Migueles-Ramírez Rodrigo A, Cambi Alessandra, Hayer Arnold, Wiseman Paul W, van den Dries Koen
Department of Quantitative Life Sciences, McGill University, Montreal, Quebec, Canada.
Department of Chemistry, McGill University, Montreal, Quebec, Canada.
J Microsc. 2025 May;298(2):204-218. doi: 10.1111/jmi.13342. Epub 2024 Jul 4.
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.
流动或集体运动是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中经常观察到的现象。为了研究活细胞中的蛋白质流动,我们和其他人之前在荧光显微镜图像时间序列上使用了时空图像相关光谱(STICS)分析。然而,在细胞中,多种蛋白质流动通常会在不同尺度上同时发生,导致荧光强度波动叠加,使用STICS分离这些波动具有挑战性。在这里,我们利用图像序列中不同蛋白质流动通常发生在不同空间尺度上的特征来解开叠加的蛋白质流动动力学。我们采用了一种新开发的和一种已建立的空间滤波算法,交替增强或减弱不同空间尺度上的局部图像强度异质性。随后,我们用STICS分析了空间滤波后的时间序列,从而能够量化图像时间序列内两种不同的叠加流动。作为我们分析方法原理的证明,我们使用了模拟荧光强度波动以及内皮细胞中非肌肉肌球蛋白II和树突状细胞中基于肌动蛋白的足体的时间序列,并揭示了这些系统中每个系统同时发生的连续和非连续流动动力学。总之,这项工作扩展了STICS在量化包括肌动球蛋白细胞骨架在内的复杂生物系统中多种蛋白质流动动力学方面的应用。