A novel approach to high accuracy of video-based microrheology

Decomposition of cell activities revealing the role of the cell cycle in driving biofunctional heterogeneity

Heterogeneity of cell phenotypes remains a barrier in progressing cell research and a challenge in conquering cancer-related drug resistance. Cell morphology, the most direct property of cell phenotype, evolves along the progression of the cell cycle; meanwhile, cell motility, the dynamic property of cell phenotype, also alters over the cell cycle. However, a quantifiable research understanding the relationship between the cell cycle and cell migration is missing. Herein, we coordinate the migratory behaviours of NIH 3T3 fibroblasts to their corresponding phases of the cell cycle, the G1, the S, and the G2 phases, and explain the relationship through the spatiotemporal arrangements between the Rho GTPases’ signals and cyclin-dependent kinase inhibitors, p21^Cip1, and p27^Kip1. Taken together, we demonstrate that both cell morphology and the dynamic subcellular behaviour are homogenous within each stage of the cell cycle phases but heterogenous between phases through quantitative cell analyses and an interactive molecular mechanism between the cell cycle and cell migration, posing potential implications in countering drug resistance.

Multi-frequency passive and active microrheology with optical tweezers

Optical tweezers have attracted significant attention for microrheological applications, due to the possibility of investigating viscoelastic properties in vivo which are strongly related to the health status and development of biological specimens. In order to use optical tweezers as a microrheological tool, an exact force calibration in the complex system under investigation is required. One of the most promising techniques for optical tweezers calibration in a viscoelastic medium is the so-called active–passive calibration, which allows determining both the trap stiffness and microrheological properties of the medium with the least a-priori knowledge in comparison to the other methods. In this manuscript, we develop an optimization of the active–passive calibration technique performed with a sample stage driving, whose implementation is more straightforward with respect to standard laser driving where two different laser beams are required. We performed microrheological measurements over a broad frequency range in a few seconds implementing an accurate multi-frequency driving of the sample stage. The optical tweezers-based microrheometer was first validated by measuring water, and then exemplarily applied to more viscous medium and subsequently to a viscoelastic solution of methylcellulose in water. The described method paves the way to microrheological precision metrology in biological samples with high temporal- and spatial-resolution allowing for investigation of even short time-scale phenomena.

Microrheology for biomaterial design

Microrheology analyzes the microscopic behavior of complex materials by measuring the diffusion and transport of embedded particle probes. This experimental method can provide valuable insight into the design of biomaterials with the ability to connect material properties and biological responses to polymer-scale dynamics and interactions. In this review, we discuss how microrheology can be harnessed as a characterization method complementary to standard techniques in biomaterial design. We begin by introducing the core principles and instruments used to perform microrheology. We then review previous studies that incorporate microrheology in their design process and highlight biomedical applications that have been supported by this approach. Overall, this review provides rationale and practical guidance for the utilization of microrheological analysis to engineer novel biomaterials.

A comparison of methods to assess cell mechanical properties

The mechanical properties of cells influence their cellular and subcellular functions, including cell adhesion, migration, polarization, and differentiation, as well as organelle organization and trafficking inside the cytoplasm. Yet reported values of cell stiffness and viscosity vary substantially, which suggests differences in how the results of different methods are obtained or analyzed by different groups. To address this issue and illustrate the complementarity of certain approaches, here we present, analyze, and critically compare measurements obtained by means of some of the most widely used methods for cell mechanics: atomic force microscopy, magnetic twisting cytometry, particle-tracking microrheology, parallel-plate rheometry, cell monolayer rheology, and optical stretching. These measurements highlight how elastic and viscous moduli of MCF-7 breast cancer cells can vary 1,000-fold and 100-fold, respectively. We discuss the sources of these variations, including the level of applied mechanical stress, the rate of deformation, the geometry of the probe, the location probed in the cell, and the extracellular microenvironment.

