Xiong Yuan, Kabacoff Cathryn, Franca-Koh Jonathan, Devreotes Peter N, Robinson Douglas N, Iglesias Pablo A
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
BMC Syst Biol. 2010 Mar 24;4:33. doi: 10.1186/1752-0509-4-33.
The ability of a cell to change shape is crucial for the proper function of many cellular processes, including cell migration. One type of cell migration, referred to as amoeboid motility, involves alternating cycles of morphological expansion and retraction. Traditionally, this process has been characterized by a number of parameters providing global information about shape changes, which are insufficient to distinguish phenotypes based on local pseudopodial activities that typify amoeboid motility.
We developed a method that automatically detects and characterizes pseudopodial behavior of cells. The method uses skeletonization, a technique from morphological image processing to reduce a shape into a series of connected lines. It involves a series of automatic algorithms including image segmentation, boundary smoothing, skeletonization and branch pruning, and takes into account the cell shape changes between successive frames to detect protrusion and retraction activities. In addition, the activities are clustered into different groups, each representing the protruding and retracting history of an individual pseudopod.
We illustrate the algorithms on movies of chemotaxing Dictyostelium cells and show that our method makes it possible to capture the spatial and temporal dynamics as well as the stochastic features of the pseudopodial behavior. Thus, the method provides a powerful tool for investigating amoeboid motility.
细胞改变形状的能力对于许多细胞过程（包括细胞迁移）的正常功能至关重要。一种细胞迁移类型，称为变形虫运动，涉及形态扩张和收缩的交替循环。传统上，这个过程由一些提供有关形状变化全局信息的参数来表征，这些参数不足以根据典型变形虫运动的局部伪足活动来区分表型。
我们开发了一种自动检测和表征细胞伪足行为的方法。该方法使用骨架化，这是一种来自形态图像处理的技术，用于将形状简化为一系列连接线。它涉及一系列自动算法，包括图像分割、边界平滑、骨架化和分支修剪，并考虑连续帧之间的细胞形状变化以检测突出和收缩活动。此外，这些活动被聚类为不同的组，每个组代表单个伪足的突出和收缩历史。
我们在趋化性盘基网柄菌细胞的电影上展示了这些算法，并表明我们的方法能够捕捉伪足行为的时空动态以及随机特征。因此，该方法为研究变形虫运动提供了一个强大的工具。
