基于适配体-阳离子化合物诱导纳米金聚集比色法快速检测苏丹红

Colorimetric Detection of Sudan Based on the Aptamer and Cationic Compound Induced Gold Nanoparticles Aggregation

本研究以苏丹红Ⅲ适配体为识别元件,以未修饰的纳米金传感信号,以聚二烯丙基二甲基氯化铵(PDDA)作为纳米金聚集的诱导剂,构建了一种简单、经济、快速的苏丹红比色检测方法。在优化条件下评估本方法的检测灵敏度、准确性和特异性,最后应用于食品中苏丹红快速检测,并将检测结果与国标法(GB/T 19681-2005)对比验证。结果显示,在PDDA浓度20 nmol/L、适配体浓度5 nmol/L、反应时间4 min等优化条件下,纳米金吸光度比值(A_(650nm)/A_(530nm))与苏丹红Ⅲ浓度呈良好线性关系(R=0.986),线性检测范围为3.13~50 ng/mL,可视化检测限为3.13 ng/mL,检测时间约为5 min。特异性分析显示,本方法对苏丹红Ⅰ、Ⅱ、Ⅲ和Ⅳ有高的特异性,与柠檬黄、日落黄、分散橙11等无交叉反应。将本方法应用于食品中苏丹红检测,加标回收率为85.4%~102.5%,相对标准偏差为3.37%~6.75%。本方法具有操作简便、快速、结果易读等优点,适用于批量样品中苏丹红的现场快速检测。

In this study,a simple,economical and rapid colorimetric assay was developed for the detection of Sudan,in which Sudan-binding aptamer was used as recognition element,unmodified gold nanoparticles(AuNPs)as sensing signal,and poly(diallyldimethylammonium chloride)(PDDA)as inducer for gold nanoparticle aggregation.The sensitivity,accuracy and specificity of developed method were evaluated under optimized condition.Finally,the colorimetric sensor was applied to detection Sudan in food samples,and the results were compared with GB standard method(GB/T 19681-2005).The best procedure for Sudan analysis in our system was:The concentration of aptamer at 5 nmol/L,the concentration of PDDA at 20 nmol/L,and the reaction time was 4 min.The correlation between concentration of SudanⅢand absorbance ratio of gold nanoparticles(A_(650nm)/A_(530nm))was observed to be linear within the range of 3.13 to 50 ng/mL.The limit of visual detection was 3.13 ng/mL by naked-eye observation.The detection time was 5 min.The colorimetric sensor had high specificity for SudanⅠ,Ⅱ,ⅢandⅣ,and no cross-reactivity towards sunset yellow,tartrazine,and 1-amino-2-methylanthraquinone.Further,the colorimetric sensor was applied to measure SudanⅢin spiked real samples,and the recoveries were in the range of 85.4%~102.5%,with relative standard deviations of 3.37%~6.75%.Our study provides a simple,fast,and easy to read method for Sudan analysis,which can be applied in future on-site detection in food samples.