Huang Tianxun, Zheng Yan, Yan Ya, Yang Lingling, Yao Yihui, Zheng Jiaxin, Wu Lina, Wang Xu, Chen Yuqing, Xing Jinchun, Yan Xiaomei
The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, The Key Laboratory for Chemical Biology of Fujian Province, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005, P.R. China.
Zhongshan Hospital, Xiamen University, Xiamen, Fujian 361005, P.R. China.
Biosens Bioelectron. 2016 Jun 15;80:323-330. doi: 10.1016/j.bios.2016.01.054. Epub 2016 Jan 22.
The evolution and spread of antibiotic-resistant pathogens has become a major threat to public health. Advanced tools are urgently needed to quickly diagnose antibiotic-resistant infections to initiate appropriate treatment. Here we report the development of a highly sensitive flow cytometric method to probe minority population of antibiotic-resistant bacteria via single cell detection. Monoclonal antibody against TEM-1 β-lactamase and Alexa Fluor 488-conjugated secondary antibody were used to selectively label resistant bacteria green, and nucleic acid dye SYTO 62 was used to stain all the bacteria red. A laboratory-built high sensitivity flow cytometer (HSFCM) was applied to simultaneously detect the side scatter and dual-color fluorescence signals of single bacteria. By using E. coli JM109/pUC19 and E. coli JM109 as the model systems for antibiotic-resistant and antibiotic-susceptible bacteria, respectively, as low as 0.1% of antibiotic-resistant bacteria were accurately quantified. By monitoring the dynamic population change of a bacterial culture with the administration of antibiotics, we confirmed that under the antimicrobial pressure, the original low population of antibiotic-resistant bacteria outcompeted susceptible strains and became the dominant population after 5hours of growth. Detection of antibiotic-resistant infection in clinical urine samples was achieved without cultivation, and the bacterial load of susceptible and resistant strains can be faithfully quantified. Overall, the HSFCM-based quantitative method provides a powerful tool for the fundamental studies of antibiotic resistance and holds the potential to provide rapid and precise guidance in clinical therapies.
抗生素耐药性病原体的演变和传播已成为对公众健康的重大威胁。迫切需要先进的工具来快速诊断抗生素耐药性感染，以便启动适当的治疗。在此，我们报告了一种高灵敏度流式细胞术方法的开发，该方法可通过单细胞检测来探测抗生素耐药细菌的少数群体。使用针对TEM-1β-内酰胺酶的单克隆抗体和Alexa Fluor 488偶联的二抗将耐药细菌选择性地标记为绿色，并用核酸染料SYTO 62将所有细菌染成红色。应用实验室构建的高灵敏度流式细胞仪（HSFCM）同时检测单个细菌的侧向散射和双色荧光信号。分别以大肠杆菌JM109/pUC19和大肠杆菌JM109作为抗生素耐药和抗生素敏感细菌的模型系统，可准确量化低至0.1%的抗生素耐药细菌。通过监测添加抗生素后细菌培养物中动态群体变化，我们证实，在抗菌压力下，原本数量较少的抗生素耐药细菌在生长5小时后超过了敏感菌株并成为优势群体。无需培养即可实现临床尿液样本中抗生素耐药感染的检测，并且可以如实地量化敏感和耐药菌株的细菌载量。总体而言，基于HSFCM的定量方法为抗生素耐药性的基础研究提供了强大工具，并有可能在临床治疗中提供快速而精确的指导。