The Biophysics of 3D Cell Migration

Three-dimensional (3D) cell culture systems have gained increasing interest not only for 3D migration studies but also for their use in drug screening, tissue engineering, and ex vivo modeling of metastatic behavior in the field of cancer biology and morphogenesis in the field of developmental biology. The goal of studying cells in a 3D context is to attempt to more faithfully recapitulate the physiological microenvironment of tissues, including mechanical and structural parameters that we envision will reveal more predictive data for development programs and disease states. In this review, we discuss the pros and cons of several well-characterized 3D cell culture systems for performing 3D migration studies. We discuss the intracellular and extracellular signaling mechanisms that govern cell migration. We also describe the mathematical models and relevant assumptions that can be used to describe 3D cell movement.

Characterizing gelatin hydrogel viscoelasticity with diffusing colloidal probe microscopy

In this study, we investigate viscoelasticity in gelatin hydrogels using diffusing colloidal probe microscopy (DCPM) to directly measure the elastic potential energy interaction between colloidal probes and the underlying viscoelastic media. Gelatin samples are prepared in four different concentrations between 0.3wt% and 0.6wt% to examine changes in viscoelasticity with concentration. A force balance describing the interaction between the colloidal probes and the hydrogel as a spring-damper system lead to a simple model for mean square displacement. A histogram of locations sampled by the colloidal probes is directly related to the elastic potential energy and the effective spring constant of the gelatin hydrogels. The effective spring constant is a fixed parameter used in the mean square displacement model to find effective viscosity. These parameters are comparable to viscoelastic parameters obtain by a microrheology analysis of two-dimensional mean square displacements. These results can serve as a guide for assessing hydrogel systems where viscoelastic properties are an important factor in biomaterial design.

Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis

Cell migration is an essential process in organism development and physiological maintenance. Although current methods permit accurate comparisons of the effects of molecular manipulations and drug applications on cell motility, effects of alterations in subcellular activities on motility cannot be fully elucidated from those methods. Here, we develop a strategy termed cell-nuclear (CN) correlation to parameterize represented dynamic subcellular activities and to quantify their contributions in mesenchymal-like migration. Based on the biophysical meaning of the CN correlation, we propose a cell migration potential index (CMPI) to measure cell motility. When the effectiveness of CMPI was evaluated with respect to one of the most popular cell migration analysis methods, Persistent Random Walk, we found that the cell motility estimates among six cell lines used in this study were highly consistent between these two approaches. Further evaluations indicated that CMPI can be determined using a shorter time period and smaller cell sample size, and it possesses excellent reliability and applicability, even in the presence of a wide range of noise, as might be generated from individual imaging acquisition systems. The novel approach outlined here introduces a robust strategy through an analysis of subcellular locomotion activities for single cell migration assessment.

Differential vesicular sorting of AMPA and GABAA receptors

In mature neurons AMPA receptors cluster at excitatory synapses primarily on dendritic spines, whereas GABAA receptors cluster at inhibitory synapses mainly on the soma and dendritic shafts. The molecular mechanisms underlying the precise sorting of these receptors remain unclear. By directly studying the constitutive exocytic vesicles of AMPA and GABAA receptors in vitro and in vivo, we demonstrate that they are initially sorted into different vesicles in the Golgi apparatus and inserted into distinct domains of the plasma membrane. These insertions are dependent on distinct Rab GTPases and SNARE complexes. The insertion of AMPA receptors requires SNAP25-syntaxin1A/B-VAMP2 complexes, whereas insertion of GABAA receptors relies on SNAP23-syntaxin1A/B-VAMP2 complexes. These SNARE complexes affect surface targeting of AMPA or GABAA receptors and synaptic transmission. Our studies reveal vesicular sorting mechanisms controlling the constitutive exocytosis of AMPA and GABAA receptors, which are critical for the regulation of excitatory and inhibitory responses in neurons.

