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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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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. |
format | Online Article Text |
id | pubmed-6249734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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