Biomedical subjects

Jan-Ulrich Kreft

Publications and source records attributed to Jan-Ulrich Kreft.

3 recordsLinked to original sources

PubMed2004

Biofilms promote altruism.

The origin of altruism is a fundamental problem in evolution, and the maintenance of biodiversity is a fundamental problem in ecology. These two problems combine with the fundamental microbiological question of whether it is always advantageous for a unicellular organism to grow as fast as possible. The common basis for these three themes is a trade-off between growth rate and growth yield, which in turn is based on irreversible thermodynamics. The trade-off creates an evolutionary alternative between two strategies: high growth yield at low growth rate versus high growth rate at low growth yield. High growth yield at low growth rate is a case of an altruistic strategy because it increases the fitness of the group by using resources economically at the cost of decreased fitness, or growth rate, of the individual. The group-beneficial behaviour is advantageous in the long term, whereas the high growth rate strategy is advantageous in the short term. Coexistence of species requires differences between their niches, and niche space is typically divided into four 'axes' (time, space, resources, predators). This neglects survival strategies based on cooperation, which extend the possibilities of coexistence, arguing for the inclusion of cooperation as the fifth 'axis'. Here, individual-based model simulations show that spatial structure, as in, for example, biofilms, is necessary for the origin and maintenance of this 'primitive' altruistic strategy and that the common belief that growth rate but not yield decides the outcome of competition is based on chemostat models and experiments. This evolutionary perspective on life in biofilms can explain long-known biofilm characteristics, such as the structural organization into microcolonies, the often-observed lack of mixing among microcolonies, and the shedding of single cells, as promoting the origin and maintenance of the altruistic strategy. Whereas biofilms enrich altruists, enrichment cultures, microbiology's paradigm for isolating bacteria into pure culture, select for highest growth rate.

Altruism↗

PubMed2004

Particle-based multidimensional multispecies biofilm model.

In this paper we describe a spatially multidimensional (two-dimensional [2-D] and three-dimensional [3-D]) particle-based approach for modeling the dynamics of multispecies biofilms growing on multiple substrates. The model is based on diffusion-reaction mass balances for chemical species coupled with microbial growth and spreading of biomass represented by hard spherical particles. Effectively, this is a scaled-up version of a previously proposed individual-based biofilm model. Predictions of this new particle-based model were quantitatively compared with those obtained with an established one-dimensional (1-D) multispecies model for equivalent problems. A nitrifying biofilm containing aerobic ammonium and nitrite oxidizers, anaerobic ammonium oxidizers, and inert biomass was chosen as an example. The 2-D and 3-D models generally gave the same results. If only the average flux of nutrients needs to be known, 2-D and 1-D models are very similar. However, the behavior of intermediates, which are produced and consumed in different locations within the biofilm, is better described in 2-D and 3-D models because of the multidirectional concentration gradients. The predictions of 2-D or 3-D models are also different from those of 1-D models for slowly growing or minority species in the biofilm. This aspect is related to the mechanism of biomass spreading or advection implemented in the models and should receive more attention in future experimental studies.

Anaerobiosis↗

PubMed1998

BacSim, a simulator for individual-based modelling of bacterial colony growth.

The generic, quantitative, spatially explicit, individual-based model BacSim was developed to simulate growth and behaviour of bacteria. The potential of this approach is in relating the properties of microscopic entities - cells - to the properties of macroscopic, complex systems such as biofilms. Here, the growth of a single Escherichia coli cell into a colony was studied. The object-oriented program BacSim is an extension of Gecko, an ecosystem dynamics model which uses the Swarm toolkit for multi-agent simulations. The model describes bacterial properties including substrate uptake, metabolism, maintenance, cell division and death at the individual cell level. With the aim of making the model easily applicable to various bacteria under different conditions, the model uses as few as eight readily obtainable parameters which can be randomly varied. For substrate diffusion, a two-dimensional diffusion lattice is used. For growth-rate-dependent cell size variation, a conceptual model of cell division proposed by Donachie was examined. A mechanistic version of the Donachie model led to unbalanced growth at higher growth rates, whereas including a minimum period between subsequent replication initiations ensured balanced growth only if this period was unphysiologically long. Only a descriptive version of the Donachie model predicted cell sizes correctly. For maintenance, the Herbert model (constant specific rate of biomass consumption) and for substrate uptake, the Michaelis-Menten or the Best equations were implemented. The simulator output faithfully reproduced all input parameters. Growth characteristics when maintenance and uptake rates were proportional to either cell mass or surface area are compared. The authors propose a new generic measure of growth synchrony to quantify the loss of synchrony due to random variation of cell parameters or spatial heterogeneity. Variation of the maximal uptake rate completely desynchronizes the simulated culture but variation of the volume-at-division does not. A new measure for spatial heterogeneity is introduced: the standard deviation of substrate concentrations as experienced by the cells. Spatial heterogeneity desynchronizes population growth by subdividing the population into parts synchronously growing at different rates. At a high enough spatial heterogeneity, the population appears to grow completely asynchronously.

Algorithms↗