Title:
METAGENOMICS APPROACHES FOR IMPROVED WATER QUALITY MONITORING, MICROBIAL SOURCE TRACKING, AND PUBLIC HEALTH RISK ASSESSMENT
METAGENOMICS APPROACHES FOR IMPROVED WATER QUALITY MONITORING, MICROBIAL SOURCE TRACKING, AND PUBLIC HEALTH RISK ASSESSMENT
Author(s)
Suttner, Brittany
Advisor(s)
Konstantinidis, Kostas T.
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Abstract
Fecal contamination of water is a primary source of waterborne pathogens and is one of the most common impairments of water quality, affecting over a billion people worldwide. Because it is not practical to directly monitor the numerous pathogens that cause waterborne diseases, water quality and public health risk are assessed using fecal indicator bacteria (FIB) as proxies for pathogens. However, there are many known limitations associated with current methods that lead to inaccurate water quality and risk assessments, including low host-specificity and -sensitivity (e.g., not all members of a host type carry the marker), and false positive signals from “naturalized” populations of FIB that are commonly found in the extraenteric environment. Accordingly, identifying the source of fecal pollution (e.g., municipal sewage, livestock, or wildlife) remains challenging for current methods. To provide new, more robust biomarkers for microbial source tracking (MST), we used shotgun metagenomic sequencing to compare the decay kinetics of fecal microbes from different sources (i.e., cow, pigs, humans, and municipal sewage) in freshwater mesocosms simulating a pollution event. We identified several host-specific metagenome assembled genomes (MAGs) and functional genes as putative biomarkers for more robust MST and demonstrated the advantages of metagenomic methods over traditional qPCR and culture-based tests. Notably, the identified MAGs differed from the most commonly used FIB both taxonomically and functionally. Further, we provided evidence that FIB cannot be effectively distinguished from their naturalized counterparts based on our mesocosm incubations, an important limitation that is not applicable to the newly proposed MAGs. Finally, we applied our biomarkers and newly developed bioinformatics pipelines to time series metagenomics data from creek sediments in Salinas Valley (California) and showed that these sediment communities are robust against inputs from agricultural surface runoff and cattle ranching.
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Date Issued
2020-12-03
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Text
Resource Subtype
Dissertation