Multiple reassortment events in the evolutionary history of H1N1 influenza A virus since 1918

Effect of human H3N2 influenza virus reassortment on influenza incidence and severity during the 2017-18 influenza season in the USA: a retrospective observational genomic analysis

BACKGROUND

During the 2017-18 influenza season in the USA, there was a high incidence of influenza illness and mortality. However, no apparent antigenic change was identified in the dominant H3N2 viruses, and the severity of the season could not be solely attributed to a vaccine mismatch. We aimed to investigate whether the altered virus properties resulting from gene reassortment were underlying causes of the increased case number and disease severity associated with the 2017-18 influenza season.

METHODS

Samples included were collected from patients with influenza who were prospectively recruited during the 2016-17 and 2017-18 influenza seasons at the Johns Hopkins Hospital Emergency Departments in Baltimore, MD, USA, as well as from archived samples from Johns Hopkins Health System sites. Among 647 recruited patients with influenza A virus infection, 411 patients with whole-genome sequences were available in the Johns Hopkins Center of Excellence for Influenza Research and Surveillance network during the 2016-17 and 2017-18 seasons. Phylogenetic trees were constructed based on viral whole-genome sequences. Representative viral isolates of the two seasons were characterised in immortalised cell lines and human nasal epithelial cell cultures, and patients' demographic data and clinical outcomes were analysed.

FINDINGS

Unique H3N2 reassortment events were observed, resulting in two predominant strains in the 2017-18 season: HA clade 3C.2a2 and clade 3C.3a, which had novel gene segment constellations containing gene segments from HA clade 3C.2a1 viruses. The reassortant re3C.2a2 viruses replicated with faster kinetics and to a higher peak titre compared with the parental 3C.2a2 and 3C.2a1 viruses (48 h vs 72 h). Furthermore, patients infected with reassortant 3C.2a2 viruses had higher Influenza Severity Scores than patients infected with the parental 3C.2a2 viruses (median 3·00 [IQR 1·00-4·00] vs 1·50 [1·00-2·00]; p=0·018).

INTERPRETATION

Our findings suggest that the increased severity of the 2017-18 influenza season was due in part to two intrasubtypes, cocirculating H3N2 reassortant viruses with fitness advantages over the parental viruses. This information could help inform future vaccine development and public health policies.

FUNDING

The Center of Excellence for Influenza Research and Response in the US, National Science and Technology Council, and Chang Gung Memorial Hospital in Taiwan.

Genes involved in the limited spread of SARS-CoV-2 in the lower respiratory airways of hamsters may be associated with adaptive evolution

Novel respiratory viruses can cause a pandemic and then evolve to coexist with humans. The Omicron strain of severe acute respiratory syndrome coronavirus 2 has spread worldwide since its emergence in late 2021, and its sub-lineages are now established in human society. Compared to previous strains, Omicron is markedly less invasive in the lungs and causes less severe disease. One reason for this is that humans are acquiring immunity through previous infection and vaccination, but the nature of the virus itself is also changing. Using our newly established low-volume inoculation system, which reflects natural human infection, we show that the Omicron strain spreads less efficiently into the lungs of hamsters compared with an earlier Wuhan strain. Furthermore, by characterizing chimeric viruses with the Omicron gene in the Wuhan strain genetic background and vice versa, we found that viral genes downstream of ORF3a, but not the S gene, were responsible for the limited spread of the Omicron strain in the lower airways of the virus-infected hamsters. Moreover, molecular evolutionary analysis of SARS-CoV-2 revealed a positive selection of genes downstream of ORF3a (M and E genes). Our findings provide insight into the adaptive evolution of the virus in humans during the pandemic convergence phase.IMPORTANCEThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has spread worldwide since its emergence in late 2021, and its sub-lineages are established in human society. Compared to previous strains, the Omicron strain is less invasive in the lower respiratory tract, including the lungs, and causes less severe disease; however, the mechanistic basis for its restricted replication in the lower airways is poorly understood. In this study, using a newly established low-volume inoculation system that reflects natural human infection, we demonstrated that the Omicron strain spreads less efficiently into the lungs of hamsters compared with an earlier Wuhan strain and found that viral genes downstream of ORF3a are responsible for replication restriction in the lower respiratory tract of Omicron-infected hamsters. Furthermore, we detected a positive selection of genes downstream of ORF3a (especially the M and E genes) in SARS-CoV-2, suggesting that these genes may undergo adaptive changes in humans.

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.

Natural History of Influenza B Virus-Current Knowledge on Treatment, Resistance and Therapeutic Options

Influenza B virus (IBV) significantly impacts the health and the economy of the global population. WHO global health estimates project 1 billion flu cases annually, with 3 to 5 million resulting in severe disease and 0.3 to 0.5 million influenza-related deaths worldwide. Influenza B virus epidemics result in significant economic losses due to healthcare expenses, reduced workforce productivity, and strain on healthcare systems. Influenza B virus epidemics, such as the 1987-1988 Yamagata lineage outbreak and the 2001-2002 Victoria lineage outbreak, had a significant global impact. IBV's fast mutation and replication rates facilitate rapid adaptation to the environment, enabling the evasion of existing immunity and the development of resistance to virus-targeting treatments. This leads to annual outbreaks and necessitates the development of new vaccination formulations. This review aims to elucidate IBV's evolutionary genomic organization and life cycle and provide an overview of anti-IBV drugs, resistance, treatment options, and prospects for IBV biology, emphasizing challenges in preventing and treating IBV infection.

Evolution of Influenza A(H3N2) Viruses in 2 Consecutive Seasons of Genomic Surveillance, 2021-2023

Background

The circulation and the genomic evolution of influenza A(H3N2) viruses during the 2021/2022 and 2022/2023 seasons were studied and associated with infection outcomes.

Methods

Remnant influenza A-positive samples following standard-of-care testing from patients across the Johns Hopkins Health System (JHHS) were used for the study. Samples were randomly selected for whole viral genome sequencing. The sequence-based pEpitope model was used to estimate the predicted vaccine efficacy (pVE) for circulating H3N2 viruses. Clinical data were collected and associated with viral genomic data.

