Dataset Information

Identification of CD8⁺ T cell epitopes through proteasome cleavage site predictions.

ABSTRACT:

Background

We previously introduced PCPS (Proteasome Cleavage Prediction Server), a web-based tool to predict proteasome cleavage sites using n-grams. Here, we evaluated the ability of PCPS immunoproteasome cleavage model to discriminate CD8⁺ T cell epitopes.

Results

We first assembled an epitope dataset consisting of 844 unique virus-specific CD8⁺ T cell epitopes and their source proteins. We then analyzed cleavage predictions by PCPS immunoproteasome cleavage model on this dataset and compared them with those provided by a related method implemented by NetChop web server. PCPS was clearly superior to NetChop in term of sensitivity (0.89 vs. 0.79) but somewhat inferior with regard to specificity (0.55 vs. 0.60). Judging by the Mathew's Correlation Coefficient, PCPS predictions were overall superior to those provided by NetChop (0.46 vs. 0.39). We next analyzed the power of C-terminal cleavage predictions provided by the same PCPS model to discriminate CD8⁺ T cell epitopes, finding that they could be discriminated from random peptides with an accuracy of 0.74. Following these results, we tuned the PCPS web server to predict CD8⁺ T cell epitopes and predicted the entire SARS-CoV-2 epitope space.

Conclusions

We report an improved version of PCPS named iPCPS for predicting proteasome cleavage sites and peptides with CD8⁺ T cell epitope features. iPCPS is available for free public use at https://imed.med.ucm.es/Tools/pcps/ .

SUBMITTER: Gomez-Perosanz M

PROVIDER: S-EPMC7733697 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundRespiratory syncytial virus (RSV) is the most common cause of viral lower respiratory tract infections (LRTIs) in young children around the world and an important cause of LRTI in the elderly. The available treatments and FDA-approved vaccines for RSV only lessen the severity of the infection and are recommended for infants and elderly people.MethodsWe focused on developing a broad-spectrum vaccine that activates the immune system to directly combat RSV. The objective of this study is to identify CD4+ and CD8+ T-cell epitopes using an immunoinformatics approach to develop RSV vaccines. The efficacy of these peptides was validated through in-vitro and in-vivo studies involving healthy and diseased animal models.ResultsFor each major histocompatibility complex (MHC) class-I and II, we found three epitopes of RSV proteins including F, G, and SH with an antigenic score of >0.5 and a projected SVM score of <5. Experimental validation of these peptides on female BALB/c mice was conducted before and after infection with the RSV A2 line 19f. We found that the 3RVMHCI (CD8+) epitope of the F protein showed significant results of white blood cells (19.72 × 103 cells/μl), neutrophils (6.01 × 103 cells/μl), lymphocytes (12.98 × 103 cells/μl), IgG antibodies (36.9 µg/ml), IFN-γ (86.96 ng/L), and granzyme B (691.35 pg/ml) compared to control at the second booster dose of 10 µg. Similarly, 4RVMHCII (CD4+) of the F protein substantially induced white blood cells (27.08 × 103 cells/μl), neutrophils (6.58 × 103 cells/μl), lymphocytes (16.64 × 103 cells/μl), IgG antibodies (46.13 µg/ml), IFN-γ (96.45 ng/L), and granzyme B (675.09 pg/ml). In-vitro studies showed that 4RVMHCII produced a significant level of antibodies in sera on day 45 comparable to mice infected with the virus. 4RVMHCII also induced high IFN-γ and IL-2 secretions on the fourth day of the challenge compared to the preinfectional stage.ConclusionIn conclusion, epitopes of the F protein showed considerable immune response and are suitable for further validation.

Project description:Examining CD8+ and CD4+ T cell responses after primary Yellow Fever vaccination in a cohort of 210 volunteers, we have identified and tetramer-validated 92 CD8+ and 50 CD4+ T cell epitopes, many inducing strong and prevalent (i.e., immunodominant) T cell responses. Restricted by 40 and 14 HLA-class I and II allotypes, respectively, these responses have wide population coverage and might be of considerable academic, diagnostic and therapeutic interest. The broad coverage of epitopes and HLA overcame the otherwise confounding effects of HLA diversity and non-HLA background providing the first evidence of T cell immunodomination in humans. Also, double-staining of CD4+ T cells with tetramers representing the same HLA-binding core, albeit with different flanking regions, demonstrated an extensive diversification of the specificities of many CD4+ T cell responses. We suggest that this could reduce the risk of pathogen escape, and that multi-tetramer staining is required to reveal the true magnitude and diversity of CD4+ T cell responses. Our T cell epitope discovery approach uses a combination of (1) overlapping peptides representing the entire Yellow Fever virus proteome to search for peptides containing CD4+ and/or CD8+ T cell epitopes, (2) predictors of peptide-HLA binding to suggest epitopes and their restricting HLA allotypes, (3) generation of peptide-HLA tetramers to identify T cell epitopes, and (4) analysis of ex vivo T cell responses to validate the same. This approach is systematic, exhaustive, and can be done in any individual of any HLA haplotype. It is all-inclusive in the sense that it includes all protein antigens and peptide epitopes, and encompasses both CD4+ and CD8+ T cell epitopes. It is efficient and, importantly, reduces the false discovery rate. The unbiased nature of the T cell epitope discovery approach presented here should support the refinement of future peptide-HLA class I and II predictors and tetramer technologies, which eventually should cover all HLA class I and II isotypes. We believe that future investigations of emerging pathogens (e.g., SARS-CoV-2) should include population-wide T cell epitope discovery using blood samples from patients, convalescents and/or long-term survivors, who might all hold important information on T cell epitopes and responses.

Dataset Information

Identification of CD8⁺ T cell epitopes through proteasome cleavage site predictions.

Background

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Identification of CD8+ T cell epitopes through proteasome cleavage site predictions.

Background

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Identification of CD8⁺ T cell epitopes through proteasome cleavage site predictions.