The evolution of epidemic influenza

Epidemiological dynamics and phylogeography of influenza virus in southern China

BACKGROUND

Understanding the epidemiological dynamics of influenza virus is central to surveillance and vaccine strain selection. It has been suggested that tropical and subtropical regions represent the global source of influenza epidemics. However, our understanding of the epidemiological dynamics of influenza virus in these regions is limited by a relative lack of long-term data.

METHODS

We analyzed epidemiological and virological data on influenza recorded over a period of 15 years from the metropolitan city of Shenzhen in subtropical southern China. We used wavelet analysis to determine the periodicity of influenza epidemics and molecular phylogeographic analysis to investigate the role of Shenzhen and southern China in the global evolution of influenza virus.

RESULTS

We show that southern China is unlikely to represent an epicenter of global influenza activity, because activity in Shenzhen is characterized by significant annual cycles, multiple viral introductions every year, limited persistence across epidemic seasons, and viruses that generally are not positioned on the trunk of the global influenza virus phylogeny.

CONCLUSIONS

We propose that novel influenza viruses emerge and evolve in multiple geographic localities and that the global evolution of influenza virus is complex and does not simply originate from a southern Chinese epicenter.

Molecular evolutionary analysis of pH1N1 2009 influenza virus in Reunion Island, South West Indian Ocean region: a cohort study

Background/Objectives

Molecular epidemiology is a powerful tool to decipher the dynamics of viral transmission, quasispecies temporal evolution and origins. Little is known about the pH1N1 molecular dynamics in general population. A prospective study (CoPanFlu-RUN) was carried out in Reunion Island to characterize pH1N1 genetic variability and molecular evolution occurring in population during the pH1N1 Influenza pandemic in 2009.

Methodology

We directly amplified pH1N1 genomes from 28 different nasal swabs (26 individuals from 21 households). Fifteen strains were fully sequenced and 13 partially. This includes pairs of sequences from different members of 5 separate households; and two pairs from individuals, collected at different times. We assessed the molecular evolution of pH1N1 by genetic variability and phylogenetic analyses.

Principal Findings

We found that i) Reunion pH1N1 sequences stemmed from global “clade 7” but shaped two phylogenetic sub-clades; ii) D239E mutation was identified in the hemagglutinin protein of all Reunion sequences, a mutation which has been associated elsewhere with mild-, upper-respiratory tract pH1N1 infecting strains; iii) Date estimates from molecular phylogenies predicted clade emergence some time before the first detection of pH1N1 by the epidemiological surveillance system; iv) Phylogenetic relatedness was observed between Reunion pH1N1 viruses and those from other countries in South-western Indian Ocean area; v) Quasispecies populations were observed within households and individuals of the cohort-study.

Conclusions

Surveillance and/or prevention systems presently based on Influenza virus sequence variation should take into account that the majority of studies of pH1N1 Influenza generate genetic data for the HA/NA viral segments obtained from hospitalized-patients, which is potentially non-representative of the overall viral diversity within whole populations. Our observations highlight the importance of collecting unbiased data at the community level and conducting whole genome analysis to accurately understand viral dynamics.

FluShuffle and FluResort: new algorithms to identify reassorted strains of the influenza virus by mass spectrometry

BACKGROUND

Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented.

RESULTS

The FluShuffle and FluResort algorithms were tested with both experimental and simulated mass spectra of whole virus digests. FluShuffle considers different combinations of viral protein identities that match the mass spectral data using a Gibbs sampling algorithm employing a mixed protein Markov chain Monte Carlo (MCMC) method. FluResort utilizes those identities to calculate the weighted distance of each across two or more different phylogenetic trees constructed through viral protein sequence alignments. Each weighted mean distance value is normalized by conversion to a Z-score to establish a reassorted strain.

CONCLUSIONS

The new FluShuffle and FluResort algorithms can correctly identify the origins of influenza viral proteins and the number of reassortment events required to produce the strains from the high resolution mass spectral data of whole virus proteolytic digestions. This has been demonstrated in the case of constructed vaccine strains as well as common human seasonal strains of the virus. The algorithms significantly improve the capability of the proteotyping approach to identify reassorted viruses that pose the greatest pandemic risk.

Phylodynamic analysis of a viral infection network

Viral infections by sexual and droplet transmission routes typically spread through a complex host-to-host contact network. Clarifying the transmission network and epidemiological parameters affecting the variations and dynamics of a specific pathogen is a major issue in the control of infectious diseases. However, conventional methods such as interview and/or classical phylogenetic analysis of viral gene sequences have inherent limitations and often fail to detect infectious clusters and transmission connections. Recent improvements in computational environments now permit the analysis of large datasets. In addition, novel analytical methods have been developed that serve to infer the evolutionary dynamics of virus genetic diversity using sample date information and sequence data. This type of framework, termed "phylodynamics," helps connect some of the missing links on viral transmission networks, which are often hard to detect by conventional methods of epidemiology. With sufficient number of sequences available, one can use this new inference method to estimate theoretical epidemiological parameters such as temporal distributions of the primary infection, fluctuation of the pathogen population size, basic reproductive number, and the mean time span of disease infectiousness. Transmission networks estimated by this framework often have the properties of a scale-free network, which are characteristic of infectious and social communication processes. Network analysis based on phylodynamics has alluded to various suggestions concerning the infection dynamics associated with a given community and/or risk behavior. In this review, I will summarize the current methods available for identifying the transmission network using phylogeny, and present an argument on the possibilities of applying the scale-free properties to these existing frameworks.

