Programmable Molecular Technology Initiative

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The information on this page focuses primarily on the work involving my research group.

Project participants:

  • Nancy Cao (Alumni, )
  • Clare Hayes (Alumni, EAS)
  • Lani Kim (Alumni, Ch/Ec)
  • Andrey Shur (Alumni, BE)
  • Yong Wu (Alumni, ChE)
  • Emzo de los Santos (PhD student, BE → U. Warwick)
  • Dan Siegal (-Gaskins) (postdoc, BE → Schafer Corp)*
  • Nadine Dabby (Postdoc, BE)
  • Vanessa Jonsson (PhD student, CDS)*
  • Joe Meyerowitz (PhD student, BMB)

Collaborators:

  • Niles Pierce (Caltech BBE)
  • Frances Arnold (CCE, BE)
  • Steve Mayo (BBE)

Objectives

Pmti11.png

Biological organisms depend on remarkable molecular machines whose function is encoded within the molecules themselves – nucleic acid and protein sequences programmed by evolution to catalyze reactions, synthesize molecules, haul cargo, regulate development, and defeat pathogens. The proposed Programmable Molecular Technology Initiative (PMTI) will extend and exploit principles for engineering these versatile biomolecules with the mission of pioneering high-impact technologies centered in three focus areas: molecular instruments for readout and regulation of cell state, programmable molecular logic for selectively treating diseased cells while leaving normal cells untouched, and efficient microbial synthesis of biofuels from non-food renewable resources.

  • Efficient microbial synthesis of biofuels from non-food renewable resources: We seek to achieve dramatic reductions in the cost of producing biofuels using re-programmed metabolic pathways in microbes, supporting an industrial revolution in the production of liquid fuels from renewable non-food resources. The focus of our work is in the re-programmed yeast stress response pathway that tolerates toxins generated during biofuel synthesis.
  • Principles and foundations for programming molecular function: We seek to establish the underpinnings for future generations of programmable molecular technologies, including (1) languages, simulators and compilers for automated analysis and design of nucleic acid systems, (2) programmable self-organization of active molecular structures and (3) feedback control mechanisms for programming developmental patterning.

References



This research is funded by the Gordon and Betty Moore Foundation through Grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative.

  • Agency: Gordon and Betty Moore Foundation
  • Grant number: GBMF2809
  • Start date: 1 Jun 2012
  • End date: 30 Sep 2017
  • Support: ~2 graduate students + supplies
  • Reporting: annual reports due in December