The Transcript from the σ <sup>28</sup> -Dependent Promoter Is Translationally Inert in the Expression of the σ <sup>28</sup> -Encoding Gene <i>fliA</i> in the <i>fliAZ</i> Operon of Salmonella enterica Serovar Typhimurium
Bibliographic record
Abstract
There are three classes of promoters for flagellar operons in Salmonella. Class 2 promoters are transcribed by σ(70) RNA polymerase in the presence of an essential activator, FlhD(4)C(2), and activated by an auxiliary regulator, FliZ. Class 3 promoters are transcribed by σ(28) RNA polymerase and repressed by an anti-σ(28) factor, FlgM. σ(28) (FliA) and FliZ are encoded by the fliA and fliZ genes, respectively, which together constitute an operon transcribed in this order. This operon is transcribed from both class 2 and class 3 promoters, suggesting that it should be activated by its own product, σ(28), even in the absence of FlhD(4)C(2). However, σ(28)-dependent transcription occurs in vivo only in the presence of FlhD(4)C(2), indicating that transcription from the class 2 promoter is a prerequisite to that from the class 3 promoter. In this study, we examined the effects of variously modified versions of the fliA regulatory region on transcription and translation of the fliA gene. We showed that FliA is not significantly translated from the class 3 transcript. In contrast, the 5'-terminal AU-rich sequence found in the class 2 transcript confers efficient fliA translation. Replacement of the Shine-Dalgarno sequence of the fliA gene with a better one improved fliA translation from the class 3 transcript. These results suggest that the 5'-terminal AU-rich sequence of the class 2 transcript may assist ribosome binding. FliZ was shown to be expressed from both the class 2 and class 3 transcripts.
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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 | 0.001 |
| 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 | 0.001 |
| 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".