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Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling

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 st...

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Autores principales: Naldi, Aurélien, Carneiro, Jorge, Chaouiya, Claudine, Thieffry, Denis
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2932677/
https://www.ncbi.nlm.nih.gov/pubmed/20824124
http://dx.doi.org/10.1371/journal.pcbi.1000912
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author Naldi, Aurélien
Carneiro, Jorge
Chaouiya, Claudine
Thieffry, Denis
author_facet Naldi, Aurélien
Carneiro, Jorge
Chaouiya, Claudine
Thieffry, Denis
author_sort Naldi, Aurélien
collection PubMed
description 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 this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have 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, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico.
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spelling pubmed-29326772010-09-07 Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling Naldi, Aurélien Carneiro, Jorge Chaouiya, Claudine Thieffry, Denis PLoS Comput Biol Research Article 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 this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have 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, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico. Public Library of Science 2010-09-02 /pmc/articles/PMC2932677/ /pubmed/20824124 http://dx.doi.org/10.1371/journal.pcbi.1000912 Text en Naldi et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Naldi, Aurélien
Carneiro, Jorge
Chaouiya, Claudine
Thieffry, Denis
Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
title Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
title_full Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
title_fullStr Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
title_full_unstemmed Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
title_short Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
title_sort diversity and plasticity of th cell types predicted from regulatory network modelling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2932677/
https://www.ncbi.nlm.nih.gov/pubmed/20824124
http://dx.doi.org/10.1371/journal.pcbi.1000912
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