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Monitoring longitudinal antimicrobial resistance trends of Staphylococcus aureus strains worldwide over the past 100 years to decipher its evolution and transmission.
Fang, Guan-Yu; Wu, Feng-Hua; Mu, Xiao-Jing; Jiang, Yu-Jian; Liu, Xing-Quan.
Afiliação
  • Fang GY; 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. Electronic address: fangguanyu@zafu.edu.cn.
  • Wu FH; 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.
  • Mu XJ; School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, PR China.
  • Jiang YJ; School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, PR China.
  • Liu XQ; 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. Electronic address: liuxq@zafu.edu.cn.
J Hazard Mater ; 465: 133136, 2024 Mar 05.
Article em En | MEDLINE | ID: mdl-38056258
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infecções Estafilocócicas / Eliminação de Resíduos Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infecções Estafilocócicas / Eliminação de Resíduos Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article