Antigenic Maps of Influenza A(H3N2) Produced With Human Antisera Obtained After Primary Infection

Evaluation of Different Machine Learning Approaches to Predict Antigenic Distance Among Newcastle Disease Virus (NDV) Strains

Newcastle disease virus (NDV) continues to present a significant challenge for vaccination due to its rapid evolution and the emergence of new variants. Although molecular and sequence data are now quickly and inexpensively produced, genetic distance rarely serves as a good proxy for cross-protection, while experimental studies to assess antigenic differences are time consuming and resource intensive. In response to these challenges, this study explores and compares several machine learning (ML) methods to predict the antigenic distance between NDV strains as determined by hemagglutination-inhibition (HI) assays. By analyzing F and HN gene sequences alongside corresponding amino acid features, we developed predictive models aimed at estimating antigenic distances. Among the models evaluated, the random forest (RF) approach outperformed traditional linear models, achieving a predictive accuracy with an R2 value of 0.723 compared to only 0.051 for linear models based on genetic distance alone. This significant improvement demonstrates the usefulness of applying flexible ML approaches as a rapid and reliable tool for vaccine selection, minimizing the need for labor-intensive experimental trials. Moreover, the flexibility of this ML framework holds promise for application to other infectious diseases in both animals and humans, particularly in scenarios where rapid response and ethical constraints limit conventional experimental approaches.

Nonhuman primate antigenic cartography of SARS-CoV-2

Virus neutralization profiles against primary infection sera and corresponding antigenic cartography are integral part of the COVID-19 and influenza vaccine strain selection processes. Human single variant exposure sera have previously defined the antigenic relationships among SARS-CoV-2 variants but are now largely unavailable due to widespread population immunity. Therefore, antigenic characterization of future SARS-CoV-2 variants will require an animal model, analogous to using ferrets for influenza virus. We evaluated neutralization profiles against 23 SARS-CoV-2 variants in nonhuman primates (NHPs) after single variant exposure and generated an NHP-derived antigenic map. We identified a distant antigenic region occupied by BA.2.86, JN.1, and the descendants KP.2, KP.3, and KZ.1.1.1. We also found that the monovalent XBB.1.5 mRNA vaccine induced broad immunity against the mapped antigenic space. In addition, substantial concordance was observed between our NHP-derived and two human antigenic maps, demonstrating the utility of NHPs as a surrogate for antigenic cartography in humans.

Measures of Population Immunity Can Predict the Dominant Clade of Influenza A (H3N2) in the 2017-2018 Season and Reveal Age-Associated Differences in Susceptibility and Antibody-Binding Specificity

BACKGROUND

For antigenically variable pathogens such as influenza, strain fitness is partly determined by the relative availability of hosts susceptible to infection with that strain compared with others. Antibodies to the hemagglutinin (HA) and neuraminidase (NA) confer substantial protection against influenza infection. We asked if a cross-sectional antibody-derived estimate of population susceptibility to different clades of influenza A (H3N2) could predict the success of clades in the following season.

METHODS

We collected sera from 483 healthy individuals aged 1 to 90 years in the summer of 2017 and analyzed neutralizing responses to the HA and NA of representative strains using focus reduction neutralization tests (FNRT) and enzyme-linked lectin assays (ELLA). We estimated relative population-average and age-specific susceptibilities to circulating viral clades and compared those estimates to changes in clade frequencies in the following 2017-2018 season.

RESULTS

The clade to which neutralizing antibody titers were lowest, indicating greater population susceptibility, dominated the next season. Titer correlations between viral strains varied by age, suggesting age-associated differences in epitope targeting driven by shared past exposures. Yet substantial unexplained variation remains within age groups.

CONCLUSIONS

This study indicates how representative measures of population immunity might improve evolutionary forecasts and inform selective pressures on influenza.

Measures of population immunity can predict the dominant clade of influenza A (H3N2) in the 2017-2018 season and reveal age-associated differences in susceptibility and antibody-binding specificity

Background

For antigenically variable pathogens such as influenza, strain fitness is partly determined by the relative availability of hosts susceptible to infection with that strain compared to others. Antibodies to the hemagglutinin (HA) and neuraminidase (NA) confer substantial protection against influenza infection. We asked if a cross-sectional antibody-derived estimate of population susceptibility to different clades of influenza A (H3N2) could predict the success of clades in the following season.

Methods

We collected sera from 483 healthy individuals aged 1 to 90 years in the summer of 2017 and analyzed neutralizing responses to the HA and NA of representative strains using Focus Reduction Neutralization Tests (FNRT) and Enzyme-Linked Lectin Assays (ELLA). We estimated relative population-average and age-specific susceptibilities to circulating viral clades and compared those estimates to changes in clade frequencies in the following 2017-18 season.

