Automated FRET Two‐Hybrid Analysis

ABSTRACT The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance‐Uniformity‐based Region of I...

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Vydané v:	Journal of biophotonics Ročník 18; číslo 9; s. e70033 - n/a
Hlavní autori:	Wei, Zhiqiang, Xu, Yanling, Wang, Jingzhen, Sun, Beini, Huang, Qialing, Zhuang, Zhengfei, Chen, Tongsheng, Hu, Min
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Weinheim WILEY‐VCH Verlag GmbH & Co. KGaA 01.09.2025 Wiley Subscription Services, Inc
Predmet:	Algorithms automated data processing Automation Energy transfer Fluorescence resonance energy transfer Fluorescence Resonance Energy Transfer - methods FRET quantitative analysis FRET two‐hybrid assay Humans Image analysis Image processing Image Processing, Computer-Assisted Stoichiometry Two-Hybrid System Techniques FRET two‐hybrid assay image processing FRET quantitative analysis stoichiometry automated data processing
ISSN:	1864-063X, 1864-0648, 1864-0648
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Abstract	ABSTRACT The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance‐Uniformity‐based Region of Interest Selection (LURS) algorithm, accelerating processing 12‐fold (6 h → 30 min) for three‐channel FRET imaging. Validation with FRET standards (C32V: E D C 32 V = 0.30 ± 0.01 , S C 32 V = 1.06 ± 0.14 ; CVC: E D CVC = 0.40 ± 0.02 , S CVC = 1.90 ± 0.11 ) matched reference values. Applied to Bcl‐xL/Bak interactions under A1331852 treatment, LURS revealed dose‐dependent stoichiometry reduction ( 1.87 → 1.12 ). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies. We developed an automated FRET two‐hybrid platform using the LURS algorithm, accelerating image analysis 12‐fold (6 h → 30 min). Validated with C32V/CVC constructs, it accurately measured FRET efficiency and stoichiometry ( n D / n A = 1.06 ± 0.14/C32V; 1.90 ± 0.11/CVC), matching reported values. Applied to Bcl‐xL/Bak interaction under A1331852, it revealed stoichiometry reduction (1.87 → 1.12), enabling HTS‐compatible drug discovery.
AbstractList	The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance‐Uniformity‐based Region of Interest Selection (LURS) algorithm, accelerating processing 12‐fold (6 h 30 min) for three‐channel FRET imaging. Validation with FRET standards (C32V: , ; CVC: , ) matched reference values. Applied to Bcl‐xL/Bak interactions under A1331852 treatment, LURS revealed dose‐dependent stoichiometry reduction (). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies. ABSTRACT The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance‐Uniformity‐based Region of Interest Selection (LURS) algorithm, accelerating processing 12‐fold (6 h → 30 min) for three‐channel FRET imaging. Validation with FRET standards (C32V: E D C 32 V = 0.30 ± 0.01 , S C 32 V = 1.06 ± 0.14 ; CVC: E D CVC = 0.40 ± 0.02 , S CVC = 1.90 ± 0.11 ) matched reference values. Applied to Bcl‐xL/Bak interactions under A1331852 treatment, LURS revealed dose‐dependent stoichiometry reduction ( 1.87 → 1.12 ). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies. We developed an automated FRET two‐hybrid platform using the LURS algorithm, accelerating image analysis 12‐fold (6 h → 30 min). Validated with C32V/CVC constructs, it accurately measured FRET efficiency and stoichiometry ( n D / n A = 1.06 ± 0.14/C32V; 1.90 ± 0.11/CVC), matching reported values. Applied to Bcl‐xL/Bak interaction under A1331852, it revealed stoichiometry reduction (1.87 → 1.12), enabling HTS‐compatible drug discovery. The fluorescence resonance energy transfer (FRET) two-hybrid assay enables live-cell detection of biomolecular complexes but faces high-throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance-Uniformity-based Region of Interest Selection (LURS) algorithm, accelerating processing 12-fold (6 h 30 min) for three-channel FRET imaging. Validation with FRET standards (C32V: , ; CVC: , ) matched reference values. Applied to Bcl-xL/Bak interactions under A1331852 treatment, LURS revealed dose-dependent stoichiometry reduction ( ). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies. The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance‐Uniformity‐based Region of Interest Selection (LURS) algorithm, accelerating processing 12‐fold (6 h → 30 min) for three‐channel FRET imaging. Validation with FRET standards (C32V: E D C 32 V = 0.30 ± 0.01 , S C 32 V = 1.06 ± 0.14 ; CVC: E D CVC = 0.40 ± 0.02 , S CVC = 1.90 ± 0.11 ) matched reference values. Applied to Bcl‐xL/Bak interactions under A1331852 treatment, LURS revealed dose‐dependent stoichiometry reduction ( 1.87 → 1.12 ). