Team:KULeuven/Antifreeze

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<div id="modeling_submenu"><a href="https://2011.igem.org/Team:KULeuven/Modeling">overview</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<a href="https://2011.igem.org/Team:KULeuven/Freeze">Freeze</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<a href="https://2011.igem.org/Team:KULeuven/Antifreeze" style="color:#000; border-bottom:2px solid #000;">Antifreeze</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<a href="https://2011.igem.org/Team:KULeuven/Death">Cell Death</a></div>
<div id="modeling_submenu"><a href="https://2011.igem.org/Team:KULeuven/Modeling">overview</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<a href="https://2011.igem.org/Team:KULeuven/Freeze">Freeze</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<a href="https://2011.igem.org/Team:KULeuven/Antifreeze" style="color:#000; border-bottom:2px solid #000;">Antifreeze</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<a href="https://2011.igem.org/Team:KULeuven/Death">Cell Death</a></div>
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<br><br>
<h3>Modeling Antifreeze</h3>
<h3>Modeling Antifreeze</h3>
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<br><p>The purpose of this subsystem is to synthesize antifreeze protein as respons on a given stimulus. In nature, the antifreeze protein is intracellularly produced by  Pseudomonas Syringae to prevent cells from freezing. However in this project,we try to prevent the environment from freezing. In order to accomplish this, we design a new biobrick which gives rise to the coupling of the antifreeze protein to the extracellular membrane. To check if we have transcribed the antifreeze protein, we coupled melanin production to the inducible promoter as well. Melanin is a black pigment, which will visualise the antifreeze system.
<br><p>The purpose of this subsystem is to synthesize antifreeze protein as respons on a given stimulus. In nature, the antifreeze protein is intracellularly produced by  Pseudomonas Syringae to prevent cells from freezing. However in this project,we try to prevent the environment from freezing. In order to accomplish this, we design a new biobrick which gives rise to the coupling of the antifreeze protein to the extracellular membrane. To check if we have transcribed the antifreeze protein, we coupled melanin production to the inducible promoter as well. Melanin is a black pigment, which will visualise the antifreeze system.
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<br><p>The promoter we use for both proteins is the plux-CI promotor (BBa_R0065). It is a hybrid promoter responding to cI repressor and LuxR-AHL complex. CI repressor negatively regulates this promoter and LuxR-AHL complex activates its transcription. The effect of cI is dominant over LuxR-AHL.
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<br><p>The promoter we use for both proteins is the <i>pLux-CI</i> promoter (<a href=" http://partsregistry.org/Part:BBa_R0065" target=”blank”>BBa_R0065</a>). It is a hybrid promoter responding to cI repressor and LuxR-AHL complex. CI repressor negatively regulates this promoter and LuxR-AHL complex activates its transcription. The effect of cI is dominant over LuxR-AHL.<br><br>
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<br><p>ANTIFREEZE SCHEME
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<center>
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<img src="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/antifreeze_scheme.jpg"><br><br>
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<br><p>BIOBRICK ANTIFREEZE
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<img src="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/biobrick_antifreeze.jpg"><br><br>
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<br><p>ODEantifreeze2.pdf  
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<a href="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/ODEantifreeze2.pdf"><img src="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/pdf_icon.jpg"> ODE</a><br><br>
<br><p>We used the same kind of mathematical mass equations to describe the overall system. This will not be completely correct, but because of the complexity of the system, it would take too long to check the accuracy of every individual reaction and parameter in detail. In future research it would be interesting to improve the equations and some parameters which are indicated important in the sensitivity analysis. In the full model, the parameters and equations are most up to date.
<br><p>We used the same kind of mathematical mass equations to describe the overall system. This will not be completely correct, but because of the complexity of the system, it would take too long to check the accuracy of every individual reaction and parameter in detail. In future research it would be interesting to improve the equations and some parameters which are indicated important in the sensitivity analysis. In the full model, the parameters and equations are most up to date.
<br><br>
<br><br>
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<br><p>PARAMETER TABLE
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<br><h2>2. AntiFreeze Model </h2>
<br><h2>2. AntiFreeze Model </h2>
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<center>
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<br><h2>3. Simulations </h2>
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<a href="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/model_antifreeze.jpg" rel="lightbox" title="Antifreeze model"><img src="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/model_antifreeze_small.jpg" border="0"></a><br><br>
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<a href="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/model_antifreeze.zip">Click here to download the Antifreeze model</a><br><br>
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<h2>3. Simulations </h2>
<br><p>In this model we did not implement LuxR-AHL association. We assume that all LuxI would be converted in AHL. LuxR and LuxI are described in the model as separate activators for transcription of OmpA-AFP and MelA, which is biologically not correct. Normally LuxR and AHL form first a complex and then stimulate transcription of the plux-CI promoter. In the full model is the LuxR-AHL association included.
<br><p>In this model we did not implement LuxR-AHL association. We assume that all LuxI would be converted in AHL. LuxR and LuxI are described in the model as separate activators for transcription of OmpA-AFP and MelA, which is biologically not correct. Normally LuxR and AHL form first a complex and then stimulate transcription of the plux-CI promoter. In the full model is the LuxR-AHL association included.
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<br><p>In the antifreeze model, AFP production is induced by L-arabinose and repressed by lactose. The simulation tests are performed with different amounts of lactose and L-arabinose to check the overall working of the system.
<br><p>In the antifreeze model, AFP production is induced by L-arabinose and repressed by lactose. The simulation tests are performed with different amounts of lactose and L-arabinose to check the overall working of the system.
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<br><p>In figure 1 the production of AFP is displayed after stimulating cells with L-arabinose. The ratio of the concentration of the two compound, arabinose and lactose, has an influence on production levels of AFP and MelA. By varying the inputconcentrations of arabinose and lactose, you can check the output produced. There is a huge amount of lactose acquired in relation to arabinose to inhibit the production of AFP. When there is 50 times more lactose than arabinose (figure 2), there is still production of AFP. This is not a realistic outcome. It is the wrong simplification of the model mentioned earlier that’s lying at the basis of it: LuxR and LuxI are here separate activators instead of one activator complex LuxR-AHL. We will take this mistakes into account when we will improve our model.  
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<br><p>In figure 1 the production of AFP is displayed after stimulating cells with L-arabinose. The ratio of the concentration of the two compound, arabinose and lactose, has an influence on production levels of AFP and MelA. By varying the inputconcentrations of arabinose and lactose, you can check the output produced. There is a huge amount of lactose acquired in relation to arabinose to inhibit the production of AFP. When there is 50 times more lactose than arabinose (figure 2), there is still production of AFP. This is not a realistic outcome. It is the wrong simplification of the model mentioned earlier that’s lying at the basis of it: LuxR and LuxI are here separate activators instead of one activator complex LuxR-AHL. We will take this mistakes into account when we will improve our model.<br><br>
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<br><p>FIGURE 1: simulation with arabinose value 1, lactose value 0, time duration 100s
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<center>
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<br><p>FIGRURE 2: Simulation with L-arabinose value 1, lactose value 50, time interval 100s
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<img src="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/figure1_simulation100arabinose1_lactose0.png"><br><br>
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<br><br>
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FIGURE 1: simulation with arabinose value 1, lactose value 0, time duration 100s<br><br>
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<center>
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<img src="http://homes.esat.kuleuven.be/~igemwiki/images/modeling/figure2_simulation100arabinose1_lactose50.png"><br><br>
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</center>
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FIGURE 2: Simulation with L-arabinose value 1, lactose value 50, time interval 100s<br><br>
<br><h2>4. Sensitivity analysis</h2>
<br><h2>4. Sensitivity analysis</h2>
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The sensitivity analysis for AFP or MelA reveal that in the beginning the sensitivity of the transcription parameter plays a more important role than other parameters, but after a while the sensitivity of the degradation parameters becomes more important. This means that we need an accurate estimate of these parameters, because they have a big influence on the output of the simulation.<br><br>
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The sensitivity analysis for AFP or MelA reveal that in the beginning the sensitivity of the transcription parameter plays a more important role than other parameters, but after a while the sensitivity of the degradation parameters becomes more important. This means that we need an accurate estimate of these parameters, because they have a big influence on the output of the simulation.
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<br><br><br>

