Literature DB >> 24972155

A continuum approximation to an off-lattice individual-cell based model of cell migration and adhesion.

Alistair M Middleton1, Christian Fleck2, Ramon Grima3.   

Abstract

Cell-cell adhesion plays a key role in the collective migration of cells and in determining correlations in the relative cell positions and velocities. Recently, it was demonstrated that off-lattice individual cell based models (IBMs) can accurately capture the correlations observed experimentally in a migrating cell population. However, IBMs are often computationally expensive and difficult to analyse mathematically. Traditional continuum-based models, in contrast, are amenable to mathematical analysis and are computationally less demanding, but typically correspond to a mean-field approximation of cell migration and so ignore cell-cell correlations. In this work, we address this problem by using an off-lattice IBM to derive a continuum approximation which does take into account correlations. We furthermore show that a mean-field approximation of the off-lattice IBM leads to a single partial integro-differential equation of the same form as proposed by Sherratt and co-workers to model cell adhesion. The latter is found to be only effective at approximating the ensemble averaged cell number density when mechanical interactions between cells are weak. In contrast, the predictions of our novel continuum model for the time-evolution of the ensemble cell number density distribution and of the density-density correlation function are in close agreement with those obtained from the IBM for a wide range of mechanical interaction strengths. In particular, we observe 'front-like' propagation of cells in simulations using both our IBM and our continuum model, but not in the continuum model simulations obtained using the mean-field approximation.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Keywords:  Cell movement; Correlations; Langevin equations; Partial differential equations; Stochastic simulations

Mesh:

Year:  2014        PMID: 24972155     DOI: 10.1016/j.jtbi.2014.06.011

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  15 in total

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Journal:  Phys Rev E       Date:  2019-09       Impact factor: 2.529

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7.  Spatial structure arising from neighbour-dependent bias in collective cell movement.

Authors:  Rachelle N Binny; Parvathi Haridas; Alex James; Richard Law; Matthew J Simpson; Michael J Plank
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8.  Spatiotemporal Dynamics of Insulitis in Human Type 1 Diabetes.

Authors:  Kyle C A Wedgwood; Sarah J Richardson; Noel G Morgan; Krasimira Tsaneva-Atanasova
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9.  Learning differential equation models from stochastic agent-based model simulations.

Authors:  John T Nardini; Ruth E Baker; Matthew J Simpson; Kevin B Flores
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10.  BIO-LGCA: A cellular automaton modelling class for analysing collective cell migration.

Authors:  Andreas Deutsch; Josué Manik Nava-Sedeño; Simon Syga; Haralampos Hatzikirou
Journal:  PLoS Comput Biol       Date:  2021-06-15       Impact factor: 4.475

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