Dataset Information

Cryptosporidium source tracking in the Potomac River watershed.

ABSTRACT: To better characterize Cryptosporidium in the Potomac River watershed, a PCR-based genotyping tool was used to analyze 64 base flow and 28 storm flow samples from five sites in the watershed. These sites included two water treatment plant intakes, as well as three upstream sites, each associated with a different type of land use. The uses, including urban wastewater, agricultural (cattle) wastewater, and wildlife, posed different risks in terms of the potential contribution of Cryptosporidium oocysts to the source water. Cryptosporidium was detected in 27 base flow water samples and 23 storm flow water samples. The most frequently detected species was C. andersoni (detected in 41 samples), while 14 other species or genotypes, almost all wildlife associated, were occasionally detected. The two common human-pathogenic species, C. hominis and C. parvum, were not detected. Although C. andersoni was common at all four sites influenced by agriculture, it was largely absent at the urban wastewater site. There were very few positive samples as determined by Environmental Protection Agency method 1623 at any site; only 8 of 90 samples analyzed (9%) were positive for Cryptosporidium as determined by microscopy. The genotyping results suggest that many of the Cryptosporidium oocysts in the water treatment plant source waters were from old calves and adult cattle and might not pose a significant risk to human health.

SUBMITTER: Yang W

PROVIDER: S-EPMC2576682 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

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Cryptosporidium source tracking in the Potomac River watershed.

Yang Wenli W Chen Plato P Villegas Eric N EN Landy Ronald B RB Kanetsky Charles C Cama Vitaliano V Dearen Theresa T Schultz Cherie L CL Orndorff Kenneth G KG Prelewicz Gregory J GJ Brown Miranda H MH Young Kim Roy KR Xiao Lihua L

Applied and environmental microbiology 20080905 21

To better characterize Cryptosporidium in the Potomac River watershed, a PCR-based genotyping tool was used to analyze 64 base flow and 28 storm flow samples from five sites in the watershed. These sites included two water treatment plant intakes, as well as three upstream sites, each associated with a different type of land use. The uses, including urban wastewater, agricultural (cattle) wastewater, and wildlife, posed different risks in terms of the potential contribution of Cryptosporidium oo ...[more]

PMID: 18776033

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Project description:Taihu Lake is one of the largest freshwater lakes in China, serving as an important source of drinking water; >60% of source water to this lake is provided by the Tiaoxi River. This river faces serious fecal contamination issues, and therefore, a comprehensive investigation to identify the sources of fecal contamination was carried out and is presented here. The performance of existing universal (BacUni and GenBac), human (HF183-Taqman, HF183-SYBR, BacHum, and Hum2), swine (Pig-2-Bac), ruminant (BacCow), and avian (AV4143 and GFD) associated microbial source tracking (MST) markers was evaluated prior to their application in this region. The specificity and sensitivity results indicated that BacUni, HF183-TaqMan, Pig-2-Bac, and GFD assays are the most suitable in identifying human and animal fecal contamination. Therefore, these markers along with marker genes specific to selected bacterial pathogens were quantified in water and sediment samples of the Tiaoxi River, collected from 15 locations over three seasons during 2014 and 2015. Total/universal Bacteroidales markers were detected in all water and sediment samples (mean concentration 6.22 log10 gene copies/100 ml and 6.11 log10 gene copies/gram, respectively), however, the detection of host-associated MST markers varied. Human and avian markers were the most frequently detected in water samples (97 and 89%, respectively), whereas in sediment samples, only human-associated markers were detected more often (86%) than swine (64%) and avian (8.8%) markers. The results indicate that several locations in the Tiaoxi River are heavily polluted by fecal contamination and this correlated well with land use patterns. Among the five bacterial pathogens tested, Shigella spp. and Campylobacter jejuni were the most frequently detected pathogens in water (60% and 62%, respectively) and sediment samples (91% and 53%, respectively). Shiga toxin-producing Escherichia coli (STEC) and pathogenic Leptospira spp. were less frequently detected in water samples (55% and 33%, respectively) and sediment samples (51% and 13%, respectively), whereas E. coli O157:H7 was only detected in sediment samples (11%). Overall, the higher prevalence and concentrations of Campylobacter jejuni, Shigella spp., and STEC, along with the MST marker detection at a number of locations in the Tiaoxi River, indicates poor water quality and a significant human health risk associated with this watercourse. GRAPHICAL ABSTRACTTracking fecal contamination and pathogens in watersheds using molecular methods.

Project description:The vast number of chemicals potentially reaching aquatic environment pose a challenge in maintaining the quality of water resources. However, best management practices to improve water quality are typically focused on reducing nutrient transport without assessing how these practices may impact the occurrence of micropollutants. The potential for co-management of nutrients and organic micropollutants exists, but few studies have comprehensively evaluated the suite of contaminants associated with different water quality management practices (riparian zone restoration, stormwater management, etc.). Furthermore, most studies dealing with the determination of micropollutants in environmental samples include only a limited number of target analytes, leaving many contaminants undetected. To address this limitation, there has been a gradual shift in environmental monitoring from using target analysis to either suspect screening analysis (SSA) or non-targeted analysis (NTA), which relies on accurate mass measurements, mass spectral fragmentation patterns, and retention time information obtained using liquid chromatography coupled to high-resolution mass spectrometry. The work presented in this paper focuses on a wide-scope detection of micropollutants in surface water samples from the Potomac River watershed (United States). An in-house database composed of 1039 compounds based on experimental analysis of primary standards was established, and SSA workflow was optimized and applied to determine the presence of micropollutants in surface water. A total of 103 micropollutants were detected in the samples, some of which are contaminants that were not previously monitored and belong to various classes such as pharmaceuticals, personal care products, per-and polyfluoroalkyl substances and other persistent industrial chemicals. The impact of best management practices being implemented for nitrogen and phosphorus reductions were also assessed for their potential to reduce micropollutant transport. This work illustrates the advantages of suspect screening methods to determine a large number of micropollutants in environmental samples and reveals the potential to co-manage a diverse array of micropollutants based on shared transport and transformation mechanisms in watersheds.

Dataset Information

Cryptosporidium source tracking in the Potomac River watershed.

Publications

Cryptosporidium source tracking in the Potomac River watershed.

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