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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Characterizing SARS-CoV-2 Transcription of Subgenomic and Genomic RNAs During Early Human Infection Using Multiplexed Droplet Digital Polymerase Chain Reaction
Journal of Infectious Diseases, Volume 227, No. 8, Year 2023
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Description
Background: Control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission requires understanding SARS-CoV-2 replication dynamics. Methods: We developed a multiplexed droplet digital polymerase chain reaction (ddPCR) assay to quantify SARS-CoV-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 quantitative PCR (qPCR) and viral culture. Results: sgRNAs were quantifiable across a range of qPCR cycle threshold (Ct) values and correlated with Ct values. The ratio sgRNA:gRNA 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. sgRNA:gRNA 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. © 2022 The Author(s).
Authors & Co-Authors
Hwang, Hyon S.
United States, Baltimore
Johns Hopkins University
Grudda, Tanner
United States, Baltimore
Johns Hopkins University
Gallagher, Nicholas D.
United States, Baltimore
Johns Hopkins University
Luo, Chunhuai
United States, Baltimore
Johns Hopkins University
Robinson, Matthew L.
United States, Baltimore
Johns Hopkins University
Conte, Abigail R.
United States, Baltimore
Johns Hopkins University
Vergara, Candelaria I.
United States, Baltimore
Johns Hopkins University
Pekosz, Andrew S.
United States, Baltimore
Johns Hopkins University
Mostafa, Heba H.
United States, Baltimore
Johns Hopkins University
Manabe, Yukari C.
United States, Baltimore
Johns Hopkins University
Thio, Chloe Lynne
United States, Baltimore
Johns Hopkins University
Balagopal, Ashwin
United States, Baltimore
Johns Hopkins University
Statistics
Citations: 2
Authors: 12
Affiliations: 2
Identifiers
Doi:
10.1093/infdis/jiac472
ISSN:
00221899
Research Areas
Covid
Genetics And Genomics
Study Approach
Quantitative