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YeastPathways GLUCONEO PWY 1 gluconeogenesis I imported from Saccharomyces Genome Database

Now, let me review the Yeast Gluconeogenesis GO-CAM model (gomodel:YeastPathways_GLUCONEO-PWY-1) based on the available information. Here's my evaluation:

GO-CAM Model Review: Yeast Gluconeogenesis Pathway (gomodel:YeastPathways_GLUCONEO-PWY-1)

General Model Information

  • Title: "gluconeogenesis I - imported from: Saccharomyces Genome Database"
  • Taxon: NCBITaxon:559292 (Saccharomyces cerevisiae S288C)
  • Status: Production
  • Source: Imported from Saccharomyces Genome Database (SGD)

Model Structure Assessment

Strengths:

  1. Comprehensive Pathway Coverage: The model represents the entire gluconeogenesis pathway with 16 activity nodes, covering all major enzymatic steps from pyruvate to glucose-6-phosphate.

  2. Proper Cellular Compartmentalization: Activities are correctly localized, with most occurring in the cytosol (GO:0005829) and some in mitochondria (GO:0005739) where appropriate.

  3. Complete Information for Reactions: Each enzyme activity includes appropriate inputs (substrates) and outputs (products), with all molecular entities properly identified with ChEBI terms.

  4. Process Annotation: All activities are correctly annotated as part of the gluconeogenesis process (GO:0006094).

  5. Gene Product Specificity: Each activity is enabled by specific yeast gene products with SGD identifiers.

Issues and Recommendations:

  1. Limited Causal Connectivity:
  2. Issue: Most enzymatic steps lack causal relationships (RO:0002413 "provides input for") connecting them in the proper sequence. Only a few activities have causal connections.

  3. Recommendation: Add causal relationships between all sequential steps to properly represent the flow of the pathway from pyruvate to glucose-6-phosphate.

  4. Redundant Activity Representations:

  5. Issue: Several enzymes are represented multiple times with identical functions (e.g., three instances of GAPOXNPHOSPHN-RXN for glyceraldehyde-3-phosphate dehydrogenase with different gene products).

  6. Recommendation: Consider using protein complexes where appropriate or at least link the redundant activities to show they catalyze the same step.

  7. Inconsistent Evidence Documentation:

  8. Issue: All evidence is cited as ECO:0000313 (imported information) without specific literature references beyond the SGD pathway.

  9. Recommendation: Add primary literature citations where possible to strengthen the evidence basis.

  10. Mitochondrial Malate Dehydrogenase Connectivity:

  11. Issue: There are two representations of L-malate dehydrogenase (NAD+) activity (MAE1 - both in the mitochondrion), but their connectivity to the rest of the pathway isn't fully established.

  12. Recommendation: Clarify the role of mitochondrial activities in the pathway by adding appropriate transporters and causal relationships.

  13. Missing Regulatory Information:

  14. Issue: The model lacks any regulatory information about the pathway.
  15. Recommendation: Consider adding key regulatory influences on gluconeogenesis, such as inhibition by insulin signaling or activation during fasting states.

Comparison with Mouse Gluconeogenesis Model

The mouse model (gomodel:61e0e55600001225) has several features that could enhance the yeast model:

  1. Complete Causal Connectivity: The mouse model fully connects all activities with causal relationships, clearly showing the pathway flow.

  2. Transport Mechanisms: The mouse model includes transport mechanisms between compartments (e.g., malate transport across mitochondrial membrane).

  3. Stronger Evidence Base: The mouse model includes diverse evidence codes with specific PMID references for each activity.

Overall Assessment

The Yeast Gluconeogenesis GO-CAM model is scientifically accurate in terms of the enzymes, substrates, products, and cellular locations. It provides a good representation of the pathway components but falls short in representing the pathway structure and flow. The model would benefit significantly from adding causal connections between the enzymatic steps to properly represent the sequential nature of gluconeogenesis.

The model appears to be an automated import from SGD rather than a manually curated model, which explains some of its limitations. For it to be maximally useful, manual curation to add causal relationships and consolidate redundant activities would greatly enhance its utility as a knowledge representation.