Droplet digital PCR application for the detection of SARS-CoV-2 in air sample

Abstract

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) may transmit through airborne route particularly when the aerosol particles remain in enclosed spaces with inadequate ventilation. There has been no standard recommended method of determining the virus in air due to limitations in pre-analytical and technical aspects. Furthermore, the presence of low virus loads in air samples could result in false negatives. Our study aims to explore the feasibility of detecting SARS-CoV-2 ribonucleic acid (RNA) in air samples using droplet digital polymerase chain reaction (ddPCR). Active and passive air sampling was conducted between December 2021 and February 2022 with the presence of COVID-19 confirmed cases in two hospitals and a quarantine center in Klang Valley, Malaysia. SARS-CoV-2 RNA in air was detected and quantified using ddPCR and real-time reverse transcriptase-polymerase chain reaction (RT-PCR). The comparability of two different digital PCR platforms (QX200 and QIAcuity) to RT-PCR were also investigated. Additionally negative staining transmission electron microscopy was performed to visualize virus ultrastructure. Detection rates of SARS-CoV-2 in air samples using ddPCR were higher compared to RT-PCR, which were 15.2% (22/145) and 3.4% (5/145), respectively. The sensitivity and specificity of ddPCR was 100 and 87%, respectively. After excluding 17 negative samples (50%) by both QX200 and QIAcuity, 15% samples (5/34) were found to be positive both ddPCR and dPCR. There were 23.5% (8/34) samples that were detected positive by ddPCR but negative by dPCR. In contrast, there were 11.7% (4/34) samples that were detected positive by dPCR but negative by ddPCR. The SARS-CoV-2 detection method by ddPCR is precise and has a high sensitivity for viral RNA detection. It could provide advances in determining low viral titter in air samples to reduce false negative reports, which could complement detection by RT-PCR.

Keywords: SARS-CoV-2 RNA; air sample; droplet digital PCR; sensitivity; specificity.

Figure 1

Schematic workflow of the experimental air sampling set-up and molecular detection platform. (A) Upstream process to detect SARS-CoV-2 in air samples and (B) downstream analysis for SARS-CoV-2 detection by RT-PCR, reverse transcription quantitative polymerase chain reaction; ddPCR, droplet digital PCR; TEM, transmission electron microscope; dPCR, digital PCR.

Figure 2

The QuantasoftTM Software (Bio-Rad Laboratories) generated ddPCR two-dimensional scatterplots for the SARS-CoV-2 RNA in air samples. (A) Showed samples with a high number of droplets in the FAM and FAM+HEX-channel, while (B) displayed fewer droplets in both channels in contrast to the number of droplets in (A). The X-axis represented the fluorescence intensity in the HEX-channel (channel 2), while the Y-axis represented the fluorescence intensity in the FAM-channel (channel 1). The background fluorescence is represented by the gray dots, the fluorescence detected in the FAM+HEX-channel (E gene) is represented by the yellow dots, and the fluorescence detected in the FAM-channel (N2 gene) is represented by the red dots.

Figure 3

Viral with capsid were seen under negative staining through TEM in 18,000x magnification. These identifications were confirmed with ddPCR.

Figure 4

Summary of SARS-CoV-2 detection in air samples isolated from air sampler membrane filter using different platforms ddPCR, RT-PCR and TEM.

Figure 5

Number of positive and negative air samples detection from diagnostic performance for SARS-CoV-2 detection using ddPCR and dPCR platforms.