Abstract
Background: The poultry industry is one of the most rapidly growing sectors, producing the highest amount of animal-derived protein per unit time while also being the second-largest consumer of antibiotics. The widespread and accelerating spread of antimicrobial resistance (AMR) underscores the necessity of regular monitoring studies. Periodic assessments, especially focusing on commensal strains, can serve as indicators of emerging resistance patterns. Methods: This study assesses the antimicrobial susceptibility profiles of putative commensal Staphylococcus strains (n = 166) isolated from large-scale turkey flocks in Hungary using minimal inhibitory concentration (MIC) determination. The isolated strains were tested against antibiotics of veterinary and public health importance. The results were analyzed using the Kruskal-Wallis test and the Mann-Whitney U test, as well as t-tests. Additionally, correlation analysis and principal component analysis were performed. Results: Our findings revealed the highest resistance rates to tiamulin (90.4%), doxycycline (79.5%), and enrofloxacin (68.7%). Conclusions: These results reflect the extensive antibiotic use in the poultry sector, which contributes to the widespread presence of antimicrobial resistance. As regular monitoring and the identification of trends can aid in mitigating the spread of resistance, these findings should be complemented by data on antibiotic usage at the surveyed farms in further studies. The observed resistance rate of 18.1% to vancomycin is particularly concerning from a public health perspective, given that comparative human data show only a 0.05% resistance rate. Additionally, for multidrug-resistant strains, next-generation sequencing should be utilized to elucidate the genetic mechanisms underlying resistance, particularly in strains exhibiting high levels of resistance to vancomycin, which is of critical importance in human medicine, as well as to the critically important enrofloxacin and the widely used doxycycline and tiamulin. However, the limitations of the study should also be acknowledged, including the relatively small sample size, which is significantly lower than that of available human data, as well as the spatial distribution of the samples.