Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses

We introduce a phylogeny-aware framework for predicting linear B-cell epitope (LBCE)-containing regions within proteins. Our approach leverages evolutionary information by using a taxonomic scaffold to build models trained on hierarchically structured data. The resulting models present performance equivalent or superior to generalist methods, despite using simpler features and a fraction of the data volume required by current state-of-the-art predictors. This allows the utilization of available data for major pathogen lineages to facilitate the prediction of LBCEs for emerging infectious agents. We demonstrate the efficacy of our approach by predicting new LBCEs in the monkeypox (MPXV) and vaccinia viruses. Experimental validation of selected targets using sera from infected patients confirms the presence of LBCEs, including candidates for the differential serodiagnosis of recent MPXV infections. These results point to the use of phylogeny-aware predictors as a useful strategy to facilitate the targeted development of immunodiagnostic tools.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2024-09-23
DOI
https://doi.org/10.1093/bib/bbae527
Citations
5
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
1.17

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article

Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses

Felipe Campelo, Giliane de Souza Trindade, Pedro Bastos, Felipe Campos de Melo Iani et al.
5 citations
Briefings in Bioinformatics
vaccines and immunoinformatics approaches
1.17
article

Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses

Felipe Campelo, Giliane de Souza Trindade, Pedro Bastos, Felipe Campos de Melo Iani, Ricardo Toshio Fujiwara, Ana Laura Grossi de Oliveira, Augusto César Parreiras de Jesus, Daniella Castanheira Bartholomeu, Talita Adelino, Francisco Pereira Lobo, Jodie Ashford, João Luís Reis-Cunha, Anikó Ekárt, Vanêssa Gomes Fraga, Marcos Vinícius Ferreira Silva, Lilian Lacerda Bueno
article en
5 citations

Abstract

We introduce a phylogeny-aware framework for predicting linear B-cell epitope (LBCE)-containing regions within proteins. Our approach leverages evolutionary information by using a taxonomic scaffold to build models trained on hierarchically structured data. The resulting models present performance equivalent or superior to generalist methods, despite using simpler features and a fraction of the data volume required by current state-of-the-art predictors. This allows the utilization of available data for major pathogen lineages to facilitate the prediction of LBCEs for emerging infectious agents. We demonstrate the efficacy of our approach by predicting new LBCEs in the monkeypox (MPXV) and vaccinia viruses. Experimental validation of selected targets using sera from infected patients confirms the presence of LBCEs, including candidates for the differential serodiagnosis of recent MPXV infections. These results point to the use of phylogeny-aware predictors as a useful strategy to facilitate the targeted development of immunodiagnostic tools.

Briefings in BioinformaticsVol. 25(6)
Universidade Federal de Minas Gerais (BR), Aston University (GB), Baylor College of Medicine (US), University of Bristol (GB), Institut des Sciences Biologiques (FR), Ezequiel Dias Foundation (BR), Biomedical Research Institute (US), University of York (GB)
Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Medical Research Council, Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 21%
vaccines and immunoinformatics approaches
1.17
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