Molecular Characterization of Staphylococcus aureus Isolated from Raw Milk Samples of Dairy Cows in Manhiça District, Southern Mozambique.
Nilsa NhatsaveMarcelino GarrineAugusto Messa JuniorArsénia J MassingaAnélsio CossaRaúl VazAngelina OmbiTomás F ZimbaHélder AlfredoInácio MandomandoCesaltina TchamoPublished in: Microorganisms (2021)
Staphylococcal infections are among the most common foodborne diseases. We performed the antibiotic susceptibility and molecular characterization of S. aureus from milk samples of dairy cows in Manhiça District. We observed a high frequency of S. aureus (41%, 58/143), in which 71% (41/58) were from commercial farms and 29% (17/58) from smallholder farms. Half of the isolates (50%, 29/58) were resistant to at least one antibiotic, with higher rates of resistance to penicillin (43%, 25/58), followed by tetracycline (16%, 9/58). Multidrug-resistant and methicillin-resistant S. aureus isolates were rare (5%, 3/58 and 3%, 2/58, respectively). The genetic diversity was low, with predominance of human-adapted strains being: ST1/CC1-t5388 (78%) and ST152-t1299 (10%), followed by ST8/CC8-t1476 (5%) and ST5/CC5-t002 (3%) and lastly, ST508/CC45-t331 and ST152-t355, with 2% each. The Panton-Valentine leukocidin (PVL) gene was detected among 14% (8/58) of the isolates, while genes encoding staphylococcal enterotoxins were scarce (3%, 2/58). Our findings revealed a high frequency of S. aureus, with high rates of resistance to the antibiotics commonly used in veterinary and human medicine. Further investigations focusing on the molecular epidemiology of S. aureus from cattle and farmers will provide detailed insights on the genetic relatedness between the strains.
Keyphrases
- staphylococcus aureus
- high frequency
- genetic diversity
- dairy cows
- methicillin resistant staphylococcus aureus
- transcranial magnetic stimulation
- biofilm formation
- multidrug resistant
- endothelial cells
- genome wide
- escherichia coli
- copy number
- drug resistant
- dna methylation
- pluripotent stem cells
- bioinformatics analysis
- transcription factor