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

Identification and relative abundance of naturally presented and cross-reactive influenza A virus MHC class I-restricted T cell epitopes

Cytotoxic T lymphocytes are key for controlling viral infection. Unravelling CD8+ T cell-mediated immunity to distinct influenza virus strains and subtypes across prominent HLA types is relevant for combating seasonal infections and emerging new variants. Using an immunopeptidomics approach, naturally presented influenza A virus-derived ligands restricted to HLA-A*24:02, HLA-A*68:01, HLA-B*07:02, and HLA-B*51:01 molecules were identified. Functional characterization revealed multifunctional memory CD8+ T cell responses for nine out of sixteen peptides. Peptide presentation kinetics was optimal around 12 h post infection and presentation of immunodominant epitopes shortly after infection was not always persistent. Assessment of immunogenic epitopes revealed that they are highly conserved across the major zoonotic reservoirs and may contain a single substitution in the vicinity of the anchor residues. These findings demonstrate how the identified epitopes promote T cell pools, possibly cross-protective in individuals and can be potential targets for vaccination.

Using an adaptive modeling framework to identify avian influenza spillover risk at the wild-domestic interface

The wild to domestic bird interface is an important nexus for emergence and transmission of highly pathogenic avian influenza (HPAI) viruses. Although the recent incursion of HPAI H5N1 Clade 2.3.4.4b into North America calls for emergency response and planning given the unprecedented scale, readily available data-driven models are lacking. Here, we provide high resolution spatial and temporal transmission risk models for the contiguous United States. Considering virus host ecology, we included weekly species-level wild waterfowl (Anatidae) abundance and endemic low pathogenic avian influenza virus prevalence metrics in combination with number of poultry farms per commodity type and relative biosecurity risks at two spatial scales: 3 km and county-level. Spillover risk varied across the annual cycle of waterfowl migration and some locations exhibited persistent risk throughout the year given higher poultry production. Validation using wild bird introduction events identified by phylogenetic analysis from 2022 to 2023 HPAI poultry outbreaks indicate strong model performance. The modular nature of our approach lends itself to building upon updated datasets under evolving conditions, testing hypothetical scenarios, or customizing results with proprietary data. This research demonstrates an adaptive approach for developing models to inform preparedness and response as novel outbreaks occur, viruses evolve, and additional data become available.

Potential pandemic risk of circulating swine H1N2 influenza viruses

Influenza A viruses in swine have considerable genetic diversity and continue to pose a pandemic threat to humans due to a potential lack of population level immunity. Here we describe a pipeline to characterize and triage influenza viruses for their pandemic risk and examine the pandemic potential of two widespread swine origin viruses. Our analysis reveals that a panel of human sera collected from healthy adults in 2020 has no cross-reactive neutralizing antibodies against a α-H1 clade strain (α-swH1N2) but do against a γ-H1 clade strain. The α-swH1N2 virus replicates efficiently in human airway cultures and exhibits phenotypic signatures similar to the human H1N1 pandemic strain from 2009 (H1N1pdm09). Furthermore, α-swH1N2 is capable of efficient airborne transmission to both naïve ferrets and ferrets with prior seasonal influenza immunity. Ferrets with H1N1pdm09 pre-existing immunity show reduced α-swH1N2 viral shedding and less severe disease signs. Despite this, H1N1pdm09-immune ferrets that became infected via the air can still onward transmit α-swH1N2 with an efficiency of 50%. These results indicate that this α-swH1N2 strain has a higher pandemic potential, but a moderate level of impact since there is reduced replication fitness and pathology in animals with prior immunity.

Prediction of viral families and hosts of single-stranded RNA viruses based on K-Mer coding from phylogenetic gene sequences

There are billions of virus species worldwide, and viruses, the smallest parasitic entities, pose a serious threat. Therefore, fighting associated disorders requires an understanding of the genetic structure of viruses. Considering the wide diversity and rapid evolution of viruses, there is a critical need to quickly and accurately classify viral species and their potential hosts to better understand transmission dynamics, facilitating the development of targeted therapies. Recognizing this, this study has investigated the classes of RNA viruses based on their genomic sequences using Machine Learning (ML) and Deep Learning (DL) models. The PhyVirus dataset, consisting of pathogenic Single-stranded RNA viruses of Baltimore group four (+ssRNA) and five (-ssRNA) with different hosts and species, was analyzed. The dataset containing viral gene sequences was analyzed using the K-Mer coding technique, which is based on base words of various lengths. The study used classical ML algorithms (Random Forest, Gradient Boosting and Extra Trees) and the Fully Connected Deep Neural Network, a Deep Learning algorithm, to predict viral families and hosts. Detailed analyses were performed on the classifier performance in scenarios with different train-test ratios and different word lengths (k-values) for K-Mer. The observed results show that Fully Connected Deep Neural Network has a high success rate of 99.60 % in predicting virus families. In predicting virus hosts, the Extra Trees classifier achieved the highest success rate of 81.53 %. This study is considered to be the first classification study in the literature on this dataset, which has a very large family and host diversity consisting of gene sequences of Single-stranded RNA viruses. Our detailed investigations on how varying word lengths based on K-Mer coding in gene sequences affect the classification into viral families and hosts make this study particularly valuable. This study shows that ML and DL methods have the potential to produce valuable results in phylogenetic studies. In addition, the results and high-performance values show that these methods can be successfully used in regenerative applications of gene sequences or in studies such as the elimination of losses in gene sequences.

Immune memory shapes human polyclonal antibody responses to H2N2 vaccination

Influenza A virus subtype H2N2, which caused the 1957 influenza pandemic, remains a global threat. A recent phase 1 clinical trial investigating a ferritin nanoparticle vaccine displaying H2 hemagglutinin (HA) in H2-naive and H2-exposed adults enabled us to perform comprehensive structural and biochemical characterization of immune memory on the breadth and diversity of the polyclonal serum antibody response elicited. We temporally map the epitopes targeted by serum antibodies after vaccine prime and boost, revealing that previous H2 exposure results in higher responses to the variable HA head domain. In contrast, initial responses in H2-naive participants are dominated by antibodies targeting conserved epitopes. We use cryoelectron microscopy and monoclonal B cell isolation to describe the molecular details of cross-reactive antibodies targeting conserved epitopes on the HA head, including the receptor-binding site and a new site of vulnerability deemed the medial junction. Our findings accentuate the impact of pre-existing influenza exposure on serum antibody responses post-vaccination.

Epitopes in the HA and NA of H5 and H7 avian influenza viruses that are important for antigenic drift

Avian influenza viruses evolve antigenically to evade host immunity. Two influenza A virus surface glycoproteins, the haemagglutinin and neuraminidase, are the major targets of host immunity and undergo antigenic drift in response to host pre-existing humoral and cellular immune responses. Specific sites have been identified as important epitopes in prominent subtypes such as H5 and H7, which are of animal and public health significance due to their panzootic and pandemic potential. The haemagglutinin is the immunodominant immunogen, it has been extensively studied, and the antigenic reactivity is closely monitored to ensure candidate vaccine viruses are protective. More recently, the neuraminidase has received increasing attention for its role as a protective immunogen. The neuraminidase is expressed at a lower abundance than the haemagglutinin on the virus surface but does elicit a robust antibody response. This review aims to compile the current information on haemagglutinin and neuraminidase epitopes and immune escape mutants of H5 and H7 highly pathogenic avian influenza viruses. Understanding the evolution of immune escape mutants and the location of epitopes is critical for identification of vaccine strains and development of broadly reactive vaccines that can be utilized in humans and animals.

Divergent Pathogenesis and Transmission of Highly Pathogenic Avian Influenza A(H5N1) in Swine

Highly pathogenic avian influenza (HPAI) viruses have potential to cross species barriers and cause pandemics. Since 2022, HPAI A(H5N1) belonging to the goose/Guangdong 2.3.4.4b hemagglutinin phylogenetic clade have infected poultry, wild birds, and mammals across North America. Continued circulation in birds and infection of multiple mammalian species with strains possessing adaptation mutations increase the risk for infection and subsequent reassortment with influenza A viruses endemic in swine. We assessed the susceptibility of swine to avian and mammalian HPAI H5N1 clade 2.3.4.4b strains using a pathogenesis and transmission model. All strains replicated in the lung of pigs and caused lesions consistent with influenza A infection. However, viral replication in the nasal cavity and transmission was only observed with mammalian isolates. Mammalian adaptation and reassortment may increase the risk for incursion and transmission of HPAI viruses in feral, backyard, or commercial swine.