Estimating allele age and selection coefficient from time-serial data

Recent advances in sequencing technologies have made available an ever-increasing amount of ancient genomic data. In particular, it is now possible to target specific single nucleotide polymorphisms in several samples at different time points. Such time-series data are also available in the context of experimental or viral evolution. Time-series data should allow for a more precise inference of population genetic parameters and to test hypotheses about the recent action of natural selection. In this manuscript, we develop a likelihood method to jointly estimate the selection coefficient and the age of an allele from time-serial data. Our method can be used for allele frequencies sampled from a single diallelic locus. The transition probabilities are calculated by approximating the standard diffusion equation of the Wright-Fisher model with a one-step process. We show that our method produces unbiased estimates. The accuracy of the method is tested via simulations. Finally, the utility of the method is illustrated with an application to several loci encoding coat color in horses, a pattern that has previously been linked with domestication. Importantly, given our ability to estimate the age of the allele, it is possible to gain traction on the important problem of distinguishing selection on new mutations from selection on standing variation. In this coat color example for instance, we estimate the age of this allele, which is found to predate domestication.

Cleavage activation of the human-adapted influenza virus subtypes by matriptase reveals both subtype and strain specificities

Cleavage activation of the hemagglutinin (HA) precursor is an essential step in the influenza virus replication cycle that is driven by host cell proteases. HA cleavage activation is required for virus-endosome membrane fusion and the subsequent release of the influenza virus genome into the cytoplasm. Previous studies have determined that HA cleavage is most likely driven by either membrane-bound or extracellular trypsin-like proteases that reside in the respiratory tract. However, there is still uncertainty regarding which proteases are critical for HA cleavage in vivo. Therefore, further investigation of HA cleavage activation is needed in order to gain insight into the critical proteases involved. Matriptase is a member of the type II transmembrane serine protease family that is highly expressed in a membrane-bound form throughout the respiratory tract. One feature of matriptase is that, once activated, the catalytic domain is secreted into the extracellular space and so serves as a functional extracellular protease. In this study, we have determined that the secreted, catalytic domain of matriptase has the ability to cleave and activate HA from the influenza virus H1 subtype but not the H2 and H3 subtypes. Furthermore, matriptase selectively cleaved the HA of particular strains within the H1 subtype, revealing both subtype and H1 strain specificity. Matriptase was also found to activate thrombolytic zymogens that have been shown to cleave and activate the influenza virus HA. Our data demonstrate that matriptase has the ability to cleave HA directly or indirectly by activating HA-cleaving zymogens.

Antigenic analysis of highly pathogenic avian influenza virus H5N1 sublineages co-circulating in Egypt

Highly pathogenic avian influenza virus H5N1 has spread across Eurasia and Africa, and outbreaks are now endemic in several countries, including Indonesia, Vietnam and Egypt. Continuous circulation of H5N1 virus in Egypt, from a single infected source, has led to significant genetic diversification with phylogenetically separable sublineages, providing an opportunity to study the impact of genetic evolution on viral phenotypic variation. In this study, we analysed the phylogeny of H5 haemagglutinin (HA) genes in influenza viruses isolated in Egypt from 2006 to 2011 and investigated the effect of conserved amino acid mutations in the HA genes in each of the sublineages on their antigenicity. The analysis showed that viruses in at least four sublineages still persisted in poultry in Egypt as of 2011. Using reverse genetics to generate HA-reassortment viruses with specific HA mutations, we found antigenic drift in the HA in two influenza virus sublineages, compared with the other currently co-circulating influenza virus sublineages in Egypt. Moreover, the two sublineages with significant antigenic drift were antigenically distinguishable. Our findings suggested that phylogenetically divergent H5N1 viruses, which were not antigenically cross-reactive, were co-circulating in Egypt, indicating that there was a problem in using a single influenza virus strain as seed virus to produce influenza virus vaccine in Egypt and providing data for designing more efficacious control strategies in H5N1-endemic areas.

Compensatory evolution of net-charge in influenza A virus hemagglutinin

The propagation of influenza A virus depends on the balance between the activities of hemagglutinin (HA) for binding to host cells and neuraminidase (NA) for releasing from infected cells (HA-NA balance). Since the host cell membrane and the sialic acid receptor are negatively charged, the amino acid substitutions increasing (charge+) and decreasing (charge−) the positive charge of HA subunit 1 (HA1) enhance and reduce, respectively, the binding avidity and affinity. The positive charge of HA1 in human influenza A virus bearing subtype H3N2 (A/H3N2 virus) was observed to have increased during evolution, but the evolutionary mechanism for this observation was unclear because this may disrupt the HA-NA balance. Here we show, from the phylogenetic analysis of HA for human A/H3N2 and A/H1N1 viruses, that the relative frequencies of charge+ and charge− substitutions were elevated on the branches where the number of N-glycosylation sites (NGS) increased and decreased, respectively, compared to those where the number of NGS did not change. On the latter branches, the net-charge of HA1 appeared to have been largely maintained to preserve its structure and function. Since the charge+ and charge− substitutions in HA1 have opposite effects to the gain and loss of NGS on the binding and release of the virus, the net-charge of HA1 may have evolved to compensate for the effect of the gain and loss of NGS, probably through changing the avidity. Apparently, the relative frequency of charge− substitutions in HA1 of A/H3N2 virus was elevated after the introduction of oseltamivir, and that of charge+ substitutions in HA1 of A/H1N1 virus was elevated after the spread of oseltamivir resistance. These observations may also be explained by the compensatory effect of the net-charge in HA1 on the NA activity for keeping the HA-NA balance.

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.

