John William McCauley

Influenza A virus (IAV) zoonotic transmission and continuous evolution in multiple host species heighten the risk of emerging novel strains at the human-animal interface. Digitally immune-optimized hemagglutinin (HA), neuraminidase (NA), and matrix-2 (M2) vaccine antigens were engineered and combined as a single DNA expression construct (DVX-H1N1) to maximize immune responses to human seasonal, pandemic, and zoonotic H1N1 IAVs. Immunization of mice with DVX antigens induced broad neutralizing antibody responses to human- and swine-origin H1N1 isolates. The DVX-H1N1 candidate was then evaluated in the well-recognized swine challenge model for human influenza in comparison to two benchmark controls representing conventional whole inactivated virus (WIV) vaccines that were either homologous or heterologous to the H1N1 pandemic 2009 subclade 1A.3.3.2 challenge strain, A/swine/England/1353/2009 (H1N1). Serology demonstrated that DVX-H1N1 immunization induced immune responses across a broad spectrum of human and swine H1N1 strains representing antigenic drift and reassortment. Following intranasal virus challenge, nasal shedding of viral RNA was significantly suppressed in the DVX-H1N1 and the homologous control WIV vaccinated groups in comparison to naive controls and the heterologous WIV vaccinated groups. These findings demonstrate that in both swine and mouse models, the DVX-H1N1 vaccine induced broad immune responses and, in pigs, controlled viral infection comparable to conventional strain-matched, but unlike mismatched WIV vaccines. IMPORTANCE: Influenza A virus (IAV) transmission across the animal-human interface is a recognized global health threat. Swine are a key animal reservoir enabling the emergence of novel strains with pandemic potential, posing a threat for animal health and zoonotic spillover to humans. Vaccination remains the most effective intervention against influenza, with current strategies relying on human seasonal strain selection guided by biannual World Health Organization (WHO) recommendations. This approach is challenging owing to viral antigenic drift, reassortment in animal reservoirs, and imperfect antigenic matching between vaccine strains and circulating viruses. These factors reduce vaccine effectiveness and increase threats posed by emerging novel strains, emphasizing the need for next-generation influenza vaccines that improve vaccine-mediated protection and longevity of immunity against an evolving virus. We describe a proof-of-concept digitally immune-optimized antigen vaccine platform with broad immunogenicity and robust efficacy in the swine model, a translational system with the potential to mitigate influenza threats at the human-animal interface.

Background: Surveillance of influenza infections and virus characterisation are essential to guide prevention strategies. In the Central African Republic (CAR), data on influenza viruses are patchy and poorly documented. Objective: To study the clinical, seasonal, genetic and phenotypic characteristics of influenza viruses circulating in the CAR population. Materials and Methods: From January 2015 to December 2018, the presence of influenza A and B viruses in patients presenting with influenza‐like illness (ILI) symptoms or severe acute respiratory infections (SARI) was investigated by RT‐qPCR. Influenza genetic diversity was evaluated by phylogenetic analyses, and antigenic properties were investigated by haemagglutination inhibition assays, whereas reduced susceptibility to neuraminidase inhibitors was assessed through the presence of known genetic markers and neuraminidase assay. The relationship between patients' clinical characteristics and infection status was investigated using statistical analyses. Results: Over the surveillance period influenza viruses were detected in 9.7% of samples ( n = 6134), with the highest intensity of circulation occurring in 2016 (15.8%), attributed mainly to A(H3N2). Periods of increased influenza transmission (June to October) generally coincided with rainy seasons; however, variations in terms of monthly distribution of cases between years were evident. Hospitalisation rates (SARI) were most frequent in infants (0–11 months, 37.9%) and young children (1–4 years, 24.8%), whereas influenza prevalences were highest in the 15–49 (12.0%) and ≥ 50 (15.2%) years old categories. A new A(H1N1)pdm09 6B.1 hemagglutinin subgroup characterised by amino acid substitutions S84N, S162N and I216T was detected in 2015, with associated antigenic drift, and subsequently, two of these viruses showed highly reduced inhibition by oseltamivir. Conclusion: This study showcases the value of local influenza sentinel networks to specifically inform vaccination strategies and highlights the need for improved strain characterisation in tropical regions.

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.

Vaccination remains our main defence against influenza, which causes substantial annual mortality and poses a serious pandemic threat. Influenza virus evades immunity by rapidly changing its surface antigens but, even when the vaccine is well matched to the current circulating virus strains, influenza vaccines are not as effective as many other vaccines. Influenza vaccine development has traditionally focused on the induction of protective antibodies, but there is mounting evidence that T cell responses are also protective against influenza. Thus, future vaccines designed to promote both broad T cell effector functions and antibodies may provide enhanced protection. As we discuss, such vaccines present several challenges that require new strategic and economic considerations. Vaccine-induced T cells relevant to protection may reside in the lungs or lymphoid tissues, requiring more invasive assays to assess the immunogenicity of vaccine candidates. T cell functions may contain and resolve infection rather than completely prevent infection and early illness, requiring vaccine effectiveness to be assessed based on the prevention of severe disease and death rather than symptomatic infection. It can be complex and costly to measure T cell responses and infrequent clinical outcomes, and thus innovations in clinical trial design are needed for economic reasons. Nevertheless, the goal of more effective influenza vaccines justifies renewed and intensive efforts.

