Novel Sequence-Based Mapping of Recently Emerging H5NX Influenza Viruses Reveals Pandemic Vaccine Candidates

Association of disease severity and genetic variation during primary Respiratory Syncytial Virus infections

BACKGROUND

Respiratory Syncytial Virus (RSV) disease in young children ranges from mild cold symptoms to severe symptoms that require hospitalization and sometimes result in death. Studies have shown a statistical association between RSV subtype or phylogenic lineage and RSV disease severity, although these results have been inconsistent. Associations between variation within RSV gene coding regions or residues and RSV disease severity has been largely unexplored.

METHODS

Nasal swabs from children (< 8 months-old) infected with RSV in Rochester, NY between 1977-1998 clinically presenting with either mild or severe disease during their first cold-season were used. Whole-genome RSV sequences were obtained using overlapping PCR and next-generation sequencing. Both whole-genome phylogenetic and non-phylogenetic statistical approaches were performed to associate RSV genotype with disease severity.

RESULTS

The RSVB subtype was statistically associated with disease severity. A significant association between phylogenetic clustering of mild/severe traits and disease severity was also found. GA1 clade sequences were associated with severe disease while GB1 was significantly associated with mild disease. Both G and M2-2 gene variation was significantly associated with disease severity. We identified 16 residues in the G gene and 3 in the M2-2 RSV gene associated with disease severity.

CONCLUSION

These results suggest that phylogenetic lineage and the genetic variability in G or M2-2 genes of RSV may contribute to disease severity in young children undergoing their first infection.

Prediction of Antigenic Distance in Influenza A Using Attribute Network Embedding

Owing to the rapid changes in the antigenicity of influenza viruses, it is difficult for humans to obtain lasting immunity through antiviral therapy. Hence, tracking the dynamic changes in the antigenicity of influenza viruses can provide a basis for vaccines and drug treatments to cope with the spread of influenza viruses. In this paper, we developed a novel quantitative prediction method to predict the antigenic distance between virus strains using attribute network embedding techniques. An antigenic network is built to model and combine the genetic and antigenic characteristics of the influenza A virus H3N2, using the continuous distributed representation of the virus strain protein sequence (ProtVec) as a node attribute and the antigenic distance between virus strains as an edge weight. The results show a strong positive correlation between supplementing genetic features and antigenic distance prediction accuracy. Further analysis indicates that our prediction model can comprehensively and accurately track the differences in antigenic distances between vaccines and influenza virus strains, and it outperforms existing methods in predicting antigenic distances between strains.

Implementing sequence-based antigenic distance calculation into immunological shape space model

BACKGROUND

In 2009, a novel influenza vaccine was distributed worldwide to combat the H1N1 influenza "swine flu" pandemic. However, antibodies induced by the vaccine display differences in their specificity and cross-reactivity dependent on pre-existing immunity. Here, we present a computational model that can capture the effect of pre-existing immunity on influenza vaccine responses. The model predicts the region of the virus hemagglutinin (HA) protein targeted by antibodies after vaccination as well as the level of cross-reactivity induced by the vaccine. We tested our model by simulating a scenario similar to the 2009 pandemic vaccine and compared the results to antibody binding data obtained from human subjects vaccinated with the monovalent 2009 H1N1 influenza vaccine.

RESULTS

We found that both specificity and cross-reactivity of the antibodies induced by the 2009 H1N1 influenza HA protein were affected by the viral strain the individual was originally exposed. Specifically, the level of antigenic relatedness between the original exposure HA antigen and the 2009 HA protein affected antigenic-site immunodominance. Moreover, antibody cross-reactivity was increased when the individual's pre-existing immunity was specific to an HA protein antigenically distinct from the 2009 pandemic strain. Comparison of simulation data with antibody binding data from human serum samples demonstrated qualitative and quantitative similarities between the model and real-life immune responses to the 2009 vaccine.

