ruth M. Shuman
  • Min Amd Letter Date
    12/11/2016 - 8 years ago
  • Max Amd Letter Date
    12/11/2016 - 8 years ago
  • ARRA Amount

Institutions

  • Name
    Enevolv, Inc.
  • City
    Cambridge
  • State
    MA
  • Country
    United States
  • Address
    83 Cambridge Parkway W806
  • Postal Code
    021421241
  • Phone Number
    8065434788

Investigators

  • First Name
    Noah
  • Last Name
    Taylor
  • Email Address
    n.taylor@enevolv.com
  • Start Date
    12/11/2016 12:00:00 AM

Program Element

  • Text
    SMALL BUSINESS PHASE I
  • Code
    5371

Program Reference

  • Text
    SMALL BUSINESS PHASE I
  • Code
    5371
  • Text
    Biotechnology
  • Code
    8038