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对 SARS-CoV-2 的全基因组测序:利用系统发育和结构建模来了解当地病毒的进化情况。

Whole-genome Sequencing of SARS-CoV-2: Using Phylogeny and Structural Modeling to Contextualize Local Viral Evolution.

机构信息

59th Medical Wing, Clinical Investigations and Research Support Laboratory, Lackland Air Force Base, Lackland AFB, TX 78236, USA.

出版信息

Mil Med. 2022 Jan 4;187(1-2):e130-e137. doi: 10.1093/milmed/usab031.

Abstract

INTRODUCTION

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a global pandemic resulting in over 1 million deaths worldwide. In the Department of Defense (DoD), over 129,000 personnel (civilians, dependents, and active duty) have been infected with the virus to date. Rapid estimations of transmission and mutational patterns of virus outbreaks can be accomplished using whole-genome viral sequencing. Deriving interpretable and actionable results from pathogen sequence data is accomplished by the construction of phylogenetic trees (from local and global virus sequences) and by the creation of protein maps, to visualize and predict the effects of structural protein amino acid mutations.

MATERIALS AND METHODS

We developed a sequencing and bioinformatics workflow for molecular epidemiological SARS-CoV-2 surveillance using excess clinical specimens collected under an institutional review board exempt protocol at Joint Base San Antonio, Lackland AFB. This workflow includes viral RNA isolation, viral load quantification, tiling-based next-generation sequencing, sequencing and bioinformatics analysis, and data visualization via phylogenetic trees and protein mapping.

RESULTS

Sequencing of 37 clinical specimens collected at JBSA/Lackland revealed that by June 2020, SAR-CoV-2 strains carrying the 614G mutation were the predominant cause of local coronavirus disease 2019 infections. We identified 109 nucleotide changes in the coding region of the SARS-CoV-2 genome (which lead to 63 unique, non-synonymous amino acid mutations), one mutation in the 5'-untranslated region (UTR), and two mutations in the 3'UTR. Furthermore, we identified and mapped six additional spike protein amino acid changes-information which could potentially aid vaccine design.

CONCLUSION

The workflow presented here is designed to enable DoD public health officials to track viral evolution and conduct near real-time evaluation of future outbreaks. The generation of molecular epidemiological sequence data is critical for the development of disease intervention strategies-most notably, vaccine design. Overall, we present a streamlined sequencing and bioinformatics methodology aimed at improving long-term readiness efforts in the DoD.

摘要

简介

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)的爆发引发了全球大流行,导致全球超过 100 万人死亡。在国防部(DoD),迄今为止,已有超过 129,000 人(包括平民、家属和现役军人)感染了该病毒。使用全基因组病毒测序可以快速估计病毒爆发的传播和突变模式。通过构建系统发育树(来自本地和全球病毒序列)和创建蛋白质图谱,可以从病原体序列数据中得出可解释和可操作的结果,以可视化和预测结构蛋白氨基酸突变的影响。

材料和方法

我们开发了一种使用机构审查委员会豁免协议下收集的多余临床标本进行分子流行病学 SARS-CoV-2 监测的测序和生物信息学工作流程,该工作流程在 Joint Base San Antonio,Lackland AFB 进行。该工作流程包括病毒 RNA 分离、病毒载量定量、基于平铺的下一代测序、测序和生物信息学分析,以及通过系统发育树和蛋白质图谱进行数据可视化。

结果

对在 JBSA/Lackland 收集的 37 个临床标本进行测序后发现,到 2020 年 6 月,携带 614G 突变的 SAR-CoV-2 株是当地 COVID-19 感染的主要原因。我们在 SARS-CoV-2 基因组的编码区发现了 109 个核苷酸变化(导致 63 个独特的非同义氨基酸突变),5'-非翻译区(UTR)中有一个突变,3'UTR 中有两个突变。此外,我们还鉴定并映射了六个额外的刺突蛋白氨基酸变化信息,这些信息可能有助于疫苗设计。

结论

这里提出的工作流程旨在使国防部公共卫生官员能够跟踪病毒进化并对未来的爆发进行实时评估。生成分子流行病学序列数据对于制定疾病干预策略至关重要,尤其是疫苗设计。总的来说,我们提出了一种简化的测序和生物信息学方法,旨在提高国防部的长期准备工作。

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Variants in SARS-CoV-2 associated with mild or severe outcome.与轻度或重度结果相关的新冠病毒变体。
Evol Med Public Health. 2021 Jun 27;9(1):267-275. doi: 10.1093/emph/eoab019. eCollection 2021.
3
Geographic and Genomic Distribution of SARS-CoV-2 Mutations.新型冠状病毒2变异株的地理和基因组分布
Front Microbiol. 2020 Jul 22;11:1800. doi: 10.3389/fmicb.2020.01800. eCollection 2020.
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Variant analysis of SARS-CoV-2 genomes.SARS-CoV-2 基因组变异分析。
Bull World Health Organ. 2020 Jul 1;98(7):495-504. doi: 10.2471/BLT.20.253591. Epub 2020 Jun 2.

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