Team:Grenoble-EMSE-LSU/Project/Validation/Future

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<h3>Test of the Device</h3>
<h3>Test of the Device</h3>
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<p>To test the device, and to show that a model predictive control algorithm is able to automatically run the experiment. A XXX program will be written to automatize the manual procedure that we employed for the <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Validation">proof of concept</a> experiment .</p>
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<p>To test the device, and to show that a model predictive control algorithm is able to automatically run the experiment. A Java program will be written to automatize the manual procedure that we employed for the <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Validation">proof of concept</a> experiment .</p>
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<h2> Perspectives</h2>
<h2> Perspectives</h2>
<h3> Studying bacterial resistance to oxidative stress</h3>
<h3> Studying bacterial resistance to oxidative stress</h3>
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<p>The possibility to independently control the amount of KillerRed expressed in the cells and its phototoxic activity will allow us to obtain cell suspension growing at a precisely defined oxidative stress. Our device indeed allows controlling the ROS production rate in living bacteria. In the frame of our model, this means making the quantity IK/C constant. Assuming that ROS disappear at a rate proportional to the ROS concentration, the ROS concentration per living cell will thus remain constant. Our bio-electronic system can thus be useful to study the influence of ROS on cell growth, and to investigate how different genes and molecule affect bacterial resistance to oxidative stress. Practically, one would first determine the specific parameters of the bacterial suspension as explained before, then the light intensity time profile will be calculated with our model and applied to the bacterial suspension. </p>
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<p>The possibility to independently control the amount of KillerRed expressed in the cells and its phototoxic activity will allow us to obtain cell suspension growing at a precisely defined oxidative stress. Our device indeed allows controlling the ROS production rate in living bacteria. In the frame of our model, this means making the quantity $\frac{IK}{C}$ constant. Assuming that ROS disappear at a rate proportional to the ROS concentration, the ROS concentration per living cell will thus remain constant. Our bio-electronic system can thus be useful to study the influence of ROS on cell growth, and to investigate how different genes and molecule affect bacterial resistance to oxidative stress. Practically, one would first determine the specific parameters of the bacterial suspension as explained before, then the light intensity time profile will be calculated with our model and applied to the bacterial suspension. </p>
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Latest revision as of 03:57, 5 October 2013

Grenoble-EMSE-LSU, iGEM


Grenoble-EMSE-LSU, iGEM

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