Loss of PopZ At activity in Agrobacterium tumefaciens by Deletion or Depletion Leads to Multiple Growth Poles, Minicells, and Growth Defects.

Agrobacterium tumefaciens grows by addition of peptidoglycan (PG) at one pole of the bacterium. During the cell cycle, the cell needs to maintain two different developmental programs, one at the growth pole and another at the inert old pole. Proteins involved in this process are not yet well characterized. To further characterize the role of pole-organizing protein A. tumefaciens PopZ (PopZ At ), we created deletions of the five PopZ At domains and assayed their localization. In addition, we created a popZAt deletion strain (ΔpopZAt ) that exhibited growth and cell division defects with ectopic growth poles and minicells, but the strain is unstable. To overcome the genetic instability, we created an inducible PopZ At strain by replacing the native ribosome binding site with a riboswitch. Cultivated in a medium without the inducer theophylline, the cells look like ΔpopZAt cells, with a branching and minicell phenotype. Adding theophylline restores the wild-type (WT) cell shape. Localization experiments in the depleted strain showed that the domain enriched in proline, aspartate, and glutamate likely functions in growth pole targeting. Helical domains H3 and H4 together also mediate polar localization, but only in the presence of the WT protein, suggesting that the H3 and H4 domains multimerize with WT PopZ At , to stabilize growth pole accumulation of PopZ AtIMPORTANCEAgrobacterium tumefaciens is a rod-shaped bacterium that grows by addition of PG at only one pole. The factors involved in maintaining cell asymmetry during the cell cycle with an inert old pole and a growing new pole are not well understood. Here we investigate the role of PopZ At , a homologue of Caulobacter crescentus PopZ (PopZ Cc ), a protein essential in many aspects of pole identity in C. crescentus We report that the loss of PopZ At leads to the appearance of branching cells, minicells, and overall growth defects. As many plant and animal pathogens also employ polar growth, understanding this process in A. tumefaciens may lead to the development of new strategies to prevent the proliferation of these pathogens. In addition, studies of A. tumefaciens will provide new insights into the evolution of the genetic networks that regulate bacterial polar growth and cell division

Efficient calculation of local dose distribution for response modelling in proton and ion beams

We present an algorithm for fast and accurate computation of the local dose distribution in MeV beams of protons, carbon ions or other heavy-charged particles. It uses compound Poisson-process modelling of track interaction and succesive convolutions for fast computation. It can handle mixed particle fields over a wide range of fluences. Since the local dose distribution is the essential part of several approaches to model detector efficiency or cellular response it has potential use in ion-beam dosimetry and radiotherapy.Comment: 9 pages, 3 figure

Canalization and Symmetry in Boolean Models for Genetic Regulatory Networks

Canalization of genetic regulatory networks has been argued to be favored by evolutionary processes due to the stability that it can confer to phenotype expression. We explore whether a significant amount of canalization and partial canalization can arise in purely random networks in the absence of evolutionary pressures. We use a mapping of the Boolean functions in the Kauffman N-K model for genetic regulatory networks onto a k-dimensional Ising hypercube to show that the functions can be divided into different classes strictly due to geometrical constraints. The classes can be counted and their properties determined using results from group theory and isomer chemistry. We demonstrate that partially canalized functions completely dominate all possible Boolean functions, particularly for higher k. This indicates that partial canalization is extremely common, even in randomly chosen networks, and has implications for how much information can be obtained in experiments on native state genetic regulatory networks.Comment: 14 pages, 4 figures; version to appear in J. Phys.

Response of Boolean networks to perturbations

We evaluate the probability that a Boolean network returns to an attractor after perturbing h nodes. We find that the return probability as function of h can display a variety of different behaviours, which yields insights into the state-space structure. In addition to performing computer simulations, we derive analytical results for several types of Boolean networks, in particular for Random Boolean Networks. We also apply our method to networks that have been evolved for robustness to small perturbations, and to a biological example

A complete devil's staircase in the Falicov-Kimball model

We consider the neutral, one-dimensional Falicov-Kimball model at zero temperature in the limit of a large electron--ion attractive potential, U. By calculating the general n-ion interaction terms to leading order in 1/U we argue that the ground-state of the model exhibits the behavior of a complete devil's staircase.Comment: 6 pages, RevTeX, 3 Postscript figure

Self-organization of heterogeneous topology and symmetry breaking in networks with adaptive thresholds and rewiring

We study an evolutionary algorithm that locally adapts thresholds and wiring in Random Threshold Networks, based on measurements of a dynamical order parameter. A control parameter $p$ determines the probability of threshold adaptations vs. link rewiring. For any $p < 1$, we find spontaneous symmetry breaking into a new class of self-organized networks, characterized by a much higher average connectivity $\bar{K}_{evo}$ than networks without threshold adaptation ($p =1$). While $\bar{K}_{evo}$ and evolved out-degree distributions are independent from $p$ for $p <1$, in-degree distributions become broader when $p \to 1$, approaching a power-law. In this limit, time scale separation between threshold adaptions and rewiring also leads to strong correlations between thresholds and in-degree. Finally, evidence is presented that networks converge to self-organized criticality for large $N$.Comment: 4 pages revtex, 6 figure