Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

MHCcluster, a method for functional clustering of MHC molecules

  • Original Paper
  • Published:
Immunogenetics Aims and scope Submit manuscript

Abstract

The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Altschul SF, Madden TL et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    Article  PubMed  CAS  Google Scholar 

  • de Groot NG, Heijmans CM et al (2008) Pinpointing a selective sweep to the chimpanzee MHC class I region by comparative genomics. Mol Ecol 17(8):2074–2088

    Article  PubMed  Google Scholar 

  • Doytchinova IA, Guan P et al (2004) Identifiying human MHC supertypes using bioinformatic methods. J Immunol 172(7):4314–4323

    PubMed  CAS  Google Scholar 

  • Erup Larsen M, Kloverpris H et al (2011) HLArestrictor-a tool for patient-specific predictions of HLA restriction elements and optimal epitopes within peptides. Immunogenetics 63(1):43–55

    Article  PubMed  Google Scholar 

  • Harndahl M, Justesen S et al (2009) Peptide binding to HLA class I molecules: homogenous, high-throughput screening, and affinity assays. J Biomol Screen 14(2):173–180

    Article  PubMed  CAS  Google Scholar 

  • Harndahl M, Rasmussen M et al (2011) Real-time, high-throughput measurements of peptide-MHC-I dissociation using a scintillation proximity assay. J Immunol Methods 374(1–2):5–12

    Article  PubMed  CAS  Google Scholar 

  • Hertz T, Yanover C (2007) Identifying HLA supertypes by learning distance functions. Bioinformatics 23(2):e148–e155

    Article  PubMed  CAS  Google Scholar 

  • Hobohm U, Scharf M et al (1992) Selection of representative protein data sets. Protein Sci 1:409–417

    Article  PubMed  CAS  Google Scholar 

  • Hoof I, Peters B et al (2009) NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics 61(1):1–13

    Article  PubMed  CAS  Google Scholar 

  • Huson DH, Bryant D (2006) Application of phylogenetic networks in evolutionary studies. Mol Biol Evol 23(2):254–267

    Article  PubMed  CAS  Google Scholar 

  • Karosiene E, Lundegaard C et al (2011) NetMHCcons: a consensus method for the major histocompatibility complex class I predictions. Immunogenetics 64(3):177–186

    Article  PubMed  Google Scholar 

  • Larkin MA, Blackshields G et al (2007) Clustal W and Clustal X version 2.0. Bioinformatics 23(21):2947–2948

    Article  PubMed  CAS  Google Scholar 

  • Lund O, Nielsen M et al (2004) Definition of supertypes for HLA molecules using clustering of specificity matrices. Immunogenetics 55(12):797–810

    Article  PubMed  CAS  Google Scholar 

  • Lundegaard C, Lund O et al (2010) Major histocompatibility complex class I binding predictions as a tool in epitope discovery. Immunology 130(3):309–318

    Article  PubMed  CAS  Google Scholar 

  • Middleton D, Menchaca L et al (2003) “New allele frequency database: http://www.allelefrequencies.net.” Tissue Antigens 61(5):403–407

  • NCBI Resource Coordinators (2013) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 41(Database issue):D8–D20

  • Nielsen M, Lundegaard C et al (2007) NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence. PLoS One 2(8):e796

    Article  PubMed  Google Scholar 

  • Nielsen M, Lundegaard C et al (2008) Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol 4(7):e1000107

    Article  PubMed  Google Scholar 

  • Nielsen M, Justesen S et al (2010a) NetMHCIIpan-2.0—improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure. Immunol Res 6:9

    Article  Google Scholar 

  • Nielsen M, Lund O et al (2010b) MHC class II epitope predictive algorithms. Immunology 130(3):319–328

    Article  PubMed  CAS  Google Scholar 

  • Rao X, Costa AI et al (2009) A comparative study of HLA binding affinity and ligand diversity: implications for generating immunodominant CD8+ T cell responses. J Immunol 182(3):1526–1532

    PubMed  CAS  Google Scholar 

  • Rapin N, Hoof I et al (2008) MHC motif viewer. Immunogenetics 60(12):759–765

    Article  PubMed  CAS  Google Scholar 

  • Rapin N, Hoof I et al (2010) The MHC motif viewer: a visualization tool for MHC binding motifs. Current protocols in immunology. Chapter 18: Unit 18.17. doi:10.1002/0471142735.im1817s88

  • Robinson J, Marsh SG (2007) The IMGT/HLA database. Methods Mol Biol 409:43–60

    Article  PubMed  CAS  Google Scholar 

  • 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

    Article  PubMed  CAS  Google Scholar 

  • Thomsen MC, Nielsen M (2012) Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion. Nucleic Acids Res 40 (Web Server issue):W281–287

  • van Deutekom HW, Hoof I et al (2011) A comparative analysis of viral peptides presented by contemporary human and chimpanzee MHC class I molecules. J Immunology 187(11):5995–5600

    Article  Google Scholar 

  • Vita R, Zarebski L et al (2010) The immune epitope database 2.0. Nucleic Acids Res 38 (database issue):D854–862

  • Yewdell JW, Bennink JR (1999) Immunodominance in major histocompatibility complex class I-restricted T lymphocyte responses. Annu Rev Immunol 17:51–88

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

MN is researcher at the Argentinean National Research Council (CONICET). This work was supported by NIH grant HHSN272200900045C.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Morten Nielsen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Thomsen, M., Lundegaard, C., Buus, S. et al. MHCcluster, a method for functional clustering of MHC molecules. Immunogenetics 65, 655–665 (2013). https://doi.org/10.1007/s00251-013-0714-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00251-013-0714-9

Keywords

Navigation