TY - JOUR
T1 - Identification of HLA-E Binding Mycobacterium tuberculosis-Derived Epitopes through Improved Prediction Models
AU - Ruibal, Paula
AU - Franken, Kees L.M.C.
AU - van Meijgaarden, Krista E.
AU - van Wolfswinkel, Marjolein
AU - Derksen, Ian
AU - Scheeren, Ferenc A.
AU - van Veelen, Peter A.
AU - Abeel, Thomas
AU - Joosten, Simone A.
AU - More Authors, null
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2022
Y1 - 2022
N2 - Tuberculosis (TB) remains one of the deadliest infectious diseases worldwide, posing great social and economic burden to affected countries. Novel vaccine approaches are needed to increase protective immunity against the causative agent Mycobacterium tuberculosis (Mtb) and to reduce the development of active TB disease in latently infected individuals. Donor-unrestricted T cell responses represent such novel potential vaccine targets. HLA-E-restricted T cell responses have been shown to play an important role in protection against TB and other infections, and recent studies have demonstrated that these cells can be primed in vitro. However, the identification of novel pathogen-derived HLA-E binding peptides presented by infected target cells has been limited by the lack of accurate prediction algorithms for HLA-E binding. In this study, we developed an improved HLA-E binding peptide prediction algorithm and implemented it to identify (to our knowledge) novel Mtb-derived peptides with capacity to induce CD8+ T cell activation and that were recognized by specific HLA-E-restricted T cells in Mycobacterium-exposed humans. Altogether, we present a novel algorithm for the identification of pathogen- or self-derived HLA-E-presented peptides.
AB - Tuberculosis (TB) remains one of the deadliest infectious diseases worldwide, posing great social and economic burden to affected countries. Novel vaccine approaches are needed to increase protective immunity against the causative agent Mycobacterium tuberculosis (Mtb) and to reduce the development of active TB disease in latently infected individuals. Donor-unrestricted T cell responses represent such novel potential vaccine targets. HLA-E-restricted T cell responses have been shown to play an important role in protection against TB and other infections, and recent studies have demonstrated that these cells can be primed in vitro. However, the identification of novel pathogen-derived HLA-E binding peptides presented by infected target cells has been limited by the lack of accurate prediction algorithms for HLA-E binding. In this study, we developed an improved HLA-E binding peptide prediction algorithm and implemented it to identify (to our knowledge) novel Mtb-derived peptides with capacity to induce CD8+ T cell activation and that were recognized by specific HLA-E-restricted T cells in Mycobacterium-exposed humans. Altogether, we present a novel algorithm for the identification of pathogen- or self-derived HLA-E-presented peptides.
UR - http://www.scopus.com/inward/record.url?scp=85139398864&partnerID=8YFLogxK
U2 - 10.4049/jimmunol.2200122
DO - 10.4049/jimmunol.2200122
M3 - Article
C2 - 36096642
AN - SCOPUS:85139398864
VL - 209
SP - 1555
EP - 1565
JO - Journal of immunology (Baltimore, Md. : 1950)
JF - Journal of immunology (Baltimore, Md. : 1950)
SN - 0022-1767
IS - 8
ER -
