Deep Mutational Scan of the Highly Conserved Influenza A Virus M1 Matrix Protein Reveals Substantial Intrinsic Mutational Tolerance

Polyanhydride nanovaccine against H3N2 influenza A virus generates mucosal resident and systemic immunity promoting protection

Influenza A virus (IAV) causes significant morbidity and mortality worldwide due to seasonal epidemics and periodic pandemics. The antigenic drift/shift of IAV continually gives rise to new strains and subtypes, aiding IAV in circumventing previously established immunity. As a result, there has been substantial interest in developing a broadly protective IAV vaccine that induces, durable immunity against multiple IAVs. Previously, a polyanhydride nanoparticle-based vaccine or nanovaccine (IAV-nanovax) encapsulating H1N1 IAV antigens was reported, which induced pulmonary B and T cell immunity and resulted in cross-strain protection against IAV. A key feature of IAV-nanovax is its ability to easily incorporate diverse proteins/payloads, potentially increasing its ability to provide broad protection against IAV and/or other pathogens. Due to human susceptibility to both H1N1 and H3N2 IAV, several H3N2 nanovaccines were formulated herein with multiple IAV antigens to examine the "plug-and-play" nature of the polyanhydride nanovaccine platform and determine their ability to induce humoral and cellular immunity and broad-based protection similar to IAV-nanovax. The H3N2-based IAV nanovaccine formulations induced systemic and mucosal B cell responses which were associated with antigen-specific antibodies. Additionally, systemic and lung-tissue resident CD4 and CD8 T cell responses were enhanced post-vaccination. These immune responses corresponded with protection against both homologous and heterosubtypic IAV infection. Overall, these results demonstrate the plug-and-play nature of the polyanhydride nanovaccine platform and its ability to generate immunity and protection against IAV utilizing diverse antigenic payloads.

Deep mutational scanning of hepatitis B virus reveals a mechanism for cis-preferential reverse transcription

Hepatitis B virus (HBV) is a small double-stranded DNA virus that chronically infects 296 million people. Over half of its compact genome encodes proteins in two overlapping reading frames, and during evolution, multiple selective pressures can act on shared nucleotides. This study combines an RNA-based HBV cell culture system with deep mutational scanning (DMS) to uncouple cis- and trans-acting sequence requirements in the HBV genome. The results support a leaky ribosome scanning model for polymerase translation, provide a fitness map of the HBV polymerase at single-nucleotide resolution, and identify conserved prolines adjacent to the HBV polymerase termination codon that stall ribosomes. Further experiments indicated that stalled ribosomes tether the nascent polymerase to its template RNA, ensuring cis-preferential RNA packaging and reverse transcription of the HBV genome.

popDMS infers mutation effects from deep mutational scanning data

Deep mutational scanning (DMS) experiments provide a powerful method to measure the functional effects of genetic mutations at massive scales. However, the data generated from these experiments can be difficult to analyze, with significant variation between experimental replicates. To overcome this challenge, we developed popDMS, a computational method based on population genetics theory, to infer the functional effects of mutations from DMS data. Through extensive tests, we found that the functional effects of single mutations and epistasis inferred by popDMS are highly consistent across replicates, comparing favorably with existing methods. Our approach is flexible and can be widely applied to DMS data that includes multiple time points, multiple replicates, and different experimental conditions.

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.

Deep mutational scanning reveals the functional constraints and evolutionary potential of the influenza A virus PB1 protein

IMPORTANCE

The influenza virus polymerase is important for adaptation to new hosts and, as a determinant of mutation rate, for the process of adaptation itself. We performed a deep mutational scan of the polymerase basic 1 (PB1) protein to gain insights into the structural and functional constraints on the influenza RNA-dependent RNA polymerase. We find that PB1 is highly constrained at specific sites that are only moderately predicted by the global structure or larger domain. We identified a number of beneficial mutations, many of which have been shown to be functionally important or observed in influenza virus' natural evolution. Overall, our atlas of PB1 mutations and their fitness impacts serves as an important resource for future studies of influenza replication and evolution.

