Design and characterization of synthetic microRNA based gene expression circuits
Abstract/Contents
- Abstract
- The complexity of mammalian cells is largely due to the sophisticated control mechanisms employed to modulate the expression of endogenous genes. Various molecules in the cell are organized into circuits, which can respond to both changes in levels of intracellular molecules, as well as changes in the environment, by upregulating or downregulating the expression of any number of genes. The ability to interface with these endogenous programs to create novel molecular circuits would greatly advance our cellular engineering capabilities for a variety of applications. I first present a method to design and characterize synthetic circuits incorporating microRNAs (miRNAs). I derived and experimentally validated a model to capture the relationship between miRNA and target gene expression levels. I then extended the model to a more complex circuit incorporating an miRNA-based molecular switch to predict the impact of ligand levels on miRNA levels, and ultimately target gene expression levels, in the cell. Finally, I demonstrate the utility of this framework by using the model to inform the development of a synthetic circuit incorporating miRNAs responsive to intracellular protein levels, and show that this genetic circuit can serve as a sensitive, noninvasive sensor of nuclear protein concentration. Next, I extended the regulatory capabilities of synthetic miRNAs by developing a circuit that could perform OFF logic in response to levels of endogenous proteins within cells. This circuit was created by combining two different synthetic RNA-based regulators, a ligand-responsive ribozyme and a miRNA, to achieve the desired behavior. I developed a model that incorporates the component parameters and accurately described the behavior of this circuit. Finally, I combined a MS2-responsive ribozyme with a miRNA that targeted an MS2-dsRed fusion protein into this circuit architecture such that the system exerted negative feedback over MS2 levels within the cell. These powerful tools will enable the much more sophisticated engineering of biological systems as well as highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable, and predictable systems-level behaviors.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2014 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Bloom, Ryan J |
|---|---|
| Associated with | Stanford University, Department of Bioengineering. |
| Primary advisor | Smolke, Christina D |
| Thesis advisor | Smolke, Christina D |
| Thesis advisor | Covert, Markus |
| Thesis advisor | Kay, Mark Allan |
| Advisor | Covert, Markus |
| Advisor | Kay, Mark Allan |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Ryan J Bloom. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2014. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2014 by Ryan J Bloom
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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