Team:ETH Zurich/achievements

From 2013.igem.org

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<h1> We achieved </h1>
<h1> We achieved </h1>
<b>Pre-Processing:</b><br><br>
<b>Pre-Processing:</b><br><br>
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- Characterize the AHL diffusion on agar plates and define, with the predition from the model and the experimental results, the distance between colonies, the strengh of the  promoter controlling LuxI production and the incubation time for the diffusion.<br>
+
- to characterize the AHL diffusion on agar plates and define, with predictions from the model and the [https://2013.igem.org/Team:ETH_Zurich/Experiments_2 experimental results], the distance between colonies, the strengh of the  promoter controlling LuxI production and the incubation time needed to establish a proper AHL gradient.<br>
-
- To astablish several AHL gradients from different mines on one plate, intersections of gradients result in higher AHL levels for the detection of 1, 2 or 3 mines.<br>
+
- to establish several [https://2013.igem.org/Team:ETH_Zurich/Experiments_2#diffusion_experiment AHL gradients] from different mines on one plate, intersections of gradients result in higher AHL levels for the detection of 1, 2 or 3 mines.<br>
-
- Make a spatio-temporal model of AHL difussion<br><br>
+
- to make a [https://2013.igem.org/Team:ETH_Zurich/Modeling/Reaction_Diffusion_OOHL 2D spatio-temporal model] for AHL, that encompasses local reactions and diffusion.<br><br>
   
   
<b>Processing:</b><br><br>
<b>Processing:</b><br><br>
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- to design a P<sub>LuxR</sub> promoter 1st libary by site directed mutagenisis and a 2nd on by rational design  with different EC<sub>50</sub>.<br>
+
- to create a [https://2013.igem.org/Team:ETH_Zurich/Experiments_5#first mutant first mutant] P<sub>LuxR</sub> variant form P<sub>LuxR</sub> wild-type promoter by site directed mutagenisis and a [https://2013.igem.org/Team:ETH_Zurich/Experiments_5#secondlibrary 2nd library] by rational design  with different EC<sub>50</sub>.<br>
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- to measured the dose-response of those promoters in liquid culture as well as on agar plates and determined the EC<sub>50</sub> going from 0.02nM to 6482nM in liquid culture and from 4.45nM to 12'555nM on agar plates.<br>
+
- to measure the dose-response of those promoters by [https://2013.igem.org/Team:ETH_Zurich/Experiments_5#first mutant single cell analysis] and determined the EC<sub>50</sub> going from 0.02 nM to 6482 nM in liquid culture (for the wild-type and G1) and from 4.45 nM to 12'555 nM on agar plates (for the whole library).<br>
-
- to find a analytical solution for the EC<sub>50</sub> of the promoter we need and therby choose the right candidate from the libary.<br>
+
- to find a [https://2013.igem.org/Team:ETH_Zurich/Modeling/Analytical_Approximations analytical solution] for the EC<sub>50</sub> of the promoter we need and therby choose the right candidate from the libary.<br>
-
- a proof-of-principle using a GFP reporter.<br><br>
+
&rArr; '''a proof-of-principle using a GFP reporter.''' [https://2013.igem.org/Team:ETH_Zurich/Experiments_6 Experiment] / [https://2013.igem.org/Team:ETH_Zurich/GFP Model]<br><br>
   
   
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<b>Optimization:</b>
<b>Optimization:</b>
<br><br>
<br><br>
-
- the identification of the leakyness source.<br>
+
- the identification of the [https://2013.igem.org/Team:ETH_Zurich/Optimization leakiness source].<br>
-
- to model different solution to reduce the leakiness.<br>
+
- to model [https://2013.igem.org/Team:ETH_Zurich/Optimization different solutions] to reduce the leakiness, such as destabilization of proteins and double negative regulation.<br>
-
- to optimize the circuit to reduce the leakiness by introduction of a negative feedback loop.<br>
+
- to [https://2013.igem.org/Team:ETH_Zurich/Optimization optimize the circuit] to reduce the leakiness by introduction of a positive feedback loop.<br>
   