Mutational fitness landscape of human influenza H3N2 neuraminidase

Influenza neuraminidase (NA) has received increasing attention as an effective vaccine target. However, its mutational tolerance is not well characterized. Here, the fitness effects of >6,000 mutations in human H3N2 NA are probed using deep mutational scanning. Our result shows that while its antigenic regions have high mutational tolerance, there are solvent-exposed regions with low mutational tolerance. We also find that protein stability is a major determinant of NA mutational fitness. The deep mutational scanning result correlates well with mutational fitness inferred from natural sequences using a protein language model, substantiating the relevance of our findings to the natural evolution of circulating strains. Additional analysis further suggests that human H3N2 NA is far from running out of mutations despite already evolving for >50 years. Overall, this study advances our understanding of the evolutionary potential of NA and the underlying biophysical constraints, which in turn provide insights into NA-based vaccine design.

Influenza A Virus M1 Protein Non-Specifically Deforms Charged Lipid Membranes and Specifically Interacts with the Raft Boundary

Topological rearrangements of biological membranes, such as fusion and fission, often require a sophisticated interplay between different proteins and cellular membranes. However, in the case of fusion proteins of enveloped viruses, even one molecule can execute membrane restructurings. Growing evidence indicates that matrix proteins of enveloped viruses can solely trigger the membrane bending required for another crucial step in virogenesis, the budding of progeny virions. For the case of the influenza A virus matrix protein M1, different studies report both in favor and against M1 being able to produce virus-like particles without other viral proteins. Here, we investigated the physicochemical mechanisms of M1 membrane activity on giant unilamellar vesicles of different lipid compositions using fluorescent confocal microscopy. We confirmed that M1 predominantly interacts electrostatically with the membrane, and its ability to deform the lipid bilayer is non-specific and typical for membrane-binding proteins and polypeptides. However, in the case of phase-separating membranes, M1 demonstrates a unique ability to induce macro-phase separation, probably due to the high affinity of M1's amphipathic helices to the raft boundary. Thus, we suggest that M1 is tailored to deform charged membranes with a specific activity in the case of phase-separating membranes.

Exploring the expanse between theoretical questions and experimental approaches in the modern study of evolvability

Despite several decades of computational and experimental work across many systems, evolvability remains on the periphery with regards to its status as a widely accepted and regularly applied theoretical concept. Here we propose that its marginal status is partly a result of large gaps between the diverse but disconnected theoretical treatments of evolvability and the relatively narrower range of studies that have tested it empirically. To make this case, we draw on a range of examples-from experimental evolution in microbes, to molecular evolution in proteins-where attempts have been made to mend this disconnect. We highlight some examples of progress that has been made and point to areas where synthesis and translation of existing theory can lead to further progress in the still-new field of empirical measurements of evolvability.

Protein Folding Interdiction Strategy for Therapeutic Drug Development in Viral Diseases: Ebola VP40 and Influenza A M1

In a recent paper, we proposed the folding interdiction target region (FITR) strategy for therapeutic drug design in SARS-CoV-2. This paper expands the application of the FITR strategy by proposing therapeutic drug design approaches against Ebola virus disease and influenza A. We predict target regions for folding interdicting drugs on correspondingly relevant structural proteins of both pathogenic viruses: VP40 of Ebola, and matrix protein M1 of influenza A. Identification of the protein targets employs the sequential collapse model (SCM) for protein folding. It is explained that the model predicts natural peptide candidates in each case from which to start the search for therapeutic drugs. The paper also discusses how these predictions could be tested, as well as some challenges likely to be found when designing effective therapeutic drugs from the proposed peptide candidates. The FITR strategy opens a potential new avenue for the design of therapeutic drugs that promises to be effective against infectious diseases.

Effect of serial in vivo passages on the adaptation of H1N1 avian influenza virus to pigs

Introduction

The lack of proofreading activity of the viral polymerase and the segmented nature of the influenza A virus (IAV) genome are responsible for the genetic diversity of IAVs and for their ability to adapt to a new host. We tried to adapt avian IAV (avIAV) to the pig by serial passages in vivo and assessed the occurrence of point mutations and their influence on viral fitness in the pig’s body.

