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.
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.
