Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
PLoS Comput Biol. 2018 Jan 8;14(1):e1005900. doi: 10.1371/journal.pcbi.1005900. eCollection 2018 Jan.
Cell migration is a central biological process that requires fine coordination of molecular events in time and space. A deregulation of the migratory phenotype is also associated with pathological conditions including cancer where cell motility has a causal role in tumor spreading and metastasis formation. Thus cell migration is of critical and strategic importance across the complex disease spectrum as well as for the basic understanding of cell phenotype. Experimental studies of the migration of cells in monolayers are often conducted with 'wound healing' assays. Analysis of these assays has traditionally relied on how the wound area changes over time. However this method does not take into account the shape of the wound. Given the many options for creating a wound healing assay and the fact that wound shape invariably changes as cells migrate this is a significant flaw. Here we present a novel software package for analyzing concerted cell velocity in wound healing assays. Our method encompasses a wound detection algorithm based on cell confluency thresholding and employs a Bayesian approach in order to estimate concerted cell velocity with an associated likelihood. We have applied this method to study the effect of siRNA knockdown on the migration of a breast cancer cell line and demonstrate that cell velocity can track wound healing independently of wound shape and provides a more robust quantification with significantly higher signal to noise ratios than conventional analyses of wound area. The software presented here will enable other researchers in any field of cell biology to quantitatively analyze and track live cell migratory processes and is therefore expected to have a significant impact on the study of cell migration, including cancer relevant processes. Installation instructions, documentation and source code can be found at http://bowhead.lindinglab.science licensed under GPLv3.
细胞迁移是一个基本的生物学过程，需要在时间和空间上精细协调分子事件。迁移表型的失调也与病理状况有关，包括癌症，其中细胞迁移在肿瘤扩散和转移形成中起着因果作用。因此，细胞迁移在复杂疾病谱中以及对细胞表型的基本理解中都具有至关重要的战略意义。细胞在单层中迁移的实验研究通常使用“伤口愈合”测定法进行。这些测定法的分析传统上依赖于伤口面积随时间的变化。然而，这种方法没有考虑到伤口的形状。鉴于创建伤口愈合测定法的许多选择，以及随着细胞迁移伤口形状不可避免地发生变化的事实，这是一个重大缺陷。在这里，我们提出了一种用于分析伤口愈合测定中协同细胞速度的新软件包。我们的方法包括基于细胞汇合度阈值的伤口检测算法，并采用贝叶斯方法来估计协同细胞速度及其相关可能性。我们已经应用此方法研究了 siRNA 敲低对乳腺癌细胞系迁移的影响，并证明细胞速度可以独立于伤口形状跟踪伤口愈合，并提供比传统的伤口面积分析更稳健的定量分析，具有更高的信噪比。这里介绍的软件将使细胞生物学领域的其他研究人员能够定量分析和跟踪活细胞迁移过程，因此有望对细胞迁移的研究产生重大影响，包括与癌症相关的过程。安装说明、文档和源代码可在 http://bowhead.lindinglab.science 上找到，许可证为 GPLv3。
