The expression of accessory non-structural proteins V and W in Newcastle disease virus (NDV) infections depends on RNA editing. These proteins are derived from frameshifts of the sequence coding for the P protein via co-transcriptional insertion of one or two guanines in the mRNA. However, a larger number of guanines can be inserted with lower frequencies. We analysed data from deep RNA sequencing of samples from in vitro and in vivo NDV infections to uncover the patterns of mRNA editing in NDV. The distribution of insertions is well described by a simple Markov model of polymerase stuttering, providing strong quantitative confirmation of the molecular process hypothesised by Kolakofsky and collaborators three decades ago. Our results suggest that the probability that the NDV polymerase would stutter is about 0.45 initially, and 0.3 for further subsequent insertions. The latter probability is approximately independent of the number of previous insertions, the host cell, and viral strain. However, in LaSota infections, we also observe deviations from the predicted V/W ratio of about 3:1 according to this model, which could be attributed to deviations from this stuttering model or to further mechanisms downregulating the abundance of W protein.

Although enveloped viruses canonically mediate particle entry through virus-cell fusion, certain viruses can spread by cell-cell fusion, brought about by receptor engagement and triggering of membrane-bound, viral-encoded fusion proteins on the surface of cells. The formation of pathogenic syncytia or multinucleated cells is seen in vivo, but their contribution to viral pathogenesis is poorly understood. For the negative-strand paramyxoviruses respiratory syncytial virus (RSV) and Nipah virus (NiV), cell-cell spread is highly efficient because their oligomeric fusion protein complexes are active at neutral pH. The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has also been reported to induce syncytia formation in infected cells, with the spike protein initiating cell-cell fusion. Whilst it is well established that fusion protein-specific antibodies can block particle attachment and/or entry into the cell (canonical virus neutralization), their capacity to inhibit cell-cell fusion and the consequences of this neutralization for the control of infection are not well characterized, in part because of the lack of specific tools to assay and quantify this activity. Using an adapted bimolecular fluorescence complementation assay, based on a split GFP-Renilla luciferase reporter, we have established a micro-fusion inhibition test (mFIT) that allows the identification and quantification of these neutralizing antibodies. This assay has been optimized for high-throughput use and its applicability has been demonstrated by screening monoclonal antibody (mAb)-mediated inhibition of RSV and NiV fusion and, separately, the development of fusion-inhibitory antibodies following NiV vaccine immunization in pigs. In light of the recent emergence of coronavirus disease 2019 (COVID-19), a similar assay was developed for SARS-CoV-2 and used to screen mAbs and convalescent patient plasma for fusion-inhibitory antibodies. Using mFITs to assess antibody responses following natural infection or vaccination is favourable, as this assay can be performed entirely at low biocontainment, without the need for live virus. In addition, the repertoire of antibodies that inhibit cell-cell fusion may be different to those that inhibit particle entry, shedding light on the mechanisms underpinning antibody-mediated neutralization of viral spread.

Recent evidence indicates that local immune responses and tissue resident memory T cells (TRM) are critical for protection against respiratory infections but there is little information on the contributions of upper and lower respiratory tract (URT and LRT) immunity. To provide a rational basis for designing methods for optimal delivery of vaccines to the respiratory tract in a large animal model, we investigated the distribution of droplets generated by a mucosal atomization device (MAD) and two vibrating mesh nebulizers (VMNs) and the immune responses induced by delivery of influenza virus by MAD in pigs. We showed that droplets containing the drug albuterol, a radiolabel (^99mTc-DTPA) or a model influenza virus vaccine (S-FLU) have similar aerosol characteristics. ^99mTc-DTPA scintigraphy showed that VMNs deliver droplets with uniform distribution throughout the lungs as well as the URT. Surprisingly MAD administration (1ml/nostril) also delivered a high proportion of the dose to the lungs, albeit concentrated in a small area. After MAD administration of influenza virus, antigen specific T cells were found at high frequency in nasal turbinates, trachea, broncho-alveolar lavage, lungs, tracheobronchial nodes and blood. We conclude that the pig is useful for investigating optimal targeting of vaccines to the respiratory tract.

