Influenza Research Database: An integrated bioinformatics resource for influenza virus research

Analysis of the Genetic Diversity Associated With the Drug Resistance and Pathogenicity of Influenza A Virus Isolated in Bangladesh From 2002 to 2019

The subtype prevalence, drug resistance- and pathogenicity-associated mutations, and the distribution of the influenza A virus (IAV) isolates identified in Bangladesh from 2002 to 2019 were analyzed using bioinformatic tools. A total of 30 IAV subtypes have been identified in humans (4), avian species (29), and environment (5) in Bangladesh. The predominant subtypes in human and avian species are H1N1/H3N2 and H5N1/H9N2, respectively. However, the subtypes H5N1/H9N2 infecting humans and H3N2/H1N1 infecting avian species have also been identified. Among the avian species, the maximum number of subtypes (27) have been identified in ducks. A 3.56% of the isolates showed neuraminidase inhibitor (NAI) resistance with a prevalence of 8.50, 1.33, and 2.67% in avian species, humans, and the environment, respectively, the following mutations were detected: V116A, I117V, D198N, I223R, S247N, H275Y, and N295S. Prevalence of adamantane-resistant IAVs was 100, 50, and 30.54% in humans, the environment, and avian species, respectively, the subtypes H3N2, H1N1, H9N2, and H5N2 were highly prevalent, with the subtype H5N1 showing a comparatively lower prevalence. Important PB2 mutations such D9N, K526R, A588V, A588I, G590S, Q591R, E627K, K702R, and S714R were identified. A wide range of IAV subtypes have been identified in Bangladesh with a diversified genetic variation in the NA, M2, and PB2 proteins providing drug resistance and enhanced pathogenicity. This study provides a detailed analysis of the subtypes, and the host range of the IAV isolates and the genetic variations related to their proteins, which may aid in the prevention, treatment, and control of IAV infections in Bangladesh, and would serve as a basis for future investigations.

Molecular epidemiologic characteristics of hemagglutinin from five waves of avian influenza A (H7N9) virus infection, from 2013 to 2017, in Zhejiang Province, China

There have been five waves of influenza A (H7N9) epidemics in Zhejiang Province between 2013 and 2017. Although the epidemiological characteristics of the five waves have been reported, the molecular genetics aspects, including the phylogeny, evolution, and mutation of hemagglutinin (HA), have not been systematically investigated. A total of 154 H7N9 samples from Zhejiang Province were collected between 2013 and 2017 and sequenced using an Ion Torrent Personal Genome Machine. The starting dates of the waves were 16 March 2013, 1 July 2013, 1 July 2014, 1 July 2015, and 1 July 2016. Single-nucleotide polymorphisms (SNPs) and amino acid mutations were counted after the HA sequences were aligned. The evolution of H7N9 matched the temporal order of the five waves, among which wave 3 played an important role. The 55 SNPs and 14 amino acid mutations with high frequency identified among the five waves revealed the dynamic occurrence of mutation in the process of viral dissemination. Wave 3 contributed greatly to the subsequent epidemic of waves 4 and 5 of H7N9. Compared with wave 1, wave 5 was characterized by more mutations, including A143V and R148K, two mutations that have been reported to weaken the immune response. In addition, some amino acid mutations were observed in wave 5 that led to more lineages. It is necessary to strengthen the surveillance of subsequent H7N9 influenza outbreaks.

Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

Coding-Complete Genome Sequence of Swine Influenza Virus Isolate A/Swine/Karaganda/04/2020 (H1N1) from Kazakhstan

Here, we report the coding-complete genome sequence of a clinical sample of influenza virus obtained from a pig at a livestock farm in Karaganda, Central Kazakhstan, during a pig study in 2020. Isolate A/Swine/Karaganda/04/2020 (H1N1) belongs to clade 1A.3.2.2 lineage 1A, which includes the 2009 H1N1 pandemic strains.

virusMED: an atlas of hotspots of viral proteins

Metal binding sites, antigen epitopes and drug binding sites are the hotspots in viral proteins that control how viruses interact with their hosts. virusMED (virus Metal binding sites, Epitopes and Drug binding sites) is a rich internet application based on a database of atomic interactions around hotspots in 7041 experimentally determined viral protein structures. 25306 hotspots from 805 virus strains from 75 virus families were characterized, including influenza, HIV-1 and SARS-CoV-2 viruses. Just as Google Maps organizes and annotates points of interest, virusMED presents the positions of individual hotspots on each viral protein and creates an atlas upon which newly characterized functional sites can be placed as they are being discovered. virusMED contains an extensive set of annotation tags about the virus species and strains, viral hosts, viral proteins, metal ions, specific antibodies and FDA-approved drugs, which permits rapid screening of hotspots on viral proteins tailored to a particular research problem. The virusMED portal (https://virusmed.biocloud.top) can serve as a window to a valuable resource for many areas of virus research and play a critical role in the rational design of new preventative and therapeutic agents targeting viral infections.

Influenza A virus segments five and six can harbor artificial introns allowing expanded coding capacity

Influenza A viruses encode their genomes across eight, negative sense RNA segments. The six largest segments produce mRNA transcripts that do not generally splice; however, the two smallest segments are actively spliced to produce the essential viral proteins NEP and M2. Thus, viral utilization of RNA splicing effectively expands the viral coding capacity without increasing the number of genomic segments. As a first step towards understanding why splicing is not more broadly utilized across genomic segments, we designed and inserted an artificial intron into the normally nonsplicing NA segment. This insertion was tolerated and, although viral mRNAs were incompletely spliced, we observed only minor effects on viral fitness. To take advantage of the unspliced viral RNAs, we encoded a reporter luciferase gene in frame with the viral ORF such that when the intron was not removed the reporter protein would be produced. This approach, which we also show can be applied to the NP encoding segment and in different viral genetic backgrounds, led to high levels of reporter protein expression with minimal effects on the kinetics of viral replication or the ability to cause disease in experimentally infected animals. These data together show that the influenza viral genome is more tolerant of splicing than previously appreciated and this knowledge can be leveraged to develop viral genetic platforms with utility for biotechnology applications.

Unlike most host mRNAs, some viral mRNAs encode multiple discrete, functional proteins. One method influenza A viruses use to increase the protein products from two of their eight RNA genome segments is splicing. Splicing requires host machinery to remove part of the viral mRNA, the intron, to generate a different mRNA product. Although only certain influenza viral segments naturally splice, we were interested in whether additional segments could splice to produce multiple proteins. We inserted artificial introns harboring reporter genes into otherwise nonsplicing genomic segments of an H1N1 influenza A virus and found that this modification was well tolerated by the virus. We further demonstrated that an unrelated H3N2 influenza A virus could similarly support splicing and express a reporter protein from an artificial intron. These findings have implications for our understanding of how viruses expand their coding capacity with a limited genome. Additionally, encoding reporter proteins in spliced intronic sequences also represents a new method of generating reporter viruses requiring limited manipulation of the viral RNA.

