Mathematical model of activation of transforming growth factor - β1 with application to liver fibrosis progression

• المؤلف الرئيسي: Venkatraman, Lakshmi
• مؤلفون آخرون: Sourav Saha Bhowmick
• التنسيق: Theses and Dissertations
• اللغة: English
• منشور في: 2014
• الموضوعات: DRNTU::Engineering::Computer science and engineering
• الوصول للمادة أونلاين: http://hdl.handle.net/10356/60570
• المؤسسة: Nanyang Technological University

Transforming growth factor-β1 (TGF-β1) plays important roles in diverse cellular programs and extracellular activation of TGF-β1 from its latent form is an important stage in its physiological regulation. Plasmin has long been accepted as an activator of TGF-β1, but experimental data using in vivo fibrosis models, indicates that plasmin can negatively regulate TGF-β1 levels. In an effort to understand the role of plasmin in TGF-β1 activation, we first built a computational model of plasmin activation by urokinase. Ordinary differential equations were constructed to model the conversion of precursor plasminogen into active plasmin. Computational simulations and bifurcation analysis predicted a bistable system which was tested using cell-free experiments with recombinant proteins. Our results indicated that ultrasensitive, bistable activation of urokinase-plasmin is possible in the presence of substrate competition. We next built a computational model including both plasmin activation and plasmin mediated TGF-β1 activation. We find in computational modeling that at a systems level, plasmin can cause a cooperative, switch-like decrease in TGF-β1 activation. Model predictions were tested using co-culture models of hepatocytes and hepatic stellate cells treated with plasminogen. Treated cells displayed decreased activation of TGF-β1 with sigmoidal dose-response and hysteresis. This decline was accompanied by degradation of thrombospondin-1, an important physiological activator of TGF-β1 that can be cleaved by plasmin. Antagonistic interplay between plasmin and thrombospondin-1 is an important feature of our model, and is confirmed by our experiments. These results suggest novel mechanisms and hidden pitfalls for addressing TGFβ-related diseases, and provide a new explanation for a puzzling behavior in fibrosis.