An Elastic Analysis of Listeria monocytogenes Propulsion

Gerbal, Fabien; Chaikin, P. M.; Rabin, Yitzhak; Prost, Jacques

doi:10.1016/s0006-3495(00)76473-3

Cited by 196 publications

(250 citation statements)

References 37 publications

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“…Based on the available experimental results we find that the quantity λ 2 is in fact quite small. Taking a value of ξ ≃ 10 5 Pa·s/µ 2 [19], η ≃ 10 4 Pa·s [12,20], and R 0 ≃ 10 µm we find λ 2 ≃ 10 −3 .…”

mentioning

confidence: 94%

“…In general, integrins cluster to form focal adhesions whose size and mechanical properties are determined by chemical and mechanical cues and can regulate the force that they exert. If, however, the actin velocity relative to the substrate is small compared to a/τ , where a is a molecular size and τ is the average time during which an integrin remains bound, then the force exerted by the moving filaments on the substrate can be expressed as a friction force, proportional to the actin velocity [5,11,12,13].…”

mentioning

confidence: 99%

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Viscous-Fingering-Like Instability of Cell Fragments

2008

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We present a novel flow instability that can arise in thin films of cytoskeletal fluids if the friction with the substrate on which the film lies is sufficiently strong. We consider a two dimensional, membrane-bound fragment containing actin filaments that is perturbed from its initially circular state, where actin polymerizes at the edge and flows radially inward while depolymerizing in the fragment. Performing a linear stability analysis of the initial state due to perturbations of the fragment boundary, we find, in the limit of very large friction, that the perturbed actin velocity and pressure fields obey the very same laws governing the viscous fingering instability of an interface between immiscible fluids in a Hele-Shaw cell. A feature of this instability that is remarkable in the context of cell motility, is that its existence is independent of the strength of the interaction between cytoskeletal filaments and myosin motors, and moreover that it is completely driven by the free energy of actin polymerization at the fragment edge.

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mentioning

confidence: 94%

mentioning

confidence: 99%

Viscous-Fingering-Like Instability of Cell Fragments

2008

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“…The polymerisation is balanced by depolymerisation to conserve mass. When calculating the velocity profile, equations (2.4) and (2.5), as we do to obtain Figures 6,[8][9][10][11][12], the depolymerisation rate k d should also be included in the incompressibility condition (2.2) and therefore appears in equation (2.5) in the additional term…”

Section: Self-polymerisationmentioning

confidence: 99%

“…Following [9] we argue that the friction coefficientξ for a polymeric gel depends on the normal constraint. Qualitatively a high normal constraint increases the attachment rate of polymers onto the channel walls by lowering the entropic barrier, and decreases the detachment rate.…”

Section: Pressure Dependent Frictionmentioning

confidence: 99%

Mechanisms of Cell Motion in Confined Geometries

Hawkins

Voituriez

2010

Math. Model. Nat. Phenom.

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Abstract. We present a simple mechanism of cell motility in a confined geometry, inspired by recent motility assays in microfabricated channels. This mechanism relies mainly on the coupling of actin polymerisation at the cell membrane to geometric confinement. We first show analytically using a minimal model of polymerising viscoelastic gel confined in a narrow channel that spontaneous motion occurs due to polymerisation alone. Interestingly, this mechanism does not require specific adhesion with the channel walls, and yields velocities potentially larger than the polymerisation velocity of the gel. We then study the effect of the contractile activity of myosin motors, and show that whilst it is not necessary to induce motion, it quantitatively increases the velocity of motion in the polymerisation mechanism we describe. Our model qualitatively accounts for recent experiments which show that cells without specific adhesion proteins are motile only in confined environments while they are unable to move on a flat surface. It also constitutes a first step in the study of cell migration in more complex confined geometries such as living tissues.

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“…It is important to note that models based on thermodynamic arguments provide only theoretical limits within which the system can operate, but do not provide mechanistic details. Elegant models that analyze the relationship between filament assembly and force generation have been proposed at both the single filament and at the `actin-gel' level [61,70]. Integration of these mechanochemical models of filament assembly and force generation with models of the signaling networks might enable prediction of how signals from the extracellular matrix can control the rate of cell movement.…”

Section: From Signaling Network To Functionsmentioning

confidence: 99%

Computational approaches for modeling regulatory cellular networks

Eungdamrong

Iyengar

2004

Trends in Cell Biology

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Cellular components interact with each other to form networks that process information and evoke biological responses. A deep understanding of the behavior of these networks requires the development and analysis of mathematical models. In this article, different types of mathematical representations for modeling signaling networks are described, and the advantages and disadvantages of each type are discussed. Two experimentally well-studied signaling networks are then used as examples to illustrate the insight that could be gained through modeling. Finally, the modeling approach is expanded to describe how signaling networks might regulate cellular machines and evoke phenotypic behaviors.During the past two decades, substantial progress has been made in understanding the biochemical properties of cellular components, in addition to the organization of various molecular machines such as those involved in transcription and motility. From these studies of components and pathways, the design principles underlying cellular networks have emerged [1,2]. However, a substantial number of experiments is still needed to build up thè parts list' for a cell and to specify `parts function' in terms of cellular location, dynamics and regulatory organization. Because of the sheer number of components and interactions, the analysis of regulatory interactions is not easily achieved through intuition; even pathways and networks with few components are configured into systems that display complex behaviors. Hence, it is becoming increasingly clear that quantitative descriptions that lead to predictive models can be of great use in analyzing signaling pathways.Models of regulatory networks can be developed at various levels. Each level has its value. The simplest models of regulatory pathways and networks depict them as connections maps (http://stke.sciencemag.org), which are useful starting points for detailed analyses of signaling pathways. Although many signaling pathways have been identified by the study of binary reactions, connections are increasingly deduced from high-throughput experimental analyses of both protein-protein interactions [3][4][5][6] and protein location and expression patterns [7,8]. However, these connection maps are largely qualitative and, hence, only limited mathematical analysis can be undertaken. Such analyses often fall along the line of statistical correlations (`clustering'), which reveals co-regulation of each component [9], or an analysis of how the components are connected, which describes the statistical properties of the network as a whole [10][11][12]. An advantage of these models is that they can be developed for large numbers of components and interactions, and are useful in obtaining an To understand how extracellular signals evoke dynamic cellular responses, an analysis of the chemical reactions that constitute a biological system is needed. Typically, such models are built in three stages. First, a biochemical scheme that depicts the chemical reactions between the components in the...

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An Elastic Analysis of Listeria monocytogenes Propulsion

Cited by 196 publications

References 37 publications

Viscous-Fingering-Like Instability of Cell Fragments

Viscous-Fingering-Like Instability of Cell Fragments

Mechanisms of Cell Motion in Confined Geometries

Computational approaches for modeling regulatory cellular networks

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