Identification of Rare PB2-D701N Mutation from a Patient with Severe Influenza: Contribution of the PB2-D701N Mutation to the Pathogenicity of Human Influenza

Genome characterization of influenza A and B viruses in New South Wales, Australia, in 2019: A retrospective study using high-throughput whole genome sequencing

BACKGROUND

During the 2019 severe influenza season, New South Wales (NSW) experienced the highest number of cases in Australia. This study retrospectively investigated the genetic characteristics of influenza viruses circulating in NSW in 2019 and identified genetic markers related to antiviral resistance and potential virulence.

METHODS

The complete genomes of influenza A and B viruses were amplified using reverse transcription-polymerase chain reaction (PCR) and sequenced with an Illumina MiSeq platform.

RESULTS

When comparing the sequencing data with the vaccine strains and reference sequences, the phylogenetic analysis revealed that most NSW A/H3N2 viruses (n = 68; 94%) belonged to 3C.2a1b and a minority (n = 4; 6%) belonged to 3C.3a. These viruses all diverged from the vaccine strain A/Switzerland/8060/2017. All A/H1N1pdm09 viruses (n = 20) showed genetic dissimilarity from vaccine strain A/Michigan/45/2015, with subclades 6B.1A.5 and 6B.1A.2 identified. All B/Victoria-lineage viruses (n = 21) aligned with clade V1A.3, presenting triple amino acid deletions at positions 162-164 in the hemagglutinin protein, significantly diverging from the vaccine strain B/Colorado/06/2017. Multiple amino acid substitutions were also found in the internal proteins of influenza viruses, some of which have been previously reported in hospitalized influenza patients in Thailand. Notably, the oseltamivir-resistant marker H275Y was present in one immunocompromised patient infected with A/H1N1pdm09 and the resistance-related mutation I222V was detected in another A/H3N2-infected patient.

CONCLUSIONS

Considering antigenic drift and the constant evolution of circulating A and B strains, we believe continuous monitoring of influenza viruses in NSW via the high-throughput sequencing approach provides timely and pivotal information for both public health surveillance and clinical treatment.

Cell-intrinsic genomic reassortment of pandemic H1N1 2009 and Eurasian avian-like swine influenza viruses results in potentially zoonotic variants

Influenza A viruses (IAV) cause annual epidemics and occasional pandemics in humans. The most recent pandemic outbreak occurred in 2009 with H1N1pdm09. This virus, which most likely reassorted in swine before its transmission to humans, was reintroduced into the swine population and continues circulating ever since. In order to assess its potential to cause reassortants on a cellular level, human origin H1N1pdm09 and a recent Eurasian avian-like H1N1 swine IAV were (co-)passaged in the newly generated swine lung cell line C22. Co-infection with both viruses gave rise to numerous reassortants that additionally carry different mutations which can partially be found in nature as well. Reassortment most frequently affected the PB1, PA and NA segments with the swine IAV as recipient. These reassortants reached higher titers in swine lung cells and were able to replicate in genuine human lung tissue explants ex vivo, suggesting a possible zoonotic potential. Interestingly, reassortment and mutations in the viral ribonucleoprotein complex influence the viral polymerase activity in a cell type and species-specific manner. In summary, we demonstrate reassortment promiscuity of these viruses in a novel swine lung cell model and indicate a possible zoonotic potential of the reassortants.

Detection of respiratory viruses directly from clinical samples using next-generation sequencing: A literature review of recent advances and potential for routine clinical use

Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. The advent of next‐generation sequencing (NGS) has revolutionised the field of virus discovery and identification, particularly in the detection of unknown respiratory viruses. We systematically reviewed the application of NGS technologies for detecting respiratory viruses from clinical samples and outline potential barriers to the routine clinical introduction of NGS. The five databases searched for studies published in English from 01 January 2010 to 01 February 2021, which led to the inclusion of 52 studies. A total of 14 different models of NGS platforms were summarised from included studies. Among these models, second‐generation sequencing platforms (e.g., Illumina sequencers) were used in the majority of studies (41/52, 79%). Moreover, NGS platforms have proven successful in detecting a variety of respiratory viruses, including influenza A/B viruses (9/52, 17%), SARS‐CoV‐2 (21/52, 40%), parainfluenza virus (3/52, 6%), respiratory syncytial virus (1/52, 2%), human metapneumovirus (2/52, 4%), or a viral panel including other respiratory viruses (16/52, 31%). The review of NGS technologies used in previous studies indicates the advantages of NGS technologies in novel virus detection, virus typing, mutation identification, and infection cluster assessment. Although there remain some technical and ethical challenges associated with NGS use in clinical laboratories, NGS is a promising future tool to improve understanding of respiratory viruses and provide a more accurate diagnosis with simultaneous virus characterisation.

