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

Host genotype and sex shape influenza evolution and defective viral genomes

Viral evolution during initial pandemic waves favors mutations that enhance replication and transmission over antigenic escape. Host genotype and sex strongly shape this early adaptation, yet their individual and combined effects remain unclear. We experimentally adapted influenza A virus to male and female BALB/c and C57BL/6 mice, generating 28 independent lineages, and employed a novel 'rolling sphere' approach to identify mutational hotspots in three-dimensional protein structures. In BALB/c mice, adaptation favored nonsynonymous substitutions linked to increased virulence, including a hemagglutinin variant exclusively fixed in female lineages. It also revealed the first demonstration of sex-dependent selection shaping a viral protein interface. In female-adapted viruses, substitutions disrupting a key NS1 dimerization motif converged on a single residue, while in male-adapted viruses, they were dispersed across the same interface. Conversely, adaptation to C57BL/6 resulted in fewer substitutions but promoted defective viral genome formation, leading to reduced cytopathic effect and attenuated virulence. This provides the first in vivo evidence that host genotype alone can modulate defective viral genome formation. Our results offer critical insights into host-pathogen interactions and reveal that selective pressures imposed by specific genotype-sex combinations can increase virulence across host genotypes, enabling new epidemiological modeling and disease control strategies.

India should invest in the expansion of genomic epidemiology for vector-borne diseases filariasis, malaria and visceral leishmaniasis that are targeted for elimination

Genomic epidemiology (GE) is an integration of genomics and epidemiology. The field has evolved significantly in the past decade, enhancing our understanding of genetic susceptibility, drug resistance, disease transmission patterns, outbreak surveillance, and vaccine development. It employs an arsenal of advanced tools such as whole-genome sequencing and single-nucleotide polymorphisms for analysis, tracing pathogen evolution, mapping genetic variations, and tracking drug resistance. The role of GE in infectious disease management extends beyond outbreak control to routine public health practices, precision medicine, and determining treatment policies. The expansion of GE can significantly bolster global health defenses by effectively enabling the detection and response to emerging health threats. However, challenges such as sampling bias, data quality, integration, standardization of computational pipelines, and need for trained personnel remain. To tackle these challenges, we must invest in building capacity, improving infrastructure, providing training, and fostering collaborations between scientists and public health officials. Concerted efforts must focus on overcoming existing hurdles and promoting seamless integration of basic research into public health frameworks to fully realize its potential. It is timely for India to rapidly expand its base in GE to gain valuable insights into genetic variations and disease susceptibilities. This will provide a fillip towards eliminating the three dominant vector-borne diseases in India: filariasis, malaria, and visceral leishmaniasis.

Phylogeography and reassortment patterns of human influenza A viruses in sub-Saharan Africa

The role of sub-Saharan Africa in the global spread of influenza viruses remains unclear due to insufficient spatiotemporal sequence data. Here, we analyzed 222 codon-complete sequences of influenza A viruses (IAVs) sampled between 2011 and 2013 from five countries across sub-Saharan Africa (Kenya, Zambia, Mali, Gambia, and South Africa); these genomes were compared with 1209 contemporaneous global genomes using phylogeographical approaches. The spread of influenza in sub-Saharan Africa was characterized by (i) multiple introductions of IAVs into the region over consecutive influenza seasons, with viral importations originating from multiple global geographical regions, some of which persisted in circulation as intra-subtype reassortants for multiple seasons, (ii) virus transfer between sub-Saharan African countries, and (iii) virus export from sub-Saharan Africa to other geographical regions. Despite sparse data from influenza surveillance in sub-Saharan Africa, our findings support the notion that influenza viruses persist as temporally structured migrating metapopulations in which new virus strains can emerge in any geographical region, including in sub-Saharan Africa; these lineages may have been capable of dissemination to other continents through a globally migrating virus population. Further knowledge of the viral lineages that circulate within understudied sub-Saharan Africa regions is required to inform vaccination strategies in those regions.

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.