A computational approach to design a multiepitope vaccine against H5N1 virus

Since 1997, highly pathogenic avian influenza viruses, such as H5N1, have been recognized as a possible pandemic hazard to men and the poultry business. The rapid rate of mutation of H5N1 viruses makes the whole process of designing vaccines extremely challenging. Here, we used an in silico approach to design a multi-epitope vaccine against H5N1 influenza A virus using hemagglutinin (HA) and neuraminidase (NA) antigens. B-cell epitopes, Cytotoxic T lymphocyte (CTL) and Helper T lymphocyte (HTL) were predicted via IEDB, NetMHC-4 and NetMHCII-2.3 respectively. Two adjuvants consisting of Human β-defensin-3 (HβD-3) along with pan HLA DR-binding epitope (PADRE) have been chosen to induce more immune response. Linkers including KK, AAY, HEYGAEALERAG, GPGPGPG and double EAAAK were utilized to link epitopes and adjuvants. This construct encodes a protein having 350 amino acids and 38.46 kDa molecular weight. Antigenicity of ~ 1, the allergenicity of non-allergen, toxicity of negative and solubility of appropriate were confirmed through Vaxigen, AllerTOP, ToxDL and DeepSoluE, respectively. The 3D structure of H5N1 was refined and validated with a Z-Score of - 0.87 and an overall Ramachandran of 99.7%. Docking analysis showed H5N1 could interact with TLR7 (docking score of - 374.08 and by 4 hydrogen bonds) and TLR8 (docking score of - 414.39 and by 3 hydrogen bonds). Molecular dynamics simulations results showed RMSD and RMSF of 0.25 nm and 0.2 for H5N1-TLR7 as well as RMSD and RMSF of 0.45 nm and 0.4 for H5N1-TLR8 complexes, respectively. Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) confirmed stability and continuity of interaction between H5N1-TLR7 with the total binding energy of - 29.97 kJ/mol and H5N1-TLR8 with the total binding energy of - 23.9 kJ/mol. Investigating immune response simulation predicted evidence of the ability to stimulate T and B cells of the immunity system that shows the merits of this H5N1 vaccine proposed candidate for clinical trials.

MetagenomicKG: a knowledge graph for metagenomic applications

Motivation

The sheer volume and variety of genomic content within microbial communities makes metagenomics a field rich in biomedical knowledge. To traverse these complex communities and their vast unknowns, metagenomic studies often depend on distinct reference databases, such as the Genome Taxonomy Database (GTDB), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Bacterial and Viral Bioinformatics Resource Center (BV-BRC), for various analytical purposes. These databases are crucial for genetic and functional annotation of microbial communities. Nevertheless, the inconsistent nomenclature or identifiers of these databases present challenges for effective integration, representation, and utilization. Knowledge graphs (KGs) offer an appropriate solution by organizing biological entities and their interrelations into a cohesive network. The graph structure not only facilitates the unveiling of hidden patterns but also enriches our biological understanding with deeper insights. Despite KGs having shown potential in various biomedical fields, their application in metagenomics remains underexplored.

Results

We present MetagenomicKG, a novel knowledge graph specifically tailored for metagenomic analysis. MetagenomicKG integrates taxonomic, functional, and pathogenesis-related information from widely used databases, and further links these with established biomedical knowledge graphs to expand biological connections. Through several use cases, we demonstrate its utility in enabling hypothesis generation regarding the relationships between microbes and diseases, generating sample-specific graph embeddings, and providing robust pathogen prediction.

Availability and Implementation

The source code and technical details for constructing the MetagenomicKG and reproducing all analyses are available at Github: https://github.com/KoslickiLab/MetagenomicKG. We also host a Neo4j instance: http://mkg.cse.psu.edu:7474 for accessing and querying this graph.

Targeted genomic sequencing of avian influenza viruses in wetland sediment from wild bird habitats

Diverse influenza A viruses (IAVs) circulate in wild birds, including highly pathogenic strains that infect poultry and humans. Consequently, surveillance of IAVs in wild birds is a cornerstone of agricultural biosecurity and pandemic preparedness. Surveillance is traditionally done by testing wild birds directly, but obtaining these specimens is labor intensive, detection rates can be low, and sampling is often biased toward certain avian species. As a result, local incursions of dangerous IAVs are rarely detected before outbreaks begin. Testing environmental specimens from wild bird habitats has been proposed as an alternative surveillance strategy. These specimens are thought to contain diverse IAVs deposited by a broad range of avian hosts, including species that are not typically sampled by surveillance programs. To enable this surveillance strategy, we developed a targeted genomic sequencing method for characterizing IAVs in these challenging environmental specimens. It combines custom hybridization probes, unique molecular index-based library construction, and purpose-built bioinformatic tools, allowing IAV genomic material to be enriched and analyzed with single-fragment resolution. We demonstrated our method on 90 sediment specimens from wetlands around Vancouver, Canada. We recovered 2,312 IAV genome fragments originating from all eight IAV genome segments. Eleven hemagglutinin subtypes and nine neuraminidase subtypes were detected, including H5, the current global surveillance priority. Our results demonstrate that targeted genomic sequencing of environmental specimens from wild bird habitats could become a valuable complement to avian influenza surveillance programs.IMPORTANCEIn this study, we developed genome sequencing tools for characterizing avian influenza viruses in sediment from wild bird habitats. These tools enable an environment-based approach to avian influenza surveillance. This could improve early detection of dangerous strains in local wild birds, allowing poultry producers to better protect their flocks and prevent human exposures to potential pandemic threats. Furthermore, we purposefully developed these methods to contend with viral genomic material that is diluted, fragmented, incomplete, and derived from multiple strains and hosts. These challenges are common to many environmental specimens, making these methods broadly applicable for genomic pathogen surveillance in diverse contexts.

PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network

Vaccination stands as the most effective and economical strategy for prevention and control of influenza. The primary target of neutralizing antibodies is the surface antigen hemagglutinin (HA). However, ongoing mutations in the HA sequence result in antigenic drift. The success of a vaccine is contingent on its antigenic congruence with circulating strains. Thus, predicting antigenic variants and deducing antigenic clusters of influenza viruses are pivotal for recommendation of vaccine strains. The antigenicity of influenza A viruses is determined by the interplay of amino acids in the HA1 sequence. In this study, we exploit the ability of convolutional neural networks (CNNs) to extract spatial feature representations in the convolutional layers, which can discern interactions between amino acid sites. We introduce PREDAC-CNN, a model designed to track antigenic evolution of seasonal influenza A viruses. Accessible at http://predac-cnn.cloudna.cn, PREDAC-CNN formulates a spatially oriented representation of the HA1 sequence, optimized for the convolutional framework. It effectively probes interactions among amino acid sites in the HA1 sequence. Also, PREDAC-CNN focuses exclusively on physicochemical attributes crucial for the antigenicity of influenza viruses, thereby eliminating unnecessary amino acid embeddings. Together, PREDAC-CNN is adept at capturing interactions of amino acid sites within the HA1 sequence and examining the collective impact of point mutations on antigenic variation. Through 5-fold cross-validation and retrospective testing, PREDAC-CNN has shown superior performance in predicting antigenic variants compared to its counterparts. Additionally, PREDAC-CNN has been instrumental in identifying predominant antigenic clusters for A/H3N2 (1968-2023) and A/H1N1 (1977-2023) viruses, significantly aiding in vaccine strain recommendation.

VarEPS-Influ:an risk evaluation system of occurred and virtual variations of influenza virus genomes

Influenza viruses undergo frequent genomic mutations, leading to potential cross-species transmission, phenotypic changes, and challenges in diagnostic reagents and vaccines. Accurately evaluating and predicting the risk of such variations remain significant challenges. To address this, we developed the VarEPS-Influ database, an influenza virus variations risk evaluation system (VarEPS-Influ). This database employs a 'multi-dimensional evaluation of mutations' strategy, utilizing various tools to assess the physical and chemical properties, primary, secondary, and tertiary structures, receptor affinity, antibody binding capacity, antigen epitopes, and other aspects of the variation's impact. Additionally, we consider space-time distribution, host species distribution, pedigree analysis, and frequency of mutations to provide a comprehensive risk evaluation of mutations and viruses. The VarEPS-Influ database evaluates both observed variations and virtual variations (variations that have not yet occurred), thereby addressing the time-lag issue in risk predictions. Our current one-stop evaluation system for influenza virus genomic variation integrates 1065290 sequences from 224 927 Influenza A, B and C isolates retrieved from public resources. Researchers can freely access the data at https://nmdc.cn/influvar/.

