Team:Grenoble/Projet/Results

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    <h2>Post-transcriptional regulation<h2>
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<p>The RsmA system has a homologous in Escherichia Coli named CsrA. We know these two system are extremely closed on
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structural and functional sides. The most difference between this two regulation systems is on target regulon.
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For example, in Pseudomonas aeruginosa Rsma regulate many virulence genes as type III secretion system
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(anja Brencic and Stephen Lory). In Escherichia coli, RsmA homologous regulate metabolic network.
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Our goal is to integrate this translational regulation system in the toggle switch. We need to know whether it influence
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the bacteria’s life.</p>
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<div class="left">
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<a href="https://static.igem.org/mediawiki/2011/9/91/Growth_cur_final2.png"><img src="https://static.igem.org/mediawiki/2011/9/91/Growth_cur_final2.png"
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<div class="blocbackground" id="Achievements">
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alt="logo iGEM"/></a>
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    <h1>Achievements</h1>
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<div class="legend"><strong>Figure 1 RsmA influence on DH5α growth.</strong> Bacteria from overnight culture were reseeding in rich medium supplemented with tetracycline at 20mg/ml and also IPTG at the concentration given in the legend.</div>
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<p>Figure 1 present growth curve of DH5α carries into a plasmid pVLT31 with or without rsmA and Natural RBS cloned downstream
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<div  class="blocbackground" id="Content">
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the Plac promoter. Two triads can be seen. The triad containing the strains with empty plasmid shows an upper growth curve
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<h2>Table of content</h2>
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compared to the second triad carries pVLT31-rsmA. But it’s important to say that the two groups start their growth not at
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the same value. That explains a time lag between these two groups. After normalization of all curves, no differences
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between these two kind of bacteria could be seen. We conclude that the RsmA overexpression hasn’t effects on the growth of bacteria.</p>
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    <h2>Construction of a Toggle Switch test</h2>
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    <p>
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In order to test if our system could work, we construct a toggle switch test based on Gardner's work <a href="#1">[1]</a>.
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</p>
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<img src="https://static.igem.org/mediawiki/2011/1/1d/Toggle_GeoGeo%281%29.png" class="centerwide" style="box-shadow: none"/>
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<p>
<p>
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For realized this toggle, we used 4 primary bricks :
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We describe here the modeling and experimental results obtained for each network module,  
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<ul>
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in order to validate our model and optimize the device: the toggle switch, the quorum sensing
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<li>pTet : <a href="http://partsregistry.org/Part:BBa_R0040">BBa_R0040</a></li>
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and the translational regulation system RsmA.
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<li>RBS-LacI-oo-pLac : <a href="http://partsregistry.org/Part:BBa_Q04121">BBa_Q04121</a></li>
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<ol>
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<li>RBS-GFP : <a href="http://partsregistry.org/Part:BBa_E0240">BBa_E0240</a></li>
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<li>Validation of the genetic network</li>
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<li>RBS-TetR composed of RBS <a href="http://partsregistry.org/Part:BBa_B0034">BBa_B0034</a> and TetR <a href="http://partsregistry.org/Part:BBa_C0040">BBa_C0040</a></li>
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<li>The essential role of rmsA regulation system</li>
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</ul>
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<li>Device optimization and specifications</li>
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</p>
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</ol>
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<p>
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In each part, we tried to speak about both experiment and modelling, in order to validate our model and optimized
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First we put RBS-GFP behind RBS-TetR, and Q04121 behind pTet: both size are around 1 500 bp. The following gel shows that both constructions
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by simulation the device.<br/><br/>
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were at the expected size. Construction were confirmed by sequencing.
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Results/Toggle" ><img class="icon" src="https://static.igem.org/mediawiki/2011/2/20/Bouton_toggle.png"/></a>
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      <big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Results/Toggle" class="menu">Validation of the network</a></big></big><br/>
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    <div class="legend">
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<strong>Figure 1:</strong>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Toggle#TS_QS">Toggle Switch and Quorum sensing behavior</a><br/>
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First step of cloning gel
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Toggle#Validation">Validation of the model</a><br/>
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</div>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Toggle#Dynamic">Dynamic study of the stability</a><br/><br/><br/>
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    <p>
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In a last step of cloning, we put RBS-tetR-RBS-GFP behind pTet-Q04121. The size is around 3 000 bp. The following gel shows that
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Results/rmsA" ><img class="icon" src="https://static.igem.org/mediawiki/2011/9/97/Bouton_regulation.png"/></a>
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constructions was at the expected size. In addition to this test, transformation of bacteria have grown on plate with IPTG to block
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them in the fluorescence way. And some of the bacteria were fluorescent. Construction was also confirmed by sequencing.
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<big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Results/rmsA" class="menu">The essential role of rsmA regulation system</a></big></big><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/rmsA#Necessity">Why do we need this system ?</a><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/rmsA#fha">Leader sequence characterization</a><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/rmsA#rsma">rsmA characterization</a><br/><br/><br/>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Results/Device" ><img class="icon" src="https://static.igem.org/mediawiki/2011/7/70/Bouton_general_modeling.png"/></a>
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<big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Results/Device" class="menu">Device specificities and optimization</a></big></big><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Device#Optimization">Optimization of the device</a><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Device#Limit">Determination of the limit of quantification</a><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Device#Statistic">Stochastic study for statistic determination of several device specificities</a><br/><br/><br/>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Results/Sensitivity" ><img class="icon" src="https://static.igem.org/mediawiki/2011/f/fd/Bouton_model_sensitivity.png"/></a>
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<big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Results/Sensitivity" class="menu">Sensitivity to parameters study</a></big></big><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Sensitivity#Robustness">Robustness of our system</a><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Results/Sensitivity#Mercury">Applicable to mercury</a><br/><br/><br/><br/>
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    </p>
    </p>
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<table class="noborudre">
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<td><img src="https://static.igem.org/mediawiki/2011/c/c5/Toggletest.png" class="centerwide" style="box-shadow: none"/>
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</div>
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<strong>Figure 2:</strong>
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Last step of cloning gel
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<td><img src="https://static.igem.org/mediawiki/2011/8/82/Image_2.jpg" class="centerwide" style="box-shadow: none"/>
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<strong>Figure 3:</strong>
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Fluorescence test picture
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</table>
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<p>
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To test this system, bacterias had grown in an aTc preculture to block them in a nonfluorescent way. This bacteria were put
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in a 96 wells plate with a two dimensionnal gradient (aTc and IPTG). After 10 hours of acquisition, we obtained the following curve :
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</p>
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<img src="https://static.igem.org/mediawiki/2011/2/2d/Fusion.png" class="centerwide" style="box-shadow: none"/>
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<p>
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We can get from this graph that between an aTc concentration of 50ng/mL and 150 ng/mL there is a switch after 3 hours of experiment.
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However, we can see more fluorescence than expected. In fact, the GFP protein has an half life of 10 hours and it was impossible to get
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no fluorescence.
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</p>
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<p>
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We also did an experiment on bacterias which had grown in an IPTG preculture. But we did'nt see a switch because IPTG block bacterias in
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the fluorescence way. Because of the half life of GFP, it was possible to detect a switch only with bacteria which had grown with aTc.
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</p>
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<p>
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To go further, it will be very interesting to put an LVA tag on GFP in order to control its degradation. In this case we will be abble to see
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the switch in both case and with more magnitude.
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    <optgroup label="Modelling Homepage">
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    <optgroup label="Table of content">
     
