Maria Concetta Palumbo | PubMed Health

PubMed2006

Metabolic pathways variability and sequence/networks comparisons.

BACKGROUND: In this work a simple method for the computation of relative similarities between homologous metabolic network modules is presented. The method is similar to classical sequence alignment and allows for the generation of phenotypic trees amenable to be compared with correspondent sequence based trees. The procedure can be applied to both single metabolic modules and whole metabolic network data without the need of any specific assumption. RESULTS: We demonstrate both the ability of the proposed method to build reliable biological classification of a set of microorganisms and the strong correlation between the metabolic network wiring and involved enzymes sequence space. CONCLUSION: The method represents a valuable tool for the investigation of genotype/phenotype correlations allowing for a direct comparison of different species as for their metabolic machinery. In addition the detection of enzymes whose sequence space is maximally correlated with the metabolic network space gives an indication of the most crucial (on an evolutionary viewpoint) steps of the metabolic process.

Algorithms↗

PubMed2005

Functional essentiality from topology features in metabolic networks: a case study in yeast.

The relation between the position of mutations in Saccharomyces cerevisiae metabolic network and their lethality is the subject of this work. We represent the topology of the network by a directed graph: nodes are metabolites and arcs represent the reactions; a mutation corresponds to the removal of all the arcs referring to the deleted enzyme. Using publicly available knock-out data, we show that lethality corresponds to the lack of alternative paths in the perturbed network linking the nodes affected by the enzyme deletion. Such feature is at the basis of the recently recognized importance of 'marginal' arcs of metabolic networks.

Energy Metabolism↗