Narrow Results

Economics is a very powerful discipline that focuses on some important aspects of our life, in particular, constrained maximization equilibrium in resource allocation. However, orthodox economics based on simplified models and many economists much captured by such models have too narrow a focus, ignoring many important factors including the importance of competition for relative standing, environmental disruption, and behaviour patterns inconsistent with the narrow concept of rationality. Economics has also become excessively formalistic, sacrificing relevance for technical sophistication. Extensions of economics to overcome these weaknesses have been and are being made. The incorporation of these advances will make economics more useful. But more time and resources may be needed to train economists properly.

The producibility of metabolites from available resources is investigated systematically using flux balance analysis (FBA) and network expansion. Calculations are performed for the genome-scale metabolic networks of Escherichia coli and Methanosarcina barkeri. Strict biological interpretation of the results obtained with FBA leads to the concept of sustainability, which reduces the set of producible metabolites by assuming a growing and dividing cell. A systematic comparison showed that applying network expansion in many cases results in exactly the set of all sustainable metabolites. The purely heuristic approach of allowing for certain cofactors to facilitate reactions during the process of network expansion dramatically helps to improve agreement of the results from the two different approaches. In conclusion, we state that network expansion, due to its enormous advantages in computational speed, is a valuable alternative to determining producible metabolites with FBA.

Studies of genome-scale metabolic networks allow for qualitative and quantitative descriptions of an organism's capability to convert nutrients into products. The set of synthesizable products strongly depends on the provided nutrients as well as on the structure of the metabolic network. Here, we apply the method of network expansion and the concept of scopes, describing the synthesizing capacities of an organism when certain nutrients are provided. We analyze the biosynthetic properties of four species: Arabidopsis thaliana, Saccharomyces cerevisiae, Buchnera aphidicola, and Escherichia coli. Matthäus et al. [12] have recently developed a method to identify clusters of scopes, reflecting specific biological functions and exhibiting a hierarchical arrangement, using the network comprising all reactions in KEGG. We extend this method by considering random sets of nutrients on well-curated networks of the investigated species from BioCyc. We identify structural properties of the networks that allow to differentiate their biosynthetic capabilities. Furthermore, we evaluate the quality of the clustering of scopes applied to the species-specific networks. Our study provides a novel assessment of the biosynthetic properties of different species.

Cooperation between organisms of different species is a widely observed phenomenon in biology, ranging from large scale systems such as whole ecosystems to more direct interactions like symbiotic relationships. In the present work, we explore inter-species cooperations on the level of metabolic networks.

For our analysis, we extract 447 organism specific metabolic networks from the KEGG database [7] and assess their biosynthetic capabilities by applying the method of network expansion [5]. We simulate the cooperation of two organisms by unifying their metabolic networks and introduce a measure, the gain Γ, quantifying the amount by which the biosynthetic capability of an organism is enhanced due to the cooperation with another species. For all theoretically possible pairs of organisms, this synergetic effect is determined and we systematically analyze its dependency on the dissimilarities of the interacting partners. We describe these dissimilarities by two different distance measures, where one is based on structural, the other on evolutionary differences.

With the presented method, we provide a conceptional framework to study the metabolic effects resulting from an interaction of different species. We outline possible enhancements of our analysis: by defining more realistic interacting networks and applying alternative structural investigation methods, our concept can be used to study specific symbiotic and parasitic relationships and may help to understand the global interplay of metabolic pathways over the boundary of organism specific systems.