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协方差预测了对 SARS-CoV-2 作为人类病原体的出现和持续进化至关重要的保守蛋白质残基相互作用。

Covariance predicts conserved protein residue interactions important for the emergence and continued evolution of SARS-CoV-2 as a human pathogen.

机构信息

Department of Microbiology, Harvard Medical School, Boston, Massachusetts, United States of America.

出版信息

PLoS One. 2022 Jul 27;17(7):e0270276. doi: 10.1371/journal.pone.0270276. eCollection 2022.

Abstract

SARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that likely emerged from animal reservoirs. Differences in nucleotide and protein sequence composition within related β-coronaviruses are often used to better understand CoV evolution, host adaptation, and their emergence as human pathogens. Here we report the comprehensive analysis of amino acid residue changes that have occurred in lineage B β-coronaviruses that show covariance with each other. This analysis revealed patterns of covariance within conserved viral proteins that potentially define conserved interactions within and between core proteins encoded by SARS-CoV-2 related β-coronaviruses. We identified not only individual pairs but also networks of amino acid residues that exhibited statistically high frequencies of covariance with each other using an independent pair model followed by a tandem model approach. Using 149 different CoV genomes that vary in their relatedness, we identified networks of unique combinations of alleles that can be incrementally traced genome by genome within different phylogenic lineages. Remarkably, covariant residues and their respective regions most abundantly represented are implicated in the emergence of SARS-CoV-2 and are also enriched in dominant SARS-CoV-2 variants.

摘要

SARS-CoV-2 是三种已被确认的冠状病毒(CoVs)之一,这三种冠状病毒在 21 世纪引发了疫情或大流行,可能源自动物宿主。相关的β冠状病毒在核苷酸和蛋白质序列组成上的差异通常用于更好地了解 CoV 的进化、宿主适应以及它们作为人类病原体的出现。在这里,我们报告了对彼此之间具有共变关系的谱系 B β冠状病毒中氨基酸残基变化的综合分析。这项分析揭示了保守病毒蛋白内共变模式,这些模式可能定义了 SARS-CoV-2 相关β冠状病毒编码的核心蛋白之间和内部的保守相互作用。我们不仅确定了单个对,还使用独立对模型和串联模型方法确定了彼此之间具有统计学上高共变频率的氨基酸残基网络。使用 149 种不同的 CoV 基因组,这些基因组在相关性上存在差异,我们确定了独特等位基因组合的网络,可以在不同的系统发育谱系中逐代递增地追踪基因组。值得注意的是,共变残基及其各自的区域最丰富地代表了 SARS-CoV-2 的出现,并且在占主导地位的 SARS-CoV-2 变体中也很丰富。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6503/9328546/343aa1ca7882/pone.0270276.g001.jpg

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