Comparison of Microbial and Chemical Source Tracking Markers To Identify Fecal Contamination Sources in the Humber River (Toronto, Ontario, Canada) and Associated Storm Water Outfalls

Abstract

Storm water runoff is a major source of pollution, and understanding the components of storm water discharge is essential to remediation efforts and proper assessment of risks to human and ecosystem health. In this study, culturable Escherichia coli and ampicillin-resistant E. coli levels were quantified and microbial source tracking (MST) markers (including markers for general Bacteroidales spp., human, ruminant/cow, gull, and dog) were detected in storm water outfalls and sites along the Humber River in Toronto, Ontario, Canada, and enumerated via endpoint PCR and quantitative PCR (qPCR). Additionally, chemical source tracking (CST) markers specific for human wastewater (caffeine, carbamazepine, codeine, cotinine, acetaminophen, and acesulfame) were quantified. Human and gull fecal sources were detected at all sites, although concentrations of the human fecal marker were higher, particularly in outfalls (mean outfall concentrations of 4.22 log₁₀ copies, expressed as copy numbers [CN]/100 milliliters for human and 0.46 log₁₀ CN/100 milliliters for gull). Higher concentrations of caffeine, acetaminophen, acesulfame, E. coli, and the human fecal marker were indicative of greater raw sewage contamination at several sites (maximum concentrations of 34,800 ng/liter, 5,120 ng/liter, 9,720 ng/liter, 5.26 log₁₀ CFU/100 ml, and 7.65 log₁₀ CN/100 ml, respectively). These results indicate pervasive sewage contamination at storm water outfalls and throughout the Humber River, with multiple lines of evidence identifying Black Creek and two storm water outfalls with prominent sewage cross-connection problems requiring remediation. Limited data are available on specific sources of pollution in storm water, though our results indicate the value of using both MST and CST methodologies to more reliably assess sewage contamination in impacted watersheds.

Importance: Storm water runoff is one of the most prominent non-point sources of biological and chemical contaminants which can potentially degrade water quality and pose risks to human and ecosystem health. Therefore, identifying fecal contamination in storm water runoff and outfalls is essential for remediation efforts to reduce risks to public health. This study employed multiple methods of identifying levels and sources of fecal contamination in both river and storm water outfall sites, evaluating the efficacy of using culture-based enumeration of E. coli, molecular methods of determining the source(s) of contamination, and CST markers as indicators of fecal contamination. The results identified pervasive human sewage contamination in storm water outfalls and throughout an urban watershed and highlight the utility of using both MST and CST to identify raw sewage contamination.

FIG 1

Box plots of (A) culturable E. coli and (B) Amp^r E. coli at each sampling site. Box plots show the median E. coli concentration between the 25th and 75th data quartiles; whiskers extend to the outermost data point within ±1.5 data points of this interquartile range. Open circles depict outlier values.

FIG 2

Box plots of human and gull qPCR marker concentrations for each site. Box plots show the median E. coli concentration between the 25th and 75th data quartiles; whiskers extend to the outermost data point within ±1.5 data points of this interquartile range. Open circles depict outlier values. WWTP, wastewater treatment plant.

FIG 3

Mean inverse cycle thresholds obtained using qPCR arrays with targets for (A) human and (B) gull and Canada goose.

FIG 4

Box plots of (A) caffeine, (B) cotinine, (C) acetaminophen, (D) acesulfame, and (E) carbamazepine for each site. Box plots show the median E. coli concentration between the 25th and 75th data quartiles; whiskers extend to the outermost data point within ±1.5 data points of this interquartile range. Open circles depict outlier values, and asterisks depict extreme values.