Whole genome analysis of influenza A(H3) viruses detected between 2016-2018 in the scope of EuroEVA/I-MOVE vaccine effectiveness study

Abstract

Abstract publicado em: https://www.escaide.eu/sites/escaide/files/documents/book_escaide2018_updated-dec-2018.pdfBackground: NGS techniques, allow a much deeper genetic analysis of influenza viruses, compared to traditional Sanger sequencing of hemagglutinin gene. The present study aims to perform phylogenetic and mutational analysis at whole-genome level in order to search for genetic features related to vaccine failure. Methods: Nasopharyngeal swabs were collected during 2016/17 and 2017/18 winter seasons, from ILI patients participating in EuroEVA/I-MOVE study. Whole genome sequences were obtained for 179 influenza A(H3) viruses by NGS in a MiSeq platform and subsequent bioinformatics analysis using the web-based platform INSaFLU (https://insaflu.insa.pt/). Additional fine-tune sequence analysis was performed using MEGA-7. Results: All sequenced viruses clustered in 2 HA-based genetic groups: 58 (32.4%) in 3C.2a group and 121 (67.6%) in 3C.2a1. Vaccine failure cases were detected in a higher proportion in 3C.2a1 group (20/121, 16.5%) than in 3C.2a (8/58, 13.8%). WGS analysis further revealed intra-subtype reassortments based on the closest genetic relatedness of each viral segment to the representative virus of seasonal A(H3) genetic (sub-)groups, with viruses being distributed in 6 different patterns of genome constellation. The group with all genomic segments most closely related to A/Singapore/INFIMH-16-0019/2016 harboured a higher number of vaccine failure cases (14/69, 20.3%). Despite 16 viruses (from 28 detected in vaccinated cases) presented amino acid substitutions not found in unvaccinated cases, these substitutions revealed a sporadic pattern. Conclusions: Vaccine failure cases were not exclusive of any genetic group or reassortment pattern, although they were found in slightly higher proportion among 3C.2a1 viruses and in viruses with all genetic segments mostly similar to A/Singapore/INFIMH-16-0019/2016. The further use of WGS in flu surveillance is essential to better understand genetic determinants of infection and evolutionary dynamics of influenza virus.info:eu-repo/semantics/draf

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