Team:Evry/pop scale

From 2013.igem.org

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La Figure 2 représente l'automate qui modélise la bactérie. Cet automate à deux parties : la production d'enterobactines et la croissance.
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The <a href="#Fig2">Figure 2</a> represents the bacteriial automaton. It has two functions : the division and the ennterobactin production.<br/>
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The bacteria produces enterobactins. This production is ruled by an activator. This activator is a step functionn (from 0 to 1) with a K<sub>a</sub> threshold, fixed thanks to the <a href="https://2013.igem.org/Team:Evry/Modelmeta1">sensor model</a>:
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The bacteria produces enterobactins. This production is ruled by a activator. Cette activateur est une fonction palier de 0 à 1 avec un seuil K<sub>a</sub> fixer grace au modèle du senseur, dont voici l'expression :
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<img src="https://static.igem.org/mediawiki/2013/8/84/Activpopscale.png" width="30%"/></br>
<img src="https://static.igem.org/mediawiki/2013/8/84/Activpopscale.png" width="30%"/></br>
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Enterobactin chelate iron. For this automoton, we have one rules : <b> One Enterobactin atom can chelate one Iron Ion</b>
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The enterobactins chelate iron. For this automoton, we have one rule : <b> One Enterobactin atom can chelate one Iron molecule</b><br/>
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L'automate est tout de même conditionné par un une probabilité de rencontre :<img src="https://static.igem.org/mediawiki/2013/3/32/Formulechela.png" width="20%"/>.
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Still, the automaton is ruled by an encounter probability: <img src="https://static.igem.org/mediawiki/2013/3/32/Formulechela.png" width="20%"/>.
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<h2>Parameters tuning :</h2>
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Revision as of 03:24, 29 October 2013

Iron coli project

Introduction

The Enterobactin production model showed us that our bacteria take too much time to produce enterobactins, which disables the flush strategy.
In response, we changed the strategy, by delivering a gel that would block the bacteria in the jejunum.
This model is thus very similar to the flush treatment model, except for the longer time scale, and the computational method.

Goals

Assumptions

  • No regulation of the patient's iron absorption
  • Constant iron flow in the intestine
  • Homogeneous fluid
  • The bacterial natural absorption is insignificant compared to the chelation
  • The patient ingests 20mg of iron per day (Guideline Daily Amounts)

Materials and methods

This model is based on a cellular automaton algorithm : both the bacteria and the enterobactins are cellular automaton.

Absorption
Figure 1 : Influence graph.

The Figure 1 represents the influence between the system's variables.
Absorption
Figure 2 : Graph of bacteria automaton.
Pgrowth Division Probability
Pdeath Death probability
age variable rate of bacteria ageing

The Figure 2 represents the bacteriial automaton. It has two functions : the division and the ennterobactin production.
The bacteria produces enterobactins. This production is ruled by an activator. This activator is a step functionn (from 0 to 1) with a Ka threshold, fixed thanks to the sensor model:

The enterobactins chelate iron. For this automoton, we have one rule : One Enterobactin atom can chelate one Iron molecule
Still, the automaton is ruled by an encounter probability: .

Results

Parameter values

Name Value Unit Description Reference
mu 0.2 s-1 Iron absorption rate by the body
IronQuantity0 4.5.10-9 mol-1 Iron pulse value
Sact 10**-9 m Duodenum length [3]
α 0.3 s-1 Duodenum absorption rate tuned
σ 0.72 s-1 Regulation coefficient tuned

References:

Retrieved from "http://2013.igem.org/Team:Evry/pop_scale"