Biology subjects

Arendsee, Z. W.

Publications and source records attributed to Arendsee, Z. W..

5 recordsLinked to original sources

bioRxiv2025

Sources and sinks of influenza A virus genomic diversity in swine from 2009 to 2022 in the United States

Influenza A virus (IAV) in swine in the U.S. is surveilled to monitor genetic evolution to inform intervention efforts and aid pandemic preparedness. We describe data from the U.S. Department of Agriculture National Surveillance Plan for Influenza A Virus in Pigs from 2009 to 2022. Clinical respiratory cases were subtyped followed by sequencing of hemagglutinin (HA) and neuraminidase (NA), and a subset of viruses were whole genome sequenced. Phylogenetic analysis identified geographic and temporal IAV reassortment hotspots. Regions acting as IAV genomic diversity sources or sinks were quantified, and dissemination was qualified and modeled. The dominant IAV clades were H1N2 (1B.2.1), H3N2 (1990.4.a), and H1N1 (H1-1A.3.3.3-c3). Internal genes were classified as triple-reassortant (T) or pandemic 2009 (P), and three genome constellations represented 73.5% of detections across the last two years. In some years, the distribution of IAV diversity was so narrowly distributed that it presented a statistical signal associated with local adaptation. We also demonstrated that the source of most IAV genomic diversity was in Midwest states (IL, MO, IA), and while this was correlated with swine inventory, the emergence and persistence of diversity was tied to swine transport across the U.S. The continued regional detection of unique HA, NA, and genome constellations provides support for targeted interventions to improve animal health and enhance pandemic preparedness. ImportanceVariation in the genetic diversity of influenza A virus (IAV) in swine through time and between regions impacts control efforts. This study quantified the genomic diversity of swine IAV collected from 2009-2022 at regional and national levels and modeled sources and sinks of that diversity. Seasonal patterns of IAV transmission were observed, and some locations contributed disproportionately to the emergence of genomic diversity. Minor groups of viruses had the potential to disseminate across the U.S. with animal movement. The identification of these patterns demonstrates the importance of a robust surveillance system to inform vaccine updates that reflect regional patterns of genetic diversity. We show how preemptive interventions in swine IAV diversity hubs could reduce reassortment and the emergence of novel genomic diversity, and how these efforts are likely to reduce the transmission of swine IAV within swine and between swine and humans.

microbiology↗

bioRxiv2022

Reverse-zoonoses of 2009 H1N1 pandemic influenza A viruses and evolution in United States swine results in viruses with zoonotic potential

The 2009 H1N1 pandemic (pdm09) lineage of influenza A virus (IAV) crosses interspecies barriers with frequent human-to-swine spillovers each year. These spillovers reassort and drift within swine populations, leading to genetically and antigenically novel IAV that represent a zoonotic threat. We quantified interspecies transmission of the pdm09 lineage, persistence in swine, and identified how evolution in swine impacted zoonotic risk. Human and swine pdm09 case counts between 2010 and 2020 were correlated and human pdm09 burden and circulation directly impacted the detection of pdm09 in pigs. However, there was a relative absence of pdm09 circulation in humans during the 2020-21 season that was not reflected in swine. During the 2020-21 season, most swine pdm09 detections originated from human-to-swine spillovers from the 2018-19 and 2019-20 seasons that persisted in swine. We identified contemporary swine pdm09 representatives of each persistent spillover and quantified cross-reactivity between human seasonal H1 vaccine strains and the swine strains using a panel of monovalent ferret antisera in hemagglutination inhibition (HI) assays. The swine pdm09s had variable antigenic reactivity to vaccine antisera, but each swine pdm09 clade exhibited significant reduction in cross-reactivity to one or more of the human seasonal vaccine strains. Further supporting zoonotic risk, we showed phylogenetic evidence for 17 swine-to-human transmission events of pdm09 from 2010 to 2021, 11 of which were not previously classified as variants, with each of the zoonotic cases associated with persistent circulation of pdm09 in pigs. These data demonstrate that reverse-zoonoses and evolution of pdm09 in swine results in viruses that are capable of zoonotic transmission and represent a potential pandemic threat. Author SummaryThe diversity and evolution of influenza A virus (IAV) in pigs is linked to the emergence of IAV with pandemic potential. Human-to-swine transmission of the 2009 H1N1 pandemic (pdm09) IAV lineage repeatedly occurred across the past decade and has increased genetic diversity in pigs: sporadic swine-to-human cases are associated with these viruses. We measured the frequency of human-to-swine transmission of the H1N1 pandemic IAV lineage between 2009 and 2021 and determined how this affected the diversity of IAV in swine and zoonotic risk. We detected 371 separate human-to-swine spillovers, with the frequency of interspecies transmission increasing when the burden of IAV was highest in the human population. Most spillovers were single events without sustained transmission, but a small subset resulted in the emergence, persistence, and cocirculation of different pdm09 genetic clades in US pigs. Each of the pdm09 representative of different persistent spillovers was genetically and antigenically different from human seasonal vaccine strains. The persistence of pdm09 within pigs resulted in at least five recent swine-to-human transmission events. These data suggest that controlling IAV infection in humans working with swine can minimize spillover into pigs, reduce resulting genetic diversity of IAV in pigs, and proactively reduce the potential for swine-to-human transmission of IAV with pandemic potential.

