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Construction and analysis of a modular model of caspase activation in apoptosis

BACKGROUND: A key physiological mechanism employed by multicellular organisms is apoptosis, or programmed cell death. Apoptosis is triggered by the activation of caspases in response to both extracellular (extrinsic) and intracellular (intrinsic) signals. The extrinsic and intrinsic pathways are cha...

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Autores principales: Harrington, Heather A, Ho, Kenneth L, Ghosh, Samik, Tung, KC
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672941/
https://www.ncbi.nlm.nih.gov/pubmed/19077196
http://dx.doi.org/10.1186/1742-4682-5-26
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author Harrington, Heather A
Ho, Kenneth L
Ghosh, Samik
Tung, KC
author_facet Harrington, Heather A
Ho, Kenneth L
Ghosh, Samik
Tung, KC
author_sort Harrington, Heather A
collection PubMed
description BACKGROUND: A key physiological mechanism employed by multicellular organisms is apoptosis, or programmed cell death. Apoptosis is triggered by the activation of caspases in response to both extracellular (extrinsic) and intracellular (intrinsic) signals. The extrinsic and intrinsic pathways are characterized by the formation of the death-inducing signaling complex (DISC) and the apoptosome, respectively; both the DISC and the apoptosome are oligomers with complex formation dynamics. Additionally, the extrinsic and intrinsic pathways are coupled through the mitochondrial apoptosis-induced channel via the Bcl-2 family of proteins. RESULTS: A model of caspase activation is constructed and analyzed. The apoptosis signaling network is simplified through modularization methodologies and equilibrium abstractions for three functional modules. The mathematical model is composed of a system of ordinary differential equations which is numerically solved. Multiple linear regression analysis investigates the role of each module and reduced models are constructed to identify key contributions of the extrinsic and intrinsic pathways in triggering apoptosis for different cell lines. CONCLUSION: Through linear regression techniques, we identified the feedbacks, dissociation of complexes, and negative regulators as the key components in apoptosis. The analysis and reduced models for our model formulation reveal that the chosen cell lines predominately exhibit strong extrinsic caspase, typical of type I cell, behavior. Furthermore, under the simplified model framework, the selected cells lines exhibit different modes by which caspase activation may occur. Finally the proposed modularized model of apoptosis may generalize behavior for additional cells and tissues, specifically identifying and predicting components responsible for the transition from type I to type II cell behavior.
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spelling pubmed-26729412009-04-24 Construction and analysis of a modular model of caspase activation in apoptosis Harrington, Heather A Ho, Kenneth L Ghosh, Samik Tung, KC Theor Biol Med Model Research BACKGROUND: A key physiological mechanism employed by multicellular organisms is apoptosis, or programmed cell death. Apoptosis is triggered by the activation of caspases in response to both extracellular (extrinsic) and intracellular (intrinsic) signals. The extrinsic and intrinsic pathways are characterized by the formation of the death-inducing signaling complex (DISC) and the apoptosome, respectively; both the DISC and the apoptosome are oligomers with complex formation dynamics. Additionally, the extrinsic and intrinsic pathways are coupled through the mitochondrial apoptosis-induced channel via the Bcl-2 family of proteins. RESULTS: A model of caspase activation is constructed and analyzed. The apoptosis signaling network is simplified through modularization methodologies and equilibrium abstractions for three functional modules. The mathematical model is composed of a system of ordinary differential equations which is numerically solved. Multiple linear regression analysis investigates the role of each module and reduced models are constructed to identify key contributions of the extrinsic and intrinsic pathways in triggering apoptosis for different cell lines. CONCLUSION: Through linear regression techniques, we identified the feedbacks, dissociation of complexes, and negative regulators as the key components in apoptosis. The analysis and reduced models for our model formulation reveal that the chosen cell lines predominately exhibit strong extrinsic caspase, typical of type I cell, behavior. Furthermore, under the simplified model framework, the selected cells lines exhibit different modes by which caspase activation may occur. Finally the proposed modularized model of apoptosis may generalize behavior for additional cells and tissues, specifically identifying and predicting components responsible for the transition from type I to type II cell behavior. BioMed Central 2008-12-10 /pmc/articles/PMC2672941/ /pubmed/19077196 http://dx.doi.org/10.1186/1742-4682-5-26 Text en Copyright © 2008 Harrington et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Harrington, Heather A
Ho, Kenneth L
Ghosh, Samik
Tung, KC
Construction and analysis of a modular model of caspase activation in apoptosis
title Construction and analysis of a modular model of caspase activation in apoptosis
title_full Construction and analysis of a modular model of caspase activation in apoptosis
title_fullStr Construction and analysis of a modular model of caspase activation in apoptosis
title_full_unstemmed Construction and analysis of a modular model of caspase activation in apoptosis
title_short Construction and analysis of a modular model of caspase activation in apoptosis
title_sort construction and analysis of a modular model of caspase activation in apoptosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672941/
https://www.ncbi.nlm.nih.gov/pubmed/19077196
http://dx.doi.org/10.1186/1742-4682-5-26
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