Abstract：
Flow or collective movement is a frequently observed phenomenon for many cellular components including the cytoskeletal proteins actin and myosin. To study protein flow in living cells, we and others have previously used spatiotemporal image correlation spectroscopy (STICS) analysis on fluorescence microscopy image time series. Yet, in cells, multiple protein flows often occur simultaneously on different scales resulting in superimposed fluorescence intensity fluctuations that are challenging to separate using STICS. Here, we exploited the characteristic that distinct protein flows often occur at different spatial scales present in the image series to disentangle superimposed protein flow dynamics. We employed a newly developed and an established spatial filtering algorithm to alternatively accentuate or attenuate local image intensity heterogeneity across different spatial scales. Subsequently, we analysed the spatially filtered time series with STICS, allowing the quantification of two distinct superimposed flows within the image time series. As a proof of principle of our analysis approach, we used simulated fluorescence intensity fluctuations as well as time series of nonmuscle myosin II in endothelial cells and actin-based podosomes in dendritic cells and revealed simultaneously occurring contiguous and noncontiguous flow dynamics in each of these systems. Altogether, this work extends the application of STICS for the quantification of multiple protein flow dynamics in complex biological systems including the actomyosin cytoskeleton.
摘要：
对于包括细胞骨架蛋白肌动蛋白和肌球蛋白在内的许多细胞成分，流动或集体运动是经常观察到的现象。为了研究活细胞中的蛋白质流动，我们和其他人以前使用时空图像相关光谱（STICS）分析荧光显微镜图像时间序列。然而，在细胞中，多个蛋白质流通常在不同的尺度上同时发生，导致叠加的荧光强度波动，这对于使用STICS进行分离是具有挑战性的。这里,我们利用了不同的蛋白质流经常发生在图像系列中存在的不同空间尺度上的特征来解开叠加的蛋白质流动力学。我们采用了一种新开发的和已建立的空间滤波算法，以交替地强调或衰减不同空间尺度上的局部图像强度异质性。随后，我们用STICS分析了空间滤波的时间序列，允许量化图像时间序列内的两个不同的叠加流。作为我们分析方法原理的证明，我们使用了模拟的荧光强度波动以及内皮细胞中的非肌肉肌球蛋白II和树突状细胞中的基于肌动蛋白的足细胞的时间序列,并揭示了在这些系统中同时发生的连续和不连续流动动力学.总之,这项工作扩展了STICS在包括肌动球蛋白细胞骨架在内的复杂生物系统中定量多种蛋白质流动动力学的应用。
