Fig. 4
Msn regulates cortical stiffness. a Schematic representation explaining how the curvature analysis was performed by the ADAPT plugin of ImageJ. This analysis calculates the curvature at each pixel of the cell boundary as the angle (θ) subtended by vectors (v1 and v2) to two points n pixels away in each direction, for every time points. We represented the outcome as a heat map (positive curvature in red and negative curvature in blue) consisting of the kymograph of the different calculated curvatures. b Segmental curvatures calculated for each pixel at each time points are color-coded (red colors, positive curvature/convex; blue colors, negative curvatures/concave) and represented as a kymograph for control and Msn-depleted clusters. c Schematic representation of the curvatures observed in b. Extreme concave areas are restricted to the front of migration in the control clusters whereas they are found simultaneously at several positions of Msn-depleted clusters. d Cluster sphericity of control and Msn-depleted clusters (n = 21 and 17 independent BC clusters, respectively). e Representation of threshold curvature maps to highlight strong positive curvatures (>80o). Such curvatures are shown in black, while others are displayed in white. Events of strong positive curvature are automatically detected and indicated by purple asterisks at the front of the cluster and by green asterisks on the side of the cluster. f Quantification of the number of strong positive curvature events formed at the front and at the side of control and Msn-depleted clusters (n = 6 and 8 independent BC clusters, respectively). g Quantification of the strong positive curvature event lifetimes at the front and at the side of control and Msn-depleted clusters (n = 6 and eight independent BC clusters, respectively). *p < 0.05; ***p < 0.001, unpaired Student’s t-test. Error bars show s.e.m
