Research article
Phylophenetic properties of metabolic pathway topologies as revealed by global analysis
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* Corresponding author: Runsheng Chen crs@sun5.ibp.ac.cn
- † Equal contributors
1 Bioinformatics Laboratory and National Laboratory of Bromacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
2 Bioinformatics Research Group, Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Beijing 100080, China
3 Graduate School of the Chinese Academy of Sciences, Beijing, China
BMC Bioinformatics 2006, 7:252 doi:10.1186/1471-2105-7-252
Published: 9 May 2006Abstract
Background
As phenotypic features derived from heritable characters, the topologies of metabolic pathways contain both phylogenetic and phenetic components. In the post-genomic era, it is possible to measure the "phylophenetic" contents of different pathways topologies from a global perspective.
Results
We reconstructed phylophenetic trees for all available metabolic pathways based on topological similarities, and compared them to the corresponding 16S rRNA-based trees. Similarity values for each pair of trees ranged from 0.044 to 0.297. Using the quartet method, single pathways trees were merged into a comprehensive tree containing information from a large part of the entire metabolic networks. This tree showed considerably higher similarity (0.386) to the corresponding 16S rRNA-based tree than any tree based on a single pathway, but was, on the other hand, sufficiently distinct to preserve unique phylogenetic information not reflected by the 16S rRNA tree.
Conclusion
We observed that the topology of different metabolic pathways provided different phylogenetic and phenetic information, depicting the compromise between phylogenetic information and varying evolutionary pressures forming metabolic pathway topologies in different organisms. The phylogenetic information content of the comprehensive tree is substantially higher than that of any tree based on a single pathway, which also gave clues to constraints working on the topology of the global metabolic networks, information that is only partly reflected by the topologies of individual metabolic pathways.