Team:Evry/Model/phenol model

From 2014.igem.org

(Difference between revisions)
Line 5: Line 5:
<html>
<html>
<div align=justify>
<div align=justify>
-
 
<h1>Phenol sensor model</h1>
<h1>Phenol sensor model</h1>
<br/>
<br/>
Line 12: Line 11:
<p>
<p>
In this section we model the phenol sensor in Kappa.  
In this section we model the phenol sensor in Kappa.  
-
Kappa is a rule based language allowing the expression of protein-protein interactions in order to build executable models of protein networks.
+
Kappa is a rule based language allowing the expression of protein-protein interactions in order to build executable models of protein networks. This project is supported by the harvard medical school and can be found in the <a href="http://www.kappalanguage.org/">Kappa homepage</a>.
-
according to literature, the phenol sensor is composed of phosphoriled Dmpr dimers forming hexamers and binding on the P0 site as described in the schemas bellow from  
+
This model is then simulated using KaSim, an open source stochastic simulator for rule-based models written in Kappa.
-
 
+
Basically, KaSim takes one or several Kappa files as input and generates stochastic trajectories of various observables.
 +
according to literature, the phenol sensor is composed of phosphoriled Dmpr dimers forming hexamers and binding on the P0 site as described in the schemas bellow from <b>David Tropel and Jan Roelof van der Meer researches</b>[1].
 +
</p>
<div class="center"><img src="https://static.igem.org/mediawiki/2014/e/ea/Phenol_model.png"></div>
<div class="center"><img src="https://static.igem.org/mediawiki/2014/e/ea/Phenol_model.png"></div>
<br/>
<br/>
-
</p>
 
-
 
<p>
<p>
-
More precisely we are interested in finding: what is the quantity of compound that is in contact with our bacterium ?</br><br/>
+
From this article and various other[2,3,4,5,6]
-
 
+
<b><u>References :</u></b>
-
With this quantity and the number of bacteria in the sponge, we can the connect with the models developed for <a href="https://2014.igem.org/Team:Evry/Model/pcb_model">PCB</a> and <a href="">phenol (TODO) </a> sensing and then relate the sensing capacity to the concentration of compound in the surrounding water.
+
-
</p>
+
-
 
+
-
<p>
+
-
To answer this question, we built two different model :
+
-
 
+
<ol>
<ol>
-
<li>A simple model where we consider only water flows without trying to take into acount the very specific geometry of the sponge.</li>
+
<li><b>TRANSCRIPTIONAL REGULATORS FOR AROMATIC DEGRADATION</b>, David Tropel and Jan Roelof van der Meer, <i>Microbiol. Mol. Biol.</i> Rev. 2004</li>
-
<li>A 2D diffusion model where we take into acount the geometry of the sponge.</li>
+
<li><b>Biodegradation of phenol</b>, C. Indu Nair, K. Jayachandran and Shankar Shashidhar, <i>African Journal of Biotechnology Vol. 7</i>, pp. 4951-4958, 29 December, 2008</li>
 +
<li><b>Bacterial promoters triggering biodegradation of aromatic pollutants</b>,Eduardo Díaz* and María A Prieto, <i>Current Opinion in Biotechnology</i> 2000,</li>
 +
<li><b>Genetics and biochemistry of phenol degradation by Pseudomonas sp. CF600</b>, Justin Powlowski & Victoria Shingler, <i>Biodegradation v5</i> 1994</li>
 +
<li><b>Role of the DmpR-Mediated Regulatory Circuit in Bacterial Biodegradation Properties in Methylphenol-Amended Soils</b>, Inga Sarand, Eleonore Skärfstad, Mats Forsman, Martin Romantschuk and Victoria Shingler, <i>Appl. Environ. Microbiol</i>, 2001</li>
 +
<li><b>An Effective Strategy for a Whole-Cell Biosensor Based on Putative Effector Interaction Site of the Regulatory DmpR Protein</b>, Saurabh Gupta, Mritunjay Saxena , Neeru Saini , Mahmooduzzafar , Rita Kumar, Anil Kumar, <i>PLoS ONE 7(8): e43527</i> 2012</li>
 +
<li><b>Sensing of aromatic compounds by the DmpR transcriptional activator of phenol-catabolizing Pseudomonas sp. strain CF600</b>, V Shingler and T Moore, <i>J. Bacteriol.</i> 1994</li>
</ol>
</ol>
-
</p>
 
-
 
-
<p>
 
-
Throughout this section we base our study on the <i>Spongia Officinalis</i> species, because i) there are evidences that pseudovibrio bacteria live inside (TODO: cite) and ii) its is a quite common type of sponge.<br/>
 
-
</p>
 
-
 
-
<h2>Model 1: Simple Fluxes</h2>
 
-
 
-
<p>
 
-
For this model, we make simple computations based on the intake and expeled quantities of water. Our main assumptions are the following :
 
-
 
-
<ol>
 
-
<li>Bacteria are uniformely distributed in the sponge</li>
 
-
<li>Compounds diffuse instantly inside the sponge (the quantity of compound in the same everywhere inside)</li>
 
-
</ol>
 
-
 
-
These two assumptions imply that each bacterium is in contact with the same quantity of compound.
 
