Elasticity, dynamics and relaxation in biopolymer networks

Kroy, Klaus

doi:10.1016/j.cocis.2005.10.001

Cited by 32 publications

(36 citation statements)

References 69 publications

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“…Such contributions could then be dissected with genetic or pharmacological interventions to tie together cell behavior at the molecular and mesoscopic scales. Less ambitiously, it was hoped that the cell mechanical response would at least closely resemble the response of various purified biopolymer gel models (typically F-actin), whose rheology has been intensively studied since the 1980's (Kroy, 2006). In reality, however, the rheological responses of cells measured to date have not contained identifiable molecular timescales and have not been satisfactorily reproduced by any biopolymer gel model yet studied.…”

Section: Introductionmentioning

confidence: 99%

Multiple‐Particle Tracking and Two‐Point Microrheology in Cells

Crocker

Hoffman

2007

Methods in Cell Biology

190

195

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Mechanical stress and stiffness are increasingly recognized to play important roles in numerous cell biological processes, notably cell differentiation and tissue morphogenesis. Little definite is known, however, about how stress propagates through different cell structures or how it is converted to biochemical signals via mechanotransduction, due in large part to the difficulty of interpreting many cell mechanics experiments. A newly developed technique, two-point microrheology (TPM), can provide highly interpretable, quantitative measurements of cells' frequency-dependent shear moduli and spectra of their fluctuating intracellular stresses. TPM is a non-invasive method based on measuring the Brownian motion of large numbers of intracellular particles using multiple particle tracking. While requiring only hardware available in many cell biology laboratories-a phase microscope and digital video camera, as a statistical technique, it also requires the automated analysis of many thousands of micrographs. Here we describe in detail the algorithms and software tools used for such large-scale multiple particle tracking, as well as common sources of error and the microscopy methods needed to minimize them. Moreover, we describe the physical principles behind TPM and other passive microrheology methods, their limitations, and typical results for cultured epithelial cells. ABSTRACT Mechanical stress and stiffness are increasingly recognized to play important roles in numerous cell biological processes, notably cell differentiation and tissue morphogenesis. Little definite is known, however, about how stress propagates through different cell structures or how it is converted to biochemical signals via mechanotransduction, due in large part to the difficulty of interpreting many cell mechanics experiments. A newly developed technique, two-point microrheology (TPM), can provide highly interpretable, quantitative measurements of cells' frequency-dependent shear moduli and spectra of their fluctuating intracellular stresses. TPM is a non-invasive method based on measuring the Brownian motion of large numbers of intracellular particles using multiple particle tracking. While requiring only hardware available in many cell biology laboratories-a phase microscope and digital video camera, as a statistical technique, it also requires the automated analysis of many thousands of micrographs. Here we describe in detail the algorithms and software tools used for such large-scale multiple particle tracking, as well as common sources of error and the microscopy methods needed to minimize them. Moreover, we describe the physical principles behind TPM and other passive microrheology methods, their limitations, and typical results for cultured epithelial cells.

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Section: Introductionmentioning

confidence: 99%

Multiple‐Particle Tracking and Two‐Point Microrheology in Cells

Crocker

Hoffman

2007

Methods in Cell Biology

190

195

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“…[20,[26][27][28]. The tube properties are characterized by the entanglement length L e (the arc length over which the bending energy equals the confinement energy) or equivalently by the tube diameter d. Both quantities are related by the basic roughness relation d 2 L 3 e / p of the WLC, which also implies that the transverse mean-square deflections from a clamped end grow like the third power of the wavelength.…”

Section: The Tube Modelmentioning

confidence: 99%

Dynamic structure factor of a stiff polymer in a glassy solution

2008

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Abstract. We provide a comprehensive overview of the current theoretical understanding of the dynamic structure factor of stiff polymers in semidilute solution based on the wormlike chain (WLC) model. We extend previous work by computing exact numerical coefficients and an expression for the dynamic mean square displacement (MSD) of a free polymer and compare various common approximations for the hydrodynamic interactions, which need to be treated accurately if one wants to extract quantitative estimates for model parameters from experimental data. A recent controversy about the initial slope of the dynamic structure factor is thereby resolved. To account for the interactions of the polymer with a surrounding (sticky) polymer solution, we analyze an extension of the WLC model, the glassy wormlike chain (GWLC), which predicts near power-law and logarithmic long-time tails in the dynamic structure factor.

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“…At large deformation (above 3.6 strain) the polymer coil is highly stretched, the chain presumably deviates from Gaussian statistics and final hardening is observed. Elasticity of a single polymer chain and polymeric networks has been well studied both theoretically and experimentally in biological systems and gels 21,20,22,23 ; however, stretching of polymer chains in melt has not been directly captured from rheology due to the presence of viscous contributions to the measured stress.…”

Section: Resultsmentioning

confidence: 99%

Mechanistic model for deformation of polymer nanocomposite melts under large amplitude shear

Şenses

Akcora

2013

J Polym Sci B Polym Phys

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We report the mechanical response of a model nanocomposite system of poly(styrene) (PS)silica to large-amplitude oscillatory shear deformations. Nonlinear behavior of PS nanocomposites is discussed with the changes in particle dispersion upon deformation to provide a complete physical picture of their mechanical properties. The elastic stresses for the particle and polymer are resolved by decomposing the total stress into its purely elastic and viscous components for composites at different strain levels within a cycle of deformation. We propose a mechanistic model which captures the deformation of particles and polymer networks at small and large strains, respectively. We show, for the first time, that chain stretching in a polymer nanocomposite obtained in large amplitude oscillatory deformation is in good agreement with the nonlinear chain deformation theory of polymeric networks.

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Elasticity, dynamics and relaxation in biopolymer networks

Cited by 32 publications

References 69 publications

Multiple‐Particle Tracking and Two‐Point Microrheology in Cells

Multiple‐Particle Tracking and Two‐Point Microrheology in Cells

Dynamic structure factor of a stiff polymer in a glassy solution

Mechanistic model for deformation of polymer nanocomposite melts under large amplitude shear

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