Antigenic sites of H1N1 influenza virus hemagglutinin revealed by natural isolates and inhibition assays

IAV-CNN: A 2D Convolutional Neural Network Model to Predict Antigenic Variants of Influenza A Virus

The rapid evolution of influenza viruses constantly leads to the emergence of novel influenza strains that are capable of escaping from population immunity. The timely determination of antigenic variants is critical to vaccine design. Empirical experimental methods like hemagglutination inhibition (HI) assays are time-consuming and labor-intensive, requiring live viruses. Recently, many computational models have been developed to predict the antigenic variants without considerations of explicitly modeling the interdependencies between the channels of feature maps. Moreover, the influenza sequences consisting of similar distribution of residues will have high degrees of similarity and will affect the prediction outcome. Consequently, it is challenging but vital to determine the importance of different residue sites and enhance the predictive performance of influenza antigenicity. We have proposed a 2D convolutional neural network (CNN) model to infer influenza antigenic variants (IAV-CNN). Specifically, we apply a new distributed representation of amino acids, named ProtVec that can be applied to a variety of downstream proteomic machine learning tasks. After splittings and embeddings of influenza strains, a 2D squeeze-and-excitation CNN architecture is constructed that enables networks to focus on informative residue features by fusing both spatial and channel-wise information with local receptive fields at each layer. Experimental results on three influenza datasets show IAV-CNN achieves state-of-the-art performance combining the new distributed representation with our proposed architecture. It outperforms both traditional machine algorithms with the same feature representations and the majority of existing models in the independent test data. Therefore we believe that our model can be served as a reliable and robust tool for the prediction of antigenic variants.

Imprinting, immunodominance, and other impediments to generating broad influenza immunity

Natural influenza virus infections and seasonal vaccinations often do not confer broadly neutralizing immunity across diverse influenza strains. In addition, the virus is capable of rapid antigenic drift in order to evade pre-existing immunity. The surface glycoproteins, hemagglutinin, and neuraminidase can easily mutate their immunodominant epitopes without impacting fitness. Skewing human antibody repertoires to target more conserved epitopes is thus an expanding area of research: Many groups are attempting to produce universal influenza vaccines that can protect across a wide variety of strains. Achieving this goal will require a detailed understanding of how infection history impacts humoral responses. It will also require the ability to manipulate or enhance B cell selection in order to expand clones that can recognize subdominant but protective epitopes. In this review, we will discuss what immune imprinting means to immunologists and describe efforts to overcome or silence imprinting in order to improve vaccination efficiency.

Allele-specific nonstationarity in evolution of influenza A virus surface proteins

Influenza A virus (IAV) is a major public health problem and a pandemic threat. Its evolution is largely driven by diversifying positive selection so that relative fitness of different amino acid variants changes with time due to changes in herd immunity or genomic context, and novel amino acid variants attain fitness advantage. Here, we hypothesize that diversifying selection also has another manifestation: the fitness associated with a particular amino acid variant should decline with time since its origin, as the herd immunity adapts to it. By tracing the evolution of antigenic sites at IAV surface proteins, we show that an amino acid variant becomes progressively more likely to become replaced by another variant with time since its origin-a phenomenon we call "senescence." Senescence is particularly pronounced at experimentally validated antigenic sites, implying that it is largely driven by host immunity. By contrast, at internal sites, existing variants become more favorable with time, probably due to arising contingent mutations at other epistatically interacting sites. Our findings reveal a previously undescribed facet of adaptive evolution and suggest approaches for prediction of evolutionary dynamics of pathogens.

Effect of strain-specific maternally-derived antibodies on influenza A virus infection dynamics in nursery pigs

Reducing the number of influenza A virus (IAV) infected pigs at weaning is critical to minimize IAV spread to other farms. Sow vaccination is a common measure to reduce influenza levels at weaning. However, the impact of maternally-derived antibodies on IAV infection dynamics in growing pigs is poorly understood. We evaluated the effect of maternally-derived antibodies at weaning on IAV prevalence at weaning, time of influenza infection, number of weeks that pigs tested IAV positive, and estimated quantity of IAV in nursery pigs. We evaluated 301 pigs within 10 cohorts for their influenza serological (seroprevalence estimated by hemagglutination inhibition (HI) test) and virological (prevalence) status. Nasal swabs were collected weekly and pigs were bled 3 times throughout the nursery period. There was significant variability in influenza seroprevalence, HI titers and influenza prevalence after weaning. Increase in influenza seroprevalence at weaning was associated with low influenza prevalence at weaning and delayed time to IAV infection throughout the nursery. Piglets with IAV HI titers of 40 or higher at weaning were also less likely to test IAV positive at weaning, took longer to become infected, tested IAV RT-PCR positive for fewer weeks, and had higher IAV RT-PCR cycle threshold values compared to piglets with HI titers less than 40. Our findings suggest that sow vaccination or infection status that results in high levels of IAV strain-specific maternally-derived antibodies may help to reduce IAV circulation in both suckling and nursery pigs.

