Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020
Abstract 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 ambiti...
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Nature Portfolio
2021
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oai:doaj.org-article:e765d30d19d848ffa2ce7f8a62e28df02021-12-02T18:02:30ZExploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 202010.1038/s41598-021-97667-92045-2322https://doaj.org/article/e765d30d19d848ffa2ce7f8a62e28df02021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97667-9https://doaj.org/toc/2045-2322Abstract 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.Nena BollenMaria ArtesiKeith DurkinSamuel L. HongBarney PotterBouchra BoujemlaBert VanmechelenJoan Martí-CarrerasTony Wawina-BokalangaCécile MeexSébastien BontemsMarie-Pierre HayetteEmmanuel AndréPiet MaesVincent BoursGuy BaeleSimon DellicourNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021) |
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Medicine R Science Q |
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Medicine R Science Q Nena Bollen Maria Artesi Keith Durkin Samuel L. Hong Barney Potter Bouchra Boujemla Bert Vanmechelen Joan Martí-Carreras Tony Wawina-Bokalanga Cécile Meex Sébastien Bontems Marie-Pierre Hayette Emmanuel André Piet Maes Vincent Bours Guy Baele Simon Dellicour Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020 |
| description |
Abstract 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. |
| format |
article |
| author |
Nena Bollen Maria Artesi Keith Durkin Samuel L. Hong Barney Potter Bouchra Boujemla Bert Vanmechelen Joan Martí-Carreras Tony Wawina-Bokalanga Cécile Meex Sébastien Bontems Marie-Pierre Hayette Emmanuel André Piet Maes Vincent Bours Guy Baele Simon Dellicour |
| author_facet |
Nena Bollen Maria Artesi Keith Durkin Samuel L. Hong Barney Potter Bouchra Boujemla Bert Vanmechelen Joan Martí-Carreras Tony Wawina-Bokalanga Cécile Meex Sébastien Bontems Marie-Pierre Hayette Emmanuel André Piet Maes Vincent Bours Guy Baele Simon Dellicour |
| author_sort |
Nena Bollen |
| title |
Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020 |
| title_short |
Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020 |
| title_full |
Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020 |
| title_fullStr |
Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020 |
| title_full_unstemmed |
Exploiting genomic surveillance to map the spatio-temporal dispersal of SARS-CoV-2 spike mutations in Belgium across 2020 |
| title_sort |
exploiting genomic surveillance to map the spatio-temporal dispersal of sars-cov-2 spike mutations in belgium across 2020 |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/e765d30d19d848ffa2ce7f8a62e28df0 |
| work_keys_str_mv |
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1718378900888748032 |