Environ. Sci. Technol. 2010, 44, 7777–7782
Use of Barcoded Pyrosequencing and Shared OTUs To Determine Sources of Fecal Bacteria in Watersheds TATSUYA UNNO,† JEONGHWAN JANG,† DUKKI HAN,† JOON HA KIM,† MICHAEL J. SADOWSKY,§ OK-SUN KIM,| J O N G S I K C H U N , | A N D H O R - G I L H U R * ,†,‡ Department of Environmental Science and Engineering and International Environmental Research Center, Gwangju Institute of Science and Technology, Gwangju 500-712, Republic of Korea, Department of Soil, Water, and Climate and BioTechnology Institute, University of Minnesota, St. Paul, Minnesota 55108, and School of Biological Sciences, Seoul National University, NS70, 56-1 Daehak-dong, Kwanak-gu, Seoul 151-742, Republic of Korea
Received May 4, 2010. Revised manuscript received August 19, 2010. Accepted August 24, 2010.
While many current microbial source tracking (MST) methods rely on the use of specific molecular marker genes to identify sources of fecal contamination, these methods often fail to determine all point and nonpoint contributors of fecal inputs into waterways. In this study, we developed a new librarydependent MST method that uses pyrosequencing-derived shared operational taxonomy units (OTUs) to define sources of fecal contamination in waterways. A total 56,841 pyrosequencing reads of 16S rDNA obtained from the feces of humans and animals were evaluated and used to compare fecal microbial diversity in three freshwater samples obtained from the Yeongsan river basin in Jeonnam Province, South Korea. Sites included an urbanized agricultural area (Y1) (Escherichia coli counts g1600 CFU/100 mL), an open area (Y2) with no major industrial activities (940 CFU/100 mL), and a typical agricultural area (Y3) (g1600 CFU/100 mL). Data analyses indicated that the majority of bacteria in the feces of humans and domesticated animals were comprised of members of the phyla Bacteroidetes or Firmicutes, whereas the majority of bacteria in wild goose feces and freshwater samples were classified to the phylum Proteobacteria. Analysis of OTUs shared between the fecal and environmental samples suggested that the potential sources of the fecal contamination at the sites were of human and swine origin. Quantification of fecal contamination was also examined by comparing the density of pyrosequencing reads in each fecal sample within shared OTUs. Taken together, our results indicated that analysis of shared OTUs derived from * Corresponding author phone: +82-62-970-2437; fax: +82-62970-2434; e-mail:
[email protected]. Corresponding author address: Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology, Gwangju 500-712, South Korea. † Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology. § University of Minnesota. | Seoul National University. ‡ International Environmental Research Center, Gwangju Institute of Science and Technology. 10.1021/es101500z
2010 American Chemical Society
Published on Web 09/20/2010
barcoded pyrosequencing reads provide the necessary resolution and discrimination to be useful as a next generation platform for microbial source tracking studies.
Introduction According to the World Health Organization (WHO), diarrhea kills over 2 million people globally each year, and fecal contamination of water is one of the major contributing factors to disease incidence. Determining the sources of fecal contaminants in waterways using microbial source tracking methodologies has attracted much attention in recent years. However, current technologies often fail to consistently identify fecal contaminants in watersheds, prompting development of new and more sensitive methods (1, 2). The application of 16S rDNA as a genetic marker for microbial source tracking has received recent attention, and markers purportedly specific for fecal bacteria (mainly Bacteroidales) originating from humans, bovine, and other animals have been developed and evaluated (3-5). Recently, however, the use of these marker genes has been questioned since there were large discrepancies in the performance of primers across different bovine populations, the lowest specificity was about 47%, and marker genes for all potential contamination sources are not available. In addition, several of the markers have been reported to have low sensitivity when used in quantitative PCR (qPCR) assays with environmental DNA (6), and there is generally a lack of correlation between the numbers of Bacteriodales present and counts of fecal indicator bacteria. Ley et al. (7) used a 16S rDNA sequence library approach to examine how diet and phylogeny influences bacterial diversity. They reported that microbial diversity increases from carnivory to omnivory to herbivory, and these results indirectly support the contention that there is significant discrepancy in diversity and types of fecal bacteria in humans (omnivores) and livestock animals (herbivores). To date, several other studies have reported the use of culture-based 16S rDNA libraries to identify host specific microbial species in other animals, including C. marimammalium in gull feces (8), and Lactobacillus sobrius/amylovorus in pig manure (9). While some of the identified marker genes hold great promise for assessing sources of fecal bacteria or feces in the environment, others have not proven useful due to issues of lack of sensitivity and cross-reactivity. This may in part be due to our lack of understanding of the broad microbial diversity present in intestinal environments, which is due, in part, to inherent deficiencies in using traditional culture based 16S rDNA library approaches. Studies of microbial diversity using reassociation kinetics for bacterial community DNA from pristine soils revealed that bacterial species diversity is more than 2 orders of magnitude