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Whole genome sequencing identifies zoonotic transmission of MRSA isolates with the novel mecA homologue mecC

Several methicillin-resistant Staphylococcus aureus (MRSA) lineages that carry a novel mecA homologue (mecC) have recently been described in livestock and humans. In Denmark, two independent human cases of mecC-MRSA infection have been linked to a livestock reservoir. We investigated the molecular e...

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Detalles Bibliográficos
Autores principales: Harrison, Ewan M, Paterson, Gavin K, Holden, Matthew TG, Larsen, Jesper, Stegger, Marc, Larsen, Anders Rhod, Petersen, Andreas, Skov, Robert L, Christensen, Judit Marta, Bak Zeuthen, Anne, Heltberg, Ole, Harris, Simon R, Zadoks, Ruth N, Parkhill, Julian, Peacock, Sharon J, Holmes, Mark A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: WILEY-VCH Verlag 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628104/
https://www.ncbi.nlm.nih.gov/pubmed/23526809
http://dx.doi.org/10.1002/emmm.201202413
Descripción
Sumario:Several methicillin-resistant Staphylococcus aureus (MRSA) lineages that carry a novel mecA homologue (mecC) have recently been described in livestock and humans. In Denmark, two independent human cases of mecC-MRSA infection have been linked to a livestock reservoir. We investigated the molecular epidemiology of the associated MRSA isolates using whole genome sequencing (WGS). Single nucleotide polymorphisms (SNP) were defined and compared to a reference genome to place the isolates into a phylogenetic context. Phylogenetic analysis revealed two distinct farm-specific clusters comprising isolates from the human case and their own livestock, whereas human and animal isolates from the same farm only differed by a small number of SNPs, which supports the likelihood of zoonotic transmission. Further analyses identified a number of genes and mutations that may be associated with host interaction and virulence. This study demonstrates that mecC-MRSA ST130 isolates are capable of transmission between animals and humans, and underscores the potential of WGS in epidemiological investigations and source tracking of bacterial infections.