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Carbohydrate-Based Vaccines

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Attention for Chapter 5: Generation of Monoclonal Antibodies against Defined Oligosaccharide Antigens
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Chapter title
Generation of Monoclonal Antibodies against Defined Oligosaccharide Antigens
Chapter number 5
Book title
Carbohydrate-Based Vaccines
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2874-3_5
Pubmed ID
Book ISBNs
978-1-4939-2873-6, 978-1-4939-2874-3
Authors

Felix Broecker, Chakkumkal Anish, Peter H. Seeberger, Broecker, Felix, Anish, Chakkumkal, Seeberger, Peter H.

Abstract

Unique carbohydrate antigens are expressed on the surface of various pathogens, including bacteria, parasites, and viruses, and aberrant glycosylation is a frequent feature of cancer cells. Antibodies recognizing such carbohydrate antigens may be used for the specific detection of potentially harmful cells, immunohistochemistry, and diagnostic and therapeutic applications. The generation of specific and strongly binding antibodies against defined carbohydrate epitopes is challenging, since isolated carbohydrates often suffer from low purity, usually have limited immunogenicity, and induce antibodies of low affinity. We describe a protocol to generate highly affine monoclonal antibodies (mAbs) against pure and defined synthetic carbohydrate antigens. First, an oligosaccharide is covalently coupled to an immunogenic carrier protein to obtain a glycoconjugate. This glycoconjugate is used to raise oligosaccharide-specific antibodies in mice, and splenocytes are fused with myeloma cells to form hybridomas. Hybridoma clones producing oligosaccharide-specific mAbs are selected by glycan microarray screening. Selected clones are expanded and mAbs are purified from the cell culture supernatant. This protocol is suitable to procure carbohydrate-specific mAbs of high specificity, selectivity, and affinity that may be useful for a variety of biochemical and medical applications.

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The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Student > Master 3 15%
Researcher 3 15%
Professor > Associate Professor 2 10%
Student > Doctoral Student 1 5%
Other 4 20%
Unknown 3 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 35%
Biochemistry, Genetics and Molecular Biology 3 15%
Chemistry 3 15%
Computer Science 1 5%
Nursing and Health Professions 1 5%
Other 2 10%
Unknown 3 15%