Characterizing and Evaluating the Zoonotic Potential of Novel Viruses Discovered in Vampire Bats

The contemporary surge in metagenomic sequencing has transformed knowledge of viral diversity wildlife. However, evaluating which newly discovered viruses pose sufficient risk infecting humans to merit detailed laboratory characterization and surveillance remains largely speculative. Machine learning algorithms have been developed address this imbalance by ranking the relative likelihood human infection based on genome sequences, but are not yet routinely applied at time their discovery. Here, we characterized genomes detected through feces saliva from common vampire bats (Desmodus rotundus) used these data as a case study zoonotic potential using molecular data. Of 58 families, including 17 infect mammals, only known zoonosis was rabies virus; however, additional were families Hepeviridae, Coronaviridae, Reoviridae, Astroviridae Picornaviridae, all contain human-infecting species. In phylogenetic analyses, novel bat most frequently grouped with other that currently humans. agreement, machine models built information ranked similarly, yielding little insight into potential. contrast, composition-based estimated different levels potential, even for closely related viruses, categorizing one out four hepeviruses two three picornaviruses having high priority further research. We highlight value beyond ad hoc consideration phylogeny provide recommendations wildlife host frequent contact domestic animals.