Results

A total of 121 683 respiratory specimens were tested for influenza at JHHS between 1 September 2021 and 31 December 2022. Among them, 6071 (4.99%) tested positive for influenza A. Of these, 805 samples were randomly selected for sequencing, with hemagglutinin (HA) segments characterized for 610 samples. Among the characterized samples, 581 were H3N2 (95.2%). Phylogenetic analysis of HA segments revealed the exclusive circulation of H3N2 viruses with HA segments of the 3C.2a1b.2a.2 clade. Analysis of a total of 445 complete H3N2 genomes revealed reassortments; 200 of 227 of the 2022/2023 season genomes (88.1%) were found to have reassorted with clade 3C.2a1b.1a. The pVE was estimated to be -42.53% for the 2021/2022 season and 30.27% for the 2022/2023 season. No differences in clinical presentations or admissions were observed between the 2 seasons.

Conclusions

The increased numbers of cases and genomic diversity of influenza A(H3N2) during the 2022/2023 season were not associated with a change in disease severity compared to the previous influenza season.

Genetic variants of Dabie bandavirus: classification and biological/clinical implications

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by Dabie bandavirus (DBV), a novel Bandavirus in the family Phenuiviridae. The first case of SFTS was reported in China, followed by cases in Japan, South Korea, Taiwan and Vietnam. With clinical manifestations including fever, leukopenia, thrombocytopenia, and gastrointestinal symptoms, SFTS has a fatality rate of approximately 10%. In recent years, an increasing number of viral strains have been isolated and sequenced, and several research groups have attempted to classify the different genotypes of DBV. Additionally, accumulating evidence indicates certain correlations between the genetic makeup and biological/clinical manifestations of the virus. Here, we attempted to evaluate the genetic classification of different groups, align the genotypic nomenclature in different studies, summarize the distribution of different genotypes, and review the biological and clinical implications of DBV genetic variations.

Phylogenomic analysis uncovers a 9-year variation of Uganda influenza type-A strains from the WHO-recommended vaccines and other Africa strains

Genetic characterisation of circulating influenza viruses directs annual vaccine strain selection and mitigation of infection spread. We used next-generation sequencing to locally generate whole genomes from 116 A(H1N1)pdm09 and 118 A(H3N2) positive patient swabs collected across Uganda between 2010 and 2018. We recovered sequences from 92% (215/234) of the swabs, 90% (193/215) of which were whole genomes. The newly-generated sequences were genetically and phylogenetically compared to the WHO-recommended vaccines and other Africa strains sampled since 1994. Uganda strain hemagglutinin (n = 206), neuraminidase (n = 207), and matrix protein (MP, n = 213) sequences had 95.23-99.65%, 95.31-99.79%, and 95.46-100% amino acid similarity to the 2010-2020 season vaccines, respectively, with several mutated hemagglutinin antigenic, receptor binding, and N-linked glycosylation sites. Uganda influenza type-A virus strains sequenced before 2016 clustered uniquely while later strains mixed with other Africa and global strains. We are the first to report novel A(H1N1)pdm09 subclades 6B.1A.3, 6B.1A.5(a,b), and 6B.1A.6 (± T120A) that circulated in Eastern, Western, and Southern Africa in 2017-2019. Africa forms part of the global influenza ecology with high viral genetic diversity, progressive antigenic drift, and local transmissions. For a continent with inadequate health resources and where social distancing is unsustainable, vaccination is the best option. Hence, African stakeholders should prioritise routine genome sequencing and analysis to direct vaccine selection and virus control.

A Cold Case of Equine Influenza Disentangled with Nanopore Sequencing

Massive sequencing techniques have allowed us to develop straightforward approaches for the whole genome sequencing of viruses, including influenza viruses, generating information that is useful for improving the levels and dimensions of data analysis, even for archival samples. Using the Nanopore platform, we determined the whole genome sequence of an H3N8 equine influenza virus, identified from a 2005 outbreak in Apulia, Italy, whose origin had remained epidemiologically unexplained. The virus was tightly related (>99% at the nucleotide level) in all the genome segments to viruses identified in Poland in 2005–2008 and it was seemingly introduced locally with horse trading for the meat industry. In the phylogenetic analysis based on the eight genome segments, strain ITA/2005/horse/Bari was found to cluster with sub-lineage Florida 2 in the HA and M genes, whilst in the other genes it clustered with strains of the Eurasian lineage, revealing a multi-reassortant nature.

Influenza A virus reassortment is strain dependent

RNA viruses can exchange genetic material during coinfection, an interaction that creates novel strains with implications for viral evolution and public health. Influenza A viral genetic exchange can occur when genome segments from distinct strains reassort in coinfected cells. Predicting potential genomic reassortment between influenza strains has been a long-standing goal. Experimental coinfection studies have shed light on factors that limit or promote reassortment. However, determining the reassortment potential between diverse Influenza A strains has remained elusive. To address this challenge, we developed a high throughput genotyping approach to quantify reassortment among a diverse panel of human influenza virus strains encompassing two pandemics (swine and avian origin), three specific epidemics, and both circulating human subtypes A/H1N1 and A/H3N2. We found that reassortment frequency (the proportion of reassortants generated) is an emergent property of specific pairs of strains where strain identity is a predictor of reassortment frequency. We detect little evidence that antigenic subtype drives reassortment as intersubtype (H1N1xH3N2) and intrasubtype reassortment frequencies were, on average, similar. Instead, our data suggest that certain strains bias the reassortment frequency up or down, independently of the coinfecting partner. We observe that viral productivity is also an emergent property of coinfections, but uncorrelated to reassortment frequency; thus viral productivity is a separate factor affecting the total number of reassortants produced. Assortment of individual segments among progeny and pairwise segment combinations within progeny generally favored homologous combinations. These outcomes were not related to strain similarity or shared subtype but reassortment frequency was closely correlated to the proportion of both unique genotypes and of progeny with heterologous pairwise segment combinations. We provide experimental evidence that viral genetic exchange is potentially an individual social trait subject to natural selection, which implies the propensity for reassortment is not evenly shared among strains. This study highlights the need for research incorporating diverse strains to discover the traits that shift the reassortment potential to realize the goal of predicting influenza virus evolution resulting from segment exchange.

