Monitoring SARS-CoV-2 genetic variability: A post-market surveillance workflow for combined bioinformatic and laboratory evaluation of commercial RT-PCR assay performance

OBJECTIVE

The speed at which Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is mutating has made it necessary to frequently assess how these genomic changes impact the performance of diagnostic real-time polymerase chain reaction (RT-PCR) assays. Herein, we describe a generic three-step workflow to assess the effect of genomic mutations on inclusivity and sensitivity of RT-PCR assays.

METHODS

Sequences collected from the Global Initiative on Sharing All Influenza Data (GISAID) were mapped to a SARS-CoV-2 reference genome to evaluate the position and prevalence of mismatches in the oligonucleotide-binding sites of the QIAstat-Dx, an RT-PCR panel designed to detect SARS-CoV-2. The frequency of mutations and their impact on melting temperature were assessed, and sequences flagged by risk-based criteria were examined in vitro.

RESULTS

Out of 8,900,393 SARS-CoV-2 genome sequences analyzed, only 173 (0.0019%) genomes contained potentially critical mutations for the QIAstat-Dx; follow-up in-vitro testing confirmed no impact on the assays' performance.

CONCLUSIONS

The current study demonstrates that SARS-CoV-2 genetic variants do not affect the performance of the QIAstat-Dx device. It is recommended that manufacturers incorporate this workflow into obligatory post-marketing surveillance activities, as this approach could potentially enhance genetic monitoring of their product.

Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness

Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans.

Ct values as a diagnostic tool for monitoring SARS-CoV-2 viral load using the QIAstat-Dx® Respiratory SARS-CoV-2 Panel

OBJECTIVES

Qualitative real-time polymerase chain reaction tests are not designed to provide quantitative or semiquantitative results because cycle threshold (Ct) values are not normalized to standardized controls of known concentration. The aim of this study was to characterize SARS-CoV-2 viral loads based on Ct values, using the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

METHODS

Different lineages of SARS-CoV-2 clinical samples and the World Health Organization international standard were used to assess the linearity of the QIAstat-Dx Respiratory SARS-CoV-2 Panel. Limit of detection for the different lineages was characterized.

RESULTS

Comparable efficiencies and linearity for all samples resulted in R² ≥0.99, covering a dynamic range of 1,000,000-100 copies/mL for the SARS-CoV-2 assay, showing linear correlation between Ct values and viral load down to 300 copies/mL.

CONCLUSION

The SARS-CoV-2 Ct values provided by the QIAstat-Dx® Respiratory SARS-CoV-2 Panel could be used as a surrogate for viral load given the linear correlation between Ct values and viral concentration down to limit of detection. This panel allows to obtain reproducible Ct values for SARS-CoV-2 ribonucleic acid downstream of the sample collection, reducing the sample-to-Ct workflow variability. Ct values can help provide a reliable assessment and comparison of viral loads in patients when tested with the QIAstat-Dx Respiratory SARS-CoV-2 Panel.