Automated Curation of Metabolic Reconstructions
Author Information
Author(s): Satish Kumar Vinay, Dasika Madhukar S, Maranas Costas D
Primary Institution: The Pennsylvania State University
Hypothesis
Can an optimization-based procedure effectively identify and fill gaps in microbial metabolic reconstructions?
Conclusion
The study presents systematic methods to identify and fill gaps in genome-scale metabolic reconstructions, demonstrating that many gaps can be resolved by modifying existing models and adding missing reactions.
Supporting Evidence
- About 10% of metabolites in E. coli and 30% in S. cerevisiae cannot carry any flux.
- The dominant mechanism for restoring flow is reversing the directionality of existing reactions.
- The study provides a list of hypotheses for further experimental testing.
Takeaway
The researchers found ways to fix problems in how we understand the metabolism of certain organisms by figuring out what was missing and adding it in.
Methodology
The study used optimization-based procedures called GapFind and GapFill to identify no-production metabolites and restore their connectivity in metabolic networks.
Limitations
Some metabolites could not be fixed by the proposed mechanisms, indicating limitations in the current metabolic models.
Digital Object Identifier (DOI)
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