High-throughput droplet-based analysis of influenza A virus genetic reassortment by single-virus RNA sequencing

The segmented RNA genome of influenza A viruses (IAVs) enables viral evolution through genetic reassortment after multiple IAVs coinfect the same cell, leading to viruses harboring combinations of eight genomic segments from distinct parental viruses. Existing data indicate that reassortant genotypes are not equiprobable; however, the low throughput of available virology techniques does not allow quantitative analysis. Here, we have developed a high-throughput single-cell droplet microfluidic system allowing encapsulation of IAV-infected cells, each cell being infected by a single progeny virion resulting from a coinfection process. Customized barcoded primers for targeted viral RNA sequencing enabled the analysis of 18,422 viral genotypes resulting from coinfection with two circulating human H1N1pdm09 and H3N2 IAVs. Results were highly reproducible, confirmed that genetic reassortment is far from random, and allowed accurate quantification of reassortants including rare events. In total, 159 out of the 254 possible reassortant genotypes were observed but with widely varied prevalence (from 0.038 to 8.45%). In cells where eight segments were detected, all 112 possible pairwise combinations of segments were observed. The inclusion of data from single cells where less than eight segments were detected allowed analysis of pairwise cosegregation between segments with very high confidence. Direct coupling analysis accurately predicted the fraction of pairwise segments and full genotypes. Overall, our results indicate that a large proportion of reassortant genotypes can emerge upon coinfection and be detected over a wide range of frequencies, highlighting the power of our tool for systematic and exhaustive monitoring of the reassortment potential of IAVs.

Adaptive evolution of PB1 from influenza A(H1N1)pdm09 virus towards an enhanced fitness

PB1 influenza virus retain traces of interspecies transmission and adaptation. Previous phylogenetic analyses highlighted mutations L298I, R386K and I517V in PB1 to have putatively ameliorated the A(H1N1)pdm09 adaptation to the human host. This study aimed to evaluate the reversal of these mutations and infer the role of these residues in the virus overall fitness and adaptation. We generate PB1-mutated viruses introducing I298L, K386R and V517I mutations in PB1 and evaluate their phenotypic impact on viral growth and on antigen yield. We observed a decrease in viral growth accompanied by a reduction in hemagglutination titer and neuraminidase activity, in comparison with wt. Our data indicate that the adaptive evolution occurred in the PB1 leads to an improved overall viral fitness; and such biologic advantaged has the potential to be applied to the optimization of influenza vaccine seed prototypes.

Genetics and Pathogenicity of Natural Reassortant of Infectious Bursal Disease Virus Emerging in Latvia

Infectious bursal disease virus is an immunosuppressive pathogen that, despite applied vaccination, is affecting the poultry industry worldwide. This report presents the genetic and pathotypic characterization of a natural reassortant emerging in Europe (Latvia). Genetic characterization showed that strain 25/11/Latvia/2011 represents genotype A3B1, whose segment A is derived from very virulent strains, while segment B is from the classic-like genogroup. Phylogenetic maximum likelihood inference of the B-segment sequence clustered the reassortant strain together with the US antigenic variant E strain. However, the obtained full-length sequence of 25/11/Latvia/2011 revealed that not only reassortment but also dozens of mutations shaped the unique genetic makeup. Phenotypic characterization showed no mortality and no clinical signs of disease but a severe bursa of Fabricius atrophy and splenomegaly in the convalescent birds at 10 days post infection. The results obtained indicate that the acquired genetic constellation contributed to a decrease in virulence; nevertheless, the infection causes severe damage to lymphoid organs, which can lead to impaired immune responses.

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.

The past, current and future epidemiological dynamic of SARS-CoV-2

SARS-CoV-2, the agent of the COVID-19 pandemic, emerged in late 2019 in China, and rapidly spread throughout the world to reach all continents. As the virus expanded in its novel human host, viral lineages diversified through the accumulation of around two mutations a month on average. Different viral lineages have replaced each other since the start of the pandemic, with the most successful Alpha, Delta and Omicron variants of concern (VoCs) sequentially sweeping through the world to reach high global prevalence. Neither Alpha nor Delta was characterized by strong immune escape, with their success coming mainly from their higher transmissibility. Omicron is far more prone to immune evasion and spread primarily due to its increased ability to (re-)infect hosts with prior immunity. As host immunity reaches high levels globally through vaccination and prior infection, the epidemic is expected to transition from a pandemic regime to an endemic one where seasonality and waning host immunization are anticipated to become the primary forces shaping future SARS-CoV-2 lineage dynamics. In this review, we consider a body of evidence on the origins, host tropism, epidemiology, genomic and immunogenetic evolution of SARS-CoV-2 including an assessment of other coronaviruses infecting humans. Considering what is known so far, we conclude by delineating scenarios for the future dynamic of SARS-CoV-2, ranging from the good-circulation of a fifth endemic 'common cold' coronavirus of potentially low virulence, the bad-a situation roughly comparable with seasonal flu, and the ugly-extensive diversification into serotypes with long-term high-level endemicity.

Evolutionary Dynamics of Mexican Lineage H5N2 Avian Influenza Viruses

We have demonstrated for the first time a comprehensive evolutionary analysis of the Mexican lineage H5N2 avian influenza virus (AIV) using complete genome sequences (n = 189), from its first isolation in 1993 until 2019. Our study showed that the Mexican lineage H5N2 AIV originated from the North American wild bird gene pool viruses around 1990 and is currently circulating in poultry populations of Mexico, the Dominican Republic, and Taiwan. Since the implementation of vaccination in 1995, the highly pathogenic AIV (HPAIV) H5N2 virus was eradicated from Mexican poultry in mid-1995. However, the low pathogenic AIV (LPAIV) H5N2 virus has continued to circulate in domestic poultry populations in Mexico, eventually evolving into five distinct clades. In the current study, we demonstrate that the evolution of Mexican lineage H5N2 AIVs involves gene reassortments and mutations gained over time. The current circulating Mexican lineage H5N2 AIVs are classified as LPAIV based on the amino acid sequences of the hemagglutinin (HA) protein cleavage site motif as well as the results of the intravenous pathogenicity index (IVPI). The immune pressure from vaccinations most likely has played a significant role in the positive selection of antigenic drift mutants within the Mexican H5N2 AIVs. Most of the identified substitutions in these viruses are located on the critical antigenic residues of the HA protein and as a result, might have contributed to vaccine failures. This study highlights and stresses the need for vaccine updates while emphasizing the importance of continued molecular monitoring of the HA protein for its antigenic changes compared to the vaccines used.

