Plasmonic ELISA based on enzyme-assisted etching of Au nanorods for the highly sensitive detection of aflatoxin B1 in corn samples

纳米棒 黄曲霉毒素 肉眼 化学 材料科学 葡萄糖氧化酶 检出限 线性范围 色谱法 辣根过氧化物酶 表面等离子共振 等离子体子 纳米颗粒 分析化学(期刊) 核化学 纳米技术 生物化学 光电子学 食品科学
作者
Ying Xiong,Ke Pei,Yunqing Wu,Hong Duan,Weihua Lai,Yonghua Xiong
出处
期刊:Sensors and Actuators B-chemical [Elsevier]
卷期号:267: 320-327 被引量:94
标识
DOI:10.1016/j.snb.2018.04.027
摘要

In this work, we reported an advanced enzyme-assisted etching method using gold nanorods (AuNRs) as signal output of plasmonic enzyme-linked immunosorbent assay (pELISA) for the quantitative or qualitative detection of aflatoxin B1 (AFB1) in real corn samples. AFB1-labeled glucose oxidase was adopted as the competing antigen to catalyze glucose into H2O2. Meanwhile, horseradish peroxidase was employed to catalyze H2O2 and hence generate .OH. The AuNRs with the aspect ratio of 2:1 were chemically etched by OH to a rod-like morphology. This occurrence reduced the optical density at 650 nm and resulted in a vivid color response from bluish-green to red easily detectable by a microplate reader for quantitative AFB1 analysis or by the naked eye for qualitative AFB1 detection. Various parameters that may influence the detection performance of pELISA were investigated. The proposed method showed an extremely high sensitivity for qualitative AFB1 detection, with a visible cut-off value of 12.5 pg/mL. The technique also achieved a good linear range of 3.1–150 pg/mL for quantitative AFB1 analysis, with a half-maximal inhibitory concentration of 22.3 pg/mL, which was approximately 32 folds lower than those of conventional ELISA (707 pg/mL). The average recoveries for corn samples spiked with different concentrations of AFB1 ranged from 82% to 115%, with a coefficient of variation that ranged from 2% to 13%. These values corresponded to an acceptable accuracy and precision for the proposed method. In addition, the reliability of the proposed method was further confirmed by the liquid chromatography–tandem mass spectrometry (LC–MS/MS) method. In brief, this work offers an improved screening strategy with high sensitivity and robustness for the qualitative or quantitative detection of mycotoxins or other pollutants in food safety monitoring.
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