BackgroundInfluenza A Virus (IAV) causes respiratory disease in swine and is a zoonotic pathogen. Uncontrolled IAV in swine herds not only affects animal health, it also impacts production through increased costs associated with treatment and prevention efforts. The Iowa State University Veterinary Diagnostic Laboratory (ISU VDL) diagnoses influenza respiratory disease in swine and provides epidemiological analyses on samples submitted by veterinarians.DescriptionTo assess the incidence of IAV in swine and inform stakeholders, the ISU FLUture website was developed as an interactive visualization tool that allows the exploration of the ISU VDL swine IAV aggregate data in the clinical diagnostic database. The information associated with diagnostic cases has varying levels of completeness and is anonymous, but minimally contains: sample collection date, specimen type, and IAV subtype. Many IAV positive samples are sequenced, and in these cases, the hemagglutinin (HA) sequence and genetic classification are completed. These data are collected and presented on ISU FLUture in near real-time, and more than 6,000 IAV positive diagnostic cases and their epidemiological and evolutionary information since 2003 are presented to date. The database and web interface provides rapid and unique insight into the trends of IAV derived from both large- and small-scale swine farms across the United States of America.ConclusionISU FLUture provides a suite of web-based tools to allow stakeholders to search for trends and correlations in IAV case metadata in swine from the ISU VDL. Since the database infrastructure is updated in near real-time and is integrated within a high-volume veterinary diagnostic laboratory, earlier detection is now possible for emerging IAV in swine that subsequently cause vaccination and control challenges. The access to real-time swine IAV data provides a link with the national USDA swine IAV surveillance system and allows veterinarians to make objective decisions regarding the management and control of IAV in swine. The website is publicly accessible at http://influenza.cvm.iastate.edu.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2408-7) contains supplementary material, which is available to authorized users.

Influenza vaccines historically have been multivalent, whole virus inactivated products. The first bivalent, intranasal, live attenuated influenza vaccine (LAIV; Ingelvac Provenza), with H1N1 and H3N2 subtypes, has been approved for use in swine. We investigated the LAIV hemagglutinin ( HA) sequences in diagnostic cases submitted to the Iowa State University Veterinary Diagnostic Laboratory and potential vaccine virus reassortment with endemic influenza A virus (IAV) in swine. From January 3 to October 11, 2018, IAV HA sequences demonstrating 99.5–99.9% nucleotide homology to the H1 HA or 99.4–100% nucleotide homology to the H3 HA parental strains in the LAIV were detected in 58 of 1,116 (5.2%) porcine respiratory cases (H1 HA A/swine/Minnesota/37866/1999[H1N1; MN99]; H3 HA A/swine/Texas/4199-2/1998[H3N2; TX98]). Nine cases had co-detection of HA genes from LAIV and wild-type IAV in the same specimen. Thirty-five cases had associated epidemiologic information that indicated they were submitted from 11 states representing 31 individual sites and 17 production systems in the United States. Whole genome sequences from 11 cases and another subset of 2 plaque-purified IAV were included in our study. Ten whole genome sequences, including 1 plaque-purified IAV, contained at least one internal gene from endemic IAV detected within the past 3 y. Phylogenetic analysis of whole genome sequences indicated that reassortment occurred between vaccine virus and endemic field strains circulating in U.S. swine. Our data highlight the need and importance of continued IAV surveillance to detect emerging IAV with LAIV genes in the swine population.

