Intracellular transport by single-headed kinesin KIF1A: effects of single-motor mechanochemistry and steric interactions

Separation of dense colloidal suspensions in narrow channels: A stochastic model

The flow of a colloidal suspension in a narrow channel of periodically varying width is described by the one-dimensional generalized asymmetric exclusion process. Each site admits multiple particle occupancy. We consider particles of two different sizes. The sites available to particles form a comblike geometry: entropic traps due to variation of channel width are modeled by dead ends, or pockets, attached individually to each site of a one-dimensional chain. This geometry, combined with periodically alternating external driving, leads to a ratchet effect which is very sensitive to particle size, thus enabling particle sorting. A typical behavior is reversal of the current orientation when we change the density of small and big particles. In an optimal situation, the two types of particles move in opposite directions, and particle separation is in principle perfect. We show that in the simplest situation with one type of particles only, this model is exactly soluble. In the general case we use enhanced mean-field approximation as well as direct numerical simulations.

One-dimensional discrete aggregation-fragmentation model

We study here one-dimensional model of aggregation and fragmentation of clusters of particles obeying the stochastic discrete-time kinetics of the generalized totally asymmetric simple exclusion process (gTASEP) on open chains. The gTASEP is essentially the ordinary TASEP with backward-ordered sequential update (BSU), however, equipped with two hopping probabilities: p and p_{m}. The second modified probability p_{m} models a special kinematic interaction between the particles of a cluster in addition to the simple hard-core exclusion interaction, existing in the ordinary TASEP. We focus on the nonequilibrium stationary properties of the gTASEP in the generic case of attraction between the particles of a cluster. In this case the particles of a cluster have higher chance to stay together than to split, thus producing higher throughput in the system. We explain how the topology of the phase diagram in the case of irreversible aggregation, occurring when the modified probability equals unity, changes sharply to the one, corresponding to the ordinary TASEP with BSU, as soon as the modified probability becomes less than unity and aggregation-fragmentation of clusters appears. We estimate various physical quantities in the system and determine the parameter-dependent injection and ejection critical values by extensive computer simulations. With the aid of random walk theory, supported by the Monte Carlo simulations, the properties of the phase transitions between the three stationary phases are assessed.

Stationary RNA polymerase fluctuations during transcription elongation

We study fluctuation effects of nonsteric molecular interactions between RNA polymerase (RNAP) motors that move simultaneously on the same DNA track during transcription elongation. Based on a stochastic model that allows for the exact analytical computation of the stationary distribution of RNAPs as a function of their density, interaction strength, nucleoside triphosphate concentration, and rate of pyrophosphate release we predict an almost geometric headway distribution of subsequent RNAP transcribing on the same DNA segment. The localization length which characterizes the decay of the headway distribution depends directly only the average density of RNAP and the interaction strength, but not on specific single-RNAP properties. Density correlations are predicted to decay exponentially with the distance (in units of DNA base pairs), with a correlation length that is significantly shorter than the localization length.

Structural conditions on complex networks for the Michaelis-Menten input-output response

The Michaelis-Menten (MM) fundamental formula describes how the rate of enzyme catalysis depends on substrate concentration. The familiar hyperbolic relationship was derived by timescale separation for a network of three reactions. The same formula has subsequently been found to describe steady-state input-output responses in many biological contexts, including single-molecule enzyme kinetics, gene regulation, transcription, translation, and force generation. Previous attempts to explain its ubiquity have been limited to networks with regular structure or simplifying parametric assumptions. Here, we exploit the graph-based linear framework for timescale separation to derive general structural conditions under which the MM formula arises. The conditions require a partition of the graph into two parts, akin to a "coarse graining" into the original MM graph, and constraints on where and how the input variable occurs. Other features of the graph, including the numerical values of parameters, can remain arbitrary, thereby explaining the formula's ubiquity. For systems at thermodynamic equilibrium, we derive a necessary and sufficient condition. For systems away from thermodynamic equilibrium, especially those with irreversible reactions, distinct structural conditions arise and a general characterization remains open. Nevertheless, our results accommodate, in much greater generality, all examples known to us in the literature.