Results

The clade to which neutralizing antibody titers were lowest, indicating greater population susceptibility, dominated the next season. Titer correlations between viral strains varied by age, suggesting age-associated differences in epitope targeting driven by shared past exposures. Yet substantial unexplained variation remains within age groups.

Conclusions

This study indicates how representative measures of population immunity might improve evolutionary forecasts and inform selective pressures on influenza.

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.

Antigenic cartography using variant-specific hamster sera reveals substantial antigenic variation among Omicron subvariants

Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) has developed substantial antigenic variability. As the majority of the population now has pre-existing immunity due to infection or vaccination, the use of experimentally generated animal immune sera can be valuable for measuring antigenic differences between virus variants. Here, we immunized Syrian hamsters by two successive infections with one of nine SARS-CoV-2 variants. Their sera were titrated against 16 SARS-CoV-2 variants, and the resulting titers were visualized using antigenic cartography. The antigenic map shows a condensed cluster containing all pre-Omicron variants (D614G, Alpha, Delta, Beta, Mu, and an engineered B.1+E484K variant) and considerably more diversity among a selected panel of Omicron subvariants (BA.1, BA.2, BA.4/BA.5, the BA.5 descendants BF.7 and BQ.1.18, the BA.2.75 descendant BN.1.3.1, the BA.2-derived recombinants XBB.2 and EG.5.1, and the BA.2.86 descendant JN.1). Some Omicron subvariants were as antigenically distinct from each other as the wildtype is from the Omicron BA.1 variant. Compared to titers measured in human sera, titers in hamster sera are of higher magnitude, show less fold change, and result in a more compact antigenic map topology. The results highlight the potential of sera from hamsters for the continued antigenic characterization of SARS-CoV-2.

Evolution of the Antigenic Landscape in Children and Young Adults with COVID-19 and MIS-C

There is minimal knowledge regarding the durability of neutralization capacity and level of binding antibody generated against the highly transmissible circulating Omicron subvariants following SARS-CoV-2 infection in children with acute COVID-19 and those diagnosed with multisystem inflammatory syndrome in children (MIS-C) in the absence of vaccination. In this study, SARS-CoV-2 neutralization titers against the ancestral strain (WA1) and Omicron sublineages were evaluated in unvaccinated children admitted for COVID-19 (n = 32) and MIS-C (n = 32) at the time of hospitalization (baseline) and at six to eight weeks post-discharge (follow-up) between 1 April 2020, and 1 September 2022. In addition, antibody binding to the spike receptor binding domain (RBD) from WA1, BA.1, BA.2.75, and BA.4/BA.5 was determined using surface plasmon resonance (SPR). At baseline, the children with MIS-C demonstrated two-fold to three-fold higher binding and neutralizing antibodies against ancestral WA1 compared to those with COVID-19. Importantly, in children with COVID-19, the virus neutralization titers against the Omicron subvariants at six to eight weeks post-discharge reached the same level as those with MIS-C had at baseline but were higher than titers at 6-8 weeks post-discharge for MIS-C cases. Cross-neutralization capacity against recently emerged Omicron BQ.1, BQ.1.1, and XBB.1 variants was very low in children with either COVID-19 or MIS-C at all time points. These findings about post-infection immunity in children with either COVID-19 or MIS-C suggest the need for vaccinations in children with prior COVID-19 or MIS-C to provide effective protection from emerging and circulating SARS-CoV-2 variants.

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 the A/Hong Kong/45/2019 (H3N2) and A/Perth/16/2009 (H3N2) strains 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 fixed in influenza variants after 2020 cause the greatest escape from sera from younger individuals. 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.

Neutralization of SARS-CoV-2 Omicron BQ.1, BQ.1.1 and XBB.1 variants following SARS-CoV-2 infection or vaccination in children

Emergence of highly transmissible Omicron subvariants led to increased SARS-CoV-2 infection and disease in children. However, minimal knowledge exists regarding the neutralization capacity against circulating Omicron BA.4/BA.5, BA.2.75, BQ.1, BQ.1.1 and XBB.1 subvariants following SARS-CoV-2 vaccination in children versus during acute or convalescent COVID-19, or versus multisystem inflammatory syndrome (MIS-C). Here, we evaluate virus-neutralizing capacity against SARS-CoV-2 variants in 151 age-stratified children ( <5, 5-11, 12-21 years old) hospitalized with acute severe COVID-19 or MIS-C or convalescent mild (outpatient) infection compared with 62 age-stratified vaccinated children. An age-associated effect on neutralizing antibodies is observed against SARS-CoV-2 following acute COVID-19 or vaccination. The primary series BNT162b2 mRNA vaccinated adolescents show higher vaccine-homologous WA-1 neutralizing titers compared with <12 years vaccinated children. Post-infection antibodies did not neutralize BQ.1, BQ.1.1 and XBB.1 subvariants. In contrast, monovalent mRNA vaccination induces more cross-neutralizing antibodies in young children <5 years against BQ.1, BQ.1.1 and XBB.1 variants compared with ≥5 years old children. Our study demonstrates that in children, infection and monovalent vaccination-induced neutralization activity is low against BQ.1, BQ.1.1 and XBB.1 variants. These findings suggest a need for improved SARS-CoV-2 vaccines to induce durable, more cross-reactive neutralizing antibodies to provide effective protection against emerging variants in children.

