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Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach

BACKGROUND: A microorganism is a complex biological system able to preserve its functional features against external perturbations and the ability of the living systems to oppose to these external perturbations is defined “robustness”. The antibiotic resistance, developed by different bacteria strai...

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Detalles Bibliográficos
Autores principales: Autiero, Ida, Costantini, Susan, Colonna, Giovanni
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2707609/
https://www.ncbi.nlm.nih.gov/pubmed/19593454
http://dx.doi.org/10.1371/journal.pone.0006226
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author Autiero, Ida
Costantini, Susan
Colonna, Giovanni
author_facet Autiero, Ida
Costantini, Susan
Colonna, Giovanni
author_sort Autiero, Ida
collection PubMed
description BACKGROUND: A microorganism is a complex biological system able to preserve its functional features against external perturbations and the ability of the living systems to oppose to these external perturbations is defined “robustness”. The antibiotic resistance, developed by different bacteria strains, is a clear example of robustness and of ability of the bacterial system to acquire a particular functional behaviour in response to environmental changes. In this work we have modeled the whole mechanism essential to the methicillin-resistance through a systems biology approach. The methicillin is a β-lactamic antibiotic that act by inhibiting the penicillin-binding proteins (PBPs). These PBPs are involved in the synthesis of peptidoglycans, essential mesh-like polymers that surround cellular enzymes and are crucial for the bacterium survival. METHODOLOGY: The network of genes, mRNA, proteins and metabolites was created using CellDesigner program and the data of molecular interactions are stored in Systems Biology Markup Language (SBML). To simulate the dynamic behaviour of this biochemical network, the kinetic equations were associated with each reaction. CONCLUSIONS: Our model simulates the mechanism of the inactivation of the PBP by methicillin, as well as the expression of PBP2a isoform, the regulation of the SCCmec elements (SCC: staphylococcal cassette chromosome) and the synthesis of peptidoglycan by PBP2a. The obtained results by our integrated approach show that the model describes correctly the whole phenomenon of the methicillin resistance and is able to respond to the external perturbations in the same way of the real cell. Therefore, this model can be useful to develop new therapeutic approaches for the methicillin control and to understand the general mechanism regarding the cellular resistance to some antibiotics.
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spelling pubmed-27076092009-07-13 Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach Autiero, Ida Costantini, Susan Colonna, Giovanni PLoS One Research Article BACKGROUND: A microorganism is a complex biological system able to preserve its functional features against external perturbations and the ability of the living systems to oppose to these external perturbations is defined “robustness”. The antibiotic resistance, developed by different bacteria strains, is a clear example of robustness and of ability of the bacterial system to acquire a particular functional behaviour in response to environmental changes. In this work we have modeled the whole mechanism essential to the methicillin-resistance through a systems biology approach. The methicillin is a β-lactamic antibiotic that act by inhibiting the penicillin-binding proteins (PBPs). These PBPs are involved in the synthesis of peptidoglycans, essential mesh-like polymers that surround cellular enzymes and are crucial for the bacterium survival. METHODOLOGY: The network of genes, mRNA, proteins and metabolites was created using CellDesigner program and the data of molecular interactions are stored in Systems Biology Markup Language (SBML). To simulate the dynamic behaviour of this biochemical network, the kinetic equations were associated with each reaction. CONCLUSIONS: Our model simulates the mechanism of the inactivation of the PBP by methicillin, as well as the expression of PBP2a isoform, the regulation of the SCCmec elements (SCC: staphylococcal cassette chromosome) and the synthesis of peptidoglycan by PBP2a. The obtained results by our integrated approach show that the model describes correctly the whole phenomenon of the methicillin resistance and is able to respond to the external perturbations in the same way of the real cell. Therefore, this model can be useful to develop new therapeutic approaches for the methicillin control and to understand the general mechanism regarding the cellular resistance to some antibiotics. Public Library of Science 2009-07-13 /pmc/articles/PMC2707609/ /pubmed/19593454 http://dx.doi.org/10.1371/journal.pone.0006226 Text en Autiero et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Autiero, Ida
Costantini, Susan
Colonna, Giovanni
Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach
title Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach
title_full Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach
title_fullStr Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach
title_full_unstemmed Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach
title_short Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach
title_sort modeling of the bacterial mechanism of methicillin-resistance by a systems biology approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2707609/
https://www.ncbi.nlm.nih.gov/pubmed/19593454
http://dx.doi.org/10.1371/journal.pone.0006226
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