Non-random reassortment in human influenza A viruses

IAVCP (Influenza A Virus Consensus and Phylogeny): Automatic Identification of the Genomic Sequence of the Influenza A Virus from High-Throughput Sequencing Data

Recently, high-throughput sequencing of influenza A viruses has become a routine test. It should be noted that the extremely high diversity of the influenza A virus complicates the task of determining the sequences of all eight genome segments. For a fast and accurate analysis, it is necessary to select the most suitable reference for each segment. At the same time, there is no standardized method in the field of decoding sequencing results that allows the user to update the sequence databases to which the reads obtained by virus sequencing are compared. The IAVCP (influenza A virus consensus and phylogeny) was developed with the goal of automatically analyzing high-throughput sequencing data of influenza A viruses. Its goals include the extraction of a consensus genome directly from paired raw reads. In addition, the pipeline enables the identification of potential reassortment events in the evolutionary history of the virus of interest by analyzing the topological structure of phylogenetic trees that are automatically reconstructed.

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app .

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

A Conserved Stem-Loop Structure within ORF5 Is a Frequent Recombination Hotspot for Porcine Reproductive and Respiratory Syndrome Virus 1 (PRRSV-1) with a Particular Modified Live Virus (MLV) Strain

The emergence of recombinant PRRSV strains has been observed for more than a decade. These recombinant viruses are characterized by a genome that contains genetic material from at least two different parental strains. Due to the advanced sequencing techniques and a growing number of data bank entries, the role of PRRSV recombinants has become increasingly important since they are sometimes associated with clinical outbreaks. Chimeric viruses observed more recently are products of PRRSV wild-type and vaccine strains. Here, we report on three PRRSV-1 isolates from geographically distant farms with differing clinical manifestations. A sequencing and recombination analysis revealed that these strains are crossovers between different wild-type strains and the same modified live virus vaccine strain. Interestingly, the recombination breakpoint of all analyzed isolates appears at the beginning of open reading frame 5 (ORF5). RNA structure predictions indicate a conserved stem loop in close proximity to the recombination hotspot, which is a plausible cause of a polymerase template switch during RNA replication. Further research into the mechanisms of the stem loop is needed to help understand the PRRSV recombination process and the role of MLVs as parental strains.

Cellular and Natural Viral Engineering in Cognition-Based Evolution

Neo-Darwinism conceptualizes evolution as the continuous succession of predominately random genetic variations disciplined by natural selection. In that frame, the primary interaction between cells and the virome is relegated to host-parasite dynamics governed by selective influences. Cognition-Based Evolution regards biological and evolutionary development as a reciprocating cognition-based informational interactome for the protection of self-referential cells. To sustain cellular homeorhesis, cognitive cells collaborate to assess the validity of ambiguous biological information. That collective interaction involves coordinate measurement, communication, and active deployment of resources as Natural Cellular Engineering. These coordinated activities drive multicellularity, biological development, and evolutionary change. The virome participates as the vital intercessory among the cellular domains to ensure their shared permanent perpetuation. The interactions between the virome and the cellular domains represent active virocellular cross-communications for the continual exchange of resources. Modular genetic transfers between viruses and cells carry bioactive potentials. Those exchanges are deployed as nonrandom flexible tools among the domains in their continuous confrontation with environmental stresses. This alternative framework fundamentally shifts our perspective on viral-cellular interactions, strengthening established principles of viral symbiogenesis. Pathogenesis can now be properly appraised as one expression of a range of outcomes between cells and viruses within a larger conceptual framework of Natural Viral Engineering as a co-engineering participant with cells. It is proposed that Natural Viral Engineering should be viewed as a co-existent facet of Natural Cellular Engineering within Cognition-Based Evolution.

TreeKnit: Inferring ancestral reassortment graphs of influenza viruses

When two influenza viruses co-infect the same cell, they can exchange genome segments in a process known as reassortment. Reassortment is an important source of genetic diversity and is known to have been involved in the emergence of most pandemic influenza strains. However, because of the difficulty in identifying reassortment events from viral sequence data, little is known about their role in the evolution of the seasonal influenza viruses. Here we introduce TreeKnit, a method that infers ancestral reassortment graphs (ARG) from two segment trees. It is based on topological differences between trees, and proceeds in a greedy fashion by finding regions that are compatible in the two trees. Using simulated genealogies with reassortments, we show that TreeKnit performs well in a wide range of settings and that it is as accurate as a more principled bayesian method, while being orders of magnitude faster. Finally, we show that it is possible to use the inferred ARG to better resolve segment trees and to construct more informative visualizations of reassortments.

Influenza viruses evolve quickly and escape immune defenses which requires frequent update of vaccines. Understanding this evolution is key to an effective public health response. The genome of influenza viruses is made up of 8 pieces called segments, each coding for different viral proteins. Within each segment, evolution is an asexual process in which genetic diversity is generated by mutations. But influenza also diversifies through reassortment which can occur when two different viruses infect the same cell: offsprings can then contain a combination of segments from both viruses. Reassortment is akin to sexual reproduction and can generate viruses that combine segments from diverged viral lineages. Reassortment is a crucial component of viral evolution, but it is challenging to reconstruct where reassortments happened and which segments share history. Here, we develop a method called TreeKnit to detect reassortment events. TreeKnit is based on genealogical trees of single segments that can be reconstructed using standard bioinformatics tools. Inconsistencies between these trees are then used as signs of reassortment. We show that TreeKnit is as accurate as other recent methods, but runs much faster. Our method will facilitate the study of reassortment and its consequences for influenza evolution.

Rapid emergence of a PB2 D701N substitution during adaptation of an H9N2 avian influenza virus in mice

H9N2 avian influenza viruses (AIVs) have been isolated frequently from multiple avian species and, occasionally, from humans. To explore the potential molecular basis of cross-species transmission of H9N2 AIVs, an H9N2 AIV (A/chicken/Zhejiang/221/2016) was serially passaged in mouse lung. The results showed that the mouse-adapted H9N2 virus exhibited higher virulence and replicated more efficiently in mouse lung and liver. Whole-genome sequencing showed an amino acid substitution, D701N, in the PB2 protein, which is likely associated with the increased replicative ability of H9N2 virus in mice. The rapid emergence of adaptive substitutions indicates the necessity of continuous monitoring of H9N2 virus in poultry.

