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Design and Development of Aptamer–Gold Nanoparticle Based Colorimetric Assays for In-the-field Applications
Published on: June 23, 2016
A simple, highly sensitive colorimetric immunosensor for the detection of alternariol monomethyl ether in fruit by
Yan Man1,2,3, Junan Ren1,2,3, Bingru Li1,2,3
1Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Abstract:
Alternariol monomethyl ether (AME) is one of the major Alternaria mycotoxins present in a wide range of fruits, vegetables, grains, and their products, and possesses the properties of mutagenicity and carcinogenicity. In this study, a simple, rapid, and highly sensitive colorimetric immunosensor based on magnetic nanoparticles (MNPs) was firstly developed for the detection of AME in fruit by nonaggregated gold nanoparticles (GNPs). AME-BSA-Fe3O4 MNP conjugates and free AME molecules in samples competitively bind with monoclonal antibody (mAb)-GNP conjugates. After magnetic separation, the UV absorbance of the nonaggregated GNP supernatant was measured directly. The absorption intensity was proportional to the concentration of AME in the sample. Carboxyl-group-modified AME, AME-bovine serum albumin (BSA) conjugates, anti-AME mAbs, AME-BSA-Fe3O4 MNP conjugates, and mAb-GNP conjugates were prepared and characterized. The effect of GNP sizes (16, 24, and 40 nm) on the colorimetric determination of AME was studied. Under optimized conditions, the limit of detection and the linear range for AME were 0.16 ng/mL and 0.08-0.48 ng/mL, respectively. Moreover, the colorimetric immunosensor developed has lower cross-reactivity with AME analogues. The recoveries of spiked fruits ranged from 80.6% to 90.7%. The colorimetric immunosensor developed provides a promising method for simple, rapid, highly sensitive, and highly specific detection of other mycotoxins in the field of food safety. Graphical abstract Competitive colorimetric immunosensor based on MNPs for the detection of AME by non-aggregated GNPs.
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