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The complexity of fecal microbial communities and overlap among human and other animal sources have made it difficult to identify source-specific fecal indicator bacteria. However, the advent of next-generation sequencing technologies now provides increased sequencing power to resolve microbial community composition within and among environments. These data can be mined for information on source-specific phylotypes and/or assemblages of phylotypes (i.e., microbial signatures). We report the development of a new genetic marker for human fecal contamination identified through microbial pyrotag sequence analysis of the V6 region of the 16S rRNA gene. Sequence analysis of 37 sewage samples and comparison with database sequences revealed a human-associated phylotype within the Lachnospiraceae family, which was closely related to the genus Blautia. This phylotype, termed Lachno2, was on average the second most abundant fecal bacterial phylotype in sewage influent samples from Milwaukee, WI. We developed a quantitative PCR (qPCR) assay for Lachno2 and used it along with the qPCR-based assays for human Bacteroidales (based on the HF183 genetic marker), total Bacteroidales spp., and enterococci and the conventional Escherichia coli and enterococci plate count assays to examine the prevalence of fecal and human fecal pollution in Milwaukee's harbor. Both the conventional fecal indicators and the human-associated indicators revealed chronic fecal pollution in the harbor, with significant increases following heavy rain events and combined sewer overflows. The two human-associated genetic marker abundances were tightly correlated in the harbor, a strong indication they target the same source (i.e., human sewage). Human adenoviruses were routinely detected under all conditions in the harbor, and the probability of their occurrence increased by 154% for every 10-fold increase in the human indicator concentration. Both Lachno2 and human Bacteroidales increased specificity to detect sewage compared to general indicators, and the relationship to a human pathogen group suggests that the use of these alternative indicators will improve assessments for human health risks in urban waters.
Fecal pollution in urban waterways is a major impairment to water quality in cities across the United States (56), and waterborne disease risk remains a significant public health issue (3). There are numerous pathways by which urban waterways may become contaminated. Combined sewer overflows (CSOs) and sanitary sewer overflows (SSOs) garner the most attention, as these events introduce nearly 4 trillion liters of untreated sewage into the nation's waterways each year (57). However, less conspicuous routes such as stormwater drainage (1, 33, 41), upstream agricultural inputs (24), runoff from large impervious city surfaces (17, 41), and leaking sanitary sewers (40, 41, 45) may also deliver significant amounts of fecal pollution to waterways. These multiple modes of fecal pollution transport result in a variety of pollution source contributors, including humans, pets, urban wildlife, and agricultural animals. In order to mitigate or prevent future pollution events, it will be important to identify both the environmental conditions that promote pollution and the organisms contributing to the fecal pollution.
Typically, fecal pollution is assessed by measuring culturable levels of fecal coliforms, Escherichia coli, or enterococci (51), which have been found to correlate with health risks to swimmers (14, 37). However, these general indicators are less useful for investigating the source of fecal pollution because of their lack of host specificity (5, 18), a nonspecific relationship with human pathogens (31, 41, 42), and the ability of the indicators to persist and/or reproduce in nature (6, 8, 20, 60). As a result of these issues, several alternative fecal pollution detection assays have been developed (7, 12, 16), including many that were designed to detect and quantify human-derived sources (7, 21, 24, 32, 46, 48). Most of these indicators rely upon identifying a taxonomically narrow set of bacteria (e.g., a single species). Despite the relevance and increasing use of bacterially based human fecal indicators, each of these methods is incapable of discriminating between humans and at least one other animal source (48). In addition, a significant association between these novel indicators and the presence of human pathogens in the environment has yet to be established, although this is partly due to a lack of studies examining these relationships (31, 58).
Next-generation sequencing techniques make it possible to characterize a large portion of the single gene diversity of a microbial community. The human microbiome project is at the forefront of a wave of studies characterizing 16S rRNA gene microbial diversity from a vast number of environments (34, 53). With this in mind, it was recently suggested that leveraging the microbiome projects and applying new sequencing technologies (e.g., 454, Illumina, SOLiD, Ion Torrent) could identify many new source-specific targets and/or redefine approaches for tracking fecal pollution sources through the use of multitaxon signatures (29). In this previous study, the authors noted that the bacterial family Lachnospiraceae and the well-studied Bacteroidales order were particularly abundant in sewage and many individual human fecal samples, making these groups prime targets for identifying new source-associated fecal markers and/or microbial signatures.
