Requirement and Redundancy of the Src Family Kinases Fyn and Lyn in Perforin-Dependent Killing of Cryptococcus neoformans by NK Cells
Bibliographic record
Abstract
Natural killer (NK) cells directly recognize and kill fungi, such as the pathogenic fungus Cryptococcus neoformans, via cytolytic mechanisms. However, the precise signaling pathways governing this NK cell microbicidal activity and the implications for fungal recognition are still unknown. Previously, it was reported that NK cell anticryptococcal activity is mediated through a conserved phosphatidylinositol 3-kinase-extracellular signal-regulated kinase 1/2 (PI3K-ERK1/2) pathway. Using YT (a human NK-like cell line) and primary human NK cells, we sought to identify the upstream, receptor-proximal signaling elements that led to fungal cytolysis. We demonstrate that Src family kinases were activated in response to C. neoformans. Furthermore, pharmacologic inhibition with an Src kinase inhibitor blocked C. neoformans-induced downstream activation of PI3K and ERK1/2 and abrogated cryptococcal killing. At the same time, the inhibitor disrupted the polarization of perforin-containing granules toward the NK cell-cryptococcal synapse but had no effect on conjugate formation between the organism and the NK cell. Finally, small interfering RNA (siRNA) double (but not single) knockdown of two Src family kinases, Fyn and Lyn, blocked cryptococcal killing. Together these data demonstrate a mechanism whereby the Src family kinases, Fyn and Lyn, redundantly mediate anticryptococcal activity through the activation of PI3K and ERK1/2, which in turn facilitates killing by inducing the polarization of perforin-containing granules to the NK cell-cryptococcal synapse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".