Evolution and Antigenic Advancement of N2 Neuraminidase of Swine Influenza A Viruses Circulating in the United States following Two Separate Introductions from Human Seasonal Viruses

Two separate introductions of human seasonal N2 neuraminidase genes were sustained in U.S. swine since 1998 (N2-98) and 2002 (N2-02). Herein, we characterized the antigenic evolution of the N2 of swine influenza A virus (IAV) across 2 decades following each introduction. The N2-98 and N2-02 expanded in genetic diversity, with two statistically supported monophyletic clades within each lineage. To assess antigenic drift in swine N2 following the human-to-swine spillover events, we generated a panel of swine N2 antisera against representative N2 and quantified the antigenic distance between wild-type viruses using enzyme-linked lectin assay and antigenic cartography. The antigenic distance between swine and human N2 was smallest between human N2 circulating at the time of each introduction and the archetypal swine N2. However, sustained circulation and evolution in swine of the two N2 lineages resulted in significant antigenic drift, and the N2-98 and N2-02 swine N2 lineages were antigenically distinct. Although intralineage antigenic diversity was observed, the magnitude of antigenic drift did not consistently correlate with the observed genetic differences. These data represent the first quantification of the antigenic diversity of neuraminidase of IAV in swine and demonstrated significant antigenic drift from contemporary human seasonal strains as well as antigenic variation among N2 detected in swine. These data suggest that antigenic mismatch may occur between circulating swine IAV and vaccine strains. Consequently, consideration of the diversity of N2 in swine IAV for vaccine selection may likely result in more effective control and aid public health initiatives for pandemic preparedness. IMPORTANCE Antibodies inhibiting the neuraminidase (NA) of IAV reduce clinical disease, virus shedding, and transmission, particularly in the absence of neutralizing immunity against hemagglutinin. To understand antibody recognition of the genetically diverse NA in U.S. swine IAV, we characterized the antigenic diversity of N2 from swine and humans. N2 detected in swine IAV were derived from two distinct human-to-swine spillovers that persisted, are antigenically distinct, and underwent antigenic drift. These findings highlight the need for continued surveillance and vaccine development in swine with increased focus on the NA. Additionally, human seasonal N2 isolated after 2005 were poorly inhibited by representative swine N2 antisera, suggesting a lack of cross-reactive NA antibody-mediated immunity between contemporary swine and human N2. Bidirectional transmission between humans and swine represents a One Health challenge, and determining the correlates of immunity to emerging IAV strains is critical to mitigating zoonotic and reverse-zoonotic transmission.

Influenza virus genotype to phenotype predictions through machine learning: a systematic review

Background: There is great interest in understanding the viral genomic predictors of phenotypic traits that allow influenza A viruses to adapt to or become more virulent in different hosts. Machine learning techniques have demonstrated promise in addressing this critical need for other pathogens because the underlying algorithms are especially well equipped to uncover complex patterns in large datasets and produce generalizable predictions for new data. As the body of research where these techniques are applied for influenza A virus phenotype prediction continues to grow, it is useful to consider the strengths and weaknesses of these approaches to understand what has prevented these models from seeing widespread use by surveillance laboratories and to identify gaps that are underexplored with this technology. Methods and Results: We present a systematic review of English literature published through 15 April 2021 of studies employing machine learning methods to generate predictions of influenza A virus phenotypes from genomic or proteomic input. Forty-nine studies were included in this review, spanning the topics of host discrimination, human adaptability, subtype and clade assignment, pandemic lineage assignment, characteristics of infection, and antiviral drug resistance. Conclusions: Our findings suggest that biases in model design and a dearth of wet laboratory follow-up may explain why these models often go underused. We, therefore, offer guidance to overcome these limitations, aid in improving predictive models of previously studied influenza A virus phenotypes, and extend those models to unexplored phenotypes in the ultimate pursuit of tools to enable the characterization of virus isolates across surveillance laboratories.

Parallel evolution between genomic segments of seasonal human influenza viruses reveals RNA-RNA relationships

The influenza A virus (IAV) genome consists of eight negative-sense viral RNA (vRNA) segments that are selectively assembled into progeny virus particles through RNA-RNA interactions. To explore putative intersegmental RNA-RNA relationships, we quantified similarity between phylogenetic trees comprising each vRNA segment from seasonal human IAV. Intersegmental tree similarity differed between subtype and lineage. While intersegmental relationships were largely conserved over time in H3N2 viruses, they diverged in H1N1 strains isolated before and after the 2009 pandemic. Surprisingly, intersegmental relationships were not driven solely by protein sequence, suggesting that IAV evolution could also be driven by RNA-RNA interactions. Finally, we used confocal microscopy to determine that colocalization of highly coevolved vRNA segments is enriched over other assembly intermediates at the nuclear periphery during productive viral infection. This study illustrates how putative RNA interactions underlying selective assembly of IAV can be interrogated with phylogenetics.

The viruses responsible for influenza evolve rapidly during infection. Changes typically emerge in two key ways: through random mutations in the genetic sequence of the virus, or by reassortment. Reassortment can occur when two or more strains infect the same cell. Once in a cell, viral particles ‘open up’ to release their genetic material so it can make copies of itself using the cell’s machinery. The new copies of the genetic material of the virus are used to make new viral particles, which then envelop the genetic material and are released from the cell to infect other cells. If several strains of a virus infect the same cell, a new viral particle may pick up genetic segments from each of the infecting strains, creating a new strain via reassortment.

Several factors are known to affect the success of the reassortment process. For example, if the new strain acquires a genetic defect that hinders its replication cycle, it is likely to die out quickly. Other times, this trading of genetic information can create a strain that is more resistant to the human immune system, allowing it to sweep across the globe and cause a deadly pandemic. However, a key part of the reassortment process that still remains unclear is how genome segments from two different influenza strains recognize each other before merging together to create hybrid daughter viruses.

To explore this further, Jones et al. used a technique called fluorescence microscopy. They found that genome segments that evolved along similar paths were more likely to cluster in the same area inside infected cells, and therefore, more likely to be reassorted together into a new strain during assembly of daughter viruses. This suggests that assembly may guide the evolutionary path taken by individual genomic segments. Jones et al. also looked at the evolution of different genome segments collected from patients suffering from seasonal influenza, and found that these segments had a distinct evolutionary path to those in pandemic-causing strains.

This research provides new insights into the role of reassortment in the evolution of influenza viruses during infection. In particular, it suggests that how the genome segments interact with one another may have a previously unknown and important role in guiding this evolution. These insights could be used to predict future reassortment events based on evolutionary relationships between influenza virus genomic segments, and may in the future be used as part of risk assessment tools to predict the emergence of new pandemic strains.

RNA Modifications in Genomic RNA of Influenza A Virus and the Relationship between RNA Modifications and Viral Infection

Recent studies about the transcriptome-wide presence of RNA modifications have revealed their importance in many cellular functions. Nevertheless, information about RNA modifications in viral RNA is scarce, especially for negative-strand RNA viruses. Here we provide a catalog of RNA modifications including m1A, ac4C, m7G, inosine, and pseudouridine on RNA derived from an influenza A virus infected into A549 cells, as studied by RNA immunoprecipitation followed by deep-sequencing. Possible regions with RNA modifications were found in the negative-strand segments of viral genomic RNA. In addition, our analyses of previously published data revealed that the expression levels of the host factors for RNA modifications were affected by an infection with influenza A virus, and some of the host factors likely have a proviral effect. RNA modification is a novel aspect of host-virus interactions leading to the discovery of previously unrecognized viral pathogenicity mechanisms and has the potential to aid the development of novel antivirals.

Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting

Background

Local transmission of seasonal influenza viruses (IVs) can be difficult to resolve. Here, we study if coupling high-throughput sequencing (HTS) of hemagglutinin (HA) and neuraminidase (NA) genes with variant analysis can resolve strains from local transmission that have identical consensus genome. We analyzed 24 samples collected over four days in January 2020 at a large university in the US. We amplified complete hemagglutinin (HA) and neuraminidase (NA) genomic segments followed by Illumina sequencing. We identified consensus complete HA and NA segments using BLASTn and performed variant analysis on strains whose HA and NA segments were 100% similar.

Results

Twelve of the 24 samples were PCR positive, and we detected complete HA and/or NA segments by de novo assembly in 83.33% (10/12) of them. Similarity and phylogenetic analysis showed that 70% (7/10) of the strains were distinct while the remaining 30% had identical consensus sequences. These three samples also had IAV and IBV co-infection. However, subsequent variant analysis showed that they had distinct variant profiles. While the IAV HA of one sample had no variant, another had a T663C mutation and another had both C1379T and C1589A.

Conclusion

In this study, we showed that HTS coupled with variant analysis of only HA and NA genes can help resolve variants that are closely related. We also provide evidence that during a short time period in the 2019–2020 season, co-infection of IAV and IBV occurred on the university campus and both 2020/2021 and 2021/2022 WHO recommended H1N1 vaccine strains were co-circulating.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06526-5.

