Identification of antimicrobial resistance-associated genes through whole genome sequencing of high and low MIC isolates of <i>Mycoplasma bovis</i>
Bibliographic record
Abstract
Abstract Antimicrobial resistance (AMR) in Mycoplasma bovis has previously been associated with mutations within topoisomerases and ribosomal genes rather than specific resistance-conferring genes. This study used whole genome sequencing (WGS) to identify potential new AMR mechanisms. It was found that a 2019 clinical isolate with high MIC (2019-043682) had a new core genome multilocus sequencing (cgMLST) type (ST10-like) and 91% homology with the published genome of M. bovis PG45. Closely related to PG45, a 1982 isolate (1982-M6152) shared the same cgMLST type (ST17), 97.2% homology and similar low MIC results. Known and potential AMR-associated genetic events were identified through comparison with the published M. bovis PG45 genome. Isolate 2019-043682 had 507 genes with non-synonymous mutations (NSMs) and 67 genes disrupted. Isolate 1982-M6152 had 81 NSMs and 20 disruptions. Based on functional roles and known mechanisms of antimicrobials, a 55 gene subset was assessed for potential AMR mechanisms. Of these, 14 were previously identified from other bacteria as sites of AMR mutation, 41 shared similar functions to them, and 11 contained gene-disrupting mutations. This study indicated that M. bovis may obtain high AMR characteristics by mutating or disrupting other functional genes, in addition to topoisomerases and ribosomal genes.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".