A novel ORF1a-based SARS-CoV-2 RT-PCR assay to resolve inconclusive samples

BACKGROUND: India bears the second largest burden of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. A multitude of reverse transcription polymerase chain reaction (RT-PCR) detection assays with disparate gene targets, including automated high-throughput platforms, are available. Varying concordance and interpretation of diagnostic results in this setting can result in significant reporting delays, leading to suboptimal disease management. This article reports the development of a novel ORF1a-based SARS-CoV-2 RT-PCR assay – Viroselect – that shows high concordance with conventional assays and the ability to resolve inconclusive results generated during the peak of the epidemic in Mumbai, India. METHODS: A unique target region within SARS-CoV-2 ORF1a – the non-structural protein 3 (nsp3) region – was used to design and develop the assay. This hypervariable region (1923–3956) between SARS-CoV-2, SARS-CoV-1 and Middle East respiratory syndrome coronavirus was utilized to design the primers and probes for the RT-PCR assay. The concordance of this assay with commonly used emergency use authorization (US Food and Drug Administration) manual kits and an automated high-throughput testing platform was evaluated. Further, a retrospective analysis was carried out using Viroselect on samples reported as ‘inconclusive’ between April and October 2020. RESULTS: In total, 701 samples were tested. Concordance analysis of 477 samples demonstrated high overall agreement of Viroselect with both manual (87.6%) and automated (84.7%) assays. Also, in the retrospective analysis of 224 additional samples reported as ‘inconclusive’, Viroselect was able to resolve 100% (19/19) and 93.7% (192/205) of samples which had inconclusive results on manual and automated high-throughput platforms, respectively. CONCLUSION: Viroselect had high concordance with conventional assays, both manual and automated, and has potential to resolve inconclusive samples.