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Updated: Sep 14, 2025

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
Identification of tickborne pathogens in cattle and sheep ticks from Kyrgyzstan using next-generation sequencing
Ji Ye Seo1, Jin Seo Park1, Bekbolsun Aknazarov2
1Division of Vectors and Parasitic Diseases, Korea Disease Control and Prevention Agency, 187 Osongsaengmyeong 2-ro, Osong-eup, Heungdeok-gu, Cheongju, 28159, Chungbuk, Republic of Korea.
Background:
Various tickborne diseases and pathogens in livestock have been reported in Kyrgyzstan; however, comprehensive molecular analyses from ticks and their tickborne pathogen diversity in the region are lacking. This study aimed to identify tick species and bacterial pathogens infesting cattle and sheep across Kyrgyzstan using amplicon-based next-generation sequencing (NGS).
Methods:
In 2022, ticks were collected from livestock across seven provinces and subjected to molecular analyses. Genomic DNA was extracted from ticks for species identification based on cytochrome c oxidase I (COI) gene sequence analyses. Pathogens were screened using amplicon NGS targeting the V3-V4 region of the 16S rRNA gene, followed by confirmation using polymerase chain reaction (PCR) and Sanger sequencing.
Results:
A total of 546 ticks belonging to two families, five genera, and 12 species were identified. The dominant species were Dermacentor spp. (30.2%), Hyalomma marginatum (17.2%), Hyalomma scupense (13.4%), and Haemaphysalis punctata (11.7%). Furthermore, 11.7% of ticks tested positive for bacterial pathogens, including spotted fever group Rickettsiae (8.6%), Anaplasma (2.7%), Ehrlichia (0.2%), and Bartonella (0.2%). Coxiella burnetii and Francisella tularensis were not detected.
Conclusions:
This is the first nationwide study on bacterial pathogens in ticks in Kyrgyzstan and the first reports of spotted fever group Rickettsiae and Bartonella in the country. These findings improve our understanding of tickborne disease epidemiology and highlight the utility of NGS as an efficient screening method for capturing pathogen diversity in arthropod vectors.
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