ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic has led to a public health crisis and global panic. This infectious disease is caused by a novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Digital polymerase chain reaction (dPCR), which is an emerging nucleic acid amplification technology that allows absolute quantification of nucleic acids, plays an important role in the detection of SARS-CoV-2. In this review, we introduce the principle and advantages of dPCR, and review the applications of dPCR in the COVID-19 pandemic, including detection of low copy number viruses, measurement of the viral load, preparation of reference materials, monitoring of virus concentration in the environment, detection of viral mutations, and evaluation of anti-SARS-CoV-2 drugs. We also discuss the challenges of dPCR in clinical practice.
ABSTRACT
In article number 20200082, Yong Guo and co-workers have shown the detection of SARS-CoV-2 RNA by digital PCR.
ABSTRACT
BACKGROUND: Qualitative and quantitative detection of nucleic acids of SARS-CoV-2, the pathogen that causes coronavirus disease 2019 (COVID-19), plays a significant role in COVID-19 diagnosis, surveillance, prevention, and control. METHODS: A total of 117 samples from 30 patients with confirmed COVID-19 and 61 patients without COVID-19 were collected. Reverse transcriptase quantitative PCR (RT-qPCR) and droplet digital PCR (ddPCR) were used for qualitative and quantitative analyses of these samples to evaluate the diagnostic performance and applicability of the two methods. RESULTS: The positive detection rates of RT-qPCR and ddPCR were 93.3% and 100%, respectively. Among the 117 samples, 6 samples were tested single-gene positive by RT-qPCR but positive by ddPCR, and 3 samples were tested negative by RT-qPCR but positive by ddPCR. The viral load of samples with inconsistent results were relatively low (3.1-20.5 copies/test). There were 17 samples (37%) with a viral load below 20 copies/test among the 46 positive samples, and only 9 of them were successfully detected by RT-qPCR. A severe patient was dynamically monitored. All 6 samples from this patient were tested negative by RT-qPCR, but 4 samples were tested positive by ddPCR with a low viral load. CONCLUSION: Qualitative analysis of COVID-19 samples can meet the needs of clinical screening and diagnosis, while quantitative analysis provides more information to the research community. Although both ddPCR and RT-qPCR can provide qualitative and quantitative results, ddPCR showed higher sensitivity and lower limit of detection than RT-qPCR, and it does not rely on the standard curve to quantify viral load. Therefore, ddPCR offers greater advantages than RT-qPCR.