| Abstrakt: |
Monitoring the prevalence of antimicrobial resistance genes (ARGs) is vital for addressing the global crisis of antibiotic-resistant bacterial infections. Despite its importance, the characterization of ARGs and microbiome structures, as well as the identification of indicators for routine ARG monitoring in pig farms, are still lacking, particularly concerning variations in antimicrobial exposure in different countries or regions. Here, metagenomics and random forest machine learning were used to elucidate the ARG profiles, microbiome structures, and ARG contamination indicators in pig manure under different antimicrobial pressures between China and Europe. Results showed that Chinese pigs exposed to high-level antimicrobials exhibited higher total and plasmid-mediated ARG abundances compared to those in European pigs (P<0.05). ANT(6)-Ib, APH(3')-IIIa, and tet(40) were identified as shared core ARGs between the two pig populations. Furthermore, the core ARGs identified in pig populations were correlated with those found in human populations within the same geographical regions. Lactobacillus and Prevotella were identified as the dominant genera in the core microbiomes of Chinese and European pigs, respectively. Forty ARG markers and 43 biomarkers were able to differentiate between the Chinese and European pig manure samples with accuracies of 100% and 98.7%, respectively. Indicators for assessing ARG contamination in Chinese and European pigs also achieved high accuracy (r=0.72–0.88). Escherichia flexneri in both Chinese and European pig populations carried between 21 and 37 ARGs. The results of this study emphasize the importance of global collaboration in reducing antimicrobial resistance risk and provide validated indicators for evaluating the risk of ARG contamination in pig farms. [ABSTRACT FROM AUTHOR] |
