Literature DB >> 22843980

Automated glycopeptide analysis--review of current state and future directions.

David C Dallas1, William F Martin, Serenus Hua, J Bruce German.   

Abstract

Glycosylation of proteins is involved in immune defense, cell-cell adhesion, cellular recognition and pathogen binding and is one of the most common and complex post-translational modifications. Science is still struggling to assign detailed mechanisms and functions to this form of conjugation. Even the structural analysis of glycoproteins-glycoproteomics-remains in its infancy due to the scarcity of high-throughput analytical platforms capable of determining glycopeptide composition and structure, especially platforms for complex biological mixtures. Glycopeptide composition and structure can be determined with high mass-accuracy mass spectrometry, particularly when combined with chromatographic separation, but the sheer volume of generated data necessitates computational software for interpretation. This review discusses the current state of glycopeptide assignment software-advances made to date and issues that remain to be addressed. The various software and algorithms developed so far provide important insights into glycoproteomics. However, there is currently no freely available software that can analyze spectral data in batch and unambiguously determine glycopeptide compositions for N- and O-linked glycopeptides from relevant biological sources such as human milk and serum. Few programs are capable of aiding in structural determination of the glycan component. To significantly advance the field of glycoproteomics, analytical software and algorithms are required that: (i) solve for both N- and O-linked glycopeptide compositions, structures and glycosites in biological mixtures; (ii) are high-throughput and process data in batches; (iii) can interpret mass spectral data from a variety of sources and (iv) are open source and freely available.

Entities:  

Keywords:  N-linked; O-linked; bioinformatics; glycopeptide; glycopeptidomics; glycoproteomics

Mesh:

Substances:

Year:  2012        PMID: 22843980      PMCID: PMC3659302          DOI: 10.1093/bib/bbs045

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  60 in total

1.  Automated interpretation of MS/MS spectra of oligosaccharides.

Authors:  Haixu Tang; Yehia Mechref; Milos V Novotny
Journal:  Bioinformatics       Date:  2005-06       Impact factor: 6.937

2.  Specific enrichment methods for glycoproteome research.

Authors:  Lijuang Zhang; Haojie Lu; Pengyuan Yang
Journal:  Anal Bioanal Chem       Date:  2010-01       Impact factor: 4.142

3.  A new computer program (GlycoX) to determine simultaneously the glycosylation sites and oligosaccharide heterogeneity of glycoproteins.

Authors:  Hyun Joo An; John S Tillinghast; David L Woodruff; David M Rocke; Carlito B Lebrilla
Journal:  J Proteome Res       Date:  2006-10       Impact factor: 4.466

4.  Large-scale assignment of N-glycosylation sites using complementary enzymatic deglycosylation.

Authors:  Wei Zhang; Hong Wang; Lei Zhang; Jun Yao; Pengyuan Yang
Journal:  Talanta       Date:  2011-04-16       Impact factor: 6.057

Review 5.  Application of nano-LC-based glycomics towards biomarker discovery.

Authors:  Serenus Hua; Carlito Lebrilla; Hyun Joo An
Journal:  Bioanalysis       Date:  2011-11       Impact factor: 2.681

6.  Analytical performance of immobilized pronase for glycopeptide footprinting and implications for surpassing reductionist glycoproteomics.

Authors:  Eric D Dodds; Richard R Seipert; Brian H Clowers; J Bruce German; Carlito B Lebrilla
Journal:  J Proteome Res       Date:  2009-02       Impact factor: 4.466

7.  Development of a robust and high throughput method for profiling N-linked glycans derived from plasma glycoproteins by NanoLC-FTICR mass spectrometry.

Authors:  Michael S Bereman; Douglas D Young; Alexander Deiters; David C Muddiman
Journal:  J Proteome Res       Date:  2009-07       Impact factor: 4.466

8.  Development of a nanoLC LTQ orbitrap mass spectrometric method for profiling glycans derived from plasma from healthy, benign tumor control, and epithelial ovarian cancer patients.

