SARS-CoV-2结构蛋白在α、β、γ和δ变体中的突变:生物信息学分析。

JMIR bioinformatics and biotechnology Pub Date : 2023-07-14 eCollection Date: 2023-01-01 DOI:10.2196/43906
Saima Rehman Khetran, Roma Mustafa
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引用次数: 0

摘要

背景:COVID-19和中东呼吸综合征是由冠状病毒引起的两种呼吸道流行病。由SARS-CoV-2引起的新型疾病COVID-19于2019年12月在中国湖北省武汉市首次报告,并在2-3个月内成为大流行病,影响了全世界的社会和经济平台。尽管疫苗发展迅速,但其流通一直存在障碍,包括缺乏基础资源、免疫不力、疫苗人工复制等。近三年来,武汉病毒的原始毒株出现了多个变种,这可能会对控制和疫苗开发带来进一步的挑战:本研究的目的是利用生物信息学方法全面分析 SARS-CoV-2 变异株(VoCs)中的突变,以确定新的突变位点,从而帮助针对这些位点开发新的疫苗:方法:将 SARS-CoV-2 棘突蛋白(YP_009724390)和核壳蛋白(YP_009724397)的参考序列与检索到的来自 14 个国家的 4 个 VoCs 分离物的序列进行比较,以进行突变和进化分析。进行了多重序列比对,并使用 MEGA(版本 6)以 1000 次引导重复的邻接法构建了系统发生树。使用 MultAlin 在线工具(5.4.1 版)分析了氨基酸序列中的突变:结果:在四种 VoCs 中,共发现 143 个非同义突变和 8 个核壳蛋白缺失。多重序列比对和氨基酸替换分析发现了新的突变,包括埃及(MW533289)、英国(MT906649)和其他地区报道的 G72W、M2101I、L139F、209-211 缺失、G212S、P199L、P67S、I292T 和未知氨基酸替换。变异体 B.1.1.7(Alpha 变异体)和 B.1.617.2(Delta 变异体)具有较高的传播性和致死性,其氨基酸替换为 D614G、R203K 和 G204R,在大多数序列中的流行率较高。新型SARS-CoV-2变体蛋白与之前报道的一些β-冠状病毒蛋白之间的系统发生分析表明,β-冠状病毒物种对进化支系的支持较弱或根本不支持:结论:这项研究有助于更好地了解 SARS-CoV-2 及其四个主要变种的基本性质。检测到的大量新型突变也有助于更好地了解 VoCs,并帮助确定合适的突变作为疫苗靶标。此外,这些数据还为 VoCs 中的新型变异提供了证据,有助于深入了解 SARS-CoV-2 的流行病学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Mutations of SARS-CoV-2 Structural Proteins in the Alpha, Beta, Gamma, and Delta Variants: Bioinformatics Analysis.

Mutations of SARS-CoV-2 Structural Proteins in the Alpha, Beta, Gamma, and Delta Variants: Bioinformatics Analysis.

Mutations of SARS-CoV-2 Structural Proteins in the Alpha, Beta, Gamma, and Delta Variants: Bioinformatics Analysis.

Background: COVID-19 and Middle East Respiratory Syndrome are two pandemic respiratory diseases caused by coronavirus species. The novel disease COVID-19 caused by SARS-CoV-2 was first reported in Wuhan, Hubei Province, China, in December 2019, and became a pandemic within 2-3 months, affecting social and economic platforms worldwide. Despite the rapid development of vaccines, there have been obstacles to their distribution, including a lack of fundamental resources, poor immunization, and manual vaccine replication. Several variants of the original Wuhan strain have emerged in the last 3 years, which can pose a further challenge for control and vaccine development.

Objective: The aim of this study was to comprehensively analyze mutations in SARS-CoV-2 variants of concern (VoCs) using a bioinformatics approach toward identifying novel mutations that may be helpful in developing new vaccines by targeting these sites.

Methods: Reference sequences of the SARS-CoV-2 spike (YP_009724390) and nucleocapsid (YP_009724397) proteins were compared to retrieved sequences of isolates of four VoCs from 14 countries for mutational and evolutionary analyses. Multiple sequence alignment was performed and phylogenetic trees were constructed by the neighbor-joining method with 1000 bootstrap replicates using MEGA (version 6). Mutations in amino acid sequences were analyzed using the MultAlin online tool (version 5.4.1).

Results: Among the four VoCs, a total of 143 nonsynonymous mutations and 8 deletions were identified in the spike and nucleocapsid proteins. Multiple sequence alignment and amino acid substitution analysis revealed new mutations, including G72W, M2101I, L139F, 209-211 deletion, G212S, P199L, P67S, I292T, and substitutions with unknown amino acid replacement, reported in Egypt (MW533289), the United Kingdom (MT906649), and other regions. The variants B.1.1.7 (Alpha variant) and B.1.617.2 (Delta variant), characterized by higher transmissibility and lethality, harbored the amino acid substitutions D614G, R203K, and G204R with higher prevalence rates in most sequences. Phylogenetic analysis among the novel SARS-CoV-2 variant proteins and some previously reported β-coronavirus proteins indicated that either the evolutionary clade was weakly supported or not supported at all by the β-coronavirus species.

Conclusions: This study could contribute toward gaining a better understanding of the basic nature of SARS-CoV-2 and its four major variants. The numerous novel mutations detected could also provide a better understanding of VoCs and help in identifying suitable mutations for vaccine targets. Moreover, these data offer evidence for new types of mutations in VoCs, which will provide insight into the epidemiology of SARS-CoV-2.

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