Exploring genetic signatures of zoonotic influenza A virus at the swine-human interface with phylogenetic and ancestral sequence reconstruction

Authors: ANKER, KLARA - Staten Serum Institute; CIUCANI, MARTA - Staten Serum Institute; NISSEN, JAKOB - Staten Serum Institute; Anderson, Tavis; PEDERSEN, ANDERS - Technical University Of Denmark; TREBBIEN, RAMONA - Staten Serum Institute

Submitted to: Virus Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/25/2025
Publication Date: 4/26/2025
Citation: Anker, K.M., Ciucani, M.M., Nissen, J.N., Anderson, T.K., Pedersen, A.G., Trebbien, R., Exploring genetic signatures of zoonotic influenza A virus at the swine-human interface with phylogenetic and ancestral sequence reconstruction. Virus Evolution. 2025; veaf028. https://doi.org/10.1093/ve/veaf028.
DOI: https://doi.org/10.1093/ve/veaf028

Interpretive Summary: Human-to-swine influenza A virus (IAV) spillover events are relatively common and have led to the establishment of multiple virus lineages in the swine population worldwide, leading to important economic losses in the pork industry. The circulation of human IAV in swine also increases the risk of reassortment and emergence of novel viruses that retain the ability to infect and transmit in humans, an event exemplified by the H1N1 pandemic in 2009. However, the molecular changes driving IAV adaptation to pigs following the introduction of a human virus into the host and determining whether these changes impact the ability of the virus to be transmitted back to humans are not understood. In this study we conducted a comprehensive genetic analysis of swine and human IAV using machine learning and evolutionary techniques. We were able to demonstrate that evolutionary changes following movement of the virus from people to pigs, and pigs to people, varied across each of the eight IAV genes. Within each of the genes there were specific regions and amino acid positions that appeared to facilitate interspecies transmission. These data identify genetic signatures across the genome of IAV in swine that are associated with adaptation to the swine host and that impact zoonotic potential. These positions may be tracked and used as valuable markers for early-warning genomic surveillance systems to minimize the potential for zoonotic transmission.

Technical Abstract: Influenza A viruses (IAVs) in swine have zoonotic potential and pose a continuous threat of causing human pandemics, as demonstrated by the H1N1 pandemic in 2009. Despite increased genomic surveillance, we have limited knowledge of the IAV evolutionary dynamics leading to such zoonotic events and no clear understanding of genetic markers associated with interspecies transmission of IAV between humans and swine. To explore this, we analyzed a comprehensive publicly available whole genome dataset of human and swine IAV sequences. We conducted phylogenetic analyses and inference of ancestral host and sequence states for each IAV segment and mapped inferred mutations that were associated with transmission within and between swine and human hosts. We developed a custom python library to combine information from host and ancestral sequence annotated trees and applied statistical models to identify genetic markers associated with intra- or interspecies transmissions between swine and humans. This included analyzing mutation rates and the selective pressures acting on the viral proteins following intra- and interspecies transmissions and using a scalable, gradient-boosted decision tree machine learning approach to predict key amino acid positions critical for different transmission types. Our analyses indicated complex mutational patterns within and across viral proteins, but also suggested that specific protein regions and amino acid positions of especially several of the internal gene segments were more important for interspecies transmission. Our findings identify potential genetic signatures across the IAV proteins associated with host adaptation and zoonotic potential, offering valuable markers for early-warning genomic surveillance systems to enhance animal health and minimize the potential for zoonotic transmission of IAV.