Toribio-Celestino Laura, San Millan Alvaro
Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain.
Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain; Centro de Investigación Biológica en Red de Epidemiología y Salud Pública, Instituto de Salud Carlos III, Madrid, Spain.
Trends Microbiol. 2025 Sep;33(9):937-947. doi: 10.1016/j.tim.2025.04.011. Epub 2025 May 14.
Antimicrobial resistance (AMR) is one of the most pressing global health problems, with plasmids playing a central role in its evolution and dissemination. Over the past decades, many studies have investigated the ecoevolutionary dynamics between plasmids and their bacterial hosts. However, what drives the epidemiological success of certain plasmid-bacterium associations remains unclear. In this opinion article, we review which factors influence these associations and underline that studying plasmid-host interactions of clinical relevance is critical for understanding the evolution and spread of AMR. We also highlight the increasing importance of integrating experimental research with bioinformatics and machine learning tools to study plasmid-bacteria dynamics. This combined approach will assist researchers to dissect the molecular mechanisms underlying successful plasmid-host associations and to design strategies to prevent and predict future high-risk associations.
抗菌药物耐药性(AMR)是最紧迫的全球健康问题之一,质粒在其演变和传播中起着核心作用。在过去几十年里,许多研究调查了质粒与其细菌宿主之间的生态进化动态。然而,驱动某些质粒 - 细菌组合在流行病学上取得成功的因素仍不清楚。在这篇观点文章中,我们回顾了哪些因素影响这些组合,并强调研究具有临床相关性的质粒 - 宿主相互作用对于理解AMR的演变和传播至关重要。我们还强调了将实验研究与生物信息学和机器学习工具相结合以研究质粒 - 细菌动态的重要性日益增加。这种综合方法将帮助研究人员剖析成功的质粒 - 宿主组合背后的分子机制,并设计预防和预测未来高风险组合的策略。