An integrative model of FGF2-induced signaling and muscle cell proliferation

This work is dedicated to a computational framework for predicting FGF2-induced cell proliferation in bovine satellite cells by integrating mechanistic and statistical modeling approaches covering signaling events up to the point of nuclear translocation of key effectors. The model advances previous studies by introducing a third signaling pathway, p38, alongside the established ERK and Akt pathways, to capture a more comprehensive view of signaling dynamics. Sensitivity and stability analyses are performed to assess the system's robustness, specifically its ability to return to equilibrium following perturbations in initial conditions and kinetic parameters, and to identify key regulatory components. At the experimental level, the effects of media additives such as BSA (Bovine Serum Albumin), fetuin, and FGF2 on cell proliferation are explored using linear models, providing statistical insights into their contributions and interactions. To connect intracellular signaling with population-level dynamics, we propose an integrative model that incorporates time-dependent signaling features into a logistic-type population growth formulation. The model predicts cell proliferation based on simulated signaling outputs (area under curves and time-to-peak of pERK, pAkt, and Pp38) alongside experimentally controlled media components. The model's predictive accuracy is assessed using experimental data across multiple cell lines of bovine satellite cells, demonstrating its ability to capture both within cell line variability and overall proliferation trends. This combination of mechanistic and statistical techniques may provide a robust framework for predicting cellular responses while addressing the challenge of modeling biological processes.