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Cited by 245

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Growth, detection, quantification, and inactivation of SARS-CoV-2

Open access
Case, James Brett, Bailey, Adam L., Kim, Arthur S., Chen, Rita E., Diamond, Michael S.·2020·Virology

Abstract

Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 is the agent responsible for the coronavirus disease 2019 (COVID-19) global pandemic. SARS-CoV-2 is closely related to SARS-CoV, which caused the 2003 SARS outbreak. Although numerous reagents were developed to study SARS-CoV infections, few have been applicable to evaluating SARS-CoV-2 infection and immunity. Current limitations in studying SARS-CoV-2 include few validated assays with fully replication-competent wild-type virus. We have developed protocols to propagate, quantify, and work with infectious SARS-CoV-2. Here, we describe: (1) virus stock generation, (2) RT-qPCR quantification of SARS-CoV-2 RNA; (3) detection of SARS-CoV-2 antigen by flow cytometry, (4) quantification of infectious SARS-CoV-2 by focus-forming and plaque assays; and (5) validated protocols for virus inactivation. Collectively, these methods can be adapted to a variety of experimental designs, which should accelerate our understanding of SARS-CoV-2 biology and the development of effective countermeasures against COVID-19.

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Metadata

Authors
Case, J. B., Bailey, A. L., Kim, A. S., Chen, R. E., & Diamond, M. S.
Venue
Virology
Publisher
Elsevier BV
Published
2020-09
Volume
548
Pages
39-48
ISSN
0042-6822 (ISSN-L)
OpenAlex
W3035628751
Cited by
245
References
5
FWCI
5.25
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Growth, detection, quantification, and inactivation of SARS-CoV-2. https://app.cochat.ai/papers/10.1016/j.virol.2020.05.015
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Case, J. B., Bailey, A. L., Kim, A. S., Chen, R. E., & Diamond, M. S. (2020). Growth, detection, quantification, and inactivation of SARS-CoV-2. Virology. https://doi.org/10.1016/j.virol.2020.05.015

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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