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Experimentally guided computational model discovers important elements for social behavior in myxobacteria.

Hendrata M, Yang Z, Lux R, Shi W - PLoS ONE (2011)

Bottom Line: The simulation is able to produce both gliding pattern and spontaneous aggregation center formation as observed in experiments.The model is tested against several known M. xanthus mutants and our modification of parameter values relevant for the individual mutants produces good phenotypic agreements.This outcome indicates the strong predictive potential of our model for the social behaviors of uncharacterized mutants and their expected phenotypes during development.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, California State University Los Angeles, Los Angeles, California, United States of America. mhendra@calstatela.edu

ABSTRACT
Identifying essential factors in cellular interactions and organized movement of cells is important in predicting behavioral phenotypes exhibited by many bacterial cells. We chose to study Myxococcus xanthus, a soil bacterium whose individual cell behavior changes while in groups, leading to spontaneous formation of aggregation center during the early stage of fruiting body development. In this paper, we develop a cell-based computational model that solely relies on experimentally determined parameters to investigate minimal elements required to produce the observed social behaviors in M. xanthus. The model verifies previously known essential parameters and identifies one novel parameter, the active turning, which we define as the ability and tendency of a cell to turn to a certain angle without the presence of any obvious external factors. The simulation is able to produce both gliding pattern and spontaneous aggregation center formation as observed in experiments. The model is tested against several known M. xanthus mutants and our modification of parameter values relevant for the individual mutants produces good phenotypic agreements. This outcome indicates the strong predictive potential of our model for the social behaviors of uncharacterized mutants and their expected phenotypes during development.

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Simulation images of cells' gliding behavior showing the effect of various parameters to the gliding patterns.The following parameters listed in Table 1 are included in the model: (A) Basic cellular properties. (B) Basic cellular properties and polarity reversal. (C) Basic cellular properties, polarity reversal and quorum sensing. (D) Basic cellular properties, polarity reversal, quorum sensing and EPS slime production and following. (E) Basic cellular properties, polarity reversal, quorum sensing, EPS slime production and following, and active turning. (F) Experimental image of wild-type cells and their gliding pattern. All simulations start with 100 cells in a domain with periodic boundary conditions and run for 2 hours (360 simulation time steps).
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pone-0022169-g001: Simulation images of cells' gliding behavior showing the effect of various parameters to the gliding patterns.The following parameters listed in Table 1 are included in the model: (A) Basic cellular properties. (B) Basic cellular properties and polarity reversal. (C) Basic cellular properties, polarity reversal and quorum sensing. (D) Basic cellular properties, polarity reversal, quorum sensing and EPS slime production and following. (E) Basic cellular properties, polarity reversal, quorum sensing, EPS slime production and following, and active turning. (F) Experimental image of wild-type cells and their gliding pattern. All simulations start with 100 cells in a domain with periodic boundary conditions and run for 2 hours (360 simulation time steps).

Mentions: Four different sets of simulations were carried out for various purposes. The first set of simulations (Fig. 1) was performed to test the necessity of the four parameters mentioned above in simulating myxobacteria gliding behavior prior to aggregation during development. The values for these parameters are summarized in Table 1, items 1–4. We start with only the basic cell parameters (Table 1, item 1) and sequentially include additional parameters to the model until all four are used. We simulate 100 cells, initially placed randomly over the surface with periodic boundary conditions, for two hours. EPS slime traces are plotted and shown as light blue dots.


Experimentally guided computational model discovers important elements for social behavior in myxobacteria.

Hendrata M, Yang Z, Lux R, Shi W - PLoS ONE (2011)

Simulation images of cells' gliding behavior showing the effect of various parameters to the gliding patterns.The following parameters listed in Table 1 are included in the model: (A) Basic cellular properties. (B) Basic cellular properties and polarity reversal. (C) Basic cellular properties, polarity reversal and quorum sensing. (D) Basic cellular properties, polarity reversal, quorum sensing and EPS slime production and following. (E) Basic cellular properties, polarity reversal, quorum sensing, EPS slime production and following, and active turning. (F) Experimental image of wild-type cells and their gliding pattern. All simulations start with 100 cells in a domain with periodic boundary conditions and run for 2 hours (360 simulation time steps).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3139613&req=5

pone-0022169-g001: Simulation images of cells' gliding behavior showing the effect of various parameters to the gliding patterns.The following parameters listed in Table 1 are included in the model: (A) Basic cellular properties. (B) Basic cellular properties and polarity reversal. (C) Basic cellular properties, polarity reversal and quorum sensing. (D) Basic cellular properties, polarity reversal, quorum sensing and EPS slime production and following. (E) Basic cellular properties, polarity reversal, quorum sensing, EPS slime production and following, and active turning. (F) Experimental image of wild-type cells and their gliding pattern. All simulations start with 100 cells in a domain with periodic boundary conditions and run for 2 hours (360 simulation time steps).
Mentions: Four different sets of simulations were carried out for various purposes. The first set of simulations (Fig. 1) was performed to test the necessity of the four parameters mentioned above in simulating myxobacteria gliding behavior prior to aggregation during development. The values for these parameters are summarized in Table 1, items 1–4. We start with only the basic cell parameters (Table 1, item 1) and sequentially include additional parameters to the model until all four are used. We simulate 100 cells, initially placed randomly over the surface with periodic boundary conditions, for two hours. EPS slime traces are plotted and shown as light blue dots.

Bottom Line: The simulation is able to produce both gliding pattern and spontaneous aggregation center formation as observed in experiments.The model is tested against several known M. xanthus mutants and our modification of parameter values relevant for the individual mutants produces good phenotypic agreements.This outcome indicates the strong predictive potential of our model for the social behaviors of uncharacterized mutants and their expected phenotypes during development.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, California State University Los Angeles, Los Angeles, California, United States of America. mhendra@calstatela.edu

ABSTRACT
Identifying essential factors in cellular interactions and organized movement of cells is important in predicting behavioral phenotypes exhibited by many bacterial cells. We chose to study Myxococcus xanthus, a soil bacterium whose individual cell behavior changes while in groups, leading to spontaneous formation of aggregation center during the early stage of fruiting body development. In this paper, we develop a cell-based computational model that solely relies on experimentally determined parameters to investigate minimal elements required to produce the observed social behaviors in M. xanthus. The model verifies previously known essential parameters and identifies one novel parameter, the active turning, which we define as the ability and tendency of a cell to turn to a certain angle without the presence of any obvious external factors. The simulation is able to produce both gliding pattern and spontaneous aggregation center formation as observed in experiments. The model is tested against several known M. xanthus mutants and our modification of parameter values relevant for the individual mutants produces good phenotypic agreements. This outcome indicates the strong predictive potential of our model for the social behaviors of uncharacterized mutants and their expected phenotypes during development.

Show MeSH