Models

Dataset Information

0

Schliemann2011_TNF_ProAntiApoptosis


ABSTRACT: This model is from the article: Heterogeneity Reduces Sensitivity of Cell Death for TNF-Stimuli Schliemann M, Bullinger E, Borchers S, Allgower F, Findeisen R, Scheurich P. BMC Syst Biol. 2011 Dec 28;5(1):204. 22204418 , Abstract: BACKGROUND: Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate membrane receptor, TNF receptor type 1 (TNF-R1), the proinflammatory cytokine Tumor Necrosis Factor (TNF) activates pro-apoptotic signaling via caspase activation, but at the same time also stimulates nuclear factor kappaB (NF-kappaB)-mediated survival pathways. Differential dose-response relationships of these two major TNF signaling pathways have been described experimentally and using mathematical modeling. However, the quantitative analysis of the complex interplay between pro- and anti-apoptotic signaling pathways is an open question as it is challenging for several reasons: the overall signaling network is complex, various time scales are present, and cells respond quantitatively and qualitatively in a heterogeneous manner. RESULTS: This study analyzes the complex interplay of the crosstalk of TNF-R1 induced pro- and anti-apoptotic signaling pathways based on an experimentally validated mathematical model. The mathematical model describes the temporal responses on both the single cell level as well as the level of a heterogeneous cell population, as observed in the respective quantitative experiments using TNF-R1 stimuli of different strengths and durations. Global sensitivity of the heterogeneous population was quantified by measuring the average gradient of time of death versus each population parameter. This global sensitivity analysis uncovers the concentrations of Caspase-8 and Caspase-3, and their respective inhibitors BAR and XIAP, as key elements for deciding the cell's fate. A simulated knockout of the NF-kappaB-mediated anti-apoptotic signaling reveals the importance of this pathway for delaying the time of death, reducing the death rate in the case of pulse stimulation and significantly increasing cell-to-cell variability. CONCLUSIONS: Cell ensemble modeling of a heterogeneous cell population including a global sensitivity analysis presented here allowed us to illuminate the role of the different elements and parameters on apoptotic signaling. The receptors serve to transmit the external stimulus; procaspases and their inhibitors control the switching from life to death, while NF-kappaB enhances the heterogeneity of the cell population. The global sensitivity analysis of the cell population model further revealed an unexpected impact of heterogeneity, i.e. the reduction of parametric sensitivity. Note: SBML model generated from Matlab system description on 12-July-2011 21:08:15 by exportSBML Copyright Eric Bullinger 2007-2011

SUBMITTER: Monica Schliemann  

PROVIDER: BIOMD0000000407 | BioModels | 2012-01-16

REPOSITORIES: BioModels

altmetric image

Publications

Heterogeneity reduces sensitivity of cell death for TNF-stimuli.

Schliemann Monica M   Bullinger Eric E   Borchers Steffen S   Allgöwer Frank F   Findeisen Rolf R   Scheurich Peter P  

BMC systems biology 20111228


<h4>Background</h4>Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate membrane receptor, TNF receptor type 1 (TNF-R1), the proinflammatory cytokine Tumor Necrosis Factor (TNF) activates pro-apoptotic signaling via caspase activation, but at the same time also stimulates nuclear factor κB (NF-κB)-mediated survival pathways. Differential dose-response relationships  ...[more]

Similar Datasets

2011-12-30 | GSE26129 | GEO
| E-GEOD-26129 | biostudies-arrayexpress
| E-MTAB-1900 | biostudies-arrayexpress
2020-02-20 | GSE128247 | GEO
2020-02-20 | GSE128248 | GEO
2008-09-17 | GSE12787 | GEO
| PRJNA807815 | ENA
| E-MTAB-13416 | biostudies-arrayexpress
| PRJNA482003 | ENA
| E-GEOD-12787 | biostudies-arrayexpress