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Seasonal influenza epidemics are associated with high mortality and morbidity in the human population. Influenza surveillance is critical for providing information to national influenza programmes and for making vaccine composition predictions. Vaccination prevents viral infections, but rapid influenza evolution results in emerging mutants that differ antigenically from vaccine strains. Current influenza surveillance relies on Sanger sequencing of the haemagglutinin (HA) gene. Its classification according to World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC) guidelines is based on combining certain genotypic amino acid mutations and phylogenetic analysis. Next-generation sequencing technologies enable a shift to whole-genome sequencing (WGS) for influenza surveillance, but this requires laboratory workflow adaptations and advanced bioinformatics workflows. In this study, 253 influenza A(H3N2) positive clinical specimens from the 2016–2017 Belgian season underwent WGS using the Illumina MiSeq system. HA-based classification according to WHO/ECDC guidelines did not allow classification of all samples. A new approach, considering the whole genome, was investigated based on using powerful phylogenomic tools including beast and Nextstrain, which substantially improved phylogenetic classification. Moreover, Bayesian inference via beast facilitated reassortment detection by both manual inspection and computational methods, detecting intra-subtype reassortants at an estimated rate of 15 %. Real-time analysis (i.e. as an outbreak is ongoing) via Nextstrain allowed positioning of the Belgian isolates into the globally circulating context. Finally, integration of patient data with phylogenetic groups and reassortment status allowed detection of several associations that would have been missed when solely considering HA, such as hospitalized patients being more likely to be infected with A(H3N2) reassortants, and the possibility to link several phylogenetic groups to disease severity indicators could be relevant for epidemiological monitoring. Our study demonstrates that WGS offers multiple advantages for influenza monitoring in (inter)national influenza surveillance, and proposes an improved methodology. This allows leveraging all information contained in influenza genomes, and allows for more accurate genetic characterization and reassortment detection.

As one of the main influenza antigens, neuraminidase (NA) in H3N2 virus has evolved extensively for more than 50 years due to continuous immune pressure. While NA has emerged as an effective vaccine target recently, biophysical constraints on the antigenic evolution of NA remain largely elusive. Here, we apply deep mutational scanning to characterize the local fitness landscape in an antigenic region of NA in six different human H3N2 strains that were isolated around 10 years apart. The local fitness landscape correlates well among strains and the pairwise epistasis is highly conserved. Our analysis further demonstrates that local net charge governs the pairwise epistasis in this antigenic region. In addition, we show that residue coevolution in this antigenic region can be predicted by charge states and pairwise epistasis. Overall, this study demonstrates the importance of quantifying epistasis and the underlying biophysical constraint for building a predictive model of influenza evolution.

The antigenic drift theory states that influenza evolves via the gradual accumulation of mutations, decreasing a host's immune protection against previous strains. Influenza vaccines are designed accordingly, under the premise of antigenic drift. However, a paradox exists at the centre of influenza research. If influenza evolved primarily through mutation in multiple epitopes, multiple influenza strains should co-circulate. Such a multitude of strains would render influenza vaccines quickly inefficacious. Instead, a single or limited number of strains dominate circulation each influenza season. Unless additional constraints are placed on the evolution of influenza, antigenic drift does not adequately explain these observations. Here, we explore the constraints placed on antigenic drift and a competing theory of influenza evolution - antigenic thrift. In contrast to antigenic drift, antigenic thrift states that immune selection targets epitopes of limited variability, which constrain the variability of the virus. We explain the implications of antigenic drift and antigenic thrift and explore their current and potential uses in the context of influenza vaccine design. ispartof: VACCINES vol:9 issue:6 ispartof: location:Switzerland status: published

Pigs have long been recognized as “mixing vessels” in which new viruses are formed by reassortment involving various influenza virus lineages (avian, animal, human). However, surveillance of swine influenza viruses only gained real significance after the 2009 pandemic. A fundamentally important point is the fact that there is still no regular surveillance of swine flu in Russia, and the role of swine viruses is underestimated since, as a rule, they do not cause serious disease in animals. Since the pig population in Russia is large, it is obvious that the lack of monitoring and insufficient study of swine influenza evolution constitutes a gap in animal influenza surveillance, not only for Russia, but globally. A 6 year joint effort enabled identification of SIV subtypes that circulate in the pig population of Russia’s European geographic region. The swine influenza viruses isolated were antigenically and genetically diverse. Some were similar to human influenza viruses of A(H1N1)pdm09 and A(H3N2) subtype, while others were reassortant A(H1pdm09N2) and A(H1avN2) and were antigenically distinct from human H1N1 and H1N1pdm09 strains. Analysis of swine serum samples collected throughout the seasons showed that the number of sera positive for influenza viruses has increased in recent years. This indicates that swine populations are highly susceptible to infection with human influenza viruses. It also stresses the need for regular SIV surveillance, monitoring of viral evolution, and strengthening of pandemic preparedness.

Seasonal influenza vaccines represent a positive intervention to limit the spread of the virus and protect public health. Yet continual influenza evolution and its ability to evade immunity pose a constant threat. For these reasons, vaccines with improved potency and breadth of protection remain an important need. We previously developed a next-generation influenza vaccine that displays the trimeric influenza hemagglutinin (HA) on a ferritin nanoparticle (NP) to optimize its presentation. Similar to other vaccines, HA-nanoparticle vaccine efficacy is increased by the inclusion of adjuvants during immunization. To identify the optimal adjuvants to enhance influenza immunity, we systematically analyzed TLR agonists for their ability to elicit immune responses. HA-NPs were compatible with nearly all adjuvants tested, including TLR2, TLR4, TLR7/8, and TLR9 agonists, squalene oil-in-water mixtures, and STING agonists. In addition, we chemically conjugated TLR7/8 and TLR9 ligands directly to the HA-ferritin nanoparticle. These TLR agonist-conjugated nanoparticles induced stronger antibody responses than nanoparticles alone, which allowed the use of a 5000-fold-lower dose of adjuvant than traditional admixtures. One candidate, the oil-in-water adjuvant AF03, was also tested in non-human primates and showed strong induction of neutralizing responses against both matched and heterologous H1N1 viruses. These data suggest that AF03, along with certain TLR agonists, enhance strong neutralizing antibody responses following influenza vaccination and may improve the breadth, potency, and ultimately vaccine protection in humans.

Mortality rates in influenza appear to have been shaped by evolution. During the 1918 pandemic, mortality rates were lower in children compared with adults. This mortality difference occurs in a wide variety of infectious diseases. It has been replicated in mice and might be due to greater tolerance of infection, not greater resistance. Importantly, combination treatment with inexpensive and widely available generic drugs (e.g. statins and angiotensin receptor blockers) might change the damaging host response in adults to a more tolerant response in children. These drugs might work by modifying endothelial dysfunction, mitochondrial biogenesis and immunometabolism. Treating the host response might be the only practical way to reduce global mortality during the next influenza pandemic. It might also help reduce mortality due to seasonal influenza and other forms of acute critical illness. To realize these benefits, we need laboratory and clinical studies of host response treatment before and after puberty.

Seasonal influenza causes a substantial public health burden, as well as being a key substrate for pandemic emergence. Future climatic and demographic changes may alter both the magnitude, frequency and timing of influenza epidemics and the prospects for pathogen evolution, however, these issues have not been addressed systematically. Here, we use a parsimonious influenza model, grounded in theoretical understanding of the link between climate, demography and transmission to project future changes globally. We find that climate change generally acts to reduce the intensity of influenza epidemics as specific humidity increases. However, this reduction in intensity is accompanied by increased seasonal epidemic persistence with latitude, which may increase suitability for year-round local influenza evolution. Using a range of population growth scenarios, we find that the number of global locations with high evolution suitability may double by 2050. High population growth in tropical Africa could thus make this region a locus of novel strain emergence, shifting the current focus from South East Asia.

Biological species, including viruses, change through generations and over time in the process known as evolution. Viruses may evolve at high, uneven, and fluctuating rates among genome sites. The accumulated changes, through either mutation or recombination with other species, are first fixed in the genome of successful individuals that give rise to genetic lineages. The relationship between biological lineages related by common descent is called ‘phylogeny’. For inferring phylogeny, the differences between aligned sequences of genomes and proteins are quantified and depicted in the form of a tree, in which contemporary species and their intermediate and common ancestors occupy, respectively, the terminal nodes, internal nodes, and the root. The tree is characterized by a topology, length of branches, shape, and the root position. A complex mathematical apparatus has been developed for phylogeny inference that can evaluate inter-species differences, facilitate tree building and comparison of trees, and assess the fit between data and tree through, typically, computationally intensive calculations. A reconstructed tree is an approximation of the true phylogeny that practically remains unknown. The phylogenetic analysis is used in applied and fundamental virus research, including epidemiology, diagnostics, forensic studies, phylogeography, evolutionary studies, and virus taxonomy. It can provide an evolutionary perspective on variation of any trait that can be measured for a group of viruses.

A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Here, we launch INSaFLU (“INSide the FLU”), which, to the best of our knowledge, is the first influenza-specific bioinformatics free web-based suite that deals with primary data (reads) towards the automatic generation of the output data that are actually the core first-line “genetic requests” for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants’ annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform advanced, multi-step software intensive analyses in a user-friendly manner without previous training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects’ management, being a transparent and highly flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus completely cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tune data analysis. This platform additionally flags samples as “putative mixed infections” if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional “consensus-based” influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants, but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. In summary, INSaFLU supplies public health laboratories and influenza researchers with an open “one size fits all” framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.INSaFLU can be accessed through https://insaflu.insa.pt (see homepage view in Figure 1).

Influenza H9N2 subtype viruses and their reassortants (such as H7N9) are posing increasing threats to birds and humans in China. During 2009–2013, multiple novel subtype viruses with H9N2 original genes emerged in China. Yet, the genetic evolution of H9N2 viruses in various host organisms in China has not been systematically investigated since 2009. In the present study, we performed large-scale sequence analysis of H9N2 viral genomes from public databases, representing the spectrum of viruses isolated from birds, mammals and humans in China from 1994 to 2013, and updated the clade classification for each segment. We identified 117 distinct genotypes in 730 H9N2 viruses. We analyzed the sequences of all eight segments in each virus and found three important time points: the years 2000, 2006 and 2010. In the periods divided by these years, genotypic diversity, geographic distribution and host range changed considerably. Genotypic diversity fluctuated greatly in 2000 and 2006. Since 2010, a single genotype became predominant in poultry throughout China, and the eastern coastal region became the newly identified epidemic center. Throughout their 20-year prevalence in China, H9N2 influenza viruses have emerged and adapted from aquatic birds to chickens. The minor avian species and wild birds exacerbated H9N2 genotypes by providing diversified genes, and chickens were the most prevalent vector in which the viruses evolved and expanded their prevalence. It is the necessity for surveillance and disease control on live-bird markets, poultry farms and wild-bird habitats in China.

Phylogenetic networks are used to estimate evolutionary relationships among biological entities or taxa involving reticulate events such as horizontal gene transfer, hybridization, recombination, and reassortment. In the past decade, many phylogenetic tree and network reconstruction methods have been proposed. Despite that they are highly accurate in reconstructing simple to moderate complex reticulate events, the performance decreases when several reticulate events are present simultaneously. In this paper, we proposed QS-Net, a phylogenetic network reconstruction method taking advantage of information on the relationship among six taxa. To evaluate the performance of QS-Net, we conducted experiments on three artificial sequence data simulated from an evolutionary tree, an evolutionary network involving three reticulate events, and a complex evolutionary network involving five reticulate events. Comparison with popular phylogenetic methods including Neighbor-Joining, Split-Decomposition, Neighbor-Net, and Quartet-Net suggests that QS-Net is comparable with other methods in reconstructing tree-like evolutionary histories, while it outperforms them in reconstructing reticulate events. In addition, we also applied QS-Net in real data including a bacterial taxonomy data consisting of 36 bacterial species and the whole genome sequences of 22 H7N9 influenza A viruses. The results indicate that QS-Net is capable of inferring commonly believed bacterial taxonomy and influenza evolution as well as identifying novel reticulate events. The software QS-Net is publically available at https://github.com/Tmyiri/QS-Net.