Antigenic characterization of influenza and SARS-CoV-2 viruses

Antigenic characterization of emerging and re-emerging viruses is necessary for the prevention of and response to outbreaks, evaluation of infection mechanisms, understanding of virus evolution, and selection of strains for vaccine development. Primary analytic methods, including enzyme-linked immunosorbent/lectin assays, hemagglutination inhibition, neuraminidase inhibition, micro-neutralization assays, and antigenic cartography, have been widely used in the field of influenza research. These techniques have been improved upon over time for increased analytical capacity, and some have been mobilized for the rapid characterization of the SARS-CoV-2 virus as well as its variants, facilitating the development of highly effective vaccines within 1 year of the initially reported outbreak. While great strides have been made for evaluating the antigenic properties of these viruses, multiple challenges prevent efficient vaccine strain selection and accurate assessment. For influenza, these barriers include the requirement for a large virus quantity to perform the assays, more than what can typically be provided by the clinical samples alone, cell- or egg-adapted mutations that can cause antigenic mismatch between the vaccine strain and circulating viruses, and up to a 6-month duration of vaccine development after vaccine strain selection, which allows viruses to continue evolving with potential for antigenic drift and, thus, antigenic mismatch between the vaccine strain and the emerging epidemic strain. SARS-CoV-2 characterization has faced similar challenges with the additional barrier of the need for facilities with high biosafety levels due to its infectious nature. In this study, we review the primary analytic methods used for antigenic characterization of influenza and SARS-CoV-2 and discuss the barriers of these methods and current developments for addressing these challenges.

The beginning and ending of a respiratory viral pandemic-lessons from the Spanish flu

The COVID‐19 pandemic goes into its third year and the world population is longing for an end to the pandemic. Computer simulations of the future development of the pandemic have wide error margins and predictions on the evolution of new viral variants of SARS‐CoV‐2 are uncertain. It is thus tempting to look into the development of historical viral respiratory pandemics for insight into the dynamic of pandemics. The Spanish flu pandemic of 1918 caused by the influenza virus H1N1 can here serve as a potential model case. Epidemiological observations on the shift of influenza mortality from very young and old subjects to high mortality in young adults delimitate the pandemic phase of the Spanish flu from 1918 to 1920. The identification and sequencing of the Spanish flu agent allowed following the H1N1 influenza virus after the acute pandemic phase. During the 1920s H1N1 influenza virus epidemics with substantial mortality were still observed. As late as 1951, H1N1 strains of high virulence evolved but remained geographically limited. Until 1957, the H1N1 virus evolved by accumulation of mutations (‘antigenic drift’) and some intratypic reassortment. H1N1 viruses were then replaced by the pandemic H2N2 influenza virus from 1957, which was in 1968 replaced by the pandemic H3N2 influenza virus; both viruses were descendants from the Spanish flu agent but showed the exchange of entire gene segments (‘antigenic shift’). In 1977, H1N1 reappeared from an unknown source but caused only mild disease. However, H1N1 achieved again circulation in the human population and is now together with the H3N2 influenza virus an agent of seasonal influenza winter epidemics.

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.

Emergence and adaptive evolution of influenza D virus

As a novel member of the Orthomyxoviridae, influenza D virus (IDV) was firstly isolated from swine. However, cattle were found to serve as its primary reservoir. The study of IDV emergence can shed light into the dynamics of zoonotic infections and interspecies transmission. Although there is an increasing number of strains and sequenced IDV strains, their origin, epidemiology and evolutionary dynamics remain unclear. In this study, we reconstruct the diversity and evolutionary dynamics of IDVs. Molecular detection of swine tissue samples shows that six IDV positive samples were identified in the Eastern China. Phylogenetic analyses suggest three major IDV lineages designated as D/Japan, D/OK and D/660 as well as intermediate lineages. IDVs show strong association with geographical location indicating a high level of local transmission, which suggests IDVs tend to establish a local lineage of in situ evolution. In addition, the D/OK lineage widely circulates in swine in Eastern China, and all of the Chinese virus isolates form a distinct sub-clade (D/China sub-lineage). Furthermore, we identified important amino acids in the HEF gene under positive selection that might affect its receptor binding cavity relevant for its broader cell tropism. The combined results highlight that more attention should be paid to the potential threat of IDV to livestock and farming in China.

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.

Social networks applied to Dengue, H1N1, and Zika epidemics: An integrative literature review

BACKGROUND

Health crises occur both regionally and globally. Online social networks are widely used technical resources that allow users to share large amounts of information with increasing reach and velocity. Thus, the capacity of spreading information about epidemics through social media allows members of a population and health professionals or agencies to collaborate.

METHOD

This study presents results obtained in an integrative review, including examples of how social media enabled collaboration in health surveillance to treat the epidemies of Dengue, Zika, and H1N1. The literature review covers studies published between 2009 and 2017.

RESULTS

The studies reviewed indicate that social media interactions are tools for the rapid dissemination of information. These networks operate at low cost and allow information to reach audiences in need of information and who otherwise would not receive it. Social media allowed researchers to monitor evolving epidemics and obtain epidemiological data useful for decision-making in health surveillance.

CONCLUSIONS

Despite the widespread use of social networks, there are opportunities for improvement, especially in technology for treatment.

