Contextualization procedure and modeling of monocyte specific TLR signaling.

Innate immunity is the first line of defense against invasion of pathogens. Toll-like receptor (TLR) signaling is involved in a variety of human diseases extending far beyond immune system-related diseases, affecting a number of different tissues and cell-types. Computational models often do not acc...

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Autores principales:	Maike K Aurich, Ines Thiele
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bf6019c409f34ce6b92335433c0abf7c
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spelling	oai:doaj.org-article:bf6019c409f34ce6b92335433c0abf7c2021-11-18T08:06:10ZContextualization procedure and modeling of monocyte specific TLR signaling.1932-620310.1371/journal.pone.0049978https://doaj.org/article/bf6019c409f34ce6b92335433c0abf7c2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23236359/?tool=EBIhttps://doaj.org/toc/1932-6203Innate immunity is the first line of defense against invasion of pathogens. Toll-like receptor (TLR) signaling is involved in a variety of human diseases extending far beyond immune system-related diseases, affecting a number of different tissues and cell-types. Computational models often do not account for cell-type specific differences in signaling networks. Investigation of these differences and its phenotypic implications could increase understanding of cell signaling and processes such as inflammation. The wealth of knowledge for TLR signaling has been recently summarized in a stoichiometric signaling network applicable for constraint-based modeling and analysis (COBRA). COBRA methods have been applied to investigate tissue-specific metabolism using omics data integration. Comparable approaches have not been conducted using signaling networks. In this study, we present ihsTLRv2, an updated TLR signaling network accounting for the association of 314 genes with 558 network reactions. We present a mapping procedure for transcriptomic data onto signaling networks and demonstrate the generation of a monocyte-specific TLR network. The generated monocyte network is characterized through expression of a specific set of isozymes rather than reduction of pathway contents. While further tailoring the network to a specific stimulation condition, we observed that the quantitative changes in gene expression due to LPS stimulation affected the tightly connected set of genes. Differential expression influenced about one third of the entire TLR signaling network, in particular, NF-κB activation. Thus, a cell-type and condition-specific signaling network can provide functional insight into signaling cascades. Furthermore, we demonstrate the energy dependence of TLR signaling pathways in monocytes.Maike K AurichInes ThielePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 12, p e49978 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maike K Aurich Ines Thiele Contextualization procedure and modeling of monocyte specific TLR signaling.
description	Innate immunity is the first line of defense against invasion of pathogens. Toll-like receptor (TLR) signaling is involved in a variety of human diseases extending far beyond immune system-related diseases, affecting a number of different tissues and cell-types. Computational models often do not account for cell-type specific differences in signaling networks. Investigation of these differences and its phenotypic implications could increase understanding of cell signaling and processes such as inflammation. The wealth of knowledge for TLR signaling has been recently summarized in a stoichiometric signaling network applicable for constraint-based modeling and analysis (COBRA). COBRA methods have been applied to investigate tissue-specific metabolism using omics data integration. Comparable approaches have not been conducted using signaling networks. In this study, we present ihsTLRv2, an updated TLR signaling network accounting for the association of 314 genes with 558 network reactions. We present a mapping procedure for transcriptomic data onto signaling networks and demonstrate the generation of a monocyte-specific TLR network. The generated monocyte network is characterized through expression of a specific set of isozymes rather than reduction of pathway contents. While further tailoring the network to a specific stimulation condition, we observed that the quantitative changes in gene expression due to LPS stimulation affected the tightly connected set of genes. Differential expression influenced about one third of the entire TLR signaling network, in particular, NF-κB activation. Thus, a cell-type and condition-specific signaling network can provide functional insight into signaling cascades. Furthermore, we demonstrate the energy dependence of TLR signaling pathways in monocytes.
format	article
author	Maike K Aurich Ines Thiele
author_facet	Maike K Aurich Ines Thiele
author_sort	Maike K Aurich
title	Contextualization procedure and modeling of monocyte specific TLR signaling.
title_short	Contextualization procedure and modeling of monocyte specific TLR signaling.
title_full	Contextualization procedure and modeling of monocyte specific TLR signaling.
title_fullStr	Contextualization procedure and modeling of monocyte specific TLR signaling.
title_full_unstemmed	Contextualization procedure and modeling of monocyte specific TLR signaling.
title_sort	contextualization procedure and modeling of monocyte specific tlr signaling.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/bf6019c409f34ce6b92335433c0abf7c
work_keys_str_mv	AT maikekaurich contextualizationprocedureandmodelingofmonocytespecifictlrsignaling AT inesthiele contextualizationprocedureandmodelingofmonocytespecifictlrsignaling
_version_	1718422255536439296

Contextualization procedure and modeling of monocyte specific TLR signaling.

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