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Comparison of analytical sensitivity and efficiency for SARS-CoV-2 primer sets by TaqMan-based and SYBR Green-based RT-qPCR

  • Yile Tao
  • , Yang Yue
  • , Guangyu Qiu
  • , Zheng Ji
  • , Martin Spillman
  • , Zhibo Gai
  • , Qingfa Chen
  • , Michel Bielecki
  • , Michael Huber
  • , Alexandra Trkola
  • , Qiyuan Wang
  • , Junji Cao
  • , Jing Wang
  • Swiss Federal Institute of Technology Zurich
  • Swiss Federal Laboratories for Materials Science and Technology (Empa)
  • Shaanxi Normal University
  • University of Zurich
  • Liaocheng University
  • CAS - Institute of Earth Environment
  • Chinese Academy of Sciences

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Abstract: The pandemic of coronavirus disease 2019 (COVID-19) continues to threaten public health. For developing countries where vaccines are still in shortage, cheaper alternative molecular methods for SARS-CoV-2 identification can be crucial to prevent the next wave. Therefore, 14 primer sets recommended by the World Health Organization (WHO) was evaluated on testing both clinical patient and environmental samples with the gold standard diagnosis method, TaqMan-based RT-qPCR, and a cheaper alternative method, SYBR Green-based RT-qPCR. Using suitable primer sets, such as ORF1ab, 2019_nCoV_N1 and 2019_nCoV_N3, the performance of the SYBR Green approach was comparable or better than the TaqMan approach, even when considering the newly dominating or emerging variants, including Delta, Eta, Kappa, Lambda, Mu, and Omicron. ORF1ab and 2019_nCoV_N3 were the best combination for sensitive and reliable SARS-CoV-2 molecular diagnostics due to their high sensitivity, specificity, and broad accessibility. Key points: • With suitable primer sets, the SYBR Green method performs better than the TaqMan one. • With suitable primer sets, both methods should still detect the new variants well. • ORF1ab and 2019_nCoV_N3 were the best combination for SARS-CoV-2 detection.

Original languageEnglish
Pages (from-to)2207-2218
Number of pages12
JournalApplied Microbiology and Biotechnology
Volume106
Issue number5-6
DOIs
StatePublished - Mar 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • COVID-19
  • RT-qPCR
  • SARS-CoV-2
  • SYBR Green
  • TaqMan probe

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