RVdb: a comprehensive resource and analysis platform for rhinovirus research

Rhinovirus (RV), a prominent causative agent of both upper and lower respiratory diseases, ranks among the most prevalent human respiratory viruses. RV infections are associated with various illnesses, including colds, asthma exacerbations, croup and pneumonia, imposing significant and extended societal burdens. Characterized by a high mutation rate and genomic diversity, RV displays a diverse serological landscape, encompassing a total of 174 serotypes identified to date. Understanding RV genetic diversity is crucial for epidemiological surveillance and investigation of respiratory diseases. This study introduces a comprehensive and high-quality RV data resource, designated RVdb (http://rvdb.mgc.ac.cn), covering 26 909 currently identified RV strains, along with RV-related sequences, 3D protein structures and publications. Furthermore, this resource features a suite of web-based utilities optimized for easy browsing and searching, as well as automatic sequence annotation, multiple sequence alignment (MSA), phylogenetic tree construction, RVdb BLAST and a serotyping pipeline. Equipped with a user-friendly interface and integrated online bioinformatics tools, RVdb provides a convenient and powerful platform on which to analyse the genetic characteristics of RVs. Additionally, RVdb also supports the efforts of virologists and epidemiologists to monitor and trace both existing and emerging RV-related infectious conditions in a public health context.

Comparative Genomic Analysis of Bacterial Data in BV-BRC: An Example Exploring Antimicrobial Resistance

As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.bv-brc.org/ . The combined BV-BRC leverages the functionality of the original resources for bacterial and viral research communities with a unified data model, enhanced web-based visualization and analysis tools, and bioinformatics services. Here we demonstrate how antimicrobial resistance data can be analyzed in the new resource.

Antigenic Architecture of the H7N2 Influenza Virus Hemagglutinin Belonging to the North American Lineage

The North American low pathogenic H7N2 avian influenza A viruses, which lack the 220-loop in the hemagglutinin (HA), possess dual receptor specificity for avian- and human-like receptors. The purpose of this work was to determine which amino acid substitutions in HA affect viral antigenic and phenotypic properties that may be important for virus evolution. By obtaining escape mutants under the immune pressure of treatment with monoclonal antibodies, antigenically important amino acids were determined to be at positions 125, 135, 157, 160, 198, 200, and 275 (H3 numbering). These positions, except 125 and 275, surround the receptor binding site. The substitutions A135S and A135T led to the appearance of an N-glycosylation site at 133N, which reduced affinity for the avian-like receptor analog and weakened binding with tested monoclonal antibodies. Additionally, the A135S substitution is associated with the adaptation of avian viruses to mammals (cat, human, or mouse). The mutation A160V decreased virulence in mice and increased affinity for the human-type receptor analog. Conversely, substitution G198E, in combination with 157N or 160E, displayed reduced affinity for the human-type receptor analog.

Influenza-A mediated pre-existing immunity levels to SARS-CoV-2 could predict early COVID-19 outbreak dynamics

Susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is highly variable and could be mediated by a cross-protective pre-immunity. We identified 14 cross-reactive peptides between SARS-CoV-2 and influenza A H1N1, H3N2, and human herpesvirus (HHV)-6A/B with potential relevance. The H1N1 peptide NGVEGF was identical to a peptide in the most critical receptor binding motif in SARS-CoV-2 spike protein that interacts with the angiotensin converting enzyme 2 receptor. About 62%-73% of COVID-19-negative blood donors in Stockholm had antibodies to this peptide in the early pre-vaccination phase of the pandemic. Seasonal flu vaccination enhanced neutralizing capacity to SARS-CoV-2 and T cell immunity to this peptide. Mathematical modeling taking the estimated pre-immunity levels to flu into account could fully predict pre-Omicron SARS-CoV-2 outbreaks in Stockholm and India. This cross-immunity provides mechanistic explanations to the epidemiological observation that influenza vaccination protected people against early SARS-CoV-2 infections and implies that flu-mediated cross-protective immunity significantly dampened the first SARS-CoV-2 outbreaks.

Genetic diversity and characterization of rhinoviruses from Chinese clinical samples with a global perspective

IMPORTANCE

Based on clinical samples collected in China, we detected and reported 22 types for the first time in China, as well as three types for the first time in Asia, and reported their genetic characteristics and diversity. We identified a novel type of Rhinovirus (RV), A110, highlighting its unique genetic features. We annotated the genomic structure and serotype of all the existing RV sequences in the database, and four novel RV types were identified and their genetic diversity reported. Combined with the sequence annotation, we constructed a complete VP1 data set of RV and conducted the first large-scale evolutionary dynamics analysis of RV. Based on a high-quality data set, we conducted a comprehensive analysis of the guanine-cytosine (GC) content variations among serotypes of RVs. This study provides crucial theoretical support and valuable data for understanding RV's genetic diversity and developing antiviral strategies.

Infection and tissue distribution of highly pathogenic avian influenza A type H5N1 (clade 2.3.4.4b) in red fox kits (Vulpes vulpes)

Avian influenza H5N1 is a highly pathogenic virus that primarily affects birds. However, it can also infect other animal species, including mammals. We report the infection of nine juvenile red foxes (Vulpes vulpes) with Highly Pathogenic Avian Influenza A type H5N1 (Clade 2.3.4.4b) in the spring of 2022 in the central, western, and northern regions of New York, USA. The foxes displayed neurologic signs, and examination of brain and lung tissue revealed lesions, with brain lesions ranging from moderate to severe meningoencephalitis. Analysis of tissue tropism using RT-PCR methods showed a comparatively lower Ct value in the brain, which was confirmed by in situ hybridization targeting Influenza A RNA. The viral RNA labelling was highly clustered and overlapped the brain lesions, observed in neurons, and grey matter. Whole viral genome sequences obtained from the affected foxes were subjected to phylogenetic and mutation analysis to determine influenza A clade, host specificity, and potential occurrence of viral reassortment. Infections in red foxes likely occurred due to preying on infected wild birds and are unlikely due to transmission between foxes or other mammals.

Global distribution, receptor binding, and cross-species transmission of H6 influenza viruses: risks and implications for humans

The H6 subtype of avian influenza virus (AIV) is a pervasive subtype that is ubiquitously found in both wild bird and poultry populations across the globe. Recent investigations have unveiled its capacity to infect mammals, thereby expanding its host range beyond that of other subtypes and potentially facilitating its global transmission. This heightened breadth also endows H6 AIVs with the potential to serve as a genetic reservoir for the emergence of highly pathogenic avian influenza strains through genetic reassortment and adaptive mutations. Furthermore, alterations in key amino acid loci within the H6 AIV genome foster the evolution of viral infection mechanisms, which may enable the virus to surmount interspecies barriers and infect mammals, including humans, thus posing a potential threat to human well-being. In this review, we summarize the origins, dissemination patterns, geographical distribution, cross-species transmission dynamics, and genetic attributes of H6 influenza viruses. This study holds implications for the timely detection and surveillance of H6 AIVs.

PARNAS: Objectively Selecting the Most Representative Taxa on a Phylogeny

The use of next-generation sequencing technology has enabled phylogenetic studies with hundreds of thousands of taxa. Such large-scale phylogenies have become a critical component in genomic epidemiology in pathogens such as SARS-CoV-2 and influenza A virus. However, detailed phenotypic characterization of pathogens or generating a computationally tractable dataset for detailed phylogenetic analyses requires objective subsampling of taxa. To address this need, we propose parnas, an objective and flexible algorithm to sample and select taxa that best represent observed diversity by solving a generalized k-medoids problem on a phylogenetic tree. parnas solves this problem efficiently and exactly by novel optimizations and adapting algorithms from operations research. For more nuanced selections, taxa can be weighted with metadata or genetic sequence parameters, and the pool of potential representatives can be user-constrained. Motivated by influenza A virus genomic surveillance and vaccine design, parnas can be applied to identify representative taxa that optimally cover the diversity in a phylogeny within a specified distance radius. We demonstrated that parnas is more efficient and flexible than existing approaches. To demonstrate its utility, we applied parnas to 1) quantify SARS-CoV-2 genetic diversity over time, 2) select representative influenza A virus in swine genes derived from over 5 years of genomic surveillance data, and 3) identify gaps in H3N2 human influenza A virus vaccine coverage. We suggest that our method, through the objective selection of representatives in a phylogeny, provides criteria for quantifying genetic diversity that has application in the the rational design of multivalent vaccines and genomic epidemiology. PARNAS is available at https://github.com/flu-crew/parnas.

