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Dynamical Model of Drug Accumulation in Bacteria: Sensitivity Analysis and Experimentally Testable Predictions.
Vesselinova, Neda; Alexandrov, Boian S; Wall, Michael E.
Afiliación
  • Vesselinova N; Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America.
  • Alexandrov BS; University of California Los Angeles, Los Angeles, CA, 90095, United States of America.
  • Wall ME; Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America.
PLoS One ; 11(11): e0165899, 2016.
Article en En | MEDLINE | ID: mdl-27824914
ABSTRACT
We present a dynamical model of drug accumulation in bacteria. The model captures key features in experimental time courses on ofloxacin accumulation initial uptake; two-phase response; and long-term acclimation. In combination with experimental data, the model provides estimates of import and export rates in each phase, the time of entry into the second phase, and the decrease of internal drug during acclimation. Global sensitivity analysis, local sensitivity analysis, and Bayesian sensitivity analysis of the model provide information about the robustness of these estimates, and about the relative importance of different parameters in determining the features of the accumulation time courses in three different bacterial species Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The results lead to experimentally testable predictions of the effects of membrane permeability, drug efflux and trapping (e.g., by DNA binding) on drug accumulation. A key prediction is that a sudden increase in ofloxacin accumulation in both E. coli and S. aureus is accompanied by a decrease in membrane permeability.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / Antibacterianos / Modelos Biológicos Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / Antibacterianos / Modelos Biológicos Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos