Copper is a common heavy metal and is considered as a priority pollutant. At present, copper released from agricultural, industrial and mining wastes into water environment poses a serious threat to the stability of ecosystem. The lack of effective warning tools for copper pollution has led to many negative effects. For example, contaminated soils in China's Jiuhua Mountains have led to the accumulation of more than 40 mg kg-1 of copper ions in food crops, posing a potential health hazard to residents, while copper contamination from the Salvador mine in Chile highlights its enormous impact on marine invertebrates, fish and algae in the Chañaral Bay. Although trace copper plays an important role in physiological processes, high-dose copper exposure can destroy endocrine and immune systems, and lead to oxidative stress, liver cirrhosis, renal dysfunction and serious neurodegenerative diseases. Therefore, it is urgent to develop an effective and environmentally friendly copper in-situ analysis method as an implementation tool for water quality assessment, which can provide direct basis for eliminating copper pollution.

  The conventional determination methods of copper include anodic stripping voltammetry, ultraviolet-visible spectrometry, fluorescence spectrometry, colorimetry, flame atomic absorption spectrometry (FAAS), X-ray fluorescence spectrometry (XFS) and inductively coupled plasma emission spectrometry (ICP-OES). Among them, anodic stripping voltammetry and ultraviolet-visible spectroscopy are insensitive. XFS is a quantitative analysis of fluorescence intensity emitted by atoms excited by radiation energy. FAAS and ICP-OES measured HM concentration by observing the characteristic peaks formed in the gas phase. These methods can be used to detect heavy metals comprehensively, and have high sensitivity and accuracy. However, they usually require

  It requires expensive equipment, laborious operation, professional technicians and complicated pretreatment process. In addition, due to the huge equipment and complex detection process, it is not suitable for real-time measurement and in-situ analysis.

  Recently, biosensors based on microbial fuel cell (MFC) have been widely developed as a new substitute for pollutant detection, which has the advantages of miniaturization, easy operation and low cost. However, this technology for monitoring specific substrates has not been fully utilized. As a low-power in-situ sensing tool, MFC biosensor mediated by synthetic biology has shown great potential in system design and engineering application in electrochemistry field. By combining different promoters and voltage output elements to design "AND" and "OR" circuit logic gates, modular genetic elements can be used to customize biosensors for analyzing various or multiple target pollutants. Therefore, the combination of synthetic biology and engineering will further expand the application potential of MFC biosensors in detecting specific substrates.

  We decided to create a biosensor for copper ion detection based on microbial fuel cell (MFC), which provides an economical, sensitive and practical technology for copper ion detection

  Engineering strains were used in biosensors based on microbial fuel cell (MFC).

  In the presence of copper ion, copper-sensitive promoter pcutR is activated, ribB gene is expressed, which promotes riboflavin synthesis, and riboflavin promotes electron transfer to generate voltage. With the help of porin encoded by oprF, it promotes electron transfer and increases the voltage generation of MFC.

  The equation Y = 0.3199 X + 259.199 (Y voltage, X copper concentration) was obtained by fitting the data of copper ion concentration with the maximum voltage produced by MFC. After adding external copper ions to our MFC biosensor, our sensor generates voltage. By substituting the maximum voltage Y into the equation Y = 0.3199X + 259.19, the copper ion concentration X can be obtained, and we can detect whether the copper ion concentration in water meets the standard according to X.

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