Comparative analysis of sigma factors RpoS, FliA, and RpoN in <i>Edwardsiella tarda</i>
Bibliographic record
Abstract
Sigma factors are important regulators that bacteria employ to cope with environmental changes. Studies on the functions of sigma factors have uncovered their roles in many important cellular activities, such as growth, stress tolerance, motility, biofilm formation, and virulence. However, comparative analyses of sigma factors that examine their common and unique features or elucidate their cross-regulatory relationships have rarely been conducted for Edwardsiella tarda. Here, we characterized and compared motility and resistance to oxidative stress of E. tarda strains complemented with rpoS, fliA, and rpoN mutants. The results suggest that the sigma factors FliA and RpoN regulated motility, whereas RpoS exhibited no such function. RpoS and RpoN were essential for oxidative stress resistance, whereas FliA had no obvious impact under oxidative stress conditions. Furthermore, 2-dimensional gel electrophoresis based proteomics analysis combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry revealed 12 differentially expressed protein spots that represented 11 proteins between the mutant and wild-type strains. Quantification of the expression of target genes by quantitative reverse transcription PCR confirmed the results of our proteomics analysis. Collectively, these results suggest that these sigma factors are multifunctional mediators involved in controlling the expression of many metabolic pathway genes.
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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) | 0.000 | 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".