Monocyte lipid rafts contain proteins implicated in vesicular trafficking and phagosome formation
Bibliographic record
Abstract
Lipid rafts are membrane microdomains of unique lipid composition that segregate proteins with poorly understood consequences for membrane organization. Identification of raft associated proteins could therefore provide novel insight into raft-dependent functions. Monocytes process antigens for presentation to T cells by ingesting pathogens into calcium-dependent plasma membrane invaginations called "phagosomes" which develop by sequential fusion with the endoplasmic reticulum, early and late endosomes. We investigated the protein composition of Triton X-100 insoluble low density membranes of the monocyte cell-line THP-1 by matrix-assisted laser desorption/ionization-time of flight and tandem mass spectrometry. The ganglioside GM1 colocalized on the plasma membrane with the raft markers flotillin 1 and 2, which were enriched in low buoyant density fractions containing 52 identifiable proteins, 28 of which have not been reported in rafts, and nine of which are associated with the endoplasmic reticulum (ER). Remarkably, 27 of the 52 proteins are components of phagosomes, including the ER protein calnexin which we demonstrate is phosphorylated on serine 562, a switch controlling calcium homeostasis. The presence of the early and late endosome trafficking proteins Rab-1, and Rab-7 together with the late endosome protein LIMPII, indicate lipid rafts are present throughout endosome maturation. Identification of vacuolar ATP synthase, and synaptosomal-associated protein-23, proteins implicated in membrane fusion, together with the cytoskeletal proteins actin, alpha-actinin, and vimentin, and Rac 1, 2, and 3, regulators of cytoskeletal assembly, indicate monocyte lipid rafts contain the machinery to direct vesicular fusion and actin based vesicular migration throughout phagosome development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".