Influenza virus-mediated membrane fusion: determinants of hemagglutinin fusogenic activity and experimental approaches for assessing virus fusion

Hemagglutinin (HA) is the viral protein that facilitates the entry of influenza viruses into host cells. This protein controls two critical aspects of entry: virus binding and membrane fusion. In order for HA to carry out these functions, it must first undergo a priming step, proteolytic cleavage, which renders it fusion competent. Membrane fusion commences from inside the endosome after a drop in lumenal pH and an ensuing conformational change in HA that leads to the hemifusion of the outer membrane leaflets of the virus and endosome, the formation of a stalk between them, followed by pore formation. Thus, the fusion machinery is an excellent target for antiviral compounds, especially those that target the conserved stem region of the protein. However, traditional ensemble fusion assays provide a somewhat limited ability to directly quantify fusion partly due to the inherent averaging of individual fusion events resulting from experimental constraints. Inspired by the gains achieved by single molecule experiments and analysis of stochastic events, recently-developed individual virion imaging techniques and analysis of single fusion events has provided critical information about individual virion behavior, discriminated intermediate fusion steps within a single virion, and allowed the study of the overall population dynamics without the loss of discrete, individual information. In this article, we first start by reviewing the determinants of HA fusogenic activity and the viral entry process, highlight some open questions, and then describe the experimental approaches for assaying fusion that will be useful in developing the most effective therapies in the future.

[Research progress on influenza antiviral small RNAs]

Worldwide influenza caused by influenza virus is a respiratory disease which threats the public health by seasonal epidemics or global influenza outbreak. Vaccines and drugs are current therapies, but there are many restricted factors such as neurotoxicity, side effects of gastrointestinal, and drug resistance. New technologies, particularly RNAi mediated by small RNAs, has become a potential and robust method in influenza antiviral research for its high efficiency, specific, and speedy. Following the spread and epidemic of the influenza virus, application of small RNAs into influenza antiviral research has been reported increasingly. The small RNAs, PA-2087, NP-1496, and M-950, which targets PA, NP, and M2 genes, respectively, are the most effective anti-influenza siRNAs up to now. siRNA of targeting conservative region of different influenza viral genes has broader effect on virus inhibition. The combination of siRNAs of targeting different genes can achieve better virus inhibition. In this review, we mainly described the progress of siRNAs and miRNAs for anti-influenza virus, and the prospects and hurdles of influenza RNAi therapy as well.

Canalization of the evolutionary trajectory of the human influenza virus

BACKGROUND

Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. However, despite strong pressure to evolve away from human immunity and to diversify in antigenic phenotype, H3N2 influenza shows paradoxically limited genetic and antigenic diversity present at any one time. Here, we propose a simple model of antigenic evolution in the influenza virus that accounts for this apparent discrepancy.

RESULTS

In this model, antigenic phenotype is represented by a N-dimensional vector, and virus mutations perturb phenotype within this continuous Euclidean space. We implement this model in a large-scale individual-based simulation, and in doing so, we find a remarkable correspondence between model behavior and observed influenza dynamics. This model displays rapid evolution but low standing diversity and simultaneously accounts for the epidemiological, genetic, antigenic, and geographical patterns displayed by the virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis.

CONCLUSIONS

Selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable. In the model, the influenza population shows a 1- to 2-year timescale of repeatability, suggesting a window in which evolutionary dynamics could be, in theory, predictable.

Comparison of neutralizing and hemagglutination-inhibiting antibody responses for evaluating the seasonal influenza vaccine

Evaluation of the efficacy of influenza vaccines is essential for vaccine development. This study evaluated the neutralizing and hemagglutination-inhibition antibody response in subjects receiving the 2006-07 and 2007-08 seasonal influenza vaccines. ELISA-based microneutralization demonstrated a greater mean-fold increase and seroconversion rate than the hemagglutination-inhibition assay. The increase in the antibody titers against influenza H1 were higher than those against influenza H3 and influenza B, indicating that the H1 vaccine strain in the 2006-07 and 2007-08 seasons was more immunogenic. These data suggest that the neutralizing antibody response is a better measurement of influenza vaccine efficacy.

Fatal cases of influenza A(H3N2) in children: insights from whole genome sequence analysis

During the Northern Hemisphere winter of 2003–2004 the emergence of a novel influenza antigenic variant, A/Fujian/411/2002-like(H3N2), was associated with an unusually high number of fatalities in children. Seventeen fatal cases in the UK were laboratory confirmed for Fujian/411-like viruses. To look for phylogenetic patterns and genetic markers that might be associated with increased virulence, sequencing and phylogenetic analysis of the whole genomes of 63 viruses isolated from fatal cases and non fatal “control” cases was undertaken. The analysis revealed the circulation of two main genetic groups, I and II, both of which contained viruses from fatal cases. No associated amino acid substitutions could be linked with an exclusive or higher occurrence in fatal cases. The Fujian/411-like viruses in genetic groups I and II completely displaced other A(H3N2) viruses, but they disappeared after 2004. This study shows that two A(H3N2) virus genotypes circulated exclusively during the winter of 2003–2004 in the UK and caused an unusually high number of deaths in children. Host factors related to immune state and differences in genetic background between patients may also play important roles in determining the outcome of an influenza infection.

A comparative study of human TLR 7/8 stimulatory trimer compositions in influenza A viral genomes

Background

Variation in the genomes of single-stranded RNA viruses affects their infectivity and pathogenicity in two ways. First, viral genome sequence variations lead to changes in viral protein sequences and activities. Second, viral genome sequence variation produces diversity at the level of nucleotide composition and diversity in the interactions between viral RNAs and host toll-like receptors (TLRs). A viral genome-typing method based on this type of diversity has not yet been established.

Methodology/Principal Findings

In this study, we propose a novel genomic trait called the “TLR stimulatory trimer composition” (TSTC) and two quantitative indicators, Score S and Score N, named “TLR stimulatory scores” (TSS). Using the complete genome sequences of 10,994 influenza A viruses (IAV) and 251 influenza B viruses, we show that TSTC analysis reveals the diversity of Score S and Score N among the IAVs isolated from various hosts. In addition, we show that low values of Score S are correlated with high pathogenicity and pandemic potential in IAVs. Finally, we use Score S and Score N to construct a logistic regression model to recognize IAV strains that are highly pathogenic or have high pandemic potential.