H1N1 seasonal influenza virus evolutionary rate changed over time

It was previously shown that the seasonal H1N1 influenza virus antigenic drift occurred at a slower rate than the seasonal H3N2 virus during the first decade of the 21th century. It was hypothesized that the slower antigenic evolution led to a decrease in average ages of infection, which in turn resulted in lower level of global viral circulation. It is unclear what caused the difference between the two viruses, but a plausible explanation may be related to the fact that the H1N1 virus had been in human population for much longer than the H3N2 virus. This would suggest that H1N1 antigenic drift in an earlier period may have been different from a more recent period. To test this hypothesis, we analyzed seasonal H1N1 influenza sequences during various time periods. In comparison to more recent H1N1 virus, the older H1N1 virus during the first half of the 20th century showed evidences of higher nonsynnonymous/synonymous ration (dN/dS) in its hemagglutinin (HA) gene. We compared amino acid sequence changes in the HA epitopes for each outbreak season and found that there were less changes in later years. Amino acid sequence diversity in the epitopes as measured by sequence entropy became smaller for each passing decade. These suggest that there might be some limit to the antigenic drift. The longer an influenza virus has drifted in human population, the less flexibility it may become. With less flexibility to adapt and escape the host immunity, the virus may have to rely more on younger naïve population.

Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses

BACKGROUND

The human influenza viruses undergo rapid evolution (especially in hemagglutinin (HA), a glycoprotein on the surface of the virus), which enables the virus population to constantly evade the human immune system. Therefore, the vaccine has to be updated every year to stay effective. There is a need to characterize the evolution of influenza viruses for better selection of vaccine candidates and the prediction of pandemic strains. Studies have shown that the influenza hemagglutinin evolution is driven by the simultaneous mutations at antigenic sites. Here, we analyze simultaneous or co-occurring mutations in the HA protein of human influenza A/H3N2, A/H1N1 and B viruses to predict potential mutations, characterizing the antigenic evolution.

METHODS

We obtain the rules of mutation co-occurrence using association rule mining after extracting HA1 sequences and detect co-mutation sites under strong selective pressure. Then we predict the potential drifts with specific mutations of the viruses based on the rules and compare the results with the "observed" mutations in different years.

RESULTS

The sites under frequent mutations are in antigenic regions (epitopes) or receptor binding sites.

CONCLUSIONS

Our study demonstrates the co-occurring site mutations obtained by rule mining can capture the evolution of influenza viruses, and confirms that cooperative interactions among sites of HA1 protein drive the influenza antigenic evolution.

Influenza evolution and H3N2 vaccine effectiveness, with application to the 2014/2015 season

Influenza A is a serious disease that causes significant morbidity and mortality, and vaccines against the seasonal influenza disease are of variable effectiveness. In this article, we discuss the use of the pepitope method to predict the dominant influenza strain and the expected vaccine effectiveness in the coming flu season. We illustrate how the effectiveness of the 2014/2015 A/Texas/50/2012 [clade 3C.1] vaccine against the A/California/02/2014 [clade 3C.3a] strain that emerged in the population can be estimated via pepitope In addition, we show by a multidimensional scaling analysis of data collected through 2014, the emergence of a new A/New Mexico/11/2014-like cluster [clade 3C.2a] that is immunologically distinct from the A/California/02/2014-like strains.

