title: Elucidation of Signaling Pathways from Large-Scale Phosphoproteomic Data Using Protein Interaction Networks.
abstract: Phosphoproteomic experiments typically identify sites within a protein that are differentially phosphorylated between two or more cell states. However, the interpretation of these data is hampered by the lack of methods that can translate site-specific information into global maps of active proteins and signaling networks, especially as the phosphoproteome is often undersampled. Here, we describe PHOTON, a method for interpreting phosphorylation data within their signaling context, as captured by protein-protein interaction networks, to identify active proteins and pathways and pinpoint functional phosphosites. We apply PHOTON to interpret existing and novel phosphoproteomic datasets related to epidermal growth factor and insulin responses. PHOTON substantially outperforms the widely used cutoff approach, providing highly reproducible predictions that are more in line with current biological knowledge. Altogether, PHOTON overcomes the fundamental challenge of delineating signaling pathways from large-scale phosphoproteomic data, thereby enabling translation of environmental cues to downstream cellular responses.
authors.affiliation: Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, 69978 Tel Aviv, Israel; Blavatnik School of Computer Sciences, Tel Aviv University, 69978 Tel Aviv, Israel.
authors.forename: Jan Daniel
authors.initials: JD
authors.lastname: Rudolph
authors.affiliation: Division of Toxicology, Leiden Amsterdam Center for Drug Research, Leiden University, 2311 Leiden, the Netherlands.
authors.forename: Marjo
authors.initials: M
authors.lastname: de Graauw
authors.affiliation: Division of Toxicology, Leiden Amsterdam Center for Drug Research, Leiden University, 2311 Leiden, the Netherlands.
authors.forename: Bob
authors.initials: B
authors.lastname: van de Water
authors.affiliation: Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, 69978 Tel Aviv, Israel. Electronic address: geiger@tauex.tau.ac.il.
authors.forename: Tamar
authors.initials: T
authors.lastname: Geiger
authors.affiliation: Blavatnik School of Computer Sciences, Tel Aviv University, 69978 Tel Aviv, Israel. Electronic address: roded@post.tau.ac.il.
authors.forename: Roded
authors.initials: R
authors.lastname: Sharan
keywords: mass spectrometry; phosphorylation; protein interaction networks; proteomics; signal transduction