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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2010-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20824124/?tool=EBI |
| _version_ | 1818401736507785216 |
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| author | Aurélien Naldi Jorge Carneiro Claudine Chaouiya Denis Thieffry |
| author_facet | Aurélien Naldi Jorge Carneiro Claudine Chaouiya Denis Thieffry |
| author_sort | Aurélien Naldi |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T07:57:12Z |
| format | Article |
| id | doaj.art-345597f0b6934d768974d39581c068f5 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-14T07:57:12Z |
| publishDate | 2010-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-345597f0b6934d768974d39581c068f52022-12-21T23:10:31ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-09-0169e100091210.1371/journal.pcbi.1000912Diversity and plasticity of Th cell types predicted from regulatory network modelling.Aurélien NaldiJorge CarneiroClaudine ChaouiyaDenis ThieffryAlternative 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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20824124/?tool=EBI |
| spellingShingle | Aurélien Naldi Jorge Carneiro Claudine Chaouiya Denis Thieffry Diversity and plasticity of Th cell types predicted from regulatory network modelling. PLoS Computational Biology |
| 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 |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20824124/?tool=EBI |
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