Temporal and Gene Reassortment Analysis of Influenza C Virus Outbreaks in Hong Kong, SAR, China.

From 2014 to week 07/2020 the Centre for Health Protection in Hong Kong conducted screening for influenza C virus (ICV). A retrospective analysis of ICV detections to week 26/2019 revealed persistent low-level circulation with outbreaks occurring biennially in the winters of 2015 to 2016 and 2017 to 2018 (R. S. Daniels et al., J Virol 94:e01051-20, 2020, https://doi.org/10.1128/JVI.01051-20). Here, we report on an outbreak occurring in 2019 to 2020, reinforcing the observation of biennial seasonality in Hong Kong. All three outbreaks occurred in similar time frames, were subsequently dwarfed by seasonal epidemics of influenza types A and B, and were caused by similar proportions of C/Kanagawa/1/76 (K)-lineage and C/São Paulo/378/82 S1- and S2-sublineage viruses. Ongoing genetic drift was observed in all genes, with some evidence of amino acid substitution in the hemagglutinin-esterase-fusion (HEF) glycoprotein possibly associated with antigenic drift. A total of 61 ICV genomes covering the three outbreaks were analyzed for reassortment, and 9 different reassortant constellations were identified, 1 K-lineage, 4 S1-sublineage, and 4 S2-sublineage, with 6 of these being identified first in the 2019-1920 outbreak (2 S2-lineage and 4 S1-lineage). The roles that virus interference/enhancement, ICV persistent infection, genome evolution, and reassortment might play in the observed seasonality of ICV in Hong Kong are discussed. IMPORTANCE Influenza C virus (ICV) infection of humans is common, with the great majority of people being infected during childhood, though reinfection can occur throughout life. While infection normally results in "cold-like" symptoms, severe disease cases have been reported in recent years. However, knowledge of ICV is limited due to poor systematic surveillance and an inability to propagate the virus in large amounts in the laboratory. Following recent systematic surveillance in Hong Kong SAR, China, and direct ICV gene sequencing from clinical specimens, a 2-year cycle of disease outbreaks (epidemics) has been identified, with gene mixing playing a significant role in ICV evolution. Studies like those reported here are key to developing an understanding of the impact of influenza C virus infection in humans, notably where comorbidities exist and severe respiratory disease can develop.

Molecular Characterization of Influenza C Viruses from Outbreaks in Hong Kong SAR, China.

In 2014, the Centre for Health Protection in Hong Kong introduced screening for influenza C virus (ICV) as part of its routine surveillance for infectious agents in specimens collected from patients presenting with symptoms of respiratory viral infection, including influenza-like illness (ILI). A retrospective analysis of ICV detections up to week 26 of 2019 revealed persistent low-level circulation, with two outbreaks having occurred in the winters of 2015 to 2016 and 2017 to 2018. These outbreaks occurred at the same time as, and were dwarfed by, seasonal epidemics of influenza types A and B. Gene sequencing studies on stored ICV-positive clinical specimens from the two outbreaks have shown that the hemagglutinin-esterase (HE) genes of the viruses fall into two of the six recognized genetic lineages (represented by C/Kanagawa/1/76 and C/São Paulo/378/82), with there being significant genetic drift compared to earlier circulating viruses within both lineages. The location of a number of encoded amino acid substitutions in hemagglutinin-esterase fusion (HEF) glycoproteins suggests that antigenic drift may also have occurred. Observations of ICV outbreaks in other countries, with some of the infections being associated with severe disease, indicates that ICV infection has the potential to have significant clinical and health care impacts in humans.IMPORTANCE Influenza C virus infection of humans is common, and reinfection can occur throughout life. While symptoms are generally mild, severe disease cases have been reported, but knowledge of the virus is limited, as little systematic surveillance for influenza C virus is conducted and the virus cannot be studied by classical virologic methods because it cannot be readily isolated in laboratories. A combination of systematic surveillance in Hong Kong SAR, China, and new gene sequencing methods has been used in this study to assess influenza C virus evolution and provides evidence for a 2-year cycle of disease outbreaks. The results of studies like that reported here are key to developing an understanding of the impact of influenza C virus infection in humans and how virus evolution might be associated with epidemics.

Detection of Influenza C Virus Infection among Hospitalized Patients, Cameroon.

We report 3 cases of influenza C virus in children hospitalized with severe acute respiratory infection in Cameroon. Two of these case-patients had grave clinical manifestations, but all 3 recovered. The lack of specific antiviral drugs for influenza C virus highlights the need to identify and describe cases involving this virus.

