Persistent Cell Motion in the Absence of External Signals: A Search Strategy for Eukaryotic Cells

Department of Physics, Princeton University, Princeton, New Jersey, United States of America.
PLoS ONE (Impact Factor: 3.23). 02/2008; 3(5):e2093. DOI: 10.1371/journal.pone.0002093
Source: PubMed


Eukaryotic cells are large enough to detect signals and then orient to them by differentiating the signal strength across the length and breadth of the cell. Amoebae, fibroblasts, neutrophils and growth cones all behave in this way. Little is known however about cell motion and searching behavior in the absence of a signal. Is individual cell motion best characterized as a random walk? Do individual cells have a search strategy when they are beyond the range of the signal they would otherwise move toward? Here we ask if single, isolated, Dictyostelium and Polysphondylium amoebae bias their motion in the absence of external cues.
We placed single well-isolated Dictyostelium and Polysphondylium cells on a nutrient-free agar surface and followed them at 10 sec intervals for approximately 10 hr, then analyzed their motion with respect to velocity, turning angle, persistence length, and persistence time, comparing the results to the expectation for a variety of different types of random motion.
We find that amoeboid behavior is well described by a special kind of random motion: Amoebae show a long persistence time ( approximately 10 min) beyond which they start to lose their direction; they move forward in a zig-zag manner; and they make turns every 1-2 min on average. They bias their motion by remembering the last turn and turning away from it. Interpreting the motion as consisting of runs and turns, the duration of a run and the amplitude of a turn are both found to be exponentially distributed. We show that this behavior greatly improves their chances of finding a target relative to performing a random walk. We believe that other eukaryotic cells may employ a strategy similar to Dictyostelium when seeking conditions or signal sources not yet within range of their detection system.

Download full-text


Available from: Simon F Nørrelykke
  • Source
    • "Individual cells and bodies which follow these dynamics have a prevalent non-Gaussian diffusion [14]. Similar type of trajectories develop a multimodal search behavior that has been modeled and analyzed experimentally for different types of random motion [15], anomalous dynamics [16], Lévy distributions [17], intermittency [18], collective motion [19], and also by direct observation of the diatom kinematics in constrained regions [20] [21]. In this work, our viewpoint is that trajectories with more complex random walks, which are typical for cellular systems, can be approached by the underlying scaling laws of fractional dynamics [17] [22]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: We present the results of an experiment with light microscopy performed to capture the trajectories of live Nitzschia sp. diatoms. The time series corresponding to the motility of this kind of cells along ninety-five circular-like trajectories have been obtained and analyzed with the scaling statistical method of detrended fluctuation analysis optimized via a wavelet transform. In this way, we determined the Hurst parameters, in two orthogonal directions, which characterize the nature of the motion of live diatoms in light microscopy experiments. We have found mean values of these directional Hurst parameters between 0.70 and 0.63 with overall standard errors below 0.15. These numerical values give evidence that the motion of Nitzschia sp. diatoms is of persistent type and suggest an active cell motility with a kind of memory associated with long-range correlations on the path of their trajectories. For the collected statistics, we also find that the values of the Hurst exponents depend on the number of abrupt turns that occur in the diatom trajectory and on the type of wavelet, although their mean values do not change much
    Full-text · Article · Oct 2014 · Physica A: Statistical Mechanics and its Applications
  • Source
    • "where ξ(t) is a Gaussian white noise. As a general framework , the O-U process proved apt to describe some key features of microbial motion, for instance the experimentally observed persistence of velocity [3] [4]. However, the O-U process fails to recover other statistical properties of the motion, in particular the probability distribution of swimming speed P(v). "
    [Show abstract] [Hide abstract]
    ABSTRACT: The motility of microorganisms in liquid media is an important issue in active matter and it is not yet fully understood. Previous theoretical approaches dealing with the microscopic description of microbial movement have modeled the propelling force exerted by the organism as a Gaussian white noise term in the equation of motion. We present experimental results for ciliates of the genus Colpidium, which do not agree with the Gaussian white noise hypothesis. We propose a new stochastic model that goes beyond such assumption and displays good agreement with the experimental statistics of motion, such as velocity distribution and velocity autocorrelation.
    Full-text · Article · Jul 2014
  • Source
    • "Leukocyte migration in the presence and absence of a signal has been described as a random walk,23, 24, 25, 26, 27 and we considered four different random walk processes: (i) Brownian motion random walk (BM, Supplementary Equation 1), where all transitions from a given state to an other have equal probability, that is, a type of isotopic random walk; (ii) biased random walk (BRW, Supplementary Equation 2) in which the movement of a cell is influenced by drift into a specific direction; (iii) persistent random walk (PRW, Supplementary Equation 3), where the cell has a higher probability of keeping the direction from the previous step than changing the direction; and (iv) biased persistent random walk (BPRW, Supplementary Equation 4), where in addition to the persistence a certain (absolute) direction of movement is favoured.11, 12 Our models do not consider the distribution of the step length. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The recruitment and migration of macrophages and neutrophils is an important process during the early stages of the innate immune system in response to acute injury. Transgenic pu.1:EGFP zebrafish permit the acquisition of leukocyte migration trajectories during inflammation. Currently, these high-quality live-imaging data are mainly analysed using general statistics, for example, cell velocity. Here, we present a spatio-temporal analysis of the cell dynamics using transition matrices, which provide information of the type of cell migration. We find evidence that leukocytes exhibit types of migratory behaviour, which differ from previously described random walk processes. Dimethyl sulfoxide treatment decreased the level of persistence at early time points after wounding and ablated temporal dependencies observed in untreated embryos. We then use pharmacological inhibition of p38 and c-Jun N-terminal kinase mitogen-activated protein kinases to determine their effects on in vivo leukocyte migration patterns and discuss how they modify the characteristics of the cell migration process. In particular, we find that their respective inhibition leads to decreased and increased levels of persistent motion in leukocytes following wounding. This example shows the high level of information content, which can be gained from live-imaging data if appropriate statistical tools are used.Immunology and Cell Biology advance online publication, 20 November 2012; doi:10.1038/icb.2012.57.
    Full-text · Article · Nov 2012 · Immunology and Cell Biology
Show more