Heterologous prime-boost H1N1 vaccination exacerbates disease following challenge with a mismatched H1N2 influenza virus in the swine model

Influenza A viruses (IAVs) pose a significant threat to both human and animal health. Developing IAV vaccine strategies able to elicit broad heterologous protection against antigenically diverse IAV strains is pivotal in effectively controlling the disease. The goal of this study was to examine the immunogenicity and protective efficacy of diverse H1N1 influenza vaccine strategies including monovalent, bivalent, and heterologous prime-boost vaccination regimens, against a mismatched H1N2 swine influenza virus. Five groups were homologous prime-boost vaccinated with either an oil-adjuvanted whole-inactivated virus (WIV) monovalent A/swine/Georgia/27480/2019 (GA19) H1N2 vaccine, a WIV monovalent A/sw/Minnesota/A02636116/2021 (MN21) H1N1 vaccine, a WIV monovalent A/California/07/2009 (CA09) H1N1, a WIV bivalent vaccine composed of CA09 and MN21, or adjuvant only (mock-vaccinated group). A sixth group was prime-vaccinated with CA09 WIV and boosted with MN21 WIV (heterologous prime-boost group). Four weeks post-boost pigs were intranasally and intratracheally challenged with A/swine/Georgia/27480/2019, an H1N2 swine IAV field isolate. Vaccine-induced protection was evaluated based on five critical parameters: (i) hemagglutination inhibiting (HAI) antibody responses, (ii) clinical scores, (iii) virus titers in nasal swabs and respiratory tissue homogenates, (iv) BALf cytology, and (v) pulmonary pathology. While all vaccination regimens induced seroprotective titers against homologous viruses, heterologous prime-boost vaccination failed to enhance HAI responses against the homologous vaccine strains compared to monovalent vaccine regimens and did not expand the scope of cross-reactive antibody responses against antigenically distinct swine and human IAVs. Mismatched vaccination regimens not only failed to confer clinical and virological protection post-challenge but also exacerbated disease and pathology. In particular, heterologous-boosted pigs showed prolonged clinical disease and increased pulmonary pathology compared to mock-vaccinated pigs. Our results demonstrated that H1-specific heterologous prime-boost vaccination, rather than enhancing cross-protection, worsened the clinical outcome and pathology after challenge with the antigenically distant A/swine/Georgia/27480/2019 strain.

Structural Consequences of Antigenic Variants of Human A/H3N2 Influenza Viruses

The genetic basis of antigenic drift of human A/H3N2 influenza virus is crucial to understanding the constraints of influenza evolution and determinants of vaccine escape. Amino acid changes at only seven positions near the receptor binding site of the surface hemagglutinin protein have been shown to be responsible for the major antigenic changes for over forty years. Experimental structures of HA are now available for the majority of the observed antigenic clusters of A/H3N2. An analysis of the HA structures of these viruses reveals the likely consequences of these mutations on the structure of HA and thus, provides a structural basis for the antigenic changes seen in human influenza viruses.

Mapping the Antibody Repertoires in Ferrets with Repeated Influenza A/H3 Infections: Is Original Antigenic Sin Really "Sinful"?

The influenza-specific antibody repertoire is continuously reshaped by infection and vaccination. The host immune response to contemporary viruses can be redirected to preferentially boost antibodies specific for viruses encountered early in life, a phenomenon called original antigenic sin (OAS) that is suggested to be responsible for diminished vaccine effectiveness after repeated seasonal vaccination. Using a new computational tool called Neutralization Landscapes, we tracked the progression of hemagglutination inhibition antibodies within ferret antisera elicited by repeated influenza A/H3 infections and deciphered the influence of prior exposures on the de novo antibody response to evolved viruses. The results indicate that a broadly neutralizing antibody signature can nevertheless be induced by repeated exposures despite OAS induction. Our study offers a new way to visualize how immune history shapes individual antibodies within a repertoire, which may help to inform future universal influenza vaccine design.

