WNT-induced association of Frizzled and LRP6 is not sufficient for the initiation of WNT/β-catenin signaling
Bibliographic record
Abstract
Abstract The Wingless/Int-1 (WNT) signaling network is essential to orchestrate central physiological processes such as embryonic development and tissue homeostasis. In the currently held tenet, WNT/β-catenin signaling is initiated by WNT-induced recruitment of Frizzleds (FZDs) and LRP5/6 followed by the formation of a multiprotein signalosome complex. Here, we use bioluminescence resonance energy transfer (BRET) to show that different WNT paralogs dynamically trigger FZD-LRP6 association. While WNT-induced receptor interaction was independent of C-terminal LRP6 phosphorylation, it was allosterically modulated by binding of the phosphoprotein Dishevelled (DVL) to FZD. WNT-16B emerged as a ligand of particular interest, as it efficiently promoted FZD-LRP6 association but, unlike WNT-3A, did not lead to WNT/β-catenin signaling. Transcriptomic analysis further revealed distinct transcriptional fingerprints of WNT-3A and WNT-16B stimulation in HEK293 cells. Additionally, single-molecule tracking demonstrated that, despite increasing FZD 5 and LRP6 confinement, WNT-16B stimulation did not result in formation of higher-order receptor clusters, in contrast to WNT-3A. Our results suggest that FZD-WNT-LRP5/6 complex formation alone is not sufficient for the initiation of WNT/β-catenin signaling. Instead, we propose a two-step model, where initial ligand-induced FZD-LRP6 association must be followed by receptor clustering into higher-order complexes and subsequent phosphorylation of LRP6 for efficient activation of WNT/β-catenin signaling.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".