Phylogenetic analysis and evolutionary dynamics of H3N2 canine and feline influenza virus strains from 2006 to 2019

H3N2 feline influenza virus (FIV) and canine influenza virus (CIV) are very common in cats and dogs. Due to the ability of the influenza virus to spread across hosts and frequent contact between pets and people, there exist huge public health problems. In this study, we collected H3N2 CIV and FIV genomes from 2006 to 2019 from NCBI and analyzed the evolutionary dynamics and molecular variation using a series of phylogenetic analysis methods. Results indicated that H3N2 FIVs were closely related to CIVs with high posterior probability and CIVs and FIVs have certain regional characteristics. However, compared with previous studies, the significance of geographical structure correlation decreased. Furthermore, we also found that the intrasubtypic reassortment between FIVs and CIVs were common during epidemics. The integrated analysis was also performed for different selection pressure acting on HA (566 codons), NA (469 codons), M1 (252 codons), and M2 (97 codons) proteins. One HA, two NA, three M1, and two M2 sites were found under positive selection. We subsequently performed the evolutionary dynamics of H3N2 CIV. The results indicated that the time of the most recent common ancestor of CIV H3N2 may have occurred earlier than indicated in a previous study. The Bayesian skyline plot analysis in this study showed the period of divergence of major H3N2 CIVs segments occurred between 2008 and 2010. Notably, according to our research, the PB1 has experienced two divergence periods (2006-2008 and 2009-2011).

Distribution and evolution of H1N1 influenza A viruses with adamantanes-resistant mutations worldwide from 1918 to 2019

H1N1 influenza is a kind of acute respiratory infectious disease that has a high socioeconomic and medical burden each year around the world. In the past decades, H1N1 influenza viruses have exhibited high resistance to adamantanes, which has become a serious issue. To understand the up-to-date distribution and evolution of H1N1 influenza viruses with adamantanes-resistant mutations, we conducted a deep analysis of 15875 M2 protein and 8351 MP nucleotides sequences. Results of the distribution analyses showed that 77.32% of H1N1 influenza viruses harbored-resistance mutations of which 73.52% were S31N, And the mutant variants mainly appeared in North America and Europe and H1N1 influenza viruses with S31N mutation became the circulating strains since 2009 all over the world. In addition, 80.65% of human H1N1 influenza viruses and 74.61% of swine H1N1 influenza viruses exhibited adamantanes resistance, while the frequency was only 1.86% in avian H1N1 influenza viruses. Studies from evolutionary analyses indicated that the avian-origin swine H1N1 influenza viruses replaced the classical human H1N1 influenza viruses and became the circulating strains after 2009; The interspecies transmission among avian, swine, and human strains over the past 20 years contributed to the 2009 swine influenza pandemic. Results of our study clearly clarify the historical drug resistance level of H1N1 influenza viruses around the world and demonstrated the evolution of adamantanes-resistant mutations in H1N1 influenza viruses. Our findings emphasize the necessity for monitoring the adamantanes susceptibility of H1N1 influenza viruses and draw attention to analyses of the evolution of drug-resistant H1N1 influenza variants.

Diversity and Reassortment Rate of Influenza A Viruses in Wild Ducks and Gulls

Influenza A viruses (IAVs) evolve via point mutations and reassortment of viral gene segments. The patterns of reassortment in different host species differ considerably. We investigated the genetic diversity of IAVs in wild ducks and compared it with the viral diversity in gulls. The complete genomes of 38 IAVs of H1N1, H1N2, H3N1, H3N2, H3N6, H3N8, H4N6, H5N3, H6N2, H11N6, and H11N9 subtypes isolated from wild mallard ducks and gulls resting in a city pond in Moscow, Russia were sequenced. The analysis of phylogenetic trees showed that stable viral genotypes do not persist from year to year in ducks owing to frequent gene reassortment. For comparison, similar analyses were carried out using sequences of IAVs isolated in the same period from ducks and gulls in The Netherlands. Our results revealed a significant difference in diversity and rates of reassortment of IAVs in ducks and gulls.

The evolution and future of influenza pandemic preparedness

The influenza virus is a global threat to human health causing unpredictable yet recurring pandemics, the last four emerging over the course of a hundred years. As our knowledge of influenza virus evolution, distribution, and transmission has increased, paths to pandemic preparedness have become apparent. In the 1950s, the World Health Organization (WHO) established a global influenza surveillance network that is now composed of institutions in 122 member states. This and other surveillance networks monitor circulating influenza strains in humans and animal reservoirs and are primed to detect influenza strains with pandemic potential. Both the United States Centers for Disease Control and Prevention and the WHO have also developed pandemic risk assessment tools that evaluate specific aspects of emerging influenza strains to develop a systematic process of determining research and funding priorities according to the risk of emergence and potential impact. Here, we review the history of influenza pandemic preparedness and the current state of preparedness, and we propose additional measures for improvement. We also comment on the intersection between the influenza pandemic preparedness network and the current SARS-CoV-2 crisis. We must continually evaluate and revise our risk assessment and pandemic preparedness plans and incorporate new information gathered from research and global crises.

A comprehensive influenza reporter virus panel for high-throughput deep profiling of neutralizing antibodies

Broadly neutralizing antibodies (bnAbs) have been developed as potential countermeasures for seasonal and pandemic influenza. Deep characterization of these bnAbs and polyclonal sera provides pivotal understanding for influenza immunity and informs effective vaccine design. However, conventional virus neutralization assays require high-containment laboratories and are difficult to standardize and roboticize. Here, we build a panel of engineered influenza viruses carrying a reporter gene to replace an essential viral gene, and develop an assay using the panel for in-depth profiling of neutralizing antibodies. Replication of these viruses is restricted to cells expressing the missing viral gene, allowing it to be manipulated in a biosafety level 2 environment. We generate the neutralization profile of 24 bnAbs using a 55-virus panel encompassing the near-complete diversity of human H1N1 and H3N2, as well as pandemic subtype viruses. Our system offers in-depth profiling of influenza immunity, including the antibodies against the hemagglutinin stem, a major target of universal influenza vaccines.

