Characterization of Cell Boundary and Confocal Effects Improves Quantitative FRAP Analysis.
Characterization of Cell Boundary and Confocal Effects Improves Quantitative FRAP Analysis.
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细胞边界和共焦效应的表征改进了定量 FRAP 分析。
DOI：
10.1016/j.bpj.2018.01.013
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发表时间：
2018
影响因子：
3.4
通讯作者：
Tüzel,Erkan
中科院分区：
文献类型：
--
作者：
Kingsley,JamesL;Bibeau,JeffreyP;Mousavi,SIman;Unsal,Cem;Chen,Zhilu;Huang,Xinming;Vidali,Luis;Tüzel,Erkan
光漂白后荧光恢复（FRAP）是细胞生物学家研究囊泡、蛋白质和其他分子在细胞质、细胞核或细胞膜中的扩散和结合动力学的重要工具。尽管在过去的几十年里已经开发了许多FRAP模型，但3D细胞几何形状的复杂边界对恢复曲线的影响，以及感兴趣的区域和光学效应（成像、光漂白、光开关和扫描）的影响尚未得到很好的研究。在这里，我们建立了一个FRAP过程的三维计算模型，该模型考虑了颗粒扩散、细胞边界效应和扫描共聚焦显微镜的光学特性，并使用小立小藻的尖端生长细胞验证了该模型。然后，我们展示了这些细胞边界和光学效应如何混淆FRAP恢复曲线的解释，包括给定荧光团的动态状态的数量，在广泛的细胞几何形状中-在二维和三维中-即哺乳动物细胞的细胞核，丝状足和板足，以及细胞类型，如出芽酵母，pombe酵母和尖端生长的植物细胞。我们探索了现有的分析和算法FRAP模型在这些不同细胞几何形状中的性能，并确定VCell VirtualFRAP工具提供了测量扩散系数的最佳精度。我们的计算模型不仅限于这些细胞类型，还可以通过我们提供的基于java的图形化应用程序轻松扩展到其他细胞几何形状。这种基于粒子的模拟-称为数字共聚焦显微镜套件或dcms -还可以执行荧光动力学分析，如数量和亮度，荧光相关光谱和光栅图像相关光谱，并可以帮助塑造这些技术的解释方式。
Fluorescence recovery after photobleaching (FRAP) is an important tool used by cell biologists to study the diffusion and binding kinetics of vesicles, proteins, and other molecules in the cytoplasm, nucleus, or cell membrane. Although many FRAP models have been developed over the past decades, the influence of the complex boundaries of 3D cellular geometries on the recovery curves, in conjunction with regions of interest and optical effects (imaging, photobleaching, photoswitching, and scanning), has not been well studied. Here, we developed a 3D computational model of the FRAP process that incorporates particle diffusion, cell boundary effects, and the optical properties of the scanning confocal microscope, and validated this model using the tip-growing cells ofPhyscomitrella patens. We then show how these cell boundary and optical effects confound the interpretation of FRAP recovery curves, including the number of dynamic states of a given fluorophore, in a wide range of cellular geometries—both in two and three dimensions—namely nuclei, filopodia, and lamellipodia of mammalian cells, and in cell types such as the budding yeast,Saccharomyces pombe, and tip-growing plant cells. We explored the performance of existing analytical and algorithmic FRAP models in these various cellular geometries, and determined that the VCell VirtualFRAP tool provides the best accuracy to measure diffusion coefficients. Our computational model is not limited only to these cells types, but can easily be extended to other cellular geometries via the graphical Java-based application we also provide. This particle-based simulation—called the Digital Confocal Microscopy Suite or DCMS—can also perform fluorescence dynamics assays, such as number and brightness, fluorescence correlation spectroscopy, and raster image correlation spectroscopy, and could help shape the way these techniques are interpreted.