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Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement
Cytokines such as TNF and FASL can trigger death or survival depending on cell lines and cellular conditions. The mechanistic details of how a cell chooses among these cell fates are still unclear. The understanding of these processes is important since they are altered in many diseases, including c...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2832675/ https://www.ncbi.nlm.nih.gov/pubmed/20221256 http://dx.doi.org/10.1371/journal.pcbi.1000702 |
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author | Calzone, Laurence Tournier, Laurent Fourquet, Simon Thieffry, Denis Zhivotovsky, Boris Barillot, Emmanuel Zinovyev, Andrei |
author_facet | Calzone, Laurence Tournier, Laurent Fourquet, Simon Thieffry, Denis Zhivotovsky, Boris Barillot, Emmanuel Zinovyev, Andrei |
author_sort | Calzone, Laurence |
collection | PubMed |
description | Cytokines such as TNF and FASL can trigger death or survival depending on cell lines and cellular conditions. The mechanistic details of how a cell chooses among these cell fates are still unclear. The understanding of these processes is important since they are altered in many diseases, including cancer and AIDS. Using a discrete modelling formalism, we present a mathematical model of cell fate decision recapitulating and integrating the most consistent facts extracted from the literature. This model provides a generic high-level view of the interplays between NFκB pro-survival pathway, RIP1-dependent necrosis, and the apoptosis pathway in response to death receptor-mediated signals. Wild type simulations demonstrate robust segregation of cellular responses to receptor engagement. Model simulations recapitulate documented phenotypes of protein knockdowns and enable the prediction of the effects of novel knockdowns. In silico experiments simulate the outcomes following ligand removal at different stages, and suggest experimental approaches to further validate and specialise the model for particular cell types. We also propose a reduced conceptual model implementing the logic of the decision process. This analysis gives specific predictions regarding cross-talks between the three pathways, as well as the transient role of RIP1 protein in necrosis, and confirms the phenotypes of novel perturbations. Our wild type and mutant simulations provide novel insights to restore apoptosis in defective cells. The model analysis expands our understanding of how cell fate decision is made. Moreover, our current model can be used to assess contradictory or controversial data from the literature. Ultimately, it constitutes a valuable reasoning tool to delineate novel experiments. |
format | Text |
id | pubmed-2832675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28326752010-03-11 Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement Calzone, Laurence Tournier, Laurent Fourquet, Simon Thieffry, Denis Zhivotovsky, Boris Barillot, Emmanuel Zinovyev, Andrei PLoS Comput Biol Research Article Cytokines such as TNF and FASL can trigger death or survival depending on cell lines and cellular conditions. The mechanistic details of how a cell chooses among these cell fates are still unclear. The understanding of these processes is important since they are altered in many diseases, including cancer and AIDS. Using a discrete modelling formalism, we present a mathematical model of cell fate decision recapitulating and integrating the most consistent facts extracted from the literature. This model provides a generic high-level view of the interplays between NFκB pro-survival pathway, RIP1-dependent necrosis, and the apoptosis pathway in response to death receptor-mediated signals. Wild type simulations demonstrate robust segregation of cellular responses to receptor engagement. Model simulations recapitulate documented phenotypes of protein knockdowns and enable the prediction of the effects of novel knockdowns. In silico experiments simulate the outcomes following ligand removal at different stages, and suggest experimental approaches to further validate and specialise the model for particular cell types. We also propose a reduced conceptual model implementing the logic of the decision process. This analysis gives specific predictions regarding cross-talks between the three pathways, as well as the transient role of RIP1 protein in necrosis, and confirms the phenotypes of novel perturbations. Our wild type and mutant simulations provide novel insights to restore apoptosis in defective cells. The model analysis expands our understanding of how cell fate decision is made. Moreover, our current model can be used to assess contradictory or controversial data from the literature. Ultimately, it constitutes a valuable reasoning tool to delineate novel experiments. Public Library of Science 2010-03-05 /pmc/articles/PMC2832675/ /pubmed/20221256 http://dx.doi.org/10.1371/journal.pcbi.1000702 Text en Calzone 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 Calzone, Laurence Tournier, Laurent Fourquet, Simon Thieffry, Denis Zhivotovsky, Boris Barillot, Emmanuel Zinovyev, Andrei Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement |
title | Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement |
title_full | Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement |
title_fullStr | Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement |
title_full_unstemmed | Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement |
title_short | Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement |
title_sort | mathematical modelling of cell-fate decision in response to death receptor engagement |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2832675/ https://www.ncbi.nlm.nih.gov/pubmed/20221256 http://dx.doi.org/10.1371/journal.pcbi.1000702 |
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