Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs)...

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Autores principales:	Martin H Schaefer, Tiago J S Lopes, Nancy Mah, Jason E Shoemaker, Yukiko Matsuoka, Jean-Fred Fontaine, Caroline Louis-Jeune, Amie J Eisfeld, Gabriele Neumann, Carol Perez-Iratxeta, Yoshihiro Kawaoka, Hiroaki Kitano, Miguel A Andrade-Navarro
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/e759ad74877144fcb8e54790c4b22681
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spelling	oai:doaj.org-article:e759ad74877144fcb8e54790c4b226812021-11-18T05:52:33ZAdding protein context to the human protein-protein interaction network to reveal meaningful interactions.1553-734X1553-735810.1371/journal.pcbi.1002860https://doaj.org/article/e759ad74877144fcb8e54790c4b226812013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23300433/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs), which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays) or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the annotated human PPI network via a web frontend that allows the construction of context-specific networks in several ways.Martin H SchaeferTiago J S LopesNancy MahJason E ShoemakerYukiko MatsuokaJean-Fred FontaineCaroline Louis-JeuneAmie J EisfeldGabriele NeumannCarol Perez-IratxetaYoshihiro KawaokaHiroaki KitanoMiguel A Andrade-NavarroPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 1, p e1002860 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Martin H Schaefer Tiago J S Lopes Nancy Mah Jason E Shoemaker Yukiko Matsuoka Jean-Fred Fontaine Caroline Louis-Jeune Amie J Eisfeld Gabriele Neumann Carol Perez-Iratxeta Yoshihiro Kawaoka Hiroaki Kitano Miguel A Andrade-Navarro Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
description	Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs), which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays) or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the annotated human PPI network via a web frontend that allows the construction of context-specific networks in several ways.
format	article
author	Martin H Schaefer Tiago J S Lopes Nancy Mah Jason E Shoemaker Yukiko Matsuoka Jean-Fred Fontaine Caroline Louis-Jeune Amie J Eisfeld Gabriele Neumann Carol Perez-Iratxeta Yoshihiro Kawaoka Hiroaki Kitano Miguel A Andrade-Navarro
author_facet	Martin H Schaefer Tiago J S Lopes Nancy Mah Jason E Shoemaker Yukiko Matsuoka Jean-Fred Fontaine Caroline Louis-Jeune Amie J Eisfeld Gabriele Neumann Carol Perez-Iratxeta Yoshihiro Kawaoka Hiroaki Kitano Miguel A Andrade-Navarro
author_sort	Martin H Schaefer
title	Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
title_short	Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
title_full	Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
title_fullStr	Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
title_full_unstemmed	Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
title_sort	adding protein context to the human protein-protein interaction network to reveal meaningful interactions.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/e759ad74877144fcb8e54790c4b22681
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Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

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