Medical Journals

Large-scale Phosphorylation Analysis of Mouse Liver.

Authors:
  • Villén Judit
  • Beausoleil Sean A
  • Gerber Scott A
  • Gygi Steven P

From: Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA.

Proceedings of the National Academy of Sciences of the United States of America

  • Publish Date: Jan 2007
  • ISSN: 0027-8424
  • Volume: 104
  • Issue: 5
  • Pages: 1488-93
  • Medium: Print
  • Language: English
  • Citation (JAMA): Villén Judit, Beausoleil Sean A, Gerber Scott A, et al. Large-scale Phosphorylation Analysis of Mouse Liver.. Proc. Natl. Acad. Sci. U.S.A. Jan 2007;104:1488-93

Abstract

Protein phosphorylation is a complex network of signaling and regulatory events that affects virtually every cellular process. Our understanding of the nature of this network as a whole remains limited, largely because of an array of technical challenges in the isolation and high-throughput sequencing of phosphorylated species. In the present work, we demonstrate that a combination of tandem phosphopeptide enrichment methods, high performance MS, and optimized database search/data filtering strategies is a powerful tool for surveying the phosphoproteome. Using our integrated analytical platform, we report the identification of 5,635 nonredundant phosphorylation sites from 2,328 proteins from mouse liver. From this list of sites, we extracted both novel and known motifs for specific Ser/Thr kinases including a “dipolar” motif. We also found that C-terminal phosphorylation was more frequent than at any other location and that the distribution of potential kinases for these sites was unique. Finally, we identified double phosphorylation motifs that may be involved in ordered phosphorylation.

Mesh Headings (Keywords): Algorithms, Amino Acid Motifs, Amino Acid Sequence, Animals, Liver, Liver Extracts, Mass Spectrometry, Mice, Molecular Sequence Data, Peptides, Phosphorylation, Proteomics, Signal Transduction


Check for Full Text / PubMed Unique Identifier (PMID): 17242355


This abstract is part of PubMed, a service of the U.S. National Library of Medicine. PubMed includes more than 17 million citations from MEDLINE and other life science journals for biomedical articles. See Copyright and Disclaimers.

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The data herein was last updated on July 8th, 2008 and may not reflect the most current and accurate data available from NLM.


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