Novel isoforms of influenza virus PA-X and PB1-F2 indicated by automatic annotation

The influenza A virus genome contains 8 gene segments encoding 10 commonly recognized proteins. Additional protein products have been identified, including PB1-F2 and PA-X. We report the in-silico identification of novel isoforms of PB1-F2 and PA-X in influenza virus genomes sequenced from avian samples. The isoform observed in PA-X includes a mutated stop codon that should extend the protein product by 8 amino acids. The isoform observed in PB1-F2 includes two nonsense mutations that should truncate the N-terminal region of the protein product and remove the entire mitochondrial targeting domain. Both isoforms were uncovered during automatic annotation of CEIRS sequence data. Nominally termed PA-X8 and PB1-F2-Cterm, both predicted isoforms were subsequently found in other annotated influenza genomes previously deposited in GenBank. Both isoforms were noticed due to discrepant annotations output by two annotation engines, indicating a benefit of incorporating multiple algorithms during gene annotation.

A novel mechanism of enhanced transcription activity and fidelity for influenza A viral RNA-dependent RNA polymerase

During RNA elongation, the influenza A viral (IAV) RNA-dependent RNA polymerase (RdRp) residues in the active site interact with the triphosphate moiety of nucleoside triphosphate (NTP) for catalysis. The molecular mechanisms by which they control the rate and fidelity of NTP incorporation remain elusive. Here, we demonstrated through enzymology, virology and computational approaches that the R239 and K235 in the PB1 subunit of RdRp are critical to controlling the activity and fidelity of transcription. Contrary to common beliefs that high-fidelity RdRp variants exert a slower incorporation rate, we discovered a first-of-its-kind, single lysine-to-arginine mutation on K235 exhibited enhanced fidelity and activity compared with wild-type. In particular, we employed a single-turnover NTP incorporation assay for the first time on IAV RdRp to show that K235R mutant RdRp possessed a 1.9-fold increase in the transcription activity of the cognate NTP and a 4.6-fold increase in fidelity compared to wild-type. Our all-atom molecular dynamics simulations further elucidated that the higher activity is attributed to the shorter distance between K235R and the triphosphate moiety of NTP compared with wild-type. These results provide novel insights into NTP incorporation and fidelity control mechanisms, which lay the foundation for the rational design of IAV vaccine and antiviral targets.

Influenza in Malaysian adult patients hospitalized with community-acquired pneumonia, acute exacerbation of chronic obstructive pulmonary disease or asthma: a multicenter, active surveillance study

Background

Available data on influenza burden across Southeast Asia are largely limited to pediatric populations, with inconsistent findings.

Methods

We conducted a multicenter, hospital-based active surveillance study of adults in Malaysia with community-acquired pneumonia (CAP), acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and acute exacerbation of asthma (AEBA), who had influenza-like illness ≤10 days before hospitalization. We estimated the rate of laboratory-confirmed influenza and associated complications over 13 months (July 2018–August 2019) and described the distribution of causative influenza strains. We evaluated predictors of laboratory-confirmed influenza and severe clinical outcomes using multivariate analysis.

Results

Of 1106 included patients, 114 (10.3%) were influenza-positive; most were influenza A (85.1%), with A/H1N1pdm09 being the predominant circulating strain during the study following a shift from A/H3N2 from January–February 2019 onwards. In multivariate analyses, an absence of comorbidities (none versus any comorbidity [OR (95%CI), 0.565 (0.329–0.970)], p = 0.038) and of dyspnea (0.544 (0.341–0.868)], p = 0.011) were associated with increased risk of influenza positivity. Overall, 184/1106 (16.6%) patients were admitted to intensive care or high-dependency units (ICU/HDU) (13.2% were influenza positive) and 26/1106 (2.4%) died (2.6% were influenza positive). Males were more likely to have a severe outcome (ICU/HDU admission or death).

Conclusions

Influenza was a significant contributor to hospitalizations associated with CAP, AECOPD and AEBA. However, it was not associated with ICU/HDU admission in this population.

Study registration, NMRR ID: NMRR-17-889-35,174.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06360-9.

Exploiting Pan Influenza A and Pan Influenza B Pseudotype Libraries for Efficient Vaccine Antigen Selection

We developed an influenza hemagglutinin (HA) pseudotype library encompassing Influenza A subtypes HA1-18 and Influenza B subtypes (both lineages) to be employed in influenza pseudotype microneutralization (pMN) assays. The pMN is highly sensitive and specific for detecting virus-specific neutralizing antibodies against influenza viruses and can be used to assess antibody functionality in vitro. Here we show the production of these viral HA pseudotypes and their employment as substitutes for wildtype viruses in influenza neutralization assays. We demonstrate their utility in detecting serum responses to vaccination with the ability to evaluate cross-subtype neutralizing responses elicited by specific vaccinating antigens. Our findings may inform further preclinical studies involving immunization dosing regimens in mice and may help in the creation and selection of better antigens for vaccine design. These HA pseudotypes can be harnessed to meet strategic objectives that contribute to the strengthening of global influenza surveillance, expansion of seasonal influenza prevention and control policies, and strengthening pandemic preparedness and response.

Tracking the pipeline: immunoinformatics and the COVID-19 vaccine design

With the onset of the COVID-19 pandemic, the amount of data on genomic and proteomic sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stored in various databases has exponentially grown. A large volume of these data has led to the production of equally immense sets of immunological data, which require rigorous computational approaches to sort through and make sense of. Immunoinformatics has emerged in the recent decades as a field capable of offering this approach by bridging experimental and theoretical immunology with state-of-the-art computational tools. Here, we discuss how immunoinformatics can assist in the development of high-performance vaccines and drug discovery needed to curb the spread of SARS-CoV-2. Immunoinformatics can provide a set of computational tools to extract meaningful connections from the large sets of COVID-19 patient data, which can be implemented in the design of effective vaccines. With this in mind, we represent a pipeline to identify the role of immunoinformatics in COVID-19 treatment and vaccine development. In this process, a number of free databases of protein sequences, structures and mutations are introduced, along with docking web servers for assessing the interaction between antibodies and the SARS-CoV-2 spike protein segments as most commonly considered antigens in vaccine design.

mLoc-mRNA: predicting multiple sub-cellular localization of mRNAs using random forest algorithm coupled with feature selection via elastic net

BACKGROUND

Localization of messenger RNAs (mRNAs) plays a crucial role in the growth and development of cells. Particularly, it plays a major role in regulating spatio-temporal gene expression. The in situ hybridization is a promising experimental technique used to determine the localization of mRNAs but it is costly and laborious. It is also a known fact that a single mRNA can be present in more than one location, whereas the existing computational tools are capable of predicting only a single location for such mRNAs. Thus, the development of high-end computational tool is required for reliable and timely prediction of multiple subcellular locations of mRNAs. Hence, we develop the present computational model to predict the multiple localizations of mRNAs.

RESULTS

The mRNA sequences from 9 different localizations were considered. Each sequence was first transformed to a numeric feature vector of size 5460, based on the k-mer features of sizes 1-6. Out of 5460 k-mer features, 1812 important features were selected by the Elastic Net statistical model. The Random Forest supervised learning algorithm was then employed for predicting the localizations with the selected features. Five-fold cross-validation accuracies of 70.87, 68.32, 68.36, 68.79, 96.46, 73.44, 70.94, 97.42 and 71.77% were obtained for the cytoplasm, cytosol, endoplasmic reticulum, exosome, mitochondrion, nucleus, pseudopodium, posterior and ribosome respectively. With an independent test set, accuracies of 65.33, 73.37, 75.86, 72.99, 94.26, 70.91, 65.53, 93.60 and 73.45% were obtained for the respective localizations. The developed approach also achieved higher accuracies than the existing localization prediction tools.

CONCLUSIONS

This study presents a novel computational tool for predicting the multiple localization of mRNAs. Based on the proposed approach, an online prediction server "mLoc-mRNA" is accessible at http://cabgrid.res.in:8080/mlocmrna/ . The developed approach is believed to supplement the existing tools and techniques for the localization prediction of mRNAs.

