Issue 15, 2019

Indirect competitive ELISA and colloidal gold-based immunochromatographic strip for amantadine detection in animal-derived foods

Abstract

In this research, an indirect competitive enzyme-linked immunosorbent assay (ELISA) and colloidal gold-based immunochromatographic (GICG) strip were developed for the detection of the antiviral drug amantadine (AM) in animal-derived foods. Under the optimized conditions of coating antigen (AM-BSA) content of 0.01 μg per well, antibody concentration of 145.3 ng mL−1, 0.5% defatted milk powder solution as the blocking solution, and phosphate buffer solution (0.01 mol L−1, pH 7.4) as the diluent, the ELISA displayed a linear range of 1.0–80.0 μg L−1 for AM, with good sensitivity (IC50: 4.2 μg L−1) and detection limit (LOD: 1.0 μg L−1). The recoveries of AM in selected animal-derived samples ranged from 85.2% to 115.6%. Under the optimized conditions for the GICG with a whole antigen and second antibody dilution of 40- and 60-fold, respectively, pH of the probe coupling buffer of 8 and concentration of gold-labeled antibody of 5 μg mL−1, the visual LOD of the GICG was 10 μg L−1 and the detection was completed within 10 min with a relatively simple pretreatment of the food samples. The developed ELISA and GICG strip also showed high specificity with low cross-reactivity toward AM analogues and other drugs. These results indicate that the developed ELISA and GICG strip offer the accurate, sensitive, specific, and fast detection of AM in animal-derived food samples.

Graphical abstract: Indirect competitive ELISA and colloidal gold-based immunochromatographic strip for amantadine detection in animal-derived foods

Supplementary files

Article information

Article type
Paper
Submitted
25 Dec. 2018
Accepted
11 Marts 2019
First published
14 Marts 2019

Anal. Methods, 2019,11, 2027-2032

Indirect competitive ELISA and colloidal gold-based immunochromatographic strip for amantadine detection in animal-derived foods

M. Pan, J. Yang, S. Li, G. Wang, J. Wang and S. Wang, Anal. Methods, 2019, 11, 2027 DOI: 10.1039/C8AY02806K

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