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Visual dual dot immunoassay for the simultaneous detection of kanamycin and streptomycin in milk

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Abstract

Aminoglycoside (AG) antibiotics such as kanamycin (KAN) and streptomycin (STR) are widely used against bacterial infections in animals. Our aim was to develop a multiplex paper-based visual method to monitor the residues of KAN and STR in milk with the features of cost-effectiveness and visual readout. In this study, monoclonal antibodies (mAbs) against STR were developed and used. The most sensitive mAb, named 6H3D5, displayed enhanced cross-reactivity to dihydrostreptomycin (101.62%) and no cross-reactivity to other related antibiotics. Additionally, a new dual dot enzyme-linked immunosorbent assay (ELISA) was established for the simultaneous detection of KAN and STR in milk. All the experiments were performed in triplicate. The limit of detection (LOD) with the naked eye was 2.7 ng mL−1 for KAN and 12.5 ng mL−1 for STR. The quantitative detection ranges of KAN and STR were 0.38–38.66 and 2.47–31.90 ng mL−1, with LODs at 0.09 and 1.37 ng mL−1, respectively. Good correlations between the dual dot-ELISA and UPLC-MS/MS were observed for the detection of KAN (R = 0.911) and STR (R = 0.902). For quantitative analysis, the recovery rates for KAN and STR were 84.2–119.8% and 93.3–124.5% respectively. In commercial milk samples, KAN was found to be present up to a concentration of 1.47 ng mL−1, whereas STR was below the LOD. This dual dot-ELISA provides a new model for multi-compound analysis in a single assay enabling effective monitoring of food quality.

Graphical abstract: Visual dual dot immunoassay for the simultaneous detection of kanamycin and streptomycin in milk

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Publication details

The article was received on 13 Sep 2018, accepted on 25 Nov 2018 and first published on 26 Nov 2018


Article type: Paper
DOI: 10.1039/C8AY02006J
Citation: Anal. Methods, 2019, Advance Article
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    Visual dual dot immunoassay for the simultaneous detection of kanamycin and streptomycin in milk

    D. Wei, H. Meng, K. Zeng and Z. Huang, Anal. Methods, 2019, Advance Article , DOI: 10.1039/C8AY02006J

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