Epitope-targeting platform for broadly protective influenza vaccines

Seasonal influenza vaccines are often ineffective because they elicit strain-specific antibody responses to mutation-prone sites on the hemagglutinin (HA) head. Vaccines that provide long-lasting immunity to conserved epitopes are needed. Recently, we reported a nanoparticle-based vaccine platform produced by solid-phase peptide synthesis (SPPS) for targeting linear and helical protein-based epitopes. Here, we illustrate its potential for building broadly protective influenza vaccines. Targeting known epitopes in the HA stem, neuraminidase (NA) active site, and M2 ectodomain (M2e) conferred 50-75% survival against 5LD50 influenza B and H1N1 challenge; combining stem and M2e antigens increased survival to 90%. Additionally, protein sequence and structural information were employed in tandem to identify alternative epitopes that stimulate greater protection; we report three novel HA and NA sites that are highly conserved in type B viruses. One new target in the HA stem stimulated 100% survival, highlighting the value of this simple epitope discovery strategy. A candidate influenza B vaccine targeting two adjacent HA stem sites led to >104-fold reduction in pulmonary viral load. These studies describe a compelling platform for building vaccines that target conserved influenza epitopes.

What can phylodynamics bring to animal health research?

Infectious diseases are a major burden to global economies, and public and animal health. To date, quantifying the spread of infectious diseases to inform policy making has traditionally relied on epidemiological data collected during epidemics. However, interest has grown in recent phylodynamic techniques to infer pathogen transmission dynamics from genetic data. Here, we provide examples of where this new discipline has enhanced disease management in public health and illustrate how it could be further applied in animal health. In particular, we describe how phylodynamics can address fundamental epidemiological questions, such as inferring key transmission parameters in animal populations and quantifying spillover events at the wildlife-livestock interface, and generate important insights for the design of more effective control strategies.

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Introduction: Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral diseases that are yet to come. Although machine learning (ML) have shown to improve predictions on the biological potential of chemicals and accelerate the discovery of drugs over the past decade, new methods and their combinations have improved their performance and established promising perspectives regarding ML in the search for new antivirals.Areas covered: The authors consider some interesting areas that deal with different ML techniques applied to antivirals. Recent innovative studies on ML and antivirals were selected and analyzed in detail. Also, the authors provide a brief look at the past to the present to detect advances and bottlenecks in the area.Expert opinion: From classical ML techniques, it was possible to boost the searches for antivirals. However, from the emergence of new algorithms and the improvement in old approaches, promising results will be achieved every day, as we have observed in the case of SARS-CoV-2. Recent experience has shown that it is possible to use ML to discover new antiviral candidates from virtual screening and drug repurposing.

Quantifying the Persistence of Vaccine-Related T Cell Epitopes in Circulating Swine Influenza A Strains from 2013-2017

When swine flu vaccines and circulating influenza A virus (IAV) strains are poorly matched, vaccine-induced antibodies may not protect from infection. Highly conserved T cell epitopes may, however, have a disease-mitigating effect. The degree of T cell epitope conservation among circulating strains and vaccine strains can vary, which may also explain differences in vaccine efficacy. Here, we evaluate a previously developed conserved T cell epitope-based vaccine and determine the persistence of T cell epitope conservation over time. We used a pair-wise homology score to define the conservation between the vaccine’s swine leukocyte antigen (SLA) class I and II-restricted epitopes and T cell epitopes found in 1272 swine IAV strains sequenced between 2013 and 2017. Twenty-four of the 48 total T cell epitopes included in the epitope-based vaccine were highly conserved and found in >1000 circulating swine IAV strains over the 5-year period. In contrast, commercial swine IAV vaccines developed in 2013 exhibited a declining conservation with the circulating IAV strains over the same 5-year period. Conserved T cell epitope vaccines may be a useful adjunct for commercial swine flu vaccines and to improve protection against influenza when antibodies are not cross-reactive.

Balanced Cellular and Humoral Immune Responses Targeting Multiple Antigens in Adults Receiving a Quadrivalent Inactivated Influenza Vaccine

The role of T cell immunity has been acknowledged in recent vaccine development and evaluation. We tested the humoral and cellular immune responses to Flucelvax^®, a quadrivalent inactivated seasonal influenza vaccine containing two influenza A (H1N1 Singapore/GP1908/2015 IVR-180 and H3N2 North Carolina/04/2016) and two influenza B (Iowa/06/2017 and Singapore/INFTT-16-0610/2016) virus strains, using peripheral blood mononuclear cells stimulated by pools of peptides overlapping all the individual influenza viral protein components. Baseline reactivity was detected against all four strains both at the level of CD4 and CD8 responses and targeting different proteins. CD4 T cell reactivity was mostly directed to HA/NA proteins in influenza B strains, and NP/M1/M2/NS1/NEP proteins in the case of the Influenza A strains. CD8 responses to both influenza A and B viruses preferentially targeted the more conserved core viral proteins. Following vaccination, both CD4 and CD8 responses against the various influenza antigens were increased in day 15 to day 91 post vaccination period, and maintained a Th1 polarized profile. Importantly, no vaccine interference was detected, with the increased responses balanced across all four included viral strains for both CD4 and CD8 T cells, and targeting HA and multiple additional viral antigens.

Comorbidities and Susceptibility to COVID-19: A Generalized Gene Set Data Mining Approach

The COVID-19 pandemic has led to over 2.26 million deaths for almost 104 million confirmed cases worldwide, as of 4 February 2021 (WHO). Risk factors include pre-existing conditions such as cancer, cardiovascular disease, diabetes, and obesity. Although several vaccines have been deployed, there are few alternative anti-viral treatments available in the case of reduced or non-existent vaccine protection. Adopting a long-term holistic approach to cope with the COVID-19 pandemic appears critical with the emergence of novel and more infectious SARS-CoV-2 variants. Our objective was to identify comorbidity-associated single nucleotide polymorphisms (SNPs), potentially conferring increased susceptibility to SARS-CoV-2 infection using a computational meta-analysis approach. SNP datasets were downloaded from a publicly available genome-wide association studies (GWAS) catalog for 141 of 258 candidate COVID-19 comorbidities. Gene-level SNP analysis was performed to identify significant pathways by using the program MAGMA. An SNP annotation program was used to analyze MAGMA-identified genes. Differential gene expression was determined for significant genes across 30 general tissue types using the Functional and Annotation Mapping of GWAS online tool GENE2FUNC. COVID-19 comorbidities (n = 22) from six disease categories were found to have significant associated pathways, validated by Q-Q plots (p < 0.05). Protein-protein interactions of significant (p < 0.05) differentially expressed genes were visualized with the STRING program. Gene interaction networks were found to be relevant to SARS and influenza pathogenesis. In conclusion, we were able to identify the pathways potentially affected by or affecting SARS-CoV-2 infection in underlying medical conditions likely to confer susceptibility and/or the severity of COVID-19. Our findings have implications in future COVID-19 experimental research and treatment development.

A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data

In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.

Machine Learning Methods for Predicting Human-Adaptive Influenza A Viruses Based on Viral Nucleotide Compositions

Each influenza pandemic was caused at least partly by avian- and/or swine-origin influenza A viruses (IAVs). The timing of and the potential IAVs involved in the next pandemic are currently unpredictable. We aim to build machine learning (ML) models to predict human-adaptive IAV nucleotide composition. A total of 217,549 IAV full-length coding sequences of the PB2 (polymerase basic protein-2), PB1, PA (polymerase acidic protein), HA (hemagglutinin), NP (nucleoprotein), and NA (neuraminidase) segments were decomposed for their codon position-based mononucleotides (12 nts) and dinucleotides (48 dnts). A total of 68,742 human sequences and 68,739 avian sequences (1:1) were resampled to characterize the human adaptation-associated (d)nts with principal component analysis (PCA) and other ML models. Then, the human adaptation of IAV sequences was predicted based on the characterized (d)nts. Respectively, 9, 12, 11, 13, 10 and 9 human-adaptive (d)nts were optimized for the six segments. PCA and hierarchical clustering analysis revealed the linear separability of the optimized (d)nts between the human-adaptive and avian-adaptive sets. The results of the confusion matrix and the area under the receiver operating characteristic curve indicated a high performance of the ML models to predict human adaptation of IAVs. Our model performed well in predicting the human adaptation of the swine/avian IAVs before and after the 2009 H1N1 pandemic. In conclusion, we identified the human adaptation-associated genomic composition of IAV segments. ML models for IAV human adaptation prediction using large IAV genomic data sets can facilitate the identification of key viral factors that affect virus transmission/pathogenicity. Most importantly, it allows the prediction of pandemic influenza.

