Dataset Information

Digital PCR assay for the effective detection of COVID-19 patients with SARS-CoV-2 low viral load.

ABSTRACT:

Objective

Viral nucleic acid detection by real-time reverse transcription polymerase chain reaction (qPCR) is the current standard method for diagnosis of SARS-CoV-2 infection. However, due to low viral load in some COVID-19 patients, false negative results from this method have been repeatedly reported.

Method

In this study, we compared the sensitivity and specificity of digital PCR (dPCR) in simulated samples and clinical samples with qPCR assay through a series of vigorous tests.

Results

The results showed that dPCR was more sensitive than qPCR especially for samples with low viral load (≤3 copies). In addition, dPCR had similar specificity as qPCR and could effectively distinguish other human coronaviruses and influenza virus from SARS-CoV-2. More importantly, dPCR was more sensitive than qPCR in detecting the virus in the "negative" samples from recurrent COVID-19 patients.

Conclusions

In summary, dPCR could serve as a powerful complement to the current qPCR method for SARS-CoV-2 detection, especially for the samples with extremely low viral load, such as recurrent COVID-19 patients.

SUBMITTER: Sun Y

PROVIDER: S-EPMC8149472 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Publications

Digital PCR assay for the effective detection of COVID-19 patients with SARS-CoV-2 low viral load.

Sun Yong Y Ding Chengchao C Chen Qingqing Q Xie Jiajia J Yu Junling J Shi Yonglin Y Jiang Chengcheng C Zhang Zhuhui Z He Hongliang H Ge Yinglu Y Li Wenting W He Jun J Gao Yong Y

Journal of virological methods 20210526

<h4>Objective</h4>Viral nucleic acid detection by real-time reverse transcription polymerase chain reaction (qPCR) is the current standard method for diagnosis of SARS-CoV-2 infection. However, due to low viral load in some COVID-19 patients, false negative results from this method have been repeatedly reported.<h4>Method</h4>In this study, we compared the sensitivity and specificity of digital PCR (dPCR) in simulated samples and clinical samples with qPCR assay through a series of vigorous test ...[more]

PMID: 34051244

Similar Datasets

Project description:ObjectivesTo exploit the features of digital PCR for implementing SARS-CoV-2 observational studies by reliably including the viral load factor expressed as copies/μL.MethodsA small cohort of 51 Covid-19 positive samples was assessed by both RT-qPCR and digital PCR assays. A linear regression model was built using a training subset, and its accuracy was assessed in the remaining evaluation subset. The model was then used to convert the stored cycle threshold values of a large dataset of 6208 diagnostic samples into copies/μL of SARS-CoV-2. The calculated viral load was used for a single cohort retrospective study. Finally, the cohort was randomly divided into a training set (n = 3095) and an evaluation set (n = 3113) to establish a logistic regression model for predicting case-fatality and to assess its accuracy.ResultsThe model for converting the Ct values into copies/μL was suitably accurate. The calculated viral load over time in the cohort of Covid-19 positive samples showed very low viral loads during the summer inter-epidemic waves in Italy. The calculated viral load along with gender and age allowed building a predictive model of case-fatality probability which showed high specificity (99.0%) and low sensitivity (21.7%) at the optimal threshold which varied by modifying the threshold (i.e. 75% sensitivity and 83.7% specificity). Alternative models including categorised cVL or raw cycle thresholds obtained by the same diagnostic method also gave the same performance.ConclusionThe modelling of the cycle threshold values using digital PCR had the potential of fostering studies addressing issues regarding Sars-CoV-2; furthermore, it may allow setting up predictive tools capable of early identifying those patients at high risk of case-fatality already at diagnosis, irrespective of the diagnostic RT-qPCR platform in use. Depending upon the epidemiological situation, public health authority policies/aims, the resources available and the thresholds used, adequate sensitivity could be achieved with acceptable low specificity.

Project description:Quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay is the gold standard recommended to test for acute SARS-CoV-2 infection. However, it generally requires expensive equipment such as RNA isolation instruments and real-time PCR thermal cyclers. As a pandemic, COVID-19 has spread indiscriminately, and many low resource settings and developing countries do not have the means for fast and accurate COVID-19 detection to control the outbreak. Additionally, long assay times, in part caused by slow sample preparation steps, have created a large backlog when testing patient samples suspected of COVID-19. With many PCR-based molecular assays including an extraction step, this can take a significant amount of time and labor, especially if the extraction is performed manually. Using COVID-19 clinical specimens, we have collected evidence that the RT-qPCR assay can feasibly be performed directly on patient sample material in virus transport medium (VTM) without an RNA extraction step, while still producing sensitive test results. If RNA extraction steps can be omitted without significantly affecting clinical sensitivity, the turn-around time of COVID-19 tests, and the backlog we currently experience can be reduced drastically. Furthermore, our data suggest that rapid RT-PCR can be implemented for sensitive and specific molecular diagnosis of COVID-19 in locations where sophisticated laboratory instruments are not available. Our USD 300 set up achieved rapid RT-PCR using thin-walled PCR tubes and a water bath setup using sous vide immersion heaters, a Raspberry Pi computer, and a single servo motor that can process up to 96 samples at a time. Using COVID-19 positive clinical specimens, we demonstrated that RT-PCR assays can be performed in as little as 12 min using untreated samples, heat-inactivated samples, or extracted RNA templates with our low-cost water bath setup. These findings can help rapid COVID-19 testing to become more accessible and attainable across the globe.

Dataset Information

Digital PCR assay for the effective detection of COVID-19 patients with SARS-CoV-2 low viral load.

Objective

Method

Results

Conclusions

Publications

Digital PCR assay for the effective detection of COVID-19 patients with SARS-CoV-2 low viral load.

Similar Datasets

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