Class IA Phosphatidylinositol 3-Kinase p110α Regulates Phagosome Maturation
Bibliographic record
Abstract
Of the various phosphatidylinositol 3- kinases (PI3Ks), only the class III enzyme Vps34 has been shown to regulate phagosome maturation. During studies of phagosome maturation in THP-1 cells deficient in class IA PI3K p110α, we discovered that this PI3K isoform is required for vacuole maturation to progress beyond acquisition of Rab7 leading to delivery of lysosomal markers. Bead phagosomes from THP-1 cells acquired p110α and contained PI3P and PI(3,4,5)P3; however, p110α and PI(3,4,5)P3 levels in phagosomes from p110α knockdown cells were decreased. Phagosomes from p110α knock down cells showed normal acquisition of both Rab5 and EEA-1, but were markedly deficient in the lysosomal markers LAMP-1 and LAMP-2, and the lysosomal hydrolase, β-galactosidase. Phagosomes from p110α deficient cells also displayed impaired fusion with Texas Red dextran-loaded lysosomes. Despite lacking lysosomal components, phagosomes from p110α deficient cells recruited normal levels of Rab7, Rab-interacting lysosomal protein (RILP) and homotypic vacuole fusion and protein sorting (HOPs) components Vps41 and Vps16. The latter observations demonstrated that phagosomal Rab7 was active and capable of recruiting effectors involved in membrane fusion. Nevertheless, active Rab7 was not sufficient to bring about the delivery of lysosomal proteins to the maturing vacuole, which is shown for the first time to be dependent on a class I PI3K.
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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 | 0.001 |
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".