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使用彩色混合 Petri 网和模拟模型检查进行空间群体感应建模。

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

机构信息

Department of Computer Science, Brunel University London, Uxbridge, UB8 3PH, UK.

Computer Science Department, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, D-03046, Germany.

出版信息

BMC Bioinformatics. 2019 Apr 18;20(Suppl 4):173. doi: 10.1186/s12859-019-2690-z.

Abstract

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.

摘要

背景

群体感应驱动细菌生物膜的形成,以确保只有当菌落达到足够的大小和密度时才会发生生物膜的形成。这种空间行为是通过在扩散场景中广播自动诱导物来实现的。当考虑肠道微生物群在肠道健康中的作用时,这一行为尤其有趣。这种行为发生在细菌生长的四个阶段的背景下,特别是在自动诱导物产生的指数阶段(第 2 阶段)和生物膜形成的静止阶段(第 3 阶段)。

结果

我们已经使用彩色混合 Petri 网逐步开发了一个灵活的计算模型,用于由 Autoinducer 2(AI-2)驱动的 E.coli 生物膜的形成,该模型易于针对不同的空间概念进行配置。该模型描述了基因转录、信号转导、细胞内外运输的基本组成部分,以及系统的两相性质。我们建立在之前发表的关于 AI-2 产生的非空间随机 Petri 网模型的基础上,保持了有限营养环境的假设,以及我们在 NETTAB 2017 研讨会上首次提出的生物膜形成的空间混合 Petri 网模型。首先,我们分别考虑没有空间的两个模型,然后将它们组合起来,最后添加空间。我们详细描述了我们逐步的模型开发和验证。我们的模拟结果支持了这样的预期行为,即生物膜的形成在细菌菌落大小和密度较高的区域增加。我们的分析技术包括基于线性时间时态逻辑的行为检查。

结论

我们的建模和分析方法的优点是描述了群体感应和相关的生物膜形成,涵盖了细菌生长的两个阶段,同时考虑了使用灵活且易于维护的计算模型的细菌空间分布。所有的计算结果都是可重复的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1618/6471779/e448ecf88be8/12859_2019_2690_Fig1_HTML.jpg

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