Evaluation and Performance of Rapid Methods for Identifying and Tracking Sources of Fecal Pollution in Coastal Watersheds

Fecal contamination of coastal waters is known to degrade the environment and poses a health risk to recreational beach users. Fecal indicator bacteria (FIB) are used around the world to assess water quality and characterize fecal contamination. Elevated levels of FIB have been linked to health risks in epidemiological studies. However, some limitations exist with this indicator. FIB cannot be used to identify the specific sources as they originate from both human and animal sources. FIB may also persist and regrow in the environment. In order to effectively remediate the cause of pollution and characterize the hazards at chronically impaired beaches it is necessary to measure indicators that can provide information about the sources of the general fecal pollution. Tracking pollution sources at impaired beaches is critical to ensuring the health of coastal watersheds and reducing the incidence of swimming related illness. Molecular methods have gained popularity to identify and detect sources of fecal contamination using host-associated markers. The work presented here addresses areas warranting further research in the state of the science of water quality monitoring. In Chapter 2, we demonstrate that host-associated markers exhibit similar limits of detection in different water types and are robust in environmental field applications. Additionally, we provide a cost-benefit analysis and provide water quality managers with information supporting the inclusion of molecular methods in current monitoring practices. This body of work also presents novel methods for rapid and viability-based detection of recent fecal contamination with propidium monoazide (PMA-qPCR) and a field portable method covalently-linked IMS/ATP technique (Cov-IMS/ATP). In Chapters 3 and 4, we present results on optimization and specificity of the Cov-IMS/ATP. We evaluated the performance of Cov-IMS/ATP at three different watersheds for rapid quantification of enterococci, and show this method to be a robust tool in assessing water quality at complex sites. This work also addresses drawbacks of traditional qPCR to quantify viable fecal contamination. We validate the PMA-qPCR method and demonstrate its performance in detecting recent fecal contamination in environmental waters. Use of these methods demonstrates a new framework that can enhance current microbial source tracking studies and water quality monitoring

Visualizing microbial pollution in Santa Monica Bay with Geographic Information Systems (GIS) and through field-testing a rapid, robust, field-portable water detection sensing system

Geographic Information Systems (GIS) is a powerful mapping tool that can be used to reveal spatial and temporal relationships of a criteria of interest. We have used GIS to visualize the seasonal and spatial distribution of microbial pollution obtained from the Heal the Bay beach water quality report (2007). These maps can be used to inform sampling decisions; more specifically, we can use it to identify areas of chronic pollution and can be used as a testbed for a rapid sensing system for bacteria. This rapid detection system can be used to provide higher resolution and understanding of water pollution as well as assist in understanding/characterizing environmental water quality in specific areas. We propose the subsequent use of an covalently-linked immumomagnetic separation/ATP quantification assay that is rapid, robust, and field-portable as an instrument to conduct monitoring of E. coli and Enterococcus in marine and freshwater systems

Disparate Antibiotic Resistance Gene Quantities Revealed across 4 Major Cities in California: A Survey in Drinking Water, Air, and Soil at 24 Public Parks.

Widespread prevalence of multidrug and pandrug-resistant bacteria has prompted substantial concern over the global dissemination of antibiotic resistance genes (ARGs). Environmental compartments can behave as genetic reservoirs and hotspots, wherein resistance genes can accumulate and be laterally transferred to clinically relevant pathogens. In this work, we explore the ARG copy quantities in three environmental media distributed across four cities in California and demonstrate that there exist city-to-city disparities in soil and drinking water ARGs. Statistically significant differences in ARGs were identified in soil, where differences in blaSHV gene copies were the most striking; the highest copy numbers were observed in Bakersfield (6.0 × 10-2 copies/16S-rRNA gene copies and 2.6 × 106 copies/g of soil), followed by San Diego (1.8 × 10-3 copies/16S-rRNA gene copies and 3.0 × 104 copies/g of soil), Fresno (1.8 × 10-5 copies/16S-rRNA gene copies and 8.5 × 102 copies/g of soil), and Los Angeles (5.8 × 10-6 copies/16S-rRNA gene copies and 5.6 × 102 copies/g of soil). In addition, ARG copy numbers in the air, water, and soil of each city are contextualized in relation to globally reported quantities and illustrate that individual genes are not necessarily predictors for the environmental resistome as a whole

Disparate Antibiotic Resistance Gene Quantities Revealed across 4 Major Cities in California: A Survey in Drinking Water, Air, and Soil at 24 Public Parks

Widespread prevalence of multidrug and pandrug-resistant bacteria has prompted substantial concern over the global dissemination of antibiotic resistance genes (ARGs). Environmental compartments can behave as genetic reservoirs and hotspots, wherein resistance genes can accumulate and be laterally transferred to clinically relevant pathogens. In this work, we explore the ARG copy quantities in three environmental media distributed across four cities in California and demonstrate that there exist city-to-city disparities in soil and drinking water ARGs. Statistically significant differences in ARGs were identified in soil, where differences in blaSHV gene copies were the most striking; the highest copy numbers were observed in Bakersfield (6.0 × 10-2 copies/16S-rRNA gene copies and 2.6 × 106 copies/g of soil), followed by San Diego (1.8 × 10-3 copies/16S-rRNA gene copies and 3.0 × 104 copies/g of soil), Fresno (1.8 × 10-5 copies/16S-rRNA gene copies and 8.5 × 102 copies/g of soil), and Los Angeles (5.8 × 10-6 copies/16S-rRNA gene copies and 5.6 × 102 copies/g of soil). In addition, ARG copy numbers in the air, water, and soil of each city are contextualized in relation to globally reported quantities and illustrate that individual genes are not necessarily predictors for the environmental resistome as a whole