Chapter title |
Molecular Methods and Bioinformatic Tools for Adjuvant Characterization by High-Throughput Sequencing
|
---|---|
Chapter number | 26 |
Book title |
Vaccine Adjuvants
|
Published in |
Methods in molecular biology, October 2016
|
DOI | 10.1007/978-1-4939-6445-1_26 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6443-7, 978-1-4939-6445-1
|
Authors |
Steven R. Wiley, Vanitha S. Raman |
Editors |
Christopher B. Fox |
Abstract |
Adjuvants in vaccine formulations are designed to enhance immune responses against a target antigen or pathogen. The ability of these vaccines to induce activation and differentiation of mature naïve B cells to produce pathogen-specific antibodies (immunoglobulins; Ig) helps guarantee long-lived humoral immunity. This process involves clonal expansion of antigen-specific B cells, genomic rearrangement of Ig heavy (IgH) and light (IgL) loci, somatic hypermutation (SHM), and clonal selection for affinity-matured antibody, resulting in a vast but directed repertoire of B cells expressing highly specific antibody proteins. High-throughput sequencing of the IgH and IgL complementary determining regions (CDRs) derived from various B cell populations provides an unprecedented way to observe dynamic responses of the humoral immune repertoire in response to vaccination. However, applying high-throughput sequencing (HTS) methodologies to multi-armed in vivo experiments requires careful coordination of sample preparation with downstream bioinformatics, particularly with regard to issues of quantitation, sequence fidelity, bar-coding, and multiplexing strategies. Here, we overview strategies of high-throughput sequencing and analysis of the adaptive immune complex loci applied to multi-armed, multiplexed experiments. |
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Unknown | 2 | 100% |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
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Unknown | 3 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Professor | 1 | 33% |
Student > Ph. D. Student | 1 | 33% |
Lecturer | 1 | 33% |
Readers by discipline | Count | As % |
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Veterinary Science and Veterinary Medicine | 1 | 33% |
Biochemistry, Genetics and Molecular Biology | 1 | 33% |
Medicine and Dentistry | 1 | 33% |