This research seeks to further develop the general framework for optimizing human-engineered biological circuits. Here, mathematical modeling identifies mutational targets for directed evolution. This identification constrains the evolutionary search space, while directed evolution re-engineers the targets without mechanistic or detailed structural information. This proposal advocates using directed evolution to first systematically perturb the mutational target to generate components with a wide range of functionality, then to evaluate circuit behavior for each component. The benefits of this technique are (1) the library of components can be used interchangeably with other circuits, and (2) systematic perturbation permits model validation and refinement. This strategy will be used to examine the Lux quorum-sensing module, which regulates gene expression in bacteria as a function of the population density. Because bacteria thrive in diverse conditions, this technology has potential applications in biosensing and biomedicine. Additionally, characterizing this module should address several fundamental questions: how bacteria regulate cell-cell communication, how the configuration found in nature might have evolved, and whether or not cell-cell communication can coordinate population behavior in the presence of intracellular stochasticity and cell-to-cell variation. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32CA120055-02
Application #
7295964
Study Section
Special Emphasis Panel (ZRG1-F14-A (20))
Program Officer
Jakowlew, Sonia B
Project Start
2006-09-01
Project End
2009-08-31
Budget Start
2007-09-01
Budget End
2008-08-31
Support Year
2
Fiscal Year
2007
Total Cost
$48,796
Indirect Cost
Name
California Institute of Technology
Department
Type
Schools of Engineering
DUNS #
009584210
City
Pasadena
State
CA
Country
United States
Zip Code
91125
Srivastava, Rishi; Haseltine, Eric L; Mastny, Ethan et al. (2011) The stochastic quasi-steady-state assumption: reducing the model but not the noise. J Chem Phys 134:154109
Haseltine, Eric L; Yin, John; Rawlings, James B (2008) Implications of decoupling the intracellular and extracellular levels in multi-level models of virus growth. Biotechnol Bioeng 101:811-20
Haseltine, Eric L; Arnold, Frances H (2008) Implications of rewiring bacterial quorum sensing. Appl Environ Microbiol 74:437-45
Mastny, Ethan A; Haseltine, Eric L; Rawlings, James B (2007) Two classes of quasi-steady-state model reductions for stochastic kinetics. J Chem Phys 127:094106