Here we examined harbor water from Milwaukee, WI, for fecal contamination with conventional and alternative indicators and used pyrosequencing to characterize the harbor microbial community during dry weather, rain, and combined sewer overflow events. We hypothesized that human fecal pollution, including human pathogens, was entering the harbor outside of sewer overflow scenarios. We used pyrosequencing data to identify and then develop a new quantitative PCR (qPCR) assay for a small subset of Lachnospiraceae phylotypes that were highly abundant in sewage influent and prevalent in human fecal communities. We then leveraged both our own and publicly available data sets to further examine the specificity of the previously described total Bacteroidales spp. (13), human Bacteroidales (7, 21), and our new qPCR assay. Finally, adenovirus counts taken concurrently with our human fecal indicator data allowed us to assess how these markers related directly to the presence of human pathogens in the environment.
Thirty-seven wastewater treatment plant (WWTP) influent samples were taken from two major facilities servicing metropolitan Milwaukee, WI. Samples were collected from both the Jones Island (300 millions of gallons per day [MGD] maximum flow) and South Shore (250 MGD maximum flow) treatment plants on 20 April 2005; 18 April, 21 August, 16 October, 20 November, and 11 December 2007; 17 March, 1 April, 8 April, 28 May, 11 June, 10 July, 8 October, and 10 December 2008; and 31 March, 22 April, 13 May, and 5 August 2009: an additional Jones Island sample was collected on 21 August 2008. Samples were collected to a total volume of 1 liter from 24-h flow-weighted influent beginning at 6 a.m. on the preceding day to 6 a.m. on the stated collection day. The 24-hour samples were then filtered (100 ml or until filter clogging) through a 0.45-μm-pore-size mixed cellulose esters filter (Millipore, Billerica, MA) and frozen at −80°C until further processing.
Surface samples from water in Milwaukee's harbor were collected at a point of confluence for the Milwaukee, Menomonee, and Kinnickinnic Rivers (i.e., the harbor channel) but prior to discharge outside the breakwall into Lake Michigan (see the work of Mueller-Spitz et al.  for coordinate details). Samples were collected on 7 April, 1 May, 5 and 19 June, 17 and 27 July, 7, 9, 20, 21, and 22 August, 11 and 28 September, and 2 October 2007 and on 11 April, 20 May, 9, 10, 11, 13, 16, 17, and 24 June, 1 and 8 July, and 5 September 2008. Lake Michigan surface water samples were collected at a station 3.2 km east of Milwaukee's harbor on 23 June and 5 August 2010 and at a station 2.7 km from shore but 4.3 km north of Milwaukee's harbor on 5 August 2010. These three samples serve as uncontaminated controls for the harbor samples. For each of these harbor and lake samples, three surface water samples were collected, mixed, and subsampled into a 1-liter bottle. Each 1-liter bottle was stored on ice until being returned to the lab (within 3 h), and subsequently 200 ml (harbor) or 400 ml (lake) was filtered (no prefilter) onto a 0.22-μm-pore-size mixed cellulose esters filter (47-mm diameter; Millipore, Billerica, MA). Filters were folded and placed in 2-ml screw-cap tubes and then stored at −80°C until further processing.
To extract DNA from samples, frozen sample filters were removed from the freezer and immediately crushed into small pieces in the tube by using a sterile spatula. The frozen filter pieces were added to a tube containing a bead-beating matrix and buffers according to the standard protocol for the Fast DNA spin kit for soil (MP Biomedicals, Solon, OH). DNA extractions were further carried out according to the manufacturers' instructions. Samples sent for pyrosequencing were further purified using the MO BIO PowerClean DNA cleanup kit (MO BIO Laboratories Inc., Carlsbad, CA). DNA concentrations were measured using the NanoDrop ND-1000 (Thermo Fisher Scientific Inc., Pittsburgh, PA).
Three 16S rRNA gene 454 pyrosequencing data sets were queried for the presence of specific fecal-indicator bacteria. All data sets have been processed and stored as part of the VAMPS database (http://vamps.mbl.edu). The first data set consisted of the 37 WWTP influent samples described above. Of these samples, eight (Jones Island and South Shore samples from 20 April 2005 and 18 April, 21 August, and 11 December 2007) were sequenced and described previously (29). The remaining 29 samples were processed in the same manner as part of this study, with the V6 hypervariable region of the 16S rRNA gene being amplified, sequenced using a Roche genome sequencer GS-FLX, trimmed, quality controlled, and aligned (29). The amplification and quality control process for this 37-sample data set resulted in 1,062,510 bacterial sequence reads for analysis. The second data set consisted of 48 human fecal samples yielding 1,202,874 bacterial sequences for analysis. These samples were collected and deposited by Dethlefsen et al. (11) from five individuals before, during, and after treatment with antibiotics and by Turnbaugh et al. (52) from 11 families of lean and obese twins and their mothers; sample and sequence details can be obtained from their respective publications. The third data set, collected and deposited by Shanks et al. (47), consisted of 30 adult beef cattle fecal samples taken from cows at six different feed operations. The pyrosequencing data from these fecal samples resulted in 620,611 quality sequences for analysis. Sample and sequence details are described in the work of Shanks et al. (47). All described in silico analyses of the previously deposited data sets were performed directly for the present study.
