QuanTI-FRET: a framework for quantitative FRET measurements in living cells

التفاصيل البيبلوغرافية
العنوان: QuanTI-FRET: a framework for quantitative FRET measurements in living cells
المؤلفون: Coullomb, Alexis, Bidan, Cecile M., Qian, Chen, Wehnekamp, Fabian, Oddou, Christiane, Albiges-Rizo, Corinne, Lamb, Don. C., Dupont, Aurelie
سنة النشر: 2019
المجموعة: Physics (Other)
مصطلحات موضوعية: Physics - Biological Physics, Physics - Optics
الوصف: Foerster Resonance Energy Transfer (FRET) allows for the visualization of nanometer-scale distances and distance changes. This sensitivity is regularly achieved in single-molecule experiments in vitro but is still challenging in biological materials. Despite many efforts, quantitative FRET in living samples is either restricted to specific instruments or limited by the complexity of the required analysis. With the recent development and expanding utilization of FRET-based biosensors, it becomes essential to allow biologists to produce quantitative results that can directly be compared. Here, we present a new calibration and analysis method allowing for quantitative FRET imaging in living cells with a simple fluorescence microscope. Aside from the spectral crosstalk corrections, two additional correction factors were defined from photophysical equations, describing the relative differences in excitation and detection efficiencies. The calibration is achieved in a single step, which renders the Quantitative Three-Image FRET (QuanTI-FRET) method extremely robust. The only requirement is a sample of known stoichiometry donor:acceptor, which is naturally the case for intramolecular FRET constructs. We show that QuanTI-FRET gives absolute FRET values, independent of the instrument or the expression level. Through the calculation of the stoichiometry, we assess the quality of the data thus making QuanTI-FRET usable confidently by non-specialists.
Comment: 13 pages, 3 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/1912.07899
رقم الأكسشن: edsarx.1912.07899
قاعدة البيانات: arXiv