Suppr超能文献

用于环境水中亚砷酸盐检测的细菌生物传感器的进化。

Evolved bacterial biosensor for arsenite detection in environmental water.

机构信息

†Key Laboratory of Ion Beam Bioengineering, Hefei Institutes of Physical Science, Chinese Academy of Sciences and Anhui Province, Hefei 230031, Anhui, People's Republic of China.

‡School of Life Sciences, University of Science and Technology of China, Hefei 230026, Anhui, People's Republic of China.

出版信息

Environ Sci Technol. 2015 May 19;49(10):6149-55. doi: 10.1021/acs.est.5b00832. Epub 2015 May 5.

Abstract

Arsenic, a ubiquitous presence in the biosphere, often occurs from both natural and anthropogenic sources. Bacterial biosensors based on genetically engineered bacteria have promising applications in detecting the chemical compound and its toxicity. However, most of the bacteria biosensors take advantage of the existing wild-type substrate-induced promoters, which are often low in specificity, affinity and sensitivity, and thus limiting their applications in commercial or field use. In this study, we developed an in vivo evolution procedure with a bidirectional selection scheme for improving the sensitivity of an arsenite-responsive bacterial biosensor through optimization of the inducible operon. As a proof of concept, we evolved the arsenite-induced arsR operon for both low background and high expression through three successive rounds of fluorescence activated cell sorting (FACS) with bidirectional strategy. An arsR operon variant with 12-fold higher activity over the control was isolated, confirming multiple rounds of construction and screening of mutation library, as described here, can be efficiently applied to bacterial biosensor optimization. The evolved arsenite-responsive biosensor demonstrated an excellent performance in the detection of low trace arsenite in environmental water. These results indicate that the technologies of directed evolution could be used to improve the performance of bacterial biosensors, which will be helpful in promoting the practical application of bacterial biosensors.

摘要

砷是一种在生物圈中普遍存在的物质,通常来自自然和人为来源。基于基因工程细菌的细菌生物传感器在检测化学化合物及其毒性方面具有广阔的应用前景。然而,大多数细菌生物传感器利用现有的野生型底物诱导启动子,这些启动子特异性、亲和力和灵敏度往往较低,因此限制了它们在商业或现场应用中的应用。在本研究中,我们开发了一种体内进化程序,采用双向选择方案,通过优化诱导操纵子来提高亚砷酸盐响应细菌生物传感器的灵敏度。作为概念验证,我们通过三轮荧光激活细胞分选(FACS)进行双向策略,分别对低背景和高表达的亚砷酸盐诱导的 arsR 操纵子进行了进化。分离出的 arsR 操纵子变体的活性比对照提高了 12 倍,证实了如这里所述的多次构建和突变文库筛选可以有效地应用于细菌生物传感器的优化。进化后的亚砷酸盐响应生物传感器在检测环境水中的痕量亚砷酸盐方面表现出优异的性能。这些结果表明,定向进化技术可用于提高细菌生物传感器的性能,这将有助于促进细菌生物传感器的实际应用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验