间接免疫荧光试验在检测风疹病毒感染中的应用

目的建立检测风疹病毒(RV)抗原E1、E2、C的间接免疫荧光试验(IFA),为快速、敏感地检测临床标本中的RV提供一种重要的检测手段。方法采用荧光素标记的羊抗鼠IgG抗体,检测病毒抗原与抗风疹病毒衣壳蛋白E1、E2、C蛋白的单克隆抗体的结合物。用该系统测定中国麻疹实验室网络送检的咽拭子标本,并与病毒分离结果和临床诊断进行比较。结果IFA方法可以快速、敏感地检测临床标本中的RV。经检测咽拭子标本38份,其中28份采集于临床诊断风疹病例;6例采集于出疹患者,但诊断不明;4份采集于风疹病例的接触者。检测结果有22份风疹阳性标本。IFA的结果与病毒分离结果完全一致,但与临床诊断不一致,IFA结果的阳性数低于临床诊断风疹病例数。结论IFA方法简单可行、敏感特异,结果易于判断,是中国麻疹实验室网络中进行RV检测的重要方法之一。同时IFA方法也可以作为临床快速诊断RV感染的备选方法之一。

Application on Indirect Immunofluorescence Assay (IFA) in Detectinn Rubella Viral Infections

Objective To establish an indirect immunofluorescence assay(IFA) for detecting Rubella viral infections,and provide an important method for rapid,sensitive detecting Rubella viruses in clinical specimens.Methods Fluorescent goat anti mouse IgG conjugate was used to detect the complex of Rubella antigens and Rubella monoclonal antibodies to virion protein E_1,E_2,and C.Then this system was used to detect the throat swab specimens collected in Chinese Measles and Rubella laboratory network;also the results were compared with viral isolation results and clinical diagnosis.Results This system can detect Rubella viruses in clinical specimens rapidly and sensitively,totally 38 throat swab specimens were detected,among the 38 specimens,26 were collected from clinical diagnosed patients,6 were collected from patients with unknown eruption,4 were collected from contactors of Rubella patients,and 22 of 38 were positive.The results of IFA were same with that of virus isolation,but it was not coincident with the clinical diagnosis,the positive rate is less than the clinical diagnosis rate.Conclusion The clinical diagnosis of Rubella is not so reliable,so the diagnose of Rubella must depend on laboratory diagnosis,immunofluorescence assay(IFA)is simple,sensitive,the results will be known within a short time and easy to read,so it can be used as one of the best methods for rapid detection of Rubella infection for clinic,it is one of the important methods for detecting Rubella virus in the Chinese measles and Rubella laboratory network.