Microbial community profiling of sewage contamination in the Great Lakes

描述（由申请人提供）：五大湖的污水污染是一个主要的环境和人类健康威胁。五个劳伦特五大湖拥有超过1000个休闲海滩，并作为4000万人的饮用水源。污水溢流将含有有害生物和致病生物的复杂微生物种群引入支流和近岸沃茨。潜在的人类污水污染的水质监测通常依赖于可培养的粪便指示细菌的检测;这些方法不直接监测危险病原体的存在，也不区分人类和动物粪便污染源。这项建议将超越指示生物的分布。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细菌（包括潜在的人类病原体）的不同种类和相对丰度。我们的实验策略将描述核糖体RNA（rRNA）基因中快速进化的高变区，每个高变区都可以作为样品中微生物发生的代表。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。当用于查询来自约130，000种细菌的参考数据库时，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，我们将在污水污染的环境中遵循。我们将确定一系列微生物，这些微生物可以作为人类污水污染的标志。一些正在进行的研究提供了一个框架，用于解释全面的社区数据的背景下，人类病毒的测量，羽流扩散建模，粪便指示生物的分子和微生物测量。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人员和政府机构能够更好地预防和应对水传播疾病的威胁。公共卫生相关性：污水溢出会对饮用水质量和休闲海滩产生负面影响。目前检测粪便污染的方法不能区分污染源（人类或非人类），也不能直接证明致病微生物的存在。我们的项目将采用新的测序技术来创建一个污水衍生微生物的综合群落概况，从中将确定关键成员，这将提高我们检测和跟踪地表沃茨污水污染的能力。

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.