Time for T? Immunoinformatics addresses vaccine design for neglected tropical and emerging infectious diseases

Terry, Frances; Moise, Leonard; Martin, Rebecca; Torres, Melissa; Pilotte, Nils; Williams, Steven A.; Groot, Anne S. De

doi:10.1586/14760584.2015.955478

Cited by 40 publications

(43 citation statements)

References 90 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The immunity associated with protection from these pathogens remains largely unknown to the researchers. So, the vaccine development against these newly emerging infectious diseases is demanding and challenging work (Terry et al, 2015). Therefore, the genome sequence screening of viral pathogens could be the potential step for the identification of vaccine target against the newly emerging infectious diseases.…”

Section: Discussionmentioning

confidence: 99%

“…So, the development of a vaccine against this infectious pathogen is more difficult and challenging work. Therefore, immunoinformatics study could be an effective approach for the screening of dominant immunogens from the available genome sequence data for effective vaccine design against emerging infectious and neglected tropical disease (Terry et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Overlapping CD8 + and CD4 + T-cell epitopes identification for the progression of epitope-based peptide vaccine from nucleocapsid and glycoprotein of emerging Rift Valley fever virus using immunoinformatics approach

Adhikari

Rahman

2017

Infection, Genetics and Evolution

View full text Add to dashboard Cite

Rift Valley fever virus (RVFV) is an emergent arthropod-borne zoonotic infectious viral pathogen which causes fatal diseases in the humans and ruminants. Currently, no effective and licensed vaccine is available for the prevention of RVFV infection in endemic as well as in non-endemic regions. So, an immunoinformatics-driven genome-wide screening approach was performed for the identification of overlapping CD8+ and CD4+ T-cell epitopes and also linear B-cell epitopes from the conserved sequences of the nucleocapsid (N) and glycoprotein (G) of RVFV. We identified overlapping 99.39% conserved 1 CD8+ T-cell epitope (MMHPSFAGM) from N protein and 100% conserved 7 epitopes (AVFALAPVV, LAVFALAPV, FALAPVVFA, VFALAPVVF, IAMTVLPAL, FFDWFSGLM, and FLLIYLGRT) from G protein and also identified IL-4 and IFN-γ induced (99.39% conserved) 1 N protein CD4+ T-cell epitope (HMMHPSFAGMVDPSL) and 100% conserved 5 G protein CD4+ T-cell epitopes (LPALAVFALAPVVFA, PALAVFALAPVVFAE, GIAMTVLPALAVFAL, GSWNFFDWFSGLMSW, and FFLLIYLGRTGLSKM). The overlapping CD8+ and CD4+ T-cell epitopes were bound with most conserved HLA-C*12:03 and HLA-DRB1*01:01, respectively with the high binding affinity (kcal/mol). The combined population coverage analysis revealed that the allele frequencies of these epitopes are high in endemic and non-endemic regions. Besides, we found 100% conserved and non-allergenic 2 decamer B-cell epitopes, GVCEVGVQAL and RVFNCIDWVH of G protein had the sequence similarity with the nonamer CD8+ T-cell epitopes, VCEVGVQAL and RVFNCIDWV, respectively. Consequently, these epitopes may be used for the development of epitope-based peptide vaccine against emerging RVFV. However, in vivo and in vitro experiments are required for their efficient use as a vaccine.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Overlapping CD8 + and CD4 + T-cell epitopes identification for the progression of epitope-based peptide vaccine from nucleocapsid and glycoprotein of emerging Rift Valley fever virus using immunoinformatics approach

Adhikari

Rahman

2017

Infection, Genetics and Evolution

View full text Add to dashboard Cite

show abstract

“…It uses PigMatrix, an algorithm that predicts class I and II T‐cell epitopes specific to swine MHC (Swine Leukocyte Antigen, SLA) alleles while also analyzing the TCR‐facing residues of T‐cell epitopes, to predict and assess epitope similarities between input pathogen protein sequences. PigMatrix and associated tools that comprise the iVAX vaccine design toolkit were previously validated in retrospective and prospective studies of SLA‐restricted influenza epitopes . Here, we used EpiCC to determine the T‐cell epitope relatedness of HA proteins from 23 swine IAV strains representing the major H1 phylo‐clusters circulating in the North American swine population.…”

Section: Introductionmentioning

confidence: 99%

T‐cell epitope content comparison (EpiCC) of swine H1 influenza A virus hemagglutinin