Conclusions/Significance

Results from the TSTC analysis indicate that there are large differences between human and avian IAV genomes (except for segment 3), as illustrated by Score S. Moreover, segments 1, 2, 3 and 4 may be major determinants of the stimulatory activity exerted on human TLRs 7 and 8. We also find that a low Score S value is associated with high pathogenicity and pandemic potential in IAV. The π value from the TSS-derived logistic regression model is useful for recognizing emerging IAVs that have high pathogenicity and pandemic potential.

Emerged HA and NA mutants of the pandemic influenza H1N1 viruses with increasing epidemiological significance in Taipei and Kaohsiung, Taiwan, 2009-10

The 2009 influenza pandemic provided an opportunity to observe dynamic changes of the hemagglutinin (HA) and neuraminidase (NA) of pH1N1 strains that spread in two metropolitan areas -Taipei and Kaohsiung. We observed cumulative increases of amino acid substitutions of both HA and NA that were higher in the post–peak than in the pre-peak period of the epidemic. About 14.94% and 3.44% of 174 isolates had one and two amino acids changes, respective, in the four antigenic sites. One unique adaptive mutation of HA2 (E374K) was first detected three weeks before the epidemic peak. This mutation evolved through the epidemic, and finally emerged as the major circulated strain, with significantly higher frequency in the post-peak period than in the pre-peak (64.65% vs 9.28%, p<0.0001). E374K persisted until ten months post-nationwide vaccination without further antigenic changes (e.g. prior to the highest selective pressure). In public health measures, the epidemic peaked at seven weeks after oseltamivir treatment was initiated. The emerging E374K mutants spread before the first peak of school class suspension, extended their survival in high-density population areas before vaccination, dominated in the second wave of class suspension, and were fixed as herd immunity developed. The tempo-spatial spreading of E374K mutants was more concentrated during the post–peak (p = 0.000004) in seven districts with higher spatial clusters (p<0.001). This is the first study examining viral changes during the naïve phase of a pandemic of influenza through integrated virological/serological/clinical surveillance, tempo-spatial analysis, and intervention policies. The vaccination increased the percentage of E374K mutants (22.86% vs 72.34%, p<0.001) and significantly elevated the frequency of mutations in Sa antigenic site (2.36% vs 23.40%, p<0.001). Future pre-vaccination public health efforts should monitor amino acids of HA and NA of pandemic influenza viruses isolated at exponential and peak phases in areas with high cluster cases.

Evidence for N-glycan shielding of antigenic sites during evolution of human influenza A virus hemagglutinin

After the emergence of influenza A viruses in the human population, the number of N-glycosylation sites (NGS) in the globular head region of hemagglutinin (HA) has increased continuously for several decades. It has been speculated that the addition of NGS to the globular head region of HA has conferred selective advantages to the virus by preventing the binding of antibodies (Ab) to antigenic sites (AS). Here, the effect of N-glycosylation on the binding of Ab to AS in human influenza A virus subtype H3N2 (A/H3N2) was examined by inferring natural selection at AS and other sites (NAS) that are located close to and distantly from the NGS in the three-dimensional structure of HA through a comparison of the rates of synonymous (d(S)) and nonsynonymous (d(N)) substitutions. When positions 63, 122, 126, 133, 144, and 246 in the globular head region of HA were non-NGS, the d(N)/d(S) was >1 and positive selection was detected at the AS located near these positions. However, the d(N)/d(S) value decreased and the evidence of positive selection disappeared when these positions became NGS. In contrast, d(N)/d(S) at the AS distantly located from the positions mentioned above and at the NAS of any location were generally <1 and did not decrease when these positions changed from non-NGS to NGS. These results suggest that the attachment of N-glycans to the NGS in the globular head region of HA prevented the binding of Ab to AS in the evolutionary history of human A/H3N2 virus.

Reassortment Networks and the evolution of pandemic H1N1 swine-origin influenza

Prior research developed Reassortment Networks to reconstruct the evolution of segmented viruses under both reassortment and mutation. We report their application to the swine-origin pandemic H1N1 virus (S-OIV). A database of all influenza A viruses, for which complete genome sequences were available in Genbank by October 2009, was created and dynamic programming was used to compute distances between all corresponding segments. A reassortment network was created to obtain the minimum cost evolutionary paths from all viruses to the exemplar S-OIV A/California/04/2009. This analysis took 35 hours on the Cray Extreme Multithreading (XMT) supercomputer, which has special hardware to permit efficient parallelization. Six specific H1N1/H1N2 bottleneck viruses were identified that almost always lie on minimum cost paths to S-OIV. We conjecture that these viruses are crucial to S-OIV evolution and worthy of careful study from a molecular biology viewpoint. In phylogenetics, ancestors are typically medians that have no functional constraints. In our method, ancestors are not inferred, but rather chosen from previously observed viruses along a path of mutation and reassortment leading to the target virus. This specificity and functional constraint render our results actionable for further experiments in vitro and in vivo.

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.

Does history repeat itself? Wavelets and the phylodynamics of influenza A

Unprecedented global surveillance of viruses will result in massive sequence data sets that require new statistical methods. These data sets press the limits of Bayesian phylogenetics as the high-dimensional parameters that comprise a phylogenetic tree increase the already sizable computational burden of these techniques. This burden often results in partitioning the data set, for example, by gene, and inferring the evolutionary dynamics of each partition independently, a compromise that results in stratified analyses that depend only on data within a given partition. However, parameter estimates inferred from these stratified models are likely strongly correlated, considering they rely on data from a single data set. To overcome this shortfall, we exploit the existing Monte Carlo realizations from stratified Bayesian analyses to efficiently estimate a nonparametric hierarchical wavelet-based model and learn about the time-varying parameters of effective population size that reflect levels of genetic diversity across all partitions simultaneously. Our methods are applied to complete genome influenza A sequences that span 13 years. We find that broad peaks and trends, as opposed to seasonal spikes, in the effective population size history distinguish individual segments from the complete genome. We also address hypotheses regarding intersegment dynamics within a formal statistical framework that accounts for correlation between segment-specific parameters.

