Whole-genome sequencing of Western Canadian Borrelia spp. collected from diverse tick and animal hosts reveals short-lived local genotypes interspersed with longer-lived continental genotypes
Bibliographic record
Abstract
Changing climates are allowing the geographic expansion of ticks and their animal hosts, increasing the risk of Borrelia-caused zoonoses in Canada. However, little is known about the genomic diversity of Borrelia from the west of the Canadian Rockies and from the tick vectors Ixodes pacificus, Ixodes auritulus and Ixodes angustus. Here, we report the whole-genome shotgun sequences of 51 Borrelia isolates from multiple tick species collected on a range of animal hosts between 1993 and 2016, located primarily in coastal British Columbia. The bacterial isolates represented three different species from the Lyme disease-causing Borrelia burgdorferi sensu lato genospecies complex [Borrelia burgdorferi sensu stricto (n=47), Borrelia americana (n=3) and Borrelia bissettiae (n=1)]. The traditional eight-gene multi-locus sequence typing (MLST) strategy was applied to facilitate comparisons across studies. This identified 13 known Borrelia sequence types (STs), established 6 new STs, and assigned 5 novel types to the nearest sequence types. B. burgdorferi s. s. isolates were further differentiated into ten ospC types, plus one novel ospC with less than 92 % nucleotide identity to all previously defined ospC types. The MLST types resampled over extended time periods belonged to previously described STs that are distributed across North America. The most geographically widespread ST, ST.12, was isolated from all three tick species. Conversely, new B. burgdorferi s. s. STs from Vancouver Island and the Vancouver region were only detected for short periods, revealing a surprising transience in space, time and host tick species, possibly due to displacement by longer-lived genotypes that expanded across North America. This article contains data hosted by Microreact.
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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 | 0.002 | 0.003 |
| 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".