Authors:  Michael S Bereman; Taufika Islam Williams; David C Muddiman
Journal:  Anal Chem       Date:  2009-02-01       Impact factor: 6.986

9.  GlycoSpectrumScan: fishing glycopeptides from MS spectra of protease digests of human colostrum sIgA.

Authors:  Nandan Deshpande; Pia H Jensen; Nicolle H Packer; Daniel Kolarich
Journal:  J Proteome Res       Date:  2010-02-05       Impact factor: 4.466

10.  Glycomic approach for potential biomarkers on prostate cancer: profiling of N-linked glycans in human sera and pRNS cell lines.

Authors:  Maria Lorna A de Leoz; Hyun Joo An; Scott Kronewitter; Jaehan Kim; Sean Beecroft; Ruth Vinall; Suzanne Miyamoto; Ralph de Vere White; Kit S Lam; Carlito Lebrilla
Journal:  Dis Markers       Date:  2008       Impact factor: 3.434

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  31 in total

Review 1.  Glycomics and glycoproteomics of viruses: Mass spectrometry applications and insights toward structure-function relationships.

Authors:  John F Cipollo; Lisa M Parsons
Journal:  Mass Spectrom Rev       Date:  2020-04-29       Impact factor: 10.946

2.  Glycopeptide Site Heterogeneity and Structural Diversity Determined by Combined Lectin Affinity Chromatography/IMS/CID/MS Techniques.

Authors:  Feifei Zhu; Jonathan C Trinidad; David E Clemmer
Journal:  J Am Soc Mass Spectrom       Date:  2015-04-04       Impact factor: 3.109

3.  Use of an informed search space maximizes confidence of site-specific assignment of glycoprotein glycosylation.

Authors:  Kshitij Khatri; Joshua A Klein; Joseph Zaia
Journal:  Anal Bioanal Chem       Date:  2016-10-12       Impact factor: 4.142

4.  XGlycScan: An Open-source Software For N-linked Glycosite Assignment, Quantification and Quality Assessment of Data from Mass Spectrometry-based Glycoproteomic Analysis.

Authors:  Paul Aiyetan; Bai Zhang; Zhen Zhang; Hui Zhang
Journal:  MOJ Proteom Bioinform       Date:  2014

Review 5.  Proteomics, Glycomics, and Glycoproteomics of Matrisome Molecules.

Authors:  Rekha Raghunathan; Manveen K Sethi; Joshua A Klein; Joseph Zaia
Journal:  Mol Cell Proteomics       Date:  2019-08-30       Impact factor: 5.911

Review 6.  Why Glycosylation Matters in Building a Better Flu Vaccine.

Authors:  Deborah Chang; Joseph Zaia
Journal:  Mol Cell Proteomics       Date:  2019-10-11       Impact factor: 5.911

Review 7.  Glycosylation profiling to evaluate glycoprotein immunogens against HIV-1.

Authors:  Anna-Janina Behrens; Weston B Struwe; Max Crispin
Journal:  Expert Rev Proteomics       Date:  2017-09-14       Impact factor: 3.940

Review 8.  Algorithms and design strategies towards automated glycoproteomics analysis.

Authors:  Han Hu; Kshitij Khatri; Joseph Zaia
Journal:  Mass Spectrom Rev       Date:  2016-01-04       Impact factor: 10.946

Review 9.  A review of methods for interpretation of glycopeptide tandem mass spectral data.

Authors:  Han Hu; Kshitij Khatri; Joshua Klein; Nancy Leymarie; Joseph Zaia
Journal:  Glycoconj J       Date:  2015-11-26       Impact factor: 2.916

10.  SweetSEQer, simple de novo filtering and annotation of glycoconjugate mass spectra.

Authors:  Oliver Serang; John W Froehlich; Jan Muntel; Gary McDowell; Hanno Steen; Richard S Lee; Judith A Steen
Journal:  Mol Cell Proteomics       Date:  2013-02-26       Impact factor: 5.911

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