Optimized workflow for high-throughput whole genome surveillance of Influenza A virus

Influenza A viruses (IAVs) affect human and animal health and occasionally cause zoonotic spillovers. Whole genome sequencing (WGS) is essential for characterizing the genetic diversity of influenza A virus (IAV) across host species and mitigating its impact on human and animal health. While multisegment RT-PCR (mRT-PCR) enables the simultaneous amplification of all genomic segments in a single reaction, its sensitivity for larger segments remains suboptimal. To improve WGS sensitivity, we optimized the mRT-PCR protocol by modifying RT and PCR cycling conditions, resulting in improved recovery and representation of all eight IAV genomic segments. Furthermore, we developed a dual-barcoding approach for the Oxford Nanopore platform, allowing for high-throughput multiplexing of IAV-positive samples without compromising sensitivity. The resulting workflow is robust, scalable, and applicable to samples of avian, swine, and human origin, even at low viral loads. This optimized approach provides a practical solution for genomic surveillance at the human–animal interface, supporting early detection, evolutionary monitoring, and rapid identification of zoonotic spillover events.