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.

项目概要/摘要 当地来源的产志贺毒素大肠杆菌 (STEC) 会显着增加疾病风险； 然而，由于无法区分本地病例和非本地病例，无法全面描述本地病例 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。 利用系统流行病学阐明 STEC 维持和维持的途径和机制 为了实现这一目标，当前研究的总体目标是确定传播的特征。 与当地 STEC 传播相关的病原体、宿主和环境。 本地来源感染的 STEC 病例与外部菌株感染的病例明显不同 中心假设将通过追求三个具体目标来检验：1）区分和 表征本地传播的 STEC 菌株（O157 和非 O157），2) 识别宿主特征 与获取本地与非本地 STEC 菌株相关，以及 3) 确定环境特征 在目标 1 中，将使用结构化合并系统动力学模型来 生成从向明尼苏达州卫生部报告的病例中分离出的 STEC 菌株的系统发育 (MDH) 自 2016 年以来与明尼苏达州以外分离的菌株进行比较并可在 NCBI 上找到推断的位置。 树节点将用于将 STEC 菌株分类为局部或非局部。将使用广义线性模型来分类。 将应变特征整合到树中并确定它们对局部 MN STEC 有效性的影响 第二个目标将评估宿主特征的关联， 目标 3 中，包括年龄、性别和潜在暴露与本地与非本地 STEC 之间的关联。 将估计物理和社会环境的特征以及当地 STEC 传播 为了实现这些目标，PI 博士 Gillian Tarr 将获得高级学位。 生物信息学和系统动力学建模方面的培训也将增强她的知识。 食品生产和分配系统，并进一步发展她的研究管理技能。 食品安全研究的历史以及与 MDH 的合作，明尼苏达大学提供了最佳的 本研究的导师团队拥有生物信息学和应用方面的专业知识。 系统发育建模，包括 STEC 和食品系统主题专家。 申请人认为，这是创新的，因为它将 1) 描述本地传输系统的特征，而无需 限制孤立的疫情爆发或使用近期旅行等代理手段，以及 2) 采用结构化联合行动 尚未在任何类似的疾病系统中用于此目的的模型。 识别输入性病例的传播情况并确定本地病例的宿主、病原体和环境特征 传输是一个重大贡献，因为它使得特定的假设得以发展和测试 当地水库和传播途径，然后可以针对这些目标采取量身定制的干预措施。