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

The physics of bacterial decision making

The choice that bacteria make between sporulation and competence when subjected to stress provides a prototypical example of collective cell fate determination that is stochastic on the individual cell level, yet predictable (deterministic) on the population level. This collective decision is performed by an elaborated gene network. Considerable effort has been devoted to simplify its complexity by taking physics approaches to untangle the basic functional modules that are integrated to form the complete network: (1) A stochastic switch whose transition probability is controlled by two order parameters—population density and internal/external stress. (2) An adaptable timer whose clock rate is normalized by the same two previous order parameters. (3) Sensing units which measure population density and external stress. (4) A communication module that exchanges information about the cells' internal stress levels. (5) An oscillating gate of the stochastic switch which is regulated by the timer. The unique circuit architecture of the gate allows special dynamics and noise management features. The gate opens a window of opportunity in time for competence transitions, during which the circuit generates oscillations that are translated into a chain of short intervals with high transition probability. In addition, the unique architecture of the gate allows filtering of external noise and robustness against variations in circuit parameters and internal noise. We illustrate that a physics approach can be very valuable in investigating the decision process and in identifying its general principles. We also show that both cell-cell variability and noise have important functional roles in the collectively controlled individual decisions

Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks

It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrateComment: 39 pages, 15 figures, to appear in PLOS Computational Biolog

Swarming and complex pattern formation in Paenibacillus vortex studied by imaging and tracking cells

<p>Abstract</p> <p>Background</p> <p>Swarming motility allows microorganisms to move rapidly over surfaces. The Gram-positive bacterium <it>Paenibacillus vortex </it>exhibits advanced cooperative motility on agar plates resulting in intricate colonial patterns with geometries that are highly sensitive to the environment. The cellular mechanisms that underpin the complex multicellular organization of such a simple organism are not well understood.</p> <p>Results</p> <p>Swarming by <it>P. vortex </it>was studied by real-time light microscopy, by <it>in situ </it>scanning electron microscopy and by tracking the spread of antibiotic-resistant cells within antibiotic-sensitive colonies. When swarming, <it>P. vortex </it>was found to be peritrichously flagellated. Swarming by the curved cells of <it>P. vortex </it>occurred on an extremely wide range of media and agar concentrations (0.3 to 2.2% w/v). At high agar concentrations (> 1% w/v) rotating colonies formed that could be detached from the main mass of cells by withdrawal of cells into the latter. On lower percentage agars, cells moved in an extended network composed of interconnected "snakes" with short-term collision avoidance and sensitivity to extracts from swarming cells. <it>P. vortex </it>formed single Petri dish-wide "supercolonies" with a colony-wide exchange of motile cells. Swarming cells were coupled by rapidly forming, reversible and non-rigid connections to form a loose raft, apparently connected <it>via </it>flagella. Inhibitors of swarming (<it>p</it>-Nitrophenylglycerol and Congo Red) were identified. Mitomycin C was used to trigger filamentation without inhibiting growth or swarming; this facilitated dissection of the detail of swarming. Mitomycin C treatment resulted in malcoordinated swarming and abortive side branch formation and a strong tendency by a subpopulation of the cells to form minimal rotating aggregates of only a few cells.</p> <p>Conclusion</p> <p><it>P. vortex </it>creates complex macroscopic colonies within which there is considerable reflux and movement and interaction of cells. Cell shape, flagellation, the aversion of cell masses to fuse and temporary connections between proximate cells to form rafts were all features of the swarming and rotation of cell aggregates. Vigorous vortex formation was social, i.e. required > 1 cell. This is the first detailed examination of the swarming behaviour of this bacterium at the cellular level.</p