The Antibody Response Against Neuraminidase in Human Influenza A (H3N2) Virus Infections During 2018/2019 Flu Season: Focusing on the Epitopes of 329-N-Glycosylation and E344 in N2

Seasonal influenza A (H3N2) virus has been a concern since its first introduction in humans in 1968. Accumulating antigenic changes in viral hemagglutinin (HA), particularly recent cocirculations of multiple HA genetic clades, allow H3N2 virus evade into humans annually. From 2010, the binding of neuraminidase (NA) to sialic acid made the traditional assay for HA inhibition antibodies (Abs) unsuitable for antigenicity characterization. Here, we investigated the serum anti-NA response in a cohort with a seroconversion of microneutralizing (MN) Abs targeting the circulating strain, A/Singapore/INFIMH-16-0019/2016 (H3N2, 3C.2a1)-like, a virus during 2018/2019 flu seasons. We discovered that MN Ab titers show no difference between children and adults. Nevertheless, higher titers of Abs with NA activity inhibition (NI) activity of 129 and seroconversion rate of 68.42% are presented in children aged 7-17 years (n = 19) and 73.47 and 41.17% in adults aged 21-59 years (n = 17), respectively. The MN Abs generated in children display direct correlations with HA- and NA-binding Abs or NI Abs. The NI activity exhibited cross-reactivity to N2 of H3N2 viruses of 2007 and 2013, commonly with 329-N-glycosylation and E344 in N2, a characteristic of earlier 3C.2a H3N2 virus in 2014. The percentage of such viruses pronouncedly decreased and was even replaced by those dominant H3N2 viruses with E344K and 329 non-glycosylation, which have a significantly low activity to the tested antisera. Our findings suggest that NI assay is a testable assay applied in H3N2 infection in children, and the antigenic drift of current N2 should be considered for vaccine selection.

Birth cohort relative to an influenza A virus's antigenic cluster introduction drives patterns of children's antibody titers

An individual's antibody titers to influenza A strains are a result of the complicated interplay between infection history, cross-reactivity, immune waning, and other factors. It has been challenging to disentangle how population-level patterns of humoral immunity change as a function of age, calendar year, and birth cohort from cross-sectional data alone. We analyzed 1,589 longitudinal sera samples from 260 children across three studies in Nicaragua, 2006-16. Hemagglutination inhibition (HAI) titers were determined against four H3N2 strains, one H1N1 strain, and two H1N1pdm strains. We assessed temporal patterns of HAI titers using an age-period-cohort modeling framework. We found that titers against a given virus depended on calendar year of serum collection and birth cohort but not on age. Titer cohort patterns were better described by participants' ages relative to year of likely introduction of the virus's antigenic cluster than by age relative to year of strain introduction or by year of birth. These cohort effects may be driven by a decreasing likelihood of early-life infection after cluster introduction and by more broadly reactive antibodies at a young age. H3N2 and H1N1 viruses had qualitatively distinct cohort patterns, with cohort patterns of titers to specific H3N2 strains reaching their peak in children born 3 years prior to that virus's antigenic cluster introduction and with titers to H1N1 and H1N1pdm strains peaking for children born 1-2 years prior to cluster introduction but not being dramatically lower for older children. Ultimately, specific patterns of strain circulation and antigenic cluster introduction may drive population-level antibody titer patterns in children.

Influenza immune escape under heterogeneous host immune histories

In a pattern called immune imprinting, individuals gain the strongest immune protection against the influenza strains encountered earliest in life. In many recent examples, differences in early infection history can explain birth year-associated differences in susceptibility (cohort effects). Susceptibility shapes strain fitness, but without a clear conceptual model linking host susceptibility to the identity and order of past infections general conclusions on the evolutionary and epidemic implications of cohort effects are not possible. Failure to differentiate between cohort effects caused by differences in the set, rather than the order (path), of past infections is a current source of confusion. We review and refine hypotheses for path-dependent cohort effects, which include imprinting. We highlight strategies to measure their underlying causes and emergent consequences.

Advances in Development and Application of Influenza Vaccines

Influenza A virus is one of the most important zoonotic pathogens that can cause severe symptoms and has the potential to cause high number of deaths and great economic loss. Vaccination is still the best option to prevent influenza virus infection. Different types of influenza vaccines, including live attenuated virus vaccines, inactivated whole virus vaccines, virosome vaccines, split-virion vaccines and subunit vaccines have been developed. However, they have several limitations, such as the relatively high manufacturing cost and long production time, moderate efficacy of some of the vaccines in certain populations, and lack of cross-reactivity. These are some of the problems that need to be solved. Here, we summarized recent advances in the development and application of different types of influenza vaccines, including the recent development of viral vectored influenza vaccines. We also described the construction of other vaccines that are based on recombinant influenza viruses as viral vectors. Information provided in this review article might lead to the development of safe and highly effective novel influenza vaccines.

