Session M11: Mechanics of Cells and Tissues III

Live

The scaling of the properties of biological systems with their size is central to development and physiology. However, such scaling remains poorly explored in cell mechanics and mechanosensing. By examining how a Drosophila epithelium responds to morphogenetic forces, we identified a class of apical stress fibers (aSFs) anchored to adherens junctions. aSF number scales with cell apical area, in agreement with mathematical models showing that such scaling can prevent larger cells from elongating under mechanical stress. Furthermore, aSFs promote clustering of Hippo pathway components, thereby scaling Hippo activity and thus proliferation rate with area. We found that aSFs nucleate at tricellular junctions (TCJs), then move across the cell before eventually breaking, most often when they encounter another TCJ. This observation motivates a simple geometric mechanism that can quantitatively account for most of the scaling of aSF number with cell size: Because larger cells have more TCJs, they nucleate more aSFs; because these TCJs are typically farther apart, each aSF survives longer before breaking. Development, homeostasis, and repair entail changes in epithelial cell area driven by mechanical forces; our work highlights how, in turn, cell mechanosensitivity scales with cell area.   

Live

We perform combined atomic force microscopy (AFM) and fluorescence microscopy experiments to investigate the relationship between external temperature, soma volume and elastic modulus for cortical neurons. We measure how changes in ambient temperature affect the volume and the mechanical properties of neuronal cells. The experiments demonstrate that both the volume and the elastic modulus of the neuron soma vary with changes in temperature. Our results show a decrease by a factor of 2 in the soma elastic modulus as the ambient temperature increases from room (25C) to physiological (37C) temperature, while the volume of the soma increases by a factor of 1.3 during the same temperature sweep. Using high resolution AFM force mapping we measure the temperature - induced variations within different regions of the elasticity maps (low and high values of elastic modulus), and correlate these variations with the dynamics of the cytoskeleton. We quantify the change in soma volume with temperature and propose a simple theoretical model that relates this change with variations in elastic modulus. These results have significant implications for understanding neuron functions, as ambient temperature and physiological conditions could change during neuronal development.   

Live

The morphology of spread cells carries information about cell state at a single cell level. We have imaged thousands of cells in different experimental conditions and developed a large number of morphological parameters to quantify cell shape and cytoskeletal morphology. Using these images we demonstrated that cell morphology at the single cell level is a sensitive readout of cell state, and lower-dimensional projections can identify similar and dissimilar changes in cellular morphology[1]. However, morphological features capture aspects of the structure and organization of the cytoskeleton, which are inextricably linked with the shape a cell acquires on a surface. We extend our previous work to study the interelations between cell and nuclear shape and cytoskeletal organization. Using data-driven predictive modeling we show that morphological parameters are inter-related, and provide mechanistic insight into the determination of shape and the relation between shape and function.
[1] Alizadeh et. al. Cellular morphological features are predictive markers of cancer cell state, Computers in Biology and Medicine Oct. 2020   

Live

The ability of cells to take and change shape is a fundamental feature underlying development, wound repair, and tissue maintenance. Central to this process is physical and signaling interactions between the three cytoskeletal polymeric networks: F-actin, microtubules, and intermediate filaments (IFs). Vimentin is an IF protein that is essential to the mechanical resilience of cells and regulates cross-talk amongst the cytoskeleton, but its role in how cells sense and respond to the surrounding extracellular matrix is largely unclear. To investigate vimentin’s role in substrate sensing, we designed polyacrylamide hydrogels that mimic the elastic and viscoelastic nature of in vivo tissues. Using wild-type and vimentin-null mouse embryonic fibroblasts, we show that vimentin enhances cell spreading on viscoelastic substrates, even though it has little effect in the limit of purely elastic substrates. Our results provide compelling evidence that the vimentin cytoskeletal network is a physical modulator of how cells sense and respond to mechanical properties of their extracellular environment.   