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies. The fluorescence resonance energy transfer (FRET) two-hybrid assay enables live-cell detection of biomolecular complexes but faces high-throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance-Uniformity-based Region of Interest Selection (LURS) algorithm, accelerating processing 12-fold (6 h → 30 min) for three-channel FRET imaging. Validation with FRET standards (C32V: E D C 32 V = 0.30 ± 0.01 , S C 32 V = 1.06 ± 0.14 ; CVC: E D CVC = 0.40 ± 0.02 , S CVC = 1.90 ± 0.11 ) matched reference values. Applied to Bcl-xL/Bak interactions under A1331852 treatment, LURS revealed dose-dependent stoichiometry reduction ( 1.87 → 1.12 ). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies.The fluorescence resonance energy transfer (FRET) two-hybrid assay enables live-cell detection of biomolecular complexes but faces high-throughput screening (HTS) limitations due to laborious image analysis. We developed an automated platform using the Luminance-Uniformity-based Region of Interest Selection (LURS) algorithm, accelerating processing 12-fold (6 h → 30 min) for three-channel FRET imaging. Validation with FRET standards (C32V: E D C 32 V = 0.30 ± 0.01 , S C 32 V = 1.06 ± 0.14 ; CVC: E D CVC = 0.40 ± 0.02 , S CVC = 1.90 ± 0.11 ) matched reference values. Applied to Bcl-xL/Bak interactions under A1331852 treatment, LURS revealed dose-dependent stoichiometry reduction ( 1.87 → 1.12 ). The method achieved precise signal extraction while preserving native cellular conditions, overcoming throughput constraints in dynamic protein interaction studies.
Author	Hu, Min Xu, Yanling Chen, Tongsheng Huang, Qialing Wei, Zhiqiang Sun, Beini Wang, Jingzhen Zhuang, Zhengfei
Author_xml	– sequence: 1 givenname: Zhiqiang surname: Wei fullname: Wei, Zhiqiang organization: South China Normal University – sequence: 2 givenname: Yanling surname: Xu fullname: Xu, Yanling organization: South China Normal University – sequence: 3 givenname: Jingzhen surname: Wang fullname: Wang, Jingzhen organization: South China Normal University – sequence: 4 givenname: Beini surname: Sun fullname: Sun, Beini organization: South China Normal University – sequence: 5 givenname: Qialing surname: Huang fullname: Huang, Qialing organization: South China Normal University – sequence: 6 givenname: Zhengfei surname: Zhuang fullname: Zhuang, Zhengfei organization: South China Normal University – sequence: 7 givenname: Tongsheng surname: Chen fullname: Chen, Tongsheng organization: South China Normal University – sequence: 8 givenname: Min orcidid: 0000-0001-5567-7930 surname: Hu fullname: Hu, Min email: hmin@scnu.edu.cn organization: South China Normal University
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Cites_doi	10.1088/2040-8986/ac3675 10.1038/s41419‐019‐1407‐6 10.1038/nprot.2016.128 10.1529/biophysj.106.096206 10.1038/nmeth.4593 10.1529/biophysj.105.061853 10.1364/PRJ.485521 10.1016/S0896‐6273(01)00438‐X 10.1038/ncomms13709 10.1016/j.bbrc.2019.03.089 10.1016/j.bspc.2019.101585 10.1109/ICCV51070.2023.00371 10.3390/molecules26216339 10.1529/biophysj.103.022087 10.1038/s41467-023-38808-8 10.1529/biophysj.106.088773 10.1038/s41592‐019‐0530‐8 10.1016/j.xpro.2023.102459 10.1073/pnas.1905924116 10.1021/acsmedchemlett.9b00568 10.1016/j.xinn.2023.100425 10.1038/s41420-023-01338-9 10.1111/jmi.12783 10.1007/978-981-16-5640-8_50 10.1063/1.5021466 10.1142/S1793545820500212
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Notes	This work was supported by grants from the Key‐Area Research and Development Program of Guangdong Province (Grant No. 2022B0303040003), National Natural Science Foundation of China (NSFC) (Grant No. 62135003 and 62475077), Guangdong Basic and Applied Basic Research Foundation (Grant No. 2024A1515010586), and Graduate Research Innovation Program of South China Normal University (Grant No. 2024KYLX074). Funding ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
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Snippet	ABSTRACT The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput... The fluorescence resonance energy transfer (FRET) two‐hybrid assay enables live‐cell detection of biomolecular complexes but faces high‐throughput screening... The fluorescence resonance energy transfer (FRET) two-hybrid assay enables live-cell detection of biomolecular complexes but faces high-throughput screening...
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SubjectTerms	Algorithms automated data processing Automation Energy transfer Fluorescence resonance energy transfer Fluorescence Resonance Energy Transfer - methods FRET quantitative analysis FRET two‐hybrid assay Humans Image analysis Image processing Image Processing, Computer-Assisted Stoichiometry Two-Hybrid System Techniques
Title	Automated FRET Two‐Hybrid Analysis
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