Temporally structured metapopulation dynamics and persistence of influenza A H3N2 virus in humans

Populations of seasonal influenza virus experience strong annual bottlenecks that pose a considerable extinction risk. It has been suggested that an influenza source population located in tropical Southeast or East Asia seeds annual temperate epidemics. Here we investigate the seasonal dynamics and migration patterns of influenza A H3N2 virus by analysis of virus samples obtained from 2003 to 2006 from Australia, Europe, Japan, New York, New Zealand, Southeast Asia, and newly sequenced viruses from Hong Kong. In contrast to annual temperate epidemics, relatively low levels of relative genetic diversity and no seasonal fluctuations characterized virus populations in tropical Southeast Asia and Hong Kong. Bayesian phylogeographic analysis using discrete temporal and spatial characters reveal high rates of viral migration between urban centers tested. Although the virus population that migrated between Southeast Asia and Hong Kong persisted through time, this was dependent on virus input from temperate regions and these tropical regions did not maintain a source for annual H3N2 influenza epidemics. We further show that multiple lineages may seed annual influenza epidemics, and that each region may function as a potential source population. We therefore propose that the global persistence of H3N2 influenza A virus is the result of a migrating metapopulation in which multiple different localities may seed seasonal epidemics in temperate regions in a given year. Such complex global migration dynamics may confound control efforts and contribute to the emergence and spread of antigenic variants and drug-resistant viruses.

Toward a quantitative understanding of viral phylogeography

Phylogeographic approaches help uncover the imprint that spatial epidemiological processes leave in the genomes of fast evolving viruses. Recent Bayesian inference methods that consider phylogenetic diffusion of discretely and continuously distributed traits offer a unique opportunity to explore genotypic and phenotypic evolution in greater detail. To provide a taste of the recent advances in viral diffusion approaches, we highlight key findings arising at the intrahost, local and global epidemiological scales. We also outline future areas of research and discuss how these may contribute to a quantitative understanding of the phylodynamics of RNA viruses.

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.

Mass spectrometry based proteomic studies on viruses and hosts--a review

In terms of proteomic research in the 21st century, the realm of virology is still regarded as an enormous challenge mainly brought by three aspects, namely, studying on the complex proteome of the virus with unexpected variations, developing more accurate analytical techniques as well as understanding viral pathogenesis and virus-host interaction dynamics. Progresses in these areas will be helpful to vaccine design and antiviral drugs discovery. Mass spectrometry based proteomics have shown exceptional display of capabilities, not only precisely identifying viral and cellular proteins that are functionally, structurally, and dynamically changed upon virus infection, but also enabling us to detect important pathway proteins. In addition, many isolation and purification techniques and quantitative strategies in conjunction with MS can significantly improve the sensitivity of mass spectrometry for detecting low-abundant proteins, replenishing the stock of virus proteome and enlarging the protein-protein interaction maps. Nevertheless, only a small proportion of the infectious viruses in both of animal and plant have been studied using this approach. As more virus and host genomes are being sequenced, MS-based proteomics is becoming an indispensable tool for virology. In this paper, we provide a brief review of the current technologies and their applications in studying selected viruses and hosts.

Tracking the 2009 H1N1 influenza virus in the Italian region Campania

A novel swine-origin influenza A (H1N1) virus affecting humans was detected in April 2009 in Mexico, Canada, and USA. The S-OIV infection caused a mild to severe febrile respiratory disease throughout the world. Here, we briefly review the main features of influenza A viruses, which caused also other pandemics in the past, and focus in particular on the epidemiology data of the H1N1 influenza in the Italian region Campania, which resulted the most affected by the S-OIV and the one with more lethal cases. In Campania, the peak of influenza preceded of about 2 weeks the incidence peak at the national level. Moreover, the percentage of H1N1-positive patients was much higher in the main town Naples, compared to the other Campania provinces. The age group from 7 months to 17 years was the most affected by the H1N1 infection (43.45%), similarly to what reported at the national level. Here, we discuss the possible reasons of the high H1N1 incidence in Campania and the implications that these findings could have on the future prevention campaigns.

Evolutionary pathways of the pandemic influenza A (H1N1) 2009 in the UK

The emergence of the influenza (H1N1) 2009 virus provided a unique opportunity to study the evolution of a pandemic virus following its introduction into the human population. Virological and clinical surveillance in the UK were comprehensive during the first and second waves of the pandemic in 2009, with extensive laboratory confirmation of infection allowing a detailed sampling of representative circulating viruses. We sequenced the complete coding region of the haemagglutinin (HA) segment of 685 H1N1 pandemic viruses selected without bias during two waves of pandemic in the UK (April-December 2009). Phylogenetic analysis showed that although temporal accumulation of amino acid changes was observed in the HA sequences, the overall diversity was less than that typically seen for seasonal influenza A H1N1 or H3N2. There was co-circulation of multiple variants as characterised by signature amino acid changes in the HA. A specific substitution (S203T) became predominant both in UK and global isolates. No antigenic drift occurred during 2009 as viruses with greater than four-fold reduction in their haemagglutination inhibition (HI) titre ("low reactors") were detected in a low proportion (3%) and occurred sporadically. Although some limited antigenic divergence in viruses with four-fold reduction in HI titre might be related to the presence of 203T, additional studies are needed to test this hypothesis.