Gutiérrez

Rapp-Gabrielson

Terry

et al. 2017

Influenza Resp Viruses

Self Cite

View full text Add to dashboard Cite

BackgroundPredicting vaccine efficacy against emerging pathogen strains is a significant problem in human and animal vaccine design. T‐cell epitope cross‐conservation may play an important role in cross‐strain vaccine efficacy. While influenza A virus (IAV) hemagglutination inhibition (HI) antibody titers are widely used to predict protective efficacy of 1 IAV vaccine against new strains, no similar correlate of protection has been identified for T‐cell epitopes.ObjectiveWe developed a computational method (EpiCC) that facilitates pairwise comparison of protein sequences based on an immunological property—T‐cell epitope content—rather than sequence identity, and evaluated its ability to classify swine IAV strain relatedness to estimate cross‐protective potential of a vaccine strain for circulating viruses.MethodsT‐cell epitope relatedness scores were assessed for 23 IAV HA sequences representing the major H1 swine IAV phylo‐clusters circulating in North American swine and HA sequences in a commercial inactivated vaccine (FluSure XP ®). Scores were compared to experimental data from previous efficacy studies.ResultsHigher EpiCC scores were associated with greater protection by the vaccine against strains for 23 field IAV strain vaccine comparisons. A threshold for EpiCC relatedness associated with full or partial protection in the absence of cross‐reactive HI antibodies was identified. EpiCC scores for field strains for which FluSure protective efficacy is not yet available were also calculated.ConclusionEpiCC thresholds can be evaluated for predictive accuracy of protection in future efficacy studies. EpiCC may also complement HI cross‐reactivity and phylogeny for selection of influenza strains in vaccine development.

show abstract

“…Nevertheless, for emerging highly pathogenic pathogens, like MERS-CoV, H5N1, and H7N9, although their genome sequences are available in GenBank database, their immunity associated with protection is currently largely unknown. These gaps in understanding immune protection make developing vaccines against these highly pathogenic viruses more difficult and challenging [26]. Therefore, an immunoinformatics-driven approach to thoroughly screen the dominant immunogens based on available genome sequences data of pathogens is essential and promising for effective vaccine design of emerging infectious diseases [26].…”

Section: Introductionmentioning

confidence: 99%

Epitope-Based Vaccine Target Screening against Highly Pathogenic MERS-CoV: An In Silico Approach Applied to Emerging Infectious Diseases

et al. 2015

View full text Add to dashboard Cite

Middle East respiratory syndrome coronavirus (MERS-CoV) with pandemic potential is a major worldwide threat to public health. However, vaccine development for this pathogen lags behind as immunity associated with protection is currently largely unknown. In this study, an immunoinformatics-driven genome-wide screening strategy of vaccine targets was performed to thoroughly screen the vital and effective dominant immunogens against MERS-CoV. Conservancy and population coverage analysis of the epitopes were done by the Immune Epitope Database. The results showed that the nucleocapsid (N) protein of MERS-CoV might be a better protective immunogen with high conservancy and potential eliciting both neutralizing antibodies and T-cell responses compared with spike (S) protein. Further, the B-cell, helper T-cell and cytotoxic T lymphocyte (CTL) epitopes were screened and mapped to the N protein. A total of 15 linear and 10 conformal B-cell epitopes that may induce protective neutralizing antibodies were obtained. Additionally, a total of 71 peptides with 9-mer core sequence were identified as helper T-cell epitopes, and 34 peptides were identified as CTL epitopes. Based on the maximum HLA binding alleles, top 10 helper T-cell epitopes and CTL epitopes that may elicit protective cellular immune responses against MERS-CoV were selected as MERS vaccine candidates. Population coverage analysis showed that the putative helper T-cell epitopes and CTL epitopes could cover the vast majority of the population in 15 geographic regions considered where vaccine would be employed. The B- and T-cell stimulation potentials of the screened epitopes is to be further validated for their efficient use as vaccines against MERS-CoV. Collectively, this study provides novel vaccine target candidates and may prompt further development of vaccines against MERS-CoV and other emerging infectious diseases.

show abstract

Time for T? Immunoinformatics addresses vaccine design for neglected tropical and emerging infectious diseases

Cited by 40 publications

References 90 publications

Overlapping CD8 + and CD4 + T-cell epitopes identification for the progression of epitope-based peptide vaccine from nucleocapsid and glycoprotein of emerging Rift Valley fever virus using immunoinformatics approach

Overlapping CD8 + and CD4 + T-cell epitopes identification for the progression of epitope-based peptide vaccine from nucleocapsid and glycoprotein of emerging Rift Valley fever virus using immunoinformatics approach

T‐cell epitope content comparison (EpiCC) of swine H1 influenza A virus hemagglutinin

Epitope-Based Vaccine Target Screening against Highly Pathogenic MERS-CoV: An In Silico Approach Applied to Emerging Infectious Diseases

Contact Info

Product

Resources

About