Whole-genome analysis to determine the rate and patterns of intra-subtype reassortment among influenza type-A viruses in Africa

Influenza type-A viruses (IAVs) present a global burden of human respiratory infections and mortality. Genome reassortment is an important mechanism through which epidemiologically novel influenza viruses emerge and a core step in the safe reassortment-incompetent live-attenuated influenza vaccine development. Currently, there are no data on the rate, spatial and temporal distribution, and role of reassortment in the evolution and diversification of IAVs circulating in Africa. We aimed to detect intra-subtype reassortment among Africa pandemic H1N1pdm09 (2009-10), seasonal H1N1pdm09 (2011-20), and seasonal H3N2 viruses and characterize the genomic architecture and temporal and spatial distribution patterns of the resulting reassortants. Our study was nested within the Uganda National Influenza Surveillance Programme. Next-generation sequencing was used to generate whole genomes (WGs) from 234 H1N1pdm09 (n = 116) and H3N2 (n = 118) viruses sampled between 2010 and 2018 from seven districts in Uganda. We combined our newly generated WGs with 658 H1N1pdm09 and 1131 H3N2 WGs sampled between 1994 and 2020 across Africa and identified reassortants using an automated Graph Incompatibility Based Reassortment Finder software. Viral reassortment rates were estimated using a coalescent reassortant constant population model. Phylogenetic analysis was used to assess the effect of reassortment on viral genetic evolution. We observed a high frequency of intra-subtype reassortment events, 12 · 4 per cent (94/758) and 20 · 9 per cent (256/1,224), and reassortants, 13 · 3 per cent (101/758) and 38 · 6 per cent (472/1,224), among Africa H1N1pdm09 and H3N2 viruses, respectively. H1N1pdm09 reassorted at higher rates (0.1237-0.4255) than H3N2 viruses (0 · 00912-0.0355 events/lineage/year), a case unique to Uganda. Viral reassortants were sampled in 2009 through 2020, except in 2012. 78 · 2 per cent (79/101) of H1N1pdm09 reassortants acquired new non-structural, while 57 · 8 per cent (273/472) of the H3N2 reassortants had new hemagglutinin (H3) genes. Africa H3N2 viruses underwent more reassortment events involving larger reassortant sets than H1N1pdm09 viruses. Viruses with a specific reassortment architecture circulated for up to five consecutive years in specific countries and regions. The Eastern (Uganda and Kenya) and Western Africa harboured 84 · 2 per cent (85/101) and 55 · 9 per cent (264/472) of the continent's H1N1pdm09 and H3N2 reassortants, respectively. The frequent reassortment involving multi-genes observed among Africa IAVs showed the intracontinental viral evolution and diversification possibly sustained by viral importation from outside Africa and/or local viral genomic mixing and transmission. Novel reassortant viruses emerged every year, and some persisted in different countries and regions, thereby presenting a risk of influenza outbreaks in Africa. Our findings highlight Africa as part of the global influenza ecology and the advantage of implementing routine whole-over partial genome sequencing and analyses to monitor circulating and detect emerging viruses. Furthermore, this study provides evidence and heightens our knowledge on IAV evolution, which is integral in directing vaccine strain selection and the update of master donor viruses used in recombinant vaccine development.

Reassortment Network of Influenza A Virus

Influenza A virus (IAV) genomes are composed of eight single-stranded RNA segments. Genetic exchange through reassortment of the segmented genomes often endows IAVs with new genetic characteristics, which may affect transmissibility and pathogenicity of the viruses. However, a comprehensive understanding of the reassortment history of IAVs remains lacking. To this end, we assembled 40,296 whole-genome sequences of IAVs for analysis. Using a new clustering method based on Mean Pairwise Distances in the phylogenetic trees, we classified each segment of IAVs into clades. Correspondingly, reassortment events among IAVs were detected by checking the segment clade compositions of related genomes under specific environment factors and time period. We systematically identified 1,927 possible reassortment events of IAVs and constructed their reassortment network. Interestingly, minimum spanning tree of the reassortment network reproved that swine act as an intermediate host in the reassortment history of IAVs between avian species and humans. Moreover, reassortment patterns among related subtypes constructed in this study are consistent with previous studies. Taken together, our genome-wide reassortment analysis of all the IAVs offers an overview of the leaping evolution of the virus and a comprehensive network representing the relationships of IAVs.

Whole-genome-based phylogenomic analysis of the Belgian 2016-2017 influenza A(H3N2) outbreak season allows improved surveillance

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.

Rotavirus A Genome Segments Show Distinct Segregation and Codon Usage Patterns

Reassortment of the Rotavirus A (RVA) 11-segment dsRNA genome may generate new genome constellations that allow RVA to expand its host range or evade immune responses. Reassortment may also produce phylogenetic incongruities and weakly linked evolutionary histories across the 11 segments, obscuring reassortment-specific epistasis and changes in substitution rates. To determine the co-segregation patterns of RVA segments, we generated time-scaled phylogenetic trees for each of the 11 segments of 789 complete RVA genomes isolated from mammalian hosts and compared the segments’ geodesic distances. We found that segments 4 (VP4) and 9 (VP7) occupied significantly different tree spaces from each other and from the rest of the genome. By contrast, segments 10 and 11 (NSP4 and NSP5/6) occupied nearly indistinguishable tree spaces, suggesting strong co-segregation. Host-species barriers appeared to vary by segment, with segment 9 (VP7) presenting the weakest association with host species. Bayesian Skyride plots were generated for each segment to compare relative genetic diversity among segments over time. All segments showed a dramatic decrease in diversity around 2007 coinciding with the introduction of RVA vaccines. To assess selection pressures, codon adaptation indices and relative codon deoptimization indices were calculated with respect to different host genomes. Codon usage varied by segment with segment 11 (NSP5) exhibiting significantly higher adaptation to host genomes. Furthermore, RVA codon usage patterns appeared optimized for expression in humans and birds relative to the other hosts examined, suggesting that translational efficiency is not a barrier in RVA zoonosis.

Gene Segment Interactions Can Drive the Emergence of Dominant Yet Suboptimal Gene Constellations During Influenza Virus Reassortment

A segmented genome enables influenza virus to undergo reassortment when two viruses infect the same cell. Although reassortment is involved in the creation of pandemic influenza strains and is routinely used to produce influenza vaccines, our understanding of the factors that drive the emergence of dominant gene constellations during this process is incomplete. Recently, we defined a spectrum of interactions between the gene segments of the A/Udorn/307/72 (H3N2) (Udorn) strain that occur within virus particles, a major interaction being between the NA and PB1 gene segments. In addition, we showed that the Udorn PB1 is preferentially incorporated into reassortant viruses that express the Udorn NA. Here we use an influenza vaccine seed production model where eggs are coinfected with Udorn and the high yielding A/Puerto Rico/8/34 (H1N1) (PR8) virus and track viral genotypes through the reassortment process under antibody selective pressure to determine the impact of Udorn NA-PB1 co-selection. We discovered that 86% of the reassortants contained the PB1 from the Udorn parent after the initial co-infection and this bias towards Udorn PB1 was maintained after two further passages. Included in these were certain gene constellations containing Udorn HA, NA, and PB1 that confered low replicative fitness yet rapidly became dominant at the expense of more fit progeny, even when co-infection ratios of the two viruses favoured PR8. Fitness was not compromised, however, in the corresponding reassortants that also contained Udorn NP. Of particular note is the observation that relatively unfit reassortants could still fulfil the role of vaccine seed candidates as they provided high haemagglutinin (HA) antigen yields through co-production of non-infectious particles and/or by more HA molecules per virion. Our data illustrate the dynamics and complexity of reassortment and highlight how major gene segment interactions formed during packaging, in addition to antibody pressure, initially restrict the reassortant viruses that are formed.

