SigB Is a Dominant Regulator of Virulence in Staphylococcus aureus Small-Colony Variants
Bibliographic record
Abstract
Staphylococcus aureus small-colony variants (SCVs) are persistent pathogenic bacteria characterized by slow growth and, for many of these strains, an increased ability to form biofilms and to persist within host cells. The virulence-associated gene expression profile of SCVs clearly differs from that of prototypical strains and is often influenced by SigB rather than by the agr system. One objective of this work was to confirm the role of SigB in the control of the expression of virulence factors involved in biofilm formation and intracellular persistence of SCVs. This study shows that extracellular proteins are involved in the formation of biofilm by three SCV strains, which, additionally, have a low biofilm-dispersing activity. It was determined that SigB activity modulates biofilm formation by strain SCV CF07-S and is dominant over that of the agr system without being solely responsible for the repression of proteolytic activity. On the other hand, the expression of fnbA and the control of nuclease activity contributed to the SigB-dependent formation of biofilm of this SCV strain. SigB was also required for the replication of CF07-S within epithelial cells and may be involved in the colonization of lungs by SCVs in a mouse infection model. This study methodically investigated SigB activity and associated mechanisms in the various aspects of SCV pathogenesis. Results confirm that SigB activity importantly influences the production of virulence factors, biofilm formation and intracellular persistence for some clinical SCV strains.
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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 | 0.000 |
| 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".