Material and Methods

A total of 25 in vivo avIAV passages of the A/duck/Bavaria/77 strain were performed by inoculation of 50 piglets, and after predetermined numbers of passages 20 uninoculated piglets were exposed to the virus through contact with inoculated animals. Clinical signs of swine influenza were assessed daily. Nasal swabs and lung tissue were used to detect IAV RNA by real-time RT-PCR and isolates from selected passages were sequenced.

Results

Apart from a rise in rectal temperature and a sporadic cough, no typical clinical signs were observed in infected pigs. The original strain required 20 passages to improve its replication ability noticeably. A total of 29 amino-acid substitutions were identified. Eighteen of them were detected in the first sequenced isolate, of which 16 were also in all other analysed strains. Additional mutations were detected with more passages. One substitution, threonine (T) 135 to serine (S) in neuraminidase (NA), was only detected in an IAV isolate from a contact-exposed piglet.

Conclusion

Passaging 25 times allowed us to obtain a partially swine-adapted IAV. The improvement in isolate replication ability was most likely related to S654 to glycine (G) substitution in the basic protein (PB) 1 as well as to aspartic acid (D) 701 to asparagine (N) and arginine (R) 477 to G in PB2, glutamic acid (E) 204 to D and G239E in haemagglutinin and T135S in NA.

Antigenic evolution of human influenza H3N2 neuraminidase is constrained by charge balancing

As one of the main influenza antigens, neuraminidase (NA) in H3N2 virus has evolved extensively for more than 50 years due to continuous immune pressure. While NA has recently emerged as an effective vaccine target, biophysical constraints on the antigenic evolution of NA remain largely elusive. Here, we apply combinatorial mutagenesis and next-generation sequencing to characterize the local fitness landscape in an antigenic region of NA in six different human H3N2 strains that were isolated around 10 years apart. The local fitness landscape correlates well among strains and the pairwise epistasis is highly conserved. Our analysis further demonstrates that local net charge governs the pairwise epistasis in this antigenic region. In addition, we show that residue coevolution in this antigenic region is correlated with the pairwise epistasis between charge states. Overall, this study demonstrates the importance of quantifying epistasis and the underlying biophysical constraint for building a model of influenza evolution.

An evolution-based high-fidelity method of epistasis measurement: Theory and application to influenza

Linkage effects in a multi-locus population strongly influence its evolution. The models based on the traveling wave approach enable us to predict the average speed of evolution and the statistics of phylogeny. However, predicting statistically the evolution of specific sites and pairs of sites in the multi-locus context remains a mathematical challenge. In particular, the effects of epistasis, the interaction of gene regions contributing to phenotype, is difficult to predict theoretically and detect experimentally in sequence data. A large number of false-positive interactions arises from stochastic linkage effects and indirect interactions, which mask true epistatic interactions. Here we develop a proof-of-principle method to filter out false-positive interactions. We start by demonstrating that the averaging of haplotype frequencies over multiple independent populations is necessary but not sufficient for epistatic detection, because it still leaves high numbers of false-positive interactions. To compensate for the residual stochastic noise, we develop a three-way haplotype method isolating true interactions. The fidelity of the method is confirmed analytically and on simulated genetic sequences evolved with a known epistatic network. The method is then applied to a large sequence database of neurominidase protein of influenza A H1N1 obtained from various geographic locations to infer the epistatic network responsible for the difference between the pre-pandemic virus and the pandemic strain of 2009. These results present a simple and reliable technique to measure epistatic interactions of any sign from sequence data.

Interactions between genomic sites create a fitness landscape. The knowledge of topology and strength of interactions is vital for predicting the escape of viruses from drugs and immune response and their passing through fitness valleys. Many efforts have been invested into measuring these interactions from DNA sequence sets. Unfortunately, reproducibility of the results remains low due partly to a very small fraction of interaction pairs and partly to stochastic linkage noise masking true interactions. Here we propose a method to separate stochastic linkage and indirect interactions from epistatic interactions and apply it to influenza virus sequence data.