Progress and Challenge in Computational Identification of Influenza Virus Reassortment

Genomic reassortment is an important evolutionary mechanism for influenza viruses. In this process, the novel viruses acquire new characteristics by the exchange of the intact gene segments among multiple influenza virus genomes, which may cause flu endemics and epidemics within or even across hosts. Due to the safety and ethical limitations of the experimental studies on influenza virus reassortment, numerous computational researches on the influenza virus reassortment have been done with the explosion of the influenza virus genomic data. A great amount of computational methods and bioinformatics databases were developed to facilitate the identification of influenza virus reassortments. In this review, we summarized the progress and challenge of the bioinformatics research on influenza virus reassortment, which can guide the researchers to investigate the influenza virus reassortment events reasonably and provide valuable insight to develop the related computational identification tools.

Non-Random Genome Editing and Natural Cellular Engineering in Cognition-Based Evolution

Neo-Darwinism presumes that biological variation is a product of random genetic replication errors and natural selection. Cognition-Based Evolution (CBE) asserts a comprehensive alternative approach to phenotypic variation and the generation of biological novelty. In CBE, evolutionary variation is the product of natural cellular engineering that permits purposive genetic adjustments as cellular problem-solving. CBE upholds that the cornerstone of biology is the intelligent measuring cell. Since all biological information that is available to cells is ambiguous, multicellularity arises from the cellular requirement to maximize the validity of available environmental information. This is best accomplished through collective measurement purposed towards maintaining and optimizing individual cellular states of homeorhesis as dynamic flux that sustains cellular equipoise. The collective action of the multicellular measurement and assessment of information and its collaborative communication is natural cellular engineering. Its yield is linked cellular ecologies and mutualized niche constructions that comprise biofilms and holobionts. In this context, biological variation is the product of collective differential assessment of ambiguous environmental cues by networking intelligent cells. Such concerted action is enabled by non-random natural genomic editing in response to epigenetic impacts and environmental stresses. Random genetic activity can be either constrained or deployed as a 'harnessing of stochasticity'. Therefore, genes are cellular tools. Selection filters cellular solutions to environmental stresses to assure continuous cellular-organismal-environmental complementarity. Since all multicellular eukaryotes are holobionts as vast assemblages of participants of each of the three cellular domains (Prokaryota, Archaea, Eukaryota) and the virome, multicellular variation is necessarily a product of co-engineering among them.

Characterization of the low-pathogenic H7N7 avian influenza virus in Shanghai, China

H7N7 avian influenza virus (AIV) can divided into low-pathogenic AIV and high-pathogenic AIV groups. It has been shown to infect humans and animals. Its prevalence state in wild birds in China remains largely unclear. In this study, a new strain of H7N7 AIV, designated CM1216, isolated from wild birds in Shanghai, China, was characterized. Phylogenetic and nucleotide sequence analyses of CM1216 revealed that HA, NA, PB1, NP, and M genes shared the highest nucleotide identity with the Japan H7 subtype AIV circulated in 2019; the PB2 and PA genes shared the highest nucleotide identity with the Korea H7 subtype AIV circulated in wild birds in 2018, while NS gene of CM1216 was 98.93% identical to that of the duck AIV circulating in Bangladesh, and they all belong to the Eurasian lineage. A Bayesian phylogenetic reconstruction of the 2 surface genes of CM1216 showed that multiple reassortments might have occurred in 2015. Mutations were found in HA (A135 T, T136S, and T160 A [H3 numbering]), M1 (N30D and T215 A), NS1 (P42S and D97 E), PB2 (R389 K), and PA (N383D) proteins; these mutations have been shown to be related to mammalian adaptation and changes in virulence of AIVs. Infection studies demonstrated that CM1216 could infect mice and cause symptoms characteristic of influenza virus infection and proliferate in the lungs without prior adaption. This study demonstrates the need for routine surveillance of AIVs in wild birds and detection of their evolution to become a virus with high pathogenicity and ability to infect humans.

HopPER: an adaptive model for probability estimation of influenza reassortment through host prediction

Background

Influenza reassortment, a mechanism where influenza viruses exchange their RNA segments by co-infecting a single cell, has been implicated in several major pandemics since 19th century. Owing to the significant impact on public health and social stability, great attention has been received on the identification of influenza reassortment.

Methods

We proposed a novel computational method named HopPER (Host-prediction-based Probability Estimation of Reassortment), that sturdily estimates reassortment probabilities through host tropism prediction using 147 new features generated from seven physicochemical properties of amino acids. We conducted the experiments on a range of real and synthetic datasets and compared HopPER with several state-of-the-art methods.

Results

It is shown that 280 out of 318 candidate reassortants have been successfully identified. Additionally, not only can HopPER be applied to complete genomes but its effectiveness on incomplete genomes is also demonstrated. The analysis of evolutionary success of avian, human and swine viruses generated through reassortment across different years using HopPER further revealed the reassortment history of the influenza viruses.

Conclusions

Our study presents a novel method for the prediction of influenza reassortment. We hope this method could facilitate rapid reassortment detection and provide novel insights into the evolutionary patterns of influenza viruses.

Evolution and rapid spread of a reassortant A(H3N2) virus that predominated the 2017-2018 influenza season

The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus's North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70 per cent of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, hemagglutination inhibition assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

Implications of segment mismatch for influenza A virus evolution

Influenza A virus (IAV) is an RNA virus with a segmented genome. These viral properties allow for the rapid evolution of IAV under selective pressure, due to mutation occurring from error-prone replication and the exchange of gene segments within a co-infected cell, termed reassortment. Both mutation and reassortment give rise to genetic diversity, but constraints shape their impact on viral evolution: just as most mutations are deleterious, most reassortment events result in genetic incompatibilities. The phenomenon of segment mismatch encompasses both RNA- and protein-based incompatibilities between co-infecting viruses and results in the production of progeny viruses with fitness defects. Segment mismatch is an important determining factor of the outcomes of mixed IAV infections and has been addressed in multiple risk assessment studies undertaken to date. However, due to the complexity of genetic interactions among the eight viral gene segments, our understanding of segment mismatch and its underlying mechanisms remain incomplete. Here, we summarize current knowledge regarding segment mismatch and discuss the implications of this phenomenon for IAV reassortment and diversity.

