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SensorFRET: A Standardless Approach to Measuring Pixel-based Spectral Bleed-through and FRET Efficiency using Spectral Imaging

机译:SensorFRET:使用光谱成像技术测量基于像素的光谱渗漏和FRET效率的无标方法

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摘要

Fluorescence microscopy of FRET-based biosensors allow nanoscale interactions to be probed in living cells. This paper describes a novel approach to spectrally resolved fluorescence microscopy, termed sensorFRET, that enables quantitative measurement of FRET efficiency. This approach is an improvement on existing methods (FLIM, sRET, luxFRET, pFRET), as it does not require single fluorophore standards to be measured with every experiment and the acquisition is intensity independent, allowing the laser power to be optimized for varying levels of fluorophore expression. Additionally, it was found that all spectral based methods, including sensorFRET, fail at specific fluorophore-excitation wavelength combinations. These combinations can be determined a priori using sensorFRET, whereas other methods would give no indication of inaccuracies. This method was thoroughly validated and compared to existing methods using simulated spectra, Fluorescein and TAMRA dye mixtures as a zero FRET control, and Cerulean-Venus FRET standards as positive FRET controls. Simulations also provided a means of quantifying the uncertainty in each measurement by relating the fit residual of noisy spectra to the standard deviation of the measured FRET efficiency. As an example application, Teal-Venus force sensitive biosensors integrated into E-cadherin were used to resolve piconewton scale forces along different parts of an individual cell junction.
机译:基于FRET的生物传感器的荧光显微镜可以在活细胞中探测纳米级的相互作用。本文介绍了一种新的光谱分辨荧光显微镜方法,称为sensorFRET,它能够定量测量FRET效率。这种方法是对现有方法(FLIM,sRET,luxFRET,pFRET)的改进,因为它不需要在每个实验中都测量单个荧光团标准品,并且采集不受强度的影响,因此可以针对不同水平的激光功率进行优化荧光团表达。此外,发现所有基于光谱的方法(包括sensorFRET)在特定的荧光团激发波长组合下均失败。可以使用sensorFRET事先确定这些组合,而其他方法则不会给出任何不准确的迹象。对该方法进行了彻底的验证,并将其与使用模拟光谱,荧光素和TAMRA染料混合物作为零FRET对照以及Cerulean-Venus FRET标准作为正FRET对照的现有方法进行比较。模拟还提供了一种通过将噪声频谱的拟合残差与测得的FRET效率的标准偏差相关联来量化每次测量中不确定性的方法。作为一个示例应用程序,集成到E-钙粘着蛋白中的Teal-Venus力敏感生物传感器用于解决沿单个细胞连接不同部分的皮微尺度力。

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