NfiS, a species-specific regulatory noncoding RNA of Pseudomonas stutzeri, enhances oxidative stress tolerance in Escherichia coli
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Noncoding RNAs (ncRNAs) can finely control the expression of target genes at the posttranscriptional level in prokaryotes. Regulatory small RNAs (sRNAs) designed to control target gene expression for applications in metabolic engineering and synthetic biology have been successfully developed and used. However, the effect on the heterologous expression of species- or strain-specific ncRNAs in other bacterial strains remains poorly understood. In this work, a Pseudomonas stutzeri species-specific regulatory ncRNA, NfiS, which has been shown to play an important role in the response to oxidative stress as well as osmotic stress in P. stutzeri A1501, was cloned and transferred to the Escherichia coli strain Trans10. Recombinant NfiS-expressing E. coli , namely, Trans10- nfiS , exhibited significant enhancement of tolerance to oxidative stress. To map the possible gene regulatory networks mediated by NfiS in E. coli under oxidative stress, a microarray assay was performed to delineate the transcriptomic differences between Trans10- nfiS and wild-type E. coli under H 2 O 2 shock treatment conditions. In all, 1184 genes were found to be significantly altered, and these genes were divided into mainly five functional categories: stress response, regulation, metabolism related, transport or membrane protein and unknown function. Our results suggest that the P. stutzeri species-specific ncRNA NfiS acts as a regulator that integrates adaptation to H 2 O 2 with other cellular stress responses and helps protect E. coli cells against oxidative damage.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it