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

@article{wagner2026benchmarking,
  title = {{Benchmarking and optimisation of bait-capture metagenomics for sequencing of respiratory viruses at scale}},
  author = {Josef Wagner and Diana Rajan and Sarah Frances Field and Emma Betteridge and Katie Bellis and Marissa Knoll and Duncan Ng and Diego Teixeira and Beth Blane and Asha Akram and Catarina de Sousa and Joe Brennan and Dinesh Aggarwal and George MacIntyre-Cockett and Sandra E. Chaudron and Nicholas Grayson and Ben Hyatt and Andrew Wong and Anastasia Galvin and Ya-Lin Huang and David Jackson and Matthew Forbes and Frank Schwach and Andrea Frick-Kretschmer and Katerina Figueroa and Florent Lassalle and William Roberts-Sengier and Adrianne Lignes and Fernanda Novaes and Salma Fatima and Kevin Howe and Sara Stott and David Bonsall and Ewan M. Harrison},
  journal = {Genome Medicine},
  year = {2026},
  month = jul,
  doi = {10.1186/s13073-026-01725-8},
  url = {https://doi.org/10.1186/s13073-026-01725-8},
  note = {CC BY 4.0},
}

TY  - JOUR
TI  - Benchmarking and optimisation of bait-capture metagenomics for sequencing of respiratory viruses at scale
AU  - Josef Wagner
AU  - Diana Rajan
AU  - Sarah Frances Field
AU  - Emma Betteridge
AU  - Katie Bellis
AU  - Marissa Knoll
AU  - Duncan Ng
AU  - Diego Teixeira
AU  - Beth Blane
AU  - Asha Akram
AU  - Catarina de Sousa
AU  - Joe Brennan
AU  - Dinesh Aggarwal
AU  - George MacIntyre-Cockett
AU  - Sandra E. Chaudron
AU  - Nicholas Grayson
AU  - Ben Hyatt
AU  - Andrew Wong
AU  - Anastasia Galvin
AU  - Ya-Lin Huang
AU  - David Jackson
AU  - Matthew Forbes
AU  - Frank Schwach
AU  - Andrea Frick-Kretschmer
AU  - Katerina Figueroa
AU  - Florent Lassalle
AU  - William Roberts-Sengier
AU  - Adrianne Lignes
AU  - Fernanda Novaes
AU  - Salma Fatima
AU  - Kevin Howe
AU  - Sara Stott
AU  - David Bonsall
AU  - Ewan M. Harrison
PY  - 2026
DA  - 2026/07/01
JO  - Genome Medicine
DO  - 10.1186/s13073-026-01725-8
UR  - https://doi.org/10.1186/s13073-026-01725-8
AB  - 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.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s13073-026-01725-8.
SN  - 1756-994X
ER  -