Hemagglutinin sequence clusters and the antigenic evolution of influenza A virus

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.

Predicting the emergence of H3N2 influenza viruses reveals contrasted modes of evolution of HA and NA antigens

Vaccine design for rapidly changing viruses is based on empirical surveillance of strains circulating in a given season to assess those that will most likely spread during the next season. The choice of which strains to include in the vaccine is critical, as an erroneous decision can lead to a nonimmunized human population that will then be at risk in the face of an epidemic or, worse, a pandemic. Here, we present the first steps toward a very general phylogenetic approach to predict the emergence of novel viruses. Our genomic model builds upon natural features of viral evolution such as selection and recombination / reassortment, and incorporates episodic bursts of evolution and or of recombination. As a proof-of-concept, we assess the performance of this model in a retrospective study, focusing: (i) on the emergence of an unexpected H3N2 influenza strain in 2007, and (ii) on a longitudinal design. Based on the analysis of hemagglutinin (HA) and neuraminidase (NA) genes, our results show a lack of predictive power in both experimental designs, but shed light on the mode of evolution of these two antigens: (i) supporting the lack of significance of recombination in the evolution of this influenza virus, and (ii) showing that HA evolves episodically while NA changes gradually.

Genome-wide mutagenesis of influenza virus reveals unique plasticity of the hemagglutinin and NS1 proteins

The molecular basis for the diversity across influenza strains is poorly understood. To gain insight into this question, we mutagenized the viral genome and sequenced recoverable viruses. Only two small regions in the genome were enriched for insertions, the hemagglutinin head and the immune-modulatory nonstructural protein 1. These proteins play a major role in host adaptation, and thus need to be able to evolve rapidly. We propose a model in which certain influenza A virus proteins (or protein domains) exist as highly plastic scaffolds, which will readily accept mutations yet retain their functionality. This model implies that the ability to rapidly acquire mutations is an inherent aspect of influenza HA and nonstructural protein 1 proteins; further, this may explain why rapid antigenic drift and a broad host range is observed with influenza A virus and not with some other RNA viruses.

Modeling the global transmission of antiviral-resistant influenza viruses

BACKGROUND

The mutations that confer resistance to antiviral agents are thought to be detrimental, or at best neutral, to influenza virus fitness. The fact that resistant influenza strains can circulate and sometimes replace sensitive strains is of great public health concern.

OBJECTIVES

We used mathematical modeling to test various hypotheses about the transmission of antiviral-resistant influenza viruses by comparing the model's output with the observed rise in antiviral resistance of seasonal A(H1N1) influenza viruses between 2006 and 2009.

METHODS

We developed a mathematical model of the transmission of influenza among 321 cities around the globe. In the model, influenza strains resistant to antiviral agents competed with sensitive strains.

RESULTS AND CONCLUSIONS

We found that a resistant strain of influenza could not displace the sensitive strain as rapidly as has been observed unless it was more transmissible than the sensitive strain in the general population. We believe that an antiviral-resistant strain displaced the antiviral-sensitive seasonal A(H1N1) virus by hitchhiking on an escape mutation. Because of the complex global patterns of influenza circulation, tracking the emergence and spread of antiviral resistance must be a coordinated global effort.

Experimental challenge of chicken vaccinated with commercially available H5 vaccines reveals loss of protection to some highly pathogenic avian influenza H5N1 strains circulating in Hong Kong/China

Highly pathogenic avian influenza (HPAI) H5N1 virus continues to circulate in poultry in Asia and Africa posing a threat to both public and animal health. Vaccination, used as an adjunct to improved bio-security and stamping-out policies, contributed to protecting poultry in Hong Kong from HPAI H5N1 infection in 2004-2008 although the virus was repeatedly detected in dead wild birds. The detection of clade 2.3.4 H5N1 viruses in poultry markets and a farm in Hong Kong in 2008 raised the question whether this virus has changed to evade protection from the H5 vaccines in use. We tested the efficacy of three commercial vaccines (Nobilis, Poulvac and Harbin Re-5 vaccine) in specific pathogen free white leghorn chickens against a challenge with A/chicken/Hong Kong/8825-2/2008 (clade 2.3.4) isolated from vaccinated poultry in Hong Kong and A/chicken/Hong Kong/782/2009 (clade 2.3.2). Harbin Re5 vaccine provided the best, albeit not complete protection against challenge with the clade 2.3.4 virus. All three vaccines provided good protection from death and significantly reduced virus shedding following challenge with the clade 2.3.2 virus. Only Harbin Re-5 was able to completely protect chickens from virus shedding as well as mortality. Sera from vaccinated chickens had lower geometric hemagglutination inhibition titers against A/chicken/Hong Kong/8825-2/08, as compared to two other clade 2.3.4 and one clade 0 virus. Alignment of amino-acid sequences of the haemagglutinin of A/chicken/Hong Kong/8825-2/08 and the other H5 viruses revealed several mutations in positions including 69, 71, 83, 95, 133,140, 162, 183, 189, 194 and 270 (H5 numbering) which may correlate with loss of vaccine protection. Our results indicated that the tested HPAI H5N1 (2.3.4) virus has undergone antigenic changes that allow it to evade immunity from poultry vaccines. This highlights the need for continued surveillance and monitoring of vaccine induced immunity, with experimental vaccine challenge studies being done where indicated.

Matriptase proteolytically activates influenza virus and promotes multicycle replication in the human airway epithelium

Influenza viruses do not encode any proteases and must rely on host proteases for the proteolytic activation of their surface hemagglutinin proteins in order to fuse with the infected host cells. Recent progress in the understanding of human proteases responsible for influenza virus hemagglutinin activation has led to the identification of members of the type II transmembrane serine proteases TMPRSS2 and TMPRSS4 and human airway trypsin-like protease; however, none has proved to be the sole enzyme responsible for hemagglutinin cleavage. In this study, we identify and characterize matriptase as an influenza virus-activating protease capable of supporting multicycle viral replication in the human respiratory epithelium. Using confocal microscopy, we found matriptase to colocalize with hemagglutinin at the apical surface of human epithelial cells and within endosomes, and we showed that the soluble form of the protease was able to specifically cleave hemagglutinins from H1 virus, but not from H2 and H3 viruses, in a broad pH range. We showed that small interfering RNA (siRNA) knockdown of matriptase in human bronchial epithelial cells significantly blocked influenza virus replication in these cells. Lastly, we provide a selective, slow, tight-binding inhibitor of matriptase that significantly reduces viral replication (by 1.5 log) of H1N1 influenza virus, including the 2009 pandemic virus. Our study establishes a three-pronged model for the action of matriptase: activation of incoming viruses in the extracellular space in its shed form, upon viral attachment or exit in its membrane-bound and/or shed forms at the apical surface of epithelial cells, and within endosomes by its membrane-bound form where viral fusion takes place.

The antigenic evolution of influenza: drift or thrift?

It is commonly assumed that antibody responses against the influenza virus are polarized in the following manner: strong antibody responses are directed at highly variable antigenic epitopes, which consequently undergo 'antigenic drift', while weak antibody responses develop against conserved epitopes. As the highly variable epitopes are in a constant state of flux, current antibody-based vaccine strategies are focused on the conserved epitopes in the expectation that they will provide some level of clinical protection after appropriate boosting. Here, we use a theoretical model to suggest the existence of epitopes of low variability, which elicit a high degree of both clinical and transmission-blocking immunity. We show that several epidemiological features of influenza and its serological and molecular profiles are consistent with this model of 'antigenic thrift', and that identifying the protective epitopes of low variability predicted by this model could offer a more viable alternative to regularly update the influenza vaccine than exploiting responses to weakly immunogenic conserved regions.

Components of selection in the evolution of the influenza virus: linkage effects beat inherent selection

The influenza virus is an important human pathogen, with a rapid rate of evolution in the human population. The rate of homologous recombination within genes of influenza is essentially zero. As such, where two alleles within the same gene are in linkage disequilibrium, interference between alleles will occur, whereby selection acting upon one allele has an influence upon the frequency of the other. We here measured the relative importance of selection and interference effects upon the evolution of influenza. We considered time-resolved allele frequency data from the global evolutionary history of the haemagglutinin gene of human influenza A/H3N2, conducting an in-depth analysis of sequences collected since 1996. Using a model that accounts for selection-caused interference between alleles in linkage disequilibrium, we estimated the inherent selective benefit of individual polymorphisms in the viral population. These inherent selection coefficients were in turn used to calculate the total selective effect of interference acting upon each polymorphism, considering the effect of the initial background upon which a mutation arose, and the subsequent effect of interference from other alleles that were under selection. Viewing events in retrospect, we estimated the influence of each of these components in determining whether a mutant allele eventually fixed or died in the global viral population. Our inherent selection coefficients, when combined across different regions of the protein, were consistent with previous measurements of dN/dS for the same system. Alleles going on to fix in the global population tended to be under more positive selection, to arise on more beneficial backgrounds, and to avoid strong negative interference from other alleles under selection. However, on average, the fate of a polymorphism was determined more by the combined influence of interference effects than by its inherent selection coefficient.

Success in life is the product of many factors. Inherent ability often underlies great achievement. But other factors may play their part. The circumstances a child is born into may help or hinder his or her progress. Later events also have their effect; a life may be influenced by a lucky break, or an unforeseen disaster. In this work, we examine the factors underlying success for mutations in the HA gene of human influenza virus A/H3N2, defining success as the attainment of a high frequency in the global population. We examined the history of the gene from 1968 until 2010. For each observed mutation, a mathematical model was used to estimate the inherent benefit or disadvantage it conferred to the virus. We calculated the advantageousness or otherwise of the background upon which it arose, and the subsequent effect of interference from other mutations under selection. We found that successful mutations tended to have an advantageous background, and were subsequently fortunate in avoiding negative events throughout their lifetime. Beneficial mutations were more likely to be successful. But a mutation's chances of success were influenced more by circumstances of birth and subsequent events, than by its inherent effect on the virus.

Whole genome characterization, phylogenetic and genome signature analysis of human pandemic H1N1 virus in Thailand, 2009-2012

BACKGROUND

Three waves of human pandemic influenza occurred in Thailand in 2009-2012. The genome signature features and evolution of pH1N1 need to be characterized to elucidate the aspects responsible for the multiple waves of pandemic.

METHODOLOGY/FINDINGS

Forty whole genome sequences and 584 partial sequences of pH1N1 circulating in Thailand, divided into 1(st), 2(nd) and 3(rd) wave and post-pandemic were characterized and 77 genome signatures were analyzed. Phylogenetic trees of concatenated whole genome and HA gene sequences were constructed calculating substitution rate and d(N)/d(S) of each gene. Phylogenetic analysis showed a distinct pattern of pH1N1 circulation in Thailand, with the first two isolates from May, 2009 belonging to clade 5 while clades 5, 6 and 7 co-circulated during the first wave of pH1N1 pandemic in Thailand. Clade 8 predominated during the second wave and different proportions of the pH1N1 viruses circulating during the third wave and post pandemic period belonged to clades 8, 11.1 and 11.2. The mutation analysis of pH1N1 revealed many adaptive mutations which have become the signature of each clade and may be responsible for the multiple pandemic waves in Thailand, especially with regard to clades 11.1 and 11.2 as evidenced with V731I, G154D of PB1 gene, PA I330V, HA A214T S160G and S202T. The substitution rate of pH1N1 in Thailand ranged from 2.53×10(-3)±0.02 (M2 genes) to 5.27×10(-3)±0.03 per site per year (NA gene).

CONCLUSIONS

All results suggested that this virus is still adaptive, maybe to evade the host's immune response and tends to remain in the human host although the d(N)/d(S) were under purifying selection in all 8 genes. Due to the gradual evolution of pH1N1 in Thailand, continuous monitoring is essential for evaluation and surveillance to be prepared for and able to control future influenza activities.

Distinct effects on diversifying selection by two mechanisms of immunity against Streptococcus pneumoniae

Antigenic variation to evade host immunity has long been assumed to be a driving force of diversifying selection in pathogens. Colonization by Streptococcus pneumoniae, which is central to the organism's transmission and therefore evolution, is limited by two arms of the immune system: antibody- and T cell- mediated immunity. In particular, the effector activity of CD4⁺ T_H17 cell mediated immunity has been shown to act in trans, clearing co-colonizing pneumococci that do not bear the relevant antigen. It is thus unclear whether T_H17 cell immunity allows benefit of antigenic variation and contributes to diversifying selection. Here we show that antigen-specific CD4⁺ T_H17 cell immunity almost equally reduces colonization by both an antigen-positive strain and a co-colonized, antigen-negative strain in a mouse model of pneumococcal carriage, thus potentially minimizing the advantage of escape from this type of immunity. Using a proteomic screening approach, we identified a list of candidate human CD4⁺ T_H17 cell antigens. Using this list and a previously published list of pneumococcal Antibody antigens, we bioinformatically assessed the signals of diversifying selection among the identified antigens compared to non-antigens. We found that Antibody antigen genes were significantly more likely to be under diversifying selection than the T_H17 cell antigen genes, which were indistinguishable from non-antigens. Within the Antibody antigens, epitopes recognized by human antibodies showed stronger evidence of diversifying selection. Taken together, the data suggest that T_H17 cell-mediated immunity, one form of T cell immunity that is important to limit carriage of antigen-positive pneumococcus, favors little diversifying selection in the targeted antigen. The results could provide new insight into pneumococcal vaccine design.

