Tn<i>917-lac</i>mutagenesis of<i>Streptococcus mutans</i>to identify environmentally regulated genes
Bibliographic record
Abstract
Previously, we demonstrated successful Tn917 mutagenesis of the oral pathogen Streptococcus mutans using pTV1-OK (Km(r), repATs), a temperature conditional replicative delivery vector carrying a lactococcal pWVO1Ts backbone. In this report we describe the construction and utilization of pTV32-OK, a plasmid harboring Tn917-lac (em(r), beta-gal(+)) that was employed to isolate transcriptional fusions of the Escherichia coli lacZ reporter gene with streptococcal promoters in S. mutans strain NG8. Tn917-lac transposition occurred at a frequency of ca. 10(-6) with 20% of the resultant em(r) clones displaying varying levels of lacZ expression. Tn917-lac mutants that expressed beta-galactosidase activity under growth conditions of glucose limitation, acidic pH, 35 mM NaCl, and elevated (42 degrees C) temperature were isolated. Further characterization of one of the mutants with increased beta-gal activity under glucose limitation, strain AS42, revealed maximal activity in batch culture in stationary phase after glucose depletion. The beta-gal activity of AS42 also was found to be repressed 3-fold in medium containing 2% glucose relative to measured activity from cells suspended in the same medium containing no glucose. Further phenotypic analysis revealed that AS42 had a 30% lower growth yield than the parent strain NG8 when grown in pH 5 medium. Sequence analysis of the region harboring the transposon revealed that the lacZ fusion occurred near the 3'-end of a gene encoding a homolog of an ATP binding protein from a family of Gram-positive ABC transporters. These findings demonstrate that Tn917-lac mutagenesis can be used to identify environmentally regulated genes in S. mutans and possibly in other medically relevant streptococcal species.
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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".