An Antigenic Thrift-Based Approach to Influenza Vaccine Design

The antigenic drift theory states that influenza evolves via the gradual accumulation of mutations, decreasing a host’s immune protection against previous strains. Influenza vaccines are designed accordingly, under the premise of antigenic drift. However, a paradox exists at the centre of influenza research. If influenza evolved primarily through mutation in multiple epitopes, multiple influenza strains should co-circulate. Such a multitude of strains would render influenza vaccines quickly inefficacious. Instead, a single or limited number of strains dominate circulation each influenza season. Unless additional constraints are placed on the evolution of influenza, antigenic drift does not adequately explain these observations. Here, we explore the constraints placed on antigenic drift and a competing theory of influenza evolution – antigenic thrift. In contrast to antigenic drift, antigenic thrift states that immune selection targets epitopes of limited variability, which constrain the variability of the virus. We explain the implications of antigenic drift and antigenic thrift and explore their current and potential uses in the context of influenza vaccine design.

A human coronavirus evolves antigenically to escape antibody immunity

There is intense interest in antibody immunity to coronaviruses. However, it is unknown if coronaviruses evolve to escape such immunity, and if so, how rapidly. Here we address this question by characterizing the historical evolution of human coronavirus 229E. We identify human sera from the 1980s and 1990s that have neutralizing titers against contemporaneous 229E that are comparable to the anti-SARS-CoV-2 titers induced by SARS-CoV-2 infection or vaccination. We test these sera against 229E strains isolated after sera collection, and find that neutralizing titers are lower against these "future" viruses. In some cases, sera that neutralize contemporaneous 229E viral strains with titers >1:100 do not detectably neutralize strains isolated 8-17 years later. The decreased neutralization of "future" viruses is due to antigenic evolution of the viral spike, especially in the receptor-binding domain. If these results extrapolate to other coronaviruses, then it may be advisable to periodically update SARS-CoV-2 vaccines.

Machine Learning Prediction and Experimental Validation of Antigenic Drift in H3 Influenza A Viruses in Swine

The antigenic diversity of influenza A viruses (IAV) circulating in swine challenges the development of effective vaccines, increasing zoonotic threat and pandemic potential. High-throughput sequencing technologies can quantify IAV genetic diversity, but there are no accurate approaches to adequately describe antigenic phenotypes. This study evaluated an ensemble of nonlinear regression models to estimate virus phenotype from genotype. Regression models were trained with a phenotypic data set of pairwise hemagglutination inhibition (HI) assays, using genetic sequence identity and pairwise amino acid mutations as predictor features. The model identified amino acid identity, ranked the relative importance of mutations in the hemagglutinin (HA) protein, and demonstrated good prediction accuracy. Four previously untested IAV strains were selected to experimentally validate model predictions by HI assays. Errors between predicted and measured distances of uncharacterized strains were 0.35, 0.61, 1.69, and 0.13 antigenic units. These empirically trained regression models can be used to estimate antigenic distances between different strains of IAV in swine by using sequence data. By ranking the importance of mutations in the HA, we provide criteria for identifying antigenically advanced IAV strains that may not be controlled by existing vaccines and can inform strain updates to vaccines to better control this pathogen.IMPORTANCE Influenza A viruses (IAV) in swine constitute a major economic burden to an important global agricultural sector, impact food security, and are a public health threat. Despite significant improvement in surveillance for IAV in swine over the past 10 years, sequence data have not been integrated into a systematic vaccine strain selection process for predicting antigenic phenotype and identifying determinants of antigenic drift. To overcome this, we developed nonlinear regression models that predict antigenic phenotype from genetic sequence data by training the model on hemagglutination inhibition assay results. We used these models to predict antigenic phenotype for previously uncharacterized IAV, ranked the importance of genetic features for antigenic phenotype, and experimentally validated our predictions. Our model predicted virus antigenic characteristics from genetic sequence data and provides a rapid and accurate method linking genetic sequence data to antigenic characteristics. This approach also provides support for public health by identifying viruses that are antigenically advanced from strains used as pandemic preparedness candidate vaccine viruses.

Earliest infections predict the age distribution of seasonal influenza A cases

Seasonal variation in the age distribution of influenza A cases suggests that factors other than age shape susceptibility to medically attended infection. We ask whether these differences can be partly explained by protection conferred by childhood influenza infection, which has lasting impacts on immune responses to influenza and protection against new influenza A subtypes (phenomena known as original antigenic sin and immune imprinting). Fitting a statistical model to data from studies of influenza vaccine effectiveness (VE), we find that primary infection appears to reduce the risk of medically attended infection with that subtype throughout life. This effect is stronger for H1N1 compared to H3N2. Additionally, we find evidence that VE varies with both age and birth year, suggesting that VE is sensitive to early exposures. Our findings may improve estimates of age-specific risk and VE in similarly vaccinated populations and thus improve forecasting and vaccination strategies to combat seasonal influenza.

