Zheng Da-Wei, Liu Xiao-Ying, Zhang Ping, Su Lan, Wang Li-Min, Wei Xiao-Dan, Wang Hui-Qin, Lin Tai-Feng
J Nanosci Nanotechnol. 2018 Oct 1;18(10):6776-6785. doi: 10.1166/jnn.2018.15510.
Rapid detection of food-borne pathogens is the most critical and urgent issue among all the current food safety problems. As enhanced substrate, nanoparticles are widely used in surface enhanced Raman scattering (SERS) because of unique optical and physicochemical properties. In this study, Au nanoparticles with monodisperse and good reproducibility were synthesized by using sodium citrate reduction method. Applying Au nanoparticles sol as enhanced substrate, a portable Raman spectrometer had been applied for rapid detection of single and mixture pathogenic bacterial contamination by SERS. The results indicated that Escherichia coli, Salmonella typhimirium, Shigella flexner and Staphylococcus aureus showed specific Raman phenotypes at 600∼1700 cm-1. Generally, different bacteria could be easily and instantly recognized by its Raman phenotypes. The PC-LDA classification model was set up by combined bacterial Raman phenotypes with the multivariate statistical analysis. With the short-time inoculation, four enteropathogenic bacteria could be rapidly, precisely, sensitively and specifically identified. Furthermore, the model also had a good ability to predict the mixed contamination. This research provides the possibility of rapid detection in the food and biomedical fields.
在当前所有食品安全问题中，食源性病原体的快速检测是最为关键和紧迫的问题。作为增强基底，纳米粒子因其独特的光学和物理化学性质而被广泛应用于表面增强拉曼散射（SERS）。在本研究中，采用柠檬酸钠还原法合成了具有单分散性且重现性良好的金纳米粒子。将金纳米粒子溶胶作为增强基底，应用便携式拉曼光谱仪通过SERS对单一和混合病原菌污染进行快速检测。结果表明，大肠杆菌、鼠伤寒沙门氏菌、福氏志贺氏菌和金黄色葡萄球菌在600∼1700 cm-1处呈现出特定的拉曼表型。一般来说，不同细菌可通过其拉曼表型轻松、即时地识别出来。通过将细菌拉曼表型与多元统计分析相结合，建立了PC-LDA分类模型。通过短时间接种，可快速、准确、灵敏且特异地鉴定出四种肠道病原菌。此外，该模型对混合污染也具有良好的预测能力。本研究为食品和生物医学领域的快速检测提供了可能性。
