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双辅助异源抗原筛选:提高侧向流动免疫分析灵敏度的有效策略。

Dual-assist heterologous antigens screening: An effective strategy to improve the sensitivity of lateral flow immunoassay.

机构信息

State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, China.

Jiangxi Provincial Center for Disease Control and Prevention, Nanchang, 330029, China.

出版信息

Food Chem. 2025 Jan 15;463(Pt 2):141131. doi: 10.1016/j.foodchem.2024.141131. Epub 2024 Sep 4.

DOI:10.1016/j.foodchem.2024.141131
PMID:39276540
Abstract

Heterologous strategy has promising applications in improving the sensitivity of competitive immunoassay. In this study, the potential heterologous coating antigens (HEA) were screened from eight imidacloprid (IMI) structural analogs based on the cross-reactivity (CR) of a prepared antibody. Computer-aided molecular modeling was used to predict the optimal HEA. Compared with the homologous coating antigen (HOA), the predicted HEA prepared from acetamiprid (CR = 0.23 %) increased the detection sensitivity of the enzyme-linked immunoassay and colloidal gold nanoparticle-based lateral flow immunoassay (HOA-Au-LFIA) by 5.6 and 4.1 times, respectively. Subsequently, the HEA and aggregation-induced emission fluorescent labels were integrated into a lateral flow immunoassay platform (HEA-AIE-LFIA). The limit of detection was 0.12 ng mL for HEA-AIE-LFIA, which was 7.7-fold lower than that of HOA-Au-LFIA. Furthermore, HEA-AIE-LFIA was applied to detect IMI in food samples with excellent recoveries (86.41 %-111.25 %). Overall, this strategy of screening for superior HEA has great potential for improving LFIA sensitivity.

摘要

异源策略在提高竞争免疫分析的灵敏度方面具有广阔的应用前景。本研究基于制备抗体的交叉反应性(CR),从八种吡虫啉(IMI)结构类似物中筛选潜在的异源包被抗原(HEA)。采用计算机辅助分子建模预测最佳的 HEA。与同源包被抗原(HOA)相比,由噻虫嗪(CR = 0.23%)制备的预测 HEA 分别将酶联免疫吸附测定和胶体金纳米颗粒侧向流动免疫测定(HOA-Au-LFIA)的检测灵敏度提高了 5.6 倍和 4.1 倍。随后,将 HEA 和聚集诱导发射荧光标记物集成到侧向流动免疫测定平台(HEA-AIE-LFIA)中。HEA-AIE-LFIA 的检测限为 0.12ng mL,比 HOA-Au-LFIA 低 7.7 倍。此外,HEA-AIE-LFIA 还应用于检测食品样品中的 IMI,回收率优异(86.41%-111.25%)。总体而言,这种筛选优异 HEA 的策略对于提高 LFIA 的灵敏度具有巨大的潜力。

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