Monitoring longitudinal antimicrobial resistance trends of Staphylococcus aureus strains worldwide over the past 100 years to decipher its evolution and transmission

JOURNAL OF HAZARDOUS MATERIALS(2024)

引用 0|浏览7
暂无评分
摘要
Staphylococcus aureus inhabits diverse habitats including food waste and wastewater treatment plants. Cases of S. aureus-induced infection are commonly reported worldwide. The emergence of antimicrobial resistance (AMR) of S. aureus is a growing public health threat worldwide. Here, we longitudinally monitored global trends in antibiotic resistance genes (ARGs) of 586 S. aureus strains, isolated between 1884 and 2022. The ARGs in S. aureus exhibited a significant increase over time (P < 0.0001). Mobile genetic elements play a crucial role in the transfer of ARGs in S. aureus strains. The structural equation model results revealed a significant correlation between the human development index and rising antibiotic consumption, which subsequently leads to an in-direct escalation of AMR in S. aureus strains. Lastly, a machine learning algorithm successfully predicted the AMR risk of global terrestrial S. aureus with over 70% accuracy. Overall, these findings provided valuable insights for managing AMR in S. aureus.
更多
查看译文
关键词
Staphylococcus aureus,Genomic analysis,Antimicrobial resistance,Mobile genetic elements,Machine learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要