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Characterization and identification of protein O-GlcNAcylation sites with substrate specificity.

ABSTRACT: BACKGROUND: Protein O-GlcNAcylation, involving the attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues. Elucidation of O-GlcNAcylation sites on proteins is required in order to decipher its crucial roles in regulating cellular processes and aid in drug design. With an increasing number of O-GlcNAcylation sites identified by mass spectrometry (MS)-based proteomics, several methods have been proposed for the computational identification of O-GlcNAcylation sites. However, no development that focuses on the investigation of O-GlcNAcylated substrate motifs has existed. Thus, we were motivated to design a new method for the identification of protein O-GlcNAcylation sites with the consideration of substrate site specificity. RESULTS: In this study, 375 experimentally verified O-GlcNAcylation sites were collected from dbOGAP, which is an integrated resource for protein O-GlcNAcylation. Due to the difficulty in characterizing the substrate motifs by conventional sequence logo analysis, a recursively statistical method has been applied to obtain significant conserved motifs. To construct the predictive models learned from the identified substrate motifs, we adopted Support Vector Machines (SVMs). A five-fold cross validation was used to evaluate the predictive model, achieving sensitivity, specificity, and accuracy of 0.76, 0.80, and 0.78, respectively. Additionally, an independent testing set, which was really blind to the training data of predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (0.94) and outperform three other O-GlcNAcylation site prediction tools. CONCLUSION: This work proposed a computational method to identify informative substrate motifs for O-GlcNAcylation sites. The evaluation of cross validation and independent testing indicated that the identified motifs were effective in the identification of O-GlcNAcylation sites. A case study demonstrated that the proposed method could be a feasible means of conducting preliminary analyses of protein O-GlcNAcylation. We also anticipated that the revealed substrate motif may facilitate the study of extensive crosstalk between O-GlcNAcylation and phosphorylation. This method may help unravel their mechanisms and roles in signaling, transcription, chronic disease, and cancer.

SUBMITTER: Wu HY

PROVIDER: S-EPMC4290634 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Characterization and identification of protein O-GlcNAcylation sites with substrate specificity.

Wu Hsin-Yi HY Lu Cheng-Tsung CT Kao Hui-Ju HJ Chen Yi-Ju YJ Chen Yu-Ju YJ Lee Tzong-Yi TY

BMC bioinformatics 20141208

<h4>Background</h4>Protein O-GlcNAcylation, involving the attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues. Elucidation of O-GlcNAcylation sites on proteins is required in order to decipher its crucial roles in regulating cellular processes and aid in drug design. With an increasing number of O-GlcNAcylation sites identified by mass spectrometry (MS)-based proteomics, several methods have been proposed for the computational identification of ...[more]

PMID: 25521204

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Project description:Viruses infect humans and progress inside the body leading to various diseases and complications. The phosphorylation of viral proteins catalyzed by host kinases plays crucial regulatory roles in enhancing replication and inhibition of normal host-cell functions. Due to its biological importance, there is a desire to identify the protein phosphorylation sites on human viruses. However, the use of mass spectrometry-based experiments is proven to be expensive and labor-intensive. Furthermore, previous studies which have identified phosphorylation sites in human viruses do not include the investigation of the responsible kinases. Thus, we are motivated to propose a new method to identify protein phosphorylation sites with its kinase substrate specificity on human viruses. The experimentally verified phosphorylation data were extracted from virPTM--a database containing 301 experimentally verified phosphorylation data on 104 human kinase-phosphorylated virus proteins. In an attempt to investigate kinase substrate specificities in viral protein phosphorylation sites, maximal dependence decomposition (MDD) is employed to cluster a large set of phosphorylation data into subgroups containing significantly conserved motifs. The experimental human phosphorylation sites are collected from Phospho.ELM, grouped according to its kinase annotation, and compared with the virus MDD clusters. This investigation identifies human kinases such as CK2, PKB, CDK, and MAPK as potential kinases for catalyzing virus protein substrates as confirmed by published literature. Profile hidden Markov model is then applied to learn a predictive model for each subgroup. A five-fold cross validation evaluation on the MDD-clustered HMMs yields an average accuracy of 84.93% for Serine, and 78.05% for Threonine. Furthermore, an independent testing data collected from UniProtKB and Phospho.ELM is used to make a comparison of predictive performance on three popular kinase-specific phosphorylation site prediction tools. In the independent testing, the high sensitivity and specificity of the proposed method demonstrate the predictive effectiveness of the identified substrate motifs and the importance of investigating potential kinases for viral protein phosphorylation sites.

