bistability and oscillations in the huang-ferrell model of mapk signaling双稳态和振荡huang-ferrell mapk信号模型.pdf

Bistability and Oscillations in the Huang-Ferrell Model of MAPK Signaling 1 2 1,3 1,4* Liang Qiao , Robert B. Nachbar , Ioannis G. Kevrekidis , Stanislav Y. Shvartsman 1 Department of Chemical Engineering, Princeton University, Princeton, New Jersey, United States of America, 2 Applied Computer Science and Mathematics, Merck Research Laboratories, Rahway, New Jersey, United States of America, 3 Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America, 4 Lewis-Sigler Institute for Integrative Genomics, Princeton, New Jersey, United States of America Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this level of uncertainty, model analysis should emphasize statistics of systems-level properties, rather than the detailed structure of solutions or boundaries separating different dynamic regimes. Based on the combination of random parameter search and continuation algorithms, we developed a methodology for the statistical analysis of mechanistic signaling models. In applying it to the well-studied MAPK cascade model, we discovered a large region of oscillations and explained their emergence from single-stage bistability. The surprising abundance of strongly nonlinear (oscillatory and bistable) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures.