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.
Pubmed ID: 21890473 RIS Download
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Database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)
View all literature mentionsA quantitative proteomics software package for analyzing large-scale mass-spectrometric data sets. It is a set of algorithms that include peak detection and scoring of peptides, mass calibration, database searches for protein identification, protein quantification, and provides summary statistics.
View all literature mentionsCell line HEK293T is a Transformed cell line with a species of origin Homo sapiens (Human)
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