Streptococcus pneumoniae, or pneumococcus, is a leading cause of morbidity and mortality in young children and elderly persons worldwide. Current pneumococcus vaccines target a limited number of clinically important serotypes, while strains with serotypes not targeted by current vaccines are increasing in importance in both carriage and invasive disease. As a result, there has been a substantial interest to develop novel, cost-effective vaccines based on protein antigens from pneumococcus. To this end, it is critical to understand how the human immune system exerts selection pressures on the targeted antigens. Two immune mechanisms targeting pneumococcal protein antigens have been documented, mediated by antibody and T cells, respectively. In this study, we screened for pneumococcal antigens that are commonly recognized by human CD4⁺ T_H17 cells. Using a mouse model of pneumococcal colonization, we demonstrate that T_H17 cell-based immunity almost equally reduces colonization by both an antigen-positive strain and a co-colonizing, antigen-negative strain. Furthermore, we demonstrate that the DNA sequences of T_H17 cell antigens demonstrate no detectable signs of being under selective pressure, unlike pneumococcal antigens known to be strong antibody targets. Thus, one form of the T cell-mediated immunity that is important to limit carriage of antigen-positive pneumococcus favors little diversifying selection in the targeted antigen. These results suggest evolution of escape from T_H17 -based vaccines may be slower than from antibody-based vaccines.

N-linked glycosylation in the hemagglutinin of influenza A viruses

Since the 1918 influenza A virus (IAV) pandemic, H1N1 viruses have circulated in human populations. The hemagglutinin (HA) of IAV determines viral antigenicity and often undergoes N-linked glycosylation (NLG) at several sites. Interestingly, structural analysis of the 1918 and 2009 H1N1 pandemic viruses revealed antigenic similarities attributable to the conserved epitopes and the NLG statuses of their HA proteins. NLG of the globular head of HA is known to modulate the antigenicity, fusion activity, virulence, receptor-binding specificity, and immune evasion of IAV. In addition, the HA of IAV often retains additional mutations. These supplemental mutations compensate for the attenuation of viral properties resulting from the introduced NLG. In human H1N1 viruses, the number and location of NLG sites has been regulated in accordance with the antigenic variability of the NLG-targeted antibody-binding site. The relationship between the NLG and the antigenic variance in HA appears to be stably controlled in the viral context.

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

The antigenic sites of hemagglutinin (HA) are crucial for understanding antigenic drift and vaccine strain selection for influenza viruses. In 1982, 32 epitope residues (called laboratory epitope residues) were proposed for antigenic sites of H1N1 HA based on the monoclonal antibody-selected variants. Interestingly, these laboratory epitope residues only cover 28% (23/83) mutation positions for 9 H1N1 vaccine strain comparisons (from 1977 to 2009). Here, we propose the entropy and likelihood ratio to model amino acid diversity and antigenic variant score for inferring 41 H1N1 HA epitope residues (called natural epitope residues) with statistically significant scores according to 1572 HA sequences and 197 pairs of HA sequences with hemagglutination inhibition (HI) assays of natural isolates. By combining both natural and laboratory epitope residues, we identified 62 (11 overlapped) residues clustered into five antigenic sites (i.e., A-E) which are highly correlated to the antigenic sites of H3N2 HA. Our method recognizes sites A, B and C as critical sites for escaping from neutralizing antibodies in H1N1 virus. Experimental results show that the accuracies of our models are 81.2% and 82.2% using 41 and 62 epitope residues, respectively, for predicting antigenic variants on 197 paring HA sequences. In addition, our model can detect the emergence of epidemic strains and reflect the genetic diversity and antigenic variant between the vaccine and circulating strains. Finally, our model is theoretically consistent with the evolution rates of H3N2 and H1N1 viruses and is often consistent to WHO vaccine strain selections. We believe that our models and the inferred antigenic sites of HA are useful for understanding the antigenic drift and evolution of influenza A H1N1 virus.

Clonal interference in the evolution of influenza

The seasonal influenza A virus undergoes rapid evolution to escape human immune response. Adaptive changes occur primarily in antigenic epitopes, the antibody-binding domains of the viral hemagglutinin. This process involves recurrent selective sweeps, in which clusters of simultaneous nucleotide fixations in the hemagglutinin coding sequence are observed about every 4 years. Here, we show that influenza A (H3N2) evolves by strong clonal interference. This mode of evolution is a red queen race between viral strains with different beneficial mutations. Clonal interference explains and quantifies the observed sweep pattern: we find an average of at least one strongly beneficial amino acid substitution per year, and a given selective sweep has three to four driving mutations on average. The inference of selection and clonal interference is based on frequency time series of single-nucleotide polymorphisms, which are obtained from a sample of influenza genome sequences over 39 years. Our results imply that mode and speed of influenza evolution are governed not only by positive selection within, but also by background selection outside antigenic epitopes: immune adaptation and conservation of other viral functions interfere with each other. Hence, adapting viral proteins are predicted to be particularly brittle. We conclude that a quantitative understanding of influenza's evolutionary and epidemiological dynamics must be based on all genomic domains and functions coupled by clonal interference.

Genomic analysis of 16 Colorado human NL63 coronaviruses identifies a new genotype, high sequence diversity in the N-terminal domain of the spike gene and evidence of recombination

This study compared the complete genome sequences of 16 NL63 strain human coronaviruses (hCoVs) from respiratory specimens of paediatric patients with respiratory disease in Colorado, USA, and characterized the epidemiology and clinical characteristics associated with circulating NL63 viruses over a 3-year period. From 1 January 2009 to 31 December 2011, 92 of 9380 respiratory specimens were found to be positive for NL63 RNA by PCR, an overall prevalence of 1 %. NL63 viruses were circulating during all 3 years, but there was considerable yearly variation in prevalence and the month of peak incidence. Phylogenetic analysis comparing the genome sequences of the 16 Colorado NL63 viruses with those of the prototypical hCoV-NL63 and three other NL63 viruses from the Netherlands demonstrated that there were three genotypes (A, B and C) circulating in Colorado from 2005 to 2010, and evidence of recombination between virus strains was found. Genotypes B and C co-circulated in Colorado in 2005, 2009 and 2010, but genotype A circulated only in 2005 when it was the predominant NL63 strain. Genotype C represents a new lineage that has not been described previously. The greatest variability in the NL63 virus genomes was found in the N-terminal domain (NTD) of the spike gene (nt 1-600, aa 1-200). Ten different amino acid sequences were found in the NTD of the spike protein among these NL63 strains and the 75 partial published sequences of NTDs from strains found at different times throughout the world.

Evolutionary history and phylodynamics of influenza A and B neuraminidase (NA) genes inferred from large-scale sequence analyses

Background

Influenza neuraminidase (NA) is an important surface glycoprotein and plays a vital role in viral replication and drug development. The NA is found in influenza A and B viruses, with nine subtypes classified in influenza A. The complete knowledge of influenza NA evolutionary history and phylodynamics, although critical for the prevention and control of influenza epidemics and pandemics, remains lacking.

Methodology/Principal findings

Evolutionary and phylogenetic analyses of influenza NA sequences using Maximum Likelihood and Bayesian MCMC methods demonstrated that the divergence of influenza viruses into types A and B occurred earlier than the divergence of influenza A NA subtypes. Twenty-three lineages were identified within influenza A, two lineages were classified within influenza B, and most lineages were specific to host, subtype or geographical location. Interestingly, evolutionary rates vary not only among lineages but also among branches within lineages. The estimated tMRCAs of influenza lineages suggest that the viruses of different lineages emerge several months or even years before their initial detection. The d_N/d_S ratios ranged from 0.062 to 0.313 for influenza A lineages, and 0.257 to 0.259 for influenza B lineages. Structural analyses revealed that all positively selected sites are at the surface of the NA protein, with a number of sites found to be important for host antibody and drug binding.

