CRISPR-Cas9 knockout of <i>qseB</i> induced asynchrony between motility and biofilm formation in <i>Escherichia coli</i>
Bibliographic record
Abstract
Generally, cell motility and biofilm formation are tightly regulated. The QseBC two-component system (TCS) serves as a bridge for bacterial signal transmission, in which the protein QseB acts as a response regulator bacterial motility, biofilm formation, and virulence. The mechanisms that govern the interaction between QseBC and their functions have been studied in general, but the regulatory role of QseB on bacterial motility and biofilm formation is unknown. In this study, the CRISPR-Cas9 system was used to construct the Escherichia coli MG1655ΔqseB strain (strain ΔqseB), and the effects of the qseB gene on changes in motility and biofilm formation in the wild type (WT) were determined. The motility assay results showed that the ΔqseB strain had higher (p < 0.05) motility than the WT strain. However, there was no difference in the formation of biofilm between the ΔqseB and WT strains. Real-time quantitative PCR illustrated that deletion of qseB in the WT strain downregulated expression of the type I pili gene fimA. Therefore, we might conclude that the ΔqseB induced the downregulation of fimA, which led to asynchrony between motility and biofilm formation in E. coli, providing new insight into the functional importance of QseB in regulating cell motility and biofilm formation.
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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 | 0.001 |
| 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".