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结合公民科学与基因组学,以单蜱分辨率研究蜱、病原体和共生微生物组。

Combining Citizen Science and Genomics to Investigate Tick, Pathogen, and Commensal Microbiome at Single-Tick Resolution.

作者信息

Chauhan Gaurav, McClure Jesse, Hekman Jessica, Marsh Patrick W, Bailey Jeffrey A, Daniels Rachel F, Genereux Diane P, Karlsson Elinor K

机构信息

Bioinformatics and Integrative Biology Program, University of Massachusetts Medical School, Worcester, MA, United States.

Vertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.

出版信息

Front Genet. 2020 Jan 21;10:1322. doi: 10.3389/fgene.2019.01322. eCollection 2019.

Abstract

The prevalence of tickborne diseases worldwide is increasing virtually unchecked due to the lack of effective control strategies. The transmission dynamics of tickborne pathogens are influenced by the tick microbiome, tick co-infection with other pathogens, and environmental features. Understanding this complex system could lead to new strategies for pathogen control, but will require large-scale, high-resolution data. Here, we introduce Project Acari, a citizen science-based project to assay, at single-tick resolution, species, pathogen infection status, microbiome profile, and environmental conditions of tens of thousands of ticks collected from numerous sites across the United States. In the first phase of the project, we collected more than 2,400 ticks wild-caught by citizen scientists and developed high-throughput methods to process and sequence them individually. Applying these methods to 192 ticks collected in a region with a high incidence of Lyme disease, we found that 62% were colonized by , the Lyme disease pathogen. In contrast to previous reports, we did not find an association between the microbiome diversity of a tick and its probability of carrying . However, we did find undescribed associations between carriage and the presence of specific microbial taxa within individual ticks. Our findings underscore the power of coupling citizen science with high-throughput processing to reveal pathogen dynamics. Our approach can be extended for massively parallel screening of individual ticks, offering a powerful tool to elucidate the ecology of tickborne disease and to guide pathogen-control initiatives.

摘要

由于缺乏有效的控制策略,全球蜱传疾病的流行率实际上在不受控制地上升。蜱传病原体的传播动态受到蜱微生物组、蜱与其他病原体的共同感染以及环境特征的影响。了解这个复杂的系统可能会带来病原体控制的新策略,但这需要大规模、高分辨率的数据。在这里,我们介绍螨类项目,这是一个基于公民科学的项目,以单蜱分辨率分析从美国各地众多地点收集的数以万计蜱的物种、病原体感染状况、微生物组概况和环境条件。在该项目的第一阶段,我们收集了公民科学家野外捕获的2400多只蜱,并开发了高通量方法对它们进行单独处理和测序。将这些方法应用于在莱姆病高发地区收集的192只蜱,我们发现62%被莱姆病病原体伯氏疏螺旋体定殖。与之前的报告相反,我们没有发现蜱的微生物组多样性与其携带伯氏疏螺旋体的概率之间存在关联。然而,我们确实发现了单个蜱体内伯氏疏螺旋体携带情况与特定微生物类群的存在之间存在未描述的关联。我们的研究结果强调了将公民科学与高通量处理相结合以揭示病原体动态的力量。我们的方法可以扩展到对单个蜱进行大规模平行筛选,为阐明蜱传疾病的生态学和指导病原体控制倡议提供一个强大的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e75a/6985576/2cd84a673db8/fgene-10-01322-g001.jpg

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