Abstract
An accurate and sensitive competitive enzyme-linked immunosorbent assay (ELISA) based on persistent luminescence nanoparticles Zn2GeO4:Mn2+, Eu3+ (ZGME) was developed for detecting ochratoxin A (OTA), a powerfully toxic mycotoxin usually found in grains. As a signal output element of autofluorescence-free biosensors, ZGME can be integrated into ELISA with glucose oxidase (GOx)-binding OTA molecules due to its excellent pH-responsive persistent luminescence. In the absence of OTA, the OTA-GOx conjugate was captured by the anti-OTA monoclonal antibody (anti-OTA mAb) pre-coated on the 96-well plate. The results indicate a decrease in the pH value of the solution, which triggered the quenching of ZGME luminescence due to GOx-dependent gluconic acid production. The presence of OTA inhibited the binding of OTA-GOx on the plate, thus decreasing the production of gluconic acid and increasing the persistent luminous intensity of ZGME. Under the optimized concentrations of anti-OTA mAb and OTA-GOx, quantitative determination of OTA was achieved by plotting the increase or decrease in persistent luminescence intensity of ZGME at 535 nm. In this study, the linear range was from 0.1 μg L−1 to 63 μg L−1, and the limit of detection (LOD) was as low as 0.045 μg L−1. In five food samples (corn grit, brown rice, soybean, rice, and wheat), the results exhibited good stability and repeatability, with a recovery range from 81.3% to 94.4% and a relative standard deviation (RSD) of less than 4.2%. Hence, the established method provides a sensitive, accurate, and autofluorescence-free approach for the determination of OTA in different grain samples.
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Acknowledgements
We are thankful for the financial support from the National Natural Science Foundation of China (No. 21966024 and 21768003), the Natural Science Foundation of Ningxia (No. 2022AAC03045), and the Key research and development projects in Xingtai, Hebei, Special project in the field of social development (No. 2022zz049).
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Yinghui Wang: Conceptualization, Methodology, Investigation, Data curation, Writing—original draft. Ling Yu: Software, Data curation, Formal analysis. Hui Zhang: Formal analysis. Runzhi Zhu: Formal analysis. Zhe Meng: Writing—review & editing.
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Wang, Y., Yu, L., Zhang, H. et al. Competitive ELISA based on pH-responsive persistent luminescence nanoparticles for autofluorescence-free biosensor determination of ochratoxin A in cereals. Anal Bioanal Chem 415, 1877–1887 (2023). https://doi.org/10.1007/s00216-023-04591-0
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DOI: https://doi.org/10.1007/s00216-023-04591-0