Navigating the cell: how motors overcome roadblocks and traffic jams to efficiently transport cargo

Intracellular transport plays an essential role in maintaining the organization of cells. The importance of long-range, bi-directional transport is evidenced by the fact that its failure goes hand in hand with several diseases including neurodegenerative diseases such as Alzheimer's and Amyotrophic Lateral Sclerosis. The nanoscale cellular transport machinery consisting of cytoskeletal tracks and motor-proteins is responsible for effectively delivering important materials to specific locations inside the cell. Motor-proteins manage to overcome several challenges in the crowded cellular environment to achieve well-coordinated and effective transport. In recent years, thanks to state-of-the-art single molecule biophysical tools, we have started to gain insights into the cellular traffic rules. This perspective summarizes the challenges that motors face in navigating the complex cytoskeleton and the lessons learned about transport in crowded environments from both bottom-up in vitro studies as well as top-down in vivo studies.

Chaos in kicked ratchets

We present a minimal one-dimensional deterministic continuous dynamical system that exhibits chaotic behavior and complex transport properties. Our model is an overdamped rocking ratchet with finite dissipation, that is periodically kicked with a δ function driving force, without finite inertia terms or temporal or spatial stochastic forces. To our knowledge this is the simplest model reported in the literature for a ratchet, with this complex behavior. We develop an analytical approach that predicts many key features of the system, such as current reversals, as well as the presence of chaotic behavior and bifurcation. Our analytical approach allows us to study the transition from regular to chaotic motion as well as a tangent bifurcation associated with this transition. We show that our approach can be easily extended to other types of periodic driving forces. The square wave is shown as an example.

Cooperative action of KIF1A Brownian motors with finite dwell time

We study in detail the cooperative action of small groups of KIF1A motors in its monomeric (single-headed) form within an arrangement relevant to vesicle traffic or membrane tube extraction. It has been recently shown that under these circumstances, the presence of a finite dwell time in the motor cycle contributes to remarkably enhance collective force generation [D. Oriola and J. Casademunt, Phys. Rev. Lett. 111, 048103 (2013)]. We analyze this mechanism in detail by means of a two-state noise-driven ratchet model with hard-core repulsive interactions. We obtain staircase-shaped velocity-force curves and show that motors self-organize in clusters with a nontrivial force distribution that conveys a large part of the load to the central motors. Under heavy loads, large clusters adopt a synchronic mode of totally asymmetric steps. We also find a dramatic increase of the collective efficiency with the number of motors. Finally, we complete the study by addressing different interactions that impose spatial constraints such as rigid coupling and raft-induced confinement. Our results reinforce the hypothesis that the specificity of KIF1A to axonal vesicular transport may be deeply related to its high cooperativity.

Effect of the microtubule-associated protein tau on dynamics of single-headed motor proteins KIF1A

Intracellular transport based on molecular motors and its regulation are crucial to the functioning of cells. Filamentary tracks of the cells are abundantly decorated with nonmotile microtubule-associated proteins, such as tau. Motivated by experiments on kinesin-tau interactions [Dixit et al., Science 319, 1086 (2008)] we developed a stochastic model of interacting single-headed motor proteins KIF1A that also takes into account the interactions between motor proteins and tau molecules. Our model reproduces experimental observations and predicts significant effects of tau on bound time and run length which suggest an important role of tau in regulation of kinesin-based transport.

Running faster together: huge speed up of thermal ratchets due to hydrodynamic coupling

We present simulations that reveal a surprisingly large effect of hydrodynamic coupling on the speed of thermal ratchet motors. The model that we use considers particles performing thermal ratchet motion in a hydrodynamic solvent. Using particle-based, mesoscopic simulations that maintain local momentum conservation, we analyze quantitatively how the coupling to the surrounding fluid affects ratchet motion. We find that coupling can increase the mean velocity of the moving particles by almost 2 orders of magnitude, precisely because ratchet motion has both a diffusive and a deterministic component. The resulting coupling also leads to the formation of aggregates at longer times. The correlated motion that we describe increases the efficiency of motor-delivered cargo transport and we speculate that the mechanism that we have uncovered may play a key role in speeding up molecular motor-driven intracellular transport.

