Network Modeling Approach to Predict Myofibroblast Differentiation

Cell Mol Bioeng. 2014 Sep;7(3):446-459. doi: 10.1007/s12195-014-0344-9. Epub 2014 Jul 6.

Abstract

Fibrotic disease is a major cause of morbidity and mortality and is characterized by the transition of resident fibroblast cells into active myofibroblasts, identified by their expression of alpha smooth muscle actin. Myofibroblast differentiation is regulated by growth factor signaling and mechanical signals transduced through integrins, which converge at focal adhesion proteins (Src and FAK) and MAPK signaling, but lead to divergent outcomes. While details are known about individual pathways, little is known about their interactions. To this end, an ODE-based model of this cell signaling network was developed in parallel with in vitro experiments to analyze potential mechanisms of crosstalk and regulation of αSMA production. We found that cells lacking Src or FAK produce significantly less or more αSMA than wild type cells, respectively. Transforming growth factor beta 1 and fibroblast growth factor signal through ERK and MAPK p38 with different dynamic profiles to increase or decrease αSMA expression, respectively. Our model effectively recreated αSMA expression levels across a set of 22 experimental conditions and matched some features of transient phosphorylation of ERK and p38. These results support a potential mechanism for regulation of fibroblast differentiation: αSMA production is promoted by active p38 and Src and opposed by ERK.

Keywords: Alpha-smooth muscle actin (αSMA); Extracellular signaling-related kinase (ERK); Fibroblast growth factor (FGF); Focal adhesion kinase (FAK); Integrin; Src; Transforming growth factor beta (TGF-β1); p38.