The Mixed Lineage Kinase DLK Is Oligomerized by Tissue Transglutaminase during Apoptosis
Bibliographic record
Abstract
Current evidence suggests that the mixed lineage kinase family member dual leucine zipper-bearing kinase (DLK) might play a significant role in the regulation of cell growth and differentiation, particularly during the process of tissue remodeling. To further explore this working model, we have investigated the regulation of host and recombinant DLK in NIH3T3 and COS-1 cells undergoing apoptosis. Using calphostin C, a potent and selective inhibitor of protein kinase C and a recognized apoptosis inducer for various cell types, we demonstrate, by immunoblot analysis, that DLK protein levels are rapidly and dramatically down-regulated during the early phases of apoptosis. Down-regulation in calphostin C-treated cells was also accompanied by the appearance of SDS- and mercaptoethanol-resistant high molecular weight DLK immunoreactive oligomers. Experiments aimed at elucidating the mechanism(s) underlying DLK oligomerization revealed that the tissue transglutaminase (tTG) inhibitor monodansylcadaverine antagonized the effects of calphostin C almost completely, thereby suggesting the involvement of a tTG-catalyzed reaction as the root cause of DLK down-regulation and accumulation as high molecular weight species. In support of this notion, we also show that DLK can serve as a substrate for tTG-dependent cross-linking in vitro and that this covalent post-translational modification leads to the functional inactivation of DLK. Taken together, these observations suggest that transglutamination and oligomerization may constitute a relevant physiological mechanism for the regulation of DLK activity.
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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".