An Hyunsu, Eun Minho, Yi Jawoon, Park Jihwan
School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Republic of Korea.
Anti-Virus Research Center, Gwangju Institute of Science and Technology (GIST), Republic of Korea.
Brief Bioinform. 2022 Mar 10;23(2). doi: 10.1093/bib/bbac056.
The development of autoimmune diseases following SARS-CoV-2 infection, including multisystem inflammatory syndrome, has been reported, and several mechanisms have been suggested, including molecular mimicry. We developed a scalable, comparative immunoinformatics pipeline called cross-reactive-epitope-search-using-structural-properties-of-proteins (CRESSP) to identify cross-reactive epitopes between a collection of SARS-CoV-2 proteomes and the human proteome using the structural properties of the proteins. Overall, by searching 4 911 245 proteins from 196 352 SARS-CoV-2 genomes, we identified 133 and 648 human proteins harboring potential cross-reactive B-cell and CD8+ T-cell epitopes, respectively. To demonstrate the robustness of our pipeline, we predicted the cross-reactive epitopes of coronavirus spike proteins, which were recognized by known cross-neutralizing antibodies. Using single-cell expression data, we identified PARP14 as a potential target of intermolecular epitope spreading between the virus and human proteins. Finally, we developed a web application (https://ahs2202.github.io/3M/) to interactively visualize our results. We also made our pipeline available as an open-source CRESSP package (https://pypi.org/project/cressp/), which can analyze any two proteomes of interest to identify potentially cross-reactive epitopes between the proteomes. Overall, our immunoinformatic resources provide a foundation for the investigation of molecular mimicry in the pathogenesis of autoimmune and chronic inflammatory diseases following COVID-19.
感染严重急性呼吸综合征冠状病毒2（SARS-CoV-2）后自身免疫性疾病的发展，包括多系统炎症综合征，已有报道，并且提出了几种机制，包括分子模拟。我们开发了一种名为“利用蛋白质结构特性进行交叉反应表位搜索”（CRESSP）的可扩展的比较免疫信息学流程，以利用蛋白质的结构特性来识别一组SARS-CoV-2蛋白质组与人类蛋白质组之间的交叉反应表位。总体而言，通过搜索来自196352个SARS-CoV-2基因组的4911245种蛋白质，我们分别鉴定出133种和648种含有潜在交叉反应性B细胞和CD8 + T细胞表位的人类蛋白质。为了证明我们流程的稳健性，我们预测了冠状病毒刺突蛋白的交叉反应表位，这些表位可被已知的交叉中和抗体识别。利用单细胞表达数据，我们确定聚（ADP-核糖）聚合酶14（PARP14）是病毒与人类蛋白质之间分子间表位扩散的潜在靶点。最后，我们开发了一个网络应用程序（https://ahs2202.github.io/3M/）来交互式地可视化我们的结果。我们还将我们的流程作为一个开源的CRESSP软件包（https://pypi.org/project/cressp/）提供，该软件包可以分析任何两个感兴趣的蛋白质组，以识别蛋白质组之间潜在的交叉反应表位。总体而言，我们的免疫信息学资源为研究COVID-19后自身免疫性疾病和慢性炎症性疾病发病机制中的分子模拟提供了基础。
