Transmission cluster characteristics of global, regional, and lineage-specific SARS-CoV-2 phylogenies.

Mattia Prosperi, Brittany Rife, Simone Marini, Marco Salemi
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引用次数: 1

Abstract

The SARS-CoV-2 pandemic has been presenting in periodic waves and multiple variants, of which some dominated over time with increased transmissibility. SARS-CoV-2 is still adapting in the human population, thus it is crucial to understand its evolutionary patterns and dynamics ahead of time. In this work, we analyzed transmission clusters and topology of SARS-CoV-2 phylogenies at the global, regional (North America) and clade-specific (Delta and Omicron) epidemic scales. We used the Nextstrain's nCov open global all-time phylogeny (September 2022, 2,698 strains, 2,243 for North America, 499 for Delta21A, and 543 for Omicron20M), with Nextstrain's clade annotation and Pango lineages. Transmission clusters were identified using Phylopart, DYNAMITE, and several tree imbalance measures were calculated, including staircase-ness, Sackin and Colless index. We found that the phylogenetic clustering profiles of the global epidemic have highest diversification at a distance threshold of 3% (divergence of 10, where the tree sampled median is 49). Phylopart and DYNAMITE clusters moderately-to-highly agree with the Pango nomenclature and the Nextstrain's clade. At the regional and clade-specific scale, transmission clustering profiles tend to flatten and similar clusters are found at distance thresholds between 0.05% and 25%. All the considered phylogenies exhibit high tree imbalance with respect to what expected in random phylogenies, suggesting short infection times and antigenic drift, perhaps due to progressive transition from innate to adaptive immunity in the population.

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全球、区域和谱系特异性SARS-CoV-2系统发育的传播聚集性特征
SARS-CoV-2大流行一直以周期性波和多种变体的形式出现,其中一些随着时间的推移占主导地位,传播性增加。SARS-CoV-2仍在人群中适应,因此提前了解其进化模式和动态至关重要。在这项工作中,我们分析了SARS-CoV-2在全球、区域(北美)和分支特异性(Delta和Omicron)流行尺度上的传播聚集性和系统发育的拓扑结构。我们使用Nextstrain的nCov公开全球历史系统发育(2022年9月,2,698株,北美2,243株,Delta21A 499株,Omicron20M 543株),并使用Nextstrain的进化枝注释和Pango谱系。利用Phylopart和DYNAMITE对传播集群进行了识别,并计算了阶梯度、Sackin和Colless指数等树木不平衡指标。我们发现,全球流行病的系统发育聚类曲线在距离阈值为3%时具有最高的多样性(差异为10,其中树样中位数为49)。Phylopart和DYNAMITE集群与Pango命名法和Nextstrain的进化支中度至高度一致。在区域和进化支特定尺度上,传播聚类曲线趋于平缓,在距离阈值为0.05%至25%之间时发现了类似的聚类。所有被考虑的系统发生都表现出高度的树不平衡,这表明感染时间短,抗原漂移,可能是由于群体从先天免疫到适应性免疫的渐进转变。
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