Homologous recombination in negative sense RNA viruses

Recombination is an important process that influences biological evolution at many different levels. More and more homologous recombination events have been reported among negative sense RNA viruses recently. While sporadic authentic examples indicate that homologous recombination does occur, recombination seems to be generally rare or even absent in most negative sense RNA viruses, and most of the homologous recombination events reported in the literature were likely generated artificially due to lab contamination or inappropriate bioinformatics methods. Homologous recombination in negative sense RNA viruses should be reported with caution in the future, and only after stringent quality control efforts. Moreover, co-infection experiments should be performed to confirm whether recombination can occur.

Influenza emergence in the face of evolutionary constraints

Different influenza subtypes can evolve at very different rates, but the causes are not well understood. In this paper, we explore whether differences in transmissibility between subtypes can play a role if there are fitness constraints on antigenic evolution. We investigate the problem using a mathematical model that separates the interaction of strains through cross-immunity from the process of emergence for new antigenic variants. Evolutionary constraints are also included with antigenic mutation incurring a fitness cost. We show that the transmissibility of a strain can become disproportionately important in dictating the rate of antigenic drift: strains that spread only slightly more easily can have a much higher rate of emergence. Further, we see that the effect continues when vaccination is considered; a small increase in the rate of transmission can make it much harder to control the frequency at which new strains emerge. Our results not only highlight the importance of considering both transmission and fitness constraints when modelling influenza evolution, but may also help in understanding the differences between the emergence of H1N1 and H3N2 subtypes.

Identification of amino acids in highly pathogenic avian influenza H5N1 virus hemagglutinin that determine avian influenza species specificity

To test the role of neutralizing antibodies (nAbs) and receptor adaptation in interspecies transmission of influenza virus, two H5N1 strains, isolated from human and avian hosts, with four amino acid differences in hemagglutinin (HA) and seven HA mutations were studied. We found that a mutation at amino acid position 90 in the H5N1 HA, outside the receptor-binding domain (RBD), could simultaneously induce changes in the RBD conformation to escape from nAb binding and alter the receptor preference through long-range regulation. This mutation was deemed a “key event” for interspecies transmission. It is likely a result of positive selection caused by antibodies, allowing the original invasion by new species-specific variants. A mutation at amino acid position 160 in the RBD only induced a change in receptor preference. This mutation was deemed a “maintaining adaptation”, which ensured that influenza virus variants would be able to infect new organisms of a different species successfully. The mutation is the result of adaptation caused by the receptor. Our results suggest that continuing occurrence of these two types of mutations made the variants persist in the new host species.

Reassortment and mutations associated with emergence and spread of oseltamivir-resistant seasonal influenza A/H1N1 viruses in 2005-2009

A dramatic increase in the frequency of the H275Y mutation in the neuraminidase (NA), conferring resistance to oseltamivir, has been detected in human seasonal influenza A/H1N1 viruses since the influenza season of 2007-2008. The resistant viruses emerged in the ratio of 14.3% and quickly reached 100% in Taiwan from September to December 2008. To explore the mechanisms responsible for emergence and spread of the resistant viruses, we analyzed the complete genome sequences of 25 viruses collected during 2005-2009 in Taiwan, which were chosen from various clade viruses, 1, 2A, 2B-1, 2B-2, 2C-1 and 2C-2 by the classification of hemagglutinin (HA) sequences. Our data revealed that the dominant variant, clade 2B-1, in the 2007-2008 influenza emerged through an intra-subtype 4+4 reassortment between clade 1 and 2 viruses. The dominant variant acquired additional substitutions, including A206T in HA, H275Y and D354G in NA, L30R and H41P in PB1-F2, and V411I and P453S in basic polymerase 2 (PB2) proteins and subsequently caused the 2008-2009 influenza epidemic in Taiwan, accompanying the widespread oseltamivir-resistant viruses. We also characterized another 3+5 reassortant virus which became double resistant to oseltamivir and amantadine. Comparison of oseltamivir-resistant influenza A/H1N1 viruses belonging to various clades in our study highlighted that both reassortment and mutations were associated with emergence and spread of these viruses and the specific mutation, H275Y, conferring to antiviral resistance, was acquired in a hitch-hiking mechanism during the viral evolutionary processes.

Prediction of directional changes of influenza A virus genome sequences with emphasis on pandemic H1N1/09 as a model case

Influenza virus poses a significant threat to public health, as exemplified by the recent introduction of the new pandemic strain H1N1/09 into human populations. Pandemics have been initiated by the occurrence of novel changes in animal sources that eventually adapt to human. One important issue in studies of viral genomes, particularly those of influenza virus, is to predict possible changes in genomic sequence that will become hazardous. We previously established a clustering method termed ‘BLSOM’ (batch-learning self-organizing map) that does not depend on sequence alignment and can characterize and compare even 1 million genomic sequences in one run. Strategies for comparing a vast number of genomic sequences simultaneously become increasingly important in genome studies because of remarkable progresses in nucleotide sequencing. In this study, we have constructed BLSOMs based on the oligonucleotide and codon composition of all influenza A viral strains available. Without prior information with regard to their hosts, sequences derived from strains isolated from avian or human sources were successfully clustered according to the hosts. Notably, the pandemic H1N1/09 strains have oligonucleotide and codon compositions that are clearly different from those of human seasonal influenza A strains. This enables us to infer future directional changes in the influenza A viral genome.

[Advances on genomic evolution of influenza virus]

Four influenza virus pandemics occurred since the beginning of the 20th century. In 1918, 1957, 1968 and 2009, this disease threatened human health and social living greatly. The progress in genomic evolution of influenza virus promoted exploring pathogenic mechanism, surveilling epidemic, preparing influenza vaccine and developing anti-virus drugs. Here, we reviewed the progress in genomic evolution of influenza virus that included evolution mechanism, antigenic evolution, and anti-drug.

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.

