Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates: E coli 536

Aston Pharmacy School, Life and Health Sciences, Aston University, Aston Triangle, Birmingham, B4 7ET, UK.
Bioinformation (Impact Factor: 0.5). 03/2012; 8(6):272-5. DOI: 10.6026/97320630008272
Source: PubMed


Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify
antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell
epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major
Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated
by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model
pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach
was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences
that bind across more than one HLA allele with high affinity (IC50 < 50nM). The reliability of software programmes used,
polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

Download full-text


Available from: Darren Flower, Oct 01, 2015
1 Follower
33 Reads
  • Source
    • "While in silico planning has been found to greatly facilitate peptide design, not all peptides predicted in silico are optimally immunogenic in vivo[41] and it remains essential to test predicted peptides in vivo so as to ascertain that the needed T-cell response is elicited. Numerous in silico studies have shown the value of using prediction programs to assess the efficiency of binding of putative epitopes to human alleles [42-45]. Also, [46] showed an increase in the use of in silico prediction studies with an improvement of epitope prediction programs available. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Host genetics influence the outcome of HCV disease. HCV is also highly mutable and escapes host immunity. HCV genotypes are geographically distributed and HCV subtypes have been shown to have distinct repertoires of HLA-restricted viral epitopes which explains the lack of cross protection across genotypes observed in some studies. Despite this, immune databases and putative epitope vaccines concentrate almost exclusively on HCV genotype 1 class I-epitopes restricted by the HLA-A*02 allele. While both genotype and allele predominate in developed countries, we hypothesise that HCV variation and population genetics will affect the efficacy of proposed epitope vaccines in South Africa. This in silico study investigates HCV viral variability within well-studied epitopes identified in genotype 1 and uses algorithms to predict the immunogenicity of their variants from other less studied genotypes and thus rate the most promising vaccine candidates for the South African population. Six class I- and seven class II- restricted epitope sequences within the core, NS3, NS4B and NS5B regions were compared across the six HCV genotypes using local genotype 5a sequence data together with global data. Common HLA alleles in the South African population are A30:01, A02:01, B58:02, B07:02; DRB1*13:01 and DRB1*03:01. Epitope binding to 13 class I- and 8 class –II alleles were described using web-based prediction servers, Immune Epitope Database, (IEDB) and Propred. Online population coverage tools were used to assess vaccine efficacy. Results Despite the homogeneity of genotype 1 and genotype 5 over the epitopes, there was limited promiscuity to local HLA-alleles.Host differences will make a putative vaccine less effective in South Africa. Of the 6 well-characterized class I- epitopes, only 2 class I- epitopes were promiscuous and 3 of the 7 class-II epitopes were better conserved and promiscuous. By fine tuning the putative vaccine using an optimal cocktail of genotype 1 and 5a epitopes and local HLA data, the coverage was raised from 65.85% to 91.87% in South African Blacks. Conclusion While in vivo and in vitro studies are needed to confirm immunogenic epitopes, in silico HCV epitope vaccine design which takes into account HCV variation and host allele frequency will maximize population coverage in different ethnic groups.
    BMC Immunology 12/2012; 13(1):67. DOI:10.1186/1471-2172-13-67 · 2.48 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Melanoma antigens are immunogens expressed in various malignancies but silenced in somatic tissues. They are grouped into ten subfamilies and at least one subfamily is expressed in a cancer type. Given the specificity of in silico epitope targets previously used in vaccine technology against MAGE protein family, peptide length, epitope conservation and HLA allele diversity studies have not been performed. This in silico study is the first focusing on conserved epitopes design across HLA alleles for the MAGE proteins family with aim to analyze domain distribution and conservation through ClustalO, Jalview 2.7 and Cytoscape 2.8.3 routine stand alone software, analyze protein sequence topology through TMHMM server 2.0 and identify universal B and T cell epitopes via a pipeline of predictive servers (BCPREDS, IEDB, ProPred-I, ProPred, MHCPred 2.0 and T-EPITOPE designer) and tested for antigenicity using VaxiJen 2.0 server. There was a notable absence of strong MAGE Homology Domain conservation which could be explained as a consequence of weak functional constraints during gene evolution. Twenty predicted antigenic B cell epitopes (18-20-mers) from individual sub families derived >10 T cell epitopes (8-15-mers) binding to human leukocyte antigen alleles; HLA-A*0201, -A*0204, -B*2705, -DRB1*0101, and -DRB1*0401. Eight and nine monomer T cell epitopes were found to be the most conserved with 9 monomers having the highest coverage for HLA allele types and different MAGE protein subclasses thus making them universal epitopes for MAGE Proteins. However, other epitopes (10-15-mers) are only conserved within subclasses. These findings will inform the design of a multivalent universal MAGE vaccine that targets many tumors. Our pipeline confirms some reported epitopes (from in vitro studies) thus showing the efficacy of using in silico tools in epitope prediction
  • [Show abstract] [Hide abstract]
    ABSTRACT: Urinary tract infections (UTIs) are among the most common of bacterial infections in humans. Although a number of Gram-negative bacteria can cause UTIs, most cases are due to infection by uropathogenic E. coli (UPEC). Genomic studies have shown that UPEC encode a number of specialized activities that allow the bacteria to initiate and maintain infections in the environment of the urinary tract. Proteomic analyses have complemented the genomic data and have documented differential patterns of protein synthesis for bacteria growing ex vivo in human urine or recovered directly from the urinary tracts of infected mice. These studies provide valuable insights into the molecular basis of UPEC pathogenesis and have aided the identification of putative vaccine targets. Despite the substantial progress that has been achieved, many future challenges remain in the application of proteomics to provide a comprehensive view of bacterial pathogenesis in both acute and chronic UTIs.
    Expert Review of Proteomics 01/2014; 11(1). DOI:10.1586/14789450.2014.877845 · 2.90 Impact Factor
Show more