<i>uvrA</i> Is an Acid-Inducible Gene Involved in the Adaptive Response to Low pH in <i>Streptococcus mutans</i>
Bibliographic record
Abstract
The pH-inducible acid tolerance response (ATR) is believed to play a major role in acid adaptation and virulence of Streptococcus mutans. To study this phenomenon in S. mutans JH1005, differential display PCR was used to identify and clone 13 cDNA products that had increased expression in response to pH 5.0 compared to that of pH 7.5-grown cells. One of these products, confirmed to be pH inducible by RNA dot blot and reverse transcription-PCR analyses, had 67% identity to a uvrA-UV repair excinuclease gene in Bacillus subtilis. Further sequence analysis of the uvrA homologue using the S. mutans genome database revealed that the complete gene was encoded in an open reading frame (ORF) of 2,829 bp (944 amino acids; 104.67 kDa). Immediately 3' of uvrA was an ORF encoding a putative aminopeptidase gene (pepP). uvrA knockouts were constructed in S. mutans strains JH1005, NG8, and UA159 using allelic-exchange mutagenesis, replacing the entire gene with an erythromycin resistance cassette. As with uvrA mutants in other bacteria, the S. mutans uvrA mutants were extremely sensitive to UV irradiation. The uvrA mutant of S. mutans JH1005 was also more sensitive than the wild type to growth at pH 5.0, showing a 15% reduction in growth rate and a 14% reduction in final resting culture density. Acid-adapted S. mutans JH1005 uvrA mutants were shown to be more resistant to UV irradiation than was the parent but were unable to survive exposure to a killing pH of 3.0. Moreover, agarose gel electrophoretic analysis of chromosomal DNA isolated from uvrA-deficient cells exposed to low pH demonstrated more DNA damage than that for the wild-type strain. Here we suggest that uvrA and the nucleotide excision repair pathway are involved in the repair of acid-induced DNA damage and are associated with successful adaptation of S. mutans to low pH.
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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".