Stability analysis of a state-dependent delay differential equation for cell maturation: analytical and numerical methods

J Math Biol. 2019 Jul;79(1):281-328. doi: 10.1007/s00285-019-01357-0. Epub 2019 Apr 19.

Abstract

We consider a mathematical model describing the maturation process of stem cells up to fully mature cells. The model is formulated as a differential equation with state-dependent delay, where maturity is described as a continuous variable. The maturation rate of cells may be regulated by the amount of mature cells and, moreover, it may depend on cell maturity: we investigate how the stability of equilibria is affected by the choice of the maturation rate. We show that the principle of linearised stability holds for this model, and develop some analytical methods for the investigation of characteristic equations for fixed delays. For a general maturation rate we resort to numerical methods and we extend the pseudospectral discretisation technique to approximate the state-dependent delay equation with a system of ordinary differential equations. This is the first application of the technique to nonlinear state-dependent delay equations, and currently the only method available for studying the stability of equilibria by means of established software packages for bifurcation analysis. The numerical method is validated on some cases when the maturation rate is independent of maturity and the model can be reformulated as a fixed-delay equation via a suitable time transformation. We exploit the analytical and numerical methods to investigate the stability boundary in parameter planes. Our study shows some drastic qualitative changes in the stability boundary under assumptions on the model parameters, which may have important biological implications.

Keywords: Characteristic equation; Linearised stability; Progenitor phase; Pseudospectral; Stem cell; Threshold-type delay.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Differentiation*
  • Cell Self Renewal*
  • Computer Simulation
  • Models, Biological*
  • Stem Cells / physiology*
  • Time Factors