Exponential Distribution of Locomotion Activity in Cell Cultures

Czirók, András; Schlett, Katalin; Madarász, Emı́lia; Vicsek, Tamás

doi:10.1103/physrevlett.81.3038

Cited by 100 publications

(98 citation statements)

References 25 publications

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“…At long times, however, it will tend to a Gaussian distribution, as the central limit theorem requires. So, we see that, provided our window of experimental times cannot reach the asymptotic regime t κ −1 an exponential decay of the velocities will be found, as observed in [10,33]. This cannot explain, however, why power-law tails have been observed in other experimental works.…”

Section: D) Speed and Velocity Distributionsmentioning

confidence: 59%

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Persistent random motion: Uncovering cell migration dynamics

Campos

Méndez

Llopis

2010

Journal of Theoretical Biology

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In this paper we study analytically the stick-slip models recently introduced to explain the stochastic migration of free cells. We show that persistent motion of cells of many different types is compatible with stochastic reorientation models which admit an analytical mesoscopic treatment. This is proved by examining and discussing experimental data compiled from different sources in the literature, and by fitting some of these results too. We are able to explain many of the 'apparently complex' migration patterns obtained recently from cell tracking data, like powerlaw dependences in the mean square displacement or non-Gaussian behavior for the kurtosis and the velocity distributions, which depart from the predictions of the classical Ornstein-Uhlenbeck process.

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Section: D) Speed and Velocity Distributionsmentioning

confidence: 59%

“…To be more specific, one of the components of the velocity (for example, v x ) is observed to exhibit this unexpected behavior [8,10,25,26,33]. This is clearly a departure from the OU process, where all the components of the velocity are Gaussian variables.…”

Section: D) Speed and Velocity Distributionsmentioning

confidence: 99%

Persistent random motion: Uncovering cell migration dynamics

Campos

Méndez

Llopis

2010

Journal of Theoretical Biology

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“…2A), and the average single-cell distribution from one experiment displays a distinct non-Gaussian tail (Fig. 2B) that has previously been shown to be a general feature of non-sheet-forming motile cells (37). The existence of similar non-Gaussian single-cell speed distributions suggests by the central limit theorem that each cell does not have an inherent velocity scale, but rather that cell speed is a dependent variable.…”

Section: Resultsmentioning

confidence: 85%

“…This is shown below through a number of statistical tests. Although simpler theoretical models have been presented in the past with the objective of investigating certain traits of the collective migration phenomena (21,22,37,(42)(43)(44)(45), none of these models is able to simultaneously account for a wide variety of the migration data such as ours, and our model thus provides one of the simplest ways of incorporating all of our observations in a physically transparent formulation.…”

Section: Resultsmentioning

confidence: 99%

Migration of cells in a social context

Vedel

Tay

Johnston

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

103

104

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In multicellular organisms and complex ecosystems, cells migrate in a social context. Whereas this is essential for the basic processes of life, the influence of neighboring cells on the individual remains poorly understood. Previous work on isolated cells has observed a stereotypical migratory behavior characterized by short-time directional persistence with long-time random movement. We discovered a much richer dynamic in the social context, with significant variations in directionality, displacement, and speed, which are all modulated by local cell density. We developed a mathematical model based on the experimentally identified "cellular traffic rules" and basic physics that revealed that these emergent behaviors are caused by the interplay of single-cell properties and intercellular interactions, the latter being dominated by a pseudopod formation bias mediated by secreted chemicals and pseudopod collapse following collisions. The model demonstrates how aspects of complex biology can be explained by simple rules of physics and constitutes a rapid test bed for future studies of collective migration of individual cells.cell migration | single-cell analysis | physical modeling | microfluidics C ollective migration, from migrating cells in tissue (1-3) to swarming insects (4) to flocks of birds (5) and pedestrians in heavy traffic (6), constitutes one of the most fascinating spectacles in nature. In addition to its aesthetic qualities, social cell migration is involved in embryonic development (7), wound healing (8), and immune response (9), and unregulated migration leads to disease, including cancer metastasis (10). Previous work on single-cell migration has focused on isolated (11)(12)(13)(14)(15)(16)(17)(18)(19)(20) or strongly polarized and aligning (21, 22) cell types, mostly using population-averaged bulk assays (23) or simple observations in a social context (2, 3). However, strongly cross-correlated cell motion and collective substrate deformation has been found to arise in mechanically interlinked cells transmitting forces through both cell-cell linkages and the substrate (24-29). These studies revealed useful information on cell migration, but because in general the relevant interactions in a social context and their relative importance are not established, migratory behavior of cells in a social context remains as one of the major unresolved problems in biology (30). Furthermore, striking social effects such as highly sensitive collective responses in a number of sensing systems [e.g., quorum sensing (31, 32) and onset of collective behavior in Dictyostelium discoideum (33)] mediated by increased levels of cell-secreted signals in higher cell density indicate that mechanical links are not necessary for collective behavior. At the subcellular level, many types of nonswimming motile cells involved in multicellular biology [e.g., fibroblasts, Dictyostelium, and neutrophils (13,14,(16)(17)(18)] have been found to transmit traction force to the substrate by intracellularly polymerizing their cytoskeleton...

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“…Since then, several problems involving cell movement have been addressed by computational means, including neuron displacement (4-6), flagellar movement (7), migration of tumor cells (8), congregation at point sources of food (9), sperm displacement (10)(11)(12)(13)(14)(15), white blood cell motion (16), and chromosome movement (17). The investigation by Czir ok (18) represents one of the few approaches to general cell movement considering large databases, which resulted in the interesting verification that the cumulative velocity magnitudes follow an exponential distribution. Interesting results regarding 3D trajectory characterization have been reported by Crenshaw (19).…”

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confidence: 99%

An integrated approach to the characterization of cell movement

2005

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Background: Most phenomena in developmental biology involve or depend upon cell migration. This article describes a comprehensive framework for the characterization and analysis of trajectories defined by cell movement. The following two perspectives are considered: (a) the behavior of each individual cell and (b) interactions between neighboring pairs of cells. Methods: The measurements considered for individual trajectories include the velocity magnitude and orientation, maximum spatial dispersion, displacement effectiveness, and displacement entropies. Interactions between two trajectories are characterized by comparing the respective velocities.

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Exponential Distribution of Locomotion Activity in Cell Cultures

Cited by 100 publications

References 25 publications

Persistent random motion: Uncovering cell migration dynamics

Persistent random motion: Uncovering cell migration dynamics

Migration of cells in a social context

An integrated approach to the characterization of cell movement

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