Diacylglycerol Kinases Terminate Diacylglycerol Signaling during the Respiratory Burst Leading to Heterogeneous Phagosomal NADPH Oxidase Activation
Bibliographic record
Abstract
It is commonly assumed that all phagosomes have identical molecular composition. This assumption has remained largely unchallenged due to a paucity of methods to distinguish individual phagosomes. We devised an assay that extends the utility of nitro blue tetrazolium for detection and quantification of NAPDH oxidase (NOX) activity in individual phagosomes. Implementation of this assay revealed that in murine macrophages there is heterogeneity in the ability of individual phagosomes to generate superoxide, both between and within cells. To elucidate the molecular basis of the variability in NOX activation, we employed genetically encoded fluorescent biosensors to evaluate the uniformity in the distribution of phospholipid mediators of the oxidative response. Despite variability in superoxide generation, the distribution of phosphatidylinositol 3,4,5-trisphosphate, phosphatidylinositol 3-phosphate, and phosphatidic acid was nearly identical in all phagosomes. In contrast, diacylglycerol (DAG) was not generated uniformly across the phagosomal population, varying in a manner that directly mirrored superoxide production. Modulation of DAG levels suggested that NOX activation is precluded when phagosomes fail to reach a critical DAG concentration. In particular, forced expression of diacylglycerol kinase β abrogated DAG accumulation at the phagosome, leading to impaired respiratory burst. Conversely, pharmacological inhibition of DAG kinases or expression of an inactive diacylglycerol kinase β mutant increased the proportion of DAG-positive phagosomes, concomitantly potentiating phagosomal NOX activity. Our data suggest that diacylglycerol kinases limit the extent of NADPH oxidase activation, curtailing the production of potentially harmful reactive oxygen species. The resulting heterogeneity in phagosome responsiveness could enable the survival of a fraction of invading microorganisms. Background: Cell population-based studies obscure potential phagosomal heterogeneity. Results: We used a dynamic assay to monitor superoxide production in single phagosomes and uncovered variability in NADPH oxidase activity. Conclusion: The heterogeneity is attributable to variations in local DAG accumulation, which is controlled by DAG kinases. Significance: Heterogeneity in phagosome responsiveness could enable the survival of a fraction of invading microorganisms.
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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 | 0.001 |
| 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".