Microbial community profiling of sewage contamination in the Great Lakes

描述(申请人提供)：五大湖的污水污染是对环境和人类健康的重大威胁。五个劳伦斯五大湖拥有1000多个休闲海滩，是4000万人的饮用水来源。污水溢出将含有共生生物和病原体的复杂微生物种群引入支流和近岸水域。监测水质中潜在的人类污水污染通常依赖于可培养的粪便指示菌的检测；这种方法不直接监测危险病原体的存在，也不区分人类和动物的粪便污染源。这项提案将着眼于指示性生物体的分布。它将使用大规模并行的DNA测序策略来清点通过污水排放事件进入环境的不同种类和相对丰富的细菌(包括潜在的人类病原体)。我们的实验策略将表征核糖体RNA(RRNA)基因中快速演变的高变区，每个高变区都可作为样本中出现微生物的代理。使用大规模并行测序技术，我们将为每个样本生成30,000到225,000个标签序列。当对来自约130,000个细菌的参考数据库进行查询时，这些标签将识别细菌物种的分类亲和力和相对丰度。这些数据将产生全面的微生物群落概况，我们将在污水污染环境中遵循这些概况。我们将确定一系列微生物，这些微生物可以作为人类污水产生的污染的特征。一些正在进行的研究为在人类病毒测量、羽流扩散模型以及粪便指示生物的分子和微生物测量的背景下解释全面的群落数据提供了一个框架。这项工作的综合性和跨学科性质为研究生提供了一个独特的培训机会，让他们参与一个跨越微生物生态学和遗传学、微生物学、公共卫生和海洋学学科的项目。这项研究的结果将使负责保护我们的自然资源和保护公众健康的水资源管理者和政府机构能够更好地预防和应对水传播的疾病威胁。与公共健康相关：污水溢出会对饮用水质量和休闲海滩造成负面影响。目前检测粪便污染的方法没有区分污染源(人类或非人类)，也没有直接证明是否存在致病生物体。我们的项目将采用新的测序技术来创建污水衍生微生物的全面群落概况，从中确定关键成员，从而提高我们检测和跟踪地表水中污水污染的能力。

DESCRIPTION (provided by applicant): Sewage contamination in the Great Lakes is a major environmental and human health threat. The five Laurentian Great Lakes have over 1000 recreation beaches and serve as a drinking water source to 40 million people. Sewage overflows introduce complex microbial populations containing both commensal and pathogenic organisms into tributaries and near-shore waters. The monitoring of water quality for potential human sewage contamination usually relies on the detection of cultivable fecal indicator bacteria; such methods do not directly monitor the presence of dangerous pathogens, nor do they differentiate human from animal sources of fecal pollution. This proposal will look beyond the distribution of indicator organisms. It will use massively parallel, DNA sequencing strategies to inventory the different kinds and relative abundance of bacteria (including potential human pathogens) that enter the environment through sewage discharge events. Our experimental strategy will characterize rapidly evolving hypervariable regions in ribosomal RNA (rRNA) genes, each of which serves as a proxy for the occurrence of a microorganism in a sample. Using massively parallel sequencing technology we will generate between 30,000 and 225,000 tag sequences for each sample. When used as queries against a reference database from ~130,000 bacteria, these tags will identify the taxonomic affinity and relative abundance of bacterial species. These data will produce comprehensive microbial community profiles that we will follow in sewage contaminated environments. We will identify an array of microbes that can serve as signatures of human sewage derived pollution. Several ongoing studies provide a framework for interpreting comprehensive community data in the context of measurements of human viruses, plume dispersion modeling, and molecular and microbiological measurements of fecal indicator organisms. The integrative and interdisciplinary nature of this effort offers a unique training opportunity for graduate students to participate in a project that crosses the disciplines of microbial ecology and genetics, microbiology, public health, and oceanography. The results of this research will enable water resource managers and governmental agencies, charged with preservation of our natural resources and protection of public health, to better prevent and respond to waterborne disease threats. PUBLIC HEALTH RELEVANCE: Sewage overflows can negatively impact both drinking water quality and recreational beaches. Current methods to detect fecal pollution do not distinguish the source of pollution (human or non-human), nor do they directly demonstrate the presence of disease-causing organisms. Our project will employ new sequencing technologies to create a comprehensive community profile of sewage derived microorganisms, from which key members will be identified that will improve our ability to detect and track sewage contamination in surface waters.