Deep amplicon sequencing highlights low intra-host genetic variability of Echinococcus multilocularis and high prevalence of the European-type haplotypes in coyotes and red foxes in Alberta, Canada
Bibliographic record
Abstract
Echinococcus multilocularis (Em) is a zoonotic parasite considered a global emergent pathogen. Recent findings indicate that the parasite is expanding its range in North America and that European-type haplotypes are circulating in western Canada. However, genetic analyses are usually conducted only on a few parasites out of thousands of individuals within each definitive host, likely underestimating the prevalence of less common haplotypes. Moreover, mixed infections with several mtDNA haplotypes in the same host have been reported, but their relative abundance within the host was never estimated. We aimed to 1) estimate the frequency of co-infections of different Em haplotypes in coyotes (Canis latrans) and red foxes (Vulpes vulpes) from western Canada and their relative abundance within the definitive hosts, 2) detect less prevalent haplotypes by sampling a larger proportion of the parasite subpopulation per host, and 3) investigate differences in the distribution of Em haplotypes in these main definitive hosts; foxes and coyotes. We extracted DNA from ~10% of the worm subpopulation per host (20 foxes and 47 coyotes) and used deep amplicon sequencing (NGS technology) on four loci, targeting the most polymorphic regions from the mitochondrial genes cox1 (814 bp), nad1 (344 bp), and cob (387 bp). We detected the presence of mixed infections with multiple Em haplotypes and with different Echinococcus species including Em and E. granulosus s.l. genotypes G8/G10, low intraspecific diversity of Em, and a higher abundance of the European-type haplotypes in both hosts. Our results suggest a population expansion of the European over the North American strain in Alberta and a limited distribution of some European-type haplotypes. Our findings indicate that deep amplicon sequencing represents a valuable tool to characterize Em in multiple hosts, to assess the current distribution and possible origins of the European strain in North America. The potential use of next-generation sequencing technologies is particularly important to understand the patterns of geographic expansion of this parasite.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".