Garrido-Maestu Alejandro, Azinheiro Sarah, Carvalho Joana, Espiña Begoña, Prado Marta
Department of Life Sciences, Nano4Food - Food Quality and Safety Research Group, International Iberian Nanotechnology Laboratory, Av. Mestre José Veiga s/n, 4715-330 Braga, Portugal.
J Food Sci Technol. 2020 Nov;57(11):4143-4151. doi: 10.1007/s13197-020-04450-1. Epub 2020 Apr 24.
continues to be a major health issue in Europe, as well as worldwide. Faster methods, not only for detection, but also for sample preparation are of great interest particularly for this slow-growing pathogen. Immunomagnetic separation has been previously reported to be an effective way to concentrate bacteria, and remove inhibitors. In the present study, different commercial antibodies were evaluated to select the most appropriate one, in order to develop a highly specific method. Additionally, magnetic nanoparticles, instead of microparticles, were selected due to their reported advantages (higher surface-volume ration and faster kinetics). Finally, the separation protocol, with a calculated capture efficiency of 95%, was combined with real-time PCR for highly sensitive detection of the concentrated bacteria. The optimized IMS-qPCR allowed to reduce hands-on time in the sample treatment, without affecting the overall performance of the method as a very low limit of detection was still obtained (9.7 CFU/ 25 g) with values for sensitivity, specificity, accuracy, positive and negative predictive values of 100%, resulting in a kappa index of concordance of 1.00. These results were obtained in spiked food samples of different types (chicken, fish, milk, hard and fresh cheese), further demonstrating the applicability of the optimized methodology presented.
在欧洲以及全球范围内,它仍然是一个主要的健康问题。对于这种生长缓慢的病原体,不仅检测速度更快的方法,而且样品制备速度更快的方法都备受关注。免疫磁分离此前已被报道是一种浓缩细菌并去除抑制剂的有效方法。在本研究中,对不同的商业抗体进行了评估,以选择最合适的抗体,从而开发出一种高度特异性的方法。此外,由于磁性纳米颗粒具有所报道的优势(更高的表面体积比和更快的动力学),所以选择了磁性纳米颗粒而非微粒。最后,将计算捕获效率为95%的分离方案与实时PCR相结合,用于对浓缩细菌进行高灵敏度检测。优化后的免疫磁分离-实时荧光定量PCR方法减少了样品处理的实际操作时间,同时由于仍能获得非常低的检测限(9.7 CFU/25 g)且灵敏度、特异性、准确性、阳性和阴性预测值均为100%,kappa一致性指数为1.00,因此并未影响该方法的整体性能。这些结果是在不同类型的加标食品样品(鸡肉、鱼肉、牛奶、硬质和新鲜奶酪)中获得的,进一步证明了所提出的优化方法的适用性。