A multi-marker assessment of sewage contamination in streams using human-associated indicator bacteria, human-specific viruses, and pharmaceuticals.

Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological (n = 21) and chemical (n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years. Five-day composite water samples (n = 98) were collected biweekly, and sewage influent samples (n = 25) were collected monthly at a Milwaukee, WI water reclamation facility. We found the vast majority of markers were not sensitive enough to detect sewage contamination. To compare analytes for monitoring applications, five consistently detected human sewage indicators were used to evaluate temporal patterns of sewage contamination, including microbiological (pepper mild mottle virus, human Bacteroides, human Lachnospiraceae) and chemical (acetaminophen, metformin) markers. The proportion of human sewage in each stream was estimated using the mean influent concentration from the water reclamation facility and the mean concentration of all stream samples for each sewage indicator marker. Estimates of instream sewage pollution varied by marker, differing by up to two orders of magnitude, but four of the five sewage markers characterized Underwood Creek (mean proportions of human sewage ranged 0.0025 % - 0.075 %) as less polluted than Menomonee River (proportions ranged 0.013 % - 0.14 %) by an order of magnitude more. Chemical markers correlated with each other and yielded higher estimates of sewage pollution than microbial markers, which exhibited greater temporal variability. Transport, attenuation, and degradation processes can influence chemical and microbial markers differently and cause variation in human sewage estimates. Given the range of potential human and ecological health effects of human sewage contamination, robust characterization of sewage contamination that uses multiple lines of evidence supports monitoring and research applications.

Anthropogenic particle concentrations and fluxes in an urban river are temporally variable and impacted by storm events.

Anthropogenic particles (AP), which include microplastics and other synthetic, semisynthetic, and anthropogenically modified materials, are pollutants of concern in aquatic ecosystems worldwide. Rivers are important conduits and retention sites for AP, and time series data on the movement of these particles in lotic ecosystems are needed to assess the role of rivers in the global AP cycle. Much research assessing AP pollution extrapolates stream loads based on single time point measurements, but lotic ecosystems are highly variable over time (e.g., seasonality and storm events). The accuracy of models describing AP dynamics in rivers is constrained by the limited studies that examine how frequent changes in discharge drive particle retention and transport. This study addressed this knowledge gap by using automated, high-resolution sampling to track AP concentrations and fluxes during multiple storm events in an urban river (Milwaukee River) and comparing these measurements to commonly monitored water quality metrics. AP concentrations and fluxes varied significantly across four storm events, highlighting the temporal variability of AP dynamics. When data from the sampling periods were pooled, there were increases in particle concentration and flux during the early phases of the storms, suggesting that floods may flush AP into the river and/or resuspend particles from the benthic zone. AP flux was closely linked to river discharge, suggesting large loads of AP are delivered downstream during storms. Unexpectedly, AP concentrations were not correlated with other simultaneously measured water quality metrics, including total suspended solids, fecal coliforms, chloride, nitrate, and sulfate, indicating that these metrics cannot be used to estimate AP. These data will contribute to more accurate models of particle dynamics in rivers and global plastic export to oceans. PRACTITIONER POINTS: Anthropogenic particle (AP) concentrations and fluxes in an urban river varied across four storm events. AP concentrations and fluxes were the highest during the early phases of the storms. Storms increased AP transport downstream compared with baseflow. AP concentrations did not correlate with other water quality metrics during storms.

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized. Flow composited river samples were collected over low-flow ( n = 89) and rainfall or snowmelt runoff events ( n = 130). Approximately 90% of samples had evidence of human fecal pollution, with highest loads from urban watersheds. Ruminant indicators were found in ∼60-100% of runoff-event samples in agricultural watersheds, with concentrations and loads related to cattle density. Rain depth, season, agricultural tile drainage, and human or cattle density explained variability in daily flux of human or ruminant indicators. Mapping host-associated indicator loads to watershed discharge points sheds light on the type, level, and possible health risk from fecal pollution entering the Great Lakes and can inform total maximum daily load implementation and other management practices to target specific fecal pollution sources.

High levels of sewage contamination released from urban areas after storm events: A quantitative survey with sewage specific bacterial indicators.

