QsvR and OpaR coordinately regulate the transcription of <i>cpsS</i> and <i>cpsR</i> in <i>Vibrio parahaemolyticus</i>
Bibliographic record
Abstract
Vibrio parahaemolyticus, the leading cause of seafood-associated gastroenteritis, has a strong capacity to form biofilms on surfaces, which is strictly regulated by the CpsS–CpsR–CpsQ regulatory cascade. OpaR, a master regulator of quorum sensing, is a global regulator that controls multiple cellular pathways including biofilm formation and virulence. QsvR is an AraC-type regulator that works coordinately with OpaR to control biofilm formation and virulence gene expression of V. parahaemolyticus. QsvR and OpaR activate cpsQ transcription. OpaR also activates cpsR transcription, but lacks the detailed regulatory mechanisms. Furthermore, it is still unknown whether QsvR regulates cpsR transcription, as well as whether QsvR and OpaR regulate cpsS transcription. In this study, the results of quantitative real-time PCR and LacZ fusion assays demonstrated that deletion of qsvR and/or opaR significantly decreased the expression levels of cpsS and cpsR compared to the wild-type strain. However, the results of two-plasmid lacZ reporter and electrophoretic mobility-shift assays showed that both QsvR and OpaR were unable to bind the regulatory DNA regions of cpsS and cpsR. Therefore, transcription of cpsS and cpsR was coordinately and indirectly activated by QsvR and OpaR. This work enriched our knowledge on the regulatory network of biofilm formation in V. parahaemolyticus.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".