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Synthetic Circuits for Feedback and Detection in Bacteria

Citation

Hsiao, Victoria (2016) Synthetic Circuits for Feedback and Detection in Bacteria. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9WD3XJW. http://resolver.caltech.edu/CaltechTHESIS:05082016-170628018

Abstract

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Synthetic biology, synthetic gene circuits, integrases, two-component system, ODE models, stochastic models, E. coli
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Bioengineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Murray, Richard M.
Thesis Committee:
  • Elowitz, Michael B. (chair)
  • Murray, Richard M.
  • Pierce, Niles A.
  • Rothemund, Paul W. K.
Defense Date:25 April 2016
Funders:
Funding AgencyGrant Number
Institute for Collaborative BiotechnologiesW911NF-09-0001
NDSEG FellowshipUNSPECIFIED
Record Number:CaltechTHESIS:05082016-170628018
Persistent URL:http://resolver.caltech.edu/CaltechTHESIS:05082016-170628018
DOI:10.7907/Z9WD3XJW
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1021/sb500024bDOIPublished journal article for biomolecular tracker project in ACS Synthetic Biology
http://dx.doi.org/10.1101/029967DOIBioRxiv of manuscript for population-based event detector project
ORCID:
AuthorORCID
Hsiao, Victoria0000-0001-9297-1522
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9705
Collection:CaltechTHESIS
Deposited By: Victoria Hsiao
Deposited On:25 May 2016 16:20
Last Modified:25 May 2016 20:25

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