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Systematic analysis of protein phosphorylation networks from phosphoproteomic data.

ABSTRACT: In eukaryotes, hundreds of protein kinases (PKs) specifically and precisely modify thousands of substrates at specific amino acid residues to faithfully orchestrate numerous biological processes, and reversibly determine the cellular dynamics and plasticity. Although over 100,000 phosphorylation sites (p-sites) have been experimentally identified from phosphoproteomic studies, the regulatory PKs for most of these sites still remain to be characterized. Here, we present a novel software package of iGPS for the prediction of in vivo site-specific kinase-substrate relations mainly from the phosphoproteomic data. By critical evaluations and comparisons, the performance of iGPS is satisfying and better than other existed tools. Based on the prediction results, we modeled protein phosphorylation networks and observed that the eukaryotic phospho-regulation is poorly conserved at the site and substrate levels. With an integrative procedure, we conducted a large-scale phosphorylation analysis of human liver and experimentally identified 9719 p-sites in 2998 proteins. Using iGPS, we predicted a human liver protein phosphorylation networks containing 12,819 potential site-specific kinase-substrate relations among 350 PKs and 962 substrates for 2633 p-sites. Further statistical analysis and comparison revealed that 127 PKs significantly modify more or fewer p-sites in the liver protein phosphorylation networks against the whole human protein phosphorylation network. The largest data set of the human liver phosphoproteome together with computational analyses can be useful for further experimental consideration. This work contributes to the understanding of phosphorylation mechanisms at the systemic level, and provides a powerful methodology for the general analysis of in vivo post-translational modifications regulating sub-proteomes.

SUBMITTER: Song C

PROVIDER: S-EPMC3494146 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Systematic analysis of protein phosphorylation networks from phosphoproteomic data.

Song Chunxia C Ye Mingliang M Liu Zexian Z Cheng Han H Jiang Xinning X Han Guanghui G Songyang Zhou Z Tan Yexiong Y Wang Hongyang H Ren Jian J Xue Yu Y Zou Hanfa H

Molecular & cellular proteomics : MCP 20120713 10

In eukaryotes, hundreds of protein kinases (PKs) specifically and precisely modify thousands of substrates at specific amino acid residues to faithfully orchestrate numerous biological processes, and reversibly determine the cellular dynamics and plasticity. Although over 100,000 phosphorylation sites (p-sites) have been experimentally identified from phosphoproteomic studies, the regulatory PKs for most of these sites still remain to be characterized. Here, we present a novel software package o ...[more]

PMID: 22798277

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Project description:BackgroundSparganosis caused by Spirometra erinaceieuropaei spargana is a zoonotic parasitic infection that has been reported in many countries, including China, Japan, Thailand and Korea, as well as European countries and the USA. The biological and clinical significance of the parasite have previously been reported. Although the genomic and transcriptomic analysis of S. erinaceieuropaei provided insightful views about the development and pathogenesis of this species, little knowledge has been acquired in terms of post-translational regulation that is essential for parasite growth, development and reproduction. Here, we performed site-specific phosphoproteomic profiling, with an aim to obtain primary information about the global phosphorylation status of spargana.ResultsA total of 3228 phosphopeptides and 3461 phosphorylation sites were identified in 1758 spargana proteins. The annotated phosphoproteins were involved in a variety of biological pathways, including cellular (28%), metabolic (20%) and single-organism (17%) processes. The functional enrichment of phosphopeptides by Gene Ontology analysis indicated that most spargana phosphoproteins were related to the cytoskeleton cellular compartment, signaling molecular function, and a variety of biological processes, including a molecular function regulator, guanyl-nucleotide exchange factor activity, protein kinase activities, and calcium ion binding. The highly enriched pathways of phosphorylation proteins include the phosphatidylinositol signaling system, phagosome, endocytosis, inositol phosphate metabolism, terpenoid backbone biosynthesis, and peroxisome. Domain analysis identified an EF-hand domain and pleckstrin homology domain among the key domains.ConclusionsTo our knowledge, this study performed the first global phosphoproteomic analysis of S. erinaceieuropaei. The dataset reported herein provides a valuable resource for future studies on the signaling pathways of this important zoonotic parasite.

