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Updated: May 1, 2026

Using In Vitro Fluorescence Resonance Energy Transfer to Study the Dynamics Of Protein Complexes at a Millisecond Time Scale

Using In Vitro Fluorescence Resonance Energy Transfer to Study the Dynamics Of Protein Complexes at a Millisecond Time Scale

Published on: March 14, 2019

Automated FRET Two-Hybrid Analysis.

Zhiqiang Wei^1,2, Yanling Xu^1,2, Jingzhen Wang^1,2

¹MOE Key Laboratory of Laser Life Science & Institute of Laser Life Science, College of Biophotonics, School of Optoelectronic Science and Engineering, South China Normal University, Guangzhou, Guangdong, China.

Journal of Biophotonics

|April 23, 2025

Summary

We developed an automated platform for fluorescence resonance energy transfer (FRET) imaging, significantly speeding up analysis. This advance overcomes high-throughput screening limitations in studying dynamic protein interactions.

Keywords:

FRET quantitative analysis FRET two‐hybrid assay automated data processing image processing stoichiometry

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Last Updated: May 1, 2026

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Published on: March 14, 2019

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Published on: October 14, 2022

Area of Science:

Biochemistry
Cell Biology
Biophysics

Background:

Fluorescence resonance energy transfer (FRET) two-hybrid assays detect biomolecular complexes in live cells.
Current FRET imaging analysis is laborious, limiting high-throughput screening (HTS).

Purpose of the Study:

To develop an automated platform for accelerated FRET imaging analysis.
To overcome throughput limitations in studying dynamic protein interactions.

Main Methods:

Developed the Luminance-Uniformity-based Region of Interest Selection (LURS) algorithm for automated image analysis.
Applied LURS to three-channel FRET imaging, processing data 12-fold faster.
Validated the method using FRET standards.

Main Results:

Achieved a 12-fold acceleration in FRET image processing (6 hours to 30 minutes).
Validation with FRET standards confirmed accurate signal extraction.
Demonstrated dose-dependent reduction in Bcl-xL/Bak complex stoichiometry under A1331852 treatment.

Conclusions:

The LURS algorithm provides precise signal extraction for FRET imaging.
Automated analysis preserves native cellular conditions and overcomes HTS throughput constraints.
Enables efficient dynamic protein interaction studies.