Andreas Deutsch

Collective phenomena in interacting cell systems

Previous and current research

Our main research is targeted at the development of mathematical models and simulation tools for detecting organizational principles of selected biological systems. We focus on collective behaviour of "cellular systems" which drives in particular the development of organismic forms. Disorders in cell interaction can imply diseases and malignant pattern formation (e.g. tumour growth). We work on concrete interdisciplinary projects on the basis of local, national and international cooperations. Important insights into function and regulation of biological systems can be gained from the linking of mathematical modelling and computational tools with biological/medical (in vitro, in vivo) data. The group has developed cellular automaton models as new standard mathematical modelling method for uncovering principles of cellular and signalling networks and published a monograph on cellular automaton models. Applications include problems in bacterial pattern formation, biological development, bone remodelling, and cancer growth.

In particular, we have previously applied our mathematical modelling approach to better understand collective phenomena in colonies of myxobacteria. Populations of bacterial cells exhibit rich collective dynamics and self-organization, in which the constituent cells adopt specific functions in response to environmental conditions. Pattern formation in these systems is generally thought to rely on specific long-range or short-range cooperative mechanisms of communication between cells, that are genetically controlled and lead to morphogenetic cell movements. In contrast, we have shown that the combination of active cell motion and an elongated cell shape is enough to produce clustering and collective motion. That is, clustering and the related coordinated collective motion do not in any way require genetic control or cooperative communication, but can arise quite naturally from active cell motion and an elongated cell shape. Our evidence supports the idea that gliding bacteria can coordinate their motion and aggregate, provided they are rod-shaped and cell density is sufficiently high. We are currently working on extensions of these ideas to other phases of the myxobacterial life cycle (e.g. fruiting body).

We have also demonstrated that mathematical modelling can contribute to deciphering the principles of tumour growth and invasion. Besides more and more complex molecular investigations, mathematical modelling of selected aspects of tumour growth has become attractive within the last years (mathematical oncology). We have used cellular automaton models to successfully predict in vitro tumour growth and invasion. Simulations show that such models permit to investigate characteristic growth and invasion scenarios. In the future, in silico simulations shall allow to test clinical therapies. This requires development of new models (e.g. multiscale models based on cellular automata and lattice Boltzmann models). Special emphasis lies on the extension of the models to three dimensions and the incorporation of patient data.

Fig. Collective behaviour (cluster formation) in computer simulation of interacting bacterial cells. Simulation snapshots for different cell anisotropy (length-width ratio) and the same packing fraction. Arrows indicate the direction of motion of some of the clusters (from F. Peruani, A. Deutsch, and M. Bär, Nonequilibrium clustering of self-propelled rods, Phys. Rev. E, 74, 030904, 2006).

Future prospects and goals

Our future research is targeted towards problems from cell and developmental biology as well as extension of our models to further medical applications. In close cooperation with experimentalists we will try to decipher the organization of the endocytic system, myotome patterning, and regeneration of limbs in axolotl and zebra fish.  Together with clinicians from Germany and Switzerland we want to analyze glioma brain tumours, especially progression from less malignant to malignant types. A further goal is to develop mathematical models and computer simulations for a better understanding of bone remodelling and feedback mechanisms with biological and non biological implants in healthy and diseased bones (osteoporosis, multiple myelom).

About

1991: Dr. rer. nat. in Mathematical Biology, University of Bremen 1992-1999: Research assistant at the department “Theoretical Biology”, University of Bonn 1999: Habilitation and Venia legendi in “Theoretical biology”  1999-2001: Guest scientist at Max Planck Institute for the Physics of Complex Systems, Dresden 2001-today: Head of department “Methods of Innovative Computing”, Centre for High Performance Computing (ZIH), Technische Universität Dresden

Selected publications

M. Tektonidis, H. Hatzikirou, A. Chauviere, M. Simon, K. Schaller & A. Deutsch. (2011): Identification of intrinsic in vitro cellular mechanisms for glioma invasion, J. Theoret. Biol., doi: 10.1016/j.jtbi.2011.07.012

F. Peruani, T. Klauss, A. Deutsch, A. Voss-Böhme (2011): Traffic jams, gliders and bands in the quest for collective motion of self-propelled, particles, Phys. Rev. Lett.

C. Landsberg, F. Stenger, A. Deutsch, M. Gelinsky, A. Rösen-Wolff, & A. Voigt (2011): Chemotaxis of mesenchymal stem cells within 3D biomimetic scaffolds--a modeling approach, J.  Biomechan., 44, 359 - 364

P. del Conte-Zerial, L. Brusch, J. Rink, C. Collinet, Y. Kalaidzidis, M. Zerial, & A. Deutsch (2008): Membrane identity and GTPase cascades regulated by toggle and cut-out switches. Mol. Syst. Biol., 4, 206

A. Deutsch, & S. Dormann (2005): Cellular automaton modeling of biological pattern formation: characterization, applications, and analysis Birkhäuser, Boston

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