Two optimal mutation rates in obligate pathogens subject to deleterious mutation

Pathogen species with high mutation rates are likely to accumulate deleterious mutations that reduce their reproductive potential within the host. By altering the within-host growth rate of the pathogen, the deleterious mutation load has the potential to affect epidemiological properties such as prevalence, mean pathogen load, and the mean duration of infections. Here, I examine an epidemiological model that allows for multiple segregating mutations that affect within-host replication efficiency. The model demonstrates a complex range of outcomes depending on pathogen mutation rate, including two distinct, widely separated mutation rates associated with high pathogen prevalence. The low mutation rate prevalence peak is associated with small amounts of genetic diversity within the pathogen population, relatively stable prevalence and infection dynamics, and genetic variation partitioned between hosts. The high mutation rate peak is characterized by considerable genetic diversity both within and between hosts, relatively frequent invasions by more virulent types, and is qualitatively similar to an RNA virus quasispecies. The two prevalence peaks are separated by a valley where natural selection favors evolution toward the optimal within-host state, which is associated with high virulence and relatively rapid host mortality. Both chronic and acute infections are examined using stochastic forward simulations.

Implications of global and regional patterns of highly pathogenic avian influenza virus H5N1 clades for risk management

This paper analyses the publicly available data on the distribution and evolution of highly pathogenic avian influenza virus (HPAIV) H5N1 clades, whilst acknowledging the biases resulting from the non-random selection of isolates for gene sequencing. The data indicate molecular heterogeneity in the global distribution of HPAIV H5N1, in particular in different parts of East and Southeast Asia. Analysis of the temporal pattern of haemagglutinin clade data shows a progression from clade 0 (the 'dominant' clade between 1996 and 2002) to clade 1 (2003-2005) and then to clade 2.3.4 (2005 onwards). This process continuously produces variants, depending on the frequency of virus multiplication in the host population, which is influenced by geographical variation in poultry density, poultry production systems and also HPAI risk management measures such as vaccination. Increased multilateral collaboration needs to focus on developing enhanced disease surveillance and control targeted at evolutionary 'hotspots'.

Proteotyping to establish gene origin within reassortant influenza viruses

The application of a rapid and direct proteotyping approach with which to identify the gene origin of viral antigens in a reassortant influenza strain is demonstrated. The reassortant strain, constructed for a vaccine against type A 2009 H1N1 pandemic influenza, contains genes derived from a wild-type pandemic strain (A/California/7/2009) and an egg adapted high-growth strain (denoted NYMC X-157) derived from an earlier A/Puerto Rico/8/34 strain. The proteotyping approach employs modern proteomics methods and high resolution mass spectrometry to correctly establish that the genes of the surface antigens, hemagglutinin and neuraminidase, are derived from the A/California/7/2009 strain while those for nucleoprotein and matrix protein M1 antigens are derived from the NYMC X-157 strain. This is achieved for both gel-separated antigens and those from a whole vaccine digest. Furthermore, signature peptides detected in the mass spectra of the digested antigens enable the engineered reassortant strain to be identified as a type A virus of the H1N1 subtype in accord with earlier studies. The results demonstrate that proteotyping approach provides a more direct and rapid approach over RT-PCR with which to characterize reassortant strains of the influenza virus at the molecular protein level. Given that these strains pose the greatest risk to human and animal health and have been responsible for all human pandemics of the 20th and 21st centuries, there is a vital need for the origins and evolutionary history of these strains to be rapidly established.

Comparison of the incidence of influenza in relation to climate factors during 2000-2007 in five countries

Relatively few international comparisons of the incidence of influenza related to climate parameters have been performed, particularly in the Eastern hemisphere. In this study, the incidence of influenza and climate data such as temperature, relative humidity, and rainfall, from cities at different latitudes with contrasting climates: Singapore, Hong Kong (China), Ulaanbaatar (Mongolia), Vancouver (Canada), and three Australian cities (Brisbane, Melbourne and Sydney) were examined to determine whether there was any overall relationship between the incidence of influenza and climate. Applying time-series analyses to the more comprehensive datasets, it was found that relative humidity was associated with the incidence of influenza A in Singapore, Hong Kong, Brisbane, and Vancouver. In the case of influenza B, the mean temperature was the key climate variable associated with the incidence of influenza in Hong Kong, Brisbane, Melbourne, and Vancouver. Rainfall was not significantly correlated with the incidence of influenza A or B in any of these cities.

The nonadaptive nature of the H1N1 2009 Swine Flu pandemic contrasts with the adaptive facilitation of transmission to a new host

BACKGROUND

The emergence of the 2009 H1N1 Influenza pandemic followed a multiple reassortment event from viruses originally circulating in swines and humans, but the adaptive nature of this emergence is poorly understood.

RESULTS

Here we base our analysis on 1180 complete genomes of H1N1 viruses sampled in North America between 2000 and 2010 in swine and human hosts. We show that while transmission to a human host might require an adaptive phase in the HA and NA antigens, the emergence of the 2009 pandemic was essentially nonadaptive. A more detailed analysis of the NA protein shows that the 2009 pandemic sequence is characterized by novel epitopes and by a particular substitution in loop 150, which is responsible for a nonadaptive structural change tightly associated with the emergence of the pandemic.

CONCLUSIONS

Because this substitution was not present in the 1918 H1N1 pandemic virus, we posit that the emergence of pandemics is due to epistatic interactions between sites distributed over different segments. Altogether, our results are consistent with population dynamics models that highlight the epistatic and nonadaptive rise of novel epitopes in viral populations, followed by their demise when the resulting virus is too virulent.

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.

Dynamics of glycoprotein charge in the evolutionary history of human influenza

Background

Influenza viruses show a significant capacity to evade host immunity; this is manifest both as large occasional jumps in the antigenic phenotype of viral surface molecules and in gradual antigenic changes leading to annual influenza epidemics in humans. Recent mouse studies show that avidity for host cells can play an important role in polyclonal antibody escape, and further that electrostatic charge of the hemagglutinin glycoprotein can contribute to such avidity.

