Team:Tianjin

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<p style="font-size:30px;font-family:Arial, Helvetica, sans-serif;text-align:center;color:#a7a7a7;word-spacing:0.3em;">Abstract</p>
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<p style="font-size:16px;font-family:Arial, Helvetica, sans-serif;line-height:150%; word-spacing:0.2em;">Biosynthesized alkanes are promising candidates for drop-in replacement of petroleum. Our goal is to optimize the pathway of alkane synthesis and get high productivity. We picked out several key points in the pathway from glucose to various alkanes and generated a large number of strains with different productivity. In order to select out the ones with highest productivity, we designed a device named AlkFinder. The core of AlkFinder is a biosensor which can recognize sensitively alkane molecules within the cell and turn on the expression of downstream genes functioning as selection module. With AlkFinder, we managed to select the optimized genes of the pathway effectively and efficiently.  
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Among all kinds of biofuels, alkanes stand out because of its excellent properties. Due to the inconspicuous property of alkanes, the current alkane detection or sensing methods can hardly meet the demands. Our project offers a novel solution to the problem. In our project we constructed a sensor that could respond to certain alkanes. We developed a mathematical model to find ways to optimize and regulate the sensor. After construction, we performed an in vivo alkane sensing test. The qualitative test showed AlkSensor could function as we expected. Besides, we characterized AlkSensor with different inducers and obtained the quantitative response relationship of AlkSensor. What is more, we designed an selection strategy based on AlkSensor to select out the strains with high productivity of alkanes. A preliminary test was performed and the result verified the feasibility of this design.
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<p style="color:#FFF;"><center><h1>Sponsor</h1></center></p>
 
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Latest revision as of 05:41, 13 October 2013

Abstract

Among all kinds of biofuels, alkanes stand out because of its excellent properties. Due to the inconspicuous property of alkanes, the current alkane detection or sensing methods can hardly meet the demands. Our project offers a novel solution to the problem. In our project we constructed a sensor that could respond to certain alkanes. We developed a mathematical model to find ways to optimize and regulate the sensor. After construction, we performed an in vivo alkane sensing test. The qualitative test showed AlkSensor could function as we expected. Besides, we characterized AlkSensor with different inducers and obtained the quantitative response relationship of AlkSensor. What is more, we designed an selection strategy based on AlkSensor to select out the strains with high productivity of alkanes. A preliminary test was performed and the result verified the feasibility of this design.

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