Effects of 3D geometries on cellular gradient sensing and polarization
Name
nihms802371.pdf
Size
733.93 KB
Format
Adobe PDF
Checksum (MD5)
f4a33a474447138c0795c7ecf392904d
Author(s) • • • •
Andasari, Vivi
Zaman, Muhammad H
Spill, Fabian
Mak, Michael
Kamm, Roger Dale
Date Issued
June 2016
Journal
Physical Biology
Publisher
IOP Publishing
Citation
Spill, Fabian et al. “Effects of 3D Geometries on Cellular Gradient Sensing and Polarization.” Physical Biology 13, 3 (June 2016): 036008 © 2016 IOP Publishing Ltd
Version
Author's final manuscript
Abstract
During cell migration, cells become polarized, change their shape, and move in response to various internal and external cues. Cell polarization is defined through the spatio-temporal organization of molecules such as PI3K or small GTPases, and is determined by intracellular signaling networks. It results in directional forces through actin polymerization and myosin contractions. Many existing mathematical models of cell polarization are formulated in terms of reaction-diffusion systems of interacting molecules, and are often defined in one or two spatial dimensions. In this paper, we introduce a 3D reaction-diffusion model of interacting molecules in a single cell, and find that cell geometry has an important role affecting the capability of a cell to polarize, or change polarization when an external signal changes direction. Our results suggest a geometrical argument why more roundish cells can repolarize more effectively than cells which are elongated along the direction of the original stimulus, and thus enable roundish cells to turn faster, as has been observed in experiments. On the other hand, elongated cells preferentially polarize along their main axis even when a gradient stimulus appears from another direction. Furthermore, our 3D model can accurately capture the effect of binding and unbinding of important regulators of cell polarization to and from the cell membrane. This spatial separation of membrane and cytosol, not possible to capture in 1D or 2D models, leads to marked differences of our model from comparable lower-dimensional models.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1088/1478-3975/13/3/036008