Nationwide and long-term molecular epidemiologic studies of mumps viruses that circulated in Japan between 1986 and 2017

In Japan, major mumps outbreaks still occur every 4–5 years because of low mumps vaccine coverage (30–40%) owing to the voluntary immunization program. Herein, to prepare for a regular immunization program, we aimed to reveal the nationwide and long-term molecular epidemiological trends of the mumps virus (MuV) in Japan. Additionally, we performed whole-genome sequencing (WGS) using next-generation sequencing to assess results from conventional genotyping using MuV sequences of the small-hydrophobic (SH) gene. We analyzed 1,064 SH gene sequences from mumps clinical samples and MuV isolates collected from 25 prefectures from 1986 to 2017. The results showed that six genotypes, namely B (110), F (1), G (900), H (3), J (41), and L (9) were identified, and the dominant genotypes changed every decade in Japan since the 1980s. Genotype G has been exclusively circulating since the early 2000s. Seven clades were identified for genotype G using SH sequence-based classification. To verify the results, we performed WGS on 77 representative isolates of genotype G using NGS and phylogenetically analyzed them. Five clades were identified with high bootstrap values and designated as Japanese clade (JPC)-1, -2, -3, -4, -5. JPC-1 and -3 accounted for over 80% of the total genotype G isolates (68.3 and 13.8%, respectively). Of these, JPC-2 and -5, were newly identified clades in Japan through this study. This is the first report describing the nationwide and long-term molecular epidemiology of MuV in Japan. The results provide information about Japanese domestic genotypes, which is essential for evaluating the mumps elimination progress in Japan after the forthcoming introduction of the mumps vaccine into Japan’s regular immunization program. Furthermore, the study shows that WGS analysis using NGS is more accurate than results obtained from conventional SH sequence-based classification and is a powerful tool for accurate molecular epidemiology studies.

Genome-Wide Reassortment Analysis of Influenza A H7N9 Viruses Circulating in China during 2013-2019

Reassortment with the H9N2 virus gave rise to the zoonotic H7N9 avian influenza virus (AIV), which caused more than five outbreak waves in humans, with high mortality. The frequent exchange of genomic segments between H7N9 and H9N2 has been well-documented. However, the reassortment patterns have not been described and are not yet fully understood. Here, we used phylogenetic analyses to investigate the patterns of intersubtype and intrasubtype/intralineage reassortment across the eight viral segments. The H7N9 virus and its progeny frequently exchanged internal genes with the H9N2 virus but rarely with the other AIV subtypes. Before beginning the intrasubtype/intralineage reassortment analyses, five Yangtze River Delta (YRD A-E) and two Pearl River Delta (PRD A-B) clusters were divided according to the HA gene phylogeny. The seven reset segment genes were also nomenclatured consistently. As revealed by the tanglegram results, high intralineage reassortment rates were determined in waves 2–3 and 5. Additionally, the clusters of PB2 c05 and M c02 were the most dominant in wave 5, which could have contributed to the onset of the largest H7N9 outbreak in 2016–2017. Meanwhile, a portion of the YRD-C cluster (HP H7N9) inherited their PB2, PA, and M segments from the co-circulating YRD-E (LP H7N9) cluster during wave 5. Untanglegram results revealed that the reassortment rate between HA and NA was lower than HA with any of the other six segments. A multidimensional scaling plot revealed a robust genetic linkage between the PB2 and PA genes, indicating that they may share a co-evolutionary history. Furthermore, we observed relatively more robust positive selection pressure on HA, NA, M2, and NS1 proteins. Our findings demonstrate that frequent reassortment, particular reassorted patterns, and adaptive mutations shaped the H7N9 viral genetic diversity and evolution. Increased surveillance is required immediately to better understand the current state of the HP H7N9 AIV.

A random priming amplification method for whole genome sequencing of SARS-CoV-2 virus

BACKGROUND

Non-targeted whole genome sequencing is a powerful tool to comprehensively identify constituents of microbial communities in a sample. There is no need to direct the analysis to any identification before sequencing which can decrease the introduction of bias and false negatives results. It also allows the assessment of genetic aberrations in the genome (e.g., single nucleotide variants, deletions, insertions and copy number variants) including in noncoding protein regions.