Conclusions/Significance

The divergence into influenza type A and B from a putative ancestral NA was followed by the divergence of type A into nine NA subtypes, of which 23 lineages subsequently diverged. This study provides a better understanding of influenza NA lineages and their evolutionary dynamics, which may facilitate early detection of newly emerging influenza viruses and thus improve influenza surveillance.

Reactivity of human convalescent sera with influenza virus hemagglutinin protein mutants at antigenic site A

How the antibodies of individual convalescent human sera bind to each amino acid residue at the antigenic sites of hemagglutinin (HA) of influenza viruses, and how the antigenic drift strains of influenza viruses are selected by human sera, is not well understood. In our previous study, it was found by a binding assay with a chimeric HA between A/Kamata/14/91 (Ka/91) and A/Aichi/2/68 that convalescent human sera, following Ka/91 like (H3N2) virus infection, bind to antigenic site A of Ka/91 HA. Here using chimeric HAs possessing single amino acid substitutions at site A, it was determined how those human sera recognize each amino acid residue at antigenic site A. It was found that the capacity of human sera to recognize amino acid substitutions at site A differs from one person to another and that some amino acid substitutions result in all convalescent human sera losing their binding capacity. Among these amino acid substitutions, certain ones might be selected by chance, thus creating successive antigenic drift. Phylogenetic analysis of the drift strains of Ka/91 showed amino acid substitutions at positions 133, 135 and 145 were on the main stream of the phylogenetic tree. Indeed, all of the investigated convalescent sera failed to recognize one of them.

Inference of genotype-phenotype relationships in the antigenic evolution of human influenza A (H3N2) viruses

Distinguishing mutations that determine an organism's phenotype from (near-) neutral ‘hitchhikers’ is a fundamental challenge in genome research, and is relevant for numerous medical and biotechnological applications. For human influenza viruses, recognizing changes in the antigenic phenotype and a strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We have developed a method for inferring ‘antigenic trees’ for the major viral surface protein hemagglutinin. In the antigenic tree, antigenic weights are assigned to all tree branches, which allows us to resolve the antigenic impact of the associated amino acid changes. Our technique predicted antigenic distances with comparable accuracy to antigenic cartography. Additionally, it identified both known and novel sites, and amino acid changes with antigenic impact in the evolution of influenza A (H3N2) viruses from 1968 to 2003. The technique can also be applied for inference of ‘phenotype trees’ and genotype–phenotype relationships from other types of pairwise phenotype distances.

The molecular evolution of any organism is described by changes in the genotype resulting from genetic drift or selection to maintain or establish fitness under the given environmental conditions. Identification of phenotype-defining changes and their distinction from (near-) neutral (‘hitchhikers’) ones is a fundamental challenge in genome research. The standard approach involves time- and cost-intensive mutation experiments, which are typically low throughput, due to their experimental nature. We have developed a computational method for the inference of phenotypic impact of genotypic changes that is applicable to any system, within or across species, where homologous genetic sequences and associated pairwise phenotype distances are available. We demonstrate the accuracy of our method by application to the human influenza A (H3N2) virus. This exemplary system is of particular interest, as recognizing changes in the antigenic phenotype and a viral strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We accurately identified known sites and amino acid changes with antigenic impact over 35 years of evolution, and provide further details on individual antigenically relevant changes in the evolution of influenza A (H3N2) viruses.

Real time forecasting of near-future evolution

A metaphor for adaptation that informs much evolutionary thinking today is that of mountain climbing, where horizontal displacement represents change in genotype, and vertical displacement represents change in fitness. If it were known a priori what the 'fitness landscape' looked like, that is, how the myriad possible genotypes mapped onto fitness, then the possible paths up the fitness mountain could each be assigned a probability, thus providing a dynamical theory with long-term predictive power. Such detailed genotype-fitness data, however, are rarely available and are subject to change with each change in the organism or in the environment. Here, we take a very different approach that depends only on fitness or phenotype-fitness data obtained in real time and requires no a priori information about the fitness landscape. Our general statistical model of adaptive evolution builds on classical theory and gives reasonable predictions of fitness and phenotype evolution many generations into the future.

Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation

One of the primary efforts in influenza vaccine strain recommendation is to monitor through gene sequencing the viral surface protein haemagglutinin (HA) variants that lead to viral antigenic changes. Here we have developed a computational method, denoted as PREDAC, to predict antigenic clusters of influenza A (H3N2) viruses with high accuracy from viral HA sequences. Application of PREDAC to large-scale HA sequence data of H3N2 viruses isolated from diverse regions of Mainland China identified 17 antigenic clusters that have dominated for at least one season between 1968 and 2010. By tracking the dynamics of the dominant antigenic clusters, we not only find that dominant antigenic clusters change more frequently in China than in the United States/Europe, but also characterize the antigenic patterns of seasonal H3N2 viruses within China. Furthermore, we demonstrate that the coupling of large-scale HA sequencing with PREDAC can significantly improve vaccine strain recommendation for China.

Correlation of polymerase replication fidelity with genetic evolution of influenza A/Fujian/411/02(H3N2) viruses

Influenza virus evolves continuously through mutations presumed to result from evolutionary pressure driving viral replication. This study examined the relationship between the genetic evolution and replication fidelity of influenza viruses. Analysis of influenza sequences from National Centre for Biotechnology Information (NCBI) database revealed a gradual decrease in the rate of genetic evolution of A/Fujian/411/02(H3N2)-like variants after the emergence and predominance of the A/H3N2 Fujian strain in 2002. This decrease may be related to an increase in replication fidelity, which was investigated by assessing mutation frequencies of reassortant viruses carrying the PB1 segment of Fujian variants isolated between 2003 and 2005 in a sequencing-based plaque assay. The data revealed a threefold decrease in substitution per site of the reassortant viruses carrying the Fujian PB1 segments isolated in 2004-2005 compared with those circulating in 2003. The decrease in mutation frequency paralleled a decrease in genetic evolution of the Fujian variants from the NCBI database. This correlation implicates changes in the polymerase replication fidelity as contributing to altered genetic evolution of influenza viruses.

Rohlin distance and the evolution of influenza A virus: weak attractors and precursors

The evolution of the hemagglutinin amino acids sequences of Influenza A virus is studied by a method based on an informational metrics, originally introduced by Rohlin for partitions in abstract probability spaces. This metrics does not require any previous functional or syntactic knowledge about the sequences and it is sensitive to the correlated variations in the characters disposition. Its efficiency is improved by algorithmic tools, designed to enhance the detection of the novelty and to reduce the noise of useless mutations. We focus on the USA data from 1993/94 to 2010/2011 for A/H3N2 and on USA data from 2006/07 to 2010/2011 for A/H1N1. We show that the clusterization of the distance matrix gives strong evidence to a structure of domains in the sequence space, acting as weak attractors for the evolution, in very good agreement with the epidemiological history of the virus. The structure proves very robust with respect to the variations of the clusterization parameters, and extremely coherent when restricting the observation window. The results suggest an efficient strategy in the vaccine forecast, based on the presence of "precursors" (or "buds") populating the most recent attractor.

