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dc.contributor.author
Osterbye, Thomas
dc.contributor.author
Nielsen, Morten
dc.contributor.author
Dudek, Nadine L.
dc.contributor.author
Ramarathinam, Sri H.
dc.contributor.author
Purcell, Anthony W.
dc.contributor.author
Schafer-Nielsen, Claus
dc.contributor.author
Buus, Soren
dc.date.available
2020-08-25T16:28:56Z
dc.date.issued
2020-06
dc.identifier.citation
Osterbye, Thomas; Nielsen, Morten; Dudek, Nadine L.; Ramarathinam, Sri H.; Purcell, Anthony W.; et al.; HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions; American Association of Immunologists; Journal of Immunology; 205; 1; 6-2020; 290-299
dc.identifier.issn
0022-1767
dc.identifier.uri
http://hdl.handle.net/11336/112352
dc.description.abstract
The ability to predict and/or identify MHC binding peptides is an essential component of T cell epitope discovery, something that ultimately should benefit the development of vaccines and immunotherapies. In particular, MHC class I prediction tools have matured to a point where accurate selection of optimal peptide epitopes is possible for virtually all MHC class I allotypes; in comparison, current MHC class II (MHC-II) predictors are less mature. Because MHC-II restricted CD4+ T cells control and orchestrated most immune responses, this shortcoming severely hampers the development of effective immunotherapies. The ability to generate large panels of peptides and subsequently large bodies of peptide-MHC-II interaction data are key to the solution of this problem, a solution that also will support the improvement of bioinformatics predictors, which critically relies on the availability of large amounts of accurate, diverse, and representative data. In this study, we have used rHLA-DRB1*01:01 and HLA-DRB1*03:01 molecules to interrogate high-density peptide arrays, in casu containing 70,000 random peptides in triplicates. We demonstrate that the binding data acquired contains systematic and interpretable information reflecting the specificity of the HLA-DR molecules investigated, suitable of training predictors able to predict T cell epitopes and peptides eluted from human EBV-transformed B cells. Collectively, with a cost per peptide reduced to a few cents, combined with the flexibility of rHLA technology, this poses an attractive strategy to generate vast bodies of MHC-II binding data at an unprecedented speed and for the benefit of generating peptide-MHC-II binding data as well as improving MHC-II prediction tools.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Association of Immunologists
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
MHC class II
dc.subject
Peptide microarray
dc.subject
High throughput
dc.subject.classification
Otras Ciencias de la Salud
dc.subject.classification
Ciencias de la Salud
dc.subject.classification
CIENCIAS MÉDICAS Y DE LA SALUD
dc.title
HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-07-01T17:02:41Z
dc.journal.volume
205
dc.journal.number
1
dc.journal.pagination
290-299
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Osterbye, Thomas. Universidad de Copenhagen; Dinamarca
dc.description.fil
Fil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina
dc.description.fil
Fil: Dudek, Nadine L.. Monash University; Australia
dc.description.fil
Fil: Ramarathinam, Sri H.. Monash University; Australia
dc.description.fil
Fil: Purcell, Anthony W.. Monash University; Australia
dc.description.fil
Fil: Schafer-Nielsen, Claus. No especifíca;
dc.description.fil
Fil: Buus, Soren. University Of Copenhagen, Faculty Of Health Sciences;
dc.journal.title
Journal of Immunology
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.jimmunol.org/content/205/1/290
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.4049/jimmunol.2000224
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