Zhang Xiya, Yu Xuezhi, Wen Kai, Li Chenglong, Mujtaba Mari Ghulam, Jiang Haiyang, Shi Weimin, Shen Jianzhong, Wang Zhanhui
Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University , Beijing 100193, People's Republic of China.
Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety , Beijing 100193, People's Republic of China.
J Agric Food Chem. 2017 Sep 13;65(36):8063-8071. doi: 10.1021/acs.jafc.7b02827. Epub 2017 Aug 31.
The detecting labels used for lateral flow immunoassays (LFAs) have been traditionally gold nanoparticles (GNPs) and, more recently, luminescent nanoparticles, such as quantum dots (QDs). However, these labels have low sensitivity and are costly, in particular, for trace detection of mycotoxins in cereals. Here, we provided a simple preparation procedure for amorphous carbon nanoparticles (ACNPs) and described multiplex LFAs employing ACNPs as labels (ACNP-LFAs) for detecting three Fusarium mycotoxins. The analytical performance of ACNPs in LFA was compared to GNPs and QDs using the same immunoreagents, except for the labels, allowing for their analytical characteristics to be objectively compared. The visual limit of detection for ACNP-LFAs in buffer was 8-fold better than GNPs and 2-fold better than QDs. Under optimized conditions, the quantitative limit of detection of ACNP-LFAs in maize was as low as 20 μg/kg for deoxynivalenol, 13 μg/kg for T-2 toxin, and 1 μg/kg for zearalenone. These measurements were much lower than the action level of these mycotoxins in maize. The accuracy and precision of the ACNP-LFAs were evaluated by analysis of spiked and incurred maize samples with recoveries of 84.6-109% and coefficients of variation below 13%. The results of ACNP-LFAs using naturally incurred maize samples showed good agreement with results from high-performance liquid chromatography-tandem mass spectrometry, indicating that ACNPs were more sensitive labels than and a promising alternative to GNPs used in LFAs for detecting mycotoxins in cereals.
传统上，用于侧向流动免疫分析（LFA）的检测标记物是金纳米颗粒（GNP），最近则是发光纳米颗粒，如量子点（QD）。然而，这些标记物灵敏度低且成本高，尤其是用于谷物中霉菌毒素的痕量检测时。在此，我们提供了一种无定形碳纳米颗粒（ACNP）的简单制备方法，并描述了采用ACNP作为标记物的多重LFA（ACNP-LFA）用于检测三种镰刀菌霉菌毒素。除标记物外，使用相同的免疫试剂将LFA中ACNP的分析性能与GNP和QD进行了比较，从而能够客观地比较它们的分析特性。缓冲液中ACNP-LFA的目视检测限比GNP好8倍，比QD好2倍。在优化条件下，ACNP-LFA在玉米中对脱氧雪腐镰刀菌烯醇的定量检测限低至20μg/kg，对T-2毒素为13μg/kg，对玉米赤霉烯酮为1μg/kg。这些测量值远低于这些霉菌毒素在玉米中的行动水平。通过分析加标和实际污染的玉米样品评估了ACNP-LFA的准确性和精密度，回收率为84.6-109%，变异系数低于13%。使用天然污染玉米样品的ACNP-LFA结果与高效液相色谱-串联质谱法的结果显示出良好的一致性，表明ACNP是比LFA中用于检测谷物中霉菌毒素的GNP更灵敏的标记物，且是一种有前景的替代物。