Inhibition of influenza virus replication by constrained peptides targeting nucleoprotein

BACKGROUND

Because of high mutation rates, new drug-resistant viruses are rapidly evolving, thus making the necessary control of influenza virus infection difficult.

METHODS

We screened a constrained cysteine-rich peptide library mimicking μ-conotoxins from Conus geographus and a proline-rich peptide library mimicking lebocin 1 and 2 from Bombyx mori by using influenza virus RNA polymerase (PB1, PB2 and PA) and nucleoprotein (NP) as baits.

RESULTS

Among the 22 peptides selected from the libraries, we found that the NP-binding proline-rich peptide, PPWCCCSPMKRASPPPAQSDLPATPKCPP, inhibited influenza replicon activity to mean±sd 40.7%±15.8% when expressed as a GFP fusion peptide in replicon cells. Moreover, when the GFP fusion peptide was transduced into cells by an HIV-TAT protein transduction domain sequence, the replication of influenza virus A/WSN/33 (WSN) at a multiplicity of infection of 0.01 was inhibited to 20% and 69% at 12 and 24 h post-infection, respectively. In addition, the TAT-GFP fusion peptide was able to slightly protect Balb/c mice from WSN infection when administrated prior to the infection.

CONCLUSIONS

These results suggest the potential of this peptide as the seed of an anti-influenza drug and reveal the usefulness of the constrained peptide strategy for generating inhibitors of influenza infection. The results also suggest that influenza NP, which is conserved among the influenza A viruses, is a good target for influenza inhibition, despite being the most abundant protein in infected cells.

Patterns of predicted T-cell epitopes associated with antigenic drift in influenza H3N2 hemagglutinin

Antigenic drift allowing escape from neutralizing antibodies is an important feature of transmission and survival of influenza viruses in host populations. Antigenic drift has been studied in particular detail for influenza A H3N2 and well defined antigenic clusters of this virus documented. We examine how host immunogenetics contributes to determination of the antibody spectrum, and hence the immune pressure bringing about antigenic drift. Using uTOPE™ bioinformatics analysis of predicted MHC binding, based on amino acid physical property principal components, we examined the binding affinity of all 9-mer and 15-mer peptides within the hemagglutinin 1 (HA1) of 447 H3N2 virus isolates to 35 MHC-I and 14 MHC-II alleles. We provide a comprehensive map of predicted MHC-I and MHC-II binding affinity for a broad array of HLA alleles for the H3N2 influenza HA1 protein. Each HLA allele exhibited a characteristic predicted binding pattern. Cluster analysis for each HLA allele shows that patterns based on predicted MHC binding mirror those described based on antibody binding. A single amino acid mutation or position displacement can result in a marked difference in MHC binding and hence potential T-helper function. We assessed the impact of individual amino acid changes in HA1 sequences between 10 virus isolates from 1968-2002, representative of antigenic clusters, to understand the changes in MHC binding over time. Gain and loss of predicted high affinity MHC-II binding sites with cluster transitions were documented. Predicted high affinity MHC-II binding sites were adjacent to antibody binding sites. We conclude that host MHC diversity may have a major determinant role in the antigenic drift of influenza A H3N2.

Gnarled-trunk evolutionary model of influenza A virus hemagglutinin

Human influenza A viruses undergo antigenic changes with gradual accumulation of amino acid substitutions on the hemagglutinin (HA) molecule. A strong antigenic mismatch between vaccine and epidemic strains often requires the replacement of influenza vaccines worldwide. To establish a practical model enabling us to predict the future direction of the influenza virus evolution, relative distances of amino acid sequences among past epidemic strains were analyzed by multidimensional scaling (MDS). We found that human influenza viruses have evolved along a gnarled evolutionary pathway with an approximately constant curvature in the MDS-constructed 3D space. The gnarled pathway indicated that evolution on the trunk favored multiple substitutions at the same amino acid positions on HA. The constant curvature was reasonably explained by assuming that the rate of amino acid substitutions varied from one position to another according to a gamma distribution. Furthermore, we utilized the estimated parameters of the gamma distribution to predict the amino acid substitutions on HA in subsequent years. Retrospective prediction tests for 12 years from 1997 to 2009 showed that 70% of actual amino acid substitutions were correctly predicted, and that 45% of predicted amino acid substitutions have been actually observed. Although it remains unsolved how to predict the exact timing of antigenic changes, the present results suggest that our model may have the potential to recognize emerging epidemic strains.

[Bioinformatics technologies for the analysis of antigenic evolution of influenza viruses]

Human influenza viruses mutate from time to time, causing annual epidemics worldwide. The strong immune pressure in the human population selects a new variant every year, and the antigenic change is one of the primary reasons why vaccination is not a perfect measure to control seasonal influenza. Thus prediction of antigenic change of influenza A virus has been one of the major public health goals. In this review bioinformatics technologies that have been developed to achieve this goal were summarized.

The global spread of drug-resistant influenza

Resistance to oseltamivir, the most widely used influenza antiviral drug, spread to fixation in seasonal influenza A(H1N1) between 2006 and 2009. This sudden rise in resistance seemed puzzling given the low overall level of the oseltamivir usage and the lack of a correlation between local rates of resistance and oseltamivir usage. We used a stochastic simulation model and deterministic approximations to examine how such events can occur, and in particular to determine how the rate of fixation of the resistant strain depends both on its fitness in untreated hosts as well as the frequency of antiviral treatment. We found that, for the levels of antiviral usage in the population, the resistant strain will eventually spread to fixation, if it is not attenuated in transmissibility relative to the drug-sensitive strain, but not at the speed observed in seasonal H1N1. The extreme speed with which the resistance spread in seasonal H1N1 suggests that the resistant strain had a transmission advantage in untreated hosts, and this could have arisen from genetic hitchhiking, or from the mutations responsible for resistance and compensation. Importantly, our model also shows that resistant virus will fail to spread if it is even slightly less transmissible than its sensitive counterpart--a finding of relevance given that resistant pandemic influenza (H1N1) 2009 may currently suffer from a small, but nonetheless experimentally perceptible reduction in transmissibility.

Evolutionary dynamics of influenza A nucleoprotein (NP) lineages revealed by large-scale sequence analyses

Influenza A viral nucleoprotein (NP) plays a critical role in virus replication and host adaptation, however, the underlying molecular evolutionary dynamics of NP lineages are less well-understood. In this study, large-scale analyses of 5094 NP nucleotide sequences revealed eight distinct evolutionary lineages, including three host-specific lineages (human, classical swine and equine), two cross-host lineages (Eurasian avian-like swine and swine-origin human pandemic H1N1 2009) and three geographically isolated avian lineages (Eurasian, North American and Oceanian). The average nucleotide substitution rate of the NP lineages was estimated to be 2.4 × 10(-3) substitutions per site per year, with the highest value observed in pandemic H1N1 2009 (3.4 × 10(-3)) and the lowest in equine (0.9 × 10(-3)). The estimated time of most recent common ancestor (TMRCA) for each lineage demonstrated that the earliest human lineage was derived around 1906, and the latest pandemic H1N1 2009 lineage dated back to December 17, 2008. A marked time gap was found between the times when the viruses emerged and were first sampled, suggesting the crucial role for long-term surveillance of newly emerging viruses. The selection analyses showed that human lineage had six positive selection sites, whereas pandemic H1N1 2009, classical swine, Eurasian avian and Eurasian swine had only one or two sites. Protein structure analyses revealed several positive selection sites located in epitope regions or host adaptation regions, indicating strong adaptation to host immune system pressures in influenza viruses. Along with previous studies, this study provides new insights into the evolutionary dynamics of influenza A NP lineages. Further lineage analyses of other gene segments will allow better understanding of influenza A virus evolution and assist in the improvement of global influenza surveillance.

Molecular basis of antigenic drift in Influenza A/H3N2 strains (1968-2007) in the light of antigenantibody interactions

The emergence of new strains of Influenza virus have caused several pandemics over the last hundred years with the latest being the H1N1 Swine flu pandemic of 2009. The Hemagglutinin (HA) protein of the Influenza virus is the primary target of human immune system and is responsible for generation of protective antibodies in humans. Mutations in this protein results in change in antigenic regions (antigenic drift) which consequently leads to loss of immunity in hosts even in vaccinated population (herd immunity). This necessitates periodic changes in the Influenza vaccine composition. In this paper, we investigate the molecular basis of the reported loss of herd immunity in vaccinated population (vaccine component: Influenza A/X-31/1968 (H3N2)) which resulted in the outbreak due to strain Influenza A/Port Chalmers/1/1973 (H3N2). Also, the effects of antigenic drift in HA protein (H3N2 vaccine strains 1968-2007) on the 3D structures as well as interactions with BH151, a 1968 antibody, has been studied. Rigid body molecular docking protocol has been used to study the antigen-antibody interactions. We believe that the present study will help in better understanding of host-pathogen interactions at the molecular level.

Partial immunity and vaccination for influenza

In this article, we estimated the basic reproductive numbers by mathematical modeling and computer simulation using the hospitalization data of influenza type A (H3N2) from the United States as provided by the Centers for Disease Control and Prevention (CDC) from the 2001 to 2006 influenza seasons, respectively. The mean value of basic reproductive number from the 2001-2002 to 2005-2006 influenza seasons is 1.2440, with a 95% confidence interval of 1.1170-1.3710. Our model predicts that the proportion of vaccination of susceptible is 20% and 60 million doses of vaccines should be prepared for each influenza season in the United States. The chi-square test of goodness of fit indicates that our model fits the data reasonably well.

MEM spectral analysis for predicting influenza epidemics in Japan

OBJECTIVES

The prediction of influenza epidemics has long been the focus of attention in epidemiology and mathematical biology. In this study, we tested whether time series analysis was useful for predicting the incidence of influenza in Japan.

METHODS

The method of time series analysis we used consists of spectral analysis based on the maximum entropy method (MEM) in the frequency domain and the nonlinear least squares method in the time domain. Using this time series analysis, we analyzed the incidence data of influenza in Japan from January 1948 to December 1998; these data are unique in that they covered the periods of pandemics in Japan in 1957, 1968, and 1977.

RESULTS

On the basis of the MEM spectral analysis, we identified the periodic modes explaining the underlying variations of the incidence data. The optimum least squares fitting (LSF) curve calculated with the periodic modes reproduced the underlying variation of the incidence data. An extension of the LSF curve could be used to predict the incidence of influenza quantitatively.

CONCLUSIONS

Our study suggested that MEM spectral analysis would allow us to model temporal variations of influenza epidemics with multiple periodic modes much more effectively than by using the method of conventional time series analysis, which has been used previously to investigate the behavior of temporal variations in influenza data.

Evolutionary genomics of the pandemic 2009 H1N1 influenza viruses (pH1N 1v)

Background

A new strain of human H1N1 influenza A viruses was broken out in the April 2009 and caused worldwide pandemic emergency. The present study is trying to estimate a temporal reassortment history of 2009 H1N1 viruses by phylogenetic analysis based on a total 394 sequences of H1N1viruses isolated from swine, human and avian.

Results

Phylogenetic trees of eight gene segments showed that viruses sampled from human formed a well-supported clade, whereas swine and avian lineages were intermixed together. A new divergence swine sublineage containing gene segments of 2009 H1N1 viruses was characterized, which were closely related with swine viruses collected from USA and South Korea during 2004 to 2007 in six segments (PB2, PB1, PA, HA, NP and NS), and to swine viruses isolated from Thailand during 2004 to 2005 in NA and M. Substitution rates were varied drastically among eight segments and the average substitution rate was generally higher in 2009 H1N1 than in swine and human viruses (F_2,23 = 5.972, P < 0.01). Similarly, higher d_N/d_S substitution ratios were identified in 2009 H1N1 than in swine and human viruses except M2 gene (F_{2, 25} = 3.779, P < 0.05). The ages of 2009 H1N1 viruses were estimated around 0.1 to 0.5 year, while their common ancestors with closest related swine viruses existed between 9.3 and 17.37 years ago.

Conclusion

Our results implied that at least four reassortments or transmissions probably occurred before 2009 H1N1 viruses. Initial reassortment arose in 1976 and avian-like Eurasian swine viruses emerged. The second transmission happened in Asia and North America between 1988 and 1992, and mostly influenced six segments (PB2, PB1, PA, HA, NP and NS). The third reassortment occurred between North American swine and avian viruses during 1998 to 2000, which involved PB2 and PA segments. Recent reassortments occurred among avian-to-swine reassortant, Eurasian and classical swine viruses during 2004 to 2005. South Korea, Thailand and USA, were identified as locations where reassortments most likely happened. The co-circulation of multiple swine sublineages and special lifestyle in Asia might have facilitated mixing of diverse influenza viruses, leading to generate a novel virus strain.

Quantifying selection and diversity in viruses by entropy methods, with application to the haemagglutinin of H3N2 influenza

Many viruses evolve rapidly. For example, haemagglutinin (HA) of the H3N2 influenza A virus evolves to escape antibody binding. This evolution of the H3N2 virus means that people who have previously been exposed to an influenza strain may be infected by a newly emerged virus. In this paper, we use Shannon entropy and relative entropy to measure the diversity and selection pressure by an antibody in each amino acid site of H3 HA between the 1992-1993 season and the 2009-2010 season. Shannon entropy and relative entropy are two independent state variables that we use to characterize H3N2 evolution. The entropy method estimates future H3N2 evolution and migration using currently available H3 HA sequences. First, we show that the rate of evolution increases with the virus diversity in the current season. The Shannon entropy of the sequence in the current season predicts relative entropy between sequences in the current season and those in the next season. Second, a global migration pattern of H3N2 is assembled by comparing the relative entropy flows of sequences sampled in China, Japan, the USA and Europe. We verify this entropy method by describing two aspects of historical H3N2 evolution. First, we identify 54 amino acid sites in HA that have evolved in the past to evade the immune system. Second, the entropy method shows that epitopes A and B on the top of HA evolve most vigorously to escape antibody binding. Our work provides a novel entropy-based method to predict and quantify future H3N2 evolution and to describe the evolutionary history of H3N2.

