A computational study of stress fiber-focal adhesion dynamics governing cell contractility

Mechanical Cues for Triggering and Regulating Cellular Movement Selectively at the Single-Cell Level

Cell motility plays important roles in many biophysical and physiological processes ranging from in vitro biomechanics, wound healing, to cancer metastasis. This work introduces a new means to trigger and regulate motility individually using transient mechanical stimulus applied to designated cells. Using BV2 microglial cells, our investigations indicate that motility can be reproducibly and reliably initiated using mechanical compression of the cells. The location and magnitude of the applied force impact the movement of the cell. Based on observations from this investigation and current knowledge of BV2 cellular motility, new physical insights are revealed into the underlying mechanism of force-induced single cellular movement. The process involves high degrees of myosin activation to repair actin cortex breakages induced by the initial mechanical compression, which leads to focal adhesion degradation, lamellipodium detachment, and finally, cell polarization and movement. Modern technology enables accurate control over force magnitude and location of force delivery, thus bringing us closer to programming cellular movement at the single-cell level. This approach is of generic importance to other cell types beyond BV2 cells and has the intrinsic advantages of being transient, non-toxic, and non-destructive, thus exhibiting high translational potentials including mechano-based therapy.

Multi-cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space

Cells interacting through an extracellular matrix (ECM) exhibit emergent behaviors resulting from collective intercellular interaction. In wound healing and tissue development, characteristic compaction of ECM gel is induced by multiple cells that generate tensions in the ECM fibers and coordinate their actions with other cells. Computational prediction of collective cell-ECM interaction based on first principles is highly complex especially as the number of cells increase. Here, we introduce a computationally-efficient method for predicting nonlinear behaviors of multiple cells interacting mechanically through a 3-D ECM fiber network. The key enabling technique is superposition of single cell computational models to predict multicellular behaviors. While cell-ECM interactions are highly nonlinear, they can be linearized accurately with a unique method, termed Dual-Faceted Linearization. This method recasts the original nonlinear dynamics in an augmented space where the system behaves more linearly. The independent state variables are augmented by combining auxiliary variables that inform nonlinear elements involved in the system. This computational method involves a) expressing the original nonlinear state equations with two sets of linear dynamic equations b) reducing the order of the augmented linear system via principal component analysis and c) superposing individual single cell-ECM dynamics to predict collective behaviors of multiple cells. The method is computationally efficient compared to original nonlinear dynamic simulation and accurate compared to traditional Taylor expansion linearization. Furthermore, we reproduce reported experimental results of multi-cell induced ECM compaction.

Collective behaviors of multiple cells interacting through an ECM are prohibitively complex to predict with a mechanistic computational model due to its highly nonlinear dynamics and high dimensional space. We introduce a methodology where nonlinear dynamics of single cells are superposed to predict collective multi-cellular behaviors through a developed linearization method. We represent nonlinear single cell dynamics with linear state equations by augmenting the independent state variables with a set of auxiliary variables. We then transform the linear augmented state equations to a low-dimensional latent model and superpose the linear latent models of individual cells to predict collective behaviors that emerge from multi-cellular interactions. The method successfully reproduced experimental results of cell-induced ECM compaction.

Effect of Loading History on Airway Smooth Muscle Cell-Matrix Adhesions

Integrin-mediated adhesions between airway smooth muscle (ASM) cells and the extracellular matrix (ECM) regulate how contractile forces generated within the cell are transmitted to its external environment. Environmental cues are known to influence the formation, size, and survival of cell-matrix adhesions, but it is not yet known how they are affected by dynamic fluctuations associated with tidal breathing in the intact airway. Here, we develop two closely related theoretical models to study adhesion dynamics in response to oscillatory loading of the ECM, representing the dynamic environment of ASM cells in vivo. Using a discrete stochastic-elastic model, we simulate individual integrin binding and rupture events and observe two stable regimes in which either bond formation or bond rupture dominate, depending on the amplitude of the oscillatory loading. These regimes have either a high or low fraction of persistent adhesions, which could affect the level of strain transmission between contracted ASM cells and the airway tissue. For intermediate loading, we observe a region of bistability and hysteresis due to shared loading between existing bonds; the level of adhesion depends on the loading history. These findings are replicated in a related continuum model, which we use to investigate the effect of perturbations mimicking deep inspirations (DIs). Because of the bistability, a DI applied to the high adhesion state could either induce a permanent switch to a lower adhesion state or allow a return of the system to the high adhesion state. Transitions between states are further influenced by the frequency of oscillations, cytoskeletal or ECM stiffnesses, and binding affinities, which modify the magnitudes of the stable adhesion states as well as the region of bistability. These findings could explain (in part) the transient bronchodilatory effect of a DI observed in asthmatics compared to a more sustained effect in normal subjects.

