Literature DB >> 23363876

Interplay between population dynamics and drug tolerance of Staphylococcus aureus persister cells.

Sabrina Lechner1, Pintu Patra, Stefan Klumpp, Ralph Bertram.   

Abstract

Population dynamics parameters of Staphylococcus aureus strain SA113 were quantified based on growth and killing experiments with batch culture cells in rich medium. Eradication kinetics and the concomitant isolation of a subpopulation of drug-tolerant SA113 persisters upon treatment with super-minimal inhibitory concentrations of antibiotics such as ciprofloxacin, daptomycin, and tobramycin served as a basis for mathematical analyses. According to a two-state model for stochastic phenotype switching, levels of persister cells and their eradication rates were influenced by the antibiotics used for isolation, clearly indicating a heterogeneous pool of S. aureus persisters. Judging from time-dependent experiments, the persisters' degree of drug tolerance correlated with the duration of antibiotic challenge. Moreover, cross-tolerance experiments with cells consecutively treated with two different antibiotics revealed that multi-drug tolerance is not a necessary trait of S. aureus persisters isolated by antibiotic challenge. In some cases, the results depended on the order of the two antibiotic treatments, suggesting that antibiotic tolerance may be achieved by a combination of preexisting persisters and an adaptive response to drug exposure. Counts of live cells which had endured drug treatment increased only after lag phases of at least 3 h after the shift to non-selective conditions. Thus, this study provides quantitative insights into population dynamics of S. aureus persisters with regard to antibiotic challenge.
Copyright © 2013 S. Karger AG, Basel.

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Year:  2013        PMID: 23363876     DOI: 10.1159/000346073

Source DB:  PubMed          Journal:  J Mol Microbiol Biotechnol        ISSN: 1464-1801


  8 in total

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Authors:  Gabriel Carvalho; Damien Balestrino; Christiane Forestier; Jean-Denis Mathias
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5.  Relating switching rates between normal and persister cells to substrate and antibiotic concentrations: a mathematical modelling approach supported by experiments.

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6.  Identifying determinants of persistent MRSA bacteremia using mathematical modeling.

Authors:  Tsuyoshi Mikkaichi; Michael R Yeaman; Alexander Hoffmann
Journal:  PLoS Comput Biol       Date:  2019-07-11       Impact factor: 4.475

7.  Population dynamics of bacterial persistence.

Authors:  Pintu Patra; Stefan Klumpp
Journal:  PLoS One       Date:  2013-05-13       Impact factor: 3.240

8.  Transposon Mutagenesis Identifies Novel Genes Associated with Staphylococcus aureus Persister Formation.

Authors:  Wenjie Wang; Jiazhen Chen; Gang Chen; Xin Du; Peng Cui; Jing Wu; Jing Zhao; Nan Wu; Wenhong Zhang; Min Li; Ying Zhang
Journal:  Front Microbiol       Date:  2015-12-23       Impact factor: 5.640

  8 in total

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