Team:Osaka/SIGNAL

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<p style="text-indent: 1em">To make an effective simulation program we regarded the cell's movement as a diffusion. Therefore we applied the fick's second law of diffusion in modeling the cells movement along with the diffusion of autoinducers. Since the law of diffusion is a differential equation(strictly speaking a partial differential equation) the need for a numerical solution was inevitable. We used the finite difference method showen in equation (1)  
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<p>To make an effective simulation program we regarded the cell's movement as a diffusion. Therefore we applied the fick's second law of diffusion in modeling the cells movement along with the diffusion of autoinducers. Since the law of diffusion is a differential equation(strictly speaking a partial differential equation) the need for a numerical solution was inevitable. We used the finite difference method showen in equation (1)  
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Then applied it and converted it which gave us the equation (2) and (3), each representing   
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<img src="https://static.igem.org/mediawiki/2009/7/71/Osaka_cell_diffuse_equation.png"width="45%" height="45%"> ...(2)
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<img src="https://static.igem.org/mediawiki/2009/1/17/Osaka_AI_diffuse_equation.png"width="30%" height="30%"> ...(3)
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Revision as of 12:20, 10 October 2009

Home of iGEMOSAKA wiki

SIGNAL

Overview

We will be using signaling parts from quorum sensing systems of various bacteria to implement intracellular communication between bacterial colonies of different 'colors'. If it works, we can for example cause two colonies of bacteria to change color or stop moving as they approach each other, hopefully resulting in interesting patterns.


Currently we are working on 2 distinct groups of parts: 'Senders' and 'Receivers'. 'Senders' code for enzymes that produce AHL signal molecules, which diffuse out of the cell, through the culture medium and into the receiving cell, where a receptor protein encoded by the 'Receiver' binds the signals, forming a complex which in turn can bind to and upregulate transcription from specific promoter.


To test the effectiveness of our signaling system, we will first test the Receivers by attaching a GFP coding unit (rbs + protein coding region + terminator) behind the Receiver's AHL-activated promoter. We will then directly add chemically-derived AHL into culture solutions of these 'Test Receivers' and look for GFP fluorescence which will indicate that transcription has been activated by AHL.


Following that, we will test the Senders by using the above Receivers. We can determine the amount of AHL produced by the Senders by comparing transcription activity induced by the Senders in relation to AHL-induced trancription activity.


Once both Sender and Receiver function has been confirmed and characterized, we will then attempt to characterize the function of the whole system in a way that relates to our intended usage. We will spot two colonies, one of Senders and one of Receivers, on a soft agar plate and determine the maximum distance that the Senders can successfully activate the Receivers. Of course, this will only work if the AHL molecules can effectively diffuse through the agar medium.


Stay tuned for more updates! :)

Object

Under construction

Implement

Under construction


Model

To make an effective simulation program we regarded the cell's movement as a diffusion. Therefore we applied the fick's second law of diffusion in modeling the cells movement along with the diffusion of autoinducers. Since the law of diffusion is a differential equation(strictly speaking a partial differential equation) the need for a numerical solution was inevitable. We used the finite difference method showen in equation (1)
Then applied it and converted it which gave us the equation (2) and (3), each representing the diffusion of the cell(or colony) and the autoinducer.
...(2)
...(3)