低水平头孢吡肟暴露诱导环境细菌高水平耐药:分子机制和进化动态。

Low-Level Cefepime Exposure Induces High-Level Resistance in Environmental Bacteria: Molecular Mechanism and Evolutionary Dynamics.

机构信息

College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.

Departments of Microbiology & General Intensive Care Unit of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.

出版信息

Environ Sci Technol. 2022 Nov 1;56(21):15074-15083. doi: 10.1021/acs.est.2c00793. Epub 2022 May 24.

Abstract

Antibiotics exert selective pressures on clinically relevant antibiotic resistance. It is critical to understand how antibiotic resistance evolves in environmental microbes exposed to subinhibitory concentrations of antibiotics and whether evolutionary dynamics and emergence of resistance are predictable. In this study, isolated from wastewater activated sludge were subcultured in a medium containing 10 ng/mL cefepime for 40 days (∼300 generations). Stepwise mutations were accumulated, leading to an ultimate 200-fold increase in the minimum inhibitory concentration (MIC) of cefepime. Early stage mutation in DNA polymerase-encoding gene played an important role in antibiotic resistance evolution. Diverse resistance mechanisms were employed and validated experimentally, including increased efflux, biofilm formation, reduced antibiotic uptake, and drug inactivation. The cefepime minimal selective concentrations (MSCs) and relative fitness of susceptible, intermediate, and resistant mutants were determined. Agent-based modeling of the modified Moran process enabled simulations of resistance evolution and predictions of the emergence time and frequency of resistant mutants. The unraveled cefepime resistance mechanisms could be employed by broader bacteria, and the newly developed model is applicable to the predictions of general resistance evolution. The improved knowledge facilitates the assessment, prediction, and mitigation of antibiotic resistance progression in antibiotic-polluted environments.

摘要

抗生素对临床相关抗生素耐药性产生选择性压力。了解在亚抑菌浓度的抗生素下暴露的环境微生物中抗生素耐药性如何演变,以及耐药性的进化动态和出现是否可预测,这一点至关重要。在这项研究中,从废水活性污泥中分离出的细菌在含有 10ng/mL 头孢吡肟的培养基中培养 40 天(约 300 代)。逐步积累突变,导致头孢吡肟的最小抑菌浓度(MIC)最终增加了 200 倍。DNA 聚合酶编码基因中的早期突变在抗生素耐药性进化中起着重要作用。实验验证了多种耐药机制,包括增加外排、生物膜形成、减少抗生素摄取和药物失活。确定了头孢吡肟的最小选择浓度(MSC)和敏感、中间和耐药突变体的相对适应性。基于代理的修正 Moran 过程模型能够模拟耐药性进化,并预测耐药突变体的出现时间和频率。揭示的头孢吡肟耐药机制可能被更广泛的细菌利用,新开发的模型适用于一般耐药性进化的预测。这一改进的认识有助于对抗生素污染环境中抗生素耐药性进展进行评估、预测和缓解。

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