Antigenic mapping of the hemagglutinin of the H9 subtype influenza A viruses using sera from Japanese quail (Coturnix c. japonica)

IMPORTANCE

Determining the relevant amino acids involved in antigenic drift on the surface protein hemagglutinin (HA) is critical to understand influenza virus evolution and efficient assessment of vaccine strains relative to current circulating strains. We used antigenic cartography to generate an antigenic map of the H9 hemagglutinin (HA) using sera produced in one of the most relevant minor poultry species, Japanese quail. Key antigenic positions were identified and tested to confirm their impact on the antigenic profile. This work provides a better understanding of the antigenic diversity of the H9 HA as it relates to reactivity to quail sera and will facilitate a rational approach for selecting more efficacious vaccines against poultry-origin H9 influenza viruses in minor poultry species.

Characterization of A/H7 influenza virus global antigenic diversity and key determinants in the hemagglutinin globular head mediating A/H7N9 antigenic evolution

IMPORTANCE

A/H7 avian influenza viruses cause outbreaks in poultry globally, resulting in outbreaks with significant socio-economical impact and zoonotic risks. Occasionally, poultry vaccination programs have been implemented to reduce the burden of these viruses, which might result in an increased immune pressure accelerating antigenic evolution. In fact, evidence for antigenic diversification of A/H7 influenza viruses exists, posing challenges to pandemic preparedness and the design of vaccination strategies efficacious against drifted variants. Here, we performed a comprehensive analysis of the global antigenic diversity of A/H7 influenza viruses and identified the main substitutions in the hemagglutinin responsible for antigenic evolution in A/H7N9 viruses isolated between 2013 and 2019. The A/H7 antigenic map and knowledge of the molecular determinants of their antigenic evolution add value to A/H7 influenza virus surveillance programs, the design of vaccines and vaccination strategies, and pandemic preparedness.

Multi-omics data integration reveals the complexity and diversity of host factors associated with influenza virus infection

Influenza viruses pose a significant and ongoing threat to human health. Many host factors have been identified to be associated with influenza virus infection. However, there is currently a lack of an integrated resource for these host factors. This study integrated human genes and proteins associated with influenza virus infections for 14 subtypes of influenza A viruses, as well as influenza B and C viruses, and built a database named H2Flu to store and organize these genes or proteins. The database includes 28,639 differentially expressed genes (DEGs), 1,850 differentially expressed proteins, and 442 proteins with differential posttranslational modifications after influenza virus infection, as well as 3,040 human proteins that interact with influenza virus proteins and 57 human susceptibility genes. Further analysis showed that the dynamic response of human cells to virus infection, cell type and strain specificity contribute significantly to the diversity of DEGs. Additionally, large heterogeneity was also observed in protein-protein interactions between humans and different types or subtypes of influenza viruses. Overall, the study deepens our understanding of the diversity and complexity of interactions between influenza viruses and humans, and provides a valuable resource for further studies on such interactions.

Does Vaccine-Induced Maternally-Derived Immunity Protect Swine Offspring against Influenza a Viruses? A Systematic Review and Meta-Analysis of Challenge Trials from 1990 to May 2021

It is unclear if piglets benefit from vaccination of sows against influenza. For the first time, methods of evidence-based medicine were applied to answer the question: "Does vaccine-induced maternally-derived immunity (MDI) protect swine offspring against influenza A viruses?". Challenge trials were reviewed that were published from 1990 to April 2021 and measured at least one of six outcomes in MDI-positive versus MDI-negative offspring (hemagglutination inhibition (HI) titers, virus titers, time to begin and time to stop shedding, risk of infection, average daily gain (ADG), and coughing) (n = 15). Screening and extraction of study characteristics was conducted in duplicate by two reviewers, with data extraction and assessment for risk of bias performed by one. Homology was defined by the antigenic match of vaccine and challenge virus hemagglutinin epitopes. Results: Homologous, but not heterologous MDI, reduced virus titers in piglets. There was no difference, calculated as relative risks (RR), in infection incidence risk over the entire study period; however, infection hazard (instantaneous risk) was decreased in pigs with MDI (log HR = -0.64, 95% CI: -1.13, -0.15). Overall, pigs with MDI took about a ½ day longer to begin shedding virus post-challenge (MD = 0.51, 95% CI: 0.03, 0.99) but the hazard of infected pigs ceasing to shed was not different (log HR = 0.32, 95% CI: -0.29, 0.93). HI titers were synthesized qualitatively and although data on ADG and coughing was extracted, details were insufficient for conducting meta-analyses. Conclusion: Homology of vaccine strains with challenge viruses is an important consideration when assessing vaccine effectiveness. Herd viral dynamics are complex and may include concurrent or sequential exposures in the field. The practical significance of reduced weaned pig virus titers is, therefore, not known and evidence from challenge trials is insufficient to make inferences on the effects of MDI on incidence risk, time to begin or to cease shedding virus, coughing, and ADG. The applicability of evidence from single-strain challenge trials to field practices is limited. Despite the synthesis of six outcomes, challenge trial evidence does not support or refute vaccination of sows against influenza to protect piglets. Additional research is needed; controlled trials with multi-strain concurrent or sequential heterologous challenges have not been conducted, and sequential homologous exposure trials were rare. Consensus is also warranted on (1) the selection of core outcomes, (2) the sizing of trial populations to be reflective of field populations, (3) the reporting of antigenic characterization of vaccines, challenge viruses, and sow exposure history, and (4) on the collection of non-aggregated individual pig data.

Efficacy of oseltamivir treatment in influenza virus-infected obese mice

Obesity has been epidemiologically and empirically linked with more severe diseases upon influenza infection. To ameliorate severe disease, treatment with antivirals, such as the neuraminidase inhibitor oseltamivir, is suggested to begin within days of infection especially in high-risk hosts. However, this treatment can be poorly effective and may generate resistance variants within the treated host. Here, we hypothesized that obesity would reduce oseltamivir treatment effectiveness in the genetically obese mouse model. We demonstrated that oseltamivir treatment does not improve viral clearance in obese mice. While no traditional variants associated with oseltamivir resistance emerged, we did note that drug treatment failed to quench the viral population and did lead to phenotypic drug resistance in vitro. Together, these studies suggest that the unique pathogenesis and immune responses in obese mice could have implications for pharmaceutical interventions and the within-host dynamics of the influenza virus population. IMPORTANCE Influenza virus infections, while typically resolving within days to weeks, can turn critical, especially in high-risk populations. Prompt antiviral administration is crucial to mitigating these severe sequalae, yet concerns remain if antiviral treatment is effective in hosts with obesity. Here, we show that oseltamivir does not improve viral clearance in genetically obese or type I interferon receptor-deficient mice. This suggests a blunted immune response may impair oseltamivir efficacy and render a host more susceptible to severe disease. This study furthers our understanding of oseltamivir treatment dynamics both systemically and in the lungs of obese mice, as well as the consequences of oseltamivir treatment for the within-host emergence of drug-resistant variants.

Immune memory shapes human polyclonal antibody responses to H2N2 vaccination

Influenza A virus subtype H2N2, which caused the 1957 influenza pandemic, remains a global threat. A recent phase I clinical trial investigating a ferritin nanoparticle displaying H2 hemagglutinin in H2-naïve and H2-exposed adults. Therefore, we could perform comprehensive structural and biochemical characterization of immune memory on the breadth and diversity of the polyclonal serum antibody response elicited after H2 vaccination. We temporally map the epitopes targeted by serum antibodies after first and second vaccinations and show previous H2 exposure results in higher responses to the variable head domain of hemagglutinin while initial responses in H2-naïve participants are dominated by antibodies targeting conserved epitopes. We use cryo-EM and monoclonal B cell isolation to describe the molecular details of cross-reactive antibodies targeting conserved epitopes on the hemagglutinin head including the receptor binding site and a new site of vulnerability deemed the medial junction. Our findings accentuate the impact of pre-existing influenza exposure on serum antibody responses.

Human-to-swine introductions and onward transmission of 2009 H1N1 pandemic influenza viruses in Brazil

Introduction

Once established in the human population, the 2009 H1N1 pandemic virus (H1N1pdm09) was repeatedly introduced into swine populations globally with subsequent onward transmission among pigs.

Methods

To identify and characterize human-to-swine H1N1pdm09 introductions in Brazil, we conducted a large-scale phylogenetic analysis of 4,141 H1pdm09 hemagglutinin (HA) and 3,227 N1pdm09 neuraminidase (NA) gene sequences isolated globally from humans and swine between 2009 and 2022.

