Pre-B cell colony enhancing factor induces Nampt-dependent translocation of the insulin receptor out of lipid microdomains in A549 lung epithelial cells
Bibliographic record
Abstract
Pre-B cell colony-enhancing factor (PBEF) is a highly conserved pleiotropic protein reported to be an alternate ligand for the insulin receptor (IR). We sought to clarify the relationship between PBEF and insulin signaling by evaluating the effects of PBEF on the localization of the IRβ chain to lipid rafts in A549 epithelial cells. We isolated lipid rafts from A549 cells and detected the IR by immunoprecipitation from raft fractions or whole cell lysates. Cells were treated with rPBEF, its enzymatic product nicotinamide adenine dinucleotide (NAD), or the Nampt inhibitor daporinad to study the effect of PBEF on IRβ movement. We used coimmunoprecipitation studies in cells transfected with PBEF and IRβ constructs to detect interactions between PBEF, the IRβ, and caveolin-1 (Cav-1). PBEF was present in both lipid raft and nonraft fractions, whereas the IR was found only in lipid raft fractions of resting A549 cells. The IR-, PBEF-, and Cav-1-coimmunoprecipitated rPBEF treatment resulted in the movement of IRβ- and tyrosine-phosphorylated Cav-1 from lipid rafts to nonrafts, an effect that could be blocked by daporinad, suggesting that this effect was facilitated by the Nampt activity of PBEF. The addition of PBEF to insulin-treated cells resulted in reduced Akt phosphorylation of both Ser⁴⁷³ and Thr³⁰⁸. We conclude that PBEF can inhibit insulin signaling through the IR by Nampt-dependent promotion of IR translocation into the nonraft domains of A549 epithelial cells. PBEF-induced alterations in the spatial geometry of the IR provide a mechanistic explanation for insulin resistance in inflammatory states associated with upregulation of PBEF.
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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) | 0.001 | 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".