Mathematical modelling in cell migration: tackling biochemistry in changing geometries

被引:3
|
作者
Stinner, Bjorn [1 ]
Bretschneider, Till [2 ]
机构
[1] Univ Warwick, Dept Math, Coventry CV4 7AL, W Midlands, England
[2] Univ Warwick, Dept Comp Sci, Coventry CV4 7AL, W Midlands, England
基金
英国生物技术与生命科学研究理事会;
关键词
LEVEL SET METHODS; MOTILITY; CHEMOTAXIS; DIFFUSION; ADHESION;
D O I
10.1042/BST20190311
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Directed cell migration poses a rich set of theoretical challenges. Broadly, these are concerned with (1) how cells sense external signal gradients and adapt; (2) how actin polymerisation is localised to drive the leading cell edge and Myosin-II molecular motors retract the cell rear; and (3) how the combined action of cellular forces and cell adhesion results in cell shape changes and net migration. Reaction-diffusion models for biological pattern formation going back to Turing have long been used to explain generic principles of gradient sensing and cell polarisation in simple, static geometries like a circle. In this minireview, we focus on recent research which aims at coupling the biochemistry with cellular mechanics and modelling cell shape changes. In particular, we want to contrast two principal modelling approaches: (1) interface tracking where the cell membrane, interfacing cell interior and exterior, is explicitly represented by a set of moving points in 2D or 3D space and (2) interface capturing. In interface capturing, the membrane is implicitly modelled analogously to a level line in a hilly landscape whose topology changes according to forces acting on the membrane. With the increased availability of high-quality 3D microscopy data of complex cell shapes, such methods will become increasingly important in data-driven, image-based modelling to better understand the mechanochemistry underpinning cell motion.
引用
收藏
页码:419 / 428
页数:10
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