METHODS

The performance of four different random priming amplification methods to recover RNA viral genetic material of SARS-CoV-2 were compared in this study. In method 1 (H-P) the reverse transcriptase (RT) step was performed with random hexamers whereas in methods 2-4 RT incorporating an octamer primer with a known tag. In methods 1 and 2 (K-P) sequencing was applied on material derived from the RT-PCR step, whereas in methods 3 (SISPA) and 4 (S-P) an additional amplification was incorporated before sequencing.

RESULTS

The SISPA method was the most effective and efficient method for non-targeted/random priming whole genome sequencing of SARS-CoV-2 that we tested. The SISPA method described in this study allowed for whole genome assembly of SARS-CoV-2 and influenza A(H1N1)pdm09 in mixed samples. We determined the limit of detection and characterization of SARS-CoV-2 virus which was 103 pfu/ml (Ct, 22.4) for whole genome assembly and 101 pfu/ml (Ct, 30) for metagenomics detection.

CONCLUSIONS

The SISPA method is predominantly useful for obtaining genome sequences from RNA viruses or investigating complex clinical samples as no prior sequence information is needed. It might be applied to monitor genomic virus changes, virus evolution and can be used for fast metagenomics detection or to assess the general picture of different pathogens within the sample.

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

Genomic characterization of circulating influenza type-A viruses (IAVs) directs the selection of appropriate vaccine formulations and early detection of potentially pandemic virus strains. However, longitudinal data on the genomic evolution and transmission of IAVs in Africa are scarce, limiting Africa's benefits from potential influenza control strategies. We searched seven databases: African Journals Online, Embase, Global Health, Google Scholar, PubMed, Scopus, and Web of Science according to the PRISMA guidelines for studies that sequenced and/or genomically characterized Africa IAVs. Our review highlights the emergence and diversification of IAVs in Africa since 1993. Circulating strains continuously acquired new amino acid substitutions at the major antigenic and potential N-linked glycosylation sites in their hemagglutinin proteins, which dramatically affected vaccine protectiveness. Africa IAVs phylogenetically mixed with global strains forming strong temporal and geographical evolution structures. Phylogeographic analyses confirmed that viral migration into Africa from abroad, especially South Asia, Europe, and North America, and extensive local viral mixing sustained the genomic diversity, antigenic drift, and persistence of IAVs in Africa. However, the role of reassortment and zoonosis remains unknown. Interestingly, we observed substitutions and clades and persistent viral lineages unique to Africa. Therefore, Africa's contribution to the global influenza ecology may be understated. Our results were geographically biased, with data from 63% (34/54) of African countries. Thus, there is a need to expand influenza surveillance across Africa and prioritize routine whole-genome sequencing and genomic analysis to detect new strains early for effective viral control.

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.

Genomic Evaluation of the Genus Coltivirus Indicates Genetic Diversity among Colorado Tick Fever Virus Strains and Demarcation of a New Species

The type species of the genus Coltivirus, Colorado tick fever virus (CTFV), was discovered in 1943 and is the most common tick-borne viral infection in the Western US. Despite its long history, very little is known about the molecular diversity of viruses classified within the species Colorado tick fever coltivirus. Previous studies have suggested genetic variants and potential serotypes of CTFV, but limited genetic sequence information is available for CTFV strains. To address this knowledge gap, we report herein the full-length genomes of five strains of CTFV, including Salmon River virus and California hare coltivirus (CTFV-Ca). The sequence from the full-length genome of Salmon River virus identified a high genetic identity to the CTFV prototype strain with >90% amino acid identity in all the segments except segment four, suggesting Salmon River virus is a strain of the species Colorado tick fever coltivirus. Additionally, analysis suggests that segment four has been associated with reassortment in at least one strain. The CTFV-Ca full-length genomic sequence was highly variable from the prototype CTFV in all the segments. The genome of CTFV-Ca was most similar to the Eyach virus, including similar segments six and seven. These data suggest that CTFV-Ca is not a strain of CTFV but a unique species. Additional sequence information of CTFV strains will improve the molecular surveillance tools and provide additional taxonomic resolution to this understudied virus.