Influenza A viruses have regularly jumped to new hosts to cause epidemics or pandemics, an evolutionary process that involves variation in the viral traits necessary to overcome host barriers and facilitate transmission. Mice are not a natural host for influenza virus, but are frequently used as models in studies of pathogenesis, often after multiple passages to achieve higher viral titers that result in clinical disease such as weight loss or death. Here we examine the processes of influenza A virus infection and evolution in mice by comparing deep sequence variation of a human H1N1 pandemic virus, a seasonal H3N2 virus, and a H3N2 canine influenza virus during experimental passage. We also compared replication and sequence variation in wild-type mice expressing N-glycolylneuraminic acid (Neu5Gc) with that seen in mice expressing only N-acetylneuraminic acid (Neu5Ac). Viruses derived from plasmids were propagated in MDCK cells and then passaged in mice up to four times. Full genome deep sequencing of the plasmids, cultured viruses, and viruses from mice at various passages revealed only small numbers of mutational changes. The H3N2 canine influenza virus showed increases in frequency of sporadic mutations in the PB2, PA, and NA segments. The H1N1 pandemic virus grew well in mice, and while it exhibited the maintenance of some minority mutations, there was no clear adaptive evolution. The H3N2 seasonal virus did not establish in the mice. Finally, there were no clear sequence differences associated with the presence or absence of Neu5Gc.SIGNIFICANCEMice are commonly used as a model to study the growth and virulence of influenza A viruses in mammals, but are not a natural host and have distinct sialic acid receptor profiles compared to humans. Using experimental infections with different subtypes of influenza A virus derived from different hosts we found that evolution of influenza A virus in mice did not necessarily proceed through the linear accumulation of host-adaptive mutations, that there was variation in the patterns of mutations detected in each repetition, and the mutation dynamics depended on the virus examined. In addition, variation in the viral receptor, sialic acid, did not effect influenza evolution in this model. Overall this shows that mice provide a useful animal model for influenza, but that host passage evolution will vary depending on the virus being tested.

The ability of influenza viruses to rapidly evolve has caused significant challenges in viral surveillance, diagnosis, and therapeutic development. Molecular sequencing methods, though powerful tools for monitoring influenza evolution at the genetic level, are not able to fully characterize the antigenic properties of influenza viruses. Understanding influenza virus antigenicity is critical to vaccine development and disease prevention. Traditional immunoassays which have been widely used for evaluating influenza antigenicity have limited throughput. To alleviate these problems, new bioanalytical tools to investigate influenza antigenicity by measuring antibody-antigen binding are an active area of research. Herein, we review immunosensor technologies from the aspects of various sensing principles, while highlighting recent developments in multiplex, label-free detection strategies. Highlighted technologies include electrochemical immunosensors relying on impedimetric detection; these demonstrate simple design and cost effectiveness for mass production. Antibody arrays implemented on an optical interferometric sensor system allow systematic characterization of influenza antigenicity. Quartz microbalance immunosensors are highly sensitive but have yet to be explored for multiplex sensing. Immunosensors made on lateral flow strips have shown promise in rapid diagnosis of influenza subtypes. We anticipate that these and other technologies discussed in the review will facilitate advances in the study of influenza, and other viral pathogens.

Influenza A is a serious disease that causes significant morbidity and mortality, and vaccines against the seasonal influenza disease are of variable effectiveness. In this paper, we discuss use of the $p_{\rm epitope}$ method to predict the dominant influenza strain and the expected vaccine effectiveness in the coming flu season. We illustrate how the effectiveness of the 2014/2015 A/Texas/50/2012 [clade 3C.1] vaccine against the A/California/02/2014 [clade 3C.3a] strain that emerged in the population can be estimated via pepitope. In addition, we show by a multidimensional scaling analysis of data collected through 2014, the emergence of a new A/New Mexico/11/2014-like cluster [clade 3C.2a] that is immunologically distinct from the A/California/02/2014-like strains., 19 pages, 4 figures

Influenza A virus is characterized by high genetic diversity. However, most of what is known about influenza evolution has come from consensus sequences sampled at the epidemiological scale that only represent the dominant virus lineage within each infected host. Less is known about the extent of within-host virus diversity and what proportion of this diversity is transmitted between individuals. To characterize virus variants that achieve sustainable transmission in new hosts, we examined within-host virus genetic diversity in household donor-recipient pairs from the first wave of the 2009 H1N1 pandemic when seasonal H3N2 was co-circulating. Although the same variants were found in multiple members of the community, the relative frequencies of variants fluctuated, with patterns of genetic variation more similar within than between households. We estimated the effective population size of influenza A virus across donor-recipient pairs to be approximately 100-200 contributing members, which enabled the transmission of multiple lineages, including antigenic variants.

Identifying viral mutations that confer escape from antibodies is crucial for understanding the interplay between immunity and viral evolution. We describe a high-throughput approach to quantify the selection that monoclonal antibodies exert on all single amino-acid mutations to a viral protein. This approach, mutational antigenic profiling, involves creating all replication-competent protein variants of a virus, selecting with antibody, and using deep sequencing to identify enriched mutations. We use mutational antigenic profiling to comprehensively identify mutations that enable influenza virus to escape four monoclonal antibodies targeting hemagglutinin, and validate key findings with neutralization assays. We find remarkable mutation-level idiosyncrasy in antibody escape: for instance, at a single residue targeted by two antibodies, some mutations escape both antibodies while other mutations escape only one or the other. Because mutational antigenic profiling rapidly maps all mutations selected by an antibody, it is useful for elucidating immune specificities and interpreting the antigenic consequences of viral genetic variation., Author summary Many viruses evolve rapidly, and this evolution sometimes enables them to escape antibodies that would otherwise neutralize their infectivity. An important aspect of studying this evolution is determining which viral mutations can mediate antibody escape. The classic way of identifying such mutations is to select or test them one by one. However, a vast number of possible mutations can be made to a virus. For instance, there are over 10,000 single amino-acid mutations that can be made to the most abundant surface protein of influenza virus, hemagglutinin. This is too many to test one by one, and so all previous studies of antibody escape have examined just a fraction of the possible amino-acid mutations to any given viral protein. Here we describe a new approach to quantify the selection that an antibody exerts on all these mutations in a single experiment. This approach enables us to reproducibly and sensitively identify mutations that affect antibody neutralization—for instance, at individual sites in hemagglutinin, we can distinguish which of several different mutations have the largest effect on antibody escape. The ability to completely map viral escape from antibodies opens the door to much more detailed characterization of viral antigenic evolution.

