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Integrative top-down system metabolic modeling in experimental disease states via data-driven Bayesian methods.
Jung-Wook Bang1, Derek J Crockford, Elaine Holmes
1Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology & Anaesthetics, Sir Alexander Fleming Building, Imperial College, London SW7 2AZ, UK.
Journal of Proteome Research
|January 9, 2008
Summary
This study introduces metabolic interactome maps, a novel systems biology approach using biofluid data to model complex metabolic interactions and assess organismal health. This method aids in understanding liver injury and other dysfunctions from noninvasive measurements.
Area of Science:
- Systems biology
- Metabolomics
- Bioinformatics
Background:
- Metabolic profiles in biofluids reflect organismal health.
- Current metabolic pathway modeling faces challenges due to complex biological systems.
- Novel methods are needed for analyzing minimally invasive metabolic data.
Purpose of the Study:
- To develop a new approach for analyzing metabolic data to reconstruct patho-physiological modulations.
- To create probabilistic graphical models of metabolite dependencies, termed metabolic interactome maps.
- To infer system-level mechanistic information on homeostasis and assess lesion reversibility.
Main Methods:
- Utilized spectroscopically derived metabolic data from experimental liver injury models (hydrazine and alpha-napthylisothiocyanate).
- Developed probabilistic graphical models to represent metabolite dependencies.
- Constructed "metabolic interactome maps" to visualize these dependencies.
Main Results:
- Metabolic interactome maps provide insightful models of metabolite dependencies.
- System-level mechanistic information on homeostasis was inferred from the maps.
- Variations in metabolic network patterns correlated with the reversibility of induced liver lesions.
Conclusions:
- Spectroscopically derived metabolic data can generate powerful metabolic interactome maps.
- This approach offers a way to assess system-level dysfunction from noninvasive measurements in animal and human studies.
- Metabolic interactome maps enhance understanding of homeostasis and disease progression.
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