Evaluation of COVID-19 RT-qPCR Test in Multi sample Pools.


Journal

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
ISSN: 1537-6591
Titre abrégé: Clin Infect Dis
Pays: United States
ID NLM: 9203213

Informations de publication

Date de publication:
19 11 2020
Historique:
received: 30 03 2020
accepted: 30 04 2020
pubmed: 3 5 2020
medline: 15 12 2020
entrez: 3 5 2020
Statut: ppublish

Résumé

The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a current pandemic of unprecedented scale. Although diagnostic tests are fundamental to the ability to detect and respond, overwhelmed healthcare systems are already experiencing shortages of reagents associated with this test, calling for a lean immediately applicable protocol. RNA extracts of positive samples were tested for the presence of SARS-CoV-2 using reverse transcription quantitative polymerase chain reaction, alone or in pools of different sizes (2-, 4-, 8-, 16-, 32-, and 64-sample pools) with negative samples. Transport media of additional 3 positive samples were also tested when mixed with transport media of negative samples in pools of 8. A single positive sample can be detected in pools of up to 32 samples, using the standard kits and protocols, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, although this may require additional amplification cycles. Single positive samples can be detected when pooling either after or prior to RNA extraction. As it uses the standard protocols, reagents, and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for coronavirus disease 2019 would allow expanding current screening capacities, thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.

Sections du résumé

BACKGROUND
The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a current pandemic of unprecedented scale. Although diagnostic tests are fundamental to the ability to detect and respond, overwhelmed healthcare systems are already experiencing shortages of reagents associated with this test, calling for a lean immediately applicable protocol.
METHODS
RNA extracts of positive samples were tested for the presence of SARS-CoV-2 using reverse transcription quantitative polymerase chain reaction, alone or in pools of different sizes (2-, 4-, 8-, 16-, 32-, and 64-sample pools) with negative samples. Transport media of additional 3 positive samples were also tested when mixed with transport media of negative samples in pools of 8.
RESULTS
A single positive sample can be detected in pools of up to 32 samples, using the standard kits and protocols, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, although this may require additional amplification cycles. Single positive samples can be detected when pooling either after or prior to RNA extraction.
CONCLUSIONS
As it uses the standard protocols, reagents, and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for coronavirus disease 2019 would allow expanding current screening capacities, thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.

Identifiants

pubmed: 32358960
pii: 5828059
doi: 10.1093/cid/ciaa531
pmc: PMC7197588
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2073-2078

Commentaires et corrections

Type : CommentIn

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Auteurs

Idan Yelin (I)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.

Noga Aharony (N)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.

Einat Shaer Tamar (ES)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.

Amir Argoetti (A)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.

Esther Messer (E)

Safety Unit, Technion - Israel Institute of Technology, Haifa, Israel.

Dina Berenbaum (D)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.

Einat Shafran (E)

Virology laboratory, Rambam Health Care Campus, Haifa, Israel.

Areen Kuzli (A)

Virology laboratory, Rambam Health Care Campus, Haifa, Israel.

Nagham Gandali (N)

Virology laboratory, Rambam Health Care Campus, Haifa, Israel.

Omer Shkedi (O)

Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.

Tamar Hashimshony (T)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.

Yael Mandel-Gutfreund (Y)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel.

Michael Halberthal (M)

Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.
Rambam Health Care Campus, Haifa, Israel.

Yuval Geffen (Y)

Bacteriology laboratory, Rambam Health Care Campus, Haifa, Israel.

Moran Szwarcwort-Cohen (M)

Virology laboratory, Rambam Health Care Campus, Haifa, Israel.

Roy Kishony (R)

Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel.

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