Stochastic nonlinear dynamics of confined cell migration in two-state systems

Brückner, David B.; Fink, Alexandra; Schreiber, Christoph; Röttgermann, Peter J. F.; Rädler, Joachim O.; Broedersz, Chase P.

doi:10.1038/s41567-019-0445-4

Cited by 107 publications

(183 citation statements)

References 48 publications

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“…Furthermore, it facilitates studies of the active properties of cells, such as an activity-induced tension and active fluctuations of cells [50][51][52] and vesicles [53,54]. Future work in the area of cell motility may include more complex micropatterned substrates [55], many-flexocyte simulations to study collective behavior ranging from the circling observed in small keratinocyte colonies [56] to wound healing [7], and a coupling of mechanics and activity to biochemical reactions [57,58]. In some biological cells, such as neutrophils, cytoskeletal filaments that exert strongly localized forces on lipid-bilayer membranes lead to the formation of sheet-like (lamellipodia) and tube-like (filopodia) protrusions [59], whereas in other cells, such as keratocytes, filopodia are absent.…”

Section: Discussionmentioning

confidence: 99%

Vesicles with internal active filaments: self-organized propulsion controls shape, motility, and dynamical response

2019

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Self-propulsion and navigation due to the sensing of environmental conditions-such as durotaxis and chemotaxis-are remarkable properties of biological cells that cannot be modeled by singlecomponent self-propelled particles. Therefore, we introduce and study 'flexocytes', deformable vesicles with enclosed attached self-propelled pushing and pulling filaments that align due to steric and membrane-mediated interactions. Using computer simulations in two dimensions, we show that the membrane deforms under the propulsion forces and forms shapes mimicking motile biological cells, such as keratocytes and neutrophils. When interacting with walls or with interfaces between different substrates, the internal structure of a flexocyte reorganizes, resulting in a preferred angle of reflection or deflection, respectively. We predict a correlation between motility patterns, shapes, characteristics of the internal forces, and the response to micropatterned substrates and external stimuli. We propose that engineered flexocytes with desired mechanosensitive capabilities enable the construction of soft-matter microbots.Models with explicit filaments have been used to study specific biological processes, such as filopodia formation [23] and lamellipodial waves [24,25].Many self-organized machineries constructed from various active and passive components inherently include regulation and sensing capability. The internal components react differently to stimuli and the machinery can therefore process external information. The interplay between active and spatial selforganization can be found in biological cells and engineered colloidal systems, as well as in biological or artificial systems on significantly larger length scales. For example, diffusiophoretic Janus colloids form spinning superstructures that can autonomously regulate themselves [26], groups of ants collectively carry a large cargo to their nest [27], and microbots in deformable mobile confinement [28] demonstrate complex responses to environmental cues.Here, we introduce self-propelled 'flexocytes', a minimal model system to study the motility of mechanosensitive active vesicles based on self-organization of explicit protrusion and retraction forces. The model consists of active filaments in vesicles pulling or pushing on the membrane, and is suitable for singleagent and multi-agent simulations. We perform Brownian dynamics simulations for this system in the overdamped regime to model substrate friction and internal noise. We find that the filaments in the flexocytes self-organize to reproduce cellular shapes and motility patterns, giving rise to dynamical phase transitions. Furthermore, we show that explicit pulling forces are sufficient to recover behavior of keratocytes: such flexocytes are reflected at walls and deflected at friction interfaces. Motility in our simulations is subject to noise. Interestingly, additional explicit pushing forces lead to less persistent motion, induce trapping at walls, and reduce deflection at interfaces. Therefore, we propose 'scatte...

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Section: Discussionmentioning

confidence: 99%

Vesicles with internal active filaments: self-organized propulsion controls shape, motility, and dynamical response

2019

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“…Previous works showed in vitro, as a proof of a principle, that local asymmetries in cellular environment can bias cell directionality in another mode of migration named ratchetaxis (10)(11)(12)(13)(14)(15)(16)(17). This type of behavior can lead to long-term directionality and stresses the importance of stochastic probing associated to cell protrusions, as well as the role of environment topology.…”

Section: Introductionmentioning

confidence: 93%

Cell motion as a stochastic process controlled by focal contacts dynamics

Vecchio

Thiagarajan

Caballero

et al. 2019

Preprint

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Directed cell motion is essential in physiological and pathological processes such as morphogenesis, wound healing and cancer spreading. Chemotaxis has often been proposed as the driving mechanism, even though evidence of long-range gradients is often lacking in vivo. By patterning adhesive regions in space, we control cell shape and the associated potential to move along one direction in another mode of migration coined ratchetaxis. We report that focal contacts distributions collectively dictate cell directionality, and bias is non-linearly increased by gap distance between adhesive regions. Focal contact dynamics on micro-patterns allow to integrate these phenomena in a consistent model where each focal contact can be translated into a force with known amplitude and direction, leading to quantitative predictions for cell motion in every condition. Altogether, our study shows how local and minutes timescale dynamics of focal adhesions and their distribution lead to long term cellular motion with simple geometric rules.

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“…Active cell motility is powered by cytoskeletal dynamics which is regulated by cell polarity, a spatial imbalance of signaling molecules 1,17,43 . Following 35 , we represent cell polarity as a vector quantity p σ , and we assume that the motile force is a nonlinear (Hill) function of polarity:…”

Section: Intra-cellular Dynamicsmentioning

confidence: 99%

“…The synchronization of cell polarity during collective migration as well as the guidance from mechanical environmental cues are poorly understood 17 . The process likely involves cell-cell junctions are mediated by adhesion proteins (e.g., transmembrane receptor E-cadherin) coupled to the contractile actomyosin cytoskeleton through cytoplasmic adaptor proteins (e.g., α-catenin) 4 .…”

Section: Introductionmentioning

confidence: 99%

Multiscale modelling of motility wave propagation in cell migration

Khataee

Neufeld

Czirók

2020

Preprint

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The collective motion of cell monolayers within a tissue is a fundamental biological process that occurs during tissue formation, wound healing, cancerous invasion, and viral infection. Experiments have shown that at the onset of migration, the motility is self-generated as a polarization wave starting from the leading edge of the monolayer and progressively propagates into the bulk. However, it is unclear how the propagation of this motility wave is influenced by cellular properties. Here, we investigate this using a computational model based on the Potts model coupled to the dynamics of intracellular polarization. The model captures the propagation of the polarization wave initiated at the leading edge and suggests that the cells cortex can regulate the migration modes: strongly contractile cells may depolarize the monolayer, whereas less contractile cells can form swirling movement. Cortical contractility is further found to limit the cells motility, which (i) decelerates the wave speed and the leading edge progression, and (ii) destabilises the leading edge into migration fingers. Together, our model describes how different cellular properties can contribute to the regulation of collective cell migration.

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Stochastic nonlinear dynamics of confined cell migration in two-state systems

Cited by 107 publications

References 48 publications

Vesicles with internal active filaments: self-organized propulsion controls shape, motility, and dynamical response

Vesicles with internal active filaments: self-organized propulsion controls shape, motility, and dynamical response

Cell motion as a stochastic process controlled by focal contacts dynamics

Multiscale modelling of motility wave propagation in cell migration

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