SILVI, an open-source pipeline for T-cell epitope selection

Autor: Pissarra, Joana, Dorkeld, Franck, Loire, Etienne, Bonhomme, Vincent, Sereno, Denis, Lemesre, Jean-Loup, Holzmuller, Philippe
Přispěvatelé: Interactions hôtes-vecteurs-parasites-environnement dans les maladies tropicales négligées dues aux trypanosomatides (UMR INTERTRYP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université de Bordeaux (UB), Centre de Biologie pour la Gestion des Populations (UMR CBGP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), This research received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642609, from the French National Research Institute for Sustainable Development (Institut de Recherche pour le Developpement), and from the French Government (Agence Nationale de la Recherche) Investissement d'Avenir programme, Laboratoire d'Excellence (LabEx) 'French Parasitology Alliance For Health Care' (ANR-11-LABX-0024, PARAFRAP)., ANR-11-LABX-0024,ParaFrap,Alliance française contre les maladies parasitaires(2011), European Project: 642609,H2020,H2020-MSCA-ITN-2014,EUROLEISH-NET(2015)
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: PLoS ONE
PLoS ONE, 2022, 17 (9), pp.e0273494. ⟨10.1371/journal.pone.0273494⟩
PloS One
ISSN: 1932-6203
Popis: The first release of the SILVI script generated during the current study, including the source code and all data files, are publicly available in the GitHub repository (https://github.com/JoanaPissarra/SILVI2020) and the Zenodo repository (https://doi.org/10.5281/zenodo.6865909).; International audience; High-throughput screening of available genomic data and identification of potential antigenic candidates have promoted the development of epitope-based vaccines and therapeutics. Several immunoinformatic tools are available to predict potential epitopes and other immunogenicity-related features, yet it is still challenging and time-consuming to compare and integrate results from different algorithms. We developed the R script SILVI (short for: from in silico to in vivo ), to assist in the selection of the potentially most immunogenic T-cell epitopes from Human Leukocyte Antigen (HLA)-binding prediction data. SILVI merges and compares data from available HLA-binding prediction servers, and integrates additional relevant information of predicted epitopes, namely BLASTp alignments with host proteins and physical-chemical properties. The two default criteria applied by SILVI and additional filtering allow the fast selection of the most conserved, promiscuous, strong binding T-cell epitopes. Users may adapt the script at their discretion as it is written in open-source R language. To demonstrate the workflow and present selection options, SILVI was used to integrate HLA-binding prediction results of three example proteins, from viral, bacterial and parasitic microorganisms, containing validated epitopes included in the Immune Epitope Database (IEDB), plus the Human Papillomavirus (HPV) proteome. Applying different filters on predicted IC50, hydrophobicity and mismatches with host proteins allows to significantly reduce the epitope lists with favourable sensitivity and specificity to select immunogenic epitopes. We contemplate SILVI will assist T-cell epitope selections and can be continuously refined in a community-driven manner, helping the improvement and design of peptide-based vaccines or immunotherapies. SILVI development version is available at: https://github.com/JoanaPissarra/SILVI2020 and https://doi.org/10.5281/zenodo.6865909 .
Databáze: OpenAIRE
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