On the Measurement of Energy Dissipation of Adhered Cells with the Quartz Microbalance with Dissipation Monitoring

We previously reported the finding of a linear correlation between the change of energy dissipation (Δ D) of adhered cells measured with the quartz crystal microbalance with dissipation monitoring (QCM-D) and the level of focal adhesions of the cells. To account for this correlation, we have developed a theoretical framework for assessing the Δ D-response of adhered cells. We rationalized that the mechanical energy of an oscillating QCM-D sensor coupled with a cell monolayer is dissipated through three main processes: the interfacial friction through the dynamic restructuring (formation and rupture) of cell-extracellular matrix (ECM) bonds, the interfacial viscous damping by the liquid trapped between the QCM-D sensor and the basal membrane of the cell layer, and the intracellular viscous damping through the viscous slip between the cytoplasm and stress fibers as well as among stress fibers themselves. Our modeling study shows that the interfacial viscous damping by the trapped liquid is the primary process for energy dissipation during the early stage of the cell adhesion, whereas the dynamic restructuring of cell-ECM bonds becomes more prevalent during the later stage of the cell adhesion. Our modeling study also establishes a positive linear correlation between the Δ D-response and the level of cell adhesion quantified with the number of cell-ECM bonds, which corroborates our previous experimental finding. This correlation with a wide well-defined linear dynamic range provides a much needed theoretical validation of the dissipation monitoring function of the QCM-D as a powerful quantitative analytical tool for cell study.

An integrated enhancement and reconstruction strategy for the quantitative extraction of actin stress fibers from fluorescence micrographs

BACKGROUND

The stress fibers are prominent organization of actin filaments that perform important functions in cellular processes such as migration, polarization, and traction force generation, and whose collective organization reflects the physiological and mechanical activities of the cells. Easily visualized by fluorescence microscopy, the stress fibers are widely used as qualitative descriptors of cell phenotypes. However, due to the complexity of the stress fibers and the presence of other actin-containing cellular features, images of stress fibers are relatively challenging to quantitatively analyze using previously developed approaches, requiring significant user intervention. This poses a challenge for the automation of their detection, segmentation, and quantitative analysis.

RESULT

Here we describe an open-source software package, SFEX (Stress Fiber Extractor), which is geared for efficient enhancement, segmentation, and analysis of actin stress fibers in adherent tissue culture cells. Our method made use of a carefully chosen image filtering technique to enhance filamentous structures, effectively facilitating the detection and segmentation of stress fibers by binary thresholding. We subdivided the skeletons of stress fiber traces into piecewise-linear fragments, and used a set of geometric criteria to reconstruct the stress fiber networks by pairing appropriate fiber fragments. Our strategy enables the trajectory of a majority of stress fibers within the cells to be comprehensively extracted. We also present a method for quantifying the dimensions of the stress fibers using an image gradient-based approach. We determine the optimal parameter space using sensitivity analysis, and demonstrate the utility of our approach by analyzing actin stress fibers in cells cultured on various micropattern substrates.

CONCLUSION

We present an open-source graphically-interfaced computational tool for the extraction and quantification of stress fibers in adherent cells with minimal user input. This facilitates the automated extraction of actin stress fibers from fluorescence images. We highlight their potential uses by analyzing images of cells with shapes constrained by fibronectin micropatterns. The method we reported here could serve as the first step in the detection and characterization of the spatial properties of actin stress fibers to enable further detailed morphological analysis.

Mechanical remodeling of normally sized mammalian cells under a gravity vector

Translocation of the dense nucleus along a gravity vector initiates mechanical remodeling of a cell, but the underlying mechanisms of cytoskeletal network and focal adhesion complex (FAC) reorganization in a mammalian cell remain unclear. We quantified the remodeling of an MC3T3-E1 cell placed in upward-, downward-, or edge-on-orientated substrate. Nucleus longitudinal translocation presents a high value in downward orientation at 24 h or in edge-on orientation at 72 h, which is consistent with orientation-dependent distribution of perinuclear actin stress fibers and vimentin cords. Redistribution of total FAC area and fractionized super mature adhesion number coordinates this dependence at short duration. This orientation-dependent remodeling is associated with nucleus flattering and lamin A/C phosphorylation. Actin depolymerization or Rho-associated protein kinase signaling inhibition abolishes the orientation dependence of nucleus translocation, whereas tubulin polymerization inhibition or vimentin disruption reserves the dependence. A biomechanical model is therefore proposed for integrating the mechanosensing of nucleus translocation with cytoskeletal remodeling and FAC reorganization induced by a gravity vector.-Zhang, C., Zhou, L., Zhang, F., Lü, D., Li, N., Zheng, L., Xu, Y., Li, Z., Sun, S., Long, M. Mechanical remodeling of normally sized mammalian cells under a gravity vector.

Tissue-Mimicking Geometrical Constraints Stimulate Tissue-Like Constitution and Activity of Mouse Neonatal and Human-Induced Pluripotent Stem Cell-Derived Cardiac Myocytes

The present work addresses the question of to what extent a geometrical support acts as a physiological determining template in the setup of artificial cardiac tissue. Surface patterns with alternating concave to convex transitions of cell size dimensions were used to organize and orientate human-induced pluripotent stem cell (hIPSC)-derived cardiac myocytes and mouse neonatal cardiac myocytes. The shape of the cells, as well as the organization of the contractile apparatus recapitulates the anisotropic line pattern geometry being derived from tissue geometry motives. The intracellular organization of the contractile apparatus and the cell coupling via gap junctions of cell assemblies growing in a random or organized pattern were examined. Cell spatial and temporal coordinated excitation and contraction has been compared on plain and patterned substrates. While the α-actinin cytoskeletal organization is comparable to terminally-developed native ventricular tissue, connexin-43 expression does not recapitulate gap junction distribution of heart muscle tissue. However, coordinated contractions could be observed. The results of tissue-like cell ensemble organization open new insights into geometry-dependent cell organization, the cultivation of artificial heart tissue from stem cells and the anisotropy-dependent activity of therapeutic compounds.