Proteomic Analysis of Src Family Kinases Signaling Complexes in Golgi/Endosomal Fractions Using a Site-Selective Anti-Phosphotyrosine Antibody: Identification of LRP1-Insulin Receptor Complexes
Bibliographic record
Abstract
A role for Src Family Kinases (SFKs) in the dynamics of endocytic and secretory pathways has previously been reported. Identification of low-abundance compartmentalized complexes still remains challenging, highlighting the need for novel tools. Here we describe analysis of SFK-signaling complexes of hepatic Golgi/endosomes (G/E) fractions by sequential affinity enrichment of proteins. Mouse G/E permeabilized membranes were first validated in terms of electron microscopy, 1-D electrophoresis (1-DE), insulin-mediated endocytosis and protein content. With the use of quantitative N-terminal labeling of tryptic peptides (iTRAQ), 1-DE and IEF tryptic peptides separation methods, a total of 666 proteins were identified, including the SFK Lyn. Following insulin injection, a series of proteins were recognized by an anti-phosphotyrosine antibody (alpha P42-2) raised against the residue most frequently phosphorylated by SFK on the adenoviral protein E4orf4 and that cross-reacts with endosomal SFK targets. By using affinity chromatography coupled with mass spectrometry, we identified 16 proteins classified as (1) recycling receptors, (2) vesicular trafficking proteins, (3) actin network proteins, (4) metabolism proteins, or (5) signaling proteins. One of these proteins, low density lipoprotein-related protein 1 (LRP1), which is a known SFK substrate, was found to associate with the internalized insulin receptor (IR), suggesting the presence of a co-internalization process. The identification of these proteomes should, thus, contribute to a better understanding of the molecular mechanisms that regulate trafficking events and insulin clearance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".