Macroscopic model of self-propelled bacteria swarming with regular reversals

Gejji, Richard; Lushnikov, Pavel M.; Alber, Mark

doi:10.1103/physreve.85.021903

Cited by 12 publications

(11 citation statements)

References 36 publications

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“…Previous hypotheses of the mechanistic basis for aggregation predicted that decreased cell movement inside aggregates was the major driver of aggregate growth (21,24,31,32,38). We tested the hypothesis that the observed decrease in cell movement at the higher cell densities inside aggregates is sufficient to drive aggregation by incorporating density dependence into the simulations.…”

Section: Resultsmentioning

confidence: 98%

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

Cotter

Schüttler

Igoshin

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

145

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Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with datadriven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.agent-based simulation | image processing | emergent behavior | fluorescent imaging | cell communication C ollective cell migration is essential for many developmental processes, including fruiting body development of myxobacteria (1) and Dictyostelium (2), embryonic gastrulation (3, 4), and neural crest development (5). Conversely, cancer cell metastases represent detrimental migratory events that disseminate dysfunctional cells (6). In all these processes, a population of cells leaves its current location and migrates in a coordinated manner to new locations where motility becomes reduced. Remarkable progress has been made in studying the intracellular machinery of these organisms (7). Much less is known about the systemlevel coordination of cell migration. Cell movement in these systems is a 3D, dynamic process coordinated by a combination of diverse physical and chemical cues acting on the cells (3,5,8). Recent developments in tracking individual cell movement in vivo have provided unprecedented detail and revealed surprising levels of heterogeneity (5, 7). Reverse engineering of how these individual cell movements lead to collective migration patterns has proved difficult. Whereas computational models are able to test whether a given set of ad hoc assumptions lead to e...

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Section: Resultsmentioning

confidence: 98%

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

Cotter

Schüttler

Igoshin

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

145

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“…We also neglected a number of other complicated factors that affect the dynamics of real myxobacteria, such as C-signaling, the chemotactic effects of slime tracks and realistic direction-reversal dynamics of individual bacteria. (For details about nonlinear diffusion model of self-propelled rods reversing with specific frequency see [39].) We anticipate that these factors can be taken into consideration within our general modeling approach.…”

Section: Discussionmentioning

confidence: 99%

Continuum modeling of myxobacteria clustering

et al. 2013

Self Cite

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In this paper we develop a continuum theory of clustering in ensembles of self-propelled inelastically colliding rods with applications to collective dynamics of common gliding bacteria Myxococcus Xanthus. A multiphase hydrodynamic model that couples densities of oriented and isotropic phases is described. This model is used for the analysis of an instability that leads to spontaneous formation of directionally moving dense clusters within initially dilute isotropic “gas” of myxobacteria. Numerical simulations of this model confirm the existence of stationary dense moving clusters and also elucidate the properties of their collisions. The results are shown to be in a qualitative agreement with experiments.

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“…After collisions, the bacteria acquire nearly identical nematic orientation. This makes myxobacteria a very interesting model system to study the collective behavior of self-propelled rod-like particles (Gejji et al, 2012;Harvey et al, 2013Harvey et al, , 2011Peruani et al, 2012).…”

Section: Chlamydomonas Reinhardtiimentioning

confidence: 99%

Physics of microswimmers—single particle motion and collective behavior: a review

2015

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Locomotion and transport of microorganisms in fluids is an essential aspect of life. Search for food, orientation toward light, spreading of off-spring, and the formation of colonies are only possible due to locomotion. Swimming at the microscale occurs at low Reynolds numbers, where fluid friction and viscosity dominates over inertia. Here, evolution achieved propulsion mechanisms, which overcome and even exploit drag. Prominent propulsion mechanisms are rotating helical flagella, exploited by many bacteria, and snake-like or whip-like motion of eukaryotic flagella, utilized by sperm and algae. For artificial microswimmers, alternative concepts to convert chemical energy or heat into directed motion can be employed, which are potentially more efficient. The dynamics of microswimmers comprises many facets, which are all required to achieve locomotion. In this article, we review the physics of locomotion of biological and synthetic microswimmers, and the collective behavior of their assemblies. Starting from individual microswimmers, we describe the various propulsion mechanism of biological and synthetic systems and address the hydrodynamic aspects of swimming. This comprises synchronization and the concerted beating of flagella and cilia. In addition, the swimming behavior next to surfaces is examined. Finally, collective and cooperate phenomena of various types of isotropic and anisotropic swimmers with and without hydrodynamic interactions are discussed.

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Macroscopic model of self-propelled bacteria swarming with regular reversals

Cited by 12 publications

References 36 publications

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

Continuum modeling of myxobacteria clustering

Physics of microswimmers—single particle motion and collective behavior: a review

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