Bacteriocin ST91KM, produced by Streptococcus gallolyticus subsp. macedonicus ST91KM, is a narrow-spectrum peptide active against bacteria associated with mastitis in dairy cattle
Bibliographic record
Abstract
Streptococcus gallolyticus subsp. macedonicus ST91KM produces a bacteriocin (macedocin ST91KM) active against Streptococcus agalactiae, Streptococcus dysgalactiae subsp. dysgalactiae, Streptococcus uberis, Staphylococcus aureus, and Staphylococcus epidermidis. Macedocin ST91KM is, according to tricine-SDS PAGE, between 2.0 and 2.5 kDa in size. Antimicrobial activity remained unchanged after 2 h of incubation at pH 2.0-10.0 and after 100 min at 100 degrees C. The peptide was inactivated after 20 min at 121 degrees C and when treated with proteolytic enzymes. Treatment with alpha-amylase had no effect on activity, suggesting that the mode of action does not depend on glycosylation. Amplification of the genome of strain ST91KM with primers designed from the macedocin precursor gene (mcdA) produced 2 fragments (approximately 375 and 220 bp) instead of one 150-bp fragment, as recorded for macedocin produced by Streptococcus gallolyticus subsp. macedonicus ACA-DC 198. Strain ACA-DC 198 was not available. However, DNA amplified from strain LMG 18488 (ACA-DC 206), genetically closely related to strain ACA-DC 198, revealed 99% homology to the mcdA of strain ACA-DC 198 (accession No. DQ835394). Macedocin ST91KM may thus be a second putative bacteriocin described for Streptococcus gallolyticus subsp. macedonicus.
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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".