In order to obtain a number of relatively long 16S rRNA gene sequences (~800 bp) containing the Lachno2 V6 region (see Table S1 in the supplemental material for the sequence), from which we could design a qPCR assay for Lachno2, we cloned and sequenced rRNA genes from Milwaukee sewage samples using taxon-specific primers. Sample DNA was amplified using a mixture of forward primers, one targeting the Clostridium coccoides group (CcocF ) and a newly designed primer, BF-063 (5′-AAG TGA CGG TAC CTG AAT AA-3′), targeting sequences closely related to the C. coccoides group that also contained the Lachno2 V6 region. The universal 1492R primer was used as the reverse primer. For each sample, four PCRs using the CcocF and 1492R primer set were pooled with one reaction using the BF-063 and 1492R primer set prior to PCR cleanup. This ratio was determined based on the number of exact matches to each primer among sequences contained in the Ribosomal Database Project (RDP) (9). PCR products were purified using Qiagen PCR purification kit (Qiagen Inc., Valencia, CA). Products were then cloned into the pCR2.1 vector by using the TOPO TA cloning kit (Invitrogen, Carlsbad, CA). Sequencing was carried out from the 1492R primer by using the ABI BigDye Terminator Kit (Applied Biosystems, Foster City, CA) on an ABI Prism 3700xi (Applied Biosystems, Foster City, CA). Sequences were trimmed for quality using PHRED (15). All quality sequences were analyzed for chimeras using Mallard (4). Sequences flagged by Mallard were analyzed using Chimera Check (9) and removed if determined to be chimeric.
A number of cloned sequences were identified as having the Lachno2 V6 sequence. Thirty-two of these sequences that spanned the diversity of clones containing the Lachno2 region and several near full-length sequences from isolates closely related to the clones were initially aligned using the FAST_ALIGNER ARB tool (27) before the alignment was heuristically adjusted using primary and secondary rRNA structure as a guide. After alignment, a mask excluding all gaps and trimming sequences to an equal length was applied. The resulting final alignment of 738 positions was used in neighbor-joining phylogenetic analysis in ARB with 1,000 bootstrap calculations.
Harbor water samples were analyzed using the U.S. Environmental Protection Agency methods for enterococci and E. coli enumeration. To enumerate these fecal indicators, samples were filtered through a 0.45-μm-pore-size nitrocellulose filter (47-mm diameter; Millipore, Billerica, MA), placed on modified mTEC (55) and MEI (54) agars, incubated for 24 h at 41°C (enterococci) or 44.5°C (E. coli), and counted for CFU. We note here that the method for E. coli enumeration differs from EPA Method 1603 (55) in that there was not a primary incubation at 35°C for 2 h. The volume of water filtered for each sample varied depending on the expected level of contamination.
In ARB, a PT server was constructed consisting of the sequenced sewage clones and several closely related bacterial taxa (including 2 to 4 sequences each from Lactococcus, Bacillus, Clostridium perfringens, Pseudomonas, Bacteroides, and Arcobacter). The probe design function was used to query the PT server for potential primer/probe regions of variability between the Lachno2 sequences and our database containing our clones and previously published sequences (Silva database , November 2009). Potential probe/primer sequences were obtained from the queries and rematched to the database to check for specificity. The Primer Express software (Applied Biosystems by Life Technologies) was used to analyze primers and probes for potential primer-dimer interactions and hairpins. The Lachno2 forward primer is 5′-TTC GCA AGA ATG AAA CTC AAA G-3′, the reverse complement of the universal C. coccoides primer Ccoc-R (28); the Lachno2 reverse primer is 5′-AAG GAA AGA TCC GGT TAA GGA TC-3′; and the probe sequence is 5′-(6-carboxyfluorescein [6-FAM])-ACC AAG TCT TGA CAT CCG-(minor groove binder [MGB])-3′.
