MHCcluster, a method for functional clustering of MHC molecules

Autores
Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Thomsen, Martin. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Lundegaard, Claus. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca
Fil: Lund, Ole. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Nielsen, Morten. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Fisicoquímica Biológicas; Argentina. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Materia
Mhc
Specificity
Functional Clustering
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/4529

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network_name_str CONICET Digital (CONICET)
spelling MHCcluster, a method for functional clustering of MHC moleculesThomsen, MartinLundegaard, ClausBuus, SørenLund, OleNielsen, MortenMhcSpecificityFunctional Clusteringhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The 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.Fil: Thomsen, Martin. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaFil: Lundegaard, Claus. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaFil: Lund, Ole. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaFil: Nielsen, Morten. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Fisicoquímica Biológicas; Argentina. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaSpringer2013-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/4529Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten; MHCcluster, a method for functional clustering of MHC molecules; Springer; Immunogenetics; 65; 9; 9-2013; 655-6650093-7711enginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s00251-013-0714-9info:eu-repo/semantics/altIdentifier/issn/0093-7711info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs00251-013-0714-9info:eu-repo/semantics/altIdentifier/url/http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750724/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:30Zoai:ri.conicet.gov.ar:11336/4529instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:30.339CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv MHCcluster, a method for functional clustering of MHC molecules
title MHCcluster, a method for functional clustering of MHC molecules
spellingShingle MHCcluster, a method for functional clustering of MHC molecules
Thomsen, Martin
Mhc
Specificity
Functional Clustering
title_short MHCcluster, a method for functional clustering of MHC molecules
title_full MHCcluster, a method for functional clustering of MHC molecules
title_fullStr MHCcluster, a method for functional clustering of MHC molecules
title_full_unstemmed MHCcluster, a method for functional clustering of MHC molecules
title_sort MHCcluster, a method for functional clustering of MHC molecules
dc.creator.none.fl_str_mv Thomsen, Martin
Lundegaard, Claus
Buus, Søren
Lund, Ole
Nielsen, Morten
author Thomsen, Martin
author_facet Thomsen, Martin
Lundegaard, Claus
Buus, Søren
Lund, Ole
Nielsen, Morten
author_role author
author2 Lundegaard, Claus
Buus, Søren
Lund, Ole
Nielsen, Morten
author2_role author
author
author
author
dc.subject.none.fl_str_mv Mhc
Specificity
Functional Clustering
topic Mhc
Specificity
Functional Clustering
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Thomsen, Martin. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Lundegaard, Claus. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca
Fil: Lund, Ole. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Nielsen, Morten. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Fisicoquímica Biológicas; Argentina. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
description 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.
publishDate 2013
dc.date.none.fl_str_mv 2013-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/4529
Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten; MHCcluster, a method for functional clustering of MHC molecules; Springer; Immunogenetics; 65; 9; 9-2013; 655-665
0093-7711
url http://hdl.handle.net/11336/4529
identifier_str_mv Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten; MHCcluster, a method for functional clustering of MHC molecules; Springer; Immunogenetics; 65; 9; 9-2013; 655-665
0093-7711
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s00251-013-0714-9
info:eu-repo/semantics/altIdentifier/issn/0093-7711
info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs00251-013-0714-9
info:eu-repo/semantics/altIdentifier/url/http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750724/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
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repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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