Using SWAT, Bacteroidales microbial source tracking markers, and fecal indicator bacteria to predict waterborne pathogen occurrence in an agricultural watershed

Developing the capability to predict pathogens in surface water is important for reducing the risk that such organisms pose to human health. In this study, three primary data source scenarios (measured stream flow and water quality, modelled stream flow and water quality, and host-associated Bacteroidales) are investigated within a Classification and Regression Tree Analysis (CART) framework for classifying pathogen (Escherichia coli 0157:H7, Salmonella, Campylobacter, Cryptosporidium, and Giardia) presence and absence (P/A) for a 178 km(2) agricultural watershed. To provide modelled data, a Soil Water Assessment Tool (SWAT) model was developed to predict stream flow, total suspended solids (TSS), total N and total P, and fecal indicator bacteria loads; however, the model was only successful for flow and total N and total P simulations, and did not accurately simulate TSS and indicator bacteria transport. Also, the SWAT model was not sensitive to an observed reduction in the cattle population within the watershed that may have resulted in significant reduction in E. coli concentrations and Salmonella detections. Results show that when combined with air temperature and precipitation, SWAT modelled stream flow and total P concentrations were useful for classifying pathogen P/A using CART methodology. From a suite of host-associated Bacteroidales markers used as independent variables in CART analysis, the ruminant marker was found to be the best initial classifier of pathogen P/A. Of the measured sources of independent variables, air temperature, precipitation, stream flow, and total P were found to be the most important variables for classifying pathogen P/A. Results indicate a close relationship between cattle pollution and pathogen occurrence in this watershed, and an especially strong link between the cattle population and Salmonella detections.

The occurrence and sources of Campylobacter spp., Salmonella enterica and Escherichia coli O157:H7 in the Salmon River, British Columbia, Canada

In this study, we wished to assess the prevalence and determine the sources of three zoonotic bacterial pathogens (Salmonella, Campylobacter, and Escherichia coli O157:H7) in the Salmon River watershed in southwestern British Columbia. Surface water, sewage, and animal faecal samples were collected from the watershed. Selective bacterial culture and PCR techniques were used to isolate these three pathogens and indicator bacteria from these samples and characterize them. Campylobacter was the most prevalent pathogen in all samples, followed by Salmonella, and E. coli O157:H7. E. coli O157:H7 and Salmonella isolation rates from water, as well as faecal coliform densities correlated positively with precipitation, while Campylobacter isolation rates correlated negatively with precipitation. Analysis of DNA extracted from water samples for the presence of Bacteroides host-species markers, and comparisons of C. jejuni flaA-RFLP types and Salmonella serovars from faecal and water samples provided evidence that human sewage and specific domestic and wild animal species were sources of these pathogens; however, in most cases the source could not be determined or more than one source was possible. The frequent isolation of these zoonotic pathogens in the Salmon River highlights the risks to human health associated with intentional and unintentional consumption of untreated surface waters.

Seasonal relationships among indicator bacteria, pathogenic bacteria, Cryptosporidium oocysts, Giardia cysts, and hydrological indices for surface waters within an agricultural landscape

The South Nation River basin in eastern Ontario, Canada is characterized by mixed agriculture. Over 1600 water samples were collected on a bi-weekly basis from up to 24 discrete sampling sites on river tributaries of varying stream order within the river basin between 2004 and 2006. Water samples were analyzed for: densities of indicator bacteria (Escherichia coli, Clostridium perfringens, enterococci, total and fecal coliforms), the presence of pathogenic bacteria (Listeria monocytogenes, E. coli O157:H7, Salmonella spp., Campylobacter spp.), and densities of parasite Giardia cysts and Cryptosporidium oocysts. Relationships between indicator bacteria, pathogens, and parasite oocysts/cysts were overall weak, seasonally dependent, site specific, but primarily positive. However, L. monocytogenes was inversely related with indicator bacteria densities. Campylobacter, Salmonella, Giardia cysts and Cryptosporidium oocysts were most frequently detected in the fall. E. coli O157:H7 was detected at a very low frequency. Exploratory decision tree analyses found overall that E. coli densities were the most utilitarian classifiers of parasite/pathogen presence and absence, followed closely by fecal coliforms, and to a lesser extent enterococci and total coliforms. Indicator bacteria densities that classified pathogen presence and absence groupings, were all below 100 CFU per 100 mL(-1). Microorganism relationships with rainfall indices and tributary discharge variables were globally weak to modest, and generally inconsistent among season, site and microorganism. But, overall rainfall and discharge were primarily positively associated with indicator bacteria densities and pathogen detection. Instances where a pathogen was detected in the absence of a detectable bacterial indicator were extremely infrequent; thus, the fecal indicators were conservative surrogates for a variety of pathogenic microorganisms in this agricultural setting. The results from this study indicate that no one indicator or simple hydrological index is entirely suitable for all environmental systems and pathogens/parasites, even within a common geographic setting. These results place more firmly into context that robust prediction and/or indicator utility will require a more firm understanding of microorganism distribution in the landscape, the nature of host sources, and transport/environmental fate affinities among pathogens and indicators.

Tracking host sources of Cryptosporidium spp. in raw water for improved health risk assessment

Recent molecular evidence suggests that different species and/or genotypes of Cryptosporidium display strong host specificity, altering our perceptions regarding the zoonotic potential of this parasite. Molecular forensic profiling of the small-subunit rRNA gene from oocysts enumerated on microscope slides by U.S. Environmental Protection Agency method 1623 was used to identify the range and prevalence of Cryptosporidium species and genotypes in the South Nation watershed in Ontario, Canada. Fourteen sites within the watershed were monitored weekly for 10 weeks to assess the occurrence, molecular composition, and host sources of Cryptosporidium parasites impacting water within the region. Cryptosporidium andersoni, Cryptosporidium muskrat genotype II, Cryptosporidium cervine genotype, C. baileyi, C. parvum, Cryptosporidium muskrat genotype I, the Cryptosporidium fox genotype, genotype W1, and genotype W12 were detected in the watershed. The molecular composition of the Cryptosporidium parasites, supported by general land use analysis, indicated that mature cattle were likely the main source of contamination of the watershed. Deer, muskrats, voles, birds, and other wildlife species, in addition to sewage (human or agricultural) may also potentially impact water quality within the study area. Source water protection studies that use land use analysis with molecular genotyping of Cryptosporidium parasites may provide a more robust source-tracking tool to characterize fecal impacts in a watershed. Moreover, the information is vital for assessing environmental and human health risks posed by water contaminated with zoonotic and/or anthroponotic forms of Cryptosporidium.

The development of a DNA microarray-based assay for the characterization of commercially formulated microbial products

Commercially formulated bioproducts containing a complex consortia of bacteria as an active ingredient pose a significant challenge for regulatory agencies and companies seeking to assess the safety and efficacy of these bioproducts. The main challenge stems from how to characterize the bacterial composition of these products, for which there is presently a lack of suitable methods. A prototype DNA microarray composed of oligonucleotide probes for functional genes, virulence factors, and taxonomic genes for a number of bacterial species was developed to examine the utility of microarray technology as a molecular tool for characterizing consortia bioproducts. The genomic DNA from four different products was extracted by two methods and examined with the microarray prototype and by denaturing gradient gel electrophoresis (DGGE). Although the identity of the consortial species remains unknown, the microarray assay provided unique and reproducible hybridization patterns for all four products, and agreed with the fingerprints generated by DGGE. The ability to differentiate between a variety of consortia products demonstrates that DNA microarrays have the potential to be a powerful tool in monitoring complex microbial communities.