Sequences matching the primers/probe for the Lachno2 qPCR assay and two previously designed fecal marker qPCR assays, total Bacteroidales spp. (13) and human Bacteroidales (7, 21), were identified with the RDP probe match feature allowing for one mismatch per primer/probe and matching only sequences from the RDP database where the quality criterion was set to good and length was ≥1,200 bp (59). All sequences matching these criteria for each primer/probe set (i.e., qPCR assay) were downloaded as an alignment from RDP. The V6 region from each sequence in the alignment (each qPCR assay has a separate alignment) was then extracted and used as a query against samples from the three V6 pyrosequencing data sets. Exact matches between the query V6 sequences for each qPCR assay and the V6 sequences in each sample in the three data sets were identified. The abundance of the matched V6 sequences in each sample for each assay were summed and divided by the total number of bacterial V6 sequences obtained in each sample, thereby providing a relative abundance calculation for each qPCR assay in each sample.
Quantitative PCR for all assays was carried out using an ABI StepOne real-time PCR system with TaqMan hydrolysis probe chemistry. Primer, probe, and target sequences for the total Bacteroidales spp. and enterococcal assays can be found in the work of Dick and Field (13) and of Ludwig and Schleifer (26), respectively. The qPCR assay for human Bacteroidales followed methods previously published by Kildare et al. (21), with the exception that we used the HF183 forward primer first reported by Bernhard and Field (7). Standard curves were generated during each run and consisted of a linearized plasmid containing the target sequence. Standard curves were run with DNA serially diluted from 1.5 × 106 to 1.5 × 101 copies/reaction. Standards were run in triplicate, and each sample was run in duplicate in a final volume of 25 μl with a final concentration of 1 μM for each primer, 80 nM for the probe, 5 μl of DNA diluted to 4 ng/μl, and 12.5 μl of an Applied Biosystems TaqMan master mix. Amplification consisted of the following cycles: 50°C for 2 min followed by 95°C for 10 min, and 40 cycles of denaturing at 95°C for 15 s followed by a combined annealing-elongation step at 60°C for 1 min. The amplification efficiency of the standard curves for the newly designed Lachno2 assay was 1.98. In previous studies, on the same river/harbor system examined here, we found inhibition in <1% of more than 350 water samples following dilution of extracted DNA to 4 ng/μl (41), the dilution also carried out in this study. Inhibition assays as described by Shanks et al. (48) were carried out for all samples using the Lachno2 qPCR assay, and no inhibition was detected.
For all qPCR assays, the data are reported as copy numbers per 100 ml of original sample water, which was calculated by taking into account the original water volume sampled, the resulting volume following a DNA extraction, the volume of extracted DNA entering the qPCRs, and the relationship of the qPCR standard curve to the fluorescence product of the qPCR amplification in each sample. Standard Pearson product-moment correlation coefficients (r) were calculated for the comparison of qPCR-based fecal indicator data. Log transformations were carried out on all data prior to use in Pearson's r calculations.
Sample collection end dates for sewage samples analyzed for viruses were 18 May, 8 June, 13 July, 10 August, 14 September, 12 October, 9 November, and 14 December 2009 and 11 January 2010; harbor sample collection dates are listed above. Adenovirus concentrations in sewage were measured from 4-liter, 7-day flow-weighted composite samples provided by the Milwaukee Metropolitan Sewerage District from the South Shore WWTP. The entire 4-liter volume was concentrated by polyethylene glycol flocculation (23) to 2- to 4-ml final concentrated sample volumes (FCSVs). Adenoviruses in harbor channel water were collected by continuous pumping of 100 to 200 liters through a glass wool filter (23) while the sampling boat made a transect along the width of the channel. Glass wool filters were eluted with 3% beef extract (wt/vol) containing 0.5 M glycine (pH 9.5), and the eluent was additionally concentrated by polyethylene glycol to a 2-ml FCSV. DNA was extracted from a 280-μl FCSV with the QIAamp DNA blood minikit and buffer AVL (Qiagen, Valencia, CA). qPCR was performed on a LightCycler 480 instrument (Roche Diagnostics, Mannheim, Germany) using the LightCycler 480 probes master kit (Roche Diagnostics). Six microliters of extracted DNA was added to 14 μl of master mix for a final reaction volume of 20 μl. Harbor water adenoviruses were quantified using the primers 5′-GGA CGC CTC GGA GTA CCT GA-3′ and 5′-CGC TGI GAC CIG TCT GTG G-3′ and the TaqMan 5′-CAC CGA TAC GTA CTT CAG CCT GGG T-3′ probe designed by Cromeans et al. (10), which primarily target serotypes 2, 5, 6, 40, and 41. Sewage adenovirus analysis, conducted later, relied on the primers and probes developed by Kuo et al. (22), which more broadly target adenovirus subgroups A, B, C, D, and F. Subgroups C and F include serotypes 2, 5, 6, 40, and 41. Thermocycling began with 95°C for 10 min followed by 45 cycles of 15 s at 94°C and 1 min at 60°C. All samples were checked for PCR inhibition following previously described methods for detecting hepatitis G virus cDNA seeded into qPCR mixtures containing sample DNA (23). The detection limit was one genomic copy of the viruses per 20-μl qPCR volume. A subsample from the sewage and harbor FCSVs was used for DNA extraction and qPCR for the human fecal markers as described above.
