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监测过去 100 年来全球金黄色葡萄球菌菌株的纵向抗菌耐药趋势,以破译其进化和传播。

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

机构信息

College of Food and Health, Zhejiang A&F University, Hangzhou 311300, PR China; National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, PR China.

College of Food and Health, Zhejiang A&F University, Hangzhou 311300, PR China; National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, PR China.

出版信息

J Hazard Mater. 2024 Mar 5;465:133136. doi: 10.1016/j.jhazmat.2023.133136. Epub 2023 Dec 1.

Abstract

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 indirect 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.

摘要

金黄色葡萄球菌栖息于多种生境,包括食物垃圾和废水处理厂。金黄色葡萄球菌引起的感染病例在全球范围内屡有报道。金黄色葡萄球菌对抗生素耐药性(AMR)的出现是全球日益严重的公共卫生威胁。在这里,我们纵向监测了 586 株金黄色葡萄球菌菌株的抗生素耐药基因(ARGs)的全球趋势,这些菌株分别于 1884 年至 2022 年期间分离得到。金黄色葡萄球菌中的 ARGs 随时间呈显著增加趋势(P<0.0001)。移动遗传元件在金黄色葡萄球菌菌株中 ARGs 的转移中发挥着关键作用。结构方程模型的结果表明,人类发展指数与抗生素消费的上升之间存在显著相关性,这进而导致金黄色葡萄球菌菌株的 AMR 间接升级。最后,机器学习算法成功预测了全球陆地金黄色葡萄球菌的 AMR 风险,准确率超过 70%。总的来说,这些发现为管理金黄色葡萄球菌的 AMR 提供了有价值的见解。

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