     
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    <option value="#Content" selected="selected">Table of content</option>
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                                    <option value="/Deterministic#Our_EquationsTS" >Our equations - Toggle switch</option>
 
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                                    <option value="/Deterministic#Our_EquationsQS" >Our equations - Quorum sensing</option>
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    <optgroup label="Toggle Switch" >
                                  
                                  
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                                     <option value="/Toggle#TS_QS" >Toggle Switch and Quorum Sensing</option>
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                                     <option value="/Toggle#Validation" >Validation of the model</option>
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                                    <option value="/rmsA#fha">Leader sequence characterization</option>
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                                    <option value="/rmsA#rsma">rsmA characterization</option>
                                  
                                  
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                                     <option value="/Stochastic#Gillespie_algorithm">Gillespie algorithm</option>
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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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Latest revision as of 03:20, 29 October 2011

Grenoble 2011, Mercuro-Coli iGEM


Achievements

Table of content

We describe here the modeling and experimental results obtained for each network module, in order to validate our model and optimize the device: the toggle switch, the quorum sensing and the translational regulation system RsmA.

  1. Validation of the genetic network
  2. The essential role of rmsA regulation system
  3. Device optimization and specifications
In each part, we tried to speak about both experiment and modelling, in order to validate our model and optimized by simulation the device.

Validation of the network
Toggle Switch and Quorum sensing behavior
Validation of the model
Dynamic study of the stability


The essential role of rsmA regulation system
Why do we need this system ?
Leader sequence characterization
rsmA characterization


Device specificities and optimization
Optimization of the device
Determination of the limit of quantification
Stochastic study for statistic determination of several device specificities


Sensitivity to parameters study
Robustness of our system
Applicable to mercury



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