Team:Grenoble/Projet/Design

From 2011.igem.org

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<h1>Design and principle</h1>
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    <h1>Modelling</h1>
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<h2><a href="#toggle">Toggle Switch</a></h2>
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  <h2>Table of content</h2>  
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<h2><a href="#qs">Quorum Sensing</a></h2>
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  Our synthetic biology constructions feature tens of parameters and at this scale human brains can only guess how the whole system would work. We of course needed mathematical modelling in order to check the effectiveness of the genetic circuit.<br/><br/>
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<h2 id="toggle">Toggle switch explanation</h2>
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  In the particular case of our circuit and final use of the bacteria, the modelling team also had to give the specificities (size, number of bacteria, IPTG gradient specificities) of the measuring device we intend to produce.<br/><br/>
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<h3>In a few words</h3>
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Our project is based on a toggle switch system. So we have to explain how it works. Basically <u><b>it corresponds to an irreversible choice between two pathways depending on the environment.</b></u> In reality, the reversibility is possible but very difficult to obtain because of the strength of the interactions and the stability of the system (defined by hysteresis * insérer un lien ici*).
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<a href="https://static.igem.org/mediawiki/2011/b/b6/Toggle1.png"><img src="https://static.igem.org/mediawiki/2011/b/b6/Toggle1.png" alt="2 pathways toggle switch" title="Choose one way, no turning back !"></a>
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<h3>Genetically, what is happening ?</h3>
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Contrary to us, bacteria can’t think or make voluntary choices. So how can they choose a pathway? Through our project, we are creating a genetic system which helps bacteria to take such a decision. For that, we exploit chemical components of the environment which influence the bacterial behaviour. By taking into account two proteins repressing each other’s expression (LacI and XR), we create the fundaments of a toggle system that can switch when using two inducers (IPTG and X) in the medium.
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<a href="https://static.igem.org/mediawiki/2011/7/7c/Toggle2.png"><img src="https://static.igem.org/mediawiki/2011/7/7c/Toggle2.png" alt="" title=""></a>
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  In the next pages we expose which algorithms we used for both deterministic modelling and stochastic modelling, explain our MATLAB scripts (available <a href="http://igemgrenoble-files.perso.sfr.fr/2011/MATLAB_Archives/">here</a>) and finally give the results of our simulations.<br/><br/>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic" ><img class="icon" src="https://static.igem.org/mediawiki/2011/b/b4/Icon_deterministic.png"/></a>
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  <td><a href="https://static.igem.org/mediawiki/2011/8/8d/Toggle3.png"><img src="https://static.igem.org/mediawiki/2011/8/8d/Toggle3.png" alt="" title="" width="400"></a></td>
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      <big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic" class="menu">Deterministic Modelling :</a></big></big><br/>
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  <td><p>Suppose that initially the genes in the Toggle Switch are both expressed.</p></td>
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<a class="menu">Our equations and how we obtained them.</a><br/>
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<a class="menu">Our algorithms</a><br/>
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  <td><a href="https://static.igem.org/mediawiki/2011/0/0a/Toggle4.png"><img src="https://static.igem.org/mediawiki/2011/0/0a/Toggle4.png" alt="" title="" width="400"></a></td>
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<a class="menu">Isoclines and Hysteresis</a><br/><br/>
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If the effect of LacI is dominant through the presence of a high level of IPTG, the bacteria will synthesise more XR and switch off the expression of lacI
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  <a ><img class="icon" src="https://static.igem.org/mediawiki/2011/6/67/Icon_stochastic.png"/></a>
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<big><big><a class="menu">Stochastic Modelling :</a></big></big><br/>
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  <td><a href="https://static.igem.org/mediawiki/2011/d/d5/Toggle5.png.png"><img src="https://static.igem.org/mediawiki/2011/d/d5/Toggle5.png" alt="" title="" width="400"></a></td>
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<a class="menu">Geoffrey</a><br/>
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  <td><p>The bacteria toggle to one side and totally block the expression of lacI.</p></td>
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<a class="menu">Gillespie algorithm</a><br/>
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<a class="menu">Mean, standard deviation and statistical properties</a><br/><br/>
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  <td><a href="https://static.igem.org/mediawiki/2011/1/15/Toggle6.png"><img src="https://static.igem.org/mediawiki/2011/1/15/Toggle6.png" alt="" title="" width="400"></a></td>
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  <td><p>We need to use very high level of the second inducer X to try to switch the toggle back because the active pathway creates an excess of XR, inhibiting lacI expression.</p></td>
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  <a><img class="icon" src="https://static.igem.org/mediawiki/2011/3/34/Icon_parameters.png"/></a>
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<br/><big><big><a class="menu">Parameters</a></big></big><br/><br/><br/><br/>
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  <td><a href="https://static.igem.org/mediawiki/2011/9/97/Toggle7.png"><img src="https://static.igem.org/mediawiki/2011/9/97/Toggle7.png" alt="" title="" width="400"></a></td>
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  <td><p>The amount of X would have to be so high as to relieve the inhibition of lacI expression and consequently turn off the other pathway.</p></td>
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  <a><img class="icon" src="https://static.igem.org/mediawiki/2011/e/e1/Icon_results.png"/></a>
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      <big><big><a class="menu">Results :</a></big></big><br/>
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      <a class="menu">Validation of our genetical network</a><br/>
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      <a class="menu">Device</a><br/><br/>
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<h3>Importance of Toggle Switch for 'Le Projet'  ? </h3>
 
