Abstract
The characterization of Mycobacterium tuberculosis antigens inducing CD4(+) T-cell responses could critically contribute to the development of subunit vaccines for M. tuberculosis. Here we performed computational analysis by using T-cell epitope prediction software (known as TEPITOPE) to predict promiscuous HLA-DR ligands in the products of the mce genes of M. tuberculosis. The analysis of the proliferative responses of CD4(+) T cells from patients with pulmonary tuberculosis to selected peptides displaying promiscuous binding to HLA-DR in vitro led us to the identification of a peptide that induced proliferation of CD4(+) cells from 50% of the tested subjects. This study demonstrates that a systematic computational approach can be used to identify T-cell epitopes in proteins expressed by an intracellular pathogen.
Publication types
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, P.H.S.
MeSH terms
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Amino Acid Sequence
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Antibodies, Bacterial / immunology
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Antigen Presentation / immunology
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Antigens, Bacterial / genetics
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Antigens, Bacterial / immunology*
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Bacterial Proteins / genetics
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Bacterial Proteins / immunology*
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CD4-Positive T-Lymphocytes / cytology
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CD4-Positive T-Lymphocytes / immunology*
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Cell Division
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Cells, Cultured
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Epitope Mapping
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Epitopes, T-Lymphocyte / immunology*
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HLA-DR Antigens / immunology*
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Humans
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Immunoglobulin G / immunology
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Molecular Sequence Data
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Mycobacterium tuberculosis / immunology*
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Peptides / immunology
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Protein Binding
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Sequence Homology, Amino Acid
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Tuberculosis, Pulmonary / blood
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Tuberculosis, Pulmonary / immunology*
Substances
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Antibodies, Bacterial
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Antigens, Bacterial
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Bacterial Proteins
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Epitopes, T-Lymphocyte
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HLA-DR Antigens
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Immunoglobulin G
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Peptides
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mce2 protein, Mycobacterium tuberculosis