O3–07–05: Arf6 controls rapid lysosomal transport of cell surface APP and beta‐amyloid production by macropinocytosis
Bibliographic record
Abstract
Many experiments show that beta-amyloid peptides are generated by the cleavage of the Amyloid Precursor Protein (APP) after internalization from the cell surface. The rapid production of beta-amyloid from cell surface APP has led many to believe that endosomes are the responsible compartment but this has never been directly demonstrated. Work in our laboratory has demonstrated that APP and gamma secretase proteins and activity are enriched in the lysosome, suggesting that this compartment might participate in beta-amyloid production. Furthermore we have recently identified a novel pathway that is able to transport APP directly from the cell surface to the lysosome, suggesting a new pathway for beta-amyloid production. To characterize lysosomal APP trafficking from the cell surface, we generated constructs with an N-terminal (extracellular) HA epitope tag. Early endosomes and lysosomes were identified using fluorescent protein-tagged rab5 and LAMP1. We then transfected SN56 cells with these constructs and surface labeled the cells with a fluorescent (or gold) labeled anti-HA antibody. Internalization was then followed using laser scanning confocal microscopy and electron microscopy. To characterize this pathway, we screened a panel of fluorescently-tagged dominant negative regulatory proteins. Beta-amyloid production was quantitated by ELISA. Arf6 expression in the hippocampus of normal and AD individuals was examined by immunohistochemistry. Here, we demonstrate that APP is transported to lysosomes within minutes by way of large (>500nm) structures that are too large to be clathrin coated vesicles. By electon microscopy, these are large clear vesicles characteristic of macropinosomes. This process is inhibited by dominant negative mutations in Arf6, as well as Arf6 Knockdown by siRNA. We also find that Arf6 is expressed in in the hippocampal CA1 region of AD and control tissues, but spreads throughout the hippocampus (including CA3 and 4 regions) in individuals with AD. Arf6 dominant negative constructs markedly reduce beta-amyloid production. These experiments demonstrate that Arf6 controls macropinocytosis of cell surface APP to lysosomes and beta-amyloid production. Therefore Arf6 may be a therapeutic target in AD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".