Alternative cell differentiation pathways are believed to arise from the concerted action of signalling pathways and transcriptional regulatory networks. However, the prediction of mammalian cell differentiation from the knowledge of the presence of specific signals and transcriptional factors is still a daunting challenge. In this respect, the vertebrate hematopoietic system, with its many branching differentiation pathways and cell types, is a compelling case study.
In [1], it is proposed an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, it is relied on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, it is used an original model reduction approach [2], together with a stable state identification algorithm [3]. To assess the effects of heterogeneous environments on Th cell differentiation, it is performed a systematic series of simulations, considering various prototypic environments.
Consequently, it is identified stable states corresponding to canonical Th1, Th2, Th17 and Treg subtypes, but these were found to coexist with other transient hybrid cell types that co-express combinations of Th1, Th2, Treg and Th17 markers in an environment-dependent fashion. In the process, the logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, this logical model can be used to explore novel differentiation pathways in silico.
References
- . 2010. Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling. PLoS Computational Biology. 6(9):e1000912.
- . 2011. Dynamically consistent reduction of logical regulatory graphs. Theoretical Computer Science. 412(21):2207-2218.
- . 2007. Decision Diagrams for the Representation and Analysis of Logical Models of Genetic Networks. Computational Methods in Systems Biology. 4695:233-247.