Repository logo
 

Optimizing a synthetic signaling system, using mathematical modeling to direct experimental work

Simple item page
dc.contributor.authorHavens, Keira, author
dc.contributor.authorMedford, June, advisor
dc.contributor.authorPrasad, Ashok, advisor
dc.contributor.authorAntunes, Mauricio, committee member
dc.contributor.authorPeersen, Olve, committee member
dc.date.accessioned2007-01-03T06:42:49Z
dc.date.available2007-01-03T06:42:49Z
dc.date.issued2014
dc.description.abstractSynthetic biology uses engineering principles and biological parts to probe existing biological networks and build new biological systems. As biological components become better characterized, synthetic biology can make use of predictive mathematical models to analyze the activity of 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 showed that increasing the concentration of a single component of the synthetic signaling system, the PBP, results in a 100 fold increase in sensitivity, and an order of magnitude increase in fold change response in the response of the bacterial testing platform. Additional mathematical exploration of the system identified another component, the number of PhoB inducible promoters, which could be adjusted to further increase maximum signal. In addition, our model has suggested additional 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. Once validated, this modeling based protocol, using a microbial platform for developing and optimizing plant synthetic systems, will serve as a foundation for engineering advanced plant synthetic systems.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierHavens_colostate_0053N_12341.pdf
dc.identifier.urihttp://hdl.handle.net/10217/82601
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectkinetic model
dc.subjectmodel validation
dc.subjectquantitative biology
dc.subjectsignal transduction
dc.subjectsynthetic biology
dc.subjecttwo component systems
dc.titleOptimizing a synthetic signaling system, using mathematical modeling to direct experimental work
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineBiology
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Havens_colostate_0053N_12341.pdf
Size:
2.94 MB
Format:
Adobe Portable Document Format
Description:
Download

Collections

2000-2019
Theses and Dissertations