greater than estimates based on using traditional culture dependent method (10, 11). Pyrosequencing, a next generation sequencing technology that determines DNA sequences by using a “sequencing by synthesis” approach, has revolutionized the study of microbial diversity (12). While the first pyrosequencers, such as the Roche 454 FLX system, only produced average readlengths of 100 bp, more recent advances have increased read lengths to about 400 bp, with considerable cost reduction (13). Pyrosequencing has been further improved by allowing for the simultaneous analysis of 1544 samples by using errorcorrecting barcoded primers (14). Short 16S rDNA pyrosequencing reads have proven useful for microbial community analysis (15) and has been widely applied to study microbial VOL. 44, NO. 20, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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diversity in soils (16, 17), fermented seafood (18), human saliva (19), wastewater treatment facilities (20), human and animals GI tracts (21-25), and the ecology of diseaseproducing microorganisms (26). Dowd et al. (27) investigated microbial community structure in dairy cattle feces using a pyrosequencing approach. They reported that the majority of microorganisms revealed by using this approach were not found in previous studies using traditional culture-based methods. Since a barcoded pyrosequencing approach targeting bacterial 16S rDNA sequences has the necessary resolving power to reveal undiscovered microbial diversity in feces, this technique will likely prove to be useful to define future microbial markers for microbial source tracking applications. In the studies reported here, we examined the microbial community structure in feces from humans and farm animals and further investigated the usefulness of barcoded pyrosequencing as a microbial source tracking tool. Here we report that pyrosequencing-derived shared operational taxonomy units (OTUs) and the density of pyrosequencing reads in each fecal sample within shared OTUs are useful tools to define sources of fecal contamination in waterways.
Materials and Methods Fecal and Environmental DNA Extraction. A total 150 fecal swabs were collected from 30 randomly selected individual chickens, ducks, beef cattle, dairy cattle, and swine from three farms in Jeonnam Province, South Korea. Thirty fecal samples were obtained from wild geese resting near lake Gochunam in the same region. In addition, 30 fecal samples were obtained from 30 healthy human volunteers at the Gwangju Institute of Science and Technology, Gwangju, South Korea. All fecal swabs from identical source animals or humans were pooled into a single test tube and DNA was extracted using a stool DNA extraction kit (Bioneer Inc. South Korea). DNA was also extracted from 50 mL freshwater samples collected from three sites (Y1, Y2, and Y3) of the Yeongsan River, Jeonnam Province, South Korea using the same DNA extraction kit. The number, size, and description of samples used in this study are described in the Supporting Information and summarized in Table SI-S1. Pyrosequencing. Genomic DNA extracted from fecal and environmental samples was amplified using primers barcoded with 8 nucleotides and targeting the V1 and V3 regions of the bacterial 16S rRNA as described previously (28, 29). All pyrosequencing reads obtained in this study were submitted to the Sequence Read Archive (SRA) under study accession number ERP000189. Analyses for r Diversity of Fecal Bacteria Community. Since frequent pyrosequencing error was observed when reads were shorter than 300 bp, all reads shorter than 300 bp were removed from the entire analyses (data not shown). Operational taxonomy units (OTUs) were defined by using the CD-HIT program (30), qualitative species richness was estimated using Chao1 and ACE, and quantitative species richness/evenness was estimated by using nonparametric Shannon and Simpson indices by using the Mothur program v.1.8.0 (31). Analyses of β Diversity of Fecal Bacteria Community. Species classification of each pyrosequencing read was carried out using the EzTaxon-e database (http://www. eztaxon-e.org) as described by Chun et al. (32, 33). Each pyrosequencing read was taxonomically assigned by using a combination of initial BLASTN-based searches (34) and pairwise similarity comparisons as described previously (32). The relative abundance of each taxon was clustered by using Bionumerics version 6.0 software (Applied Maths, Sint Martens Latem, Belgium). The weighted UniFrac service (35) was used to analyze OTU divergence. 7778
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Determination of Pyrosequencing Reads Shared between Fecal and Environmental Samples. Shared OTUs between fecal and environmental samples were identified, at a dissimilarity level 0.03, by using the Mothur program. Differences in the number of reads among each fecal and environmental sample within shared OTUs were expressed as a density ratio.
Results and Discussion Species Richness and Diversity in Fecal Bacteria Community Characterized by Barcoded Pyrosequencing. A total 56,841 pyrosequencing reads, comprised of 18,825 OTUs, were obtained from the human and animal fecal samples examined. Results in Table SI-S2 summarize the number of reads, OTUs, and indices that estimate diversity richness from the 16S rDNA samples analyzed. Relatively low species richness and diversity, at a dissimilarity level of 0.03, were found in the duck and goose fecal samples, followed by the human fecal sample (Table SI-S2 and Figure SI-S1). Approximately 20 to 30% of the pyrosequencing reads were classified at a 97% similarity level, except those from fecal samples obtained from beef and dairy cattle. Similarly,
