COVseq is a cost-effective workflow for mass-scale SARS-CoV-2 genomic surveillance.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
23 06 2021
Historique:
received: 14 01 2021
accepted: 01 06 2021
entrez: 24 6 2021
pubmed: 25 6 2021
medline: 20 7 2021
Statut: epublish

Résumé

While mass-scale vaccination campaigns are ongoing worldwide, genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical to monitor the emergence and global spread of viral variants of concern (VOC). Here, we present a streamlined workflow-COVseq-which can be used to generate highly multiplexed sequencing libraries compatible with Illumina platforms from hundreds of SARS-CoV-2 samples in parallel, in a rapid and cost-effective manner. We benchmark COVseq against a standard library preparation method (NEBNext) on 29 SARS-CoV-2 positive samples, reaching 95.4% of concordance between single-nucleotide variants detected by both methods. Application of COVseq to 245 additional SARS-CoV-2 positive samples demonstrates the ability of the method to reliably detect emergent VOC as well as its compatibility with downstream phylogenetic analyses. A cost analysis shows that COVseq could be used to sequence thousands of samples at less than 15 USD per sample, including library preparation and sequencing costs. We conclude that COVseq is a versatile and scalable method that is immediately applicable for SARS-CoV-2 genomic surveillance and easily adaptable to other pathogens such as influenza viruses.

Identifiants

pubmed: 34162869
doi: 10.1038/s41467-021-24078-9
pii: 10.1038/s41467-021-24078-9
pmc: PMC8222401
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3903

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Auteurs

Michele Simonetti (M)

Bienko-Crosetto Lab for Quantitative Genome Biology, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Science for Life Laboratory, Solna, Sweden.

Ning Zhang (N)

Bienko-Crosetto Lab for Quantitative Genome Biology, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Science for Life Laboratory, Solna, Sweden.
Department of Breast Surgery, Qilu hospital of Shandong University, Ji'nan, China.

Luuk Harbers (L)

Bienko-Crosetto Lab for Quantitative Genome Biology, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Science for Life Laboratory, Solna, Sweden.

Maria Grazia Milia (MG)

Laboratory of Microbiology and Virology, Ospedale 'Amedeo di Savoia', Turin, Italy.

Silvia Brossa (S)

Instituto di Candiolo FPO-IRCCS, Candiolo, Turin, Italy.

Thi Thu Huong Nguyen (TT)

Bienko-Crosetto Lab for Quantitative Genome Biology, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Science for Life Laboratory, Solna, Sweden.

Francesco Cerutti (F)

Laboratory of Microbiology and Virology, Ospedale 'Amedeo di Savoia', Turin, Italy.

Enrico Berrino (E)

Instituto di Candiolo FPO-IRCCS, Candiolo, Turin, Italy.
Department of Medical Sciences, University of Turin, Turin, Italy.

Anna Sapino (A)

Instituto di Candiolo FPO-IRCCS, Candiolo, Turin, Italy.
Department of Medical Sciences, University of Turin, Turin, Italy.

Magda Bienko (M)

Bienko-Crosetto Lab for Quantitative Genome Biology, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Science for Life Laboratory, Solna, Sweden.

Antonino Sottile (A)

Instituto di Candiolo FPO-IRCCS, Candiolo, Turin, Italy.

Valeria Ghisetti (V)

Laboratory of Microbiology and Virology, Ospedale 'Amedeo di Savoia', Turin, Italy. valeria.ghisetti@gmail.com.

Nicola Crosetto (N)

Bienko-Crosetto Lab for Quantitative Genome Biology, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden. nicola.crosetto@ki.se.
Science for Life Laboratory, Solna, Sweden. nicola.crosetto@ki.se.

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Classifications MeSH