Improving immunological insights into the ferret model of human viral infectious disease

Ferrets are a well-established model for studying both the pathogenesis and transmission of human respiratory viruses and evaluation of antiviral vaccines. Advanced immunological studies would add substantial value to the ferret models of disease but are hindered by the low number of ferret-reactive reagents available for flow cytometry and immunohistochemistry. Nevertheless, progress has been made to understand immune responses in the ferret model with a limited set of ferret-specific reagents and assays. This review examines current immunological insights gained from the ferret model across relevant human respiratory diseases, with a focus on influenza viruses. We highlight key knowledge gaps that need to be bridged to advance the utility of ferrets for immunological studies.

Antigenic Change in Human Influenza A(H2N2) Viruses Detected by Using Human Plasma from Aged and Younger Adult Individuals

Human influenza A(H2N2) viruses emerged in 1957 and were replaced by A(H3N2) viruses in 1968. The antigenicity of human H2N2 viruses has been tested by using ferret antisera or mouse and human monoclonal antibodies. Here, we examined the antigenicity of human H2N2 viruses by using human plasma samples obtained from 50 aged individuals who were born between 1928 and 1933 and from 33 younger adult individuals who were born after 1962. The aged individuals possessed higher neutralization titers against H2N2 viruses isolated in 1957 and 1963 than those against H2N2 viruses isolated in 1968, whereas the younger adults who were born between 1962 and 1968 possessed higher neutralization titers against H2N2 viruses isolated in 1963 than those against other H2N2 viruses. Antigenic cartography revealed the antigenic changes that occurred in human H2N2 viruses during circulation in humans for 11 years, as detected by ferret antisera. These results show that even though aged individuals were likely exposed to more recent H2N2 viruses that are antigenically distinct from the earlier H2N2 viruses, they did not possess high neutralizing antibody titers to the more recent viruses, suggesting immunological imprinting of these individuals with the first H2N2 viruses they encountered and that this immunological imprinting lasts for over 50 years.

Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin

A longstanding question is how influenza virus evolves to escape human immunity, which is polyclonal and can target many distinct epitopes. Here, we map how all amino-acid mutations to influenza's major surface protein affect viral neutralization by polyclonal human sera. The serum of some individuals is so focused that it selects single mutations that reduce viral neutralization by over an order of magnitude. However, different viral mutations escape the sera of different individuals. This individual-to-individual variation in viral escape mutations is not present among ferrets that have been infected just once with a defined viral strain. Our results show how different single mutations help influenza virus escape the immunity of different members of the human population, a phenomenon that could shape viral evolution and disease susceptibility.

Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets

The strength and breadth of an individual's antibody repertoire is an important predictor of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but have not previously been included in mathematical models of antibody landscapes, including: titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting a role for a mechanism describing diminishing antibody boosting with repeated exposures. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be identifiable with a larger set of experiments. These results highlight the potential use of repeat exposure animal models in revealing short-term, strain-specific immune dynamics of influenza.

What can we learn about influenza infection and vaccination from transcriptomics?

Transcriptomics studies the set of RNA transcripts produced by the genome using high-throughput sequencing and bioinformatics. This growing field has revolutionized our understanding of host-pathogen interactions, revealing new insights into the host response to influenza infection and vaccination. Studies using transcriptomics have identified a unique immunosignature for influenza discernable from other bacterial and viral pathogens, key transcriptional factors that discriminate early from late, mild versus severe, and symptomatic versus asymptomatic infection. Recent studies evaluating the host response to influenza vaccines have revealed key differences in live versus inactivated influenza vaccines, identified early transcriptional signatures that predict hemagglutinin antibody production following vaccination, increased our understanding of how adjuvants enhance the immune response to influenza vaccine antigens, and demonstrate biologic variability in the response to vaccination due to host factors. These studies demonstrate the potential for influenza transcriptomics to be applied to clinical care, understanding the mechanisms of infection, and informing vaccine development.

Age-specific differences in the dynamics of protective immunity to influenza

Influenza A viruses evolve rapidly to escape host immunity, causing reinfection. The form and duration of protection after each influenza virus infection are poorly understood. We quantify the dynamics of protective immunity by fitting individual-level mechanistic models to longitudinal serology from children and adults. We find that most protection in children but not adults correlates with antibody titers to the hemagglutinin surface protein. Protection against circulating strains wanes to half of peak levels 3.5–7 years after infection in both age groups, and wanes faster against influenza A(H3N2) than A(H1N1)pdm09. Protection against H3N2 lasts longer in adults than in children. Our results suggest that influenza antibody responses shift focus with age from the mutable hemagglutinin head to other epitopes, consistent with the theory of original antigenic sin, and might affect protection. Imprinting, or primary infection with a subtype, has modest to no effect on the risk of non-medically attended infections in adults.

