The rGO@AuNPs modified label-free electrochemical immunosensor to sensitive detection of CP-BNYVV protein of Rhizomania disease agent in sugar beet.

Abstract

For the first time, a novel simple label-free electrochemical immunosensor was fabricated for sensitive detection of the coat protein of beet necrotic yellow vein virus (CP-BNYVV) as the causal agent of Rhizomania disease in sugar beet. To boost the amplification of the electrochemical signal, gold nanoparticles-reduced graphene oxide (AuNPs-rGO) nanocomposite was employed to modify the glassy carbon electrode. Anti-BNYVV polyclonal was immobilized onto a modified electrode by applying a thiol linker via a self-assembly monolayer (SAM) and activating the functionalized surface using (3-aminopropyl triethoxysilane) and glutaraldehyde. The determination step relied on the forming of an immunocomplex between the antigen and oriented antibody, resulting in a decrease in current in the [Fe (CN)₆]^3-/4- redox reaction. The response value exhibited direct proportionality to the concentrations of CP-BNYVV. Scanning electron microscopy, energy dispersive x-ray, cyclic voltammetry, and electrochemical impedance spectroscopy techniques collectively provided a comprehensive understanding of the structural, morphological, and electrochemical features during the modification steps. Under optimized experimental conditions, the fast Fourier transform square wave voltammetry responds to the logarithm of CP-BNYVV concentrations in a wide linear range from 0.5 to 50000 pg/mL and the limit of detection is calculated to be 150 fg/mL, implying the admirable sensitivity. Selectivity assay exhibited no cross-reactivity with other proteins from interfering virus samples. Satisfactory reproducibility and stability were achieved with a relative standard deviation of 3.1% and a stable value of 90% after 25 days, respectively. More importantly, the high performance of the immunosensor resulted in the direct detection of CP-BNYVV in spiked and infected plant samples, which affords a sensing platform with huge potential application for the early detection of BNYVV virus in field conditions.