Results

Phylodynamic analysis revealed that during the period between 2009 and 2011, there was a rapid transmission of the H1N1pdm09 virus from humans to swine in Brazil. Multiple introductions of the virus were observed, but most of them resulted in self-limited infections in swine, with limited onward transmission. Only a few sustained transmission clusters were identified during this period. After 2012, there was a reduction in the number of human-to-swine H1N1pdm09 transmissions in Brazil.

Discussion

The virus underwent continuous antigenic drift, and a balance was established between swine-to-swine transmission and extinction, with minimal sustained onward transmission from humans to swine. These results emphasize the dynamic interplay between human-to-swine transmission, antigenic drift, and the establishment of swine-to-swine transmission in shaping the evolution and persistence of H1N1pdm09 in swine populations.

Misclassified: identification of zoonotic transition biomarker candidates for influenza A viruses using deep neural network

Introduction: Zoonotic transition of Influenza A viruses is the cause of epidemics with high rates of morbidity and mortality. Predicting which viral strains are likely to transition from their genetic sequence could help in the prevention and response against these zoonotic strains. We hypothesized that features predictive of viral hosts could be leveraged to identify biomarkers of zoonotic viral transition. Methods: We trained deep learning models to predict viral hosts based on the virus mRNA or protein sequences. Our multi-host dataset contained 848,630 unique nucleotide sequences obtained from the NCBI Influenza Virus and Influenza Research Databases. Each sequence, representing one gene from one viral strain, was classified into one of the three host categories: Avian, Human, and Swine. Trained models were analyzed using various neural network interpretation methods to identify interesting candidates for zoonotic transition biomarkers. Results: Using mRNA sequences as input led to higher prediction accuracies than amino acids, suggesting that the codon sequence contains information relevant to viral hosts that is lost during protein translation. UMAP visualization of the latent space of our classifiers showed that viral sequences clustered according to their host of origin. Interestingly, sequences from pandemic zoonotic viral strains localized at the margins between hosts, while zoonotic sequences incapable of Human-to-Human transmission localized with non-zoonotic viruses from the same host. In addition, host prediction for pandemic zoonotic sequences had low prediction accuracy, which was not the case for the other zoonotic strains. This supports our hypothesis that ambiguously predicted viral sequences bear features associated with cross-species infectivity. Finally, we compared misclassified sequences to well-classified ones to extract interesting candidates for zoonotic transition biomarkers. While features varied significantly between pairs of species and viral genes, several codons were conserved in Swine-to-Human and Avian-to-Human misclassified sequences, and in particular in the NA, HA, and NP genes, suggesting their importance for zoonosis in Humans. Discussion: Analysis of viral sequences using neural network interpretation approaches revealed important genetic differences between zoonotic viruses with pandemic potential, compared to non-zoonotic viral strains or zoonotic viruses incapable of Human-to-Human transmission.

Cut site preference allows influenza A virus PA-X to discriminate between host and viral mRNAs

Many viruses block host gene expression to take over the infected cell. This process, termed host shutoff, is thought to promote viral replication by preventing antiviral responses and redirecting cellular resources to viral processes. Several viruses from divergent families accomplish host shutoff through RNA degradation by endoribonucleases. However, viruses also need to ensure expression of their own genes. The influenza A virus endoribonuclease PA-X solves this problem by sparing viral mRNAs and some host RNAs necessary for viral replication. To understand how PA-X distinguishes between RNAs, we characterized PA-X cut sites transcriptome-wide using 5' rapid amplification of complementary DNA ends coupled to high-throughput sequencing. This analysis, along with RNA structure predictions and validation experiments using reporters, shows that PA-Xs from multiple influenza strains preferentially cleave RNAs at GCUG tetramers in hairpin loops. Importantly, GCUG tetramers are enriched in the human but not the influenza transcriptome. Moreover, optimal PA-X cut sites inserted in the influenza A virus genome are quickly selected against during viral replication in cells. This finding suggests that PA-X evolved these cleavage characteristics to preferentially target host over viral mRNAs in a manner reminiscent of cellular self versus non-self discrimination.

Reverse-zoonoses of 2009 H1N1 pandemic influenza A viruses and evolution in United States swine results in viruses with zoonotic potential

The 2009 H1N1 pandemic (pdm09) lineage of influenza A virus (IAV) crosses interspecies barriers with frequent human-to-swine spillovers each year. These spillovers reassort and drift within swine populations, leading to genetically and antigenically novel IAV that represent a zoonotic threat. We quantified interspecies transmission of the pdm09 lineage, persistence in swine, and identified how evolution in swine impacted zoonotic risk. Human and swine pdm09 case counts between 2010 and 2020 were correlated and human pdm09 burden and circulation directly impacted the detection of pdm09 in pigs. However, there was a relative absence of pdm09 circulation in humans during the 2020-21 season that was not reflected in swine. During the 2020-21 season, most swine pdm09 detections originated from human-to-swine spillovers from the 2018-19 and 2019-20 seasons that persisted in swine. We identified contemporary swine pdm09 representatives of each persistent spillover and quantified cross-reactivity between human seasonal H1 vaccine strains and the swine strains using a panel of monovalent ferret antisera in hemagglutination inhibition (HI) assays. The swine pdm09s had variable antigenic reactivity to vaccine antisera, but each swine pdm09 clade exhibited significant reduction in cross-reactivity to one or more of the human seasonal vaccine strains. Further supporting zoonotic risk, we showed phylogenetic evidence for 17 swine-to-human transmission events of pdm09 from 2010 to 2021, 11 of which were not previously classified as variants, with each of the zoonotic cases associated with persistent circulation of pdm09 in pigs. These data demonstrate that reverse-zoonoses and evolution of pdm09 in swine results in viruses that are capable of zoonotic transmission and represent a potential pandemic threat.

Cross-species transmission and PB2 mammalian adaptations of highly pathogenic avian influenza A/H5N1 viruses in Chile

H5N1 highly pathogenic avian influenza viruses (HPAIV) emerged in wild birds in Chile in December 2022 and spilled over into poultry, marine mammals, and one human. Between December 9, 2022 - March 14, 2023, a coordinated government/academic response detected HPAIV by real-time RT-PCR in 8.5% (412/4735) of samples from 23 avian and 3 mammal orders. Whole-genome sequences obtained from 77 birds and 8 marine mammals revealed that all Chilean H5N1 viruses belong to lineage 2.3.4.4b and cluster monophyletically with viruses from Peru, indicating a single introduction from North America into Peru/Chile. Mammalian adaptations were identified in the PB2 segment: D701N in two sea lions, one human, and one shorebird, and Q591K in the human and one sea lion. Minor variant analysis revealed that D701N was present in 52.9 - 70.9% of sequence reads, indicating the presence of both genotypes within hosts. Further surveillance of spillover events is warranted to assess the emergence and potential onward transmission of mammalian adapted H5N1 HPAIV in South America.

Influenza C and D Viruses Demonstrated a Differential Respiratory Tissue Tropism in a Comparative Pathogenesis Study in Guinea Pigs

Influenza C virus (ICV) is increasingly associated with community-acquired pneumonia (CAP) in children and its disease severity is worse than the influenza B virus, but similar to influenza A virus associated CAP. Despite the ubiquitous infection landscape of ICV in humans, little is known about its replication and pathobiology in animals. The goal of this study was to understand the replication kinetics, tissue tropism, and pathogenesis of human ICV (huICV) in comparison to the swine influenza D virus (swIDV) in guinea pigs. Intranasal inoculation of both viruses did not cause clinical signs, however, the infected animals shed virus in nasal washes. The huICV replicated in the nasal turbinates, soft palate, and trachea but not in the lungs while swIDV replicated in all four tissues. A comparative analysis of tropism and pathogenesis of these two related seven-segmented influenza viruses revealed that swIDV-infected animals exhibited broad tissue tropism with an increased rate of shedding on 3, 5, and 7 dpi and high viral loads in the lungs compared to huICV. Seroconversion occurred late in the huICV group at 14 dpi, while swIDV-infected animals seroconverted at 7 dpi. Guinea pigs infected with huICV exhibited mild to moderate inflammatory changes in the epithelium of the soft palate and trachea, along with mucosal damage and multifocal alveolitis in the lungs. In summary, the replication kinetics and pathobiological characteristics of ICV in guinea pigs agree with the clinical manifestation of ICV infection in humans, and hence guinea pigs could be used to study these distantly related influenza viruses. IMPORTANCE Similar to influenza A and B, ICV infections are seen associated with bacterial and viral co-infections which complicates the assessment of its real clinical significance. Further, the antivirals against influenza A and B viruses are ineffective against ICV which mandates the need to study the pathobiological aspects of this virus. Here we demonstrated that the respiratory tract of guinea pigs possesses specific viral receptors for ICV. We also compared the replication kinetics and pathogenesis of huICV and swIDV, as these viruses share 50% sequence identity. The tissue tropism and pathology associated with huICV in guinea pigs are analogous to the mild respiratory disease caused by ICV in humans, thereby demonstrating the suitability of guinea pigs to study ICV. Our comparative analysis revealed that huICV and swIDV replicated differentially in the guinea pigs suggesting that the type-specific genetic differences can result in the disparity of the viral shedding and tissue tropism.

