Development of Rapid Canine Fecal Source Identification PCR-Based Assays

Green, Hyatt; White, Karen M.; Kelty, Cathy A.; Shanks, Orin C.

doi:10.1021/es502637b

Cited by 43 publications

(30 citation statements)

References 38 publications

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“…For all plates, the negative control produced no band on the subsequent gel, while the positive control produced a band of the correct molecular weight for the corresponding target. Cycler conditions were consistent with previously published assays (47)(48)(49).…”

Section: Methodsmentioning

confidence: 79%

“…PCR assays included general (Bac32), human (HF183), ruminant (CF128), and dog (DG37) Bacteroidales assays and gull Catellicoccus (Gull2) assays, performed with previously published primer sets (47)(48)(49). MST assays for qPCR included general (GenBactF3), human (HF183), cow (CowM2), and dog (DG37) Bacteroidales assays and gull Catellicoccus (qGull4) assays, performed with previously published primer and probe sets (49)(50)(51)(52)(53).…”

Section: Methodsmentioning

confidence: 99%

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Comparison of Microbial and Chemical Source Tracking Markers To Identify Fecal Contamination Sources in the Humber River (Toronto, Ontario, Canada) and Associated Storm Water Outfalls

Staley

Grabuski

Sverko

et al. 2016

Appl Environ Microbiol

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Storm water runoff is a major source of pollution, and understanding the components of storm water discharge is essential to remediation efforts and proper assessment of risks to human and ecosystem health. In this study, culturable Escherichia coli and ampicillin-resistant E. coli levels were quantified and microbial source tracking (MST) markers (including markers for general Bacteroidales spp., human, ruminant/cow, gull, and dog) were detected in storm water outfalls and sites along the Humber River in Toronto, Ontario, Canada, and enumerated via endpoint PCR and quantitative PCR (qPCR). Additionally, chemical source tracking (CST) markers specific for human wastewater (caffeine, carbamazepine, codeine, cotinine, acetaminophen, and acesulfame) were quantified. Human and gull fecal sources were detected at all sites, although concentrations of the human fecal marker were higher, particularly in outfalls (mean outfall concentrations of 4.22 log 10 copies, expressed as copy numbers [CN]/ 100 milliliters for human and 0.46 log 10 CN/100 milliliters for gull). Higher concentrations of caffeine, acetaminophen, acesulfame, E. coli, and the human fecal marker were indicative of greater raw sewage contamination at several sites (maximum concentrations of 34,800 ng/liter, 5,120 ng/liter, 9,720 ng/liter, 5.26 log 10 CFU/100 ml, and 7.65 log 10 CN/100 ml, respectively). These results indicate pervasive sewage contamination at storm water outfalls and throughout the Humber River, with multiple lines of evidence identifying Black Creek and two storm water outfalls with prominent sewage cross-connection problems requiring remediation. Limited data are available on specific sources of pollution in storm water, though our results indicate the value of using both MST and CST methodologies to more reliably assess sewage contamination in impacted watersheds. IMPORTANCEStorm water runoff is one of the most prominent non-point sources of biological and chemical contaminants which can potentially degrade water quality and pose risks to human and ecosystem health. Therefore, identifying fecal contamination in storm water runoff and outfalls is essential for remediation efforts to reduce risks to public health. This study employed multiple methods of identifying levels and sources of fecal contamination in both river and storm water outfall sites, evaluating the efficacy of using culture-based enumeration of E. coli, molecular methods of determining the source(s) of contamination, and CST markers as indicators of fecal contamination. The results identified pervasive human sewage contamination in storm water outfalls and throughout an urban watershed and highlight the utility of using both MST and CST to identify raw sewage contamination. S torm water runoff has been identified as one of the most prominent non-point sources of both biological and chemical contaminants, degrading water quality and posing risks to public health in impacted recreational waters (1-3). The high level of fecal contamination present in storm water ru...

