Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020.
Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020.
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DOI：
10.1038/s41598-021-97667-9
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发表时间：
2021-09-17
影响因子：
4.6
通讯作者：
Dellicour S
中科院分区：
文献类型：
--
作者：
Bollen N;Artesi M;Durkin K;Hong SL;Potter B;Boujemla B;Vanmechelen B;Martí-Carreras J;Wawina-Bokalanga T;Meex C;Bontems S;Hayette MP;André E;Maes P;Bours V;Baele G;Dellicour S
2020年底，检测到几种新的SARS-CoV-2变异株--指定的关注变异株--并迅速怀疑其与更高的传播性和可能逃避疫苗诱导的免疫力有关。在比利时，这一发现促使启动了一项更雄心勃勃的基因组监测计划，该计划正在大幅增加SARS-CoV-2基因组的数量，以分析监测病毒谱系和变异的传播。为了有效地分析大量的基因组数据，这些数据是增加测序工作的结果，简化的分析策略至关重要。在这项研究中，我们说明了如何有效地映射的时空分布的目标突变在区域一级。作为概念验证，我们重点关注比利时列日省，该省在2020年一直进行采样，但也是第二次欧洲疫情的主要震中之一。具体而言，我们采用最近开发的地理工作流程来推断与刺突蛋白（S98 F，A222 V和S477 N）上的三个特定突变相关的病毒谱系的区域传播历史，并通过时间来量化它们的相对重要性。我们的分析管道能够分析大型数据集，并有可能快速应用和更新，以在整个流行病过程中跟踪空间和时间上的目标突变。
At the end of 2020, several new variants of SARS-CoV-2—designated variants of concern—were detected and quickly suspected to be associated with a higher transmissibility and possible escape of vaccine-induced immunity. In Belgium, this discovery has motivated the initiation of a more ambitious genomic surveillance program, which is drastically increasing the number of SARS-CoV-2 genomes to analyse for monitoring the circulation of viral lineages and variants of concern. In order to efficiently analyse the massive collection of genomic data that are the result of such increased sequencing efforts, streamlined analytical strategies are crucial. In this study, we illustrate how to efficiently map the spatio-temporal dispersal of target mutations at a regional level. As a proof of concept, we focus on the Belgian province of Liège that has been consistently sampled throughout 2020, but was also one of the main epicenters of the second European epidemic wave. Specifically, we employ a recently developed phylogeographic workflow to infer the regional dispersal history of viral lineages associated with three specific mutations on the spike protein (S98F, A222V and S477N) and to quantify their relative importance through time. Our analytical pipeline enables analysing large data sets and has the potential to be quickly applied and updated to track target mutations in space and time throughout the course of an epidemic.
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影响因子：
4.3
作者：
Kalkauskas A;Perron U;Sun Y;Goldman N;Baele G;Guindon S;De Maio N
通讯作者：
De Maio N
影响因子：
10.7
作者：
Dellicour S;Durkin K;Hong SL;Vanmechelen B;Martí-Carreras J;Gill MS;Meex C;Bontems S;André E;Gilbert M;Walker C;Maio N;Faria NR;Hadfield J;Hayette MP;Bours V;Wawina-Bokalanga T;Artesi M;Baele G;Maes P
通讯作者：
Maes P
影响因子：
5.3
作者：
Sagulenko P;Puller V;Neher RA
通讯作者：
Neher RA
影响因子：
2.4
作者：
Bruce, B. D.;Stevens, J. D.;Malcolm, H.
通讯作者：
Malcolm, H.
影响因子：
10.7
作者：
Katoh K;Standley DM
通讯作者：
Standley DM