Large-scale implementation of standardized quantitative real-time PCR fecal source identification procedures in the Tillamook Bay Watershed.
Xiang LiMano SivaganesanCatherine A KeltyAmity Zimmer-FaustPat ClintonJay R ReichmanYork JohnsonWilliam MatthewsStephanie BaileyOrin C ShanksPublished in: PloS one (2019)
Fecal pollution management remains one of the biggest challenges for water quality authorities worldwide. Advanced fecal pollution source identification technologies are now available that can provide quantitative information from many animal groups. As public interest in these methodologies grows, it is vital to use standardized procedures with clearly defined data acceptance metrics and conduct field studies demonstrating the use of these techniques to help resolve real-world water quality challenges. Here we apply recently standardized human-associated qPCR methods with custom data acceptance metrics (HF183/BacR287 and HumM2), along with established procedures for ruminant (Rum2Bac), cattle (CowM2 and CowM3), canine (DG3 and DG37), and avian (GFD) fecal pollution sources to (i) demonstrate the feasibility of implementing standardized qPCR procedures in a large-scale field study, and (ii) characterize trends in fecal pollution sources in the research area. A total of 602 water samples were collected over a one-year period at 29 sites along the Trask, Kilchis, and Tillamook rivers and tributaries in the Tillamook Bay Watershed (OR, USA). Host-associated qPCR results were combined with high-resolution geographic information system (GIS) land use and general indicator bacteria (E. coli) measurements to elucidate water quality fecal pollution trends. Results demonstrate the feasibility of implementing standardized fecal source identification qPCR methods with established data acceptance metrics in a large-scale field study leading to new investigative leads suggesting that elevated E. coli levels may be linked to specific pollution sources and land use activities in the Tillamook Bay Watershed.
Keyphrases
- water quality
- high resolution
- healthcare
- electronic health record
- escherichia coli
- heavy metals
- endothelial cells
- big data
- quality improvement
- real time pcr
- mass spectrometry
- mental health
- heart failure
- risk assessment
- emergency department
- particulate matter
- air pollution
- health information
- data analysis
- atrial fibrillation
- induced pluripotent stem cells
- case control
- adverse drug