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Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages

BACKGROUND: Release of immuno-regulatory cytokines and chemokines during inflammatory response is mediated by a complex signaling network. Multiple stimuli produce different signals that generate different cytokine responses. Current knowledge does not provide a complete picture of these signaling p...

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Detalles Bibliográficos
Autores principales: Pradervand, Sylvain, Maurya, Mano R, Subramaniam, Shankar
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1431720/
https://www.ncbi.nlm.nih.gov/pubmed/16507166
http://dx.doi.org/10.1186/gb-2006-7-2-r11
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author Pradervand, Sylvain
Maurya, Mano R
Subramaniam, Shankar
author_facet Pradervand, Sylvain
Maurya, Mano R
Subramaniam, Shankar
author_sort Pradervand, Sylvain
collection PubMed
description BACKGROUND: Release of immuno-regulatory cytokines and chemokines during inflammatory response is mediated by a complex signaling network. Multiple stimuli produce different signals that generate different cytokine responses. Current knowledge does not provide a complete picture of these signaling pathways. However, using specific markers of signaling pathways, such as signaling proteins, it is possible to develop a 'coarse-grained network' map that can help understand common regulatory modules for various cytokine responses and help differentiate between the causes of their release. RESULTS: Using a systematic profiling of signaling responses and cytokine release in RAW 264.7 macrophages made available by the Alliance for Cellular Signaling, an analysis strategy is presented that integrates principal component regression and exhaustive search-based model reduction to identify required signaling factors necessary and sufficient to predict the release of seven cytokines (G-CSF, IL-1α, IL-6, IL-10, MIP-1α, RANTES, and TNFα) in response to selected ligands. This study provides a model-based quantitative estimate of cytokine release and identifies ten signaling components involved in cytokine production. The models identified capture many of the known signaling pathways involved in cytokine release and predict potentially important novel signaling components, like p38 MAPK for G-CSF release, IFNγ- and IL-4-specific pathways for IL-1a release, and an M-CSF-specific pathway for TNFα release. CONCLUSION: Using an integrative approach, we have identified the pathways responsible for the differential regulation of cytokine release in RAW 264.7 macrophages. Our results demonstrate the power of using heterogeneous cellular data to qualitatively and quantitatively map intermediate cellular phenotypes.
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spelling pubmed-14317202006-04-07 Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages Pradervand, Sylvain Maurya, Mano R Subramaniam, Shankar Genome Biol Research BACKGROUND: Release of immuno-regulatory cytokines and chemokines during inflammatory response is mediated by a complex signaling network. Multiple stimuli produce different signals that generate different cytokine responses. Current knowledge does not provide a complete picture of these signaling pathways. However, using specific markers of signaling pathways, such as signaling proteins, it is possible to develop a 'coarse-grained network' map that can help understand common regulatory modules for various cytokine responses and help differentiate between the causes of their release. RESULTS: Using a systematic profiling of signaling responses and cytokine release in RAW 264.7 macrophages made available by the Alliance for Cellular Signaling, an analysis strategy is presented that integrates principal component regression and exhaustive search-based model reduction to identify required signaling factors necessary and sufficient to predict the release of seven cytokines (G-CSF, IL-1α, IL-6, IL-10, MIP-1α, RANTES, and TNFα) in response to selected ligands. This study provides a model-based quantitative estimate of cytokine release and identifies ten signaling components involved in cytokine production. The models identified capture many of the known signaling pathways involved in cytokine release and predict potentially important novel signaling components, like p38 MAPK for G-CSF release, IFNγ- and IL-4-specific pathways for IL-1a release, and an M-CSF-specific pathway for TNFα release. CONCLUSION: Using an integrative approach, we have identified the pathways responsible for the differential regulation of cytokine release in RAW 264.7 macrophages. Our results demonstrate the power of using heterogeneous cellular data to qualitatively and quantitatively map intermediate cellular phenotypes. BioMed Central 2006 2006-02-20 /pmc/articles/PMC1431720/ /pubmed/16507166 http://dx.doi.org/10.1186/gb-2006-7-2-r11 Text en Copyright © 2006 Pradervand et al.; licensee BioMed Central Ltd.
spellingShingle Research
Pradervand, Sylvain
Maurya, Mano R
Subramaniam, Shankar
Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages
title Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages
title_full Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages
title_fullStr Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages
title_full_unstemmed Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages
title_short Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages
title_sort identification of signaling components required for the prediction of cytokine release in raw 264.7 macrophages
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1431720/
https://www.ncbi.nlm.nih.gov/pubmed/16507166
http://dx.doi.org/10.1186/gb-2006-7-2-r11
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