Phosphatidylinositol 4-kinase III beta regulates cell shape, migration, and focal adhesion number
Bibliographic record
Abstract
Cell shape is regulated by cell adhesion and cytoskeletal and membrane dynamics. Cell shape, adhesion, and motility have a complex relationship and understanding them is important in understanding developmental patterning and embryogenesis. Here we show that the lipid kinase phosphatidylinositol 4-kinase III beta (PI4KIIIβ) regulates cell shape, migration, and focal adhesion (FA) number. PI4KIIIβ generates phosphatidylinositol 4-phosphate (PI4P) from phosphatidylinositol and is highly expressed in a subset of human breast cancers. PI4KIIIβ and the PI4P it generates regulate a variety of cellular functions, ranging from control of Golgi structure, fly fertility, and Akt signaling. Here, we show that loss of PI4KIIIβ expression decreases cell migration and alters cell shape in NIH3T3 fibroblasts. The changes are accompanied by an increase in the number of FA in cells lacking PI4KIIIβ. Furthermore, we find that PI4P-containing vesicles move to the migratory leading edge during migration and that some of these vesicles tether to and fuse with FA. Fusion is associated with FA disassembly. This suggests a novel regulatory role for PI4KIIIβ and PI4P in cell adhesion and cell shape maintenance.
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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 | 0.001 | 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".