Neutralization and Binding Profile of Monoclonal Antibodies Generated Against Influenza A H1N1 Viruses

Monoclonal antibodies (MAbs) provide scope for the development of better therapeutics and diagnostic tools. Herein, we describe the binding and neutralization profile(s) for a panel of murine MAbs generated against influenza A H1N1 viruses elicited by immunization with pandemic H1 recombinant hemagglutinin (rHA)/whole virus or seasonal H1 rHA. Neutralizing MAbs, MA-2070 and MA-M, were obtained after pandemic A/California/07/2009 (H1N1) virus/rHA immunization(s). Both MAbs reacted specifically with rHA from A/California/07/2009 and A/England/195/2009 in ELISA. MA-2070 bound rHA of A/California/07/2009 with high affinity (KD = 51.36 ± 9.20 nM) and exhibited potent in vitro neutralization (IC50 = 2.50 μg/mL). MA-2070 bound within the stem domain of HA. MA-M exhibited both hemagglutination inhibition (HI, 1.50 μg/mL) and in vitro neutralization (IC50 = 0.66 μg/mL) activity against the pandemic A/California/07/2009 virus and showed higher binding affinity (KD = 9.80 ± 0.67 nM) than MA-2070. MAb, MA-H generated against the seasonal A/Solomon Islands/03/2006 (H1N1) rHA binds within the head domain and bound the seasonal H1N1 (A/Solomon Islands/03/2006 and A/New Caledonia/20/1990) rHAs with high affinity (KD; 0.72-8.23 nM). MA-H showed high HI (2.50 μg/mL) and in vitro neutralization (IC50 = 2.61 μg/mL) activity against the A/Solomon Islands/03/2006 virus. All 3 MAbs failed to react in ELISA with rHA from various strains of H2N2, H3N2, H5N1, H7N9, and influenza virus B, suggesting their specificity for either pandemic or seasonal H1N1 influenza virus. The MAbs reported here may be useful in developing diagnostic assays.

Identification of Low- and High-Impact Hemagglutinin Amino Acid Substitutions That Drive Antigenic Drift of Influenza A(H1N1) Viruses

Determining phenotype from genetic data is a fundamental challenge. Identification of emerging antigenic variants among circulating influenza viruses is critical to the vaccine virus selection process, with vaccine effectiveness maximized when constituents are antigenically similar to circulating viruses. Hemagglutination inhibition (HI) assay data are commonly used to assess influenza antigenicity. Here, sequence and 3-D structural information of hemagglutinin (HA) glycoproteins were analyzed together with corresponding HI assay data for former seasonal influenza A(H1N1) virus isolates (1997–2009) and reference viruses. The models developed identify and quantify the impact of eighteen amino acid substitutions on the antigenicity of HA, two of which were responsible for major transitions in antigenic phenotype. We used reverse genetics to demonstrate the causal effect on antigenicity for a subset of these substitutions. Information on the impact of substitutions allowed us to predict antigenic phenotypes of emerging viruses directly from HA gene sequence data and accuracy was doubled by including all substitutions causing antigenic changes over a model incorporating only the substitutions with the largest impact. The ability to quantify the phenotypic impact of specific amino acid substitutions should help refine emerging techniques that predict the evolution of virus populations from one year to the next, leading to stronger theoretical foundations for selection of candidate vaccine viruses. These techniques have great potential to be extended to other antigenically variable pathogens.

Influenza A viruses are characterized by rapid antigenic drift: structural changes in B-cell epitopes that facilitate escape from pre-existing immunity. Consequently, seasonal influenza continues to impose a major burden on human health. Accurate quantification of the antigenic impact of specific amino acid substitutions is a pre-requisite for predicting the fitness and evolutionary outcome of variant viruses. Using assays to attribute antigenic variation to amino acid sequence changes we identify substitutions that contribute to antigenic drift and quantify their impact. We show that substitutions identified as low-impact are a critical component of virus antigenic evolution and by including these, as well as the high-impact substitutions often focused on, the accuracy of predicting antigenic phenotypes of emerging viruses from genotype is doubled.

Assessing Antigenic Drift of Seasonal Influenza A(H3N2) and A(H1N1)pdm09 Viruses

Under selective pressure from the host immune system, antigenic epitopes of influenza virus hemagglutinin (HA) have continually evolved to escape antibody recognition, termed antigenic drift. We analyzed the genomes of influenza A(H3N2) and A(H1N1)pdm09 virus strains circulating in Thailand between 2010 and 2014 and assessed how well the yearly vaccine strains recommended for the southern hemisphere matched them. We amplified and sequenced the HA gene of 120 A(H3N2) and 81 A(H1N1)pdm09 influenza virus samples obtained from respiratory specimens and calculated the perfect-match vaccine efficacy using the p_epitope model, which quantitated the antigenic drift in the dominant epitope of HA. Phylogenetic analysis of the A(H3N2) HA1 genes classified most strains into genetic clades 1, 3A, 3B, and 3C. The A(H3N2) strains from the 2013 and 2014 seasons showed very low to moderate vaccine efficacy and demonstrated antigenic drift from epitopes C and A to epitope B. Meanwhile, most A(H1N1)pdm09 strains from the 2012–2014 seasons belonged to genetic clades 6A, 6B, and 6C and displayed the dominant epitope mutations at epitopes B and E. Finally, the vaccine efficacy for A(H1N1)pdm09 (79.6–93.4%) was generally higher than that of A(H3N2). These findings further confirmed the accelerating antigenic drift of the circulating influenza A(H3N2) in recent years.

