Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting

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Abstract

Background: Local transmission of seasonal influenza viruses (IVs) can be difficult to resolve. Here, we study if coupling high-throughput sequencing (HTS) of hemagglutinin (HA) and neuraminidase (NA) genes with variant analysis can resolve strains from local transmission that have identical consensus genome. We analyzed 24 samples collected over four days in January 2020 at a large university in the US. We amplified complete hemagglutinin (HA) and neuraminidase (NA) genomic segments followed by Illumina sequencing. We identified consensus complete HA and NA segments using BLASTn and performed variant analysis on strains whose HA and NA segments were 100% similar. Results: Twelve of the 24 samples were PCR positive, and we detected complete HA and/or NA segments by de novo assembly in 83.33% (10/12) of them. Similarity and phylogenetic analysis showed that 70% (7/10) of the strains were distinct while the remaining 30% had identical consensus sequences. These three samples also had IAV and IBV co-infection. However, subsequent variant analysis showed that they had distinct variant profiles. While the IAV HA of one sample had no variant, another had a T663C mutation and another had both C1379T and C1589A. Conclusion: In this study, we showed that HTS coupled with variant analysis of only HA and NA genes can help resolve variants that are closely related. We also provide evidence that during a short time period in the 2019–2020 season, co-infection of IAV and IBV occurred on the university campus and both 2020/2021 and 2021/2022 WHO recommended H1N1 vaccine strains were co-circulating.

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Faleye, T. O. C., Adams, D., Adhikari, S., Sandrolini, H., Halden, R. U., Varsani, A., & Scotch, M. (2021). Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting. BMC Infectious Diseases, 21(1). https://doi.org/10.1186/s12879-021-06526-5

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