We systematically and quantitatively evaluate whether endoplasmic reticulum (ER) proteostasis factors impact the mutational tolerance of secretory pathway proteins. We focus on influenza hemaggluttinin (HA), a viral membrane protein that folds in the host’s ER via a complex pathway. By integrating chemical methods to modulate ER proteostasis with deep mutational scanning to assess mutational tolerance, we discover that upregulation of ER proteostasis factors broadly enhances HA mutational tolerance across diverse structural elements. Remarkably, this proteostasis network-enhanced mutational tolerance occurs at the same sites where mutational tolerance is most reduced by propagation at fever-like temperature. These findings have important implications for influenza evolution, because influenza immune escape is contingent on HA possessing sufficient mutational tolerance to evade antibodies while maintaining the capacity to fold and function. More broadly, this work provides the first experimental evidence that ER proteostasis mechanisms define the mutational tolerance and, therefore, the evolution of secretory pathway proteins.

Influenza vaccine composition is reviewed before every flu season because influenza viruses constantly evolve through antigenic changes. To inform vaccine updates, laboratories that contribute to the World Health Organization Global Influenza Surveillance and Response System monitor the antigenic phenotypes of circulating viruses all year round. Vaccine strains are selected in anticipation of the upcoming influenza season to allow adequate time for production. A mismatch between vaccine strains and predominant strains in the flu season can significantly reduce vaccine effectiveness. Models for predicting the evolution of influenza based on the relationship of genetic mutations and antigenic characteristics of circulating viruses may inform vaccine strain selection decisions. We review the literature on state-of-the-art tools and prediction methodologies utilized in modeling the evolution of influenza to inform vaccine strain selection. We then discuss areas that are open for improvement and need further research.

Since its emergence in 2013, the H7N9 low-pathogenic avian influenza virus (LPAIV) has been circulating in domestic poultry in China, causing five waves of human infections. A novel H7N9 highly pathogenic avian influenza virus (HPAIV) variant possessing multiple basic amino acids at the cleavage site of the hemagglutinin (HA) protein was first reported in two cases of human infection in January 2017. More seriously, those novel H7N9 HPAIV variants have been transmitted and caused outbreaks on poultry farms in eight provinces in China. Herein, we demonstrate the presence of three different amino acid motifs at the cleavage sites of these HPAIV variants which were isolated from chickens and humans and likely evolved from the preexisting LPAIVs. Animal experiments showed that these novel H7N9 HPAIV variants are both highly pathogenic in chickens and lethal to mice. Notably, human-origin viruses were more pathogenic in mice than avian viruses, and the mutations in the PB2 gene associated with adaptation to mammals (E627K, A588V, and D701N) were identified by next-generation sequencing (NGS) and Sanger sequencing of the isolates from infected mice. No polymorphisms in the key amino acid substitutions of PB2 and HA in isolates from infected chicken lungs were detected by NGS. In sum, these results highlight the high degree of pathogenicity and the valid transmissibility of this new H7N9 variant in chickens and the quick adaptation of this new H7N9 variant to mammals, so the risk should be evaluated and more attention should be paid to this variant. IMPORTANCE Due to the recent increased numbers of zoonotic infections in poultry and persistent human infections in China, influenza A(H7N9) virus has remained a public health threat. Most of the influenza A(H7N9) viruses reported previously have been of low pathogenicity. Now, these novel H7N9 HPAIV variants have caused human infections in three provinces and outbreaks on poultry farms in eight provinces in China. We analyzed the molecular features and compared the relative characteristics of one H7N9 LPAIV and two H7N9 HPAIVs isolated from chickens and two human-origin H7N9 HPAIVs in chicken and mouse models. We found that all HPAIVs both are highly pathogenic and have valid transmissibility in chickens. Strikingly, the human-origin viruses were more highly pathogenic than the avian-origin viruses in mice, and dynamic mutations were confirmed by NGS and Sanger sequencing. Our findings offer important insight into the origin, adaptation, pathogenicity, and transmissibility of these viruses to both poultry and mammals.

Influenza viruses undergo rapid antigenic evolution. Analysis of a large dataset of influenza virus sequences, using host age as a proxy for immune experience, shows no evidence for immune positive selection driving antigenic evolution in individual infected humans.

Most studies on seasonal influenza A/H3N2 virus adaptation have focused on the main antigenic gene, haemagglutinin. However, there is increasing evidence that the genome-wide genetic background of novel antigenic variants can influence these variants’ emergence probabilities and impact their patterns of dominance in the population. This suggests that non-antigenic genes may be important in shaping the viral evolutionary dynamics. To better understand the role of selection on non-antigenic genes in the adaptive evolution of seasonal influenza viruses, we here develop a simple population genetic model that considers a virus with one antigenic and one non-antigenic gene segment. By simulating this model under different regimes of selection and reassortment, we find that the empirical patterns of lineage turnover for the antigenic and non-antigenic gene segments are best captured when there is both limited viral coinfection and selection operating on both gene segments. In contrast, under a scenario of only neutral evolution in the non-antigenic gene segment, we see persistence of multiple lineages for long periods of time in that segment, which is not compatible with the observed molecular evolutionary patterns. Further, we find that reassortment, occurring in coinfected individuals, can increase the speed of viral adaptive evolution by primarily reducing selective interference and genetic linkage effects mediated by the non-antigenic gene segment. Together, these findings suggest that, for influenza, with 6 internal or non-antigenic gene segments, the evolutionary dynamics of novel antigenic variants are likely to be influenced by the genome-wide genetic background as a result of linked selection among both beneficial and deleterious mutations.

The hemagglutinin subtypes from Influenza A can be divided into distinct lineages. This is important for tracing the evolutionary history of the gene. It allows regional lineages to be identified and studied. The process of lineage identification depends on phylogenetic analysis to identify the distinct clades within the data. Identification of lineages within the Influenza Internal genes would help to simplify the analysis of reassortment where these genes are transferred between subtypes. In this paper we show that a rapid clustering method can be used to assign lineages to the internal gene segments without the need for a full phylogenetic analysis.