microbiology↗

bioRxiv2022

Interspecies transmission from pigs to ferrets of antigenically distinct swine H1 influenza A viruses with loss in reactivity to human vaccine virus antisera as measures of relative zoonotic risk

During the last decade, endemic swine H1 influenza A viruses (IAV) from six different genetic clades of the hemagglutinin gene caused zoonotic infections in humans. The majority of zoonotic events with swine IAV were restricted to a single case with no subsequent transmission. However, repeated introduction of human-seasonal H1N1, continual reassortment between endemic swine IAV, and subsequent drift in the swine host resulted in highly diverse swine IAV with human-origin genes that may become a risk to the human population. To prepare for the potential of a future swine-origin IAV pandemic in humans, public health laboratories selected candidate vaccine viruses (CVV) for use as vaccine seed strains. To assess the pandemic risk of contemporary US swine H1N1 or H1N2 strains, we quantified the genetic diversity of swine H1 HA genes, and identified representative strains from each circulating clade. We then characterized the representative swine IAV against human seasonal vaccine and CVV strains using ferret antisera in hemagglutination inhibition assays (HI). HI assays revealed that 1A.3.3.2 (pdm) and 1B.2.1 (delta-2) demonstrated strong cross reactivity to human seasonal vaccines or CVVs. However, swine IAV from three clades that represent more than 50% of the detected swine IAVs in the USA showed significant reduction in cross-reactivity compared to the closest CVV virus: 1A.1.1.3 (alpha-deletion), 1A.3.3.3-clade 3 (gamma), and 1B.2.2.1 (delta-1a). Representative viruses from these three clades were further characterized in a pig-to-ferret transmission model and shown to exhibit variable transmission efficiency. Our data prioritize specific genotypes of swine H1N1 and H1N2 to further investigate in the risk they pose to the human population. ImportanceInfluenza A virus (IAV) is endemic in both humans and pigs and there is occasional bidirectional transmission of viruses. The process of interspecies transmission introduces novel viruses that increases the viral diversity in each host, impacting viral ecology and challenging control efforts through vaccine programs. Swine-origin IAVs have the potential to cause human pandemics, and pandemic preparation efforts include the identification and generation of candidate vaccine viruses (CVV) derived from epidemiologically relevant swine IAV surface proteins. The CVVs are derived from swine IAV detected and isolated in humans, and are updated infrequently; consequently the efficacy of these vaccines against contemporary swine IAV is unclear given rapid turnover and change of diversity. In this report we perform a risk assessment of contemporary swine H1 IAVs, determine whether current CVVs cross-react, and illustrate how swine-origin IAV replicate, transmit, and cause disease in a swine-to-ferret model system. In doing so, we identify the swine IAV that have lost cross-reactivity to current pandemic preparedness vaccines and demonstrate the utility of swine-to-ferret transmission experiments to further inform risk assessment.

microbiology↗

bioRxiv2022

classLog: Logistic regression for the classification of genetic sequences

Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in real-time genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output more rapidly than other classification methods. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog.

bioinformatics↗

bioRxiv2020

Machine learning prediction and experimental validation of antigenic drift in H3 influenza A viruses in swine

The antigenic diversity of influenza A virus (IAV) circulating in swine challenges the development of effective vaccines, increasing zoonotic threat and pandemic potential. High throughput sequencing technologies are able to quantify IAV genetic diversity, but there are no accurate approaches to adequately describe antigenic phenotypes. This study evaluated an ensemble of non-linear regression models to estimate virus phenotype from genotype. Regression models were trained with a phenotypic dataset 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. Error between predicted and measured distances of uncharacterized strains were 0.34, 0.70, 2.19, and 0.17 antigenic units. These empirically trained regression models can be used to estimate antigenic distances between different strains of IAV in swine 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.

bioinformatics↗