Model-guided Discovery and Optimization of Cell-based Sensors

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This is a MURI project led by Chris Voigt at MIT and involving Domitilla Del Vecchio (MIT), Michael Laub (MIT), Vincent Noireaux (UMN), Eduardo Sontag (Rutgers), Howard Salis (Penn State) and Jeff Tabor (Rice). The information on this page focuses primarily on the work involving my research group.

Current participants:

Additional participants:

Past participants:


  • Chris Voigt (MIT)
  • Domitilla Del Vecchio (MIT)
  • Michael Laub (MIT)
  • Vincent Noireaux (UMN)


  • Eduardo Sontag (Rutgers)
  • Howard Salis (Penn State)
  • Jeff Tabor (Rice)



We are applying tools from synthetic biology to construct high-performance and robust sensors that respond to non-natural signals. Our collaborators are focused on the design of sensors for the non-visible light spectrum (UV and IR) and magnetic fields, including the use of discovery methods to build first-generation genetic sensors. In practice, while these synthetic sensors are responsive under lab conditions, they lack the performance, reliability, and environmental robustness necessary for in-field applications. To this end, we are applying tools from control theory and a new concept for the in vitro characterization of genetic devices (“breadboarding”) to develop parts and design principles that make the sensors robust to environment, genetic context, and host.

  • Task 3.1: Analyze the robustness of alternative sensors designs that incorporate positive and negative feedback loops
  • Task 3.2: Quantify the impact of feedback loop timescales on sensor robustness
  • Task 3.3: Determine the design principles for robustness of of phosphorelay circuits to changes in the concentration of ATP and AcetylBP.


  • Agency: Office of Naval Research
  • Grant number: N00014-13-1-0074
  • Start date: 1 Feb 2013
  • End date: 30 Jan 2018
  • Support: ~2 graduate students + supplies
  • Reporting: annual reports due in June