Quantifying viral load and characterizing virus diversity in wildlife samples with target enrichment sequencing

Metagenomics is a powerful tool for characterizing viruses, with broad applications across diverse disciplines, from understanding the ecology and evolutionary history of viruses to identifying causative agents of emerging outbreaks with unknown aetiology. Additionally, metagenomic data contain valuable information about the amount of virus present within samples (i.e. viral load), which can provide insights into transmission potential, time since infection and, in turn, epidemic trajectories. However, before we can effectively use metagenomic data to inform transmission, we need to understand the general relationship between sequencing outputs and viral load. Here, using a commercially available probe panel targeting a wide diversity of viruses, we investigated the detection and recovery of virus genomes by spiking known concentrations of DNA and RNA viruses into wild rodent faecal samples. In total, 15 experimental replicates were sequenced with target enrichment sequencing and compared to shotgun sequencing of the same background samples. Target-enriched sequencing recovered all spike-in viruses at every concentration (10², 10³ and 10⁵±1 log genome copies) and showed a log-linear relationship between spike-in concentration and mean read depth. Background viruses (including Kobuvirus and Cardiovirus) were recovered consistently across all biological and technical replicates and by shotgun sequencing, but genome coverage was variable between virus genera and likely reflected the composition of the target enrichment probe panel. Overall, our study highlights the strengths and weaknesses of using commercially available panels to quantify and characterize wildlife viromes and underscores the importance of probe panel design for accurately interpreting coverage and read depth. To advance the use of metagenomics for understanding virus transmission, further research will be needed to elucidate how sequencing strategy (e.g. library depth and pooling), virome composition and probe design influence viral read counts and genome coverage.