Bleb nucleation through membrane pealing

We study the nucleation of blebs, i.e., protrusions arising from a local detachment of the membrane from the cortex of a cell. Based on a simple model of elastic linkers with force-dependent kinetics, we show that bleb nucleation is governed by membrane peeling. By this mechanism, the growth or shrinkage of a detached membrane patch is completely determined by the linker kinetics, regardless of the energetic cost of the detachment. We predict the critical nucleation radius for membrane peeling and the corresponding effective energy barrier. These may be typically smaller than those predicted by classical nucleation theory, implying a much faster nucleation. We also perform simulations of a continuum stochastic model of membrane-cortex adhesion to obtain the statistics of bleb nucleation times as a function of the stress on the membrane. The determinant role of membrane peeling changes our understanding of bleb nucleation and opens new directions in the study of blebs

Spontaneous motility of actin lamellar fragments

We show that actin lamellar fragments driven solely by polymerization forces at the bounding membrane are generically motile when the circular symmetry is spontaneously broken, with no need of molecular motors or global polarization. We base our study on a nonlinear analysis of a recently introduced minimal model [Callan-Jones et al Phys. Rev. Lett. 100, 258106 (2008)]. We prove the nonlinear instability of the center of mass and find an exact and simple relation between shape and center-of-mass velocity. A complex subcritical bifurcation scenario into traveling solutions is unfolded, where finite velocities appear through a nonadiabatic mechanism. Examples of traveling solutions and their stability are studied numericall

Cooperative force generation of KIF1A Brownian motors

KIF1A is a kinesin motor protein that can work processively in a monomeric (single-headed) form by using a noise-driven ratchet mechanism. Here, we show that the combination of a passive diffusive state and finite-time kinetics of adenosine triphosphate hydrolysis provides a powerful mechanism of cooperative force generation, implying for instance that ∼ 10 monomeric KIF1As can team up to become ∼ 100 times stronger than a single one. Consequently, we propose that KIF1A could outperform conventional (double-headed) kinesin collectively and thus explain its specificity in axonal trafficking. We elucidate the cooperativity mechanism with a lattice model that includes multiparticle transitions

Kinetic roughening in two-phase fluid flow through a random Hele-Shaw cell

A nonlocal interface equation is derived for two-phase fluid flow, with arbitrary wettability and viscosity contrast, c = ( μ 1 − μ 2 ) / ( μ 1 + μ 2 ) , in a model porous medium defined as a Hele-Shaw cell with random gap b 0 + δ b . Fluctuations of both capillary and viscous pressure are explicitly related to the microscopic quenched disorder, yielding conserved, nonconserved, and power-law correlated noise terms. Two length scales are identified that control the possible scaling regimes and which scale with capillary number Ca as ℓ 1 ∼ b 0 ( c C a ) − 1 / 2 and ℓ 2 ∼ b 0 C a − 1 . Exponents for forced fluid invasion are obtained from numerical simulation and compared with recent experiments

Self-organization and cooperativity of weakly coupled molecular motors under unequal loading

We study the collective dynamics of Brownian motors moving on a one-dimensional track when an external load is applied to the leading motor. Motors are driven by a two-state ratchet mechanism, which is appropriate to single-headed kinesins, and their relative motion is only constrained by their mutual interaction potential (weak coupling). We show that unequal loading enhances cooperativity, leading to the formation of clusters with velocities and efficiencies higher than those predicted by simple superposition. When a weak attraction between motors is present, we find nonmonotonic collective velocity-force curves, hysteretic phenomena, and a dynamic self-regulation mechanism that selects the cluster size for optimal performance

