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Carbohydrate-Based Vaccines

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Attention for Chapter 3: The Glycan Array Platform as a Tool to Identify Carbohydrate Antigens
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Chapter title
The Glycan Array Platform as a Tool to Identify Carbohydrate Antigens
Chapter number 3
Book title
Carbohydrate-Based Vaccines
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2874-3_3
Pubmed ID
Book ISBNs
978-1-4939-2873-6, 978-1-4939-2874-3
Authors

Li Xia, Jeffrey C. Gildersleeve, Xia, Li, Gildersleeve, Jeffrey C.

Abstract

Carbohydrate antigens are important targets for the immune system, but identification of key glycan antigens is challenging. Direct analysis of glycomes by mass spectrometry is difficult, and detection reagents, such as monoclonal antibodies and lectins, are only available for a small subset of glycans. An alternative approach involves profiling serum anti-glycan antibody populations to identify unique antibodies or changes in antibody subpopulations. Glycan microarray technology allows rapid evaluation of hundreds to thousands of antigen-antibody interactions in a single experiment. This high-throughput format is particularly useful in profiling complex anti-glycan antibodies in serum. Here we elaborate the use of this technology to explore clinically relevant carbohydrate antigens by profiling serum anti-glycan antibodies. Detailed protocols from glycan microarray fabrication to microarray binding assays and analysis of microarray data are presented.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 40%
Student > Ph. D. Student 3 20%
Student > Master 1 7%
Student > Bachelor 1 7%
Professor > Associate Professor 1 7%
Other 1 7%
Unknown 2 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 27%
Agricultural and Biological Sciences 4 27%
Chemistry 2 13%
Social Sciences 1 7%
Unknown 4 27%