Dataset Information

An integrative modeling framework reveals plasticity of TGF-? signaling.

ABSTRACT:

Background

The TGF-? 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-? is associated with complex signaling pathways. Differential models describe the dynamics of the TGF-? canonical pathway, but modeling the non-canonical networks constitutes a major challenge. Here, we propose a qualitative approach to explore all TGF-?-dependent signaling pathways.

Results

Using a new formalism, CADBIOM, which is based on guarded transitions and includes temporal parameters, we have built the first discrete model of TGF-? 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-? target genes reveal the association of specific pathways with distinct biological processes. We identify 31 different combinations of TGF-? with other extracellular stimuli involved in non-canonical TGF-? pathways that regulate specific gene networks. Extensive analysis of gene expression data further demonstrates that genes sharing CADBIOM trajectories tend to be co-regulated.

Conclusions

As applied here to TGF-? 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.

SUBMITTER: Andrieux G

PROVIDER: S-EPMC4007780 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Publications

An integrative modeling framework reveals plasticity of TGF-β signaling.

Andrieux Geoffroy G Le Borgne Michel M Théret Nathalie N

BMC systems biology 20140312

<h4>Background</h4>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. Here, we propose a qualitative approach to explore all TGF ...[more]

PMID: 24618419

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Project description:BackgroundThe family of TGF-? ligands is large and its members are involved in many different signaling processes. These signaling processes strongly differ in type with TGF-? ligands eliciting both sustained or transient responses. Members of the TGF-? family can also act as morphogen and cellular responses would then be expected to provide a direct read-out of the extracellular ligand concentration. A number of different models have been proposed to reconcile these different behaviours. We were interested to define the set of minimal modifications that are required to change the type of signal processing in the TGF-? signaling network.ResultsTo define the key aspects for signaling plasticity we focused on the core of the TGF-? signaling network. With the help of a parameter screen we identified ranges of kinetic parameters and protein concentrations that give rise to transient, sustained, or oscillatory responses to constant stimuli, as well as those parameter ranges that enable a proportional response to time-varying ligand concentrations (as expected in the read-out of morphogens). A combination of a strong negative feedback and fast shuttling to the nucleus biases signaling to a transient rather than a sustained response, while oscillations were obtained if ligand binding to the receptor is weak and the turn-over of the I-Smad is fast. A proportional read-out required inefficient receptor activation in addition to a low affinity of receptor-ligand binding. We find that targeted modification of single parameters suffices to alter the response type. The intensity of a constant signal (i.e. the ligand concentration), on the other hand, affected only the strength but not the type of the response.ConclusionsThe architecture of the TGF-? pathway enables the observed signaling plasticity. The observed range of signaling outputs to TGF-? ligand in different cell types and under different conditions can be explained with differences in cellular protein concentrations and with changes in effective rate constants due to cross-talk with other signaling pathways. It will be interesting to uncover the exact cellular differences as well as the details of the cross-talks in future work.