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Fabrication of a Label-Free Electrochemical Immunosensor for Direct Detection of Candidatus Phytoplasma Aurantifolia Publisher



Ebrahimi M1 ; Norouzi P1, 2 ; Safarnejad MR3 ; Tabaei O1 ; Hajihashemi H1
Authors
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Authors Affiliations
  1. 1. Center of Excellence in Electrochemistry, University of Tehran, Tehran, Iran
  2. 2. Endocrinology & Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Iranian Research Institute of Plant Protection, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran

Source: Journal of Electroanalytical Chemistry Published:2019


Abstract

A novel label-free electrochemical immunosensor was fabricated for selective and sensitive detection of Candidatus Phytoplasma Aurantifolia (CPA), the main factor of witches broom diseases, in tree sap samples. CPA antibody was immobilized on a thiol terminated surface of a gold electrode modified by gold nanoparticles; the surface was then activated by mixture of N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC) and N-HydroxySuccinamide (NHS). Scanning electron microscopy (SEM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were employed for surface characterization. All the electrochemical measurements of CPA were accomplished based on the [Fe(CN)6]3−/4− solution response as the standard redox probe. CPA detection was carried out using square wave voltammetry (SWV) technique, at frequency of 20 Hz and amplitude of 0.1 V. In order to reach the maximum efficiency in performance of the immunosensor, Anti-CPA 1 mg mL− 1, pH 7.4 and the incubation time of 45 min were selected as optimized experimental conditions. According to the calibration curve data, the obtained linear range was 0.005 to 100 μg mL− 1, with limit of detection (LOD) of 1.5 ng mL− 1, which was lower than the value reported for ELISA method applied for CPA detection. The immunosensor demonstrated adequate selectivity and stability besides; there was no significant interference observed from other probable protein based components in the real sample matrix. © 2019 Elsevier B.V.