Difference between revisions of "Team:William and Mary/Description"

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<div style = 'padding-left: 190px; padding-bottom: 10px;font-size: 25px' ><b>Motivation</b></div>
  
<center>  <div style = 'padding-right: 70px; padding-left: 70px;' >ATTRIBUTIONS </div> </center>
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One of the main goals of synthetic biology is to create a modular genetic basis for the independent control of circuit behavior properties. Much progress has been made in achieving this aim for properties like gene expression strength (where well-characterized ribosome binding sites (RBSs) can be swapped within a genetic part), circuit architecture (where promoters can be swapped out to introduce connections and feedback architectures), and even gene expression noise (through a combination of the above two modulations). However, in order to move into the next phase of synthetic biology, we need to be able to control the dynamical properties of circuits— we want to move beyond circuits that focus on endpoint, steady-state values and explore the rich variety of dynamical systems. Fundamentally, gaining controlling of dynamical systems implies gaining control of temporal dynamics. 
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One of the main goals of synthetic biology is to create a modular genetic basis for the independent control of circuit behavior properties. Much progress has been made in achieving this aim for properties like gene expression strength (where well-characterized ribosome binding sites (RBSs) can be swapped within a genetic part), circuit architecture (where promoters can be swapped out to introduce connections and feedback architectures), and even gene expression noise (through a combination of the above two modulations).
 
However, in order to move into the next phase of synthetic biology, we need to be able to control the dynamical properties of circuits— we want to move beyond circuits that focus on endpoint, steady-state values and explore the rich variety of dynamical systems. Fundamentally, gaining controlling of dynamical systems implies gaining control of temporal dynamics. 
 
  
Currently, there is no good way to control the temporal dynamics of gene expression. Current control strategies require either a rewiring of the circuit architecture to achieve different time-dependent dynamics [1, 2] or a complete circumvention of transcriptional circuitry altogether, relying on post-translational dynamics like phosphorylation [3] or protein-protein interactions [4] to transmit information through a circuit. These approaches are often inaccessible to iGEM teams because they require too drastic an overhaul of existing circuit implementations.
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To alleviate this issue, and to enable future iGEM teams to create robust dynamical circuits, we created a protein degradation based ‘plug-and-play’ style system that allows modular and predictable control of the gene expression speed of a given circuit without requiring a fundamental redesign of existing circuit architecture.
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Currently, there is no good way to control the temporal dynamics of gene expression. Current control strategies require either a rewiring of the circuit architecture to achieve different time-dependent dynamics [1, 2] or a complete circumvention of transcriptional circuitry altogether, relying on post-translational dynamics like phosphorylation [3] or protein-protein interactions [4] to transmit information through a circuit. These approaches are often inaccessible to iGEM teams because they require too drastic an overhaul of existing circuit implementations. To alleviate this issue, and to enable future iGEM teams to create robust dynamical circuits, we created a protein degradation based ‘plug-and-play’ style system that allows modular and predictable control of the gene expression speed of a given circuit without requiring a fundamental redesign of existing circuit architecture.
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<center><div style = 'padding-right: 0px; padding-bottom: 20px;font-size: 25px' >General Support</div> </center>
 
  
<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 30px;' >We would like to extend our sincerest thanks to our team advisor and PI, Dr. Margaret Saha. Her endless dedication and enthusiasm towards our research and well-being could not be more greatly appreciated.
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We would like to thank Dr. Gregory Smith, Co-PI, for his mathematical modeling expertise and his general advisement of our math team. We also want to thank Dr. Eric Bradley for his tireless assistance with lab facilities and management. </div>
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<div style = 'padding-left: 190px; padding-bottom: 10px;font-size: 25px' ><b>Degradation Based Control of Gene Expression Speed</b></div>
  
  
<center><div style = 'padding-right: 0px; padding-bottom: 20px;font-size: 25px' >Modeling Support</div></center>
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<div style = 'padding-right: 190px; padding-left: 190px;line-height: 30px; text-indent: 50px;' >John Marken, Graduate Research Student, provided us with mathematical modeling advice and invaluable assistance with data analysis. His guidance during brainstorming was also pivotal in determining our project idea.</div> </div>
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<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >Preliminary mathematical analysis reveals that degradation rate is the key factor in controlling gene expression speed. Consider the simple kinetic model....</div>
  
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<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >Thus in order to create a plug-and-play style system to control gene expression speed, we developed and characterized a suite of BioBrick parts which allow for simple, modular and predictable changes to the gene expression speed of arbitrary proteins.</div>
  
<div style = 'padding-right: 190px; padding-left: 190px;line-height: 30px; text-indent: 50px;' >We would like to thank Dr. Hannes Schniepp, Dr. Oliver Kerscher, and Dr. Joshua Puzey for partcipating in our Bioengineering Speaker Series.</div>
 
  
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<center><div style = 'padding-right: px; padding-bottom: 20px;font-size: 25px' >Funding Support </div></center>
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<div style = 'padding-left: 190px; padding-bottom: 10px;font-size: 25px' ><b>Orthogonal Degradation Tags</b></div>
  