Coordinated Evolution of Influenza A Surface Proteins

The surface proteins hemagglutinin (HA) and neuraminidase (NA) of human influenza A virus evolve under selection pressures to escape adaptive immune responses and antiviral drug treatments. In addition to these external selection pressures, some mutations in HA are known to affect the adaptive landscape of NA, and vice versa, because these two proteins are physiologically interlinked. However, the extent to which evolution of one protein affects the evolution of the other one is unknown. Here we develop a novel phylogenetic method for detecting the signatures of such genetic interactions between mutations in different genes – that is, inter-gene epistasis. Using this method, we show that influenza surface proteins evolve in a coordinated way, with mutations in HA affecting subsequent spread of mutations in NA and vice versa, at many sites. Of particular interest is our finding that the oseltamivir-resistance mutations in NA in subtype H1N1 were likely facilitated by prior mutations in HA. Our results illustrate that the adaptive landscape of a viral protein is remarkably sensitive to its genomic context and, more generally, that the evolution of any single protein must be understood within the context of the entire evolving genome.

The fitness of an organism depends on the coordinated function of many genes. Thus, how a mutation in one gene affects fitness often depends on what mutations are present in other genes. This dependence is called “genetic interaction” or “epistasis”. The prevalence and type of such interactions are not well understood. Epistasis can be inferred from time-series sequencing data when a mutation in one gene is observed to facilitate the spread of a mutation in another gene. However, the situation is much more complicated when new combinations of genes are formed by processes such as recombination or reassortment. In such cases, deducing the time and order of genetic changes is difficult. Here, we devise a method to infer pairs of mutations in different genes which closely follow one another in the presence of reassortment. We apply it to evolution of two surface proteins of influenza A virus, hemagglutinin and neuraminidase, which are important targets for the human immune system and drugs. We show that mutations in one of these proteins are often facilitated by prior mutations, or compensated by subsequent mutations, in the other protein. In particular, drug-resistance mutations in neuraminidase were likely made possible by prior mutation in hemagglutinin. Knowledge of such interactions is necessary to fully understand and predict evolution.

Computational Identification of Antigenicity-Associated Sites in the Hemagglutinin Protein of A/H1N1 Seasonal Influenza Virus

The antigenic variability of influenza viruses has always made influenza vaccine development challenging. The punctuated nature of antigenic drift of influenza virus suggests that a relatively small number of genetic changes or combinations of genetic changes may drive changes in antigenic phenotype. The present study aimed to identify antigenicity-associated sites in the hemagglutinin protein of A/H1N1 seasonal influenza virus using computational approaches. Random Forest Regression (RFR) and Support Vector Regression based on Recursive Feature Elimination (SVR-RFE) were applied to H1N1 seasonal influenza viruses and used to analyze the associations between amino acid changes in the HA1 polypeptide and antigenic variation based on hemagglutination-inhibition (HI) assay data. Twenty-three and twenty antigenicity-associated sites were identified by RFR and SVR-RFE, respectively, by considering the joint effects of amino acid residues on antigenic drift. Our proposed approaches were further validated with the H3N2 dataset. The prediction models developed in this study can quantitatively predict antigenic differences with high prediction accuracy based only on HA1 sequences. Application of the study results can increase understanding of H1N1 seasonal influenza virus antigenic evolution and accelerate the selection of vaccine strains.