Analytical tools for single-molecule fluorescence imaging in cellulo

Recent technological advances in cutting-edge ultrasensitive fluorescence microscopy have allowed single-molecule imaging experiments in living cells across all three domains of life to become commonplace. Single-molecule live-cell data is typically obtained in a low signal-to-noise ratio (SNR) regime sometimes only marginally in excess of 1, in which a combination of detector shot noise, sub-optimal probe photophysics, native cell autofluorescence and intrinsically underlying stochasticity of molecules result in highly noisy datasets for which underlying true molecular behaviour is non-trivial to discern. The ability to elucidate real molecular phenomena is essential in relating experimental single-molecule observations to both the biological system under study as well as offering insight into the fine details of the physical and chemical environments of the living cell. To confront this problem of faithful signal extraction and analysis in a noise-dominated regime, the 'needle in a haystack' challenge, such experiments benefit enormously from a suite of objective, automated, high-throughput analysis tools that can home in on the underlying 'molecular signature' and generate meaningful statistics across a large population of individual cells and molecules. Here, I discuss the development and application of several analytical methods applied to real case studies, including objective methods of segmenting cellular images from light microscopy data, tools to robustly localize and track single fluorescently-labelled molecules, algorithms to objectively interpret molecular mobility, analysis protocols to reliably estimate molecular stoichiometry and turnover, and methods to objectively render distributions of molecular parameters.

Statistical analysis of cell migration in 3D using the anisotropic persistent random walk model

Cell migration through 3D extracellular matrices (ECMs) is crucial to the normal development of tissues and organs and in disease processes, yet adequate analytical tools to characterize 3D migration are lacking. The motility of eukaryotic cells on 2D substrates in the absence of gradients has long been described using persistent random walks (PRWs). Recent work shows that 3D migration is anisotropic and features an exponential mean cell velocity distribution, rendering the PRW model invalid. Here we present a protocol for the analysis of 3D cell motility using the anisotropic PRW model. The software, which is implemented in MATLAB, enables statistical profiling of experimentally observed 2D and 3D cell trajectories, and it extracts the persistence and speed of cells along primary and nonprimary directions and an anisotropic index of migration. Basic computer skills and experience with MATLAB software are recommended for successful use of the protocol. This protocol is highly automated and fast, taking <30 min to analyze trajectory data per biological condition.

Microrheology of cells with magnetic force modulation atomic force microscopy

We propose a magnetic force modulation method to measure the stiffness and viscosity of living cells using a modified AFM apparatus. An oscillating magnetic field makes a magnetic cantilever oscillate in contact with the sample, producing a small AC indentation. By comparing the amplitude of the free cantilever motion (A0) with the motion of the cantilever in contact with the sample (A1), we determine the sample stiffness and viscosity. To test the method, the frequency-dependent stiffness of 3T3 fibroblasts was determined as a power law k(s)(f) = α + β(f/f¯)(γ) (α = 7.6 × 10(-4) N m(-1), β = 1.0 × 10(-4) N m(-1), f¯ = 1 Hz, γ = 0.6), where the coefficient γ = 0.6 is in good agreement with rheological data of actin solutions with concentrations similar to those in cells. The method also allows estimation of the internal friction of the cells. In particular we found an average damping coefficient of 75.1 μN s m(-1) for indentation depths ranging between 1.0 μm and 2.0 μm.

Depth-resolved cellular microrheology using HiLo microscopy

It is increasingly important to measure cell mechanical properties in three-dimensional environments. Particle tracking microrheology (PTM) can measure cellular viscoelastic properties; however, out-of-plane data can introduce artifacts into these measurements. We developed a technique that employs HiLo microscopy to reduce out-of-plane contributions. This method eliminated signals from 90% of probes 0.5 μm or further from the focal plane, while retaining all in-plane probes. We used this technique to characterize live-cell bilayers and found that there were significant, frequency-dependent changes to the extracted cell moduli when compared to conventional analysis. Our results indicate that removal of out-of-plane information is vital for accurate assessments of cell mechanical properties.