Project description:As an energy-sensitive post-translational modification, O-GlcNAcylation plays a major role in endothelial nitric oxide synthase (eNOS) activity regulation. However, effects of glucose deprivation on eNOS O-GlcNAcylation and the presence of novel O-GlcNAcylation sites of eNOS under glucose deprivation remain unknown. Hence, we aim to determine the effects of glucose deprivation on O-GlcNAcylation and novel O-GlcNAcylation sites of eNOS. Bovine aortic endothelial cells (BAECs) and Sprague-Dawley rats were induced by glucose deprivation and their eNOS O-GlcNAcylation was subjected to immunoblotting. eNOS and transfected eNOS were purified by pull-down assay and immunoprecipitation respectively. Novel O-GlcNAcylation sites of eNOS were predicted by HPLC-MS and MS/MS Ion and determined by immunoblotting. eNOS activity was detected by Elisa and isotope labeling method. In BAECs and rat thoracic aorta, low glucose-associated activation of eNOS was accompanied by elevated O-GlcNAcylation, which did not affect O-linked serine phosphorylation at 1179/1177 residues. Changes in this post-translational modification were associated with increased O-GlcNAc transferase (OGT) expression and were reversed by AMPK knockdown. Immunoblot analysis of cells expressing His-tagged wild-type human eNOS and human eNOS carrying a mutation at the Ser1177 phosphorylation site confirmed an increase in O-GlcNAcylation by glucose deprivation. A marked increase in O-GlcNAcylation indicated that eNOS contained novel O-GlcNAcylation sites that were activated by glucose deprivation. Immunoblot analysis of cells expressing His-tagged human eNOS carrying a mutation at Ser738 and Ser867 confirmed an increase in O-GlcNAcylation by glucose deprivation. Conversely, in His-tagged human eNOS carrying a mutation at Thr866, O-GlcNAcylation was unaffected by glucose deprivation. Differences in culture conditions were identified using two-way analysis of variance (ANOVA), one-way ANOVA, and unpaired Student's t-test. Glucose deprivation increases O-GlcNAcylation and activity of eNOS, potentially by the AMPK-OGT pathway, suggesting that Thr866 is a novel O-GlcNAcylation site involved in glucose-deprivation mediated eNOS activation.

Project description:BACKGROUND:Glutarylation, the addition of a glutaryl group (five carbons) to a lysine residue of a protein molecule, is an important post-translational modification and plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified glutarylated peptides increases, it becomes imperative to investigate substrate motifs to enhance the study of protein glutarylation. We carried out a bioinformatics investigation of glutarylation sites based on amino acid composition using a public database containing information on 430 non-homologous glutarylation sites. RESULTS:The TwoSampleLogo analysis indicates that positively charged and polar amino acids surrounding glutarylated sites may be associated with the specificity in substrate site of protein glutarylation. Additionally, the chi-squared test was utilized to explore the intrinsic interdependence between two positions around glutarylation sites. Further, maximal dependence decomposition (MDD), which consists of partitioning a large-scale dataset into subgroups with statistically significant amino acid conservation, was used to capture motif signatures of glutarylation sites. We considered single features, such as amino acid composition (AAC), amino acid pair composition (AAPC), and composition of k-spaced amino acid pairs (CKSAAP), as well as the effectiveness of incorporating MDD-identified substrate motifs into an integrated prediction model. Evaluation by five-fold cross-validation showed that AAC was most effective in discriminating between glutarylation and non-glutarylation sites, according to support vector machine (SVM). CONCLUSIONS:The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/ .

Dataset Information

Characterization and identification of protein O-GlcNAcylation sites with substrate specificity.

Publications

Characterization and identification of protein O-GlcNAcylation sites with substrate specificity.

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