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

Hendrata, Melisa; Yang, Zhe; Lux, Renate; Shi, Wenyuan

doi:10.1371/journal.pone.0022169

Cited by 9 publications

(9 citation statements)

References 49 publications

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“…Although computational approaches have been extensively used in hypothesizing models of aggregation (24,(31)(32)(33)(34)(35)(36), the lack of quantitative datasets describing cell movement during aggregation has left the cell behaviors that drive the process conjectural. As a result of these models, cell length-to-width ratio (35), cell alignment (35,37), active turning (36), density-dependent speed reduction (37), physical jamming (31,32,34), and streaming (32,34) have been introduced as cell behaviors required to generate aggregates in simulations.…”

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confidence: 99%

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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confidence: 99%

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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“…Despite the swarming and aggregating dynamics observed using only a small set of P system rewrite rules, there are a number of limitations; orientation is limited to the eight adjacent spaces in the multi-environment P system substrate; the time step is a simple count and the execution of rules are determined stochastically with no consideration of temporal dynamics; and, slime remains indefinitely, reducing the A-motility to a random walk as the simulation progresses. Compared with recent particle continuum [33] and continuous [34] based modelling, conventional models of Myxobacteria continue to dominate, chiefly through their ability to model structural properties of bacterium. Finally, there is a degree of abstraction from the traditional cell-line P system paradigm in the way in which the mixing of bacteria is treated.…”

Section: Resultsmentioning

confidence: 99%

A P system model of swarming and aggregation in a Myxobacterial colony

Nash

Kalvala

2019

J Membr Comput

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Bacterial communities provide an interesting subject for the study of emergence and complexity as the consequence of many local interactions. In particular, the soil-dwelling social bacterium Myxobacteria demonstrates two distinct types of motility, social motility via the sensing of bacterial slime deposits and adventurous motility. Both modes of motility are governed by local interactions. Using P systems, a membrane computing methodology based on compartmental rewrite rules for modelling computational processes; this work demonstrates how minimal set of rules can model swarming and aggregating behaviour in Myxobacteria bacterial populations. Our model uses a multi-environment P system similar a 2D cellular automaton to represent the substrate environment whilst stochastic rule selection dictates Myxobacterial motion according to behaviour observed in vitro. The rules account for both mechanisms of motility, the deposit and detection of slime, a change in direction due to C-signal induction and the mixing of population numbers. Simulations demonstrate an extensible computational framework for the modelling of bacterial behaviour, with the potential for extension into additional emergent behaviours.

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“…That some M. xanthus EPS can have a lubricating function explains the puzzling observation that more EPS often lead to more motility, rather than less motility, as would be the case if EPS were to function only as a "glue". For example, the highly motile cells that actively drive fruiting body formation move in the presence of high concentrations of EPS (15,16). M. xanthus alone among bacteria is capable of S-motility.…”

Section: Resultsmentioning

confidence: 99%

“…This reversal behavior, which is driven by chemotaxis, allows cells to retrace their paths and form fruiting bodies (12,13), which incorporate significant concentrations of EPS within their structures (14,15). Although it is clear that this coupling between TFP and EPS is critical to the formation of structured fruiting bodies by M. xanthus, it is not known how M. xanthus TFP-EPS technology allows it to achieve its unique coordinated multicellular movements (15,16), given that TFP and EPS exist in a variety of bacterial species (17) that do not exhibit S-motility.…”

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confidence: 99%

Earthquake-like dynamics in Myxococcus xanthus social motility

Gibiansky

Dahmen

et al. 2013

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

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Myxococcus xanthus is a bacterium capable of complex social organization. Its characteristic social ("S")-motility mechanism is mediated by type IV pili (TFP), linear actuator appendages that propel the bacterium along a surface. TFP are known to bind to secreted exopolysaccharides (EPS), but it is unclear how M. xanthus manages to use the TFP-EPS technology common to many bacteria to achieve its unique coordinated multicellular movements. We examine M. xanthus S-motility, using high-resolution particle-tracking algorithms, and observe aperiodic stick-slip movements. We show that they are not due to chemotaxis, but are instead consistent with a constant TFP-generated force interacting with EPS, which functions both as a glue and as a lubricant. These movements are quantitatively homologous to the dynamics of earthquakes and other crackling noise systems. These systems exhibit critical behavior, which is characterized by a statistical hierarchy of discrete "avalanche" motions described by a power law distribution. The measured critical exponents from M. xanthus are consistent with mean field theoretical models and with other crackling noise systems, and the measured Lyapunov exponent suggests the existence of highly branched EPS. Such molecular architectures, which are common for efficient lubricants but rare in bacterial EPS, may be necessary for S-motility: We show that the TFP of leading "locomotive" cells initiate the collective motion of follower cells, indicating that lubricating EPS may alleviate the force generation requirements on the lead cell and thus make S-motility possible.biofilm | proteobacteria | sociomicrobiology | twitching | tribology T he soil bacterium myxococcus xanthus is an advanced Gramnegative bacterium that is capable of highly organized social behavior (1). For example, M. xanthus can form predatory "wolf packs" to prey on other species, and under starvation conditions, they can self-organize into macroscopic fruiting bodies to ensure community survival (2). This rudimentary social behavior (3) relies on the gliding ability to move in the direction of the cell's long axis on solid surfaces, which is regulated by the adventurous ("A")-and social ("S")-motility systems (4). As two distinct motility systems, A-motility allows movement of individual and isolated cells, whereas S-motility controls the coordinated motility of large numbers of cells. S-motility in M. xanthus is mechanistically equivalent to the twitching motilities in Pseudomonas aeruginosa and Neisseria gonorrheae (5), which are all driven by type IV pili (TFP) (6). TFP are located at the two bacterial poles and propel the cell by cycles of extension, attachment, and retraction (7,8). Recently it has been shown that TFP are used to sense the exopolysaccharides (EPS) that are secreted by other cells onto the cell body or the surface (9, 10), which enables M. xanthus to coordinate movement along EPS tracks. Although only one pole is piliated at a time, bacteria are known to reverse direction by disassembling the TFP apparatus...

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

Cited by 9 publications

References 49 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

A P system model of swarming and aggregation in a Myxobacterial colony

Earthquake-like dynamics in Myxococcus xanthus social motility

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