When cells migrate through constricting pores, they incur DNA damage and develop genomic variation. Experiments show that this damage is not due to DNA breakage from mechanical stress on chromatin in the deformed nucleus. Here we propose a model for a mechanism by which nuclear deformation can lead to DNA damage. We treat the nucleus as an elastic-fluid system with an elastic component (chromatin) and fluid component that can be squeezed out when the nucleus is deformed. We couple the elastic-fluid model to the kinetics of DNA breakage and repair by assuming that the local volume fraction of the elastic component controls the rate of damage per unit volume due to naturally occurring DNA breaks, whereas the volume fraction of the fluid component controls the rate of repair of DNA breaks per unit volume by repair factors, which are soluble in the fluid. By comparing our results to a number of experiments on controlled migration through pores, we show that squeeze-out of the fluid, and hence of the mobile repair factors, is sufficient to account for the extent of DNA damage and genomic variation observed experimentally. We also use our model for migration through a cylindrical pore to estimate the variation with tissue stiffness of the mutation rate in tumors.

In the beating heart, cardiac myocytes (CMs) contract in a coordinated fashion, generating contractile wave fronts that propagate through the heart with each beat. Coordinating this wave front requires fast and robust signaling mechanisms between CMs. The primary signaling mechanism has long been identified as electrical: gap junctions conduct ions between CMs, triggering membrane depolarization, intracellular calcium release, and actomyosin contraction. In contrast, we propose here that, in the early embryonic heart tube, the signaling mechanism coordinating beats is mechanical rather than electrical. We present a simple biophysical model in which CMs are mechanically excitable inclusions embedded within the extracellular matrix (ECM), modeled as an elastic-fluid biphasic material. Our model predicts strong stiffness dependence in both the heartbeat velocity and strain in isolated hearts, as well as the strain for a hydrogel-cultured CM, in quantitative agreement with recent experiments. We challenge our model with experiments disrupting electrical conduction by perfusing intact adult and embryonic hearts with a gap junction blocker, β-glycyrrhetinic acid (BGA). We find this treatment causes rapid failure in adult hearts but not embryonic hearts—consistent with our hypothesis. Last, our model predicts a minimum matrix stiffness necessary to propagate a mechanically coordinated wave front. The predicted value is in accord with our stiffness measurements at the onset of beating, suggesting that mechanical signaling may initiate the very first heartbeats.

At zero temperature a disordered solid corresponds to a local minimum in the energy landscape. As the temperature is raised or the system is driven with a mechanical load, the system explores different minima via dynamical events in which particles rearrange their relative positions. We have shown recently that the dynamics of particle rearrangements are strongly correlated with a structural quantity associated with each particle, “softness”, which we can identify using supervised machine learning. Particles of a given softness have a well-defined energy scale that governs local rearrangements; because of this property, softness greatly simplifies our understanding of glassy dynamics. Here we investigate the correlation of softness with other commonly used structural quantities, such as coordination number and local potential energy. We show that although softness strongly correlates with these properties, its predictive power for rearrangement dynamics is much higher. We introduce a useful metric for quantifying the quality of structural quantities as predictors of dynamics. We hope that, in the future, authors introducing new structural measures of dynamics will compare their proposals quantitatively to softness using this metric. We also show how softness correlations give insight into rearrangements. Finally, we explore the physical meaning of softness using unsupervised dimensionality reduction and reduced curve-fitting models, and show that softness can be recast in a form that is amenable to analytical treatment.

