Self-organizing models of bacterial aggregation states

  • Received: 01 July 2007 Accepted: 29 June 2018 Published: 01 January 2008
  • MSC : Primary: 93C10, 81T80; Secondary: 46N60.

  • In this work, aggregation states of bacteria on engineered surfaces are investigated both from the experimental point of view and from the theo- retical one. The starting point of this work is a series of experiments carried out on abiotic surfaces in which bacteria adhere forming self-organized patterns. To reproduce the main characteristics of the phenomenon a model based on self-organization of a group of agents has been used. The agents represent bac- teria and are free to move on a given surface. On the basis of local rules they may adhere and then eventually form self-organized aggregates. Our numerical results demonstrate that few simple rules are able to explain the emergence of self-organized patterns. Depending on the parameters used, the model is able to reproduce the aggregation patterns observed under different experimental conditions and to predict the behavior of a culture of two bacterial species.

    Citation: Manuela Caratozzolo, Santina Carnazza, Luigi Fortuna, Mattia Frasca, Salvatore Guglielmino, Giovanni Gurrieri, Giovanni Marletta. Self-organizing models of bacterial aggregation states[J]. Mathematical Biosciences and Engineering, 2008, 5(1): 75-83. doi: 10.3934/mbe.2008.5.75

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  • In this work, aggregation states of bacteria on engineered surfaces are investigated both from the experimental point of view and from the theo- retical one. The starting point of this work is a series of experiments carried out on abiotic surfaces in which bacteria adhere forming self-organized patterns. To reproduce the main characteristics of the phenomenon a model based on self-organization of a group of agents has been used. The agents represent bac- teria and are free to move on a given surface. On the basis of local rules they may adhere and then eventually form self-organized aggregates. Our numerical results demonstrate that few simple rules are able to explain the emergence of self-organized patterns. Depending on the parameters used, the model is able to reproduce the aggregation patterns observed under different experimental conditions and to predict the behavior of a culture of two bacterial species.


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