A logistic regression for the relationship between the sum abundance of the human fecal indicators (sum copies per ml in each sample of Lachno2 and human Bacteroidales) from qPCR data and adenovirus presence in the harbor water samples was carried out using the glm() function with a binomial distribution family specified in the R statistics package (R Development Core Team, 2007). The logistic regression was set up so that the adenovirus data were the dependent variable.
16S rRNA gene clone sequences identified in this study have GenBank nucleotide sequence accession numbers JF826248 to JF826279. The 16S rRNA gene pyrotag sequences generated for this study are available through the Visualization and Analysis of Microbial Population Structures (VAMPS) database (www.vamps.mbl.edu/).
Sequence analysis of 37 sewage influent samples revealed that the most common feces-associated phylotypes belonged to the taxonomic group Lachnospiraceae. A single Lachnospiraceae-associated phylotype, termed Lachno2, was the second most abundant human feces-associated phylotype in the sewage samples (mean relative abundance, 0.3%) (Fig. 1). The most abundant sewage feces-associated phylotype did not show specificity between human and cattle fecal samples (data not shown). Lachno2 was also abundant in a data set of human fecal samples collected in studies by Dethlefsen et al. (11) and Turnbaugh et al. (52) (Fig. 1) but was not detected in cattle fecal samples (47). The sample variability for Lachno2 among all sewage samples, which are comprised of a flow-weighted composite of ~1.1 million people, was much less (~20-fold) than the sample variability among individual human fecal samples.
Clone libraries targeting the C. coccoides group (28), which contains the Lachnospiraceae family, were constructed from Milwaukee WWTP samples. A total of 115 unique clones of the Lachno2 phylotype were identified. The longer sequence information provided by the 500- to 1,000-bp clone sequences revealed that the Lachno2 phylotype is most closely related to the isolate Blautia wexlerae WAL 14507, a Gram-positive fecal anaerobe, and several near-full-length clones termed Ruminococcus obeum (Fig. 2). Analysis of these clone sequences with the RDP classifier (59) suggested each belonged to the genus Blautia, as all sequences were classified as Blautia with 100% confidence. Sequence identity calculations demonstrated that clones representing the Lachno2 phylotype had relatively little sequence variation (mean sequence identity = 98.6%).
Primers and a probe were designed to target Lachno2 in a qPCR assay (see Materials and Methods). An RDP probe match analysis (0 mismatches for each primer/probe) against the public databases suggested high specificity for our Lachno2-based qPCR assay, as 696 of 706 matched sequences (>1,200 bp) were classified as Blautia. Of the 706 sequences, there were 19 unique V6 regions (see Table S1 in the supplemental material), which indicated that the qPCR assay targeted a slightly broader group than the unique Lachno2 phylotype. Based on the recovery of these phylotypes in the curated RDP data set (RDP criteria: ≥1,200 bp, quality = good, and “both” isolates and uncultured sequences), all but two of these phylotypes were recovered from human fecal content. Of the two nonhuman phylotypes, one was recovered from African elephant feces and the other from a mouse intestinal tract. Of the 19 qPCR-targeted phylotypes, the Lachno2 phylotype was the dominant phylotype in sewage samples (median = 88% of the recovered V6 sequences from the 19 phylotypes among 37 samples). Extending the allowed mismatches to one mismatch per primer/probe broadened the assay detection to 892 (882 classified as Blautia) total sequences and 66 unique V6 sequences (see Table S1 in the supplemental material).
In silico analysis, allowing one mismatch for each primer/probe sequence, revealed that sequences targeted by the total Bacteroidales spp. assay were highly variable and in some cases very abundant in individual fecal samples (up to 57.3% and 40.9% of total bacterial sequences in human and cattle fecal samples, respectively). In sewage, total Bacteroidales spp. were also highly abundant but were more evenly distributed among samples (up to 5.8% of total bacterial sequences) (Fig. 3). Likewise, the human Bacteroidales and Lachno2 assays targeted sequences that were abundant in the human fecal (up to 16.6% and 18.6% of total bacterial sequences, respectively) and sewage (up to 2.1% and 0.9%, respectively) data sets, but neither of these human-associated assays targeted abundant sequences in the cattle data set (Fig. 3). Of the five cow fecal samples containing Lachno2-related sequences, the highest percentage of Lachno2 observed was 0.02%, and all of the Lachno2 sequences associated with the cattle fecal samples were from clones harboring a mismatch in at least two of the three Lachno2 primers/probe (data not shown).
