Mass spectrometry-driven phosphoproteomics: patterning the systems biology mosaic
Article first published online: 2 JUL 2013
© 2013 Wiley Periodicals, Inc.
Wiley Interdisciplinary Reviews: Developmental Biology
Volume 3, Issue 1, pages 83–112, January/February 2014
How to Cite
Jünger, M. A. and Aebersold, R. (2014), Mass spectrometry-driven phosphoproteomics: patterning the systems biology mosaic. WIREs Dev Biol, 3: 83–112. doi: 10.1002/wdev.121
- Issue published online: 16 DEC 2013
- Article first published online: 2 JUL 2013
Protein phosphorylation is the best-studied posttranslational modification and plays a role in virtually every biological process. Phosphoproteomics is the analysis of protein phosphorylation on a proteome-wide scale, and mainly uses the same instrumentation and analogous strategies as conventional mass spectrometry (MS)-based proteomics. Measurements can be performed either in a discovery-type, also known as shotgun mode, or in a targeted manner which monitors a set of a priori known phosphopeptides, such as members of a signal transduction pathway, across biological samples. Here, we delineate the different experimental levels at which measures can be taken to optimize the scope, reliability, and information content of phosphoproteomic analyses. Various chromatographic and chemical protocols exist to physically enrich phosphopeptides from proteolytic digests of biological samples. Subsequent mass spectrometric analysis revolves around peptide ion fragmentation to generate sequence information and identify the backbone sequence of phosphopeptides as well as the phosphate group attachment site(s), and different modes of fragmentation like collision-induced dissociation (CID), electron transfer dissociation (ETD), and higher energy collisional dissociation (HCD) have been established for phosphopeptide analysis. Computational tools are important for the identification and quantification of phosphopeptides and mapping of phosphorylation sites, the deposition of large-scale phosphoproteome datasets in public databases, and the extraction of biologically meaningful information by data mining, integration with other data types, and descriptive or predictive modeling. Finally, we discuss how orthogonal experimental approaches can be employed to validate newly identified phosphorylation sites on a biochemical, mechanistic, and physiological level. WIREs Dev Biol 2014, 3:83–112. doi: 10.1002/wdev.121
Conflict of interest: The author has declared no conflicts of interest for this article.
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