Objectives: To assess patients with different types of mutations of the β myosin heavy chain (β MHC) gene causing hypertrophic cardiomyopathy (HCM) and to determine the prognosis of patients according to the affected functional domain of β MHC. Design and setting: Cohort study of subjects referred to an HCM clinic at an academic hospital. Patients: 70 probands from the HCM clinic were screened for mutations of the β MHC gene and 148 family members of the genotype positive probands were further assessed. The control group for the genetic studies consisted of 106 healthy subjects. Main outcome measures: Direct DNA sequencing was used to screen 70 probands for mutations of the β MHC gene. Family members underwent genotypic and detailed clinical, ECG, and echocardiographic assessments. The survival of genotype positive subjects was evaluated according to the type of functional domain affected by the missense mutation and according to phenotypic characteristics. Results: A mutation of the β MHC gene was detected in 15 of 70 probands (21%). Of 148 family members studied in these 15 families, 74 were identified with a β MHC defect. Eleven mutations were detected, including four novel mutations: Ala196Thr, Pro211Leu, Val404Leu, and Arg870Cys. Median survival was 66 years (95% confidence interval (CI) 64 to 77 years) in all affected subjects. There was a significant difference in survival between subjects according to the affected functional domain (p = 0.02). Significant independent predictors of decreased survival were the non-conservative (that is, associated with a change in the amino acid charge) missense mutations that affected the actin binding site (hazard ratio 4.4, 95% CI 1.6 to 11.8; p = 0.003) and those that affected the rod portion of β MHC (hazard ratio 4.8, 95% CI 1.2 to 19.4; p = 0.03). No phenotypic characteristics were associated with decreased survival or cardiovascular morbidity. Conclusions: The type of β MHC functional domain affected by the missense mutation is predictive of overall prognosis in HCM.H ypertrophic cardiomyopathy (HCM) is a primary and clinically diverse cardiac disorder that is caused by a defect in one of 10 genes encoding proteins of the myofibrillar apparatus: β myosin heavy chain (β MHC), α myosin heavy chain, myosin binding protein C, troponin T, α tropomyosin, troponin I, myosin essential light chain 1, myosin regulatory light chain 2, α cardiac actin, or titin. [1][2][3] There is significant genetic heterogeneity in HCM with more than 150 mutations now implicated in its pathogenesis. The β MHC gene was the first gene identified with this condition.6 Defects of the β MHC gene account for the largest proportion of cases of HCM and many of the initial genotypephenotype correlative studies of HCM were based on subjects with defects of β MHC. Certain mutations have been associated with a significantly shorter life expectancy in patients with HCM. 4 7-10 However, the associations between specific genotypes and overall prognosis are based on findings from a limited number of familie...

The diversity of the 8 genes of influenza A viruses (IAV) in swine reflects introductions from nonswine hosts and subsequent antigenic drift and shift. Here, we curated a data set and present a pipeline that assigns evolutionary lineage and genetic clade to query gene segments.

In the past decade, different members of the genus Mamastrovirus have been associated with outbreaks of neurologic disease in humans, cattle, sheep, mink, and, most recently, porcine astrovirus 3 (PoAstV3) in swine. We performed a retrospective analysis of 50 cases of porcine neurologic disease of undetermined cause but with microscopic lesions compatible with a viral encephalomyelitis to better understand the role and pathogenesis of PoAstV3 infection. Nucleic acid was extracted from formalin-fixed paraffin-embedded (FFPE) tissue for reverse transcription quantitative polymerase chain reaction (RT-qPCR) testing for PoAstV3. In addition, 3 cases with confirmed PoAstV3-associated disease were assayed by RT-qPCR to investigate PoAstV3 tissue distribution. PoAstV3 was detected in central nervous system (CNS) tissue via RT-qPCR and in situ hybridization in 13 of 50 (26%) FFPE cases assayed. PoAstV3 was rarely detected in any tissues outside the CNS. Positive cases from the retrospective study included pigs in various production categories beginning in 2010, the earliest year samples were available. Based on these results, PoAstV3 appears to be a recurring putative cause of viral encephalomyelitis in swine that is rarely detected outside of the CNS at the time of clinical neurologic disease, unlike other common viral causes of neurologic disease in swine.

Although antigenic motifs were largely associated with antigenic distances, substantial diversity among co-circulating viruses poses a significant challenge for effective vaccine development. Continued surveillance and antigenic characterization of circulating strains is critical for improving vaccine efforts to control C-IV H3 IAV in U.S. swine.

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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.