Microorganisms (May 2021)
Molecular Characterization of Antimicrobial Resistance and Virulence Genes of Bacterial Pathogens from Bovine and Caprine Mastitis in Northern Lebanon
Abstract
Mastitis is an infectious disease encountered in dairy animals worldwide that is currently a growing concern in Lebanon. This study aimed at investigating the etiology of the main mastitis-causing pathogens in Northern Lebanon, determining their antimicrobial susceptibility profiles, and identifying their antimicrobial resistance (AMR) genes. A total of 101 quarter milk samples were collected from 77 cows and 11 goats presenting symptoms of mastitis on 45 dairy farms. Bacterial identification was carried out through matrix-assisted laser desorption/ionization-time of flight mass spectrometry. Antimicrobial susceptibility was tested by disc diffusion and broth microdilution methods. Molecular characterization included polymerase chain reaction (PCR) screening for genes encoding extended-spectrum beta-lactamases (ESBLs) and plasmid-mediated AmpC among Enterobacterales isolates, and virulence factors among Staphylococcus isolates. Escherichia coli isolates were subjected to phylogenetic typing by a quadruplex PCR method. The most frequently identified species were Streptococcus uberis (19.2%), Streptococcus agalactiae (15.1%), E. coli (12.3%), and Staphylococcus aureus (10.96%). Gram-positive bacteria were resistant to macrolides and tetracycline, whereas gram-negative bacteria displayed resistance to ampicillin and tetracycline. Two ESBL genes, blaTEM (83.3%) and blaOXA (16.7%), and one AmpC beta-lactamase gene, blaCMY-II (16.7%), were detected among six E. coli isolates, which mainly belonged to phylogenetic group B1. Among Staphylococcus spp., the mecA gene was present in three isolates. Furthermore, four isolates contained at least one toxin gene, and all S. aureus isolates carried the ica operon. These findings revealed the alarming risk of AMR in the Lebanese dairy chain and the importance of monitoring antimicrobial usage.
Keywords