Search

Active particles with their characteristic feature of self-propulsion are regarded as the simplest models for motility in living systems. The accumulation of active particles in low activity regions has led to the general belief that chemotaxis requires additional features and at least a minimal ability to process information and to control motion. We show that self-propelled particles display chemotaxis and move into regions of higher activity, if the particles perform work on passive objects, or cargo, to which they are bound. The origin of this cooperative chemotaxis is the exploration of the activity gradient by the active particle when bound to a load, resulting in an average excess force on the load in the direction of higher activity. Using a minimalistic theoretical model, we capture the most relevant features of these active-passive dimers and in particular we predict the crossover between anti-chemotactic and chemotactic behaviour. Moreover we show that merely connecting active particles to chains is sufficient to obtain the crossover from anti-chemotaxis to chemotaxis with increasing chain length. Such an active complex is capable of moving up a gradient of activity such as provided by a gradient of fuel and to accumulate where the fuel concentration is at its maximum. The observed transition is of significance to proto-forms of life enabling them to locate a source of nutrients even in the absence of any supporting sensomotoric apparatus.

Using Brownian dynamics simulations, the motion of active Brownian particles (ABPs) in the presence of fuel (or 'food') sources is studied. It is an established fact that within confined stationary systems, the activity of ABPs generates density profiles that are enhanced in regions of low activity, which is generally referred to as 'anti-chemotaxis'. We demonstrate that -- contrary to common believes -- in non-stationary setups, emerging here as a result of short fuel bursts, our model ABPs do instead exhibit signatures of chemotactic behavior. In direct competition with inactive, but otherwise identical Brownian particles (BPs), the ABPs are shown to fetch a larger amount of food. From a biological perspective, the ability to turn active would, despite of the absence of sensoric devices, encompass an evolutionary advantage., Comment: 6 pages, 7 figures

In this paper a lattice model for the diffusional transport of particles in the interphase cell nucleus is proposed. The dynamic behaviour of single chains on the lattice is investigated and Rouse scaling is verified. Dynamical dense networks are created by a combined version of the bond fluctuation method and a Metropolis Monte Carlo algorithm. Semidilute behaviour of the dense chain networks is shown. By comparing diffusion of particles in a static and a dynamical chain network, we demonstrate that chain diffusion does not alter the diffusion process of small particles. However, we prove that a dynamical network facilitates the transport of large particles. By weighting the mean square displacement trajectories of particles in the static chain network data from the dynamical network can be reconstructed. Additionally, it is shown that subdiffusive behaviour of particles on short time scales results from trapping processes in the crowded environment of the chain network. In the presented model a protein with 30 nm diameter has an effective diffusion coefficient of 1.24E-11 m^2/s in a chromatin fiber network., Comment: submitted to J. Chem. Phys

In this paper a lattice model for diffusional transport of particles in the interphase cell nucleus is proposed. Dense networks of chromatin fibers are created by three different methods: randomly distributed, non-interconnected obstacles, a random walk chain model, and a self avoiding random walk chain model with persistence length. By comparing a discrete and a continuous version of the random walk chain model, we demonstrate that lattice discretization does not alter particle diffusion. The influence of the 3D geometry of the fiber network on the particle diffusion is investigated in detail, while varying occupation volume, chain length, persistence length and walker size. It is shown that adjacency of the monomers, the excluded volume effect incorporated in the self avoiding random walk model, and, to a lesser extent, the persistence length, affect particle diffusion. It is demonstrated how the introduction of the effective chain occupancy, which is a convolution of the geometric chain volume with the walker size, eliminates the conformational effects of the network on the diffusion, i.e., when plotting the diffusion coefficient as a function of the effective chain volume, the data fall onto a master curve., Comment: 9 pages, 8 figures

The recently introduced method of excess collisions (MEC) is modified to estimate diffusion-controlled reaction times inside systems of arbitrary size. The resulting MEC-E equations contain a set of empirical parameters, which have to be calibrated in numerical simulations inside a test system of moderate size. Once this is done, reaction times of systems of arbitrary dimensions are derived by extrapolation, with an accuracy of 10 to 15 percent. The achieved speed up, when compared to explicit simulations of the reaction process, is increasing proportional to the extrapolated volume of the cell., Comment: 8 pages, 4 figures, submitted to J. Chem. Phys

In this paper, a new method to efficiently simulate diffusion controlled second order chemical reactions is derived and applied to site-specific DNA-binding proteins. The protein enters a spherical cell and propagates via two competing modes, a free diffusion and a DNA-sliding mode, to search for its specific binding site in the center of the cell. There is no need for a straightforward simulation of this process. Instead, an alternative and exact approach is shown to be essentially faster than explicit random-walk simulations. The speed-up of this novel simulation technique is rapidly growing with system size., Comment: 7 pages, 2 figures

The diffusion-controlled limit of reaction times for site-specific DNA-binding proteins is derived from first principles. We follow the generally accepted concept that a protein propagates via two competitive modes, a three-dimensional diffusion in space and a one-dimensional sliding along the DNA. However, our theoretical treatment of the problem is new. The accuracy of our analytical model is verified by numerical simulations. The results confirm that the unspecific binding of protein to DNA, combined with sliding, is capable to reduce the reaction times significantly., Comment: 4 pages, 2 figures Nov 22 2005 - accepted for PRL