Guangdong Provincial Key Laboratory of Food Quality and Safety, College of Food Science, South China Agricultural University, Guangzhou, 510642, China.
College of Mathematics and Infromatics, College of Software Engineering, South China Agricultural University, Guangzhou, 510642, China.
Biosens Bioelectron. 2020 Jun 15;158:112178. doi: 10.1016/j.bios.2020.112178. Epub 2020 Mar 31.
In this study, a smartphone-based quantitative dual detection mode device, integrated with gold nanoparticles (GNPs) and time-resolved fluorescence microspheres (TRFMs) lateral flow immunoassays (LFIA) for multiplex mycotoxins in cereals were established. The most frequently used visible light and fluorescence detection modes were integrated in one device. A user-friendly application was self-written to rapidly quantify results. GNPs-LFIA and TRFMs-LFIA were used to detect aflatoxin B1 (AFB1), zearalenone (ZEN), deoxynivalenol (DON), T-2 toxin (T-2), and fumonisin B1 (FB1). The visible limits of detection (vLODs) were 10/2.5/1.0/10/0.5, 2.5/0.5/0.5/2.5/0.5 μg/kg for the two methods, respectively. The quantitative limits of detection (qLODs) were 0.59/0.24/0.32/0.9/0.27, 0.42/0.10/0.05/0.75/0.04 μg/kg, respectively. The recoveries of both LFIAs ranged from 84.0%-110.0%. A parallel analysis in 30 naturally contaminated cereal samples was conducted by liquid chromatography-tandem mass spectrometry (LC-MS/MS), the results showed good consistency, indicating the practical reliability of the established methods. The developed two smartphone-based LFIAs provide a promising technique for multiplex, highly sensitive, and on-site detection of mycotoxins.
本研究建立了一种基于智能手机的定量双检测模式装置,集成了金纳米粒子(GNPs)和时间分辨荧光微球(TRFMs)侧向流动免疫分析(LFIA),用于检测谷物中的多种真菌毒素。最常用的可见光和荧光检测模式集成在一个装置中。编写了一个用户友好的应用程序,用于快速定量结果。使用 GNPs-LFIA 和 TRFMs-LFIA 检测黄曲霉毒素 B1(AFB1)、玉米赤霉烯酮(ZEN)、脱氧雪腐镰刀菌烯醇(DON)、T-2 毒素(T-2)和伏马菌素 B1(FB1)。两种方法的可见检测限(vLOD)分别为 10/2.5/1.0/10/0.5 和 2.5/0.5/0.5/2.5/0.5μg/kg。定量检测限(qLOD)分别为 0.59/0.24/0.32/0.9/0.27 和 0.42/0.10/0.05/0.75/0.04μg/kg。两种 LFIA 的回收率均在 84.0%-110.0%之间。通过液相色谱-串联质谱法(LC-MS/MS)对 30 个自然污染谷物样品进行平行分析,结果表明具有良好的一致性,表明所建立方法的实际可靠性。开发的两种基于智能手机的 LFIA 为真菌毒素的多重、高灵敏度和现场检测提供了一种有前途的技术。