Abstract
Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only nine main functional binding specificities it is possible to cover the binding properties of almost all known HLA class I molecules. Here we present a comprehensive study of the functional relationship between all HLA molecules with known specificities in a uniform and automated way. We have developed a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some of the alleles in the A1 supertype into a new A26 supertype, and some of the alleles in the B27 supertype into a new B39 supertype. Furthermore the B8 alleles may define their own supertype. We also use the published specificities for a number of HLA-DR types to define clusters with similar specificities. We report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows for selection of representative HLA molecules that can cover the HLA specificity space better. This makes it possible to target most of the known HLA alleles with known specificities using only a few peptides, and may be used in construction of vaccines. Supplementary material is available at http://www.cbs.dtu.dk/researchgroups/immunology/supertypes.html.
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References
Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402
Boeckmann B, Bairoch A, Apweiler R, Blatter MC, Estreicher A, Gasteiger E, Martin MJ, Michoud K, O’Donovan C, Phan I, Pilbout S, Schneider M (2003) The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res 31:365–370
Brusic V, Rudy G, Harrison LC (1998) MHCPEP, a database of MHC-binding peptides: update 1997. Nucleic Acids Res 26:368–371
Cover TM, Thomas JA (1991) Elements of information theory. Wiley, New York
Eddy SR (1998) Related profile hidden Markov models. Bioinformatics 14:755–763
Guercio MF del, Sidney J, Hermanson G, Perez C, Grey HM, Kubo RT, Sette A (1995) Binding of a peptide antigen to multiple HLA alleles allows definition of an A2-like supertype. J Immunol 1995 154:685–693
Gulukota K, DeLisi C (1996) Related HLA allele selection for designing peptide vaccines. Genet Anal 13:81–86
Hammer J, Bono E, Gallazzi F, Belunis C, Nagy Z, Sinigaglia F (1994) Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning. J Exp Med 180:2353–2358
Hammer J, Sturniolo T, Sinigaglia F (1997) HLA class II peptide binding specificity and autoimmunity. Adv Immunol 66:67–100
Henikoff S, Henikoff JG (1994) Position-based sequence weights. J Mol Biol 243:574–578
Ishioka GY, Fikes J, Hermanson G, Livingston B, Crimi C, Qin M, del Guercio MF, Oseroff C, Dahlberg C, Alexander J, Chesnut RW, Sette A (1999) Utilization of MHC class I transgenic mice for development of minigene DNA vaccines encoding multiple HLA-restricted CTL epitopes. J Immunol 162:3915–3925
Lawrence CE, Altschul SF, Boguski MS, Liu JS, Neuwald AF, Wootton JC (1993) Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science 262:208–214
Lyngs, Pedersen CN, Nielsen HR (1999) Metrics and similarity measures for hidden Markov models. Proc Int Conf Intell Syst Mol Biol:178–186
Marsh SGE, Parham P, Barber LD (2000) The HLA facts book. Academic Press, London
Nielsen M, Lundegaard C, Worning P, Lauemr SL, Buus S, Brunak S, Lund O (2004) Improved prediction of MHC class II epitopes using a Gibbs sampling approach. Bioinformatics (in press)
Press WH, Flannery BP, Teukolsky SA, Vetterling, WT (1992) Numerical recipies in C. Cambridge University Press, Cambridge
Rammensee HG, Friede T, Stevanoviic S (1995) MHC ligands and peptide motifs: first listing. Immunogenetics 41:178–228
Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S (1999) SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50:213–219
Rodriguez F, An LL, Harkins S, Zhang J, Yokoyama M, Widera G, Fuller JT, Kincaid C, Campbell IL, Whitton JL (1998) DNA immunization with minigenes: low frequency of memory cytotoxic T lymphocytes and inefficient antiviral protection are rectified by ubiquitination. J Virol 72:5174–5181
Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425
Schneider TD, Stephens RM (1990) Sequence logos: a new way to display consensus sequences. Nucleic Acids Res 18:6097–100
Sette A, Sidney J (1999) Nine major HLA class I supertypes account for the vast preponderance of HLA-A and -B polymorphism. Immunogenetics 50:201–212
Sidney J, del Guercio MF, Southwood S, Engelhard VH, Appella E, Rammensee HG, Falk K, Rotzschke O, Takiguchi M, Kubo RT, et al (1995) Several HLA alleles share overlapping peptide specificities. J Immunol 154:247–259
Sidney J, Grey HM, Southwood S, Celis E, Wentworth PA, del Guercio MF, Kubo RT, Chesnut RW, Sette A (1996) Definition of an HLA-A3-like supermotif demonstrates the overlapping peptide binding repertoires of common HLA molecules. Hum Immunol 45:79–93
Singh H, Raghava GP (2001) ProPred: prediction of HLA-DR binding sites. Bioinformatics 17:1236–237
Southwood S, Sidney J, Kondo A, del Guercio MF, Appella E, Hoffman S, Kubo RT, Chesnut RW, Grey HM, Sette A (1998) Several common HLA-DR types share largely overlapping peptide binding repertoires. J Immunol 160:3363–3373
Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Braxenthaler M, Gallazzi F, Protti MP, Sinigaglia F, Hammer J (1999) Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol 17:555–561
Sylvester-Hvid C, Kristensen N, Blicher T, Ferre H, Lauemoller SL, Wolf XA, Lamberth K, Nissen MH, Pedersen LO, Buus S (2002) Establishment of a quantitative ELISA capable of determining peptide — MHC class I interaction. Tissue Antigens 59:251–258
Acknowledgements
This work is part of the IHWG and was supported by the Danish National Research Foundation, the Danish MRC (grant 22-01-0272), the 5th Framework Programme of the European Commission (grant QLRT-1999-00173), NIH (grant AI49213-02) and the Bioinformatic Program of the Dutch Science Foundation (NWO PGBMI 015).
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Lund, O., Nielsen, M., Kesmir, C. et al. Definition of supertypes for HLA molecules using clustering of specificity matrices. Immunogenetics 55, 797–810 (2004). https://doi.org/10.1007/s00251-004-0647-4
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DOI: https://doi.org/10.1007/s00251-004-0647-4