Fitness cost of reassortment in human influenza

Reassortment, which is the exchange of genome sequence between viruses co-infecting a host cell, plays an important role in the evolution of segmented viruses. In the human influenza virus, reassortment happens most frequently between co-existing variants within the same lineage. This process breaks genetic linkage and fitness correlations between viral genome segments, but the resulting net effect on viral fitness has remained unclear. In this paper, we determine rate and average selective effect of reassortment processes in the human influenza lineage A/H3N2. For the surface proteins hemagglutinin and neuraminidase, reassortant variants with a mean distance of at least 3 nucleotides to their parent strains get established at a rate of about 10⁻² in units of the neutral point mutation rate. Our inference is based on a new method to map reassortment events from joint genealogies of multiple genome segments, which is tested by extensive simulations. We show that intra-lineage reassortment processes are, on average, under substantial negative selection that increases in strength with increasing sequence distance between the parent strains. The deleterious effects of reassortment manifest themselves in two ways: there are fewer reassortment events than expected from a null model of neutral reassortment, and reassortant strains have fewer descendants than their non-reassortant counterparts. Our results suggest that influenza evolves under ubiquitous epistasis across proteins, which produces fitness barriers against reassortment even between co-circulating strains within one lineage.

The genome of the human influenza virus consists of 8 disjoint RNA polymer segments. These segments can undergo reassortment: when two viruses co-infect a host cell, they can produce viral offspring with a new combination of segments. In this paper, we show that reassortment within a given influenza lineage induces a fitness cost that increases in strength with increasing genetic distance of the parent viruses. Our finding suggests that evolution continuously produces viral proteins whose fitness depends on each other; reassortment reduces fitness by breaking up successful combinations of proteins. Thus, selection across proteins constrains viral evolution within a given lineage, and it may be an important factor in defining a viral species.

Seasonal H3N2 and 2009 Pandemic H1N1 Influenza A Viruses Reassort Efficiently but Produce Attenuated Progeny

Reassortment of gene segments between coinfecting influenza A viruses (IAVs) facilitates viral diversification and has a significant epidemiological impact on seasonal and pandemic influenza. Since 1977, human IAVs of H1N1 and H3N2 subtypes have cocirculated with relatively few documented cases of reassortment. We evaluated the potential for viruses of the 2009 pandemic H1N1 (pH1N1) and seasonal H3N2 lineages to reassort under experimental conditions. Results of heterologous coinfections with pH1N1 and H3N2 viruses were compared to those obtained following coinfection with homologous, genetically tagged, pH1N1 viruses as a control. High genotype diversity was observed among progeny of both coinfections; however, diversity was more limited following heterologous coinfection. Pairwise analysis of genotype patterns revealed that homologous reassortment was random while heterologous reassortment was characterized by specific biases. pH1N1/H3N2 reassortant genotypes produced under single-cycle coinfection conditions showed a strong preference for homologous PB2-PA combinations and general preferences for the H3N2 NA, pH1N1 M, and H3N2 PB2 except when paired with the pH1N1 PA or NP. Multicycle coinfection results corroborated these findings and revealed an additional preference for the H3N2 HA. Segment compatibility was further investigated by measuring chimeric polymerase activity and growth of selected reassortants in human tracheobronchial epithelial cells. In guinea pigs inoculated with a mixture of viruses, parental H3N2 viruses dominated but reassortants also infected and transmitted to cage mates. Taken together, our results indicate that strong intrinsic barriers to reassortment between seasonal H3N2 and pH1N1 viruses are few but that the reassortants formed are attenuated relative to parental strains.IMPORTANCE The genome of IAV is relatively simple, comprising eight RNA segments, each of which typically encodes one or two proteins. Each viral protein carries out multiple functions in coordination with other viral components and the machinery of the cell. When two IAVs coinfect a cell, they can exchange genes through reassortment. The resultant progeny viruses often suffer fitness defects due to suboptimal interactions among divergent viral components. The genetic diversity generated through reassortment can facilitate the emergence of novel outbreak strains. Thus, it is important to understand the efficiency of reassortment and the factors that limit its potential. The research described here offers new tools for studying reassortment between two strains of interest and applies those tools to viruses of the 2009 pandemic H1N1 and seasonal H3N2 lineages, which currently cocirculate in humans and therefore have the potential to give rise to novel epidemic strains.

The effective rate of influenza reassortment is limited during human infection

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited.

The influenza virus is an important cause of disease in the human population. During the course of an infection the virus can evolve rapidly. An important mechanism of viral evolution is reassortment, whereby different segments of the influenza genome are shuffled with other segments, producing new viral combinations. Here we study natural selection and reassortment during the course of infections occurring in human hosts. Examining viral genome sequence data from these infections, we note that genetic variants that were acquired during the growth of viruses in culture are selected against in the human host. In addition, we find evidence that the effective rate of reassortment is low. We suggest that the spatial separation between viruses in different parts of the host airway may limit the extent to which genetically distinct segments reassort with one another. Within the global population of influenza viruses, reassortment remains an important factor. However, reassortment is not so rapid as to exclude the possibility of interactions between genome segments affecting the course of influenza evolution during a single infection.

Frequency of influenza H3N2 intra-subtype reassortment: attributes and implications of reassortant spread

BACKGROUND

Increasing evidence suggests that influenza reassortment not only contributes to the emergence of new human pandemics but also plays an important role in seasonal influenza epidemics, disease severity, evolution, and vaccine efficacy. We studied this process within 2091 H3N2 full genomes utilizing a combination of the latest reassortment detection tools and more conventional phylogenetic analyses.

RESULTS

We found that the amount of H3N2 intra-subtype reassortment depended on the number of sampled genomes, occurred with a steady frequency of 3.35%, and was not affected by the geographical origins, evolutionary patterns, or previous reassortment history of the virus. We identified both single reassortant genomes and reassortant clades, each clade representing one reassortment event followed by successful spread of the reassorted variant in the human population. It was this spread that was mainly responsible for the observed high presence of H3N2 intra-subtype reassortant genomes. The successfully spread variants were generally sampled within one year of their formation, highlighting the risk of their rapid spread but also presenting an opportunity for their rapid detection. Simultaneous spread of several different reassortant lineages was observed, and despite their limited average lifetime, second and third generation reassortment was detected, as well as reassortment between viruses belonging to different vaccine-associated clades, likely displaying differing antigenic properties. Some of the spreading reassortants remained confined to certain geographical regions, while others, sharing common properties in amino acid positions of the HA, NA, and PB2 segments, were found throughout the world.

