The Role of PIKfyve in the Neutrophil Innate Immune Response
Bibliographic record
Abstract
Phosphoinositides are lipid signals that help control leukocyte function including phagocytosis, phagosome maturation and chemotaxis. For example, phosphatidylinositol‐3,5‐bisphosphate (PtdIns(3,5)P2), a lysosomal phosphoinositide, was recently shown to control phagosome maturation in macrophages. Here, we investigated the role of PtdIns(3,5)P2 in neutrophils. Neutrophils are the most abundant leukocyte and the first leukocyte involved in cell‐mediated immunity because of their proficiency in chemotaxis. Once at a site of infection, neutrophils release bactericidal molecules by degranulation, production of reactive oxygen species and phagocytosis of pathogens. Here, we pre‐treated neutrophils with apilimod, an inhibitor of PIKfyve, the kinase that synthesizes PtdIns(3,5)P2 and examined the effects on neutrophils. Overall, we observed that PIKfyve loss of function was highly detrimental to neutrophils. First, apilimod‐treated neutrophils led to lysosome‐vacuoation but not granule‐vacuolation. Second, PIKfyve inhibited cells showed reduced cell velocity and directionality towards an fMLP‐gradient. Third, apilimod treated cells showed an ~80% decrease in its phagocytosis of bacteria and a 75% decrease in phagosomes stained for lysosome markers. Lastly, neutrophils treated with apilimod showed a ~50% decrease in the production of superoxide, a reactive oxygen species produced by respiratory burst to kill bacteria. Currently, we are testing whether PIKfyve activity is necessary for activation of the Rac GTPase, which is essential for the above neutrophil functions. Indeed, preliminary results show that PIKfyve inhibited cells have reduced levels of Rac‐GTP bound.
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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 | 0.001 |
| 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".