Dynamics and Distribution of Klothoβ (KLB) and Fibroblast Growth Factor Receptor-1 (FGFR1) in Living Cells Reveal the Fibroblast Growth Factor-21 (FGF21)-induced Receptor Complex
Bibliographic record
Abstract
FGF21 stimulates FGFR1c activity in cells that co-express Klothoβ (KLB); however, relatively little is known about the interaction of these receptors at the plasma membrane. We measured the dynamics and distribution of fluorescent protein-tagged KLB and FGFR1c in living cells using fluorescence recovery after photobleaching and number and brightness analysis. We confirmed that fluorescent protein-tagged KLB translocates to the plasma membrane and is active when co-expressed with FGFR1c. FGF21-induced signaling was enhanced in cells treated with lactose, a competitive inhibitor of the galectin lattice, suggesting that lattice-binding modulates KLB and/or FGFR1c activity. Fluorescence recovery after photobleaching analysis consistently revealed that lactose treatment increased KLB mobility at the plasma membrane, but did not affect the mobility of FGFR1c. The association of endogenous KLB with the galectin lattice was also confirmed by co-immunoprecipitation with galectin-3. KLB mobility increased when co-expressed with FGFR1c, suggesting that the two receptors form a heterocomplex independent of the galectin lattice. Number and brightness analysis revealed that KLB and FGFR1c behave as monomers and dimers at the plasma membrane, respectively. Co-expression resulted in monomeric expression of KLB and FGFR1c consistent with formation of a 1:1 heterocomplex. Subsequent addition of FGF21 induced FGFR1 dimerization without changing KLB aggregate size, suggesting formation of a 1:2 KLB-FGFR1c signaling complex. Overall, these data suggest that KLB and FGFR1 form a 1:1 heterocomplex independent of the galectin lattice that transitions to a 1:2 complex upon the addition of FGF21.
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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 | 0.001 | 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".