Influenza A virus can quickly acquire genetic mutations that may be associated with increased virulence, host switching or antigenic changes. To provide new insights into the evolutionary dynamics and the adaptive strategies of distinct avian influenza lineages in response to environmental and host factors, we compared two distinct avian influenza epidemics caused by the H7N1 and H7N3 subtypes that circulated under similar epidemiological conditions, including the same domestic species reared in the same densely populated poultry area for similar periods of time. The two strains appear to have experienced largely divergent evolution: the H7N1 viruses evolved into a highly pathogenic form, while the H7N3 did not. However, a more detailed molecular and evolutionary analysis revealed several common features: (i) the independent acquisition of 32 identical mutations throughout the entire genome; (ii) the evolution and persistence of two sole genetic groups with similar genetic characteristics; (iii) a comparable pattern of amino acid variability of the HA proteins during the low pathogenic epidemics; and (iv) similar rates of nucleotide substitutions. These findings suggest that the evolutionary trajectories of viruses with the same virulence level circulating in analogous epidemiological conditions may be similar. In addition, our deep sequencing analysis of 15 samples revealed that 17 of the 32 parallel mutations were already present at the beginning of the two epidemics, suggesting that fixation of these mutations may occur with different mechanisms, which may depend on the fitness gain provided by each mutation. This highlighted the difficulties in predicting the acquisition of mutations that can be correlated to viral adaptation to specific epidemiological conditions or to changes in virus virulence.

One important feature of the mammalian immune system is the highly specific binding of antigens to antibodies. Antibodies generated in response to one infection may also provide some level of cross immunity to other infections. One model to describe this cross immunity is the notion of antigenic space, which assigns each antibody and each virus a point in ℝ(n). Past studies using hemagglutination data have suggested the dimensionality of antigenic space, n, is low. We propose that influenza evolution may be modeled as a Gaussian random walk. We then show that hemagluttination data would be consistent with a walk in very high dimensions. The discrepancy between our result and prior studies is due to the fact that random walks can appear low dimensional according to a variety of analyses including principal component analysis (PCA) and multidimensional scaling (MDS). A high dimensionality of antigenic space is of importance to modelers, as it suggests a smaller role for pre-existing immunity within the host population.

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

Predicting and constraining RNA virus evolution require understanding the molecular factors that define the mutational landscape accessible to these pathogens. RNA viruses typically have high mutation rates, resulting in frequent production of protein variants with compromised biophysical properties. Their evolution is necessarily constrained by the consequent challenge to protein folding and function. We hypothesized that host proteostasis mechanisms may be significant determinants of the fitness of viral protein variants, serving as a critical force shaping viral evolution. Here, we test that hypothesis by propagating influenza in host cells displaying chemically-controlled, divergent proteostasis environments. We find that both the nature of selection on the influenza genome and the accessibility of specific mutational trajectories are significantly impacted by host proteostasis. These findings provide new insights into features of host-pathogen interactions that shape viral evolution, and into the potential design of host proteostasis-targeted antiviral therapeutics that are refractory to resistance., National Institutes of Health (U.S.) (Award 1DP2GM119162), National Institutes of Health (U.S.) (Grant P30-ES002109)

Highly pathogenic H5N1 avian influenza A viruses display a remarkable genetic and antigenic diversity. We examined to what extent genetic distances between several H5N1 viruses from different clades correlate with antigenic differences and vaccine performance. H5-specific antisera were generated, and cross-reactivity and antigenic distances between 12 different viruses were determined. In general, antigenic distances increased proportional to genetic distances although notable exceptions were observed. Antigenic distances correlated better with genetic variation in 27 selected, antigenically-relevant H5 residues, than in the complete HA1 domain. Variation in these selected residues could accurately predict the antigenic distances for a novel H5N8 virus. Protection provided by vaccines against heterologous H5N1 challenge viruses indicated that cross-protection also correlates better with genetic variation in the selected antigenically-relevant residues than in complete HA1. When time is limited, variation at these selected residues may be used to accurately predict antigenic distance and vaccine performance.

Avian influenza virus subtype H9N2 has been circulating in the Middle East since the 1990s. For uncertain reasons, H9N2 was not detected in Egyptian farms until the end of 2010. Circulation of H9N2 viruses in Egyptian poultry in the presence of the enzootic highly pathogenic H5N1 subtype adds a huge risk factor to the Egyptian poultry industry. In this study, 22 H9N2 viruses collected from 2011 to 2013 in Egypt were isolated and sequenced. The genomic signatures and protein sequences of these isolates were analyzed. Multiple mammalian-host-associated mutations were detected that favor transmission from avian to mammalian hosts. Other mutations related to virulence were also identified. Phylogenetic data showed that Egyptian H9N2 viruses were closely related to viruses isolated from neighboring Middle Eastern countries, and their HA gene resembled those of viruses of the G1-like lineage. No reassortment was detected with H5N1 subtypes. Serological analysis of H9N2 virus revealed antigenic conservation among Egyptian isolates. Accordingly, continuous surveillance that results in genetic and antigenic characterization of H9N2 in Egypt is warranted.

Influenza imposes a great burden on society, not only in its seasonal appearance that affects both humans and domesticated animals but also through the constant threat of potential pandemics. Migratory birds are considered to be the reservoir hosts for influenza viruses, but other animals must also be considered. The recently identified influenza-like virus genome, from H17N10 in bats, was shown to be markedly different from genomes of other known influenza viruses, as both its surface glycoproteins hemagglutinin (HA) and neuraminidase (NA) do not have canonical functions. However, no studies on other individual proteins from this particular virus have been reported until now. Here, we describe the structure of the N-terminal domain of PA from H17N10 influenza-like virus at 2.7-Å resolution and show that it has a fold similar to those of homologous PA domains present in more familiar influenza A virus strains. Moreover, we demonstrate that it possesses endonuclease activity and that the histidine residue in the active site is essential for this activity. Although this particular influenza virus subtype is probably not infectious for humans (even its virus state has not been confirmed in bats, as only the genome has been sequenced), reassortment of canonical influenza viruses with certain segments from H17N10 cannot be ruled out at this stage. Therefore, further studies are urgently needed for the sake of influenza prevention and control.

Infections with the influenza C virus causing respiratory symptoms are common, particularly among children. Since isolation and detection of the virus are rarely performed, compared with influenza A and B viruses, the small number of available sequences of the virus makes it difficult to analyze its evolutionary dynamics. Recently, we reported the full genome sequence of 102 strains of the virus. Here, we exploited the data to elucidate the evolutionary characteristics and phylodynamics of the virus compared with influenza A and B viruses. Along with our data, we obtained public sequence data of the hemagglutinin-esterase gene of the virus; the dataset consists of 218 unique sequences of the virus collected from 14 countries between 1947 and 2014. Informatics analyses revealed that (1) multiple lineages have been circulating globally; (2) there have been weak and infrequent selective bottlenecks; (3) the evolutionary rate is low because of weak positive selection and a low capability to induce mutations; and (4) there is no significant positive selection although a few mutations affecting its antigenicity have been induced. The unique evolutionary dynamics of the influenza C virus must be shaped by multiple factors, including virological, immunological, and epidemiological characteristics.