Live

The ability of cells to move through small spaces depends on the mechanical properties of the cellular cytoskeleton and nuclear deformability. The cytoskeleton is comprised of three interacting, semi-flexible polymer networks: actin, microtubules, and intermediate filaments (IF). Vimentin is an IF protein that protects the cell nucleus from damage and provides elasticity to the cytoskeleton, but its role in how cells move through confining 3D spaces remains unclear. We develop a minimal model of cells moving through confined geometries that effectively includes all three types of cytoskeletal filaments. We find that increased bulk cytoskeletal stiffness, due to vimentin coupling to the actin cortex, leads to more deformed nuclei and decreased cell speed for channel geometries approximately less than the width of a cell. Vimentin also allows for more efficient stress transmission between the cell cortex and the nucleus to more readily control the position of the nucleus within the cell. We posit that as the nucleus position deviates further from the center of mass of the cell, microtubules become more oriented in a particular direction to enhance cell polarity. We provide a quantitative interpretation for recent cell motility experiments with and without vimentin   

Live

Shear forces in tissues are prevalent in many important biological processes including embryonic development, organogenesis and tumor invasion. The intercellular transmission of shear forces and the rheological response of a tissue remains, however, poorly understood. In this work, we use a minimal cell-based computational model to investigate the rheology of confluent epithelial tissues. We systematically probe the effects of single-cell stiffness, polarized cell motility and the strain rate on intercellular stress. We elucidate how the interplay of these parameters affects the collective organization of cell shapes, intercellular tension and cellular rearrangements. Based on these numerical results, we construct a continuum elasto-plastic description of tissue rheology.   

Live

Particle image velocimetry (PIV) has been successfully adapted from fluid dynamics to investigate collective cell motion, due to its strength in analyzing label-free images in particular phase-contrast images. In PIV-based analysis, the motion of any features is measured, without distinction of the two most notable features in phase-contrast images, cell boundaries and nuclei. Here we describe the use of deep learning to identify cell nuclei based on a UNet convolutional neural network for nucleus segmentation. This enables nuclear tracking and analysis of the individual and collective motion of cell groups. We will compare both individual and collective motion for sheets of epithelial cells of varying metastatic potential as an example of the behaviors that can be captured by our techniques.   

Live

During collective cell migration, cells coordinate their motion with their neighbors giving rise to collectively moving packs spanning multiple cell lengths. However, the physical mechanism controlling the collective pack size remains unclear. We hypothesized that one factor affecting pack size is coordination of propulsive traction between neighboring cells. To test this hypothesis, we used the self-propelled Voronoi model and experimental data on cell tractions and motion. We calibrated the model using a new experimental measurement of persistence time of propulsive traction and subsequently implemented an alignment of traction between each cell and its immediate neighbors. Comparison of spatial autocorrelation of cellular tractions and velocity between the experimental data and the model suggested the presence of coordinated traction between neighboring cells, thus confirming our hypothesis. The results give a new evidence for alignment of traction between neighboring cells, which is a physical mechanism by which cells coordinate motion with their neighbors.   

Live

Cellular protein patterns emerge from a combination of protein interactions, transport, and chemical reactions at the molecular level, and are key to information transmission during cellular processes. While pattern formation is considered a dynamical phase transition, protein patterns are inherently out of equilibrium, and a continuous influx of chemicals and energy are required to create and maintain these dissipative structures. What is the work needed to create and maintain a pattern, and what is the efficiency with which information exchanges through these patterns? Here we use chaotic dynamics of Rho-GTP patterns on the membrane of starfish oocytes as a model system to answer these crucial thermodynamic questions. We perform biochemical and metabolic perturbations to tune spatiotemporal oscillations of the patterns, and use information theory metrics, such as irreversibility, to quantify lower bounds of energy dissipation in the system. This approach provides a better understanding of the chaotic and nonequilibrium dynamics of Rho-GTP spatiotemporal patterns.   

