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Social interactions in myxobacterial swarming.

Wu Y, Jiang Y, Kaiser D, Alber M - PLoS Comput. Biol. (2007)

Bottom Line: Also, the model is able to quantify the contributions of S motility and A motility to swarming.Some pathogenic bacteria spread over infected tissue by swarming.The model described here may shed some light on their colonization process.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, University of Notre Dame, Notre Dame, Indiana, United States of America.

ABSTRACT
Swarming, a collective motion of many thousands of cells, produces colonies that rapidly spread over surfaces. In this paper, we introduce a cell-based model to study how interactions between neighboring cells facilitate swarming. We chose to study Myxococcus xanthus, a species of myxobacteria, because it swarms rapidly and has well-defined cell-cell interactions mediated by type IV pili and by slime trails. The aim of this paper is to test whether the cell contact interactions, which are inherent in pili-based S motility and slime-based A motility, are sufficient to explain the observed expansion of wild-type swarms. The simulations yield a constant rate of swarm expansion, which has been observed experimentally. Also, the model is able to quantify the contributions of S motility and A motility to swarming. Some pathogenic bacteria spread over infected tissue by swarming. The model described here may shed some light on their colonization process.

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Time Evolution of the Global Order Parameter(A) Plots of the order parameter Ω for the simulation of swarming near colony edge with initial cell density of 50 K-S units.(B) Plot of the ratio of global order parameters for A+S+ and A+S− swarms.
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pcbi-0030253-g010: Time Evolution of the Global Order Parameter(A) Plots of the order parameter Ω for the simulation of swarming near colony edge with initial cell density of 50 K-S units.(B) Plot of the ratio of global order parameters for A+S+ and A+S− swarms.

Mentions: The order parameter Ω has been specifically designed for myxobacterial swarming. Figure 10 shows values of Ω for the simulation of swarming near colony edge with initial cell density of 50 K-S units. We find that the order of collective motion in both A+S+ and A+S− swarms steadily increase, and that A+S+ cells achieve a much higher (about 2-fold) order than A+S− cells.


Social interactions in myxobacterial swarming.

Wu Y, Jiang Y, Kaiser D, Alber M - PLoS Comput. Biol. (2007)

Time Evolution of the Global Order Parameter(A) Plots of the order parameter Ω for the simulation of swarming near colony edge with initial cell density of 50 K-S units.(B) Plot of the ratio of global order parameters for A+S+ and A+S− swarms.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2230681&req=5

pcbi-0030253-g010: Time Evolution of the Global Order Parameter(A) Plots of the order parameter Ω for the simulation of swarming near colony edge with initial cell density of 50 K-S units.(B) Plot of the ratio of global order parameters for A+S+ and A+S− swarms.
Mentions: The order parameter Ω has been specifically designed for myxobacterial swarming. Figure 10 shows values of Ω for the simulation of swarming near colony edge with initial cell density of 50 K-S units. We find that the order of collective motion in both A+S+ and A+S− swarms steadily increase, and that A+S+ cells achieve a much higher (about 2-fold) order than A+S− cells.

Bottom Line: Also, the model is able to quantify the contributions of S motility and A motility to swarming.Some pathogenic bacteria spread over infected tissue by swarming.The model described here may shed some light on their colonization process.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, University of Notre Dame, Notre Dame, Indiana, United States of America.

ABSTRACT
Swarming, a collective motion of many thousands of cells, produces colonies that rapidly spread over surfaces. In this paper, we introduce a cell-based model to study how interactions between neighboring cells facilitate swarming. We chose to study Myxococcus xanthus, a species of myxobacteria, because it swarms rapidly and has well-defined cell-cell interactions mediated by type IV pili and by slime trails. The aim of this paper is to test whether the cell contact interactions, which are inherent in pili-based S motility and slime-based A motility, are sufficient to explain the observed expansion of wild-type swarms. The simulations yield a constant rate of swarm expansion, which has been observed experimentally. Also, the model is able to quantify the contributions of S motility and A motility to swarming. Some pathogenic bacteria spread over infected tissue by swarming. The model described here may shed some light on their colonization process.

Show MeSH