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.

Inference of population genetic parameters from an irregular time series of seasonal influenza virus sequences

Basic summary statistics that quantify the population genetic structure of influenza virus are important for understanding and inferring the evolutionary and epidemiological processes. However, the sampling dates of global virus sequences in the last several decades are scattered nonuniformly throughout the calendar. Such temporal structure of samples and the small effective size of viral population hampers the use of conventional methods to calculate summary statistics. Here, we define statistics that overcome this problem by correcting for the sampling-time difference in quantifying a pairwise sequence difference. A simple linear regression method jointly estimates the mutation rate and the level of sequence polymorphism, thus providing an estimate of the effective population size. It also leads to the definition of Wright's FST for arbitrary time-series data. Furthermore, as an alternative to Tajima's D statistic or the site-frequency spectrum, a mismatch distribution corrected for sampling-time differences can be obtained and compared between actual and simulated data. Application of these methods to seasonal influenza A/H3N2 viruses sampled between 1980 and 2017 and sequences simulated under the model of recurrent positive selection with metapopulation dynamics allowed us to estimate the synonymous mutation rate and find parameter values for selection and demographic structure that fit the observation. We found that the mutation rates of HA and PB1 segments before 2007 were particularly high and that including recurrent positive selection in our model was essential for the genealogical structure of the HA segment. Methods developed here can be generally applied to population genetic inferences using serially sampled genetic data.

Evaluation of the added value of viral genomic information for predicting severity of influenza infection

BACKGROUND

The severity of an influenza infection is influenced by both host and viral characteristics. This study aims to assess the relevance of viral genomic data for the prediction of severe influenza A(H3N2) infections among patients hospitalized for severe acute respiratory infection (SARI), in view of risk assessment and patient management.

METHODS

160 A(H3N2) influenza positive samples from the 2016-2017 season originating from the Belgian SARI surveillance were selected for whole genome sequencing. Predictor variables for severity were selected using a penalized elastic net logistic regression model from a combined host and genomic dataset, including patient information and nucleotide mutations identified in the viral genome. The goodness-of-fit of the model combining host and genomic data was compared using a likelihood-ratio test with the model including host data only. Internal validation of model discrimination was conducted by calculating the optimism-adjusted area under the Receiver Operating Characteristic curve (AUC) for both models.

RESULTS

The model including viral mutations in addition to the host characteristics had an improved fit ([Formula: see text]=12.03, df = 3, p = 0.007). The optimism-adjusted AUC increased from 0.671 to 0.732.

CONCLUSIONS

Adding genomic data (selected season-specific mutations in the viral genome) to the model containing host characteristics improved the prediction of severe influenza infection among hospitalized SARI patients, thereby offering the potential for translation into a prospective strategy to perform early season risk assessment or to guide individual patient management.

Next Generation Sequencing and Bioinformatics Methodologies for Infectious Disease Research and Public Health: Approaches, Applications, and Considerations for Development of Laboratory Capacity

Next generation sequencing (NGS) combined with bioinformatics has successfully been used in a vast array of analyses for infectious disease research of public health relevance. For instance, NGS and bioinformatics approaches have been used to identify outbreak origins, track transmissions, investigate epidemic dynamics, determine etiological agents of a disease, and discover novel human pathogens. However, implementation of high-quality NGS and bioinformatics in research and public health laboratories can be challenging. These challenges mainly include the choice of the sequencing platform and the sequencing approach, the choice of bioinformatics methodologies, access to the appropriate computation and information technology infrastructure, and recruiting and retaining personnel with the specialized skills and experience in this field. In this review, we summarize the most common NGS and bioinformatics workflows in the context of infectious disease genomic surveillance and pathogen discovery, and highlight the main challenges and considerations for setting up an NGS and bioinformatics-focused infectious disease research public health laboratory. We describe the most commonly used sequencing platforms and review their strengths and weaknesses. We review sequencing approaches that have been used for various pathogens and study questions, as well as the most common difficulties associated with these approaches that should be considered when implementing in a public health or research setting. In addition, we provide a review of some common bioinformatics tools and procedures used for pathogen discovery and genome assembly, along with the most common challenges and solutions. Finally, we summarize the bioinformatics of advanced viral, bacterial, and parasite pathogen characterization, including types of study questions that can be answered when utilizing NGS and bioinformatics.

