Team:Evry/Modeling

From 2013.igem.org

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     <li>On the Structure:
     <li>On the Structure:
       <ul>
       <ul>
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    <ul>
 
       <li>Each header section presents the methods used in the model, and could be compared to a "Material and Methods" section in an article;</li>
       <li>Each header section presents the methods used in the model, and could be compared to a "Material and Methods" section in an article;</li>
       <li>Each subsequence page presents the different simulations and answers obtained with the model; as in the "Result" section in an article;</li>
       <li>Each subsequence page presents the different simulations and answers obtained with the model; as in the "Result" section in an article;</li>

Revision as of 15:21, 26 October 2013

Iron coli project

Modeling Overview

New since European Jamboree

Following the different remarks made by the team, judges, and other people, we reworked entirely the modeling section :

  • On the Structure:
    • Each header section presents the methods used in the model, and could be compared to a "Material and Methods" section in an article;
    • Each subsequence page presents the different simulations and answers obtained with the model; as in the "Result" section in an article;
  • On the Content:

Introduction:

In the begining, our goal was to chelate iron in the duodenum, using bacteria that would flush through the duodenum and produce the siderophores. The aim was to predict the sufficient quantity of produced siderophores to reduce the iron intestinal absorption. We first had in mind a flush strategy, meaning we prioritized an approach where the bacteria would start their iron sensing and siderophore production before entering the duodenum. This qualitative Flush treatment model showed us that it is theoratically possible to significantly reduce the patient's iron absorption.

The conclusions were promising, encouraging and comforting regarding our strategy choice. Right afterwards, the aim was to detail the delay of siderophore production for a given bacterial production through an Enterobactin production model. This approach gave us more detail about timings. Unfortunately, the conclusions were in contradiction with the qualitative model because the delay is to big to be compatible with a flush strategy. This conclusion greatly influenced the biological part, especially in the design of the capsule. Because the iron absorption is split among the duodenum (60%) and the jejunum (40%), we decided to enhance growth in the proximal area of the jejunum. This is also why we chose to deliver a sticky gel with our bacteria and optimize its growth.

As a final part in the modeling, we also wanted to know how much siderophore can be produced and how we can improve this. We answered this with a Flux model, a flux balance analysis approach.

Models using ODEs:


Flush treatment
Enterobactin production


Models using other methods:

Flux model Population scale
Flux model Population scale


Tools:

When working on a scientific project, it is always good to properly define and clarify the tools we are going to use. These pages contain the theorical background for our models:

Programming methods Logistic functions Chemical reasoning