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== Project Details== | == Project Details== | ||
| + | ===Introduction to Zinc Fingers === | ||
| + | === Introduction to Genetic Toggle Switches === | ||
| + | The Genetic Toggle Switch was among the first artificially constructed Gene Regulatory Networks. The original Genetic Toggle Switch consisted of the ptrc-2 (lacI repressible) promoter paired with the temperature sensitive lambda repressor and the PLs1con (lambda repressible) promoter paired with the lacI repressor. Subsequently, induction of the ptrc-2 promoter would repress the PLs1con promoter through expression of the lambda repressor, while induction of the PLs1con promoter would repress the ptrc-2 promoter through expression of the lacI repressor. Switching of the toggle switch from one promoter to another was accomplished by addition of either Isopropyl β-D-1-thiogalactopyranoside (IPTG), which causes the lacI to unbind allowing the ptrc-2 to switch on, or a thermal pulse, which causes the lambda repressor to unbind and allow the PLs1con promoter to switch on. In order to characterize the toggle switch, a GFPmut3 structural gene was placed downstream of the Ptrc-2 promoter so that induction of the Ptrc-2 promoter would result in high expression of GFPmut3 while induction of PLs1con would result in low expression of GFPmut3. | ||
| + | '''Characteristics of Genetic Toggle Switches''' | ||
| + | In general, Genetic Toggle Switches have several characteristics which make them unique from other Gene Regulatory networks. For example, Genetic Toggle Switches must be capable of bi-stable behavior, meaning that they should only exist in one of two stable states instead of in a variety of intermediate states. Bi-stability also suggests that a certain threshold must be passed before the toggle switch can switch from one state to another. In addition, toggle switches should have low basal transcriptional noise to prevent random switching without outside induction. Finally, a reporter or marker structural gene, such as a fluorescent protein, should be present in order to characterize the effectiveness of the toggle switch. | ||
| + | |||
| + | === Design of Zinc Finger Transcription Factors === | ||
Revision as of 03:51, 29 September 2011
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Overall project
Additions to the synthetic biologists' toolkit are expected to be interoperable and modular in order to facilitate standardization of these tools. The Genetic Toggle Switch originally presented by Gardner et al (2000) was a major breakthrough in synthetic biology and utilized constitutive promoters. Here, we use Zinc Fingers as transcriptional repressors in a newly designed interfacing network, the controller, for a modified version of the original toggle switch. The controller interface is made with emphasis on interoperability and applications in mind. Specifically, we use zinc finger repressors and degradation tags to reduce cross-talk and make the network more robust. Nine ZF transcription factors are computationally characterized and submitted to the registry. The interfacing controller and toggle switch are stochastically modeled to predict gene expression levels and are subjected to experimental testing.
Project Details
Introduction to Zinc Fingers
Introduction to Genetic Toggle Switches
The Genetic Toggle Switch was among the first artificially constructed Gene Regulatory Networks. The original Genetic Toggle Switch consisted of the ptrc-2 (lacI repressible) promoter paired with the temperature sensitive lambda repressor and the PLs1con (lambda repressible) promoter paired with the lacI repressor. Subsequently, induction of the ptrc-2 promoter would repress the PLs1con promoter through expression of the lambda repressor, while induction of the PLs1con promoter would repress the ptrc-2 promoter through expression of the lacI repressor. Switching of the toggle switch from one promoter to another was accomplished by addition of either Isopropyl β-D-1-thiogalactopyranoside (IPTG), which causes the lacI to unbind allowing the ptrc-2 to switch on, or a thermal pulse, which causes the lambda repressor to unbind and allow the PLs1con promoter to switch on. In order to characterize the toggle switch, a GFPmut3 structural gene was placed downstream of the Ptrc-2 promoter so that induction of the Ptrc-2 promoter would result in high expression of GFPmut3 while induction of PLs1con would result in low expression of GFPmut3.
Characteristics of Genetic Toggle Switches In general, Genetic Toggle Switches have several characteristics which make them unique from other Gene Regulatory networks. For example, Genetic Toggle Switches must be capable of bi-stable behavior, meaning that they should only exist in one of two stable states instead of in a variety of intermediate states. Bi-stability also suggests that a certain threshold must be passed before the toggle switch can switch from one state to another. In addition, toggle switches should have low basal transcriptional noise to prevent random switching without outside induction. Finally, a reporter or marker structural gene, such as a fluorescent protein, should be present in order to characterize the effectiveness of the toggle switch.
Design of Zinc Finger Transcription Factors
Network Design
A variety of Network designs using zinc finger transcription factors were considered before we settled on the Genetic Toggle Switch. Some of the rejected designs included novel uses of AND/OR gates to create a "bacterial encryption security" system. Network design began with simple white board drawings before moving on to more sophisticated drawing and modeling software.
In redesigning the genetic toggle switch we sought to retain the following important characteristics of the original toggle switch.
-Bi-stability
-Low Basal Transcriptional Noise
-Toggling via Chemical Inducers
-Usage of Constitutive Repressible Promoters
-Usage of fluorescent proteins to indicate stable states
In order to redesign the genetic toggle switch we used a variety of programs including ApE (A plasmid Editor) to string together the sequences for our plasmids and TinkerCell to create a diagram of our network as well as to model the network dynamics using stochastic differential equations.
