• 文献标题:   Epitope-imprinted polydopamine and reduced graphene oxide-based sensing interface for label-free detection of gliadin
  • 文献类型:   Article
  • 作  者:   CORPUZ A, KHUMSAP T, BAMRUNGSAP S, THU VT, NGUYEN LT
  • 作者关键词:   epitope imprinting, polydopamine, screen printed carbon electrode, gliadin, gluten, reduce graphene oxide
  • 出版物名称:   JOURNAL OF FOOD COMPOSITION ANALYSIS
  • ISSN:   0889-1575 EI 1096-0481
  • 通讯作者地址:  
  • 被引频次:   0
  • DOI:   10.1016/j.jfca.2022.105090 EA DEC 2022
  • 出版年:   2023

▎ 摘  要

Detection of gluten and its components in foods is paramount in ensuring safety of gluten-sensitive individuals. However, the conventional immunodetection methods including gold standard enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction, and advanced proteomic methods suffer from high cost, complicated instrumentation and protocol, and slow assay turnaround time. Herein, we developed an inexpensive electrochemical sensor for gliadin (GLI) detection using electrochemically reduced graphene oxide for sensitivity enhancement and PQQPFPQQ epitope-imprinted polydopamine as selective recognition interface. The sensing performance was improved by optimizing key process factors including template/monomer ratio, prepolymerization period, electropolymerization and electrochemical reduction cycles, elution time, and rebinding pH and time. The sensor shows a linear relationship between current response and GLI concentration in the 1-15 ppm range with high affinity to the epitope template (imprinting factor IF = 8.68) and target GLI (IF = 3.14), low limits of detection (0. 70 ppm) and quantification (2.33 ppm). The sensor also exhibits excellent selectivity against potential interferents including ovalbumin (selectivity factor SF = 0.15), folic acid (SF = 0.25), and casein (SF = 0.39) in buffered matrix. The obtained sensor-to-sensor reproducibility, repeatability, and stability ensure its sensitive determination of native GLI in rice flour matrix with coefficient of variance in the range of 2.52-4.27 %, and recovery rates of 99.1-101.9 %. The results fare better than those analyzed by traditional ELISA and similar methods. The developed sensor could be used as a reliable platform for rapid detection of allergic gluten components in processed food products.