Genetic and Antigenic Characterization of an Expanding H3 Influenza A Virus Clade in U.S. Swine Visualized by Nextstrain.

Defining factors that influence spatial and temporal patterns of influenza A virus (IAV) is essential to inform vaccine strain selection and strategies to reduce the spread of potentially zoonotic swine-origin IAV. The relative frequency of detection of the H3 phylogenetic clade 1990.4.a (colloquially known as C-IVA) in U.S. swine declined to 7% in 2017 but increased to 32% in 2019. We conducted phylogenetic and phenotypic analyses to determine putative mechanisms associated with increased detection. We created an implementation of Nextstrain to visualize the emergence, spatial spread, and genetic evolution of H3 IAV in swine, identifying two C-IVA clades that emerged in 2017 and cocirculated in multiple U.S. states. Phylodynamic analysis of the hemagglutinin (HA) gene documented low relative genetic diversity from 2017 to 2019, suggesting clonal expansion. The major H3 C-IVA clade contained an N156H amino acid substitution, but hemagglutination inhibition (HI) assays demonstrated no significant antigenic drift. The minor HA clade was paired with the neuraminidase (NA) clade N2-2002B prior to 2016 but acquired and maintained an N2-2002A in 2016, resulting in a loss of antigenic cross-reactivity between N2-2002B- and -2002A-containing H3N2 strains. The major C-IVA clade viruses acquired a nucleoprotein (NP) of the H1N1pdm09 lineage through reassortment in the replacement of the North American swine-lineage NP. Instead of genetic or antigenic diversity within the C-IVA HA, our data suggest that population immunity to H3 2010.1 along with the antigenic diversity of the NA and the acquisition of the H1N1pdm09 NP gene likely explain the reemergence and transmission of C-IVA H3N2 in swine. IMPORTANCE Genetically distinct clades of influenza A virus (IAV) in swine undermine efforts to control the disease. Swine producers commonly use vaccines, and vaccine strains are selected by identifying the most common hemagglutinin (HA) gene from viruses detected in a farm or a region. In 2019, we identified an increase in the detection frequency of an H3 phylogenetic clade, C-IVA, which was previously circulating at much lower levels in U.S. swine. Our study identified genetic and antigenic factors contributing to its resurgence by linking comprehensive phylodynamic analyses with empirical wet-lab experiments and visualized these evolutionary analyses in a Nextstrain implementation. The contemporary C-IVA HA genes did not demonstrate an increase in genetic diversity or significant antigenic changes. N2 genes did demonstrate antigenic diversity, and the expanding C-IVA clade acquired a nucleoprotein (NP) gene segment via reassortment. Virus phenotype and vaccination targeting prior dominant HA clades likely contributed to the clade's success.

Characterization of Two Porcine Parainfluenza Virus 1 Isolates and Human Parainfluenza Virus 1 Infection in Weaned Nursery Pigs.

Porcine parainfluenza virus 1 (PPIV1) is a newly characterized porcine respiratory virus. Recent experimental challenge studies in three-week-old nursery pigs failed to cause disease. However, it remains unclear how genetic differences contribute to viral pathogenesis. To characterize the pathogenesis of different PPIV1 isolates, three-week-old nursery pigs were challenged with either PPIV1 isolate USA/MN25890NS/2016 (MN16) or USA/IA84915LG/2017 (IA17). A human parainfluenza virus 1 (HPIV1) strain C35 ATCC® VR-94™ was included to evaluate swine as a model for human parainfluenza. All viruses were successfully re-isolated from bronchoalveolar lavage fluid and detected by RT-qPCR at necropsy. Microscopic lung lesions were more severe in the IA17 group compared to the non-challenged negative control (Ctrl) group whereas differences were not found between the MN16 and Ctrl groups. Immunohistochemistry staining in respiratory samples showed a consistent trend of higher levels of PPIV1 signal in the IA17 group followed by the MN16 group, and no PPIV1 signal observed in the HPIV1 or Ctrl groups. This study suggests potential pathogenesis differences between PPIV1 isolates. Additionally, these results indicate that HPIV1 is capable of replicating in nursery pigs after experimental inoculation. However, clinical disease or gross lung lesions were not observed in any of the challenge groups.

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. This is a cross-disciplinary challenge, involving genomics, proteomics, immunology, and computational approaches. We have built a computational framework called pVACtools that, when paired with a well-established genomics pipeline, produces an end-to-end solution for neoantigen characterization. pVACtools supports identification of altered peptides from different mechanisms, including point mutations, in-frame and frameshift insertions and deletions, and gene fusions. Prediction of peptide:MHC binding is accomplished by supporting an ensemble of MHC Class I and II binding algorithms within a framework designed to facilitate the incorporation of additional algorithms. Prioritization of predicted peptides occurs by integrating diverse data, including mutant allele expression, peptide binding affinities, and determination whether a mutation is clonal or subclonal. Interactive visualization via a Web interface allows clinical users to efficiently generate, review, and interpret results, selecting candidate peptides for individual patient vaccine designs. Additional modules support design choices needed for competing vaccine delivery approaches. One such module optimizes peptide ordering to minimize junctional epitopes in DNA vector vaccines. Downstream analysis commands for synthetic long peptide vaccines are available to assess candidates for factors that influence peptide synthesis. All of the aforementioned steps are executed via a modular workflow consisting of tools for neoantigen prediction from somatic alterations (pVACseq and pVACfuse), prioritization, and selection using a graphical Web-based interface (pVACviz), and design of DNA vector-based vaccines (pVACvector) and synthetic long peptide vaccines. pVACtools is available at http://www.pvactools.org.