Evaluation of diagnostic performance of SARS-CoV-2 infection using digital droplet polymerase chain reaction in individuals with or without COVID-19 symptoms

Copyright © 2024 Elsevier B.V. All rights reserved..

BACKGROUND: Reverse transcription-quantitative PCR (RT-qPCR) is commonly used to diagnose SARS-CoV-2, but it has limited sensitivity in detecting the virus in asymptomatic close contacts and convalescent patients. In this study, we propose the use of reverse transcription-digital droplet PCR (RT-ddPCR) to detect SARS-CoV-2 in clinical samples.

METHODS: The clinical performance of RT-ddPCR targeting of ORF1ab and N genes was evaluated in parallel with RT-qPCR using 200 respiratory samples collected from close contacts and patients at different phases of infection.

RESULTS: The limits of detection (LODs) for RT-ddPCR assays were determined using six dilutions of ACCUPLEX SARS-Cov-2 reference material. The LODs of ORF1ab and N genes were 3.7 copies/reaction and 2.2 copies/reaction, respectively. Compared to RT-qPCR, RT-ddPCR increased the positive rate by 12.0% in 142 samples from SARS-CoV-2-infected patients. Additionally, RT-ddPCR detected SARS-CoV-2 in three of 26 specimens from close contacts that tested negative by RT-qPCR, and infection was confirmed using follow-up samples. Finally, RT-ddPCR improved the equivocal results from RT-qPCR in 56.3% (9/16) of convalescent patient samples.

CONCLUSIONS: Detecting SARS-CoV-2 in samples with low viral loads using RT-qPCR can be challenging. However, our study suggests that RT-ddPCR, with its higher sensitivity and accuracy, is better suited for detecting low viral copies in samples, particularly those from close contacts and convalescent patients.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:554

Enthalten in:

Clinica chimica acta; international journal of clinical chemistry - 554(2024) vom: 01. Feb., Seite 117759

Sprache:

Englisch

Beteiligte Personen:

Kim, Yoonjung [VerfasserIn]
Lee, Eunyoung [VerfasserIn]
Kim, Boyeon [VerfasserIn]
Cho, Jinhee [VerfasserIn]
Ryu, Sook-Won [VerfasserIn]
Lee, Kyung-A [VerfasserIn]

Links:

Volltext

Themen:

Digital droplet polymerase chain reaction
Journal Article
RNA, Viral
RT-qPCR
SARS-CoV-2

Anmerkungen:

Date Completed 05.02.2024

Date Revised 05.02.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.cca.2023.117759

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM366747525