Interactive, computer-assisted tracking of speckle trajectories in fluorescence microscopy: application to actin polymerization and membrane fusion

Analysis of particle trajectories in images obtained by fluorescence microscopy reveals biophysical properties such as diffusion coefficient or rates of association and dissociation. Particle tracking and lifetime measurement is often limited by noise, large mobilities, image inhomogeneities, and path crossings. We present Speckle TrackerJ, a tool that addresses some of these challenges using computer-assisted techniques for finding positions and tracking particles in different situations. A dynamic user interface assists in the creation, editing, and refining of particle tracks. The following are results from application of this program: 1), Tracking single molecule diffusion in simulated images. The shape of the diffusing marker on the image changes from speckle to cloud, depending on the relationship of the diffusion coefficient to the camera exposure time. We use these images to illustrate the range of diffusion coefficients that can be measured. 2), We used the program to measure the diffusion coefficient of capping proteins in the lamellipodium. We found values ∼0.5 μm(2)/s, suggesting capping protein association with protein complexes or the membrane. 3), We demonstrate efficient measuring of appearance and disappearance of EGFP-actin speckles within the lamellipodium of motile cells that indicate actin monomer incorporation into the actin filament network. 4), We marked appearance and disappearance events of fluorescently labeled vesicles to supported lipid bilayers and tracked single lipids from the fused vesicle on the bilayer. This is the first time, to our knowledge, that vesicle fusion has been detected with single molecule sensitivity and the program allowed us to perform a quantitative analysis. 5), By discriminating between undocking and fusion events, dwell times for vesicle fusion after vesicle docking to membranes can be measured.

High-throughput ballistic injection nanorheology to measure cell mechanics

High-throughput ballistic injection nanorheology is a method for the quantitative study of cell mechanics. Cell mechanics are measured by ballistic injection of submicron particles into the cytoplasm of living cells and tracking the spontaneous displacement of the particles at high spatial resolution. The trajectories of the cytoplasm-embedded particles are transformed into mean-squared displacements, which are subsequently transformed into frequency-dependent viscoelastic moduli and time-dependent creep compliance of the cytoplasm. This method allows for the study of a wide range of cellular conditions, including cells inside a 3D matrix, cell subjected to shear flows and biochemical stimuli, and cells in a live animal. Ballistic injection lasts <1 min and is followed by overnight incubation. Multiple particle tracking for one cell lasts <1 min. Forty cells can be examined in <1 h.

Cell cycle-dependent alteration in NAC1 nuclear body dynamics and morphology

NAC1, a BTB/POZ family member, has been suggested to participate in maintaining the stemness of embryonic stem cells and has been implicated in the pathogenesis of human cancer. In ovarian cancer, NAC1 upregulation is associated with disease aggressiveness and with the development of chemoresistance. Like other BTB/POZ proteins, NAC1 forms discrete nuclear bodies in non-dividing cells. To investigate the biological role of NAC1 nuclear bodies, we characterized the expression dynamics of NAC1 nuclear bodies during different phases of the cell cycle. Fluorescence recovery after photobleaching assays revealed that NAC1 was rapidly exchanged between the nucleoplasm and NAC1 nuclear bodies in interphase cells. The number of NAC1 bodies significantly increased and their size decreased in the S phase as compared to the G₀/G₁ and G₂ phases. NAC1 nuclear bodies disappeared and NAC1 became diffuse during mitosis. NAC1 nuclear bodies reappeared immediately after completion of mitosis. These results indicate that a cell cycle-dependent regulatory mechanism controls NAC1 body formation in the nucleus and suggest that NAC1 body dynamics are associated with mitosis or cytokinesis.

Analysis of video-based microscopic particle trajectories using Kalman filtering

The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes.

A general method for improving spatial resolution by optimization of electron multiplication in CCD imaging

The electron-multiplying charge-coupled device (EMCCD) camera possesses an electron multiplying function that can effectively convert the weak incident photon signal to amplified electron output, thereby greatly enhancing the contrast of the acquired images. This device has become a popular photon detector in single-cell biophysical assays to enhance subcellular images. However, the quantitative relationship between the resolution in such measurements and the electron multiplication setting in the EMCCD camera is not well-understood. We therefore developed a method to characterize the exact dependence of the signal-to-noise-ratio (SNR) on EM gain settings over a full range of incident light intensity. This information was further used to evaluate the EMCCD performance in subcellular particle tracking. We conclude that there are optimal EM gain settings for achieving the best SNR and the best spatial resolution in these experiments. If it is not used optimally, electron multiplication can decrease the SNR and increases spatial error.