Direct evidence of amyloid precursor–like protein 1 <i>trans</i> interactions in cell–cell adhesion platforms investigated via fluorescence fluctuation spectroscopy
Bibliographic record
Abstract
The amyloid precursor–like protein 1 (APLP1) is a type I transmembrane protein that plays a role in synaptic adhesion and synaptogenesis. Past investigations indicated that APLP1 is involved in the formation of protein–protein complexes that bridge the junctions between neighboring cells. Nevertheless, APLP1–APLP1 trans interactions have never been directly observed in higher eukaryotic cells. Here, we investigated APLP1 interactions and dynamics directly in living human embryonic kidney cells using fluorescence fluctuation spectroscopy techniques, namely cross-correlation scanning fluorescence correlation spectroscopy and number and brightness analysis. Our results show that APLP1 forms homotypic trans complexes at cell–cell contacts. In the presence of zinc ions, the protein forms macroscopic clusters, exhibiting an even higher degree of trans binding and strongly reduced dynamics. Further evidence from giant plasma membrane vesicles suggests that the presence of an intact cortical cytoskeleton is required for zinc-induced cis multimerization. Subsequently, large adhesion platforms bridging interacting cells are formed through APLP1–APLP1 trans interactions. Taken together, our results provide direct evidence that APLP1 functions as a neuronal zinc-dependent adhesion protein and allow a more detailed understanding of the molecular mechanisms driving the formation of APLP1 adhesion platforms.
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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 | 0.000 |
| 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".