Tracking particles with large displacements using energy minimization

Algorithm for semi-automatic detection of insulin granule exocytosis in human pancreatic β-cells

Image processing and analysis are two significant areas that are highly important for interpreting enormous amounts of data obtained from microscopy-based experiments. Several image analysis tools exist for the general detection of fundamental cellular processes, but tools to detect highly distinct cellular functions are few. One such process is exocytosis, which involves the release of vesicular content out of the cell. The size of the vesicles and the inherent differences in the imaging parameters demand specific analysis platforms for detecting exocytosis. In this direction, we have developed an image-processing algorithm based on Lagrangian particle tracking. The tool was developed to ensure that there is efficient detection of punctate structures initially developed by mathematical equations, fluorescent beads and cellular images with fluorescently labelled vesicles that can exocytose. The detection of these punctate structures using the tool was compared with other existing tools, such as find maxima in ImageJ and manual detection. The tool not only met the precision of existing solutions but also expedited the process, resulting in a more time-efficient solution. During exocytosis, there is a sudden dip in the intensity of the fluorescently labelled vesicles that look like punctate structures. The algorithm precisely locates the vesicles' coordinates and quantifies the variations in their respective intensities. Subsequently, the algorithm processes and retrieves pertinent information from large datasets surpassing that of conventional methods under our evaluation, affirming its efficacy. Furthermore, the tool exhibits adaptability for the image analysis of diverse cellular processes, requiring only minimal modifications to ensure accurate detection of exocytosis.

The role of crosslinking density in surface stress and surface energy of soft solids

Surface stress and surface energy are two fundamental parameters that determine the surface properties of any material. While it is commonly believed that the surface stress and surface energy of liquids are identical, the relationship between the two parameters in soft polymeric gels remains debatable. In this work, we measured the surface stress and surface energy of soft silicone gels with varying weight ratios of crosslinkers in soft wetting experiments. Above a critical density, k₀, the surface stress was found to increase significantly with crosslinking density while the surface energy remained unchanged. In this regime, we can estimate a non-zero surface elastic modulus that also increases with the ratio of crosslinkers. By comparing the surface mechanics of the soft gels with their bulk rheology, the surface properties near the critical density k₀ were found to be closely related to the underlying percolation transition of the polymer networks.

FM-Track: A fiducial marker tracking software for studying cell mechanics in a three-dimensional environment

Tracking the deformation of fiducial markers in the vicinity of living cells embedded in compliant synthetic or biological gels is a powerful means to study cell mechanics and mechanobiology in three-dimensional environments. However, current approaches to track and quantify three-dimensional (3D) fiducial marker displacements remain ad-hoc, can be difficult to implement, and may not produce reliable results. Herein, we present a compact software package entitled "FM-Track," written in the popular Python language, to facilitate feature-based particle tracking tailored for 3D cell micromechanical environment studies. FM-Track contains functions for pre-processing images, running fiducial marker tracking, and post-processing and visualization. FM-Track can thus aid the study of cellular mechanics and mechanobiology by providing an extensible software platform to more reliably extract complex local 3D cell contractile information in transparent compliant gel systems.

Vinculin and the mechanical response of adherent fibroblasts to matrix deformation

Cells respond to the mechanics of their environment. Mechanical cues include extracellular matrix (ECM) stiffness and deformation, which are primarily sensed through integrin-mediated adhesions. We investigated the impact of ECM deformation on cellular forces, measuring the time-evolution of traction forces of isolated mouse fibroblasts in response to stretch and release. Stretch triggered a marked increase of traction stresses and apparent stiffness. Expression of the focal adhesion protein vinculin not only increased baseline traction forces, but also increased dissipation of mechanical energy, which was correlated with the cells’ failure to recover baseline traction forces after release of stretch.

Rapid, topology-based particle tracking for high-resolution measurements of large complex 3D motion fields

Spatiotemporal tracking of tracer particles or objects of interest can reveal localized behaviors in biological and physical systems. However, existing tracking algorithms are most effective for relatively low numbers of particles that undergo displacements smaller than their typical interparticle separation distance. Here, we demonstrate a single particle tracking algorithm to reconstruct large complex motion fields with large particle numbers, orders of magnitude larger than previously tractably resolvable, thus opening the door for attaining very high Nyquist spatial frequency motion recovery in the images. Our key innovations are feature vectors that encode nearest neighbor positions, a rigorous outlier removal scheme, and an iterative deformation warping scheme. We test this technique for its accuracy and computational efficacy using synthetically and experimentally generated 3D particle images, including non-affine deformation fields in soft materials, complex fluid flows, and cell-generated deformations. We augment this algorithm with additional particle information (e.g., color, size, or shape) to further enhance tracking accuracy for high gradient and large displacement fields. These applications demonstrate that this versatile technique can rapidly track unprecedented numbers of particles to resolve large and complex motion fields in 2D and 3D images, particularly when spatial correlations exist.

Surface elastic constants of a soft solid

Solid interfaces have intrinsic elasticity. However, in most experiments, this is obscured by bulk stresses. Through microscopic observations of the contact-line geometry of a partially wetting droplet on an anisotropically stretched substrate, we measure two surface-elastic constants that quantify the linear dependence of the surface stress of a soft polymer gel on its strain. With these two parameters, one can predict surface stresses for general deformations of the material in the linear-elastic limit.