PLoS ONE (Jan 2016)

Pooled-Peptide Epitope Mapping Strategies Are Efficient and Highly Sensitive: An Evaluation of Methods for Identifying Human T Cell Epitope Specificities in Large-Scale HIV Vaccine Efficacy Trials.

  • Andrew Fiore-Gartland,
  • Bryce A Manso,
  • David P Friedrich,
  • Erin E Gabriel,
  • Greg Finak,
  • Zoe Moodie,
  • Tomer Hertz,
  • Stephen C De Rosa,
  • Nicole Frahm,
  • Peter B Gilbert,
  • M Juliana McElrath

DOI
https://doi.org/10.1371/journal.pone.0147812
Journal volume & issue
Vol. 11, no. 2
p. e0147812

Abstract

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The interferon gamma, enzyme-linked immunospot (IFN-γ ELISpot) assay is widely used to identify viral antigen-specific T cells is frequently employed to quantify T cell responses in HIV vaccine studies. It can be used to define T cell epitope specificities using panels of peptide antigens, but with sample and cost constraints there is a critical need to improve the efficiency of epitope mapping for large and variable pathogens. We evaluated two epitope mapping strategies, based on group testing, for their ability to identify vaccine-induced T-cells from participants in the Step HIV-1 vaccine efficacy trial, and compared the findings to an approach of assaying each peptide individually. The group testing strategies reduced the number of assays required by >7-fold without significantly altering the accuracy of T-cell breadth estimates. Assays of small pools containing 7-30 peptides were highly sensitive and effective at detecting single positive peptides as well as summating responses to multiple peptides. Also, assays with a single 15-mer peptide, containing an identified epitope, did not always elicit a response providing validation that 15-mer peptides are not optimal antigens for detecting CD8+ T cells. Our findings further validate pooling-based epitope mapping strategies, which are critical for characterizing vaccine-induced T-cell responses and more broadly for informing iterative vaccine design. We also show ways to improve their application with computational peptide:MHC binding predictors that can accurately identify the optimal epitope within a 15-mer peptide and within a pool of 15-mer peptides.