CONCLUSION

We provide a novel method to evaluate expected outcomes in antibody specificity and cross-reactivity after influenza vaccination in individuals with different influenza HA antigen exposure histories. The model produced similar outcomes as what has been previously reported in humans after receiving the 2009 influenza pandemic vaccine. Our results suggest that differences in cross-reactivity after influenza vaccination should be expected in individuals with different exposure histories.

Characterizing Emerging Canine H3 Influenza Viruses

The continual emergence of novel influenza A strains from non-human hosts requires constant vigilance and the need for ongoing research to identify strains that may pose a human public health risk. Since 1999, canine H3 influenza A viruses (CIVs) have caused many thousands or millions of respiratory infections in dogs in the United States. While no human infections with CIVs have been reported to date, these viruses could pose a zoonotic risk. In these studies, the National Institutes of Allergy and Infectious Diseases (NIAID) Centers of Excellence for Influenza Research and Surveillance (CEIRS) network collaboratively demonstrated that CIVs replicated in some primary human cells and transmitted effectively in mammalian models. While people born after 1970 had little or no pre-existing humoral immunity against CIVs, the viruses were sensitive to existing antivirals and we identified a panel of H3 cross-reactive human monoclonal antibodies (hmAbs) that could have prophylactic and/or therapeutic value. Our data predict these CIVs posed a low risk to humans. Importantly, we showed that the CEIRS network could work together to provide basic research information important for characterizing emerging influenza viruses, although there were valuable lessons learned.

Human COBRA 2 vaccine contains two major epitopes that are responsible for eliciting neutralizing antibody responses against heterologous clades of viruses

Highly pathogenic H5N1 influenza viruses continue to spread around the globe and reassort with low pathogenic avian influenza viruses often resulting in morbidity and mortality to not only waterfowl, but also poultry. Our group previously developed two hemagglutinin (HA) based vaccines using a methodology termed computationally optimized broadly reactive antigen (COBRA). Each of these HA antigens, Human COBRA 2 (Hu-CO) and Human-Avian COBRA 2 (Hu-Av CO) elicit antibodies with hemagglutination-inhibition (HAI) activity against viruses from various clades, but not always the same viruses. Here, we have sought to identify residues in these two HA molecules that are critical fordifferential HAI activity against various H5Nx influenza viruses. The two HA antigens are remarkedly similar in the globular head region, except for 4 residues at amino acids 140, 141, 155, and 156. By mutating these amino acids in each HA antigen, chimeric HA proteins were used to elicit immune responses in mice. When the Asn-Thr pair at position 155-156 in the Hu-CO HA was converted to the Ser-Ala residues found in the Hu-Av CO HA, the elicited antibodies lost HAI activity against clade 2.3.2.1 H5Nx viruses, such as A/Hubei/01/2010. When this Asn-Thr motif was added at these positions in the Hu-Av CO HA molecule, HAI activity in the elicited sera against A/Hubei/01/2010 was significantly increased. We speculate that a putative N-linked glycosylation at this location in the Hu-CO HA antigen is a key driver in the elicitation of antibodies with HAI activity to different locations on wild-type H5 HA molecules resulting in differential neutralization of viral infection and protection in vivo against H5 influenza virus induced disease.

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.

Antigenic cartography of H1N1 influenza viruses using sequence-based antigenic distance calculation

BACKGROUND

The ease at which influenza virus sequence data can be used to estimate antigenic relationships between strains and the existence of databases containing sequence data for hundreds of thousands influenza strains make sequence-based antigenic distance estimates an attractive approach to researchers. Antigenic mismatch between circulating strains and vaccine strains results in significantly decreased vaccine effectiveness. Furthermore, antigenic relatedness between the vaccine strain and the strains an individual was originally primed with can affect the cross-reactivity of the antibody response. Thus, understanding the antigenic relationships between influenza viruses that have circulated is important to both vaccinologists and immunologists.

