Statistical Physics of Living Systems
Previous and Current Research
The development of an organism relies on the tightly orchestrated behavior of many cells. How do these cells, each containing the same genetic information, self-organize in order to build complex structures like the heart or the brain? To achieve this that fate of these cells must be precisely regulated, such that the right number and type of cells is created at a given time and point in development. The question of how cellular behavior is controlled is at the center of stem cell biology, and understanding the mechanisms of cell fate regulation is key for treating diseases that occur upon dysregulation, such as cancer or diabetes.
The question of cell fate regulation can be asked on different scales. In our research group, we tackle this question on all of these scales: on the smallest scale, molecules interact with the DNA and change, for example, how it is folded, modify chemical binding properties, or initiate the expression of a gene. The sum of such interactions then gives rise to the molecular “signature” that defines a cell’s identity and behavior. Novel experimental developments, in particular in genomics, for the first time allow us to obtain high-resolution information on molecular states of cells in living organisms. In collaboration with experimental groups we make use of these possibilities and apply methods from statistical physics to unveil the mechanisms regulation cell behavior on the molecular level.
Research on cell fate has historically focused on the molecular mechanisms that underlie their behavior. With the recent development of transgenic mouse models, which allow labelling and manipulation of specific cell types, more and more emphasis has been placed on the tissue scale: How does the collective behavior of many cells gives rise to the architecture that is characteristic for given kind of tissue? Mathematically, cells in a tissue can often be considered as a statistical ensemble, like, for example, particles in a gas, such that the methods from statistical physics can be successfully applied to understand cell dynamics on the tissue level. In collaboration with experimentalists we use these methods to study self-organization phenomena of cell populations in tissue development, disease and regeneration.
Biological systems are characterized by a high degree of structure on all scales. For example, cells are internally highly compartmentalized and tissues consist of populations of highly specialized cells. This achieve this order biological system operate far from thermal equilibrium, posing significant challenges to their theoretical understanding. Therefore, while methods from theoretical physics can shed new light on biological processes, living systems at the same time challenge and advance our understanding of non-equilibrium physics.
Future Projects and Goals
Emerging experimental technologies allow us describe biological processes in more and more detail. But how can we identify the collective degrees of freedom that emerge from these processes and that define their functional consequences? Methodology of non-equilibrium statistical physics is as a natural framework to study collective behaviour in biological systems. Making use of these methods we collaborate with experimental groups to unveil molecular and tissue levels mechanisms regulating cellular behaviour during tissue development, maintenance and ageing.
Methodological and Technical Expertise
- Stochastic modelling
- Statistical physics
J. K. Watson, S. Rulands, A. C. Wilkinson, A. Wuidart, M. Ousset, A. Van Keymeulen, B. Göttgens, C. Blanpain, B. D. Simons, E. L. Rawlins
Clonal dynamics reveal two distinct populations of basal cells in slow turnover airway epithelium
Cell Reports, 12(1), 90–101 (2015)
F. Lescroart, S. Chabab, X. Lin, S. Rulands, C. Paulissen, A. Rodolosse, H. Auer, Y. Achouri, C. Dubois, A. Bondue, B. D. Simons, C. Blanpain
Early lineage restriction in temporally distinct populations of Mesp1 progenitors during mammalian heart development
Nature Cell Biology 16, 829–840 (2014)
S. Rulands, D. Jahn, E. Frey
Specialization and bet hedging in heterogeneous populations
Physical Review Letters 113, 108102 (2014)
S. Rulands, A. Zielinski, E. Frey
Global attractors and extinction dynamics of cyclically competing species
Physical Review E 87, 052710 (2013)
S. Rulands, B. Klünder, E. Frey
Stability of localized wave fronts in bistable systems
Physical Review Letters 110, 038102 (2013)