A <i>yigP</i> mutant strain is a small colony variant of <i>E. coli</i> and shows pleiotropic antibiotic resistance
Bibliographic record
Abstract
Small colony variants (SCVs) are a commonly observed subpopulation of bacteria that have a small colony size and distinctive biochemical characteristics. SCVs are more resistant than the wild type to some antibiotics and usually cause persistent infections in the clinic. SCV studies have been very active during the past 2 decades, especially Staphylococcus aureus SCVs. However, fewer studies on Escherichia coli SCVs exist, so we studied an E. coli SCV during an experiment involving the deletion of the yigP locus. PCR and DNA sequencing revealed that the SCV was attributable to a defect in the yigP function. Furthermore, we investigated the antibiotic resistance profile of the E. coli SCV and it showed increased erythromycin, kanamycin, and d-cycloserine resistance, but collateral sensitivity to ampicillin, polymyxin, chloramphenicol, tetracycline, rifampin, and nalidixic acid. We tried to determine the association between yigP and the pleiotropic antibiotic resistance of the SCV by analyzing biofilm formation, cellular morphology, and coenzyme Q (Q8) production. Our results indicated that impaired Q8 biosynthesis was the primary factor that contributed to the increased resistance and collateral sensitivity of the SCV. This study offers a novel genetic basis for E. coli SCVs and an insight into the development of alternative antimicrobial strategies for clinical therapy.
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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) | 0.001 | 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 | 0.001 |
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".