Evaluation of the added value of viral genomic information for predicting severity of influenza infection

BACKGROUND

The severity of an influenza infection is influenced by both host and viral characteristics. This study aims to assess the relevance of viral genomic data for the prediction of severe influenza A(H3N2) infections among patients hospitalized for severe acute respiratory infection (SARI), in view of risk assessment and patient management.

METHODS

160 A(H3N2) influenza positive samples from the 2016-2017 season originating from the Belgian SARI surveillance were selected for whole genome sequencing. Predictor variables for severity were selected using a penalized elastic net logistic regression model from a combined host and genomic dataset, including patient information and nucleotide mutations identified in the viral genome. The goodness-of-fit of the model combining host and genomic data was compared using a likelihood-ratio test with the model including host data only. Internal validation of model discrimination was conducted by calculating the optimism-adjusted area under the Receiver Operating Characteristic curve (AUC) for both models.

RESULTS

The model including viral mutations in addition to the host characteristics had an improved fit ([Formula: see text]=12.03, df = 3, p = 0.007). The optimism-adjusted AUC increased from 0.671 to 0.732.

CONCLUSIONS

Adding genomic data (selected season-specific mutations in the viral genome) to the model containing host characteristics improved the prediction of severe influenza infection among hospitalized SARI patients, thereby offering the potential for translation into a prospective strategy to perform early season risk assessment or to guide individual patient management.

Genetic and Molecular Characterization of H9N2 Avian Influenza Viruses Isolated from Live Poultry Markets in Hubei Province, Central China, 2013-2017

H9N2 subtype avian influenza virus (AIV) is an influenza A virus that is widely spread throughout Asia, where it jeopardizes the poultry industry and provides genetic material for emerging human pathogens. To better understand the epidemicity and genetics of H9 subtype AIVs, we conducted active surveillance in live poultry markets (LPMs) in Hubei Province from 2013 to 2017. A total of 4798 samples were collected from apparent healthy poultry and environment. Real-time RT-PCR revealed that the positivity rate of influenza A was 26.6% (1275/4798), of which the H9 subtype accounted for 50.3% (641/1275) of the positive samples. Of the 132 H9N2 viral strains isolated, 48 representative strains were subjected to evolutionary analysis and genotyping. Phylogenetic analysis revealed that all H9N2 viral genes had 91.1%-100% nucleotide homology, clustered with genotype 57, and had high homology with human H9N2 viruses isolated from 2013 to 2017 in China. Using a nucleotide divergence cutoff of 95%, we identified ten distinct H9N2 genotypes that continued to change over time. Molecular analysis demonstrated that six H9N2 isolates had additional potential glycosylation sites at position 218 in the hemagglutinin protein, and all isolates had I155T and Q226L mutations. Moreover, 44 strains had A558V mutations in the PB2 protein and four had E627V mutations, along with H9N2 human infection strains A/Beijing/1/2016 and A/Beijing/1/2017. These results emphasize that the H9N2 influenza virus in Hubei continues to mutate and undergo mammalian adaptation changes, indicating the necessity of strengthening the surveillance of the AIV H9N2 subtype in LPMs.

Pathway mapping of leukocyte transcriptome in influenza patients reveals distinct pathogenic mechanisms associated with progression to severe infection

Background

Influenza infections produce a spectrum of disease severity, ranging from a mild respiratory illness to respiratory failure and death. The host-response pathways associated with the progression to severe influenza disease are not well understood.

Methods

To gain insight into the disease mechanisms associated with progression to severe infection, we analyzed the leukocyte transcriptome in severe and moderate influenza patients and healthy control subjects. Pathway analysis on differentially expressed genes was performed using a topology-based pathway analysis tool that takes into account the interaction between multiple cellular pathways. The pathway profiles between moderate and severe influenza were then compared to delineate the biological mechanisms underpinning the progression from moderate to severe influenza.

Results

107 patients (44 severe and 63 moderate influenza patients) and 52 healthy control subjects were included in the study. Severe influenza was associated with upregulation in several neutrophil-related pathways, including pathways involved in neutrophil differentiation, migration, degranulation and neutrophil extracellular trap (NET) formation. The degree of upregulation in neutrophil-related pathways were significantly higher in severely infected patients compared to moderately infected patients. Severe influenza was also associated with downregulation in immune response pathways, including pathways involved in antigen presentation such as CD4+ T-cell co-stimulation, CD8+ T cell and Natural Killer (NK) cells effector functions. Apoptosis pathways were also downregulated in severe influenza patients compare to moderate and healthy controls.

Conclusions

These findings showed that there are changes in gene expression profile that may highlight distinct pathogenic mechanisms associated with progression from moderate to severe influenza infection.