Neutralization potency of the 2023-24 seasonal influenza vaccine against circulating influenza H3N2 strains

Seasonal influenza is a severe disease that significantly impacts public health, causing millions of infections and hundreds of thousands of deaths each year. Seasonal influenza viruses, particularly the H3N2 subtype, exhibit high antigenic variability, often leading to mismatch between vaccine strains and circulating strains. Therefore, rapidly assessing the alignment between existing seasonal influenza vaccine and circulating strains is crucial for enhancing vaccine efficacy. This study, based on a pseudovirus platform, evaluated the match between current influenza H3N2 vaccine strains and circulating strains through cross-neutralization assays using clinical human immune sera against globally circulating influenza virus strains. The research results show that although mutations are present in the circulating strains, the current H3N2 vaccine strain still imparting effective protection, providing a scientific basis for encouraging influenza vaccination. This research methodology can be sustainably applied for the neutralization potency assessment of subsequent circulating strains, establishing a persistent methodological framework.

R229I substitution from oseltamivir induction in HA1 region significantly increased the fitness of a H7N9 virus bearing NA 292K

The proportion of human isolates with reduced neuraminidase inhibitors (NAIs) susceptibility in highly pathogenic avian influenza (HPAI) H7N9 virus was high. These drug-resistant strains showed good replication capacity without serious loss of fitness. In the presence of oseltamivir, R229I substitution were found in HA1 region of the HPAI H7N9 virus before NA R292K appeared. HPAI H7N9 or H7N9/PR8 recombinant viruses were developed to study whether HA R229I could increase the fitness of the H7N9 virus bearing NA 292K. Replication efficiency was assessed in MDCK or A549 cells. Neuraminidase enzyme activity and receptor-binding ability were analyzed. Pathogenicity in C57 mice was evaluated. Antigenicity analysis was conducted through a two-way HI test, in which the antiserum was obtained from immunized ferrets. Transcriptomic analysis of MDCK infected with HPAI H7N9 24hpi was done. It turned out that HA R229I substitution from oseltamivir induction in HA1 region increased (1) replication ability in MDCK(P < 0.05) and A549(P < 0.05), (2) neuraminidase enzyme activity, (3) binding ability to both α2,3 and α2,6 receptor, (4) pathogenicity to mice(more weight loss; shorter mean survival day; viral titer in respiratory tract, P < 0.05; Pathological changes in pneumonia), (5) transcriptome response of MDCK, of the H7N9 virus bearing NA 292K. Besides, HA R229I substitution changed the antigenicity of H7N9/PR8 virus (>4-fold difference of HI titre). It indicated that through the fine-tuning of HA-NA balance, R229I increased the fitness and changed the antigenicity of H7N9 virus bearing NA 292K. Public health attention to this mechanism needs to be drawn.

An explainable language model for antibody specificity prediction using curated influenza hemagglutinin antibodies

Despite decades of antibody research, it remains challenging to predict the specificity of an antibody solely based on its sequence. Two major obstacles are the lack of appropriate models and the inaccessibility of datasets for model training. In this study, we curated >5,000 influenza hemagglutinin (HA) antibodies by mining research publications and patents, which revealed many distinct sequence features between antibodies to HA head and stem domains. We then leveraged this dataset to develop a lightweight memory B cell language model (mBLM) for sequence-based antibody specificity prediction. Model explainability analysis showed that mBLM could identify key sequence features of HA stem antibodies. Additionally, by applying mBLM to HA antibodies with unknown epitopes, we discovered and experimentally validated many HA stem antibodies. Overall, this study not only advances our molecular understanding of the antibody response to the influenza virus but also provides a valuable resource for applying deep learning to antibody research.

Environment-independent distribution of mutational effects emerges from microscopic epistasis

Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, in which the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.

Evolution of Influenza A(H3N2) Viruses in Bhutan for Two Consecutive Years, 2022 and 2023

BACKGROUND

Influenza A viruses pose a significant public health threat globally and are characterized by rapid evolution of the hemagglutinin (HA) gene causing seasonal epidemics. The aim of this study was to investigate the evolutionary dynamics of A(H3N2) circulating in Bhutan during 2022 and 2023.

METHODS

We analysed 166 whole-genome sequences of influenza A(H3N2) from Bhutan, obtained from the GISAID database. We employed a Bayesian Markov Chain Monte Carlo (MCMC) framework, with a curated global dataset of HA sequences from regions with significant migration links to Bhutan. Phylogenetic, temporal, and phylogeographic analyses were conducted to elucidate the evolutionary dynamics and spatial dissemination of the viruses.

RESULTS

Our phylogenetic analysis identified the circulation of influenza A(H3N2) Clade 3C.2a1b.2a.2 in Bhutan during 2022 and 2023, with viruses further classified into three subclades: 2a.3 (39/166), 2a.3a.1 (58/166) and 2a.3b (69/166). The TMRCA estimates suggest that these viral lineages originated approximately 1.93 years prior to their detection. Phylogeographic analysis indicates introductions from the United States in 2022 and Australia in 2023. The mean evolutionary rate across all gene segments was calculated to be 4.42 × 10-3 substitutions per site per year (95% HPD: 3.19 × 10-3 to 5.84 × 10-3), with evidence of purifying selection and limited genetic diversity. Furthermore, reassortment events were rare, with an estimated rate of 0.045 events per lineage per year.

CONCLUSION

Our findings show that primary forces shaping the local evolution of the influenza A(H3N2) in Bhutan are largely stochastic, with only sporadic instances of adaptive change, and thus underscore the importance of continuous surveillance to mitigate the impact of evolving strains.

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.

Advancing Human Vaccine Development Using Humanized Mouse Models

The development of effective vaccines against infectious diseases remains a critical challenge in global health. Animal models play a crucial role in vaccine development by providing valuable insights into the efficacy, safety, and mechanisms of immune response induction, which guide the design and formulation of vaccines. However, traditional animal models often inadequately recapitulate human immune responses. Humanized mice (hu-mice) models with a functional human immune system have emerged as invaluable tools in bridging the translational gap between preclinical research and clinical trials for human vaccine development. This review summarizes commonly used hu-mice models and advances in optimizing them to improve human immune responses. We review the application of humanized mice for human vaccine development with a focus on HIV-1 vaccines. We also discuss the remaining challenges and improvements needed for the currently available hu-mice models to better facilitate the development and testing of human vaccines for infectious diseases.

Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population and how this heterogeneity affects virus evolution. Here, we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of two H3N2 strains, A/Hong Kong/45/2019 and A/Perth/16/2009, affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that were fixed in influenza variants after 2020 cause greater escape from sera from younger individuals compared with adults. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups and suggest approaches to understand how this heterogeneous selection shapes viral evolution.

Sequence-based detection of emerging antigenically novel influenza A viruses

The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe Novel Influenza Virus A Detector (NIAViD), an unsupervised machine learning tool, adept at identifying these transitions, using the HA1 sequence and associated physico-chemical properties. NIAViD performed with 88.9% (95% CI, 56.5-98.0%) and 72.7% (95% CI, 43.4-90.3%) sensitivity in training and validation, respectively, outperforming the uncalibrated null model-33.3% (95% CI, 12.1-64.6%) and does not require potentially biased, time-consuming and costly laboratory assays. The pivotal role of the Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modelling of haemagglutinin inhibition titres. We believe this approach holds promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.

Analysis of seasonal H3N2 influenza virus epidemic characteristics and whole genome features in Jining City from 2018 to 2023

Seasonal H3N2 influenza virus, known for its rapid evolution, poses a serious threat to human health. This study focuses on analyzing the influenza virus trends in Jining City (2018-2023) and understanding the evolving nature of H3N2 strains. Data on influenza-like cases were gathered from Jining City's sentinel hospitals: Jining First People's Hospital and Rencheng Maternal and Child Health Hospital, using the Chinese Influenza Surveillance Information System. Over the period from 2018 to 2023, 7844 throat swab specimens were assessed using real-time fluorescence quantitative PCR for influenza virus nucleic acid detection. For cases positive for seasonal H3N2 influenza virus, virus isolation was followed by whole genome sequencing. Evolutionary trees were built for the eight gene segments, and protein variation analysis was performed. From 2018 to 2023, influenza-like cases in Jining City represented 6.99% (237 299/3 397 247) of outpatient visits, peaking in December and January. Influenza virus was detected in 15.67% (1229/7844) of cases, primarily from December to February. Notably, no cases were found in the 2020-2021 season. Full genome sequencing was conducted on 70 seasonal H3N2 strains, revealing distinct evolutionary branches across seasons. Significant antigenic site variations in the HA protein were noted. No resistance mutations to inhibitors were found, but some strains exhibited mutations in PA, NS1, PA-X, and PB1-F2. Influenza trends in Jining City saw significant shifts in the 2020-2021 and 2022-2023 seasons. Seasonal H3N2 exhibited rapid evolution. Sustained vigilance is imperative for vaccine updates and antiviral selection.

Global antigenic landscape and vaccine recommendation strategy for low pathogenic avian influenza A (H9N2) viruses

The sustained circulation of H9N2 avian influenza viruses (AIVs) poses a significant threat for contributing to a new pandemic. Given the temporal and spatial uncertainty in the antigenicity of H9N2 AIVs, the immune protection efficiency of vaccines remains challenging. By developing an antigenicity prediction method for H9N2 AIVs, named PREDAC-H9, the global antigenic landscape of H9N2 AIVs was mapped. PREDAC-H9 utilizes the XGBoost model with 14 well-designed features. The XGBoost model was built and evaluated to predict the antigenic relationship between any two viruses with high values of 81.1 %, 81.4 %, 81.3 %, 81.1 %, and 89.4 % in accuracy, precision, recall, F1 value, and area under curve (AUC), respectively. Then the antigenic correlation network (ACnet) was constructed based on the predicted antigenic relationship for H9N2 AIVs from 1966 to 2022, and ten major antigenic clusters were identified. Of these, four novel clusters were generated in China in the past decade, demonstrating the unique complex situation there. To help tackle this situation, we applied PREDAC-H9 to calculate the cluster-transition determining sites and screen out virus strains with the high cross-protective spectrum, thus providing an in silico reference for vaccine recommendation. The proposed model will reduce the clinical monitoring workload and provide a useful tool for surveillance and control of H9N2 AIVs.

MetaFluAD: meta-learning for predicting antigenic distances among influenza viruses

Influenza viruses rapidly evolve to evade previously acquired human immunity. Maintaining vaccine efficacy necessitates continuous monitoring of antigenic differences among strains. Traditional serological methods for assessing these differences are labor-intensive and time-consuming, highlighting the need for efficient computational approaches. This paper proposes MetaFluAD, a meta-learning-based method designed to predict quantitative antigenic distances among strains. This method models antigenic relationships between strains, represented by their hemagglutinin (HA) sequences, as a weighted attributed network. Employing a graph neural network (GNN)-based encoder combined with a robust meta-learning framework, MetaFluAD learns comprehensive strain representations within a unified space encompassing both antigenic and genetic features. Furthermore, the meta-learning framework enables knowledge transfer across different influenza subtypes, allowing MetaFluAD to achieve remarkable performance with limited data. MetaFluAD demonstrates excellent performance and overall robustness across various influenza subtypes, including A/H3N2, A/H1N1, A/H5N1, B/Victoria, and B/Yamagata. MetaFluAD synthesizes the strengths of GNN-based encoding and meta-learning to offer a promising approach for accurate antigenic distance prediction. Additionally, MetaFluAD can effectively identify dominant antigenic clusters within seasonal influenza viruses, aiding in the development of effective vaccines and efficient monitoring of viral evolution.

Environment-independent distribution of mutational effects emerges from microscopic epistasis

Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, where the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global-epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.

Resurgence of influenza with increased genetic diversity of circulating viruses during the 2022-2023 season

Introduction. After two seasons of absence and low circulation, influenza activity increased significantly in the winter of 2022-2023. This study aims to characterize virological and epidemiological aspects of influenza infection in Bulgaria during the 2022-2023 season and perform a phylogenetic/molecular analysis of the hemagglutinin (HA) and neuraminidase (NA) sequences of representative influenza strains.Hypothesis/Gap Statement. Influenza A and B viruses generate new genetic groups/clades each season, replacing previously circulating variants. This results in increased antigenic distances from current vaccine strains. Strengthening existing influenza surveillance is essential to meet the challenges posed by the co-circulation of influenza and SARS-CoV-2.Methodology. We tested 2713 clinical samples from patients with acute respiratory illnesses using a multiplex real-time RT-PCR kit (FluSC2) to detect influenza A/B and Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2) simultaneously. Representative Bulgarian influenza strains were sequenced at the WHO Collaborating Centres in London, UK, and Atlanta, USA.Results. Influenza virus was detected in 694 (25.6 %) patients. Of these, 364 (52.4 %), 213 (30.7 %) and 117 (16.9 %) were positive for influenza A(H1N1)pdm09, A(H3N2) and B/Victoria lineage virus, respectively. HA genes of the 47 influenza A(H1N1)pdm09 viruses fell into clades 5a.2. and 5a.2a.1 within the 6B.5A.1A.5a.2 group. Twenty-seven A(H3N2) viruses belonging to subclades 2b, 2a.1, 2a.1b and 2a.3a.1 within the 3C.2a1b.2a.2 group were analysed. All 23 sequenced B/Victoria lineage viruses were classified into the V1A.3a.2 group. We identified amino acid substitutions in HA and NA compared with the vaccine strains, including several substitutions in the HA antigenic sites.Conclusion. The study's findings showed genetic diversity among the influenza A viruses and, to a lesser extent, among B viruses, circulating in the first season after the lifting of anti-COVID-19 measures.

Natural variation in neuraminidase activity influences the evolutionary potential of the seasonal H1N1 lineage hemagglutinin

The antigenic evolution of the influenza A virus hemagglutinin (HA) gene poses a major challenge for the development of vaccines capable of eliciting long-term protection. Prior efforts to understand the mechanisms that govern viral antigenic evolution mainly focus on HA in isolation, ignoring the fact that HA must act in concert with the viral neuraminidase (NA) during replication and spread. Numerous studies have demonstrated that the degree to which the receptor-binding avidity of HA and receptor-cleaving activity of NA are balanced with each other influences overall viral fitness. We recently showed that changes in NA activity can significantly alter the mutational fitness landscape of HA in the context of a lab-adapted virus strain. Here, we test whether natural variation in relative NA activity can influence the evolutionary potential of HA in the context of the seasonal H1N1 lineage (pdmH1N1) that has circulated in humans since the 2009 pandemic. We observed substantial variation in the relative activities of NA proteins encoded by a panel of H1N1 vaccine strains isolated between 2009 and 2019. We comprehensively assessed the effect of NA background on the HA mutational fitness landscape in the circulating pdmH1N1 lineage using deep mutational scanning and observed pronounced epistasis between NA and residues in or near the receptor-binding site of HA. To determine whether NA variation could influence the antigenic evolution of HA, we performed neutralizing antibody selection experiments using a panel of monoclonal antibodies targeting different HA epitopes. We found that the specific antibody escape profiles of HA were highly contingent upon NA background. Overall, our results indicate that natural variation in NA activity plays a significant role in governing the evolutionary potential of HA in the currently circulating pdmH1N1 lineage.

Neutralizing antibody responses against contemporary and future influenza A(H3N2) viruses in paradoxical clades elicited by repeated and single vaccinations

As one of the most effective measures to prevent seasonal influenza viruses, annual influenza vaccination is globally recommended. Nevertheless, evidence regarding the impact of repeated vaccination to contemporary and future influenza has been inconclusive. A total of 100 subjects singly or repeatedly immunized with influenza vaccines including 3C.2a1 or 3C.3a1 A(H3N2) during 2018-2019 and 2019-2020 influenza season were recruited. We investigated neutralization antibody by microneutralization assay using four antigenically distinct A(H3N2) viruses circulating from 2018 to 2023, and tracked the dynamics of B cell receptor (BCR) repertoire for consecutive vaccinations. We found that vaccination elicited cross-reactive antibody responses against future emerging strains. Broader neutralizing antibodies to A(H3N2) viruses and more diverse BCR repertoires were observed in the repeated vaccination. Meanwhile, a higher frequency of BCR sequences shared among the repeated-vaccinated individuals with consistently boosting antibody response was found than those with a reduced antibody response. Our findings suggest that repeated seasonal vaccination could broaden the breadth of antibody responses, which may improve vaccine protection against future emerging viruses.

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.

Genomic characterization of Influenza A (H1N1)pdm09 and SARS-CoV-2 from Influenza Like Illness (ILI) and Severe Acute Respiratory Illness (SARI) cases reported between July-December, 2022

Influenza Like Illness (ILI) and Severe Acute Respiratory Infection (SARI) cases are more prone to Influenza and SARS-CoV-2 infection. Accordingly, we genetically characterized Influenza and SARS-CoV-2 in 633 ILI and SARI cases by rRT-PCR and WGS. ILI and SARI cases showed H1N1pdm09 prevalence of 20.9% and 23.2% respectively. 135 (21.3%) H1N1pdm09 and 23 (3.6%) H3N2 and 5 coinfection (0.78%) of H1N1pdm09 and SARS-CoV-2 were detected. Phylogenetic analysis revealed H1N1pdm09 resemblance to clade 6B.1A.5a.2 and their genetic relatedness to InfA/Perth/34/2020, InfA/Victoria/88/2020 and InfA/Victoria/2570/2019. Pan 24 HA and 26 NA nonsynonymous mutations and novel HA (G6D, Y7F, Y78H, P212L, G339R, T508K and S523T) and NA (S229A) mutations were observed. S74R, N129D, N156K, S162N, K163Q and S164T alter HA Cb and Sa antibody recognizing site. Similarly, M19T, V13T substitution and multiple mutations in transmembrane and NA head domain drive antigenic drift. SARS-CoV-2 strains genetically characterized to Omicron BA.2.75 lineage containing thirty nonsynonymous spike mutations exhibited enhanced virulence and transmission rates. Coinfection although detected very minimal, the mutational changes in H1N1pdm09 and SARS-CoV-2 virus infected individuals could alter antibody receptor binding sites, allowing the viruses to escape immune response resulting in better adaptability and transmission. Thus continuous genomic surveillance is required to tackle any future outbreak.

Epitopes in the HA and NA of H5 and H7 avian influenza viruses that are important for antigenic drift

Avian influenza viruses evolve antigenically to evade host immunity. Two influenza A virus surface glycoproteins, the haemagglutinin and neuraminidase, are the major targets of host immunity and undergo antigenic drift in response to host pre-existing humoral and cellular immune responses. Specific sites have been identified as important epitopes in prominent subtypes such as H5 and H7, which are of animal and public health significance due to their panzootic and pandemic potential. The haemagglutinin is the immunodominant immunogen, it has been extensively studied, and the antigenic reactivity is closely monitored to ensure candidate vaccine viruses are protective. More recently, the neuraminidase has received increasing attention for its role as a protective immunogen. The neuraminidase is expressed at a lower abundance than the haemagglutinin on the virus surface but does elicit a robust antibody response. This review aims to compile the current information on haemagglutinin and neuraminidase epitopes and immune escape mutants of H5 and H7 highly pathogenic avian influenza viruses. Understanding the evolution of immune escape mutants and the location of epitopes is critical for identification of vaccine strains and development of broadly reactive vaccines that can be utilized in humans and animals.

Seasonal antigenic prediction of influenza A H3N2 using machine learning

Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by using the hemagglutination inhibition (HI) assays for surveillance purposes. It is also used to determine the need for annual influenza vaccine updates as well as for pandemic preparedness. Performing antigenic characterization of IAV on a global scale is confronted with high costs, animal availability, and other practical challenges. Here we present a machine learning model that accurately predicts (normalized) outputs of HI assays involving circulating human IAV H3N2 viruses, using their hemagglutinin subunit 1 (HA1) sequences and associated metadata. Each season, the model learns an updated nonlinear mapping of genetic to antigenic changes using data from past seasons only. The model accurately distinguishes antigenic variants from non-variants and adaptively characterizes seasonal dynamics of HA1 sites having the strongest influence on antigenic change. Antigenic predictions produced by the model can aid influenza surveillance, public health management, and vaccine strain selection activities.

Long-term evolution of human seasonal influenza virus A(H3N2) is associated with an increase in polymerase complex activity

Since the influenza pandemic in 1968, influenza A(H3N2) viruses have become endemic. In this state, H3N2 viruses continuously evolve to overcome immune pressure as a result of prior infection or vaccination, as is evident from the accumulation of mutations in the surface glycoproteins hemagglutinin (HA) and neuraminidase (NA). However, phylogenetic studies have also demonstrated ongoing evolution in the influenza A(H3N2) virus RNA polymerase complex genes. The RNA polymerase complex of seasonal influenza A(H3N2) viruses produces mRNA for viral protein synthesis and replicates the negative sense viral RNA genome (vRNA) through a positive sense complementary RNA intermediate (cRNA). Presently, the consequences and selection pressures driving the evolution of the polymerase complex remain largely unknown. Here, we characterize the RNA polymerase complex of seasonal influenza A(H3N2) viruses representative of nearly 50 years of influenza A(H3N2) virus evolution. The H3N2 polymerase complex is a reassortment of human and avian influenza virus genes. We show that since 1968, influenza A(H3N2) viruses have increased the transcriptional activity of the polymerase complex while retaining a close balance between mRNA, vRNA, and cRNA levels. Interestingly, the increased polymerase complex activity did not result in increased replicative ability on differentiated human airway epithelial (HAE) cells. We hypothesize that the evolutionary increase in polymerase complex activity of influenza A(H3N2) viruses may compensate for the reduced HA receptor binding and avidity that is the result of the antigenic evolution of influenza A(H3N2) viruses.

Selective pressure mediated by influenza virus M158-66 epitope-specific CD8+T cells promotes accumulation of extra-epitopic amino acid substitutions associated with viral resistance to these T cells

Influenza viruses are notorious for their capacity to evade host immunity. Not only can they evade recognition by virus-neutralizing antibodies, there is also evidence that they accumulate mutations in epitopes recognized by virus-specific CD8+T cells. In addition, we have shown previously that human influenza A viruses were less well recognized than avian influenza viruses by CD8+T cells directed to the highly conserved, HLA-A*02:01 restricted M158-66 epitope located in the Matrix 1 (M1) protein. Amino acid differences at residues outside the epitope were responsible for the differential recognition, and it was hypothesized that this reflected immune adaptation of human influenza viruses to selective pressure exerted by M158-66-specific CD8+T cells in the human population. In the present study, we tested this hypothesis and investigated if selective pressure exerted by M158-66 epitope-specific CD8+T cells could drive mutations at the extra-epitopic residues in vitro. To this end, isogenic influenza A viruses with the M1 gene of a human or an avian influenza virus were serially passaged in human lung epithelial A549 cells that transgenically express the HLA-A*02:01 molecule or not, in the presence or absence of M158-66 epitope-specific CD8+T cells. Especially in the virus with the M1 gene of an avian influenza virus, variants emerged with mutations at the extra-epitopic residues associated with reduced recognition by M158-66-specific T cells as detected by Next Generation Sequencing. Although the emergence of these variants was observed in the absence of selective pressure exerted by M158-66 epitope-specific CD8+T cells, their proportion was much larger in the presence of this selective pressure.

Antigenic drift expands viral escape pathways from imprinted host humoral immunity

An initial virus exposure can imprint antibodies such that future responses to antigenically drifted strains are dependent on the identity of the imprinting strain. Subsequent exposure to antigenically distinct strains followed by affinity maturation can guide immune responses toward generation of cross-reactive antibodies. How viruses evolve in turn to escape these imprinted broad antibody responses is unclear. Here, we used clonal antibody lineages from two human donors recognizing conserved influenza virus hemagglutinin (HA) epitopes to assess viral escape potential using deep mutational scanning. We show that even though antibody affinity maturation does restrict the number of potential escape routes in the imprinting strain through repositioning the antibody variable domains, escape is still readily observed in drifted strains and attributed to epistatic networks within HA. These data explain how influenza virus continues to evolve in the human population by escaping even broad antibody responses.

Predictive evolutionary modelling for influenza virus by site-based dynamics of mutations

Influenza virus continuously evolves to escape human adaptive immunity and generates seasonal epidemics. Therefore, influenza vaccine strains need to be updated annually for the upcoming flu season to ensure vaccine effectiveness. We develop a computational approach, beth-1, to forecast virus evolution and select representative virus for influenza vaccine. The method involves modelling site-wise mutation fitness. Informed by virus genome and population sero-positivity, we calibrate transition time of mutations and project the fitness landscape to future time, based on which beth-1 selects the optimal vaccine strain. In season-to-season prediction in historical data for the influenza A pH1N1 and H3N2 viruses, beth-1 demonstrates superior genetic matching compared to existing approaches. In prospective validations, the model shows superior or non-inferior genetic matching and neutralization against circulating virus in mice immunization experiments compared to the current vaccine. The method offers a promising and ready-to-use tool to facilitate vaccine strain selection for the influenza virus through capturing heterogeneous evolutionary dynamics over genome space-time and linking molecular variants to population immune response.

Natural variation in neuraminidase activity influences the evolutionary potential of the seasonal H1N1 lineage hemagglutinin

The antigenic evolution of the influenza A virus hemagglutinin (HA) gene poses a major challenge for the development of vaccines capable of eliciting long-term protection. Prior efforts to understand the mechanisms that govern viral antigenic evolution mainly focus on HA in isolation, ignoring the fact that HA must act in concert with the viral neuraminidase (NA) during replication and spread. Numerous studies have demonstrated that the degree to which the receptor binding avidity of HA and receptor cleaving activity of NA are balanced with each other influences overall viral fitness. We recently showed that changes in NA activity can significantly alter the mutational fitness landscape of HA in the context of a lab-adapted virus strain. Here, we test whether natural variation in relative NA activity can influence the evolutionary potential of HA in the context of the seasonal H1N1 lineage (pdmH1N1) that has circulated in humans since the 2009 pandemic. We observed substantial variation in the relative activities of NA proteins encoded by a panel of H1N1 vaccine strains isolated between 2009 and 2019. We comprehensively assessed the effect of NA background on the HA mutational fitness landscape in the circulating pdmH1N1 lineage using deep mutational scanning and observed pronounced epistasis between NA and residues in or near the receptor binding site of HA. To determine whether NA variation could influence the antigenic evolution of HA, we performed neutralizing antibody selection experiments using a panel of monoclonal antibodies targeting different HA epitopes. We found that the specific antibody escape profiles of HA were highly contingent upon NA background. Overall, our results indicate that natural variation in NA activity plays a significant role in governing the evolutionary potential of HA in the currently circulating pdmH1N1 lineage.

Asymmetrical Biantennary Glycans Prepared by a Stop-and-Go Strategy Reveal Receptor Binding Evolution of Human Influenza A Viruses

Glycan binding properties of respiratory viruses have been difficult to probe due to a lack of biologically relevant glycans for binding studies. Here, a stop-and-go chemoenzymatic methodology is presented that gave access to a panel of 32 asymmetrical biantennary N-glycans having various numbers of N-acetyl lactosamine (LacNAc) repeating units capped by α2,3- or α2,6-sialosides resembling structures found in airway tissues. It exploits that the branching enzymes MGAT1 and MGAT2 can utilize unnatural UDP-2-deoxy-2-trifluoro-N-acetamido-glucose (UDP-GlcNTFA) as donor. The TFA moiety of the resulting glycans can be hydrolyzed to give GlcNH2 at one of the antennae, which temporarily blocks extension by glycosyl transferases. The N-glycans were printed as a microarray that was probed for receptor binding specificities of the evolutionary distinct human A(H3N2) and A(H1N1)pdm09 viruses. It was found that not only the sialoside type but also the length of the LacNAc chain and presentation at the α1,3-antenna of N-glycans are critical for binding. Early A(H3N2) viruses bound to 2,6-sialosides at a single LacNAc moiety at the α1,3-antenna whereas later viruses required the sialoside to be presented at a tri-LacNAc moiety. Surprisingly, most of the A(H3N2) viruses that appeared after 2021 regained binding capacity to sialosides presented at a di-LacNAc moiety. As a result, these viruses again agglutinate erythrocytes, commonly employed for antigenic characterization of influenza viruses. Human A(H1N1)pdm09 viruses have similar receptor binding properties as recent A(H3N2) viruses. The data indicate that an asymmetric N-glycan having 2,6-sialoside at a di-LacNAc moiety is a commonly employed receptor by human influenza A viruses.

Influenza vaccine compatibility among hospitalized patients during and after the COVID-19 pandemic

Introduction

Following the significant decrease in SARS-CoV-2 cases worldwide, Israel, as well as other countries, have again been faced with a rise in seasonal influenza. This study compared circulating influenza A and B in hospitalized patients in Israel with the influenza strains in the vaccine following the 2021-2022 winter season which was dominated by the omicron variant.

Methods

Nasopharyngeal samples of 16,325 patients were examined for the detection of influenza A(H1N1)pdm09, influenza A(H1N1)pdm09 and influenza B. Phylogenetic trees of hemagglutinin were then prepared using sanger sequencing. Vaccine immunogenicity was also performed using the hemagglutination inhibition test.

Results

Of the 16,325 nasopharyngeal samples collected from hospitalized patients between September 2021 (Week 40) and April 2023 (Week 15), 7.5% were found to be positive for influenza. Phylogenetic analyses show that in the 2021-2022 winter season, the leading virus subtype was influenza A(H3N2), belonging to clade 3C.2a1b.2a.2. However, the following winter season was dominated by influenza A(H1N1)pdm09, which belongs to clade 6B.aA.5a.2. The circulating influenza A(H1N1)pdm09 strain showed a shift from the vaccine strain, while the co-circulating influenza A(H3N2) and influenza B strains were similar to those of the vaccine. Antigenic analysis coincided with the sequence analysis.

Discussion

Influenza prevalence during 2022-2023 returned to typical levels as seen prior to the emergence of SARS-CoV-2, which may suggest a gradual viral adaptation to SARS-CoV-2 variants. Domination of influenza A(H1N1)pdm09 was observed uniquely in Israel compared to Europe and USA and phylogenetic and antigenic analysis showed lower recognition of the vaccine with the circulating influenza A(H1N1)pdm09 in Israel compared to the vaccine.

A sequence-based machine learning model for predicting antigenic distance for H3N2 influenza virus

Introduction

Seasonal influenza A H3N2 viruses are constantly changing, reducing the effectiveness of existing vaccines. As a result, the World Health Organization (WHO) needs to frequently update the vaccine strains to match the antigenicity of emerged H3N2 variants. Traditional assessments of antigenicity rely on serological methods, which are both labor-intensive and time-consuming. Although numerous computational models aim to simplify antigenicity determination, they either lack a robust quantitative linkage between antigenicity and viral sequences or focus restrictively on selected features.

Methods

Here, we propose a novel computational method to predict antigenic distances using multiple features, including not only viral sequence attributes but also integrating four distinct categories of features that significantly affect viral antigenicity in sequences.

Results

This method exhibits low error in virus antigenicity prediction and achieves superior accuracy in discerning antigenic drift. Utilizing this method, we investigated the evolution process of the H3N2 influenza viruses and identified a total of 21 major antigenic clusters from 1968 to 2022.

Discussion

Interestingly, our predicted antigenic map aligns closely with the antigenic map generated with serological data. Thus, our method is a promising tool for detecting antigenic variants and guiding the selection of vaccine candidates.

VarEPS-Influ:an risk evaluation system of occurred and virtual variations of influenza virus genomes

Influenza viruses undergo frequent genomic mutations, leading to potential cross-species transmission, phenotypic changes, and challenges in diagnostic reagents and vaccines. Accurately evaluating and predicting the risk of such variations remain significant challenges. To address this, we developed the VarEPS-Influ database, an influenza virus variations risk evaluation system (VarEPS-Influ). This database employs a 'multi-dimensional evaluation of mutations' strategy, utilizing various tools to assess the physical and chemical properties, primary, secondary, and tertiary structures, receptor affinity, antibody binding capacity, antigen epitopes, and other aspects of the variation's impact. Additionally, we consider space-time distribution, host species distribution, pedigree analysis, and frequency of mutations to provide a comprehensive risk evaluation of mutations and viruses. The VarEPS-Influ database evaluates both observed variations and virtual variations (variations that have not yet occurred), thereby addressing the time-lag issue in risk predictions. Our current one-stop evaluation system for influenza virus genomic variation integrates 1065290 sequences from 224 927 Influenza A, B and C isolates retrieved from public resources. Researchers can freely access the data at https://nmdc.cn/influvar/.

Redirecting antibody responses from egg-adapted epitopes following repeat vaccination with recombinant or cell culture-based versus egg-based influenza vaccines

Repeat vaccination with egg-based influenza vaccines could preferentially boost antibodies targeting the egg-adapted epitopes and reduce immunogenicity to circulating viruses. In this randomized trial (Clinicaltrials.gov: NCT03722589), sera pre- and post-vaccination with quadrivalent inactivated egg-based (IIV4), cell culture-based (ccIIV4), and recombinant (RIV4) influenza vaccines were collected from healthcare personnel (18-64 years) in 2018-19 (N = 723) and 2019-20 (N = 684) influenza seasons. We performed an exploratory analysis. Vaccine egg-adapted changes had the most impact on A(H3N2) immunogenicity. In year 1, RIV4 induced higher neutralizing and total HA head binding antibodies to cell- A(H3N2) virus than ccIIV4 and IIV4. In year 2, among the 7 repeat vaccination arms (IIV4-IIV4, IIV4-ccIIV4, IIV4-RIV4, RIV4-ccIIV4, RIV4-RIV4, ccIIV4-ccIIV4 and ccIIV4-RIV4), repeat vaccination with either RIV4 or ccIIV4 further improved antibody responses to circulating viruses with decreased neutralizing antibody egg/cell ratio. RIV4 also had higher post-vaccination A(H1N1)pdm09 and A(H3N2) HA stalk antibodies in year 1, but there was no significant difference in HA stalk antibody fold rise among vaccine groups in either year 1 or year 2. Multiple seasons of non-egg-based vaccination may be needed to redirect antibody responses from immune memory to egg-adapted epitopes and re-focus the immune responses towards epitopes on the circulating viruses to improve vaccine effectiveness.

Protective human antibodies against a conserved epitope in pre- and postfusion influenza hemagglutinin

Phylogenetically and antigenically distinct influenza A and B viruses (IAV and IBV) circulate in human populations, causing widespread morbidity. Antibodies (Abs) that bind epitopes conserved in both IAV and IBV hemagglutinins (HAs) could protect against disease by diverse virus subtypes. Only one reported HA Ab, isolated from a combinatorial display library, protects against both IAV and IBV. Thus, there has been so far no information on the likelihood of finding naturally occurring human Abs that bind HAs of diverse IAV subtypes and IBV lineages. We have now recovered from several unrelated human donors five clonal Abs that bind a conserved epitope preferentially exposed in the postfusion conformation of IAV and IVB HA2. These Abs lack neutralizing activity in vitro but in mice provide strong, IgG subtype-dependent protection against lethal IAV and IBV infections. Strategies to elicit similar Abs routinely might contribute to more effective influenza vaccines.

Real world evidence for public health decision-making on vaccination policies: perspectives from an expert roundtable

INTRODUCTION

Influenza causes significant morbidity and mortality, but influenza vaccine uptake remains below most countries' targets. Vaccine policy recommendations vary, as do procedures for reviewing and appraising the evidence.

AREAS COVERED

During a series of roundtable discussions, we reviewed procedures and methodologies used by health ministries in four European countries to inform vaccine recommendations. We review the type of evidence currently recommended by each health ministry and the range of approaches toward considering randomized controlled trials (RCTs) and real-world evidence (RWE) studies when setting influenza vaccine recommendations.

EXPERT OPINION

Influenza vaccine recommendations should be based on data from both RCTs and RWE studies of efficacy, effectiveness, and safety. Such data should be considered alongside health-economic, cost-effectiveness, and budgetary factors. Although RCT data are more robust and less prone to bias, well-designed RWE studies permit timely evaluation of vaccine benefits, effectiveness comparisons over multiple seasons in large populations, and detection of rare adverse events, under real-world conditions. Given the variability of vaccine effectiveness due to influenza virus mutations and increasing diversification of influenza vaccines, we argue that consideration of both RWE and RCT evidence is the best approach to more nuanced and timely updates of influenza vaccine recommendations.

Combinatorial immune refocusing within the influenza hemagglutinin RBD improves cross-neutralizing antibody responses

The receptor-binding domain (RBD) of influenza virus hemagglutinin (HA) elicits potently neutralizing yet mostly strain-specific antibodies. Here, we evaluate the ability of several immunofocusing techniques to enhance the functional breadth of vaccine-elicited immune responses against the HA RBD. We present a series of "trihead" nanoparticle immunogens that display native-like closed trimeric RBDs from the HAs of several H1N1 influenza viruses. The series includes hyperglycosylated and hypervariable variants that incorporate natural and designed sequence diversity at key positions in the receptor-binding site periphery. Nanoparticle immunogens displaying triheads or hyperglycosylated triheads elicit higher hemagglutination inhibition (HAI) and neutralizing activity than the corresponding immunogens lacking either trimer-stabilizing mutations or hyperglycosylation. By contrast, mosaic nanoparticle display and antigen hypervariation do not significantly alter the magnitude or breadth of vaccine-elicited antibodies. Our results yield important insights into antibody responses against the RBD and the ability of several structure-based immunofocusing techniques to influence vaccine-elicited antibody responses.

The emergence of new antigen branches of H9N2 avian influenza virus in China due to antigenic drift on hemagglutinin through antibody escape at immunodominant sites

Vaccination is a crucial prevention and control measure against H9N2 avian influenza viruses (AIVs) that threaten poultry production and public health. However, H9N2 AIVs in China undergo continuous antigenic drift of hemagglutinin (HA) under antibody pressure, leading to the emergence of immune escape variants. In this study, we investigated the molecular basis of the current widespread antigenic drift of H9N2 AIVs. Specifically, the most prevalent h9.4.2.5-lineage in China was divided into two antigenic branches based on monoclonal antibody (mAb) hemagglutination inhibition (HI) profiling analysis, and 12 antibody escape residues were identified as molecular markers of these two branches. The 12 escape residues were mapped to antigenic sites A, B, and E (H3 was used as the reference). Among these, eight residues primarily increased 3`SLN preference and contributed to antigenicity drift, and four of the eight residues at sites A and B were positively selected. Moreover, the analysis of H9N2 strains over time and space has revealed the emergence of a new antigenic branch in China since 2015, which has replaced the previous branch. However, the old antigenic branch recirculated to several regions after 2018. Collectively, this study provides a theoretical basis for understanding the molecular mechanisms of antigenic drift and for developing vaccine candidates that contest with the current antigenicity of H9N2 AIVs.

Co-evolution of immunity and seasonal influenza viruses

Seasonal influenza viruses cause recurring global epidemics by continually evolving to escape host immunity. The viral constraints and host immune responses that limit and drive the evolution of these viruses are increasingly well understood. However, it remains unclear how most of these advances improve the capacity to reduce the impact of seasonal influenza viruses on human health. In this Review, we synthesize recent progress made in understanding the interplay between the evolution of immunity induced by previous infections or vaccination and the evolution of seasonal influenza viruses driven by the heterogeneous accumulation of antibody-mediated immunity in humans. We discuss the functional constraints that limit the evolution of the viruses, the within-host evolutionary processes that drive the emergence of new virus variants, as well as current and prospective options for influenza virus control, including the viral and immunological barriers that must be overcome to improve the effectiveness of vaccines and antiviral drugs.

Receptor Binding Properties of Neuraminidase for influenza A virus: An Overview of Recent Research Advances

Influenza A viruses (IAVs) pose a serious risk to both human and animal health. IAVs' receptor binding characteristics account for a major portion of their host range and tissue tropism. While the function of neuraminidase (NA) in promoting the release of progeny virus is well-known, its role in the virus entry process remains poorly understood. Studies have suggested that certain subtypes of NA can act as receptor-binding proteins, either alone or in conjunction with haemagglutinin (HA). An important distinction is that NA from the avian influenza virus have a second sialic acid-binding site (2SBS) that is preserved in avian strains but missing in human or swine strains. Those observations suggest that the 2SBS may play a key role in the adaptation of the avian influenza virus to mammalian hosts. In this review, we provide an update of the recent research advances in the receptor-binding role of NA and highlight its underestimated importance during the early stages of the IAV life cycle. By doing so, we aim to provide new insights into the mechanisms underlying IAV host adaptation and pathogenesis.

Key Amino Acid Residues That Determine the Antigenic Properties of Highly Pathogenic H5 Influenza Viruses Bearing the Clade 2.3.4.4 Hemagglutinin Gene

The H5 subtype highly pathogenic avian influenza viruses bearing the clade 2.3.4.4 HA gene have been pervasive among domestic poultry and wild birds worldwide since 2014, presenting substantial risks to human and animal health. Continued circulation of clade 2.3.4.4 viruses has resulted in the emergence of eight subclades (2.3.4.4a-h) and multiple distinct antigenic groups. However, the key antigenic substitutions responsible for the antigenic change of these viruses remain unknown. In this study, we analyzed the HA gene sequences of 5713 clade 2.3.4.4 viruses obtained from a public database and found that 23 amino acid residues were highly variable among these strains. We then generated a series of single-amino-acid mutants based on the H5-Re8 (a vaccine seed virus) background and tested their reactivity with a panel of eight monoclonal antibodies (mAbs). Six mutants bearing amino acid substitutions at positions 120, 126, 141, 156, 185, or 189 (H5 numbering) led to reduced or lost reactivity to these mAbs. Further antigenic cartography analysis revealed that the amino acid residues at positions 126, 156, and 189 acted as immunodominant epitopes of H5 viruses. Collectively, our findings offer valuable guidance for the surveillance and early detection of emerging antigenic variants.

Asymmetrical Bi-antennary Glycans Prepared by a Stop-and-Go Strategy Reveal Receptor Binding Evolution of Human Influenza A Viruses

Glycan binding properties of respiratory viruses have been difficult to probe due to a lack of biological relevant glycans for binding studies. Here, a stop-and-go chemoenzymatic methodology is presented that gave access to a panel of 32 asymmetrical bi-antennary N-glycans having various numbers of N-acetyl lactosamine (LacNAc) repeating units capped by α2,3- or α2,6-sialosides resembling structures found in airway tissues. It exploits that the branching enzymes MGAT1 and MGAT2 can utilize unnatural UDP-2-deoxy-2-trifluoro-N-acetamido-glucose (UDP-GlcNTFA) as donor. The TFA moiety of the resulting glycans can be hydrolyzed to give GlcNH2 at one of the antennae that temporarily blocks extension by glycosyl transferases. The N-glycans were printed as a microarray that was probed for receptor binding specificities of evolutionary distinct human A(H3N2) and A(H1N1)pdm09 viruses. It was found that not only the sialoside type but also the length of the LacNAc chain and presentation at the α1,3-antenna of N-glycans is critical for binding. Early A(H3N2) viruses bound to 2,6-sialosides at a single LacNAc moiety at the α1,3-antenna whereas later viruses required the sialoside to be presented at a tri-LacNAc moiety. Surprisingly, most of the A(H3N2) viruses that appeared after 2021 regained binding capacity to sialosides presented at a di-LacNAc moiety. As a result, these viruses agglutinate erythrocytes again, commonly employed for antigenic characterization of influenza viruses. Human A(H1N1)pdm09 viruses have similar receptor binding properties as recent A(H3N2) viruses. The data indicates that an asymmetric N-glycan having 2,6-sialoside at a di-LacNAc moiety is a commonly employed receptor by human influenza A viruses.

An atlas of continuous adaptive evolution in endemic human viruses

Through antigenic evolution, viruses such as seasonal influenza evade recognition by neutralizing antibodies. This means that a person with antibodies well tuned to an initial infection will not be protected against the same virus years later and that vaccine-mediated protection will decay. To expand our understanding of which endemic human viruses evolve in this fashion, we assess adaptive evolution across the genome of 28 endemic viruses spanning a wide range of viral families and transmission modes. Surface proteins consistently show the highest rates of adaptation, and ten viruses in this panel are estimated to undergo antigenic evolution to selectively fix mutations that enable the escape of prior immunity. Thus, antibody evasion is not an uncommon evolutionary strategy among human viruses, and monitoring this evolution will inform future vaccine efforts. Additionally, by comparing overall amino acid substitution rates, we show that SARS-CoV-2 is accumulating protein-coding changes at substantially faster rates than endemic viruses.

Phylogenetic identification of influenza virus candidates for seasonal vaccines

The seasonal influenza (flu) vaccine is designed to protect against those influenza viruses predicted to circulate during the upcoming flu season, but identifying which viruses are likely to circulate is challenging. We use features from phylogenetic trees reconstructed from hemagglutinin (HA) and neuraminidase (NA) sequences, together with a support vector machine, to predict future circulation. We obtain accuracies of 0.75 to 0.89 (AUC 0.83 to 0.91) over 2016-2020. We explore ways to select potential candidates for a seasonal vaccine and find that the machine learning model has a moderate ability to select strains that are close to future populations. However, consensus sequences among the most recent 3 years also do well at this task. We identify similar candidate strains to those proposed by the World Health Organization, suggesting that this approach can help inform vaccine strain selection.

Antigenic mapping of the hemagglutinin of the H9 subtype influenza A viruses using sera from Japanese quail (Coturnix c. japonica)

IMPORTANCE

Determining the relevant amino acids involved in antigenic drift on the surface protein hemagglutinin (HA) is critical to understand influenza virus evolution and efficient assessment of vaccine strains relative to current circulating strains. We used antigenic cartography to generate an antigenic map of the H9 hemagglutinin (HA) using sera produced in one of the most relevant minor poultry species, Japanese quail. Key antigenic positions were identified and tested to confirm their impact on the antigenic profile. This work provides a better understanding of the antigenic diversity of the H9 HA as it relates to reactivity to quail sera and will facilitate a rational approach for selecting more efficacious vaccines against poultry-origin H9 influenza viruses in minor poultry species.

Neuraminidase-dependent entry of influenza A virus is determined by hemagglutinin receptor-binding specificity

IMPORTANCE

Influenza A viruses (IAVs) contain hemagglutinin (HA) proteins involved in sialoglycan receptor binding and neuraminidase (NA) proteins that cleave sialic acids. While the importance of the NA protein in virion egress is well established, its role in virus entry remains to be fully elucidated. NA activity is needed for the release of virions from mucus decoy receptors, but conflicting results have been reported on the importance of NA activity in virus entry in the absence of decoy receptors. We now show that inhibition of NA activity affects virus entry depending on the receptor-binding properties of HA and the receptor repertoire present on cells. Inhibition of entry by the presence of mucus correlated with the importance of NA activity for virus entry, with the strongest inhibition being observed when mucus and OsC were combined. These results shed light on the importance in virus entry of the NA protein, an important antiviral drug target.

Characterization of A/H7 influenza virus global antigenic diversity and key determinants in the hemagglutinin globular head mediating A/H7N9 antigenic evolution

IMPORTANCE

A/H7 avian influenza viruses cause outbreaks in poultry globally, resulting in outbreaks with significant socio-economical impact and zoonotic risks. Occasionally, poultry vaccination programs have been implemented to reduce the burden of these viruses, which might result in an increased immune pressure accelerating antigenic evolution. In fact, evidence for antigenic diversification of A/H7 influenza viruses exists, posing challenges to pandemic preparedness and the design of vaccination strategies efficacious against drifted variants. Here, we performed a comprehensive analysis of the global antigenic diversity of A/H7 influenza viruses and identified the main substitutions in the hemagglutinin responsible for antigenic evolution in A/H7N9 viruses isolated between 2013 and 2019. The A/H7 antigenic map and knowledge of the molecular determinants of their antigenic evolution add value to A/H7 influenza virus surveillance programs, the design of vaccines and vaccination strategies, and pandemic preparedness.

Evolutionary stability of antigenically escaping viruses

Antigenic variation is the main immune escape mechanism for RNA viruses like influenza or SARS-CoV-2. While high mutation rates promote antigenic escape, they also induce large mutational loads and reduced fitness. It remains unclear how this cost-benefit trade-off selects the mutation rate of viruses. Using a traveling wave model for the coevolution of viruses and host immune systems in a finite population, we investigate how immunity affects the evolution of the mutation rate and other nonantigenic traits, such as virulence. We first show that the nature of the wave depends on how cross-reactive immune systems are, reconciling previous approaches. The immune-virus system behaves like a Fisher wave at low cross-reactivities, and like a fitness wave at high cross-reactivities. These regimes predict different outcomes for the evolution of nonantigenic traits. At low cross-reactivities, the evolutionarily stable strategy is to maximize the speed of the wave, implying a higher mutation rate and increased virulence. At large cross-reactivities, where our estimates place H3N2 influenza, the stable strategy is to increase the basic reproductive number, keeping the mutation rate to a minimum and virulence low.

Mapping SARS-CoV-2 antigenic relationships and serological responses

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, multiple variants escaping preexisting immunity emerged, causing reinfections of previously exposed individuals. Here, we used antigenic cartography to analyze patterns of cross-reactivity among 21 variants and 15 groups of human sera obtained after primary infection with 10 different variants or after messenger RNA (mRNA)-1273 or mRNA-1273.351 vaccination. We found antigenic differences among pre-Omicron variants caused by substitutions at spike-protein positions 417, 452, 484, and 501. Quantifying changes in response breadth over time and with additional vaccine doses, our results show the largest increase between 4 weeks and >3 months after a second dose. We found changes in immunodominance of different spike regions, depending on the variant an individual was first exposed to, with implications for variant risk assessment and vaccine-strain selection.

Proteomic and genetic analyses of influenza A viruses identify pan-viral host targets

Influenza A Virus (IAV) is a recurring respiratory virus with limited availability of antiviral therapies. Understanding host proteins essential for IAV infection can identify targets for alternative host-directed therapies (HDTs). Using affinity purification-mass spectrometry and global phosphoproteomic and protein abundance analyses using three IAV strains (pH1N1, H3N2, H5N1) in three human cell types (A549, NHBE, THP-1), we map 332 IAV-human protein-protein interactions and identify 13 IAV-modulated kinases. Whole exome sequencing of patients who experienced severe influenza reveals several genes, including scaffold protein AHNAK, with predicted loss-of-function variants that are also identified in our proteomic analyses. Of our identified host factors, 54 significantly alter IAV infection upon siRNA knockdown, and two factors, AHNAK and coatomer subunit COPB1, are also essential for productive infection by SARS-CoV-2. Finally, 16 compounds targeting our identified host factors suppress IAV replication, with two targeting CDK2 and FLT3 showing pan-antiviral activity across influenza and coronavirus families. This study provides a comprehensive network model of IAV infection in human cells, identifying functional host targets for pan-viral HDT.

An explainable language model for antibody specificity prediction using curated influenza hemagglutinin antibodies

Despite decades of antibody research, it remains challenging to predict the specificity of an antibody solely based on its sequence. Two major obstacles are the lack of appropriate models and inaccessibility of datasets for model training. In this study, we curated a dataset of >5,000 influenza hemagglutinin (HA) antibodies by mining research publications and patents, which revealed many distinct sequence features between antibodies to HA head and stem domains. We then leveraged this dataset to develop a lightweight memory B cell language model (mBLM) for sequence-based antibody specificity prediction. Model explainability analysis showed that mBLM captured key sequence motifs of HA stem antibodies. Additionally, by applying mBLM to HA antibodies with unknown epitopes, we discovered and experimentally validated many HA stem antibodies. Overall, this study not only advances our molecular understanding of antibody response to influenza virus, but also provides an invaluable resource for applying deep learning to antibody research.

Influenza H3 hemagglutinin vaccine with scrambled immunodominant epitopes elicits antibodies directed toward immunosubdominant head epitopes

Vaccination is the most effective countermeasure to reduce the severity of influenza. Current seasonal influenza vaccines mainly elicit humoral immunity targeting hemagglutinin (HA). In particular, the amino acid residues around the receptor-binding site in the HA head domain are predominantly targeted by humoral immunity as "immunodominant" epitopes. However, mutations readily accumulate in the head domain due to high plasticity, resulting in antigenic drift and vaccine mismatch, particularly with influenza A (H3N2) viruses. A vaccine strategy that targets more conserved immunosubdominant epitopes is required to attain a universal vaccine. Here, we designed an H3 HA vaccine antigen with various amino acids at immunodominant epitopes of the HA head domain, termed scrambled HA (scrHA). In ferrets, scrHA vaccination induced lower serum neutralizing antibody levels against homologous virus compared with wild-type (WT) HA vaccination; however, similar levels of moderately neutralizing titers against antigenically distinct H3N2 viruses were observed. Ferrets vaccinated with scrHA twice and then challenged with homologous or heterologous virus showed the same level of reduced virus shedding in nasal swabs as WT HA-vaccinated animals but reduced body temperature increase, whereas WT HA-vaccinated ferrets exhibited body temperature increases similar to those of mock-vaccinated animals. scrHA elicited antibodies against HA immunodominant and -subdominant epitopes at lower and higher levels, respectively, than WT HA vaccination, whereas antistalk antibodies were induced at the same level for both groups, suggesting scrHA-induced redirection from immunodominant to immunosubdominant head epitopes. scrHA vaccination thus induced broader coverage than WT HA vaccination by diluting out the immunodominancy of HA head epitopes. IMPORTANCE Current influenza vaccines mainly elicit antibodies that target the immunodominant head domain, where strain-specific mutations rapidly accumulate, resulting in frequent antigenic drift and vaccine mismatch. Targeting conserved immunosubdominant epitopes is essential to attain a universal vaccine. Our findings with the scrHA developed in this study suggest that designing vaccine antigens that "dilute out" the immunodominancy of the head epitopes may be an effective strategy to induce conserved immunosubdominant epitope-based immune responses.

H3N2 influenza A virus gradually adapts to human-type receptor binding and entry specificity after the start of the 1968 pandemic

To become established upon zoonotic transfer, influenza A viruses (IAV) need to switch binding from "avian-type" α2-3-linked sialic acid receptors (2-3Sia) to "human-type" Siaα2-6-linked sialic acid receptors (2-6Sia). For the 1968 H3N2 pandemic virus, this was accomplished by two canonical amino acid substitutions in its hemagglutinin (HA) although a full specificity shift had not occurred. The receptor repertoire on epithelial cells is highly diverse and simultaneous interaction of a virus particle with a range of low- to very low-affinity receptors results in tight heteromultivalent binding. How this range of affinities determines binding selectivity and virus motility remains largely unknown as the analysis of low-affinity monovalent HA-receptor interactions is technically challenging. Here, a biolayer interferometry assay enabled a comprehensive analysis of receptor-binding kinetics evolution upon host-switching. Virus-binding kinetics of H3N2 virus isolates slowly evolved from 1968 to 1979 from mixed 2-3/2-6Sia specificity to high 2-6Sia specificity, surprisingly followed by a decline in selectivity after 1992. By using genetically tuned HEK293 cells, presenting either a simplified 2-3Sia- or 2-6Sia-specific receptor repertoire, receptor-specific binding was shown to correlate strongly with receptor-specific entry. In conclusion, the slow and continuous evolution of entry and receptor-binding specificity of seasonal H3N2 viruses contrasts with the paradigm that human IAVs need to rapidly acquire and maintain a high specificity for 2-6Sia. Analysis of the kinetic parameters of receptor binding provides a basis for understanding virus-binding specificity, motility, and HA/neuraminidase balance at the molecular level.

Use of Biolayer Interferometry to Identify Dominant Binding Epitopes of Influenza Hemagglutinin Protein of A(H1N1)pdm09 in the Antibody Response to 2010-2011 Influenza Seasonal Vaccine

The globular head domain of influenza virus surface protein hemagglutinin (HA1) is the major target of neutralizing antibodies elicited by vaccines. As little as one amino acid substitution in the HA1 can result in an antigenic drift of influenza viruses, indicating the dominance of some epitopes in the binding of HA to polyclonal serum antibodies. Therefore, identifying dominant binding epitopes of HA is critical for selecting seasonal influenza vaccine viruses. In this study, we have developed a biolayer interferometry (BLI)-based assay to determine dominant binding epitopes of the HA1 in antibody response to influenza vaccines using a panel of recombinant HA1 proteins of A(H1N1)pdm09 virus with each carrying a single amino acid substitution. Sera from individuals vaccinated with the 2010-2011 influenza trivalent vaccines were analyzed for their binding to the HA1 panel and hemagglutination inhibition (HI) activity against influenza viruses with cognate mutations. Results revealed an over 50% reduction in the BLI binding of several mutated HA1 compared to the wild type and a strong correlation between dominant residues identified by the BLI and HI assays. Our study demonstrates a method to systemically analyze antibody immunodominance in the humoral response to influenza vaccines.