Field of Theoretical Biology at the University of Bonn

Publications | Cellular movement | Swarms and search strategies | Biological surfaces and biofilms | Evolutionary ecology and dynamics | Collective knowledge in biological systems | Diese Seite auf Deutsch

We focus our research on the interactive dynamics in biological movement, growth and evolution. Naturally we are open to other topics as well. On this page you find a summary of our research topics and projects:

Cellular movement

Topic Examples Team members Cooperations
Molecular motors   Martin Wiechert  
Polymere dynamics (SFB 611) Actine filament systems Edith Geigant, Dieter Felix, Wolfgang Alt Dr. Jürgen Lenz,
Cell form dynamics Ceratinocytes, Schizosaccharomyces pombe Edith Geigant, Wolfgang Alt Dr. Jürgen Lenz, IZB
Cell adhesion and migration Vesikel Wolfgang Alt Till Bretschneider, Jürgen Lenz
Movement in cell assemblies 2D monolayers, endothelium, epithelium, myxobacteria, tumor cells Wolfgang Alt, Michael Wurzel Schnitter (Uni Dresden)

Movement indicates life. To be in keeping with the times we have to be mentally agile and spatially mobile. That is why the baby is beaming when taking his first steps, the teen jumps onto his bike, and Michael Schumacher earns millions driving his racing car. In these examples, the human muscles make movement possible (in Michael Schumachers case the muscles in his calfs while stepping on the gas).

Molecular motors

Since H.E. Huxley's work in the late 60ies it is well-known that muscle contractions are caused by the interplay of actin and myosin. Myosin is a so-calle 'molecular motor', which transforms chemical energy in movement with an effectiveness that exceeds that of Schumacher's motor many times over.


The force generator (i.e. the motor) myosin must work with 'gears': In the muscle cell these are actin bundles, to which myosin binds and whose spatial position it moves. Actin is present not only in muscle cells but in almost all cell types, where it fulfills a bunch of tasks. To name only the most important: cells (esp. cell walls) become more stable by actin cortexes, cell layers are strengthened by actin networks, and actin (with myosin) is necessary for movement. It is amazing that single actin filaments have simple thread-like structures. However, they can be connected into one-, two-, and three-dimensional nets by various kinds of accessory proteins (named actin binding proteins), by which their physical properties are very much changed.


Below the membrane of many cells a thin layer of actin filaments is formed that gives shape and stability to the cell. Surprisingly, this happens also in vesicles which are very simple balloons surrounded by a membrane. Which factors may cause cortex formation is at present one topic of our theoretical modelling.

Zellform dynamics and cell migration


On first sight is may be surprising that some cells can move. But think of the many unicellular organisms that live in a more or less hostile environment. And even in multicellular organisms (like your body) there are single cells that can move, e.g. leukocytes (in the blood), certain skin cells (keratinocytes) which close wounds, or (much more dangerous) tumor cells during metastasis. Crawling keratinocytes change their shape: they form flat or lengthy 'pseudopods' (e.g. lamellipods) with which they pull forward. Dynamics and control of this movement are experimentally analysed and theoretically modelled in our group.

Zell adhesion and -migration

Nobody walkes on glacial ice without spikes; similarly any cell needs means to cling to its substrate: these are the so-called adhesion sites (i.e. binding sites). On the other hand, a cell can move only if adhesion to the underground can be detached again. Our group is mainly interested in movement of keratinocytes and certain kinds of tumor cells. What stimulates the keratinocyte to leave the cell layer (of the skin) and to move to the wound area? Why loosen some tumor cells from the tumor, how do they move and which paths do they follow?

Movement in cell layers

Most cells, even bacteria, do not live and move alone but in more or less close contact with neighbors. This cooperative movement leads to phenomena which are analyzed theoretically in our group. A thrilling example are gliding patterns of myxobacteria which form single- and two-laned 'streets', spirals, and wave-like patterns (rippling). However, even in cell tissues, in which cells are closely fastened to each other, e.g. in epithelia or endothelia (skin), movement is still possible (under certain circumstances like the healing of a nearby wound).

