Identification of Domains of Ataxia-telangiectasia Mutated Required for Nuclear Localization and Chromatin Association
Bibliographic record
Abstract
Ataxia-telangiectasia mutated (ATM) is essential for rapid induction of cellular responses to DNA double strand breaks (DSBs). In this study, we mapped a nuclear localization signal (NLS), 385KRKK388, within the amino terminus of ATM and demonstrate its recognition by the conventional nuclear import receptor, the importin alpha1/beta1 heterodimer. Although mutation of this NLS resulted in green fluorescent protein (GFP) x ATM(NLSm) localizing predominantly within the cytoplasm, small amounts of nuclear GFP x ATM(NLSm) were still sufficient to elicit a DNA damage response. Insertion of an heterologous nuclear export signal between GFP and ATM(NLSm) resulted in complete cytoplasmic localization of ATM, concomitantly reducing the level of substrate phosphorylation and increasing radiosensitivity, which indicates a functional requirement for ATM nuclear localization. Interestingly, the carboxyl-terminal half of ATM, containing the kinase domain, which localizes to the cytoplasm, could not autophosphorylate itself or phosphorylate substrates, nor could it correct radiosensitivity in response to DSBs even when targeted to the nucleus by insertion of an exogenous NLS, demonstrating that the ATM amino terminus is required for optimal ATM function. Moreover, we have shown that the recruitment/retention of ATM at DSBs requires its kinase activity because a kinase-dead mutant of GFP x ATM failed to form damage-induced foci. Using deletion mutation analysis we mapped a domain in ATM (amino acids 5-224) required for its association with chromatin, which may target ATM to sites of DNA damage. Combined, these data indicate that the amino terminus of ATM is crucial not only for nuclear localization but also for chromatin association, thereby facilitating the kinase activity of ATM in vivo.
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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) | 0.000 | 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) | 0.001 | 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".