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