• Ralf Steuer
• Henning Knoop (PhD Student)
• Sabrina Hoffmann (postdoc)
• Stefan Mueller (postdoc)
• Raik Otto (student)

Unicellular cyanobacteria have attracted growing attention as potential host organisms for the production of valuable organic products and provide ideal model organisms to understand oxygenic photosynthesis and phototrophic metabolism. Our current research is focused on computational methods to facilitate and enhance biofuel production using cyanobacteria. The aim is to integrate photosynthetic solar energy conversion and engine-ready fuel biosynthesis in a single biological process. We are responsible for metabolic modeling within the project “FORSYS-Partner: Systems Biology of Cyanobacterial Biofuel Production” (2008-2011), aiming at direct synthesis of ethanol. Recently, the group acquired funding to extend our approach towards volatile hydrocarbon fuels, such as ethylene, the short-chain nalkanes ethane and propane, as well as medium chain alkanes (www.directfuel.eu). We work on a high-quality reconstruction of the cyanobacterial metabolic map, supported by innovative experimental methodology, such as Transposon-Mediated Differential Hybridisation (in collaboration with the University of Freiburg).

One of the most challenging goals of computational systems biology is the development of large-scale kinetic models of cellular pathways. However, for most cellular networks, detailed kinetic modeling is not possible due to lack of knowledge kinetic parameters. To overcome some of these problems, we are interested in novel methods that allow the elucidation of large-scale metabolic networks in the face of uncertain and incomplete information. Recent work includes novel approaches that provide a bridge between structural (topological and stoichiometric) analysis and explicit kinetic simulations (Steuer et al., PNAS, 2006; Steuer and Junker, Advances in Chemical Physics, 2009). Without requiring knowledge about the explicit functional form of the kinetic rate equations and parameters, these methods seek to describe the possible dynamics of cellular networks. Our current research focuses on the dynamic stability of metabolic pathways with respect to biotechnological and biomedical applications (Grimbs et al, Mol.Sys. Biol., 2007; Steuer et al., Bioinformatics, 2007).

Noise and fluctuations are ubiquitous in living systems. Still, the interaction between complex biochemical regulatory networks and the inherent fluctuations ('noise') is only poorly understood. To elucidate the interrelation between noise and function, my work investigates the implications of stochastic fluctuations on cellular regulatory systems, such as signal transduction networks, circadian clocks, or cell cycle control systems. Previous work includes the investigation of the effects of noise on a model of the eukaryotic cell cycle. The stochastic description leads to qualitative changes in the dynamic behavior, such as the emergence of noise-induced oscillations (Steuer, J. Theor. Biol., 2004). Current research is focussed on a deeper understanding of robust and reliable information processing in living cells (with M. Kollmann, Berlin, and V. Sourjik, Heidelberg).

Metabolomic measurements provide a wealth of information about the biochemical status of cells, tissues and organs and play an important role to elucidate the function of novel genes. A remarkable inherent feature of cellular metabolism is that the concentrations of a small but significant number of metabolites are strongly correlated when measurements of biological replicates are performed. Drawing upon concepts of Nonlinear Dynamics and Computer Science, my research seeks to elucidate how comparative correlation analysis offers a way to exploit the intrinsic variability of metabolic networks to obtain significant additional information about the physiological state of the system (Morgenthal et al., Biosystems, 2006; Steuer et al., Bioinformatics, 2003).

• FORSYS-Partner: Systems Biology of Cyanobacterial Biofuel Production (BMBF)
• EU FP7 STREP: DirectFuel, www.directfuel.eu
• SysMO (via Hans Westerhoff, Manchester)