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Applied and Environmental Microbiology, July 2008, p. 3969-3976, Vol. 74, No. 13
0099-2240/08/$08.00+0 doi:10.1128/AEM.00019-08
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 Martin Luther King Drive, MS-387, Cincinnati, Ohio 45268,1 Department of Environmental Engineering, University of Cincinnati, Cincinnati, Ohio 45220,2 National Water Research Institute, Environment Canada, 867 Lakeshore Road, P.O. Box 5050, Burlington, Ontario L7R 4A6, Canada3
Received 3 January 2008/ Accepted 29 April 2008
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Most studies describing the gut microbiota of waterfowl have used culture-based methods and have focused on targeted pathogens (6, 15). As culture-based studies can provide only a limited view of natural microbial communities, recently developed molecular methods can be used to better describe the composition of waterfowl gut systems. This information is critical in order to recognize potential hazards associated with waterfowl fecal pollution and to help distinguish waterfowl fecal sources from other animal sources. Waterfowl feces has been suggested as an important source of fecal contamination in several studies (27, 34) and therefore is potentially responsible for many beach closures every year (10). Although fecal pollution in recreational waters is traced with fecal indicator bacteria, whether contamination in water is primarily associated with human, waterfowl, or other fecal sources is often undetermined. While microbial source-tracking (MST) methods that use fingerprint databases of water and fecal bacterial isolates may be able to differentiate bird feces from other fecal sources (10, 14), these methods can be laborious and time-consuming and have yet to clearly discriminate among different avian fecal sources. Alternatively, PCR-based methods that detect host-specific 16S rRNA genes and functional genes directly in water DNA extracts are becoming more popular (4, 31, 32). The latter methods have been used mainly to differentiate human and ruminant from other animal fecal sources, primarily targeting Bacteroidetes. Studies tracking sources of gull feces based on the detection of Bacteroidetes genes have had little success (12), perhaps because of the low prevalence of Bacteroidetes in bird feces and the limited knowledge of the composition of the normal microbiota of gull feces.
The aims of this study were to study microbial community composition and structure in the fecal DNA of gulls by 16S rRNA gene sequencing analysis and to develop host-specific assays for detecting gull fecal community DNA in waters.
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Sample collection and DNA extraction.
Gull fecal samples used to develop the 16S rRNA gene clone library were collected in West Virginia. Fecal DNA extracts from deposited fecal samples from the following animals were used in host specificity studies: Sus scrofa (pig), Bos taurus (bovine), Homo sapiens (human), Capra aegagrus (domestic goat), Ovis aries (sheep), Equus caballus (horse), Felis catus (cat), Canis familiaris (dog), Canis latrans (coyote), Sciurus carolinensis (gray squirrel), Odocoileus virginianus (whitetail deer), Didelphis virginiana (possum), Loragyps atratus (black vulture), Lynx rufus (bobcat), Procyon lotor (raccoon), Erinaceus sp. (hedgehog), Pongo pygmaeus (red ape), Elephas maximus (Asian elephant), Zalophus californianus (California sea lion), Callorhinus ursinus (northern fur seal), Phoca vitulina (Pacific harbor seal), Physeter macrocephalus (sperm whale), Megaptera novaeangliae (humpback whale), Phocoenoides dalli (Dall's porpoise), Phocoena phocoena (harbor porpoise), Lagenorhynchus obliquidens (Pacific white-sided dolphin), Branta canadensis (Canadian goose), Anser sp. (goose), Meleagris gallopavo (turkey), Treron sp. (pigeon), Aix sponsa (duck), Gallus gallus (chicken), Pygoscelis sp. (penguin), Psittacus sp. (parrot), Collumba livia (dove), Pelicanus sp. (pelican), Eudocimus ruber (ibis), Larus atricilla (laughing gull), and L. delawarensis (ring-billed gull). In addition, feces collected from gulls located in Georgia, Ohio, West Virginia, Florida, and Ontario (Canada) were used in host distribution studies. Feces from marine mammals were obtained directly from the animals, while samples from other animals were collected from previously deposited fecal samples. All samples were collected aseptically, placed into sterile 50-ml conical tubes with screw caps, and stored at –80°C until required. Total DNA was extracted from individual fecal samples. The Mo Bio Fecal kit (Mo Bio Laboratories, Inc., Carlsbad, CA) and the FastDNA kit (Q-Biogene, Carlsbad, CA) were used by following the protocols provided by the manufacturers. Total DNA was eluted in 50 (Mo Bio Fecal kit) or 100 µl (Fast DNA kit) of water, and DNA concentrations were measured with a NanoDrop ND-1000 UV-Vis spectrophotometer (NanoDrop Technologies, Inc., Berlin, Germany).