Protective immunity after influenza virus infection is poorly understood. Here, the authors quantify the dynamics of immunity against influenza A virus infections by fitting individual-level mechanistic models to longitudinal serology, and find that the form and dynamics of protection differ between children and adults.

Memory CD4+ T cells enhance B-cell responses to drifting influenza immunization

Influenza A annually infects 5-10% of the world's human population resulting in one million deaths. Influenza causes annual epidemics and reinfects previously exposed individuals because of antigenic drift in the glycoprotein hemagglutinin. Due to antigenic drift, the immune system is simultaneously exposed to novel and conserved parts of the influenza virus via vaccination and/or infection throughout life. Preexisting immunity has long been known to augment subsequent hemagglutination inhibitory antibody (hAb) responses. However, the preexisting immunological contributors that influence hAb responses are not understood. Therefore, we adapted and developed sequential infection and immunization mouse models using drifted influenza strains to show that MHC Class II haplotype and T-cell reactivity influences subsequent hAb responses. We found that CB6F1 mice infected with A/CA followed by immunization with A/PR8 have increased hAb responses to A/PR8 compared to C57BL/6 mice. Increased hAb responses in CB6F1 mice were CD4⁺  T-cell and B-cell dependent and corresponded to increased germinal center A/PR8-specific B and T-follicular helper cells. These results suggest conserved MHC Class II restricted epitopes within HA are essential for B cells to respond to drifting influenza and could be leveraged to boost hAb responses.

Crowd on a Chip: Label-Free Human Monoclonal Antibody Arrays for Serotyping Influenza

Rapid changes in influenza A virus (IAV) antigenicity create challenges in surveillance, disease diagnosis, and vaccine development. Further, serological methods for studying antigenic properties of influenza viruses often rely on animal models and therefore may not fully reflect the dynamics of human immunity. We hypothesized that arrays of human monoclonal antibodies (hmAbs) to influenza could be employed in a pattern-recognition approach to expedite IAV serology and to study the antigenic evolution of newly emerging viruses. Using the multiplex, label-free Arrayed Imaging Reflectometry (AIR) platform, we have demonstrated that such arrays readily discriminated among various subtypes of IAVs, including H1, H3 seasonal strains, and avian-sourced human H7 viruses. Array responses also allowed the first determination of antigenic relationships among IAV strains directly from hmAb responses. Finally, correlation analysis of antibody binding to all tested IAV subtypes allowed efficient identification of broadly reactive clones. In addition to specific applications in the context of understanding influenza biology with potential utility in "universal" flu vaccine development, these studies validate AIR as a platform technology for studying antigenic properties of viruses and also antibody properties in a high-throughput manner. We further anticipate that this approach will facilitate advances in the study of other viral pathogens.

Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology

Seasonal influenza is controlled through vaccination campaigns. Evolution of influenza virus antigens means that vaccines must be updated to match novel strains, and vaccine effectiveness depends on the ability of scientists to predict nearly a year in advance which influenza variants will dominate in upcoming seasons. In this review, we highlight a promising new surveillance tool: predictive models. Based on data-sharing and close collaboration between the World Health Organization and academic scientists, these models use surveillance data to make quantitative predictions regarding influenza evolution. Predictive models demonstrate the potential of applied evolutionary biology to improve public health and disease control. We review the state of influenza predictive modeling and discuss next steps and recommendations to ensure that these models deliver upon their considerable biomedical promise.

Is seasonal vaccination a contributing factor to the selection of influenza epidemic variants?

Influenza A/H3N2 viruses are the most common and virulent subtypes for humans. Antigenic drift, changes in antigenicity through the accumulation of mutations in the hemagglutinin (HA) gene is chiefly responsible for the continuing circulation of A/H3N2 viruses, resulting in frequent updates of vaccine strains based on new variant analyses. In humans, these drift-related mutations are considered to be primarily caused by the immune pressure elicited by natural infection. Whether or not the immune pressure elicited by vaccination (vaccine pressure) can have a certain effect on drift-related mutations is unclear. Recently, our findings suggested the possible effect of vaccine pressure on HA mutations by directly comparing amino acid differences from the corresponding vaccine strains between isolates from vaccinated and unvaccinated patients. It is possible that influenza vaccine pressure selects variants genetically distant from the vaccine strains. Considering the effect of vaccine pressure on HA mutations would contribute to further understanding the mechanism of antigenic drift, which would be helpful for predicting future epidemic viruses.

