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Modeling antibiotic resistance in the microbiota using multi-level Petri Nets

BACKGROUND: The unregulated use of antibiotics not only in clinical practice but also in farm animals breeding is causing a unprecedented growth of antibiotic resistant bacterial strains. This problem can be analyzed at different levels, from the antibiotic resistance spreading dynamics at the host...

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Autores principales: Bardini, Roberta, Di Carlo, Stefano, Politano, Gianfranco, Benso, Alfredo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249734/
https://www.ncbi.nlm.nih.gov/pubmed/30463550
http://dx.doi.org/10.1186/s12918-018-0627-1
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author Bardini, Roberta
Di Carlo, Stefano
Politano, Gianfranco
Benso, Alfredo
author_facet Bardini, Roberta
Di Carlo, Stefano
Politano, Gianfranco
Benso, Alfredo
author_sort Bardini, Roberta
collection PubMed
description BACKGROUND: The unregulated use of antibiotics not only in clinical practice but also in farm animals breeding is causing a unprecedented growth of antibiotic resistant bacterial strains. This problem can be analyzed at different levels, from the antibiotic resistance spreading dynamics at the host population level down to the molecular mechanisms at the bacteria level. In fact, antibiotic administration policies and practices affect the societal system where individuals developing resistance interact with each other and with the environment. Each individual can be seen as a meta-organism together with its associated microbiota, which proves to have a prominent role in the resistance spreading dynamics. Eventually, in each microbiota, bacterial population dynamics and vertical or horizontal gene transfer events activate cellular and molecular mechanisms for resistance spreading that can also be possible targets for its prevention. RESULTS: In this work we show how to use the Nets-Within-Nets formalism to model the dynamics between different antibiotic administration protocols and antibiotic resistance, both at the individuals population and at the single microbiota level. Three application examples are presented to show the flexibility of this approach in integrating heterogeneous information in the same model, a fundamental property when creating computational models complex biological systems. Simulations allow to explicitly take into account timing and stochastic events. CONCLUSIONS: This work demonstrates how the NWN formalism can be used to efficiently model antibiotic resistance population dynamics at different levels of detail. The proposed modeling approach not only provides a valuable tool for investigating causal, quantitative relations between different events and mechanisms, but can be also used as a valid support for decision making processes and protocol development.
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spelling pubmed-62497342018-11-26 Modeling antibiotic resistance in the microbiota using multi-level Petri Nets Bardini, Roberta Di Carlo, Stefano Politano, Gianfranco Benso, Alfredo BMC Syst Biol Research BACKGROUND: The unregulated use of antibiotics not only in clinical practice but also in farm animals breeding is causing a unprecedented growth of antibiotic resistant bacterial strains. This problem can be analyzed at different levels, from the antibiotic resistance spreading dynamics at the host population level down to the molecular mechanisms at the bacteria level. In fact, antibiotic administration policies and practices affect the societal system where individuals developing resistance interact with each other and with the environment. Each individual can be seen as a meta-organism together with its associated microbiota, which proves to have a prominent role in the resistance spreading dynamics. Eventually, in each microbiota, bacterial population dynamics and vertical or horizontal gene transfer events activate cellular and molecular mechanisms for resistance spreading that can also be possible targets for its prevention. RESULTS: In this work we show how to use the Nets-Within-Nets formalism to model the dynamics between different antibiotic administration protocols and antibiotic resistance, both at the individuals population and at the single microbiota level. Three application examples are presented to show the flexibility of this approach in integrating heterogeneous information in the same model, a fundamental property when creating computational models complex biological systems. Simulations allow to explicitly take into account timing and stochastic events. CONCLUSIONS: This work demonstrates how the NWN formalism can be used to efficiently model antibiotic resistance population dynamics at different levels of detail. The proposed modeling approach not only provides a valuable tool for investigating causal, quantitative relations between different events and mechanisms, but can be also used as a valid support for decision making processes and protocol development. BioMed Central 2018-11-22 /pmc/articles/PMC6249734/ /pubmed/30463550 http://dx.doi.org/10.1186/s12918-018-0627-1 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Bardini, Roberta
Di Carlo, Stefano
Politano, Gianfranco
Benso, Alfredo
Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
title Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
title_full Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
title_fullStr Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
title_full_unstemmed Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
title_short Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
title_sort modeling antibiotic resistance in the microbiota using multi-level petri nets
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249734/
https://www.ncbi.nlm.nih.gov/pubmed/30463550
http://dx.doi.org/10.1186/s12918-018-0627-1
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