A Dual-Recognition Electrochemical Sensor Using Bacteria-Imprinted Polymer and Concanavalin A for Sensitive and Selective Detection of Escherichia coli O157:H7
The accurate detection and quantification of pathogenic bacteria is crucial for ensuring public health. In this work, we propose a sensitive and selective sandwich electrochemical sensor for detecting <i>Escherichia coli</i> O157:H7 (<i>E. coli</i> O157:H7). The sensor employs a dual-recognition strategy that combines a bacteria-imprinted polymer (BIP) and concanavalin A (ConA). The BIP is formed in situ on the electrode surface as the capture probe, while gold nanoparticles co-functionalized with ConA and the electroactive molecule 6-(ferrocenyl)hexanethiol (Au@Fc-ConA) serve as the signaling probe. When <i>E. coli</i> O157:H7 is present, the bacteria are selectively captured by the BIP. The captured bacteria interact with Au@Fc-ConA through ConA's sugar-binding properties, triggering Fc oxidation and generating a current proportional to the bacterial concentration. The sensor exhibits a linear detection range of 10<sup>1</sup>-10<sup>5</sup> CFU mL<sup>-1</sup> and a low detection limit of 10 CFU mL<sup>-1</sup>. Additionally, it demonstrates high sensitivity in complex milk samples, detecting <i>E. coli</i> O157:H7 at concentrations as low as 10 CFU mL<sup>-1</sup>, with recoveries ranging from 94.16% to 110.6%. Even in the presence of a 100-fold higher concentration of <i>E. coli</i> O6, the sensor effectively distinguishes <i>E. coli</i> O157:H7 from it. Moreover, it exhibits high reproducibility with a relative standard deviation of 2%. This study proposes a unique dual recognition strategy that combines simplicity and high performance. This method enables the selective detection of <i>E. coli</i> O157:H7 in real samples, providing a promising tool for food safety monitoring.
Authors
- Lei Shi (ORCID: https://orcid.org/0000-0003-4027-2396)
- Juan Yan (ORCID: https://orcid.org/0000-0003-4529-2046)
- Xiangheng Niu (ORCID: https://orcid.org/0000-0003-1628-5760)
- Xiaojun Bian (ORCID: https://orcid.org/0000-0002-1750-6433)
- Yong Zhao (ORCID: https://orcid.org/0000-0003-1990-4387)
- Huijun Li (ORCID: https://orcid.org/0000-0002-2896-3867)
- Yuanbing Ma (ORCID: https://orcid.org/0009-0007-4614-0059)
- Donglei Luan (ORCID: https://orcid.org/0000-0003-2292-4880)
- Shuang Sun
Institutions
- Chinese Academy of Sciences (CN)
- State Key Laboratory of Transducer Technology (CN)
- Shanghai Institute of Microsystem and Information Technology (CN)
- Ministry of Agriculture and Rural Affairs (CN)
- Shanghai Ocean University (CN)
Publication Details
- Journal
- Foods
- Published
- 2025-03-21
- DOI
- https://doi.org/10.3390/foods14071099
- Citations
- 5
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 3.37
Funders
- Key Technology Research and Development Program of Shandong