Model for HGF/SF-induced collective motility patterns during the healing process.

<p>HGF/SF dramatically alters the morpho-dynamics of the healing wound: from a simple model, in which the front cells lead the healing in constant acceleration, to a more elaborate model in which cells in different distances from the wound lead a coordinated increased motility along with spatio-temporal phenotypic EMT-MET based collective cell motility dynamics. Untreated DA3 front layers cells are larger, more elliptical and move faster (marked by wider arrows) than cells located behind demonstrating a homogeneous motility pattern during the wound healing process (<i>Phases 1</i> and <i>2</i>). During post wound closure (<i>Phase 3</i>), all cells decelerate, shrink and round up regardless of their position. HGF/SF treatment leads to the emergence of dramatic different cell motility patterns: at the beginning, front cells are larger, more elliptical and move faster than distant cells. Throughout <i>Phase 1</i>, distant cells become larger, more elliptical and gradually join the rapid motion by accelerating layer by layer. These morphology changes and gradual acceleration continues during <i>Phase 2</i>, were distant cells maintain a higher velocity toward the wound than cells located closer to the wound edge. Finally, post wound closure (<i>Phase 3</i>), front cells shrink, round up and halt, while distant cells gradually decelerate, and change morphology in a similar manner. It is hypothesized that accelerated proliferation at the leading edge is the answer for the untreated cells gap mystery presented in the text. It is hypothesized that in treated cells proliferation occurs more intensively, but is spread approximately equally throughout the monolayer.</p

Three phases in the healing process.

<p><i>Phase 1</i>: From the first frame in the time-lapse sequence, until first contact between cells from opposing edges of the wound. <i>Phase 2</i>: until full closure of the wound. <i>Phase 3</i>: post wound closure.</p

Velocity Magnitude Maps.

<p>(a) A two-dimensional depiction of the average motility of all cells at a given distance from the wound edge (<i>y</i>-axis) at a given time (<i>x</i>-axis). Each bin (<i>t</i>,<i>d</i>) represents the average motility (µm hour⁻¹) of all cells at distance <i>d</i> from the wound at time <i>t</i>. Examples of two representative velocity magnitude maps are shown: untreated and HGF/SF-treated. The two vertical lines in each map define the partition to the three phases in the healing process. (b) The maps constructed from single-cell tracking. Examples of untreated and HGF/SF-treated cells are displayed. Comparison with the corresponding multi-cellular maps reveals that this approach provides a significant advantage over single-cell analysis. (c) Single cell tracking at several distances from the wound. Only the velocity component toward the wound is considered.</p

Motility patterns.

<p>(a–b) “Average” cell tracking toward the wound, and the displacement gap mystery. An “average” cell’s velocity at a given time and distance from the wound is defined as the average velocity component toward the wound in the strip that corresponds to the relevant location. The distance that an "average" cell travels in each frame (retrieved from the corresponding velocity fields) was accumulated to define its displacement as function of time. The <i>x</i>-axis represents time; the <i>y</i>-axis represents the “average” cell’s displacement toward the wound at several spatial locations. For untreated cells (a) it is demonstrated that front cells accumulate an expanding displacement gap over distant cells during healing. For HGF/SF-treated “average” cell tracking (b). A gap is formed between front and distant cells; however, during <i>Phase 2</i> it is shown that cells from behind progressively accelerate so that the displacement-gap formed at <i>Phase 1</i> shrinks for distant cells. (c–d) Untreated cells (c) exhibit roughly constant velocity toward the wound, whereas close cells are faster than farther cells. Distant HGF/SF-treated cells (d) exhibit gradual acceleration until they maintain higher velocity toward the wound than close cells in <i>Phase 2</i>.</p