Lessons From Influenza Pandemics of the Last 100 Years

Seasonal influenza is an annual occurrence, but it is the threat of pandemics that produces universal concern. Recurring reports of avian influenza viruses severely affecting humans have served as constant reminders of the potential for another pandemic. Review of features of the 1918 influenza pandemic and subsequent ones helps in identifying areas where attention in planning is critical. Key among such issues are likely risk groups and which interventions to employ. Past pandemics have repeatedly underscored, for example, the vulnerability of groups such as pregnant women and taught other lessons valuable for future preparedness. While a fundamental difficulty in planning for the next pandemic remains their unpredictability and infrequency, this uncertainty can be mitigated, in part, by optimizing the handling of the much more predictable occurrence of seasonal influenza. Improvements in antivirals and novel vaccine formulations are critical in lessening the impact of both pandemic and seasonal influenza.

FluReassort: a database for the study of genomic reassortments among influenza viruses

Genomic reassortment is an important genetic event in the generation of emerging influenza viruses, which can cause numerous serious flu endemics and epidemics within hosts or even across different hosts. However, there is no dedicated and comprehensive repository for reassortment events among influenza viruses. Here, we present FluReassort, a database for understanding the genomic reassortment events in influenza viruses. Through manual curation of thousands of literature references, the database compiles 204 reassortment events among 56 subtypes of influenza A viruses isolated in 37 different countries. FluReassort provides an interface for the visualization and evolutionary analysis of reassortment events, allowing users to view the events through the phylogenetic analysis with varying parameters. The reassortment networks in FluReassort graphically summarize the correlation and causality between different subtypes of the influenza virus and facilitate the description and interpretation of the reassortment preference among subtypes. We believe FluReassort is a convenient and powerful platform for understanding the evolution of emerging influenza viruses. FluReassort is freely available at https://www.jianglab.tech/FluReassort.

A Century of Swine Influenza: Is It Really Just about the Pigs?

Influenza viruses (IV) are one of the major threats to human and animal health worldwide due to the variety of species they affect. Pigs play an important role in IV ecology as the "mixing vessel," since they can be infected by swine, avian and human IV, allowing the appearance of new subtypes. Human viruses originated in swine are known as IV of swine origin or swine influenza virus (SwIV) variants. In this study, we identified knowledge tendencies of SwIV and assessed potential bias in the literature caused by these variants. We identified the most mentioned SwIV variants and manually reviewed the literature to determine the number of publications applying the whole influenza nomenclature, a partial nomenclature, only the subtype or mixed terminology, along with the proportion of articles in which the GenBank ID number was available. We observed that the 2009 H1N1 human pandemic created an important bias in SwIV research driven by an increase in human publications on the IV of swine origin. H1N1 is the most studied subtype for swine and humans, followed by H3N2. We found differences between the nomenclatures applied, where partial classifications were slightly more common. Finally, from all the publications, only 25% stated the GenBank ID of the sequence studied. This review represents the most complete exploration of trends in SwIV knowledge to date and will serve as a guidance for future search strategies in SwIV research.

Learning from history: do not flatten the curve of antiviral research!

Here, we explore the dynamics of the response of the scientific community to several epidemics, including Coronavirus Disease 2019 (COVID-19), as assessed by the numbers of clinical trials, publications, and level of research funding over time. All six prior epidemics studied [bird flu, severe acute respiratory syndrome (SARS), swine flu, Middle East Respiratory Syndrome (MERS), Ebola, and Zika] were characterized by an initial spike of research response that flattened shortly thereafter. Unfortunately, no antiviral medications have been discovered to date as treatments for any of these diseases. By contrast, the HIV/AIDS pandemic has garnered consistent research investment since it began and resulted in drugs being developed within 7 years of its start date, with many more to follow. We argue that, to develop effective treatments for COVID-19 and be prepared for future epidemics, long-term, consistent investment in antiviral research is needed.

Bayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses

Genetic recombination processes, such as reassortment, make it complex or impossible to use standard phylogenetic and phylodynamic methods. This is due to the fact that the shared evolutionary history of individuals has to be represented by a phylogenetic network instead of a tree. We therefore require novel approaches that allow us to coherently model these processes and that allow us to perform inference in the presence of such processes. Here, we introduce an approach to infer reassortment networks of segmented viruses using a Markov chain Monte Carlo approach. Our approach allows us to study different aspects of the reassortment process and allows us to show fitness benefits of reassortment events in seasonal human influenza viruses.

Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.

A method for the unbiased quantification of reassortment in segmented viruses

Reassortment of segmented viruses can be an important source of genetic diversity underlying viral evolution and emergence. Methods for the quantification of reassortment have been described but are often cumbersome and best suited for the analysis of reassortment between highly divergent parental strains. While it is useful to understand the potential of divergent parents to reassort, outcomes of such heterologous reassortment are driven by differential selection acting on the progeny and are typically strain specific. To quantify reassortment robustly, a system free of differential selection is needed. We have generated such a system for influenza A virus and for mammalian orthoreovirus by constructing well-matched parental viruses carrying small genetic tags. The method utilizes high-resolution melt technology for the identification of reassortant viruses. Ease of sample preparation and data analysis enables streamlined genotyping of a large number of virus clones. The method described here thereby allows quantification of the efficiency of reassortment and can be applied to diverse segmented viruses.

Birth Cohort Effects in Influenza Surveillance Data: Evidence That First Influenza Infection Affects Later Influenza-Associated Illness

BACKGROUND

The evolution of influenza A viruses results in birth cohorts that have different initial influenza virus exposures. Historically, A/H3 predominant seasons have been associated with more severe influenza-associated disease; however, since the 2009 pandemic, there are suggestions that some birth cohorts experience more severe illness in A/H1 predominant seasons.

METHODS

United States influenza virologic, hospitalization, and mortality surveillance data during 2000-2017 were analyzed for cohorts born between 1918 and 1989 that likely had different initial influenza virus exposures based on viruses circulating during early childhood. Relative risk/rate during H3 compared with H1 predominant seasons during prepandemic versus pandemic and later periods were calculated for each cohort.

RESULTS

During the prepandemic period, all cohorts had more influenza-associated disease during H3 predominant seasons than H1 predominant seasons. During the pandemic and later period, 4 cohorts had higher hospitalization and mortality rates during H1 predominant seasons than H3 predominant seasons.

