18 research outputs found
Studies of Bacterial Branching Growth using Reaction-Diffusion Models for Colonial Development
Various bacterial strains exhibit colonial branching patterns during growth
on poor substrates. These patterns reflect bacterial cooperative
self-organization and cybernetic processes of communication, regulation and
control employed during colonial development. One method of modeling is the
continuous, or coupled reaction-diffusion approach, in which continuous time
evolution equations describe the bacterial density and the concentration of the
relevant chemical fields. In the context of branching growth, this idea has
been pursued by a number of groups. We present an additional model which
includes a lubrication fluid excreted by the bacteria. We also add fields of
chemotactic agents to the other models. We then present a critique of this
whole enterprise with focus on the models' potential for revealing new
biological features.Comment: 1 latex file, 40 gif/jpeg files (compressed into tar-gzip). Physica
A, in pres
Modeling branching and chiral colonial patterning of lubricating bacteria
In nature, microorganisms must often cope with hostile environmental
conditions. To do so they have developed sophisticated cooperative behavior and
intricate communication capabilities, such as: direct cell-cell physical
interactions via extra-membrane polymers, collective production of
extracellular "wetting" fluid for movement on hard surfaces, long range
chemical signaling such as quorum sensing and chemotactic (bias of movement
according to gradient of chemical agent) signaling, collective activation and
deactivation of genes and even exchange of genetic material. Utilizing these
capabilities, the colonies develop complex spatio-temporal patterns in response
to adverse growth conditions. We present a wealth of branching and chiral
patterns formed during colonial development of lubricating bacteria (bacteria
which produce a wetting layer of fluid for their movement). Invoking ideas from
pattern formation in non-living systems and using ``generic'' modeling we are
able to reveal novel survival strategies which account for the salient features
of the evolved patterns. Using the models, we demonstrate how communication
leads to self-organization via cooperative behavior of the cells. In this
regard, pattern formation in microorganisms can be viewed as the result of the
exchange of information between the micro-level (the individual cells) and the
macro-level (the colony). We mainly review known results, but include a new
model of chiral growth, which enables us to study the effect of chemotactic
signaling on the chiral growth. We also introduce a measure for weak chirality
and use this measure to compare the results of model simulations with
experimental observations.Comment: 50 pages, 24 images in 44 GIF/JPEG files, Proceedings of IMA
workshop: Pattern Formation and Morphogenesis (1998
Aggregation Patterns in Stressed Bacteria
We study the formation of spot patterns seen in a variety of bacterial
species when the bacteria are subjected to oxidative stress due to hazardous
byproducts of respiration. Our approach consists of coupling the cell density
field to a chemoattractant concentration as well as to nutrient and waste
fields. The latter serves as a triggering field for emission of
chemoattractant. Important elements in the proposed model include the
propagation of a front of motile bacteria radially outward form an initial
site, a Turing instability of the uniformly dense state and a reduction of
motility for cells sufficiently far behind the front. The wide variety of
patterns seen in the experiments is explained as being due the variation of the
details of the initiation of the chemoattractant emission as well as the
transition to a non-motile phase.Comment: 4 pages, REVTeX with 4 postscript figures (uuencoded) Figures 1a and
1b are available from the authors; paper submitted to PRL
Novel type of phase transition in a system of self-driven particles
A simple model with a novel type of dynamics is introduced in order to
investigate the emergence of self-ordered motion in systems of particles with
biologically motivated interaction. In our model particles are driven with a
constant absolute velocity and at each time step assume the average direction
of motion of the particles in their neighborhood with some random perturbation
() added. We present numerical evidence that this model results in a
kinetic phase transition from no transport (zero average velocity, ) to finite net transport through spontaneous symmetry breaking of the
rotational symmetry. The transition is continuous since is
found to scale as with