Effect of Priming With Seasonal Influenza A(H3N2) Virus on the Prevalence of Cross-Reactive Hemagglutination-Inhibition Antibodies to Swine-Origin A(H3N2) Variants

Background

Recent outbreaks of swine-origin influenza A(H3N2) variant (H3N2v) viruses have raised public health concerns. Previous studies indicated that older children and young adults had the highest levels of hemagglutination-inhibition (HI) antibodies to 2010-2011 H3N2v viruses. However, newly emerging 2013 H3N2v have acquired antigenic mutations in the hemagglutinin at amino acid position 145 (N145K/R). We estimated the levels of serologic cross-reactivity among humans primed with seasonal influenza A(H3N2) (sH3N2), using postinfection ferret antisera. We also explored age-related HI antibody responses to 2012-2013 H3N2v viruses.

Methods

Human and ferret antisera were tested in HI assays against 1 representative 2012 H3N2v (145N) and 2 2013 H3N2v (145K/R) viruses, together with 9 sH3N2 viruses circulating since 1968.

Results

Low levels of cross-reactivity between the H3N2v and sH3N2 viruses from the 1970s-1990s were observed using postinfection ferret antisera. The overall seroprevalence among the sH3N2-primed population against 2012-2013 H3N2v viruses was >50%, and age-related seroprevalence was observed. Seroprevalence was significantly higher to 2013 H3N2v than to 2012 H3N2v viruses among some children likely to have been primed with A/Sydney/5/97-like (145K) or A/Wuhan/359/95-like viruses (145K).

Conclusions

A single substitution (N145K/R) was sufficient to affect seropositivity to H3N2v viruses in some individuals. Insight into age-related antibody responses to newly emerging H3N2v viruses is critical for risk assessment and pandemic preparedness.

Phylogenetic relationships of the HA and NA genes between vaccine and seasonal influenza A(H3N2) strains in Korea

Seasonal influenza is caused by two influenza A subtype (H1N1 and H3N2) and two influenza B lineage (Victoria and Yamagata) viruses. Of these antigenically distinct viruses, the H3N2 virus was consistently detected in substantial proportions in Korea during the 2010/11-2013/14 seasons when compared to the other viruses and appeared responsible for the influenza-like illness rate peak during the first half of the 2011/12 season. To further scrutinize possible causes for this, we investigated the evolutionary and serological relationships between the vaccine and Korean H3N2 strains during the 2011/12 season for the main antigenic determinants of influenza viruses, the hemagglutinin (HA) and neuraminidase (NA) genes. In the 2011/12 season, when the number of H3N2 cases peaked, the majority of the Korean strains did not belong to the HA clade of A/Perth/16/2009 vaccine, and no Korean strains were of this lineage in the NA segment. In a serological assay, post-vaccinated human sera exhibited much reduced hemagglutination inhibition antibody titers against the non-vaccine clade Korean H3N2 strains. Moreover, Korean strains harbored several amino acid differences in the HA antigenic sites and in the NA with respect to vaccine lineages during this season. Of these, the HA antigenic site C residues 45 and 261 and the NA residue 81 appeared to be the signatures of positive selection. In subsequent seasons, when H3N2 cases were lower, the HA and NA genes of vaccine and Korean strains were more phylogenetically related to each other. Combined, our results provide indirect support for using phylogenetic clustering patterns of the HA and possibly also the NA genes in the selection of vaccine viruses and the assessment of vaccine effectiveness.

Automatic detection of rate change in large data sets with an unsupervised approach: the case of influenza viruses

Influenza viruses evolve at such a high rate that vaccine recommendations need to be changed, but not quite on a regular basis. This observation suggests that the rate of evolution of these viruses is not constant through time, which begs the question as to when such rate changes occur, if they do so independently of the host in which they circulate and (or) independently of their subtype. To address these outstanding questions, we introduce a novel heuristics, Mclust*, that is based on a two-tier clustering approach in a phylogenetic context to estimate (i) absolute rates of evolution and (ii) when rate change occurs. We employ the novel approach to compare the two influenza surface proteins, hemagglutinin and neuraminidase, that circulated in avian, human, and swine hosts between 1960 and 2014 in two subtypes: H3N2 and H1N1. We show that the algorithm performs well in most conditions, accounting for phylogenetic uncertainty by means of bootstrapping and scales up to analyze very large data sets. Our results show that our approach is robust to the time-dependent artifact of rate estimation, and confirm pervasive punctuated evolution across hosts and subtypes. As such, the novel approach can potentially detect when vaccine composition needs to be updated.