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 |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:554 |
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Enthalten in: |
Clinica chimica acta; international journal of clinical chemistry - 554(2024) vom: 01. Feb., Seite 117759 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Kim, Yoonjung [VerfasserIn] |
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Links: |
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Themen: |
Digital droplet polymerase chain reaction |
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Anmerkungen: |
Date Completed 05.02.2024 Date Revised 05.02.2024 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1016/j.cca.2023.117759 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM366747525 |
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500 | |a published: Print-Electronic | ||
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520 | |a Copyright © 2024 Elsevier B.V. All rights reserved. | ||
520 | |a 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 | ||
520 | |a 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 | ||
520 | |a 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 | ||
520 | |a 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 | ||
650 | 4 | |a Journal Article | |
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700 | 1 | |a Cho, Jinhee |e verfasserin |4 aut | |
700 | 1 | |a Ryu, Sook-Won |e verfasserin |4 aut | |
700 | 1 | |a Lee, Kyung-A |e verfasserin |4 aut | |
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