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A Semi-Automatic Method for Image Analysis of Edge Dynamics in Living Cells

机译:活细胞边缘动力学图像分析的半自动方法

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Spatial asymmetry of actin edge ruffling contributes to the process of cell polarization and directional migration, but mechanisms by which external cues control actin polymerization near cell edges remain unclear. We designed a quantitative image analysis strategy to measure the spatiotemporal distribution of actin edge ruffling. Time-lapse images of endothelial cells (ECs) expressing mRFP-actin were segmented using an active contour method. In intensity line profiles oriented normal to the cell edge, peak detection identified the angular distribution of polymerized actin within 1 mu m of the cell edge, which was localized to lamellipodia and edge ruffles. Edge features associated with filopodia and peripheral stress fibers were removed. Circular statistical analysis enabled detection of cell polarity, indicated by a unimodal distribution of edge ruffles. To demonstrate the approach, we detected a rapid, nondirectional increase in edge ruffling in serum-stimulated ECs and a change in constitutive ruffling orientation in quiescent, nonpolarized ECs. Error analysis using simulated test images demonstrate robustness of the method to variations in image noise levels, edge ruffle arc length, and edge intensity gradient. These quantitative measurements of edge ruffling dynamics enable investigation at the cellular length scale of the underlying molecular mechanisms regulating actin assembly and cell polarization.
机译:肌动蛋白边缘起伏的空间不对称性有助于细胞极化和定向迁移的过程,但外部线索控制细胞边缘附近肌动蛋白聚合的机制仍不清楚。我们设计了一种定量图像分析策略,以测量肌动蛋白边缘起伏的时空分布。使用主动轮廓方法对表达mRFP-肌动蛋白的内皮细胞(EC)的延时图像进行了分割。在垂直于细胞边缘定向的强度线轮廓中,峰检测可确定聚合的肌动蛋白在细胞边缘1微米内的角分布,该分布分布于片状脂膜和边缘褶皱。去除了与丝状伪足和周围应力纤维相关的边缘特征。循环统计分析可以检测细胞极性,边缘皱纹的单峰分布表明。为了证明这种方法,我们在血清刺激的EC中检测到边缘波纹的快速,非方向性增加,并且在静态的非极化EC中检测到本构波纹的方向发生了变化。使用模拟测试图像进​​行的误差分析证明了该方法对图像噪声水平,边缘褶皱弧长和边缘强度梯度变化的鲁棒性。这些对边缘起伏动力学的定量测量使得能够在调节肌动蛋白组装和细胞极化的潜在分子机制的细胞长度尺度上进行研究。

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