-
</p>
 
-
 
-
<h5> Model Formulation </h5>
 
-
 
-
<p>
 
-
We call &phi;<sub>in</sub> (in ml/h/cm<sup>3</sup>) the quantity of compounds (<= 0.2 &mu;m) filtered by a sponge of volume V (cm<sup>3</sup>). The compound is present at concentration C (mol.ml<sup>-1</sup>). Then the quantity of compound in contact with the bacteria, Q (mol.h<sup>-1</sup>), is:<br/>
 
-
 
-
<center>
 
-
Q = &phi;<sub>in</sub>VC
 
-
</center>
 
-
</p>
 
-
 
-
<h5> Parameters </h5>
 
-
 
-
<p>
 
-
<table border="1">
 
-
<tr>
 
-
  <th>Name</th>
 
-
  <th>Value</th>
 
-
  <th>Unit</th>
 
-
  <th>Ref</th>
 
-
</tr>
 
-
<tr>
 
-
    <td>&phi;<sub>in</sub></td>
 
-
    <td>[0.1-0.3]</td>
 
-
    <td>cm<sup>3</sup>(water).cm<sup>-3</sup>(sponge).s<sup>-1</sup></td>
 
-
    <td>WATER TRANSPORT, RESPIRATION AND ENERGETICS OF THREE TROPICAL MARINE SPONGES </td>
 
-
</tr>
 
-
<tr>
 
-
    <td>V</td>
 
-
    <td>[66.8-116]</td>
 
-
    <td>cm<sup>3</sup></td>
 
-
    <td>Filtering activity of Spongia officinalis var. adriatica (Schmidt) (Porifera, Demospongiae) on bacterioplankton: Implications for bioremediation of polluted seawater</td>
 
-
</tr>
 
-
</table>
 
-
</p>
 
-
 
-
<h5> Results </h5>
 
-
 
-
<p>
 
-
We present in <b>Figure1</b> the results obtained for different parameter sets (min, mean and max values). The value of Q increases linearly with the concentration and is in the range of the &mu;mol.
 
-
 
-
<div class="center">
 
-
<div class="thumb tnone">
 
-
  <div class="thumbinner" style="width:502px;">
 
-
  <a href="https://static.igem.org/mediawiki/2014/c/ce/Simple_model_concs.png" class="image">
 
-
    <img alt="IMAGE" src="https://static.igem.org/mediawiki/2014/c/ce/Simple_model_concs.png" width="500px;" class="thumbimage"/>
 
-
  </a>
 
-
  <div class="thumbcaption">
 
-
    <div class="magnify">
 
-
    <a href="https://static.igem.org/mediawiki/2014/c/ce/Simple_model_concs.png" class="internal" title="Enlarge">
 
-
      <img src="/wiki/skins/common/images/magnify-clip.png" width="15" height="11" alt="Symbol"/>
 
-
    </a>
 
-
    </div>
 
-
    <center>Figure 1: Quantity of compound in contact with the bacteria inside the sponge (Q) as a function of the external compound concentration. Three different parameter sets used: red minimal parameter values; gree: mean parameter values; blue: max parameter values.</center>
 
-
  </div>
 
-
  </div>
 
-
</div>
 
-
</div>
 
-
</p>
 
-
 
-
<p>
 
-
The equations for the three lines in <b>Figure1</b> are the following:
 
-
 
-
<ul>
 
-
<li>Red: y = 0.00668x
 
-
<li>Green: y = 0.01828x
 
-
<li>Blue: y = 0.0348x
 
-
</ul>
 
-
</p>
 
-
 
-
<h2>Model 2: 2D diffusion</h2>
 
-
 
-
<p>
 
-
For this second model we want to take into account the geometry of the sponge. For the equations and geometry to be tractable we will consider a 2D slice of a sponge. Our assumptions are the following :
 
-
 
-
<ol>
 
-
<li>Bacteria are uniformely distributed in the sponge (as for model 1)</li>
 
-
<li>Sponge geometry is approximated as a sphere</li>
 
-
<li>The interior of the sponge is a uniform medium in which the compound diffuse isotropically with a coefficient D</li>
 
-
</ol>
 
-
</p>
 
-
 
-
<p>
 
-
We emphasize that assumption 2 may not be a pure mathematician's idealization, some <i>spongia officinalis</i> sponges have approximately spherical shapes as presented in Figure2a (Although others do not, a wide variety of shapes depending on the environment are exhibited). Some articles also represent some species of sponges as ellipsoidal, see Figure2 b (TODO cite).
 
