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

In recent years, it has been shown that some parvoviruses exhibit high substitution rates, close to those of RNA viruses. In order to monitor and determine new mutations in porcine parvovirus (PPV), recent PPV field isolates from Austria, Brazil, Germany and Switzerland were sequenced and analysed. These samples, together with sequences retrieved from GenBank, were included in three datasets, consisting of the complete NS1 and VP1 genes and a partial VP1 gene. For each dataset, the nucleotide substitution rate and the molecular clock were determined. Analysis of the PPV field isolates revealed that a recently described amino acid substitution, S436T, appeared to be common in the VP2 protein in the Austrian, Brazilian and German virus populations. Furthermore, new amino acid substitutions were identified, located mainly in the viral capsid loops. By inferring the evolutionary dynamics of the PPV sequences, nucleotide substitution rates of approximately 10 "5 substitutions per site per year for the non-structural protein gene and 10substitutions per site per year for the capsid protein gene (for both viral protein datasets) were found. The latter rate is similar to those commonly found in RNA viruses. An association of the phylogenetic tree with the molecular clock analysis revealed that the mutations on which the divergence for both capsid proteins was based occurred in the past 30 years. Based on these findings, it was concluded that PPV variants are continuously evolving and that vaccines, which are based mainly on strains isolated about 30 years ago, should perhaps be updated.

Detection and characterisation of the canine parvovirus (CPV-2) strains that are currently circulating are essential for the understanding of viral evolution and the development of measures to control its spread. In the present study, stool samples from 144 dogs were analysed by polymerase chain reaction (PCR) for CPV-2, and 29.2% (42/144) of them were positive. From the 42 positive strains, 71.4% (30) of the dogs had signs of haemorrhagic gastroenteritis. The sequencing of the 583 bp fragment of the VP2 gene from the positive strains identified 78.6% (33/42) of them as type 2c, 19% (8/42) as type 2b and 2.4% (1/42) as type 2a. A phylogenetic analysis of the variants circulating in the canine population of Brazil showed that they are very similar to those found in other countries and type 2c has become the predominant type circulating in Brazil.

Swine effluents must be correctly handled to avoid negative environmental impacts. In this study, the profiles of two swine manure treatment systems were evaluated: a solid-liquid separation step, followed by an anaerobic reactor, and an aerobic step (System 1); and a biodigester followed by serial lagoons (System 2). Both systems were described by the assessment of chemical, bacterial and viral parameters. The results showed that in System 1, there was reduction of chemicals (COD, phosphorus, total Kjeldhal nitrogen - TKN - and NH(3)), total coliforms and Escherichia coli; however, the same reduction was not observed for Salmonella sp. Viral particles were significantly reduced but not totally eliminated from the effluent. In System 2, there was a reduction of chemicals, bacteria and viruses with no detection of Salmonella sp., circovirus, parvovirus, and torque teno virus in the effluent. The chemical results indicate that the treated effluent can be reused for cleaning swine facilities. However, the microbiological results show a need of additional treatment to achieve a complete inactivation for cases when direct contact with animals is required.

The antigenic diversity of influenza A viruses (IAV) circulating in swine challenges the development of effective vaccines, increasing zoonotic threat and pandemic potential. High-throughput sequencing technologies can quantify IAV genetic diversity, but there are no accurate approaches to adequately describe antigenic phenotypes. This study evaluated an ensemble of nonlinear regression models to estimate virus phenotype from genotype. Regression models were trained with a phenotypic data set of pairwise hemagglutination inhibition (HI) assays, using genetic sequence identity and pairwise amino acid mutations as predictor features. The model identified amino acid identity, ranked the relative importance of mutations in the hemagglutinin (HA) protein, and demonstrated good prediction accuracy. Four previously untested IAV strains were selected to experimentally validate model predictions by HI assays. Errors between predicted and measured distances of uncharacterized strains were 0.35, 0.61, 1.69, and 0.13 antigenic units. These empirically trained regression models can be used to estimate antigenic distances between different strains of IAV in swine by using sequence data. By ranking the importance of mutations in the HA, we provide criteria for identifying antigenically advanced IAV strains that may not be controlled by existing vaccines and can inform strain updates to vaccines to better control this pathogen. IMPORTANCE Influenza A viruses (IAV) in swine constitute a major economic burden to an important global agricultural sector, impact food security, and are a public health threat. Despite significant improvement in surveillance for IAV in swine over the past 10 years, sequence data have not been integrated into a systematic vaccine strain selection process for predicting antigenic phenotype and identifying determinants of antigenic drift. To overcome this, we developed nonlinear regression models that predict antigenic phenotype from genetic sequence data by training the model on hemagglutination inhibition assay results. We used these models to predict antigenic phenotype for previously uncharacterized IAV, ranked the importance of genetic features for antigenic phenotype, and experimentally validated our predictions. Our model predicted virus antigenic characteristics from genetic sequence data and provides a rapid and accurate method linking genetic sequence data to antigenic characteristics. This approach also provides support for public health by identifying viruses that are antigenically advanced from strains used as pandemic preparedness candidate vaccine viruses.