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Swarms and search strategies

Topic Examples Team members Cooperations
Chemotaxis Rezeptor adaption Wolfgang Alt  
Suchstrategien Gametes of the brown algae Ectocarpus siliculosus, desert arthropodes Wolfgang Alt, Andreas Neudecker, Tobias Merkle  
Swarms flocking birds, migratory birds' behaviour, cell swarms Ralf Müller, Wolfgang Alt, Marcus Tilch  


Chemotaxis a well studied behavioural strategy of motile organisms. It helps to effectively target and reach higher or lower concentrations of a certain chemical substance (i.e. an attractant or repellant). Examples are flagellated bacteria like E. coli. Here, the mechanism is based on a transient changes of run lengths due to a change in the fraction of specific chemotaxis receptor ligand complexes. Usually the prototypical behaviour of a perfect adaptation can be observed. We study mathematical models of chemical kinetics for the signal transductions (which is fully understood for E. coli), wich can reproduce perfect adaptation on the level of receptor methylation/de-methylation . [Wolfgang Alt]

Search strategies of single cells and monads (single cell organisms)

Path of a male Ectocarpus gamete in search of a female gamete.

Eukaryotic flagellated monads and other flagellated cells show more complex search behaviour and strategies. The male gametes of the brown algae Ectocarpus siliculosus react to the sexual attractant (pheromone) Ectocarpene which female gametes of the species emit into the water, when they have settled down on a surface to wait for a male gamete. Experimental observations, statistical path analysis and stochastic simulation models indicate an optimised step-by-step search strategy:

  1. Thigmotaxis: Ectocarpene-dependent tendency to stay on a 2-dimensional surface (as oposed to swim in the 3-dimensional body of water).
  2. Chemokinesis: Curvature of the male gamete's path increases with higher concentrations of Ectocarpene.
  3. Inverse negative chemotaxis: Perception of a decreasing Ectocarpene gradient (in time) is answered by an abrupt beat of the posterior flagellum which results in a sudden change of direction towards an increasing Ectocarpene gradient.

[Andreas Neudecker]

Desert arthropodes

Path of a desert and, including homevector (red).

The amazingly precise and convergent ability of many desert arthropodes (i.e. the ant Cataglyphis fortis or the beatle Parastizopus armaticeps ) to find their way back home after successful foraging is based on an internal mechanism of "path integration", i.e. by tallying of the speed and change of angle along the path. Examination of several different mathematical models aims to find an answer to the general question of the possible form of a representation of the "location of the lair" in the organism.

Previous work has been done in cooperation with the Institutes for Zoology (Prof. H.-G. Heinzel) at the universities of Bonn and Zurich (Prof. R. Wehner) as well as the "Bonn Philosophical Seminar" (Prof. A. Bartels). We have taken this up again and will proceed in collaboration with the institutions above.

Flocking birds and multi particle systems

A central topic is the mathematical modelling of interaction dynamics during the formation of cell swarms (i.e. with myxobacteria) or flocking birds (especially migratory birds). For confluent two-dimensional monolayers of cells as they are found during embryogenesis or the healing of wounds, or for the relatively ordered flocks of wild geese or starlings, interaction terms (forces or accelerations) depend essentially on positional and speed differences of the "nearest neighbors". For the definition of these neighborhoods (wich can change in time) generalisations of the classical geometric Voronoj-Delaunay segmentation can be used. Besides simulation and analysis of corresponding multi-particle systems we study continuum limits which lead to generalised Navier-Stokes equations for the description of viscoelastic fluids with open boundaries.

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Biological surfaces and biofilms

Topic Examples Team members Cooperations
Surfactants on the alveolar films of the lung Martin Rost, Wolfgang Alt  
Microbial biofilms Plaques Jan Kreft, Andreas Dötsch  

Microbial biofilms


From a modelling perspective, biofilms, the slimy growth of microbes on a surface, share common aspects with above surfactant films in lung vesicles. Biofilms can be regarded as an ensemble of microbial cells embedded in a self-made viscoelastic extracellular matrix that can be deformed, eroded, and torn off by the shear due to flow in the liquid around the biofilm. The biofilm interface is therefore a free border, its shape influenced by growth and decay, turnover of the extracellular matrix, and detachment.