-
 
-
<div class="center">
 
-
<div class="thumb tnone">
 
-
  <div class="thumbinner" style="width:502px;">
 
-
  <a href="https://static.igem.org/mediawiki/2014/4/4a/Ellipse_sponges.png" class="image">
 
-
    <img alt="IMAGE" src="https://static.igem.org/mediawiki/2014/4/4a/Ellipse_sponges.png" width="500px;" class="thumbimage"/>
 
-
  </a>
 
-
  <div class="thumbcaption">
 
-
    <div class="magnify">
 
-
    <a href="https://static.igem.org/mediawiki/2014/4/4a/Ellipse_sponges.png" class="internal" title="Enlarge">
 
-
      <img src="/wiki/skins/common/images/magnify-clip.png" width="15" height="11" alt="Symbol"/>
 
-
    </a>
 
-
    </div>
 
-
    <center>Figure 2: Sponge morphology and functionning. a) Illustration of different sponge morphology of <i>S. officinalis</i>. b) Sponge morphology approximated as an ellipsoid and functionning of the sponge. Sources: a)Corriero et al., aquaculture (2004); b) Webster, Environmental Microbiology (2007)</center>
 
-
  </div>
 
-
  </div>
 
-
</div>
 
-
</div>
 
-
 
-
</p>
 
-
 
-
<h5> Geometry </h5>
 
-
 
-
For the simplicity of the simulations, we represent only a slice of a spherical sponge, the slice going through its center. We thus have the following geometry presented in Figure3.
 
-
 
-
<div class="center">
 
-
<div class="thumb tnone">
 
-
  <div class="thumbinner" style="width:502px;">
 
-
  <a href="https://static.igem.org/mediawiki/2014/4/4a/Ellipse_sponges.png" class="image">
 
-
    <img alt="IMAGE" src="https://static.igem.org/mediawiki/2014/4/4a/Ellipse_sponges.png" width="500px;" class="thumbimage"/>
 
-
  </a>
 
-
  <div class="thumbcaption">
 
-
    <div class="magnify">
 
-
    <a href="https://static.igem.org/mediawiki/2014/4/4a/Ellipse_sponges.png" class="internal" title="Enlarge">
 
-
      <img src="/wiki/skins/common/images/magnify-clip.png" width="15" height="11" alt="Symbol"/>
 
-
    </a>
 
-
    </div>
 
-
    <center>Figure 2: Sponge morphology and functionning. a) Illustration of different sponge morphology of <i>S. officinalis</i>. b) Sponge morphology approximated as an ellipsoid and functionning of the sponge. Sources: a)Corriero et al., aquaculture (2004); b) Webster, Environmental Microbiology (2007)</center>
 
-
  </div>
 
-
  </div>
 
-
</div>
 
-
</div>
 
-
 
-
<h5> Model Formulation </h5>
 
-
 
-
<h5> Parameters </h5>
 
-
 
-
<h5> Results </h5>
 
-
 
-
</div>
 
-
</div>
 
</div>
</div>
</html>
</html>
{{:Team:Evry/Template:HomeFooter}}
{{:Team:Evry/Template:HomeFooter}}

Revision as of 22:40, 17 October 2014

IGEM Evry 2014

Phenol Model

Phenol sensor model


Introduction

In this section we model the phenol sensor in Kappa. Kappa is a rule based language allowing the expression of protein-protein interactions in order to build executable models of protein networks. This project is supported by the harvard medical school and can be found in the Kappa homepage. This model is then simulated using KaSim, an open source stochastic simulator for rule-based models written in Kappa. Basically, KaSim takes one or several Kappa files as input and generates stochastic trajectories of various observables. according to literature, the phenol sensor is composed of phosphoriled Dmpr dimers forming hexamers and binding on the P0 site as described in the schemas bellow from David Tropel and Jan Roelof van der Meer researches[1].


From this article and various other[2,3,4,5,6] References :

  1. TRANSCRIPTIONAL REGULATORS FOR AROMATIC DEGRADATION, David Tropel and Jan Roelof van der Meer, Microbiol. Mol. Biol. Rev. 2004
  2. Biodegradation of phenol, C. Indu Nair, K. Jayachandran and Shankar Shashidhar, African Journal of Biotechnology Vol. 7, pp. 4951-4958, 29 December, 2008
  3. Bacterial promoters triggering biodegradation of aromatic pollutants,Eduardo Díaz* and María A Prieto, Current Opinion in Biotechnology 2000,
  4. Genetics and biochemistry of phenol degradation by Pseudomonas sp. CF600, Justin Powlowski & Victoria Shingler, Biodegradation v5 1994
  5. Role of the DmpR-Mediated Regulatory Circuit in Bacterial Biodegradation Properties in Methylphenol-Amended Soils, Inga Sarand, Eleonore Skärfstad, Mats Forsman, Martin Romantschuk and Victoria Shingler, Appl. Environ. Microbiol, 2001
  6. An Effective Strategy for a Whole-Cell Biosensor Based on Putative Effector Interaction Site of the Regulatory DmpR Protein, Saurabh Gupta, Mritunjay Saxena , Neeru Saini , Mahmooduzzafar , Rita Kumar, Anil Kumar, PLoS ONE 7(8): e43527 2012
  7. Sensing of aromatic compounds by the DmpR transcriptional activator of phenol-catabolizing Pseudomonas sp. strain CF600, V Shingler and T Moore, J. Bacteriol. 1994

Contacts

Retrieved from "http://2014.igem.org/Team:Evry/Model/phenol_model"