Water samples presumed to be impacted by gull feces were used to evaluate the potential of gull-specific assays as a source-tracking tool (see below). Freshwater samples were collected in sterile bottles from beaches in or near the Great Lakes (Grant Park Beach, Wisconsin; Lake Erie, Ohio; Lake Ontario, Canada) and from a pond adjacent to the San Juan Creek next to Doheny State Beach (Dana Point, California). Additionally, samples were collected from sites in northern Georgia and northern Ohio with no previous history of gull contamination, as well as from sites in northeastern Ohio impacted by non-waterfowl sources (i.e., chicken, cattle, swine). Water samples were transported to the laboratory in ice coolers and filtered (i.e., 100 to 300 ml) onto 47-mm polycarbonate membranes (0.2-µm pore size) as previously described (23). Membranes were then transferred into sterile conical tubes and kept at –80°C until further processing. Total community DNA was extracted from water samples with a Mo Bio Fecal kit and a FastDNA kit.
16S rRNA gene clone library analysis.
Sequence analysis of 16S rRNA gene clones was used to describe the phylogenetic affiliations of bacterial populations in gull fecal extracts. The 16S rRNA gene was amplified with general bacterial primers 27F (E. coli numbering positions 8 to 27: 5'-AGAGTTTGATCMTGGCTCAG-3') and 785R (E. coli numbering positions 785 to 804: 5'-ACTACCRGGGTATCTAATCC-3'). DNA extracted from eight gull fecal samples from West Virginia was pooled and used as the PCR template. PCR amplifications were performed in a PTC-240 DNA Engine Tetrad 2 Cycler (MJ Research, Inc., Alameda, CA). Reaction mixtures were prepared in a 25-µl volume and subjected to the following cycling conditions: 3 min at 95°C, followed by 22 cycles of 30 s at 95°C, 30 s at 58°C, and 60 s at 72°C and a final 10-min primer extension step at 72°C. PCR products from five reactions were pooled and cloned into pCR4.1 TOPO (Invitrogen). Individual clones were sequenced by using BigDye Terminator chemistry and an Applied Biosystems PRISM 3730XL as described by Lu et al. (23).
Sequence editing and alignment were completed with Sequencher (Gene Codes Corporation, Ann Arbor, MI). The 16S rRNA gene sequences were screened for chimeras with the Check Chimera program of the Ribosome Database Project and by manual alignments of secondary structure. The Bellerophon program (http://foo.maths.uq.edu.au/
huber/bellerophon.pl) (16) was also used to check for chimeras by comparing each sequence against the sequences from the same library. As a final check for chimeras, each sequence was split into 5' and 3' fragments, which were analyzed separately by BLAST searching of the GenBank database. Sequences for which either the 5' or the 3' fragment had significantly different closest relatives were considered probable chimeras and were removed from the data set. For 16S rRNA gene sequences, homology searches of DNA sequences in the GenBank (NR) database were done with National Center for Biotechnology Information (NCBI) BLASTn (http://www.ncbi.nlm.nih.gov/BLAST/) (1).
Conventional PCR and real-time assays.
