Development and performance testing an agnostic next-generation sequencing assay for detection of respiratory RNA viruses from clinical samples

The COVID-19 pandemic has emphasized the need for rapid, comprehensive, and user-friendly diagnostic testing strategies. Metagenomic sequencing - non-specifically sequencing all of the nucleic acid within a sample - offers researchers the opportunity to agnostically detect pathogens from clinical samples. Previous work, including work towards my PhD thesis, has demonstrated the feasibility and utility of metagenomic sequencing for the detection and characterization of RNA viruses. However, several barriers still exist that prevent the widespread translation of metagenomic sequencing methods to diagnostic laboratories including, lengthy end-to-end assay completion times, lack of automated laboratory protocols, and poor diagnostic sensitivity for weakly-positive specimens. My proposed PhD research aims to address these barriers. I will optimize and validate a metagenomic sequencing assay; my approach will include combining RNA to cDNA synthesis, amplification, and sequencing library preparation in one-step. I will also include a new method to deplete human cDNA to concentrate on sequencing of viral targets and improve diagnostic sensitivity. I will test this method on SARS-CoV-2 samples, followed by quantification of diagnostic test performance using contrived samples containing other respiratory RNA viruses (influenza A/B, respiratory syncytial virus). Finally, clinical validation of our assay will be performed using inpatient and outpatient samples collected during the 2023 respiratory virus season. This project is supported by the U.S. Biomedical Advanced Research and Development Authority, and is embedded in the BC Public Health Laboratory, ensuring that the metagenomic sequencing assay can be tested, approved, translated, and implemented in clinical and surveillance settings.