Multiplex Fragment Analysis for Flexible Detection of All SARS-CoV-2 Variants of Concern.
Journal
Clinical chemistry
ISSN: 1530-8561
Titre abrégé: Clin Chem
Pays: England
ID NLM: 9421549
Informations de publication
Date de publication:
27 07 2022
27 07 2022
Historique:
received:
16
12
2021
accepted:
07
04
2022
pubmed:
27
5
2022
medline:
30
7
2022
entrez:
26
5
2022
Statut:
ppublish
Résumé
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge, and effective tracking requires rapid return of results. Surveillance of variants is typically performed by whole genome sequencing (WGS), which can be financially prohibitive and requires specialized equipment and bioinformatic expertise. Genotyping approaches are rapid methods for monitoring SARS-CoV-2 variants but require continuous adaptation. Fragment analysis may represent an approach for improved SARS-CoV-2 variant detection. A multiplex fragment analysis approach (CoVarScan) was validated using PCR targeting variants by size and fluorescent color. Eight SARS-CoV-2 mutational hot spots in variants of concern (VOCs) were targeted. Three primer pairs (recurrently deleted region [RDR] 1, RDR2, and RDR3-4) flank RDRs in the S-gene. Three allele-specific primers target recurrent spike receptor binding domain mutants. Lastly, 2 primer pairs target recurrent deletions or insertions in ORF1A and ORF8. Fragments were resolved and analyzed by capillary electrophoresis (ABI 3730XL), and mutational signatures were compared to WGS results. We validated CoVarScan using 3544 clinical respiratory specimens. The assay exhibited 96% sensitivity and 99% specificity compared to WGS. The limit of detection for the core targets (RDR1, RDR2, and ORF1A) was 5 copies/reaction. Variants were identified in 95% of samples with cycle threshold (CT) <30 and 75% of samples with a CT 34 to 35. Assay design was frozen April 2021, but all subsequent VOCs have been detected including Delta (n = 2820), Mu, (n = 6), Lambda (n = 6), and Omicron (n = 309). Genotyping results are available in as little as 4 h. Multiplex fragment analysis is adaptable and rapid and has similar accuracy to WGS to classify SARS-CoV-2 variants.
Sections du résumé
BACKGROUND
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge, and effective tracking requires rapid return of results. Surveillance of variants is typically performed by whole genome sequencing (WGS), which can be financially prohibitive and requires specialized equipment and bioinformatic expertise. Genotyping approaches are rapid methods for monitoring SARS-CoV-2 variants but require continuous adaptation. Fragment analysis may represent an approach for improved SARS-CoV-2 variant detection.
METHODS
A multiplex fragment analysis approach (CoVarScan) was validated using PCR targeting variants by size and fluorescent color. Eight SARS-CoV-2 mutational hot spots in variants of concern (VOCs) were targeted. Three primer pairs (recurrently deleted region [RDR] 1, RDR2, and RDR3-4) flank RDRs in the S-gene. Three allele-specific primers target recurrent spike receptor binding domain mutants. Lastly, 2 primer pairs target recurrent deletions or insertions in ORF1A and ORF8. Fragments were resolved and analyzed by capillary electrophoresis (ABI 3730XL), and mutational signatures were compared to WGS results.
RESULTS
We validated CoVarScan using 3544 clinical respiratory specimens. The assay exhibited 96% sensitivity and 99% specificity compared to WGS. The limit of detection for the core targets (RDR1, RDR2, and ORF1A) was 5 copies/reaction. Variants were identified in 95% of samples with cycle threshold (CT) <30 and 75% of samples with a CT 34 to 35. Assay design was frozen April 2021, but all subsequent VOCs have been detected including Delta (n = 2820), Mu, (n = 6), Lambda (n = 6), and Omicron (n = 309). Genotyping results are available in as little as 4 h.
CONCLUSIONS
Multiplex fragment analysis is adaptable and rapid and has similar accuracy to WGS to classify SARS-CoV-2 variants.
Identifiants
pubmed: 35616102
pii: 6591832
doi: 10.1093/clinchem/hvac081
pmc: PMC9384161
doi:
Substances chimiques
RNA, Viral
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1042-1052Commentaires et corrections
Type : CommentIn
Informations de copyright
© American Association for Clinical Chemistry 2022. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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