Dynamic-energy-budget-driven fruiting-body formation in myxobacteria

Hendrata, Melisa; Birnir, Björn

doi:10.1103/physreve.81.061902

Cited by 5 publications

(10 citation statements)

References 40 publications

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“…3(b)), which is rarely discussed in early DW models. In addition, our model generates quasi-periodic collective movements with marching bands when r → 1 indicating that the aggregations of animals are more likely to appear with food shortage [26,27], which is far different from many known dynamical interpretations based on the interaction between individuals [19][20][21][22][23]. One of the noticeable features in our results is the coexistence of both scaling mobility patterns in individual level and collective movement in population level.…”

Section: Conclusion and Discussioncontrasting

confidence: 68%

Scaling mobility patterns and collective movements: Deterministic walks in lattices

2011

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Scaling mobility patterns have been widely observed for animals. In this paper, we propose a deterministic walk model to understand the scaling mobility patterns, where walkers take the leastaction walks on a lattice landscape and prey. Scaling laws in the displacement distribution emerge when the amount of prey resource approaches the critical point. Around the critical point, our model generates ordered collective movements of walkers with a quasi-periodic synchronization of walkers' directions. These results indicate that the co-evolution of walkers' least-action behavior and the landscape could be a potential origin of not only the individual scaling mobility patterns, but also the flocks of animals. Our findings provide a bridge to connect the individual scaling mobility patterns and the ordered collective movements.

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Section: Conclusion and Discussioncontrasting

confidence: 68%

Scaling mobility patterns and collective movements: Deterministic walks in lattices

2011

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“…This automatic formation of aggregation center is supported by the observations of Curtis et al [43], Holmes et al [29] and Hendrata et al [30] in their simulation models. These models included the turning and bending of cells as random fluctuations due to stochasticity in the models' algorithm.…”

Section: Discussionsupporting

confidence: 67%

“…In this paper, we show that our model successfully reproduces the array of social behaviors of M. xanthus at both low and high density, from single cells to the spontaneous formation of multicellular aggregation center involving thousands of cells without the necessity of creation of an artificial traffic jam, as used in some previous models [24] , [25] . This automatic formation of aggregation center is supported by the observations of Curtis et al [43] , Holmes et al [29] and Hendrata et al [30] in their simulation models. These models included the turning and bending of cells as random fluctuations due to stochasticity in the models' algorithm.…”

Section: Discussionsupporting

confidence: 67%

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Experimentally Guided Computational Model Discovers Important Elements for Social Behavior in Myxobacteria

et al. 2011

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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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“…[17], nor the currently known quorum sensing circuits for EPS production are incorporated in those models. Dynamic energy budget descriptions of cell dynamics [63] might provide a sophisticated framework to describe the evolution of individual cells taking into account their mass, volume, maintenance, substance secretion, and the presence of nutrients, oxygen, and toxicants. However, extensions to biofilms are yet to be devised.…”

Section: B Surfactin and Eps Productionmentioning

confidence: 99%

Differential growth of wrinkled biofilms

2015

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Biofilms are antibiotic-resistant bacterial aggregates that grow on moist surfaces and can trigger hospitalacquired infections. They provide a classical example in biology where the dynamics of cellular communities may be observed and studied. Gene expression regulates cell division and differentiation, which affect the biofilm architecture. Mechanical and chemical processes shape the resulting structure. We gain insight into the interplay between cellular and mechanical processes during biofilm development on air-agar interfaces by means of a hybrid model. Cellular behavior is governed by stochastic rules informed by a cascade of concentration fields for nutrients, waste, and autoinducers. Cellular differentiation and death alter the structure and the mechanical properties of the biofilm, which is deformed according to Föppl-Von Kármán equations informed by cellular processes and the interaction with the substratum. Stiffness gradients due to growth and swelling produce wrinkle branching. We are able to reproduce wrinkled structures often formed by biofilms on air-agar interfaces, as well as spatial distributions of differentiated cells commonly observed with B. subtilis.

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Dynamic-energy-budget-driven fruiting-body formation in myxobacteria

Cited by 5 publications

References 40 publications

Scaling mobility patterns and collective movements: Deterministic walks in lattices

Scaling mobility patterns and collective movements: Deterministic walks in lattices

Experimentally Guided Computational Model Discovers Important Elements for Social Behavior in Myxobacteria

Differential growth of wrinkled biofilms

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