Abstract

BackgroundThe TGF-β transforming growth factor is the most pleiotropic cytokine controlling a broad range of cellular responses that include proliferation, differentiation and apoptosis. The context-dependent multifunctional nature of TGF-β is associated with complex signaling pathways. Differential models describe the dynamics of the TGF-β canonical pathway, but modeling the non-canonical networks constitutes a major challenge. Here, we propose a qualitative approach to explore all TGF-β-dependent signaling pathways.ResultsUsing a new formalism, CADBIOM, which is based on guarded transitions and includes temporal parameters, we have built the first discrete model of TGF-β signaling networks by automatically integrating the 137 human signaling maps from the Pathway Interaction Database into a single unified dynamic model. Temporal property-checking analyses of 15934 trajectories that regulate 145 TGF-β target genes reveal the association of specific pathways with distinct biological processes. We identify 31 different combinations of TGF-β with other extracellular stimuli involved in non-canonical TGF-β pathways that regulate specific gene networks. Extensive analysis of gene expression data further demonstrates that genes sharing CADBIOM trajectories tend to be co-regulated.ConclusionsAs applied here to TGF-β signaling, CADBIOM allows, for the first time, a full integration of highly complex signaling pathways into dynamic models that permit to explore cell responses to complex microenvironment stimuli.

Highlights

  • The TGF-β transforming growth factor is the most pleiotropic cytokine controlling a broad range of cellular responses that include proliferation, differentiation and apoptosis

  • Building a TGF-β Computer-Aided Design for BIOlogical Models (CADBIOM) model To translate and integrate any kind of biological reaction involved in TGF-β signaling pathways, we developed a new language, CADBIOM, based on guarded-transition formalism

  • We have developed a new formalism, CADBIOM, based on guarded transitions and combined discrete abstraction to propose, for the first time, a fully integrated model for TGF-β signaling pathways

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Summary

Introduction

The TGF-β transforming growth factor is the most pleiotropic cytokine controlling a broad range of cellular responses that include proliferation, differentiation and apoptosis. The context-dependent multifunctional nature of TGF-β is associated with complex signaling pathways. Differential models describe the dynamics of the TGF-β canonical pathway, but modeling the non-canonical networks constitutes a major challenge. We propose a qualitative approach to explore all TGF-β-dependent signaling pathways. Complex signaling by the polypeptide transforming growth factor TGF-β is one of the most intriguing networks that governs multifunctional processes and plays a pivotal role in tissue homeostasis and morphogenesis [1]. The confounding pleiotropic effects of TGF-β derive from the complex nature of its signaling, whose full characterization requires modeling approaches that are still lacking. TGF-β binding to TβRII induces the recruitment and phosphorylation

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