journal article·2024-09-27

Bimetallic Nanozyme-Assisted Immunoassay for the Detection of Acetamiprid in Vegetables

Beibei Liu, Rongqi Zhai, A. M. Abd El-Aty, Jie Zhang, Guangyang Liu, Xiaodong Huang, Jun Lv, Jing Chen, Junjiang Liu, Maojun Jin, Jing Wang, Donghui Xu, Ge Chen

ACS Applied Nano Materials· Volume 7· Issue 18
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Abstract

The ability of conventional enzyme-linked immunosorbent assays to satisfy the increasing demand for advanced immunoassays is limited by their reliance on natural enzymes, low sensitivity, and narrow detection range. The development of nanozyme-assisted immunoassays is a viable approach to overcoming these constraints. Here, we report a one-step bimetallic nanozyme-assisted indirect competitive immunoassay to detect the pesticide acetamiprid in vegetables. Litchi-like bimetallic gold and platinum (Au@Pt) nanozymes with high catalytic properties and excellent biocompatibility were synthesized for this assay. The Au@Pt nanozymes were simple and inexpensive to prepare, exhibited stability and adjustable catalytic activity, and were directly conjugated with antibodies as signal probes, without the use of horseradish peroxidase-conjugated Affinipure goat antimouse IgG (IgG-HRP). Acetamiprid was shown to compete with the antigen to bind the Au@Pt probes. Subsequently, Au@Pt probes, which exhibited peroxidase-like activity, were used to catalyze the oxidation of colorless 3,3′,5,5′-tetramethylbenzidine, demonstrating the easy detection of acetamiprid through colorimetric signal monitoring. The linear range, sensitivity, relative standard deviation range, and limit of detection of the immunoassay were 1.85–327.19 μg/L, 25.58 μg/L, 0.46–10.35%, and 0.78 μg/L, respectively, satisfying the detection requirements. In conclusion, the method exhibited high sensitivity, reproducibility, and a wide linear range for the detection of acetamiprid, while eliminating the need for IgG and simplifying the experimental procedure. This new indirect competitive immunoassay has great potential value for on-site sensitive detection of acetamiprid in vegetables.
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Research context

OpenAlex topics: Advanced Nanomaterials in Catalysis · Biosensors and Analytical Detection · Advanced biosensing and bioanalysis techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, State Key Laboratory of Vegetable Biobreeding, Key Laboratory of Vegetables Quality and Safety Control, Ministry of Agriculture and Rural Affairs of China, Ministry of Agriculture Vegetable Product Quality Safety Risk Assessment Laboratory, Beijing 100081, P. R. China

College of Plant Science and Technology, Beijing University of Agriculture, Beijing 102206, P. R. China

Department of Pharmacology, Faculty of Veterinary Medicine, Cairo University, 12211 Giza, Egypt

Department of Medical Pharmacology, Faculty of Medicine, Atatürk University, Erzurum 25240, Turkey

Institute of Quality Standard and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Product Quality and Safety, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, P. R. China

Funding

China Agricultural Research System · National Key Research and Development Program of China · National Natural Science Foundation of China · Central Public-interest Scientific Institution Basal Research Fund

References (33)

Show source-provided references
1. 10.1021/acsnano.1c0526710.1021/acsnano.1c05267 ↗
2. 10.1016/j.foodchem.2023.13594910.1016/j.foodchem.2023.135949 ↗
3. 10.1021/acs.analchem.2c0360610.1021/acs.analchem.2c03606 ↗
4. 10.1002/jmv.2602410.1002/jmv.26024 ↗
5. 10.3390/foods903030510.3390/foods9030305 ↗
6. 10.1002/fsn3.99110.1002/fsn3.991 ↗
7. 10.1021/acs.analchem.2c0561710.1021/acs.analchem.2c05617 ↗
8. 10.1002/smll.20231086910.1002/smll.202310869 ↗
9. 10.1016/j.snb.2024.13566510.1016/j.snb.2024.135665 ↗
10. 10.1016/j.bios.2022.11467610.1016/j.bios.2022.114676 ↗
11. 10.1021/acs.analchem.9b0521810.1021/acs.analchem.9b05218 ↗
12. 10.1021/acs.analchem.7b0094210.1021/acs.analchem.7b00942 ↗
13. 10.1021/acsnano.3c0768010.1021/acsnano.3c07680 ↗
14. 10.1186/s12951-018-0371-010.1186/s12951-018-0371-0 ↗
15. 10.1021/acsnano.5b0320310.1021/acsnano.5b03203 ↗
16. 10.1021/acsnano.5b0426110.1021/acsnano.5b04261 ↗
17. 10.1021/acsanm.1c0434810.1021/acsanm.1c04348 ↗
18. 10.1021/acs.analchem.3c0324910.1021/acs.analchem.3c03249 ↗
19. 10.1021/acs.analchem.4c0105910.1021/acs.analchem.4c01059 ↗
20. 10.1039/D0NR00831A10.1039/D0NR00831A ↗
21. 10.1016/j.foodchem.2023.13793310.1016/j.foodchem.2023.137933 ↗
22. 10.1016/j.jhazmat.2024.13511210.1016/j.jhazmat.2024.135112 ↗
23. 10.1021/acs.jafc.9b0612510.1021/acs.jafc.9b06125 ↗
24. 10.1016/j.biomaterials.2010.09.04010.1016/j.biomaterials.2010.09.040 ↗
25. 10.1016/j.bios.2023.11555310.1016/j.bios.2023.115553 ↗
26. 10.1039/D1AN02060A10.1039/D1AN02060A ↗
27. 10.1016/j.bios.2015.03.03910.1016/j.bios.2015.03.039 ↗
28. 10.1016/j.foodcont.2023.11001310.1016/j.foodcont.2023.110013 ↗
29. 10.1038/nnano.2007.26010.1038/nnano.2007.260 ↗
30. 10.3390/foods1201019610.3390/foods12010196 ↗
31. 10.1016/j.foodchem.2021.13011810.1016/j.foodchem.2021.130118 ↗
32. 10.1016/j.saa.2020.11925710.1016/j.saa.2020.119257 ↗
33. 10.1016/j.foodchem.2021.12915710.1016/j.foodchem.2021.129157 ↗