Dynamics of TGF-β/Smad signaling

Abstract

The physiological responses to TGF-β stimulation are diverse and vary amongst different cell types and environmental conditions. Even though the principal molecular components of the canonical and the non-canonical TGF-β signaling pathways have been largely identified, the mechanism that underlies the well-established context dependent physiological responses remains a mystery. Understanding how the components of TGF-β signaling function as a system and how this system functions in the context of the global cellular regulatory network requires a more quantitative and systematic approach. Here, we review the recent progress in understanding TGF-β biology using integration of mathematical modeling and quantitative experimental analysis. These studies reveal many interesting dynamics of TGF-β signaling and how cells quantitatively decode variable doses of TGF-β stimulation.

Figure 1

Scheme of the compartmentalized TGF-β model. The kinetic parameter information is approximately estimated according to the experimental data from different cell types. The nuclear export rate constants of Smads are scaled with the ratio of cytoplasmic to nuclear volume size. It is necessary to calibrate these parameter values with quantitative data sets for modeling of TGF-β signaling responses in a specific cell type.

Figure 2

Model simulations for the time-course profile of P-Smad2 dose-response in HaCaT cells. Cells have distinct interpretations to TGF-β doses at different time scales. The early P-Smad2 signal (e.g. before 2 hour) displays a graded response to different doses of TGF-β, while the late P-Smad2 response (e.g. at 24 hour) is switch-like. The long-term ultrasensitive signaling response is critical for cellular fate decisions, for example, cell growth arrest.