Optimality of Force Transmission in a Motor-Clutch Cellular Adhesion Model

Benjamin Bangasser, Steven Rosenfeld, David Odde
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dez2wau7t5aqvklzwrcsreuwq4" style="color: black;">Biophysical Journal</a> </i> &nbsp;
dual-color Ca 2þ imaging at cytosol and primary cilia revealed highly resolved propagation of Ca 2þ from the cytosol into distal tip of primary cilia in response to ATP. In addition, we provide direct evidence of dynamic Ca 2þ signaling within primary cilia immediately after cilia bending caused by a mechanical flow. Therefore, the cilia-targeted GECI serves as a powerful tool to elucidating the roles of Ca 2þ signaling in regulating sensory functions of primary cilia. The present approach is
more &raquo; ... adily generalized to other signaling molecules and to other sub-micron cellular compartments. Tumor cell invasion requires navigation of tissue barriers of varying architecture. For instance, the extreme invasiveness of glioma cells is facilitated by their ability to migrate diffusely through brain parenchyma and approach guidance tracks along blood vessels. Brain parenchyma has a distinct physical structure characterized by densely packed neural cell processes and sub-micron extracellular space, and is largely devoid of the fibrillar collagen scaffolding typically found in stromal tissue. Consequently, glioma cells migrating in brain slices exhibit a distinct type of motility, with branched protrusions and hourglass-shaped cell-body deformations that help squeeze cells through tight spaces (Beadle et al., Mol. Biol. Cell 2008; 19(8):3357-68). However, the mechanistic details of this unique mode of motility remain incompletely understood. To address this question, we synthesized brain-mimetic nanoporous, non-fibrillar extracellular matrices (ECMs) based on cross-linked hyaluronic acid (HA), and verified that threedimensional glioma cell motility in these ECMs strikingly recapitulated the phenotype seen in brain slices (Ananthanarayanan et al. Biomaterials 2011; 32(31):7913-23). Eliminating RGD peptides from the ECM abolished invasion, suggesting a requirement for integrin-mediated adhesions for this mode of motility. Increasing matrix density, or inhibiting myosin-based cellular contractility by blebbistatin or shRNA-induced knockdown of Myosin IIA severely impaired motility. We report preliminary results from two sets of studies: First, we investigate the balance of protrusive and contractile forces in glioma cell motility by pharmacologically and genetically manipulating the Rho GTPases RhoA, Rac1, and Cdc42. Second, we explore the involvement of actinnucleating proteins such as Arp2/3 and formins in the protrusive dynamics observed in this mode of motility. Our studies help define the signaling mechanisms underlying the distinctive glioma cell motility observed in dense matrices. Hearing starts when sound-evoked mechanical vibrations of the hair-cell bundle activate mechanosensitive ion channels, giving birth to an electrical signal. As for any mechanical machine, friction impedes movements of the hair bundle and thus constrains the sensitivity and frequency selectivity of auditory transduction. Viscous drag by the surrounding fluid on the micrometric hair-bundle structure provides a minimum source of friction. Using dynamic force measurements on single hair-cell bundles, we demonstrate here that the opening and closing of the transduction channels produce internal friction forces that can dominate hydrodynamic drag. A theoretical analysis reveals that channel friction arises from coupling the dynamics of the conformational change associated with channel gating to tip-link tension. In return, channel properties can control hair-bundle friction, with faster channels producing smaller friction. We propose that this intrinsic source of friction contributes to the process that sets the hair cell's characteristic frequency of responsiveness. Motile cilia are fascinating structures, evolved very early in eukaryotes, and highly conserved throughout organisms of very different complexity. They generate the transport of fluid by periodic beating, through remarkably organized behaviour in space and time (e.g. collective waves). This allows simple unicellular organisms to swim, and allows transport of fluid in the airways and within the brain in humans. It is not understood how these spatiotemporal patterns emerge, and what sets their properties. Individual cilia are nonequilibrium systems with many degrees of freedom. We have reduced these to fewer parameters, representing the effective force laws that drive oscillations, and paralleled with nonlinear phase oscillators studied in physics. At this level, the beating cilia become sources for a velocity field, which can be approximated (in the far field) by the Oseen tensor, or taking into account the presence of solid boundaries if necessary. This becomes a more tractable (albeit still non-linear and entirely not trivial) system on which to try and understand the emergence of collective dynamical states, and how the macroscopic characteristics are linked to the microscopic cilia parameters. This presentation will report on insight gained by studying synthetic model phase oscillators, where colloidal particles are driven by optical traps (this keeps the length and time-scales of the living system, including the important role of thermal noise). The complex structural details of the cilia are coarsegrained into the details of how the colloidal particles are driven. We explore experimentally various colloidal models, finding in each case the conditions for optimal coupling. The applicability of this approach to biological data is illustrated by successfully mapping the behaviour of cilia in the alga Chlamydomonas onto the coarse-grained model, and linking the dynamics in a manyoscillator system to embryonic tissue development. 1233-Plat Characterization of Different Dynamic Modes of a Crawling Caenorhabditis Elegans by Direct Measurement of Traction Force Jin-Sung Park, Song Ih Ahn, Jennifer H. Shin. Mechanical Engineering, KAIST, Daejeon, Republic of Korea. The traction force microscopy (TFM) is a technique widely used to measure cellular traction forces that are closely related to cell migration, mechanical signaling, and other cellular functions. We apply the TFM to characterize the dynamic force patterns in different crawling modes of Caenorhabditis elegans (C. elegans) on soft gel matrices of different stiffness. When C. elegans crawls forward, it concentrates the thrust force to localized regions along the body rather than forming a uniform load distribution in its lateral direction. The dynamic force distributions appeared differentially in different behavioral modes of C. elegans including the forward, backward movement, as well as a sharp turn called the U-turn. Such dynamic behaviors of C. elegans might be considered as an effort to minimize drag resistance by reducing contact area between its body and gel surface, and these observations are very similar to recent experimental study suggested for the slithering of snake on flat surface. Microenvironmental mechanics play an important, but variable, role in determining cell morphology, traction, migration, proliferation, and differentiation with potential impacts on tumor development, growth, and invasion. Interestingly, some cell types have shown increasing migration and traction force as a function of substrate stiffness, while others have shown decreasing migration and traction force. These seemingly contradictory results may be explained by a motor-clutch model of cellular adhesion and force transmission which exhibits a maximum in traction force with respect to stiffness and may be tuned to different stiffness optima. Both stochastic and deterministic castings of the motor-clutch model provide a basis to explain the tuning of cells to different microenvironmental mechanics. A sensitivity analysis of the stochastic model suggests that molecular motors and adhesion clutches must approximately balance each other to achieve stiffness sensitivity. Consequently, individual parameters changes, which favor only the motors or the clutches, have little effect in shifting the stiffness optimum because the system loses stiffness sensitivity altogether. However, dual parameters changes, such that motors and clutches remain balanced, can shift the stiffness optimum over several orders of magnitude. This optimum occurs on the stiffness at which the time for all clutches to bind equals the cycle time of adhesion load and fail. At stiffnesses above this optimum, fewer than the maximum clutches bind, so the clutches are not utilized to their fullest extent. At stiffnesses below the optimum, clutches spontaneously fail at low loads because of the long cycle time, again resulting in an inefficient use of clutches. This determinant of the optimum stiffness was applied in conjunction with the deterministic motor-clutch model to derive a dimensionless quantity defining model behavior at any particular stiffness.
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