Emergence of HGF/SF-Induced Coordinated Cellular Motility

<div><p>Collective cell migration plays a major role in embryonic morphogenesis, tissue remodeling, wound repair and cancer invasion. Despite many decades of extensive investigations, only few analytical tools have been developed to enhance the biological understanding of this important phenomenon. Here we present a novel quantitative approach to analyze long term kinetics of bright field time-lapse wound healing. Fully-automated spatiotemporal measures and visualization of cells' motility and implicit morphology were proven to be sound, repetitive and highly informative compared to single-cell tracking analysis. We study cellular collective migration induced by tyrosine kinase-growth factor signaling (Met-Hepatocyte Growth Factor/Scatter Factor (HGF/SF)). Our quantitative approach is applied to demonstrate that collective migration of the adenocarcinoma cell lines is characterized by simple morpho-kinetics. HGF/SF induces complex morpho-kinetic coordinated collective migration: cells at the front move faster and are more spread than those further away from the wound edge. As the wound heals, distant cells gradually accelerate and enhance spread and elongation –resembling the epithelial to mesenchymal transition (EMT), and then the cells become more spread and maintain higher velocity than cells located closer to the wound. Finally, upon wound closure, front cells halt, shrink and round up (resembling mesenchymal to epithelial transition (MET) phenotype) while distant cells undergo the same process gradually. Met inhibition experiments further validate that Met signaling dramatically alters the morpho-kinetic dynamics of the healing wound. Machine-learning classification was applied to demonstrate the generalization of our findings, revealing even subtle changes in motility patterns induced by Met-inhibition. It is concluded that activation of Met-signaling induces an elaborated model in which cells lead a coordinated increased motility along with gradual differentiation-based collective cell motility dynamics. Our quantitative phenotypes may guide future investigation on the molecular and cellular mechanisms of tyrosine kinase-induced coordinate cell motility and morphogenesis in metastasis.</p> </div

Single cell morphology (area) as function of time and distance from the wound.

<p>(a) “Average” cell’s area at different distances over time. Untreated (left), and HGF/SF-treated (right) cells. The x-coordinates represent discrete distance-intervals from the wound edge, the y-coordinates are the average cells’ size at a given distance interval and at a given phase in the healing process. Color markers represent the phase in the healing process: from the initial scratch until first contact between cells from opposing borders of the wound (<i>Phase 1</i>, red), until full closure (<i>Phase 2</i>, green), post wound closure (<i>Phase 3</i>, pale blue), and last frame in the time lapse sequence (∼26 hours after the initial scratch, dark blue). The analysis demonstrates that HGF/SF induces dramatic morphological changes at the single cell level. (b) Relation between cells density and speed for untreated (left) and treated (right) cells. The cells’ density is estimated at two spatial location <248 µm (marked red), and >248 µm (marked green) from the wound edge. Based on the single cell’s area statistical analysis, speed was calculated in the same distance intervals from the velocity magnitude map. Correlation significance between velocity and density was calculated with the non-parametric Spearman's rank correlation coefficient. This analysis demonstrates a significant correlation between density and velocity with no dependency on the spatial location. This correlation is less prominent for treated cells (p<0.003, compared to p<0.0001 for untreated cells) although still statistically significant.</p

Generalization: multi-cellular speed- and texture-based classification.

<p>(a) Velocity magnitude-based vector-representation of a full time lapse sequence. Each column represents a single experiment. The vector values were calculated as the average velocity magnitude of all cells at a given distance-interval from the wound, at a given phase. The analysis demonstrates that the first six experiments (untreated) are very different from the last five (HGF/SF-treated). (b) Texture-based vector-representation of a full time lapse sequence. The LBP image-texture descriptor normalized histogram is averaged over all time frames from <i>Phase 2</i>, when most morphological changes occur. Each column is the LBP histogram extracted from a single experiment. It was demonstrated that there exists a clear discrimination between any pair of the three conditions: untreated, HGF/SF, and Met inhibition+ HGF/SF. (c) Example of a velocity magnitude map of cells treated with Met inhibition and HGF/SF. (d) Collective motility patterns of full time lapse experiments. Each column represents the normalized spatio-temporal velocity magnitude of a single experiment. It was demonstrated that there exists a clear discrimination in collective motility patterns between any pair of the three conditions: untreated, HGF/SF, and Met inhibition + HGF/SF, as Met-signaling becomes more active, the ratio between motility of distant cells and close cells decreases which implies that cells located farther from the wound become more active by Met-signaling activation.</p

Multi-cellular DIC based single cell trajectory estimation.

