Theory of periodic swarming of bacteria: Application to Proteus mirabilis - art. no. 031915

Citation
A. Czirok et al., Theory of periodic swarming of bacteria: Application to Proteus mirabilis - art. no. 031915, PHYS REV E, 6303(3), 2001, pp. 1915
Citations number
29
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Physics
Journal title
PHYSICAL REVIEW E
ISSN journal
1063-651X → ACNP
Volume
6303
Issue
3
Year of publication
2001
Part
1
Database
ISI
SICI code
1063-651X(200103)6303:3<1915:TOPSOB>2.0.ZU;2-W
Abstract
The periodic swarming of bacteria is one of the simplest examples for patte rn formation produced by the self-organized collective behavior of a large number of organisms. In the spectacular colonies of Proteus mirabilis (the most common species exhibiting this type of growth), a series of concentric rings are developed as the bacteria multiply and swarm following a scenari o that periodically repeats itself. We have developed a theoretical descrip tion for this process in order to obtain a deeper insight into some of the typical processes governing the phenomena in systems of many interacting li ving units. Our approach is based on simple assumptions directly related to the latest experimental observations on colony formation under various con ditions. The corresponding one-dimensional model consists of two coupled di fferential equations investigated here both by numerical integrations and b y analyzing the various expressions obtained from these equations using a f ew natural assumptions about the parameters of the model. We determine the phase diagram corresponding to systems exhibiting periodic swarming, and di scuss in detail how the various stages of the colony development can be int erpreted in our framework. We point out that all of our theoretical results are in excellent agreement with the complete set of available observations . Thus the present study represents one of the few examples where self-orga nized biological pattern formation is understood within a relatively simple theoretical approach, leading to results and predictions fully compatible with experiments.