Rab GTPase Mediated Procollagen Trafficking in Ascorbic Acid Stimulated Osteoblasts
Bibliographic record
Abstract
Despite advances in investigating functional aspects of osteoblast (OB) differentiation, especially studies on how bone proteins are deposited and mineralized, there has been little research on the intracellular trafficking of bone proteins during OB differentiation. Collagen synthesis and secretion is the major function of OBs and is markedly up-regulated upon ascorbic acid (AA) stimulation, significantly more so than in fibroblast cells. Understanding the mechanism by which collagen is mobilized in specialized OB cells is important for both basic cell biology and diseases involving defects in bone protein secretion and deposition. Protein trafficking along the exocytic and endocytic pathways is aided by many molecules, with Rab GTPases being master regulators of vesicle targeting. In this study, we used microarray analysis to identify the Rab GTPases that are up-regulated during a 5-day AA differentiation of OBs, namely Rab1, Rab3d, and Rab27b. Further, we investigated the role of identified Rabs in regulating the trafficking of collagen from the site of synthesis in the ER to the Golgi and ultimately to the plasma membrane utilizing Rab dominant negative (DN) expression. We also observed that experimental halting of biosynthetic trafficking by these mutant Rabs initiated proteasome-mediated degradation of procollagen and ceased global protein translation. Acute expression of Rab1 and Rab3d DN constructs partially alleviated this negative feedback mechanism and resulted in impaired ER to Golgi trafficking of procollagen. Similar expression of Rab27b DN constructs resulted in dispersed collagen vesicles which may represent failed secretory vesicles sequestered in the cytosol. A significant and strong reduction in extracellular collagen levels was also observed implicating the functional importance of Rab1, Rab3d and Rab27b in these major collagen-producing cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".