Modeling Active Cell Movement With the Potts Model
In the last decade, the cellular Potts model has been extensively used to model interacting cell systems at the tissue-level. However, in early applications of this model, cell movement was taken as a consequence of membrane fluctuations due to cell-cell interactions, or as a response to an external...
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doaj-ff13419122de4a769e3ba5a4c4605ab02020-11-25T02:28:45ZengFrontiers Media S.A.Frontiers in Physics2296-424X2018-06-01610.3389/fphy.2018.00061367945Modeling Active Cell Movement With the Potts ModelNara Guisoni0Karina I. Mazzitello1Luis Diambra2INIFTA, Universidad Nacional de La Plata - CONICET, La Plata, ArgentinaInstituto de Investigaciones Científicas y Tecnológicas en Electrónica, Universidad Nacional de Mar del Plata - CONICET, Mar del Plata, ArgentinaCentro Regional de Estudios Genómicos, Universidad Nacional de La Plata - CONICET, La Plata, ArgentinaIn the last decade, the cellular Potts model has been extensively used to model interacting cell systems at the tissue-level. However, in early applications of this model, cell movement was taken as a consequence of membrane fluctuations due to cell-cell interactions, or as a response to an external chemotactic gradient. Recent findings have shown that eukaryotic cells can exhibit persistent displacements across scales larger than cell size, even in the absence of external signals. Persistent cell motion has been incorporated to the cellular Potts model by many authors in the context of collective motion, chemotaxis and morphogenesis. In this paper, we use the cellular Potts model in combination with a random field applied over each cell. This field promotes a uniform cell motion in a given direction during a certain time interval, after which the movement direction changes. The dynamics of the direction is coupled to a first order autoregressive process. We investigated statistical properties, such as the mean-squared displacement and spatio-temporal correlations, associated to these self-propelled in silico cells in different conditions. The proposed model emulates many properties observed in different experimental setups. By studying low and high density cultures, we find that cell-cell interactions decrease the effective persistent time.https://www.frontiersin.org/article/10.3389/fphy.2018.00061/fullcell motilitycellular Potts modelcell-cell interactionsrandom walkcell adhesion |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nara Guisoni Karina I. Mazzitello Luis Diambra |
spellingShingle |
Nara Guisoni Karina I. Mazzitello Luis Diambra Modeling Active Cell Movement With the Potts Model Frontiers in Physics cell motility cellular Potts model cell-cell interactions random walk cell adhesion |
author_facet |
Nara Guisoni Karina I. Mazzitello Luis Diambra |
author_sort |
Nara Guisoni |
title |
Modeling Active Cell Movement With the Potts Model |
title_short |
Modeling Active Cell Movement With the Potts Model |
title_full |
Modeling Active Cell Movement With the Potts Model |
title_fullStr |
Modeling Active Cell Movement With the Potts Model |
title_full_unstemmed |
Modeling Active Cell Movement With the Potts Model |
title_sort |
modeling active cell movement with the potts model |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Physics |
issn |
2296-424X |
publishDate |
2018-06-01 |
description |
In the last decade, the cellular Potts model has been extensively used to model interacting cell systems at the tissue-level. However, in early applications of this model, cell movement was taken as a consequence of membrane fluctuations due to cell-cell interactions, or as a response to an external chemotactic gradient. Recent findings have shown that eukaryotic cells can exhibit persistent displacements across scales larger than cell size, even in the absence of external signals. Persistent cell motion has been incorporated to the cellular Potts model by many authors in the context of collective motion, chemotaxis and morphogenesis. In this paper, we use the cellular Potts model in combination with a random field applied over each cell. This field promotes a uniform cell motion in a given direction during a certain time interval, after which the movement direction changes. The dynamics of the direction is coupled to a first order autoregressive process. We investigated statistical properties, such as the mean-squared displacement and spatio-temporal correlations, associated to these self-propelled in silico cells in different conditions. The proposed model emulates many properties observed in different experimental setups. By studying low and high density cultures, we find that cell-cell interactions decrease the effective persistent time. |
topic |
cell motility cellular Potts model cell-cell interactions random walk cell adhesion |
url |
https://www.frontiersin.org/article/10.3389/fphy.2018.00061/full |
work_keys_str_mv |
AT naraguisoni modelingactivecellmovementwiththepottsmodel AT karinaimazzitello modelingactivecellmovementwiththepottsmodel AT luisdiambra modelingactivecellmovementwiththepottsmodel |
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