采用磁微粒分离酶联免疫法构建基于KGN细胞的雌激素生物合成筛选模型  被引量:2

Establishment of a Cell-based Screen Platform for Estrogen Biosynthesis Using Magnetic Particle-based Enzyme-linked immunosorbent Assay

在线阅读下载全文

作  者:鲁丹枫[1,2] Azimova Bahtigul Jovliqizi 张国林[1] 王飞[1] 

机构地区:[1]中国科学院成都生物研究所,成都610041 [2]中国科学院研究生院,北京100049 [3]乌兹别克斯坦科学院生物化学研究所

出  处:《天然产物研究与开发》2013年第1期27-30,67,共5页Natural Product Research and Development

基  金:国家自然科学基金项目(20932007;30900769);中国科学院"西部之光"项目;国家"重大新药创制"科技重大专项(2011ZX09307-002-02)

摘  要:雌激素在机体生长发育中发挥着重要作用,其合成代谢紊乱会导致乳腺癌和骨质疏松等疾病发生。目前,基于细胞的雌激素合成筛选模型需用到放射性底物,对环境污染大,成本较高,限制了具有组织特异性调控雌激素合成的药物筛选。我们以高表达芳香化酶的KGN细胞为检测对象,比较基于聚苯乙烯酶联免疫法和磁微粒分离酶联免疫法的雌二醇ELISA试剂盒的交叉反应和灵敏度,发现相对于聚苯乙烯酶联免疫法,磁微粒分离酶联免疫法能够稳定高效的检测雌激素合成。进一步比较培养基中酚红和底物睾酮对雌二醇检测的影响,成功建立通过磁微粒酶联免疫法检测KGN细胞雌二醇合成的筛选模型。Estrogens play important roles in the growth and development of human, and the disorders of estrogen biosyn- thesis and metabolism can lead to occurrence of many diseases such as breast cancer and osteoporosis. Currently, the cell-based screen models for estrogen biosynthesis need the use of radioactive substances, which cause environmental pollution and the cost for screening too high tO be affordable,thus severely restrict the finding of new drugs to modulate estrogen biosynthesis in a tissue-specific manner. By using human granulosa-like KGN cells which express high amount of aromatase, we found that the 17β-estradiol magnetic particle-based enzyme-linked imminosorbent assay (ELISA) was more stable and sensitive than conventional polystyrene-based ELISA in quantification of 17β-estradiol by comparing the cross-reactivity and sensitivity of the two different 17β-estradiol ELISA methods. After further examining the effects of phenol red in cell culture medium and testosterone substance concentration on the quantitative detection of 17β-estradiol ,we successfully established a human granulosa-like KGN cell-based screen platform for estrogen biosynthesis by using magnetic particle-based ELISA.

关 键 词:KGN细胞 雌激素 ELISA 筛选 

分 类 号:R915[医药卫生—微生物与生化药学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象