Modeling Non-inherited Antibiotic Resistance

A mathematical model is presented for the increase and decrease of non-inherited antibiotic resistance levels in bacteria. The model is applied to experimental data on E. coli exposed to amoxicillin or tetracyclin in different concentrations. The parameters of the model are estimated using a Monte C...

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Detalles Bibliográficos
Autores principales: Bootsma, M. C. J., van der Horst, M. A., Guryeva, T., ter Kuile, B. H., Diekmann, O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2012
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3390703/
https://www.ncbi.nlm.nih.gov/pubmed/22610796
http://dx.doi.org/10.1007/s11538-012-9731-3
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author Bootsma, M. C. J.
van der Horst, M. A.
Guryeva, T.
ter Kuile, B. H.
Diekmann, O.
author_facet Bootsma, M. C. J.
van der Horst, M. A.
Guryeva, T.
ter Kuile, B. H.
Diekmann, O.
author_sort Bootsma, M. C. J.
collection PubMed
description A mathematical model is presented for the increase and decrease of non-inherited antibiotic resistance levels in bacteria. The model is applied to experimental data on E. coli exposed to amoxicillin or tetracyclin in different concentrations. The parameters of the model are estimated using a Monte Carlo Markov Chain method. The model accurately describes build-up and decline of antibiotic resistance caused by physiological adaptations as long as no genetic changes have occurred. The main conclusion of the analysis is that short time periods are sufficient to re-obtain low MIC-values after long-lasting exposure to these antibiotics.
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spelling pubmed-33907032012-07-11 Modeling Non-inherited Antibiotic Resistance Bootsma, M. C. J. van der Horst, M. A. Guryeva, T. ter Kuile, B. H. Diekmann, O. Bull Math Biol Original Article A mathematical model is presented for the increase and decrease of non-inherited antibiotic resistance levels in bacteria. The model is applied to experimental data on E. coli exposed to amoxicillin or tetracyclin in different concentrations. The parameters of the model are estimated using a Monte Carlo Markov Chain method. The model accurately describes build-up and decline of antibiotic resistance caused by physiological adaptations as long as no genetic changes have occurred. The main conclusion of the analysis is that short time periods are sufficient to re-obtain low MIC-values after long-lasting exposure to these antibiotics. Springer-Verlag 2012-05-19 2012 /pmc/articles/PMC3390703/ /pubmed/22610796 http://dx.doi.org/10.1007/s11538-012-9731-3 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Original Article
Bootsma, M. C. J.
van der Horst, M. A.
Guryeva, T.
ter Kuile, B. H.
Diekmann, O.
Modeling Non-inherited Antibiotic Resistance
title Modeling Non-inherited Antibiotic Resistance
title_full Modeling Non-inherited Antibiotic Resistance
title_fullStr Modeling Non-inherited Antibiotic Resistance
title_full_unstemmed Modeling Non-inherited Antibiotic Resistance
title_short Modeling Non-inherited Antibiotic Resistance
title_sort modeling non-inherited antibiotic resistance
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3390703/
https://www.ncbi.nlm.nih.gov/pubmed/22610796
http://dx.doi.org/10.1007/s11538-012-9731-3
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