Immunization and Drug Metabolizing Enzymes: Focus on Hepatic Cytochrome P450 3A

OBJECTIVE

Infectious disease emergencies like the 2013-2016 Ebola epidemic and the 2009 influenza and current SARS-CoV-2 pandemics illustrate that vaccines are now given to diverse populations with preexisting pathologies requiring pharmacological management. Many natural biomolecules (steroid hormones, fatty acids, vitamins) and ~60% of prescribed medications are processed by hepatic cytochrome P450 (CYP) 3A4. The objective of this work was to determine the impact of infection and vaccines on drug metabolism.

METHODS

The impact of an adenovirus-based vaccine expressing Ebola glycoprotein (AdEBO) and H1N1 and H3N2 influenza viruses on hepatic CYP 3A4 and associated nuclear receptors was evaluated in human hepatocytes (HC-04 cells) and in mice.

RESULTS

CYP3A activity was suppressed by 55% in mice 24 h after administration of mouse-adapted H1N1, while ˂10% activity remained in HC-04 cells after infection with H1N1 and H3N2 due to global suppression of cellular translation capacity, indicated by reduction (70%, H1N1, 56%, H3N2) of phosphorylated eukaryotic translation initiation factor 4e (eIF4E). AdEBO suppressed CYP3A activity in vivo (44%) and in vitro (26%) 24 hours after infection.

CONCLUSION

As the clinical evaluation of vaccines for SARS-CoV-2 and other global pathogens rise, studies to evaluate the impact of new vaccines and emerging pathogens on CYP3A4 and other metabolic enzymes are warranted to avoid therapeutic failures that could further compromise the public health during infectious disease emergencies.

Broad Reactivity Single Domain Antibodies against Influenza Virus and Their Applications to Vaccine Potency Testing and Immunotherapy

The antigenic variability of influenza presents many challenges to the development of vaccines and immunotherapeutics. However, it is apparent that there are epitopes on the virus that have evolved to remain largely constant due to their functional importance. These more conserved regions are often hidden and difficult to access by the human immune system but recent efforts have shown that these may be the Achilles heel of the virus through development and delivery of appropriate biological drugs. Amongst these, single domain antibodies (sdAbs) are equipped to target these vulnerabilities of the influenza virus due to their preference for concave epitopes on protein surfaces, their small size, flexible reformatting and high stability. Single domain antibodies are well placed to provide a new generation of robust analytical reagents and therapeutics to support the constant efforts to keep influenza in check.

Structural insights into the substrate specificity of the endonuclease activity of the influenza virus cap-snatching mechanism

The endonuclease activity within the influenza virus cap-snatching process is a proven therapeutic target. The anti-influenza drug baloxavir is highly effective, but is associated with resistance mutations that threaten its clinical efficacy. The endonuclease resides within the N-terminal domain of the PA subunit (PA_N) of the influenza RNA dependent RNA polymerase, and we report here complexes of PA_N with RNA and DNA oligonucleotides to understand its specificity and the structural basis of baloxavir resistance mutations. The RNA and DNA oligonucleotides bind within the substrate binding groove of PA_N in a similar fashion, explaining the ability of the enzyme to cleave both substrates. The individual nucleotides occupy adjacent conserved pockets that flank the two-metal active site. However, the 2′ OH of the RNA ribose moieties engage in additional interactions that appear to optimize the binding and cleavage efficiency for the natural substrate. The major baloxavir resistance mutation at position 38 is at the core of the substrate binding site, but structural studies and modeling suggest that it maintains the necessary virus fitness via compensating interactions with RNA. These studies will facilitate the development of new influenza therapeutics that spatially match the substrate and are less likely to elicit resistance mutations.

Swine Influenza A Viruses and the Tangled Relationship with Humans

Influenza A viruses (IAVs) are the causative agents of one of the most important viral respiratory diseases in pigs and humans. Human and swine IAV are prone to interspecies transmission, leading to regular incursions from human to pig and vice versa. This bidirectional transmission of IAV has heavily influenced the evolutionary history of IAV in both species. Transmission of distinct human seasonal lineages to pigs, followed by sustained within-host transmission and rapid adaptation and evolution, represent a considerable challenge for pig health and production. Consequently, although only subtypes of H1N1, H1N2, and H3N2 are endemic in swine around the world, extensive diversity can be found in the hemagglutinin (HA) and neuraminidase (NA) genes, as well as the remaining six genes. We review the complicated global epidemiology of IAV in swine and the inextricably entangled implications for public health and influenza pandemic planning.

Host Range of Influenza A Virus H1 to H16 in Eurasian Ducks Based on Tissue and Receptor Binding Studies

Dabbling and diving ducks partly occupy shared habitats but have been reported to play different roles in wildlife infectious disease dynamics. Influenza A virus (IAV) epidemiology in wild birds has been based primarily on surveillance programs focused on dabbling duck species, particularly mallard (Anas platyrhynchos). Surveillance in Eurasia has shown that in mallards, some subtypes are commonly (H1 to H7 and H10), intermediately (H8, H9, H11, and H12), or rarely (H13 to H16) detected, contributing to discussions on virus host range and reservoir competence. An alternative to surveillance in determining IAV host range is to study virus attachment as a determinant for infection. Here, we investigated the attachment patterns of all avian IAV subtypes (H1 to H16) to the respiratory and intestinal tracts of four dabbling duck species (Mareca and Anas spp.), two diving duck species (Aythya spp.), and chicken, as well as to a panel of 65 synthetic glycan structures. We found that IAV subtypes generally showed abundant attachment to colon of the Anas duck species, mallard, and Eurasian teal (Anas crecca), supporting the fecal-oral transmission route in these species. The reported glycan attachment profile did not explain the virus attachment patterns to tissues but showed significant attachment of duck-originated viruses to fucosylated glycan structures and H7 virus tropism for Neu5Gc-LN. Our results suggest that Anas ducks play an important role in the ecology and epidemiology of IAV. Further knowledge on virus tissue attachment, receptor distribution, and receptor binding specificity is necessary to understand the mechanisms underlying host range and epidemiology of IAV.IMPORTANCE Influenza A viruses (IAVs) circulate in wild birds worldwide. From wild birds, the viruses can cause outbreaks in poultry and sporadically and indirectly infect humans. A high IAV diversity has been found in mallards (Anas platyrhynchos), which are most often sampled as part of surveillance programs; meanwhile, little is known about the role of other duck species in IAV ecology and epidemiology. In this study, we investigated the attachment of all avian IAV hemagglutinin (HA) subtypes (H1 to H16) to tissues of six different duck species and chicken as an indicator of virus host range. We demonstrated that the observed virus attachment patterns partially explained reported field prevalence. This study demonstrates that dabbling ducks of the Anas genus are potential hosts for most IAV subtypes, including those infecting poultry. This knowledge is useful to target the sampling of wild birds in nature and to further study the interaction between IAVs and birds.

Biased Mutation and Selection in RNA Viruses

RNA viruses are responsible for some of the worst pandemics known to mankind, including outbreaks of Influenza, Ebola, and COVID-19. One major challenge in tackling RNA viruses is the fact they are extremely genetically diverse. Nevertheless, they share common features that include their dependence on host cells for replication, and high mutation rates. We set out to search for shared evolutionary characteristics that may aid in gaining a broader understanding of RNA virus evolution, and constructed a phylogeny-based data set spanning thousands of sequences from diverse single-stranded RNA viruses of animals. Strikingly, we found that the vast majority of these viruses have a skewed nucleotide composition, manifested as adenine rich (A-rich) coding sequences. In order to test whether A-richness is driven by selection or by biased mutation processes, we harnessed the effects of incomplete purifying selection at the tips of virus phylogenies. Our results revealed consistent mutational biases toward U rather than A in genomes of all viruses. In +ssRNA viruses, we found that this bias is compensated by selection against U and selection for A, which leads to A-rich genomes. In -ssRNA viruses, the genomic mutational bias toward U on the negative strand manifests as A-rich coding sequences, on the positive strand. We investigated possible reasons for the advantage of A-rich sequences including weakened RNA secondary structures, codon usage bias, and selection for a particular amino acid composition, and conclude that host immune pressures may have led to similar biases in coding sequence composition across very divergent RNA viruses.

