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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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Local Order Measuring Domain
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pcbi-0030253-g009: Local Order Measuring Domain

Mentions: We first define two local measuring components to describe the local orientational order and positional order of a given cell, denoted as Ψ and P, respectively. For a given cell k (k = 1,2…M, M is the total cell number), we choose the rectangular domain (of area s0) illustrated in Figure 9 as the local measuring domain (one cell length by two cell lengths), centered at the center of mass of a cell. We then measure the total area S occupied by neighboring cells within the local measuring domain and define the local positional order as the following:


Social interactions in myxobacterial swarming.

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

Local Order Measuring Domain
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-0030253-g009: Local Order Measuring Domain
Mentions: We first define two local measuring components to describe the local orientational order and positional order of a given cell, denoted as Ψ and P, respectively. For a given cell k (k = 1,2…M, M is the total cell number), we choose the rectangular domain (of area s0) illustrated in Figure 9 as the local measuring domain (one cell length by two cell lengths), centered at the center of mass of a cell. We then measure the total area S occupied by neighboring cells within the local measuring domain and define the local positional order as the following:

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