Targeted viral meta-transciptomics from hospital floor samples
Built environment surveillance is a proven approach for tracking disease burden of some viruses within hospitals and long-term care facilities. Targeted meta-genomics and -transcriptomics offer the opportunity to survey many targets from a built environment sample, but studies from clinical settings are lacking. We swabbed six discrete floor locations within the Emergency Department of an acute care centre in Ottawa, Canada and sequenced cDNA using a panel containing targets for 132 viral taxa, identifying the overall viral burden in the hospital across locations and time. The variant profile of SARS-CoV-2 across time was determined and matched to provincial variant prevalence. The correlation between metatranscriptomic read abundances with reported cases of Influenza A, SARS-CoV-2, and respiratory syncytial virus were assessed. We quantified Influenza A, SARS-CoV-2, and respiratory syncytial virus (RSV) via qPCR, and assessed the correlation of qPCR Cq versus metatranscriptomic reads for these viruses. We sequenced a median of 1,302,882 reads per sample from 38 floor swabs collected during peak respiratory viral season (November 2022-February 2023). Diversity measures showed significant differences in viral communities across locations in the Emergency Department. Identified shifts in SARS-CoV-2 variant abundances matched the changing infection landscape reported in Ontario for the same time period. Relationships between targeted metatranscriptomic read ratios and clinical burden were not statistically significant, although we found modest correspondence between qPCR signal and metatranscriptomic read depth for RSV and SARS-CoV-2. A target metatranscriptomic approach for built environment samples characterized the viral communities and within-species diversity within an Emergency Department.  We found inconsistent utility of correlating sequencing derived viral abundance data with disease burden for three key  respiratory viruses, with exception of significant correlation between metatranscriptomic reads and Cq data from qPCR for SARS-CoV-2. We were able to recover the distribution of clinically reported SARS-CoV-2 variants from the floor swab data.