Difference between revisions of "Team:TUDelft/DennisModel"

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    <h2>Overview</h2>
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    <p> The main goal of our project revolves around predictability. Without predictability, we cannot reliably design and implement synthetic biology solutions. However, when transferring genetic circuits between different organisms, many variables change. This dramatically increases the uncertainty of the outcome. With our modeling, we aim to demonstrate ways to make a genetic circuit independent of some of these variables, thereby decreasing this uncertainty. We couple our model with a software tool that determines a coding sequence for each gene involved in the circuit in such a way that they have similar codon usage bias across species of interest. <br>
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     <h2>Overview - The Model</h2>
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     <h2>TALE - Incoherent Feed Forward Loop to control gene expression</h2>
  
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   <p> In our system we exploit a commonly applied control system known as an Incoherent Feed Forward Loop (iFFL), in which an activator regulates both a gene and a repressor of the gene ... .  This control system is established through the expression of a Transcription activator-like effector (TALE) protein.  TALE proteins recognize DNA by a simple DNA-binding mechanism which can be altered to recognize any sequence you want … . In our system the TALE protein binds to the promoter of a gene of interest and thus represses the expression of it. .... has previously described this system and showed how it results in independence of copy number for a gene of interest. Our further analyzation of this system has revealed the system to be independent of many other variables. We exploit this robustness of the system to show how it can yield predictable expression when transferring your genetic circuit between prokaryotes. <br> <br>
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   <p> In our system we exploit a commonly applied control system known as an Incoherent Feed Forward Loop (iFFL), in which an activator regulates both a gene and a repressor of the gene ... .  This control system is established through the expression of a Transcription activator-like effector (TALE) protein.  TALE proteins recognize DNA by a simple DNA-binding mechanism which can be altered to recognize any sequence you want … . In our system the TALE protein binds to the promoter of a gene of interest and thus respresses the expression of it. .... has previously described this system and showed how it results in independence of copy number for a gene of interest. <br>
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Visit our page on TALE to learn more!
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<br>
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We further analyzed this system through the use of modeling, which revealed that it's insensitive to many other variables as well, which hasn't been explored yet.  
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Transferring genetic circuits between organisms yields large variation in most (if not all) of the parameters in the system, we exploited the robustness of this model to maintain predictability even when crossing species barriers.  
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Below you can find a set of questions used to establish design requirements for both our software tools and our genetic circuit.
 
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  <h3>Rate Kinetics</h3>
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<a class="toggle" href="javascript:void(0);" ><b>Q1 How does the TALE protein bind to DNA?</b></a>
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<a class="toggle" href="javascript:void(0);" ><b>Q2 How does the iFFL behave?</b></a>
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<a class="toggle" href="javascript:void(0);" ><b>Q3 How can we make our system more robust?</b></a>
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<a class="toggle" href="javascript:void(0);" ><b>Q4 How does the system behave when transferring between organisms?</b></a>
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<p>You can find the full model description here! </p>
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<h2>Codon usage - Cross species codon harmonization</h2>
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Revision as of 17:07, 4 September 2019

Sci-Phi 29


Overview

The main goal of our project revolves around predictability. Without predictability, we cannot reliably design and implement synthetic biology solutions. However, when transferring genetic circuits between different organisms, many variables change. This dramatically increases the uncertainty of the outcome. With our modeling, we aim to demonstrate ways to make a genetic circuit independent of some of these variables, thereby decreasing this uncertainty. We couple our model with a software tool that determines a coding sequence for each gene involved in the circuit in such a way that they have similar codon usage bias across species of interest.

TALE - Incoherent Feed Forward Loop to control gene expression

In our system we exploit a commonly applied control system known as an Incoherent Feed Forward Loop (iFFL), in which an activator regulates both a gene and a repressor of the gene ... . This control system is established through the expression of a Transcription activator-like effector (TALE) protein. TALE proteins recognize DNA by a simple DNA-binding mechanism which can be altered to recognize any sequence you want … . In our system the TALE protein binds to the promoter of a gene of interest and thus respresses the expression of it. .... has previously described this system and showed how it results in independence of copy number for a gene of interest.

We further analyzed this system through the use of modeling, which revealed that it's insensitive to many other variables as well, which hasn't been explored yet. Transferring genetic circuits between organisms yields large variation in most (if not all) of the parameters in the system, we exploited the robustness of this model to maintain predictability even when crossing species barriers.

Below you can find a set of questions used to establish design requirements for both our software tools and our genetic circuit.

You can find the full model description here!

Codon usage - Cross species codon harmonization