CONCLUSIONS

Detailed surveillance of seasonal influenza reassortment patterns and variant properties may provide unique information needed for prediction of spread and construction of future influenza vaccines.

Vaccine Design for H5N1 Based on B- and T-cell Epitope Predictions

From 2003 to 2013, Indonesia had the highest number of avian influenza A cases in humans, with 192 cases and 160 fatalities. Avian influenza is caused by influenza virus type A, such as subtype H5N1. This virus has two glycoproteins: hemagglutinin and neuraminidase, which will become the primary target to be neutralized by vaccine. Vaccine is the most effective immunologic intervention. In this study, we use the epitope-based vaccine design from hemagglutinin and neuraminidase of H5N1 Indonesian strain virus by using immunoinformatics approach in order to predict the binding of B-cell and T-cell epitopes (class I and class II human leukocyte antigen [HLA]). BCPREDS was used to predict the B-cell epitope. Propred, Propred I, netMHCpan, and netMHCIIpan were used to predict the T-cell epitope. Two B-cell epitopes of hemagglutinin candidates and one B-cell epitope of neuraminidase candidates were obtained to bind T-cell CD4(+) (class II HLA), and also five T-cell epitope hemagglutinin and four T-cell epitope neuraminidase were obtained to bind T-cell CD8(+) (class I HLA). The visualization of epitopes was done using MOE 2008.10. It shows that the binding affinity of epitope-HLA was based on minimum binding free energy (ΔG binding). Based on this result, visualization, and dynamic simulation, four hemagglutinin epitopes (MEKIVLLLA, CPYLGSPSF, KCQTPMGAI, and IGTSTLNQR) and two neuraminidase epitopes (NPNQKIITI and CYPDAGEIT) were computed as having the best binding affinity from HLA ligand. The results mentioned above are from in silico experiments and need to be validated using wet experiment.

Nanomicroarray and multiplex next-generation sequencing for simultaneous identification and characterization of influenza viruses

Conventional methods for detection and discrimination of influenza viruses are time consuming and labor intensive. We developed a diagnostic platform for simultaneous identification and characterization of influenza viruses that uses a combination of nanomicroarray for screening and multiplex next-generation sequencing (NGS) assays for laboratory confirmation. The nanomicroarray was developed to target hemagglutinin, neuraminidase, and matrix genes to identify influenza A and B viruses. PCR amplicons synthesized by using an adapted universal primer for all 8 gene segments of 9 influenza A subtypes were detected in the nanomicroarray and confirmed by the NGS assays. This platform can simultaneously detect and differentiate multiple influenza A subtypes in a single sample. Use of these methods as part of a new diagnostic algorithm for detection and confirmation of influenza infections may provide ongoing public health benefits by assisting with future epidemiologic studies and improving preparedness for potential influenza pandemics.

Recombination in viruses: mechanisms, methods of study, and evolutionary consequences

Recombination is a pervasive process generating diversity in most viruses. It joins variants that arise independently within the same molecule, creating new opportunities for viruses to overcome selective pressures and to adapt to new environments and hosts. Consequently, the analysis of viral recombination attracts the interest of clinicians, epidemiologists, molecular biologists and evolutionary biologists. In this review we present an overview of three major areas related to viral recombination: (i) the molecular mechanisms that underlie recombination in model viruses, including DNA-viruses (Herpesvirus) and RNA-viruses (Human Influenza Virus and Human Immunodeficiency Virus), (ii) the analytical procedures to detect recombination in viral sequences and to determine the recombination breakpoints, along with the conceptual and methodological tools currently used and a brief overview of the impact of new sequencing technologies on the detection of recombination, and (iii) the major areas in the evolutionary analysis of viral populations on which recombination has an impact. These include the evaluation of selective pressures acting on viral populations, the application of evolutionary reconstructions in the characterization of centralized genes for vaccine design, and the evaluation of linkage disequilibrium and population structure.

The Possible Impact of Vaccination for Seasonal Influenza on Emergence of Pandemic Influenza via Reassortment

BACKGROUND

One pathway through which pandemic influenza strains might emerge is reassortment from coinfection of different influenza A viruses. Seasonal influenza vaccines are designed to target the circulating strains, which intuitively decreases the prevalence of coinfection and the chance of pandemic emergence due to reassortment. However, individual-based analyses on 2009 pandemic influenza show that the previous seasonal vaccination may increase the risk of pandemic A(H1N1) pdm09 infection. In view of pandemic influenza preparedness, it is essential to understand the overall effect of seasonal vaccination on pandemic emergence via reassortment.

METHODS AND FINDINGS

In a previous study we applied a population dynamics approach to investigate the effect of infection-induced cross-immunity on reducing such a pandemic risk. Here the model was extended by incorporating vaccination for seasonal influenza to assess its potential role on the pandemic emergence via reassortment and its effect in protecting humans if a pandemic does emerge. The vaccination is assumed to protect against the target strains but only partially against other strains. We find that a universal seasonal vaccine that provides full-spectrum cross-immunity substantially reduces the opportunity of pandemic emergence. However, our results show that such effectiveness depends on the strength of infection-induced cross-immunity against any novel reassortant strain. If it is weak, the vaccine that induces cross-immunity strongly against non-target resident strains but weakly against novel reassortant strains, can further depress the pandemic emergence; if it is very strong, the same kind of vaccine increases the probability of pandemic emergence.

CONCLUSIONS

Two types of vaccines are available: inactivated and live attenuated, only live attenuated vaccines can induce heterosubtypic immunity. Current vaccines are effective in controlling circulating strains; they cannot always help restrain pandemic emergence because of the uncertainty of the oncoming reassortant strains, however. This urges the development of universal vaccines for prevention of pandemic influenza.

