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

PLoS Comput Biol. 2013;9(1):e1002860. doi: 10.1371/journal.pcbi.1002860. Epub 2013 Jan 3.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alzheimer Disease / metabolism
  • Biocatalysis
  • Humans
  • Phosphorylation
  • Protein Binding
  • Proteins / metabolism*
  • Proteome
  • Signal Transduction
  • Viral Proteins / metabolism

Substances

  • Proteins
  • Proteome
  • Viral Proteins

Grant support

This work was supported by the Japanese Science and Technology Agency (JST, project ERATO Kawaoka), by the German Ministry of Education and Research (BMBF, grant number 01GS08170), by the Helmholtz Alliance in Systems Biology (Germany), and by United States National Institute of Allergy and Infectious Disease Public Health Service research grants. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.