Genetic diversity of tick-borne zoonotic pathogens in ixodid ticks collected from small ruminants in Northern Pakistan
Bibliographic record
Abstract
Mapping tick distribution and pathogens in unexplored areas sheds light on their importance in zoonotic and veterinary contexts. In this study, we performed a comprehensive investigation of the genetic diversity of tick and tick-borne pathogens (TBPs) detection infesting/infecting small ruminants across northern Pakistan. We collected 1587 ixodid ticks from 600 goats and sheep, an overall tick infestation rate of 50.2 %. Notably, gender-based infestation rates were higher in female goats and sheep compared to their male counterparts. Age-wise analysis showed that the tick infestation rate was higher in older animals. This study identified 11 ixodid tick species within three genera: Hyalomma , Haemaphysalis , and Rhipicephalus , which were taxonomically classified using 16S rRNA and cytochrome oxidase I (cox1) molecular markers. Sequence analysis indicated that reported ticks are similar to ixodid species found across various Asian and African countries. Tick-borne pathogens were detected by amplifying 16S rRNA and citrate synthase ( gltA ) for bacterial pathogens and 18S rRNA for apicomplexan parasites. The present study reported a diverse array of TBPs in ticks from the study area, with Rickettsia massiliae (24.5 %) and Theleria ovis (16.4 %) as the most prevalent bacterial and apicomplexan pathogens. Phylogenetically, detected TBPs shared evolutionary relatedness with identical TBPs from old and new world countries. These findings highlight the presence of zoonotic TBPs in ixodid ticks from Pakistan. In addition, it also provides a foundation for future epidemiological research on ticks and TBPs, emphasizing their relevance in both zoonotic and veterinary contexts. • A high tick infestation rate (50.2 %) was observed in small ruminants, with female and older hosts being more susceptible. • Eleven hard tick species from Hyalomma , Haemaphysalis, and Rhipicephalus identified are endemic to Northern Pakistan. • A diverse array of tick-borne pathogens (TBPs) with Rickettsia massiliae and Theileria ovis as the most prevalent by 24.5 % and 16.4 %, respectively. • Detected ticks and pathogens are phylogenetically identical to other new and old-world countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".