Association of Increased Receptor-Binding Avidity of Influenza A(H9N2) Viruses with Escape from Antibody-Based Immunity and Enhanced Zoonotic Potential.

We characterized 55 influenza A(H9N2) viruses isolated in Pakistan during 2014-2016 and found that the hemagglutinin gene is of the G1 lineage and that internal genes have differentiated into a variety of novel genotypes. Some isolates had up to 4-fold reduction in hemagglutination inhibition titers compared with older viruses. Viruses with hemagglutinin A180T/V substitutions conveyed this antigenic diversity and also caused up to 3,500-fold greater binding to avian-like and >20-fold greater binding to human-like sialic acid receptor analogs. This enhanced binding avidity led to reduced virus replication in primary and continuous cell culture. We confirmed that altered receptor-binding avidity of H9N2 viruses, including enhanced binding to human-like receptors, results in antigenic variation in avian influenza viruses. Consequently, current vaccine formulations might not induce adequate protective immunity in poultry, and emergence of isolates with marked avidity for human-like receptors increases the zoonotic risk.

Three different cone opsin gene array mutational mechanisms with genotype-phenotype correlation and functional investigation of cone opsin variants.

Mutations in the OPN1LW (L-) and OPN1MW (M-)cone opsin genes underlie a spectrum of cone photoreceptor defects from stationary loss of color vision to progressive retinal degeneration. Genotypes of 22 families with a range of cone disorders were grouped into three classes: deletions of the locus control region (LCR); missense mutation (p.Cys203Arg) in an L-/M-hybrid gene; and exon 3 single-nucleotide polymorphism (SNP) interchange haplotypes in an otherwise normal gene array. Moderate-to-high myopia was observed in all mutation categories. Individuals with LCR deletions or p.Cys203Arg mutations were more likely to have nystagmus and poor vision, with disease progression in some p.Cys203Arg patients. Three disease-associated exon 3 SNP haplotypes encoding LIAVA, LVAVA, or MIAVA were identified in our cohort. These patients were less likely to have nystagmus but more likely to show progression, with all patients over the age of 40 years having marked macular abnormalities. Previously, the haplotype LIAVA has been shown to result in exon 3 skipping. Here, we show that haplotypes LVAVA and MIAVA also result in aberrant splicing, with a residual low level of correctly spliced cone opsin. The OPN1LW/OPN1MW:c.532A>G SNP, common to all three disease-associated haplotypes, appears to be principally responsible for this mutational mechanism.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Seasonal influenza (flu) viruses cause outbreaks every winter. People infected with influenza typically develop mild respiratory symptoms. But flu infections can cause serious illness in young children, older adults and people with chronic medical conditions. Infected or vaccinated individuals develop some immunity, but the viruses evolve quickly to evade these defenses in a process called antigenic drift. As the viruses change, they can re-infect previously immune people. Scientists update the flu vaccine yearly to keep up with this antigenic drift. The immune system fights flu infections by recognizing two proteins, known as antigens, on the virus's surface, called hemagglutinin (HA) and neuraminidase (NA). However, mutations in the genes encoding these proteins can make them unrecognizable, letting the virus slip past the immune system. Scientists would like to know how these changes affect the size, severity and timing of annual influenza outbreaks. Perofsky et al. show that tracking genetic changes in HA and NA may help improve flu season predictions. The experiments compared the severity of 22 flu seasons caused by the A(H3N2) subtype in the United States with how much HA and NA had evolved since the previous year. The A(H3N2) subtype experiences the fastest rates of antigenic drift and causes more cases and deaths than other seasonal flu viruses. Genetic changes in HA and NA were a better predictor of A(H3N2) outbreak severity than the blood tests for protective antibodies that epidemiologists traditionally use to track flu evolution. However, the prevalence of another subtype of influenza A circulating in the population, called A(H1N1), was an even better predictor of how severe A(H3N2) outbreaks would be. Perofsky et al. are the first to show that genetic changes in NA contribute to the severity of flu seasons. Previous studies suggested a link between genetic changes in HA and flu season severity, and flu vaccines include the HA protein to help the body recognize new influenza strains. The results suggest that adding the NA protein to flu vaccines may improve their effectiveness. In the future, flu forecasters may want to analyze genetic changes in both NA and HA to make their outbreak predictions. Tracking how much of the A(H1N1) subtype is circulating may also be useful for predicting the severity of A(H3N2) outbreaks.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.

