Modeling antibiotic resistance in the microbiota using multi-level Petri Nets
| Autor: | Alfredo Benso, Roberta Bardini, Stefano Di Carlo, Gianfranco Politano |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Population level Computer science Antibiotic resistance Systems biology 030106 microbiology Population Computational biology Models Biological 03 medical and health sciences Mice Structural Biology PetriNets Escherichia coli Animals Heterogeneous information Petri Nets education Molecular Biology lcsh:QH301-705.5 Computational model education.field_of_study Acinetobacter Applied Mathematics Modelling biological systems Research Microbiota BIOINFORMATICS Drug Resistance Microbial Petri net Computer Science Applications Hybrid models Nets-Within-Nets 030104 developmental biology lcsh:Biology (General) Modeling and Simulation Computational systems biology Human microbiota PetriNets Nets-Within-Nets |
| Zdroj: | BMC Systems Biology BMC Systems Biology, Vol 12, Iss S6, Pp 59-79 (2018) |
| ISSN: | 1752-0509 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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