Prevalence of epistasis in the evolution of influenza A surface proteins

The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs.

Epistasis describes non-additive interactions among genetic sites: the consequence of a mutation at one site may depend on the status of the genome at other sites. In an extreme case, a mutation may have no effect if it arises on one genetic background, but a strong effect on another background. Epistatic mutations in viruses and bacteria that live under severe conditions, such as antibiotic treatments or immune pressure, often allow pathogens to develop drug resistance or escape the immune system. In this paper we develop a new phylogenetic method for detecting epistasis, and we apply this method to the surface proteins of the influenza A virus, which are important targets of the immune system and drug treatments. The authors identify and characterize hundreds of epistatic mutations in these proteins. Among those identified, we find the specific epistatic mutations that were recently shown, experimentally, to confer resistance to the drug Tamiflu. The results of this study may help to predict the course of influenza's antigenic evolution and to select more appropriate vaccines and drugs.

Changed epitopes drive the antigenic drift for influenza A (H3N2) viruses

Background

In circulating influenza viruses, gradually accumulated mutations on the glycoprotein hemagglutinin (HA), which interacts with infectivity-neutralizing antibodies, lead to the escape of immune system (called antigenic drift). The antibody recognition is highly correlated to the conformation change on the antigenic sites (epitopes), which locate on HA surface. To quantify a changed epitope for escaping from neutralizing antibodies is the basis for the antigenic drift and vaccine development.

Results

We have developed an epitope-based method to identify the antigenic drift of influenza A utilizing the conformation changes on epitopes. A changed epitope, an antigenic site on HA with an accumulated conformation change to escape from neutralizing antibody, can be considered as a "key feature" for representing the antigenic drift. According to hemagglutination inhibition (HI) assays and HA/antibody complex structures, we statistically measured the conformation change of an epitope by considering the number of critical position mutations with high genetic diversity and antigenic scores. Experimental results show that two critical position mutations can induce the conformation change of an epitope to escape from the antibody recognition. Among five epitopes of HA, epitopes A and B, which are near to the receptor binding site, play a key role for neutralizing antibodies. In addition, two changed epitopes often drive the antigenic drift and can explain the selections of 24 WHO vaccine strains.

Conclusions

Our method is able to quantify the changed epitopes on HA for predicting the antigenic variants and providing biological insights to the vaccine updates. We believe that our method is robust and useful for studying influenza virus evolution and vaccine development.

Influenza genome diversity and evolution

The influenza viruses contain highly variable genomes and are able to infect a wide range of host species. Large-scale sequencing projects have collected abundant influenza sequence data for assessing influenza genome diversity and evolution. This work reviews current influenza sequence databases characteristics and statistics, as well as recent studies utilizing these databases to unravel influenza virus diversity and evolution. Also discussed are the newest deep sequencing methods and their applications to influenza virus research.

New methods for analyzing serological data with applications to influenza surveillance

Please cite this paper as: Ndifon W. (2011) New methods for analyzing serological data with applications to influenza surveillance. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750‐2659.2010.00192.x.

Background  Two important challenges to the use of serological assays for influenza surveillance include the substantial amount of experimental effort involved and the inherent noisiness of serological data.

Results  I show that log‐transformed serological data exist in an effectively one‐dimensional space. I use this result, together with new mechanistic insights into serological assays, to develop computational methods for accurately and efficiently recovering unmeasured serological data from a sample of measured data, for systematically minimizing noise and other types of non‐antigenic variation found in the data, and for quantifying and visualizing antigenic variation. The methods can also be applied to data with effective dimensionality greater than one, under certain conditions.

Conclusion  Careful application of the methods developed here would enable the collection of better‐quality serological data on a greater number of circulating influenza viruses than is currently possible and improve the ability to identify potential epidemic and pandemic viruses before they become widespread. Although the focus here is on influenza surveillance, the described methods are more widely applicable.

Multiple outbreaks for the same pandemic: Local transportation and social distancing explain the different "waves" of A-H1N1pdm cases observed in México during 2009

Influenza outbreaks have been of relatively limited historical interest in Mexico. The 2009 influenza pandemic not only changed Mexico's health priorities but also brought to the forefront some of the strengths and weaknesses of Mexico's epidemiological surveillance and public health system. A year later, Mexico's data show an epidemic pattern characterized by three "waves''. The reasons this three-wave patterns are theoretically investigated via models that incorporate Mexico's general trends of land transportation, public health measures, and the regular opening and closing of schools during 2009. The role of vaccination is also studied taking into account delays in access and limitations in the total and daily numbers of vaccines available. The research in this article supports the view that the three epidemic "waves" are the result of the synergistic interactions of three factors: regional movement patterns of Mexicans, the impact and effectiveness of dramatic social distancing measures imposed during the first outbreak, and the summer release of school children followed by their subsequent return to classes in the fall. The three "waves" cannot be explained by the transportation patterns alone but only through the combination of transport patterns and changes in contact rates due to the use of explicit or scheduled social distancing measures. The research identifies possible vaccination schemes that account for the school calendar and whose effectiveness are enhanced by social distancing measures. The limited impact of the late arrival of the vaccine is also analyzed.

Modeling control strategies for concurrent epidemics of seasonal and pandemic H1N1 influenza

The lessons learned from the 2009-2010 H1N1 influenza pandemic, as it moves out of the limelight, should not be under-estimated, particularly since the probability of novel influenza epidemics in the near future is not negligible and the potential consequences might be huge. Hence, as the world, particularly the industrialized world, responded to the potentially devastating effects of this novel A-H1N1 strain with substantial resources, reminders of the recurrent loss of life from a well established foe, seasonal influenza, could not be ignored. The uncertainties associated with the reported and expected levels of morbidity and mortality with this novel A-H1N1 live in a backdrop of deaths, over 200,000 hospitalizations, and millions of infections (20% of the population) attributed to seasonal influenza in the USA alone, each year. So, as the Northern Hemisphere braced for the possibility of a potentially "lethal" second wave of the novel A-H1N1 without a vaccine ready to mitigate its impact, questions of who should be vaccinated first if a vaccine became available, came to the forefront of the discussion. Uncertainty grew as we learned that the vaccine, once available, would be unevenly distributed around the world. Nations capable of acquiring large vaccine supplies soon became aware that those who could pay would have to compete for a limited vaccine stockpile. The challenges faced by nations dealing jointly with seasonal and novel A-H1N1 co-circulating strains under limited resources, that is, those with no access to novel A-H1N1 vaccine supplies, limited access to the seasonal influenza vaccine, and limited access to antivirals (like Tamiflu) are explored in this study. One- and two-strain models are introduced to mimic the influenza dynamics of a single and co-circulating strains, in the context of a single epidemic outbreak. Optimal control theory is used to identify and evaluate the "best" control policies. The controls account for the cost associated with social distancing and antiviral treatment policies. The optimal policies identified might have, if implemented, a substantial impact on the novel H1N1 and seasonal influenza co-circulating dynamics. Specifically, the implementation of antiviral treatment might reduce the number of influenza cases by up to 60% under a reasonable seasonal vaccination strategy, but only by up to 37% when the seasonal vaccine is not available. Optimal social distancing policies alone can be as effective as the combination of multiple policies, reducing the total number of influenza cases by more than 99% within a single outbreak, an unrealistic but theoretically possible outcome for isolated populations with limited resources.

