Dataset Information

Evaluation of the clinical performance of single-, dual-, and triple-target SARS-CoV-2 RT-qPCR methods.

ABSTRACT: BACKGROUND:The coronavirus disease 2019 (COVID-19) has become a pandemic. Reverse transcription quantitative PCR (RT-qPCR) has played a vital role in the diagnosis of COVID-19, but the rates of false negatives is not ideal in dealing with this highly infectious virus. It is thus necessary to systematically evaluate the clinical performance of the single-, dual-, triple-target detection kits to guide the clinical diagnosis of this disease. METHODS:A series of reference materials calibrated by droplet digital PCR (ddPCR) and 57 clinical samples were used to evaluate the clinical performance of six single-, dual-, triple-target SARS-CoV-2 nucleic acid detection kits based on RT-qPCR. RESULTS:The dual-target kits, kit B and kit C had the highest and the lowest detection sensitivity, which was 125 copies/mL and 4000 copies/mL, respectively. Among the 57 clinical samples from patients with COVID-19, 47 were tested positive by the kit B, while 35, 29, 28, 30, and 29 were found positive by the kits A, C, D, E, and F, respectively. The number of targets in a detection kit is not a key factor affecting sensitivity, while the amount of sample loading may influence the performance of a detection kit. CONCLUSIONS:This study provides a guide when choosing or developing a nucleic acid detection kit for the diagnosis of COVID-19. Also, the absolute-quantification feature and high-sensitivity performance of ddPCR, suggesting that it can be used to review clinically suspected samples.

SUBMITTER: Hu X

PROVIDER: S-EPMC7550050 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation of the clinical performance of single-, dual-, and triple-target SARS-CoV-2 RT-qPCR methods.

Hu Xiaomei X Zhu Lingxiang L Luo Yijun Y Zhao Qinfei Q Tan Chianru C Chen Xiao X Zhang Huijuan H Hu Xiaojun X Lu Linping L Xiao Yongwei Y Huang Shao S He Yingke Y Sim Jacqueline Xiu Ling JXL Su Shisheng S Wang Fang F Peng Yanke Y Wang Jigang J Guo Yong Y Zhong Tianyu T

Clinica chimica acta; international journal of clinical chemistry 20201012

<h4>Background</h4>The coronavirus disease 2019 (COVID-19) has become a pandemic. Reverse transcription quantitative PCR (RT-qPCR) has played a vital role in the diagnosis of COVID-19, but the rates of false negatives is not ideal in dealing with this highly infectious virus. It is thus necessary to systematically evaluate the clinical performance of the single-, dual-, triple-target detection kits to guide the clinical diagnosis of this disease.<h4>Methods</h4>A series of reference materials ca ...[more]

PMID: 33058839

Similar Datasets

Project description:BackgroundSensitive, rapid, and accessible diagnostics continue to be critical to track the COVID-19 pandemic caused by the SARS-CoV-2 virus. RT-qPCR is the gold standard test, and comparison of methodologies and reagents, utilizing patient samples, is important to establish reliable diagnostic pipelines.MethodsHere, we assessed indirect methods that require RNA extraction with direct RT-qPCR on patient samples. Four different RNA extraction kits (Qiagen, Invitrogen, BGI and Norgen Biotek) were compared. For detection, we assessed two recently developed Taqman-based modules (BGI and Norgen Biotek), a SYBR green-based approach (NEB Luna Universal One-Step Kit) with published and newly-developed primers, and clinical results (Seegene STARMag RNA extraction system and Allplex 2019-nCoV RT-qPCR assay). We also tested and optimized direct, extraction-free detection using these RT-qPCR systems and performed a cost analysis of the different methods evaluated here.ResultsMost RNA isolation procedures performed similarly, and while all RT-qPCR modules effectively detected purified viral RNA, the BGI system provided overall superior performance (lower detection limit, lower Ct values and higher sensitivity), generating comparable results to original clinical diagnostic data, and identifying samples ranging from 65 copies to 2.1 × 105 copies of viral genome/μl. However, the BGI detection system is more expensive than other options tested here. With direct RT-qPCR, simply adding an RNase inhibitor greatly improved detection, without the need for any other treatments (e.g. lysis buffers or boiling). The best direct methods detected ~ 10 fold less virus than indirect methods, but this simplified approach reduced sample handling, as well as assay time and cost.ConclusionsWith extracted RNA, the BGI RT-qPCR detection system exhibited superior performance over the Norgen system, matching initial clinical diagnosis with the Seegene Allplex assay. The BGI system was also suitable for direct, extraction-free analysis, providing 78.4% sensitivity. The Norgen system, however, still accurately detected samples with a clinical Ct < 33 from extracted RNA, provided significant cost savings, and was superior to SYBR green assays that exhibited reduced specificity.

