Date of Award

December 2022

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Freshwater Sciences

First Advisor

Ryan J Newton

Committee Members

Troy A Skwor, Sandra L McLellan, Patrick J McNamara, Mark J McBride

Keywords

antibiotic resistance, bioinformatics, freshwater science, public health, urban ecology, wastewater treatment

Abstract

Municipal sewage provides a glimpse into the health and activities of a human society. For more than a century, sewage exploration has helped expose the sources of disease outbreaks and track disease progression over time. Recent advancements in wastewater surveillance born from the COVID-19 pandemic have potential to enhance mitigation efforts against the decades-long global health crisis of microbial antibiotic resistance. However, critical knowledge gaps exist in wastewater surveillance, stemming from a lack of understanding in sewer microbial ecology. Ecology reveals trends in how communities respond and adapt to change, which has far-reaching implications for identifying effective strategies for disease control. However, with little knowledge about sewer microbial communities, including its residents, community dynamics, and functions, no baseline picture of the sewer microbiome exists. The goal of this dissertation was to characterize the sewer microbiome using an ecological approach. The specific aims were to determine if (1) microbial communities in urban wastewater exhibit seasonal patterns in assembly; (2) if seasonal community assembly is driven by environmental bacteria responding to changes in water temperature; and (3) if temperature-driven communities modulate the composition and abundance of antibiotic resistance genes in wastewater. Results show that microbes in sewers have seasonal community dynamics akin to other natural environments, and they have adapted to this stressful environment by acquiring and maintaining mechanisms of antibiotic resistance. Using only well-established methods in DNA sequencing and analyzing a wastewater dataset covering expansive temporal and spatial scales, this dissertation builds the foundation of a baseline sewer microbiome in the United States. All data collected and analyses used were made publicly available to aid standardizing methods in global strategy plans. Together, standardizing methods and sharing data related to the sewer microbiome will improve predictive models, guide interventions, and make other public health breakthroughs in wastewater surveillance.

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