Skip to content

Now that I have a good understanding of the model and the relevant proteins, let me review the GO-CAM model gomodel:63a86a8600001202 in detail.

Review of GO-CAM Model 63a86a8600001202

Model Information

  • ID: gomodel:63a86a8600001202
  • Title: DHX16-mediated viral RNA recognition and activation of RIGI (Human)
  • Taxon: Human (NCBITaxon:9606)
  • Status: Production

Overview

This GO-CAM model represents the pathway by which DHX16 (a DEAH-box RNA helicase) recognizes viral RNA and cooperates with RIGI (RIG-I, an innate immune receptor) to trigger antiviral immunity responses. The model depicts a signaling cascade with specific molecular functions and causal relationships.

Molecular Activities and Connections

The model includes 5 primary molecular activities across 3 proteins:

  1. DHX16 (UniProtKB:O60231) has three activities:
  2. Pattern recognition receptor activity (GO:0038187)
  3. Ubiquitin binding (GO:0043130)

  4. Molecular adaptor activity (GO:0060090)

  5. RIGI (UniProtKB:O95786) has one activity:

  6. Pattern recognition receptor activity (GO:0038187)

  7. TRIM6 (UniProtKB:Q9C030) has one activity:

  8. Ubiquitin protein ligase activity (GO:0061630)

The causal connections in the model form a pathway where: - DHX16's pattern recognition receptor activity positively regulates its ubiquitin binding - DHX16's ubiquitin binding positively regulates its molecular adaptor activity - DHX16's molecular adaptor activity positively regulates RIGI's pattern recognition receptor activity - TRIM6's ubiquitin protein ligase activity positively regulates DHX16's ubiquitin binding

Cellular Context

All activities in the model occur in the cytoplasm (GO:0005737) and are part of the antiviral innate immune response (GO:0140374).

Evidence Assessment

All the molecular functions and causal connections are supported by evidence from PMID:35263596, which is a well-conducted study published in Cell Reports in 2022. The annotations have proper evidence codes (ECO:0000314 - direct assay evidence used in manual assertion).

Scientific Accuracy

The model accurately captures the findings from the primary research paper:

  1. DHX16 acts as a pattern recognition receptor by detecting specific viral RNA patterns
  2. TRIM6 creates unanchored K48-linked polyubiquitin chains
  3. DHX16 binds these unanchored polyubiquitin chains
  4. The ubiquitin-bound DHX16 acts as a molecular adaptor to enhance RIG-I-dependent innate immune signaling
  5. This cascade leads to an effective antiviral innate immune response

The paper demonstrated that DHX16's RNA helicase motif III is critical for direct interaction with specific viral RNAs, particularly those containing splicing signals from Influenza virus and SARS-CoV-2.

GO-CAM Best Practices Assessment

  1. Molecular Function Representation:
  2. The model correctly uses enabling verbs ("enabled by") to connect gene products to molecular functions

  3. The model accurately represents roles of each protein based on evidence

  4. Causal Relationships:

  5. The model uses appropriate causal predicates ("directly positively regulates") to connect activities

  6. The directional flow is logical and matches the biology

  7. Contexts:

  8. Cellular context (cytoplasm) and biological process (antiviral innate immune response) are appropriately assigned

  9. Molecular Adaptor Representation:

  10. The model appropriately annotates DHX16 with molecular adaptor activity (GO:0060090)

  11. This follows the guidelines from the "Molecular adaptor activity" document

  12. Complex Representation:

  13. The model doesn't explicitly represent complexes but instead focuses on the causal cascade
  14. This is appropriate as the molecular activities are assigned to individual proteins

Strengths

  1. The model accurately captures the novel viral RNA sensing pathway discovered in the paper.
  2. The causal relationships between DHX16, TRIM6, and RIG-I are clearly represented.
  3. Each molecular function is accurately assigned to the correct protein.
  4. The model includes appropriate biological process and cellular location contexts.
  5. All connections are supported by published experimental evidence.

Areas for Improvement

While the model is generally well constructed, there are a few minor points that could be considered for refinement:

  1. Additional Context: The model could potentially benefit from including more specific viral contexts, such as noting which viral RNAs DHX16 specifically recognizes (e.g., influenza segments 7 and 8, SARS-CoV-2 ORF1a).

  2. Molecular Details: The specific K48-linked polyubiquitin chains created by TRIM6 could be more explicitly represented, perhaps by including additional ontology terms or annotations that indicate the K48-linkage specificity.

  3. RIG-I Downstream Activity: The model focuses on the activation of RIG-I but doesn't extend to RIG-I's downstream effects. Considering that RIG-I activation leads to the activation of IRF3/IRF7 and IFN-β production, extending the model to include these downstream steps could provide a more complete picture of the pathway.

Conclusion

The GO-CAM model gomodel:63a86a8600001202 accurately represents the DHX16-mediated viral RNA recognition and RIG-I activation pathway as described in the research. It adheres to GO-CAM best practices and provides a clear representation of the causal relationships between molecular functions. The model effectively captures a novel mechanism of innate immune signaling in which DHX16 acts as both a pattern recognition receptor and a molecular adaptor to enhance RIG-I-mediated antiviral responses.

The model is well-supported by experimental evidence and represents an important contribution to our understanding of antiviral innate immune responses. With a few potential minor refinements, it serves as an excellent example of how GO-CAM can be used to represent complex biological pathways.