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Background <p>Sequencing respiratory virus genomes is essential for public health surveillance and research. Although shotgun metagenomics is pathogen agnostic, its sensitivity is limited by abundant off-target host nucleic acids. Hybridization bait capture overcomes this limitation by selectively enriching viral sequences prior to sequencing.</p> Methods <p>We evaluated three respiratory viral bait capture workflows (veSEQ, RVI-seq, and Illumina) to compare their performance and assess their suitability for scalable respiratory virus sequencing. Synthetic RNA controls and clinical samples containing SARS-CoV-2, influenza A, influenza B, human parainfluenza virus, and respiratory syncytial virus (RSV) were analysed.</p> Results <p>All three workflows demonstrated high efficiency, reproducibility and broadly comparable performance across respiratory viruses. Complete viral genomes were consistently recovered from samples containing 10,000 viral copies, while viral reads remained detectable at substantially lower viral loads, including approximately 100 copies. Workflow optimisation reduced reagent costs and enabled laboratory automation without compromising sequencing sensitivity.</p> Conclusion <p>Hybridization bait capture provides an effective and scalable approach for respiratory virus genome sequencing. Cost reductions and automation can be implemented without compromising performance, supporting its use in routine genomic surveillance and public health preparedness.</p>

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Benchmarking and optimisation of bait-capture metagenomics for sequencing of respiratory viruses at scale

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月30日

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  • Josef Wagner,
  • Diana Rajan,
  • Sarah Frances Field,
  • Emma Betteridge,
  • Katie Bellis,
  • Marissa Knoll,
  • Duncan Ng,
  • Diego Teixeira,
  • Beth Blane,
  • Asha Akram,
  • Catarina de Sousa,
  • Joe Brennan,
  • Dinesh Aggarwal,
  • George MacIntyre-Cockett,
  • Sandra E. Chaudron,
  • Nicholas Grayson,
  • Ben Hyatt,
  • Andrew Wong,
  • Anastasia Galvin,
  • Ya-Lin Huang,
  • David Jackson,
  • Matthew Forbes,
  • Frank Schwach,
  • Andrea Frick-Kretschmer,
  • Katerina Figueroa,
  • Florent Lassalle,
  • William Roberts-Sengier,
  • Adrianne Lignes,
  • Fernanda Novaes,
  • Salma Fatima,
  • Kevin Howe,
  • Sara Stott,
  • David Bonsall,
  • Ewan M. Harrison

摘要

Background

Sequencing respiratory virus genomes is essential for public health surveillance and research. Although shotgun metagenomics is pathogen agnostic, its sensitivity is limited by abundant off-target host nucleic acids. Hybridization bait capture overcomes this limitation by selectively enriching viral sequences prior to sequencing.

Methods

We evaluated three respiratory viral bait capture workflows (veSEQ, RVI-seq, and Illumina) to compare their performance and assess their suitability for scalable respiratory virus sequencing. Synthetic RNA controls and clinical samples containing SARS-CoV-2, influenza A, influenza B, human parainfluenza virus, and respiratory syncytial virus (RSV) were analysed.

Results

All three workflows demonstrated high efficiency, reproducibility and broadly comparable performance across respiratory viruses. Complete viral genomes were consistently recovered from samples containing 10,000 viral copies, while viral reads remained detectable at substantially lower viral loads, including approximately 100 copies. Workflow optimisation reduced reagent costs and enabled laboratory automation without compromising sequencing sensitivity.

Conclusion

Hybridization bait capture provides an effective and scalable approach for respiratory virus genome sequencing. Cost reductions and automation can be implemented without compromising performance, supporting its use in routine genomic surveillance and public health preparedness.