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. 2025 Jun 4;18(1):207.
doi: 10.1186/s13071-025-06857-1.

Molecular characterization of tick-borne bacterial and protozoan pathogens in parasitic ticks from Xinjiang, China

Affiliations

Molecular characterization of tick-borne bacterial and protozoan pathogens in parasitic ticks from Xinjiang, China

Bingjie Wang et al. Parasit Vectors. .

Abstract

Background: Ticks are a type of hematophagous parasite, serving as critical vectors of pathogens that cause numerous human and animal diseases. Climate change has driven the geographical expansion of tick populations and increased the global transmission risk of tick-borne diseases. However, there has been a lack of comprehensive data on tick species distribution and their associated pathogen profiles in Xinjiang, China.

Methods: Ticks were collected from 19 sampling sites across nine regions in Xinjiang. The species were identified using both morphological and molecular biological methods. The presence of tick-borne bacterial and protozoan pathogens was detected through polymerase chain reaction (PCR). Finally, sequencing and phylogenetic analyses were performed to further characterize the identified ticks and pathogens.

Results: A total of 1093 ticks were collected and identified, representing four genera and nine species, with Hyalomma asiaticum being the dominant species. Haplotype diversity and genetic differentiation analysis based on the 16S rRNA gene of the dominant species demonstrated that the Hy. asiaticum population in Xinjiang exhibits high haplotype diversity (Hd = 0.734), low nucleotide diversity (π = 0.00403), and significant genetic differentiation (Fst = 0.19716). Pathogen detection using PCR revealed an infection rate of 9.3% for Anaplasma, 18.1% for Rickettsia, and 9.0% for piroplasms. Phylogenetic analysis based on 16S rRNA sequences indicated that the Anaplasma genus identified in ticks comprised Anaplasma ovis, Anaplasma sp., and Anaplasma phagocytophilum. Phylogenetic analysis based on the opmA gene showed that the Rickettsia genus identified in ticks included Rickettsia aeschlimannii, Rickettsia conorii, Rickettsia slovaca, Rickettsia conorii subsp. raoultii, Rickettsia sp., Candidatus Rickettsia barbariae, and Candidatus Rickettsia jingxinensis. Similarly, phylogenetic analysis based on the 18S rRNA gene demonstrated that the piroplasms identified in ticks included Theileria annulata, Theileria ovis, Babesia bigemina, Babesia occultans, and Babesia sp. All gene sequences of the detected pathogens showed 99.8-100% identity with corresponding sequences deposited in GenBank.

Conclusions: This study demonstrates that Xinjiang harbors a rich diversity of tick species with a wide geographical distribution. Furthermore, the tick-borne pathogens in this region are complex and diverse. These results underscore the necessity of sustained and enhanced surveillance efforts targeting ticks and tick-borne diseases in this region.

Keywords: Anaplasma; Borrelia burgdorferi; Ehrlichia; Rickettsia; Piroplasm; Tick species; Tick-borne pathogens; Xinjiang.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was approved by the Scientific Ethics Committee of Huazhong Agricultural University. Written informed consent was obtained from herders and farm owners prior to sampling. All procedures strictly adhered to the noninvasive principle, ensuring that host animals (cattle and sheep) experienced no additional harm or stress during the process. Ticks were collected solely through superficial examination and mechanical removal from the epidermis of the animal. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Ticks collected across various regions in Xinjiang, China. In the figure, circular markers indicate sampling sites, with each color corresponding to a distinct tick species
Fig. 2
Fig. 2
Phylogenetic analysis of tick species based on 16S rRNA gene sequences. Phylogenetic tree was conducted using the neighbor-joining method under the Tamura 3-parameter model. The robustness of the tree topology was assessed through bootstrap analysis with 1000 pseudoreplicates. In the figure, the purple, green, yellow, pink, red–brown, and blue regions represent species of the Hyalomma, Rhipicephalus Dermacentor, Haemaphysalis, Ixodes, and Argasidae genera, respectively. Outgroup taxa are labeled in blue text. Bootstrap values are indicated by blue dots on the branches, with dot size proportional to the bootstrap support value (larger dots indicate higher support)
Fig. 3
Fig. 3
Haplotype phylogenetic tree (a) and network (b) of Hy. asiaticum based on 16S rRNA gene sequences. a Hap_5 and Hap_9, which were derived from the same population, are indicated by the same color, while other haplotypes, representing distinct populations, are displayed in different colors. b Haplotype network depicting the distribution of haplotypes across populations, with each color corresponding to a unique population. The size of each circle is proportional to the frequency of the respective haplotype. Transverse lines on the network represent a gene mutation site
Fig. 4
Fig. 4
Phylogenetic analysis of piroplasms based on 18S rRNA gene sequences. The phylogenetic tree was constructed using the neighbor-joining method under the Tamura–Nei parameter model. Sequences obtained from this study are highlighted with red circles in the tree
Fig. 5
Fig. 5
Phylogenetic analysis of Anaplasma based on 16S rRNA gene sequences. The phylogenetic tree was constructed using the neighbor-joining method under the Kimura two-parameter model. Red triangles indicate sequences obtained from this study
Fig. 6
Fig. 6
Phylogenetic analysis of Rickettsia based on ompA gene sequences. The phylogenetic tree was performed using the neighbor-joining method under the Tamura three-parameter model. Red diamonds indicate sequences obtained from this study

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