A Department of Defense Laboratory Consortium Approach to Next Generation Sequencing and Bioinformatics Training for Infectious Disease Surveillance in Kenya

Epidemics of emerging and re-emerging infectious diseases are a danger to civilian and military populations worldwide. Health security and mitigation of infectious disease threats is a priority of the United States Government and the Department of Defense (DoD). Next generation sequencing (NGS) and Bioinformatics (BI) enhances traditional biosurveillance by providing additional data to understand transmission, identify resistance and virulence factors, make predictions, and update risk assessments. As more and more laboratories adopt NGS and BI technologies they encounter challenges in building local capacity. In addition to choosing the right sequencing platform and approach, considerations must also be made for the complexity of bioinformatics analyses, data storage, as well as personnel and computational requirements. To address these needs, a comprehensive training program was developed covering wet lab and bioinformatics approaches to NGS. The program is meant to be modular and adaptive to meet both common and individualized needs of medical research and public health laboratories across the DoD. The training program was first deployed internationally to the Basic Science Laboratory of the US Army Medical Research Directorate-Africa in Kisumu, Kenya, which is an overseas Lab of the Walter Reed Army Institute of Research (WRAIR). A week-long workshop with intensive focus on targeted sequencing and the bioinformatics of genome assembly (n = 24 participants) was held. Post-workshop self-assessment (completed by 21 participants) noted significant median gains in knowledge domains related to NGS targeted sequencing, bioinformatics for genome assembly, and sequence quality assessment. The participants also reported that the information on study design, sample preparation, sequencing quality control, data quality assessment, reporting, and basic and advanced bioinformatics analysis were the most useful information presented in the training. While longer-term evaluations are planned, the training resulted in significant short-term improvement of a laboratory’s self-reported wet lab and bioinformatics capabilities. This framework can be used for future DoD laboratory development in the area of NGS and BI for infectious disease surveillance, ultimately enhancing this global DoD capability.

Retrospective Assessment of the Antigenic Similarity of Egg-Propagated and Cell Culture-Propagated Reference Influenza Viruses as Compared with Circulating Viruses across Influenza Seasons 2002-2003 to 2017-2018

Suboptimal vaccine effectiveness against seasonal influenza is a significant public health concern, partly explained by antigenic differences between vaccine viruses and viruses circulating in the environment. Haemagglutinin mutations within vaccine viruses acquired during serial passage in eggs have been identified as a source of antigenic variation between vaccine and circulating viruses. This study retrospectively compared the antigenic similarity of circulating influenza isolates with egg- and cell-propagated reference viruses to assess any observable trends over a 16-year period. Using annual and interim reports published by the Worldwide Influenza Centre, London, for the 2002-2003 to 2017-2018 influenza seasons, we assessed the proportions of circulating viruses which showed antigenic similarity to reference viruses by season. Egg-propagated reference viruses were well matched against circulating viruses for A/H1N1 and B/Yamagata. However, A/H3N2 and B/Victoria cell-propagated reference viruses appeared to be more antigenically similar to circulating A/H3N2 and B/Victoria viruses than egg-propagated reference viruses. These data support the possibility that A/H3N2 and B/Victoria viruses are relatively more prone to egg-adaptive mutation. Cell-propagated A/H3N2 and B/Victoria reference viruses were more antigenically similar to circulating A/H3N2 and B/Victoria viruses over a 16-year period than were egg-propagated reference viruses.

The Ecology and Evolution of Influenza Viruses

The patterns and processes of influenza virus evolution are of fundamental importance, underpinning such traits as the propensity to emerge in new host species and the ability to rapidly generate antigenic variation. Herein, we review key aspects of the ecology and evolution of influenza viruses. We begin with an exploration of the origins of influenza viruses within the orthomyxoviruses, showing how our perception of the evolutionary history of these viruses has been transformed with metagenomic sequencing. We then outline the diversity of virus subtypes in different species and the processes by which these viruses have emerged in new hosts, with a particular focus on the role played by segment reassortment. We then turn our attention to documenting the spread and phylodynamics of seasonal influenza A and B viruses in human populations, including the drivers of antigenic evolution, and finish with a discussion of virus diversity and evolution at the scale of individual hosts.

