Interaction of Zonula Occludens-1 (ZO-1) with α-Actinin-4: Application of Functional Proteomics for Identification of PDZ Domain-Associated Proteins
Bibliographic record
Abstract
The use of recombinant "bait" proteins to capture protein-binding partners, followed by identification of protein interaction networks by mass spectrometry (MS), has gained popularity and widespread acceptance. We have developed an approach using recombinant PDZ protein interaction modules of the membrane-associated guanylate kinase (MAGUK) protein zonula occludens-1 (ZO-1) to pull-down and screen for proteins that interact with these modules via their PDZ domain binding motifs. Identification of proteins by MS of pull-down material was achieved using a vacuum-based chromatography sample preparation device designed for matrix-assisted laser desorption/ionization (MALDI) MS. MS analysis of tryptic fragments in pull-down material revealed a number of potential ZO-1 interacting candidates, including the presence of peptides corresponding to the cortical membrane scaffolding protein alpha-actinin-4. Interaction of alpha-actinin-4 with ZO-1 was confirmed by coimmunoprecipitation of these two proteins from cultured cells, as well as from brain, liver, and heart, and by immunoblot detection of alpha-actinin-4 after pull-down with the first PDZ domain of ZO-1. In contrast, the highly homologous alpha-actinin family member, alpha-actinin-1, displayed no association with ZO-1. Immunofluorescence showed colocalization of alpha-actinin-4 with ZO-1 in cultured HeLa and C6 glioma cells, as well as in a variety of tissues in vivo, including brain, heart, liver, and lung. This study demonstrates the utility of MS-based functional proteomics for identifying cellular components of the ZO-1 scaffolding network. Our finding of the interaction of ZO-1 with alpha-actinin-4 provides a mechanism for linking the known protein recruitment and signaling activities of ZO-1 with alpha-actinin-4-associated plasma membrane proteins that have regulatory activities at cell-cell and cell-extracellular matrix contacts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".