Project description:BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused a global pandemic beginning in 2020, can be detected by reverse-transcription polymerase chain reaction (RT-PCR). However, owing to the urgent need for a large number of detection kits, the time spent researching and developing these kits has been shortened during the pandemic, and the kits that are being used commercially have not undergone full and independent evaluation. To ensure the accuracy of SARS-CoV-2 test results, performance verification of commercial Real-Time quantitative PCR (RT-qPCR) kits is required.MethodsThe performance of five commercial RT-qPCR diagnostic kits for SARS-CoV-2 used in China was evaluated using a coronavirus disease 2019 (COVID-19) RNA liquid performance verification reference product-manufactured by Guangzhou Bondson (BDS) Biotechnology Co., Ltd.,Guangzhou, China-that uses droplet digital RT-PCR technology combined with fluorescence quantitative PCR. The five kits of Novel Coronavirus 2019-nCoV nucleic acid detection kit (RT-qPCR method) evaluated were Da An (Da An Gene Co., Ltd. of Sun Yat-sen University), Liferiver (Shanghai ZJ Bio-Tech Co., Ltd.), Kinghawk (Beijing Kinghawk Pharmaceutical Co., Ltd.), eDiagnosis (Wuhan Easy Diagnosis Biomedicine Co., Ltd.), and Maccura (Maccura Biotechnology Co., Ltd.). Performance verification criteria included the coincidence rate, limit of detection (LoD), cross-reactivity, precision, and anti-interference. Finally, through the BDS performance verification reference product kit, clinical samples are used to verify its clinical diagnostic efficacy.ResultsThe coincidence rate was 100% for all kits except for Kinghawk, which was 95%. The LoD for Da An, eDiagnosis and Maccura was 250copies/mL, and it was 1000 copies/ml for Liferiver. Kinghawk was not able to detect its advertised LoD of 500 copies/ml. The cross-reactivity test results were all negative. Moreover, all kits had a coefficient of variation less than 5%; however, Liferiver showed the best precision. Da An, Liferiver, and eDiagnosis showed higher sensitivity to the nucleocapsid (N) gene than they did to the open reading frame (ORF) 1ab genes. Anti-interference results for all five kits were positive. The results of clinical diagnostic efficacy were that the specificity of the four kits was 1.000 (0.877-1.000), the sensitivity of Da An was 1.000 (0.850-1.000), Liferiver was 0.964 (0.798-0.998), Maccura was 0.893 (0.706-0.972), and eDiagnosis was 0.857 (0.664-0.953).ConclusionsAll commercial RT-qPCR diagnostic kits for SARS-CoV-2 passed the BDS performance verification, except for Kinghawk (batch No:20200608113) which failed to detect the LoD of 500 copies/mL. Da An and Liferiver have excellent clinical diagnostic specificity and sensitivity. This study can provide guidance for the selection or optimization of RT-qPCR diagnostic test kits for SARS-CoV-2.

Dataset Information

Evaluation of the clinical performance of single-, dual-, and triple-target SARS-CoV-2 RT-qPCR methods.

Publications

Evaluation of the clinical performance of single-, dual-, and triple-target SARS-CoV-2 RT-qPCR methods.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets