A single mutation at position 214 of influenza B hemagglutinin enhances cross-neutralization

High variability of influenza B virus (IBV) hemagglutinin (HA) impairs the cross- neutralization ability of vaccines, leading to reduce efficacy. We identified significant differences in cross-neutralization between IBV strains B/Wyoming/06/2014 and B/Brisbane/60/2008, which differ in only three amino acid residues. The 214 T point mutation was found to dramatically enhance cross-neutralization (>10-fold). Antibody-based reverse validation also revealed that this mutation significantly increased the neutralization capacity (500-62,500-fold). Furthermore, monitoring revealed that the mutation rate at this site has reached its highest level in nearly 20 years, with a prevalence exceeding 80% in sequences submitted from certain regions. Our findings provide new evidence for the selection of vaccine strains with improved cross- neutralization effects, which will aid the development of broad-spectrum vaccines by modifying minimal antigenic epitopes.

Molecular analysis of influenza A(H3N2) in a remote tropical island during 2014-2019 to identify the frequency of introduction and local circulation

BACKGROUND

The sources of new antigenic Influenza A(H3N2) variants and the role of tropical regions in the global A(H3N2) circulation remain unclear. By conducting molecular analysis, this study aimed to identify A(H3N2) introduction events and the duration of local circulation in a geographically remote tropical island.

METHODS

Nasopharyngeal/nasal samples were collected from symptomatic children under 5 years old in a remote tropical island of the Philippines between 2014 and 2019. From the 330 A(H3N2) strains detected, 150 were sequenced for the Hemagglutinin 1 (HA1) gene. Time-scaled Bayesian phylogenetic analysis identified introduction events from global A(H3N2) circulation. We estimated the duration of local circulation and its association with detected amino acid substitutions.

RESULTS

Six different A(H3N2) clades/subclades circulated during the study period. Of the 15 introduction events identified during this period, 13 resulted in local circulation lasting less than 3 months, while one led to 5-month-long circulation. Another 10-month-long local circulation event, by definition, was more likely the result of two distinct introduction events with local circulation lasting less than 3 months, respectively. Most amino acid substitutions that emerged during local circulation were sporadic. No fixed substitutions appeared at the seven key amino acid sites for antigenic changes, suggesting that introduced strains were maintained without the emergence of new antigenic variants.

CONCLUSION

In our study population, A(H3N2) circulation resulted from multiple introduction events, followed by local circulation lasting less than 3 months, with occasional long-term persistence. Our study indicates that tropical regions may contribute to maintaining globally circulating strains but may not be a source of antigenic variants.

Soluble influenza H3 trimer proteins enhance the breadth and potency of antibody response

Seasonal influenza poses a continuing threat to public health. The effectiveness of the influenza vaccine varies across seasons, with protection against H3N2 being notably less reliable. A primary contributor to this variability in vaccine efficacy is the frequent antigenic drift occurring in the major antigenic epitope located within the head domain of H3. In this study, we engineered stable soluble recombinant H3 trimer proteins referred to as HK68-10 and HK14-15, wherein interprotomer disulfide bonds were established to stabilize their trimerization; importantly, native antigenicity was preserved. Our design approach, devoid of conventional trimerization motifs, should be more viable and favorable for vaccine development, as it avoids off-target immune responses and reinforces structural integrity. These two H3 trimer proteins markedly augmented antibody responses towards conserved yet immuno-subdominant epitopes, thereby improving heterologous immuno-protection against H3N2 viruses. Serological experiment results demonstrate that the elicitation of serum cross-reactivity by soluble H3 vaccines depends on stem epitopes and conserved epitopes located within the head region as well. The research findings from this study are of significance for advancing future efforts to improve H3 vaccines.

A novel reassorted swine H3N2 influenza virus demonstrates an undetected human-to-swine spillover in Latin America and highlights zoonotic risks

Influenza A virus (FLUAV) affects a wide range of hosts, including humans and animals, posing a threat to public health. In swine, H3N2 subtype is associated with human-to-swine spillovers of seasonal viruses. In Latin America, the molecular and antigenic characteristics of swine FLUAV H3N2, as well as its phylogenetic origin, are poorly understood. Therefore, the objective of this study was to characterize the first swine H3N2 detected in Colombia. The origin and lineage of the virus were estimated through phylogenetic and molecular clock analyses. Antigenic characterization was achieved by comparing the amino acid constitution of the HA with previously reported swine FLUAVs and seasonal vaccine strains using a sequence-based method. In addition to HA and NA, internal genes were also characterized. The results showed that the Colombian H3N2 corresponded to a novel phylogenetic and antigenic swine FLUAV variant that emerged due to an independent reverse zoonotic event, likely occurring in Colombia in the early 2000s. The immunodominant epitope in the virus was predominantly present in antigenic epitope A, which showed the highest amino acid variation. Some mutations that alter the N-Glycosylation of antigenic sites at the HA were detected. Internally, the virus exhibited pandemic configuration. This study provides the first evidence of a novel FLUAV in Colombia and describes its origin, variability, and persistence in geographically restricted populations, highlighting the need for strengthen molecular surveillance of the virus in animal populations.

Conserved sites on the influenza H1 and H3 hemagglutinin recognized by human antibodies

Monoclonal antibodies (mAbs) targeting the influenza hemagglutinin (HA) can be used as prophylactics or templates for next-generation vaccines. Here, we isolated broad, subtype-neutralizing mAbs from human B cells recognizing the H1 or H3 HA "head" and a mAb engaging the conserved stem. The H1 mAbs bind the lateral patch epitope on HAs from 1933 to 2021 and a prepandemic swine H1N1 virus. We improved neutralization potency using directed evolution toward a contemporary H1 HA. Deep mutational scanning of four antigenically distinct H1N1 viruses identified potential viral escape pathways. For the H3 mAbs, we used cryo-electron microscopy to define their epitopes: One mAb binds the side of the HA head, accommodating the N133 glycan and a pocket underneath the receptor binding site; the other mAb recognizes an HA stem epitope that partially overlaps with previously characterized mAbs but with distinct antibody variable genes. Collectively, these mAbs identify conserved sites recognized by broadly-reactive mAbs that may be elicited by next-generation vaccines.

Immunological drivers of zoonotic virus emergence, evolution, and endemicity

The disruption of natural ecosystems caused by climate change and human activity is amplifying the risk of zoonotic spillover, presenting a growing global health threat. In the past two decades, the emergence of multiple zoonotic viruses has exposed critical gaps in our ability to predict epidemic trajectories and implement effective interventions. RNA viruses, in particular, are challenging to control due to their high mutation rates and ability to adapt and evade immune defenses. To better prepare for future outbreaks, it is vital that we deepen our understanding of the factors driving viral emergence, transmission, and persistence in human populations. Specifically, deciphering the interactions between antibody-mediated immunity and viral evolution will be key. In this perspective, we explore these dynamic relationships and highlight research priorities that may guide the development of more effective strategies to mitigate the impact of emerging infectious diseases.

High-throughput neutralization measurements correlate strongly with evolutionary success of human influenza strains

Human influenza viruses rapidly acquire mutations in their hemagglutinin (HA) protein that erode neutralization by antibodies from prior exposures. Here, we use a sequencing-based assay to measure neutralization titers for 78 recent H3N2 HA strains against a large set of children and adult sera, measuring ~10,000 total titers. There is substantial person-to-person heterogeneity in the titers against different viral strains, both within and across age cohorts. The growth rates of H3N2 strains in the human population in 2023 are highly correlated with the fraction of sera with low titers against each strain. Notably, strain growth rates are less correlated with neutralization titers against pools of human sera, demonstrating the importance of population heterogeneity in shaping viral evolution. Overall, these results suggest that high-throughput neutralization measurements of human sera against many different viral strains can help explain the evolution of human influenza.

VirusWarn: A mutation-based early warning system to prioritize concerning SARS-CoV-2 and influenza virus variants from sequencing data

The rapid evolution of respiratory viruses is characterized by the emergence of variants with concerning phenotypes that are efficient in antibody escape or show high transmissibility. This necessitates timely identification of such variants by surveillance networks to assist public health interventions. Here, we introduce VirusWarn, a comprehensive system designed for detecting, prioritizing, and warning of emerging virus variants from large genomic datasets. VirusWarn uses both manually-curated rules and machine-learning (ML) classifiers to generate and rank pathogen sequences based on mutations of concern and regions of interest. Validation results for SARS-CoV-2 showed that VirusWarn successfully identifies variants of concern in both assessments, with manual- and ML-derived criteria from positive selection analyses. Although initially developed for SARS-CoV-2, VirusWarn was adapted to Influenza viruses and their dynamics, and provides a robust performance, integrating a scheme that accounts for fixed mutations from past seasons. HTML reports provide detailed results with searchable tables and visualizations, including mutation plots and heatmaps. Because VirusWarn is written in Nextflow, it can be easily adapted to other pathogens, demonstrating its flexibility and scalability for genomic surveillance efforts.

Antigenic drift expands influenza viral escape pathways from recalled humoral immunity

Initial exposure to a rapidly evolving virus establishes B cell memory that biases later responses to antigenically drifted strains. This "immune imprinting" implies that subsequent exposure to a drifted strain can induce affinity maturation of memory B cells toward cross-reactivity with the drifted strain and hence toward greater overall breadth. Here, we used deep mutational scanning of H1 influenza hemagglutinins (HAs) to investigate how viruses evolve in response to these broad antibody response. We identified escape mutations from clonal antibody lineages that targeted the receptor binding site and lateral patch. By adjusting the antigen-antibody contacts, antibody affinity maturation restricted the potential escape routes for the eliciting strain. However, escape occurred readily in drifted strains. We attribute this escape-prone property of the drifted strains to epistatic networks within HA. Our data explain how the influenza virus continues to evolve in the human population by escaping even broad antibody responses.

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

Pathogenic and Antigenic Analyses of H5N1 High Pathogenicity Avian Influenza Virus Isolated in the 2022/2023 Season From Poultry Farms in Izumi City, Japan

During the winter of 2022/2023, Japan experienced its largest outbreak of high pathogenicity avian influenza (HPAI), affecting 84 poultry premises. In this study, we investigated the pathogenicity and antigenicity of A/chicken/Kagoshima/22A1T/2022 (Kagoshima/22A1T), a clade 2.3.4.4b H5N1 virus belonging to the G2b group. It was isolated from a poultry farm in Izumi City, where the largest number of consecutive cases was recorded. The 50% lethal dose, mean death time (MDT), amount of virus shed, and transmissibility in chickens of Kagoshima/22A1T were similar to those of A/chicken/Kagoshima/21A6T/2022 (Kagoshima/21A6T), the previous season's isolate of the same group, indicating that their pathogenicities were comparable. However, the antigenicity of these isolates differed according to the hemagglutination inhibition (HI) test results. We found that the amino acid substitutions in residues 189 and 193, corresponding to antigenic site B in the H3 virus of the HA1 subunit, could have an impact on the HI cross-reactivity of Kagoshima/21A6T. This study provides important insights into the factors contributing to the consecutive HPAI outbreaks on poultry farms in Izumi City during the 2022/2023 season and the prediction of antigenic changes in G2b group HPAI viruses.

Equine Influenza: Epidemiology, Pathogenesis, and Strategies for Prevention and Control

Equine influenza (EI) is a highly contagious respiratory disease caused by the equine influenza virus (EIV), posing a significant threat to equine populations worldwide. EIV exhibits considerable antigenic variability due to its segmented genome, complicating long-term disease control efforts. Although infections are rarely fatal, EIV's high transmissibility results in widespread outbreaks, leading to substantial morbidity and considerable economic impacts on veterinary care, quarantine, and equestrian activities. The H3N8 subtype has undergone significant antigenic evolution, resulting in the emergence of distinct lineages, including Eurasian and American, with the Florida sublineage being particularly prevalent. Continuous genetic surveillance and regular updates to vaccine formulations are necessary to address antigenic drift and maintain vaccination efficacy. Additionally, rare cross-species transmissions have raised concerns regarding the zoonotic potential of EIV. This review provides a comprehensive overview of the epidemiology, pathogenesis, and prevention of EI, emphasizing vaccination strategies and addressing the socio-economic consequences of the disease in regions where the equine industry is vital.

Etiological Spectrum of Acute Respiratory Infections in Bulgaria During the 2023-2024 Season and Genetic Diversity of Circulating Influenza Viruses

Influenza poses a serious threat to both individual and public health. This study aimed to investigate the virological and epidemiological characteristics of influenza infections and to explore the genetic diversity of the circulating influenza viruses. In total, 1886 nasopharyngeal specimens from patients with acute respiratory illnesses were tested against 13 respiratory viruses using a multiplex real-time PCR. Whole-genome sequencing, phylogenetic, and amino acid analyses of representative influenza strains were performed. At least one respiratory virus was detected in 869 (46.1%) patients; 87 (4.6%) were co-infected with two or three viruses. Influenza A(H1N1)pdm09 was the most prevalent virus (16.1%), followed by rhinoviruses (8.1%) and RSV (6.7%). Hemagglutinin (HA) genes of the 74 influenza A(H1N1)pdm09 viruses were categorized in subclades C.1.8, C.1.9, and C.1 within clade 5a.2a and D1, D.2, and D.3 within clade 5a.2a.1. The A(H3N2) viruses analyzed belonged to clade 2a.3a.1, subclades J.2 and J.1. The sequenced B/Victoria lineage viruses fell into clade V1A.3a.2, subclades C.5.6 and C.5.7. Amino acid substitutions in most viral proteins were identified compared with the vaccine strains, including in the HA antigenic sites. This study demonstrated the dominant distribution of the influenza A(H1N1)pdm09 virus among the respiratory viruses studied and the genetic diversity of the circulating influenza viruses.

Raman signatures of type A and B influenza viruses: molecular origin of the "catch and kill" inactivation mechanism mediated by micrometric silicon nitride powder

A multiomic study of the structural characteristics of type A and B influenza viruses by means of highly spectrally resolved Raman spectroscopy is presented. Three virus strains, A H1N1, A H3N2, and B98, were selected because of their known structural variety and because they have co-circulated with variable relative prevalence within the human population since the re-emergence of the H1N1 subtype in 1977. Raman signatures of protein side chains tyrosine, tryptophan, and histidine revealed unequivocal and consistent differences for pH characteristics at the virion surface, while different conformations of two C-S bond configurations in gauche and trans methionine rotamers provided distinct low-wavenumber fingerprints for different virus lineages/subtypes. Short-term exposure to a few percent fraction of silicon nitride (Si3N4) micrometric powder in an aqueous environment completely inactivated the influenza virions, independent of lineage/subtype dependent characteristics. The molecular-scale details of the inactivation process were studied by Raman spectroscopy and interpreted in terms of a "catch and kill" mechanism, in which the hydrolyzing ceramic surface first attracts virions with high efficiency through electrochemical interactions (mimicking cellular sialic acid) and then "poisons" the viruses by local hydrolytic elution of ammonia and nitrogen radicals. The latter event causes severe damage to the virions' structures, including structural degradation of RNA purines, rotameric scrambling of methionine residues, formation of sulfhydryl and ionized carboxyl groups, and deprotonation/torsional deformation of tyrosine, tryptophan, and histidine residues. This study confirmed the antiviral effectiveness of Si3N4 powder, which is safe to the human body and simply activated by water molecules. Raman spectroscopy was confirmed as a powerful tool in molecular virology, complementary to genomics and unique in providing direct information on virus structures at the molecular scale.

Epidemiology and Genetic Evolutionary Analysis of Influenza Virus Among Children in Hainan Island, China, 2021-2023

BACKGROUND

During the COVID-19 pandemic, we continuously monitored the epidemiology of influenza virus among pediatric patients from January 2021 to December 2023 in Hainan Island, China.

METHODS

In this study, we collected 54,974 nasopharyngeal swab samples for influenza A Virus (IAV) testing and 53,151 samples for influenza B Virus (IBV) testing from pediatric outpatients. Additionally, we also collected 19,687 nasopharyngeal swab samples from pediatric inpatients for IAV and IBV testing. Outpatient samples were screened for influenza viruses (IVs) infection by the colloidal gold method. Targeted Next-Generation Sequencing (tNGS) was used to detect influenza virus infections in inpatients. Influenza virus types were identified by analyzing the HA/NA partial regions.

RESULTS

The findings revealed a significant decrease in the infection rate of IBV over the specified period, while the infection rate of IAV exhibited a rising trend. Additionally, B/Victoria lineage was the dominant epidemic strain in 2021, while the epidemic strains in 2022 and 2023 underwent a dynamic transformation from A/H3N2 to A/H1N1. Phylogenetic analysis revealed close relationships among the circulating strains. Nonetheless, because the sample size is limited, additional research is required.

CONCLUSIONS

Our findings suggest that the predominant types of influenza viruses in the pediatric population are undergoing dynamic changes, influenced by the implementation and relaxation of non-pharmaceutical intervention measures. These findings highlight the need for adaptive influenza vaccination and containment strategies, particularly in tropical regions like Hainan, where climate and public health policies significantly impact viral transmission patterns. The insights gained from this study could inform more effective public health strategies in similar regions to mitigate the impact of influenza outbreaks in the future.

Artificial intelligence for modelling infectious disease epidemics

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI.

HA198 mutations in H9N2 avian influenza: molecular dynamics insights into receptor binding

Introduction

The H9N2 avian influenza virus is widely disseminated in poultry and poses a zoonotic threat, despite vaccination efforts. Mutations at residue 198 of hemagglutinin (HA) are critical for antigenic variation and receptor-binding specificity, but the underlying molecular mechanisms remain unclear. This study explores the molecular mechanisms by which mutations at the HA 198 site affect the antigenicity, receptor specificity, and binding affinity of the H9N2 virus.

Methods

Using the sequence of the A/Chicken/Jiangsu/WJ57/2012 strain, we constructed recombinant H9N2 viruses, including rWJ57, rWJ57/HA198A, and rWJ57/HA198T, using reverse genetics. These variants were analyzed through hemagglutination inhibition (HI) assays, receptor-destroying enzyme (RDE) assays, enzyme-linked immunosorbent assays (ELISA) and solid-phase receptor binding assays. Additionally, molecular dynamics (MD) simulations were performed to further dissect the atomic-level interactions between HA and sialic acids (SA).

Results

The results demonstrated that HA mutations significantly altered the receptor-binding properties of the virus. Specifically, rWJ57 (HA198V) exhibited 4-fold and 16-fold higher overall receptor-binding avidity compared to rWJ57/HA198A and rWJ57/HA198T, respectively. Furthermore, HA198V/T mutations significantly enhanced viral binding to human-type α2,6 SA receptors (p < 0.001), whereas the HA198A mutation exhibited a marked preference for avian-type α2,3 SA receptors (p < 0.001). Additionally, these mutations altered interactions with non-specific antibodies but not specific antibodies, with high-avidity receptor binding mutations exhibiting reduced non-specific antibody binding, suggesting a potential novel mechanism for immune evasion. MD simulations revealed HA198V/T formed stable complexes with the α2,6 SA, mediated by specific residues and water bridges, whereas HA198A formed stable complexes with the α2,3 SA. Interestingly, residue 198 interacted with the α2,6 SA via water bridges but had with showed minimal direct interaction with α2,3 SA.

Discussion

This study provides new insights into the molecular basis of receptor specificity, binding affinity, and antigenic drift in H9N2 viruses, highlighting the critical role of HA 198 mutations in regulating host adaptation. These findings are of great significance for H9N2 virus surveillance, vaccine development, and zoonotic transmission risk assessment.

Learning the fitness dynamics of pathogens from phylogenies

The dynamics of the genetic diversity of pathogens, including the emergence of lineages with increased fitness, is a foundational concept of disease ecology with key public-health implications. However, the identification of such lineages and estimation of associated fitness remain challenging, and is rarely done outside densely sampled systems1,2. Here we present phylowave, a scalable approach that summarizes changes in population composition in phylogenetic trees, enabling the automatic detection of lineages based on shared fitness and evolutionary relationships. We use our approach on a broad set of viruses and bacteria (SARS-CoV-2, influenza A subtype H3N2, Bordetella pertussis and Mycobacterium tuberculosis), which include both well-studied and understudied threats to human health. We show that phylowave recovers the main known circulating lineages for each pathogen and that it can detect specific amino acid changes linked to fitness changes. Furthermore, phylowave identifies previously undetected lineages with increased fitness, including three co-circulating B. pertussis lineages. Inference using phylowave is robust to uneven and limited observations. This widely applicable approach provides an avenue to monitor evolution in real time to support public-health action and explore fundamental drivers of pathogen fitness.

Interim estimates of vaccine effectiveness against influenza A(H1N1)pdm09 and A(H3N2) during a delayed influenza season, Canada, 2024/25

The Canadian Sentinel Practitioner Surveillance Network (SPSN) reports interim 2024/25 vaccine effectiveness (VE) against acute respiratory illness due to laboratory-confirmed influenza during a delayed season of predominant A(H1N1)pdm09 and lower A(H3N2) co-circulation. Through mid-January, the risk of outpatient illness due to influenza A is reduced by about half among vaccinated vs unvaccinated individuals. Adjusted VE is 53% (95% CI: 36-65) against A(H1N1)pdm09, comprised of clades 5a.2a and 5a.2a.1, and 54% (95% CI: 29-70) against A(H3N2), virtually all clade 2a.3a.1.

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.

Epistasis in the receptor binding domain of contemporary H3N2 viruses that reverted to bind sialylated diLacNAc repeats

Since the introduction of H3N2 influenza A viruses in the human population, these viruses have continuously evolved to escape human immunity, with mutations occurring in and around the receptor binding site. This process, called antigenic drift, recently resulted in viruses that recognize elongated glycans that are not abundantly displayed in the human respiratory tract. Such receptor specificities hampered our ability to pick and propagate vaccine strains. Using ELISA, glycan array, tissue staining, flow cytometry, and hemagglutinin assays, this study revealed that the most recent H3N2 viruses have expanded receptor specificity by regaining effective recognition to shorter glycans. In recent H3 strains, Y159 and T160 are responsible for restricted binding to elongated glycans; in contemporary strains, however, Y159N and T160I dominate with a consequent loss of strength in receptor binding. Yet, effective receptor interaction is rescued by a remote mutation in the 190-helix, Y195F. The results demonstrate epistasis of critical residues in three of the four structural elements composing the HA receptor-binding site (the 130-loop, 150-loop, and 190-helix), which synergistically contribute to shape receptor binding specificity. Interestingly, a positive correlation exists between binding to an asymmetrical N-glycan containing an α2,6 sialylated tri-LacNAc arm and binding to human and ferret respiratory tract tissues. Together, these results elucidate the epistatic nature of receptor binding specificity during influenza A virus H3N2 evolution.

Evolutionary analysis of Hemagglutinin and neuraminidase gene variation in H1N1 swine influenza virus from vaccine intervention in China

Influenza poses a significant threat to the global economy and health. Inactivated virus vaccines were introduced in China for prevention in 2018. In this study, three pairs of hemagglutinin (HA) and neuraminidase (NA) gene sequences were obtained from three Swine influenza virus (IAV-S) inactivated vaccine strains that were marketed in China in 2018. Phylogenetic analysis was carried out with HA and NA gene sequences to investigate the relationship between vaccine use and virus genetic drift. The findings showed that the evolutionary rate of HA remained relatively stable from 2012 to 2017, with an average genetic distance of approximately 0.020731195. However, following the introduction of the swine influenza vaccine, there was a notable acceleration in the evolutionary rate of HA, accompanied by a significant increase in the genetic distance. In 2018, the value was 0.111750269, while in 2019 it was 0.176389393. In contrast, the evolution of NA was relatively smooth, with an average genetic distance of approximately 0.030386708. Finally, we demonstrated that commercial vaccines are weak neutralizers of wild strains through immunization experiments in animals. Thus, we have reason to believe that mutations in the virus favor virus evasion of vaccine immunity. Our findings suggest that vaccine use may significantly impact the evolution of the influenza virus by potentially stimulating mutations. The selection pressure of vaccine antibodies played a role in regulating the variation of IAV-S-H1N1.

Influenza A virus shedding and reinfection during the post-weaning period in swine: longitudinal study of two nurseries

INTRODUCTION

Influenza A virus in swine (IAV-S) is common in the United States commercial swine population and has the potential for zoonotic transmission.

OBJECTIVE

To elucidate influenza shedding the domestic pig population, we evaluated two commercial swine farms in Illinois, United States, for 7 weeks. Farm 1 had a recent IAV-S outbreak. Farm 2 has had IAV-S circulating for several years.

METHODS

Forty post-weaning pigs on Farm 1 and 51 pigs from Farm 2 were individually monitored and sampled by nasal swabs for 7 weeks.

RESULTS

RT-PCR results over time showed most piglets shed in the first 2 weeks post weaning, with 91.2% shedding in week one, and 36.3% in week two. No difference in the number of pigs shedding was found between the two nurseries. Reinfection events did differ between the farms, with 30% of piglets on Farm 1 becoming reinfected, compared to 7.8% on Farm 2. In addition, whole genome sequencing of nasal swab samples from each farm showed identical viruses circulating between the initial infection and the reinfection periods. Sequencing also allowed for nucleic and amino acid mutation analysis in the circulating viruses, as well the identification of a potential reverse zoonosis event. We saw antigenic site mutations arising in some pigs and MxA resistance genes in almost all samples.

CONCLUSION

This study provided information on IAV-S circulation in nurseries to aid producers and veterinarians to screen appropriately for IAV-S, determine the duration of IAV-S shedding, and predict the occurrence of reinfection in the nursery period.

Conserved sites on the influenza H1 and H3 hemagglutinin recognized by human antibodies

Monoclonal antibodies (mAbs) targeting the influenza hemagglutinin (HA) have the potential to be used as prophylactics or templates for next-generation vaccines that provide broad protection. Here, we isolated broad, subtype-neutralizing mAbs from human B cells targeting the H1 or H3 HA head as well as a unique mAb targeting the stem. The H1 mAbs target the previously defined lateral patch epitope on H1 HAs and recognize HAs from 1933 to 2021 in addition to a swine H1N1 virus with pandemic potential. Using directed evolution, we improved the neutralization potency of these H1 mAbs towards a contemporary H1 strain. Using deep mutational scanning of four antigenically distinct H1N1 viruses, we identified potential viral escape pathways. For the H3 mAbs we used cryo-EM to define the targeted epitopes: one mAb recognizes the side of the H3 head, accommodating the N133 glycan and a pocket underneath the receptor binding site. The other H3 mAb recognizes an epitope in the HA stem that overlaps with previously characterized mAbs, but with distinct antibody variable genes and mode of recognition. Collectively, these mAbs identify common sites recognized by broad, subtype-specific mAbs that may be elicited by next-generation vaccines.

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.

A vaccine antigen central in influenza A(H5) virus antigenic space confers subtype-wide immunity

Highly pathogenic avian influenza A(H5) viruses globally impact wild and domestic birds, and mammals, including humans, underscoring their pandemic potential. The antigenic evolution of the A(H5) hemagglutinin (HA) poses challenges for pandemic preparedness and vaccine design. Here, the global antigenic evolution of the A(H5) HA was captured in a high-resolution antigenic map. The map was used to engineer immunogenic and antigenically central vaccine HA antigens, eliciting antibody responses that broadly cover the A(H5) antigenic space. In ferrets, a central antigen protected as well as homologous vaccines against heterologous infection with two antigenically distinct viruses. This work showcases the rational design of subtype-wide influenza A(H5) pre-pandemic vaccines and demonstrates the value of antigenic maps for the evaluation of vaccine-induced immune responses through antibody profiles.

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.