摘要
建立低密度脂蛋白受体(Low density lipoprotein receptor,LDLR)激动剂药物筛选模型,并用该模型筛选出具有上调LDLR功能的黑茶品类。合成LDLR启动子片端(189bp),克隆入含有萤火虫荧光素梅报告基因的p GL3-basic载体中,构建了重组报告基因质粒p GL3-LDLR,以p RL-TK为内参质粒,瞬时转染人肝癌细胞Hep G2;以降脂药物辛伐他汀作为阳性对照物,优化反应条件,再应用该模型对8种黑茶水提取物进行了初步筛选。结果表明,辛伐他汀对荧光素酶的表达具有较强的诱导作用,且呈一定剂量的依赖性,Z′因子为0.72,表明该模型具有很好的灵敏性和稳定性,成功地建立了靶向LDLR转录活性的双报告基因筛选体系,并发现待测黑茶均有一定的激动活性,其中金花天成茶对模型的激活值最高,激活值达1.761。
In order to screen up-regulating LDLR level tea from the different varieties of dark tea, the LDLR agonist model was constructed. LDLR promoter（189bp） was cloned and ligated into the pGL3-basi vector contained luciferase reporter gene, then the recombinant reporter plasmid pGL3-LDLR was constructed. HepG2 cells were transfected with pGL3-LDLR and internal reference plasmid TK, we used the simvastatin lowering cholesterol as a positive control, and optimized various experimental conditions. The results showed that the simvastatin can induce the expression of luciferase reporter markedly and in a dependent manner, the Z＇factor of this model was 0.72. The experiment results illustrated this model was sensitive and stable. And found that the various dark teas have a certain activity through the model, but the ＂Golden Flower＂ Tiancheng tea has the highest utr---regulating activity to this model, activated values was 1.761.
作者
吴文亮
黄建安
刘仲华
杨新河
袁勇
黄浩
杨文波
WU Wen-liang HUANG Jian-an LIU Zhong-hual YANG Xin-he YUAN Yong HUANG Hao YANG Wen-bo(Key Lab of Tea Science of Ministry of Education, Hunan Agricultural University, National Research Center of Engineering ＆ Technology for Utilization of Functional Ingredients from Botanical, Collaborative Innovation Center of Utilization of Functional Ingredients from Botanicals, Changsha 410128, China Tea Research Institute of Hunan Academy of Agricultural, Changsha 410125, China School of Life Science and Technology, Hubei Engineering University, Xiaogan 432000, China Hunan Tea Group Co., LTD, Changsha 410126, China)
出处
《茶叶通讯》
2017年第3期7-12,16,共7页
Journal of Tea Communication
基金
梧州市科学研究与技术开发计划项目(201501028)
2015年梧州市六堡茶产业化项目
湖南省自然科学基金(2016JJ6058)
