Your browser doesn't support javascript.
loading
Low-Level Cefepime Exposure Induces High-Level Resistance in Environmental Bacteria: Molecular Mechanism and Evolutionary Dynamics.
Wang, Hanqing; Feng, Youjun; Lu, Huijie.
Afiliación
  • Wang H; College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
  • Feng Y; Departments of Microbiology & General Intensive Care Unit of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
  • Lu H; College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
Environ Sci Technol ; 56(21): 15074-15083, 2022 11 01.
Article en En | MEDLINE | ID: mdl-35608924
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, Comamonas testosteroni 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 dnaE2 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.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / Antibacterianos Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / Antibacterianos Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2022 Tipo del documento: Article País de afiliación: China
...