Path-preference cellular-automaton model for traffic flow through transit points and its application to the transcription process in human cells

We all use path routing everyday as we take shortcuts to avoid traffic jams, or by using faster traffic means. Previous models of traffic flow of RNA polymerase II (RNAPII) during transcription, however, were restricted to one dimension along the DNA template. Here we report the modeling and application of traffic flow in transcription that allows preferential paths of different dimensions only restricted to visit some transit points, as previously introduced between the 5' and 3' end of the gene. According to its position, an RNAPII protein molecule prefers paths obeying two types of time-evolution rules. One is an asymmetric simple exclusion process (ASEP) along DNA, and the other is a three-dimensional jump between transit points in DNA where RNAPIIs are staying. Simulations based on our model, and comparison experimental results, reveal how RNAPII molecules are distributed at the DNA-loop-formation-related protein binding sites as well as CTCF insulator proteins (or exons). As time passes after the stimulation, the RNAPII density at these sites becomes higher. Apparent far-distance jumps in one dimension are realized by short-range three-dimensional jumps between DNA loops. We confirm the above conjecture by applying our model calculation to the SAMD4A gene by comparing the experimental results. Our probabilistic model provides possible scenarios for assembling RNAPII molecules into transcription factories, where RNAPII and related proteins cooperatively transcribe DNA.

Molecular spiders on a plane

Synthetic biomolecular spiders with "legs" made of single-stranded segments of DNA can move on a surface covered by single-stranded segments of DNA called substrates when the substrate DNA is complementary to the leg DNA. If the motion of a spider does not affect the substrates, the spider behaves asymptotically as a random walk. We study the diffusion coefficient and the number of visited sites for spiders moving on the square lattice with a substrate in each lattice site. The spider's legs hop to nearest-neighbor sites with the constraint that the distance between any two legs cannot exceed a maximal span. We establish analytic results for bipedal spiders, and investigate multileg spiders numerically. In experimental realizations legs usually convert substrates into products (visited sites). The binding of legs to products is weaker, so the hopping rate from the substrates is smaller. This makes the problem non-Markovian and we investigate it numerically. We demonstrate the emergence of a counterintuitive behavior-the more spiders are slowed down on unvisited sites, the more motile they become.

Mixed population of competing totally asymmetric simple exclusion processes with a shared reservoir of particles

We introduce a mean-field theoretical framework to describe multiple totally asymmetric simple exclusion processes (TASEPs) with different lattice lengths and entry and exit rates, competing for a finite reservoir of particles. We present relations for the partitioning of particles between the reservoir and the lattices: These relations allow us to show that competition for particles can have nontrivial effects on the phase behavior of individual lattices. For a system with nonidentical lattices, we find that when a subset of lattices undergoes a phase transition from low to high density, the entire set of lattice currents becomes independent of total particle number. We generalize our approach to systems with a continuous distribution of lattice parameters, for which we demonstrate that measurements of the current carried by a single lattice type can be used to extract the entire distribution of lattice parameters. Our approach applies to populations of TASEPs with any distribution of lattice parameters and could easily be extended beyond the mean-field case.

Shock detection in dynamics of single-headed motor proteins KIF1A via Jensen-Shannon divergence

Information theoretic quantities are useful tools to characterize symbolic sequences. In this paper, we use the Jensen-Shannon divergence to study symbolic binary sequences that represent the stationary state of a lattice-gas model describing the traffic of monomeric kinesin KIF1A. More specifically, the constructed binary sequences represent the state of a microtubule protofilament at different adenosine triphosphate (ATP) and KIF1A motor concentrations in the cytosol. The model presents some stationary regimes with phase coexistence. By using the Jensen-Shannon divergence, we develop a method of analysis that allows us to identify cases in which phase coexistence occurs and, for these cases, to locate the position of the interphase that separates the regions with different phase.

Exact solution of a heterogeneous multilane asymmetric simple exclusion process

We have proved an exact solution of a multilane totally asymmetric simple exclusion process (TASEP) with heterogeneous lane-changing rates on a torus. In the expression, the TASEP in each lane and lane-changing transition can be separable. Moreover, the lane-changing transitions satisfy the detailed balance condition, and this is the key to constructing the solution. Using the saddle-point method, the current of particles has been derived in a simple form in a thermodynamic limit. It is interesting that the dynamics depends only on a set of lane-changing parameters, not on the configuration of lanes.

