Announcing a new article publication for Zoonoses journal. Ticks are parasitic organisms that can transmit a wide range of pathogenic microorganisms. They are the second most common vectors of diseases affecting humans and animals. The occurrence and transmission of tick-borne diseases has recently shown increasing or fluctuating trends. DNA was extracted after the collection of tick samples. A library targeting the V4 hypervariable region of the 16S rRNA gene was constructed. After quality control, next-generation sequencing was performed with the Illumina NextSeq platform to analyze microbial diversity within the ticks. Samples were gathered between May 2023 and July 2023. A total of 77 ticks from five distinct regions were selected for next-generation sequencing. Molecular identification confirmed that all sequenced samples belonged to Haemaphysalis longicornis.
The most abundant bacteria belonged to the phylum Proteobacteria, which was present in all samples. Variations in sample richness and evenness were observed among sampling sites (Shannon index, P = 0.019). The bacterial diversity in LT exhibited the highest value, with an average of 2.449. Rickettsia and Coxiella were the predominant bacterial species, both of which are classified as tick-borne pathogens. The linear discriminant analysis effect size revealed significant differences in microbial composition among groups, except for the PC and LY groups, and identified distinct biomarkers for each group.
The findings indicate the high relative abundance of both pathogenic bacteria and non-pathogenic endosymbionts in H. longicornis and the potential for pathogen transmission to residents. However, further validation through human case studies is necessary. Health care providers should be aware of the possibility of the occurrence of these diseases.
Read More: https://www.scienceopen.com/hosted-document?doi=10.15212/ZOONOSES-2024-0027
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eISSN 2737-7474
ISSN 2737-7466
Yuhua Wang, Zhenhua Lu and Linli Xu et al. Microbial Composition of Haemaphysalis longicornis in Shaanxi Province, Determined Through Next-Generation Sequencing. Zoonoses. 2024. Vol. 4(1). DOI: 10.15212/ZOONOSES-2024-0027