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Analysis on relationship between extreme pathways and correlated reaction sets
Yanping Xi1, Yi-Ping Phoebe Chen, Ming Cao
1School of computer science and technology, Fudan University, Shanghai, PR China. 071021055@fudan.edu.cn
BMC Bioinformatics
|February 12, 2009
Summary
Extreme pathways in metabolic networks often act as a single unit, either fully utilizing or completely avoiding reactions within correlated reaction sets. This reveals a complementary relationship and suggests regulatory mechanisms within cellular metabolism.
Area of Science:
- Systems Biology
- Metabolic Engineering
- Computational Biology
Background:
- Constraint-based modeling is used for genome-scale metabolic networks.
- Extreme pathways and elementary flux modes characterize allowable phenotypes.
- Exponential increase in pathways complicates analysis; uniform random sampling aids phenotype study.
Purpose of the Study:
- Investigate the relationship between extreme pathways and correlated reaction sets.
- Understand how reaction dependencies are represented by pathways.
- Explore potential regulatory mechanisms in metabolic networks.
Main Methods:
- Identified correlated reaction sets for E. coli, red blood cell, and yeast metabolic networks.
- Enumerated extreme pathways for E. coli and red blood cell networks.
- Sampled extreme pathways for the large-scale yeast network.
Main Results:
- Correlated reaction sets were identified across different metabolic networks.
- Extreme pathways typically cover correlated reaction sets in an 'all or none' manner.
- Rarely, combinations of extreme pathways provide flexibility and redundancy for cell survival.
Conclusions:
- Both extreme pathways and correlated reaction sets are derived from metabolic network topology.
- A strong relationship suggests extreme pathways are regulated by correlated reaction sets.
- Correlated reaction sets may be further regulated by the organism's biological network.
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