A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method

Abstract

Human fecal pollution of recreational waters remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality research and management. However, there are currently no standardized approaches for field implementation and interpretation of qPCR data. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and a novel Bayesian weighted average approach to establish a human fecal contamination score (HFS) that can be used to prioritize sampling sites for remediation based on measured human waste levels. The HFS was then used to investigate 975 study design scenarios utilizing different combinations of sites with varying sampling intensities (daily to once per week) and number of qPCR replicates per sample (2-14 replicates). Findings demonstrate that site prioritization with HFS is feasible and that both sampling intensity and number of qPCR replicates influence reliability of HFS estimates. The novel data analysis strategy presented here provides a prescribed approach for the implementation and interpretation of human-associated HF183/BacR287 qPCR data with the goal of site prioritization based on human fecal pollution levels. In addition, information is provided for future users to customize study designs for optimal HFS performance.

Keywords: Human fecal pollution; Microbial source tracking; Site prioritization; qPCR.

Fig. 1.

Effect of sampling intensity and number of qPCR replicates (denoted by different colors) on HFS estimates across the five simulated field sites (Esco, Esco:Mcyn, Mcyn, Mcyn:Topa, and Topa). Sampling intensity was presented as the proportion of all 105 samples for a respective scenario. Panel A shows the average HFS calculated from all 100 iterations for each scenario. The HFS estimate for the best case scenario (BCS; 100% sampling intensity and 14 qPCR replicates is indicated by a dashed line (Panel A). Panel B represents the 95% inter-quantile range of HFS values across 100 iterations. (Note: y-axis truncated to maximum of 150 copies/100 mL).

Fig. 2.

Effect of sampling intensity and number of qPCR replicates (denoted by different colors) on HFS variability reported as the standard deviation of HFS values (top 5% removed) for each site and scenario across the five simulated field sites (Esco, Esco:Mcyn, Mcyn, Mcyn:Topa, and Topa). Sampling intensity was presented as the proportion of all 105 samples for a respective scenario.

Fig. 3.

Plot showing human fecal score with 95% BCI for all 100 iterations at each site under with two different design choice scenarios. Panel A shows results with a sampling intensity of 73.3% and 3 qPCR replicates. Panel B depicts thebest case scenario (BCS; 100% sampling intensity and 14 qPCR replicates). In the BCS, sites are ranked as follows: (Esco and Esco:Mcyn) > Mcyn > (Mcyn:Topa, and Topa), where the cumulative 95% BCI ranges do not overlap between field site groups. Vertical gray lines represent 95% BCI for each individual HFS iteration.

Fig. 4.

Plot depicting sampling intensity (number of sampling days divided by 105 days) and qPCR replicates per sample (2–14 replicates) combinations for a Human Fecal Score (HFS) site prioritization application. Filled circles indicate qPCR replicate and sampling intensity combinations required to achieve the same site ranking outcome [(Esco and Esco:Mcyn) > Mcyn > (Mcyn:Topa, and Topa)] as the best case scenario (14 qPCR replicates at 100% sampling intensity).