Rapid and Direct Transport of Cell Surface APP to the Lysosome defines a novel selective pathway
Bibliographic record
Abstract
BACKGROUND: A central feature of Alzheimer's disease is the cleavage of the amyloid precursor protein (APP) to form beta-amyloid peptide (Abeta) by the beta-secretase and gamma-secretase enzymes. Although this has been shown to occur after endocytosis of APP from the cell surface, the exact compartments of APP processing are not well defined. We have previously demonstrated that APP and gamma-secretase proteins and activity are highly enriched in purified rat liver lysosomes. In order to examine the lysosomal distribution and trafficking of APP in cultured cells, we generated constructs containing APP fused to a C-terminal fluorescent protein tag and N-terminal HA-epitope tag. These were co-transfected with a panel of fluorescent-protein tagged compartment markers. RESULTS: Here we demonstrate using laser-scanning confocal microscopy that although APP is present throughout the endosomal/lysosomal system in transfected Cos7 and neuronal SN56 cell lines as well as in immunostained cultured mouse neurons, it is enriched in the lysosome. We also show that the Swedish and London mutations reduce the amount of APP in the lysosome. Surprisingly, in addition to its expected trafficking from the cell surface to the early and then late endosomes, we find that cell-surface labelled APP is transported rapidly and directly from the cell surface to lysosomes in both Cos7 and SN56 cells. This rapid transit to the lysosome is blocked by the presence of either the London or Swedish mutations. CONCLUSIONS: These results demonstrate the presence of a novel, rapid and specific transport pathway from the cell surface to the lysosomes. This suggests that regulation of lysosomal traffic could regulate APP processing and that the lysosome could play a central role in the pathophysiology of Alzheimer's disease.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".