Team:Colombia/Modeling/Results

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(Differential equations results)
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Revision as of 22:02, 26 September 2012

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Results

The mathematical model should help the experimental design to optimize the circuit and our case was not the exception. The picture below shows the original design of the circuit.


Siold.png


Gen2old.png


After doing the simulation for the differential equations we have to make little changes to the proposed system:

  1. As you can see there was an unknown promoter for LuxR. First we decided that it was a constitutive promoter but the response curves of the system were not consistent with the reality (LuxR had giant concentrations and the salicylic acid never went up). We wanted this protein to interact with LuxI and turn on the response, so we thought that it may need to be in a similar concentration of LuxI. Then we put it under the same promoter, hence the two proteins will be promoted at the same time.
  2. Our desired response is the increase of Salicylic Acid when a pest gets near the bacteria. With the original system the salicylic acid increased but not as much as we wanted, so to achieve this goal we tried putting the promoter activated by Lux next to the CI promoter to see if there was an increase. After running the simulation we discovered that this solution optimized the increase of salicylic acid in the response.
  3. Looking for the right set of parameters we came to the conclusion that the hill constant k (Concentration of the substrate when the the rate of production is half of the maximum production rate) for the promoter activated by Lux had to be 4 times greater than the hill constant for the CI promoter. Which has biological sense; the Lux promoter came from a quorum sensing system, so it needs high concentration of activator because it informs the promoter that there is high cell density. On the other hand the CI promoter box came from a bacteriophage and is used to attack the bacteria as quickly as possible, so it does need small quantities of protein to fully activate its system.

The new system is showed in the picture below:


Si.png


Gen2.png



Differential equations results

Although the screening of the parameters could not be completely done, we made a manual search for them and found a set that makes the system behave as expected. Here we present the mean response of all the substances in our biological system for one cell. The impulse of the pest was made during the times 10-20.

Ralstonia

As you see below, when the system is under the presence of 3-OH-PAME the sensor is phosphorylated really fast and the complex phcR-phcA liberates the activator which has a peak and the goes a little down because is with the promoter and its not free. After the impulse is gone everything goes back to normality.


Ral1.png
Ral2.png





The LuxI- LuxR System shows and increase after it is activated by phcsA

Ral3.png

Now, looking at the species of interest, we can see how the antitoxin has greater concentration than the toxin when the 3-OH-PAME appears, this means that the cell is awake and can produce proteins. On the other hand, the Salicylic acid has an increase of almost two fold.

Ral4.png
Ral5.png



Rust:

When the system is under the presence of chitin you can see how the positive feedback of the chitoporin and chitinase works and make their concentration increase. This has as a consequence the increase of monomers of chitin and the liberation of the sensor that is gonna activate the LuxI and LuxR promoter.

Rust1.png

Like we see with the Ralstonia systema the Lux system's concentrations increase when their promoter is activated. The complex LuxI-LuxR has a peak and then goes down a little because it is busy activation of CI and Salicylic Acid.

Rust2.png

The compounds od interest behave just like expected. Like in Ralstonia the cell is awake when the chitin is present and the Salicylic Acid has a two fold increase. It is important to see that this system takes more time to go back to the steady state than the Ralstonia's system.

Rust4.png
Rust5.png