The current health crisis caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus), represents one of the greatest health challenges ever faced worldwide. The gold standard for SARS-CoV-2 diagnosis is based on reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Current RT-qPCR-based methods rely on the amplification of SARS-CoV-2 nucleic acids from rhino-pharyngeal swab samples taken from subjects with suspected COVID-19 infection. However, RT-qPCR analysis can be subject to low sensitivity, particularly in subjects with low viral load. These challenges can be attributed to variations in RT-qPCR protocols, buffers used for extraction and maintenance, as well as the quality of the RNA sample. Droplet digital PCR (ddPCR) is a highly sensitive PCR-based technology that allows absolute quantification of targets in the reaction mix by using water-oil emulsion droplet technology. However, the use of ddPCR for SARS-CoV-2 diagnosis has not been validated.
In a recent publication in the International Journal of Molecular Medicine, Falzone et al. performed a comparative analysis between RT-qPCR and ddPCR on detection of SARS-CoV-2 in relevant clinical samples. Specifically, the authors evaluated RT-qPCR with SYBR® Green or TaqMan® probe, and ddPCR with EvaGreen® Dye or TaqMan® Probe. Each method was tested on two RNA samples extracted from rhino-pharyngeal swabs, one negative control and one SARS-CoV-2 positive sample from a patient with a low viral load. Results show RT-qPCR with SYBR® Green failed to distinguish between the negative and positive SARS-CoV-2 samples. RT-qPCR with TaqMan® correctly identified the presence of SARS-CoV-2 in the positive sample only when undiluted and with a very late Ct value. On the other hand, ddPCR with EvaGreen® Dye and TaqMan® Probe was able to correctly distinguish the positive and negative SARS-CoV-2 samples in both undiluted and 10-fold diluted samples. Overall, this preliminary study suggests clinical use of ddPCR for SARS-CoV-2 diagnosis may demonstrate significant improvements in accuracy and sensitivity over conventional RT-qPCR methods.
Linear regression analysis of β‑actin ddPCR and RT‑qPCR data. (A) Linear regression of β‑actin values considering all dilutions of sample 1; (B) Linear regression analysis of β‑actin values without the inhibited undiluted sample 1. RT‑qPCR, reverse transcription‑quantitative polymerase chain reaction; ddPCR, droplet digital PCR
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