Zhang Zhaoyang, Wei Minliang, Jia Bin, Yuan Yingjin
Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China.
Microorganisms. 2024 Dec 31;13(1):51. doi: 10.3390/microorganisms13010051.
Antimicrobial resistance (AMR) represents a critical global health threat, and a thorough understanding of resistance mechanisms in is needed to guide effective treatment interventions. This review explores recent advances for investigating AMR in , including machine learning for resistance pattern analysis, laboratory evolution to generate resistant mutants, mutant library construction, and genome sequencing for in-depth characterization. Key resistance mechanisms are discussed, including drug inactivation, target modification, altered transport, and metabolic adaptation. Additionally, we highlight strategies to mitigate the spread of AMR, such as dynamic resistance monitoring, innovative therapies like phage therapy and CRISPR-Cas technology, and tighter regulation of antibiotic use in animal production systems. This review provides actionable insights into resistance mechanisms and identifies promising directions for future antibiotic development and AMR management.
抗菌耐药性(AMR)是对全球健康的一项重大威胁,需要深入了解其耐药机制以指导有效的治疗干预措施。本综述探讨了在研究AMR方面的最新进展,包括用于耐药模式分析的机器学习、生成耐药突变体的实验室进化、突变体文库构建以及用于深入表征的基因组测序。文中讨论了关键的耐药机制,包括药物失活、靶点修饰、转运改变和代谢适应。此外,我们强调了减轻AMR传播的策略,如动态耐药监测、噬菌体疗法和CRISPR-Cas技术等创新疗法,以及对动物生产系统中抗生素使用的更严格监管。本综述为耐药机制提供了可操作的见解,并确定了未来抗生素开发和AMR管理的有前景的方向。