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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Detalles Bibliográficos
Autores principales: Guisoni, Nara Cristina, Mazzitello, Karina Irma, Diambra, Luis Aníbal
Formato: Articulo
Lenguaje:Inglés
Publicado: 2018
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/98114
https://ri.conicet.gov.ar/11336/84898
https://www.frontiersin.org/articles/10.3389/fphy.2018.00061/full
Aporte de:SEDICI (UNLP) de Universidad Nacional de La Plata Ver origen
Descripción
Sumario: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 <i>in silico</i> 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.