Diversifying Selection Analysis Predicts Antigenic Evolution of 2009 Pandemic H1N1 Influenza A Virus in Humans

Although a large number of immune epitopes have been identified in the influenza A virus (IAV) hemagglutinin (HA) protein using various experimental systems, it is unclear which are involved in protective immunity to natural infection in humans. We developed a data mining approach analyzing natural H1N1 human isolates to identify HA protein regions that may be targeted by the human immune system and can predict the evolution of IAV. We identified 16 amino acid sites experiencing diversifying selection during the evolution of prepandemic seasonal H1N1 strains and found that 11 sites were located in experimentally determined B-cell/antibody (Ab) epitopes, including three distinct neutralizing Caton epitopes: Sa, Sb, and Ca2 [A. J. Caton, G. G. Brownlee, J. W. Yewdell, and W. Gerhard, Cell 31:417-427, 1982, http://dx.doi.org/10.1016/0092-8674(82)90135-0]. We predicted that these diversified epitope regions would be the targets of mutation as the 2009 H1N1 pandemic (pH1N1) lineage evolves in response to the development of population-level protective immunity in humans. Using a chi-squared goodness-of-fit test, we identified 10 amino acid sites that significantly differed between the pH1N1 isolates and isolates from the recent 2012-2013 and 2013-2014 influenza seasons. Three of these sites were located in the same diversified B-cell/Ab epitope regions as identified in the analysis of prepandemic sequences, including Sa and Sb. As predicted, hemagglutination inhibition (HI) assays using human sera from subjects vaccinated with the initial pH1N1 isolate demonstrated reduced reactivity against 2013-2014 isolates. Taken together, these results suggest that diversifying selection analysis can identify key immune epitopes responsible for protective immunity to influenza virus in humans and thereby predict virus evolution.

IMPORTANCE

The WHO estimates that approximately 5 to 10% of adults and 20 to 30% of children in the world are infected by influenza virus each year. While an adaptive immune response helps eliminate the virus following acute infection, the virus rapidly evolves to evade the established protective memory immune response, thus allowing for the regular seasonal cycles of influenza virus infection. The analytical approach described here, which combines an analysis of diversifying selection with an integration of immune epitope data, has allowed us to identify antigenic regions that contribute to protective immunity and are therefore the key targets of immune evasion by the virus. This information can be used to determine when sequence variations in seasonal influenza virus strains have affected regions responsible for protective immunity in order to decide when new vaccine formulations are warranted.

Mutations associated with severity of the pandemic influenza A(H1N1)pdm09 in humans: a systematic review and meta-analysis of epidemiological evidence

Mutations in the haemagglutinin (HA), non-structural protein 1 (NS1) and polymerase basic protein 2 (PB2) of influenza viruses have been associated with virulence. This study investigated the association between mutations in these genes in influenza A(H1N1)pdm09 virus and the risk of severe or fatal disease. Searches were conducted on the MEDLINE, EMBASE and Web of Science electronic databases and the reference lists of published studies. The PRISMA and STROBE guidelines were followed in assessing the quality of studies and writing-up. Eighteen (18) studies, from all continents, were included in the systematic review (recruiting patients 0 - 77 years old). The mutation D222G was associated with a significant increase in severe disease (pooled RD: 11 %, 95 % CI: 3.0 % - 18.0 %, p = 0.004) and the risk of fatality (RD: 23 %, 95 % CI: 14.0 %-31.0 %, p = < 0.0001). No association was observed between the mutations HA-D222N, D222E, PB2-E627K and NS1-T123V and severe/fatal disease. The results suggest that no virus quasispecies bearing virulence-conferring mutations in the HA, PB2 and NS1 predominated. However issues of sampling bias, and bias due to uncontrolled confounders such as comorbidities, and viral and bacterial coinfection, should be born in mind. Influenza A viruses should continue to be monitored for the occurrence of virulence-conferring mutations in HA, PB2 and NS1. There are suggestions that respiratory virus coinfections also affect virus virulence. Studies investigating the role of genetic mutations on disease outcome should make efforts to also investigate the role of respiratory virus coinfections.

Influenza A H1N1 pandemic strain evolution--divergence and the potential for antigenic drift variants