The Adaptive Potential of the Middle Domain of Yeast Hsp90

The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

The evolutionary origin of the universal distribution of mutation fitness effect

An intriguing fact long defying explanation is the observation of a universal exponential distribution of beneficial mutations in fitness effect for different microorganisms. To explain this effect, we use a population model including mutation, directional selection, linkage, and genetic drift. The multiple-mutation regime of adaptation at large population sizes (traveling wave regime) is considered. We demonstrate analytically and by simulation that, regardless of the inherent distribution of mutation fitness effect across genomic sites, an exponential distribution of fitness effects emerges in the long term. This result follows from the exponential statistics of the frequency of the less-fit alleles, f, that we predict to evolve, in the long term, for both polymorphic and monomorphic sites. We map the logarithmic slope of the distribution onto the previously derived fixation probability and demonstrate that it increases linearly in time. Our results demonstrate a striking difference between the distribution of fitness effects observed experimentally for naturally occurring mutations, and the "inherent" distribution obtained in a directed-mutagenesis experiment, which can have any shape depending on the organism. Based on these results, we develop a new method to measure the fitness effect of mutations for each variable residue using DNA sequences sampled from adapting populations. This new method is not sensitive to linkage effects and does not require the one-site model assumptions.

Adenoviral Vectors as Vaccines for Emerging Avian Influenza Viruses

It is evident that the emergence of infectious diseases, which have the potential for spillover from animal reservoirs, pose an ongoing threat to global health. Zoonotic transmission events have increased in frequency in recent decades due to changes in human behavior, including increased international travel, the wildlife trade, deforestation, and the intensification of farming practices to meet demand for meat consumption. Influenza A viruses (IAV) possess a number of features which make them a pandemic threat and a major concern for human health. Their segmented genome and error-prone process of replication can lead to the emergence of novel reassortant viruses, for which the human population are immunologically naïve. In addition, the ability for IAVs to infect aquatic birds and domestic animals, as well as humans, increases the likelihood for reassortment and the subsequent emergence of novel viruses. Sporadic spillover events in the past few decades have resulted in human infections with highly pathogenic avian influenza (HPAI) viruses, with high mortality. The application of conventional vaccine platforms used for the prevention of seasonal influenza viruses, such as inactivated influenza vaccines (IIVs) or live-attenuated influenza vaccines (LAIVs), in the development of vaccines for HPAI viruses is fraught with challenges. These issues are associated with manufacturing under enhanced biosafety containment, and difficulties in propagating HPAI viruses in embryonated eggs, due to their propensity for lethality in eggs. Overcoming manufacturing hurdles through the use of safer backbones, such as low pathogenicity avian influenza viruses (LPAI), can also be a challenge if incompatible with master strain viruses. Non-replicating adenoviral (Ad) vectors offer a number of advantages for the development of vaccines against HPAI viruses. Their genome is stable and permits the insertion of HPAI virus antigens (Ag), which are expressed in vivo following vaccination. Therefore, their manufacture does not require enhanced biosafety facilities or procedures and is egg-independent. Importantly, Ad vaccines have an exemplary safety and immunogenicity profile in numerous human clinical trials, and can be thermostabilized for stockpiling and pandemic preparedness. This review will discuss the status of Ad-based vaccines designed to protect against avian influenza viruses with pandemic potential.

Globally defining the effects of mutations in a picornavirus capsid

The capsids of non-enveloped viruses are highly multimeric and multifunctional protein assemblies that play key roles in viral biology and pathogenesis. Despite their importance, a comprehensive understanding of how mutations affect viral fitness across different structural and functional attributes of the capsid is lacking. To address this limitation, we globally define the effects of mutations across the capsid of a human picornavirus. Using this resource, we identify structural and sequence determinants that accurately predict mutational fitness effects, refine evolutionary analyses, and define the sequence specificity of key capsid-encoded motifs. Furthermore, capitalizing on the derived sequence requirements for capsid-encoded protease cleavage sites, we implement a bioinformatic approach for identifying novel host proteins targeted by viral proteases. Our findings represent the most comprehensive investigation of mutational fitness effects in a picornavirus capsid to date and illuminate important aspects of viral biology, evolution, and host interactions.

A virus is made up of genetic material that is encased with a protective protein coat called the capsid. The capsid also helps the virus to infect host cells by binding to the host receptor proteins and releasing its genetic material. Inside the cell, the virus hitchhikes the infected cell’s machinery to grow or replicate its own genetic material.

Viral capsids are the main target of the host’s defence system, and therefore, continuously change in an attempt to escape the immune system by introducing alterations (known as mutations) into the genes encoding viral capsid proteins. Mutations occur randomly, and so while some changes to the viral capsid might confer an advantage, others may have no effect at all, or even weaken the virus.

To better understand the effect of capsid mutations on the virus’ ability to infect host cells, Mattenberger et al. studied the Coxsackievirus B3, which is linked to heart problems and acute heart failure in humans. The researchers analysed around 90% of possible amino acid mutations (over 14,800 mutations) and correlated each mutation to how it influenced the virus’ ability to replicate in human cells grown in the laboratory.

Based on these results, Mattenberger et al. developed a computer model to predict how a particular mutation might affect the virus. The analysis also identified specific amino acid sequences of capsid proteins that are essential for certain tasks, such as building the capsid. It also included an analysis of sequences in the capsid that allow it to be recognized by another viral protein, which cuts the capsid proteins into the right size from a larger precursor. By looking for similar sequences in human genes, the researchers identified several ones that the virus may attack and inactivate to support its own replication.

These findings may help identify potential drug targets to develop new antiviral therapies. For example, proteins of the capsid that are less likely to mutate will provide a better target as they lower the possibility of the virus to become resistant to the treatment. They also highlight new proteins in human cells that could potentially block the virus in cells.

Conformational triggers associated with influenza matrix protein 1 polymerization

A central role for the influenza matrix protein 1 (M1) is to form a polymeric coat on the inner leaflet of the host membrane that ultimately provides shape and stability to the virion. M1 polymerizes upon binding membranes, but triggers for conversion of M1 from a water-soluble component of the nucleus and cytosol into an oligomer at the membrane surface are unknown. While full-length M1 is required for virus viability, the N-terminal domain (M1NT) retains membrane binding and pH-dependent oligomerization. We studied the structural plasticity and oligomerization of M1NT in solution using NMR spectroscopy. We show that the isolated domain can be induced by sterol-containing compounds to undergo a conformational change and self-associate in a pH-dependent manner consistent with the stacked dimer oligomeric interface. Surface-exposed residues at one of the stacked dimer interfaces are most sensitive to sterols. Several perturbed residues are at the interface between the N-terminal subdomains and are also perturbed by changes in pH. The effects of sterols appear to be indirect and most likely mediated by reduction in water activity. The local changes are centered on strictly conserved residues and consistent with a priming of the N-terminal domain for polymerization. We hypothesize that M1NT is sensitive to changes in the aqueous environment and that this sensitivity is part of a mechanism for restricting polymerization to the membrane surface. Structural models combined with information from chemical shift perturbations indicate mechanisms by which conformational changes can be transmitted from one polymerization interface to the other.

Insights from the comparison of genomic variants from two influenza B viruses grown in the presence of human antibodies in cell culture

Understanding the extent and limitation of viral genome evolution can provide insight about potential drug and vaccine targets. Influenza B Viruses (IBVs) infect humans in a seasonal manner and causes significant morbidity and mortality. IBVs are negative-sense single-stranded RNA viruses with a segmented genome and can be divided into two antigenically distinct lineages. The two lineages have been circulating and further evolving for almost four decades. The immune response to IBV infection can lead to antibodies that target the strain causing the infection. Some antibodies are cross-reactive and are able to bind strains from both lineages but, because of antigenic drift and immunodominance, both lineages continue to evolve and challenge human health. Here we investigate changes in the genomes of an IBVs from each lineage after passage in tissue culture in the presence of human sera containing polyclonal antibodies directed toward antigenically and temporally distinct viruses. Our previous analysis of the fourth segment, which encodes the major surface protein HA, revealed a pattern of change in which signature sequences from one lineage mutated to the signature sequences of the other lineage. Here we analyze genes from the other genomic segments and observe that most of the quasispecies’ heterogeneity occurs at the same loci in each lineage. The nature of the variants at these loci are investigated and possible reasons for this pattern are discussed. This work expands our understanding of the extent and limitations of genomic change in IBV.