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Section: Methodsmentioning

confidence: 79%

Section: Methodsmentioning

confidence: 99%

Comparison of Microbial and Chemical Source Tracking Markers To Identify Fecal Contamination Sources in the Humber River (Toronto, Ontario, Canada) and Associated Storm Water Outfalls

Staley

Grabuski

Sverko

et al. 2016

Appl Environ Microbiol

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“…Researchers and managers alike recognize the advantages of animal source information to help solve long-standing ambient water quality problems. As a result, a number of fecal source identification technologies have been developed (2)(3)(4)(5)(6)(7)(8)(9). These methods have been employed to address challenges such as the identification of septic pollution (10)(11)(12), the evaluation of agricultural waste management practices (13)(14)(15), the assessment of combined sewer overflow water quality impact (16,17), and the estimation of recreational water public health risk (18).…”

mentioning

confidence: 99%

Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods

Shanks

Kelty

Oshiro

et al. 2016

Appl Environ Microbiol

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There is growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality management. The transition from a research tool to a standardized protocol requires a high degree of confidence in data quality across laboratories. Data quality is typically determined through a series of specifications that ensure good experimental practice and the absence of bias in the results due to DNA isolation and amplification interferences. However, there is currently a lack of consensus on how best to evaluate and interpret human fecal source identification qPCR experiments. This is, in part, due to the lack of standardized protocols and information on interlaboratory variability under conditions for data acceptance. The aim of this study is to provide users and reviewers with a complete series of conditions for data acceptance derived from a multiple laboratory data set using standardized procedures. To establish these benchmarks, data from HF183/BacR287 and HumM2 human-associated qPCR methods were generated across 14 laboratories. Each laboratory followed a standardized protocol utilizing the same lot of reference DNA materials, DNA isolation kits, amplification reagents, and test samples to generate comparable data. After removal of outliers, a nested analysis of variance (ANOVA) was used to establish proficiency metrics that include lab-to-lab, replicate testing within a lab, and random error for amplification inhibition and sample processing controls. Other data acceptance measurements included extraneous DNA contamination assessments (notemplate and extraction blank controls) and calibration model performance (correlation coefficient, amplification efficiency, and lower limit of quantification). To demonstrate the implementation of the proposed standardized protocols and data acceptance criteria, comparable data from two additional laboratories were reviewed. The data acceptance criteria proposed in this study should help scientists, managers, reviewers, and the public evaluate the technical quality of future findings against an established benchmark. Fecal pollution remains a significant challenge for ambient water quality managers worldwide. In the United States alone, it is estimated that 39.2% of all rivers, lakes, and streams are unsafe for recreational use, with fecal pathogens as the number one cause of impairment (1). General fecal indicator bacteria (FIB), such as Escherichia coli and enterococci, shed by nearly all warm-blooded animals, are routinely used to assess water quality. However, general FIB cannot discriminate between different animal groups, making it challenging to pinpoint the origin of fecal pollution. Researchers and managers alike recognize the advantages of animal source information to help solve long-standing ambient water quality problems. As a result, a number of fecal source identification technologies have been developed (2-9). These methods have been employed to address challenges such as the identification ...

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“…Currently, most MST methods rely on fecal indicator microorganisms or use molecular methods that require extensive data collection before hosts can be reliably differentiated (Green et al 2014b; McLellan and Eren 2014; Ohad et al 2016). Our real-time PCR assays targeting poultry mtDNA genes can overcome the above disadvantages.…”

Section: Discussionmentioning

confidence: 99%

Quantitative detection of fecal contamination with domestic poultry feces in environments in China

Zhuang

Zhou

et al. 2017

AMB Expr

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Poultry are an important source of fecal contamination in environments. However, tools for detecting and tracking this fecal contamination are in the early stages of development. In practice, we have found that source tracking methods targeting the 16S rRNA genes of poultry-specific microbiota are not sufficiently sensitive. We therefore developed two quantitative PCR assays for detection of poultry fecal contamination, by targeting chicken and duck mitochondrial genes: NADH dehydrogenase subunit 5 (ND5) and cytochrome b (cytb). The sensitivity of both assays was 100% when tested on 50 chicken and duck fecal samples from 10 provinces of China. These assays were also tested in field samples, including soil and water collected adjacent to duck farms, and soils fertilized with chicken manure. Poultry mitochondrial DNA was detected in most of these samples, indicating that the assays are a robust method for monitoring environmental contamination with poultry feces. Complemented with existing indicators of fecal contamination, these markers should improve the efficiency and accuracy of microbial source tracking.

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Development of Rapid Canine Fecal Source Identification PCR-Based Assays

Cited by 43 publications

References 38 publications

Comparison of Microbial and Chemical Source Tracking Markers To Identify Fecal Contamination Sources in the Humber River (Toronto, Ontario, Canada) and Associated Storm Water Outfalls

Comparison of Microbial and Chemical Source Tracking Markers To Identify Fecal Contamination Sources in the Humber River (Toronto, Ontario, Canada) and Associated Storm Water Outfalls

Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods

Quantitative detection of fecal contamination with domestic poultry feces in environments in China

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