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      Amino Acid Similarity Accounts for T Cell Cross-Reactivity and for “Holes” in the T Cell Repertoire


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          Cytotoxic T cell (CTL) cross-reactivity is believed to play a pivotal role in generating immune responses but the extent and mechanisms of CTL cross-reactivity remain largely unknown. Several studies suggest that CTL clones can recognize highly diverse peptides, some sharing no obvious sequence identity. The emerging realization in the field is that T cell receptors (TcR) recognize multiple distinct ligands.

          Principal Findings

          First, we analyzed peptide scans of the HIV epitope SLFNTVATL (SFL9) and found that TCR specificity is position dependent and that biochemically similar amino acid substitutions do not drastically affect recognition. Inspired by this, we developed a general model of TCR peptide recognition using amino acid similarity matrices and found that such a model was able to predict the cross-reactivity of a diverse set of CTL epitopes. With this model, we were able to demonstrate that seemingly distinct T cell epitopes, i.e., ones with low sequence identity, are in fact more biochemically similar than expected. Additionally, an analysis of HIV immunogenicity data with our model showed that CTLs have the tendency to respond mostly to peptides that do not resemble self-antigens.


          T cell cross-reactivity can thus, to an extent greater than earlier appreciated, be explained by amino acid similarity. The results presented in this paper will help resolving some of the long-lasting discussions in the field of T cell cross-reactivity.

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          Most cited references34

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          SYFPEITHI: database for MHC ligands and peptide motifs.

          The first version of the major histocompatibility complex (MHC) databank SYFPEITHI: database for MHC ligands and peptide motifs, is now available to the general public. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. All motifs currently available are accessible as individual entries. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database content is restricted to published data only.
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            How TCRs bind MHCs, peptides, and coreceptors.

            Since the first crystal structure determinations of alphabeta T cell receptors (TCRs) bound to class I MHC-peptide (pMHC) antigens in 1996, a sizable database of 24 class I and class II TCR/pMHC complexes has been accumulated that now defines a substantial degree of structural variability in TCR/pMHC recognition. Recent determination of free and bound gammadelta TCR structures has enabled comparisons of the modes of antigen recognition by alphabeta and gammadelta T cells and antibodies. Crystal structures of TCR accessory (CD4, CD8) and coreceptor molecules (CD3epsilondelta, CD3epsilongamma) have further advanced our structural understanding of most of the components that constitute the TCR signaling complex. Despite all these efforts, the structural basis for MHC restriction and signaling remains elusive as no structural features that define a common binding mode or signaling mechanism have yet been gleaned from the current set of TCR/pMHC complexes. Notwithstanding, the impressive array of self, foreign (microbial), and autoimmune TCR complexes have uncovered the diverse ways in which antigens can be specifically recognized by TCRs.
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              A very high level of crossreactivity is an essential feature of the T-cell receptor.

              Don Mason (1998)

                Author and article information

                Role: Academic Editor
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                19 March 2008
                : 3
                : 3
                [1 ]Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
                [2 ]Theoretical Biology/Bioinformatics, University of Utrecht, Utrecht, The Netherlands
                [3 ]Academic Biomedical Centre, University of Utrecht, Utrecht, The Netherlands
                AIDS Research Center, Chinese Academy of Medical Sciences and Peking Union Medical College, China
                Author notes

                Conceived and designed the experiments: OL MN SF CK. Performed the experiments: MN SF CK. Analyzed the data: MN SF CK. Contributed reagents/materials/analysis tools: SF. Wrote the paper: OL MN SF CK RJ.

                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                Page count
                Pages: 8
                Research Article
                Immunology/Antigen Processing and Recognition
                Immunology/Immune Response
                Immunology/Immunity to Infections



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