Huang Aihua, Qiu Zhigang, Jin Min, Shen Zhiqiang, Chen Zhaoli, Wang Xinwei, Li Jun-Wen
Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Institute of Health and Environmental Medicine, Tianjin, 300050, P. R. China; Logistics College of Chinese People's Armed Police Forces, Tianjin, 300162, P. R. China.
Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Institute of Health and Environmental Medicine, Tianjin, 300050, P. R. China.
Int J Food Microbiol. 2014 Aug 18;185:27-32. doi: 10.1016/j.ijfoodmicro.2014.05.012. Epub 2014 May 21.
Bacterial pathogens are mostly responsible for food-borne diseases, and there is still substantial room for improvement in the effective detection of these organisms. In the present study, we explored a new method to detect target pathogens easily and rapidly with high sensitivity and specificity. This method uses an oligonucleotide microarray combined with quantum dots as fluorescent labels. Oligonucleotide probes targeting the 16SrRNA gene were synthesized to create an oligonucleotide microarray. The PCR products labeled with biotin were subsequently hybridized using an oligonucleotide microarray. Following incubation with CdSe/ZnS quantum dots coated with streptavidin, fluorescent signals were detected with a PerkinElmer Gx Microarray Scanner. The results clearly showed specific hybridization profiles corresponding to the bacterial species assessed. Two hundred and sixteen strains of food-borne bacterial pathogens, including standard strains and isolated strains from food samples, were used to test the specificity, stability, and sensitivity of the microarray system. We found that the oligonucleotide microarray combined with quantum dots used as fluorescent labels can successfully discriminate the bacterial organisms at the genera or species level, with high specificity and stability as well as a sensitivity of 10 colony forming units (CFU)/mL of pure culture. We further tested 105 mock-contaminated food samples and achieved consistent results as those obtained from traditional biochemical methods. Together, these results indicate that the quantum dot-based oligonucleotide microarray has the potential to be a powerful tool in the detection and identification of pathogenic bacteria in foods.
食源疾病大多由细菌病原体引起，而对这些病原体的有效检测仍有很大的改进空间。在本研究中，我们探索了一种新方法，能够轻松、快速地检测目标病原体，且具有高灵敏度和特异性。该方法使用寡核苷酸微阵列结合量子点作为荧光标记。合成了靶向16SrRNA基因的寡核苷酸探针以构建寡核苷酸微阵列。随后，将用生物素标记的PCR产物与寡核苷酸微阵列进行杂交。在用链霉亲和素包被的CdSe/ZnS量子点孵育后，使用珀金埃尔默Gx微阵列扫描仪检测荧光信号。结果清楚地显示了与所评估细菌种类相对应的特异性杂交图谱。使用216株食源细菌病原体（包括标准菌株和从食品样本中分离的菌株）来测试微阵列系统的特异性、稳定性和灵敏度。我们发现，结合量子点作为荧光标记的寡核苷酸微阵列能够成功区分属或种水平的细菌生物体，具有高特异性和稳定性，灵敏度为每毫升纯培养物10个菌落形成单位（CFU）。我们进一步测试了105个模拟污染的食品样本，结果与传统生化方法一致。总之，这些结果表明基于量子点的寡核苷酸微阵列有潜力成为食品中病原菌检测和鉴定的有力工具。
