期刊
ANALYTICAL CHEMISTRY
卷 86, 期 6, 页码 3100-3107出版社
AMER CHEMICAL SOC
DOI: 10.1021/ac404205c
关键词
-
资金
- NSFC [21375049]
- S&T Supporting Project of Jiangsu Province [BE2011621]
- National Science and Technology Support Program of China [2012BAK08B01]
- Research Fund for the Doctoral Program of Higher Education [20110093110002]
- [NCET-11-0663]
- [JUSR-P51309A]
A highly sensitive and specific multiplex method for the simultaneous detection of three pathogenic bacteria was fabricated using multicolor upconversion nanoparticles (UCNPs) as luminescence labels coupled with aptamers as the molecular recognition elements. Multicolor UCNPs were synthesized via doping with various rare-earth ions to obtain well-separated emission peaks. The aptamer sequences were selected using the systematic evolution of ligands by exponential enrichment (SELEX) strategy for Staphylococcus aureus, Vibrio parahemolyticus, and Salmonella typhimurium. When applied in this method, aptamers can be used for the specific recognition of the bacteria from complex mixtures, including those found in real food matrixes. Aptamers and multicolor UCNPs were employed to selectively capture and simultaneously quantify the three target bacteria on the basis of the independent peaks. Under optimal conditions, the correlation between the concentration of three bacteria and the luminescence signal was found to be linear from 50-10(6) cfu mL(-1). Improved by the magnetic separation and concentration effect of Fe3O4 magnetic nanoparticles, the limits of detection of the developed method were found to be 25, 10, and 15 cfu mL(-1) for S. aureus, V. parahemolyticus, and S. typhimurium, respectively. The capability of the bioassay in real food samples was also investigated, and the results were consistent with experimental results obtained from plate-counting methods. This proposed method for the detection of various pathogenic bacteria based on multicolor UCNPs has great potential in the application of food safety and multiplex nanosensors.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据