Identifying the mechanism for superdiffusivity in mouse fibroblast motility

Giuseppe Passucci, Megan E Brasch, James H Henderson, Vasily Zaburdaev and M Lisa Manning

PLOS Computational Biology, 2019, vol. 15, issue 2, 1-15

Abstract: We seek to characterize the motility of mouse fibroblasts on 2D substrates. Utilizing automated tracking techniques, we find that cell trajectories are super-diffusive, where displacements scale faster than t1/2 in all directions. Two mechanisms have been proposed to explain such statistics in other cell types: run and tumble behavior with Lévy-distributed run times, and ensembles of cells with heterogeneous speed and rotational noise. We develop an automated toolkit that directly compares cell trajectories to the predictions of each model and demonstrate that ensemble-averaged quantities such as the mean-squared displacements and velocity autocorrelation functions are equally well-fit by either model. However, neither model correctly captures the short-timescale behavior quantified by the displacement probability distribution or the turning angle distribution. We develop a hybrid model that includes both run and tumble behavior and heterogeneous noise during the runs, which correctly matches the short-timescale behaviors and indicates that the run times are not Lévy distributed. The analysis tools developed here should be broadly useful for distinguishing between mechanisms for superdiffusivity in other cells types and environments.Author summary: Cells must move through their environment in many different biological processes, from wound healing to cancer invasion to the development of an embryo. There are different ways for cells to explore the physical space around them—ranging from moving along a straight path at constant speed to executing a random walk where the cell changes direction at every time point. Understanding what mechanisms are driving motility patterns in different cell types is important for identifying possible treatments for disease. We found that mouse fibroblast cells moving on a two-dimensional substrate were super-diffusive, meaning that they were able to cover distance faster than a random walk but not as fast as a straight walk. Traditional analysis of cell trajectories was not well-suited to distinguish between different possible mechanisms for super-diffusivity, so we developed a new tool to examine cell trajectories and distinguish between mechanisms. We found that mouse fibroblasts were super-diffusive due to a combination of large fluctuations in speed and “run-and-tumble” behavior, where cells move in a straight line for a while before changing direction rapidly. We expect this tool to be useful for analyzing motion in many other cell types.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1006732

DOI: 10.1371/journal.pcbi.1006732

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