C. marimammalium PCR primers were designed by aligning 16S rRNA gene sequences from closely related species by using Primer Designer software (version 2.01; Scientific & Educational Software, Durham, NC) and the following conditions: no hairpin, no primer dimer formation, and an annealing temperature of 64 to 65°C. Assays were optimized through temperature gradients and with various concentrations of fecal DNA templates. Primers were tested for host specificity against fecal DNA composites for each of the animal types listed above. DNA composites were generated by combining equal amounts of DNA from the individual fecal samples. Assays that showed host specificity to gull composites were further tested against DNA extracts of individual avian, human, pig, and cow fecal samples. Gull samples were also used to determine the host distribution of potential markers. Detection limits of PCR assays were determined by three different approaches: (i) 10-fold dilutions of plasmid DNA (6 to 6 x 10–7 ng) containing a targeted insert in reaction mixtures with no fecal DNA background; (ii) 10-fold dilutions of plasmid DNA (6 to 6 x 10–7 ng) containing a targeted insert in reaction mixtures spiked with bird fecal DNA (10 ng/µl) made of equal amounts of chicken, turkey, and Canadian goose fecal DNA extracts; and (iii) 10-fold dilutions of gull fecal DNA (6 to 6 x 10–7 ng). PCR assays specific to Bacteroides spp. and Clostridium coccoides were used to determine the presence of potential PCR inhibitors in DNA extracts used as templates in PCR assays (4, 25). All of the assays were performed with 1 and 10 ng µl–1 fecal DNA extracts. The presence of PCR products was visualized by 2% agarose gel electrophoresis with GelStar as the nucleic acid stain (FMC BioProducts; Rockland, ME). The cycling conditions for the PCR assays were 3 min at 95°C, followed by 35 cycles of 30 s at 95°C, 30 s at 64°C, and 60 s at 72°C and a final 10-min primer extension step at 72°C. The C. marimammalium species-specific primer sequences used in this study were TGCATCGACCTAAAGTTTTGAG and GTCAAAGAGCGAGCAGTTACTA for the forward and reverse primers, respectively. We refer to this assay as Gull-2.
The C. marimammalium PCR assay was also used in real-time assays, with SYBR green as the detection dye. The assays were performed with a 7900 HT Fast Real-Time Sequence Detector (Applied Biosystems). Reaction mixtures (20 µl) contained 10 µl 2x SYBR Premix Ex Taq, 0.4 µl ROX reference dye (Takara Bio Inc., Shiga, Japan), 0.2 µM (final concentration) primers, and either 100 ng genomic DNA (fecal and water samples), a series of dilutions of plasmid DNA with a target insert with a log copy number of 8.8 to 1.8 (i.e., a copy number of 6.3 x 108 to about 63) per reaction mixture, or a series of dilutions of gull fecal DNA ranging from 60 to 6 x 10–7 ng per reaction mixture. All reaction mixtures were prepared in triplicate in MicroAmp Optical 96-well reaction plates with MicroAmp Optical Caps (Applied Biosystems). The amplification protocol consisted of 50°C for 2 min, followed by 95°C for 2 min and then 40 cycles of 95°C for 5 s, 64°C for 15 s, and a 72°C extension for 10 s and an additional disassociation at 60°C for 15 s. Data were initially analyzed with Sequence Detector software (version 2.2.2) with a 0.2 threshold. Gene copies in fecal samples were calculated from standard curves based on the log transformation of a known concentration versus the threshold cycle (CT). Comparison tests between gull species (laughing gull and ring-billed gull) were performed with Statistical Analysis Software (SAS Institute Inc., Cary, NC) by using PROC GLM with the contrast statement feature.
Nucleotide sequence accession numbers.
Representative 16S rRNA gene sequences from cloning experiments were deposited in GenBank with accession numbers EU181006 to EU181122.
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98%) were also numerous (11%), and many were closely related to Klebsiella pneumoniae, Enterobacter sp., Pseudomonas sp., and E. coli. In contrast, sequences homologous to Bacteroides represented only 1% of the total number of clones. |
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TABLE 1. Distribution of 16S rRNA genes in the gull clone library
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FIG. 1. Unrooted neighbor-joining tree of 16S rRNA gene sequences of low-G+C gram-positive bacteria, including C. marimammalium-like sequences obtained from clone libraries. Sequences were aligned, and a bootstrap consensus tree was created with MEGA 3.1 (1% divergence).
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1% of the total community). This is an important finding to those developing markers to track avian fecal pollution in environmental waters, as it suggests that Bacteroidetes bacteria might not be practical targets for the development of avian-specific assays due to their low densities in the avian gut and considering that Bacteroidetes host-specific populations represent less that 1 to 10% of the total Bacteroidetes populations (4, 20). Our data show that the dominant low-G+C gram-positive bacteria in gull feces are closely related to C. marimammalium. This finding is interesting, as C. marimammalium was recently described as a new group of low-G+C gram-positive bacteria isolated from a porpoise and a gray seal (21). This group is part of the Bacilli class and specifically belongs in the Enterococcaceae family, which houses the genera Enterococcus, Melissococcus, Tetragenococcus, and Vagococcus. Enterococcus and Vagococcus spp. are commonly found in animal feces, and in fact, Enterococcus spp. are often used as indicators of fecal pollution in freshwater and marine waters and as targets in source-tracking studies (8, 28). Several studies have shown that some Enterococcus populations might be host specific (5), although the ecology of this genus is still poorly understood. Since no strains of C. marimammalium have been isolated from avian systems thus far, we decided to determine if these results were unique to gulls or if this species is also present in other gut systems.
Host specificity PCR studies.
The Gull-2 PCR assay was designed to target C. marimammalium by using publicly available sequences and closely related clone sequences obtained in this study. In silico analysis showed that the primers have no mismatches to the C. marimammalium 16S rRNA gene. Only a limited number of unrelated 16S rRNA gene bacterial sequences in the NCBI database (e.g., B. vulgatus, Prochlorococcus marinus, Mycobacterium sp. strain JLS, and Jannaschia sp. strain CCS1) (as of 23 August 2007) showed similarity to either one of the primers, but these sequences contain several mismatches in the 3' end of the sequence. Moreover, none of the primers perfectly annealed sequences from the same species, suggesting a relatively low potential for cross-hybridization with bacterial species other than C. marimammalium.
When the Gull-2 PCR assay was used to test DNA extracts from eight bacterial strains, including Firmicutes closely related to C. marimammalium (i.e., enterococci), no cross-amplification signals were obtained, further suggesting that the assay is highly species specific. DNA from the C. marimammalium type strain produced a PCR band of the expected size (i.e., approximately 412 bp). When the PCR assay was used to test composite fecal DNA extracts from a variety of animals, including marine mammals, only gull fecal DNA extracts generated a PCR product of the correct size (Table 2). As C. marimammalium was originally isolated from marine mammals, our results suggest that C. marimammalium might not be a normal or abundant inhabitant of a marine mammal's gut. Considering that this species was originally isolated from deceased animals, this organism might be an opportunistic pathogen, which will also explain the negative results. All of the fecal samples tested yielded PCR signals with Bacteroides-Prevotella 16S rRNA gene-specific primers (4), suggesting that PCR inhibition could not explain the absence of C. marimammalium-like signals in fecal samples that tested negative for the species-specific primers. The detection limit of both positive control tests (i.e., assays containing plasmid DNA in spiked and nonspiked bird fecal DNA) was 6 x 10–6 ng DNA per PCR. The PCR assay showed a detection limit of 0.006 ng of gull fecal DNA per reaction (Fig. 2).