<p>(a) Visual comparison of manually tracked cells (green) and automated trajectories extracted from local DIC-based motion estimation (red). It is shown that the automated trajectories are highly correlated to the manually-validated trajectories. Examples of untreated (left pane) and HGF/SF-treated (right pane) are illustrated. (b) Visual illustration of the advantage in using all cells' information in comparison to part of the cells. Green trajectories are the manually-validated trajectories, red are trajectories extracted by our method. Left pane - untreated cells, right pane - treated cells.</p

Radial patterns of cell dynamics in neural rosettes.

<p><b>A.</b> Combined <i>HES5</i>::<i>eGFP</i> (green) reporter expression and immunostaining of the cortical neural progenitor marker PAX6 (red) throughout NSC progression from unstructured neuroepithelial cells (top), to early radial glial (E-RG) rosettes (middle) to mid radial glial (M-RG) rosettes (bottom). Nuclei are stained with DAPI (blue). Rosette contours are marked in white. Scale bars: 25 μm. HES5::eGFP co-localizes with PAX6+ nuclei, attesting a NSC stage. E-RG rosettes contain multiple radially organized GFP+/PAX6+ nuclei, whereas M-RG rosettes harbor GFP+/PAX6+ cells only close to rosette lumens, reflective of enhanced or reduced NSC numbers, respectively. Many cells in M-RG rosettes are not associated to apical sites (e.g., rosette lumens), reflecting the beginning of rosette disassembly. <b>B.</b> Representative <i>HES5</i>::<i>eGFP</i> and its matched phase contrast image from time-lapse imaging of an E-RG stage neural rosette (left panels) or a non-rosette area adjacent to a rosette (right panels). Rosette contours and center were manually annotated (white dashed marking). Scale bars: 25 μm. An image was acquired every 5 minutes for a total of 250 minutes. Rosette annotation for M-RG rosettes is shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004453#pcbi.1004453.s008" target="_blank">S1A Fig</a>. <b>C.</b> Motion patterns follow the expected radial angle. Average patch velocity orientation over time for an E-RG rosette (left, corresponding to panel B) and a non-rosette. Color code is illustrated in panel E (bottom). Radial organization is subjectively observed in E-RG rosettes, for both GFP and phase contrast, but not in non-rosettes. <b>D.</b> Distributions of angular alignment of all patches over the entire time course. INM patterns (tendency to follow the expected angle) are found for E-RG rosettes (left, mean angle of 29° for GFP, 36.4° for phase contrast) but not for non-rosettes (right, mean angle of 44.7° for GFP, 45.7° for phase contrast). <b>E.</b> Schematic sketch of angular alignment <b>γ</b>, the angle between the expected- and observed-motion (top). Color code for angles is illustrated in panel C (bottom).</p

Cytoarchitectural dynamics of neural rosettes reflects changes in NSC capabilities during cortical development.

<p>E-RG rosettes (top panel) correspond to early cortical radial glial cells (NSCs; green colored) that hold strong epithelial characteristics and hence organize in a radial manner with apical sites adjoining at rosette lumens—similarly to the ventricular zone of the developing cortex. M-RG rosettes (bottom) are characterized by decreased numbers of epithelial radial glial cells and elevated number of neurons (blue colored) and intermediate progenitors (red colored), which are both non-epithelial—hence decreasing rosette epithelial integrity and eventually lead to rosette disassembly at later stages. Both E-RG and M-RG rosettes perform INM—the hallmark of cortical radial glial development. INM of E-RG rosettes is characterized by basal (blue phase, right) and apical (red phase, right) motions that are faster (higher frequency of blue and red phases) and more radially organized (less twisted pattern of blue and red phases), compared to M-RG rosettes. However, for all rosettes regardless of developmental stage (top or bottom panels), basal motions (blue) are always slower yet more organized than apical motions (red). The enhanced radial organization of E-RG rosettes can be explained by enhanced radial organization of basal motions as well as inherent mechanism that increases both basal and apical motions, possibly due to the strong confining structure and high NSC abundance within E-RG rosettes. B→A, basal to apical; A→B, apical to basal.</p