Phylogeographic dynamics of tick-borne pathogens

蜱传病原体的系统发育地理学动态

• 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
• 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
• 来源: https://reporter.nih.gov/project-details/10630808
• 关键词: Affect; Anaplasma phagocytophilum; Babesia microti; Biological; Black-legged Tick; Borrelia burgdorferi; Data Set; Demography; Diffusion; Disease; Disease Vectors; Ecology; Emerging Communicable Diseases; Environment; Environmental Risk Factor; Evolution; Future; Genome; Genomic DNA; Geography; Growth; Knowledge; Modeling; Nature; New England; Pattern; Population; Population Dynamics; Population Growth; Process; Public Health; Research; Sampling; Site; Structure; System; Techniques; Technology; Ticks; Time; Vector-transmitted infectious disease; base; climatic factors; disorder control; disorder risk; emerging human pathogen; emerging pathogen; insight; microbial; microbial genome; microbial genomics; migration; next generation sequencing; novel; pathogen; prospective; tick-borne pathogen; vector-borne pathogen; whole genome

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.

病媒传染病是世界范围内最流行的新型传染病之一，是对公共卫生的主要威胁。我们的合作团队使用了我们非凡的样本集-这些样本是在肩突硬蜱迅速扩大范围的时间和空间中收集的-来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。拟议的研究目标是确定模式，和过程影响，人口动态的三个重要的新兴人类病原体-伯氏疏螺旋体，嗜吞噬细胞无形体，和Babeidae microti -通过分析基因组序列在聚结为基础的，微动态的分析框架。我们获得的生物，环境和技术知识，沿着我们不断扩大的样本集（14年来来自515个地点的75，887个蜱样本），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。我们建议使用该数据集来（a）确定3种蜱传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统计学的影响;（c）使用前瞻性采样来验证人口统计学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描述影响新出现病原体人口统计学的环境因素。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。利用这项技术，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移和人口增长的机制模型;很少有例子表明功能基础决定了自然界中病原体的传播速度和方向。拟议的生态地理扩散模型框架非常适合评估每个物种的地理结构，并确定与迁移和增长相关的环境特征。我们将利用我们提出的研究结果来开发和实验验证模型，估计未来疾病传播到新的环境中。揭示影响所有这些病媒传播病原体的分布和丰度以及由此产生的疾病风险的常见生物和非生物因素，可立即适用于疾病控制战略。

项目成果

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

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.

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

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

• DOI: 10.1371/journal.pcbi.1010137
• 发表时间: 2023-04
• 期刊: PLoS computational biology
• 影响因子: 4.3

Host phenology can drive the evolution of intermediate virulence strategies in some obligate-killer parasites.

• DOI: 10.1111/evo.14507
• 发表时间: 2022-06
• 期刊: Evolution; international journal of organic evolution