Comparison of experimental fine‐mapping to in silico prediction results of HIV‐1 epitopes reveals ongoing need for mapping experiments

Summary Methods for identifying physiologically relevant CD8 T‐cell epitopes are critically important not only for the development of T‐cell‐based vaccines but also for understanding host–pathogen interactions. As experimentally mapping an optimal CD8 T‐cell epitope is a tedious procedure, many bioi...

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Published inImmunology Vol. 143; no. 2; pp. 193 - 201
Main Authors Roider, Julia, Meissner, Tim, Kraut, Franziska, Vollbrecht, Thomas, Stirner, Renate, Bogner, Johannes R., Draenert, Rika
Format Journal Article
LanguageEnglish
Published England Wiley Subscription Services, Inc 01.10.2014
Blackwell Science Inc
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Online AccessGet full text
ISSN0019-2805
1365-2567
1365-2567
DOI10.1111/imm.12301

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Abstract Summary Methods for identifying physiologically relevant CD8 T‐cell epitopes are critically important not only for the development of T‐cell‐based vaccines but also for understanding host–pathogen interactions. As experimentally mapping an optimal CD8 T‐cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T‐cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV‐specific epitopes. Randomly – for any of the subjects' HLA type and with any matching score – the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA‐class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine‐mapping of a CD8 T‐cell epitope cannot yet be replaced.
AbstractList Summary Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host-pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi,ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly - for any of the subjects' HLA type and with any matching score - the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced. [PUBLICATION ABSTRACT]
Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host-pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly - for any of the subjects' HLA type and with any matching score - the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced.Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host-pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly - for any of the subjects' HLA type and with any matching score - the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced.
Methods for identifying physiologically relevant CD 8 T‐cell epitopes are critically important not only for the development of T‐cell‐based vaccines but also for understanding host–pathogen interactions. As experimentally mapping an optimal CD 8 T‐cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD 8 T‐cell epitope prediction tools syfpeithi , ctlpred and iedb to foretell nine experimentally mapped optimal HIV ‐specific epitopes. Randomly – for any of the subjects' HLA type and with any matching score – the optimal epitope was predicted in seven of nine epitopes using syfpeithi , in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb . The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi , in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA ‐class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine‐mapping of a CD 8 T‐cell epitope cannot yet be replaced.
Summary Methods for identifying physiologically relevant CD8 T‐cell epitopes are critically important not only for the development of T‐cell‐based vaccines but also for understanding host–pathogen interactions. As experimentally mapping an optimal CD8 T‐cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T‐cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV‐specific epitopes. Randomly – for any of the subjects' HLA type and with any matching score – the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA‐class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine‐mapping of a CD8 T‐cell epitope cannot yet be replaced.
Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host-pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly - for any of the subjects' HLA type and with any matching score - the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced.
Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host–pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi , ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly – for any of the subjects' HLA type and with any matching score – the optimal epitope was predicted in seven of nine epitopes using syfpeithi , in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb . The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi , in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced.
Author Bogner, Johannes R.
Stirner, Renate
Roider, Julia
Vollbrecht, Thomas
Meissner, Tim
Kraut, Franziska
Draenert, Rika
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Snippet Summary Methods for identifying physiologically relevant CD8 T‐cell epitopes are critically important not only for the development of T‐cell‐based vaccines but...
Methods for identifying physiologically relevant CD 8 T‐cell epitopes are critically important not only for the development of T‐cell‐based vaccines but also...
Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also...
Summary Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but...
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SubjectTerms AIDS Vaccines - immunology
CD4-Positive T-Lymphocytes - immunology
CD4-Positive T-Lymphocytes - virology
CD8 T cell
Cell Line
Computational Biology
Computer Simulation
epitope mapping
Epitope Mapping - methods
epitope prediction
Epitopes, T-Lymphocyte
Histocompatibility Antigens Class I - immunology
HIV-1 - immunology
HIV-1 - pathogenicity
Humans
Immunodominant Epitopes
MHC class I
optimal epitope
Original
Peptides
Reproducibility of Results
Software
Title Comparison of experimental fine‐mapping to in silico prediction results of HIV‐1 epitopes reveals ongoing need for mapping experiments
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fimm.12301
https://www.ncbi.nlm.nih.gov/pubmed/24724694
https://www.proquest.com/docview/1560548250
https://www.proquest.com/docview/1561035631
https://pubmed.ncbi.nlm.nih.gov/PMC4172136
Volume 143
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