Genomic Characterization of Staphylococcus aureus in Wildlife.
Carmen Martínez-SeijasPatricia MascarósVictor M Lizana MartínAlba Martí-MarcoAlberto Arnau-BonacheraEva Chillida-MartínezJesús CardellsLaura SelvaDavid VianaJuan M CorpaPublished in: Animals : an open access journal from MDPI (2023)
Staphylococcus aureus is an opportunistic multi-host pathogen that threatens both human and animal health. Animals can act as a reservoir of S. aureus for humans, but very little is known about wild animals' epidemiological role. Therefore, in this study, we performed a genomic characterization of S. aureus isolates from wildlife, hunters, and their auxiliary hunting animals of Eastern Spain. Of 20 different species, 242 wild animals were examined, of which 28.1% were S. aureus carriers. The common genet, the Iberian ibex, and the European hedgehog were the species with the highest S. aureus carriage. We identified 30 different sequence types (STs), including lineages associated with wild animals such as ST49 and ST581, multispecies lineages such as ST130, ST398, and ST425, and lineages commonly isolated from humans, including ST1 and ST5. The hunters and the single positive ferret shared ST5, ST398, or ST425 with wild animals. In wildlife isolates, the highest resistance levels were found for penicillin (32.8%). For virulence factors, 26.2% of them carried superantigens, while 14.8% harbored the immune evasion cluster (IEC), which indicates probable human origin. Our findings suggest that wild animals are a reservoir of clinically relevant genes and lineages that could have the potential to be transmitted to humans. These data support the notion that wildlife surveillance is necessary to better understand the epidemiology of S. aureus as a pathogen that circulates among humans, animals, and the environment.
Keyphrases
- staphylococcus aureus
- genetic diversity
- healthcare
- public health
- endothelial cells
- escherichia coli
- gene expression
- copy number
- biofilm formation
- health information
- dna methylation
- artificial intelligence
- transcription factor
- genome wide
- antimicrobial resistance
- induced pluripotent stem cells
- risk factors
- deep learning