<div style = 'padding-right: 190px; padding-left: 190px;line-height: 30px; text-indent: 50px;'>First and foremost, we would like to thank Dr. Dennis Manos, Vice Provost of Research. He provided us with vital financial and intellectual support, and made the time-lapse microscopy aspect of our project possible. We would also like to thank the following organizations and offices for generously providing us with the financial support necessary for realizing our project: </div>
 
  
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<center><div style = 'padding-right: 70px; padding-left: 70px;font-size: 15px; padding-bottom: 20px;' >Dean Kate Conley, Dean of the Faculty, Arts and Sciences</div>
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<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >When we were created our gene expression control system, we wanted to make sure that it was both usable across a variety of biological systems and circuits, and easily accessible to other iGEM teams. To this end, we chose to use the Mesoplasma florum Lon (mf-Lon) protease system discovered by Gur and Sauer in 2008, and developed by Collins and Cameron in 2014. This system consists of of a AAA+ protease and its associated protein degradation tags (pdt), which operate in a mechanistically similar manner to the E. Coli endogenous protease ClpXP and its associated ssrA tags. However, unlike ClpXP and ssrA tags, mf-Lon and pdts are completely orthogonal to the endogenous protein degradation systems in E. coli. Using this orthogonal degradation system helps eliminate cross talk between our system and endogenous E. coli proteins. Further, since there are pdts with a wide range of different affinities, we are able to tune degradation rate, and thus gene expression speed to a wide variety of values. This represents not only a practical advancement in the tuning of circuits, but also serves as the first report of the previously unconfirmed mathematical prediction of the relationship between degradation rate and gene expression speed.</div>
<div style = 'padding-right: 70px; padding-left: 70px;font-size: 15px; padding-bottom: 20px;' >Howard Hughes Medical Institute Science Education Grant to the College of William and Mary</div>
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<div style = 'padding-right: 70px; padding-left: 70px;font-size: 15px; padding-bottom: 20px;' >GenScript  </div>
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<div style = 'padding-right: 70px; padding-left: 70px;font-size: 15px' >Epoch Life Science Inc.</div></center>
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<div style = 'padding-left: 190px; padding-bottom: 10px;font-size: 25px' ><b>Modeling</b></div>
  
  
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<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >Math stuff. Plus we need a click through to results</div>
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Revision as of 20:43, 30 October 2017




Motivation
One of the main goals of synthetic biology is to create a modular genetic basis for the independent control of circuit behavior properties. Much progress has been made in achieving this aim for properties like gene expression strength (where well-characterized ribosome binding sites (RBSs) can be swapped within a genetic part), circuit architecture (where promoters can be swapped out to introduce connections and feedback architectures), and even gene expression noise (through a combination of the above two modulations). However, in order to move into the next phase of synthetic biology, we need to be able to control the dynamical properties of circuits— we want to move beyond circuits that focus on endpoint, steady-state values and explore the rich variety of dynamical systems. Fundamentally, gaining controlling of dynamical systems implies gaining control of temporal dynamics.
Currently, there is no good way to control the temporal dynamics of gene expression. Current control strategies require either a rewiring of the circuit architecture to achieve different time-dependent dynamics [1, 2] or a complete circumvention of transcriptional circuitry altogether, relying on post-translational dynamics like phosphorylation [3] or protein-protein interactions [4] to transmit information through a circuit. These approaches are often inaccessible to iGEM teams because they require too drastic an overhaul of existing circuit implementations. To alleviate this issue, and to enable future iGEM teams to create robust dynamical circuits, we created a protein degradation based ‘plug-and-play’ style system that allows modular and predictable control of the gene expression speed of a given circuit without requiring a fundamental redesign of existing circuit architecture.
Degradation Based Control of Gene Expression Speed
Preliminary mathematical analysis reveals that degradation rate is the key factor in controlling gene expression speed. Consider the simple kinetic model....
Thus in order to create a plug-and-play style system to control gene expression speed, we developed and characterized a suite of BioBrick parts which allow for simple, modular and predictable changes to the gene expression speed of arbitrary proteins.
Orthogonal Degradation Tags
When we were created our gene expression control system, we wanted to make sure that it was both usable across a variety of biological systems and circuits, and easily accessible to other iGEM teams. To this end, we chose to use the Mesoplasma florum Lon (mf-Lon) protease system discovered by Gur and Sauer in 2008, and developed by Collins and Cameron in 2014. This system consists of of a AAA+ protease and its associated protein degradation tags (pdt), which operate in a mechanistically similar manner to the E. Coli endogenous protease ClpXP and its associated ssrA tags. However, unlike ClpXP and ssrA tags, mf-Lon and pdts are completely orthogonal to the endogenous protein degradation systems in E. coli. Using this orthogonal degradation system helps eliminate cross talk between our system and endogenous E. coli proteins. Further, since there are pdts with a wide range of different affinities, we are able to tune degradation rate, and thus gene expression speed to a wide variety of values. This represents not only a practical advancement in the tuning of circuits, but also serves as the first report of the previously unconfirmed mathematical prediction of the relationship between degradation rate and gene expression speed.
Modeling
Math stuff. Plus we need a click through to results