A Sanger sequencing protocol for SARS-CoV-2 S-gene.

We describe a Sanger sequencing protocol for SARS-CoV-2 S-gene the Spike (S)-glycoprotein product of which, composed of receptor-binding (S1) and membrane fusion (S2) segments, is the target of vaccines used to combat COVID-19. The protocol can be used in laboratories with basic Sanger sequencing capabilities and allows rapid "at source" screening for SARS-CoV-2 variants, notably those of concern. The protocol has been applied for surveillance, with clinical specimens collected in either nucleic acid preservation lysis-mix or virus transport medium, and research involving cultured viruses, and can yield data of public health importance in a timely manner.

Genetic diversity of influenza A viruses circulating in Bulgaria during the 2018-2019 winter season.

Introduction. Influenza viruses evolve rapidly and change their antigenic characteristics, necessitating biannual updates of flu vaccines.Aim. The aim of this study was to characterize influenza viruses circulating in Bulgaria during the 2018/2019 season and to identify amino acid substitutions in them that might impact vaccine effectiveness.Methodology. Typing/subtyping of influenza viruses were performed using real-time Reverse Transcription-PCR (RT-PCR) and results of phylogenetic and amino acid sequence analyses of influenza strains are presented.Results. A(H1N1)pdm09 (66 %) predominated over A(H3N2) (34 %) viruses, with undetected circulation of B viruses in the 2018/2019 season. All A(H1N1)pdm09 viruses studied fell into the recently designated 6B.1A subclade with over 50 % falling in four subgroups: 6B.1A2, 6B.1A5, 6B.1A6 and 6B.1A7. Analysed A(H3N2) viruses belonged to subclades 3C.2a1b and 3C.2a2. Amino acid sequence analysis of 36 A(H1N1)pdm09 isolates revealed the presence of six-ten substitutions in haemagglutinin (HA), compared to the A/Michigan/45/2015 vaccine virus, three of which occurred in antigenic sites Sa and Cb, together with four-nine changes at positions in neuraminidase (NA), and a number of substitutions in internal proteins. HA1 D222N substitution, associated with increased virulence, was identified in two A(H1N1)pdm09 viruses. Despite the presence of several amino acid substitutions, A(H1N1)pdm09 viruses remained antigenically similar to the vaccine virus. The 28 A(H3N2) viruses characterized carried substitutions in HA, including some in antigenic sites A, B, C and E, in NA and internal protein sequences.Conclusion. The results of this study showed the genetic diversity of circulating influenza viruses and the need for continuous antigenic and molecular surveillance.

Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution.

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.

Vaccination is the best protection against seasonal flu. It teaches the immune system what the flu virus looks like, preparing it to fight off an infection. But the flu virus changes its molecular appearance every year, escaping the immune defences learnt the year before. So, every year, the vaccine needs updating. Since it takes almost a year to design and make a new flu vaccine, researchers need to be able to predict what flu viruses will look like in the future. Currently, this prediction relies on experiments that assess the molecular appearance of flu viruses, a complex and slow approach. One alternative is to examine the virus's genetic code. Mathematical models try to predict which genetic changes might alter the appearance of a flu virus, saving the cost of performing specialised experiments. Recent research has shown that these models can make good predictions, but including experimental measures of the virus' appearance could improve them even further. This could help the model to work out which genetic changes are likely to be beneficial to the virus, and which are not. To find out whether experimental data improves model predictions, Huddleston et al. designed a new forecasting tool which used 25 years of historical data from past flu seasons. Each forecast predicted what the virus population might look like the next year using the previous year's genetic code, experimental data, or both. Huddleston et al. then compared the predictions with the historical data to find the most useful data types. This showed that the best predictions combined changes from the virus's genetic code with experimental measures of its appearance. This new forecasting tool is open source, allowing teams across the world to start using it to improve their predictions straight away. Seasonal flu infects between 5 and 15% of the world's population every year, causing between quarter of a million and half a million deaths. Better predictions could lead to better flu vaccines and fewer illnesses and deaths.

Overview of three influenza seasons in Georgia, 2014-2017.

