Evidence map›Paper›PMID 40763172›Full record

ArticlePloS one2025

Nationwide investigation of eukaryotic pathogens in ticks from cattle and sheep in Kyrgyzstan using metabarcoding.

Singeun Oh, Nathalie Amvongo-Adjia, Hyun Jung Kim, Jun Ho Choi, Xavier Chavarria, Myung-Hee Yi, Arwa Shatta, Bekbolsun Aknazarov, Ju Yeong Kim, Jung-Won Ju

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Singeun OhDepartment of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0002-2757-9529
Nathalie Amvongo-AdjiaDepartment of Global Health and Disease Control, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea.
Hyun Jung KimDivision of Vectors and Parasitic Diseases, Korea Disease Control and Prevention Agency (KDCA), Cheongju, Republic of Korea.
Jun Ho ChoiDepartment of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-7416-3377
Xavier ChavarriaDepartment of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Seoul, Republic of Korea.
Myung-Hee YiDepartment of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Seoul, Republic of Korea.
Arwa ShattaDepartment of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Seoul, Republic of Korea.
Bekbolsun AknazarovFaculty of Veterinary Medicine, Kyrgyz National Agrarian University Named after K. I. Skryabin, Bishkek, Kyrgyzstan.
Ju Yeong KimDepartment of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jung-Won JuDivision of Vectors and Parasitic Diseases, Korea Disease Control and Prevention Agency (KDCA), Cheongju, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ticks are significant vectors of bacterial, viral, and protozoan pathogens, impacting both public health and agriculture. In Kyrgyzstan, tick-borne diseases are a growing concern for livestock and human health. While bacterial and viral pathogens are widely studied, and limited previous investigations have focused on specific Babesia and Theileria species in certain host animals, comprehensive data on tick eukaryotic microbiota and potential pathogens across diverse hosts nationwide is scarce. To address this gap, our study provides the comprehensive nationwide assessment of the potential protozoan pathogens in ticks from cattle and sheep, analyzing data of Babesia and Theileria at the genus level. We collected 472 tick samples from cattle and sheep across seven regions of Kyrgyzstan (March-July 2022). Tick species were identified via microscope and Sanger sequencing (mitochondrial COI gene). Eukaryotic microbiota was analyzed using 18S rRNA V9 NGS. Sanger sequencing identified five genera and 11 tick species. NGS analysis revealed Babesia (13.3%) and Theileria (12.7%) as among the most prevalent protozoa detected at the genus level. Babesia was significantly more prevalent in nymph-stage ticks and those collected from sheep, whereas Theileria was detected across a broader range of tick species and host animals, showing less variation across life stages. No significant differences in prevalence were observed based on tick sex or the number of hosts in the tick life cycle. Regionally, Babesia detection was highest in the Osh region, particularly in ticks collected from both cattle and sheep. This is the first comprehensive nationwide analysis of tick eukaryotic metabarcoding study in Kyrgyzstan focusing on pathogenic protozoa detected at the genus level. Findings provide crucial baseline data on Babesia and Theileria geographic and host-specific prevalence. Understanding these information is essential for advancing future research and supporting the development of effective surveillance and control strategies against babesiosis and theileriosis in regional livestock.

Indexed as

BabesiaTheileriaTicksAnimalsBabesiosisCattleCattle DiseasesDNA Barcoding, TaxonomicKyrgyzstanRNA, Ribosomal, 18SSheepSheep DiseasesTheileriasisRNA, Ribosomal, 18S

Identifiers

PMID40763172
PMCPMC12324094

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.