Benchmarking and optimisation of bait-capture metagenomics for sequencing of respiratory viruses at scale
Abstract
Sequencing of respiratory virus genomes is important for public health and research. Shotgun metagenomics although pathogen agnostic is limited by off-target DNA/RNA. Bait capture metagenomics (hybridization capture) overcomes this by selectively enriching a targeted component of the library. We sought to evaluate three different respiratory virus bait capture methods to determine any advantages between methods. We show that all three bait capture methods demonstrated high efficiency and reproducibility and generated broadly comparable results, with some minor variation at low viral copy numbers. We show that further optimisations to reduce costs and to enable automation are possible without impacting sensitivity. Overall, we demonstrate that viral bait capture methods are broadly effective for respiratory viruses and that cost reductions can be achieved without compromising performance. These results provide confidence in viral bait capture methods for the routine global surveillance of respiratory viruses for global public health monitoring and preparedness.
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