Enzyme cycling contributes to efficient induction of genome mutagenesis by the cytidine deaminase APOBEC3B
Bibliographic record
Abstract
The single-stranded DNA cytidine deaminases APOBEC3B, APOBEC3H haplotype I, and APOBEC3A can contribute to cancer through deamination of cytosine to form promutagenic uracil in genomic DNA. The enzymes must access single-stranded DNA during the dynamic processes of DNA replication or transcription, but the enzymatic mechanisms enabling this activity are not known. To study this, we developed a method to purify full length APOBEC3B and characterized it in comparison to APOBEC3A and APOBEC3H on substrates relevant to cancer mutagenesis. We found that the ability of an APOBEC3 to cycle between DNA substrates determined whether it was able to efficiently deaminate single-stranded DNA produced by replication and single-stranded DNA bound by replication protein A (RPA). APOBEC3 deaminase activity during transcription had a size limitation that inhibited APOBEC3B tetramers, but not APOBEC3A monomers or APOBEC3H dimers. Altogether, the data support a model in which the availability of single-stranded DNA is necessary, but alone not sufficient for APOBEC3-induced mutagenesis in cells because there is also a dependence on the inherent biochemical properties of the enzymes. The biochemical properties identified in this study can be used to measure the mutagenic potential of other APOBEC enzymes in the genome.
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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 | 0.001 |
| 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".