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中国精品科技期刊2020

基于还原氧化石墨烯的电化学适配体传感器对黄曲霉毒素M1的检测

惠媛媛 王毕妮 张富新 彭海帅 刘玉芳 贾蓉 任荣

惠媛媛,王毕妮,张富新,等. 基于还原氧化石墨烯的电化学适配体传感器对黄曲霉毒素M1的检测[J]. 食品工业科技,2021,42(14):249−256. doi:  10.13386/j.issn1002-0306.2020090147
引用本文: 惠媛媛,王毕妮,张富新,等. 基于还原氧化石墨烯的电化学适配体传感器对黄曲霉毒素M1的检测[J]. 食品工业科技,2021,42(14):249−256. doi:  10.13386/j.issn1002-0306.2020090147
HUI Yuanyuan, WANG Bini, ZHANG Fuxin, et al. An Electrochemical Aptasensor for Detection of Aflatoxin M1 Based on Reduced Graphene Oxide[J]. Science and Technology of Food Industry, 2021, 42(14): 249−256. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2020090147
Citation: HUI Yuanyuan, WANG Bini, ZHANG Fuxin, et al. An Electrochemical Aptasensor for Detection of Aflatoxin M1 Based on Reduced Graphene Oxide [J]. Science and Technology of Food Industry, 2021, 42(14): 249−256. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2020090147

基于还原氧化石墨烯的电化学适配体传感器对黄曲霉毒素M1的检测

doi: 10.13386/j.issn1002-0306.2020090147
基金项目: 陕西省重点研发计划重点产业创新链项(2019ZDLNY06-06;2020ZDLNY02-08);中央高校基本科研业务费专项资金(GK202003084)
详细信息
    作者简介:

    惠媛媛(1994−),女,博士研究生,研究方向:食品安全快速检测,Email:Email:huiyuanyuan2830@163.com

    通讯作者:

    王毕妮(1980−),女,博士,教授,研究方向:食品安全快速检测,Email:Email:biniwang@snnu.edu.cn

  • 中图分类号: TS207.3

An Electrochemical Aptasensor for Detection of Aflatoxin M1 Based on Reduced Graphene Oxide

  • 摘要: 本实验基于还原氧化石墨烯(RGO)构建了一种用于黄曲霉毒素M1(AFM1)检测的电化学适配体传感器。采用红枣汁还原氧化石墨烯(GO)制备RGO,RGO通过滴涂法修饰在玻碳电极(GCE)表面,利用电沉积法将纳米金修饰在RGO/GCE上,AFM1的适配体(Apt)通过Au-S键固定在AuNPs/RGO/GCE电极表面用于靶标AFM1的捕获。当AFM1存在时,AFM1与适配体特异性结合形成AFM1-Apt复合物,该复合物阻碍了电子的传递,导致电化学信号减弱。对RGO的制备条件进行优化,利用差示脉冲伏安法(DPV)监测电极表面的电化学信号,并对不同类型的毒素(黄曲霉毒素B1、黄曲霉毒素B2、赭曲霉毒素A和伏马毒素B1)、不同浓度的AFM1(1×10−7~5×10−4 ng/mL)以及羊乳样品进行检测以确定电化学适配体传感器的特异性、灵敏性和实用性。结果表明,GO:红枣汁=2:1(V:V),pH=11时所制备的RGO的导电能力最强。传感器的电信号与AFM1浓度的对数呈线性关系,检测范围为1×10−7~5×10−4 ng/mL,检测限为3.3×10−5 pg/mL,同时所建立的方法仅对AFM1的检测有响应,而对干扰毒素无响应,说明电化学适配体传感器的特异性良好。使用建立的AFM1电化学适配体传感器对羊奶中的AFM1含量进行测定,发现所构建的传感器具有很高的灵敏性和良好的选择性,有望应用于食品工业中真菌毒素的快速、准确检测当中。
  • 图  1  基于还原氧化石墨烯的电化学适配体传感器检测AFM1原理图

    Figure  1.  Schematic of the electrochemical aptasensor for the detection of AFM1 based on RGO

    图  2  不同材料还原对RGO导电性的影响

    Figure  2.  Effects of different materials reduction on RGO conductivity

    注:(a,a')发酵枣汁中的多酚;(b,b')原枣汁中的多酚;(c,c')发酵枣汁;(d,d')原枣汁;A图表示使用CV法对不同材料还原的RGO导电性的测定;B图表示使用SWV法对不同材料还原的RGO导电性的测定。

    图  3  扫描电镜图与EDS元素分布图

    Figure  3.  Images of SEM and EDS

    注:GO(A);RGO(B);GO(C);RGO(D)。

    图  4  电化学适配体传感器在5 mmoL/L [Fe(CN)6]3−/4−溶液中的CV和SWV表征图

    Figure  4.  CV and SWV characterization of electrochemical aptasensor in 5 mmoL/L [Fe(CN)6]3-/4- solution

    注:(a,a'):裸GCE;(b,b'):还原氧化石墨烯修饰后的电极;(c,c'):纳米金修饰后电极;d,d':适配体修饰后的电极;e:AFM1孵育后的电极;A表示CV表征图谱;B表示SWV表征图谱。

    图  5  不同条件下制备的RGO的导电能力

    Figure  5.  The conductivity of RGO prepared under different conditions

    注:(A)GO和红枣汁的比例;(B)不同的pH(比例是2:1)。

    图  6  不同浓度的AFM1所对应的DPV响应曲线图

    Figure  6.  Differential pulse voltammograms corresponding to different concentrations of AFM1

    注:a~g分别代表0,1×10−7,1×10−6,1×10−5,1×10−4, 5×10−4,1×10−3 ng/mL的AFM1

    图  7  DPV峰电流值与不同浓度的AFM1的校准曲线

    Figure  7.  Calibration curves of DPV peak current and AFM1 with different concentrations

    图  8  电化学适配体传感器对不同干扰物的特异性评估

    Figure  8.  Evaluation of the specificity of the aptasensor toward different interferences

    注:所有毒素的浓度均为1×10−5 ng/mL。

    表  1  本研究与报道的检测AFB1的方法的比较

    Table  1.   Comparison of reported methods for the detection of AFB1

    黄曲霉毒素检测方法检测范围(ng/mL)检测限(ng/mL)参考文献
    AFB1高效液相色谱法0.1~200.08[32]
    电化学适配体传感器1×10−8~1×10−62×10−9[33]
    电化学适配体传感器5~2000.035[34]
    电化学适配体传感器0.05~200.016[35]
    表面增强拉曼适配体传感器0.0001~1004×10-4[36]
    AFM1高效液相色谱法0.05~50.02[37]
    电化学适配体传感器0.002~0.69×10-4[22]
    电化学适配体传感器0.002~0.151.15×10−3[38]
    电化学适配体传感器0.006~0.061.98×10−3[5]
    荧光适配体传感器0.0001~0.50.0194×10−3[39]
    电化学适配体传感器1×10−7~5×10−43.3×10−8本工作
    下载: 导出CSV

    表  2  羊乳样品中AFM1的检测回收率(n=3)

    Table  2.   Recovery of AFM1 detection in goat milk (n=3)

    样品添加量AFM1
    (ng/mL)
    测得量
    (ng/mL)
    回收率
    (%)
    相对标准偏差
    (%)
    11×10−41.03×10−4103.06.82
    21×10−58.58×10−685.87.87
    31×10−69.36×10−793.65.05
    下载: 导出CSV
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  • 收稿日期:  2020-09-15
  • 网络出版日期:  2021-06-03
  • 刊出日期:  2021-07-07

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