Intrasubtype reassortments cause adaptive amino acid replacements in H3N2 influenza genes

Reassortments and point mutations are two major contributors to diversity of Influenza A virus; however, the link between these two processes is unclear. It has been suggested that reassortments provoke a temporary increase in the rate of amino acid changes as the viral proteins adapt to new genetic environment, but this phenomenon has not been studied systematically. Here, we use a phylogenetic approach to infer the reassortment events between the 8 segments of influenza A H3N2 virus since its emergence in humans in 1968. We then study the amino acid replacements that occurred in genes encoded in each segment subsequent to reassortments. In five out of eight genes (NA, M1, HA, PB1 and NS1), the reassortment events led to a transient increase in the rate of amino acid replacements on the descendant phylogenetic branches. In NA and HA, the replacements following reassortments were enriched with parallel and/or reversing replacements; in contrast, the replacements at sites responsible for differences between antigenic clusters (in HA) and at sites under positive selection (in NA) were underrepresented among them. Post-reassortment adaptive walks contribute to adaptive evolution in Influenza A: in NA, an average reassortment event causes at least 2.1 amino acid replacements in a reassorted gene, with, on average, 0.43 amino acid replacements per evolving post-reassortment lineage; and at least ~9% of all amino acid replacements are provoked by reassortments.

New approaches for unravelling reassortment pathways

BACKGROUND

Every year the human population encounters epidemic outbreaks of influenza, and history reveals recurring pandemics that have had devastating consequences. The current work focuses on the development of a robust algorithm for detecting influenza strains that have a composite genomic architecture. These influenza subtypes can be generated through a reassortment process, whereby a virus can inherit gene segments from two different types of influenza particles during replication. Reassortant strains are often not immediately recognised by the adaptive immune system of the hosts and hence may be the source of pandemic outbreaks. Owing to their importance in public health and their infectious ability, it is essential to identify reassortant influenza strains in order to understand the evolution of this virus and describe reassortment pathways that may be biased towards particular viral segments. Phylogenetic methods have been used traditionally to identify reassortant viruses. In many studies up to now, the assumption has been that if two phylogenetic trees differ, it is because reassortment has caused them to be different. While phylogenetic incongruence may be caused by real differences in evolutionary history, it can also be the result of phylogenetic error. Therefore, we wish to develop a method for distinguishing between topological inconsistency that is due to confounding effects and topological inconsistency that is due to reassortment.

RESULTS

The current work describes the implementation of two approaches for robustly identifying reassortment events. The algorithms rest on the idea of significance of difference between phylogenetic trees or phylogenetic tree sets, and subtree pruning and regrafting operations, which mimic the effect of reassortment on tree topologies. The first method is based on a maximum likelihood (ML) framework (MLreassort) and the second implements a Bayesian approach (Breassort) for reassortment detection. We focus on reassortment events that are found by both methods. We test both methods on a simulated dataset and on a small collection of real viral data isolated in Hong Kong in 1999.

CONCLUSIONS

The nature of segmented viral genomes present many challenges with respect to disease. The algorithms developed here can effectively identify reassortment events in small viral datasets and can be applied not only to influenza but also to other segmented viruses. Owing to computational demands of comparing tree topologies, further development in this area is necessary to allow their application to larger datasets.

Reassortment between two serologically unrelated bluetongue virus strains is flexible and can involve any genome segment

Coinfection of a cell by two different strains of a segmented virus can give rise to a "reassortant" with phenotypic characteristics that might differ from those of the parental strains. Bluetongue virus (BTV) is a double-stranded RNA (dsRNA) segmented virus and the cause of bluetongue, a major infectious disease of livestock. BTV exists as at least 26 different serotypes (BTV-1 to BTV-26). Prompted by the isolation of a field reassortant between BTV-1 and BTV-8, we systematically characterized the process of BTV reassortment. Using a reverse genetics approach, our study clearly indicates that any BTV-1 or BTV-8 genome segment can be rescued in the heterologous "backbone." To assess phenotypic variation as a result of reassortment, we examined viral growth kinetics and plaque sizes in in vitro experiments and virulence in an experimental mouse model of bluetongue disease. The monoreassortants generated had phenotypes that were very similar to those of the parental wild-type strains both in vitro and in vivo. Using a forward genetics approach in cells coinfected with BTV-1 and BTV-8, we have shown that reassortants between BTV-1 and BTV-8 are generated very readily. After only four passages in cell culture, we could not detect wild-type BTV-1 or BTV-8 in any of 140 isolated viral plaques. In addition, most of the isolated reassortants contained heterologous VP2 and VP5 structural proteins, while only 17% had homologous VP2 and VP5 proteins. Our study has shown that reassortment in BTV is very flexible, and there is no fundamental barrier to the reassortment of any genome segment. Given the propensity of BTV to reassort, it is increasingly important to have an alternative classification system for orbiviruses.

Co-circulation of influenza A virus strains and emergence of pandemic via reassortment: the role of cross-immunity

Reassortment is an important evolutionary route for influenza A viruses to generate pandemic strains. The pre-requisite for reassortment to occur is co-infection of different influenza virus strains in the same host population. Empirical evidence suggests that co-circulation of influenza A virus strains is common and co-infection in patients has been reported. Whether a novel virus can successfully spread among a host population is determined by its life-history (infectivity and infectious period). It is also well known that different influenza A strains interfere through the immune response of human body cells. The reassortant virus strain generated from co-infections deviates dramatically in antigenic and genetic properties from its parental strains such that human populations have limited immunity against it. We consider a mathematical model which includes two strains of influenza virus within a standard SIR model and integrate life history and cross-immunity into the evolutionary dynamics of influenza virus. We assume that, following primary infection by one strain and recovery, individuals are susceptible to secondary infection by the other strain only but with reduced probability due to cross-immunity. Co-infection is included to examine how life-history and cross-immunity interplay to regulate the co-circulation and co-infection of different influenza A virus strains in human populations. Further, we introduce novel strains via reassortment and investigate how the opportunities of a reassortant strain developing into a pandemic are constrained by its life-history and the residual immunity within human populations. We find that though the probability of pandemic emergence via reassortment increases with transmissibility of reassortant strains and the rate of reassortment, the existence of cross-immunity acquired through previous infections or vaccination can greatly constrain pandemic emergence.

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.

Use of influenza A viruses expressing reporter genes to assess the frequency of double infections in vitro

Exchange of gene segments between mammalian and avian influenza A viruses may lead to the emergence of potential pandemic influenza viruses. Since co-infection of single cells with two viruses is a prerequisite for reassortment to take place, we assessed frequencies of double-infection in vitro using influenza A/H5N1 and A/H1N1 viruses expressing the reporter genes eGFP or mCherry. Double-infected A549 and Madin-Darby canine kidney cells were detected by confocal microscopy and flow cytometry.