Influenza A Viruses in Whistling Ducks (Subfamily Dendrocygninae)

As compared to other Anseriformes, data related to influenza A virus (IAV) detection and isolation, and IAV antibody detection in whistling ducks (Dendrocygna spp. and Thalassornis leuconotus; subfamily Dendrocygninae) are limited. To better evaluate the potential role of whistling ducks in the epidemiology of IAV, we (1) conducted surveillance for IAV from black-bellied whistling ducks (BBWD, Dendrocygnaautumnalis) sampled in coastal Louisiana, USA, during February 2018 and 2019, and (2) reviewed the published literature and Influenza Resource Database (IRD) that reported results of IAV surveillance of whistling ducks. In the prospective study, from 166 BBWD sampled, one H10N7 IAV was isolated (0.6% prevalence), and overall blocking enzyme-linked immunosorbent assay (bELISA) antibody seroprevalence was 10%. The literature review included publications and data in the IRD from 1984 to 2020 that reported results from nearly 5000 collected samples. For any given collection, the IAV isolation rate never exceeded 5.5%, and seroprevalence estimates ranged from 0 to 42%. Results from our prospective study in Louisiana are consistent with this historic literature; however, although all data consistently demonstrated a low prevalence of infection, the potential role of this species in the epidemiology of IAV should not be totally discounted. In sum, whistling ducks can be infected with IAV, they represent important species on many areas where waterfowl winter, and their distribution across the globe appears to be changing.

Genomic Evidence for Sequestration of Influenza A Virus Lineages in Sea Duck Host Species

Wild birds are considered the natural reservoir of influenza A viruses (IAVs) making them critical for IAV surveillance efforts. While sea ducks have played a role in novel IAV emergence events that threatened food security and public health, very few surveillance samples have been collected from sea duck hosts. From 2014–2018, we conducted surveillance focused in the Mississippi flyway, USA at locations where sea duck harvest has been relatively successful compared to our other sampling locations. Our surveillance yielded 1662 samples from sea ducks, from which we recovered 77 IAV isolates. Our analyses identified persistence of sea duck specific IAV lineages across multiple years. We also recovered sea duck origin IAVs containing an H4 gene highly divergent from the majority of North American H4-HA with clade node age of over 65 years. Identification of IAVs with long branch lengths is indicative of substantial genomic change consistent with persistence without detection by surveillance efforts. Sea ducks play a role in the movement and long-term persistence of IAVs and are likely harboring more undetected IAV diversity. Sea ducks should be a point of emphasis for future North American wild bird IAV surveillance efforts.

Gaps in Serologic Immunity against Contemporary Swine-Origin Influenza A Viruses among Healthy Individuals in the United States

Influenza A Viruses (IAV) in domestic swine (IAV-S) are associated with sporadic zoonotic transmission at the human–animal interface. Previous pandemic IAVs originated from animals, which emphasizes the importance of characterizing human immunity against the increasingly diverse IAV-S. We analyzed serum samples from healthy human donors (n = 153) using hemagglutination-inhibition (HAI) assay to assess existing serologic protection against a panel of contemporary IAV-S isolated from swine in the United States (n = 11). Age-specific seroprotection rates (SPR), which are the proportion of individuals with HAI ≥ 1:40, corresponded with lower or moderate pandemic risk classifications for the multiple IAV-S examined (one H1-δ1, one H1-δ2, three H3-IVA, one H3-IVB, one H3-IVF). Individuals born between 2004 and 2013 had SPRs of 0% for the five classified H3 subtype IAV-S, indicating youth may be particularly predisposed to infection with these viruses. Expansion of existing immunologic gaps over time could increase likelihood of future IAV-S spillover to humans and facilitate subsequent sustained human-to-human transmission resulting in disease outbreaks with pandemic potential.

Database and Analytical Resources for Viral Research Community

Many public databases and analytical resources are available to facilitate virology research. The Virus Pathogen Database and Analysis Resource (ViPR, see “Relevant Websites section”) and Influenza Research Database (IRD, see “Relevant Websites section”) are comprehensive and highly curated repositories of genome and protein sequence records and annotations, protein structures, immune epitopes, and epidemiological and surveillance data about human and related viral pathogens. These data are acquired from public repositories, direct submissions and in-house bioinformatics analyses. The resources offer seamless integration of data, analytics and visualization, and are freely available without cost or restriction to facilitate diagnostics and therapeutics development for priority pathogens.

Next-generation computational tools and resources for coronavirus research: From detection to vaccine discovery

The COVID-19 pandemic has affected 215 countries and territories around the world with 60,187,347 coronavirus cases and 17,125,719 currently infected patients confirmed as of the November 25, 2020. Currently, many countries are working on developing new vaccines and therapeutic drugs for this novel virus strain, and a few of them are in different phases of clinical trials. The advancement in high-throughput sequence technologies, along with the application of bioinformatics, offers invaluable knowledge on genomic characterization and molecular pathogenesis of coronaviruses. Recent multi-disciplinary studies using bioinformatics methods like sequence-similarity, phylogenomic, and computational structural biology have provided an in-depth understanding of the molecular and biochemical basis of infection, atomic-level recognition of the viral-host receptor interaction, functional annotation of important viral proteins, and evolutionary divergence across different strains. Additionally, various modern immunoinformatic approaches are also being used to target the most promiscuous antigenic epitopes from the SARS-CoV-2 proteome for accelerating the vaccine development process. In this review, we summarize various important computational tools and databases available for systematic sequence-structural study on coronaviruses. The features of these public resources have been comprehensively discussed, which may help experimental biologists with predictive insights useful for ongoing research efforts to find therapeutics against the infectious COVID-19 disease.

Viral Subpopulation Screening Guides in Designing a High Interferon-Inducing Live Attenuated Influenza Vaccine by Targeting Rare Mutations in NS1 and PB2 Proteins

Influenza A viruses continue to circulate among wild birds and poultry worldwide, posing constant pandemic threats to humans. Effective control of emerging influenza viruses requires new broadly protective vaccines. Live attenuated influenza vaccines with truncations in nonstructural protein 1 (NS1) have shown broad protective efficacies in birds and mammals, which correlate with the ability to induce elevated interferon responses in the vaccinated hosts. Given the extreme diversity of influenza virus populations, we asked if we could improve an NS1-truncated live attenuated influenza vaccine developed for poultry (PC4) by selecting viral subpopulations with enhanced interferon-inducing capacities. Here, we deconstructed a de novo population of PC4 through plaque isolation, created a large library of clones, and assessed their interferon-inducing phenotypes. While most of the clones displayed the parental interferon-inducing phenotype in cell culture, few clones showed enhanced interferon-inducing phenotypes in cell culture and chickens. The enhanced interferon-inducing phenotypes were linked to either a deletion in NS1 (NS1Δ76-86) or a substitution in polymerase basic 2 protein (PB2-D309N). The NS1Δ76-86 deletion disrupted the putative eukaryotic translation initiation factor 4GI-binding domain and promoted the synthesis of biologically active interferons. The PB2-D309N substitution enhanced the early transcription of interferon mRNA, revealing a novel role for the 309D residue in suppression of interferon responses. We combined these mutations to engineer a novel vaccine candidate that induced additive amounts of interferons and stimulated protective immunity in chickens. Therefore, viral subpopulation screening approaches can guide the design of live vaccines with strong immunostimulatory properties.IMPORTANCE Effectiveness of NS1-truncated live attenuated influenza vaccines relies heavily on their ability to induce elevated interferon responses in vaccinated hosts. Influenza viruses contain diverse particle subpopulations with distinct phenotypes. We show that live influenza vaccines can contain underappreciated subpopulations with enhanced interferon-inducing phenotypes. The genomic traits of such virus subpopulations can be used to further improve the efficacy of the current live vaccines.

