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Predicting Infectivity: Comparing Four PCR-based Assays to Detect Culturable SARS-CoV-2 in Clinical Samples (preprint)
medrxiv; 2021.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2021.07.14.21260544
ABSTRACT
ABSTRACT With the COVID-19 pandemic caused by SARS-CoV-2 now in its second year, there remains an urgent need for diagnostic testing that can identify infected individuals, particularly those who harbor infectious virus. Various RT-PCR strategies have been proposed to identify specific viral RNA species that may predict the presence of infectious virus, including detection of transcriptional intermediates (e.g. subgenomic RNA [sgRNA]) and replicative intermediates (e.g. negative-strand RNA species). Using a novel primer/probe set for detection of subgenomic (sg)E transcripts, we successfully identified 100% of specimens containing culturable SARS-CoV-2 from a set of 126 clinical samples (total sgE C T values ranging from 12.3-37.5). This assay showed superior performance compared to a previously published sgRNA assay and to a negative-strand RNA assay, both of which failed to detect target RNA in a subset of samples from which we isolated live virus. In addition, total levels of viral RNA (genome, negative-strand, and sgE) detected with the WHO/Charité primer-probe set correlated closely with levels of infectious virus. Specifically, infectious virus was not detected in samples with a C T above 31.0. Clinical samples with higher levels of viral RNA also displayed cytopathic effect (CPE) more quickly than those with lower levels of viral RNA. Finally, we found that the infectivity of SARS-CoV-2 samples is significantly dependent on the cell type used for viral isolation, as Vero E6 cells expressing TMRPSS2 extended the analytical sensitivity of isolation by more than 3 C T compared to parental Vero E6 cells and resulted in faster isolation. Our work shows that using a total viral RNA Ct cut-off of >31 or specifically testing for sgRNA can serve as an effective rule-out test for viral infectivity.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
COVID-19
Language:
English
Year:
2021
Document Type:
Preprint
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