A P system model of swarming and aggregation in a Myxobacterial colony
A P system model of swarming and aggregation in a Myxobacterial colony
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DOI：
10.1007/s41965-019-00015-0
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发表时间：
2019-05
影响因子：
3.8
通讯作者：
A. Nash;Sara Kalvala
中科院分区：
文献类型：
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作者：
A. Nash;Sara Kalvala
细菌群落为研究作为许多局部相互作用的结果的出现和复杂性提供了一个有趣的课题。特别是，土壤中的社会细菌粘细菌表现出两种不同类型的运动，即通过感知细菌粘液沉积物的社会运动和冒险运动。两种运动模式均受局部相互作用控制。使用 P 系统，一种基于分区重写规则的膜计算方法，用于对计算过程进行建模；这项工作展示了如何用最小的规则集来模拟粘杆菌细菌群体中的集群和聚集行为。我们的模型使用类似于 2D 细胞自动机的多环境 P 系统来表示基质环境，同时随机规则选择根据体外观察到的行为决定粘细菌运动。这些规则考虑了运动机制、粘液的沉积和检测、C 信号感应引起的方向变化以及种群数量的混合。模拟展示了用于细菌行为建模的可扩展计算框架，并有可能扩展到其他突发行为。
Bacterial communities provide an interesting subject for the study of emergence and complexity as the consequence of many local interactions. In particular, the soil-dwelling social bacterium Myxobacteria demonstrates two distinct types of motility, social motility via the sensing of bacterial slime deposits and adventurous motility. Both modes of motility are governed by local interactions. Using P systems, a membrane computing methodology based on compartmental rewrite rules for modelling computational processes; this work demonstrates how minimal set of rules can model swarming and aggregating behaviour in Myxobacteria bacterial populations. Our model uses a multi-environment P system similar a 2D cellular automaton to represent the substrate environment whilst stochastic rule selection dictates Myxobacterial motion according to behaviour observed in vitro. The rules account for both mechanisms of motility, the deposit and detection of slime, a change in direction due to C-signal induction and the mixing of population numbers. Simulations demonstrate an extensible computational framework for the modelling of bacterial behaviour, with the potential for extension into additional emergent behaviours.