124
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A Proteome-wide, Quantitative Survey of In Vivo Ubiquitylation Sites Reveals Widespread Regulatory Roles*

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Post-translational modification of proteins by ubiquitin is a fundamentally important regulatory mechanism. However, proteome-wide analysis of endogenous ubiquitylation remains a challenging task, and almost always has relied on cells expressing affinity tagged ubiquitin. Here we combine single-step immunoenrichment of ubiquitylated peptides with peptide fractionation and high-resolution mass spectrometry to investigate endogenous ubiquitylation sites. We precisely map 11,054 endogenous putative ubiquitylation sites (diglycine-modified lysines) on 4,273 human proteins. The presented data set covers 67% of the known ubiquitylation sites and contains 10,254 novel sites on proteins with diverse cellular functions including cell signaling, receptor endocytosis, DNA replication, DNA damage repair, and cell cycle progression. Our method enables site-specific quantification of ubiquitylation in response to cellular perturbations and is applicable to any cell type or tissue. Global quantification of ubiquitylation in cells treated with the proteasome inhibitor MG-132 discovers sites that are involved in proteasomal degradation, and suggests a nonproteasomal function for almost half of all sites. Surprisingly, ubiquitylation of about 15% of sites decreased more than twofold within four hours of MG-132 treatment, showing that inhibition of proteasomal function can dramatically reduce ubiquitylation on many sites with non-proteasomal functions. Comparison of ubiquitylation sites with acetylation sites reveals an extensive overlap between the lysine residues targeted by these two modifications. However, the crosstalk between these two post-translational modifications is significantly less frequent on sites that show increased ubiquitylation upon proteasome inhibition. Taken together, we report the largest site-specific ubiquitylation dataset in human cells, and for the first time demonstrate proteome-wide, site-specific quantification of endogenous putative ubiquitylation sites.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: not found

          The protein kinase complement of the human genome.

          G. Manning (2002)
          We have catalogued the protein kinase complement of the human genome (the "kinome") using public and proprietary genomic, complementary DNA, and expressed sequence tag (EST) sequences. This provides a starting point for comprehensive analysis of protein phosphorylation in normal and disease states, as well as a detailed view of the current state of human genome analysis through a focus on one large gene family. We identify 518 putative protein kinase genes, of which 71 have not previously been reported or described as kinases, and we extend or correct the protein sequences of 56 more kinases. New genes include members of well-studied families as well as previously unidentified families, some of which are conserved in model organisms. Classification and comparison with model organism kinomes identified orthologous groups and highlighted expansions specific to human and other lineages. We also identified 106 protein kinase pseudogenes. Chromosomal mapping revealed several small clusters of kinase genes and revealed that 244 kinases map to disease loci or cancer amplicons.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

            Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred after five doublings in the cell lines and proteins studied. Protein populations from experimental and control samples are mixed directly after harvesting, and mass spectrometric identification is straightforward as every leucine-containing peptide incorporates either all normal leucine or all Leu-d3. We have applied this technique to the relative quantitation of changes in protein expression during the process of muscle cell differentiation. Proteins that were found to be up-regulated during this process include glyceraldehyde-3-phosphate dehydrogenase, fibronectin, and pyruvate kinase M2. SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Integration of biological networks and gene expression data using Cytoscape.

              Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
                Bookmark

                Author and article information

                Journal
                Mol Cell Proteomics
                mcprot
                mcprot
                MCP
                Molecular & Cellular Proteomics : MCP
                The American Society for Biochemistry and Molecular Biology
                1535-9476
                1535-9484
                October 2011
                1 September 2011
                1 September 2011
                : 10
                : 10
                : M111.013284
                Affiliations
                [1]From the ‡Department of Proteomics, The NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark;
                [2]§Department of Proteomics and Signal Transduction, Max Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
                Author notes
                ‖ To whom correspondence should be addressed: Department of Proteomics, The NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark. E-mail: chuna.choudhary@ 123456cpr.ku.dk .

                ¶ These authors contributed equally to this work.

                Article
                M111.013284
                10.1074/mcp.M111.013284
                3205876
                21890473
                f7988a5e-41a8-495b-bbdf-f274abbe99e8
                © 2011 by The American Society for Biochemistry and Molecular Biology, Inc.

                Creative Commons Attribution Non-Commercial License applies to Author Choice Articles

                History
                : 4 August 2011
                : 31 August 2011
                Categories
                Research

                Molecular biology
                Molecular biology

                Comments

                Comment on this article