Amoeboid motion in confined geometry

Wu, Hao; Thiébaud, Marine; Hu, Wen‐Chen; Farutin, Alexander; Rafaı̈, Salima; Lai, Ming-Chih; Peyla, Philippe; Misbah, Chaouqi

doi:10.1103/physreve.92.050701

Cited by 63 publications

(102 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A prominent property we have recently reported on [34] is the velocity's non-monotonous behavior with confinement C. The results are summarized in Fig. 6, where we compare the outcome of the two numerical methods showing good agreement.…”

Section: B Velocity Of the Swimmer As A Function Of Confinement And supporting

confidence: 60%

“…shape deformation time scale). Details of numerical procedure can be found in references [34,36]. We perform the time-stepping scheme as follows: The governing equations are discretized by the IBM.…”

Section: B Immersed Boundary Methodsmentioning

confidence: 99%

“…In Section III the two numerical methods used in this study are briefly detailed: the boundary integral method (BIM) [34,35] and the immersed boundary method (IBM) [36]. In Section IV, we present the main results regarding an axially moving swimmer.…”

Section: Introductionmentioning

confidence: 99%

“…Several models of directed self-propulsion by large shape deformation have been explored in the literature [26][27][28][29][30][31][32][33][34]. In two recent studies we introduced a model in which [33,34] the swimmer is considered as made of an inextensible membrane enclosing a constant volume of liquid and exerting a set of normal forces leading to deformations of the swimmer and to propulsion.…”

Section: Introductionmentioning

confidence: 99%

“…In two recent studies we introduced a model in which [33,34] the swimmer is considered as made of an inextensible membrane enclosing a constant volume of liquid and exerting a set of normal forces leading to deformations of the swimmer and to propulsion. The first study [33] dealt with purely unconfined three dimensional (3D) geometry; the more recent work was dedicated to a confined swimmer in two dimensions (2D) [34], a situation revealing several puzzling phenomena which we will look at later. Here we report on several new issues emerging for a confined amoeboid swimmer.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Amoeboid swimming in a channel

Farutin

et al. 2016

Soft Matter

Self Cite

View full text Add to dashboard Cite

Several micro-organisms, such as bacteria, algae, or spermatozoa, use flagellar or ciliary activity to swim in a fluid, while many other micro-organisms instead use ample shape deformation, described as amoeboid, to propel themselves by either crawling on a substrate or swimming. Many eukaryotic cells were believed to require an underlying substratum to migrate (crawl) by using membrane deformation (like blebbing or generation of lamellipodia) but there is now increasing evidence that a large variety of cells (including those of the immune system) can migrate without the assistance of focal adhesion, allowing them to swim as efficiently as they can crawl. This paper details the analysis of amoeboid swimming in a confined fluid by modeling the swimmer as an inextensible membrane deploying local active forces (with zero total force and torque). The swimmer displays a rich behavior: it may settle into a straight trajectory in the channel or navigate from one wall to the other depending on its confinement. The nature of the swimmer is also found to be affected by confinement: the swimmer can behave, on the average over one swimming cycle, as a pusher at low confinement, and becomes a puller at higher confinement, or vice versa. The swimmer's nature is thus not an intrinsic property. The scaling of the swimmer velocity V with the force amplitude A is analyzed in detail showing that at small enough A, V ∼ A 2 /η 2 (where η is the viscosity of the ambient fluid), whereas at large enough A, V is independent of the force and is determined solely by the stroke cycle frequency and swimmer size. This finding starkly contrasts with currently known results found from swimming models where motion is based on ciliary and flagellar activity, where V ∼ A/η. To conclude, two definitions of efficiency as put forward in the literature are analyzed with distinct outcomes. We find that one type of efficiency has an optimum as a function of confinement while the other does not. Future perspectives are outlined.

show abstract

Section: B Velocity Of the Swimmer As A Function Of Confinement And supporting

confidence: 60%

Section: B Immersed Boundary Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Amoeboid swimming in a channel

Farutin

et al. 2016

Soft Matter

Self Cite

View full text Add to dashboard Cite

show abstract

Eukaryotic cell dynamics from crawlers to swimmers

Othmer

2018

WIREs Comput Mol Sci

View full text Add to dashboard Cite

Movement requires force transmission to the environment, and motile cells are robustly, though not elegantly, designed nanomachines that often can cope with a variety of environmental conditions by altering the mode of force transmission used1. As with humans, the available modes range from momentary attachment to a substrate when crawling, to shape deformations when swimming, and at the cellular level this involves sensing the mechanical properties of the environment and altering the mode appropriately. While many types of cells can adapt their mode of movement to their microenvironment (ME)2, our understanding of how they detect, transduce and process information from the ME to determine the optimal mode is still rudimentary. The shape and integrity of a cell is determined by its cytoskeleton (CSK), and thus the shape changes that may be required to move involve controlled remodeling of the CSK. Motion in vivo is often in response to extracellular signals, which requires the ability to detect such signals and transduce them into the shape changes and force generation needed for movement. Thus the nanomachine is complex, and while much is known about individual components involved in movement, an integrated understanding of motility in even simple cells such as bacteria is not at hand. In this review we discuss recent advances in our understanding of cell motility and some of the problems remaining to be solved.

show abstract

Getting in shape and swimming: the role of cortical forces and membrane heterogeneity in eukaryotic cells

León

Othmer

2018

J. Math. Biol.

Self Cite

View full text Add to dashboard Cite

Recent research has shown that motile cells can adapt their mode of propulsion to the mechanical properties of the environment in which they find themselves – crawling in some environments while swimming in others. The latter can involve movement by blebbing or other cyclic shape changes, and both highly-simplified and more realistic models of these modes have been studied previously. Herein we study swimming that is driven by membrane tension gradients that arise from flows in the actin cortex underlying the membrane, and does not involve imposed cyclic shape changes. Such gradients can lead to a number of different characteristic cell shapes, and our first objective is to understand how different distributions of membrane tension influence the shape of cells in an inviscid quiescent fluid. We then analyze the effects of spatial variation in other membrane properties, and how they interact with tension gradients to determine the shape. We also study the effect of fluid-cell interactions and show how tension leads to cell movement, how the balance between tension gradients and a variable bending modulus determine the shape and direction of movement, and how the efficiency of movement depends on the properties of the fluid and the distribution of tension and bending modulus in the membrane.

show abstract

Amoeboid motion in confined geometry

Cited by 63 publications

References 33 publications

Amoeboid swimming in a channel

Amoeboid swimming in a channel

Eukaryotic cell dynamics from crawlers to swimmers

Getting in shape and swimming: the role of cortical forces and membrane heterogeneity in eukaryotic cells

Contact Info

Product

Resources

About