Quantitative phosphoproteomics reveals that nestin is a downstream target of dual leucine zipper kinase during retinoic acid-induced neuronal differentiation of Neuro-2a cells
Bibliographic record
Abstract
BACKGROUND: Dual leucine zipper kinase (DLK) is critical for neurite outgrowth in the developing nervous system and during nerve regeneration, but the underlying mechanisms remain largely unknown. To address this issue, we generated stable shRNA-mediated DLK-depleted Neuro-2a cell lines and analyzed their phosphoproteome after induction of neuronal differentiation by retinoic acid (RA). RESULTS: Here, we report the identification of 32 phosphopeptides that exhibited significant differences in relative abundance between control and DLK-depleted cells. Two of the most downregulated phosphopeptides identified after DLK depletion were derived from nestin, a type VI intermediate filament (IF) protein typically expressed in neural progenitor cells. The reduced abundance of these phosphopeptides in response to DLK knockdown was validated using parallel reaction monitoring (PRM)-based quantitative proteomics and paired with a concomitant reduction in nestin mRNA and protein expression, indicating that the decrease in nestin phosphorylation was due to a decrease in total nestin in DLK-depleted cells compared to control cells. This DLK-mediated regulation of nestin expression had no apparent effect on neurite formation because nestin knockdown alone was not sufficient to impair RA-induced neurite extension in parental Neuro-2a cells, and nestin overexpression failed to rescue the neurite outgrowth defect observed in DLK-depleted Neuro-2a cells. CONCLUSIONS: Together, these results demonstrate that nestin is a novel downstream target of DLK signaling but not a mediator of its ability to promote neurite outgrowth during neuronal differentiation.
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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".