Date of Award

11-5-2020

Publication Type

Master Thesis

Degree Name

Ph.D.

Department

Great Lakes Institute for Environmental Research

Keywords

Freshwater, Great Lakes, Metabarcoding, Metatranscriptomics, Microbial community dynamics, Pathogens

Supervisor

Daniel Heath

Supervisor

Subba Rao Chaganti

Rights

info:eu-repo/semantics/openAccess

Abstract

The Laurentian Great Lakes (LGLs) represent the single most valuable natural resource on the North American continent and are a critical source of drinking water, important aquatic species habitat, water for the industrial sector and tourism/recreational activities as well as many other ecological services. LGLs ecosystems are changing rapidly due to climate change effects and are thus highly susceptible and responsive to any added anthropogenic stressors. The aquatic bacterial community affects critical ecosystem functions, such as nutrient cycling, water quality, recreational activities, etc., in ecosystems such as the LGLs, but perturbations can alter both the composition and functionality of the bacterial community. These changes can result in negative effects on whole ecosystem health with an associated loss in economic and social values. Understanding the temporal and spatial variation in the composition, diversity and ultimately activity of the bacterial community is paramount in understanding overall ecosystem services providing by the bacterial community. Characterizing spatial and temporal variation (and the factors that contribute to it) can provide deeper insight into the processes and mechanisms operating in LGLs ecosystems, and ultimately improve our basic knowledge and ability to predict bacterial community composition, dynamics and function. Enumeration of Escherichia coli as a bioindicator of human fecal contamination is widely used to quantify recreational water quality and safety. The inclusion of microbial source tracking (MST) as part of water quality monitoring along with E. coli and waterborne pathogens in a novel monitoring tool could help to determine the specific fecal source (e.g. human, dog, cattle, wildlife, etc.) and has great potential for accurate estimation of water-related health risks. On the other hand, we still have an incomplete understanding of freshwater microbial ecology and community dynamics and their response to disturbance, particularly to human-related environmental stressors. We must be able to predict and track the sources of harmful bacterial outbreaks; this will require a clear understanding of the impact of environmental and anthropogenic stressors on microbial community diversity and function. The research comprising this dissertation was designed to characterize broad to fine-scale temporal and spatial variation in freshwater bacterial community composition and gene transcription. Temporal variation in freshwater bacterial community composition (bi-hourly, monthly and seasonal variation) and gene transcription profile (seasonally) was significant while spatial variation was significant but limited in magnitude. A novel monitoring approach (nanofluidic TaqMan qRT-PCR) was designed and optimized for rapid and reliable monitoring of freshwater quality for waterborne pathogens, MST markers and E. coli as a bioindicator of fecal contamination. Finally, an experimental bacterial microcosm study was used to study the response of adapted (pre-exposure to different levels of nutrient stress) bacteria communities to very high nutrient stress. This experiment revealed that pre-exposure to a higher level of nutrient stress provides greater protection against community change than low levels when the bacterial community is challenged with a very high level of a stressor. These cumulative insights into the temporal and spatial variation of the freshwater bacteria community composition and transcriptome, the development of a novel nanofluidic TaqMan qRT-PCR tool for detecting and quantifying harmful bacteria and our microcosm study outcomes provide baseline knowledge and tools which will be valuable for improving best management practices, monitoring and accurate prediction of changes in freshwater ecosystem function.

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