Imperial/Infector Detector/Modelling

From 2007.igem.org

(Difference between revisions)
(Introduction)
Line 21: Line 21:
==Introduction ==
==Introduction ==
Infector Detector (ID) is a simple biological detector, which serves to expose bacterial biofilm. It functions by exploiting the inherent AHL (Acetyl Homoserine Lactone)  production employed by certain types of quorum-sensing bacteria, in the formation of such structures.<br>
Infector Detector (ID) is a simple biological detector, which serves to expose bacterial biofilm. It functions by exploiting the inherent AHL (Acetyl Homoserine Lactone)  production employed by certain types of quorum-sensing bacteria, in the formation of such structures.<br>
 +
This section presents a preliminary model for an AHL detector, which employs the backbone of the Lux quorum sensing feedback mechanism. Figure 1 illustrates the full system we are investigating.
In the design phase, two possible system constructs were proposed, as a solution to the problem of detecting AHL-producing biofilm.  
In the design phase, two possible system constructs were proposed, as a solution to the problem of detecting AHL-producing biofilm.  
 +
According to our specifications, the most crucial feature of this system is the sensitivity to a minimum [AHL] of 5nm. In other words, this represents the minimal AHL concentration for appreciable expression of a chosen reporter protein.
 +
Furthermore, we attempt to establish a functional range for possible AHL detection. How does increased AHL concentration impact on the maximal output of reporter protein?
 +
Finally, how can the system performance be tailored, by exploiting possible inputs to the system (e.g. varying initial LuxR concentration and/or concentration of pLux promoters).
 +
How does such customization impact upon the maximal output of fluorescent reporter protein and/or response time?
-
This section presents a preliminary model for an AHL detector, which employs the backbone of the Lux quorum sensing feedback mechanism. Figure 1 illustrates the full system we are investigating.
+
We attempt to answer these questions by conducting simulation of the system ''in-silico''.
-
 
+
-
In doing so, a complete investigation of the level of sensitivity to AHL concentration needs to be performed -in other words, what is the minimal AHL concentration for appreciable expression of a chosen reporter protein. Furthermore, establish a functional range for possible AHL detection. How does increased AHL concentration impact on the maximal output of reporter protein?<br>
+
-
Finally, how can the system performance be tailored, by exploiting possible state variables (e.g. varying initial LuxR concentration and/or concentration of pLux promoters). 
+
-
 
+
-
The system performance here revolves most importantly around AHL sensitivity; however, the effect on the maximal output of fluorescent reporter protein and response time is, likewise, of great importance.
+
==Implementation & Reaction Network==
==Implementation & Reaction Network==

Revision as of 00:34, 24 October 2007



Introduction

Infector Detector (ID) is a simple biological detector, which serves to expose bacterial biofilm. It functions by exploiting the inherent AHL (Acetyl Homoserine Lactone) production employed by certain types of quorum-sensing bacteria, in the formation of such structures.
This section presents a preliminary model for an AHL detector, which employs the backbone of the Lux quorum sensing feedback mechanism. Figure 1 illustrates the full system we are investigating.

In the design phase, two possible system constructs were proposed, as a solution to the problem of detecting AHL-producing biofilm. According to our specifications, the most crucial feature of this system is the sensitivity to a minimum [AHL] of 5nm. In other words, this represents the minimal AHL concentration for appreciable expression of a chosen reporter protein. Furthermore, we attempt to establish a functional range for possible AHL detection. How does increased AHL concentration impact on the maximal output of reporter protein? Finally, how can the system performance be tailored, by exploiting possible inputs to the system (e.g. varying initial LuxR concentration and/or concentration of pLux promoters). How does such customization impact upon the maximal output of fluorescent reporter protein and/or response time?

We attempt to answer these questions by conducting simulation of the system in-silico.

Implementation & Reaction Network

Construct 1

Construct 2


Representative Model

Model 2, an energy-dependent network, where the dependence on energy assumes Hill-like dynamics

Simulations

Sensitivity Analysis?

Conclusions

<< Design | Modelling | Implementation >>