(F-212) Revolutionizing Estrogen Receptor Dimerization Monitoring with a Novel Fluorescence Resonance Energy Transfer-Based Biosensor

Introduction: The regulation of cell growth and differentiation is a crucial process, in which estrogen receptors (ERs) play a significant role. ERs consist of two subtypes, ERα and ERβ, and their dimerization status is known to affect cellular function and gene expression. Detecting ER dimerization is therefore essential, especially as ERα and ERβ form homodimers and heterodimers, which have distinct effects. To facilitate monitoring of ER dimerization, we developed fluorescence resonance energy transfer (FRET)-based ER biosensors. These biosensors allow the detection of ER dimerization dynamics in response to ligand binding, providing spatiotemporal information on ER dimerization activity. To improve the dynamic range and sensitivity of the biosensors, we varied four key parameters: ER domains (full-length or ligand-binding domains), linkers, fluorescent protein pairs, and their sequences in the biosensor design. Our optimized biosensors are well-suited for high-throughput screening, and have potential applications in drug screening for inhibitors of ER dimerization. This is a promising therapeutic strategy for ER-dependent cancers and endocrine system disorders.

Materials and Methods:

Construction of DNA plasmids:

The FRET-based ER FL biosensors were constructed by adding ERα, and ERβ full length. For the FRET-based ER LBD biosensors, we added the ligand-binding domain (LBD) of ERα, and ERβ. The ER biosensor mutant types were generated through site-directed mutagenesis. SnapGene software was utilized to simulate all cloning and site-directed mutagenesis procedures.

Microscopy and image acquisition:

During imaging, cells were maintained in a CO₂-independent medium containing 0.5% FBS, 1% Penicillin-Streptomycin, and 1X GlutaMAX^TM. We acquired images using a Leica DMi8 microscope, and utilized LAS X software to subtract the background from the image and obtain ECFP, FRET, and ratio images.

Statistical analysis:

All statistical analyses were performed using GraphPad 9.4. Statistical data were expressed as the mean ± standard error of the mean (SEM), and we conducted statistical evaluation via unpaired t-test using GraphPad 9.4. We determined significant differences using p-values (*P < 0.05, ** P < 0.01, *** P < 0.001, and **** P < 0.0001).

Results, Conclusions, and Discussions: In this study, we developed fluorescence resonance energy transfer (FRET)-based biosensors to monitor the homodimerization of ERα and ERβ, as well as the heterodimerization of ERβα, at the single-cell level. Four parameters were optimized to enhance FRET efficiency: ER domains, linkers, fluorescent protein pairs, and their order in the biosensor design. The best FRET efficiency in the ER αα biosensor was achieved using a P2A linker, mNeonGreen-ECFP fluorescent protein pairs, and the full-length ER sequence. Similarly, the ER βα biosensor showed optimal FRET efficiency using the same parameters. Both the ER ββ full-length (FL) and ligand-binding domain (LBD) biosensors exhibited similar FRET efficiency using an EV linker, with only the fluorescent protein pairs differing (mNeonGreen-ECFP for ER ββ FL and mNeonGreen-mTurquoise2 for ER ββ LBD biosensors).

The optimally selected ER biosensors have different detection limits, with the ER αα and ER ββ FL biosensors having a detection limit of 0.1-1nM, while the ER βα and ER ββ LBD biosensors have a detection limit of 1-10nM. The ER ββ FL biosensor is more sensitive than ER ββ LBD biosensor, which suggests that other domains, not just LBD, may play a role in ligand recognition and dimerization.

Therefore, these biosensors can detect and monitor dimerization induced by estrogen or estrogen-like endocrine-disrupting chemicals. Furthermore, we believe that FRET-based ER biosensors have potential applications in pharmacological drug screening to identify inhibitors of ER dimerization, which is a promising therapeutic strategy for ER-dependent cancers.

Acknowledgements (Optional): : This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2022M3E5F2017929).

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