Cellular-automaton model of the cooperative dynamics of RNA polymerase II during transcription in human cells

RNA polymerase II (RNAPII) is the responsible motor protein for transcription. Here we report the formulation and results of a cellular automaton model of the RNAPII dynamics of gene transcription that takes account the effect of the velocity change according to the gene position, such as occurs in introns and exons. We describe RNAPII dynamics in terms of the properties in the time domain, such as elapsed time, residence time, and time intervals. We found that the RNAPII molecules move as a free-flow state, though regions of reduced velocity do exist such as exons, as far as the time interval between nearest RNAPII molecules is larger than the time required for an RNAPII passing the exclusion length in the velocity reduction region. On the other hand, if the reduction is strong enough to reach a certain threshold, at the maximally reductive velocity region, a transition occurs from the RNAPII free-flow state to the states with congested and repetitive flows. We analytically obtained the conditions for these flow states and the transition threshold. From simulations of high-density RNAPII in the SAMD4A gene with the strong blockade, we confirmed the transition from free flow to the repetitive and congested flows, suggesting that the transition may serve as a regulatory mechanism of gene expression. By fitting the experimentally observed RNAPII density profile of the SAMD4A gene during the course of transcription of the normal and altered gene (in knock-down cells) with or without roadblock, we found that the RNAPII density flow is a free state. However, even in this free state, there is a long-range correlation between RNAPII molecules, ranging from 1 to 20 min, with the corresponding distance from 3 to 80 kbp, during transcription in normal cells. This long-range correlation probably relates to the higher-order DNA loop structure.

Conformational changes, diffusion and collective behavior in monomeric kinesin-based motility

Molecular motors convert chemical energy into mechanical motion and power the transport of material within living cells; the motion of a motor is thought to be influenced by stochastic chemical state transitions of the molecule as well as intramolecular diffusion of one motor head seeking the next binding site. Existing models for the motility of single-headed monomeric motors that map the system to a simplified two-state Brownian ratchet have some predictive power, but in general are unable to elucidate the contributions of different molecular level processes to the overall effective parameters. In this work, we build a detailed molecular level model of monomeric kinesin motility that naturally incorporates conformational changes (power strokes) and biased diffusion. Our results predict that mean velocity is most sensitive to the power stroke size, while run length distribution is sensitive primarily to the strength of the microtubule bias potential with a weak dependence on power stroke that can be tuned by the strength of an applied load. In addition, we demonstrate that motor pairs attached to the same cargo can cooperatively function to increase motility in both the plus- and minus-end directions. These findings illustrate the importance of a detailed mechanochemical model for dissecting the contributions of microscopic parameters to monomeric kinesin dynamics.

Driven transport on parallel lanes with particle exclusion and obstruction

We investigate a driven two-channel system where particles on different lanes mutually obstruct each other's motion, extending an earlier model by Popkov and Peschel [Phys. Rev. E 64, 026126 (2001)]. This obstruction may occur in biological contexts due to steric hinderance where motor proteins carry cargos by "walking" on microtubules. Similarly, the model serves as a description for classical spin transport where charged particles with internal states move unidirectionally on a lattice. Three regimes of qualitatively different behavior are identified, depending on the strength of coupling between the lanes. For small and large coupling strengths the model can be mapped to a one-channel problem, whereas a rich phase behavior emerges for intermediate ones. We derive an approximate but quantitatively accurate theoretical description in terms of a one-site cluster approximation, and obtain insight into the phase behavior through the current-density relations combined with an extremal-current principle. Our results are confirmed by stochastic simulations.

