Quantitative proteomics profiling of the poly(ADP-ribose)-related response to genotoxic stress
Bibliographic record
Abstract
Upon DNA damage induction, DNA-dependent poly(ADP-ribose) polymerases (PARPs) synthesize an anionic poly(ADP-ribose) (pADPr) scaffold to which several proteins bind with the subsequent formation of pADPr-associated multiprotein complexes. We have used a combination of affinity-purification methods and proteomics approaches to isolate these complexes and assess protein dynamics with respect to pADPr metabolism. As a first approach, we developed a substrate trapping strategy by which we demonstrate that a catalytically inactive Poly(ADP-ribose) glycohydrolase (PARG) mutant can act as a physiologically selective bait for the isolation of specific pADPr-binding proteins through its macrodomain-like domain. In addition to antibody-mediated affinity-purification methods, we used a pADPr macrodomain affinity resin to recover pADPr-binding proteins and their complexes. Second, we designed a time course experiment to explore the changes in the composition of pADPr-containing multiprotein complexes in response to alkylating DNA damage-mediated PARP activation. Spectral count clustering based on GeLC-MS/MS analysis was complemented with further analyses using high precision quantitative proteomics through isobaric tag for relative and absolute quantitation (iTRAQ)- and Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics. Here, we present a valuable resource in the interpretation of systems biology of the DNA damage response network in the context of poly(ADP-ribosyl)ation and provide a basis for subsequent investigations of pADPr-binding protein candidates.
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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 | 0.004 | 0.002 |
| 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 | 0.001 |
| 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".