CONCLUSIONS

Birth cohort differences in risk of influenza-associated disease by influenza A virus subtype can be seen in US influenza surveillance data and differ between prepandemic and pandemic and later periods. As the population ages, the amount of influenza-associated disease may be greater in future H1 predominant seasons than H3 predominant seasons.

Making Universal Influenza Vaccines: Lessons From the 1918 Pandemic

The year 2018 marked the 100th anniversary of the deadliest event in human history. In 1918-1919, pandemic influenza spread globally and caused an estimated 50-100 million deaths associated with unexpected clinical and epidemiological features. The descendants of the 1918 virus continue to circulate as annual epidemic viruses causing significant mortality each year. The 1918 influenza pandemic serves as a benchmark for the development of universal influenza vaccines. Challenges to producing a truly universal influenza vaccine include eliciting broad protection against antigenically different influenza viruses that can prevent or significantly downregulate viral replication and reduce morbidity by preventing development of viral and secondary bacterial pneumonia. Perhaps the most important goal of such vaccines is not to prevent influenza, but to prevent influenza deaths.

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.

Molecular insights into evolution, mutations and receptor-binding specificity of influenza A and B viruses from outpatients and hospitalized patients in Singapore

BACKGROUND

This study compared the genomes of influenza viruses that caused mild infections among outpatients and severe infections among hospitalized patients in Singapore, and characterized their molecular evolution and receptor-binding specificity.

METHODS

The complete genomes of influenza A/H1N1, A/H3N2 and B viruses that caused mild infections among outpatients and severe infections among inpatients in Singapore during 2012-2015 were sequenced and characterized. Using various bioinformatics approaches, we elucidated their evolutionary, mutational and structural patterns against the background of global and vaccine strains.

RESULTS

The phylogenetic trees of the 8 gene segments revealed that the outpatient and inpatient strains overlapped with representative global and vaccine strains. We observed a cluster of inpatients with A/H3N2 strains that were closely related to vaccine strain A/Texas/50/2012(H3N2). Several protein sites could accurately discriminate between outpatient versus inpatient strains, with site 221 in neuraminidase (NA) achieving the highest accuracy for A/H3N2. Interestingly, amino acid residues of inpatient but not outpatient isolates at those sites generally matched the corresponding residues in vaccine strains, except at site 145 of hemagglutinin (HA). This would be especially relevant for future surveillance of A/H3N2 strains in relation to their antigenicity and virulence. Furthermore, we observed a trend in which the HA proteins of influenza A/H3N2 and A/H1N1 exhibited enhanced ability to bind both avian and human host cell receptors. In contrast, the binding ability to each receptor was relatively stable for the HA of influenza B.

CONCLUSIONS

Overall, our findings extend our understanding of the molecular and structural evolution of influenza virus strains in Singapore within the global context of these dynamic 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.

Temporal Dynamics of Co-circulating Lineages of Porcine Reproductive and Respiratory Syndrome Virus

Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is the most important endemic pathogen in the U.S. swine industry. Despite control efforts involving improved biosecurity and different vaccination protocols, the virus continues to circulate and evolve. One of the foremost challenges in its control is high levels of genetic and antigenic diversity. Here, we quantify the co-circulation, emergence and sequential turnover of multiple PRRSV lineages in a single swine-producing region in the United States over a span of 9 years (2009-2017). By classifying over 4,000 PRRSV sequences (open-reading frame 5) into phylogenetic lineages and sub-lineages, we document the ongoing diversification and temporal dynamics of the PRRSV population, including the rapid emergence of a novel sub-lineage that appeared to be absent globally pre-2008. In addition, lineage 9 was the most prevalent lineage from 2009 to 2010, but its occurrence fell to 0.5% of all sequences identified per year after 2014, coinciding with the emergence or re-emergence of lineage 1 as the dominant lineage. The sequential dominance of different lineages, as well as three different sub-lineages within lineage 1, is consistent with the immune-mediated selection hypothesis for the sequential turnover in the dominant lineage. As host populations build immunity through natural infection or vaccination toward the most common variant, this dominant (sub-) lineage may be replaced by an emerging variant to which the population is more susceptible. An analysis of patterns of non- synonymous and synonymous mutations revealed evidence of positive selection on immunologically important regions of the genome, further supporting the potential that immune-mediated selection shapes the evolutionary and epidemiological dynamics for this virus. This has important implications for patterns of emergence and re-emergence of genetic variants of PRRSV that have negative impacts on the swine industry. Constant surveillance on PRRSV occurrence is crucial to a better understanding of the epidemiological and evolutionary dynamics of co-circulating viral lineages. Further studies utilizing whole genome sequencing and exploring the extent of cross-immunity between heterologous PRRS viruses could shed further light on PRRSV immunological response and aid in developing strategies that might be able to diminish disease impact.

Molecular characterization of the influenza A(H1N1)pdm09 isolates collected in the 2015-2016 season and comparison of HA mutations detected in Turkey since 2009

Influenza A(H1N1)pdm09 pandemic virus causing the 2009 global outbreak moved into the post-pandemic period, but its variants continued to be the prevailing subtype in the 2015-2016 influenza season in Europe and Asia. To determine the molecular characteristics of influenza A(H1N1)pdm09 isolates circulating during the 2015-2016 season in Turkey, we identified mutations in the hemagglutinin (HA) genes and investigated the presence of H275Y alteration in the neuraminidase genes in the randomly selected isolates. The comparison of the HA nucleotide sequences revealed a very high homology (>99.5%) among the studied influenza A(H1N1)pdm09 isolates, while a relatively low homology (96.6%-97.2%), was observed between Turkish isolates and the A/California/07/2009 vaccine virus. Overall 14 common mutations were detected in HA sequences of all 2015-2016 influenza A(H1N1)pdm09 isolates with respect to the A/California/07/2009 virus, four of which located in three different antigenic sites. Eleven rare mutations in 12 HA sequences were also detected. Phylogenetic analysis revealed that all characterized influenza A(H1N1)pdm09 isolates formed a single genetic cluster, belonging to the genetic subclade 6B.1, defined by HA amino acid substitutions S84N, S162N, and I216T. Furthermore, all isolates showed an oseltamivir-sensitive genotype, suggesting that Tamiflu (Oseltamivir) could still be the drug of choice in Turkey.

