Proteome-wide Identification of WRN-Interacting Proteins in Untreated and Nuclease-Treated Samples
Bibliographic record
Abstract
Werner syndrome (WS) is characterized by the premature onset of several age-associated pathologies. The protein defective in WS patients (WRN) is a helicase/exonuclease involved in DNA repair, replication, telomere maintenance, and transcription. Here, we present the results of a large-scale proteome analysis to determine protein partners of WRN. We expressed fluorescent tagged-WRN (eYFP-WRN) in human 293 embryonic kidney cells and detected interacting proteins by co-immunoprecipitation from cell extract. We identified by mass spectrometry 220 nuclear proteins that complexed with WRN. This number was reduced to 40 when broad-spectrum nucleases were added to the lysate. We consider these 40 proteins as directly interacting with WRN. Some of these proteins have previously been shown to interact with WRN, whereas most are new partners. Among the top 15 hits, we find the new interactors TMPO, HNRNPU, RPS3, RALY, RPS9 DDX21, and HNRNPM. These proteins are likely important components in understanding the function of WRN in preventing premature aging and deserve further investigation. We have confirmed endogenous WRN interaction with endogenous RPS3, a ribosomal protein with endonuclease activities involved in oxidative DNA damage recognition. Our results suggest that the use of nucleases during cell lysis severely restricts interacting protein partners and thus enhances specificity.
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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 | 0.003 | 0.002 |
| 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) | 0.000 | 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".