Identification of Mammalian Proteins Cross-linked to DNA by Ionizing Radiation
Bibliographic record
Abstract
Ionizing radiation (IR) is an important environmental risk factor for various cancers and also a major therapeutic agent for cancer treatment. Exposure of mammalian cells to IR induces several types of damage to DNA, including double- and single-strand breaks, base and sugar damage, as well as DNA-DNA and DNA-protein cross-links (DPCs). Little is known regarding the biological consequences of DPCs. Identifying the proteins that become cross-linked to DNA by IR would be an important first step in this regard. We have therefore undertaken a proteomics study to isolate and identify proteins involved in IR-induced DPCs. DPCs were induced in AA8 Chinese hamster ovary or GM00637 human fibroblast cells using 0-4 gray of gamma-rays under either aerated or hypoxic conditions. DPCs were isolated using a recently developed method, and proteins were identified by mass spectrometry. We identified 29 proteins as being cross-linked to DNA by IR under aerated and/or hypoxic conditions. The identified proteins include structural proteins, actin-associated proteins, transcription regulators, RNA-splicing components, stress-response proteins, cell cycle regulatory proteins, and GDP/GTP-binding proteins. The involvement of several proteins (actin, histone H2B, and others) in DPCs was confirmed by using Western blot analysis. The dose responsiveness of DPC induction was examined by staining one-dimensional SDS-polyacrylamide gels with SYPRO Tangerine followed by analysis using fluorescence imaging. Quantitation of the fluorescence signal indicated no significant difference in total yields of IR-induced DPCs generated under aerated or hypoxic conditions, although differences were observed for several individual protein bands.
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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 | 0.000 | 0.000 |
| 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".