Cooperativity of self-organized Brownian motors pulling on soft cargoes

We study the cooperative dynamics of Brownian motors moving along a one-dimensional track when an external load is applied to the leading motor, mimicking molecular motors pulling on membrane-bound cargoes in intracellular traffic. Due to the asymmetric loading, self-organized motor clusters form spontaneously. We model the motors with a two-state noise-driven ratchet formulation and study analytically and numerically the collective velocity-force and efficiency-force curves resulting from mutual interactions, mostly hard-core repulsion and weak (nonbinding) attraction. We analyze different parameter regimes including the limits of weak noise, mean-field behavior, rigid coupling, and large numbers of motors, for the different interactions. We present a general framework to classify and quantify cooperativity. We show that asymmetric loading leads generically to enhanced cooperativity beyond the simple superposition of the effects of individual motors. For weakly attracting interactions, the cooperativity is mostly enhanced, including highly coordinated motion of motors and complex nonmonotonic velocity-force curves, leading to self-regulated clusters. The dynamical scenario is enriched by resonances associated to commensurability of different length scales. Large clusters exhibit synchronized dynamics and bidirectional motion. Biological implications are discussed.

Active transport and cluster formation on 2D networks

We introduce a model for active transport on inhomogeneous networks embedded in a diffusive environment which is motivated by vesicular transport on actin filaments. In the presence of a hard-core interaction, particle clusters are observed that exhibit an algebraically decaying distribution in a large parameter regime, indicating the existence of clusters on all scales. The scale-free behavior can be understood by a mechanism promoting preferential attachment of particles to large clusters. The results are compared with a diffusion-limited aggregation model and active transport on a regular network. For both models we observe aggregation of particles to clusters which are characterized by a finite size scale if the relevant time scales and particle densities are considered.

Interacting molecular motors: efficiency and work fluctuations

We investigate the model of "reversible ratchet" with interacting particles, presented by us earlier [F. Slanina, EPL 84, 50009 (2008)]. We further clarify the effect of efficiency enhancement due to interaction and show that it is of energetic origin, rather than a consequence of reduced fluctuations. We also show complicated structures emerging in the interaction and density dependence of the current and response function. The fluctuation properties of the work and input energy indicate in detail the far-from-equilibrium nature of the dynamics.

Disordered driven lattice gases with boundary reservoirs and Langmuir kinetics

The asymmetric simple exclusion process with additional Langmuir kinetics, i.e., attachment and detachment in the bulk, is a paradigmatic model for intracellular transport. Here we study this model in the presence of randomly distributed inhomogeneities ("defects"). Using Monte Carlo simulations, we find a multitude of coexisting high- and low-density domains. The results are generic for one-dimensional driven diffusive systems with short-range interactions and can be understood in terms of a local extremal principle for the current profile. This principle is used to determine current profiles and phase diagrams as well as statistical properties of ensembles of defect samples.

Effects of the chemomechanical stepping cycle on the traffic of molecular motors

We discuss effects of the stepping kinetics of molecular motors on their traffic behavior on crowded filaments using a simple two-state chemomechanical cycle. While the general traffic behavior is quite robust with respect to the detailed kinetics of the step, a few observable parameters exhibit a strong dependence on these parameters. Most strikingly, the effective unbinding rate of the motors may both increase and decrease with increasing traffic density, depending on the details of the motor step. Likewise the run length either exhibits a strong decrease or almost no dependence on the traffic density. We compare our theoretical results with recent experimental observations on motor traffic.

Traffic of single-headed motor proteins KIF1A: effects of lane changing

KIF1A kinesins are single-headed motor proteins which move on cylindrical nanotubes called microtubules (MTs). A normal MT consists of 13 protofilaments on which the equispaced motor binding sites form a periodic array. The collective movement of the kinesins on a MT is, therefore, analogous to vehicular traffic on multilane highways where each protofilament is the analog of a single lane. Does lane changing increase or decrease the motor flux per lane? We address this fundamental question here by appropriately extending a recent model [P. Greulich, Phys. Rev. E 75, 041905 (2007)]. By carrying out analytical calculations and computer simulations of this extended model, we predict that the flux per lane can increase or decrease with the increasing rate of lane changing, depending on the concentrations of motors and the rate of hydrolysis of ATP, the "fuel" molecules. Our predictions can be tested, in principle, by carrying out in vitro experiments with fluorescently labeled KIF1A molecules.

