Interconnection of post-transcriptional regulation: The RNA-binding protein Hfq is a novel target of the Lon protease in Pseudomonas aeruginosa
Bibliographic record
Abstract
Besides being a major opportunistic human pathogen, Pseudomonas aeruginosa can be found in a wide range of environments. This versatility is linked to complex regulation, which is achieved through the action of transcriptional regulators, and post-transcriptional regulation by intracellular proteases including Lon. Indeed, lon mutants in this species show defects in motility, biofilm formation, pathogenicity and fluoroquinolone resistance. Here, the proteomic approach stable isotope labeling by amino acids in cell culture (SILAC) was used to search for novel proteolytic targets. One of the proteins that accumulated in the lon mutant was the RNA-binding protein Hfq. Further experiments demonstrated the ability of Lon to degrade Hfq in vitro. Also, overexpression of the hfq gene in the wild-type strain led to partial inhibition of swarming, swimming and twitching motilities, indicating that Hfq accumulation could contribute to the phenotypes displayed by Lon mutants. Hfq overexpression also led to the upregulation of the small regulatory RNA PhrS. Analysis of the phenotypes of strains lacking or overexpressing this sRNA indicated that the Lon protease might be indirectly regulating the levels and activity of sRNAs via Hfq. Overall, this study revealed new links in the complex regulatory chain that controls multicellular behaviours in P. aeruginosa.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".