Revealing hidden moves: <i>Staphylococcus</i> spp. exhibit motility in semisolid media
Bibliographic record
Abstract
ABSTRACT Staphylococcus spp. are generally considered non-motile due to the absence of active motility structures. However, Staphylococcus aureus , Staphylococcus xylosus , and Staphylococcus epidermidis have demonstrated passive movement. This study investigated the motility of eight additional Staphylococcus species in semisolid media. While most species exhibited some motility, Staphylococcus pseudintermedius and Staphylococcus schleiferi displayed significantly higher levels of motility. Then, we further evaluated the motility of 49 S . pseudintermedius and 30 S . schleiferi isolates, revealing strain-dependent variations. The influence of glucose, NaCl, temperature (35 and 39°C), and culture media (tryptic soy broth [TSB], brain heart infusion [BHI], and Luria Bertani [LB]) on the motility of these two species was evaluated. Glucose and NaCl induced morphological changes in the S. pseudintermedius colonies. In S. schleiferi , NaCl decreased, while glucose increased motility. Temperature and culture media also significantly affected motility, with S. schleiferi showing reduced movement in BHI and both species exhibiting decreased motility in LB compared to TSB. Shedding light on surface motility in Staphylococcus , an understudied phenomenon, can provide insights to elucidate their biology and clarify their mechanism of colonization, survival, and pathogenesis. IMPORTANCE The ability to move is an important characteristic for many bacteria to colonize and infect hosts, yet motility in Staphylococcus is understudied. Our work reveals that several species, notably S. pseudintermedius and S. schleiferi , can actively move across surfaces. This previously hidden capability may be crucial for how these bacteria spread and cause infections. Our evaluation of how different growth conditions and specific genes impact this trait shows species-dependent effects. This study opens new research avenues for understanding the mechanisms these bacteria use to spread within both the environment and their hosts.
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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 | 0.001 |
| 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".