Abstract
Living cells actively migrate in their environment to perform key biological functions—from unicellular organisms looking for food to single cells such as fibroblasts, leukocytes or cancer cells that can shape, patrol or invade tissues. Cell migration results from complex intracellular processes that enable cell self-propulsion, and has been shown to also integrate various chemical or physical extracellular signals. While it is established that cells can modify their environment by depositing biochemical signals or mechanically remodelling the extracellular matrix, the impact of such self-induced environmental perturbations on cell trajectories at various scales remains unexplored. Here, we show that cells can retrieve their path: by confining motile cells on 1D and 2D micropatterned surfaces, we demonstrate that they leave long-lived physicochemical footprints along their way, which determine their future path. On this basis, we argue that cell trajectories belong to the general class of self-interacting random walks, and show that self-interactions can rule large scale exploration by inducing long-lived ageing, subdiffusion and anomalous first-passage statistics. Altogether, our joint experimental and theoretical approach points to a generic coupling between motile cells and their environment, which endows cells with a spatial memory of their path and can dramatically change their space exploration.
Highlights
Cell migration is essential for fundamental phases of development and adult life, including embryogenesis, wound healing, and inflammatory responses[1]; it generically results from the active dynamics of its intracellular components—most prominently the cytoskeleton—which generate propulsion forces and determine the cell front-rear polarity[2,3]
Both observed behaviours were approximately distributed over the cell population, whereas behaviours that did not fall in these two classes – akin to persistent random motion – remained negligible. These observations were qualitatively unchanged upon varying the width of the track over a range comparable to a single cell size, W = 10, 20, 50 μm (Fig. 1h and Supplementary Fig. 1a–c) and were recovered with cells that were not treated with mitomycin C, in the latter case cells had to be tracked for shorter times (Supplementary Fig. 13)
Long-term consequences of spatial memory. We show both theoretically and experimentally that the reported interaction of cells with their footprint, which endows cells with a memory of their path, has important consequences on space exploration properties of cell trajectories. (i) First, the time dependent increments defined by I(T, t) ≡ 〈[x(t + T) − x(T)]2〉, which quantify the spreading speed of trajectories, are found to depend on the measurement time T at all time scales, ie to display ageing, in both 1D and 2D set-ups and in agreement with the 1D persistent self-attracting walk (PSATW) model and the 2D Self-Attracting Walk (SATW) model (Fig. 4a, b, d, e—note that cell to cell variability and fluctuations of cell speed were taken into account in the numerical simulations of the 1D PSATW model, see SI)
Summary
Cell migration is essential for fundamental phases of development and adult life, including embryogenesis, wound healing, and inflammatory responses[1]; it generically results from the active dynamics of its intracellular components—most prominently the cytoskeleton—which generate propulsion forces and determine the cell front-rear polarity[2,3]. Cells interact with various extra-cellular environments with a broad range of biochemical and biomechanical properties[2] These interactions have been shown to be two-way: environmental cues directly affect cell shape, migration, and polarity[19,20,21], and in turn, cells actively contribute to remodel their environment[22,23]. To overcome the inherent complexity of the analysis of cell migration in 3D in vivo environments, the design of micropatterned surfaces has proven to be a powerful approach[24,25,26] In such in vitro set-ups, and especially in 1D settings, the reduced dimensionality of the cellular environment allows for an extensive quantitative analysis of the phase space roamed by migrating cells. Many of the cell migration features on a 1D substrate can mimic cell behaviour in 3D matrix[22]
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