Viral reassortment as an information exchange between viral segments

Viruses have an extraordinary ability to diversify and evolve. For segmented viruses, reassortment can introduce drastic genomic and phenotypic changes by allowing a direct exchange of genetic material between coinfecting strains. For instance, multiple influenza pandemics were caused by reassortments of viruses typically found in separate hosts. What is unclear, however, are the underlying mechanisms driving these events and the level of intrinsic bias in the diversity of strains that emerge from coinfection. To address this problem, previous experiments looked for correlations between segments of strains that coinfect cells in vitro. Here, we present an information theory approach as the natural mathematical framework for this question. We study, for influenza and other segmented viruses, the extent to which a virus's segments can communicate strain information across an infection and among one another. Our approach goes beyond previous association studies and quantifies how much the diversity of emerging strains is altered by patterns in reassortment, whether biases are consistent across multiple strains and cell types, and if significant information is shared among more than two segments. We apply our approach to a new experiment that examines reassortment patterns between the 2009 H1N1 pandemic and seasonal H1N1 strains, contextualizing its segmental information sharing by comparison with previously reported strain reassortments. We find evolutionary patterns across classes of experiments and previously unobserved higher-level structures. Finally, we show how this approach can be combined with virulence potentials to assess pandemic threats.

A comprehensive analysis of reassortment in influenza A virus

Genetic reassortment plays a vital role in the evolution of the influenza virus and has historically been linked with the emergence of pandemic strains. Reassortment is believed to occur when a single host - typically swine - is simultaneously infected with multiple influenza strains. The reassorted viral strains with novel gene combinations tend to easily evade the immune system in other host species, satisfying the basic requirements of a virus with pandemic potential. Therefore, it is vital to continuously monitor the genetic content of circulating influenza strains and keep an eye out for new reassortants. We present a new approach to identify reassortants from large data sets of influenza whole genome nucleotide sequences and report the results of the first ever comprehensive search for reassortants of all published influenza A genomic data. 35 of the 52 well supported candidate reassortants we found are reported here for the first time while our analysis method offers new insight that enables us to draw a more detailed picture of the origin of some of the previously reported reassortants. A disproportionately high number (13/52) of the candidate reassortants found were the result of the introduction of novel hemagglutinin and/or neuraminidase genes into a previously circulating virus. The method described in this paper may contribute towards automating the task of routinely searching for reassortants among newly sequenced strains.

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.

Detecting transmission and reassortment events for influenza A viruses with genotype profile method

Evolutionary events of transmission and reassortment for influenza A viruses were traditionally detected by phylogenetic analysis for influenza viruses' eight gene segments. Because the phylogenetic analysis can be complex, we developed genotype profile method which packaged the phylogenetic algorithms to analyze combination patterns of gene segments and integrated epidemiology knowledge. With the method, the analysis of reassortment and transmission becomes a simple and reliable process that combines genotypes, which is identical for the biological process of the virus. An application called IVEE that implements the method is available for all academic users to apply the method http://snptransformer.sourceforge.net. Furthermore, we found that a previous summary of the reassortment events in swine influenza A viruses may be inaccurate.

FluReF, an automated flu virus reassortment finder based on phylogenetic trees

Background

Reassortments are events in the evolution of the genome of influenza (flu), whereby segments of the genome are exchanged between different strains. As reassortments have been implicated in major human pandemics of the last century, their identification has become a health priority. While such identification can be done “by hand” on a small dataset, researchers and health authorities are building up enormous databases of genomic sequences for every flu strain, so that it is imperative to develop automated identification methods. However, current methods are limited to pairwise segment comparisons.

Results

We present FluReF, a fully automated flu virus reassortment finder. FluReF is inspired by the visual approach to reassortment identification and uses the reconstructed phylogenetic trees of the individual segments and of the full genome. We also present a simple flu evolution simulator, based on the current, source-sink, hypothesis for flu cycles. On synthetic datasets produced by our simulator, FluReF, tuned for a 0% false positive rate, yielded false negative rates of less than 10%. FluReF corroborated two new reassortments identified by visual analysis of 75 Human H3N2 New York flu strains from 2005–2008 and gave partial verification of reassortments found using another bioinformatics method.

Methods

FluReF finds reassortments by a bottom-up search of the full-genome and segment-based phylogenetic trees for candidate clades—groups of one or more sampled viruses that are separated from the other variants from the same season. Candidate clades in each tree are tested to guarantee confidence values, using the lengths of key edges as well as other tree parameters; clades with reassortments must have validated incongruencies among segment trees.

Conclusions

FluReF demonstrates robustness of prediction for geographically and temporally expanded datasets, and is not limited to finding reassortments with previously collected sequences. The complete source code is available from http://lcbb.epfl.ch/software.html.

Why do RNA viruses recombine?

Recombination occurs in many RNA viruses and can be of major evolutionary significance. However, rates of recombination vary dramatically among RNA viruses, which can range from clonal to highly recombinogenic. Here, we review the factors that might explain this variation in recombination frequency and show that there is little evidence that recombination is favoured by natural selection to create advantageous genotypes or purge deleterious mutations, as predicted if recombination functions as a form of sexual reproduction. Rather, recombination rates seemingly reflect larger-scale patterns of viral genome organization, such that recombination may be a mechanistic by-product of the evolutionary pressures acting on other aspects of virus biology.

GiRaF: robust, computational identification of influenza reassortments via graph mining

Reassortments in the influenza virus—a process where strains exchange genetic segments—have been implicated in two out of three pandemics of the 20th century as well as the 2009 H1N1 outbreak. While advances in sequencing have led to an explosion in the number of whole-genome sequences that are available, an understanding of the rate and distribution of reassortments and their role in viral evolution is still lacking. An important factor in this is the paucity of automated tools for confident identification of reassortments from sequence data due to the challenges of analyzing large, uncertain viral phylogenies. We describe here a novel computational method, called GiRaF (Graph-incompatibility-based Reassortment Finder), that robustly identifies reassortments in a fully automated fashion while accounting for uncertainties in the inferred phylogenies. The algorithms behind GiRaF search large collections of Markov chain Monte Carlo (MCMC)-sampled trees for groups of incompatible splits using a fast biclique enumeration algorithm coupled with several statistical tests to identify sets of taxa with differential phylogenetic placement. GiRaF correctly finds known reassortments in human, avian, and swine influenza populations, including the evolutionary events that led to the recent ‘swine flu’ outbreak. GiRaF also identifies several previously unreported reassortments via whole-genome studies to catalog events in H5N1 and swine influenza isolates.