Nonlinear amplitude dynamics in flagellar beating

The physical basis of flagellar and ciliary beating is a major problem in biology which is still far from completely understood. The fundamental cytoskeleton structure of cilia and flagella is the axoneme, a cylindrical array of microtubule doublets connected by passive cross-linkers and dynein motor proteins. The complex interplay of these elements leads to the generation of self-organized bending waves. Although many mathematical models have been proposed to understand this process, few attempts have been made to assess the role of dyneins on the nonlinear nature of the axoneme. Here, we investigate the nonlinear dynamics of flagella by considering an axonemal sliding control mechanism for dynein activity. This approach unveils the nonlinear selection of the oscillation amplitudes, which are typically either missed or prescribed in mathematical models. The explicit set of nonlinear equations are derived and solved numerically. Our analysis reveals the spatio-temporal dynamics of dynein populations and flagellum shape for different regimes of motor activity, medium viscosity and flagellum elasticity. Unstable modes saturate via the coupling of dynein kinetics and flagellum shape without the need of invoking a nonlinear axonemal response. Hence, our work reveals a novel mechanism for the saturation of unstable modes in axonemal beating

Landscape-Inversion Phase Transition in Dipolar Colloids: Tuning the Structure and Dynamics of 2D Crystals

We study the 2D crystalline phases of paramagnetic colloidal particles with dipolar interactions and constrained on a periodic substrate. Combining theory, simulation, and experiments, we demonstrate a new scenario of first-order phase transitions that occurs via a complete inversion of the energy landscape, featuring nonconventional properties that allow for (i) tuning of crystal symmetry, (ii) control of dynamical properties of different crystalline orders via tuning of their relative stability with an external magnetic field, (iii) an equivalent but independent control of the same dynamic properties via temporal modulations of that field, and (iv) nonstandard phase-ordering kinetics involving spontaneous formation of transient metastable domains

Fluidization and active thinning by molecular kinetics in active gels

We derive the constitutive equations of an active polar gel from a model for the dynamics of elastic molecules that link polar elements. Molecular binding kinetics induces the fluidization of the material, giving rise to Maxwell viscoelasticity and, provided that detailed balance is broken, to the generation of active stresses. We give explicit expressions for the transport coefficients of active gels in terms of molecular properties, including nonlinear contributions on the departure from equilibrium. In particular, when activity favors linker unbinding, we predict a decrease of viscosity with activity active thinning of kinetic origin, which could explain some experimental results on the cell cortex. By bridging the molecular and hydrodynamic scales, our results could help understand the interplay between molecular perturbations and the mechanics of cells and tissues

Unraveling the hidden complexity of quasideterministic ratchets: random walks, graphs, and circle maps

Brownian ratchets are shown to feature a nontrivial vanishing-noise limit where the dynamics is reduced to a stochastic alternation between two deterministic circle maps (quasideterministic ratchets). Motivated by cooperative dynamics of molecular motors, here we solve exactly the problem of two interacting quasideterministic ratchets. We show that the dynamics can be described as a random walk on a graph that is specific to each set of parameters. We compute point by point the exact velocity-force V ( f ) function as a summation over all paths in the specific graph for each f , revealing a complex structure that features self-similarity and nontrivial continuity properties. From a general perspective, we unveil that the alternation of two simple piecewise linear circle maps unfolds a very rich variety of dynamical complexity, in particular the phenomenon of piecewise chaos, where chaos emerges from the combination of nonchaotic maps. We show convergence of the finite-noise case to our exact solution

Noise focusing in neuronal tissues: Symmetry breaking and localization in excitable networks with quenched disorder

We introduce a coarse-grained stochastic model for the spontaneous activity of neuronal cultures to explain the phenomenon of noise focusing, which entails localization of the noise activity in excitable networks with metric correlations. The system is modeled as a continuum excitable medium with a state-dependent spatial coupling that accounts for the dynamics of synaptic connections. The most salient feature is the emergence at the mesoscale of a vector field V ( r ) , which acts as an advective carrier of the noise. This entails an explicit symmetry breaking of isotropy and homogeneity that stems from the amplification of the quenched fluctuations of the network by the activity avalanches, concomitant with the excitable dynamics. We discuss the microscopic interpretation of V ( r ) and propose an explicit construction of it. The coarse-grained model shows excellent agreement with simulations at the network level. The generic nature of the observed phenomena is discussed