Determinants of spontaneous mutation in the bacterium <i>Escherichia coli</i> as revealed by whole-genome sequencing
Bibliographic record
Abstract
A complete understanding of evolutionary processes requires that factors determining spontaneous mutation rates and spectra be identified and characterized. Using mutation accumulation followed by whole-genome sequencing, we found that the mutation rates of three widely diverged commensal Escherichia coli strains differ only by about 50%, suggesting that a rate of 1-2 × 10(-3) mutations per generation per genome is common for this bacterium. Four major forces are postulated to contribute to spontaneous mutations: intrinsic DNA polymerase errors, endogenously induced DNA damage, DNA damage caused by exogenous agents, and the activities of error-prone polymerases. To determine the relative importance of these factors, we studied 11 strains, each defective for a major DNA repair pathway. The striking result was that only loss of the ability to prevent or repair oxidative DNA damage significantly impacted mutation rates or spectra. These results suggest that, with the exception of oxidative damage, endogenously induced DNA damage does not perturb the overall accuracy of DNA replication in normally growing cells and that repair pathways may exist primarily to defend against exogenously induced DNA damage. The thousands of mutations caused by oxidative damage recovered across the entire genome revealed strong local-sequence biases of these mutations. Specifically, we found that the identity of the 3' base can affect the mutability of a purine by oxidative damage by as much as eightfold.
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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 | 0.001 |
| 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 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".