Nanopore sequencing of influenza A and B in Oxfordshire and the United Kingdom, 2022-23

Abstract

Objectives: We evaluated Nanopore sequencing for influenza surveillance.

Methods: Influenza A and B PCR-positive samples from hospital patients in Oxfordshire, UK, and a UK-wide population survey from winter 2022-23 underwent Nanopore sequencing following targeted rt-PCR amplification.

Results: From 941 infections, successful sequencing was achieved in 292/388 (75 %) available Oxfordshire samples: 231 (79 %) A/H3N2, 53 (18 %) A/H1N1, and 8 (3 %) B/Victoria and in 53/113 (47 %) UK-wide samples. Sequencing was more successful at lower Ct values. Most same-sample replicate sequences had identical haemagglutinin segments (124/141, 88 %); 36/39 (92 %) Illumina vs. Nanopore comparisons were identical, and 3 (8 %) differed by 1 variant. Comparison of Oxfordshire and UK-wide sequences showed frequent inter-regional transmission. Infections were closely-related to 2022-23 vaccine strains. Only one sample had a neuraminidase inhibitor resistance mutation. 849/941 (90 %) Oxfordshire infections were community-acquired. 63/88 (72 %) potentially healthcare-associated cases shared a hospital ward with ≥ 1 known infectious case. 33 epidemiologically-plausible transmission links had sequencing data for both source and recipient: 8 were within ≤ 5 SNPs, of these, 5 (63 %) involved potential sources that were also hospital-acquired.

Conclusions: Nanopore influenza sequencing was reproducible and antiviral resistance rare. Inter-regional transmission was common; most infections were genomically similar. Hospital-acquired infections are likely an important source of nosocomial transmission and should be prioritised for infection prevention and control.

Keywords: Epidemiology; Influenza; Respiratory virus; Sequencing.

Fig. 1

Relationship between sequencing success and Ct values and cDNA concentrations. 541 attempted sequences had an associated Ct value and 547 an associated cDNA concentration recorded (sequencing was attempted more than once for some samples). Error bars show 95 % exact binomial confidence intervals.

Fig. 2

Distribution of single nucleotide polymorphism (SNPs) between replicate and different sample pairs. Panels A (n = 141) and C (n = 32,992) show differences for the HA segment and B (n = 124) and D (n = 29,147) for whole genomes based on all 8 segments (see Fig. S5 for sensitivity analysis using only six segments that removes several high SNP replicates; segments S2 and S3 had a greater tendency to cross mapping between flu types).

Fig. 3

Depth of coverage by influenza genome segment. Mean depth was calculated for each segment for each sample in which the HA segment was successfully sequenced, i.e., the sequences used in phylogenetic analyses. The median of the mean depth values for each influenza type and segment is shown. Error bars show interquartile ranges, IQRs.

Fig. 4

Maximum likelihood phylogeny of HA segment sequences for influenza A H3N2 (panel A), H1N1 (panel B), and influenza B/Victoria (panel C). Sequences are coloured according to source dataset, 2022–23 northern hemisphere vaccine strains are shown for context, with one strain used as an outgroup to root the tree. (See Fig. S6 for sensitivity analysis excluding segments S2 and S3 which had a greater tendency for cross mapping between influenza types.).

Fig. 5

Plausible sources for 88 potential healthcare-associated influenza infections throughout the study period, based on ward overlap during defined infectious and incubation periods. Infections acquired after > 72 h as a hospital inpatient are shown as filled circles, community-associated cases are shown as squares. Nodes are coloured by influenza subtype as determined from sequencing: A/H3N2 in blue, A/H1N1 in orange, B/Victoria in green, unknown (not sequenced or not sequenced successfully) in grey. Possible transmission events, shown as edges, are drawn where potentially healthcare-associated cases were present while at risk on the same hospital ward as an infectious case of the same influenza type (as defined by the initial diagnostic PCR, i.e. A or B). The edges are coloured according to the ward on which contact occurred. The yellow edges and blue edges represent acute medical admissions units at two hospitals and the teal edges those occurring on an acute medical ambulatory assessment unit. Orange, red, pale green, and lime green clusters occurred on acute medical / geratology wards. The turquoise cluster represents a paediatric ward, the pink cluster maternity wards, and the brown cluster a haematology ward. Thick solid edges are where transmission is supported by sequencing, i.e., ≤ 5 SNPs between cases, dotted lines indicate where sequencing makes transmission less likely either due to > 5 SNPs (all actually ≥15 SNPs) or different influenza subtypes.

Fig. 6

Epidemiology of Oxfordshire influenza. Panel A shows hospital diagnosed infections (n = 941), classified by community onset (diagnosis ≤72 h of hospital admission) vs. potentially healthcare-associated (>72 h). Panel B shows the proportion of cases that were potentially healthcare-associated, error bars indicate 95 % binomial confidence intervals, and the numbers beneath each point the number of potentially healthcare-acquired cases per week. Panel C shows successfully sequenced infections with an HA segment called (n = 269), each case > 5 HA segment SNPs different all previous cases is shown on a new horizontal line.