Abstract
Draft method C is a standardized method for quantifying E. coli densities in recreational waters using quantitative polymerase chain reaction (qPCR). The method includes a Microsoft Excel workbook that automatically screens for poor-quality data using a set of previously proposed acceptance criteria, generates weighted linear regression (WLR) composite standard curves, and calculates E. coli target gene copies in test samples. We compared standard curve parameter values and test sample results calculated with the WLR model to those from a Bayesian master standard curve (MSC) model using data from a previous multi-lab study. The two models’ mean intercept and slope estimates from twenty labs’ standard curves were within each other’s 95% credible or confidence intervals for all labs. E. coli gene copy estimates of six water samples analyzed by eight labs were highly overlapping among labs when quantified with the WLR and MSC models. Finally, we compared multiple labs’ 2016–2018 composite curves, comprised of data from individual curves where acceptance criteria were not used, to their corresponding composite curves with passing acceptance criteria. Composite curves developed from passing individual curves had intercept and slope 95% confidence intervals that were often narrower than without screening and an analysis of covariance test was passed more often. The Excel workbook WLR calculation and acceptance criteria will help laboratories implement draft method C for recreational water analysis in an efficient, cost-effective, and reliable manner.
Highlights
Quantitative real-time polymerase chain reaction has become a valuable tool for scientific research due to its specificity, sensitivity, and analysis speed
This and assessment two standard curve models: a simplified weighted linear regression (WLR) model that is currently being used in a draft method C Excel workbook; and the Bayesian master standard curve (MSC) model that was previously used to define the variability of draft method C results in a large multi-lab study [11]
While different approaches were used to determine the uncertainty ranges of the intercept and slope estimates from the two models: 95% confidence interval (CI) for WLR; and 95% BCI for MSC, the magnitude of these ranges was the same or similar in most instances and the ranges were highly overlapping for all labs
Summary
Quantitative real-time polymerase chain reaction (qPCR) has become a valuable tool for scientific research due to its specificity, sensitivity, and analysis speed. Because contact with fecal contaminated water increases the likelihood of developing gastrointestinal (GI) illnesses [1,2], public beaches are routinely monitored for the presence of Enterococcus or Escherichia coli (E. coli) to alert beach managers and recreators to incidences of fecal contamination, thereby reducing the risk of recreational exposure [3,4]. That results from an E. coli qPCR method and an approved E. coli culture method, where a health relationship has been established, can show a high degree of correlation and lead to similar recreational beach management decisions [5]. Additional studies have been conducted in 2016–2018 in the state of Michigan to assess the relationships between E. coli culture methods and an E. coli qPCR method (draft method C) developed by the U.S EPA
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