Host-virus evolutionary dynamics with specialist and generalist infection strategies: Bifurcations, bistability, and chaos

In this work, we have investigated the evolutionary dynamics of a generalist pathogen, e.g., a virus population, that evolves toward specialization in an environment with multiple host types. We have particularly explored under which conditions generalist viral strains may rise in frequency and coexist with specialist strains or even dominate the population. By means of a nonlinear mathematical model and bifurcation analysis, we have determined the theoretical conditions for stability of nine identified equilibria and provided biological interpretation in terms of the infection rates for the viral specialist and generalist strains. By means of a stability diagram, we identified stable fixed points and stable periodic orbits, as well as regions of bistability. For arbitrary biologically feasible initial population sizes, the probability of evolving toward stable solutions is obtained for each point of the analyzed parameter space. This probability map shows combinations of infection rates of the generalist and specialist strains that might lead to equal chances for each type becoming the dominant strategy. Furthermore, we have identified infection rates for which the model predicts the onset of chaotic dynamics. Several degenerate Bogdanov-Takens and zero-Hopf bifurcations are detected along with generalized Hopf and zero-Hopf bifurcations. This manuscript provides additional insights into the dynamical complexity of host-pathogen evolution toward different infection strategies.

Filamentous versus Spherical Morphology: A Case Study of the Recombinant A/WSN/33 (H1N1) Virus

Influenza A virus is a serious human pathogen that assembles enveloped virions on the plasma membrane of the host cell. The pleiomorphic morphology of influenza A virus, represented by spherical, elongated, or filamentous particles, is important for the spread of the virus in nature. Using fixative protocols for sample preparation and negative staining electron microscopy, we found that the recombinant A/WSN/33 (H1N1) (rWSN) virus, a strain considered to be strictly spherical, may produce filamentous particles when amplified in the allantoic cavity of chicken embryos. In contrast, the laboratory WSN strain and the rWSN virus amplified in Madin-Darby canine kidney cells exhibited a spherical morphology. Next-generation sequencing (NGS) suggested a rare Ser126Cys substitution in the M1 protein of rWSN, which was confirmed by the mass spectrometric analysis. No structurally relevant substitutions were found by NGS in other proteins of rWSN. Bioinformatics algorithms predicted a neutral structural effect of the Ser126Cys mutation. The mrWSN_M1_126S virus generated after the introduction of the reverse Cys126Ser substitution exhibited a similar host-dependent partially filamentous phenotype. We hypothesize that a shortage of some as-yet-undefined cellular components involved in virion budding and membrane scission may result in the appearance of filamentous particles in the case of usually "nonfilamentous" virus strains.

Genetic and serologic surveillance of canine (CIV) and equine (EIV) influenza virus in Nuevo León State, México

BACKGROUND

Despite the uncontrolled distribution of the Influenza A virus through wild birds, the detection of canine influenza virus and equine influenza virus in Mexico was absent until now. Recently, outbreaks of equine and canine influenza have been reported around the world; the virus spreads quickly among animals and there is potential for zoonotic transmission.

METHODS

Amplification of the Influenza A virus matrix gene from necropsies, nasal and conjunctival swabs from trash service horses and pets/stray dogs was performed through RT-PCR. The seroprevalence was carried out through Sandwich enzyme-linked immunosorbent assay system using the M1 recombinant protein and polyclonal antibodies anti-M1.

RESULTS

The matrix gene was amplified from 13 (19.11%) nasal swabs, two (2.94%) conjunctival swabs and five (7.35%) lung necropsies, giving a total of 20 (29.41%) positive samples in a pet dog population. A total of six (75%) positive samples of equine nasal swab were amplified. Sequence analysis showed 96-99% identity with sequences of Influenza A virus matrix gene present in H1N1, H1N2 and H3N2 subtypes. The phylogenetic analysis of the sequences revealed higher identity with matrix gene sequences detected from zoonotic isolates of subtype H1N1/2009. The detection of anti-M1 antibodies in stray dogs showed a prevalence of 123 (100%) of the sampled population, whereas in horses, 114 (92.68%) positivity was obtained.

CONCLUSION

The results unveil the prevalence of Influenza A virus in the population of horses and dogs in the state of Nuevo Leon, which could indicate a possible outbreak of equine and Canine Influenza in Mexico. We suggest that the prevalence of Influenza virus in companion animals be monitored to investigate its epizootic and zoonotic potential, in addition to encouraging the regulation of vaccination in these animal species in order to improve their quality of life.