Minimal model of directed cell motility on patterned substrates

Mizuhara, Matthew S.; Berlyand, Leonid; Aranson, Igor S.

doi:10.1103/physreve.96.052408

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…Guiding cells by substrate topography. The 3D modeling framework also allows to study cell motion on essentially flat substrates exhibiting simple topographical features, complementing experimental and theoretical analyses of cell guidance on microprinted adhesive patterns 42,59,60 . Although there are many possible surface features, we focused here on a type that has been extensively studied experimentally [21][22][23][24][25] , namely periodic grooves/ ridges on the substrate's surface.…”

Section: Resultsmentioning

confidence: 99%

Confinement and substrate topography control cell migration in a 3D computational model

2019

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Cell movement in vivo is typically characterized by strong confinement and heterogeneous, three-dimensional environments. Such external constraints on cell motility are known to play important roles in many vital processes e.g. during development, differentiation, and the immune response, as well as in pathologies like cancer metastasis. Here we develop a physics-driven three-dimensional computational modeling framework that describes lamellipodium-based motion of cells in arbitrarily shaped and topographically structured surroundings. We use it to investigate the primary in vitro model scenarios currently studied experimentally: motion in vertical confinement, confinement in microchannels, as well as motion on fibers and on imposed modulations of surface topography. We find that confinement, substrate curvature and topography modulate the cell's speed, shape and actin organization and can induce changes in the direction of motion along axes defined by the constraints. Our model serves as a benchmark to systematically explore lamellipodium-based motility and its interaction with the environment.

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Section: Resultsmentioning

confidence: 99%

Confinement and substrate topography control cell migration in a 3D computational model

2019

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“…It is a minimal version of a more general model introduced by Ziebert, et al in [30]. The original model in [30] has been extended to include spatial adhesion dynamics [29], non-homogeneous substrate effects [11,14,23], and interacting dynamics of multiple cells [12]. These extended models exhibit a wide variety of dynamical modes and can be used to understand the complex morphologies of dynamics cells.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of a cell motility model near the sharp interface limit

Bolle,

Mizuhara

2020

Preprint

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Phase-field models have recently had great success in describing the dynamic morphologies and motility of eukaryotic cells. In this work we investigate the minimal phase-field model introduced in [6]. Rigorous analysis of its sharp interface limit dynamics was completed in [15,16], where it was observed that persistent cell motion was not stable. In this work we numerically study the pre-limiting phase-field model near the sharp interface limit, to better understand this lack of persistent motion. We find that immobile, persistent, and rotating states are all exhibited in this minimal model, and investigate the loss of persistent motion in the sharp interface limit. In addition we study cell speed as a function of biophysical parameters.

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“…Motility is controlled mainly by actin polymerization and actomyosin contractility [12,13]; it is challenging to study cell motility theoretically because of the large length-scale gap between single filaments and entire cells. Therefore, generic continuum models have been developed to predict cell shape and motility on homogenous substrates [12,[14][15][16][17], on striped substrates substrates and at interfaces [18][19][20], as well as for cell-cell collisions [21]. Alternative continuum models with governing equations derived from the filamentous microstructure have been employed to include details of the cytoskeletal organization [19,22].…”

Section: Introductionmentioning

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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Minimal model of directed cell motility on patterned substrates

Cited by 7 publications

References 47 publications

Confinement and substrate topography control cell migration in a 3D computational model

Confinement and substrate topography control cell migration in a 3D computational model

Dynamics of a cell motility model near the sharp interface limit

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

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