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Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking

BACKGROUND: Quorum sensing drives biofilm formation in bacteria in order to ensure that biofilm formation only occurs when colonies are of a sufficient size and density. This spatial behaviour is achieved by the broadcast communication of an autoinducer in a diffusion scenario. This is of interest,...

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Autores principales: Gilbert, David, Heiner, Monika, Ghanbar, Leila, Chodak, Jacek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471779/
https://www.ncbi.nlm.nih.gov/pubmed/30999841
http://dx.doi.org/10.1186/s12859-019-2690-z
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author Gilbert, David
Heiner, Monika
Ghanbar, Leila
Chodak, Jacek
author_facet Gilbert, David
Heiner, Monika
Ghanbar, Leila
Chodak, Jacek
author_sort Gilbert, David
collection PubMed
description BACKGROUND: Quorum sensing drives biofilm formation in bacteria in order to ensure that biofilm formation only occurs when colonies are of a sufficient size and density. This spatial behaviour is achieved by the broadcast communication of an autoinducer in a diffusion scenario. This is of interest, for example, when considering the role of gut microbiota in gut health. This behaviour occurs within the context of the four phases of bacterial growth, specifically in the exponential stage (phase 2) for autoinducer production and the stationary stage (phase 3) for biofilm formation. RESULTS: We have used coloured hybrid Petri nets to step-wise develop a flexible computational model for E.coli biofilm formation driven by Autoinducer 2 (AI-2) which is easy to configure for different notions of space. The model describes the essential components of gene transcription, signal transduction, extra and intra cellular transport, as well as the two-phase nature of the system. We build on a previously published non-spatial stochastic Petri net model of AI-2 production, keeping the assumptions of a limited nutritional environment, and our spatial hybrid Petri net model of biofilm formation, first presented at the NETTAB 2017 workshop. First we consider the two models separately without space, and then combined, and finally we add space. We describe in detail our step-wise model development and validation. Our simulation results support the expected behaviour that biofilm formation is increased in areas of higher bacterial colony size and density. Our analysis techniques include behaviour checking based on linear time temporal logic. CONCLUSIONS: The advantages of our modelling and analysis approach are the description of quorum sensing and associated biofilm formation over two phases of bacterial growth, taking into account bacterial spatial distribution using a flexible and easy to maintain computational model. All computational results are reproducible. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2690-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-64717792019-04-24 Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking Gilbert, David Heiner, Monika Ghanbar, Leila Chodak, Jacek BMC Bioinformatics Methodology BACKGROUND: Quorum sensing drives biofilm formation in bacteria in order to ensure that biofilm formation only occurs when colonies are of a sufficient size and density. This spatial behaviour is achieved by the broadcast communication of an autoinducer in a diffusion scenario. This is of interest, for example, when considering the role of gut microbiota in gut health. This behaviour occurs within the context of the four phases of bacterial growth, specifically in the exponential stage (phase 2) for autoinducer production and the stationary stage (phase 3) for biofilm formation. RESULTS: We have used coloured hybrid Petri nets to step-wise develop a flexible computational model for E.coli biofilm formation driven by Autoinducer 2 (AI-2) which is easy to configure for different notions of space. The model describes the essential components of gene transcription, signal transduction, extra and intra cellular transport, as well as the two-phase nature of the system. We build on a previously published non-spatial stochastic Petri net model of AI-2 production, keeping the assumptions of a limited nutritional environment, and our spatial hybrid Petri net model of biofilm formation, first presented at the NETTAB 2017 workshop. First we consider the two models separately without space, and then combined, and finally we add space. We describe in detail our step-wise model development and validation. Our simulation results support the expected behaviour that biofilm formation is increased in areas of higher bacterial colony size and density. Our analysis techniques include behaviour checking based on linear time temporal logic. CONCLUSIONS: The advantages of our modelling and analysis approach are the description of quorum sensing and associated biofilm formation over two phases of bacterial growth, taking into account bacterial spatial distribution using a flexible and easy to maintain computational model. All computational results are reproducible. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2690-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-18 /pmc/articles/PMC6471779/ /pubmed/30999841 http://dx.doi.org/10.1186/s12859-019-2690-z Text en © The Author(s) 2019 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 Methodology
Gilbert, David
Heiner, Monika
Ghanbar, Leila
Chodak, Jacek
Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking
title Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking
title_full Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking
title_fullStr Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking
title_full_unstemmed Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking
title_short Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking
title_sort spatial quorum sensing modelling using coloured hybrid petri nets and simulative model checking
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471779/
https://www.ncbi.nlm.nih.gov/pubmed/30999841
http://dx.doi.org/10.1186/s12859-019-2690-z
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