H5N6 is a highly pathogenic avian influenza (HPAI) and a zoonotic disease that causes recurring endemics in East Asia. At least 155 H5N6 outbreaks, including 15 human infections, have been reported in China. These repeated outbreaks have increased concern that the H5N6 virus may cross over to humans and cause a pandemic. In February, 2016, peafowls in a breeding farm exhibited a highly contagious disease. Post-mortem examinations, including RT-PCR, and virus isolation, confirmed that the highly pathogenic H5N6 influenza virus was the causative agent, and the strain was named A/Pavo Cristatus/Jiangxi/JA1/2016. In animal experiments, it exhibited high pathogenicity in chickens and an estimated median lethal dose in mice of ~104.3 TCID50. A phylogenetic analysis showed that JA1/2016 was clustered in H5 clade 2.3.4.4. FG594-like H5N6 virus from Guangdong Province was the probable predecessor of JA1/2016, and the estimated divergence time was June 2014. Furthermore, we found that H5N6 influenza viruses can be classified into the two following groups: Group 1 and Group 2. Group 2 influenza viruses have not been detected since the end of 2014, whereas Group 1 influenza viruses have continually evolved and reassorted with the “gene pool” circulating in south China, resulting in the rise of novel subtypes of this influenza virus. An increase in the number of its identified hosts, the expanding range of its distribution, and the continual evolution of H5N6 AIVs enhance the risk that an H5N6 virus may spread to other continents and cause a pandemic.

Avian influenza virus H9N2 has been endemic in birds in the Middle East, in particular in Egypt with multiple cases of human infections since 1998. Despite concerns about the pandemic threat posed by H9N2, little is known about the biological properties of H9N2 in this epicentre of infection. Here, we investigated the evolutionary dynamics of H9N2 in the Middle East and identified phylogeny-associated PB2 mutations that acted cooperatively to increase H9N2 replication/transcription in human cells. The accumulation of PB2 mutations also correlated with an increase in H9N2 virus growth in the upper and lower airways of mice and in virulence. These mutations clustered on a solvent-exposed region in the PB2-627 domain in proximity to potential interfaces with host factors. These PB2 mutations have been found at high prevalence during evolution of H9N2 in the field, indicating that they have provided a selective advantage for viral adaptation to infect poultry. Therefore, continuous prevalence of H9N2 virus in the Middle East has generated a far more fit or optimized replication phenotype, leading to an expanded viral host range, including to mammals, which may pose public health risks beyond the current outbreaks., Author summary The G1-like clade of H9N2 influenza viruses can undergo genetic reassortment with other influenza virus subtypes to produce novel zoonotic viruses, such as the Gs/GD lineage H5N1, H7N9, H10N8, and H5N8 viruses. Since 1998, the G1-like subclade of H9N2 influenza virus has been widely circulating in birds in Central Asia and the Middle East and a number of human cases have been reported. However, little is known about the biological properties of H9N2 viruses in this epicentre of infection. Our data showed that, during about two decades of evolution in nature, G1-like subclade strains evolved to produce strains with appreciably higher replication phenotypes in Central Asia and the Middle East, which led to their expanded host range, including to humans. Therefore, G1-like subclade strains in these areas may accumulate mutations to produce novel viruses and the large gene pool in these areas would enable reassortment with other influenza viruses. This study indicated the need for studies of H9N2 viruses in such areas to monitor their evolutionary dynamics and possible genetic changes.

The ecology of highly pathogenic avian influenza (HPAI) H5N1 has significantly changed from sporadic outbreaks in terrestrial poultry to persistent circulation in terrestrial and aquatic poultry and potentially in wild waterfowl. A novel genotype of HPAI H5N1 arose in 1996 in southern China and through ongoing mutation, reassortment, and natural selection, has diverged into distinct lineages and expanded into multiple reservoir hosts. The evolution of Goose/Guangdong-lineage highly pathogenic H5N1 viruses is ongoing: while stable interactions exist with some reservoir hosts, these viruses are continuing to evolve and adapt to others, and pose an un-calculable risk to sporadic hosts, including humans.

Background/Purpose Human infections by a new avian influenza A (H7N9) virus have been reported. As of April 23, 2013, there were 108 confirmed cases including 22 deaths in China. Methods Influenza protein sequences were downloaded from the Influenza Virus Resource and GISAID EpiFlu databases. Pairwise nucleotide identities were computed for assessing the evolutionary distance of H7N9 to other known avian and human viruses, and multiple sequence alignments with their position-specific entropy values were used in discussing how mutations on species-associated signature positions were introduced in the new H7N9 which may steer its way to human infection. Results This report analyzed the genomic characteristics of this new H7N9 virus. Nucleotide sequence analysis clearly reveals its origin from avian viruses. In this article, we particularly focus on its internal genes that are found to derive from H9N2—another subtype of avian influenza A virus which has been circulating in birds for years. Amino acid sequences at species-specific genomic positions were examined. Although the new virus contains mostly avian-like residues at these signature positions, it does contain several human-like signatures. For instance, at the position 627 of PB2, the new virus has human-characteristic K instead of avian-characteristic E; in addition, PB2-627K, PA-100A, PA-356R, and PA-409N are also human-like signatures in the new H7N9 virus. Conclusion The new H7N9 is an avian influenza A virus; however, it does harbor several human virus-like signatures, which raises great concern that it may have a higher probability to cross species barriers and infect humans.

Summary Background On March 30, 2013, a novel avian influenza A H7N9 virus that infects human beings was identified. This virus had been detected in six provinces and municipal cities in China as of April 18, 2013. We correlated genomic sequences from avian influenza viruses with ecological information and did phylogenetic and coalescent analyses to extrapolate the potential origins of the virus and possible routes of reassortment events. Methods We downloaded H7N9 virus genome sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID) database and public sequences used from the Influenza Virus Resource. We constructed phylogenetic trees and did 1000 bootstrap replicates for each tree. Two rounds of phylogenetic analyses were done. We used at least 100 closely related sequences for each gene to infer the overall topology, removed suspicious sequences from the trees, and focused on the closest clades to the novel H7N9 viruses. We compared our tree topologies with those from a bayesian evolutionary analysis by sampling trees (BEAST) analysis. We used the bayesian Markov chain Monte Carlo method to jointly estimate phylogenies, divergence times, and other evolutionary parameters for all eight gene fragments. We used sequence alignment and homology-modelling methods to study specific mutations regarding phenotypes, specifically addressing the human receptor binding properties. Findings The novel avian influenza A H7N9 virus originated from multiple reassortment events. The HA gene might have originated from avian influenza viruses of duck origin, and the NA gene might have transferred from migratory birds infected with avian influenza viruses along the east Asian flyway. The six internal genes of this virus probably originated from two different groups of H9N2 avian influenza viruses, which were isolated from chickens. Detailed analyses also showed that ducks and chickens probably acted as the intermediate hosts leading to the emergence of this virulent H7N9 virus. Genotypic and potential phenotypic differences imply that the isolates causing this outbreak form two separate subclades. Interpretation The novel avian influenza A H7N9 virus might have evolved from at least four origins. Diversity among isolates implies that the H7N9 virus has evolved into at least two different lineages. Unknown intermediate hosts involved might be implicated, extensive global surveillance is needed, and domestic-poultry-to-person transmission should be closely watched in the future. Funding China Ministry of Science and Technology Project 973, National Natural Science Foundation of China, China Health and Family Planning Commission, Chinese Academy of Sciences.

Revealing the frequency and determinants of reassortment among RNA genome segments is fundamental to understanding basic aspects of the biology and evolution of the influenza virus. To estimate the extent of genomic reassortment in influenza viruses circulating in North American swine, we performed a phylogenetic analysis of 139 whole-genome viral sequences sampled during 1998–2011 and representing seven antigenically distinct viral lineages. The highest amounts of reassortment were detected between the H3 and the internal gene segments (PB2, PB1, PA, NP, M and NS), while the lowest reassortment frequencies were observed among the H1γ, H1pdm and neuraminidase segments, particularly N1. Less reassortment was observed among specific haemagglutinin–neuraminidase combinations that were more prevalent in swine, suggesting that some genome constellations may be evolutionarily more stable.

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.

This is not meant as a comprehensive report of recent influenza evolution, but is instead intended as particular observations that may be of relevance. Please also note that observed patterns reflect the GISAID database and may not be entirely representative of underlying dynamics. All analyses are based on the nextflu pipeline with continual updates posted to nextflu.org. We arrive at the following results: H3N2: In H3N2, clade 3c2.a has continued to diversify genetically with complicated and rapid dynamics of different subclades. This diversification is not reflected in serological data that shows only minor to moderate antigenic evolution. Nevertheless, the highly parallel mutation patterns and the rapid rise and fall of clades suggests competitive dynamics of phenotypically distinct viruses. H1N1pdm: Very few H1N1pdm viruses have been observed in recent months. The dominant clade continues to be 6b.1 and there is little amino acid sequence variation within HA. The only notable subclade that has been growing recently is the clade bearing HA1:R205K/S183P. This clade is dominated by North American viruses and we see no evidence that this clade has a particular competitive advantage. B/Vic: Clade 1A has continued to dominate and mutation 117V has all but taken over the global population. The rise of this mutation was fairly gradual and we have no evidence that it is associated with antigenic change or other benefit to the virus. B/Yam: Clade 3 has continued to dominate. Within clade 3, a clade with mutation HA1:251V is globally at frequency of about 80% throughout 2016. Within this clade, mutation 211R is at 25% frequency. In addition, a clade without prominent amino acid mutations has been rising throughout 2016.

Influenza viruses are often propagated in a diverse set of culturing media and additional substitutions known as passage adaptation can cause extra evolution in the target strain, leading to ineffective vaccines. Using 25,482 H3N2 HA1 sequences curated from Global Initiative on Sharing All Influenza Data and National Center for Biotechnology Information databases, we found that passage adaptation is a very dynamic process that changes over time and evolves in a seesaw like pattern. After crossing the species boundary from bird to human in 1968, the influenza H3N2 virus evolves to be better adapted to the human environment and passaging them in embryonated eggs (i.e., an avian environment) leads to increasingly stronger positive selection. On the contrary, passage adaptation to the mammalian cell lines changes from positive selection to negative selection. Using two statistical tests, we identified 19 codon positions around the receptor binding domain strongly contributing to passage adaptation in the embryonated egg. These sites show strong convergent evolution and overlap extensively with positively selected sites identified in humans, suggesting that passage adaptation can confound many of the earlier studies on influenza evolution. Interestingly, passage adaptation in recent years seems to target a few codon positions in antigenic surface epitopes, which makes it difficult to produce antigenically unaltered vaccines using embryonic eggs. Our study outlines another interesting scenario whereby both convergent and adaptive evolution are working in synchrony driving viral adaptation. Future studies from sequence analysis to vaccine production need to take careful consideration of passage adaptation.

The rapid evolution of influenza A(H3N2) viruses necessitates close monitoring of their antigenic properties so the emergence and spread of antigenic drift variants can be rapidly identified. Changes in hemagglutinin (HA) acquired by contemporary A(H3N2) viruses hinder antigenic characterization by traditional methods, thus complicating vaccine strain selection. Sequence-based approaches have been used to infer virus antigenicity; however, they are time consuming and mid-throughput. To facilitate virological surveillance and epidemiological studies, we developed and validated a pyrosequencing approach that enables identification of six HA clades of contemporary A(H3N2) viruses. The identification scheme of viruses of the H3 clades 3C.2, 3C.2a, 3C.2b, 3C.3, 3C.3a, and 3C.3b is based on the interrogation of five single nucleotide polymorphisms (SNPs) within three neighboring HA regions, namely 412 to 431, 465 to 481, and 559 to 571. Two bioinformatics tools, IdentiFire (Qiagen) and FireComb (developed in-house), were utilized to expedite pyrosequencing data analysis. The assay's analytical sensitivity was 10 focus forming units, and respiratory specimens with threshold cycle ( C T ) values of

The evolution of influenza viruses is remarkably dynamic. Influenza viruses evolve rapidly in sequence and undergo frequent reassortment of different gene segments. Homologous recombination, although commonly seen as an important component of dynamic genome evolution in many other organisms, is believed to be rare in influenza. In this study, 256 gene segments from 32 influenza A genomes were examined for homologous recombination, three recombinant H1N1 strains were detected and they most likely resulted from one recombination event between two closely rated parental sequences. These findings suggest that homologous recombination in influenza viruses tends to take place between strains sharing high sequence similarity. The three recombinant strains were isolated at different time periods and they form a clade, indicating that recombinant strains could circulate. In addition, the simulation results showed that many recombinant sequences might not be detectable by currently existing recombinant detection programs when the parental sequences are of high sequence similarity. Finally, possible ways were discussed to improve the accuracy of the detection for recombinant sequences in influenza.

