Mapping the Integrin-Linked Kinase Interactome Using SILAC
Bibliographic record
Abstract
Protein-protein interactions play an essential role in the regulation of vital biological functions. Through a network of interactions, integrin-linked kinase (ILK) functions downstream of integrin receptors to control cell spreading, migration, growth, survival, and cell cycle progression. Despite many reports on the role of ILK in the regulation of multiple signaling pathways, it is still not understood how ILK integrates and controls complex cellular signals. A more global analysis of ILK-protein complexes will give important insights in the complexity of ILK-dependent signal transduction. Here, we applied a SILAC (stable isotope labeling with amino acids in cell culture)-based proteomics approach to discover novel ILK-interacting proteins. Of 752 proteins identified in ILK immunoprecipitates, 24 proteins had SILAC ratios higher than PINCH, previously identified as direct ILK-binding partner. Some of the newly identified proteins specifically enriched in ILK immunoprecipitates, with potentially interesting roles in ILK biology, include rapamycin-insensitive companion of mTOR (Rictor), alpha- and beta-tubulin, RuvB-like 1 and 2, HS1-associating protein 1 (HAX-1), T-complex protein 1 subunits, and Ras-GTP-ase activating-like protein 1 (IQ-GAP1). Functional interactions between ILK and several of the new binding partners were confirmed by coimmunoprecipitation/Western blot and colocalization experiments. Detailed analysis showed that when ILK is found in a complex with alpha-tubulin and RuvB-like 1, alpha-parvin and PINCH are not present, suggesting that ILK has the ability to form distinct protein complexes throughout the cell. Inhibition of ILK activity with an ILK-kinase inhibitor QLT0267 or downregulation of its expression impaired the ability of RuvB-like 1 to bind to tubulin pointing toward a possible role of ILK in the regulation of RuvB-like 1/tubulin interaction. Using the power of quantitative proteomics to resolve specific from nonspecific protein interactions, we identified several novel ILK-binding proteins, which sheds light on the molecular mechanisms of regulation of ILK-dependent signal transduction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".