Multiple‐Particle Tracking and Two‐Point Microrheology in 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. 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.

Viscoelasticity of blood and viscoelastic blood analogues for use in polydymethylsiloxane in vitro models of the circulatory system

“…Note that two-point passive microrheology could not be performed due to aggregation of tracer particles at higher concentrations, resulting in poor statistics. 37 Passive microrheology is based on the diffusivity of tracer particles dispersed in a solution. For a spherical particle with a radius a diffusing in a Newtonian liquid of viscosity g, the particle's mean square displacement (MSD) is the averaged squared distance that the tracer particle travels in a given time interval, referred to as lag time (s)…”

Chapter 19 Mechanical Response of Cytoskeletal Networks

“…One approach is to develop techniques to measure mechanical properties of the cytoskeleton in living cells (Bicek et al, 2007;Brangwynne et al, 2007a;Crocker and Hoffman, 2007;Kasza et al, 2007;Panorchan et al, 2007;Radmacher, 2007). Such techniques will be critical in delineating the role of cytoskeletal elasticity in dynamic cellular processes.…”

Decorrelation correction for nanoparticle tracking analysis of dilute polydisperse suspensions in bulk flow

“…Some of the limitations of de-drifting dilute suspensions have been known for at least a decade [25], but the solution presented to date was suitable only for monodisperse suspensions [26,31]. Our work resolves known limitations of de-drifting associated with low particle concentration as well as identifies and resolves compositiondependent limitations.…”

“…The most widely used approaches serially extract Brownian behavior by first removing non-Brownian components of particle motion [25]. The effect is to revert a non-stationary process, such as random motion superposed with heterogeneous ballistic motion, to a stationary process.…”

“…The effect is to revert a non-stationary process, such as random motion superposed with heterogeneous ballistic motion, to a stationary process. The standard strategy in SPT has been to subtract an estimated non-Brownian motion defined by the ensemble-averaged displacement in each time step, a process called 'de-drifting' or 'de-trending' in the literature [25,26]. Additional processing of this estimate, such as convolution with a uniform weighting function, assumes Brownian and non-Brownian motion have separable characteristic timescales.…”