Influenza in High-Risk Hosts-Lessons Learned from Animal Models

Factoring significantly into the global burden of influenza disease are high-risk populations that suffer the bulk of infections. Classically, the very young, very old, and pregnant women have been identified as high-risk populations; however, recent research has uncovered several other conditions that contribute to severe infection. By using varied animal models, researchers have identified molecular mechanisms underpinning the increased likelihood for infection due to obesity and malnourishment, as well as insight into the role sex hormones play in antiviral immunity in males, in females, and across the life span. Additionally, novel comorbidity models have helped elucidate the role of chronic infectious and genetic diseases in influenza virus pathogenesis. Animal models play a vital role in understanding the contribution of host factors to influenza severity and immunity. An in-depth understanding of these host factors represents an important step in reducing the burden of influenza among the growing number of people living with one or more chronic medical conditions.

Virus strain influenced the interspecies transmission of influenza D virus between calves and pigs

Influenza D viruses (IDV) belong to a new genus in the family Orthomyxoviridae. IDV is the aetiologic agent of acute, mild respiratory disease in ungulate species with agricultural importance (cattle, pigs, sheep, goats, camels, etc.). Despite the initial isolate being of porcine origin, serological data suggest cattle to be the primary host of IDV. The study aims were twofold: elucidating species-specific replication kinetics of IDV in bovine and porcine hosts and defining the interspecies potential with two different IDV strains. Three calves and three pigs were intranasally inoculated with the prototypic strain D/swine/Oklahoma/1334/2017 or a genetically distinct cattle isolate, D/bovine/Texas/72/2017. Two days following infection, three naïve pigs and three naïve calves were co-housed with inoculated calves and pigs, respectively. The species of IDV origin had no effect on virus replication kinetics in the upper respiratory tract of inoculated calves and pigs; similar shedding profiles were observed for each species and virus. However, interspecies transmission was found to be associated with virus origin species; D/bovine/Texas/72/2017 and D/swine/Oklahoma/1334/2017 were directly transmitted only to contact calves or pigs, respectively. Even so, transmission efficiency was higher for calves compared to pigs. Together, these data show that cattle and pigs are permissive for IDV replication, but IDV transmission may be species dependent. Host-specific mutations likely influenced transmission efficiencies between agriculturally important mammalian species.

A Heterogeneous Swine Show Circuit Drives Zoonotic Transmission of Influenza A Viruses in the United States

Influenza pandemics are associated with severe morbidity, mortality, and social and economic disruption. Every summer in the United States, youths attending agricultural fairs are exposed to genetically diverse influenza A viruses (IAVs) circulating in exhibition swine, resulting in over 450 lab-confirmed zoonotic infections since 2010. Exhibition swine represent a small, defined population (∼1.5% of the U.S. herd), presenting a realistic opportunity to mitigate a pandemic threat by reducing IAV transmission in the animals themselves. Through intensive surveillance and genetic sequencing of IAVs in exhibition swine in six U.S. states in 2018 (n = 212), we characterized how a heterogeneous circuit of swine shows, comprising fairs with different sizes and geographic coverage, facilitates IAV transmission among exhibition swine and into humans. Specifically, we identified the role of an early-season national show in the propagation and spatial dissemination of a specific virus (H1δ-2) that becomes dominant among exhibition swine and is associated with the majority of zoonotic infections in 2018. These findings suggest that a highly targeted mitigation strategy, such as postponing swine shows for 1 to 2 weeks following the early-season national show, could potentially reduce IAV transmission in exhibition swine and spillover into humans, and this merits further study.IMPORTANCE The varying influenza A virus (IAV) exposure and infection status of individual swine facilitates introduction, transmission, and dissemination of diverse IAVs. Since agricultural fairs bring people into intimate contact with swine, they provide a unique interface for zoonotic transmission of IAV. Understanding the dynamics of IAV transmission through exhibition swine is critical to mitigating the high incidence of variant IAV cases reported in association with agricultural fairs. We used genomic sequences from our exhibition swine surveillance to characterize the hemagglutinin and full genotypic diversity of IAV at early-season shows and the subsequent dissemination through later-season agricultural fairs. We were able to identify a critical time point with important implications for downstream IAV and zoonotic transmission. With improved understanding of evolutionary origins of zoonotic IAV, we can inform public health mitigation strategies to ultimately reduce zoonotic IAV transmission and risk of pandemic IAV emergence.

In silico design of influenza a virus artificial epitope-based T-cell antigens and the evaluation of their immunogenicity in mice

The polyepitope strategy is promising approach for successfully creating a broadly protective flu vaccine, which targets T-lymphocytes (both CD4+ and CD8+) to recognise the most conserved epitopes of viral proteins. In this study, we employed a computer-aided approach to develop several artificial antigens potentially capable of evoking immune responses to different virus subtypes. These antigens included conservative T-cell epitopes of different influenza A virus proteins. To design epitope-based antigens we used experimentally verified information regarding influenza virus T-cell epitopes from the Immune Epitope Database (IEDB) (http://www.iedb.org). We constructed two "human" and two "murine" variants of polyepitope antigens. Amino acid sequences of target polyepitope antigens were designed using our original TEpredict/PolyCTLDesigner software. Immunogenic and protective features of DNA constructs encoding "murine" target T-cell immunogens were studied in BALB/c mice. We showed that mice groups immunised with a combination of computer-generated "murine" DNA immunogens had a 37.5% survival rate after receiving a lethal dose of either A/California/4/2009 (H1N1) virus or A/Aichi/2/68 (H3N2) virus, while immunisation with live flu H1N1 and H3N2 vaccine strains provided protection against homologous viruses and failed to protect against heterologous viruses. These results demonstrate that mechanisms of cross-protective immunity may be associated with the stimulation of specific T-cell responses. This study demonstrates that our computer-aided approach may be successfully used for rational designing artificial polyepitope antigens capable of inducing virus-specific T-lymphocyte responses and providing partial protection against two different influenza virus subtypes.Communicated by Ramaswamy H. Sarma.

Characterization of contemporary 2010.1 H3N2 swine influenza A viruses circulating in United States pigs

In 2012, swine influenza surveillance detected a novel reassorted influenza A virus (IAV) strain containing human-seasonal hemagglutinin (HA) and neuraminidase (NA). Subsequently, these viruses reassorted, maintaining only the human-origin H3, which resulted in a new lineage of viruses that became the most frequently detected H3 clade in US swine (2010.1 HA clade). Here, we assessed the antigenic phenotype, virulence, and transmission characteristics of this virus lineage following its introduction to swine. Relative to 2010.1 viruses from 2012 and 2014, recent 2010.1 contemporary strains from 2015 to 2017 resulted in equivalent macroscopic lung lesions and transmission in pigs. A single mutation at amino acid residue 145 within the previously defined HA antigenic motif was associated with a change of antigenic phenotype, potentially impairing vaccine efficacy. Contemporary 2010.1 viruses circulating in swine since 2012 were significantly different from both pre-2012H3N2 in swine and human-seasonal H3N2 viruses and demonstrated continued evolution within the lineage.

Antigenicity prediction and vaccine recommendation of human influenza virus A (H3N2) using convolutional neural networks

The rapid evolution of influenza A viruses poses a great challenge to vaccine development. Analytical and machine learning models have been applied to facilitate the process of antigenicity determination. In this study, we designed deep convolutional neural networks (CNNs) to predict Influenza antigenicity. Our model is the first that systematically analyzed 566 amino acid properties and 141 amino acid substitution matrices for their predictability. We then optimized the structure of the CNNs using particle swarm optimization. The optimal neural networks outperform other predictive models with a blind validation accuracy of 95.8%. Further, we applied our model to vaccine recommendations in the period 1997 to 2011 and contrasted the performance of previous vaccine recommendations using traditional experimental approaches. The results show that our model outperforms the WHO recommendation and other existing models and could potentially improve the vaccine recommendation process. Our results show that WHO often selects virus strains with small variation from year to year and learns slowly and recovers once coverage dips very low. In contrast, the influenza strains selected via our CNN model can differ quite drastically from year to year and exhibit consistently good coverage. In summary, we have designed a comprehensive computational pipeline for optimizing a CNN in the modeling of Influenza A antigenicity and vaccine recommendation. It is more cost and time-effective when compared to traditional hemagglutination inhibition assay analysis. The modeling framework is flexible and can be adopted to study other type of viruses.