Latest revision as of 22:19, 28 October 2011

KULeuven iGEM 2011

close
overview     Freeze     Antifreeze     Cell Death


Modeling Antifreeze


1. Description of the Antifreeze system


For a full description, we refer to the extended project page. This page section only shows a brief summary of the antifreeze description.

The purpose of this subsystem is to synthesize antifreeze protein as respons on a given stimulus. In nature, the antifreeze protein is intracellularly produced by Pseudomonas Syringae to prevent cells from freezing. However in this project,we try to prevent the environment from freezing. In order to accomplish this, we design a new biobrick which gives rise to the coupling of the antifreeze protein to the extracellular membrane. To check if we have transcribed the antifreeze protein, we coupled melanin production to the inducible promoter as well. Melanin is a black pigment, which will visualise the antifreeze system.

The promoter we use for both proteins is the pLux-CI promoter (BBa_R0065). It is a hybrid promoter responding to cI repressor and LuxR-AHL complex. CI repressor negatively regulates this promoter and LuxR-AHL complex activates its transcription. The effect of cI is dominant over LuxR-AHL.





ODE


We used the same kind of mathematical mass equations to describe the overall system. This will not be completely correct, but because of the complexity of the system, it would take too long to check the accuracy of every individual reaction and parameter in detail. In future research it would be interesting to improve the equations and some parameters which are indicated important in the sensitivity analysis. In the full model, the parameters and equations are most up to date.


2. AntiFreeze Model



Click here to download the Antifreeze model

3. Simulations


In this model we did not implement LuxR-AHL association. We assume that all LuxI would be converted in AHL. LuxR and LuxI are described in the model as separate activators for transcription of OmpA-AFP and MelA, which is biologically not correct. Normally LuxR and AHL form first a complex and then stimulate transcription of the plux-CI promoter. In the full model is the LuxR-AHL association included.

In the antifreeze model, AFP production is induced by L-arabinose and repressed by lactose. The simulation tests are performed with different amounts of lactose and L-arabinose to check the overall working of the system.

In figure 1 the production of AFP is displayed after stimulating cells with L-arabinose. The ratio of the concentration of the two compound, arabinose and lactose, has an influence on production levels of AFP and MelA. By varying the inputconcentrations of arabinose and lactose, you can check the output produced. There is a huge amount of lactose acquired in relation to arabinose to inhibit the production of AFP. When there is 50 times more lactose than arabinose (figure 2), there is still production of AFP. This is not a realistic outcome. It is the wrong simplification of the model mentioned earlier that’s lying at the basis of it: LuxR and LuxI are here separate activators instead of one activator complex LuxR-AHL. We will take this mistakes into account when we will improve our model.



FIGURE 1: simulation with arabinose value 1, lactose value 0, time duration 100s



FIGURE 2: Simulation with L-arabinose value 1, lactose value 50, time interval 100s


4. Sensitivity analysis

The sensitivity analysis for AFP or MelA reveal that in the beginning the sensitivity of the transcription parameter plays a more important role than other parameters, but after a while the sensitivity of the degradation parameters becomes more important. This means that we need an accurate estimate of these parameters, because they have a big influence on the output of the simulation.