A Viral Fragmentation Signature for SARS-CoV-2 in Clinical Samples Correlating with Contagiousness (preprint)

The viral load of SARS-CoV-2 in clinical samples as measured by the primary diagnostic tool of RT-PCR is an imperfect readout for infection potential as most targeted assays designed for sensitivity, indiscriminately detect short and long RNA fragments, although infectivity is embodied only in the whole virus and its intact genome. Here, we used next-generation sequencing (NGS) to characterize 155 clinical samples and show sensitive and quantitative detection of viral RNA which confirmed subgenomic RNA in 57.6% of samples and provided a novel method to determine relative integrity of viral RNA in samples. The relative abundance of long fragments quantified as a viral fragmentation score was positively associated with viral load and inversely related to time from disease onset. An empirically determined score cut-off for presence of substantially fragmented RNA was able to identify 100% of samples collected after 8 days of illness with poor infection potential in line with current clinical understanding of infectiousness of SARS-CoV-2. The quantification of longer fragments in addition to existing short targets in an NGS or RT-PCR-based assay could provide a valuable readout of infection potential simultaneous to the detection of any fragments of SARS-CoV-2 RNA in test samples.

MassMark: A Highly Scalable Multiplex NGS-based Method for High-Throughput, Accurate and Sensitive Detection of SARS-CoV-2 for Mass Testing (preprint)

Mass testing has been proposed as a strategy to address and contain the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. We have developed MassMark, a novel and highly scalable multiplex method that employs next generation sequencing for high-throughput, accurate and sensitive detection of SARS-CoV-2, while minimizing handling complexity and resources by utilizing a serial pooling strategy to accommodate over 9,000 samples per workflow. Analytical validation showed that MassMark was able to detect SARS-CoV-2 RNA down to a level of 100 copies per reaction. We evaluated the clinical performance of MassMark in a simulated screening testing with 22 characterized samples from three different sources (nasopharyngeal swabs, nasal swabs and saliva), comprising of 12 SARS-CoV-2 positive samples with mid to late Ct values (range: 22.98-32.72) and 10 negative samples. There was one false negative and no false positives, giving an overall sensitivity and specificity of 91.67% and 100% respectively, when compared against an optimized RT-PCR test with a target size within 70 bp (CDC 2019-nCoV Real-Time RT-PCR Diagnostic Panel).

Validation of Saliva and Self-Administered Nasal Swabs for COVID-19 Testing (preprint)

Background Active cases of COVID-19 has primarily been diagnosed via RT-PCR of nasopharyngeal (NP) swabs. Saliva and self-administered nasal (SN) swabs can be collected safely without trained staff. We aimed to test the sensitivity of naso-oropharyngeal saliva and SN swabs compared to NP swabs in a large cohort of migrant workers in Singapore. Methods We recruited 200 male adult subjects: 45 with acute respiratory infection, 104 asymptomatic close contacts, and 51 confirmed COVID-19 cases. Each subject underwent NP swab, SN swab and saliva collection for RT-PCR testing at 1 to 3 timepoints. We additionally used a direct-from-sample amplicon-based next-generation sequencing (NGS) workflow to establish phylogeny. Results Of 200 subjects, 91 and 46 completed second and third rounds of testing, respectively. Of 337 sets of tests, there were 150 (44.5%) positive NP swabs, 127 (37.7%) positive SN swabs, and 209 (62.0%) positive saliva. Test concordance between different sample sites was good, with a kappa statistic of 0.616 for NP and SN swabs, and 0.537 for NP and saliva. In confirmed symptomatic COVID-19 subjects, the likelihood of a positive test from any sample fell beyond 14 days of symptom onset. NGS was conducted on 18 SN and saliva samples, with phylogenetic analyses demonstrating lineages for all samples tested were Clade O (GISAID nomenclature) and lineage B.6 (PANGOLIN nomenclature). Conclusion This study supports saliva as a sensitive and less intrusive sample for COVID-19 diagnosis and further delineates the role of oropharyngeal secretions in increasing the sensitivity of testing. However, SN swabs were inferior as an alternate sample type. Our study also provides evidence that a straightforward next-generation sequencing workflow can provide direct-from-sample phylogenetic analysis for public health decision-making.