Plasma Membrane Factor XIIIA Transglutaminase Activity Regulates Osteoblast Matrix Secretion and Deposition by Affecting Microtubule Dynamics
Bibliographic record
Abstract
Transglutaminase activity, arising potentially from transglutaminase 2 (TG2) and Factor XIIIA (FXIIIA), has been linked to osteoblast differentiation where it is required for type I collagen and fibronectin matrix deposition. In this study we have used an irreversible TG-inhibitor to 'block -and-track' enzyme(s) targeted during osteoblast differentiation. We show that the irreversible TG-inhibitor is highly potent in inhibiting osteoblast differentiation and mineralization and reduces secretion of both fibronectin and type I collagen and their release from the cell surface. Tracking of the dansyl probe by Western blotting and immunofluorescence microscopy demonstrated that the inhibitor targets plasma membrane-associated FXIIIA. TG2 appears not to contribute to crosslinking activity on the osteoblast surface. Inhibition of FXIIIA with NC9 resulted in defective secretory vesicle delivery to the plasma membrane which was attributable to a disorganized microtubule network and decreased microtubule association with the plasma membrane. NC9 inhibition of FXIIIA resulted in destabilization of microtubules as assessed by cellular Glu-tubulin levels. Furthermore, NC9 blocked modification of Glu-tubulin into 150 kDa high-molecular weight Glu-tubulin form which was specifically localized to the plasma membrane. FXIIIA enzyme and its crosslinking activity were colocalized with plasma membrane-associated tubulin, and thus, it appears that FXIIIA crosslinking activity is directed towards stabilizing the interaction of microtubules with the plasma membrane. Our work provides the first mechanistic cues as to how transglutaminase activity could affect protein secretion and matrix deposition in osteoblasts and suggests a novel function for plasma membrane FXIIIA in microtubule dynamics.
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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) | 0.001 | 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".