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Development and application of EpitopeScan, a Python3 toolset for mutation tracking in SARS-CoV-2 immunogenic epitopes

Authors :
Alexander Kovalenko
Sebastien Viatte
Source :
Frontiers in Immunology, Vol 15 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

IntroductionOutbreaks of coronaviruses and especially the recent COVID-19 pandemic emphasize the importance of immunological research in this area to mitigate the effect of future incidents. Bioinformatics approaches are capable of providing multisided insights from virus sequencing data, although currently available software options are not entirely suitable for a specific task of mutation surveillance within immunogenic epitopes of SARS-CoV-2.MethodHere, we describe the development of a mutation tracker, EpitopeScan, a Python3 package with command line and graphical user interface tools facilitating the investigation of the mutation dynamics in SARS-CoV-2 epitopes via analysis of multiple-sequence alignments of genomes over time. We provide an application case by examining three Spike protein-derived immunodominant CD4+ T-cell epitopes restricted by HLA-DRB1*04:01, an allele strongly associated with susceptibility to rheumatoid arthritis (RA). Mutations in these peptides are relevant for immune monitoring of CD4+ T-cell responses against SARS-CoV-2 spike protein in patients with RA. The analysis focused on 2.3 million SARS-CoV-2 genomes sampled in England.ResultsWe detail cases of epitope conservation over time, partial loss of conservation, and complete divergence from the wild type following the emergence of the N969K Omicron-specific mutation in November 2021. The wild type and the mutated peptide represent potential candidates to monitor variant-specific CD4+ T-cell responses. EpitopeScan is available via GitHub repository https://github.com/Aleksandr-biochem/EpitopeScan.

Details

Language :
English
ISSN :
16643224
Volume :
15
Database :
Directory of Open Access Journals
Journal :
Frontiers in Immunology
Publication Type :
Academic Journal
Accession number :
edsdoj.2f07ad629af245c5bcbe64ff7d44b7bf
Document Type :
article
Full Text :
https://doi.org/10.3389/fimmu.2024.1356314