Haemagglutinin and neuraminidase sequencing delineate nosocomial influenza outbreaks with accuracy equivalent to whole genome sequencing

A Cold Case of Equine Influenza Disentangled with Nanopore Sequencing

Massive sequencing techniques have allowed us to develop straightforward approaches for the whole genome sequencing of viruses, including influenza viruses, generating information that is useful for improving the levels and dimensions of data analysis, even for archival samples. Using the Nanopore platform, we determined the whole genome sequence of an H3N8 equine influenza virus, identified from a 2005 outbreak in Apulia, Italy, whose origin had remained epidemiologically unexplained. The virus was tightly related (>99% at the nucleotide level) in all the genome segments to viruses identified in Poland in 2005–2008 and it was seemingly introduced locally with horse trading for the meat industry. In the phylogenetic analysis based on the eight genome segments, strain ITA/2005/horse/Bari was found to cluster with sub-lineage Florida 2 in the HA and M genes, whilst in the other genes it clustered with strains of the Eurasian lineage, revealing a multi-reassortant nature.

Whole-genome Sequencing Provides Data for Stratifying Infection Prevention and Control Management of Nosocomial Influenza A

Background

Influenza A virus causes annual epidemics in humans and is associated with significant morbidity and mortality. Haemagglutinin (HA) and neuraminidase (NA) gene sequencing have traditionally been used to identify the virus genotype, although their utility in detecting outbreak clusters is still unclear. The objective of this study was to determine the utility, if any, of whole-genome sequencing over HA/NA sequencing for infection prevention and control (IPC) in hospitals.

Methods

We obtained all clinical samples from influenza (H1N1)-positive patients at the Great Ormond Street Hospital between January and March 2016. Samples were sequenced using targeted enrichment on an Illumina MiSeq sequencer. Maximum likelihood trees were computed for both whole genomes and concatenated HA/NA sequences. Epidemiological data was taken from routine IPC team activity during the period.

Results

Complete genomes were obtained for 65/80 samples from 38 patients. Conventional IPC analysis recognized 1 outbreak, involving 3 children, and identified another potential cluster in the haemato-oncology ward. Whole-genome and HA/NA phylogeny both accurately identified the previously known outbreak cluster. However, HA/NA sequencing additionally identified unrelated strains as part of this outbreak cluster. A whole-genome analysis identified a further cluster of 2 infections that had been previously missed and refuted suspicions of transmission in the haemato-oncology wards.

Conclusions

Whole-genome sequencing is better at identifying outbreak clusters in a hospital setting than HA/NA sequencing. Whole-genome sequencing could provide a faster and more reliable method for outbreak monitoring and supplement routine IPC team work to allow the prevention of transmission.

Nosocomial transmission of influenza: A retrospective cross-sectional study using next generation sequencing at a hospital in England (2012-2014)

BACKGROUND

The extent of transmission of influenza in hospital settings is poorly understood. Next generation sequencing may improve this by providing information on the genetic relatedness of viral strains.

OBJECTIVES

We aimed to apply next generation sequencing to describe transmission in hospital and compare with methods based on routinely-collected data.

METHODS

All influenza samples taken through routine care from patients at University College London Hospitals NHS Foundation Trust (September 2012 to March 2014) were included. We conducted Illumina sequencing and identified genetic clusters. We compared nosocomial transmission estimates defined using classical methods (based on time from admission to sample) and genetic clustering. We identified pairs of cases with space-time links and assessed genetic relatedness.

RESULTS

We sequenced influenza sampled from 214 patients. There were 180 unique genetic strains, 16 (8.8%) of which seeded a new transmission chain. Nosocomial transmission was indicated for 32 (15.0%) cases using the classical definition and 34 (15.8%) based on genetic clustering. Of the 50 patients in a genetic cluster, 11 (22.0%) had known space-time links with other cases in the same cluster. Genetic distances between pairs of cases with space-time links were lower than for pairs without spatial links (P < .001).

CONCLUSIONS

Genetic data confirmed that nosocomial transmission contributes significantly to the hospital burden of influenza and elucidated transmission chains. Prospective next generation sequencing could support outbreak investigations and monitor the impact of infection and control measures.

Identification of influenza urban transmission patterns by geographical, epidemiological and whole genome sequencing data: protocol for an observational study

INTRODUCTION

Urban transmission patterns of influenza viruses are complex and poorly understood, and multiple factors may play a critical role in modifying transmission. Whole genome sequencing (WGS) allows the description of patient-to-patient transmissions at highest resolution. The aim of this study is to explore urban transmission patterns of influenza viruses in high detail by combining geographical, epidemiological and immunological data with WGS data.

METHODS AND ANALYSIS

The study is performed at the University Hospital Basel, University Children's Hospital Basel and a network of paediatricians and family doctors in the Canton of Basel-City, Switzerland. The retrospective study part includes an analysis of PCR-confirmed influenza cases from 2013 to 2018. The prospective study parts include (1) a household survey regarding influenza-like illness (ILI) and vaccination against influenza during the 2015/2016 season; (2) an analysis of influenza viruses collected during the 2016/2017 season using WGS-viral genomic sequences are compared with determine genetic relatedness and transmissions; and (3) measurement of influenza-specific antibody titres against all vaccinated and circulated strains during the 2016/2017 season from healthy individuals, allowing to monitor herd immunity across urban quarters. Survey data and PCR-confirmed cases are linked to data from the Statistics Office of the Canton Basel-City and visualised using geo-information system mapping. WGS data will be analysed in the context of patient epidemiological data using phylodynamic analyses, and the obtained herd immunity for each quarter. Profound knowledge on the key geographical, epidemiological and immunological factors influencing urban influenza transmission will help to develop effective counter measurements.

ETHICS AND DISSEMINATION

The study is registered and approved by the regional ethics committee as an observational study (EKNZ project ID 2015-363 and 2016-01735). It is planned to present the results at conferences and publish the data in scientific journals.

TRIAL REGISTRATION NUMBER

NCT03010007.

Evaluation of two workflows for whole genome sequencing-based typing of influenza A viruses

We compared two sample preparation protocols for whole genome sequencing of influenza A viruses. Each protocol was assessed using cDNA quantity and quality and the resulting mean genome coverage after sequencing. Both protocols produced acceptable result for samples with high viral load, whereas one protocol performed slightly better with limited virus count.

Use of Genome Sequencing to Define Institutional Influenza Outbreaks, Toronto, Ontario, Canada, 2014-15

Adequacy of the current clinical definition of institutional influenza outbreaks is unclear. We performed a retrospective genome sequencing and epidemiologic analysis of institutional influenza outbreaks that occurred during the 2014-15 influenza season in Toronto, Canada. We sequenced the 2 earliest submitted samples positive for influenza A(H3N2) from each of 38 reported institutional outbreaks in long-term care facilities. Genome sequencing showed most outbreak pairs identified by using the current clinical definition were highly related. Inclusion of surveillance samples demonstrated that outbreak sources were likely introductions from broader circulating lineages. Pairwise distance analysis using majority genome and hemagglutinin-specific genes enabled identification of thresholds for discrimination of within and between outbreak pairs; the area under the curve ranged 0.93-0.95. Routine genome sequencing for defining influenza outbreaks in long-term care facilities is unlikely to add significantly to the current clinical definition. Sequencing may prove most useful for investigating sources of outbreak introductions.