Since surface structures of the microbial cells allow specific binding forces to surfaces, the matrix, and like and unlike cells (coaggregation), biofilm models can also be considered as many particle systems with attractive and repulsive forces between them, i.e., swarms (see above).

Alveolar surfactant layers

A thin layer of surface active agents, shorter: surfactants, can drastically change the porperties of a surface. A layer of lipids or soap reduces the surface tension of an aquaeous surface by orders of magnitude. This is of crucial significance in alveoles of vertebrates' lungs which otherwise would collapse under surface tension.

The contents of lung surfactant layers have been studied in recent years: the bulk of the material consists of phospholipids, and among them dipamitoylphosphatidylcholine (DPPC) plays a major role. However, little is known about their dynamical properties because of obvious difficulties for observations. Surfactant molecules are constantly being produced and lost from the alveolar surface, so there is a steady flow which among others serves to remove dust particles.

In collaboration with Hans Wilhelm Alt (Institute for Applied Mathematics, Bonn) we try to derive and evaluate a hydrodynamical model which combines the dynamics of the bending surface of the alveole, the aquaeous layer and the lipid layer, moderated by friction and elastic forces together with random noise. A first approach uses so called `phase fields' which allow to treat the free boundaries of patches implicitly by a smooth function.

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Evolutionary ecology and dynamics

Topic Examples Team members Cooperations
Microbial cooperation and competition in biofilms Jan Kreft  
Sym- and parapatric speciation species formation in various degrees of spatial separation Martin Rost  

Microbial cooperation and competition

The interplay of cooperation and competition on two levels of selection, the individual and the group, is centre stage for life in biofilms, because cells in biofilms grow in clusters called microcolonies. Such clusters are sinks for substrate, thereby draining substrate from the surroundings by diffusion, creating a highly heterogenous resource distribution. Further growth of these clusters depends on patchy resources, leading to enhanced heterogeneity in microbial distribution and activity in a positive feedback loop. Under such conditions of substrate limitation and clustered growth, the economic use of resources becomes altruistic, defined as behaviour that increases the relative fitness of the group while decreasing the relative fitness of the altruist within the group.

Speciation in space

Speciation is the origin of new species by a split of a previously existing one into two or more. They may emerge in geographic isolation or allopatry, in full spatial mixing or sympatry or with partial overlap in livin ranges, so-called parapatry.

The predominant opinion on speciation processes has changed between extreme points over the last half century. After claiming for a few decades the prevalence of allopatric speciation the main emphasis has come back to its previous state, recognising the importance of sympatric speciation.

Phylogenetic studies based on DNA data have given striking evidence for sympatric speciation in various cases. Several model approaches over the last few yesar have unveiled its two central mechanisms: disruptive selection caused by competition and the possibility to establish reproductive isolation between subpopulations which are about two become two new sister species.

The wide range between these extremes, sympatric and allopatric speciation, has received more attention only recently. In cooperation with Birgit Kriener and Michael Lässig (Institute for Theoretical Physics, Cologne) we currently study different variations of a model of a sexually reproducing population in a spatially extended landscape.

In this model the mode of speciation is not imposed onto the population, but it is free to choose among the possible ways of isolation it wants to acquire, spatial or sexual. The choice depends on the outer conditions, which are in rough terms: habitat heterogeneity and migration rate across the landscape, densitiy and frequency dependence of competition among individuals.

As a quite generic scenario we find that reproductive isolation by mating incompatibility develops first, creating phenotypic variation in the population, which allows for spatial separation in a secondary step. This process seems to be quite robust, occuring for various types of mate choice, and for various model approaches to phenotype inheritance. It may be a tool to understand the ubiquity of spatial patchiness and mating assortativity of closely related species.

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Collective knowledge in biological systems

Topic Examples Team members Cooperations
Knowledge in biological systems Orientation of desert arthropods Tobias Merkle, Wolfgang Alt  

How can a little bug find its way through the desert in search for food and on its way back to the nest? How is the memory of spatial position and direction stored in the most efficient way? In a model frame of coupled stochastic differential equations we look for answers to these questions.

This project is part III.1 of a newly established interdisciplinary research group on forms of knowledge at Bonn university.

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