研究目的
To improve the quality, reproducibility, and usability of FRET-based tension sensors for measuring molecular-scale forces across proteins in living cells.
研究成果
The study established that mode-based numerical approaches improve the accuracy of FRET-based tension sensor measurements. It demonstrated that VinTS is compatible with immuno-labeling techniques and provided guidelines for experimental design to ensure precise and reproducible results. The work affirms FRET-based tension sensors as robust tools for studying mechanical loads in living cells.
研究不足
The study's findings may not be generally applicable to all FRET-based tension sensors or cells in different mechanical microenvironments, such as 3D cell culture. Additionally, the sensitivity of the method to small changes in tension at small sample sizes is limited.
1:Experimental Design and Method Selection:
The study focused on developing numerical methods to improve the accuracy of FRET-based tension sensor measurements using sensitized emission-based imaging. The methodology included the use of vinculin tension sensors (VinTS) to measure mechanical loads across proteins.
2:Sample Selection and Data Sources:
Mouse embryonic fibroblasts lacking vinculin (vinculin -/- MEFs) were used as the cell model. Cells were transfected with various FRET constructs, including mTFP1-2x(GGSGGS)-Venus and mTFP1-TRAF-Venus, to study FRET efficiency.
3:List of Experimental Equipment and Materials:
Key equipment included an Olympus inverted fluorescent microscope (Olympus IX83), a sCMOS ORCA-Flash4.0 V2 camera, and a LambdaLS illumination system. Materials included pcDNA3.1 plasmids, Lipofectamine 2000 Reagent, and various fluorescent proteins (mTFP1, Venus).
4:0 V2 camera, and a LambdaLS illumination system. Materials included pcDNA1 plasmids, Lipofectamine 2000 Reagent, and various fluorescent proteins (mTFP1, Venus).
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Cells were imaged live or after fixation, permeabilization, and immunolabeling. FRET images were acquired using a custom filter set, and data were corrected for imaging artifacts and spectral bleedthroughs.
5:Data Analysis Methods:
FRET efficiency was calculated using custom MATLAB software. A mode-based numerical approach was developed to characterize FRET efficiency within cells, and bootstrapping was used to estimate uncertainty.
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