Low-dimensional clustering detects incipient dominant influenza strain clusters

Influenza has been circulating in the human population and has caused three pandemics in the last century (1918 H1N1, 1957 H2N2 and 1968 H3N2). The 2009 A(H1N1) was classified by World Health Organization as the fourth pandemic. Influenza has a high evolution rate, which makes vaccine design challenging. We here consider an approach for early detection of new dominant strains. By clustering the 2009 A(H1N1) sequence data, we found two main clusters. We then define a metric to detect the emergence of dominant strains. We show on historical H3N2 data that this method is able to identify a cluster around an incipient dominant strain before it becomes dominant. For example, for H3N2 as of 30 March 2009, the method detects the cluster for the new A/British Columbia/RV1222/2009 strain. This strain detection tool would appear to be useful for annual influenza vaccine selection.

Time series analysis of incidence data of influenza in Japan

Background

Much effort has been expended on interpreting the mechanism of influenza epidemics, so as to better predict them. In addition to the obvious annual cycle of influenza epidemics, longer-term incidence patterns are present. These so-called interepidemic periods have long been a focus of epidemiology. However, there has been less investigation of the interepidemic period of influenza epidemics. In the present study, we used spectral analysis of influenza morbidity records to indentify the interepidemic period of influenza epidemics in Japan.

Methods

We used time series data of the monthly incidence of influenza in Japan from January 1948 through December 1998. To evaluate the incidence data, we conducted maximum entropy method (MEM) spectral analysis, which is useful in investigating the periodicities of shorter time series, such as that of the incidence data used in the present study. We also conducted a segment time series analysis and obtained a 3-dimensional spectral array.

Results

Based on the results of power spectral density (PSD) obtained from MEM spectral analysis, we identified 3 periodic modes as the interepidemic periods of the incidence data. Segment time series analysis revealed that the amount of amplitude of the interepidemic periods increased during the occurrence of influenza pandemics and decreased when vaccine programs were introduced.

Conclusions

The findings suggest that the temporal behavior of the interepidemic periods of influenza epidemics is correlated with the magnitude of cross-reactive immune responses.

Proteotyping to establish the lineage of type A H1N1 and type B human influenza virus

The ability to establish the lineage of type A H1N1 and type B human influenza virus strains using a new proteotyping approach is demonstrated. Lineage-specific signature peptides have been determined for the hemagglutinin antigen of type A H1N1 and type B influenza viruses. The detection of these peptides alone within the high resolution mass spectra of whole antigen digests enables the lineage of the strain to be rapidly and unequivocally assigned. This proteotyping approach complements conventional PCR approaches and should aid in the monitoring of the evolution of the influenza virus in both humans and animals.

Allele dynamics plots for the study of evolutionary dynamics in viral populations

Phylodynamic techniques combine epidemiological and genetic information to analyze the evolutionary and spatiotemporal dynamics of rapidly evolving pathogens, such as influenza A or human immunodeficiency viruses. We introduce ‘allele dynamics plots’ (AD plots) as a method for visualizing the evolutionary dynamics of a gene in a population. Using AD plots, we propose how to identify the alleles that are likely to be subject to directional selection. We analyze the method’s merits with a detailed study of the evolutionary dynamics of seasonal influenza A viruses. AD plots for the major surface protein of seasonal influenza A (H3N2) and the 2009 swine-origin influenza A (H1N1) viruses show the succession of substitutions that became fixed in the evolution of the two viral populations. They also allow the early identification of those viral strains that later rise to predominance, which is important for the problem of vaccine strain selection. In summary, we describe a technique that reveals the evolutionary dynamics of a rapidly evolving population and allows us to identify alleles and associated genetic changes that might be under directional selection. The method can be applied for the study of influenza A viruses and other rapidly evolving species or viruses.

Neutralizing epitopes of influenza virus hemagglutinin: target for the development of a universal vaccine against H5N1 lineages

The nature of influenza virus to randomly mutate and evolve into new types with diverse antigenic determinants is an important challenge in the control of influenza infection. Particularly, variations within the amino acid sequences of major neutralizing epitopes of influenza virus hemagglutinin (HA) hindered the development of universal vaccines against H5N1 lineages. Based on distribution analyses of the identified major neutralizing epitopes of hemagglutinin, we selected three vaccine strains that cover the entire variants in the neutralizing epitopes among the H5N1 lineages. HA proteins of selected vaccine strains were expressed on the baculovirus surface (BacHA), and the preclinical efficacy of the vaccine formulations was evaluated in a mouse model. The combination of three selected vaccine strains could effectively neutralize viruses from clades 1, 2.1, 2.2, 4, 7, and 8 of influenza H5N1 viruses. In contrast, a vaccine formulation containing only adjuvanted monovalent BacHA (mono-BacHA) or a single strain of inactivated whole viral vaccine was able to neutralize only clade 1 (homologous), clade 2.1, and clade 8.0 viruses. Also, the trivalent BacHA vaccine was able to protect 100% of the mice against challenge with three different clades (clade 1.0, clade 2.1, and clade 7.0) of H5N1 strains compared to mono-BacHA or inactivated whole viral vaccine. The present findings provide a rationale for the development of a universal vaccine against H5N1 lineages. Furthermore, baculoviruses displaying HA will serve as an ideal choice for a vaccine in prepandemic or pandemic situations and expedite vaccine technology without the requirement of high-level-biocontainment facilities or tedious protein purification processes.

A two-tiered model for simulating the ecological and evolutionary dynamics of rapidly evolving viruses, with an application to influenza

Understanding the epidemiological and evolutionary dynamics of rapidly evolving pathogens is one of the most challenging problems facing disease ecologists today. To date, many mathematical and individual-based models have provided key insights into the factors that may regulate these dynamics. However, in many of these models, abstractions have been made to the simulated sequences that limit an effective interface with empirical data. This is especially the case for rapidly evolving viruses in which de novo mutations result in antigenically novel variants. With this focus, we present a simple two-tiered 'phylodynamic' model whose purpose is to simulate, along with case data, sequence data that will allow for a more quantitative interface with observed sequence data. The model differs from previous approaches in that it separates the simulation of the epidemiological dynamics (tier 1) from the molecular evolution of the virus's dominant antigenic protein (tier 2). This separation of phenotypic dynamics from genetic dynamics results in a modular model that is computationally simpler and allows sequences to be simulated with specifications such as sequence length, nucleotide composition and molecular constraints. To illustrate its use, we apply the model to influenza A (H3N2) dynamics in humans, influenza B dynamics in humans and influenza A (H3N8) dynamics in equine hosts. In all three of these illustrative examples, we show that the model can simulate sequences that are quantitatively similar in pattern to those empirically observed. Future work should focus on statistical estimation of model parameters for these examples as well as the possibility of applying this model, or variants thereof, to other host-virus systems.