Dataset Information

Identification of human and animal fecal contamination after rainfall in the Han River, Korea.

ABSTRACT: We investigated the effect of rainfall on the levels and sources of microbial contamination in the Han River, Korea. Thirty-four samples were collected at two sampling sites located upstream and downstream in the river from July 2010 to February 2011. Various fecal indicator microorganisms, including total coliform, fecal coliform, Escherichia coli, Enterococcus spp., somatic and male-specific (F+) coliphage, and four major enteric viruses were analyzed. Rainfall was positively correlated with the levels of fecal coliform and norovirus at both sampling sites. Additionally, rainfall was positively correlated with the levels of total coliform, E. coli, Enterococcus spp., and F+ coliphage at the upstream site. To identify the source of fecal contamination, microbial source tracking (MST) was conducted using both male-specific (F+) RNA coliphage and the Enterococcus faecium esp gene as previously described. Our results clearly indicated that the majority of fecal contamination at the downstream Han River site was from a human source. At the upstream sampling site, contamination from human fecal matter was very limited; however, fecal contamination from non-point animal sources increased following rainfall. In conclusion, our data suggest that rainfall significantly affects the level and source of fecal contamination in the Han River, Korea.

SUBMITTER: Kim JY

PROVIDER: S-EPMC4070672 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of human and animal fecal contamination after rainfall in the Han River, Korea.

Kim Ji Young JY Lee Heetae H Lee Jung Eun JE Chung Myung-Sub MS Ko Gwang Pyo GP

Microbes and environments 20130511 2

We investigated the effect of rainfall on the levels and sources of microbial contamination in the Han River, Korea. Thirty-four samples were collected at two sampling sites located upstream and downstream in the river from July 2010 to February 2011. Various fecal indicator microorganisms, including total coliform, fecal coliform, Escherichia coli, Enterococcus spp., somatic and male-specific (F+) coliphage, and four major enteric viruses were analyzed. Rainfall was positively correlated with t ...[more]

PMID: 23666535

Similar Datasets

Project description:The model prokaryote Escherichia coli can exist as a either a commensal or a pathogen in the gut of diverse mammalian hosts. These associations, coupled with its ease of cultivation and genetic variability, have made E. coli a popular indicator organism for tracking the origin of fecal water contamination. Source tracking accuracy is predicated on the assumption that E. coli isolates recovered from contaminated water present a genetic signature characteristic of the host from which they originated. In this study, we compared the accuracy with which E. coli isolated from humans, bear, cattle and deer could be identified by standard fingerprinting methods used for library-based microbial source tracking (repetitive element PCR and pulsed-field gel electrophoresis) in relation to microarray-based analysis of genome content. Our results show that patterns of gene presence or absence were more useful for distinguishing E. coli isolates from different sources than traditional fingerprinting methods, particularly in the case of human strains. Host-associated differences in genome composition included the presence or absence of mobile IS1 elements as well as genes encoding the ferric dicitrate iron transporter (fec), E. coli common pilus (ECP), type 1 fimbriae and the CRISPR associated cas proteins. Many of these differences occurred in regions of the E. coli chromosome previously shown to be M-bM-^@M-^\hot spotsM-bM-^@M-^] for the integration of horizontally-acquired DNA. PCR primers designed to amplify the IS1 and fec loci confirmed array results and demonstrated the ease with which gene presence/absence data can be converted into a diagnostic assay. The data presented here suggest that, despite the high level of genetic diversity observed among isolates by PFGE, human-derived strains may constitute a distinct ecotype distinguished by multiple potential library-independent source tracking markers. Twelve isolates of E. coli ( 3 from bear, 3 from cattle, 3 from deer and 3 from humans) were isolated from feces and/or raw sewage. Genome content for each strain was assessed in duplicate using comparative genome hybridization with E. coli K12 MG1655 as the reference for a total of 24 arrays.

Project description:Microbial water quality is generally monitored by culturable fecal indicator bacteria (FIB), which are intended to signal human health risk due to fecal pollution. However, FIB have limited utility in most urbanized watersheds as they do not discriminate among fecal pollution sources, tend to make up a small fraction of the total microbial community, and do not inform on pollution impacts on the native ecosystem. To move beyond these limitations, we assessed entire bacterial communities and investigated how bacterial diversity relates to traditional ecological and human health-relevant water quality indicators throughout the Milwaukee River Basin. Samples were collected from 16 sites on 5 days during the summer, including both wet and dry weather events, and were processed by 16S rRNA gene amplicon sequencing. Historical water quality at each sampling location, as opposed to upstream land use, was associated significantly with bacterial community alpha diversity. Source partitioning the sequence data was important for determining water quality relationships. Sewage-associated bacterial sequences were detected in all samples, and the relative abundance of sewage sequences was strongly associated with the human Bacteroides fecal marker. From this relationship, we developed a preliminary threshold for human sewage pollution when using bacterial community sequence data. Certain abundant freshwater bacterial sequences were also associated with human fecal pollution, suggesting their possible utility in water quality monitoring. This study sheds light on how bacterial community analysis can be used to supplement current water quality monitoring techniques to better understand interactions between ecological water quality and human health indicators. IMPORTANCE Surface waters in highly developed mixed-use watersheds are frequently impacted by a wide variety of pollutants, leading to a range of impairments that must be monitored and remediated. With advancing technologies, microbial community sequencing may soon become a feasible method for routine evaluation of the ecological quality and human health risk of a water body. In this study, we partnered with a local citizen science organization to evaluate the utility of microbial community sequencing for identifying pollution sources and ecological impairments in a large mixed-use watershed. We show that changes in microbial community diversity and composition are indicative of both long-term ecological impairments and short-term fecal pollution impacts. By source partitioning the sequence data, we also estimate a threshold target for human sewage pollution, which may be useful as a starting point for future development of sequencing-based water quality monitoring techniques.

Dataset Information

Identification of human and animal fecal contamination after rainfall in the Han River, Korea.

Publications

Identification of human and animal fecal contamination after rainfall in the Han River, Korea.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets