Identifying Mechanisms of Homeostatic Signaling in Fibroblast Differentiation

Hayley C Warsinske, Shanna L Ashley, Jennifer J Linderman, Bethany B Moore, Denise E Kirschner
Bulletin of Mathematical Biology 2015, 77 (8): 1556-82
Fibroblasts play an important role in the wound-healing process by generating extracellular matrix (ECM) and undergoing differentiation into myofibroblasts, but these cells can also be involved in pathologic remodeling of tissue. Nascent ECM provides a substrate for re-epithelialization to occur, restoring damaged tissue to a functional state. Dysregulation of this process can result in fibrosis--stiffening and scarring of the tissue. Current treatments cannot halt or reverse this process. The molecular mechanisms underlying fibrotic dysregulation are poorly understood, providing an untapped pool of potential therapeutic targets. Transforming growth factor-β (TGF-β) and adhesion signaling are involved in inducing fibroblast differentiation into α-smooth muscle actin (αSMA) expressing myofibroblasts, while prostaglandin E₂ (PGE₂) has been shown to antagonize TGF-β signaling; however, the temporal and mechanistic details of this relationship have not yet been fully characterized. We measured αSMA, a marker of fibroblast to myofibroblast differentiation, as a function of: TGF-β1 receptor-ligand complex internalization, PGE₂ binding, and adhesion signaling and developed a mathematical model capturing the molecular mechanisms of fibroblast differentiation. Using our model, we predict the following: Periodic dosing with PGE₂ temporarily renders fibroblasts incapable of differentiation and refractory to additional TGF-β1 stimulation; conversely, periodic dosing with TGF-β1 in the presence of PGE₂ induces a reduced signal response that can be further inhibited by the addition of more PGE₂. Controlled fibroblast differentiation is necessary for effective wound healing; however, excessive accumulation of αSMA-expressing myofibroblasts can result in fibrosis. Homeostasis of αSMA in our model requires a balance of positive and negative regulatory signals. Sensitivity analysis predicts that PGE₂ availability, TGF-β1 availability, and the rate of TGF-β1 receptor recycling each highly influence the rates of αSMA production. With this model, we are able to demonstrate that regulation of both TGF-β1 and PGE₂ signaling levels is essential for preventing fibroblast dysregulation.

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