Dephosphorylation of the transcriptional cofactor NACA by the PP1A phosphatase enhances cJUN transcriptional activity and osteoblast differentiation
Bibliographic record
Abstract
The transcriptional cofactor nascent polypeptide-associated complex and co-regulator α (NACA) regulates osteoblast maturation and activity. NACA functions, at least in part, by binding to Jun proto-oncogene, AP-1 transcription factor subunit (cJUN) and potentiating the transactivation of AP-1 targets such as osteocalcin ( Bglap ) and matrix metallopeptidase 9 ( Mmp9 ). NACA activity is modulated by phosphorylation carried out by several kinases, but a phosphatase regulating NACA's activity remains to be identified. Here, we used affinity purification with MS in HEK293T cells to isolate NACA complexes and identified protein phosphatase 1 catalytic subunit α (PP1A) as a NACA-associated Ser/Thr phosphatase. NACA interacted with multiple components of the PP1A holoenzyme complex: the PPP1CA catalytic subunit and the regulatory subunits PPP1R9B, PPP1R12A and PPP1R18. MS analysis revealed that NACA co-expression with PPP1CA causes dephosphorylation of NACA at Thr-89, Ser-151, and Thr-174. NACA Ser/Thr-to-alanine variants displayed increased nuclear localization, and NACA dephosphorylation was associated with specific recruitment of novel NACA interactants, such as basic transcription factor 3 (BTF3) and its homolog BTF3L4. NACA and PP1A cooperatively potentiated cJUN transcriptional activity of the AP-1–responsive MMP9 -luciferase reporter, which was abolished when Thr-89, Ser-151, or Thr-174 were substituted with phosphomimetic aspartate residues. We confirmed the NACA–PP1A interaction in MC3T3-E1 osteoblastic cells and observed that NACA phosphorylation status at PP1A-sensitive sites is important for the regulation of AP-1 pathway genes and for osteogenic differentiation and matrix mineralization. These results suggest that PP1A dephosphorylates NACA at specific residues, impacting cJUN transcriptional activity and osteoblast differentiation and function.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".