BACKGROUND: Past studies have demonstrated an association between waterborne disease and heavy precipitation, and climate change is predicted to increase the frequency of these types of intense storm events in some parts of the United States. In this study, we examined the linkage between rainfall and sewage contamination of urban waterways and quantified the amount of sewage released from a major urban area under different hydrologic conditions to identify conditions that increase human risk of exposure to sewage. METHODS AND FINDINGS: Rain events and low-flow periods were intensively sampled to quantify loads of sewage based on two genetic markers for human-associated indicator bacteria (human Bacteroides and Lachnospiraceae). Samples were collected at a Lake Michigan estuary and at three river locations immediately upstream. Concentrations of indicators were analyzed using quantitative polymerase chain reaction (qPCR), and loads were calculated from streamflow data collected at each location. Human-associated indicators were found during periods of low flow, and loads increased one to two orders of magnitude during rain events from stormwater discharges contaminated with sewage. Combined sewer overflow (CSO) events increased concentrations and loads of human-associated indicators an order of magnitude greater than heavy rainfall events without CSO influence. Human-associated indicator yields (load per km2 of land per day) were related to the degree of urbanization in each watershed. Contamination in surface waters were at levels above the acceptable risk for recreational use. Further, evidence of sewage exfiltration from pipes threatens drinking water distribution systems and source water. While this study clearly demonstrates widespread sewage contamination released from urban areas, a limitation of this study is understanding human exposure and illness rates, which are dependent on multiple factors, and gaps in our knowledge of the ultimate health outcomes. CONCLUSIONS: With the prediction of more intense rain events in certain regions due to climate change, sewer overflows and contamination from failing sewer infrastructure may increase, resulting in increases in waterborne pathogen burdens in waterways. These findings quantify hazards in exposure pathways from rain events and illustrate the additional stress that climate change may have on urban water systems. This information could be used to prioritize efforts to invest in failing sewer infrastructure and create appropriate goals to address the health concerns posed by sewage contamination from urban areas.

Human-Associated Indicator Bacteria and Human-Specific Viruses in Surface Water: A Spatial Assessment with Implications on Fate and Transport.

Hydrologic, seasonal, and spatial variability of sewage contamination was studied at six locations within a watershed upstream from water reclamation facility (WRF) effluent to define relative loadings of sewage from different portions of the watershed. Fecal pollution from human sources was spatially quantified by measuring two human-associated indicator bacteria (HIB) and eight human-specific viruses (HSV) at six stream locations in the Menomonee River watershed in Milwaukee, Wisconsin from April 2009 to March 2011. A custom, automated water sampler, which included HSV filtration, was deployed at each location and provided unattended, flow-weighted, large-volume (30-913 L) sampling. In addition, wastewater influent samples were composited over discrete 7 day periods from the two Milwaukee WRFs. Of the 8 HSV, only 3 were detected, present in up to 38% of the 228 stream samples, while at least 1 HSV was detected in all WRF influent samples. HIB occurred more often with significantly higher concentrations than the HSV in stream and WRF influent samples ( p < 0.05). HSV yield calculations showed a loss from upstream to the most-downstream sub-watershed of the Menomonee River, and in contrast, a positive HIB yield from this same sub-watershed emphasizes the complexity in fate and transport properties between HSV and HIB. This study demonstrates the utility of analyzing multiple HSV and HIB to provide a weight-of-evidence approach for assessment of fecal contamination at the watershed level, provides an assessment of relative loadings for prioritizing areas within a watershed, and demonstrates how loadings of HSV and HIB can be inconsistent, inferring potential differences in fate and transport between the two indicators of human fecal presence.

EcoBLMcrX, a classical modification-dependent restriction enzyme in Escherichia coli B: Characterization in vivo and in vitro with a new approach to cleavage site determination.

