Modelling the interaction of keratinocytes and fibroblasts during normal and abnormal wound healing processes

Author:

Menon Shakti N.12,Flegg Jennifer A.12,McCue Scott W.1,Schugart Richard C.3,Dawson Rebecca A.2,McElwain D. L. Sean12

Affiliation:

1. School of Mathematical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland 4001, Australia

2. Tissue Repair and Regeneration Program, Institute of Health and Biomedical Innovation, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland 4001, Australia

3. Department of Mathematics and Computer Science, Western Kentucky University, 1906 College Heights Boulevard, Bowling Green, KY 42101-1078, USA

Abstract

The crosstalk between fibroblasts and keratinocytes is a vital component of the wound healing process, and involves the activity of a number of growth factors and cytokines. In this work, we develop a mathematical model of this crosstalk in order to elucidate the effects of these interactions on the regeneration of collagen in a wound that heals by second intention. We consider the role of four components that strongly affect this process: transforming growth factor- β , platelet-derived growth factor, interleukin-1 and keratinocyte growth factor. The impact of this network of interactions on the degradation of an initial fibrin clot, as well as its subsequent replacement by a matrix that is mainly composed of collagen, is described through an eight-component system of nonlinear partial differential equations. Numerical results, obtained in a two-dimensional domain, highlight key aspects of this multifarious process, such as re-epithelialization. The model is shown to reproduce many of the important features of normal wound healing. In addition, we use the model to simulate the treatment of two pathological cases: chronic hypoxia, which can lead to chronic wounds; and prolonged inflammation, which has been shown to lead to hypertrophic scarring. We find that our model predictions are qualitatively in agreement with previously reported observations and provide an alternative pathway for gaining insight into this complex biological process.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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