Collective cell migration plays essential roles in morphogenesis, wound healing, angiogenesis, and cancer invasion, yet quantitative measurement of leader–follower interaction strength and range remains challenging due to the lack of direct and scalable methods. Here, we present a microfabricated branch selection platform combined with a probabilistic analysis framework to quantitatively measure intercellular coupling in migrating single-cell trains. Cells migrate through microchannels with a width of one cell and encounter symmetric T-junctions at which each follower cell selects either the same branch as the preceding cell or the opposite branch. We show that branch selection sequences are captured by a first-order Markov process, with the resulting run length (cluster size) statistics following a geometric form determined by an interaction-dependent transition probability. This relationship enables direct estimation of an effective interaction parameter without requiring force measurements or molecular labeling. Monte Carlo simulations confirm that interaction strength is primarily encoded in run length statistics rather than overall left/right occupancy in symmetric junctions. Experiments with epithelial MDCK cells and endothelial MS-1 cells reveal distinct interaction signatures: MS-1 cells show significant repulsive coupling, whereas MDCK cells exhibit at most a weak attractive tendency at the leader-first follower interface, while rear clusters display repulsive signatures. Cluster order-resolved analysis further indicates that interaction effects are spatially localized near the front and do not propagate as sustained attraction along the train. These results establish the proposed platform as a scalable method for quantitative measurement of interaction strength and interaction localization in collective cell migration.
Ashizawa et al. (Sun,) studied this question.
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