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Phylogeographic dynamics of tick-borne pathogens

蜱传病原体的系统发育地理学动态

基本信息

批准号：
10630808
负责人：
Dustin Brisson
金额：
$ 46.7万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2024-05-31
项目状态：
已结题

项目摘要

Vector-borne diseases are one of the most prevalent types of emerging infectious diseases worldwide and are a major threat to public health. Our collaborative team has used our extraordinary set of samples - which were collected during the time and space of a rapid range expansion of Ixodes scapularis ticks - to elucidate the environmental and climatic factors that facilitated the emergence of this disease vector in the Northeastern United States. The proposed research aims are to identify the patterns of, and processes affecting, the population dynamics of three important emerging human pathogens - Borrelia burgdorferi, Anaplasma phagocytophilum, and Babesia microti -by analyzing genome sequences in coalescent-based, phylodynamic analytical frameworks. The biological, environmental, and technical knowledge we have acquired, along with our ever-expanding sample set (75,887 tick samples from 515 sites over 14 years), provides a powerful system to identify environmental factors affecting the demography of these pathogens. We propose to use this dataset to (a) determine the current and historical dynamic patterns of 3 tick-borne pathogens; (b) identify and quantify the influence of environmental features on the demography of each microbial species; and (c) use prospective sampling to validate demographic models and the influence of environmental factors on migration and population growth. Characterizing the environmental factors that affect the demography of emerging pathogens at very fine scales is achievable through the application of sophisticated analyses to populations of genomes. To this end, we developed the selective whole genome amplification (SWGA) technique to generate sufficient quantities of microbial genomic DNA for next generation sequencing. Using this enabling technology, we can sequence hundreds of microbial genomes in order to develop mechanistic models describing how environmental factors impact migration and population growth; few examples are known of the functional bases determining the rates and directions of dispersal of pathogens in nature. The proposed phylogeographic diffusion modeling framework is ideally suited to assess how each species is geographically structured and to identify the environmental features associated with migration and growth. We will utilize the results of our proposed studies to develop and experimentally validate models that estimate future disease spread into novel environments. Uncovering common biotic and abiotic factors that influence the distribution and abundance of, and thus disease risk from, all of these vector-borne pathogens is immediately applicable to disease control strategies.

病媒传播的疾病是世界范围内最流行的新出现的传染病类型之一，是对公共健康的主要威胁。我们的合作团队使用了我们的一组非凡的样本--这些样本是在肩膀硬蜱活动范围迅速扩大的时间和空间收集的--以阐明促进这种疾病媒介在美国东北部出现的环境和气候因素。拟议的研究目的是通过在基于聚合的系统动力学分析框架中分析基因组序列，确定三种重要的人类新出现病原体-伯氏疏螺旋体、无浆体吞噬细胞性和微小巴贝斯虫-的种群动态的模式和影响过程。我们所获得的生物学、环境和技术知识，以及我们不断扩大的样本集(14年来来自515个地点的75,887个扁虱样本)，提供了一个强大的系统来识别影响这些病原体人口统计学的环境因素。我们建议使用这一数据集来(A)确定3种由壁虱传播的病原体的当前和历史动态模式；(B)识别和量化环境特征对每个微生物物种的人口学的影响；以及(C)使用前瞻性抽样来验证人口模型以及环境因素对迁移和人口增长的影响。通过对基因组群体进行复杂的分析，可以在非常精细的尺度上确定影响新出现病原体人口统计的环境因素。为此，我们开发了选择性全基因组扩增(SWGA)技术，以产生足够数量的微生物基因组DNA，用于下一代测序。使用这种使能技术，我们可以对数百个微生物基因组进行测序，以开发描述环境因素如何影响迁徙和人口增长的机制模型；很少有人知道决定病原体在自然界中传播速度和方向的功能基础的例子。拟议的系统地理扩散模拟框架非常适合于评估每个物种的地理结构，并确定与迁徙和生长相关的环境特征。我们将利用我们提议的研究结果来开发和实验验证估计未来疾病传播到新环境的模型。揭示共同的生物和非生物因素，影响所有这些病媒传播病原体的分布和丰度，从而产生疾病风险，立即适用于疾病控制战略。

项目成果

期刊论文数量（24）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Epidemiology and Spatial Emergence of Anaplasmosis, New York, USA, 2010‒2018.

DOI：
10.3201/eid2708.210133
发表时间：
2021-08
期刊：
Emerging infectious diseases
影响因子：
11.8
作者：
Russell A;Prusinski M;Sommer J;O'Connor C;White J;Falco R;Kokas J;Vinci V;Gall W;Tober K;Haight J;Oliver J;Meehan L;Sporn LA;Brisson D;Backenson PB
通讯作者：
Backenson PB

Heartland Virus Transmission, Suffolk County, New York, USA.

DOI：
10.3201/eid2712.211426
发表时间：
2021-12
期刊：
Emerging infectious diseases
影响因子：
11.8
作者：
Dupuis AP 2nd;Prusinski MA;O'Connor C;Maffei JG;Ngo KA;Koetzner CA;Santoriello MP;Romano CL;Xu G;Ribbe F;Campbell SR;Rich SM;Backenson PB;Kramer LD;Ciota AT
通讯作者：
Ciota AT

Identification and characterization of novel lineage 1 Powassan virus strains in New York State.

纽约州的新谱系1 Powassan病毒菌株的识别和表征。

DOI：
10.1080/22221751.2022.2155585
发表时间：
2023-12
期刊：
EMERGING MICROBES & INFECTIONS
影响因子：
13.2
作者：
Lange, Rachel E.;Dupuis II, Alan P.;Prusinski, Melissa A.;Maffei, Joseph G.;Koetzner, Cheri A.;Ngo, Kiet;Backenson, Bryon;Oliver, JoAnne;Vogels, Chantal B. F.;Grubaugh, Nathan D.;Kramer, Laura D.;Ciota, Alexander T.
通讯作者：
Ciota, Alexander T.

A fast machine-learning-guided primer design pipeline for selective whole genome amplification.