Immunogenetics

, Volume 65, Issue 9, pp 655–665 | Cite as

MHCcluster, a method for functional clustering of MHC molecules

  • Martin Thomsen
  • Claus Lundegaard
  • Søren Buus
  • Ole Lund
  • Morten Nielsen
Original Paper

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.

Keywords

MHC HLA Binding motif Functional clustering MHC specificity Supertypes 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Martin Thomsen
    • 1
  • Claus Lundegaard
    • 1
    • 3
  • Søren Buus
    • 4
  • Ole Lund
    • 1
  • Morten Nielsen
    • 1
    • 2
  1. 1.Center for Biological Sequence Analysis, Department of Systems BiologyTechnical University of DenmarkLyngbyDenmark
  2. 2.Instituto de Investigaciones BiotecnológicasUniversidad Nacional de San MartínSan MartínArgentina
  3. 3.ALKHørsholmDenmark
  4. 4.Laboratory of Experimental ImmunologyUniversity of CopenhagenCopenhagen NDenmark

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