開發高效能性生物晶片應用在含氯化物生物整治及策略評估(3/3)

Polychlorinated ethylene, a kind of toxicant, is a common groundwater pollutant in Taiwan. The physicochemical properties of this pollutant is dense non-aqueous phase liquid (DNAPL) . Once it enters the underground environment, it moves quickly under the surface due to its low viscosity, which makes it difficult to be remediated. Among them, trichloroethylene (TCE) and vinyl chloride are recognized as human carcinogens. Therefore, the remediation of polyvinyl chloride is essential for the health of people. At present, many methods for remediation of polychlorinated ethylene sites are mainly focused on bioremediation. Bioremediation can be subdivided into biostimulation and bioaugmentation methods. In order to test the efficacy of biomediation, real-time dynamic biological monitoring is essential for monitoring the community of the potential bacteria for bioremediation via metagenome. However, the cost of metagenome is high, and the analysis of metagenome data is performed with bioinformatics, which could deter the use of metagenome in bioremediation. Therefore, our project will attempt to develop TCE-based genes microarray, a cost and timing- saving method, that can be efficiently tested for dechlorination bacteria and the effects of remediation. The three-year project will focus on dechlorination probe design and pre-sample testing in the first year, confirming the sensitivity and accuracy of the microarray. In the second year, we will produce microarray in small quantities and optimize the analytical process. The third year our developing microarray will be applied to pollutant water, whose data will be compared to the data of quantitative PCR and metagenomic analysis. Finally, after cost-benefit analysis, we hope to commercialize our microarray. The aim of this project is to provide an innovative technology which help a lot of companies in Taiwan, to devise a bioremediation strategy based on the kinetic changes of bacterial community. Speedy, efficiency, and cost-saving are our hot spots for developing microarray.