Culture-Independent Workflow for Nanopore MinION-Based Sequencing of Influenza A Virus

Whole-genome sequencing (WGS) of influenza A virus (IAV) is crucial for identifying diverse subtypes and newly evolved variants and for selecting vaccine strains. In developing countries, where facilities are often inadequate, WGS is challenging to perform using conventional next-generation sequencers. In this study, we established a culture-independent, high-throughput native barcode amplicon sequencing workflow that can sequence all influenza subtypes directly from a clinical specimen. All segments of IAV in 19 clinical specimens, irrespective of their subtypes, were amplified simultaneously using a two-step reverse transcriptase PCR (RT-PCR) system. First, the library was prepared using the ligation sequencing kit, barcoded individually using the native barcodes, and sequenced on the MinION MK 1C platform with real-time base-calling. Then, subsequent data analyses were performed with the appropriate tools. WGS of 19 IAV-positive clinical samples was carried out successfully with 100% coverage and 3,975-fold mean coverage for all segments. This easy-to-install and low-cost capacity-building protocol took only 24 h complete from extracting RNA to obtaining finished sequences. Overall, we developed a high-throughput portable sequencing workflow ideal for resource-limited clinical settings, aiding in real-time surveillance, outbreak investigation, and the detection of emerging viruses and genetic reassortment events. However, further evaluation is required to compare its accuracy with other high-throughput sequencing technologies to validate the widespread application of these findings, including WGS from environmental samples. IMPORTANCE The Nanopore MinION-based influenza sequencing approach we are proposing makes it possible to sequence the influenza A virus, irrespective of its diverse serotypes, directly from clinical and environmental swab samples, so that we are not limited to virus culture. This third-generation, portable, multiplexing, and real-time sequencing strategy is highly convenient for local sequencing, particularly in low- and middle-income countries like Bangladesh. Furthermore, the cost-efficient sequencing method could provide new opportunities to respond to the early phase of an influenza pandemic and enable the timely detection of the emerging subtypes in clinical samples. Here, we meticulously described the entire process that might help the researcher who will follow this methodology in the future. Our findings suggest that this proposed method is ideal for clinical and academic settings and will aid in real-time surveillance and in the detection of potential outbreak agents and newly evolved viruses.

Protein sequence features of H1N1 swine influenza A viruses detected on commercial swine farms in Serbia

Introduction

Swine influenza A viruses (swIAVs) are characterised by high mutation rates and zoonotic and pandemic potential. In order to draw conclusions about virulence in swine and pathogenicity to humans, we examined the existence of molecular markers and accessory proteins, cross-reactivity with vaccine strains, and resistance to antiviral drugs in five strains of H1N1 swIAVs.

Material and Methods

Amino acid (AA) sequences of five previously genetically characterised swIAVs were analysed in MEGA 7.0 software and the Influenza Research Database.

Results

Amino acid analysis revealed three virus strains with 590S/591R polymorphism and T271A substitution within basic polymerase 2 (PB2) AA chains, which cause enhanced virus replication in mammalian cells. The other two strains possessed D701N and R251K substitutions within PB2 and synthesised PB1-F2 protein, which are the factors of increased polymerase activity and virulence in swine. All strains synthesised PB1-N40, PA-N155, PA-N182, and PA-X proteins responsible for enhanced replication in mammalian cells and downregulation of the immune response of the host. Mutations detected within haemagglutinin antigenic sites imply the antigenic drift of the five analysed viruses in relation to the vaccine strains. All viruses show susceptibility to neuraminidase inhibitors and baloxavir marboxil, which is important in situations of incidental human infections.

Conclusion

The detection of virulence markers and accessory proteins in the analysed viruses suggests their higher propensity for replication in mammalian cells, increased virulence, and potential for transmission to humans, and implies compromised efficacy of influenza vaccines.

Ensemble learning-based early detection of influenza disease

Across the world, the seasonal disease influenza is a respiratory illness that impacts all age groups in many ways. Its symptoms are fever, chills, aches, pains, headaches, fatigue, cough, and weakness. Seasonal influenza can cause mild to severe illness and lead to death at times. The task of early detection of influenza is an important research area these days. Various studies show that machine learning techniques have attracted many researchers' attention to the early detection of influenza disease. In this paper, early detection of Influenza disease among all age groups is done using various machine learning techniques. Influenza Research Database and the Human Surveillance Records data sets are used. Data analysis is undertaken, and ensemble-based stacked algorithms are implemented on the whole data set. The performance of different models has been evaluated using different performance metrics. Overall, the study proposes efficient machine learning models that can be implemented to provide a cheaper and quicker diagnostic tool for detecting influenza.

Cell-intrinsic genomic reassortment of pandemic H1N1 2009 and Eurasian avian-like swine influenza viruses results in potentially zoonotic variants

Influenza A viruses (IAV) cause annual epidemics and occasional pandemics in humans. The most recent pandemic outbreak occurred in 2009 with H1N1pdm09. This virus, which most likely reassorted in swine before its transmission to humans, was reintroduced into the swine population and continues circulating ever since. In order to assess its potential to cause reassortants on a cellular level, human origin H1N1pdm09 and a recent Eurasian avian-like H1N1 swine IAV were (co-)passaged in the newly generated swine lung cell line C22. Co-infection with both viruses gave rise to numerous reassortants that additionally carry different mutations which can partially be found in nature as well. Reassortment most frequently affected the PB1, PA and NA segments with the swine IAV as recipient. These reassortants reached higher titers in swine lung cells and were able to replicate in genuine human lung tissue explants ex vivo, suggesting a possible zoonotic potential. Interestingly, reassortment and mutations in the viral ribonucleoprotein complex influence the viral polymerase activity in a cell type and species-specific manner. In summary, we demonstrate reassortment promiscuity of these viruses in a novel swine lung cell model and indicate a possible zoonotic potential of the reassortants.

Influenza A viruses in gulls in landfills and freshwater habitats in Minnesota, United States

Introduction: The unpredictable evolution of avian influenza viruses (AIVs) presents an ongoing threat to agricultural production and public and wildlife health. Severe outbreaks of highly pathogenic H5N1 viruses in US poultry and wild birds since 2022 highlight the urgent need to understand the changing ecology of AIV. Surveillance of gulls in marine coastal environments has intensified in recent years to learn how their long-range pelagic movements potentially facilitate inter-hemispheric AIV movements. In contrast, little is known about inland gulls and their role in AIV spillover, maintenance, and long-range dissemination. Methods: To address this gap, we conducted active AIV surveillance in ring-billed gulls (Larus delawarensis) and Franklin's gulls (Leucophaeus pipixcan) in Minnesota's natural freshwater lakes during the summer breeding season and in landfills during fall migration (1,686 samples). Results: Whole-genome AIV sequences obtained from 40 individuals revealed three-lineage reassortants with a mix of genome segments from the avian Americas lineage, avian Eurasian lineage, and a global "Gull" lineage that diverged more than 50 years ago from the rest of the AIV global gene pool. No poultry viruses contained gull-adapted H13, NP, or NS genes, pointing to limited spillover. Geolocators traced gull migration routes across multiple North American flyways, explaining how inland gulls imported diverse AIV lineages from distant locations. Migration patterns were highly varied and deviated far from assumed "textbook" routes. Discussion: Viruses circulating in Minnesota gulls during the summer breeding season in freshwater environments reappeared in autumn landfills, evidence of AIV persistence in gulls between seasons and transmission between habitats. Going forward, wider adoption of technological advances in animal tracking devices and genetic sequencing is needed to expand AIV surveillance in understudied hosts and habitats.

