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.

Characterizing a century of genetic diversity and contemporary antigenic diversity of N1 neuraminidase in influenza A virus from North American swine

Influenza A viruses (IAVs) of the H1N1 classical swine lineage became endemic in North American swine following the 1918 pandemic. Additional human-to-swine transmission events after 1918, and a spillover of H1 viruses from wild birds in Europe, potentiated a rapid increase in genomic diversity via reassortment between introductions and the endemic classical swine lineage. To determine mechanisms affecting reassortment and evolution, we conducted a phylogenetic analysis of N1 and paired HA swine IAV genes in North America between 1930 and 2020. We described fourteen N1 clades within the N1 Eurasian avian lineage (including the N1 pandemic clade), the N1 classical swine lineage, and the N1 human seasonal lineage. Seven N1 genetic clades had evidence for contemporary circulation. To assess antigenic drift associated with N1 genetic diversity, we generated a panel of representative swine N1 antisera and quantified the antigenic distance between wild-type viruses using enzyme-linked lectin assays and antigenic cartography. Within the N1 genes, the antigenic similarity was variable and reflected shared evolutionary history. Sustained circulation and evolution of N1 genes in swine had resulted in a significant antigenic distance between the N1 pandemic clade and the classical swine lineage. Between 2010 and 2020, N1 clades and N1–HA pairings fluctuated in detection frequency across North America, with hotspots of diversity generally appearing and disappearing within 2 years. We also identified frequent N1–HA reassortment events (n = 36), which were rarely sustained (n = 6) and sometimes also concomitant with the emergence of new N1 genetic clades (n = 3). These data form a baseline from which we can identify N1 clades that expand in range or genetic diversity that may impact viral phenotypes or vaccine immunity and subsequently the health of North American swine.

Swine-to-Ferret Transmission of Antigenically Drifted Contemporary Swine H3N2 Influenza A Virus Is an Indicator of Zoonotic Risk to Humans

Human-to-swine transmission of influenza A (H3N2) virus occurs repeatedly and plays a critical role in swine influenza A virus (IAV) evolution and diversity. Human seasonal H3 IAVs were introduced from human-to-swine in the 1990s in the United States and classified as 1990.1 and 1990.4 lineages; the 1990.4 lineage diversified into 1990.4.A-F clades. Additional introductions occurred in the 2010s, establishing the 2010.1 and 2010.2 lineages. Human zoonotic cases with swine IAV, known as variant viruses, have occurred from the 1990.4 and 2010.1 lineages, highlighting a public health concern. If a variant virus is antigenically drifted from current human seasonal vaccine (HuVac) strains, it may be chosen as a candidate virus vaccine (CVV) for pandemic preparedness purposes. We assessed the zoonotic risk of US swine H3N2 strains by performing phylogenetic analyses of recent swine H3 strains to identify the major contemporary circulating genetic clades. Representatives were tested in hemagglutination inhibition assays with ferret post-infection antisera raised against existing CVVs or HuVac viruses. The 1990.1, 1990.4.A, and 1990.4.B.2 clade viruses displayed significant loss in cross-reactivity to CVV and HuVac antisera, and interspecies transmission potential was subsequently investigated in a pig-to-ferret transmission study. Strains from the three lineages were transmitted from pigs to ferrets via respiratory droplets, but there were differential shedding profiles. These data suggest that existing CVVs may offer limited protection against swine H3N2 infection, and that contemporary 1990.4.A viruses represent a specific concern given their widespread circulation among swine in the United States and association with multiple zoonotic cases.

Machine Learning Prediction and Experimental Validation of Antigenic Drift in H3 Influenza A Viruses in Swine

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.

Swine Influenza A Viruses and the Tangled Relationship with Humans

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.

Raising orphans from a metadata morass: A researcher's guide to re-use of public 'omics data

More than 15 petabases of raw RNAseq data is now accessible through public repositories. Acquisition of other 'omics data types is expanding, though most lack a centralized archival repository. Data-reuse provides tremendous opportunity to extract new knowledge from existing experiments, and offers a unique opportunity for robust, multi-'omics analyses by merging metadata (information about experimental design, biological samples, protocols) and data from multiple experiments. We illustrate how predictive research can be accelerated by meta-analysis with a study of orphan (species-specific) genes. Computational predictions are critical to infer orphan function because their coding sequences provide very few clues. The metadata in public databases is often confusing; a test case with Zea mays mRNA seq data reveals a high proportion of missing, misleading or incomplete metadata. This metadata morass significantly diminishes the insight that can be extracted from these data. We provide tips for data submitters and users, including specific recommendations to improve metadata quality by more use of controlled vocabulary and by metadata reviews. Finally, we advocate for a unified, straightforward metadata submission and retrieval system.

QQS orphan gene regulates carbon and nitrogen partitioning across species via NF-YC interactions

The allocation of carbon and nitrogen resources to the synthesis of plant proteins, carbohydrates, and lipids is complex and under the control of many genes; much remains to be understood about this process. QQS (Qua-Quine Starch; At3g30720), an orphan gene unique to Arabidopsis thaliana, regulates metabolic processes affecting carbon and nitrogen partitioning among proteins and carbohydrates, modulating leaf and seed composition in Arabidopsis and soybean. Here the universality of QQS function in modulating carbon and nitrogen allocation is exemplified by a series of transgenic experiments. We show that ectopic expression of QQS increases soybean protein independent of the genetic background and original protein content of the cultivar. Furthermore, transgenic QQS expression increases the protein content of maize, a C4 species (a species that uses 4-carbon photosynthesis), and rice, a protein-poor agronomic crop, both highly divergent from Arabidopsis. We determine that QQS protein binds to the transcriptional regulator AtNF-YC4 (Arabidopsis nuclear factor Y, subunit C4). Overexpression of AtNF-YC4 in Arabidopsis mimics the QQS-overexpression phenotype, increasing protein and decreasing starch levels. NF-YC, a component of the NF-Y complex, is conserved across eukaryotes. The NF-YC4 homologs of soybean, rice, and maize also bind to QQS, which provides an explanation of how QQS can act in species where it does not occur endogenously. These findings are, to our knowledge, the first insight into the mechanism of action of QQS in modulating carbon and nitrogen allocation across species. They have major implications for the emergence and function of orphan genes, and identify a nontransgenic strategy for modulating protein levels in crop species, a trait of great agronomic significance.

Coming of age: orphan genes in plants

Sizable minorities of protein-coding genes from every sequenced eukaryotic and prokaryotic genome are unique to the species. These so-called ‘orphan genes’ may evolve de novo from non-coding sequence or be derived from older coding material. They are often associated with environmental stress responses and species-specific traits or regulatory patterns. However, difficulties in studying genes where comparative analysis is impossible, and a bias towards broadly conserved genes, have resulted in underappreciation of their importance. We review here the identification, possible origins, evolutionary trends, and functions of orphans with an emphasis on their role in plant biology. We exemplify several evolutionary trends with an analysis of Arabidopsis thaliana and present QQS as a model orphan gene.