High-throughput sequencing such as those provided by Illumina are an efficient way to understand sequence variation within viral populations. However, challenges exist in distinguishing process-introduced error from biological variance, which significantly impacts our ability to identify sub-consensus single-nucleotide variants (SNVs). Here we have taken a systematic approach to evaluate laboratory and bioinformatic pipelines to accurately identify low-frequency SNVs in viral populations. Artificial DNA and RNA “populations” were created by introducing known SNVs at predetermined frequencies into template nucleic acid before being sequenced on an Illumina MiSeq platform. These were used to assess the effects of abundance and starting input material type, technical replicates, read length and quality, short-read aligner, and percentage frequency thresholds on the ability to accurately call variants. Analyses revealed that the abundance and type of input nucleic acid had the greatest impact on the accuracy of SNV calling as measured by a micro-averaged Matthews correlation coefficient score, with DNA and high RNA inputs (10⁷ copies) allowing for variants to be called at a 0.2% frequency. Reduced input RNA (10⁵ copies) required more technical replicates to maintain accuracy, while low RNA inputs (10³ copies) suffered from consensus-level errors. Base errors identified at specific motifs identified in all technical replicates were also identified which can be excluded to further increase SNV calling accuracy. These findings indicate that samples with low RNA inputs should be excluded for SNV calling and reinforce the importance of optimising the technical and bioinformatics steps in pipelines that are used to accurately identify sequence variants.

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

Wild animals are the source of many pathogens of livestock and humans. Concerns about the potential transmission of economically important and zoonotic diseases from wildlife have led to increased surveillance at the livestock-wildlife interface. Knowledge of the types, frequency and duration of contacts between livestock and wildlife is necessary to identify risk factors for disease transmission and to design possible mitigation strategies. Observing the behaviour of many wildlife species is challenging due to their cryptic nature and avoidance of humans, meaning there are relatively few studies in this area. Further, a consensus on the definition of what constitutes a ‘contact’ between wildlife and livestock is lacking. A systematic review was conducted to investigate which livestock-wildlife contacts have been studied and why, as well as the methods used to observe each species. Over 30,000 publications were screened, of which 122 fulfilled specific criteria for inclusion in the analysis. The majority of studies examined cattle contacts with badgers or with deer; studies involving wild pig contacts with cattle or with domestic pigs were the next most frequent. There was a range of observational methods including motion-activated cameras and global positioning system collars. As a result of the wide variation and lack of consensus in the definitions of direct and indirect contacts, we developed a unified framework to define livestock-wildlife contacts that is sufficiently flexible to be applied to most wildlife and livestock species for non-vector-borne diseases. We hope this framework will help standardise the collection and reporting of contact data; a valuable step towards being able to compare the efficacy of wildlife-livestock observation methods. In doing so, it may aid the development of better disease transmission models and improve the design and effectiveness of interventions to reduce or prevent disease transmission.

Bluetongue is an economically important disease of ruminants caused by the bluetongue virus (BTV). BTV is serologically diverse, which complicates vaccination strategies. Rapid identification of the causative BTV serotypes is critical, however, real-time PCR (RT-qPCR) can be costly and time consuming to perform when the circulating serotypes are unknown. The Luminex xMAP technology is a high-throughput platform that uses fluorescent beads to detect multiple targets simultaneously. We utilized existing BTV serotyping RT-qPCR assays for BTV-1 to BTV-24 and adapted them for use with the xMAP platform. The xMAP assay specifically detected all 24 BTV serotypes when testing reference strains. In all BTV-positive samples, the sensitivity of the BTV xMAP was 87.55% whereas the sensitivity of the serotype-specific RT-qPCR was 79.85%. The BTV xMAP assay allowed for the specific detection of BTV serotypes 1–24 at a lower cost than current RT-qPCR assays. Overall, the assay provides a useful novel diagnostic tool, particularly when analyzing large sample sets. The use of the BTV xMAP assay will allow for the rapid assessment of BTV epidemiology and may inform decision-making related to control and prevention measures.

Background: Baicalin, the main metabolic component of Scutellaria baicalensis Georgi, has various pharmacological properties including anti-inflammatory, anti-oxidant, anti-apoptotic, anti-bactericidal and anti-viral. The purpose of this study was to investigate the anti-Marek’s disease virus (MDV) activities of baicalin in CEF cells.

Results: Here, we showed that baicalin could inhibit viral mRNA, protein levels and overall plaque formation in a time-dependent manner. We also found that baicalin could consistently inhibit MDV replication and directly affect the virus infectivity. Moreover, baicalin treatment has no effect on expression level of antiviral cytokine and inflammatory cytokines in MDV infected CEFs.

Conclusions: These results demonstrate that baicalin could be a potential drug against MDV infection.