Bindley Bioscience and Birck Nanotechnology Center, Department of Agricultural & Biological Engineering, Purdue University, West Lafayette, IN 47907, United States; Department of Biomedical Laboratory Science, College of Health Science, Eulji University, Seongnam 461-713, Republic of Korea.
Department of Food Science, Purdue University, West Lafayette, IN 47907, United States.
Int J Food Microbiol. 2015 Aug 3;206:60-6. doi: 10.1016/j.ijfoodmicro.2015.04.032. Epub 2015 Apr 25.
To date most LF-ICA format for pathogen detection is based on generating color signals from gold nanoparticle (AuNP) tracers that are perceivable by naked eye but often these methods exhibit sensitivity lower than those associated with the conventional enzyme-based immunological methods or mandated by the regulatory guidelines. By developing AuNP avidin-biotin constructs in which a number of enzymes can be labeled we report on an enhanced LF-ICA system to detect pathogens at very low levels. With this approach we show that as low as 100 CFU/mL of Escherichia coli O157:H7 can be detected, indicating that the limit of detection can be increased by about 1000-fold due to our signal amplification approach. In addition, extensive cross-reactivity experiments were conducted (19 different organisms were used) to test and successfully validate the specificity of the assay. Semi-quantitative analysis can be performed using signal intensities which were correlated with the target pathogen concentrations for calibration by image processing.
迄今为止,大多数用于病原体检测的 LF-ICA 格式都是基于生成可通过肉眼感知的金纳米粒子 (AuNP) 示踪剂的颜色信号,但这些方法通常灵敏度低于传统的基于酶的免疫学方法或法规指南所要求的灵敏度。通过开发可标记多种酶的 AuNP 亲和素-生物素构建体,我们报告了一种增强的 LF-ICA 系统,可在非常低的水平下检测病原体。通过这种方法,我们表明可以检测到低至 100 CFU/mL 的大肠杆菌 O157:H7,这表明由于我们的信号放大方法,检测限可以提高约 1000 倍。此外,还进行了广泛的交叉反应性实验(使用了 19 种不同的生物体)来测试并成功验证了该测定的特异性。可以使用与目标病原体浓度相关的信号强度进行半定量分析,通过图像处理进行校准。