An algorithm to quantify correlated collective cell migration behavior. (February 2013)

• Record Type: Journal Article
• Authors: Slater, Benjamin; Londono, Camila; McGuigan, Alison P.
• Is Part Of: Biotechniques. Volume 54:Number 2(2013)
• Page Start: 87
• Page End: 92
• Publication Date: 2013-02
• Subjects: collective cell migration -- correlation algorithm -- cellular monolayer -- wound healing; Biology, Experimental -- Periodicals; Molecular biology -- Periodicals; Medical technology -- Periodicals; Biology, Experimental; Medical technology; Molecular biology; Clinical Laboratory Techniques -- Periodicals; Research -- Periodicals; Medical Laboratory Science -- Periodicals; Periodicals; Electronic journals; 570
• DOI: 10.2144/000113990
• Languages: English
• ISSNs: 0736-6205

Abstract

Collective cell migration is an important process that determines cell reorganization in a number of biological events such as development and regeneration. Random cell reorganization within a confluent monolayer is a popular in vitro model system for understanding the mechanisms that underlie coordination between neighboring cells during collective motion. Here we describe a simple automated C ++ algorithm to quantify the width of streams of correlated cells moving within monolayers. Our method is efficient and allows analysis of thousands of cells in under a minute; analysis of large data sets is therefore possible without limitations due to computational time, a common analysis bottleneck. Furthermore, our method allows characterization of the variability in correlated stream widths among a cell monolayer. We quantify stream width in the human retinal epithelial cell line ARPE-19 and the fibroblast cell line BJ, and find that for both cell types, stream widths within the monolayer vary in size significantly with a peak width of 40 µm, corresponding to a width of approximately two cells. Our algorithm provides a novel analytical tool to quantify and analyze correlated cell movement in confluent sheets at a population level and to assess factors that impact coordinated collective cell migration.