Phosphorylation of the PA subunit of influenza polymerase at Y393 prevents binding of the 5'-termini of RNA and polymerase function

The influenza A virus (IAV) polymerase is a multifunctional machine that can adopt alternative configurations to perform transcription and replication of the viral RNA genome in a temporally ordered manner. Although the structure of polymerase is well understood, our knowledge of its regulation by phosphorylation is still incomplete. The heterotrimeric polymerase can be regulated by posttranslational modifications, but the endogenously occurring phosphorylations at the PA and PB2 subunits of the IAV polymerase have not been studied. Mutation of phosphosites in PB2 and PA subunits revealed that PA mutants resembling constitutive phosphorylation have a partial (S395) or complete (Y393) defect in the ability to synthesize mRNA and cRNA. As PA phosphorylation at Y393 prevents binding of the 5' promoter of the genomic RNA, recombinant viruses harboring such a mutation could not be rescued. These data show the functional relevance of PA phosphorylations to control the activity of viral polymerase during the influenza infectious cycle.

Structural insights into the broad protection against H1 influenza viruses by a computationally optimized hemagglutinin vaccine

Influenza virus poses an ongoing human health threat with pandemic potential. Due to mutations in circulating strains, formulating effective vaccines remains a challenge. The use of computationally optimized broadly reactive antigen (COBRA) hemagglutinin (HA) proteins is a promising vaccine strategy to protect against a wide range of current and future influenza viruses. Though effective in preclinical studies, the mechanistic basis driving the broad reactivity of COBRA proteins remains to be elucidated. Here, we report the crystal structure of the COBRA HA termed P1 and identify antigenic and glycosylation properties that contribute to its immunogenicity. We further report the cryo-EM structure of the P1-elicited broadly neutralizing antibody 1F8 bound to COBRA P1, revealing 1F8 to recognize an atypical receptor binding site epitope via an unexpected mode of binding.

Predictive analysis for pathogenicity classification of H5Nx avian influenza strains using machine learning techniques

Over the past decades, avian influenza (AI) outbreaks have been reported across different parts of the globe, resulting in large-scale economic and livestock loss and, in some cases raising concerns about their zoonotic potential. The virulence and pathogenicity of H5Nx (e.g., H5N1, H5N2) AI strains for poultry could be inferred through various approaches, and it has been frequently performed by detecting certain pathogenicity markers in their haemagglutinin (HA) gene. The utilization of predictive modeling methods represents a possible approach to exploring this genotypic-phenotypic relationship for assisting experts in determining the pathogenicity of circulating AI viruses. Therefore, the main objective of this study was to evaluate the predictive performance of different machine learning (ML) techniques for in-silico prediction of pathogenicity of H5Nx viruses in poultry, using complete genetic sequences of the HA gene. We annotated 2137 H5Nx HA gene sequences based on the presence of the polybasic HA cleavage site (HACS) with 46.33% and 53.67% of sequences previously identified as highly pathogenic (HP) and low pathogenic (LP), respectively. We compared the performance of different ML classifiers (e.g., logistic regression (LR) with the lasso and ridge regularization, random forest (RF), K-nearest neighbor (KNN), Naïve Bayes (NB), support vector machine (SVM), and convolutional neural network (CNN)) for pathogenicity classification of raw H5Nx nucleotide and protein sequences using a 10-fold cross-validation technique. We found that different ML techniques can be successfully used for the pathogenicity classification of H5 sequences with ∼99% classification accuracy. Our results indicate that for pathogenicity classification of (1) aligned deoxyribonucleic acid (DNA) and protein sequences, with NB classifier had the lowest accuracies of 98.41% (+/-0.89) and 98.31% (+/-1.06), respectively; (2) aligned DNA and protein sequences, with LR (L1/L2), KNN, SVM (radial basis function (RBF)) and CNN classifiers had the highest accuracies of 99.20% (+/-0.54) and 99.20% (+/-0.38), respectively; (3) unaligned DNA and protein sequences, with CNN's achieved accuracies of 98.54% (+/-0.68) and 99.20% (+/-0.50), respectively. ML methods show potential for regular classification of H5Nx virus pathogenicity for poultry species, particularly when sequences containing regular markers were frequently present in the training dataset.

Parallel recovery of chromatin accessibility and gene expression dynamics from frozen human regulatory T cells

Epigenetic features such as DNA accessibility dictate transcriptional regulation in a cell type- and cell state- specific manner, and mapping this in health vs. disease in clinically relevant material is opening the door to new mechanistic insights and new targets for therapy. Assay for Transposase Accessible Chromatin Sequencing (ATAC-seq) allows chromatin accessibility profiling from low cell input, making it tractable on rare cell populations, such as regulatory T (Treg) cells. However, little is known about the compatibility of the assay with cryopreserved rare cell populations. Here we demonstrate the robustness of an ATAC-seq protocol comparing primary Treg cells recovered from fresh or cryopreserved PBMC samples, in the steady state and in response to stimulation. We extend this method to explore the feasibility of conducting simultaneous quantitation of chromatin accessibility and transcriptome from a single aliquot of 50,000 cryopreserved Treg cells. Profiling of chromatin accessibility and gene expression in parallel within the same pool of cells controls for cellular heterogeneity and is particularly beneficial when constrained by limited input material. Overall, we observed a high correlation of accessibility patterns and transcription factor dynamics between fresh and cryopreserved samples. Furthermore, highly similar transcriptomic profiles were obtained from whole cells and from the supernatants recovered from ATAC-seq reactions. We highlight the feasibility of applying these techniques to profile the epigenomic landscape of cells recovered from cryopreservation biorepositories.

MSLP: mRNA subcellular localization predictor based on machine learning techniques

BACKGROUND

Subcellular localization of messenger RNA (mRNAs) plays a pivotal role in the regulation of gene expression, cell migration as well as in cellular adaptation. Experiment techniques for pinpointing the subcellular localization of mRNAs are laborious, time-consuming and expensive. Therefore, in silico approaches for this purpose are attaining great attention in the RNA community.

METHODS

In this article, we propose MSLP, a machine learning-based method to predict the subcellular localization of mRNA. We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.

RESULTS

Considering the combination of the above-mentioned features, ennsemble-based models achieved state-of-the-art results in mRNA subcellular localization prediction tasks for multiple benchmark datasets. We evaluated the performance of our method  in ten subcellular locations, covering cytoplasm, nucleus, endoplasmic reticulum (ER), extracellular region (ExR), mitochondria, cytosol, pseudopodium, posterior, exosome, and the ribosome. Ablation study highlighted k-mer and PseKNC to be more dominant than other features for predicting cytoplasm, nucleus, and ER localizations. On the other hand, physicochemical properties and Z-curve based features contributed the most to ExR and mitochondria detection. SHAP-based analysis revealed the relative importance of features to provide better insights into the proposed approach.

AVAILABILITY

We have implemented a Docker container and API for end users to run their sequences on our model. Datasets, the code of API and the Docker are shared for the community in GitHub at: https://github.com/smusleh/MSLP .

RT-LAMP as Diagnostic Tool for Influenza—A Virus Detection in Swine

Point-of-care diagnostic technologies are becoming more widely available for production species. Here, we describe the application of reverse transcription loop-mediated isothermal amplification (RT-LAMP) to detect the matrix (M) gene of influenza A virus in swine (IAV-S). M-specific LAMP primers were designed based on M gene sequences from IAV-S isolated in the USA between 2017 and 2020. The LAMP assay was incubated at 65 °C for 30 min, with the fluorescent signal read every 20 s. The assay’s limit of detection (LOD) was 20 M gene copies for direct LAMP of the matrix gene standard, and 100 M gene copies when using spiked extraction kits. The LOD was 1000 M genes when using cell culture samples. Detection in clinical samples showed a sensitivity of 94.3% and a specificity of 94.9%. These results show that the influenza M gene RT-LAMP assay can detect the presence of IAV in research laboratory conditions. With the appropriate fluorescent reader and heat block, the assay could be quickly validated as a low-cost, rapid, IAV-S screening tool for use on farms or in clinical diagnostic labs.

