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The State of California has mandated the preparation of a guidance document on the application of fecal source identification methods for recreational water quality management. California contains the fifth highest population of cattle in the United States, making the inclusion of cow-associated methods a logical choice. Because the performance of these methods has been shown to change based on geography and/or local animal feeding practices, laboratory comparisons are needed to determine which assays are best suited for implementation. We describe the performance characterization of two end-point PCR assays (CF128 and CF193) and five real-time quantitative PCR (qPCR) assays (Rum2Bac, BacR, BacCow, CowM2, and CowM3) reported to be associated with either ruminant or cattle feces. Each assay was tested against a blinded set of 38 reference challenge filters (19 duplicate samples) containing fecal pollution from 12 different sources suspected to impact water quality. The abundance of each host-associated genetic marker was measured for qPCR-based assays in both target and non-target animals and compared to quantities of total DNA mass, wet mass of fecal material, as well as Bacteroidales, and enterococci determined by 16S rRNA qPCR and culture-based approaches (enterococci only). Ruminant- and cow-associated genetic markers were detected in all filters containing a cattle fecal source. However, some assays cross-reacted with non-target pollution sources. A large amount of variability was evident across laboratories when protocols were not fixed suggesting that protocol standardization will be necessary for widespread implementation. Finally, performance metrics indicate that the cattle-associated CowM2 qPCR method combined with either the BacR or Rum2Bac ruminant-associated methods are most suitable for implementation., (Published by Elsevier Ltd.)

The characteristics of fecal sources, and the ways in which they are measured, can profoundly influence the interpretation of which sources are contaminating a body of water. Although feces from various hosts are known to differ in mass and composition, it is not well understood how those differences compare across fecal sources and how differences depend on characterization methods. This study investigated how nine different fecal characterization methods provide different measures of fecal concentration in water, and how results varied across twelve different fecal pollution sources. Sources investigated included chicken, cow, deer, dog, goose, gull, horse, human, pig, pigeon, septage and sewage. A composite fecal slurry was prepared for each source by mixing feces from 6 to 22 individual samples with artificial freshwater. Fecal concentrations were estimated by physical (wet fecal mass added and total DNA mass extracted), culture-based (Escherichia coli and enterococci by membrane filtration and defined substrate), and quantitative real-time PCR (Bacteroidales, E. coli, and enterococci) characterization methods. The characteristics of each composite fecal slurry and the relationships between physical, culture-based and qPCR-based characteristics varied within and among different fecal sources. An in silico exercise was performed to assess how different characterization methods can impact identification of the dominant fecal pollution source in a mixed source sample. A comparison of simulated 10:90 mixtures based on enterococci by defined substrate predicted a source reversal in 27% of all possible combinations, while mixtures based on E. coli membrane filtration resulted in a reversal 29% of the time. This potential for disagreement in minor or dominant source identification based on different methods of measurement represents an important challenge for water quality managers and researchers., (Published by Elsevier Ltd.)

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., (Copyright © 2013 Elsevier Ltd. All rights reserved.)