Seasonal Assessment of Opportunistic Premise Plumbing Pathogens in Roof-Harvested Rainwater Tanks

A seasonal study on the occurrence of six opportunistic premise plumbing pathogens (OPPPs) in 24 roof-harvested rainwater (RHRW) tanks repeatedly sampled over six monthly sampling events (<i>n</i> = 144) from August 2015 to March 2016 was conducted using quantitative qPCR. Fecal indicator bacteria (FIB) <i>Escherichia coli</i> (<i>E. coli</i>) and <i>Enterococcus</i> spp. were enumerated using culture-based methods. All tank water samples over the six events were positive for at least one OPPP (<i>Legionella</i> spp., <i>Legionella pneumophila</i>, <i>Mycobacterium</i> avium, <i>Mycobacterium intracellulare</i>, <i>Pseudmonas aeruginosa</i>, or <i>Acanthamoeba</i> spp.) during the entire course of the study. FIB were positively but weakly correlated with <i>P. aeruginosa</i> (<i>E. coli</i> vs <i>P. aeruginosa</i> τ = 0.090, <i>p</i> = 0.027; <i>Enterococcus</i> spp. vs <i>P. aeruginosa</i> τ = 0.126, <i>p</i> = 0.002), but not the other OPPPs. FIBs were more prevalent during the wet season than the dry season, and <i>L. pneumophila</i> was only observed during the wet season. However, concentrations of <i>Legionell</i>a spp., <i>M. intracellulare</i>, <i>Acanthamoeba</i> spp., and <i>M. avium</i> peaked during the dry season. Correlations were assessed between FIB and OPPPs with meteorological variables, and it was determined that <i>P. aeruginosa</i> was the only OPPP positively associated with an increased antecedent dry period, suggesting stagnation time may play a role for the occurrence of this OPPP in tank water. Infection risks may exceed commonly cited benchmarks for uses reported in the rainwater usage survey such as pool top-up, and warrant further exploration through quantitative microbial risk assessment (QMRA)

Application of SourceTracker for Accurate Identification of Fecal Pollution in Recreational Freshwater: A Double-Blinded Study

The efficacy of SourceTracker software to attribute contamination from a variety of fecal sources spiked into ambient freshwater samples was investigated. Double-blinded samples spiked with ≤5 different sources (0.025–10% vol/vol) were evaluated against fecal taxon libraries characterized by next-generation amplicon sequencing. Three libraries, including an initial library (17 nonlocal sources), a blinded source library (5 local sources), and a composite library (local and nonlocal sources), were used with SourceTracker. SourceTracker’s predictions of fecal compositions in samples were made, in part, based on distributions of taxa within abundant genera identified as discriminatory by discriminant analyses but also using a large percentage of low abundance taxa. The initial library showed poor ability to characterize blinded samples, but, using local sources, SourceTracker showed 91% accuracy (31/34) at identifying the presence of source contamination, with two false positives for sewage and one for horse. Furthermore, sink predictions of source contamination were positively correlated (Spearman’s ρ ≥ 0.88, <i>P</i> < 0.001) with spiked source volumes. Using the composite library did not significantly affect sink predictions (<i>P</i> > 0.79) compared to those made using the local sources alone. Results of this study indicate that geographically associated fecal samples are required for SourceTracker to assign host sources accurately

Application of SourceTracker for Accurate Identification of Fecal Pollution in Recreational Freshwater: A Double-Blinded Study

The efficacy of SourceTracker software to attribute contamination from a variety of fecal sources spiked into ambient freshwater samples was investigated. Double-blinded samples spiked with ≤5 different sources (0.025–10% vol/vol) were evaluated against fecal taxon libraries characterized by next-generation amplicon sequencing. Three libraries, including an initial library (17 nonlocal sources), a blinded source library (5 local sources), and a composite library (local and nonlocal sources), were used with SourceTracker. SourceTracker’s predictions of fecal compositions in samples were made, in part, based on distributions of taxa within abundant genera identified as discriminatory by discriminant analyses but also using a large percentage of low abundance taxa. The initial library showed poor ability to characterize blinded samples, but, using local sources, SourceTracker showed 91% accuracy (31/34) at identifying the presence of source contamination, with two false positives for sewage and one for horse. Furthermore, sink predictions of source contamination were positively correlated (Spearman’s ρ ≥ 0.88, <i>P</i> < 0.001) with spiked source volumes. Using the composite library did not significantly affect sink predictions (<i>P</i> > 0.79) compared to those made using the local sources alone. Results of this study indicate that geographically associated fecal samples are required for SourceTracker to assign host sources accurately

Performance Characteristics of qPCR Assays Targeting Human- and Ruminant-Associated <i>Bacteroidetes</i> for Microbial Source Tracking across Sixteen Countries on Six Continents

Numerous quantitative PCR assays for microbial fecal source tracking (MST) have been developed and evaluated in recent years. Widespread application has been hindered by a lack of knowledge regarding the geographical stability and hence applicability of such methods beyond the regional level. This study assessed the performance of five previously reported quantitative PCR assays targeting human-, cattle-, or ruminant-associated <i>Bacteroidetes</i> populations on 280 human and animal fecal samples from 16 countries across six continents. The tested cattle-associated markers were shown to be ruminant-associated. The quantitative distributions of marker concentrations in target and nontarget samples proved to be essential for the assessment of assay performance and were used to establish a new metric for quantitative source-specificity. In general, this study demonstrates that stable target populations required for marker-based MST occur around the globe. Ruminant-associated marker concentrations were strongly correlated with total intestinal <i>Bacteroidetes</i> populations and with each other, indicating that the detected ruminant-associated populations seem to be part of the intestinal core microbiome of ruminants worldwide. Consequently tested ruminant-targeted assays appear to be suitable quantitative MST tools beyond the regional level while the targeted human-associated populations seem to be less prevalent and stable, suggesting potential for improvements in human-targeted methods

Global Distribution of Human-Associated Fecal Genetic Markers in Reference Samples from Six Continents

Numerous bacterial genetic markers are available for the molecular detection of human sources of fecal pollution in environmental waters. However, widespread application is hindered by a lack of knowledge regarding geographical stability, limiting implementation to a small number of well-characterized regions. This study investigates the geographic distribution of five human-associated genetic markers (HF183/BFDrev, HF183/BacR287, BacHum-UCD, BacH, and Lachno2) in municipal wastewaters (raw and treated) from 29 urban and rural wastewater treatment plants (750–4 400 000 population equivalents) from 13 countries spanning six continents. In addition, genetic markers were tested against 280 human and nonhuman fecal samples from domesticated, agricultural and wild animal sources. Findings revealed that all genetic markers are present in consistently high concentrations in raw (median log₁₀ 7.2–8.0 marker equivalents (ME) 100 mL^–1) and biologically treated wastewater samples (median log₁₀ 4.6–6.0 ME 100 mL^–1) regardless of location and population. The false positive rates of the various markers in nonhuman fecal samples ranged from 5% to 47%. Results suggest that several genetic markers have considerable potential for measuring human-associated contamination in polluted environmental waters. This will be helpful in water quality monitoring, pollution modeling and health risk assessment (as demonstrated by QMRAcatch) to guide target-oriented water safety management across the globe