Multiple genetic switches spontaneously modulating bacterial mutability
Bibliographic record
Abstract
BACKGROUND: All life forms need both high genetic stability to survive as species and a degree of mutability to evolve for adaptation, but little is known about how the organisms balance the two seemingly conflicting aspects of life: genetic stability and mutability. The DNA mismatch repair (MMR) system is essential for maintaining genetic stability and defects in MMR lead to high mutability. Evolution is driven by genetic novelty, such as point mutation and lateral gene transfer, both of which require genetic mutability. However, normally a functional MMR system would strongly inhibit such genomic changes. Our previous work indicated that MMR gene allele conversion between functional and non-functional states through copy number changes of small tandem repeats could occur spontaneously via slipped-strand mis-pairing during DNA replication and therefore may play a role of genetic switches to modulate the bacterial mutability at the population level. The open question was: when the conversion from functional to defective MMR is prohibited, will bacteria still be able to evolve by accepting laterally transferred DNA or accumulating mutations? RESULTS: To prohibit allele conversion, we "locked" the MMR genes through nucleotide replacements. We then scored changes in bacterial mutability and found that Salmonella strains with MMR locked at the functional state had significantly decreased mutability. To determine the generalizability of this kind of mutability 'switching' among a wider range of bacteria, we examined the distribution of tandem repeats within MMR genes in over 100 bacterial species and found that multiple genetic switches might exist in these bacteria and may spontaneously modulate bacterial mutability during evolution. CONCLUSIONS: MMR allele conversion through repeats-mediated slipped-strand mis-pairing may function as a spontaneous mechanism to switch between high genetic stability and mutability during bacterial evolution.
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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 | 0.001 |
| 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) | 0.002 | 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".