Conventional culture-based fecal indicators, E. coli and enterococci, and a qPCR-based fecal indicator for total Bacteroidales spp. (13) were measured in the channel of Milwaukee's harbor on 26 dates during late spring and summer in 2007 and 2008. The sample dates included dry periods (<0.5 in. of rain within 48 h), rain events (>0.5 in. rain within 48 h), CSO events, and post-CSO periods (within 5 days). In all cases, the fecal indicators revealed that fecal pollution was chronic in Milwaukee's harbor during the spring/summer period (Fig. 4). Levels on a quarter of the dry period dates exceeded the U.S. EPA criterion for safe recreational waters (235 CFU/100 ml) for E. coli, and levels on seven of nine dates sampled during rain events also exceeded these criteria. Both the E. coli and enterococci fecal indicators increased significantly from dry to rain events (t test, P value ≤ 0.05) and often showed 20- to 50-fold increases during CSOs, a period of sewage discharge into the harbor area (Fig. 4). Likewise, the qPCR-based total Bacteroidales spp. fecal indicator was detected in all samples, including dry-weather periods (minimum = 1,641 copies/100 ml) and increased significantly (t test, P value ≤ 0.05) during and after CSO events, in some cases reaching more than 3 million copies per 100 ml of harbor water (Fig. 4).
Human fecal pollution was detected by both the Lachno2 and human Bacteroidales qPCR assays in all harbor water samples tested, which included dry, rain, and CSO periods (Fig. 5A and B). The human Bacteroidales and Lachno2 assays for human fecal contamination showed a strong correlation (Pearson's r = 0.97, P ≤ 0.01; non-CSO data, r = 0.86, P ≤ 0.01) and similar concentrations in all samples (Fig. 5B). Dramatic increases, 100- to 1,000-fold, were observed for both human fecal markers during CSO events. Elevated but not significant mean, median, and maximum Lachno2 concentrations were observed during rain events (≥0.5 in. in 48 h) compared to nonrain events (<0.5 in. in 48 h) (Fig. 5A). The average ratio for the human Bacteroidales to total Bacteroidales spp. in sewage influent samples, a predominantly human fecal source, was 3.13% ± 0.96%. This ratio was also high in the harbor during CSOs (3.81% ± 1.24%) but was significantly lower in the non-CSO samples (1.68 ± 1.09%, t test P value ≤0.05).
The standard enterococcal qPCR assay for general fecal contamination also was strongly correlated to the Lachno2 assay for human fecal contamination (Pearson's r = 0.91, P ≤ 0.01) when all data were included and when CSO-related samples were excluded (Pearson's r = 0.82, P ≤ 0.01). Comparing the concentrations of these markers in the harbor also revealed a pattern (Fig. 5C); the enterococcal assay generally exhibited higher concentrations during the dry, rain, and post-CSO periods, whereas the Lachno2 assay exhibited in every case a higher concentration during CSOs (Fig. 5C).
Three Lake Michigan samples collected ≥3.2 km from the harbor served as environmental negative controls for the qPCR assays, as this distance from shore greatly reduces the amount of fecal pollution present under all environmental scenarios (i.e., dry, rain, CSO). In all three samples, the Lachno2 and human Bacteroidales qPCR assays were below the detection threshold for the assays (50 copies per 100 ml of water), while the total Bacteroidales assay revealed levels slightly above this detection threshold at 1.8 × 102, 1.1 × 103, and 2.2 × 102 copies per 100 ml of water.
Adenovirus abundance (genome copies per 100 ml) varied by 3 orders of magnitude in sewage influent samples (Fig. 6A) and even with limited data exhibited a trend toward much higher abundance in spring and early summer than in other times of the year (Fig. 6A). The variation in adenovirus abundance contrasts with the human fecal indicator (Lachno2 plus human Bacteroidales) abundance, which was relatively stable across the sewage influent samples (maximum 2-fold variation in abundance) (Fig. 6A). Despite the difference in variability, there was a relationship between the abundance of human fecal indicators and adenovirus occurrence (Fig. 6B). A logistic regression model exhibited a good fit (goodness of fit, P value = 0.46, where P > 0.05 indicates a good model fit) and indicated that the odds of observing adenovirus in the harbor increased by 154% for every 10-fold increase in the human indicator abundance.
