The R740S mutation in the V-ATPase a3 subunit increases lysosomal pH, impairs NFATc1 translocation, and decreases in vitro osteoclastogenesis
Bibliographic record
Abstract
Vacuolar H(+) -ATPase (V-ATPase), a multisubunit enzyme located at the ruffled border and in lysosomes of osteoclasts, is necessary for bone resorption. We previously showed that heterozygous mice with an R740S mutation in the a3 subunit of V-ATPase (+/R740S) have mild osteopetrosis resulting from an ∼90% reduction in proton translocation across osteoclast membranes. Here we show that lysosomal pH is also higher in +/R740S compared with wild-type (+/+) osteoclasts. Both osteoclast number and size were decreased in cultures of +/R740S compared with +/+ bone marrow cells, with concomitant decreased expression of key osteoclast markers (TRAP, cathepsin K, OSCAR, DC-STAMP, and NFATc1), suggesting that low lysosomal pH plays an important role in osteoclastogenesis. To elucidate the molecular mechanism of this inhibition, NFATc1 activation was assessed. NFATc1 nuclear translocation was significantly reduced in +/R740S compared with +/+ cells; however, this was not because of impaired enzymatic activity of calcineurin, the phosphatase responsible for NFATc1 dephosphorylation. Protein and RNA expression levels of regulator of calcineurin 1 (RCAN1), an endogenous inhibitor of NFATc1 activation and a protein degraded in lysosomes, were not significantly different between +/R740S and +/+ osteoclasts, but the RCAN1/NFATc1 ratio was significantly higher in +/R740S versus +/+ cells. The lysosomal inhibitor chloroquine significantly increased RCAN1 accumulation in +/+ cells, consistent with the hypothesis that higher lysosomal pH impairs RCAN1 degradation, leading to a higher RCAN1/NFATc1 ratio and consequently NFATc1 inhibition. Our data indicate that increased lysosomal pH in osteoclasts leads to decreased NFATc1 signaling and nuclear translocation, resulting in a cell autonomous impairment of osteoclastogenesis in vitro.
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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) | 0.002 | 0.001 |
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".