Clinical evaluation of a fully automated, lab developed multiplex RT-PCR assay integrating dual-target SARS-CoV-2 and Influenza–A/B detection on a high-throughput platform

Background

Laboratories worldwide face high demands for molecular testing during the SARS-CoV-2 pandemic that might be further aggravated with the upcoming influenza season in the northern hemisphere. Considering that symptoms of influenza are largely undistinguishable from COVID-19, both SARS-CoV-2 and the Influenza viruses require concurrent testing by RT-PCR in patients presenting with symptoms of respiratory tract infection. In this study, we adapted and evaluated a laboratory developed multiplex RT-PCR assay for simultaneous detection of SARS-CoV-2 (dual-target), Influenza-A and Influenza-B (SC2/InflA/InflB-UCT) on a fully automated high-throughput system (cobas6800).

Methods

Analytical performance was assessed by serial dilution of quantified reference material and cell culture stocks in transport medium, including pre-treatment for chemical inactivation. For clinical evaluation, residual portions of 164 predetermined patient samples containing SARS-CoV-2 (n=52), Influenza-A (n=43) or Influenza-B (n=19), as well as a set of negative samples was subjected to the novel multiplex assay.

Results

The assay demonstrated analytical performance comparable to currently available commercial tests, with limits of detection of 94.9 cp/ml for SARS-CoV-2, 14.6 cp/ml for Influenza-A and 422.3 cp/ml for Influenza-B. Clinical evaluation showed excellent agreement with the comparator assays (sensitivity 98.1%, 97.7% and 100% for Sars-CoV-2, Influenza-A and -B respectively).

Conclusion

The SC2/InflA/InflB-UCT allows for efficient high-throughput testing for all three pathogens and thus provides streamlined diagnostics while conserving resources during the Influenza-season.

Highlights

• Simultaneous detection of highly pathogenic respiratory viruses Influenza-A/B and SARS-CoV-2

• Including a dual-target assay for SARS-CoV-2 detection

• Full automation on the cobas6800 high-throughput platform