From Topology to Dynamics of Metabolic Networks

From the Manchester Bio-Modelling Network

The Bio-Modelling Network organised a lecture on network dynamics by Ralf Steuer from Humboldt University Berlin, on Wednesday 29th of August, 12:00 in MIB Lecture Theatre.

The slides of the presentation can be downloaded here.

From Topology to Dynamics of Metabolic Networks

Cellular metabolism is characterized by an intricate network of interactions between biochemical fluxes, metabolic compounds and regulatory interactions. To investigate and eventually understand the dynamic behavior arising from such networks of interactions is often not possible by intuitive reasoning alone, but necessitates the construction of detailed mathematical models. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values.

As a step towards the transition from topology to dynamics of metabolic pathways, the talk describes a strategy to infer a variety of dynamic properties from topological and stoichiometric information alone. It is shown that it is possible to acquire a quantitative picture of the possible dynamics of metabolic systems without assuming detailed knowledge of the underlying rate equations and parameters. The approach builds upon the increasing experimental accessibility of cellular characteristics, such as metabolic fluxes and concentrations of metabolic intermediates. Each (stationary) metabolic state, characterized by a defined flux distribution and metabolite concentrations, is associated with a unique spectrum of dynamic properties, as defined by the ensemble of all possible kinetic models consistent with the respective state.

The devised strategy represents an intermediate step from flux-balance analysis to explicit kinetic models of metabolic systems. We aim at an integrative ’modeling pipeline’ that does not require knowledge of all kinetic parameters, but nonetheless allows to give a quantitative account of the possible dynamics. Utilizing this approach, the role of feedback mechanisms in the maintenance of stability is discussed using several metabolic pathways of realistic complexity. It is conjectured that dynamic aspects of cellular regulation are a major factor in determining and anticipating the easibility of intended biotechnological modifications.

References

• Steuer et al. (2006) Structural kinetic modeling of metabolic networks. Proc Natl Acad Sci U S A, 103(32):11868—11873.
• Steuer et al. (2007) From Structure to Dynamics of Metabolic Pathways: Application to the Plant Mitochondrial TCA Cycle. Bioinformatics; doi: 10.1093/bioinformatics/btm065
• Steuer, R. (2007) Computational approaches to the topology, stability and dynamics of metabolic networks. Phytochemistry, doi:10.1016/j.phytochem.2007.04.041
• Steuer, R. (2006) ) On the Analysis and Interpretation of Correlations in Metabolomic Data (Review). Brief Bioinform. 7(2):151-8.