Ratcliff Jeremy D, Merritt Brian, Gooden Hannah, Siegers Jurre Y, Srikanth Abhinaya, Yann Sokhoun, Kol Sonita, Sin Sarath, Tok Songha, Karlsson Erik A, Thielen Peter M
Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA.
Virology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia.
Microbiol Spectr. 2024 Nov 7;12(12):e0188024. doi: 10.1128/spectrum.01880-24.
Highly pathogenic avian influenza viruses continue to pose global risks to One Health, including agriculture, public, and animal health. Rapid and accurate genomic surveillance is critical for monitoring viral mutations, tracing transmission, and guiding interventions in near real-time. Oxford Nanopore sequencing holds promise for real-time influenza genotyping, but data quality from R9 chemistry has limited its adoption due to challenges resolving low-complexity regions such as the biologically critical hemagglutinin cleavage site, a homopolymer of basic amino acids that distinguish highly pathogenic strains. In this study, human and avian influenza isolates ( = 45) from Cambodia were sequenced using both R9.4.1 and R10.4.1 flow cells and chemistries to evaluate performance between approaches. Overall, R10.4.1 yielded increased data output with higher average quality compared to R9.4.1, producing improved consensus sequences using a reference-based bioinformatics approach. R10.4.1 had significantly lower minor population insertion and deletion frequencies, driven by improved performance in low sequence complexity regions prone to insertion and deletion errors, such as homopolymers. Within the hemagglutinin cleavage site, R10.4.1 resolved the correct motif in 90% of genomes compared to only 60% with R9.4.1. Further examination showed reduced frameshift mutations in consensus sequences generated with R10.4.1 that could result in incorrectly classified virulence with automated pipelines. Improved consensus genome quality from nanopore sequencing approaches, especially across biologically important low-complexity regions, is critical to reduce subjective hand-curation and will improve local and global genomic surveillance responses.
This study demonstrates significant advancement in the field of influenza virus genomic surveillance by showcasing the superior accuracy and data quality of the Oxford Nanopore R10 sequencing chemistry compared to the older R9 chemistry. Improved resolution, including in the critical hemagglutinin multi-basic cleavage site, enables more reliable monitoring and tracking of viral mutations. This accelerates the ability to respond quickly to outbreaks, potentially improving impacts on public health, agriculture, and the economy by enabling more accurate and timely interventions.
高致病性禽流感病毒继续对“同一健康”构成全球风险,包括农业、公共卫生和动物健康。快速准确的基因组监测对于监测病毒突变、追踪传播以及近乎实时地指导干预措施至关重要。牛津纳米孔测序有望实现流感病毒实时基因分型,但由于在解析低复杂度区域(如生物学上至关重要的血凝素裂解位点,这是区分高致病性毒株的碱性氨基酸同聚物)时面临挑战,R9化学技术的数据质量限制了其应用。在本研究中,使用R9.4.1和R10.4.1流动槽及化学技术对来自柬埔寨的人类和禽流感分离株(n = 45)进行测序,以评估两种方法的性能。总体而言,与R9.4.1相比,R10.4.1的数据产量增加,平均质量更高,使用基于参考的生物信息学方法产生了改进的一致序列。R10.4.1的次要群体插入和缺失频率显著更低,这是由于在易发生插入和缺失错误的低序列复杂度区域(如同聚物)表现改善所致。在血凝素裂解位点内,R10.4.1在90%的基因组中解析出正确的基序,而R9.4.1仅为60%。进一步检查表明,R10.4.1生成的一致序列中的移码突变减少,而移码突变可能导致自动管道对毒力的错误分类。纳米孔测序方法提高的一致基因组质量,特别是在生物学上重要的低复杂度区域,对于减少主观人工编辑至关重要,并将改善本地和全球的基因组监测响应。
本研究通过展示牛津纳米孔R10测序化学技术相对于旧的R9化学技术的卓越准确性和数据质量,证明了流感病毒基因组监测领域的重大进展。分辨率的提高,包括在关键的血凝素多碱性裂解位点,使得对病毒突变的监测和追踪更加可靠。这加快了对疫情爆发的快速反应能力,通过实现更准确和及时的干预,可能改善对公共卫生、农业和经济的影响。