A scalable algorithm to explore the Gibbs energy landscape of genome-scale metabolic networks

The integration of various types of genomic data into predictive models of biological networks is one of the main challenges currently faced by computational biology. Constraint-based models in particular play a key role in the attempt to obtain a quantitative understanding of cellular metabolism at genome scale. In essence, their goal is to frame the metabolic capabilities of an organism based on minimal assumptions that describe the steady states of the underlying reaction network via suitable stoichiometric constraints, specifically mass balance and energy balance (i.e. thermodynamic feasibility). The implementation of these requirements to generate viable configurations of reaction fluxes and/or to test given flux profiles for thermodynamic feasibility can however prove to be computationally intensive. We propose here a fast and scalable stoichiometry-based method to explore the Gibbs energy landscape of a biochemical network at steady state. The method is applied to the problem of reconstructing the Gibbs energy landscape underlying metabolic activity in the human red blood cell, and to that of identifying and removing thermodynamically infeasible reaction cycles in the Escherichia coli metabolic network (iAF1260). In the former case, we produce consistent predictions for chemical potentials (or log-concentrations) of intracellular metabolites; in the latter, we identify a restricted set of loops (23 in total) in the periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility in a large sample ($10^6$) of flux configurations generated randomly and compatibly with the prior information available on reaction reversibility.Comment: 11 pages, 6 figures, 1 table; for associated supporting material see http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.100256

Umweltschutz und Arbeitsschutz zwischen Eigenstaendigkeit und Gemeinsamkeit vom Programm zur Praxis

SIGLEIAB-91-8040..-80 BB 678 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Reaction network realizations of rational biochemical systems and their structural properties

30 pages, 4 figures, 1 tableIn this paper, a frequently used representation of mass-action type reaction networks is extended to a more general system class where the reaction rates are in rational function form. An algorithm is given to compute a possible reaction graph from the kinetic differential equations. However, this structure is generally non-unique, as it is illustrated through the phenomenon of dynamical equivalence, when different reaction network structures correspond to exactly the same dynamics. It is shown that under some technical assumptions, the so-called dense realization containing the maximal number of reactions, forms a super-structure in the sense that the reaction graph of any dynamically equivalent reaction network is the sub-graph of the dense realization. Additionally, optimization based methods are given to find dynamically equivalent realizations with preferred properties, such as dense realizations or sparse realizations. The introduced concepts are illustrated by examples.Peer reviewe