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TABLE 2. Host specificity results of Gull2 assay against feces from various animals
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FIG. 2. Detection limits of the Gull-2 PCR assay. (A) Plasmid DNA (10-fold dilutions of plasmid DNA ranging from 6 to 6 x 10–7 ng) containing a targeted insert in reaction mixtures with no fecal DNA background from lane 1 to lane 8 (negative control in lane 9). (B) Tenfold dilutions of plasmid DNA (6 to 6 x 10–7ng) containing a targeted insert in reaction mixtures spiked with bird fecal DNA (10 ng/µl) made of equal amounts of chicken, turkey, and Canadian goose fecal DNA extracts from lane1 to lane 8 (only bird DNA in lane 9). (C) Tenfold dilutions of seagull fecal DNA ranging from 6 to 6 x 10–7 ng/PCR mixture from lane1 to lane 8 (negative control in lane 9).
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TABLE 3. Host distribution and estimated average copy number of gull-specific marker
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FIG. 3. Performance of C. marimammalium 16S rRNA gene PCR assay against 10-fold dilutions of seagull fecal DNA starting with 60 ng (indicated as 5 log units on the x axis) to 6 pg (indicated as 1 log unit on the x axis).
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Gull PCR-based signals in water samples.
C. marimammalium was found to be ubiquitous and specific to gull feces, suggesting that assays targeting this bacterial species might be used as an indicator of gull fecal pollution in MST studies. Gull contamination is prevalent in many coastal areas, as well as in recreational waters in the Great Lakes. However, thus far, no assays have been published that can determine the presence of gull fecal contamination in surface waters. To address the value of the C. marimammalium assay in detecting gull feces in environmental waters, we tested DNA extracts from waters presumed to have a history of gull contamination against the Gull-2 assay (Table 4). All samples suspected to have been impacted with gull feces showed strong PCR signals in the Gull-2 assay, suggesting that this assay can be used to track sources in different geographic locations. Additionally, we used the assay to test waters that are impacted by other waterfowl fecal sources (i.e., Canadian geese). Water samples collected from the Toledo Botanical Garden pond (Toledo, OH), which is known to be impacted by Canadian geese (i.e., as the only waterfowl species), showed an average of 26,900 fecal coliform CFU/100 ml (W. Von Sigler, personal communication) and were negative by the Gull2 assay. Samples taken from environmental waters known to be impacted by non-waterfowl sources (i.e., swine, cattle, chickens) were also negative. In contrast, all three samples taken from a site near the Toledo Botanical Garden pond where gulls are often seen (near Lake Erie) were positive. Similar results were obtained with freshwater samples collected from Wisconsin, California, and Ontario beaches known to be frequented by gulls. More importantly, the Gull-2 assay was positive for water samples collected over beach seasons at three different Lake Ontario beaches known to be highly contaminated by gull droppings (10). A library-dependent MST study at Bayfront Park Beach on Lake Ontario demonstrated that most of the E. coli contamination at this beach was from birds rather than municipal wastewater or pets (10). Our results are relevant to the latter study, as the previous assays used could not discriminate between the importance of gull droppings and that of Canada goose droppings at these sites. Overall, our results showed that the Gull-2 assay can be used to detect the presence of gull fecal impacts at different geographic locations and that it can be used across multiple seasons (i.e., it is temporally stable).
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TABLE 4. Detection of gull feces in environmental samples by the Gull2 assay
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We are grateful to Stacy Pfaller for access to her laboratory; to Don Stoeckel, Margie Lee, Ali Boehm, William Von Sigler, Jody Harwood, John Griffith, Julie Kinzelman, and Michael Yabsley for providing fecal and water samples; to Frances Gulland and Liz Wheeler (The Marine Mammalian Center) for providing fecal samples; and to Noreen Adcock, Dennis Lye, and Randy Revetta for providing bacterial strains.
Any opinions expressed in this paper are ours and do not necessarily reflect the official positions and policies of the United States Environmental Protection Agency. Any mention of products or trade names does not constitute a recommendation for use.
Published ahead of print on 9 May 2008. ![]()
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