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Importance of Toggle Switch for Le Projet  ?
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Our Toggle switch is composed by the two repressors (LacI and TetR), also the ways express ether a Quorum Sensing receptor (CinR) or the Quorum Sensing synthesise enzyme (CinI). By this ways the bacterium will engage itself in secretion path or receptor path.
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That’s why we use Toggle Switch to have two different behaviours in one cell type, and simplify the immobilisation on plate. We use cell’s communication to finalise our biosensor so we need a homogeneous repartition of ‘sender cell’ and ‘receptor cell’ to have a good communication and response. So locate specifically (homogeneously) two type of cell, will be very hard work contrary to one ‘differentiable type cell’ that we can locate uniformly on the plate.
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    <optgroup label="Deterministic Modelling" >
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                                    <option value="/Deterministic#Our_equations" >Our equations</option>
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                                    <option value="/Deterministic#Our_algorithms" >Our algorithms</option>
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                                    <option value="/Deterministic#Isoclines">Isoclines and Hysteresis</option>
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                                    <option value="/Stochastic#Geof">Geof's</option>
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                                    <option value="/Stochastic#Gillespie_algorithm">Gillespie algorithm</option>
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                                    <option value="/Stochastic#Stats">Mean, standard deviation and stats</option>
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    <option value="/Parameters">Our parameters</option>
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                            <optgroup label="Results">
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    <option value="/Results#Validation">Validation of our Network</option>
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    <option value="/Results#Device">Device specificities</option>
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Revision as of 15:09, 18 September 2011

Grenoble 2011, Mercuro-Coli iGEM


Modelling

Table of content

Our synthetic biology constructions feature tens of parameters and at this scale human brains can only guess how the whole system would work. We of course needed mathematical modelling in order to check the effectiveness of the genetic circuit.

In the particular case of our circuit and final use of the bacteria, the modelling team also had to give the specificities (size, number of bacteria, IPTG gradient specificities) of the measuring device we intend to produce.

In the next pages we expose which algorithms we used for both deterministic modelling and stochastic modelling, explain our MATLAB scripts (available here) and finally give the results of our simulations.

Deterministic Modelling :
Our equations and how we obtained them.
Our algorithms
Isoclines and Hysteresis

Stochastic Modelling :
Geoffrey
Gillespie algorithm
Mean, standard deviation and statistical properties


Parameters



Results :
Validation of our genetical network
Device

Retrieved from "http://2011.igem.org/Team:Grenoble/Projet/Design"