Search

We consider super-diffusive Lévy walks in dimensions when the duration of a single step, i.e. a ballistic motion performed by a walker, is governed by a power-law tailed distribution of infinite variance and finite mean. We demonstrate that the probability density function (PDF) of the coordinate of the random walker has two different scaling limits at large times. One limit describes the bulk of the PDF. It is the d-dimensional generalization of the one-dimensional Lévy distribution and is the counterpart of the central limit theorem (CLT) for random walks with finite dispersion. In contrast with the one-dimensional Lévy distribution and the CLT this distribution does not have a universal shape. The PDF reflects anisotropy of the single-step statistics however large the time is. The other scaling limit, the so-called ‘infinite density’, describes the tail of the PDF which determines second (dispersion) and higher moments of the PDF. This limit repeats the angular structure of the PDF of velocity in one step. A typical realization of the walk consists of anomalous diffusive motion (described by anisotropic d-dimensional Lévy distribution) interspersed with long ballistic flights (described by infinite density). The long flights are rare but due to them the coordinate increases so much that their contribution determines the dispersion. We illustrate the concept by considering two types of Lévy walks, with isotropic and anisotropic distributions of velocities. Furthermore, we show that for isotropic but otherwise arbitrary velocity distributions the d-dimensional process can be reduced to a one-dimensional Lévy walk. We briefly discuss the consequences of non-universality for the d  >  1 dimensional fractional diffusion equation, in particular the non-uniqueness of the fractional Laplacian. [ABSTRACT FROM AUTHOR]

Here, we show that a problem of forced polymer loops can be mapped to an asymmetric simple exclusion process with reflecting boundary conditions. The dynamics of the particle system can be solved exactly using the Bethe ansatz. We thus can fully describe the relaxation dynamics of forced polymer loops. In the steady state, the conformation of the loop can be approximated by a combination of Fermi–Dirac and Brownian bridge statistics, while the exact solution is found by using the fermion integer partition theory. With the theoretical framework presented here we establish a link between the physics of polymers and statistics of many-particle systems opening new paths of exploration in both research fields. Our result can be applied to the dynamics of the biopolymers which form closed loops. One such example is the active pulling of chromosomal loops during meiosis in yeast cells which helps to align chromosomes for recombination in the viscous environment of the cell nucleus. [ABSTRACT FROM AUTHOR]

Neisseria gonorrhoeae is the causative agent of one of the most common sexually transmitted diseases, gonorrhea. Over the past two decades there has been an alarming increase of reported gonorrhea cases where the bacteria were resistant to the most commonly used antibiotics thus prompting for alternative antimicrobial treatment strategies. The crucial step in this and many other bacterial infections is the formation of microcolonies, agglomerates consisting of up to several thousands of cells. The attachment and motility of cells on solid substrates as well as the cell–cell interactions are primarily mediated by type IV pili, long polymeric filaments protruding from the surface of cells. While the crucial role of pili in the assembly of microcolonies has been well recognized, the exact mechanisms of how they govern the formation and dynamics of microcolonies are still poorly understood. Here, we present a computational model of individual cells with explicit pili dynamics, force generation and pili–pili interactions. We employ the model to study a wide range of biological processes, such as the motility of individual cells on a surface, the heterogeneous cell motility within the large cell aggregates, and the merging dynamics and the self-assembly of microcolonies. The results of numerical simulations highlight the central role of pili generated forces in the formation of bacterial colonies and are in agreement with the available experimental observations. The model can quantify the behavior of multicellular bacterial colonies on biologically relevant temporal and spatial scales and can be easily adjusted to include the geometry and pili characteristics of various bacterial species. Ultimately, the combination of the microbiological experimental approach with the in silico model of bacterial colonies might provide new qualitative and quantitative insights on the development of bacterial infections and thus pave the way to new antimicrobial treatments. [ABSTRACT FROM AUTHOR]