BACKGROUND: Influenza epidemiological and virologic data from Georgia are limited. We aimed to present Influenza Like Illness (ILI) and Severe Acute Respiratory Infection (SARI) surveillance data and characterize influenza viruses circulating in the country over three influenza seasons. METHODS: We analyzed sentinel site ILI and SARI data for the 2014-2017 seasons in Georgia. Patients' samples were screened by real-time RT-PCR and influenza viruses isolated were characterized antigenically by haemagglutination inhibition assay and genetically by sequencing of HA and NA genes. RESULTS: 32% (397/1248) of ILI and 29% (581/1997) of SARI patients tested were positive for influenza viruses. In 2014-2015 the median week of influenza detection was week 7/2015 with B/Yamagata lineage viruses dominating (79%); in 2015-2016-week 5/2016 was the median with A/H1N1pdm09 viruses prevailing (83%); and in 2016-2017 a bimodal distribution of influenza activity was observed-the first wave was caused by A/H3N2 (55%) with median week 51/2016 and the second by B/Victoria lineage viruses (45%) with median week 9/2017. For ILI, influenza virus detection was highest in children aged 5-14 years while for SARI patients most were aged >15 years and 27 (4.6%) of 581 SARI cases died during the three seasons. Persons aged 30-64 years had the highest risk of fatal outcome, notably those infected with A/H1N1pdm09 (OR 11.41, CI 3.94-33.04, p<0.001). A/H1N1pdm09 viruses analyzed by gene sequencing fell into genetic groups 6B and 6B.1; A/H3N2 viruses belonged to genetic subclades 3C.3b, 3C.3a, 3C.2a and 3C.2a1; B/Yamagata lineage viruses were of clade 3 and B/Victoria lineage viruses fell in clade1A. CONCLUSION: In Georgia influenza virus activity occurred mainly from December through March in all seasons, with varying peak weeks and predominating viruses. Around one third of ILI/ SARI cases were associated with influenza caused by antigenically and genetically distinct influenza viruses over the course of the three seasons.

The characteristics and antigenic properties of recently emerged subclade 3C.3a and 3C.2a human influenza A(H3N2) viruses passaged in MDCK cells.

BACKGROUND: Two new subclades of influenza A(H3N2) viruses became prominent during the 2014-2015 Northern Hemisphere influenza season. The HA glycoproteins of these viruses showed sequence changes previously associated with alterations in receptor-binding properties. To address how these changes influence virus propagation, viruses were isolated and propagated in conventional MDCK cells and MDCK-SIAT1 cells, cells with enhanced expression of the human receptor for the virus, and analysed at each passage. METHODS: Gene sequence analysis was undertaken as virus was passaged in conventional MDCK cells and MDCK-SIAT1 cells. Alterations in receptor recognition associated with passage of virus were examined by haemagglutination assays using red blood cells from guinea pigs, turkeys and humans. Microneutralisation assays were performed to determine how passage-acquired amino acid substitutions and polymorphisms affected virus antigenicity. RESULTS: Viruses were able to infect MDCK-SIAT1 cells more efficiently than conventional MDCK cells. Viruses of both the 3C.2a and 3C.3a subclades showed greater sequence change on passage in conventional MDCK cells than in MDCK-SIAT1 cells, with amino acid substitutions being seen in both HA and NA glycoproteins. However, virus passage in MDCK-SIAT1 cells at low inoculum dilutions showed reducing infectivity on continued passage. CONCLUSIONS: Current H3N2 viruses should be cultured in the MDCK-SIAT1 cell line to maintain faithful replication of the virus, and at an appropriate multiplicity of infection to retain infectivity.

Global update on the susceptibility of human influenza viruses to neuraminidase inhibitors, 2014-2015.

The World Health Organization (WHO) Collaborating Centres for Reference and Research on Influenza (WHO CCs) tested 13,312 viruses collected by WHO recognized National Influenza Centres between May 2014 and May 2015 to determine 50% inhibitory concentration (IC50) data for neuraminidase inhibitors (NAIs) oseltamivir, zanamivir, peramivir and laninamivir. Ninety-four per cent of the viruses tested by the WHO CCs were from three WHO regions: Western Pacific, the Americas and Europe. Approximately 0.5% (n = 68) of viruses showed either highly reduced inhibition (HRI) or reduced inhibition (RI) (n = 56) against at least one of the four NAIs. Of the twelve viruses with HRI, six were A(H1N1)pdm09 viruses, three were A(H3N2) viruses and three were B/Yamagata-lineage viruses. The overall frequency of viruses with RI or HRI by the NAIs was lower than that observed in 2013-14 (1.9%), but similar to the 2012-13 period (0.6%). Based on the current analysis, the NAIs remain an appropriate choice for the treatment and prophylaxis of influenza virus infections.