Adam Cliffe1,#, David P. Doupé1,#, HsinHo SUNG1,#, Isaac Kok Hwee LIM1, Kok Haur ONG1, Li CHENG2 and Weimiao YU*,1
1 Institute of Molecule and Cell Biology (IMCB), A*STAR, Singapore, 138673
2 Bioinformatics Institute (BII), A*STAR, Singapore, 138671
Published online in Nature Communication on 04 April 2017.
Please see http://www.nature.com/articles/ncomms14905
Understanding the mechanisms of collective cell migration is crucial for cancer metastasis, wound healing and many developmental processes. Imaging a migrating cluster in vivo is feasible, but the quantification of individual cell behaviors remains challenging. We have developed an image analysis toolkit, CCMToolKit, (https://sites.google.com/site/ccmtoolkit/) to quantify the Drosophila border cell system. In addition to chaotic motion, previous studies reported that the migrating cells are able to migrate in a highly coordinated pattern. We quantify the rotating and running migration modes in 3D while also observing a range of intermediate behaviors. Running mode is driven by cluster external protrusions. Rotating mode is associated with cluster internal cell extensions that could not be easily characterized. Although the cluster moves slower while rotating, individual cells retain their mobility and are in fact slightly more active than in running mode. We also show that individual cells may exchange positions during migration.
Understanding the complex single cell behavior in 3D coordinated collective cell migration. (A) Segmented nuclei with different cell identities in different colors. Two polar cells are in light and dark gray. (B) Reconstructed migrating cell surfaces in 3-D with nuclei in black and surface colors as in (B). (C) Morphology of the cells and cluster at a different time points. Black meshed surface represents the cluster external protrusion. (D) Cluster internal cell extensions are associated with cluster rotation. Blue bold arrows indicate the cluster internal cell extensions of a border cell and the red dotted arrows indicate the rotating direction of the cluster. (E-F) Probability distribution of Group Polarization and Angular Momentum of four movies with purely rotating (E) or running (F). There are 116 time points for cluster rotation and 134 time points for running. In this 2-D space, we can clearly see two distinct motion regimes, indicated by white arrows. (G-H) GMM fitting of Group Polarization and Angular Momentum of rotating (red surface) and running (blue surface). The decision boundary of these two modes, indicated by the yellow line, is the edge between the red and blue surface.
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