Phosphorylation of IGFBP-1 at Discrete Sites Elicits Variable Effects on IGF-I Receptor Autophosphorylation
Bibliographic record
Abstract
We previously demonstrated that hypoxia and leucine deprivation cause hyperphosphorylation of IGF-binding protein-1 (IGFBP-1) at discrete sites that markedly enhanced IGF-I affinity and inhibited IGF-I-stimulated cell growth. In this study we investigated the functional role of these phosphorylation sites using mutagenesis. We created three IGFBP-1 mutants in which individual serine (S119/S169/S98) residues were substituted with alanine and S101A was recreated for comparison. The wild-type (WT) and mutant IGFBP-1 were expressed in Chinese hamster ovary cells and IGFBP-1 in cell media was isolated using isoelectric-focusing-free-flow electrophoresis. BIACore analysis indicated that the changes in IGF-I affinity for S98A and S169A were moderate, whereas S119A greatly reduced the affinity of IGFBP-1 for IGF-I (100-fold, P < .0001). Similar results were obtained with S101A. The IGF-I affinity changes of the mutants were reflected in their ability to inhibit IGF-I-induced receptor autophosphorylation. Employing receptor-stimulation assay using IGF-IR-overexpressing P6 cells, we found that WT-IGFBP-1 inhibited IGF-IRβ autophosphorylation (~2-fold, P < .001), possibly attributable to sequestration of IGF-I. Relative to WT, S98A and S169A mutants did not inhibit receptor autophosphorylation. S119A, on the other hand, greatly stimulated the receptor (2.3-fold, P < .05). The data with S101A matched S119A. In summary, we show that phosphorylation at S98 and S169 resulted in milder changes in IGF-I action; nonetheless most dramatic inhibitory effects on the biological activity of IGF-I were due to IGFBP-1 phosphorylation at S119. Our results provide novel demonstration that IGFBP-1 phosphorylation at S119 can enhance affinity for IGF-I possibly through stabilization of the IGF-IGFBP-1 complex. These data also propose that the synergistic interaction of distinct phosphorylation sites may be important in eliciting more pronounced effects on IGF-I affinity that needs further investigation.
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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".