基于单分子技术的水中抗生素检测新方法

Real-time quantitative monitoring of antibiotics in water environment is of great importance to avoid their large-scale diffusion in the environment. Fluorescence scattering cross-correlation spectroscopy (FSCCS) can detect the dynamic information of the fluorescent probe and the noble metal probe, and the interaction between two probes by analyzing their fluctuation signals in the solution. This project focuses on developing a novel assay method for detection of antibiotics in water using FSCCS. This assay method aims to simplify the operation steps and improve the detection accuracy. To further enhance the sensitivity and selectivity of this method, fluorescence-labeled aptamers and nucleic acid labeled gold magnetic nanoparticles are chosen as optical probes, and aptamer-antibiotic reaction is chosen as assay model. Because it combines the unique identifications of aptamers, magnetic separability of magnetic nanomaterials and fluorescence enhancement effect of gold nanoparticles on fluorescent molecules, this detection method can be done without sample pretreatment, and rapid detection, high sensitivity and universal applicability are also advantages of this approach. These researches will broaden the detection of antibiotics in water, and have important theoretical research value and good practical application prospects.

实时定量检测水环境中抗生素对避免其在环境中大规模的扩散具有重要意义。荧光散射互相关光谱（FSCCS）是一种可以同时检测溶液中荧光探针和贵金属探针动力学信息，及两者相互作用的单分子检测技术。本项目将结合FSCCS技术，以简化检测步骤及提高检测准确性为目标，构建一种具有高灵敏度的检测水中抗生素新方法。为进一步提升本方法的灵敏度和选择性，该检测模型采用荧光标记适配体和核酸标记金磁纳米粒子作为光学探针，核酸适配体-抗生素相互作用为反应模型。该方法结合核酸适配体的选择性、磁性纳米材料的可磁分离性、金纳米粒子对荧光分子的荧光增强效应，具有无需样品预处理、快速检测、灵敏度高且具有普适性等优点。本项目将丰富水中抗生素的检测方法，具有重要的理论研究价值和良好的实际应用前景。

实时定量检测水环境中抗生素对避免其在环境中大规模的扩散具有重要意义。本项目从合成金磁纳米粒子（GMNPs）入手，采用点击试剂法获得具有优异生物相容性、水中稳定性、可磁分离性和可循环使用的纳米复合材料。结合分裂适配体（SPA）技术，以GMNPs和荧光分子标记的核酸适配体作为探针，恩诺沙星（ENR）和链霉素（STR）作为目标抗生素，核酸适配体-抗生素相互作用为反应模型，成功开发了一种操作简便、灵敏度高的水中多组分抗生素的检测方法。另外，借助TMB-H2O2类酶催化体系，基于抗生素、金属离子和金纳米簇三者之间的相互作用，结合线性判别分析（LDA）方法，以庆大霉素（GM）、土霉素（OTC）等6种抗生素为检测模型，发展了一种水中多组分抗生素检测新方法。本项目的研究丰富了水中抗生素的检测方法，具有良好的实际应用前景。基于本项目的研究，共发表SCI论文7篇（2篇SCI一区），申请国家发明专利2项，培养硕士研究生3名。