Inference of cell-cell interactions from population density characteristics and cell trajectories on static and growing domains
Authored by Robert J H Ross, C A Yates, R E Baker
Date Published: 2015
DOI: 10.1016/j.mbs.2015.04.002
Sponsors:
United Kingdom Engineering and Physical Sciences Research Council (EPSRC)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
A key feature of cell migration is how cell movement is affected by
cell-cell interactions. Furthermore, many cell migratory processes such
as neural crest stem cell migration {[}Thomas and Erickson, 2008;
McLennan et al., 2012] occur on growing domains or in the presence of a
chemoattractant Therefore, it is important to study interactions between
migrating cells in the context of domain growth and directed motility.
Here we compare discrete and continuum models describing the spatial and
temporal evolution of a cell population for different types of cell-cell
interactions on static and growing domains. We suggest that cell-cell
interactions can be inferred from population density characteristics in
the presence of motility bias, and these population density
characteristics for different cell-cell interactions are conserved on
both static and growing domains. We also study the expected displacement
of a tagged cell, and show that different types of cell-cell
interactions can give rise to cell trajectories with different
characteristics. These characteristics are conserved in the presence of
domain growth, however, they are diminished in the presence of motility
bias. Our results are relevant for researchers who study the existence
and role of cell-cell interactions in biological systems, so far as we
suggest that different types of cell-cell interactions could be
identified from cell density and trajectory data. (C) 2015 Elsevier Inc.
All rights reserved.
Tags
Migration
models
Mechanisms
Single
Neural crest
Specification
Biology
Adhesion
Exclusion processes
Organisms