Methodology/Principal Findings

We test the role of glycoprotein charge on sequence data from the three major subtypes of influenza A in humans, using a simple method of calculating net glycoprotein charge. Of all subtypes, H3N2 in humans shows a striking pattern of increasing positive charge since its introduction in 1968. Notably, this trend applies to both hemagglutinin and neuraminidase glycoproteins. In the late 1980s hemagglutinin charge reached a plateau, while neuraminidase charge started to decline. We identify key groups of amino acid sites involved in this charge trend.

Conclusions/Significance

To our knowledge these are the first indications that, for human H3N2, net glycoprotein charge covaries strongly with antigenic drift on a global scale. Further work is needed to elucidate how such charge interacts with other immune escape mechanisms, such as glycosylation, and we discuss important questions arising for future study.

Characterization of neuraminidases from the highly pathogenic avian H5N1 and 2009 pandemic H1N1 influenza A viruses

To study the precise role of the neuraminidase (NA), and its stalk region in particular, in the assembly, release, and entry of influenza virus, we deleted the 20-aa stalk segment from 2009 pandemic H1N1 NA (09N1) and inserted this segment, now designated 09s60, into the stalk region of a highly pathogenic avian influenza (HPAI) virus H5N1 NA (AH N1). The biological characterization of these wild-type and mutant NAs was analyzed by pseudotyped particles (pseudoparticles) system. Compared with the wild-type AH N1, the wild-type 09N1 exhibited higher NA activity and released more pseudoparticles. Deletion/insertion of the 09s60 segment did not alter this relationship. The infectivity of pseudoparticles harboring NA in combination with the hemagglutinin from HPAI H5N1 (AH H5) was decreased by insertion of 09s60 into AH N1 and was increased by deletion of 09s60 from 09N1. When isolated from the wild-type 2009H1N1 virus, 09N1 existed in the forms (in order of abundance) dimer>>tetramer>monomer, but when isolated from pseudoparticles, 09N1 existed in the forms dimer>monomer>>>tetramer. After deletion of 09s60, 09N1 existed in the forms monomer>>>dimer. AH N1 from pseudoparticles existed in the forms monomer>>dimer, but after insertion of 09s60, it existed in the forms dimer>>monomer. Deletion/insertion of 09s60 did not alter the NA glycosylation pattern of 09N1 or AH N1. The 09N1 was more sensitive than the AH N1 to the NA inhibitor oseltamivir, suggesting that the infectivity-enhancing effect of oseltamivir correlates with robust NA activity.

Spatio-temporal data comparisons for global highly pathogenic avian influenza (HPAI) H5N1 outbreaks

Highly pathogenic avian influenza subtype H5N1 is a zoonotic disease and control of the disease is one of the highest priority in global health. Disease surveillance systems are valuable data sources for various researches and management projects, but the data quality has not been paid much attention in previous studies. Based on data from two commonly used databases (Office International des Epizooties (OIE) and Food and Agriculture Organization of the United Nations (FAO)) of global HPAI H5N1 outbreaks during the period of 2003–2009, we examined and compared their patterns of temporal, spatial and spatio-temporal distributions for the first time. OIE and FAO data showed similar trends in temporal and spatial distributions if they were considered separately. However, more advanced approaches detected a significant difference in joint spatio-temporal distribution. Because of incompleteness for both OIE and FAO data, an integrated dataset would provide a more complete picture of global HPAI H5N1 outbreaks. We also displayed a mismatching profile of global HPAI H5N1 outbreaks and found that the degree of mismatching was related to the epidemic severity. The ideas and approaches used here to assess spatio-temporal data on the same disease from different sources are useful for other similar studies.

Influenza surveillance in Shenzhen, the largest migratory metropolitan city of China, 2006–2009

Shenzhen is one of the largest migratory metropolitan cities in China. A standardized influenza surveillance system has been operating in Shenzhen for several years. The objectives of the present study were to describe the epidemiology of influenza in Shenzhen and to assess the impact of pandemic H1N1 on influenza activity. An average rate of 71 cases of influenza-like illness (ILI)/1000 consultations was reported, which was greater than the rate in the preceding 3 years. Laboratory surveillance showed that the annual proportion of specimens positive for influenza was 25·4% in 2009, representing a significant increase over the proportions of 5·4%, 11·6% and 12·2% in 2006, 2007 and 2008, respectively. A total of 414 ILI outbreaks were reported in 2009, which was a marked increase compared to the previous 3 years. Influenza activity reached a record high in Shenzhen in 2009. Seasonal A/H3N2 was the dominant strain during the summer and was gradually replaced by pandemic H1N1. A semi-annual cycle for influenza circulation began to appear due to the emergence of pandemic H1N1.

Reuse, Recycle, Reweigh: Combating Influenza through Efficient Sequential Bayesian Computation for Massive Data

Massive datasets in the gigabyte and terabyte range combined with the availability of increasingly sophisticated statistical tools yield analyses at the boundary of what is computationally feasible. Compromising in the face of this computational burden by partitioning the dataset into more tractable sizes results in stratified analyses, removed from the context that justified the initial data collection. In a Bayesian framework, these stratified analyses generate intermediate realizations, often compared using point estimates that fail to account for the variability within and correlation between the distributions these realizations approximate. However, although the initial concession to stratify generally precludes the more sensible analysis using a single joint hierarchical model, we can circumvent this outcome and capitalize on the intermediate realizations by extending the dynamic iterative reweighting MCMC algorithm. In doing so, we reuse the available realizations by reweighting them with importance weights, recycling them into a now tractable joint hierarchical model. We apply this technique to intermediate realizations generated from stratified analyses of 687 influenza A genomes spanning 13 years allowing us to revisit hypotheses regarding the evolutionary history of influenza within a hierarchical statistical framework.

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.