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Journal of Biomedicine and Biotechnology
Volume 2010, Article ID 325720, 12 pages
http://dx.doi.org/10.1155/2010/325720
Review Article

High Throughput T Epitope Mapping and Vaccine Development

1Laboratory of Cellular Immunology, Advanced Biotechnology Center, Largo Benzi 10, 16132 Genoa, Italy
2Laboratory of Clinical and Experimental Immunology, G. Gaslini Institute, Largo G. Gaslini 5, 16148 Genoa, Italy

Received 12 October 2009; Revised 18 February 2010; Accepted 20 April 2010

Academic Editor: Yongqun Oliver He

Copyright © 2010 Giuseppina Li Pira et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Mapping of antigenic peptide sequences from proteins of relevant pathogens recognized by T helper (Th) and by cytolytic T lymphocytes (CTL) is crucial for vaccine development. In fact, mapping of T-cell epitopes provides useful information for the design of peptide-based vaccines and of peptide libraries to monitor specific cellular immunity in protected individuals, patients and vaccinees. Nevertheless, epitope mapping is a challenging task. In fact, large panels of overlapping peptides need to be tested with lymphocytes to identify the sequences that induce a T-cell response. Since numerous peptide panels from antigenic proteins are to be screened, lymphocytes available from human subjects are a limiting factor. To overcome this limitation, high throughput (HTP) approaches based on miniaturization and automation of T-cell assays are needed. Here we consider the most recent applications of the HTP approach to T epitope mapping. The alternative or complementary use of in silico prediction and experimental epitope definition is discussed in the context of the recent literature. The currently used methods are described with special reference to the possibility of applying the HTP concept to make epitope mapping an easier procedure in terms of time, workload, reagents, cells and overall cost.