RUI: Dynamics of Genomic Mosaicism in Non-Host Associated Escherichia Populations

该项目旨在解决流域中的大肠杆菌是否可以作为水平基因转移到宿主相关菌株(如已知的人类感染源)的宿主相关菌株的储存库。通过处理过的污水、畜牧业、野生动物、家禽以及城市和农业环境中的沉积物径流，流域可能会受到大肠杆菌的污染。几项研究表明，大肠杆菌可能会适应并保持在这些环境中，最终可能会将新特征的基因传递给与宿主相关的菌株，如大肠杆菌。除了检验这一想法外，这项研究的数据还将使更广泛的科学界能够评估现有的水质监测方法。本项目的研究将通过基于课程的研究体验(Cres)整合到STEM领域的本科生真实的研究体验中。特别是一年级和高级实验室的本科生将积极参与该项目的所有方面。该项目侧重于两个相关的科学目标：1)表征环境来源的大肠杆菌分离株的基因组多样性，以了解自然发生的种群随时间的变化；以及2)将16S群落调查的轮廓与观察到的大肠杆菌分离株基因组的变化和分水岭中的环境变化联系起来。通过分析具有代表性的全序列基因组对大肠杆菌进行的全球性研究，以及通过数百个临床分离株的基因组草稿序列对病原体亚型进行的有针对性的研究，已经成为显著的遗传多样性的特征。基因组数据的优势来自临床和宿主相关环境。该项目产生了720个环境来源的大肠杆菌分离株的基因组草稿序列。这些纵向数据可以通过基因组内容、排列和单核苷酸多态的比较基因组学来检验关于自然发生的非寄主相关种群的基因组结构和遗传交换的假设。这些数据说明了大肠杆菌种群在非宿主环境中的长期持久性，有可能成为水体中粪便指示菌基因交换和更新的储存库。寡核苷酸分型将评估大肠杆菌种群的多样性；水样将产生耦合的分离基因组序列和微生物群落16S rRNA序列。有人断言，16S rRNA的单核苷酸变化代表了基因组结构的多样性；数据将被用来检验这一断言。精细采样产生纵向16S rRNA微生物群落图谱，用于了解大肠杆菌和其他微生物种群的变化。将16S rRNA变异与基因组变异联系起来的工作使仅基于16S rRNA调查的种群变化预测成为可能。高质量的娱乐和饮用水水源对社会至关重要，随着水质监测转向基于分子的方法，这里产生的数据集的类型对于确定有效和广泛适用的监测技术至关重要。第三个目标是通过个人和基于课程的研究经验(CRE)完全纳入STEM领域的本科生。超过100名课程的学生将获得真实研究的第一手知识。这些经验的有效性将通过融合的混合方法进行评估，这些方法旨在衡量学生对STEM领域的态度，比较个人研究经验和CRE对一年级和高水平学生的影响。

This project aims to address whether Escherichia from watersheds can serve as a reservoir for horizontal gene transfer to host-associated strains such as Escherichia coli, which is a known source of human infections. Watersheds can become contaminated with Escherichia via treated sewage, livestock farming, wild animals, fowl, and sediment runoff from urban and agricultural environments. Several studies revealed that Escherichia may adapt and persist in these environments, and eventually may be able to pass the genes for new traits to host-associated strains such as Escherichia coli. In addition to examining this idea, the data from this study will allow the broader scientific community to evaluate existing water quality monitoring methods. The research for this project will be integrated into authentic research experiences for undergraduate students in STEM fields through course-based research experiences (CREs). In particular, undergraduates in first year and upper level laboratories will actively participate in all aspects of the project.This project focuses on two related scientific goals: 1) characterizing genomic diversity of environmentally derived Escherichia isolates to understand variation in naturally occurring populations over time; and 2) linking profiles of 16S community surveys to observed variation in Escherichia isolate genomes and to environmental changes in a watershed. Remarkable genetic diversity has been characterized by global studies of E. coli through analysis of representative fully sequenced genomes, and targeted studies of pathogen sub-types through hundreds of draft genome sequences of clinical isolates. The preponderance of genomic data is from clinical and host-associated environments. This project produces 720 draft genome sequences of environmentally derived Escherichia isolates. The longitudinal data enable testing hypotheses about genome structure and genetic exchange in naturally occurring, non-host-associated populations through comparative genomics of genome content, arrangement and single nucleotide polymorphisms. The data address long term persistence of Escherichia populations in non-host environments, potentially serving as reservoirs for genetic exchange and renewal of fecal indicator bacteria in bodies of water. Oligotyping will estimate diversity in the Escherichia populations; water samples will produce coupled isolate genome sequences and microbial community 16S rRNA sequences. It is asserted that single nucleotide changes in 16S rRNA represent diversity of genome structure; the data will be used to test this assertion. Fine scale sampling produces longitudinal 16S rRNA microbial community profiles used to understand changes in Escherichia and other microbial populations. Work linking 16S rRNA variation to genome variation enables prediction of population changes based on 16S rRNA surveys alone. High quality recreational and drinking water sources are essential for society, and as water quality monitoring shifts to molecular based approaches, the types of datasets produced here become critical to ascertaining effective and broadly applicable monitoring techniques. A third goal fully incorporates undergraduate students in STEM fields through individual and course-based research experiences (CREs). Over 100 students in courses will gain first-hand knowledge of authentic research. The effectiveness of these experiences will be assessed through convergent mixed methods approaches designed to gauge student attitudes toward STEM fields, comparing effects of individual research experiences and CREs on first year and upper level students.