Modeling Branching and Chiral Colonial Patterning of Lubricating Bacteria

  • Eshel Ben-Jacob
  • Inon Cohen
  • Ido Golding
  • Yonathan Kozlovsky
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 121)


In nature, microorganisms must often cope with hostile environmental conditions. To do so they have developed sophisticated cooperative behavior and intricate communication capabilities, such as: direct cell-cell physical interactions via extramembrane polymers, collective production of extracellular “wetting” fluid for movement on hard surfaces, long range chemical signaling such as quorum sensing and chemotactic (bias of movement according to gradient of chemical agent) signaling, collective activation and deactivation of genes and even exchange of genetic material. Utilizing these capabilities, the colonies develop complex spatio-temporal patterns in response to adverse growth conditions. We present a wealth of branching and chiral patterns formed during colonial development of lubricating, swimming bacteria (bacteria that produce a wetting layer of fluid so they can swim in it). Invoking ideas from pattern formation in non-living systems and using “generic” modeling we are able to reveal novel survival strategies which account for the salient features of the evolved patterns. Using the models, we demonstrate how communication leads to self-organization via cooperative behavior of the cells. In this regard, pattern formation in microorganisms can be viewed as the result of the exchange of information between the micro-level (the individual cells) and the macro-level (the colony). We mainly review known results, but include a new model of chiral growth, which enables us to study the effect of chemotactic signaling on the chiral growth. We also introduce a measure for weak chirality and use this measure to compare the results of model simulations with experimental observations.


Agar Concentration Bacterial Coloni Bacterial Density Chemotactic Signaling High Agar Concentration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Eshel Ben-Jacob
    • 1
  • Inon Cohen
    • 1
  • Ido Golding
    • 1
  • Yonathan Kozlovsky
    • 1
  1. 1.School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact SciencesTel Aviv UniversityTel AvivIsrael

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