ArticleFrontiers in microbiology2024
Microbial community characteristics and pathogens detection in
Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
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Who cites it
4 citing papers in PubMed.
- High-risk HPV and bacterial STIs in a primary screening population in rural Hainan, China: prevalence, co-infection, and association with cervical abnormalities.Frontiers in public health · 2026Article
- Sexual and regional differences in the microbiome and functional metagenome of the lone star tick, Amblyomma americanum.Animal microbiome · 2025Article
- Tick species diversity, seasonality and feeding behavior in small wild mammals in the northern foothills of the Dabie Mountains, China.International journal for parasitology. Parasites and wildlife · 2025Article
- High Diversity and Prevalence of Rickettsial Agents inMicroorganisms · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Microbial communities significantly influence the vector capacity of ticks, which, along with tick-borne diseases, pose an increasing global threat. Due to the substantial individual variability caused by various factors, it is essential to assess tick microbial communities and vectorial capacities under different environmental conditions. However, there is a relative scarcity of research on the microbial communities and pathogen transmission of ticks in different physiological states and environmental conditions, especially in Hainan Island, southern China. Methods: From 2021 to 2022, we collected 4,167 tick samples, grouping them by blood meal status, developmental stage, sex, time, geographical location, and tick species. We selected 128 samples for full-length 16S rRNA sequencing to describe microbial community characteristics and identify potential biomarkers. Seven hundred seventy-two samples were tested for seven tick-borne pathogens ( Results: Blood meal status, developmental stage, sex, time, geographical location, and tick species significantly influenced the microbial communities of ticks. We observed distinct microbial community characteristics across different states. We noted the non-random replacement of stable and transient species, with functional differences between parasitic and engorged ticks mainly driven by transient species. Functionally, we observed three distinct response patterns: driven by stable species, transient species, and both together in response to the six factors. We identified 273 potential biomarkers (200 robust core species and 73 robust differential species). Six genera and eight species of pathogens were detected in ticks, with an overall positivity rate of 12.44% (96/772). Among humans, 18.27% (38/208) of serum samples were positive for at least one tick-borne pathogen IgG. Conclusion: Our findings indicate that these six factors significantly influence both tick microbial communities and vectorial capacity, with varying effects on vector competence for different pathogens and inconsistent impacts on microbial communities under different conditions. This study supplemented the understanding of tick microbial communities on Hainan Island, assessed the relatively high risk of tick-borne pathogens in the region, and evaluated the impact of these factors on both microbial communities and vectorial capacity.
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Registered trials
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 Socratic graph.