Genetic Characterization of Frijoles and Chilibre Species Complex Viruses (Genus Phlebovirus; Family Phenuiviridae) and Three Unclassified New World Phleboviruses

The genus Phlebovirus is a diverse group of globally occurring viruses, including tick-, mosquito-, and sand fly-borne pathogens. Phleboviruses have historically been classified by serological methods. However, molecular methods alone have been used to identify emergent novel and related strains in recent years. This makes reconciling the classification of historically and newly characterized viruses challenging. To address this in part, we describe the characterization of the genomes of the Frijoles and Chilibre species complex phleboviruses, and three unclassified phleboviruses isolated in the Americas: Caimito, Itaporanga, and Rio Grande viruses that had previously only been described at the serological level. With the exception of Itaporanga virus, the phleboviruses sequenced in this study are phylogenetically related to the current species Frijoles phlebovirus, Bujaru phlebovirus, or the Chagres antigenic complex. Unexpectedly, molecular and phylogenetic analysis suggests Chilibre and Caimito viruses are taxonomically related to the family Peribunyaviridae. These viruses have a genomic architecture similar to peribunyaviruses and form monophyletic groups within the genus Pacuvirus. Our data highlight the importance of reconciling serological and molecular taxonomic classification. In addition, we suggest the taxonomy of Chilibre and Caimito viruses should be revised.

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.

Distinct molecular evolution of influenza H3N2 strains in the 2016/17 season and its implications for vaccine effectiveness

Influenza virus is a respiratory pathogen that causes seasonal epidemics by resulting in a considerable number of influenza-like illness (ILI) patients. During the 2016/17 season, ILI rates increased unusually earlier and higher than previous seasons in Korea, and most viral isolates were subtyped as H3N2 strains. Notably, the hemagglutinin (HA) of most Korean H3N2 strains retained newly introduced lysine signatures in HA antigenic sites A and D, compared with that of clade 3C.2a vaccine virus, which affected antigenic distances to the standard vaccine antisera in a hemagglutination inhibition assay. The neuraminidase (NA) of Korean H3N2 strains also harbored amino acid mutations. However, neither consistent amino acid mutations nor common phylogenetic clustering patterns were observed. These suggest that Korean H3N2 strains of the 2016/17 season might be distantly related with the vaccine virus both in genotypic and phenotypic classifications, which would adversely affect vaccine effectiveness.

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.

Notes on recombination and reassortment in multipartite/segmented viruses

Besides evolving through nucleotide substitution, viruses frequently also evolve by genetic recombination which can occur when related viral variants co-infect the same cells. Viruses with segmented or multipartite genomes can additionally evolve via the reassortment of genomic components. Various computational techniques are now available for identifying and characterizing recombination and reassortment. While these techniques have revealed both that all well studied segmented and multipartite virus species show some capacity for reassortment, and that recombination is common in many multipartite species, they have indicated that recombination is either rare or does not occur in species with segmented genomes. Reassortment and recombination can make it very difficult to study segmented/multipartite viruses using metagenomics-based approaches. Notable challenges include, both the accurate identification and assignment of genomic components to individual genomes, and the differentiation between natural 'real' recombination events and artifactual 'fake' recombination events arising from the inaccurate de novo assembly of genome component sequences determined using short read sequencing.

