Multiplex PCR Test Identifies SARS-CoV-2 Variants of Concern

Researchers from Rutgers University recently published findings that may change how we detect and track the spread of SARS-CoV-2 variants. Since the beginning of the pandemic, the team at Rutgers has been working to create COVID-19 test kits. Now, to address the ever-growing list of variants, the team decided to branch out their methodology to include some of the most common variants of SARS-CoV-2.

“It is extraordinary to see that SARS-CoV-2 was not a monolithic infection with a predictable set of clinical features, but rather an ever-evolving disease for which the different strains produce unique clinical features that affect testing, symptoms, and even which organ systems can be attacked,” explained lead investigator Sanjay Tyagi.

While deep sequencing techniques have been available for SARS-CoV-2, these tests are slow, costly, and require specialized equipment. The new work, recently published in The Journal of Molecular Diagnostics, addresses these challenges head on with an accessible, easy-to-replicate methodology. The team was able to expand upon already-designed PCR probes to create the Rutgers-RP RT-PCR assay to detect SARS-CoV-2 mutations.

For their study, researchers individually tested nine different mutations, each beacon with its own color combination of dyes. After confirming the molecular beacons were appropriately labeled, the team combined the steps into a multiplex assay to test by RT-PCR on 26 SARS-Cov2-positive patient samples, all of which underwent deep sequencing tests. The assay results fully agreed with the results from deep sequencing, with a sensitivity and specificity of 100%. 

“The tools we developed to track and identify new variants will be useful for this pandemic and for any unforeseen viruses or pathogens that may arise going forward,” said lead author Ryan J. Dikdan.

The assay was designed to be flexible, making it useful for future variants that have yet to be identified. When omicron first emerged, investigators were able to design a beacon in less than one month to accurately identify a mutation unique to omicron. In the patient population previously mentioned, they identified the omicron variant in 17 of the 33 samples, with results 100% in agreement with deep sequencing.