Novel Estrogen Receptor Dimerization BRET-Based Biosensors for Screening Estrogenic Endocrine-Disrupting Chemicals

被引:2
|
作者
Choi, Gyuho [1 ]
Kang, Hyunkoo [1 ]
Suh, Jung-Soo [1 ]
Lee, Haksoo [1 ]
Han, Kiseok [1 ]
Yoo, Gaeun [1 ]
Jo, Hyejin [2 ]
Shin, Yeong Min [2 ]
Kim, Tae-Jin [1 ,3 ,4 ,5 ]
Youn, Buhyun [1 ,3 ,5 ]
机构
[1] Pusan Natl Univ, Dept Integrated Biol Sci, Pusan 46241, South Korea
[2] Minist Food & Drug Safety, Natl Inst Food & Drug Safety Evaluat, Food Safety Risk Assessment Div, Osong 363700, Chungbuk, South Korea
[3] Pusan Natl Univ, Dept Biol Sci, Pusan 46241, South Korea
[4] Pusan Natl Univ, Inst Syst Biol, Pusan 46241, South Korea
[5] Pusan Natl Univ, Nucl Sci Res Inst, Busan 46241, South Korea
关键词
IN-VIVO; ALPHA; TECHNOLOGY; BETA; FULVESTRANT; ACTIVATION; TAMOXIFEN;
D O I
10.34133/bmr.0010
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The increasing prevalence of endocrine-disrupting chemicals (EDCs) in our environment is a growing concern, with numerous studies highlighting their adverse effects on the human endocrine system. Among the EDCs, estrogenic endocrine-disrupting chemicals (eEDCs) are exogenous compounds that perturb estrogenic hormone function by interfering with estrogen receptor (ER) homo ( alpha/ alpha, beta/ beta) or hetero ( alpha/ beta) dimerization. To date, a comprehensive screening approach for eEDCs affecting all ER dimer forms in live cells is lacking. Here, we developed ER dimerization-detecting biosensors (ERDDBs), based on bioluminescence resonance energy transfer, for dimerization detection and rapid eEDC identification. To enhance the performance of these biosensors, we determined optimal donor and acceptor locations using computational analysis. Additionally, employing HaloTag as the acceptor and incorporating the P2A peptide as a linker yielded the highest sensitivity among the prototypes. We also established stable cell lines to screen potential ER dimerization inducers among estrogen analogs (EAs). The EAs were categorized through cross-comparison of ER dimer responses, utilizing EC values derived from a standard curve established with 17 beta-estradiol. We successfully classified 26 of 72 EAs, identifying which ER dimerization types they induce. Overall, our study underscores the effectiveness of the optimized ERDDB for detecting ER dimerization and its applicability in screening and identifying eEDCs.
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收藏
页数:14
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