Phylodynamics of Shiga Toxin-Producing Escherichia coli from Local Sources

本地产志贺毒素大肠杆菌的系统动力学

• 批准号: 10616754
• 负责人: Gillian Tarr
• 金额: $ 13.76万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-02 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10616754
• 关键词: Accounting; Age; Animals; Area; Bioinformatics; Canada; Case Mixes; Case Study; Cattle; Characteristics; Child; Classification; Collaborations; Data; Deer; Detection; Development; Disease; Disease Outbreaks; Environment; Environmental Pollution; Epidemiology; Escherichia coli; Escherichia coli EHEC; Escherichia coli Infections; Escherichia coli O157:H7; Exposure to; Farm; Food; Food Safety; Food Supply; Food production; Future; Genes; Genomics; Genotype; Goals; Health; Human; Infection; Intervention; Investigation; Knowledge; Linear Models; Location; Maintenance; Mentorship; Meta-Analysis; Mexico; Milk; Minnesota; Modeling; National Institute of Allergy and Infectious Disease; Outcome; Pathway interactions; Persons; Phylogenetic Analysis; Phylogeny; Physical environment; Population; Population Density; Population Sizes; Production; Proxy; Public Health; Recording of previous events; Reporting; Research; Risk; Risk Factors; Route; Ruminants; Sheep; Shiga Toxin; Social Environment; Source; Structure; System; Testing; Training; Travel; Trees; Universities; Virulence Factors; Visit; Water; Weather; Work; density; design; disorder control; disorder risk; epidemiological model; food desert; foodborne pathogen; innovation; insight; migration; pathogen; population migration; public health intervention; rural environment; segregation; sex; skills; source localization; stem; transmission process

PROJECT SUMMARY/ABSTRACT Local sources of Shiga toxin-producing Escherichia coli (STEC) contribute significantly to disease risk; however, inability to differentiate local from non-local cases has precluded full characterization of local transmission systems. The long-term goal of this research is to develop targeted public health interventions using systems epidemiology to elucidate the pathways and mechanisms of STEC maintenance and transmission. In pursuit of this goal, the overall objective of the current study is to identify characteristics of pathogen, host, and environment associated with local STEC transmission. The central hypothesis is that STEC cases infected from local sources are significantly different than those infected by strains from outside the case’s local area. The central hypothesis will be tested by pursuing three specific aims: 1) differentiate and characterize locally transmitted STEC strains, both O157 and non-O157, 2) identify host characteristics associated with acquiring local vs. non-local STEC strains, and 3) identify environmental characteristics associated with local transmission. In aim 1, a structured coalescent phylodynamic model will be used to generate a phylogeny of STEC strains isolated from cases reported to the Minnesota Department of Health (MDH) since 2016 compared to strains isolated outside MN and available on NCBI. The inferred location of tree nodes will be used to classify STEC strains as local or non-local. A generalized linear model will be used to integrate strain characteristics into the tree and determine their influence on the local MN STEC effective population size and migration rates. The second aim will assess the association of host characteristics, including age, sex, and potential exposures, with local vs. non-local STEC. In aim 3, the association between characteristics of the physical and social environment and local STEC transmission will be estimated accounting for spatial correlation. To accomplish these aims, PI Dr. Gillian Tarr will obtain advanced training in bioinformatics and phylodynamic modeling. Dr. Tarr will also enhance her knowledge of food production and distribution systems and further develop her research management skills. With a long history of food safety research and collaboration with MDH, the University of Minnesota provides the optimal environment for this research. The mentorship team has expertise in bioinformatics and applied phylogenetic modeling and includes STEC and food systems subject matter experts. The proposed research is innovative, in the applicants’ opinions, because it will 1) characterize local transmission systems without restriction to isolated outbreaks or use of proxies such as recent travel, and 2) employ a structured coalescent model that has not been applied for this purpose in any comparable disease system. Differentiating local transmission from imported cases and identifying the host, pathogen, and environment characteristics of local transmission is a significant contribution, because it enables specific hypotheses to be developed and tested for local reservoirs and transmission pathways, which can then be targeted by tailored interventions.

项目摘要/摘要 产生志贺毒素大肠杆菌（STEC）的局部来源对疾病的风险产生了重大贡献。 但是，无法区分局部与非本地案件的全部表征 传输系统。这项研究的长期目标是制定有针对性的公共卫生干预措施 使用系统流行病学来阐明STEC维护的途径和机制 传播。为了实现这一目标，当前研究的总体目标是确定 病原体，宿主和与局部STEC传播相关的环境。中心假设是 从当地来源感染的STEC病例与外面菌株感染的病例显着不同 案件的当地。中央假设将通过追求三个具体目标来检验：1）区分和 表征O157和非O157的局部传播STEC菌株，2）识别宿主特征 与获取本地与非本地STEC菌株相关，3）确定环境特征 与本地传输相关。在AIM 1中，结构化合并系统动力学模型将用于 从报告给明尼苏达州卫生部的病例中分离出的STEC菌株的系统发育 （MDH）自2016年以来与在MN外隔离并在NCBI上可用的菌株相比。推断的位置 树节点将用于将STEC菌株分类为局部或非本地菌株。广义线性模型将用于 将应变特性整合到树中，并确定它们对本地MN STEC有效的影响 人口规模和迁移率。第二个目标将评估宿主特征的关联， 包括年龄，性别和潜在的暴露，包括本地与非本地性STEC。在AIM 3中， 将估计物理和社会环境以及本地STEC传输的特征 考虑空间相关性。为了实现这些目标，PI Gillian Tarr博士将获得高级 生物信息学和系统动力学建模的培训。塔尔博士还将增强她对 粮食生产和分销系统，并进一步发展她的研究管理技能。长时间 与MDH的食品安全研究与合作历史，明尼苏达大学提供了最佳 这项研究的环境。 Mentalship团队在生物信息学方面具有专业知识，并应用了 系统发育建模，包括STEC和食品系统主题专家。拟议的研究是 在申请人的意见中，创新性，因为它将1）在没有本地传输系统的情况下没有 限制孤立的爆发或使用诸如最近旅行之类的代理人，以及2）员工一个结构化的结合 在任何可比疾病系统中尚未用于此目的的模型。区分本地 从进口案例传播并识别局部的宿主，病原体和环境特征 传输是重要的贡献，因为它可以开发和测试特定的假设 对于本地储层和传输途径，然后可以通过量身定制的干预措施来靶向。