RESULTS

Here we develop a method of mapping antigenic relationships between influenza virus stains using a sequence-based antigenic distance approach (SBM). We used a modified version of the p-all-epitope sequence-based antigenic distance calculation, which determines the antigenic relatedness between strains using influenza hemagglutinin (HA) genetic coding sequence data and provide experimental validation of the p-all-epitope calculation. We calculated the antigenic distance between 4838 H1N1 viruses isolated from infected humans between 1918 and 2016. We demonstrate, for the first time, that sequence-based antigenic distances of H1N1 Influenza viruses can be accurately represented in 2-dimenstional antigenic cartography using classic multidimensional scaling. Additionally, the model correctly predicted decreases in cross-reactive antibody levels with 87% accuracy and was highly reproducible with even when small numbers of sequences were used.

CONCLUSION

This work provides a highly accurate and precise bioinformatics tool that can be used to assess immune risk as well as design optimized vaccination strategies. SBM accurately estimated the antigenic relationship between strains using HA sequence data. Antigenic maps of H1N1 virus strains reveal that strains cluster antigenically similar to what has been reported for H3N2 viruses. Furthermore, we demonstrated that genetic variation differs across antigenic sites and discuss the implications.

Antigenicity of the 2015-2016 seasonal H1N1 human influenza virus HA and NA proteins

Antigenic drift of the hemagglutinin (HA) and neuraminidase (NA) influenza virus proteins contributes to reduced vaccine efficacy. To analyze antigenic drift in human seasonal H1N1 viruses derived from the 2009 pandemic H1N1 virus (pH1N1-like viruses) accounts for the limited effectiveness (around 40%) of vaccination against pH1N1-like viruses during the 2015-2016 season, nasal washes/swabs collected from adult subjects in the Rochester, NY area, were used to sequence and isolate the circulating viruses. The HA and NA proteins from viruses circulating during the 2015-2016 season encoded eighteen and fourteen amino acid differences, respectively, when compared to A/California/04/2009, a strain circulating at the origin of the 2009 pandemic. The circulating strains belonged to subclade 6B.1, defined by HA amino acid substitutions S101N, S179N, and I233T. Hemagglutination-inhibiting (HAI) and HA-specific neutralizing serum antibody (Ab) titers from around 50% of pH1N1-like virus-infected subjects and immune ferrets were 2-4 fold lower for the 2015-2016 circulating strains compared to the vaccine strain. In addition, using a luminex-based mPlex HA assay, the binding of human sera from subjects infected with pH1N1-like viruses to the HA proteins from circulating and vaccine strains was not identical, strongly suggesting antigenic differences in the HA protein. Additionally, NA inhibition (NAI) Ab titers in human sera from pH1N1-like virus-infected subjects increased after the infection and there were measurable antigenic differences between the NA protein of circulating strains and the vaccine strain using both ferret and human antisera. Despite having been vaccinated, infected subjects exhibited low HAI Ab titers against the vaccine and circulating strains. This suggests that poor responses to the H1N1 component of the vaccine as well as antigenic differences in the HA and NA proteins of currently circulating pH1N1-like viruses could be contributing to risk of infection even after vaccination.

Natural and directed antigenic drift of the H1 influenza virus hemagglutinin stalk domain

The induction of antibodies specific for the influenza HA protein stalk domain is being pursued as a universal strategy against influenza virus infections. However, little work has been done looking at natural or induced antigenic variability in this domain and the effects on viral fitness. We analyzed human H1 HA head and stalk domain sequences and found substantial variability in both, although variability was highest in the head region. Furthermore, using human immune sera from pandemic A/California/04/2009 immune subjects and mAbs specific for the stalk domain, viruses were selected in vitro containing mutations in both domains that partially contributed to immune evasion. Recombinant viruses encoding amino acid changes in the HA stalk domain replicated well in vitro, and viruses incorporating two of the stalk mutations retained pathogenicity in vivo. These findings demonstrate that the HA protein stalk domain can undergo limited drift under immune pressure and the viruses can retain fitness and virulence in vivo, findings which are important to consider in the context of vaccination targeting this domain.