Identification of genetic markers of resistance to macrolide class antibiotics in <i>Mannheimia haemolytica</i> isolates from a Saskatchewan feedlot
Bibliographic record
Abstract
ABSTRACT Mannheimia haemolytica is a major contributor to bovine respiratory disease (BRD), which causes substantial economic losses to the beef industry, and there is an urgent need for rapid and accurate diagnostic tests to provide evidence for treatment decisions and support antimicrobial stewardship. Diagnostic sequencing can provide information about antimicrobial resistance genes in M. haemolytica more rapidly than conventional diagnostics. Realizing the full potential of diagnostic sequencing requires a comprehensive understanding of the genetic markers of antimicrobial resistance. We identified genetic markers of resistance in M. haemolytica to macrolide class antibiotics commonly used for control of BRD. Genome sequences were determined for 99 M. haemolytica isolates with six different susceptibility phenotypes collected over 2 years from a feedlot in Saskatchewan, Canada. Known macrolide resistance genes estT , msr (E), and mph (E) were identified in most resistant isolates within predicted integrative and conjugative elements (ICEs). ICE sequences lacking antibiotic resistance genes were detected in 10 of 47 susceptible isolates. No resistance-associated polymorphisms were detected in ribosomal RNA genes, although previously unreported mutations in the L22 and L23 ribosomal proteins were identified in 12 and 27 resistant isolates, respectively. Pangenome analysis led to the identification of 79 genes associated with resistance to gamithromycin, of which 95% (75 of 79) had no functional annotation. Most of the observed phenotypic resistance was explained by previously identified antibiotic resistance genes, although resistance to the macrolides gamithromycin and tulathromycin was not explained in 39 of 47 isolates, demonstrating the need for continued surveillance for novel determinants of macrolide resistance. IMPORTANCE Bovine respiratory disease is the costliest disease of beef cattle in North America and the most common reason for injectable antibiotic use in beef cattle. Metagenomic sequencing offers the potential to make economically significant reductions in turnaround time for diagnostic information for evidence-based selection of antibiotics for use in the feedlot. The success of diagnostic sequencing depends on a comprehensive catalog of antimicrobial resistance genes and other genome features associated with reduced susceptibility. We analyzed the genome sequences of isolates of Mannheimia haemolytica , a major bovine respiratory disease pathogen, and identified both previously known and novel genes associated with reduced susceptibility to macrolide class antimicrobials. These findings reinforce the need for ongoing surveillance for markers of antimicrobial resistance to support improved diagnostics and antimicrobial stewardship.
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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 | 0.001 | 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".