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SARS-CoV-2 缺陷病毒基因组的生物信息学分析及其对人群感染特征的影响。

Bioinformatic analysis of defective viral genomes in SARS-CoV-2 and its impact on population infection characteristics.

机构信息

Department of Life Science, Dezhou University, Dezhou, China.

State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Shanghai Jiao Tong University, Shanghai, China.

出版信息

Front Immunol. 2024 Jan 29;15:1341906. doi: 10.3389/fimmu.2024.1341906. eCollection 2024.

Abstract

DVGs (Defective Viral Genomes) are prevalent in RNA virus infections. In this investigation, we conducted an analysis of high-throughput sequencing data and observed widespread presence of DVGs in SARS-CoV-2. Comparative analysis between SARS-CoV-2 and diverse DNA viruses revealed heightened susceptibility to damage and increased sequencing sample heterogeneity within the SARS-CoV-2 genome. Whole-genome sequencing depth variability analysis exhibited a higher coefficient of variation for SARS-CoV-2, while DVG analysis indicated a significant proportion of recombination sites, signifying notable genome heterogeneity and suggesting that a large proportion of assembled virus particles contain incomplete RNA sequences. Moreover, our investigation explored the sequencing depth and DVG content differences among various strains. Our findings revealed that as the virus evolves, there is a notable increase in the proportion of intact genomes within virus particles, as evidenced by third-generation sequencing data. Specifically, the proportion of intact genome in the Omicron strain surpassed that of the Delta and Alpha strains. This observation effectively elucidates the heightened infectiousness of the Omicron strain compared to the Delta and Alpha strains. We also postulate that this improvement in completeness stems from enhanced virus assembly capacity, as the Omicron strain can promptly facilitate the binding of RNA and capsid protein, thereby reducing the exposure time of vulnerable virus RNA in the host environment and significantly mitigating its degradation. Finally, employing mathematical modeling, we simulated the impact of DVG effects under varying environmental factors on infection characteristics and population evolution. Our findings provide an explanation for the close association between symptom severity and the extent of virus invasion, as well as the substantial disparity in population infection characteristics caused by the same strain under distinct environmental conditions. This study presents a novel approach for future virus research and vaccine development.

摘要

缺陷型病毒基因组(DVGs)在 RNA 病毒感染中普遍存在。在本研究中,我们对高通量测序数据进行了分析,观察到 SARS-CoV-2 中广泛存在的 DVGs。SARS-CoV-2 与多种 DNA 病毒的比较分析表明,SARS-CoV-2 对损伤更敏感,并且其基因组内的测序样本异质性增加。全基因组测序深度变异性分析显示 SARS-CoV-2 的变异系数更高,而 DVG 分析表明存在大量重组位点,表明显著的基因组异质性,并表明大量组装的病毒颗粒含有不完整的 RNA 序列。此外,我们还研究了不同毒株之间的测序深度和 DVG 含量差异。我们的研究结果表明,随着病毒的进化,病毒颗粒内完整基因组的比例显著增加,这可以从第三代测序数据中得到证明。具体来说,Omicron 株的完整基因组比例超过了 Delta 和 Alpha 株。这一观察结果有效地解释了 Omicron 株比 Delta 和 Alpha 株具有更高的传染性。我们还推测,这种完整性的提高源于增强的病毒组装能力,因为 Omicron 株可以迅速促进 RNA 和衣壳蛋白的结合,从而减少宿主环境中脆弱病毒 RNA 的暴露时间,并显著减轻其降解。最后,我们运用数学模型模拟了在不同环境因素下 DVG 效应对感染特征和群体进化的影响。我们的研究结果为症状严重程度与病毒入侵程度之间的密切关联以及同一毒株在不同环境条件下引起的群体感染特征的显著差异提供了解释。这项研究为未来的病毒研究和疫苗开发提供了一种新的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09b1/10859446/f99a1f462f4f/fimmu-15-1341906-g001.jpg

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