目的 基于实时细胞分析(real time cell analysis，RTCA)技术对中药挥发性组分的细胞毒性及抗人腺病毒3型(human adenovirus 3，HAdV-3)的作用进行毒/效整合分析，构建抗病毒药物高通量筛选的新策略。方法 采用RTCA技术动态监测不同接种密度的A549细胞48 h生长曲线及10倍梯度稀释的HAdV-3感染A549细胞生长曲线，获得A549细胞最佳接种密度及HAdV-3最佳稀释浓度用于后续实验。以利巴韦林为阳性对照，基于RTCA技术采用曲线下面积(Area Under the Curve，AUC)方法对5种中药挥发性组分的细胞毒性及抗HAdV-3的作用进行毒/效整合分析，并与传统终点法数据处理进行对比。结果 终点法中艾叶、柴胡、薄荷、荆芥、牛蒡子、酸枣仁和利巴韦林对细胞的保护率分别为0。73％、12。50％、20。99％、44。50％、27。99％、51。50％和 82。70％;AUC 法中艾叶、柴胡、薄荷的选择性指数(Selective In-dex，SI)为负数，分别为-0。57、-0。21和-0。08。荆芥、牛蒡子、酸枣仁和利巴韦林的SI值分别为0。14、0。40、0。72和5。33。以利巴韦林的抗病毒活性为参照，终点法中酸枣仁、牛蒡子和荆芥的抗病毒活性为利巴韦林抗病毒活性的62。27％、33。85％和53。81％;AUC法中酸枣仁、牛蒡子和荆芥的抗病毒活性为利巴韦林抗病毒活性的13。51％、7。50％和2。63％。结论 传统终点法与研究采用的AUC法计算结果有较大的差异。传统的抗病毒活性筛选研究多采用终点法检测受试药物对病毒感染细胞的保护作用，无法反映整个感染周期的变化，缺乏细胞毒的数据也会对结果的判断产生偏差。研究提示基于RTCA技术对中药挥发性组分开展抗HAdV-3的毒/效整合评价，采用AUC方法计算药物的选择性指数作为高通量筛选新策略，能快速、精准地判断受试药物的抗病毒活性，具有准确性高、重复性好的优势。
Integrated Cytotoxicity/Effect Evaluation of Volatile Components of Traditional Chinese Medicine Against HAdV-3 Based on RTCA Technology:a New High-Throughput Screening Strategy
Objective Based on Real Time Cell Analysis(RTCA)technology,the cytotoxicity and anti-human adenovirus type 3(HAdV-3)of volatile components of traditional Chinese medicine were analyzed by toxicity/effect integration,anda new strate-gy was built for high-throughput screening of antiviral drugs.Methods The 48 h growth curve of A549 cells with different see-ding densities and the growth curve of A549 cells infected with HAdV-3 in 10-fold serial dilution were dynamically monitored by Real Time Cell Analysis(RTCA).The optimal seeding density of A549 cells and the optimal dilution concentration of HAdV-3 were obtained for subsequent experiments.Using ribavirin as a positive control,the cytotoxicity of 5 volatile compo-nents of traditional Chinese medicine to A549 cells and its protective effect on A549 cells infected with HAdV-3 were monitored by RTCA technology.The area under curve(AUC)method was used to analyze toxicity/efficacy of data and compared with the traditional end-point method.Results In the endpoint method,the cell protection rates of volatile components of Aiye(Folium Artemisiae Argyi),Chaihu(Radix Bupleuri),Bohe(Menthae Haplocalycis Herba),Jingjie(Herba Schizonepetae),Niubangzi(Fructus Arctii),Suanzaoren(Semen Ziziphi Spinosae)and ribavirin were 0.73％,12.50％,20.99％,44.50％,27.99％,51.50％and 82.70％,respectively.The selectivity index(SI)of volatile components of Aiye(Folium Artemisiae Argyi),Chaihu(Radix Bupleuri)and Bohe(Menthae Haplocalycis Herba)in the AUC method was negative,which was-0.57,-0.21 and-0.08,respectively.The SI values of Jingjie(Herba Schizonepetae),Niubangzi(Fructus Arctii),Suanzaoren(Semen Ziziphi Spi-nosae)and ribavirin were 0.14,0.40,0.72 and 5.33,respectively.Taking the antiviral activity of ribavirin as a reference,the antiviral activities of volatile components of Suanzaoren(Semen Ziziphi Spinosae),Niubangzi(Fructus Arctii)and Jingjie(Herba Schizonepetae)in the endpoint method were 62.27％,33.85％and 53.81％of the antiviral activity of ribavirin.In AUC meth-od,the antiviral activities of volatile components of Suanzaoren(Semen Ziziphi Spinosae),Niubangzi(Fructus Arctii)and Jingjie(Herba Schizonepetae)were 13.51％,7.50％and 2.63％of the antiviral activity of ribavirin.Conclusion The results show that there is a great difference between the traditional endpoint method and the AUC method used in this study.The traditional antivi-ral activity screening research mostly uses the endpoint method to detect the protective effect of the tested drug on virus infected cells,which cannot reflect the changes of the whole infection cycle,and the lack of cytotoxicity data will also to bias in the judg-ment of the results.This study suggested that RTCA technology was used to conduct integrated toxicity/efficacy evaluation of vol-atile components of traditional Chinese medicine against HAdV-3,and the AUC method was used to calculate SI of drugs as a new high-throughput screening strategy,which could evaluate the antiviral activity of tested drugs more quickly and accurately,with advantages of high accuracy and good repeatability.
万方数据
维普