A phylogenetic approach to detecting reassortments in viruses with segmented genomes

When multiple strains of viruses with segmented genomes co-infect a single cell, strains with novel genomic constellations may be created. This mutational process, called reassortment, has caused pandemics of influenza A virus in 1957 and 1968. Here a phylogenetic approach to detecting reassortments, which can be used even when the phylogenetic tree constructed for all strains analyzed is unreliable, is presented. A quartet of strains is examined at a time, where a phylogenetic tree is constructed for each genomic segment and the topology is compared among segments only when all quartet trees are supported with a statistical significance. The occurrence of reassortment and the segments involved in the reassortment event are inferred according to the pattern of topological difference among segments. The reassortment point for a pattern is inferred by superimposing the exterior branches of relevant quartet trees on the all-strains trees. In the analysis of H1N1 and H3N2 human influenza A viruses, a topological difference was observed for all pairs of genomic segments, suggesting that there is no pair of segments that has always co-segregated in reassortment during the evolutionary history of these viruses. When the reassortment point was inferred for the pattern of topological difference that was supported with the largest number of quartets for each virus, the results appeared to be mostly correct, suggesting that the method was largely reliable.

Theoretical aspects of immunity

The immune system recognizes a myriad of invading pathogens and their toxic products. It does so with a finite repertoire of antibodies and T cell receptors. We here describe theories that quantify the dynamics of the immune system. We describe how the immune system recognizes antigens by searching the large space of receptor molecules. We consider in some detail the theories that quantify the immune response to influenza and dengue fever. We review theoretical descriptions of the complementary evolution of pathogens that occurs in response to immune system pressure. Methods including bioinformatics, molecular simulation, random energy models, and quantum field theory contribute to a theoretical understanding of aspects of immunity.

Reassortment patterns in Swine influenza viruses

Three human influenza pandemics occurred in the twentieth century, in 1918, 1957, and 1968. Influenza pandemic strains are the results of emerging viruses from non-human reservoirs to which humans have little or no immunity. At least two of these pandemic strains, in 1957 and in 1968, were the results of reassortments between human and avian viruses. Also, many cases of swine influenza viruses have reportedly infected humans, in particular, the recent H1N1 influenza virus of swine origin, isolated in Mexico and the United States. Pigs are documented to allow productive replication of human, avian, and swine influenza viruses. Thus it has been conjectured that pigs are the “mixing vessel” that create the avian-human reassortant strains, causing the human pandemics. Hence, studying the process and patterns of viral reassortment, especially in pigs, is a key to better understanding of human influenza pandemics. In the last few years, databases containing sequences of influenza A viruses, including swine viruses, collected since 1918 from diverse geographical locations, have been developed and made publicly available. In this paper, we study an ensemble of swine influenza viruses to analyze the reassortment phenomena through several statistical techniques. The reassortment patterns in swine viruses prove to be similar to the previous results found in human viruses, both in vitro and in vivo, that the surface glycoprotein coding segments reassort most often. Moreover, we find that one of the polymerase segments (PB1), reassorted in the strains responsible for the last two human pandemics, also reassorts frequently.

Reassortment patterns in Swine influenza viruses

Previous human influenza pandemics were the results of emerging viruses from non-human reservoirs, with at least two caused by strains of mixed human and avian origin. Also, many cases of swine influenza viruses have reportedly infected humans, including the recent human H1N1 strain, isolated in Mexico and the United States. Pigs are documented to get infected with human, avian, and swine viruses and allow productive replication, thus it has been conjectured that they are the "mixing vessel" that create reassortant strains, causing the human pandemics. In this paper, we apply several statistical techniques to an ensemble of publicly available swine viruses to study the reassortment phenomena. The reassortment patterns in swine viruses confirm previous results found in human viruses that the glycoprotein coding segments reassort most often. Moreover, one of the polymerase segments (PB1), reassorted in the strains responsible for the last two human pandemics of 1957 and 1968, also reassorts frequently.

Cluster analysis of the origins of the new influenza A(H1N1) virus

In March and April 2009, a new strain of influenza A(H1N1) virus has been isolated in Mexico and the United States. Since the initial reports more than 10,000 cases have been reported to the World Health Organization, all around the world. Several hundred isolates have already been sequenced and deposited in public databases. We have studied the genetics of the new strain and identified its closest relatives through a cluster analysis approach. We show that the new virus combines genetic information related to different swine influenza viruses. Segments PB2, PB1, PA, HA, NP and NS are related to swine H1N2 and H3N2 influenza viruses isolated in North America. Segments NA and M are related to swine influenza viruses isolated in Eurasia.

Evolution of the influenza a virus: some new advances

Influenza is an RNA virus that causes mild to severe respiratory symptoms in humans and other hosts. Every year approximately half a million people around the world die from seasonal Influenza. But this number is substantially larger in the case of pandemics, with the most dramatic instance being the 1918 "Spanish flu" that killed more than 50 million people worldwide. In the last few years, thousands of Influenza genomic sequences have become publicly available, including the 1918 pandemic strain and many isolates from non-human hosts. Using these data and developing adequate bioinformatic and statistical tools, some of the major questions surrounding Influenza evolution are becoming tractable. Are the mutations and reassortments random? What are the patterns behind the virus's evolution? What are the necessary and sufficient conditions for a virus adapted to one host to infect a different host? Why is Influenza seasonal? In this review, we summarize some of the recent progress in understanding the evolution of the virus.

Highly conserved regions of influenza a virus polymerase gene segments are critical for efficient viral RNA packaging

The genome of the influenza A virus is composed of eight different segments of negative-sense RNA. These eight segments are incorporated into budding virions in an equimolar ratio through a mechanism that is not fully understood. Two different models have been proposed for packaging the viral ribonucleoproteins into newly assembling virus particles: the random-incorporation model and the selective-incorporation model. In the last few years, increasing evidence from many different laboratories that supports the selective-incorporation model has been accumulated. In particular, different groups have shown that some large viral RNA regions within the coding sequences at both the 5' and 3' ends of almost every segment are sufficient for packaging foreign RNA sequences. If the packaging regions are crucial for the viability of the virus, we would expect them to be conserved. Using large-scale analysis of influenza A virus sequences, we developed a method of identifying conserved RNA regions whose conservation cannot be explained by population structure or amino acid conservation. Interestingly, the conserved sequences are located within the regions identified as important for efficient packaging. By utilizing influenza virus reverse genetics, we have rescued mutant viruses containing synonymous mutations within these highly conserved regions. Packaging of viral RNAs in these viruses was analyzed by reverse transcription using a universal primer and quantitative PCR for individual segments. Employing this approach, we have identified regions in the polymerase gene segments that, if mutated, result in reductions of more than 90% in the packaging of that particular polymerase viral RNA. Reductions in the level of packaging of a polymerase viral RNA frequently resulted in reductions of other viral RNAs as well, and the results form a pattern of hierarchy of segment interactions. This work provides further evidence for a selective packaging mechanism for influenza A viruses, demonstrating that these highly conserved regions are important for efficient packaging.