Polyphasic Characterization Reveals that the Human Pathogen <i>Mycobacterium peregrinum</i> Type II Belongs to the Bovine Pathogen Species <i>Mycobacterium senegalense</i>
Bibliographic record
Abstract
Mycobacterium peregrinum consists of two taxa: types I and II. We evaluated 43 clinical type II strains from throughout the United States. They were responsible for soft-tissue and bone infections, catheter-related infections, and possible pneumonitis. By carbohydrate utilization, they were indistinguishable from type I strains, being D-mannitol and trehalose positive. However, they had a distinct susceptibility pattern that included intermediate ciprofloxacin MICs but low clarithromycin and doxycycline MICs of < or =1 microg/ml. These features were also shared by reference isolates of Mycobacterium senegalense from African bovine cases of "farcy." By 16S rRNA gene sequencing, the type II isolates shared 100% sequence identity with M. senegalense. Partial sequencing of the type II hsp65 gene (441 bp) revealed four sequevars showing > or =98.4% identity with each other and > or =98.6% identity with the sequence of five bovine strains of M. senegalense. There was < or =97.1% identity with M. peregrinum type I isolates and other Mycobacterium fortuitum group species. Sequencing of additional gene targets including the 16S-23S rDNA internal transcribed spacer region and the rpoB gene (partial sequence) revealed a similar phylogenetic grouping. DNA-DNA hybridization showed 76 to 99% relatedness between the bovine and human strains. These studies demonstrate that type II isolates are not isolates of M. peregrinum but represent human strains of M. senegalense. This study is the first to demonstrate this species as a human pathogen. Representative human M. senegalense strains include ATCC 35755 and newly submitted strains ATCC BAA-849, ATCC BAA-850, and ATCC BAA-851.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".