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

نویسندگان

  • Jade Rai
  • Ka In Lok
  • Chun Yin Mok
  • Harvinder Mann
  • Mohammed Noor
  • Pritesh Patel
  • Darren R Flower
چکیده

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.

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عنوان ژورنال:

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2012