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Can sugars be produced from fatty acids? A test case for pathway analysis tools.
Luis F de Figueiredo1, Stefan Schuster, Christoph Kaleta
1Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany. ldpf@minet.uni-jena.de;
Bioinformatics (Oxford, England)
|September 23, 2008
Summary
Even-chain fatty acids cannot convert to sugars at steady state without the glyoxylate shunt. Elementary modes analysis (EMA) accurately predicts metabolic pathways, unlike graph theory tools which struggle with complex systems.
Area of Science:
- Systems Biology
- Metabolic Engineering
- Computational Biochemistry
Background:
- Automated metabolic pathway determination methods based on network topology are increasingly common.
- A key biochemical question is whether even-chain fatty acids, crucial lipid components, can be converted to sugars under steady-state conditions.
- Historical evidence indicates this conversion is impossible via the Krebs cycle alone, requiring the glyoxylate shunt or alternative pathways.
Purpose of the Study:
- To analyze and compare different automated metabolic pathway determination methods.
- To use the conversion of even-chain fatty acids to sugars as a benchmark case study.
- To evaluate the efficacy of elementary modes analysis (EMA) against graph theory-based tools.
Main Methods:
- Elementary Modes Analysis (EMA) applied to a metabolic network including the Krebs cycle, glycolysis, and gluconeogenesis.
- Comparison of EMA with online graph theory tools: PathFinding and Pathway Hunter Tool.
- Analysis focused on network topology, stoichiometry, and reaction reversibility.
Main Results:
- EMA confirms that converting acetyl-CoA to glucose at steady state is not possible without the glyoxylate shunt.
- The addition of isocitrate lyase and malate synthase enables this conversion.
- PathFinding and Pathway Hunter Tool failed to accurately predict known metabolic conversions, generating unbalanced pathways and misidentifying key metabolites.
Conclusions:
- EMA accurately models metabolic pathways by considering topology and stoichiometry.
- Graph theory tools lack the necessary detail for reliable metabolic pathway analysis in complex systems.
- Accurate metabolic pathway analysis necessitates a comprehensive approach, including reaction stoichiometry and reversibility, as exemplified by EMA.
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