Identification of a Newly Conserved SLA-II Epitope in a Structural Protein of Swine Influenza Virus

Despite the role of pigs as a source of new Influenza A Virus viruses (IAV) potentially capable of initiating human pandemics, immune responses to swine influenza virus (SwIV) in pigs are not fully understood. Several SwIV epitopes presented by swine MHC (SLA) class I have been identified using different approaches either in outbred pigs or in Babraham large white inbred pigs, which are 85% identical by genome wide SNP analysis. On the other hand, some class II SLA epitopes were recently described in outbred pigs. In this work, Babraham large white inbred pigs were selected to identify SLA II epitopes from SwIV H1N1. PBMCs were screened for recognition of overlapping peptides covering the NP and M1 proteins from heterologous IAV H1N1 in IFNγ ELISPOT. A novel SLA class II restricted epitope was identified in NP from swine H1N1. This conserved novel epitope could be the base for further vaccine approaches against H1N1 in pigs.

Full-length three-dimensional structure of the influenza A virus M1 protein and its organization into a matrix layer

Matrix proteins are encoded by many enveloped viruses, including influenza viruses, herpes viruses, and coronaviruses. Underneath the viral envelope of influenza virus, matrix protein 1 (M1) forms an oligomeric layer critical for particle stability and pH-dependent RNA genome release. However, high-resolution structures of full-length monomeric M1 and the matrix layer have not been available, impeding antiviral targeting and understanding of the pH-dependent transitions involved in cell entry. Here, purification and extensive mutagenesis revealed protein–protein interfaces required for the formation of multilayered helical M1 oligomers similar to those observed in virions exposed to the low pH of cell entry. However, single-layered helical oligomers with biochemical and ultrastructural similarity to those found in infectious virions before cell entry were observed upon mutation of a single amino acid. The highly ordered structure of the single-layered oligomers and their likeness to the matrix layer of intact virions prompted structural analysis by cryo-electron microscopy (cryo-EM). The resulting 3.4-Å–resolution structure revealed the molecular details of M1 folding and its organization within the single-shelled matrix. The solution of the full-length M1 structure, the identification of critical assembly interfaces, and the development of M1 assembly assays with purified proteins are crucial advances for antiviral targeting of influenza viruses.

Multi-subunit shells of matrix proteins line the interior of infectious influenza virus particles. In this study, biochemical purification of wild-type and mutant influenza M1 proteins allows the structural determination of an oligomer whose shape corresponds to that of infectious virions and suggests mechanisms for its formation and dismantling during infection.

A chimeric influenza hemagglutinin delivered by parainfluenza virus 5 vector induces broadly protective immunity against genetically divergent influenza a H1 viruses in swine

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An HA-based vaccine candidate, created by DNA shuffling (HA-113), can be immunogenic when recombinant antigen is expressed by PIV5 (PIV5-113).

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Immunity induced by the PIV5-113 vaccine can protect mice against infection with 4 of 5 parental HAs used to create the vaccine.

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Immunity induced by PIV5-113 can protect pigs against infection with an influenza virus isolate that is known to be infectious in pigs.

Pigs are an important reservoir for human influenza viruses, and influenza causes significant economic loss to the swine industry. As demonstrated during the 2009 H1N1 pandemic, control of swine influenza virus infection is a critical step toward blocking emergence of human influenza virus. An effective vaccine that can induce broadly protective immunity against heterologous influenza virus strains is critically needed. In our previous studies [McCormick et al., 2015; PLoS One, 10(6):e0127649], we used molecular breeding (DNA shuffling) strategies to increase the breadth of the variable and conserved epitopes expressed within a single influenza A virus chimeric hemagglutinin (HA) protein. Chimeric HAs were constructed using parental HAs from the 2009 pandemic virus and swine influenza viruses that had a history of zoonotic transmission to humans. In the current study, we used parainfluenza virus 5 (PIV-5) as a vector to express one of these chimeric HA antigens, HA-113. Recombinant PIV-5 expressing HA-113 (PIV5-113) were rescued, and immunogenicity and protective efficacy were tested in both mouse and pig models. The results showed that PIV5-113 can protect mice and pigs against challenge with viruses expressing parental HAs. The protective immunity was extended against other genetically diversified influenza H1-expressing viruses. Our work demonstrates that PIV5-based influenza vaccines are efficacious as vaccines for pigs. The PIV5 vaccine vector and chimeric HA-113 antigen are discussed in the context of the development of universal influenza vaccines and the potential contribution of PIV5-113 as a candidate universal vaccine.

Infection Dynamics of Swine Influenza Virus in a Danish Pig Herd Reveals Recurrent Infections with Different Variants of the H1N2 Swine Influenza A Virus Subtype

Influenza A virus (IAV) in swine, so-called swine influenza A virus (swIAV), causes respiratory illness in pigs around the globe. In Danish pig herds, a H1N2 subtype named H1N2dk is one of the main circulating swIAV. In this cohort study, the infection dynamic of swIAV was evaluated in a Danish pig herd by sampling and PCR testing of pigs from two weeks of age until slaughter at 22 weeks of age. In addition, next generation sequencing (NGS) was used to identify and characterize the complete genome of swIAV circulating in the herd, and to examine the antigenic variability in the antigenic sites of the virus hemagglutinin (HA) and neuraminidase (NA) proteins. Overall, 76.6% of the pigs became PCR positive for swIAV during the study, with the highest prevalence at four weeks of age. Detailed analysis of the virus sequences obtained showed that the majority of mutations occurred at antigenic sites in the HA and NA proteins of the virus. At least two different H1N2 variants were found to be circulating in the herd; one H1N2 variant was circulating at the sow and nursery sites, while another H1N2 variant was circulating at the finisher site. Furthermore, it was demonstrated that individual pigs had recurrent swIAV infections with the two different H1N2 variants, but re-infection with the same H1N2 variant was also observed. Better understandings of the epidemiology, genetic and antigenic diversity of swIAV may help to design better health interventions for the prevention and control of swIAV infections in the herds.

Phosphorylation controls RNA binding and transcription by the influenza virus polymerase

The influenza virus polymerase transcribes and replicates the viral genome. The proper timing and balance of polymerase activity is important for successful replication. Genome replication is controlled in part by phosphorylation of NP that regulates assembly of the replication machinery. However, it remains unclear whether phosphorylation directly regulated polymerase activity. Here we identified polymerase phosphosites that control its function. Mutating phosphosites in the catalytic subunit PB1 altered polymerase activity and virus replication. Biochemical analyses revealed phosphorylation events that disrupted global polymerase function by blocking the NTP entry channel or preventing RNA binding. We also identified a regulatory site that split polymerase function by specifically suppressing transcription. These experiments show that host kinases phospho-regulate viral RNA synthesis directly by modulating polymerase activity and indirectly by controlling assembly of replication machinery. Further, they suggest polymerase phosphorylation may bias replication versus transcription at discrete times or locations during the infectious cycle.

The influenza virus polymerase is a multifunctional enzyme directing viral gene expression and genome replication. Immediately following infection, the polymerase primarily performs transcription to make the viral mRNAs that program the replication cycle. The polymerase then shifts output to produce more copies of the viral genome at later stages of infection. The balance between transcription and replication is critical for successful infection. Here we identify phosphorylation sites within the viral polymerase and describe how these post-translational modifications control polymerase activity. Cellular kinases modify the viral polymerase. We identified a phosphorylation site in the catalytic subunit PB1 that selectively disables transcription, but not replication. We also describe a phosphorylation site in PB1 that disrupts binding to viral RNAs, disabling all activities of the polymerase. These modifications may establish polymerases with specialized function, and help regulate the balance between transcription and replication throughout the viral life cycle.