Reassortments among Avian Influenza A(H5N1) Viruses Circulating in Indonesia, 2015-2016

Highly pathogenic avian influenza (HPAI) A(H5N1) viruses have been circulating since 2003 in Indonesia, with major impacts on poultry health, severe economic losses, and 168 fatal laboratory-confirmed human cases. We performed phylogenetic analysis on 39 full-genome H5N1 virus samples collected during outbreaks among poultry in 2015-2016 in West Java and compared them with recently published sequences from Indonesia. Phylogenetic analysis revealed that the hemagglutinin gene of all samples belonged to 2 genetic groups in clade 2.3.2.1c. We also observed these groups for the neuraminidase, nucleoprotein, polymerase, and polymerase basic 1 genes. Matrix, nonstructural protein, and polymerase basic 2 genes of some HPAI were most closely related to clade 2.1.3 instead of clade 2.3.2.1c, and a polymerase basic 2 gene was most closely related to Eurasian low pathogenicity avian influenza. Our results detected a total of 13 reassortment types among HPAI in Indonesia, mostly in backyard chickens in Indramayu.

QS-Net: Reconstructing Phylogenetic Networks Based on Quartet and Sextet

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.

Incomplete influenza A virus genomes occur frequently but are readily complemented during localized viral spread

Segmentation of viral genomes into multiple RNAs creates the potential for replication of incomplete viral genomes (IVGs). Here we use a single-cell approach to quantify influenza A virus IVGs and examine their fitness implications. We find that each segment of influenza A/Panama/2007/99 (H3N2) virus has a 58% probability of being replicated in a cell infected with a single virion. Theoretical methods predict that IVGs carry high costs in a well-mixed system, as 3.6 virions are required for replication of a full genome. Spatial structure is predicted to mitigate these costs, however, and experimental manipulations of spatial structure indicate that local spread facilitates complementation. A virus entirely dependent on co-infection was used to assess relevance of IVGs in vivo. This virus grows robustly in guinea pigs, but is less infectious and does not transmit. Thus, co-infection allows IVGs to contribute to within-host spread, but complete genomes may be critical for transmission.

Contrasting selective patterns across the segmented genome of bluetongue virus in a global reassortment hotspot

For segmented viruses, rapid genomic and phenotypic changes can occur through the process of reassortment, whereby co-infecting strains exchange entire segments creating novel progeny virus genotypes. However, for many viruses with segmented genomes, this process and its effect on transmission dynamics remain poorly understood. Here, we assessed the consequences of reassortment for selection on viral diversity through time using bluetongue virus (BTV), a segmented arbovirus that is the causative agent of a major disease of ruminants. We analysed ninety-two BTV genomes isolated across four decades from India, where BTV diversity, and thus opportunities for reassortment, are among the highest in the world. Our results point to frequent reassortment and segment turnover, some of which appear to be driven by selective sweeps and serial hitchhiking. Particularly, we found evidence for a recent selective sweep affecting segment 5 and its encoded NS1 protein that has allowed a single variant to essentially invade the full range of BTV genomic backgrounds and serotypes currently circulating in India. In contrast, diversifying selection was found to play an important role in maintaining genetic diversity in genes encoding outer surface proteins involved in virus interactions (VP2 and VP5, encoded by segments 2 and 6, respectively). Our results support the role of reassortment in driving rapid phenotypic change in segmented viruses and generate testable hypotheses for in vitro experiments aiming at understanding the specific mechanisms underlying differences in fitness and selection across viral genomes.

The 1918 influenza pandemic: 100 years of questions answered and unanswered

The 2018-2019 period marks the centennial of the "Spanish" influenza pandemic, which caused at least 50 million deaths worldwide. The unprecedented nature of the pandemic's sudden appearance and high fatality rate serve as a stark reminder of the threat influenza poses. Unusual features of the 1918-1919 pandemic, including age-specific mortality and the high frequency of severe pneumonias, are still not fully understood. Sequencing and reconstruction of the 1918 virus has allowed scientists to answer many questions about its origin and pathogenicity, although many questions remain. This Review summarizes key findings and still-to-be answered questions about this deadliest of human events.

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

Influenza A Virus Superinfection Potential Is Regulated by Viral Genomic Heterogeneity

Superinfection, the sequential infection of a single cell by two or more virions, plays an important role in determining the replicative and evolutionary potential of influenza A virus (IAV) populations. The specific mechanisms that regulate superinfection during natural infection remain poorly understood. Here, we show that superinfection susceptibility is determined by the total number of viral genes expressed within a cell and is independent of their specific identity. Virions that express a complete set of viral genes potently inhibit superinfection, while the semi-infectious particles (SIPs) that make up the bulk of IAV populations and express incomplete subsets of viral genes do not. As a result, viral populations with more SIPs undergo more-frequent superinfection. These findings identify both the primary determinant of IAV superinfection potential and a prominent role for SIPs in promoting coinfection.

Defining the specific factors that govern the evolution and transmission of influenza A virus (IAV) populations is of critical importance for designing more-effective prediction and control strategies. Superinfection, the sequential infection of a single cell by two or more virions, plays an important role in determining the replicative and evolutionary potential of IAV populations. The prevalence of superinfection during natural infection and the specific mechanisms that regulate it remain poorly understood. Here, we used a novel single virion infection approach to directly assess the effects of individual IAV genes on superinfection efficiency. Rather than implicating a specific viral gene, this approach revealed that superinfection susceptibility is determined by the total number of viral gene segments expressed within a cell. IAV particles that express a complete set of viral genes potently inhibit superinfection, while semi-infectious particles (SIPs) that express incomplete subsets of viral genes do not. As a result, virus populations that contain more SIPs undergo more-frequent superinfection. We further demonstrate that viral replicase activity is responsible for inhibiting subsequent infection. These findings identify both a major determinant of IAV superinfection potential and a prominent role for SIPs in promoting viral coinfection.