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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 17: Automated Integration of a UPLC Glycomic Profile.
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Chapter title
Automated Integration of a UPLC Glycomic Profile.
Chapter number 17
Book title
High-Throughput Glycomics and Glycoproteomics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6493-2_17
Pubmed ID
Book ISBNs
978-1-4939-6491-8, 978-1-4939-6493-2
Authors

Anna Agakova, Frano Vučković, Lucija Klarić, Gordan Lauc, Felix Agakov

Editors

Gordan Lauc, Manfred Wuhrer

Abstract

Ultra-performance liquid chromatography (UPLC) is the established technology for accurate analysis of IgG Fc N-glycosylation due to its superior sensitivity, resolution, speed, and its capability to provide branch-specific information of glycan species. Correct and cost-efficient preprocessing of chromatographic data is the major prerequisite for subsequent analyses ranging from inference of structural isomers to biomarker discovery and prediction of humoral immune response from characterized changes in glycosylation. The complexity of glycomic chromatograms poses a number of challenges for developing automated data annotation and quantitation algorithms, which frequently necessitated manual or semi-manual approaches to preprocessing, most notably to peak detection and integration. Such procedures are meticulous and time-consuming, and may be a source of confounding due to their dependence on human labelers. Although liquid chromatography is a mature field and a number of methods have been developed for automatic peak detection outside the area of glycomics analysis, we found that hardly any of them are suitable for automatic integration of UPLC glycomic profiles without substantial modifications. In this chapter, we illustrate practical challenges of automatic peak detection of UPLC glycomics chromatograms. We outline a robust, semi-supervised method ACE (Automatic Chromatogram Extraction) for automated alignment and detection of glycan peaks in chromatograms, developed by Pharmatics Limited (UK) in collaboration with Genos Limited (Croatia). Application of the tool requires minimal human interference, which results in a significant reduction in the time and cost of IgG glycomics signal integration using Waters Acquity UPLC instrument (Milford, MA, USA) in several human cohorts with blind technical replicas.

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 > Master 5 29%
Student > Ph. D. Student 3 18%
Researcher 2 12%
Other 2 12%
Professor 1 6%
Other 0 0%
Unknown 4 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 53%
Agricultural and Biological Sciences 2 12%
Arts and Humanities 1 6%
Medicine and Dentistry 1 6%
Chemistry 1 6%
Other 0 0%
Unknown 3 18%