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Smartphone-based visualized microarray detection for multiplexed harmful substances in milk
Zhoumin Li1, Zhonghui Li2, Dingyi Zhao2
1State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210093, China; School of Chemistry and Biological Science, Nanjing University Jingling College, Nanjing 210089, China.
Abstract:
In this paper, we report a sensitive, simple and inexpensive analytical method for the immunoassay microarray based on a smartphone in which various harmful substances in milk could be assayed. Tetracyclines (TCs) and Quinolones (QNs) were selected as the model targets in this study. TCs and QNs antigens were immobilized in the microarray and then samples containing free of antibiotics and corresponding antibodies as well as AgNPs labeled secondary antibodies were added to the microarray. The signal of this competitive format was further amplified by silver enhancement technique based on the development reagents and achieved a visual dots in the array. The resulting microarray could be detected by the smartphone placed in the minicartridge. The limit of detection (LOD) of this novel detection platform was 1.51ngmL-1 (TCs) and 1.74ngmL-1 (QNs). To achieve one-well quantitative analysis, a series of gradient concentration mouse IgG was immobilized in the same well. As a result, an internal standard curve was plotted by the signal of different concentrations of mouse IgG. The results showed that a quantitative detection of TCs and QNs established were consistent with external standard curve. Compared to other methods, this method was superior in terms of detection limit, time saving, and one-well quantitative detected with smartphone which were simple sample-preparation.

