@article {49737, title = {Stable isotope labeling of phosphoproteins for large-scale phosphorylation rate determination.}, journal = {Mol Cell Proteomics}, volume = {13}, year = {2014}, month = {2014 Apr}, pages = {1106-18}, abstract = {

Signals that control responses to stimuli and cellular function are transmitted through the dynamic phosphorylation of thousands of proteins by protein kinases. Many techniques have been developed to study phosphorylation dynamics, including several mass spectrometry (MS)-based methods. Over the past few decades, substantial developments have been made in MS techniques for the large-scale identification of proteins and their post-translational modifications. Nevertheless, all of the current MS-based techniques for quantifying protein phosphorylation dynamics rely on the measurement of changes in peptide abundance levels, and many methods suffer from low confidence in phosphopeptide identification due to poor fragmentation. Here we have optimized an approach for the stable isotope labeling of amino acids by phosphate using [γ-{\textonesuperior}$^{8}$O$_{4}$]ATP in nucleo to determine global site-specific phosphorylation rates. The advantages of this metabolic labeling technique are increased confidence in phosphorylated peptide identification, direct labeling of phosphorylation sites, measurement phosphorylation rates, and the identification of actively phosphorylated sites in a cell-like environment. In this study we calculated approximate rate constants for over 1,000 phosphorylation sites based on labeling progress curves. We measured a wide range of phosphorylation rate constants from 0.34 min$^{-}${\textonesuperior} to 0.001 min$^{-}${\textonesuperior}. Finally, we applied stable isotope labeling of amino acids by phosphate to identify sites that have different phosphorylation kinetics during G1/S and M phase. We found that most sites had very similar phosphorylation rates under both conditions; however, a small subset of sites on proteins involved in the mitotic spindle were more actively phosphorylated during M phase, whereas proteins involved in DNA replication and transcription were more actively phosphorylated during G1/S phase. The data have been deposited to the ProteomeXchange with the identifier PXD000680.

}, keywords = {cell cycle, HEK293 Cells, HeLa Cells, HUMANS, Isotope Labeling, Kinetics, Peptide Mapping, Phosphoproteins, Phosphorylation, proteomics, Tandem Mass Spectrometry}, issn = {1535-9484}, doi = {10.1074/mcp.O113.036145}, author = {Molden, Rosalynn C and Goya, Jonathan and Khan, Zia and Garcia, Benjamin A} } @article {49736, title = {Stoichiometry of site-specific lysine acetylation in an entire proteome.}, journal = {J Biol Chem}, volume = {289}, year = {2014}, month = {2014 Aug 1}, pages = {21326-38}, abstract = {

Acetylation of lysine ϵ-amino groups influences many cellular processes and has been mapped to thousands of sites across many organisms. Stoichiometric information of acetylation is essential to accurately interpret biological significance. Here, we developed and employed a novel method for directly quantifying stoichiometry of site-specific acetylation in the entire proteome of Escherichia coli. By coupling isotopic labeling and a novel pairing algorithm, our approach performs an in silico enrichment of acetyl peptides, circumventing the need for immunoenrichment. We investigated the function of the sole NAD(+)-dependent protein deacetylase, CobB, on both site-specific and global acetylation. We quantified 2206 peptides from 899 proteins and observed a wide distribution of acetyl stoichiometry, ranging from less than 1\% up to 98\%. Bioinformatic analysis revealed that metabolic enzymes, which either utilize or generate acetyl-CoA, and proteins involved in transcriptional and translational processes displayed the highest degree of acetylation. Loss of CobB led to increased global acetylation at low stoichiometry sites and induced site-specific changes at high stoichiometry sites, and biochemical analysis revealed altered acetyl-CoA metabolism. Thus, this study demonstrates that sirtuin deacetylase deficiency leads to both site-specific and global changes in protein acetylation stoichiometry, affecting central metabolism.

}, keywords = {Acetylation, Amino Acid Sequence, Bacterial Proteins, Chromatography, High Pressure Liquid, Computational Biology, Escherichia coli, Lysine, Molecular Sequence Data, Proteome, Tandem Mass Spectrometry}, issn = {1083-351X}, doi = {10.1074/jbc.M114.581843}, author = {Baeza, Josue and Dowell, James A and Smallegan, Michael J and Fan, Jing and Amador-Noguez, Daniel and Khan, Zia and Denu, John M} } @article {49747, title = {Protein quantification across hundreds of experimental conditions.}, journal = {Proc Natl Acad Sci U S A}, volume = {106}, year = {2009}, month = {2009 Sep 15}, pages = {15544-8}, abstract = {

Quantitative studies of protein abundance rarely span more than a small number of experimental conditions and replicates. In contrast, quantitative studies of transcript abundance often span hundreds of experimental conditions and replicates. This situation exists, in part, because extracting quantitative data from large proteomics datasets is significantly more difficult than reading quantitative data from a gene expression microarray. To address this problem, we introduce two algorithmic advances in the processing of quantitative proteomics data. First, we use space-partitioning data structures to handle the large size of these datasets. Second, we introduce techniques that combine graph-theoretic algorithms with space-partitioning data structures to collect relative protein abundance data across hundreds of experimental conditions and replicates. We validate these algorithmic techniques by analyzing several datasets and computing both internal and external measures of quantification accuracy. We demonstrate the scalability of these techniques by applying them to a large dataset that comprises a total of 472 experimental conditions and replicates.

}, keywords = {algorithms, Animals, Automatic Data Processing, Chromatography, Liquid, Databases, Factual, Fungal Proteins, HUMANS, Isotopes, Mice, Proteins, proteomics, Tandem Mass Spectrometry}, issn = {1091-6490}, doi = {10.1073/pnas.0904100106}, author = {Khan, Zia and Bloom, Joshua S and Garcia, Benjamin A and Singh, Mona and Kruglyak, Leonid} }