In this study, we examined the prevalence of human fecal waste in Milwaukee's harbor. Previous attempts to identify fecal pollution sources and assess risk from pollution events have led to the development of human-associated fecal pollution assays, many of which target the order Bacteroidales, a group of fecal anaerobes (21, 24, 32, 46, 48). However, the exact specificity and applicability of these assays in varied environments remain unknown (48); thus, we sought to identify another human fecal indicator that could complement existing genetic markers. Relying upon multiple taxa to create a human-specific indicator signature should improve source specificity and provide more consistent results among environments given likely differences in decay rates for various types of organisms.
The introduction of next-generation sequencing technology has allowed the undertaking of large microbial community sequencing projects (2, 29, 34, 39). These projects now provide a resource from which we can examine the specificity of tens of thousands of microbial phylotypes to a specific environmental habitat(s). In a previous microbial community study of WWTP influent, McLellan et al. (29) suggested that the Lachnospiraceae family would be an ideal bacterial group for fecal source tracking because of its abundance in WWTP influent samples. Closer examination of the microbial community data here revealed that a single phylotype (Lachno2), which is closely related to the genus Blautia (Fig. 3), was especially abundant in both human fecal samples and Milwaukee sewage samples but was not present in cattle fecal samples, a common fecal pollution source in the harbor (Fig. 2). The identification of database sequences and clone sequences from our own libraries containing Lachno2 further confirmed that it belonged to a phylogenetically narrow group and would therefore be an excellent candidate for a host-associated fecal indicator.
Lachno2 was consistently present, but its relative abundance varied largely from human to human, which was in contrast to the small relative abundance variation among the sewage samples (Fig. 2). Previous large sequencing efforts related to the human microbiome have indicated immense variation in the fecal communities among humans (38, 52), which has prompted some researchers to suggest that a core fecal signature will be difficult to identify (52). The sewage influent samples in this study spanned a 3-year period and represented annual, seasonal, and geographic (two WWTP service areas) variation in metropolitan Milwaukee's human population. The smaller variation in the sewage influent samples, which represent a composite of up to 1.1 million human fecal communities, suggests that the identification of core microbes in human fecal content may be identified through examination of WWTP influent samples. Future studies that examine a larger number of human fecal communities in addition to WWTP influent samples from a large geographic range could provide the needed insight to tease apart the core human fecal community.
We developed a qPCR assay for the Lachno2 phylotype and made use of the pyrosequencing data sets to examine in silico the specificity of this assay as well as previously defined total and human Bacteroidales qPCR assays. This process revealed that our assay likely targets more taxa than those associated with the unique Lachno2 phylotype, but the range of phylotypes remained phylogenetically narrow (98.9% of sequences targeted were RDP classified as Blautia), were associated with humans and not our comparison host, cattle (Fig. 3), and were almost exclusively human associated in public 16S rRNA gene databases. Our in silico analysis also revealed high person-to-person variability in the relative abundance of the total and human Bacteroidales assays in human fecal samples (Fig. 3). Interestingly, the human Bacteroidales assay targeted sequences that were a significantly (P ≤ 0.001) larger part of the community in the human fecal samples from the study of Dethlefsen et al. (11) than from the study of Turnbaugh et al. (52), while the Lachno2 marker exhibited the inverse of this relationship (P ≤ 0.001) (Fig. 3). The complementary nature of these two marker assays suggests that using them in tandem or as part of a larger profile may provide a more consistent measure of human fecal contamination than using either on its own.
Fecal pollution of urban waterways is a major contributor to waterborne illnesses in the United States and remains a widespread problem for both coastal freshwater and marine ecosystems (3, 56, 57). While simply detecting fecal pollution provides evidence of health risks, identifying the pollution source is ultimately the information needed for effective remediation efforts to take place that will significantly reduce risk. In Milwaukee, WI, major fecal pollution events in nearshore waters occur each year during combined and sanitary sewer overflows. During these periods, untreated sewage is discharged to Milwaukee's rivers and subsequently the harbor and Lake Michigan, thereby providing us an opportunity to use conventional and alternative fecal indicators to compare known human fecal contamination events with other times in which human fecal pollution should not be present.
In this study, we found that fecal pollution is chronic in Milwaukee's harbor (Fig. 4). This persistent input into the harbor suggests multiple delivery routes outside of reported sewer overflows. In urban environments, it has been demonstrated that human fecal pollution may enter receiving bodies from stormwater runoff/outfall discharge, leaking sanitary pipes, and illicit sanitary sewer connections (40, 41). Potential routes of unrecognized sewage inputs have been documented in the Milwaukee area (41), and our identification of significantly increased human fecal indicators following rain events provides further evidence that stormwater may be an important source of human-derived fecal pollution.