In April 2023, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by one new family, 14 new genera, and 140 new species. Two genera and 538 species were renamed. One species was moved, and four were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

Surface antigens of pathogens are commonly targeted by vaccine-elicited antibodies but antigenic variability, notably in RNA viruses such as influenza, HIV and SARS-CoV-2, pose challenges for control by vaccination. For example, influenza A(H3N2) entered the human population in 1968 causing a pandemic and has since been monitored, along with other seasonal influenza viruses, for the emergence of antigenic drift variants through intensive global surveillance and laboratory characterisation. Statistical models of the relationship between genetic differences among viruses and their antigenic similarity provide useful information to inform vaccine development, though accurate identification of causative mutations is complicated by highly correlated genetic signals that arise due to the evolutionary process. Here, using a sparse hierarchical Bayesian analogue of an experimentally validated model for integrating genetic and antigenic data, we identify the genetic changes in influenza A(H3N2) virus that underpin antigenic drift. We show that incorporating protein structural data into variable selection helps resolve ambiguities arising due to correlated signals, with the proportion of variables representing haemagglutinin positions decisively included, or excluded, increased from 59.8% to 72.4%. The accuracy of variable selection judged by proximity to experimentally determined antigenic sites was improved simultaneously. Structure-guided variable selection thus improves confidence in the identification of genetic explanations of antigenic variation and we also show that prioritising the identification of causative mutations is not detrimental to the predictive capability of the analysis. Indeed, incorporating structural information into variable selection resulted in a model that could more accurately predict antigenic assay titres for phenotypically-uncharacterised virus from genetic sequence. Combined, these analyses have the potential to inform choices of reference viruses, the targeting of laboratory assays, and predictions of the evolutionary success of different genotypes, and can therefore be used to inform vaccine selection processes.

The COVID-19 pandemic is the first to have emerged when Next Generation Sequencing was readily available and it has played the major role in following evolution of the causative agent, Severe Acute Respiratory Syndrome Coronavirus 2. Response to the pandemic was greatly facilitated though use of existing influenza surveillance networks: World Health Organization (WHO) Global Influenza Surveillance and Response System (GISRS), focussing largely on human influenza, and the OFFLU network of expertise on avian influenza established by the Food and Agricultural Organization of the United Nations (FAO) and the World Organization for Animal Health (WOAH). Data collection/deposition platforms associated with these networks, notably WHO’s FluNet and the Global Initiative on Sharing All Influenza Data (GISAID) were/are being used intensely. Measures introduced to combat COVID-19 resulted in greatly decreased circulation of human seasonal influenza viruses for approximately 2 years, but circulation continued in the animal sector with an upsurge in the spread of highly pathogenic avian influenza subtype H5N1 with large numbers of wild bird deaths, culling of many poultry flocks and sporadic spill over into mammalian species, including humans, thereby increasing pandemic risk potential. While there are proposals/implementations to extend use of GISRS and GISAID to other infectious disease agents (e.g. Respiratory Syncytial Virus and Monkeypox), there is need to ensure that influenza surveillance is maintained and improved in both human and animal sectors in a sustainable manner to be truly prepared (early detection) for the next influenza pandemic.

In March 2022, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by two new families (bunyaviral Discoviridae and Tulasviridae), 41 new genera, and 98 new species. Three hundred forty-nine species were renamed and/or moved. The accidentally misspelled names of seven species were corrected. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

Several variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged during the current coronavirus disease 2019 (COVID-19) pandemic. Although antibody cross-reactivity with the spike glycoproteins (S) of diverse coronaviruses, including endemic common cold coronaviruses (HCoVs), has been documented, it remains unclear whether such antibody responses, typically targeting the conserved S2 subunit, contribute to protection when induced by infection or through vaccination. Using a mouse model, we found that prior HCoV-OC43 S–targeted immunity primes neutralizing antibody responses to otherwise subimmunogenic SARS-CoV-2 S exposure and promotes S2-targeting antibody responses. Moreover, vaccination with SARS-CoV-2 S2 elicited antibodies in mice that neutralized diverse animal and human alphacoronaviruses and betacoronaviruses in vitro and provided a degree of protection against SARS-CoV-2 challenge in vivo. Last, in mice with a history of SARS-CoV-2 Wuhan–based S vaccination, further S2 vaccination induced broader neutralizing antibody response than booster Wuhan S vaccination, suggesting that it may prevent repertoire focusing caused by repeated homologous vaccination. These data establish the protective value of an S2-targeting vaccine and support the notion that S2 vaccination may better prepare the immune system to respond to the changing nature of the S1 subunit in SARS-CoV-2 variants of concern, as well as to future coronavirus zoonoses.