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DataSheet_4_Development and application of EpitopeScan, a Python3 toolset for mutation tracking in SARS-CoV-2 immunogenic epitopes.zip

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/DataSheet_4_Development_and_application_of_EpitopeScan_a_Python3_toolset_for_mutation_tracking_in_SARS-CoV-2_immunogenic_epitopes_zip/25876609
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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.

**引言**:冠状病毒暴发事件,尤其是近期的新型冠状病毒肺炎(COVID-19)大流行,凸显了在此领域开展免疫学研究的重要性,以减轻未来同类公共卫生事件的影响。生物信息学方法可从病毒测序数据中获取多维度研究视角,但当前可用的软件并不完全适用于针对新型冠状病毒(SARS-CoV-2)免疫原性表位(immunogenic epitopes)内的突变监测这一特定任务。 **方法**:本文介绍了一款突变追踪工具EpitopeScan的开发过程,这是一款面向Python3的软件包,集成了命令行与图形用户界面工具,可通过对不同时间点的病毒全基因组进行多序列比对分析,探究新型冠状病毒(SARS-CoV-2)表位的突变动态。我们选取三类由HLA-DRB1*04:01限制性的、源自刺突蛋白(Spike protein)的免疫优势CD4+ T细胞表位(CD4+ T-cell epitopes)作为研究对象,以此展示该工具的应用案例;HLA-DRB1*04:01是与类风湿关节炎(rheumatoid arthritis, RA)易感性显著相关的等位基因。这些肽段上的突变,可用于监测类风湿关节炎(RA)患者体内针对新型冠状病毒(SARS-CoV-2)刺突蛋白的CD4+ T细胞免疫应答。本次分析共纳入英国地区采集的230万条新型冠状病毒(SARS-CoV-2)全基因组序列。 **结果**:本文详细阐述了表位随时间的保守性变化、保守性部分丧失,以及2021年11月奥密克戎特异性突变N969K出现后,表位与野生型序列完全分化的案例。野生型与突变型肽段均可作为监测变异株特异性CD4+ T细胞免疫应答的潜在候选标志物。用户可通过GitHub仓库https://github.com/Aleksandr-biochem/EpitopeScan获取EpitopeScan工具。
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2024-05-22
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