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High-Throughput Glycomics and Glycoproteomics

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Cover of 'High-Throughput Glycomics and Glycoproteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Ubiquitous Importance of Protein Glycosylation.
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    Chapter 2 Laboratory Experimental Design for a Glycomic Study.
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    Chapter 3 High-Throughput Analysis of the IgG N-Glycome by UPLC-FLR.
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    Chapter 4 High-Throughput Analysis of IgG Fc Glycopeptides by LC-MS.
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    Chapter 5 Sialic Acid Derivatization for the Rapid Subclass- and Sialic Acid Linkage-Specific MALDI-TOF-MS Analysis of IgG Fc-Glycopeptides.
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    Chapter 6 The Use of Multiple Reaction Monitoring on QQQ-MS for the Analysis of Protein- and Site-Specific Glycosylation Patterns in Serum.
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    Chapter 7 Analysis of Permethylated Glycan by Liquid Chromatography (LC) and Mass Spectrometry (MS).
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    Chapter 8 High-Throughput Analysis of the Plasma N-Glycome by UHPLC.
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    Chapter 9 Site-Specific N- and O-Glycopeptide Analysis Using an Integrated C18-PGC-LC-ESI-QTOF-MS/MS Approach.
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    Chapter 10 Analysis of Milk Oligosaccharides by Mass Spectrometry.
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    Chapter 11 N- and O-Glycomics from Minor Amounts of Formalin-Fixed, Paraffin-Embedded Tissue Samples.
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    Chapter 12 Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).
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    Chapter 13 Analysis of Invertebrate and Protist N-Glycans.
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    Chapter 14 High-Throughput and High-Sensitivity Mass Spectrometry-Based N-Glycomics of Mammalian Cells.
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    Chapter 15 Analysis of N-Glycosylation of Total Membrane Proteins.
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    Chapter 16 HILIC-UPLC Analysis of Brain Tissue N-Glycans.
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    Chapter 17 Automated Integration of a UPLC Glycomic Profile.
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    Chapter 18 Databases and Associated Tools for Glycomics and Glycoproteomics.
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    Chapter 19 High-Throughput N-Glycan Analysis with Rapid Magnetic Bead-Based Sample Preparation.
Attention for Chapter 9: Site-Specific N- and O-Glycopeptide Analysis Using an Integrated C18-PGC-LC-ESI-QTOF-MS/MS Approach.
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Chapter title
Site-Specific N- and O-Glycopeptide Analysis Using an Integrated C18-PGC-LC-ESI-QTOF-MS/MS Approach.
Chapter number 9
Book title
High-Throughput Glycomics and Glycoproteomics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6493-2_9
Pubmed ID
27743362
Book ISBNs
978-1-4939-6491-8, 978-1-4939-6493-2
Authors

Kathrin Stavenhagen, Hannes Hinneburg, Daniel Kolarich, Manfred Wuhrer

Editors

Gordan Lauc, Manfred Wuhrer

Abstract

The vast heterogeneity of protein glycosylation, even of a single glycoprotein with only one glycosylation site, can give rise to a set of macromolecules with different physicochemical properties. Thus, the use of orthogonal approaches for comprehensive characterization of glycoproteins is a key requirement. This chapter describes a universal workflow for site-specific N- and O-glycopeptide analysis. In a first step glycoproteins are treated with Pronase to generate glycopeptides containing small peptide sequences for enhanced glycosylation site assignment and characterization. These glycopeptides are then separated and detected using an integrated C18-porous graphitized carbon-liquid chromatography (PGC-LC) setup online coupled to a high-resolution electrospray ionization (ESI)-quadrupole time-of-flight (QTOF)-mass spectrometer operated in a combined higher- and lower-energy CID (stepping-energy CID) mode. The LC-setup allows retention of more hydrophobic glycopeptides on C18 followed by subsequent capturing of C18-unbound (glyco)peptides by a downstream placed PGC stationary phase. Glycopeptides eluted from both columns are then analyzed within a single analysis in a combined data acquisition mode. Stepping-energy CID results in B- and Y-ion fragments originating from the glycan moiety as well as b- and y-ions derived from the peptide part. This allows simultaneous site-specific identification of the glycan and peptide sequence of a glycoprotein.

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 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 24%
Other 2 12%
Student > Postgraduate 2 12%
Student > Bachelor 1 6%
Lecturer 1 6%
Other 2 12%
Unknown 5 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 18%
Chemistry 3 18%
Agricultural and Biological Sciences 2 12%
Medicine and Dentistry 1 6%
Computer Science 1 6%
Other 0 0%
Unknown 7 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 January 2018.
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#20,346,264
of 22,893,031 outputs
Outputs from Methods in molecular biology
#9,921
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#355,303
of 420,414 outputs
Outputs of similar age from Methods in molecular biology
#845
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So far Altmetric has tracked 13,134 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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