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

Metagenomics is a powerful tool for characterising 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 contains valuable information about the amount of virus present within samples. However, we have yet to leverage metagenomics to assess viral load, which is a key epidemiological parameter. To effectively use sequencing outputs to inform transmission, we need to understand the relationship between read depth and viral load across a diverse set of viruses. Here, using target enrichment sequencing, 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, but genome coverage was variable between virus genera and likely reflected the composition of target enrichment probe panel. Overall, our study highlights the strengths and weaknesses of using commercially available panels to quantify and characterise 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, pooling), virome composition, and probe design influence viral read counts and genome coverage.