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A general approach for predicting protein epitopes targeted by antibody repertoires using whole proteomes.
Paull, Michael L; Johnston, Tim; Ibsen, Kelly N; Bozekowski, Joel D; Daugherty, Patrick S.
Afiliação
  • Paull ML; Department of Chemical Engineering, University of California Santa Barbara, California, United States of America.
  • Johnston T; Department of Chemical Engineering, University of California Santa Barbara, California, United States of America.
  • Ibsen KN; Department of Chemical Engineering, University of California Santa Barbara, California, United States of America.
  • Bozekowski JD; Department of Chemical Engineering, University of California Santa Barbara, California, United States of America.
  • Daugherty PS; Department of Chemical Engineering, University of California Santa Barbara, California, United States of America.
PLoS One ; 14(9): e0217668, 2019.
Article em En | MEDLINE | ID: mdl-31490930
ABSTRACT
Antibodies are essential to functional immunity, yet the epitopes targeted by antibody repertoires remain largely uncharacterized. To aid in characterization, we developed a generalizable strategy to predict antibody-binding epitopes within individual proteins and entire proteomes. Specifically, we selected antibody-binding peptides for 273 distinct sera out of a random library and identified the peptides using next-generation sequencing. To predict antibody-binding epitopes and the antigens from which these epitopes were derived, we tiled the sequences of candidate antigens into short overlapping subsequences of length k (k-mers). We used the enrichment over background of these k-mers in the antibody-binding peptide dataset to predict antibody-binding epitopes. As a positive control, we used this approach, termed K-mer Tiling of Protein Epitopes (K-TOPE), to predict epitopes targeted by monoclonal and polyclonal antibodies of well-characterized specificity, accurately recovering their known epitopes. K-TOPE characterized a commonly targeted antigen from Rhinovirus A, predicting four epitopes recognized by antibodies present in 87% of sera (n = 250). An analysis of 2,908 proteins from 400 viral taxa that infect humans predicted seven enterovirus epitopes and five Epstein-Barr virus epitopes recognized by >30% of specimens. Analysis of Staphylococcus and Streptococcus proteomes similarly predicted 22 epitopes recognized by >30% of specimens. Twelve of these common viral and bacterial epitopes agreed with previously mapped epitopes with p-values < 0.05. Additionally, we predicted 30 HSV2-specific epitopes that were 100% specific against HSV1 in novel and previously reported antigens. Experimentally validating these candidate epitopes could help identify diagnostic biomarkers, vaccine components, and therapeutic targets. The K-TOPE approach thus provides a powerful new tool to elucidate the organisms, antigens, and epitopes targeted by human antibody repertoires.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoma / Análise de Sequência de Proteína / Proteômica / Epitopos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Child / Humans / Middle aged Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoma / Análise de Sequência de Proteína / Proteômica / Epitopos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Child / Humans / Middle aged Idioma: En Ano de publicação: 2019 Tipo de documento: Article