Project description:BackgroundA major goal in the discovery of cellular signaling networks is to identify regulated phosphorylation sites ("phosphosites") and map them to the responsible protein kinases. The V2 vasopressin receptor is a G-protein coupled receptor (GPCR) that is responsible for regulation of renal water excretion through control of aquaporin-2-mediated osmotic water transport in kidney collecting duct cells. Genome editing experiments have demonstrated that virtually all vasopressin-triggered phosphorylation changes are dependent on protein kinase A (PKA), but events downstream from PKA are still obscure.MethodsHere, we used: 1) Tandem mass tag-based quantitative phosphoproteomics to experimentally track phosphorylation changes over time in native collecting ducts isolated from rat kidneys; 2) a clustering algorithm to classify time course data based on abundance changes and the amino acid sequences surrounding the phosphosites; and 3) Bayes' Theorem to integrate the dynamic phosphorylation data with multiple prior "omic" data sets covering expression, subcellular location, known kinase activity, and characteristic surrounding sequences to identify a set of protein kinases that are regulated secondary to PKA activation.ResultsPhosphoproteomic studies revealed 185 phosphosites regulated by vasopressin over 15 min. The resulting groups from the cluster algorithm were integrated with Bayes' Theorem to produce corresponding ranked lists of kinases likely responsible for each group. The top kinases establish three PKA-dependent protein kinase modules whose regulation mediate the physiological effects of vasopressin at a cellular level. The three modules are 1) a pathway involving several Rho/Rac/Cdc42-dependent protein kinases that control actin cytoskeleton dynamics; 2) mitogen-activated protein kinase and cyclin-dependent kinase pathways that control cell proliferation; and 3) calcium/calmodulin-dependent signaling.ConclusionsOur findings identify a novel set of downstream small GTPase effectors and calcium/calmodulin-dependent kinases with potential roles in the regulation of water permeability through actin cytoskeleton rearrangement and aquaporin-2 trafficking. The proposed signaling network provides a stronger hypothesis for the kinases mediating V2 vasopressin receptor responses, encouraging future targeted examination via reductionist approaches. Furthermore, the Bayesian analysis described here provides a template for investigating signaling via other biological systems and GPCRs. Video abstract.

Project description:BackgroundPhosphorylation is a ubiquitous and fundamental regulatory mechanism that controls signal transduction in living cells. The number of identified phosphoproteins and their phosphosites is rapidly increasing as a result of recent mass spectrometry-based approaches.ResultsWe analyzed time-course phosphoproteome data obtained previously by liquid chromatography mass spectrometry with the stable isotope labeling using amino acids in cell culture (SILAC) method. This provides the relative phosphorylation activities of digested peptides at each of five time points after stimulating HeLa cells with epidermal growth factor (EGF). We initially calculated the correlations between the phosphorylation dynamics patterns of every pair of peptides and connected the strongly correlated pairs to construct a network. We found that peptides extracted from the same intracellular fraction (nucleus vs. cytoplasm) tended to be close together within this phosphorylation dynamics-based network. The network was then analyzed using graph theory and compared with five known signal-transduction pathways. The dynamics-based network was correlated with known signaling pathways in the NetPath and Phospho.ELM databases, and especially with the EGF receptor (EGFR) signaling pathway. Although the phosphorylation patterns of many proteins were drastically changed by the EGF stimulation, our results suggest that only EGFR signaling transduction was both strongly activated and precisely controlled.ConclusionsThe construction of a phosphorylation dynamics-based network provides a useful overview of condition-specific intracellular signal transduction using quantitative time-course phosphoproteome data under specific experimental conditions. Detailed prediction of signal transduction based on phosphoproteome dynamics remains challenging. However, since the phosphorylation profiles of kinase-substrate pairs on the specific pathway were localized in the dynamics-based network, our method will be a complementary strategy to explore new components of protein signaling pathways in combination with previous methods (including software) of predicting direct kinase-substrate relationships.

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Systematic analysis of protein phosphorylation networks from phosphoproteomic data.

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Systematic analysis of protein phosphorylation networks from phosphoproteomic data.

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