Multiscale analysis of pattern formation via intercellular signalling

• Published in: Mathematical biosciences Vol. 231; no. 2; pp. 172 - 185
• Main Authors: O’Dea, R.D., King, J.R.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.06.2011
• Subjects: Cell Communication - physiology; Cell signalling; Computer Simulation; Differentiation; Feedback; Homogenisation; Intracellular Signaling Peptides and Proteins; Membrane Proteins - physiology; Models, Biological; Morphogenesis - physiology; Multiscale; Numerical Analysis, Computer-Assisted; Pattern formation; Receptors, Notch - physiology; Signal Transduction - physiology; Cell signalling; Pattern formation; Multiscale; Homogenisation
• ISSN: 0025-5564; 1879-3134
• DOI: 10.1016/j.mbs.2011.03.003

Lateral inhibition, a juxtacrine signalling mechanism by which a cell adopting a particular fate inhibits neighbouring cells from doing likewise, has been shown to be a robust mechanism for the formation of fine-grained spatial patterns (in which adjacent cells in developing tissues diverge to achieve contrasting states of differentiation), provided that there is sufficiently strong feedback. The fine-grained nature of these patterns poses problems for analysis via traditional continuum methods since these require that significant variation takes place only over lengthscales much larger than an individual cell and such systems have therefore been investigated primarily using discrete methods. Here, however, we apply a multiscale method to derive systematically a continuum model from the discrete Delta–Notch signalling model of Collier et al. (J.R. Collier, N.A.M. Monk, P.K. Maini, J.H. Lewis, Pattern formation by lateral inhibition with feedback: a mathematical model of Delta–Notch intercellular signalling, J. Theor. Biol., 183, 1996, 429–446) under particular assumptions on the parameters, which we use to analyse the generation of fine-grained patterns. We show that, on the macroscale, the contact-dependent juxtacrine signalling interaction manifests itself as linear diffusion, motivating the use of reaction–diffusion-based models for such cell-signalling systems. We also analyse the travelling-wave behaviour of our system, obtaining good quantitative agreement with the discrete system.