Transposition of pGh9:IS<i>S1</i> is random and efficient in <i>Streptococcus thermophilus</i> CNRZ368
Bibliographic record
Abstract
Streptococcus thermophilus bacteria are used as a starter in the fermentation of yogurts and many cheeses. To construct mutants of S. thermophilus CNRZ368, the use of the plasmid pGh9:ISS1 was considered. This plasmid is known to be a good tool for insertional mutagenesis in gram-positive bacteria, owing to its ability to integrate in the genome by a mechanism of replicative transposition. However, the presence of three endogenous ISS1 copies in the genome of S. thermophilus CNRZ368 and the possible occurrence of homologous recombination could reduce the efficiency of pGh9:ISS1 as a tool for generating mutants. To address this question, the ability of pGh9:ISS1 to transpose randomly in the genome of strain CNRZ368 was investigated. The results of our experiments indicated that: (i) the frequency of transposition of ISS1 was high, approximately 2 x 10(-2), in S. thermophilus CNRZ368; (ii) the integration of multiple tandem copies of the plasmid was frequent; (iii) homologous recombination events between ISS1 were not predominant; and (iv) plasmid pGh9:ISS1 transposed randomly around the S. thermophilus CNRZ368 chromosome. In addition, we describe the strategy used to localize the pGh9:ISS1 insertion locus on the physical map of strain CNRZ368 and the method used to clone the regions flanking this insertion site, especially when multiple copies of the plasmid were integrated in tandem.
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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) | 0.001 | 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 | 0.001 |
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".