摘要
目的建立酶联凝集素测定法(enzyme-linked lectin assay,ELLA)检测接种流感疫苗志愿者血清中神经氨酸酶抑制(neuraminidase inhibition,NI)抗体。方法对神经氨酸酶切底物、酶标抗体孵育浓度和时间、最适病毒量以及病毒稀释液pH值等反应条件进行优化,确定合适的反应体系,采用建立的方法检测对接种H7N9大流行流感疫苗34名志愿者血清样本进行检测。结果胎球蛋白作为酶切底物最佳包被浓度为7.5μg/ml;酶标抗体最佳稀释度为1∶500,H7N9疫苗株作为抗原使用pH6.5的稀释液稀释至浓度4.5lgCCID50/ml。疫苗接种后血清样本抗N9型NI抗体滴度较接种前均有显著增高(P<0.001),在34名志愿者中,47%的人NI抗体接种后呈阳性反应(NI抗体滴度≥40),低于HI抗体反应阳转率(P<0.05)。结论建立的基于天然底物检测NI抗体的ELLA法简单实用,为流感疫苗和血清流行病学NI抗体免疫评价体系的建立提供实验资料。
Objective To develop an enzyme-linked lectin assay(ELLA)for measuring neuraminidase inhibition(NI)antibody titers in subjects vaccinated with H7N9 influenza vaccine.Methods Neuraminidase substrate,the dilution and incubation time of enzyme-labeled antibody,the concentration of influenza antigen for coating and pH value of the dilution buffer were optimized.Based on that,ELLA was established and used to detect anti-influenza neuraminidase antibody titers in serum samples of 34 subjects before and after vaccination with H7N9 influenza vaccine.Results The optimal neuraminidase substrate was fetuin at a coating concentration of 7.5μg/ml.The optimal dilution of enzyme-labeled antibody was 1∶500.The virus strain of influenza H7N9 vaccine was used as antigen at a concentrations of 4.5lgCCID50/ml in solution with a pH of 6.5.Influenza-specific NI titers detected after immunization with vaccine were significantly higher than those before vaccination(P<0.001).In the 34 subjects receiving H7N9 vaccine,the seroconversion rate of NI antibody was 47%(≥40 in NI titer),which was lower than that of HI antibody(P<0.05).Conclusions An ELLA with natural substrate for measurement of anti-influenza NI antibody was developed.It is simple and practical and might be used in the establishment of immune evaluation system for influenza vaccines and NI antibody.
作者
赵慧
英志芳
邵铭
李娟
李长贵
Zhao Hui;Ying Zhifang;Shao Ming;Li Juan;Li Changgui(Division of Respiratory Virus Vaccines,National Institutes for Food and Drug Control,Beijing 102629,China)
出处
《中华微生物学和免疫学杂志》
CAS
CSCD
北大核心
2019年第3期217-220,共4页
Chinese Journal of Microbiology and Immunology
基金
北京市自然科学基金项目(7173277).