As human fecal content is a likely source for human health risks from fecal and/or sewage pollution, we focused on the contribution of human fecal pollution to the “total” fecal pollution in the harbor. Using the ratio of human Bacteroidales to total Bacteroidales spp. as a proxy for relative human fecal contribution to total fecal pollution (41), we observed that CSO periods in the harbor had ratios similar to what was seen for sewage, which suggests that untreated sewage is the main source of fecal pollution during these periods. During the non-CSO periods, although the human Bacteroidales component of fecal contamination remained high, the ratio dropped to roughly half of what is typically found in sewage, which suggests that both human and nonhuman sources contribute to the chronic fecal pollution in the harbor. Likewise, a comparison of the Lachno2 and enterococcal qPCR assays revealed an abundance ratio shift from a low to high Lachno2/enterococcus ratio when switching from non-CSO to CSO periods (Fig. 5C). As the enterococcal qPCR assay targets human and multiple animal fecal sources, these data further provide evidence of a decreased human fecal contribution to total fecal pollution in the harbor during non-CSO events. Nonhuman fecal pollution in urban environments can occur from multiple primary sources, including birds, domestic pets, and urban wildlife (19, 25, 49, 50). Further efforts in Milwaukee's urban environment are needed to identify and quantify all of the contributing sources.
Other studies have shown that the human Bacteroidales assay may detect bacteria from nonhuman mammal fecal material, although this cross-reactivity appears fairly minor (48). Excluding cattle, it is unknown whether the Lachno2 assay has cross-reactivity for bacteria from nonhuman animal fecal material. However, a tight correlation was observed between the human Bacteroidales and Lachno2 assays in the harbor (Fig. 5C). It is unlikely that this tight correlation would exist unless the markers had detected the same source microbial community and this source was a major polluter of the harbor. It is also unlikely that these two bacterial indicators, as members of different phyla, have an identical host distribution; thus, we suggest that their correlation in the harbor water is strong evidence that the indicators specifically identify human sewage in our system. Because there may be no single genetic marker that is exclusive to a single source, a community approach (characterizing a suite of markers) may be a very effective alternative (29). This is especially true in light of the large variability among human fecal communities (52). The tight correlation of the Lachno2 and human Bacteroidales assays suggests that these two markers are an excellent starting point for development of this source-specific community approach to human fecal pollution detection in surface waters.
Although human fecal indicators have revealed the presence of human fecal pollution in surface waters, a strong link between these indicators and human pathogen presence has yet to be established (58). Our examination of adenovirus, a group commonly used as an index for the presence of human viruses in water (31, 35), showed that a linear abundance relationship is not present between the human indicators and virus abundance in sewage; therefore, we did not expect to observe a direct correlation in harbor water. Viral titers in sewage are known to fluctuate with season (43, 44). We also observed large fluctuations in adenovirus abundance in sewage across a year, which contrasted the relative stability over time of the bacterial human fecal markers (Fig. 6A). Further, different ecological forcings upon the bacteria and viruses once in the harbor waters may cause different retention times for each group and thus also affect a potential linear relationship. Our results did, however, suggest that it is likely to find human adenovirus in the harbor when the bacterial human fecal indicator abundance is high (Fig. 6B). In fact, a logistic regression model revealed that a 10-fold increase in human indicator abundance in the harbor results in a 154% increase in the odds of observing adenovirus; thus, it may be feasible to use a bacterial human fecal signature to assess pathogen risk. The abundance of these bacterial indicators, which is 2 to 4 orders of magnitude greater then the abundance of human adenovirus in sewage, provides increased sensitivity for detecting human fecal pollution in freshwaters and makes these markers particularly suitable for tracking sewage contamination. These results also add credence to the hypothesis that tracking multiple indicators and/or human pathogens may be required to adequately assess human health risk from human fecal contamination of surface waters.
We thank Stuart E. Jones for his insightful discussion and technical assistance in applying a logistic regression model to the data, Steve Corsi for providing sewage samples for adenovirus analysis, Beth Sauer for her helpful comments on previous versions of the manuscript, and three reviewers for their astute comments.
Funding for this work was provided by NOAA's Oceans and Human Health Initiative extramural grant program (grant no. NA05NOS4781243), NIAID (grant no. 1 R21 AI076970-01A1), and University of Wisconsin Sea Grant Institute under grants from the National Sea Grant College Program, NOAA, the U.S. Department of Commerce, and the State of Wisconsin (grant no. NA10OAR4170070).
†Supplemental material for this article may be found at http://aem.asm.org/.
Published ahead of print on 29 July 2011.