Quantitative analysis of phagolysosome fusion in intact cells: inhibition by mycobacterial lipoarabinomannan and rescue by an 1α,25-dihydroxyvitamin D3–phosphoinositide 3-kinase pathway
Bibliographic record
Abstract
Macrophage cell membranes were labeled with PKH26 and subsequently incubated with latex beads to generate phagosomes surrounded by a red-fluorescent membrane suitable for flow cytometry. Following cell disruption and partial purification of phagosomes, these vesicles were readily distinguished from both cell debris and free beads released from disrupted vacuoles. Flow cytometry analysis of phagosomes stained with specific mAbs and FITC-labeled secondary antibodies showed progressive acquisition of both Rab7 and LAMP-1 consistent with movement along the endocytic pathway. Alternatively, macrophages were preloaded with the lysosomal tracer FITC-dextran before membrane labeling with PKH and incubation with latex beads. Phagosome-lysosome fusion was then quantified on the basis of the colocalization of red and green signals. Using these flow cytometry-based systems, we showed that co-internalization of beads with lysates of Mycobacterium tuberculosis, but not lysates from the nonpathogenic organism Mycobacterium smegmatis, markedly decreased phagosome acquisition of Rab7 and LAMP-1 and vesicle fusion with FITC-dextran-loaded lysosomes. Inhibition of phagolysosome fusion could be attributed, at least in part, to the mycobacterial cell wall glycolipid lipoarabinomannan, and further analysis showed complete rescue of phagosome maturation when cells were pretreated with vitamin D3 before exposure to lipoarabinomannan. Moreover, the ability of vitamin D3 to reverse the phenotype of phagosomes in the presence of the glycolipid was completely abrogated by LY-294002, suggesting that vitamin D3 promotes phagolysosome fusion via a phosphoinositide 3-kinase signaling pathway. These findings establish a robust platform technology based on labeling of phagocyte cell membranes and flow cytometry capable of supporting broad-based screens to identify microbial and other bioactive compounds that influence phagosome biology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".