High content imaging-based assay to classify estrogen receptor-α ligands based on defined mechanistic outcomes
High content imaging-based assay to classify estrogen receptor-α ligands based on defined mechanistic outcomes
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DOI：
10.1016/j.gene.2011.01.009
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发表时间：
2011-05-15
期刊：
影响因子：
3.5
通讯作者：
Mancini, M. A.
中科院分区：
文献类型：
--
作者：
Ashcroft, F. J.;Newberg, J. Y.;Mancini, M. A.
雌激素受体-α(ER)是治疗性化合物和内分泌干扰物(EDCs)的重要靶点，然而，调控ER转录活性的化学调控机制尚不清楚。在这里，我们报告了一种基于高含量分析的分析方法的发展，以描述ER活性，该方法独特地利用了ER调节启动子的显微可见的多拷贝整合。通过自动化的单细胞分析，我们同时量化了启动子的占有率、转录辅助因子的招募以及对一组ER配体和EDCs的反应所产生的大规模染色质变化。图像衍生的多参数数据被用来在高分辨率下对一组配体响应进行分类。我们提出这一系统作为一种新技术，为EDC活动提供了新的机械学见解，对基础机械学研究和药物测试都很有用。(C)2011爱思唯尔B.V.保留所有权利。
Estrogen receptor-alpha (ER) is an important target both for therapeutic compounds and endocrine disrupting chemicals (EDCs); however, the mechanisms involved in chemical modulation of regulating ER transcriptional activity are inadequately understood. Here, we report the development of a high content analysis-based assay to describe ER activity that uniquely exploits a microscopically visible multi-copy integration of an ER-regulated promoter. Through automated single-cell analyses, we simultaneously quantified promoter occupancy, recruitment of transcriptional cofactors and large-scale chromatin changes in response to a panel of ER ligands and EDCs. Image-derived multi-parametric data was used to classify a panel of ligand responses at high resolution. We propose this system as a novel technology providing new mechanistic insights into EDC activities in a manner useful for both basic mechanistic studies and drug testing. (C) 2011 Elsevier B.V. All rights reserved.