TepiTool: A Pipeline for Computational Prediction of T Cell Epitope Candidates

Paul, Sinu; Sidney, John; Sette, Alessandro; Peters, Bjoern

doi:10.1002/cpim.12

Cited by 183 publications

(148 citation statements)

References 76 publications

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“…In the case of T cell epitopes, we utilized predictive algorithms Paul et al, 2016) to map hundreds of potential human epitopes to account for HLA polymorphism and for the fact that T cell epitopes are typically derived from both structural and non-structural proteins and not limited to exposed regions. Here, as an independent validation of the predictions, we asked whether the predictions effectively identified the relatively few epitopes identified experimentally in SARS-CoV, restricted by human HLA, and conserved in SARS-CoV-2.…”

Section: Discussionmentioning

confidence: 99%

“…To predict CD4 T cell epitopes, we used the method described by Paul and co-authors (Paul et al, 2015a), as implemented in the Tepitool resource in IEDB (Paul et al, 2016). This approach was designed and validated to predict dominant epitopes independently of ethnicity and HLA polymorphism, taking advantage of the extensive cross-reactivity and repertoire overlap between different HLA class II loci and allelic variants.…”

Section: Prediction Of Sars-cov-2 T Cell Epitopesmentioning

confidence: 99%

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A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

Grifoni

Sidney

Zhang

et al. 2020

Cell Host & Microbe

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975

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Graphical Abstract Highlights d Ten experimentally defined regions within SARS-CoV have high homology with SARS-CoV-2 d Parallel bioinformatics predicted potential B and T cell epitopes for SARS-CoV-2 d Independent approaches identified the same immunodominant regions d The conserved immune regions have implications for vaccine design against multiple CoVs SUMMARYEffective countermeasures against the recent emergence and rapid expansion of the 2019 novel coronavirus (SARS-CoV-2) require the development of data and tools to understand and monitor its spread and immune responses to it. However, little information is available about the targets of immune responses to SARS-CoV-2. We used the Immune Epitope Database and Analysis Resource (IEDB) to catalog available data related to other coronaviruses. This includes SARS-CoV, which has high sequence similarity to SARS-CoV-2 and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in SARS-CoV-2 that have high homology to the SARS-CoV virus. Parallel bioinformatic predictions identified a priori potential B and T cell epitopes for SARS-CoV-2. The independent identification of the same regions using two approaches reflects the high probability that these regions are promising targets for immune recognition of SARS-CoV-2. These predictions can facilitate effective vaccine design against this virus of high priority.

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Section: Discussionmentioning

confidence: 99%

Section: Prediction Of Sars-cov-2 T Cell Epitopesmentioning

confidence: 99%

A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

Grifoni

Sidney

Zhang

et al. 2020

Cell Host & Microbe

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975

1,202

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“…This is in a proven practical manner in vaccine development. 19,37,[42][43][44][45][46][47][48][49][50][51][52] The issues of genetic polymorphism, as well as potential harmful constituents, are amplified in full-length natural proteins (Tables 1-4; Fig. 1, S1-S5).…”

Section: Discussionmentioning

confidence: 99%

Protein nanovaccine confers robust immunity against Toxoplasma

Bissati

Zhou

Paulillo³

et al. 2017

npj Vaccines

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We designed and produced a self-assembling protein nanoparticle. This self-assembling protein nanoparticle contains five CD8+ HLA-A03-11 supertypes-restricted epitopes from antigens expressed during Toxoplasma gondii’s lifecycle, the universal CD4+ T cell epitope PADRE, and flagellin as a scaffold and TLR5 agonist. These CD8+ T cell epitopes were separated by N/KAAA spacers and optimized for proteasomal cleavage. Self-assembling protein nanoparticle adjuvanted with TLR4 ligand-emulsion GLA-SE were evaluated for their efficacy in inducing IFN-γ responses and protection of HLA-A*1101 transgenic mice against T. gondii. Immunization, using self-assembling protein nanoparticle-GLA-SE, activated CD8+ T cells to produce IFN-γ. Self-assembling protein nanoparticle-GLA-SE also protected HLA-A*1101 transgenic mice against subsequent challenge with Type II parasites. Hence, combining CD8+ T cell-eliciting peptides and PADRE into a multi-epitope protein that forms a nanoparticle, administered with GLA-SE, leads to efficient presentation by major histocompatibility complex Class I and II molecules. Furthermore, these results suggest that activation of TLR4 and TLR5 could be useful for development of vaccines that elicit T cells to prevent toxoplasmosis in humans.

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“…We selected a set of 9mer and 10mer ZIKV peptides predicted to bind one or more of 27 HLA class I A and B allelic variants, which were chosen because of their high prevalence in the general population, as previously described (10). Class I binding predictions were done with Tepitool using the consensus method (53,54). For each allele, and considering 9mers and 10mers separately, the top 2% scoring peptides (n ϭ 68) based on predicted percentile rank were selected; the final set synthesized had 1,836 (68 ϫ 27) 9mers and 10mers each, for a total of 3,672 peptides (A&A, San Diego, CA).…”

Section: Methodsmentioning

confidence: 99%

Prior Dengue Virus Exposure Shapes T Cell Immunity to Zika Virus in Humans

Grifoni

Pham

Sidney

et al. 2017

J Virol

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154

214

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While progress has been made in characterizing humoral immunity to Zika virus (ZIKV) in humans, little is known regarding the corresponding T cell responses to ZIKV. Here, we investigate the kinetics and viral epitopes targeted by T cells responding to ZIKV and address the critical question of whether preexisting dengue virus (DENV) T cell immunity modulates these responses. We find that memory T cell responses elicited by prior infection with DENV or vaccination with tetravalent dengue attenuated vaccines (TDLAV) recognize ZIKV-derived peptides. This cross-reactivity is explained by the sequence similarity of the two viruses, as the ZIKV peptides recognized by DENV-elicited memory T cells are identical or highly conserved in DENV and ZIKV. DENV exposure prior to ZIKV infection also influences the timing and magnitude of the T cell response. ZIKV-reactive T cells in the acute phase of infection are detected earlier and in greater magnitude in DENV-immune patients. Conversely, the frequency of ZIKV-reactive T cells continues to rise in the convalescent phase in DENV-naive donors but declines in DENV-preexposed donors, compatible with more efficient control of ZIKV replication and/or clearance of ZIKV antigen. The quality of responses is also influenced by previous DENV exposure, and ZIKV-specific CD8 T cells from DENV-preexposed donors selectively upregulated granzyme B and PD1, unlike DENV-naive donors. Finally, we discovered that ZIKV

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TepiTool: A Pipeline for Computational Prediction of T Cell Epitope Candidates

Cited by 183 publications

References 76 publications

A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

Protein nanovaccine confers robust immunity against Toxoplasma

Prior Dengue Virus Exposure Shapes T Cell Immunity to Zika Virus in Humans

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