Occurrence of multidrug-resistant methicillin-resistant Staphylococcus aureus among healthy farm animals: a public health concern

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is an emerging pathogen causing serious public health threats. This study was conducted to investigate the occurrence of multidrug-resistant MRSA among apparently healthy farm animals to shed the light on the potential role of these animals as a reservoir for such pathogen. For this purpose, 195 nasal swabs from apparently healthy farm animals (52 sheep, 51 goats, 47 cattle and 45 buffalo) were screened for multidrug-resistant MRSA. MRSA was isolated using a selective chromogenic medium and identified by colonial characters, Gram's stain films, conventional biochemical tests, coagulase test, resistance to cefoxitin and amplification of nuc and mecA genes. The antimicrobial susceptibility testing profile was performed by disk diffusion method to identify multidrug-resistant MRSA. Of 195 samples, 7 yielded MRSA with an overall prevalence 3.6%, whereas the prevalence rates were 3.8%, 3.9%, 4.3% and 2.2% for sheep, goats, cattle and buffalo, respectively. All MRSA isolates were multidrug-resistant strains. The phylogenetic analysis of 2 mecA gene sequences from the obtained isolates revealed that both sequences were clustered in the same clade with those derived from human clinical cases from different countries to highlight the public health burden of such strains. The distribution of multidrug-resistant MRSA among all examined farm animal species being apparently healthy points out that farm animals could represent a potential reservoir for multidrug-resistant MRSA with public health implications.

Keywords: MRSA; farm animals; multidrug resistance; public health.

Figure 1.

Molecular detection of mecA gene among multidrug-resistant MRSA strains. Lane M, DNA ladder 100 bp; lane 1 negative control; Lanes 2, 3, 4, 5 positive samples showed specific bands at 776 bp.

Figure 2.

Phylogenetic consensus tree shows the evolutionary history of the obtained sequences. The analysis was carried out through neighbour-joining approach using Mega 7 software and based on the partial sequence of mecA gene.