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Multiplex Fragment Analysis for Flexible Detection of All SARS-CoV-2 Variants of Concern.
Clark, Andrew E; Wang, Zhaohui; Ostman, Emily; Zheng, Hui; Yao, Huiyu; Cantarel, Brandi; Kanchwala, Mohammed; Xing, Chao; Chen, Li; Irwin, Pei; Xu, Yan; Oliver, Dwight; Lee, Francesca M; Gagan, Jeffrey R; Filkins, Laura; Muthukumar, Alagarraju; Park, Jason Y; Sarode, Ravi; SoRelle, Jeffrey A.
  • Clark AE; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Wang Z; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Ostman E; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Zheng H; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Yao H; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Cantarel B; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Kanchwala M; Bioinformatics Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Xing C; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Chen L; McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Irwin P; McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Xu Y; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Oliver D; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Lee FM; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Gagan JR; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Filkins L; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Muthukumar A; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Park JY; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Sarode R; Department of Pathology and Laboratory Medicine, Children's Health System of Texas, Dallas, TX, USA.
  • SoRelle JA; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Clin Chem ; 68(8): 1042-1052, 2022 07 27.
Article in English | MEDLINE | ID: covidwho-1864962
ABSTRACT

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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: Clin Chem Journal subject: Chemistry, Clinical Year: 2022 Document Type: Article Affiliation country: Clinchem

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: Clin Chem Journal subject: Chemistry, Clinical Year: 2022 Document Type: Article Affiliation country: Clinchem