Mercury(编程语言)
镉
海水
环境化学
重金属
环境科学
铅(地质)
污染
生物传感器
化学
生态学
生物
计算机科学
古生物学
有机化学
程序设计语言
生物化学
作者
Shun-yu Hu,Chang-ye Hui,Can Wu,Chao-xian Gao,Zhenlie Huang,Yan Guo
标识
DOI:10.1016/j.ecolind.2024.112244
摘要
Estimating bioavailable heavy metals in seawater is closely related to the indication of ecological risk. This study combined a CadR-regulated vioABE expression module and a MerR-regulated VioC expression module to generate a novel dual-colored bacterial cell-based biosensor. After genetic optimization, the preferred biosensor could detect as low as 9.7 nM Cd(II), 24.4 nM Pb(II), and 0.5 nM Hg(II). Increased grey-green intensities were observed in Cd(II) (4.9 nM to 40 μM) and Pb(II) (24.4 nM to 200 μM) exposure groups. Interestingly, increased purple intensity was observed in the Hg(II) exposure group (3.7 to 468.8 nM) in a dose-dependent manner. A low-cost and mini-equipment biosensing process was established for detecting pollutant heavy metals in seawater, with the added advantage of providing information on the bioavailability and cytotoxicity of heavy metals. High salinity weakly interferes with the biosensing response to Hg(II). This study shows that novel colorimetric biosensors have the potential to simultaneously report various toxic metals in environmental water samples, contributing to protecting marine ecology.
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