Bioinformatics Protocols in Glycomics and Glycoproteomics

Haixu Tang1, Anoop Mayampurath1, Chuan‐Yih Yu1, Yehia Mechref2

1 School of Informatics and Computing, Indiana University, Bloomington, Indiana, 2 Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
Publication Name:  Current Protocols in Protein Science
Unit Number:  Unit 2.15
DOI:  10.1002/0471140864.ps0215s76
Online Posting Date:  April, 2014
GO TO THE FULL TEXT: PDF or HTML at Wiley Online Library

Abstract

Glycomics aims to identify the whole set of functional glycans of glycoconjugates (attached to proteins or lipids) in biological samples. Glycoproteomics aims to characterize the complete structure of all glycoproteins in biological samples, including the glycosylation sites of proteins and the various glycan structures attached to each of these sites. Mass spectrometry (MS) and microarray are high‐throughput technologies that are commonly used in glycomics and glycoproteomics, which often result in the generation of large experimental datasets. Bioinformatics approaches play an essential role in automated analysis and interpretation of such data. This unit describes and discusses the computational tools currently available for these analyses, and their glycomics and glycoproteomics applications. Curr. Protoc. Protein Sci. 76:2.15.1‐2.15.7. © 2014 by John Wiley & Sons, Inc.

Keywords: glycosylation; glycomics; glycoproteomics; bioinformatics; mass spectrometry; microarray

     
 
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Table of Contents

  • Introduction
  • Characterization of Glycan Structures
  • Glycan Annotation and Profiling in Mass Spectra
  • Analysis and Mining of Glycan Structures
  • Characterization and Prediction of Glycosylation Sites
  • Conclusions
  • Acknowledgements
  • Literature Cited
  • Tables
     