Weak and strong coupling in a two-lane asymmetric exclusion process

This paper studies a two-lane totally asymmetric simple exclusion process, in which particles could jump between the two lanes with asymmetric rates. In the weak coupling situation, the rates are inversely proportional to system size L . The appearance of localized shock in one lane and the discontinuous phase transition as revealed by Juhász [Phys. Rev. E 76, 021117 (2007)] are also reproduced. The density profiles and phase diagrams are constructed in the hydrodynamic limit, by numerically solving the steady state equations. The phase diagram in our model exhibits asymmetry, which is different from the symmetric one in Juhász's model. We have studied the phase boundary and discontinuous line analytically. The analytical results are in good agreement with that obtained from numerical integration. We also study the strong coupling situation, in which the lane changing rates are independent of L . Results completely different from that arising from weak coupling are presented. Furthermore, features different from that of the model presented by Pronina and Kolomeisky [Physica A 372, 12 (2006)] are revealed.

Interacting RNA polymerase motors on a DNA track: effects of traffic congestion and intrinsic noise on RNA synthesis

RNA polymerase (RNAP) is an enzyme that synthesizes a messenger RNA (mRNA) strand which is complementary to a single-stranded DNA template. From the perspective of physicists, an RNAP is a molecular motor that utilizes chemical energy input to move along the track formed by DNA. In many circumstances, which are described in this paper, a large number of RNAPs move simultaneously along the same track; we refer to such collective movements of the RNAPs as RNAP traffic. Here we develop a theoretical model for RNAP traffic by incorporating the steric interactions between RNAPs as well as the mechanochemical cycle of individual RNAPs during the elongation of the mRNA. By a combination of analytical and numerical techniques, we calculate the rates of mRNA synthesis and the average density profile of the RNAPs on the DNA track. We also introduce, and compute, two different measures of fluctuations in the synthesis of RNA. Analyzing these fluctuations, we show how the level of intrinsic noise in mRNA synthesis depends on the concentrations of the RNAPs as well as on those of some of the reactants and the products of the enzymatic reactions catalyzed by RNAP. We suggest appropriate experimental systems and techniques for testing our theoretical predictions.

Molecular Spiders in One Dimension

Molecular spiders are synthetic bio-molecular systems which have "legs" made of short single-stranded segments of DNA. Spiders move on a surface covered with single-stranded DNA segments complementary to legs. Different mappings are established between various models of spiders and simple exclusion processes. For spiders with simple gait and varying number of legs we compute the diffusion coefficient; when the hopping is biased we also compute their velocity.

Weakly coupled, antiparallel, totally asymmetric simple exclusion processes

We study a system composed of two parallel totally asymmetric simple exclusion processes with open boundaries, where the particles move in the two lanes in opposite directions and are allowed to jump to the other lane with rates inversely proportional to the length of the system. Stationary density profiles are determined and the phase diagram of the model is constructed in the hydrodynamic limit, by solving the differential equations describing the steady state of the system, analytically for vanishing total current and numerically for nonzero total current. The system possesses phases with a localized shock in the density profile in one of the lanes, similarly to exclusion processes endowed with nonconserving kinetics in the bulk. Besides, the system undergoes a discontinuous phase transition, where coherently moving delocalized shocks emerge in both lanes and the fluctuation of the global density is described by an unbiased random walk. This phenomenon is analogous to the phase coexistence observed at the coexistence line of the totally asymmetric simple exclusion process, however, as a consequence of the interaction between lanes, the density profiles are deformed and in the case of asymmetric lane change, the motion of the shocks is confined to a limited domain.

Molecular spiders with memory

Synthetic biomolecular spiders with "legs" made of single-stranded segments of DNA can move on a surface which is also covered by single-stranded segments of DNA complementary to the leg DNA. In experimental realizations, when a leg detaches from a segment of the surface for the first time it alters that segment, and legs subsequently bind to these altered segments more weakly. Inspired by these experiments, we investigate spiders moving along a one-dimensional substrate, whose legs leave newly visited sites at a slower rate than revisited sites. For a random walk (one-leg spider), the slowdown does not affect the long time behavior. For a bipedal spider, however, the slowdown generates an effective bias toward unvisited sites, and the spider behaves similarly to the excited walk. Surprisingly, the slowing down of the spider at new sites increases the diffusion coefficient and accelerates the growth of the number of visited sites.