Genetic landscape of Borrelia burgdorferi sensu stricto in Canada: a study of genetic diversity
Bibliographic record
Abstract
Borrelia burgdorferi sensu stricto (s.s.), the causative agent of Lyme disease in North America, exhibits considerable genetic diversity. In order to gauge rates of recombination and the degree of geographically structuring within the population we carried out a comprehensive whole-genome comparison of B. burgdorferi s.s. strains (n = 64) across three Canadian regions - Nova Scotia (NS), Ontario (ON), and Manitoba (MB). Using a multi-marker approach (MLST, ospC, RSP, RST, IGS), we identified 12 genetically coherent groups that were stable across both core and accessory genome phylogenies. Our analyses reveal a clear geographic gradient of clonality, with NS harboring highly clonal and modular populations (clonal ratio = 4, modularity Q = 0.68), while ON/MB strains exhibited more recombination, shared markers, and genetic connectivity. Genes like ospC showed high recombination rates (R/θ = 4.25), whereas others (ospA, P45-13) evolved primarily via mutation (R/θ < 0.10), illustrating distinct selective pressures in host versus vector environments. Despite these differences, lineages remained phylogenetically robust across markers. These findings highlight how evolutionary processes shape the structure and diversity of B. burgdorferi s.s. populations in Canada and provide insights into its geographic spread and population ecology.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".