Colorimetry/fluorescence dual-mode detection of Salmonella typhimurium based on self-assembly of MCOF with Au NPs nanozyme coupled AIEgen

被引:28
作者
Li, Hang [1 ]
Xu, Hui [1 ]
Yao, Shuo [1 ]
Wei, Shengnan [1 ]
Shi, Xuening [1 ]
Zhao, Chao [1 ]
Li, Juan [1 ]
Wang, Juan [1 ]
机构
[1] Jilin Univ, Sch Publ Hlth, Changchun 130021, Peoples R China
基金
中国国家自然科学基金;
关键词
Magnetic covalent organic framework; Aggregation-induced emission; Dual-mode detection; Foodborne pathogen; Linear discriminant analysis; COVALENT ORGANIC FRAMEWORK; ACID;
D O I
10.1016/j.talanta.2023.125505
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Sensitive, accurate, simple and quick monitoring of Salmonella typhimurium (S. typhimurium) in food is significant for preventing food poisoning, but still remains a challenge. Herein, a colorimetry/fluorescence dual-mode sensing strategy was fabricated to detect S. typhimurium by integrating the self-assembly of magnetic covalent organic framework (MCOF) with gold nanoparticles (Au NPs) as the peroxidase-mimicking nanozyme and aggregation-induced emission luminogen (AIEgen). S. typhimurium could competitive bind to aptamer conjugated Au NPs (Au NPs@apt), inhibit the self-assembly of MCOF with Au NPs, and shield the catalytic activity of AuNPs. After adding H2O2 and TPE-4A, the dark green solution changed to light with increasing S. typhimurium concentration, on the contrary, the fluorescent signals were generated. As a result, in colorimetry/fluorescence modes, S. typhimurium could be detected in the linear ranges of 103-108 CFU mL-1 and 101-107 CFU mL-1, with LODs of 1000 and 10 CFU mL-1, respectively. Importantly, different colors consistent with various S. typhimurium concentrations can be accurately classified by smartphone app and linear discriminant analysis (LDA). The smartphone-assisted data interpretation can generate complementary colorimetry and fluorescence signals without any sophisticated equipment and achieve on-site detection. Moreover, the proposed strategy could be explored for S. typhimurium monitoring in milk with satisfactory recoveries (97.6-100.4 %) in colorimetry and fluorescence mode and good classification and prediction performance in smartphone/LDA system, suggesting the feasibility and potential applications of the sensing platform.
引用
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页数:9
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