Cell Image Velocimetry (CIV): boosting the automated quantification of cell migration in wound healing assays
Cell Image Velocimetry (CIV): boosting the automated quantification of cell migration in wound healing assays
复制标题
DOI：
10.1039/c2ib20113e
复制
发表时间：
2012-11-01
影响因子：
2.5
通讯作者：
Koumoutsakos, Petros
中科院分区：
文献类型：
--
作者：
Milde, Florian;Franco, Davide;Koumoutsakos, Petros
通常通过在伤口愈合测定中跟踪细胞层界面的速度来量化细胞迁移。这种定量通常受到低信噪比的阻碍，特别是当采用复杂底物来模拟几何复杂环境中的体内细胞迁移时。此外，关于细胞运动的信息，在迁移的细胞层内容易获得，通常不会被收获。我们引入细胞图像测速（CIV），细胞层分割和图像测速算法的组合，以大大提高量化的伤口愈合试验的细胞迁移。由此产生的软件可以自动分析界面的速度以及细胞层内部的详细速度场。CIV被证明是高度鲁棒的图像具有低信噪比，低对比度和帧移位，它是便携式跨各种实验设置。CIV的模块化设计和参数化不限于伤口愈合测定，并且允许在任何光学显微镜数据集中探索和量化流动现象。在这里，我们展示了CIV的能力，在伤口愈合试验的地形工程表面和量化的相对优势，不同的对齐光栅对细胞迁移。
Cell migration is commonly quantified by tracking the speed of the cell layer interface in wound healing assays. This quantification is often hampered by low signal to noise ratio, in particular when complex substrates are employed to emulate in vivo cell migration in geometrically complex environments. Moreover, information about the cell motion, readily available inside the migrating cell layers, is not usually harvested. We introduce Cell Image Velocimetry (CIV), a combination of cell layer segmentation and image velocimetry algorithms, to drastically enhance the quantification of cell migration by wound healing assays. The resulting software analyses the speed of the interface as well as the detailed velocity field inside the cell layers in an automated fashion. CIV is shown to be highly robust for images with low signal to noise ratio, low contrast and frame shifting and it is portable across various experimental settings. The modular design and parametrization of CIV is not restricted to wound healing assays and allows for the exploration and quantification of flow phenomena in any optical microscopy dataset. Here, we demonstrate the capabilities of CIV in wound healing assays over topographically engineered surfaces and quantify the relative merits of differently aligned gratings on cell migration.