Introductions of Human-Origin Seasonal H3N2, H1N2 and Pre-2009 H1N1 Influenza Viruses to Swine in Brazil

In South America, the evolutionary history of influenza A virus (IAV) in swine has been obscured by historically low levels of surveillance, and this has hampered the assessment of the zoonotic risk of emerging viruses. The extensive genetic diversity of IAV in swine observed globally has been attributed mainly to bidirectional transmission between humans and pigs. We conducted surveillance in swine in Brazil during 2011-2020 and characterized 107 H1N1, H1N2, and H3N2 IAVs. Phylogenetic analysis based on HA and NA segments revealed that human seasonal IAVs were introduced at least eight times into swine in Brazil since the mid-late 1980s. Our analyses revealed three genetic clades of H1 within the 1B lineage originated from three distinct spillover events, and an H3 lineage that has diversified into three genetic clades. The N2 segment from human seasonal H1N2 and H3N2 viruses was introduced into swine six times and a single introduction of an N1 segment from the human H1N1 virus was identified. Additional analysis revealed further reassortment with H1N1pdm09 viruses. All these introductions resulted in IAVs that apparently circulate only in Brazilian herds. These results reinforce the significant contributions of human IAVs to the genetic diversity of IAV in swine and reiterate the importance of surveillance of IAV in pigs.

Comparative Surface Electrostatics and Normal Mode Analysis of High and Low Pathogenic H7N7 Avian Influenza Viruses

Influenza A viruses are rarely symptomatic in wild birds, while representing a higher threat to poultry and mammals, where they can cause a variety of symptoms, including death. H5 and H7 subtypes of influenza viruses are of particular interest because of their pathogenic potential and reported capacity to spread from poultry to mammals, including humans. The identification of molecular fingerprints for pathogenicity can help surveillance and early warning systems, which are crucial to prevention and protection from such potentially pandemic agents. In the past decade, comparative analysis of the surface features of hemagglutinin, the main protein antigen in influenza viruses, identified electrostatic fingerprints in the evolution and spreading of H5 and H9 subtypes. Electrostatic variation among viruses from avian or mammalian hosts was also associated with host jump. Recent findings of fingerprints associated with low and highly pathogenic H5N1 viruses, obtained by means of comparative electrostatics and normal modes analysis, prompted us to check whether such fingerprints can also be found in the H7 subtype. Indeed, evidence presented in this work showed that also in H7N7, hemagglutinin proteins from low and highly pathogenic strains present differences in surface electrostatics, while no meaningful variation was found in normal modes.

Antiviral Susceptibilities of Distinct Lineages of Influenza C and D Viruses

The emergence and spread of antiviral-resistant influenza viruses are of great concern. To minimize the public health risk, it is important to monitor antiviral susceptibilities of influenza viruses. Analyses of the antiviral susceptibilities of influenza A and B viruses have been conducted globally; however, those of influenza C and D viruses are limited. Here, we determined the susceptibilities of influenza C viruses representing all six lineages (C/Taylor, C/Yamagata, C/Sao Paulo, C/Aichi, C/Kanagawa, and C/Mississippi) and influenza D viruses representing four lineages (D/OK, D/660, D/Yama2016, and D/Yama2019) to RNA polymerase inhibitors (baloxavir and favipiravir) by using a focus reduction assay. All viruses tested were susceptible to both drugs. We then performed a genetic analysis to check for amino acid substitutions associated with baloxavir and favipiravir resistance and found that none of the viruses tested possessed these substitutions. Use of the focus reduction assay with the genotypic assay has proven valuable for monitoring the antiviral susceptibilities of influenza C and D viruses as well as influenza A and B viruses. Antiviral susceptibility monitoring of all influenza virus types should continue in order to assess the public health risks posed by these viruses.

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

The 2023 Nucleic Acids Research Database Issue contains 178 papers ranging across biology and related fields. There are 90 papers reporting on new databases and 82 updates from resources previously published in the Issue. Six more papers are updates from databases most recently published elsewhere. Major nucleic acid databases reporting updates include Genbank, ENA, ChIPBase, JASPAR, mirDIP and the Issue's first Breakthrough Article, NACDDB for Circular Dichroism data. Updates from BMRB and RCSB cover experimental protein structural data while AlphaFold 2 computational structure predictions feature widely. STRING and REBASE are stand-out updates in the signalling and enzymes section. Immunology-related databases include CEDAR, the second Breakthrough Article, for cancer epitopes and receptors alongside returning IPD-IMGT/HLA and the new PGG.MHC. Genomics-related resources include Ensembl, GWAS Central and UCSC Genome Browser. Major returning databases for drugs and their targets include Open Targets, DrugCentral, CTD and Pubchem. The EMPIAR image archive appears in the Issue for the first time. The entire database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, revisiting 463 entries, adding 92 new resources and eliminating 96 discontinued URLs so bringing the current total to 1764 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

Influenza A virus strain PR/8/34, but neither HAM/2009 nor WSN/33, is transiently inhibited by the PB2-targeting drug paliperidone

Influenza A virus (FLUAV) is a significant human pathogen. In silico structural analysis (PMID 28628827) has suggested that the FDA-approved drug paliperidone interferes with the binding of the FLUAV polymerase subunit PB2 to the nucleoprotein NP. We found that paliperidone inhibits FLUAV A/PR/8/34 early after infection of canine MDCK II, human A549, and human primary bronchial cells, but not at late time points. No effect was detectable against the strains A/Hamburg/05/2009 and A/WSN/33. Moreover, paliperidone indeed disturbed the interaction between the PB2 and the NP of A/PR/8/34 and reduced early viral RNA and protein synthesis by approximately 50%. Thus, paliperidone has measurable but transient and virus-strain-restricted effects on FLUAV.

Antigenic Characterization and Pandemic Risk Assessment of North American H1 Influenza A Viruses Circulating in Swine

The first pandemic of the 21st century was caused by an H1N1 influenza A virus (IAV) introduced from pigs into humans, highlighting the importance of swine as reservoirs for pandemic viruses. Two major lineages of swine H1 circulate in North America: the 1A classical swine lineage (including that of the 2009 H1N1 pandemic) and the 1B human seasonal-like lineage. Here, we investigated the evolution of these H1 IAV lineages in North American swine and their potential pandemic risk. We assessed the antigenic distance between the HA of representative swine H1 and human seasonal vaccine strains (1978 to 2015) in hemagglutination inhibition (HI) assays using a panel of monovalent antisera raised in pigs. Antigenic cross-reactivity varied by strain but was associated with genetic distance. Generally, the swine 1A lineage viruses that seeded the 2009 H1 pandemic were antigenically most similar to the H1 pandemic vaccine strains, with the exception of viruses in the genetic clade 1A.1.1.3, which had a two-amino acid deletion mutation near the receptor-binding site, which dramatically reduced antibody recognition. The swine 1B lineage strains, which arose from previously circulating (pre-2009 pandemic) human seasonal viruses, were more antigenically similar to pre-2009 human seasonal H1 vaccine viruses than post-2009 strains. Human population immunity was measured by cross-reactivity in HI assays to representative swine H1 strains. There was a broad range of titers against each swine strain that was not associated with age, sex, or location. However, there was almost no cross-reactivity in human sera to the 1A.1.1.3 and 1B.2.1 genetic clades of swine viruses, and the 1A.1.1.3 and 1B.2.1 clades were also the most antigenically distant to the human vaccine strains. Our data demonstrate that the antigenic distances of representative swine strains from human vaccine strains represent an important part of the rational assessment of swine IAV for zoonotic risk research and pandemic preparedness prioritization. IMPORTANCE Human H1 influenza A viruses (IAV) spread to pigs in North America, resulting in a sustained circulation of two major groups of H1 viruses in swine. We quantified the genetic diversity of H1 in swine and measured antigenic phenotypes. We demonstrated that the swine H1 lineages were significantly different from the human vaccine strains and that this antigenic dissimilarity increased over time as the viruses evolved in swine. Pandemic preparedness vaccine strains for human vaccines also demonstrated a loss in similarity with contemporary swine strains. Human sera revealed a range of responses to swine IAV, including two groups of viruses with little to no immunity. The surveillance and risk assessment of IAV diversity in pig populations are essential to detect strains with reduced immunity in humans and provide critical information for pandemic preparedness.

A multivalent nucleoside-modified mRNA vaccine against all known influenza virus subtypes

Seasonal influenza vaccines offer little protection against pandemic influenza virus strains. It is difficult to create effective prepandemic vaccines because it is uncertain which influenza virus subtype will cause the next pandemic. In this work, we developed a nucleoside-modified messenger RNA (mRNA)-lipid nanoparticle vaccine encoding hemagglutinin antigens from all 20 known influenza A virus subtypes and influenza B virus lineages. This multivalent vaccine elicited high levels of cross-reactive and subtype-specific antibodies in mice and ferrets that reacted to all 20 encoded antigens. Vaccination protected mice and ferrets challenged with matched and mismatched viral strains, and this protection was at least partially dependent on antibodies. Our studies indicate that mRNA vaccines can provide protection against antigenically variable viruses by simultaneously inducing antibodies against multiple antigens.