Lichtenstein Nurit, Geiger Benjamin, Kam Zvi
Weizmann Institute of Science, Department of Molecular Cell Biology, Rehovot, Israel.
Cytometry A. 2003 Jul;54(1):8-18. doi: 10.1002/cyto.a.10053.
The cytoskeleton consists of complex arrays of fibers that play indispensable roles in cell structure and function. The cytoskeletal fibers are concertedly involved in numerous cellular processes, including cell adhesion, locomotion, intracellular transport, and cell division. The organization of the cytoskeleton was extensively studied, mainly by immunofluorescence microscopy, yet these studies were mostly qualitative, and a reliable quantitative approach for determining fiber structure and distribution is still missing.
In this study we developed algorithms for filament feature extraction, based on fluorescence microscopy. These algorithms are robust against blurring by slight defocus, high background, and noise, and are applicable to both fixed, immunolabeled cells and live cells expressing fluorescently tagged cytoskeletal proteins. The implemented FiberScore program is used in order to recognize, segment, and quantify various structural parameters of the cytoskeleton, including total fiber-associated fluorescence, as well as fiber length and orientation. Furthermore, these parameters can be determined for different cytoskeletal proteins in the same sample tagged with multiple-fluorescent labels, and the results can be correlated with other cellular parameters.
FiberScore was used here for the quantification of simultaneous changes in microtubule and actin filaments induced by the microtubule-disrupting drug nocodazole. Actin filaments, which are reported to respond reciprocally to microtubule disruption, are found to be affected by both immediate and delayed signals.
Analysis of the organization of fibers by the FiberScore algorithm allows quantification of the cytoskeletal signature of cells and offers reliable multiparametric functional assays for effects of drugs and other perturbations evaluated on a cell-by-cell basis.
细胞骨架由复杂的纤维阵列组成，在细胞结构和功能中发挥着不可或缺的作用。细胞骨架纤维协同参与众多细胞过程，包括细胞黏附、运动、细胞内运输和细胞分裂。细胞骨架的组织已得到广泛研究，主要通过免疫荧光显微镜技术，但这些研究大多是定性的，目前仍缺乏一种可靠的定量方法来确定纤维结构和分布。
在本研究中，我们基于荧光显微镜技术开发了用于细丝特征提取的算法。这些算法对轻微散焦、高背景和噪声引起的模糊具有鲁棒性，适用于固定的免疫标记细胞和表达荧光标记细胞骨架蛋白的活细胞。所实现的FiberScore程序用于识别、分割和量化细胞骨架的各种结构参数，包括与纤维相关的总荧光以及纤维长度和方向。此外，对于用多种荧光标记标记的同一样本中的不同细胞骨架蛋白，可以确定这些参数，并且结果可以与其他细胞参数相关联。
在此使用FiberScore来量化由微管破坏药物诺考达唑诱导的微管和肌动蛋白丝的同时变化。据报道，肌动蛋白丝对微管破坏有相反的反应，发现其受到即时和延迟信号的影响。
通过FiberScore算法分析纤维组织能够量化细胞的细胞骨架特征，并为基于逐个细胞评估的药物和其他扰动的影响提供可靠的多参数功能测定。
