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Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay
Published on: December 19, 2018
Study sequence rules of estrogen receptor α-DNA interactions using dual polarization interferometry and computational
Hong Yan Song1, Wenjie Sun, Shyam Prabhakar
1Institute of Materials Research and Engineering, Agency for Science, Technology, and Research (A*STAR), Singapore 117602, Singapore.
Analytical Biochemistry
|October 27, 2012
Summary
Estrogen receptor alpha (ERα) binding to DNA was studied using dual polarization interferometry. This method accurately predicts ERα binding affinity across the genome, advancing our understanding of gene regulation.
Area of Science:
- Molecular Biology
- Genomics
- Biophysics
Background:
- Estrogen receptor alpha (ERα) is a transcription factor regulating gene expression.
- ERα binds to specific DNA sequences known as estrogen response elements (EREs).
- Variations in ERE sequences impact ERα binding affinity and transcriptional activity.
Purpose of the Study:
- To develop and validate an in vitro method for measuring ERα binding affinity to DNA.
- To correlate in vitro binding data with in vivo genomic binding patterns.
- To establish a reliable model for ERα-ERE interactions.
Main Methods:
- Creation of 15 singly mutated estrogen response elements (EREs).
- Measurement of ERα binding affinity using dual polarization interferometry (DPI).
- Computation of an in vivo binding energy model using the Thermodynamic Modeling of ChIP-seq (TherMos) algorithm.
Main Results:
- The in vitro binding affinity model derived from DPI strongly correlates with the in vivo TherMos model (rank correlation coefficient of 0.91).
- This indicates the DPI method is a reliable predictor of ERα binding in the whole genome.
- The study presents the first DPI analysis of protein-double-stranded DNA interactions.
Conclusions:
- Dual polarization interferometry is a powerful and sensitive tool for studying ERα-DNA interactions.
- The developed assay protocols are efficient for high-throughput screening of DNA sequences with single-base variations.
- This work provides a robust model for understanding ERα binding dynamics in vivo.
