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Biosystems. 2016 Jul;145:53-66. doi: 10.1016/j.biosystems.2016.05.012. Epub 2016 Jun 2.

On the importance of modelling the internal spatial dynamics of biological cells.

Author information

1
Department of Computer Science, University of Warwick, Coventry, West Midlands, United Kingdom. Electronic address: f.sayyid@warwick.ac.uk.
2
Department of Computer Science, University of Warwick, Coventry, West Midlands, United Kingdom. Electronic address: s.kalvala@warwick.ac.uk.

Abstract

Spatial effects such as cell shape have very often been considered negligible in models of cellular pathways, and many existing simulation infrastructures do not take such effects into consideration. Recent experimental results are reversing this judgement by showing that very small spatial variations can make a big difference in the fate of a cell. This is particularly the case when considering eukaryotic cells, which have a complex physical structure and many subtle control mechanisms, but bacteria are also interesting for the huge variation in shape both between species and in different phases of their lifecycle. In this work we perform simulations that measure the effect of three common bacterial shapes on the behaviour of model cellular pathways. To perform these experiments we develop ReDi-Cell, a highly scalable GPGPU cell simulation infrastructure for the modelling of cellular pathways in spatially detailed environments. ReDi-Cell is validated against known-good simulations, prior to its use in new work. We then use ReDi-Cell to conduct novel experiments that demonstrate the effect that three common bacterial shapes (Cocci, Bacilli and Spirilli) have on the behaviour of model cellular pathways. Pathway wavefront shape, pathway concentration gradients, and chemical species distribution are measured in the three different shapes. We also quantify the impact of internal cellular clutter on the same pathways. Through this work we show that variations in the shape or configuration of these common cell shapes alter model cell behaviour.

KEYWORDS:

GPGPU; Reaction–diffusion; Single-cell dynamics; Whole-cell simulation

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