Literature DB >> 23955282

Lattice-free models of cell invasion: discrete simulations and travelling waves.

Michael J Plank1, Matthew J Simpson.   

Abstract

Invasion waves of cells play an important role in development, disease, and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation, and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction-diffusion equation that is related to the Fisher-Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction-diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice-based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high-density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice-based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher-Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.

Mesh:

Year:  2013        PMID: 23955282     DOI: 10.1007/s11538-013-9885-7

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  4 in total

1.  Spatial moment dynamics for collective cell movement incorporating a neighbour-dependent directional bias.

Authors:  Rachelle N Binny; Michael J Plank; Alex James
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

2.  The importance of volume exclusion in modelling cellular migration.

Authors:  Louise Dyson; Ruth E Baker
Journal:  J Math Biol       Date:  2014-09-28       Impact factor: 2.259

3.  How much information can be obtained from tracking the position of the leading edge in a scratch assay?

Authors:  Stuart T Johnston; Matthew J Simpson; D L Sean McElwain
Journal:  J R Soc Interface       Date:  2014-08-06       Impact factor: 4.118

4.  Modelling collective cell migration: neural crest as a model paradigm.

Authors:  Rasa Giniūnaitė; Ruth E Baker; Paul M Kulesa; Philip K Maini
Journal:  J Math Biol       Date:  2019-10-05       Impact factor: 2.259

  4 in total

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