Chromosome segregation during cell division depends on interactions of kinetochores with dynamic microtubules (MTs). In many eukaryotes, each kinetochore binds multiple MTs, but the collective behavior of these coupled MTs is not well understood. We present a minimal model for collective kinetochore–MT dynamics, based on in vitro measurements of individual MTs and their dependence on force and kinetochore phosphorylation by Aurora B kinase. For a system of multiple MTs connected to the same kinetochore, the force–velocity relation has a bistable regime with two possible steady-state velocities: rapid shortening or slow growth. Bistability, combined with the difference between the growing and shrinking speeds, leads to center-of-mass and breathing oscillations in bioriented sister kinetochore pairs. Kinetochore phosphorylation shifts the bistable region to higher tensions, so that only the rapidly shortening state is stable at low tension. Thus, phosphorylation leads to error correction for kinetochores that are not under tension. We challenged the model with new experiments, using chemically induced dimerization to enhance Aurora B activity at metaphase kinetochores. The model suggests that the experimentally observed disordering of the metaphase plate occurs because phosphorylation increases kinetochore speeds by biasing MTs to shrink. Our minimal model qualitatively captures certain characteristic features of kinetochore dynamics, illustrates how biochemical signals such as phosphorylation may regulate the dynamics, and provides a theoretical framework for understanding other factors that control the dynamics in vivo.

The phase behavior of charged rods in the presence of interrod linkers is studied theoretically as a model for the equilibrium behavior underlying the organization of actin filaments by linker proteins in the cytoskeleton. The presence of linkers in the solution modifies the effective interrod interaction and can lead to interfilament attraction. Depending on the composition and physical properties of the system, such as linker-binding energies, filaments will orient either perpendicular or parallel to each other, leading to network-like or bundled structures. We show that such a system can have one of three generic phase diagrams, one dominated by bundles, another by networks, and the third containing both bundle and network-like phases. The first two diagrams can be found over a wide range of interaction energies, whereas the third diagram occurs only for a narrow range. These results provide theoretical understanding of the classification of linker proteins as bundling proteins or crosslinking proteins. In addition, they suggest possible mechanisms by which the cell may control cytoskeletal morphology.

We report numerical simulation results for the force-velocity relation for actin-polymerization-driven motility. We use Brownian dynamics to solve a physically consistent formulation of the dendritic nucleation model with semiflexible filaments that self-assemble and push a disk. We find that at small loads, the disk speed is independent of load, whereas at high loads, the speed decreases and vanishes at a characteristic stall pressure. Our results demonstrate that at small loads, the velocity is controlled by the reaction rates, whereas at high loads the stall pressure is determined by the mechanical properties of the branched actin network. The behavior is consistent with experiments and with our recently proposed self-diffusiophoretic mechanism for actin-polymerization-driven motility. New in vitro experiments to measure the force-velocity relation are proposed.

Polyphosphoinositides are among the most highly charged molecules in the cell membrane, and the most common polyphosphoinositide, phosphatidylinositol-4,5-bisphosphate (PIP2), is involved in many mechanical and biochemical processes in the cell membrane. Divalent cations such as calcium can cause clustering of the polyanionic PIP2, but the origin and strength of the effective attractions leading to clustering has been unclear. In addition, the question of whether the ion-mediated attractions could be strong enough to alter the mechanical properties of the membrane, to our knowledge, has not been addressed. We study phase separation in mixed monolayers of neutral and highly negatively charged lipids, induced by the addition of divalent positively charged counterions, both experimentally and numerically. We find good agreement between experiments on mixtures of PIP2 and 1-stearoyl-2-oleoyl phosphatidylcholine and simulations of a simplified model in which only the essential electrostatic interactions are retained. In addition, we find numerically that under certain conditions the effective attractions can rigidify the resulting clusters. Our results support an interpretation of PIP2 clustering as governed primarily by electrostatic interactions. At physiological pH, the simulations suggest that the effective attractions are strong enough to give nearly pure clusters of PIP2 even at small overall concentrations of PIP2.

We present the first numerical simulation of actin-driven propulsion by elastic filaments. Specifically, we use a Brownian dynamics formulation of the dendritic nucleation model of actin-driven propulsion. We show that the model leads to a self-assembled network that exerts forces on a disk and pushes it with an average speed. This simulation approach is the first to observe a speed that varies nonmonotonically with the concentration of branching proteins (Arp2/3), capping protein, and depolymerization rate, in accord with experimental observations. Our results suggest a new interpretation of the origin of motility. When we estimate the speed that this mechanism would produce in a system with realistic rate constants and concentrations as well as fluid flow, we obtain a value that is within an order-of-magnitude of the polymerization speed deduced from experiments.