The Utility and Limitations of Current Web-Available Algorithms To Predict Peptides Recognized by CD4 T Cells in Response to Pathogen Infection

Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA.
The Journal of Immunology (Impact Factor: 4.92). 03/2012; 188(9):4235-48. DOI: 10.4049/jimmunol.1103640
Source: PubMed


The ability to track CD4 T cells elicited in response to pathogen infection or vaccination is critical because of the role these cells play in protective immunity. Coupled with advances in genome sequencing of pathogenic organisms, there is considerable appeal for implementation of computer-based algorithms to predict peptides that bind to the class II molecules, forming the complex recognized by CD4 T cells. Despite recent progress in this area, there is a paucity of data regarding the success of these algorithms in identifying actual pathogen-derived epitopes. In this study, we sought to rigorously evaluate the performance of multiple Web-available algorithms by comparing their predictions with our results--obtained by purely empirical methods for epitope discovery in influenza that used overlapping peptides and cytokine ELISPOTs--for three independent class II molecules. We analyzed the data in different ways, trying to anticipate how an investigator might use these computational tools for epitope discovery. We come to the conclusion that currently available algorithms can indeed facilitate epitope discovery, but all shared a high degree of false-positive and false-negative predictions. Therefore, efficiencies were low. We also found dramatic disparities among algorithms and between predicted IC(50) values and true dissociation rates of peptide-MHC class II complexes. We suggest that improved success of predictive algorithms will depend less on changes in computational methods or increased data sets and more on changes in parameters used to "train" the algorithms that factor in elements of T cell repertoire and peptide acquisition by class II molecules.

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Available from: Andrea Sant, Sep 27, 2014
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    • "An additional benchmarking dataset, based on influenza virus-specific CD4+ T-cell epitopes from five major influenza virus proteins in mice expressing a distinct set of class II molecules, was obtained from a recently published study [26]. For DR1-restricted epitopes (Additional file 1: Figure S3), both Predivac and NetMHCIIPan-2.0 reached a comparable accuracy (AUC 0.700), although Predivac delivered the highest specificity. "
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    ABSTRACT: Background CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge. Results We developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design. Conclusions The comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at:
    BMC Bioinformatics 02/2013; 14(1):52. DOI:10.1186/1471-2105-14-52 · 2.58 Impact Factor
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    • "Studies by our group have shown that the persistence of a peptide with MHC class II molecules is a key feature in determining its immunodominance in the elicited response [48], [50], [72], [73]. If this deterministic feature extends to Tfh cells, it may be possible to apply this relationship to the design of epitope-based vaccines to focus the Tfh response. "
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    ABSTRACT: T follicular helper (Tfh) cells potentiate high-affinity, class-switched antibody responses, the predominant correlate of protection from vaccines. Despite intense interest in understanding both the generation and effector functions of this lineage, little is known about the epitope specificity of Tfh cells generated during polyclonal responses. To date, studies of peptide-specific Tfh cells have relied on either the transfer of TcR transgenic cells or use of peptide∶MHC class II tetramers and antibodies to stain TcR and follow limited peptide specificities. In order to comprehensively evaluate polyclonal responses generated from the natural endogenous TcR repertoire, we developed a sorting strategy to separate Tfh cells from non-Tfh cells and found that their epitope-specific responses could be tracked with cytokine-specific ELISPOT assays. The immunodominance hierarchies of Tfh and non-Tfh cells generated in response to immunization with several unrelated protein antigens were remarkably similar. Additionally, increasing the kinetic stability of peptide-MHC class II complexes enhanced the priming of both Tfh and conventional CD4 T cells. These findings may provide us with a strategy to rationally and selectively modulate epitope-specific Tfh responses. By understanding the parameters that control epitope-specific priming, vaccines may be tailored to enhance or focus Tfh responses to facilitate optimal B cell responses.
    PLoS ONE 10/2012; 7(10):e46952. DOI:10.1371/journal.pone.0046952 · 3.23 Impact Factor
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    ABSTRACT: The adaptive immune response starts when CD4+ T cells recognize peptide antigens presented by class II molecules of the Major Histocompatibility Complex (MHCII). Two outstanding features of MHCII molecules are their polymorphism and the ability of each allele to bind a large panoply of peptides. The ability of each MHCII molecule to interact with a limited, though broad, range of amino acid sequences, or "permissive specificity" of binding, is the result of structural flexibility. This flexibility has been identified through biochemical and biophysical studies, and molecular dynamic simulations have modeled the conformational rearrangements that the peptide and the MHCII undergo during interaction. Moreover, there is evidence that the structural flexibility of the peptide/MHCII complex correlates with the activity of the "peptide-editing" molecule DM. In light of the impact that these recent findings have on our ability to predict MHCII epitopes, a review of the structural and thermodynamic determinants of peptide binding to MHCII is proposed.
    Immunologic Research 06/2012; 56(1). DOI:10.1007/s12026-012-8342-2 · 3.10 Impact Factor
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