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- W3000309623 abstract "Persisters are a subpopulation of cells that have enhanced abilities to survive antibiotics and other stressful conditions. Recently, it was found that when persisters were repeatedly regrown and retreated with the same antibiotic for several cycles, the new population will become tolerant to the drug. In this study, we applied such cyclic antibiotic treatment on Escherichia coli populations using different classes of antibiotics (ampicillin, ciprofloxacin, and apramycin) during the exponential phase. After a few cycles, we observed that the evolved populations exhibit high tolerance to the specific class of antibiotic used during the evolution experiments, which are achieved by single-point mutations in one or several genes. Interestingly, all evolved populations show multidrug tolerance at the stationary phase, indicating that they have higher triggered persister fraction. Proteomic analysis and cross-comparison of the regulated proteomes of the tolerant populations during the stationary phase identified protein candidates with similar expression profiles that might be important for the tolerance phenotype. Susceptibility tests of mutants lacking gene coding for these protein candidates showed that they have significantly reduced survival toward antibiotics not only during the stationary phase, but also during the exponential phase. We demonstrated how proteomics, combined with cyclic antibiotic treatment as a means to enrich tolerant populations, is a promising avenue to obtain fresh insights into the phenomenon of persistence." @default.
- W3000309623 created "2020-01-23" @default.
- W3000309623 creator A5010704175 @default.
- W3000309623 creator A5085021194 @default.
- W3000309623 date "2020-01-10" @default.
- W3000309623 modified "2023-10-16" @default.
- W3000309623 title "Proteomic Investigation of Tolerant <i>Escherichia coli</i> Populations from Cyclic Antibiotic Treatment" @default.
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- W3000309623 doi "https://doi.org/10.1021/acs.jproteome.9b00687" @default.
- W3000309623 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31920087" @default.
- W3000309623 hasPublicationYear "2020" @default.
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