Neuronal calcium sensor 1 and phosphatidylinositol 4-OH kinase βinteract in neuronal cells and are translocated to membranes during nucleotide-evoked exocytosis
Bibliographic record
Abstract
Neuronal calcium sensor 1 (NCS-1) belongs to a family of EF-hand calcium-binding proteins and is mainly expressed in neurons and neuroendocrine cells, where it causes facilitation of neurotransmitter release through unknown mechanisms. The yeast homologue of NCS-1 has been demonstrated to interact with and regulate the activity of yeast phosphatidylinositol 4-OH kinase beta (PI4Kbeta). However, in neurons and neurosecretory cells NCS-1 has not unequivocally been shown to interact with PI4Kbeta. Here we have compared the subcellular distribution of NCS-1 and PI4Kbeta and investigated whether they are capable of forming complexes. In neurons, both proteins are widely distributed and are present in perikarya and, to a lesser extent, in nerve terminals. A consistent portion of NCS-1 and PIK4beta is cytosolic, whereas a portion of both proteins appears to be associated with the membranes of the endoplasmic reticulum and the Golgi complex. Very small amounts of NCS-1 and PI4Kbeta are present in synaptic vesicles. Our results further demonstrate that in neurosecretory cells, endogenous NCS-1 and PIK4beta interact to form a complex that can be immunoisolated from membrane as well as from cytosolic fractions. Moreover, both proteins can be recruited to membranes when cells are treated with nucleotide receptor agonists known to increase polyphosphoinositide turnover and concomitantly induce exocytosis of secretory vesicles. Finally, in PC12 cells overexpressing NCS-1, the amount of PI4Kbeta associated with the membranes is increased concomitantly with the increased levels of NCS-1 detected in the same membrane fractions. Together, these findings demonstrate that mammalian NCS-1 and PI4Kbeta interact under physiological conditions, which suggest a possible role for NCS-1 in the translocation of PI4Kbeta to target membranes.
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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) | 0.002 | 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".