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Now that I have a better understanding of the biological context, let me review the GO-CAM model in detail:

Review of GO-CAM Model: gomodel:5ae3b0f600000435 "Regulation of sprouting angiogenesis via dll4, egfl6, itgb1a (D. rerio)"

Model Overview

This model represents the regulation of sprouting angiogenesis in zebrafish (Danio rerio) through the interactions between three key proteins: dll4, egfl6, and itgb1a. The model focuses on how these proteins regulate the process of sprouting angiogenesis, which is critical for proper blood vessel formation during development.

Model Structure and Biological Accuracy

The model includes four key molecular activities:

  1. EGFL6 (ZFIN:ZDB-GENE-040718-157) has two annotated molecular functions:
  2. Receptor ligand activity (GO:0048018)
  3. Integrin binding (GO:0005178)
  4. Occurs in somite (ZFA:0000155)

  5. Part of positive regulation of cell migration involved in sprouting angiogenesis (GO:0090050)

  6. ITGB1A (ZFIN:ZDB-GENE-060803-2) has:

  7. Signaling receptor activity (GO:0038023)

  8. Occurs in endothelial cell (ZFA:0009065)

  9. DLL4 (ZFIN:ZDB-GENE-041014-73) has:

  10. Notch binding (GO:0005112)

  11. Part of Notch signaling pathway (GO:0007219)

  12. Causal Relationships:

  13. EGFL6 directly positively regulates ITGB1A
  14. EGFL6 has part EGFL6 (representing its integrin binding activity)
  15. ITGB1A directly negatively regulates DLL4

The biological evidence supporting these relationships is based on literature including PMID:27780917 and experimental evidence including mutant phenotype evidence (ECO:0000315).

Compliance with GO-CAM Best Practices

Based on the examination of the model and the GO-CAM best practices, I've identified the following:

Strengths:

  1. Proper use of causal relationships: The model correctly uses RO:0002629 (directly positively regulates) to connect the ligand activity (EGFL6) to its receptor (ITGB1A).

  2. Appropriate evidence codes: The model uses appropriate evidence codes for each assertion, including experimental evidence (ECO:0000315 - mutant phenotype evidence used in manual assertion) and author statements (ECO:0000304).

  3. Cellular context: The model includes information about the cellular localization of the activities (somite for EGFL6 and endothelial cell for ITGB1A).

  4. Biological process context: Each activity is appropriately contextualized with the relevant biological process.

Areas for Improvement:

  1. Missing input relationships: According to the signaling receptor activity annotation guidelines, the receptor (ITGB1A) should have a "has input" relationship to its downstream effector. Currently, there is no specification of what molecular entity ITGB1A has as input.

  2. Regulation pathway completion: While the model shows ITGB1A negatively regulates DLL4, it's not entirely clear how DLL4's Notch binding activity fits into the larger regulatory pathway. Based on the literature, DLL4-Notch signaling plays a critical role in regulating sprouting angiogenesis, but the model doesn't completely capture the downstream effects of DLL4 activity.

  3. Limited information on specific mechanism: The model provides a high-level overview of the regulatory relationships but doesn't fully capture the details of how these activities lead to the regulation of sprouting angiogenesis.

Biological Content Accuracy

From the literature I retrieved, it appears that:

  1. DLL4 is a critical Notch ligand in vascular development that is expressed in tip cells of growing blood vessel sprouts and helps regulate proper angiogenesis.

  2. EGFL6 appears to be functioning as a receptor ligand that positively regulates ITGB1A (integrin beta 1a), which is involved in signaling receptor activity.

  3. The negative regulation of DLL4 by ITGB1A aligns with literature showing complex regulatory networks in sprouting angiogenesis, where integrin signaling can modulate Notch pathway components.

The model appears to be biologically accurate in depicting a pathway where EGFL6 activates ITGB1A signaling, which in turn negatively regulates DLL4-mediated Notch signaling. This regulatory circuit would contribute to the proper control of sprouting angiogenesis during zebrafish development.

Recommendations for Improvement

  1. Add "has input" relationship: Add a "has input" relationship from ITGB1A to its downstream effector to better comply with the signaling receptor activity annotation guidelines.

  2. Complete the regulatory pathway: Consider expanding the model to show the downstream effects of DLL4-Notch binding, possibly including the effects on cxcr4a expression which was highlighted in the literature as an important factor regulated by Notch signaling during angiogenesis.

  3. Add additional biological context: The model could benefit from additional information about how this regulatory circuit fits into the broader process of sprouting angiogenesis and blood vessel formation.

  4. Include cellular details: The literature indicates specific cellular dynamics (tip cells vs. stalk cells) that are important for understanding the spatial regulation of angiogenesis. Including these details would enhance the model's biological accuracy.

Conclusion

The GO-CAM model "Regulation of sprouting angiogenesis via dll4, egfl6, itgb1a (D. rerio)" provides a valuable representation of a key regulatory pathway in sprouting angiogenesis in zebrafish. It accurately captures the basic relationships between EGFL6, ITGB1A, and DLL4, supported by experimental evidence.

While the model largely follows GO-CAM best practices, there are opportunities for enhancement, particularly in specifying the inputs for receptor activities and expanding the model to more fully capture the downstream effects of DLL4-Notch signaling.

The model is biologically sound and supported by literature evidence, depicting a regulatory circuit that contributes to the control of sprouting angiogenesis during zebrafish development.