Keira L. Havens: Master’s Thesis Defense
Optimizing a synthetic signaling system, using mathematical modeling to direct experimental work
CSU Biology Department
Advisor: June Medford
Synthetic biology uses engineering principles and biological parts to probe existing biological networks and build new biological systems. This thesis demonstrates the utility of modeling in optimizing a synthetic signaling system for a bacterial testing platform and advances the use of model-based bacterial systems as an effective tool of plant synthetic biology.
Using models in combination with experimental data, I was able to show that increasing the concentration of a single component of the synthetic signaling system resulted in a 100 fold increase in sensitivity, and an order of magnitude increase in fold change in the response of the bacterial testing platform. Additional mathematical exploration of the system identified another component, which could be adjusted to further increase maximum signal. In addition, the model has suggested other avenues of research, including the potential to introduce new functions, such as memory, to the existing circuit. In this way the prototype synthetic signaling system developed by the Medford Lab has been refined to improve detection and generate substantial response, moving the technology closer to real-world use.
Event Date: 2013-12-20
Event Start Time: 10:30 AM
Event End Time:
Event Location: Yares 208