Team:ESBS-Strasbourg/Results/Modelling
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<li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Results/Modelling"> | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Results/Modelling"> | ||
Modeling</a></li> | Modeling</a></li> | ||
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</ul> | </ul> | ||
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<li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Notebook/Microfluidics"> | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Notebook/Microfluidics"> | ||
Microfluidics</a></li> | Microfluidics</a></li> | ||
+ | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Results/Device">Lighting device</a></li> | ||
<li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Notebook/Labbook"> | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Notebook/Labbook"> | ||
Lab-book</a></li> | Lab-book</a></li> | ||
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- | <p><br/><a> | + | <p><br/><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice"> |
HUMAN PRACTICE</a></p> | HUMAN PRACTICE</a></p> | ||
<ul> | <ul> | ||
- | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice | + | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice#organisation"> |
Organisation</a></li> | Organisation</a></li> | ||
- | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice | + | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice#survey"> |
Survey</a></li> | Survey</a></li> | ||
- | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice | + | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice#video"> |
The ClpX video</a></li> | The ClpX video</a></li> | ||
- | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice | + | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice#game"> |
The ClpX game</a></li> | The ClpX game</a></li> | ||
- | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/ | + | <li><a href="https://2010.igem.org/Team:ESBS-Strasbourg/Humanpractice#safety"> |
Project Safety</a></li> | Project Safety</a></li> | ||
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<td width="10" rowspan=7 bgcolor="#222222"> | <td width="10" rowspan=7 bgcolor="#222222"> | ||
</div> | </div> | ||
- | + | <div id="windowbox" style="position:fixed; top:50%; left:20px; width:11%;"> | |
+ | <span style="color:ivory;"> | ||
+ | | ||
+ | <a href="https://2010.igem.org/Team:ESBS-Strasbourg/science"> | ||
+ | <img border="0" src="https://static.igem.org/mediawiki/2010/d/da/ESBS-Strasbourg-Clpx.gif" width="70" height="85" ></a> | ||
+ | <br> | ||
+ | Let me guide you</span> | ||
<td width="800" bgcolor="#414141"> | <td width="800" bgcolor="#414141"> | ||
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- | Our system is made up of a block named | + | Our system is made up of a block named PCC (including the Phytochrome, ClpX and ClpP) and an other block, the DAS_GPF_ PIF chain where GFP is the TAG protein which is used to illustrate the mechanism. This system can be boiled down to the following four states scheme: |
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- | The first state is the state where | + | The first state is the state where PCC and DAS_GFP_PIF are free. Then PCC can form a complex with DAS, called PCC_DAS, with k<sub>1,0</sub> the coefficient of this complexation, or with PIF, called PCC_PIF, with k<sub>0,1</sub> the coefficient of this complexation. The last state is the PCC_DAS_PIF complex which is reached from PCC_DAS state by the complexation coefficient k<sub>0,1</sub>*c<sub>1,1</sub> or from PCC_PIF by k<sub>1,0</sub>*c<sub>1,1</sub>, where c<sub>1,1</sub> is the the coupling factor between the two sites of complexation. |
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- | The TAG protein can only be degraded in | + | The TAG protein can only be degraded in PCC_DAS or PCC_DAS_PIF conformation, because DAS must be linked to launch the protein degradation process. This is why there are single arrows between states PCC and PCC_DAS and between PCC_PIF and PCC_DAS_PIF. |
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- | k<sub>1,0</sub> is very small so the formation of | + | k<sub>1,0</sub> is very small so the formation of PCC_DAS is scarce. k<sub>0,1</sub> is a coefficient which depends on the light's wavelength and this variance corresponds to the different physical structures of the PIF receptor (active or passive). With a 660 nm red light, PIF receptor is active and this coefficient is high but with a 730 nm infra-red light, PIF receptor is inactive and k<sub>0,1</sub> becomes very small. So to model this coefficient we use a Gaussian function centered on 660: |
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- | For each species, | + | For each species, PCC, PIF and DAS, we use this mechanism to compute the species concentration produced, respectively PCC_prod, PIF_prod and DAS_prod. We must now compute the effective concentration of these species with these equations: |
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- | where PIF_l and DAS_l are the concentrations of PIF and DAS linked to the DAS_GFP_PIF chain already complexed at the other boundary (respectively DAS and PIF). We obtain the same equation for the different species. This is because we compute separately DAS, PIF and | + | where PIF_l and DAS_l are the concentrations of PIF and DAS linked to the DAS_GFP_PIF chain already complexed at the other boundary (respectively DAS and PIF). We obtain the same equation for the different species. This is because we compute separately DAS, PIF and PCC’s concentrations for the complexation mechanism but we do have the same DAS_GFP_PIF free chain concentration as the free phytochrome concentration. So for the simulation results we just show the PCC and the DAS_GFP_PIF concentration because DAS and PIF concentrations are the same: |
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- | The last but the most important concentration to show is the TAG protein's (GFP) concentration. First we compute the concentration of GFP produced, GFP_prod, with the same mechanism introduced in the previous part. Then, the concentration of | + | The last but the most important concentration to show is the TAG protein's (GFP) concentration. First we compute the concentration of GFP produced, GFP_prod, with the same mechanism introduced in the previous part. Then, the concentration of PCC fixed GFP (ready to be degraded), GFP_l, is given by: |
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<center><img src="https://static.igem.org/mediawiki/2010/c/c1/Lowlevel_simus_3.png" width="700px"></center> | <center><img src="https://static.igem.org/mediawiki/2010/c/c1/Lowlevel_simus_3.png" width="700px"></center> | ||
+ | <br> | ||
+ | <br> | ||
+ | We have seen that this model is accurate but it has some drawbacks too. It is based on ODEs so it requires the use of a numerical solver, leading to slow simulations. It depends on parameters that should be estimated with experiments and the more the parameters are accurate, the more the simulations are close to real cell behavior. | ||
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<div class="heading">4. Conclusion</div> | <div class="heading">4. Conclusion</div> | ||
<div class="desc"> | <div class="desc"> | ||
+ | <br> | ||
+ | <br> | ||
+ | The first simulation we have introduced is made at high-level and is compared to the high-level model previously obtained in the following scheme: | ||
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<center><img src="https://static.igem.org/mediawiki/2010/8/8d/Lowlevel_simus_4.png" width="700px"></center> | <center><img src="https://static.igem.org/mediawiki/2010/8/8d/Lowlevel_simus_4.png" width="700px"></center> | ||
+ | <br> | ||
+ | <br> | ||
+ | The delay in the high-level model was included after the low-level simulation to make both models match. | ||
+ | <br> | ||
+ | <br> | ||
+ | The modeling part of our system takes advantage of microelectronics knowledge, which has proven itself, and resumes the main steps of the design flow used in this field to design a system. | ||
+ | <br> | ||
+ | <br> | ||
+ | Each model has its own interest that we have seen previously, but it is the possibility to use them jointly that may be relevant, in order to simulate systems quickly with different levels of detail depending on the need (sensitive part or not, already validated or not ...). | ||
+ | <br> | ||
+ | <br> | ||
+ | We did not have enough time to study the parameters extraction. Using characterization software like IC-CAP on our system, we still have to extract the parameters of the model to make it match with the real biological system. | ||
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Latest revision as of 16:37, 27 October 2010
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