High content imaging-based assay to classify estrogen receptor-α ligands based on defined mechanistic outcomes.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.
Gene (Impact Factor: 2.08). 05/2011; 477(1-2):42-52. DOI: 10.1016/j.gene.2011.01.009
Source: PubMed

ABSTRACT Estrogen receptor-α (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.

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