Integrating patient and whole-genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses

Genetic surveillance of seasonal influenza is largely focused on sequencing of the haemagglutinin gene. Consequently, our understanding of the contribution of the remaining seven gene segments to the evolution and epidemiological dynamics of seasonal influenza is relatively limited. The increased availability of next-generation sequencing technologies allows rapid and economic whole-genome sequencing (WGS) of influenza virus. Here, 150 influenza A(H3N2) positive clinical specimens with linked epidemiological data, from the 2014/15 season in Scotland, were sequenced directly using both Sanger sequencing of the HA1 region and WGS using the Illumina MiSeq platform. Sequences generated by the two methods were highly correlated, and WGS provided on average >90 % whole genome coverage. As reported in other European countries during 2014/15, all strains belonged to genetic group 3C, with subgroup 3C.2a predominating. Multiple inter-subgroup reassortants were identified, including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Cases of severe acute respiratory illness were significantly clustered on phylogenies of multiple gene segments indicating potential genetic factors warranting further investigation. Severe cases were also more likely to be associated with reassortant viruses and to occur later in the season. These results suggest that WGS provides an opportunity to develop our understanding of the relationship between the influenza genome and disease severity and the epidemiological consequences of within-subtype reassortment. Therefore, increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

Selection on non-antigenic gene segments of seasonal influenza A virus and its impact on adaptive evolution

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

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.

Population Diversity and Collective Interactions during Influenza Virus Infection

Influenza A virus (IAV) continues to pose an enormous and unpredictable global public health threat, largely due to the continual evolution of escape from preexisting immunity and the potential for zoonotic emergence. Understanding how the unique genetic makeup and structure of IAV populations influences their transmission and evolution is essential for developing more-effective vaccines, therapeutics, and surveillance capabilities. Owing to their mutation-prone replicase and unique genome organization, IAV populations exhibit enormous amounts of diversity both in terms of sequence and functional gene content. Here, I review what is currently known about the genetic and genomic diversity present within IAV populations and how this diversity may shape the replicative and evolutionary dynamics of these viruses.

Adaptive evolution during the establishment of European avian-like H1N1 influenza A virus in swine

An H1N1 subtype influenza A virus with all eight gene segments derived from wild birds (including mallards), ducks and chickens, caused severe disease outbreaks in swine populations in Europe beginning in 1979 and successfully adapted to form the European avian‐like swine (EA‐swine) influenza lineage. Genes of the EA‐swine lineage that are clearly segregated from its closest avian relatives continue to circulate in swine populations globally and represent a unique opportunity to study the adaptive process of an avian‐to‐mammalian cross‐species transmission. Here, we used a relaxed molecular clock model to test whether the EA‐swine virus originated through the introduction of a single avian ancestor as an entire genome, followed by an analysis of host‐specific selection pressures among different gene segments. Our data indicated independent introduction of gene segments via transmission of avian viruses into swine followed by reassortment events that occurred at least 1–4 years prior to the EA‐swine outbreak. All EA‐swine gene segments exhibit greater selection pressure than avian viruses, reflecting both adaptive pressures and relaxed selective constraints that are associated with host switching. Notably, we identified key amino acid mutations in the viral surface proteins (H1 and N1) that play a role in adaptation to new hosts. Following the establishment of EA‐swine lineage, we observed an increased frequency of intrasubtype reassortment of segments compared to the earlier strains that has been associated with adaptive amino acid replacements, disease severity and vaccine escape. Taken together, our study provides key insights into the adaptive changes in viral genomes following the transmission of avian influenza viruses to swine and the early establishment of the EA‐swine lineage.

Full genomic characterization of California serogroup viruses, genus Orthobunyavirus, family Peribunyaviridae including phylogenetic relationships

Thorough molecular characterization of reference viruses supports the detection of emerging human pathogens as well as studies of evolutionary relationships. However, full characterization of the tripartite RNA genomes of many viruses of the clinically important family Peribunyaviridae remains incomplete, making it difficult to identify emerging strains. Here, we report the full genome sequences of nine viruses belonging to the California serogroup and describe multi-segment analyses of these and previously published California serogroup strain data to determine the role of segment reassortment in the evolution of this serogroup. Phylogenetic trees from the small, medium, and large segments suggest long term, independent evolution of the majority of strains. However, trees from each segment were not entirely congruent and evidence of reassortment among some strains is presented. Of unique interest, the L segment phylogeny reveals divergent branching patterns for encephalitic versus non-encephalitic viruses in both major clades of the California serogroup.