Team:Evry/Modeling
From 2013.igem.org
Line 43: | Line 43: | ||
</tr> | </tr> | ||
<tr width="100%"> | <tr width="100%"> | ||
- | <td align="center"><b>Programming | + | <td align="center"><b>Programming methods</b></span></td> |
- | <td align="center"><b> | + | <td align="center"><b>Logistic functions</b></span></td> |
<td align="center"><b>Chemical reasoning</b></span></td> | <td align="center"><b>Chemical reasoning</b></span></td> | ||
</table> | </table> |
Revision as of 00:21, 5 October 2013
Model overview
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 duodenum 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 a metabolic 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.
Modeling Parts:
duodénum | zoom sur les parois | bactérie | FBA |
Duodenum model | Population scale | Metabolic model | Flux model |
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 |