 
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Materials

GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Figures

Videos

Literature Cited

Literature Cited
   Aoki‐Kinoshita, K.F. 2008. An introduction to bioinformatics for glycomics research. PLoS Computat. Biol. 4:e1000075.
   Ashline, D.J. , Lapadula, A.J. , Liu, Y.H. , Lin, M. , Grace, M. , Pramanik, B. , and Vernon, N. 2007. Carbohydrate structural isomers analyzed by sequential mass spectrometry. Anal. Chem. 79:3830‐3842.
   Blixt, O. , Head, S. , Mondala, T. , Scanlan, C. , Huflejt, M.E. , Alvarez, R. , Bryan, M.C. , Fazio, F. , Calarese, D. , and Stevens, J. 2004. Printed covalent glycan array for ligand profiling of diverse glycan binding proteins. Proc. Natl. Acad. Sci. U.S.A. 101:17033‐17038.
   Ceroni, A. , Maass, K. , Geyer, H. , Geyer, R. , Dell, A. , and Haslam, S.M. 2008. GlycoWorkbench: A tool for the computer‐assisted annotation of mass spectra of glycans. J. Proteome Res. 7:1650‐1659.
   Cooper, C.A. , Joshi, H.J. , Harrison, M.J. , Wilkins, M.R. , and Packer, N.H. 2003. GlycoSuiteDB: A curated relational database of glycoprotein glycan structures and their biological sources. 2003 update. Nucleic Acids Res. 31:511‐513.
   Dell, A. and Morris, H.R. 2001. Glycoprotein structure determination by mass spectrometry. Science 291:2351‐2356.
   Dwek, R. , Edge, C.J. , Harvey, D. , Wormald, M. , and Parekh, R. 1993. Analysis of glycoprotein‐associated oligosaccharides. Annu. Rev. Biochem. 62:65‐100.
   Gerken, T.A. , Jamison, O. , Perrine, C.L. , Collette, J.C. , Moinova, H. , Ravi, L. , Markowitz, S.D. , Shen, W. , Patel, H. , and Tabak, L.A. 2011. Emerging paradigms for the initiation of mucin‐type protein O‐glycosylation by the polypeptide GalNAc transferase family of glycosyltransferases. J. Biol. Chem. 286:14493‐14507.
   Goldberg, D. , Sutton‐Smith, M. , Paulson, J. , and Dell, A. 2005. Automatic annotation of matrix‐assisted laser desorption/ionization N‐glycan spectra. Proteomics 5:865‐875.
   Jaitly, N. , Mayampurath, A. , Littlefield, K. , Adkins, J.N. , GA, A. , and Smith, R.D. 2009. Decon2LS: An open‐source software package for automated processing and visualization of high resolution mass spectrometry data. BMC Bioinformatics 10:87.
   Jiang, H. , Aoki‐Kinoshita, K.F. , and Ching, W.K. 2011. Extracting glycan motifs using a biochemicallyweighted kernel. Bioinformation 7:405.
   Kuboyama, T. , Hirata, K. , Aoki‐Kinoshita, K.F. , Kashima, H. , and Yasuda, H. 2006. A gram distribution kernel applied to glycan classification and motif extraction. Genome Inform. Series 17:25.
   Lapadula, A.J. , Hatcher, P.J. , Hanneman, A.J. , Ashline, D.J. , Zhang, H. , and Vernon, N. 2005. Congruent strategies for carbohydrate sequencing. 3. OSCAR: An algorithm for assigning oligosaccharide topology from MS n data. Anal. Chem. 77:6271‐6279.
   Maxwell, E. , Tan, Y. , Tan, Y. , Hu, H. , Benson, G. , Aizikov, K. , Conley, S. , Staples, G.O. , Slysz, G.W. , Smith, R.D. , and Zaia, J. 2012. GlycReSoft: A Software Package for Automated Recognition of Glycans from LC/MS Data. PLoS One 7:e45474.
   National Research Council, 2012. Transforming Glycoscience: A Roadmap for the Future. National Academies Press, Washington, D.C.
   North, S.J. , Hitchen, P.G. , Haslam, S.M. , and Dell, A. 2009. Mass spectrometry in the analysis of N‐linked and O‐linked glycans. Curr. Opin. Struct. Biol. 19:498‐506.
   Porter, A. , Yue, T. , Heeringa, L. , Day, S. , Suh, E. , and Haab, B.B. 2010. A motif‐based analysis of glycan array data to determine the specificities of glycan‐binding proteins. Glycobiology 20:369‐380.
   Raman, R. , Raguram, S. , Venkataraman, G. , Paulson, J.C. , and Sasisekharan, R. 2005. Glycomics: An integrated systems approach to structure‐function relationships of glycans. Nat. Methods 2:817‐824.
   Steentoft, C. , Vakhrushev, S.Y. , Vester‐Christensen, M.B. , Schjoldager, K.T.B.G. , Kong, Y. , Bennett, E.P. , Mandel, U. , Wandall, H. , Levery, S.B. , and Clausen, H. 2011. Mining the O‐glycoproteome using zinc‐finger nuclease‐glycoengineered SimpleCell lines. Nat. Methods 8:977‐982.
   Tang, H. , Mechref, Y. , and Novotny, M.V. 2005. Automated interpretation of MS/MS spectra of oligosaccharides. Bioinformatics 21:i431‐i439.
   Varki, A. , Cummings, R. , Esko, J. , Freeze, H. , Hart, G. , and Marth, J. 1999. Essentials of Glycobiology. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York.
   Von Der Lieth, C.W. , Bohne‐Lang, A. , Lohmann, K.K. , and Frank, M. 2004. Bioinformatics for glycomics: Status, methods, requirements and perspectives. Brief. Bioinformatics 5:164‐178.
   Wang, L. , Aryal, U.K. , Dai, Z. , Mason, A.C. , Monroe, M.E. , Tian, Z.X. , Zhou, J.Y. , Su, D. , Weitz, K.K. , and Liu, T. 2011. Mapping N‐linked glycosylation sites in the secretome and whole cells of Aspergillus niger using hydrazide chemistry and mass spectrometry. J. Proteome Res. 11:143‐156.
   Wuhrer, M. , de Boer, A.R. , and Deelder, A.M. 2008. Structural glycomics using hydrophilic interaction chromatography (HILIC) with mass spectrometry. Mass Spectrom. Rev. 28:192‐206.
   Yamanishi, Y. , Bach, F. , and Vert, J.P. 2007. Glycan classification with tree kernels. Bioinformatics 23:1211‐1216.
   Yu, C.‐Y. , Mayampurath, A. , Hu, Y. , Mechref, Y. , and Tang, H. 2013. Automated annotation and quantification of glycans using liquid chromatography‐mass spectrometry (LC‐MS). Bioinformatics 29:1706‐1707.
   Zhang, H. , Li, X. , Martin, D.B. , and Aebersold, R. 2003. Identification and quantification of N‐linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nat. Biotechnol. 21:660‐666.
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library