SENSING SUPERFUND CHEMICALS WITH RECOMBINANT SYSTEMS

某些细菌含有编码蛋白质和/或酶的基因， 降低或增强对有毒化合物的抵抗力。 将从这些构建生物发光报告质粒 基因(包含其启动子元件)与其他基因连锁 具有发光能力(细菌荧光素酶基因)。 这些质粒将被依次导入到合适的宿主菌中 生产一种生物检测系统，能够检测低血压 超级基金中铬等有害物质的浓度 (Vi)、砷(亚砷酸盐和亚砷酸盐)和镍。重组人 将对细菌进行抗药性基因的表达和 在危险物质存在的情况下的荧光素酶基因。 具体而言，当目标有害物质存在于 抗病相关蛋白的产生 构建的报告质粒将被诱导。由于同样的原因 含有荧光素酶基因的质粒中，荧光素酶也会 产生了细菌，细菌就会发光。这种生物发光是 与目标危险化学品的存在直接相关 并构成分析信号。基因设计的 细菌在生物传感器研究中的应用 探测系统。通过将这些细菌放置在光学元件的前面 将开发高灵敏度和选择性的光纤生物传感器 能够监测超级基金有害物质的水平 环境样本(地下水和土壤)。建筑的建设 传感器将在光学设计方面进行优化， 细菌筛选和细菌固定化。诸如以下因素 壳体中固体表面的响应时间、选择性和效果 将对土壤进行评估。将通过以下方式进行进一步评估 在超级基金的实际样本中测试传感器响应 使用传统的提取和提取方法对污染物进行量化 光谱技术。

Certain bacteria contain genes that encode proteins and/or enzymes, which degrade or confer resistance to toxic compounds. Bioluminescent reporter plasmids will be constructed from these genes (containing their promoter elements) by linkage to other genes with the capability of light emission (bacterial luciferase genes). These plasmids will be introduces into suitable host bacteria in order to produce a biological detection system, capable of detecting low concentrations of Superfund hazardous substances such as chromium (VI), arsenic (arsenate and arsenite), and nickel. The recombinant bacteria will be examined for expression of the resistance genes and the luciferase genes in the presence of the hazardous substances. Specifically, when the targeted hazardous substance is present in the sample, production of resistance-related proteins from the genes in the constructed reported plasmid will be induces. Since the same plasmid contains the luciferase genes, luciferase will also be produced and the bacteria will bioluminesce. This bioluminescence is directly related to the presence of the targeted hazardous chemical and constitutes the analytical signal. The genetically designed bacteria will be employed in the development of biosensor based detection systems. By positioning these bacteria in front of optical fibers highly sensitive and selective biosensors will be developed capable of monitoring the level of Superfund hazardous substances in environmental samples (groundwater and soil). The construction of the sensors will be optimized with respect to the optical design, bacteria selection, and bacteria immobilization. Factors such as response time, selectivity, and effect of the solid surface in the case of soil will be evaluated. Further evaluation will be carried out by testing the sensor response in actual Superfund samples and quantification of the contaminants using traditional extraction and spectroscopic techniques.