An analysis of the epitope knowledge related to Mycobacteria

Immunome Research, Dec 2007

Martin J Blythe, Qing Zhang, Kerrie Vaughan, Romulo de Castro, Nima Salimi, Huynh-Hoa Bui, David M Lewinsohn, Joel D Ernst, Bjoern Peters, Alessandro Sette

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An analysis of the epitope knowledge related to Mycobacteria

Immunome Research An analysis of the epitope knowledge related to Mycobacteria Martin J Blythe 2 Qing Zhang 2 Kerrie Vaughan 2 Romulo de Castro Jr 2 Nima Salimi 2 Huynh-Hoa Bui 2 David M Lewinsohn 1 Joel D Ernst 0 Bjoern Peters 2 Alessandro Sette 2 0 Division of Infectious Diseases, New York University School of Medicine , 550 First Avenue, Smilow 901, New York, 10016 , USA 1 Portland VA Medical Center/Oregon Heath and Science University , R&D 11, PVAMC, 3710 SW US Veterans Road, Portland, Oregon, 97239 , USA 2 Department of Vaccine Discovery, La Jolla Institute for Allergy and Immunology , 9420 Athena Circle, La Jolla, California, 92037 , USA Background: Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, remains a leading cause of infectious disease morbidity and mortality, and is responsible for more than 2 million deaths a year. Reports about extremely drug resistant (XDR) strains have further heightened the sense of urgency for the development of novel strategies to prevent and treat TB. Detailed knowledge of the epitopes recognized by immune responses can aid in vaccine and diagnostics development, and provides important tools for basic research. The analysis of epitope data corresponding to M. tuberculosis can also identify gaps in our knowledge, and suggest potential areas for further research and discovery. The Immune Epitope Database (IEDB) is compiled mainly from literature sources, and describes a broad array of source organisms, including M. tuberculosis and other Mycobacterial species. Description: A comprehensive analysis of IEDB data regarding the genus Mycobacteria was performed. The distribution of antibody/B cell and T cell epitopes was analyzed in terms of their associated recognition cell type effector function and chemical properties. The various species, strains and proteins which the epitope were derived, were also examined. Additional variables considered were the host in which the epitopes were defined, the specific TB disease state associated with epitope recognition, and the HLA associated with disease susceptibility and endemic regions were also scrutinized. Finally, based on these results, standardized reference datasets of mycobacterial epitopes were generated. Conclusion: All current TB-related epitope data was cataloged for the first time from the published literature. The resulting inventory of more than a thousand different epitopes should prove a useful tool for the broad scientific community. Knowledge gaps specific to TB epitope data were also identified. In summary, few non-peptidic or post-translationally modified epitopes have been defined. Most importantly epitopes have apparently been defined from only 7% of all ORFs, and the top 30 most frequently studied protein antigens contain 65% of the epitopes, leaving the majority of M. tuberculosis genome unexplored. A lack of information related to the specific strains from which epitopes are derived is also evident. Finally, the generation of reference lists of mycobacterial epitopes should also facilitate future vaccine and diagnostic research. Background The goal of the Immune Epitope Database and Analysis Resource (IEDB) [1] is to compile epitope-specific immunological data, as well as analysis tools, and to facilitate the characterization of immune responses in humans and other higher vertebrates. Epitope information can be useful to the scientific community in the design, characterization, and identification of potential vaccines and diagnostics, as well as to assist in basic investigation of immune responses and host-pathogen interactions. In terms of the type of immune responses and associated epitopes considered, we describe epitopes recognized in the context of the adaptive immune response, namely antibody/B and T cell epitopes. Each type of epitope is defined as the molecular structure that is bound by an antibody or T cell receptor. Curation of data relating to NIAID Category A, B, and C pathogens [2], emerging and re-emerging infectious diseases and various other pathogens into the IEDB is current with the published literature (see [1] for a current list). To date, the database describes epitopes sourced from over 4,000 publications detailing in excess of 32,000 distinct epitopes. Besides epitopes composed of amino acids, the IEDB includes information from all other chemical classes of non-peptidic antigens, including lipids, glycolipids, carbohydrates, DNA, RNA, and small organic molecules. The information can be searched using multiple parameters. For each epitope, specific fields summarize immunological data, including detailed information related to the immunized/infected host organism and source of the antigenic determinant. Associated fields also describe the experimental techniques used to characterize the epitope, and the immunological response detected [ 3,4 ]. The IEDB also hosts various bioinformaticstools to analyze epitope data, including: populationcoverage [ 5 ]; ep (...truncated)


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Martin J Blythe, Qing Zhang, Kerrie Vaughan, Romulo de Castro, Nima Salimi, Huynh-Hoa Bui, David M Lewinsohn, Joel D Ernst, Bjoern Peters, Alessandro Sette. An analysis of the epitope knowledge related to Mycobacteria, Immunome Research, 2007, pp. 10, Volume 3, Issue 1, DOI: 10.1186/1745-7580-3-10