Simple and accurate genomic classification model for distinguishing between human and pig Staphylococcus aureus

Autor: Huiliu Zhou, Wenyin Du, Dejia Ouyang, Yuehe Li, Yajie Gong, Zhenjiang Yao, Minghao Zhong, Xinguang Zhong, Xiaohua Ye
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Communications Biology, Vol 7, Iss 1, Pp 1-11 (2024)
Druh dokumentu: article
ISSN: 2399-3642
DOI: 10.1038/s42003-024-06883-2
Popis: Abstract Staphylococcus aureus (S. aureus) can cause various infections in humans and animals, contributing to high morbidity and mortality. To prevent and control cross-species transmission of S. aureus, it is necessary to understand the host-associated genetic variants. We performed a two-stage genome-wide association study (GWAS) including initial screening and further validation to compare genomic differences between human and pig S. aureus, aiming to identify host-associated determinants. Our multiple GWAS analyses found six consensus significant k-mers associated with host species, providing novel genetic evidence for distinguishing human from pig S. aureus. The best k-mer predictor achieved a high classification accuracy of 98.12% on its own and had extremely high resolution similar to the SNPs-based phylogeny, offering a very simple target for predicting the cross-species transmission risk of S. aureus. The final k-mer model revealed that 90% of S. aureus isolates from farm workers were predicted as livestock origin, suggesting a high risk of cross-species transmission. Bayesian inference revealed different cross-species transmission directions, with the human-to-pig transmission for ST5 and the pig-to-human transmission for ST398. Our findings provide a simple and accurate k-mer model for identifying and predicting the cross-species transmission risk of S. aureus.
Databáze: Directory of Open Access Journals
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