Arginine Catabolic Mobile Element in Evolution and Pathogenicity of the Community-Associated Methicillin-Resistant Staphylococcus aureus Strain USA300
Bibliographic record
Abstract
USA300 is a predominant community-associated methicillin-resistant Staphylococcus aureus strain which carries an arginine catabolic mobile element (ACME). ACME contains potential virulence factors including an arginine deiminase (arc) pathway and an oligopeptide permease (opp-3) system, which are proposed to play a role in bacterial virulence and transmission. However, the role of ACME in evolution and pathogenicity of USA300 remains to be elucidated. ACME and arcA deletion mutants were created by allelic replacement from a USA300 clinical isolate. By comparing wild type and isogenic ACME deletion USA300 strains, ACME was shown not to contribute to bacterial survival on plastic surfaces, and mouse skin surfaces. ACME did not contribute to bacterial virulence in cell invasion and cytotoxicity assays, invertebrate killing assays and a mouse skin infection model. Wild-type ACME negative USA300 clinical isolates showed similar associations with invasive anatomic sites as ACME positive isolates. Our experiments also demonstrated that ACME can spontaneously excise from the bacterial chromosome to generate an ACME deletion strain at a low frequency. Our results do not support that the ACME element alone is a significant factor in the transmission and virulence of USA300 strain, and ACME may have been coincidently incorporated into the genome of USA300.
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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 | 0.001 |
| 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".