Robust Multi-Layer Control Systems for Cooperative Cellular Behaviors

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The goal of this project is to develop and demonstrate a multi-layer intra- and inter-cellular control systems integrated to create complex, spatially-organized, multi-functional model system for wound healing. Our system makes use of a layered control architecture with feedback at the DNA, RNA, protein, cellular and population levels to provide programmed phenotypic differentiation and interconnection between multiple cell types.

This project is an active collaboration with John Doyle, Michael Elowitz and Niles Pierce. This page describes the activities taking place in Richard Murray's group.

Current participants:

  • Leopold Green (Postdoc, BE)
  • Chelsea Hu (Postdoc, BE)
  • Reed McCardell (PhD student, BE)
  • Ayush Pandey (PhD student, EE)
  • Mark Prator (Technician, EAS)
  • Xinying (Cindy) Ren (PhD student, CDS)

Additional participants:

  • Andrew Halleran (PhD student, BE)
  • Michaelle Mayalu (Postdoc, CMS)
  • Andrey Shur (PhD student, BE)

Collaborators:

  • John Doyle (Caltech CMS)
  • Michael Elowitz (Caltech BBE)
  • Niles Pierce (Caltech BBE)

Past participants:

  • Ania Baetica (Alumni, CDS)
  • Samuel Clamons (PhD student, BE)
  • Victoria Hsiao (PhD student, BE)
  • James Parkin (PhD student, BE)
  • Anandh Swaminathan (Alumni, CDS)

Objectives

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Phase I* objectives (Murray group):

  • Biological controllers: Integrate multiple feedback controllers in E. coli, demonstrating ability to simultaneously modulate multiple input/output pairs.
  • Testbeds: Expand micro- and macro-fluidic devicesfor temporal measurement and control of growth environments for integrated bacterial systems and individual mammalian systems.
  • Testbeds: Conceptualize, design and develop a laboratory testbed for measurement and control of bacterial systems that is capable of emulating a wound-healing environment.
  • Theory: Apply computational framework for sensor fusion to stochastic biological system data and integrate the results of the sensor fusion methods.
  • Theory: Design an integrated feedback controller that uses time- scale separation to run a fast “inner” control loop and a slow “outer” control loop.
  • Theory: Expand predictive models for multi-cellular systems in a cooperative control framework that allows robustness analysis and controller design of global input/output dynamics and interconnection structure.

References



The project or effort depicted was or is sponsored by the Defense Advanced Research Projects Agency (Agreement HR0011-17-2-0008). The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

  • Agency: DARPA
  • Grant number: HR0011-17-2-0008
  • Start date: 19 Oct 2016
  • End date: 18 Oct 2020
  • Support: 1-2 postdocs, 3 graduate students, 1 FTE technician
  • Reporting: Monthly updates + quarterly reports