Here we characterize the modification-dependent restriction enzyme (MDE) EcoBLMcrX in vivo, in vitro and in its genomic environment. MDE cleavage of modified DNAs protects prokaryote populations from lethal infection by bacteriophage with highly modified DNA, and also stabilizes lineages by reducing gene import when sparse modification occurs in the wrong context. The function and distribution of MDE families are thus important. Here we describe the properties of EcoBLMcrX, an enzyme of the E. coli B lineage, in vivo and in vitro. Restriction in vivo and the genome location of its gene, ecoBLmcrX, were determined during construction and sequencing of a B/K-12 hybrid, ER2566. In classical restriction literature, this B system was named r6 or rglAB. Like many genome defense functions, ecoBLmcrX is found within a genomic island, where gene content is variable among natural E. coli isolates. In vitro, EcoBLMcrX was compared with two related enzymes, BceYI and NhoI. All three degrade fully cytosine-modified phage DNA, as expected for EcoBLMcrX from classical T4 genetic data. A new method of characterizing MDE specificity was developed to better understand action on fully-modified targets such as the phage that provide major evolutionary pressure for MDE maintenance. These enzymes also cleave plasmids with m5C in particular motifs, consistent with a role in lineage-stabilization. The recognition sites were characterized using a site-ranking approach that allows visualization of preferred cleavage sites when fully-modified substrates are digested. A technical constraint on the method is that ligation of one-nucleotide 5' extensions favors G:C over A:T approximately five-fold. Taking this bias into account, we conclude that EcoBLMcrX can cleave 3' to the modified base in the motif Rm5C|. This is compatible with, but less specific than, the site reported by others. Highly-modified site contexts, such as those found in base-substituted virulent phages, are strongly preferred.

Quantification of human-associated fecal indicators reveal sewage from urban watersheds as a source of pollution to Lake Michigan.

Sewage contamination of urban waterways from sewer overflows and failing infrastructure is a major environmental and public health concern. Fecal coliforms (FC) are commonly employed as fecal indicator bacteria, but do not distinguish between human and non-human sources of fecal contamination. Human Bacteroides and human Lachnospiraceae, two genetic markers for human-associated indicator bacteria, were used to identify sewage signals in two urban rivers and the estuary that drains to Lake Michigan. Grab samples were collected from the rivers throughout 2012 and 2013 and hourly samples were collected in the estuary across the hydrograph during summer 2013. Human Bacteroides and human Lachnospiraceae were highly correlated with each other in river samples (Pearson's r = 0.86), with average concentrations at most sites elevated during wet weather. These human indicators were found during baseflow, indicating that sewage contamination is chronic in these waterways. FC are used for determining total maximum daily loads (TMDLs) in management plans; however, FC concentrations alone failed to prioritize river reaches with potential health risks. While 84% of samples with >1000 CFU/100 ml FC had sewage contamination, 52% of samples with moderate (200-1000 CFU/100 ml) and 46% of samples with low (<200 CFU/100 ml) FC levels also had evidence of human sewage. Load calculations in the in the Milwaukee estuary revealed storm-driven sewage contamination varied greatly among events and was highest during an event with a short duration of intense rain. This work demonstrates urban areas have unrecognized sewage inputs that may not be adequately prioritized for remediation by the TMDL process. Further analysis using these approaches could determine relationships between land use, storm characteristics, and other factors that drive sewage contamination in urban waterways.

Sewage reflects the microbiomes of human populations.