Live

Like any other living organisms, micron-sized bacteria grow and thrive in diverse environments by efficiently allocating energy resources to growth, metabolism, shape maintenance and proliferation. To understand how a bacterium regulate its growth rate, cell shape and size in different environmental conditions, we develop a mechanistic model based on the budgeting of energy contributions for key cellular functions: nutrient import into the cell, energy expended for growth, cellular metabolism, shape maintenance and energy loss due to dissipation. In this framework, optimizing the rate of assimilation of physiological energy translates into optimizing cellular fitness for proliferation. This energy allocation theory allows us to uncover the feedback motifs for cellular adaptive response to chemical, mechanical, and thermal perturbations. By calibrating model parameters with available experimental data for the model organism E. coli, we quantitatively predict the growth and morpho dynamics of E. coli in different environmental perturbations induced by nutrient shifts, temperature changes and osmotic shocks.   

Live

The mechanical properties of most animal cells are dominated by the actin cortex, a ~ 0.5 µm thick layer of actin filaments including a multitude of associated proteins, which is attached to the inner side of the cell membrane and encapsulates the cytoplasm. Cells can actively change their shape and volume, but osmotic pressure prohibits any substantial volume change in response to external forces. We have mechanically indented suspended spherical with a dual optical tweezers set-up to measure response. For small, slow indentations we find a linear elastic response. To relate this response to cell material properties we use finite-element modeling to model the cell as a weakly pressurized elastic shell. We can match experimental results for up to 5 % indentation by assuming a 0.5 µm thick cortex with Young’s modulus of 6 KPa. For realistic parameters, volume changes are indeed entirely negligible and deformation is accompanied by an increase in surface area. Assuming a simple Hertz model, in contrast, would result in a cell modulus of 12 Pa. This finding might explain the widely different values of cell stiffness reported in the literature.   

Live

Cell migration is responsible for positive responses in one’s body in aid of healing of wounds, or infamously, invasion of cancer cells through the connective tissues. To better understand these major physiological phenomena, quantification of traction forces is necessary. The most common method to use is Traction Force Microscopy (TFM). Here, we have employed fluorescent superparamagnetic beads as detection markers. During the polymerization process of the polyacrylamide gel, an external magnetic field is applied and a single layer of superparamagnetic beads formed along the surface of the substrate. Such configuration reduces background noise, improving the spatial resolution to 50-nm with 40x magnification for the XY plane. Since the magnetic beads are located at the surface, marker positions are directly influenced by traction forces. Polyacrylamide gels of 1 through 30 kPa stiffness were used for the traction force measurement. The maximum traction force through the 48-hour cellular phase is measured to be 3.7 nN in 2 kPa, while the average traction force is registered to be 1.2 nN in 2 kPa. Increasing stiffness doesn’t change the maximum traction force, but increases the average force. The directions of the traction force exerted on the cell were analyzed for comparison.   

On Demand

The quantification of photonics localization is an important technique to study the molecular specific structural abnormalities. Chronic alcoholism results in medical, behavioral, and psychological problems which initially damages the brain at the cellular level. While the probiotic treatment helps in retrieving the physical damage to the alcoholic’s brain. The effects of probiotic Lactobacillus Plantarum treatment on chronic alcoholic brain cells/chromatin using the inverse participation ratio (IPR) a technique in a mouse model is reported. We construct optical lattices based on the confocal images and quantify the degree of structural disorder (L_d). The astrocytes, and microglial cells, and chromatin of brain cells are probed for molecular specific overexpression stained with appropriate dyes/proteins. The alcohol-treated glial cells and chromatin have an increase in the L_d which might be due to an adverse effect of alcohol. However, the decreases in the L_d of brain cells and chromatin when fed with alcohol and probiotics simultaneously confirm that probiotics soothe the brain and help to reduce the structural abnormalities. The potential application of this confocal-IPR technique to diagnosing alcohol’s effect and probiotic treatment in chronic alcoholism will be discussed.