Methodology article

Metabolic pathways variability and sequence/networks comparisons

Kyaw Tun¹, Pawan K Dhar¹, Maria C Palumbo² and Alessandro Giuliani^3*

• * Corresponding author: Alessandro Giuliani alessandro.giuliani@iss.it

Author Affiliations

¹ Systems Biology Group, Bioinformatics Institute, 30 Biopolis Way, 138671, Singapore

² Department of Physiology and Pharmacology, University of Rome 'La Sapienza', P.Le Aldo Moro 10, 00182, Roma, Italy

³ Department of Environment and Health, Istituto Superiore di Sanita', Viale Regina Elena 299, 00161, Roma, Italy

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BMC Bioinformatics 2006, 7:24 doi:10.1186/1471-2105-7-24

Published: 18 January 2006

Abstract

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 microrganisms and the strong correlation between the metabolic network wiringand involved enzymes sequence space.

Conclusion

The method represents a valuable tool for the investigation of genotype/phenotype correlationsallowing 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 metabolicnetwork space gives an indication of the most crucial (on an evolutionary viewpoint) steps of the metabolic process.