| Chapter title |
High-Throughput Analysis of the Plasma N-Glycome by UHPLC.
|
|---|---|
| Chapter number | 8 |
| Book title |
High-Throughput Glycomics and Glycoproteomics
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6493-2_8 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6491-8, 978-1-4939-6493-2
|
| Authors |
Barbara Adamczyk, Henning Stöckmann, Róisín O’Flaherty, Niclas G. Karlsson, Pauline M. Rudd, Adamczyk, Barbara, Stöckmann, Henning, O’Flaherty, Róisín, Karlsson, Niclas G., Rudd, Pauline M. |
| Editors |
Gordan Lauc, Manfred Wuhrer |
| Abstract |
The understanding of glycosylation alterations in health and disease has evolved significantly and glycans are considered to be relevant biomarker candidates. High-throughput analytical technologies capable of generating high-quality, large-scale glycoprofiling data are in high demand. Here, we describe an automated sample preparation workflow and analysis of N-linked glycans from plasma samples using hydrophilic interaction liquid chromatography with fluorescence detection on an ultrahigh-performance liquid chromatography (UHPLC) instrument. Samples are prepared in 96-well plates and the workflow features rapid glycoprotein denaturation, enzymatic glycan release, glycan purification on solid-supported hydrazide, fluorescent labeling, and post-labeling cleanup with solid-phase extraction. The development of a novel approach for plasma N-glycan analysis and its implementation on a robotic platform significantly reduces the time required for sample preparation and minimizes technical variation. It is anticipated that the developed method will contribute to expanding high-throughput capabilities to analyze protein glycosylation. |
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| Country | Count | As % |
|---|---|---|
| Sweden | 2 | 20% |
| Poland | 1 | 10% |
| Ghana | 1 | 10% |
| Switzerland | 1 | 10% |
| United States | 1 | 10% |
| United Kingdom | 1 | 10% |
| Unknown | 3 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 60% |
| Scientists | 4 | 40% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 24% |
| Student > Ph. D. Student | 4 | 19% |
| Researcher | 3 | 14% |
| Unspecified | 1 | 5% |
| Professor > Associate Professor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 29% |
| Agricultural and Biological Sciences | 2 | 10% |
| Chemistry | 2 | 10% |
| Medicine and Dentistry | 2 | 10% |
| Computer Science | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 6 | 29% |