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Characterizing SARS-CoV-2 transcription of subgenomic and genomic RNAs during early human infection using multiplexed droplet digital PCR.
Hwang, Hyon S; Lo, Che-Min; Murphy, Michael; Grudda, Tanner; Gallagher, Nicholas; Luo, Chun Huai; Robinson, Matthew L; Mirza, Agha; Conte, Madison; Conte, Abigail; Zhou, Ruifeng; Vergara, Candelaria; Brooke, Christopher B; Pekosz, Andrew; Mostafa, Heba H; Manabe, Yukari C; Thio, Chloe L; Balagopal, Ashwin.
  • Hwang HS; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Lo CM; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Murphy M; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Grudda T; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Gallagher N; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Luo CH; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Robinson ML; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Mirza A; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Conte M; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Conte A; W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Zhou R; W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Vergara C; Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Brooke CB; Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
  • Pekosz A; W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Mostafa HH; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Manabe YC; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Thio CL; W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Balagopal A; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
J Infect Dis ; 2022 Dec 05.
Article in English | MEDLINE | ID: covidwho-2296790
ABSTRACT

BACKGROUND:

Control of SARS-CoV-2 (SCV-2) transmission requires understanding SCV-2 replication dynamics.

METHODS:

We developed a multiplexed droplet digital PCR (ddPCR) assay to quantify SCV-2 subgenomic RNAs (sgRNAs), which are only produced during active viral replication, and discriminate them from genomic RNAs (gRNAs). We applied the assay to specimens from 144 people with single nasopharyngeal samples and 27 people with >1 sample. Results were compared to qPCR and viral culture.

RESULTS:

sgRNAs were quantifiable across a range of qPCR cycle threshold (Ct) values and correlated with Ct values. The ratio of sgRNAgRNA was stable across a wide range of Ct values, whereas adjusted amounts of N sgRNA to a human housekeeping gene declined with higher Ct values. Adjusted sgRNA and gRNA amounts were quantifiable in culture-negative samples, although levels were significantly lower than in culture-positive samples. Daily testing of 6 persons revealed that sgRNA is concordant with culture results during the first week of infection but may be discordant with culture later in infection. Further, sgRNAgRNA is constant during infection despite changes in viral culture.

CONCLUSIONS:

Ct values from qPCR correlate with active viral replication. More work is needed to understand why some cultures are negative despite presence of sgRNA.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Year: 2022 Document Type: Article Affiliation country: Infdis

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Full text: Available Collection: International databases Database: MEDLINE Language: English Year: 2022 Document Type: Article Affiliation country: Infdis