In addition to influenza A subtypes, two distinct lineages of influenza B virus also cause seasonal epidemics to humans. Recently, Dudas et al. have done evolutionary analyses of reassortment patterns of the virus and suggested genetic lineage relationship between PB1, PB2, and HA genes. Using genetic plasmids and reassortant viruses, we here demonstrate that a homologous lineage PB1-PB2 pair exhibits better compatibility than a heterologous one and that the lineage relationship between PB1 and HA is more important for viral replication than that between PB2 and HA. However, co-adaptation of PB1-PB2-HA genes appears to be affected by complete gene constellation. ispartof: Scientific Reports vol:6 issue:1 pages:27480- ispartof: location:England status: published

Given the frequent mutation of antigenic features, the constancy of genetic and antigenic diversity of influenza within a subtype is surprising. While the emergence of new strains and antigenic features is commonly attributed to selection by the human immune system, the mechanism that ensures the extinction of older strains remains controversial. To replicate this dynamics of replacement current models utilize mechanisms such as short-lived strain-transcending immunity, a direct competition for hosts, stochastic extinction or constrained antigenic evolution. Building on the idea of short-lived immunity we introduce a minimal model that exhibits the aforementioned dynamics of replacement. Our model relies only on competition due to an antigen specific immune-response in an unconstrained antigenic space. Furthermore the model explains the size of typical influenza epidemics as well as the tendency that new epidemics are associated with mutations of old antigens.

The distinctive features of human influenza A phylogeny have inspired many mathematical and computational studies of viral infections spreading in a host population, but our understanding of the mechanisms that shape the coupled evolution of host immunity, disease incidence and viral antigenic properties is far from complete. In this paper we explore the epidemiology and the phylogeny of a rapidly mutating pathogen in a host population with a weak immune response, that allows re-infection by the same strain and provides little cross-immunity. We find that mutation generates explosive diversity and that, as diversity grows, the system is driven to a very high prevalence level. This is in stark contrast with the behavior of similar models where mutation gives rise to a large epidemic followed by disease extinction, under the assumption that infection with a strain provides lifelong immunity. For low mutation rates, the behavior of the system shows the main qualitative features of influenza evolution. Our results highlight the importance of heterogeneity in the human immune response for understanding influenza A phenomenology. They are meant as a first step toward computationally affordable, individual based models including more complex host-pathogen interactions.

The influenza C virus is spread worldwide and causes diseases of the upper and (less frequently) lower respiratory tract in human. The virus is not pandemic, but it circulates together with pandemic influenza A and B viruses during winter months and has quite similar clinical manifestations. The influenza C virus is also encountered in animals (pigs and dogs) and is known to override the interspecific barriers of transmssion. The immune system of mammals often fails to recognize new antigenic variants of influenza C virus, which invariably arise in nature, resulting in outbreaks of diseases, although the structure of antigens in influenza C virus in general is much more stable than those of influenza viruses A and B. Variability of genetic information in natural isolates of viruses is determined by mutations, reassortment, and recombination. However, recombination events very rarely occur in genomes of negative-strand RNA viruses, including those of influenza, and virtually have no effect on their evolution. Unambiguous explanations for this phenomenon have thus far not been proposed. There is no proof of recombination processes in the influenza C virus genome. On the contrary, reassortant viruses derived from different strains of influenza C virus frequently appear in vitro and are likely to be common in nature. The genome of influenza C virus comprises seven segments. Based on the comparison of sequences in one of its genes (HEF), six genetic or antigenic lineages of this virus can be distinguished (Yamagata/26/81, Aichi/1/81, Mississippi/80, Taylor/1233/47, Sao Paulo/378/82, and Kanagawa/1/76). However, the available genetic data show that all the seven segments of the influenza C virus genome evolve independently.

In this study, we identify a recombinant pb1 gene, a recombinant MP segment and a recombinant PA segment. The pb1 gene is recombined from two Eurasia swine H1N1 influenza virus lineages. It belongs to a H1N1 swine clade circulating in Europe and Asia from 1999 to 2009. The mosaic MP segment descends from H7 avian and H1N1 human virus lineages and pertains to a large human H1N1 virus family circulating in Asia, Europe and America from 1918 to 2007. The recombinant PA segment originated from two swine H1N1 lineages is found in a swine H1N1 group prevailing in Asia and Europe from 1999 to 2003. These results collectively falsify the hypothesis that influenza virus do not evolve by homologous recombination. Since recombination not only leads to virus genome diversity but also can alter its host adaptation and pathogenecity; the genetic mechanism should not be neglected in influenza virus surveillance.

Influenza A viruses are single-stranded RNA viruses capable of evolving rapidly to adapt to environmental conditions. Examples include the establishment of a virus in a novel host or an adaptation to increasing immunity within the host population due to prior infection or vaccination against a circulating strain. Knowledge of the viral protein regions under positive selection is therefore crucial for surveillance. We have developed a method for detecting positively selected patches of sites on the surface of viral proteins, which we assume to be relevant for adaptive evolution. We measure positive selection based on dN/dS ratios of genetic changes inferred by considering the phylogenetic structure of the data and suggest a graph-cut algorithm to identify such regions. Our algorithm searches for dense and spatially distinct clusters of sites under positive selection on the protein surface. For the hemagglutinin protein of human influenza A viruses of the subtypes H3N2 and H1N1, our predicted sites significantly overlap with known antigenic and receptor-binding sites. From the structure and sequence data of the 2009 swine-origin influenza A/H1N1 hemagglutinin and PB2 protein, we identified regions that provide evidence of evolution under positive selection since introduction of the virus into the human population. The changes in PB2 overlap with sites reported to be associated with mammalian adaptation of the influenza A virus. Application of our technique to the protein structures of viruses of yet unknown adaptive behavior could identify further candidate regions that are important for host–virus interaction.