SARS-CoV-2 RNA quantification using droplet digital RT-PCR

Kinloch, Natalie N.; Ritchie, Gordon; Dong, Winnie; Cobarrubias, Kyle D.; Sudderuddin, Hanwei; Lawson, Tanya; Matic, Nancy; Montaner, Julio S.G.; Leung, Victor; Romney, Marc G.; Lowe, Christopher F.; Brumme, Chanson J.; Brumme, Zabrina L.

Quantitative viral load assays have transformed our understanding of – and ability to manage − viral diseases. They hold similar potential to advance COVID-19 control and prevention, but SARS-CoV-2 viral load tests are not yet widely available. SARS-CoV-2 molecular diagnostic tests, which typically employ real-time reverse transcriptase-polymerase chain reaction (RT-PCR), yield semi-quantitative results only. Reverse transcriptase droplet digital PCR (RT-ddPCR), a technology that partitions each reaction into 20,000 nanolitre-sized droplets prior to amplification, offers an attractive platform for SARS-CoV-2 RNA quantification. We evaluated eight primer/probe sets originally developed for real-time RT-PCR-based SARS-CoV-2 diagnostic tests for use in RT-ddPCR, and identified three (Charité-Berlin E-Sarbeco and Pasteur Institute IP2 and IP4) as the most efficient, precise and sensitive for RT-ddPCR-based SARS-CoV-2 RNA quantification. Analytical efficiency of the E-Sarbeco primer/probe set, for example, was ~83%, while assay precision, as measured by the coefficient of variation, was ~2% at 1000 input copies/reaction. Lower limits of quantification and detection for this primer/probe set were 18.6 and 4.4 input SARS-CoV-2 RNA copies/reaction, respectively. SARS-CoV-2 RNA viral loads in a convenience panel of 48 COVID-19-positive diagnostic specimens spanned a 6.2log10 range, confirming substantial viral load variation in vivo. We further calibrated RT-ddPCR-derived SARS-CoV-2 E gene copy numbers against cycle threshold (Ct) values from a commercial real-time RT-PCR diagnostic platform. The resulting log-linear relationship can be used to mathematically derive SARS-CoV-2 RNA copy numbers from Ct values, allowing the wealth of available diagnostic test data to be harnessed to address foundational questions in SARS-CoV-2 biology.