Factors affecting the presence of human-associated and fecal indicator real-time quantitative PCR genetic markers in urban-impacted recreational beaches.

Urban runoff can carry a variety of pollutants into recreational beaches, often including bacterial pathogens and indicators of fecal contamination. To develop complete recreational criteria and risk assessments, it is necessary to understand conditions under which human contamination could be present at beaches solely impacted by urban runoff. Accurately estimating risk requires understanding sources, concentrations, and transport mechanisms of microbial contaminants in these environments. By applying microbial source tracking methods and empirical modeling, we assessed the presence and level of human contamination at urban runoff impacted recreational beaches. We also identified environmental parameters and pollution sources that can influence the concentration and transport of culturable and molecular fecal indicator bacteria (FIB) in systems impacted solely by urban runoff. Water samples and physico-chemical parameters were collected from shoreline locations from three South Carolina (SC) beaches (five locations per beach) and two Florida (FL) beaches (three locations per beach). Each SC beach was directly impacted by swashes or tidal creeks receiving stormwater runoff from the urbanized area and therefore were designated as swash drain associated (SDA) beaches, while FL beaches were designated as non-swash drain associated (NSDA). Sampling in swash drains (SD; three sites per SD) directly impacting each SC beach was also conducted. Results indicate that although culturable (enterococci) and real-time quantitative polymerase chain reaction (qPCR) (EC23S857, Entero1, and GenBac3) FIB concentrations were, on average, higher at SD locations, SDA beaches did not have consistently higher molecular FIB signals compared to NSDA beaches. Both human-associated markers (HF183 and HumM2) were concomitantly found only at SDA beaches. Bacteroidales species-specific qPCR markers (BsteriF1 and BuniF2) identified differences in the Bacteroidales community, depending on beach type. The marker for general Bacteroidales was most abundant at SD locations and exhibited a high correlation with both culturable and other molecular markers. Combining molecular information with predictive modeling allowed us to identify both alongshore movement of currents and SD outflow as significant influences on the concentration of molecular and culturable indicators in the bathing zone. Data also suggests that combining methodologies is a useful and cost effective approach to help understand transport dynamics of fecal contamination and identify potential sources of contamination at marine beaches.

Evaluation of the repeatability and reproducibility of a suite of qPCR-based microbial source tracking methods.

Many PCR-based methods for microbial source tracking (MST) have been developed and validated within individual research laboratories. Inter-laboratory validation of these methods, however, has been minimal, and the effects of protocol standardization regimes have not been thoroughly evaluated. Knowledge of factors influencing PCR in different laboratories is vital to future technology transfer for use of MST methods as a tool for water quality management. In this study, a blinded set of 64 filters (containing 32 duplicate samples generated from 12 composite fecal sources) were analyzed by three to five core laboratories with a suite of PCR-based methods utilizing standardized reagents and protocols. Repeatability (intra-laboratory variability) and reproducibility (inter-laboratory variability) of observed results were assessed. When standardized methodologies were used, intra- and inter-laboratory %CVs were generally low (median %CV 0.1-3.3% and 1.9-7.1%, respectively) and comparable to those observed in similar inter-laboratory validation studies performed on other methods of quantifying fecal indicator bacteria (FIB) in environmental samples. ANOVA of %CV values found three human-associated methods (BsteriF1, BacHum, and HF183Taqman) to be similarly reproducible (p > 0.05) and significantly more reproducible (p < 0.05) than HumM2. This was attributed to the increased variability associated with low target concentrations detected by HumM2 (approximately 1-2 log10copies/filter lower) compared to other human-associated methods. Cow-associated methods (BacCow and CowM2) were similarly reproducible (p > 0.05). When using standardized protocols, variance component analysis indicated sample type (fecal source and concentration) to be the major contributor to total variability with that from replicate filters and inter-laboratory analysis to be within the same order of magnitude but larger than inherent intra-laboratory variability. However, when reagents and protocols were not standardized, inter-laboratory %CV generally increased with a corresponding decline in reproducibility. Overall, these findings verify the repeatability and reproducibility of these MST methods and highlight the need for standardization of protocols and consumables prior to implementation of larger scale MST studies involving multiple laboratories.

Performance evaluation of canine-associated Bacteroidales assays in a multi-laboratory comparison study.

The contribution of fecal pollution from dogs in urbanized areas can be significant and is an often underestimated problem. Microbial source tracking methods (MST) utilizing quantitative PCR of dog-associated gene sequences encoding 16S rRNA of Bacteroidales are a useful tool to estimate these contributions. However, data about the performance of available assays are scarce. The results of a multi-laboratory study testing two assays for the determination of dog-associated Bacteroidales (DogBact and BacCan-UCD) on 64 single and mixed fecal source samples created from pooled fecal samples collected in California are presented here. Standardization of qPCR data treatment lowered inter-laboratory variability of sensitivity and specificity results. Both assays exhibited 100% sensitivity. Normalization methods are presented that eliminated random and confirmed non-target responses. The combination of standardized qPCR data treatment, use of normalization via a non-target specific Bacteroidales assay (GenBac3), and application of threshold criteria improved the calculated specificity significantly for both assays. Such measures would reasonably improve MST data interpretation not only for canine-associated assays, but for all qPCR assays used in identifying and monitoring fecal pollution in the environment.

Combining land use information and small stream sampling with PCR-based methods for better characterization of diffuse sources of human fecal pollution.

Diffuse sources of human fecal pollution allow for the direct discharge of waste into receiving waters with minimal or no treatment. Traditional culture-based methods are commonly used to characterize fecal pollution in ambient waters, however these methods do not discern between human and other animal sources of fecal pollution making it difficult to identify diffuse pollution sources. Human-associated quantitative real-time PCR (qPCR) methods in combination with low-order headwatershed sampling, precipitation information, and high-resolution geographic information system land use data can be useful for identifying diffuse source of human fecal pollution in receiving waters. To test this assertion, this study monitored nine headwatersheds over a two-year period potentially impacted by faulty septic systems and leaky sanitary sewer lines. Human fecal pollution was measured using three different human-associated qPCR methods and a positive significant correlation was seen between abundance of human-associated genetic markers and septic systems following wet weather events. In contrast, a negative correlation was observed with sanitary sewer line densities suggesting septic systems are the predominant diffuse source of human fecal pollution in the study area. These results demonstrate the advantages of combining water sampling, climate information, land-use computer-based modeling, and molecular biology disciplines to better characterize diffuse sources of human fecal pollution in environmental waters.