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 in alkane biosynthesis research. Our project offers a novel solution to the problem. In our project we constructed a sensor, named AlkSensor, that could respond to certain alkanes. We developed a mathematical model to find ways to optimize and regulate the sensor. After the construction of AlkSensor, 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 relationship between AlkSensor’s input and output. 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.
"
