Antimicrobial susceptibility of western Canadian Brachyspira isolates: Development and standardization of an agar dilution susceptibility test method
Bibliographic record
Abstract
The re-emergence of Brachyspira-associated disease in pigs since the late 2000s has illuminated some of the diagnostic challenges associated with this genus; notably, the lack of standardized antimicrobial susceptibility testing (AST) methods and interpretive criteria. Consequently, laboratories have relied heavily on highly variable in-house developed methods. There are currently no published investigations describing the antimicrobial susceptibility of Brachyspira isolates collected from pigs in Canada. The first objective of this study was therefore to develop a standardized protocol for conducting agar dilution susceptibility testing of Brachyspira spp., including determining the optimal standardized inoculum density, a key test variable that impacts test performance. The second objective was to determine the susceptibility of a collection of western Canadian Brachyspira isolates using the standardized methodology. After assessing multiple media, an agar dilution test was standardized in terms of starting inoculum (1-2 × 108 CFU/ml), incubation temperature and time, and assessed for repeatability. The antimicrobial susceptibility of a collection of clinical porcine Brachyspira isolates (n = 87) collected between 2009-2016 was then determined. This method was highly reproducible; repeat susceptibility testing yielded identical results 92% of the time. Although most of the isolates had very low MICs to the commonly used antimicrobials to treat Brachyspira-associated infections, several isolates with elevated MICs (>32 μg/ml) for tiamulin, valnemulin, tylosin, tylvalosin, and lincomycin were identified. Overall, this study underscores the importance of establishing CLSI approved clinical breakpoints for Brachyspira to facilitate the interpretation of test results and support the evidence-based selection of antimicrobials in swine industry.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".