Open AccessWhole genome sequencing identifies zoonotic transmission of MRSA isolates with the novel mecA homologue mecC
Author(s) -
Harrison Ewan M.,
Paterson Gavin K.,
Holden Matthew T.G.,
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.
Publication year - 2013
Publication title -
embo molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.923
H-Index - 107
eISSN - 1757-4684
pISSN - 1757-4676
DOI - 10.1002/emmm.201202413
Subject(s) - biology , context (archaeology) , genome , phylogenetic tree , whole genome sequencing , molecular epidemiology , genetics , staphylococcus aureus , virulence , sccmec , transmission (telecommunications) , methicillin resistant staphylococcus aureus , microbiology and biotechnology , gene , genotype , bacteria , paleontology , engineering , electrical engineering
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.