The emergence of a novel A(H1N1) strain in 2009 was the first influenza pandemic of the genomic age, and unprecedented surveillance of the virus provides the opportunity to better understand the evolution of influenza. We examined changes in the nucleotide coding regions and the amino acid sequences of the hemagglutinin (HA), neuraminidase (NA), and nucleoprotein (NP) segments of the A(H1N1)pdm09 strain using publicly available data. We calculated the nucleotide and amino acid hamming distance from the vaccine strain A/California/07/2009 for each sequence. We also estimated Pepitope-a measure of antigenic diversity based on changes in the epitope regions-for each isolate. Finally, we compared our results to A(H3N2) strains collected over the same period. Our analysis found that the mean hamming distance for the HA protein of the A(H1N1)pdm09 strain increased from 3.6 (standard deviation [SD]: 1.3) in 2009 to 11.7 (SD: 1.0) in 2013, while the mean hamming distance in the coding region increased from 7.4 (SD: 2.2) in 2009 to 28.3 (SD: 2.1) in 2013. These trends are broadly similar to the rate of mutation in H3N2 over the same time period. However, in contrast to H3N2 strains, the rate of mutation accumulation has slowed in recent years. Our results are notable because, over the course of the study, mutation rates in H3N2 similar to that seen with A(H1N1)pdm09 led to the emergence of two antigenic drift variants. However, while there has been an H1N1 epidemic in North America this season, evidence to date indicates the vaccine is still effective, suggesting the epidemic is not due to the emergence of an antigenic drift variant. Our results suggest that more research is needed to understand how viral mutations are related to vaccine effectiveness so that future vaccine choices and development can be more predictive.

A predictive fitness model for influenza

The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.

Structural stability of influenza A(H1N1)pdm09 virus hemagglutinins

The noncovalent interactions that mediate trimerization of the influenza hemagglutinin (HA) are important determinants of its biological activities. Recent studies have demonstrated that mutations in the HA trimer interface affect the thermal and pH sensitivities of HA, suggesting a possible impact on vaccine stability (). We used size exclusion chromatography analysis of recombinant HA ectodomain to compare the differences among recombinant trimeric HA proteins from early 2009 pandemic H1N1 viruses, which dissociate to monomers, with those of more recent virus HAs that can be expressed as trimers. We analyzed differences among the HA sequences and identified intermolecular interactions mediated by the residue at position 374 (HA0 numbering) of the HA2 subdomain as critical for HA trimer stability. Crystallographic analyses of HA from the recent H1N1 virus A/Washington/5/2011 highlight the structural basis for this observed phenotype. It remains to be seen whether more recent viruses with this mutation will yield more stable vaccines in the future.

IMPORTANCE

Hemagglutinins from the early 2009 H1N1 pandemic viruses are unable to maintain a trimeric complex when expressed in a recombinant system. However, HAs from 2010 and 2011 strains are more stable, and our work highlights that the improvement in stability can be attributed to an E374K substitution in the HA2 subunit of the stalk that emerged naturally in the circulating viruses.

Amino acid sequence diversity of the major human papillomavirus capsid protein: implications for current and next generation vaccines

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We evaluated amino acid diversity of the major capsid protein of HPV.

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Residues displaying high entropy were found within surface-exposed domains.

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We discuss the implications of this diversity on the current and next generation HPV vaccines.

Despite the fidelity of host cell polymerases, the human papillomavirus (HPV) displays a degree of genomic polymorphism resulting in distinct genotypes and intra-type variants. The current HPV vaccines target the most prevalent genotypes associated with cervical cancer (HPV16/18) and genital warts (HPV6/11). Although these vaccines confer some measure of cross-protection, a multivalent HPV vaccine is in the pipeline that aims to broaden vaccine protection against other cervical cancer-associated genotypes including HPV31, HPV33, HPV45, HPV52 and HPV58. Both current and next generation vaccines comprise virus-like particles, based upon the major capsid protein, L1, and vaccine-induced, type-specific protection is likely mediated by neutralizing antibodies targeting L1 surface-exposed domains.

The aim of this study was to perform an in silico analysis of existing full length L1 sequences representing vaccine-relevant HPV genotypes in order to address the degree of naturally-occurring, intra-type polymorphisms. In total, 1281 sequences from the Americas, Africa, Asia and Europe were assembled. Intra-type entropy was low and/or limited to non-surface-exposed residues for HPV6, HPV11 and HPV52 suggesting a minimal effect on vaccine antibodies for these genotypes. For HPV16, intra-type entropy was high but the present analysis did not reveal any significant polymorphisms not previously identified. For HPV31, HPV33, HPV58, however, intra-type entropy was high, mostly mapped to surface-exposed domains and in some cases within known neutralizing antibody epitopes. For HPV18 and HPV45 there were too few sequences for a definitive analysis, but HPV45 displayed some degree of surface-exposed residue diversity. In most cases, the reference sequence for each genotype represented a minority variant and the consensus L1 sequences for HPV18, HPV31, HPV45 and HPV58 did not reflect the L1 sequence of the currently available HPV pseudoviruses. These data highlight a number of variant amino acid residues that warrant further investigation for vaccine and natural history studies of HPV.