Analytical methods : advancing methods and applications · 2025
In-cell NMR reveals metabolic adaptations in central carbon pathways driving antibiotic tolerance in Salmonella Typhimurium.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zahid Alexandra L N, Wang Ke-Chuan, Thomsen Line Elnif, Meier Sebastian, Jensen Pernille Rose
Аннотация
Antibiotic tolerance presents a significant challenge in eradicating bacterial infections, as tolerant strains can survive antibiotic treatment, contributing to the recurrence of infections and the development of resistance. However, unlike antibiotic resistance, tolerance is not detectable by standard susceptibility assays such as minimal inhibitory concentration (MIC) tests. Consequently, antibiotic tolerance often goes unnoticed in clinical settings. Bacterial metabolism is closely linked to antibiotic efficacy, and thus presents as a potential target for novel diagnostic methods. Recent advancements in nuclear magnetic resonance (NMR) spectroscopy, including dynamic nuclear polarization (DNP-NMR), enable a non-invasive real-time approach to analyzing bacterial metabolism. In this study, we applied both 1H and in-cell 13C NMR spectroscopy to investigate metabolic adaptations in a tolerance-evolved Salmonella Typhimurium strain, C10, developed through ten cycles of ampicillin treatment. Our results demonstrated that despite similar MICs and growth rates, the C10 strain exhibited a 25-fold increase in tolerance compared to the wild-type, while exhibiting lower metabolic activity. Under ampicillin stress, however, the C10 strain maintained higher metabolic activity and demonstrated greater resilience in glucose consumption and metabolite production relative to the wild-type. Using DNP-NMR, rapid metabolic shifts in the C10 strain were identified within 10 minutes of exposure to high concentrations of ampicillin, characterized by accumulation of key metabolites such as pyruvate and acetate. Overall, our findings underscore the potential of real-time NMR-based analyses to provide deeper insights into antibiotic tolerance and distinguish between susceptible and tolerant bacterial strains.