   
<b>Output:</b><br><br>
<b>Output:</b><br><br>
-
- to implement several different reporters (hydrolases and fluorencent proteins) in one construct.<br>
+
- to implement [https://2013.igem.org/Team:ETH_Zurich/Experiments_3 several reporters] (hydrolases and fluorescent proteins) in one construct.<br>
-
- to show different colormetric (yellow, salmon, violett, green, blue) response for 5 hydrolases.<br>
+
- to show different [https://2013.igem.org/Team:ETH_Zurich/Experiments_3 colorimetric responses] (yellow, salmon, magenta, violett, green and blue) for five hydrolases.<br>
-
- to show the orthogonality of all 5 hydrolases.<br>
+
- to show the [https://2013.igem.org/Team:ETH_Zurich/Experiments_3#orthogonal orthogonality] between hydrolase.<br>
-
- to characterize the hydrolases by Michaelis-Menten kinetics.<br>
+
- to show a [https://2013.igem.org/Team:ETH_Zurich/Experiments_3#overlay color overlay].<br>
-
<br><br>
+
- to [https://2013.igem.org/Team:ETH_Zurich/Experiments_3 characterize] the hydrolases with Michaelis-Menten kinetics.<br>
-
<i> A preliminary game with the hydrolases.</i><br><br>
+
 
 +
 
-
<i> Establish a spatio-temporal model of the proof-of-principle and the final game.</i>
+
<b>Information processing:</b><br><br>
 +
- to establish a spatio-temporal model of the [https://2013.igem.org/Team:ETH_Zurich/Modeling final game].
 +
<b>Human practice:</b><br><br>
 +
- analyze the [https://2013.igem.org/Team:ETH_Zurich/Human relationship] between synthetic biology and games.<br>
 +
- remote controled [https://2013.igem.org/Team:ETH_Zurich/World roboter playing] of the game.<br>
 +
- set-up an [https://2013.igem.org/Team:ETH_Zurich/HEducational educational kit] containing all parts needed to build  Colisweeper.<br>
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Latest revision as of 01:10, 29 October 2013

Header2.png
80px-Eth igem logo.png

We achieved

Pre-Processing:

- to characterize the AHL diffusion on agar plates and define, with predictions from the model and the experimental results, the distance between colonies, the strengh of the promoter controlling LuxI production and the incubation time needed to establish a proper AHL gradient.
- to establish several AHL gradients from different mines on one plate, intersections of gradients result in higher AHL levels for the detection of 1, 2 or 3 mines.
- to make a 2D spatio-temporal model for AHL, that encompasses local reactions and diffusion.


Processing:

- to create a mutant first mutant PLuxR variant form PLuxR wild-type promoter by site directed mutagenisis and a 2nd library by rational design with different EC50.
- to measure the dose-response of those promoters by mutant single cell analysis and determined the EC50 going from 0.02 nM to 6482 nM in liquid culture (for the wild-type and G1) and from 4.45 nM to 12'555 nM on agar plates (for the whole library).
- to find a analytical solution for the EC50 of the promoter we need and therby choose the right candidate from the libary.

a proof-of-principle using a GFP reporter. Experiment / Model


Optimization:

- the identification of the leakiness source.
- to model different solutions to reduce the leakiness, such as destabilization of proteins and double negative regulation.
- to optimize the circuit to reduce the leakiness by introduction of a positive feedback loop.


Output:

- to implement several reporters (hydrolases and fluorescent proteins) in one construct.
- to show different colorimetric responses (yellow, salmon, magenta, violett, green and blue) for five hydrolases.
- to show the orthogonality between hydrolase.
- to show a color overlay.
- to characterize the hydrolases with Michaelis-Menten kinetics.


Information processing:

- to establish a spatio-temporal model of the final game.

Human practice:

- analyze the relationship between synthetic biology and games.
- remote controled roboter playing of the game.
- set-up an educational kit containing all parts needed to build Colisweeper.