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Characterizing the metabolic phenotype: a phenotype phase plane analysis
Jeremy S Edwards1, Ramprasad Ramakrishna, Bernhard O Palsson
1Department of Chemical Engineering, University of Delaware, Newark, Delaware 19716, USA. edwards@che.udel.edu
Biotechnology and Bioengineering
|December 18, 2001
Summary
This study introduces a novel "phase plane" analysis for metabolic networks, mapping optimal flux distributions across various conditions. This approach reveals distinct metabolic states and genotype-phenotype relationships for improved understanding.
Area of Science:
- Systems Biology
- Metabolic Engineering
- Computational Biology
Background:
- Genome-scale metabolic reconstructions are essential for understanding cellular metabolism.
- Flux Balance Analysis (FBA) traditionally analyzes one condition at a time, limiting insights into metabolic capabilities.
- A comprehensive view requires analyzing metabolic networks across diverse growth conditions.
Purpose of the Study:
- To develop a novel "phase plane" analysis for metabolic networks.
- To map optimal metabolic flux distributions across a range of conditions defined by substrate availability.
- To characterize distinct metabolic states and their relationship to genotype-phenotype dynamics.
Main Methods:
- Reconstruction of genome-scale metabolic maps.
- Broadened Flux Balance Analysis (FBA) to map flux distributions onto a substrate availability plane.
- Identification and interpretation of distinct metabolic phases using shadow price isoclines.
- Generation of Phenotype Phase Planes (PhPPs) for Escherichia coli.
Main Results:
- A finite number of qualitatively distinct metabolic pathway utilization patterns were identified, dividing the phase plane into discrete phases.
- Isoclines derived from shadow prices effectively classify the metabolic network's state.
- Phenotype Phase Planes (PhPPs) were generated for E. coli, illustrating metabolic phenotypes under varying carbon sources and oxygenation levels.
Conclusions:
- The developed "phase plane" analysis provides a powerful tool for understanding metabolic genotype-phenotype relations across multiple conditions.
- This methodology offers a more comprehensive view of metabolic network capabilities compared to traditional single-condition FBA.
- The study demonstrates the utility of PhPPs for analyzing microbial metabolism, with implications for metabolic engineering and synthetic biology.
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