UNLABELLED: Molecular characterizations of the gut microbiome from individual human stool samples have identified community patterns that correlate with age, disease, diet, and other human characteristics, but resources for marker gene studies that consider microbiome trends among human populations scale with the number of individuals sampled from each population. As an alternative strategy for sampling populations, we examined whether sewage accurately reflects the microbial community of a mixture of stool samples. We used oligotyping of high-throughput 16S rRNA gene sequence data to compare the bacterial distribution in a stool data set to a sewage influent data set from 71 U.S. cities. On average, only 15% of sewage sample sequence reads were attributed to human fecal origin, but sewage recaptured most (97%) human fecal oligotypes. The most common oligotypes in stool matched the most common and abundant in sewage. After informatically separating sequences of human fecal origin, sewage samples exhibited ~3× greater diversity than stool samples. Comparisons among municipal sewage communities revealed the ubiquitous and abundant occurrence of 27 human fecal oligotypes, representing an apparent core set of organisms in U.S. populations. The fecal community variability among U.S. populations was significantly lower than among individuals. It clustered into three primary community structures distinguished by oligotypes from either: Bacteroidaceae, Prevotellaceae, or Lachnospiraceae/Ruminococcaceae. These distribution patterns reflected human population variation and predicted whether samples represented lean or obese populations with 81 to 89% accuracy. Our findings demonstrate that sewage represents the fecal microbial community of human populations and captures population-level traits of the human microbiome. IMPORTANCE: The gut microbiota serves important functions in healthy humans. Numerous projects aim to define a healthy gut microbiome and its association with health states. However, financial considerations and privacy concerns limit the number of individuals who can be screened. By analyzing sewage from 71 cities, we demonstrate that geographically distributed U.S. populations share a small set of bacteria whose members represent various common community states within U.S. adults. Cities were differentiated by their sewage bacterial communities, and the community structures were good predictors of a city's estimated level of obesity. Our approach demonstrates the use of sewage as a means to sample the fecal microbiota from millions of people and its potential to elucidate microbiome patterns associated with human demographics.

Urban microbial ecology of a freshwater estuary of Lake Michigan.

Freshwater estuaries throughout the Great Lakes region receive stormwater runoff and riverine inputs from heavily urbanized population centers. While human and animal feces contained in this runoff are often the focus of source tracking investigations, non-fecal bacterial loads from soil, aerosols, urban infrastructure, and other sources are also transported to estuaries and lakes. We quantified and characterized this non-fecal urban microbial component using bacterial 16S rRNA gene sequences from sewage, stormwater, rivers, harbor/estuary, and the lake surrounding Milwaukee, WI, USA. Bacterial communities from each of these environments had a distinctive composition, but some community members were shared among environments. We used a statistical biomarker discovery tool to identify the components of the microbial community that were most strongly associated with stormwater and sewage to describe an "urban microbial signature," and measured the presence and relative abundance of these organisms in the rivers, estuary, and lake. This urban signature increased in magnitude in the estuary and harbor with increasing rainfall levels, and was more apparent in lake samples with closest proximity to the Milwaukee estuary. The dominant bacterial taxa in the urban signature were Acinetobacter, Aeromonas, and Pseudomonas, which are organisms associated with pipe infrastructure and soil and not typically found in pelagic freshwater environments. These taxa were highly abundant in stormwater and sewage, but sewage also contained a high abundance of Arcobacter and Trichococcus that appeared in lower abundance in stormwater outfalls and in trace amounts in aquatic environments. Urban signature organisms comprised 1.7% of estuary and harbor communities under baseflow conditions, 3.5% after rain, and >10% after a combined sewer overflow. With predicted increases in urbanization across the Great Lakes, further alteration of freshwater communities is likely to occur with potential long term impacts on the function of estuarine and nearshore ecosystems.

Systematically variable planktonic carbon metabolism along a land-to-lake gradient in a Great Lakes coastal zone.

During the summers of 2002-2013, we measured rates of carbon metabolism in surface waters of six sites across a land-to-lake gradient from the upstream end of drowned river-mouth Muskegon Lake (ML) (freshwater estuary) to 19 km offshore in Lake Michigan (LM) (a Great Lake). Despite considerable inter-year variability, the average rates of gross production (GP), respiration (R) and net production (NP) across ML (604 ± 58, 222 ± 22 and 381 ± 52 µg C L-1 day-1, respectively) decreased steeply in the furthest offshore LM site (22 ± 3, 55 ± 17 and -33 ± 15 µg C L-1day-1, respectively). Along this land-to-lake gradient, GP decreased by 96 ± 1%, whereas R only decreased by 75 ± 9%, variably influencing the carbon balance along this coastal zone. All ML sites were consistently net autotrophic (mean GP:R = 2.7), while the furthest offshore LM site was net heterotrophic (mean GP:R = 0.4). Our study suggests that pelagic waters of this Great Lakes coastal estuary are net carbon sinks that transition into net carbon sources offshore. Reactive and dynamic estuarine coastal zones everywhere may contribute similarly to regional and global carbon cycles.