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.

Separating signal from noise in wastewater data: An algorithm to identify community-level COVID-19 surges in real time

Wastewater monitoring has provided health officials with early warnings for new COVID-19 outbreaks, but to date, no approach has been validated to distinguish signal (sustained surges) from noise (background variability) in wastewater data to alert officials to the need for heightened public health response. We analyzed 62 wk of data from 19 sites participating in the North Carolina Wastewater Monitoring Network to characterize wastewater metrics around the Delta and Omicron surges. We found that wastewater data identified outbreaks 4 to 5 d before case data (reported on the earlier of the symptom start date or test collection date), on average. At most sites, correlations between wastewater and case data were similar regardless of how wastewater concentrations were normalized and whether calculated with county-level or sewershed-level cases, suggesting that officials may not need to geospatially align case data with sewershed boundaries to gain insights into disease transmission. Although wastewater trend lines captured clear differences in the Delta versus Omicron surge trajectories, no single wastewater metric (detectability, percent change, or flow-population normalized viral concentrations) reliably signaled when these surges started. After iteratively examining different combinations of these three metrics, we developed the Covid-SURGE (Signaling Unprecedented Rises in Groupwide Exposure) algorithm, which identifies unprecedented signals in the wastewater data. With a true positive rate of 82%, a false positive rate of 7%, and strong performance during both surges and in small and large sites, our algorithm provides public health officials with an automated way to flag community-level COVID-19 surges in real time.

Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs

BACKGROUND

In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field.

OBJECTIVES

We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system.

DISCUSSION

Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.

Halophilic bacteria in a Lake Michigan drainage basin as potential biological indicators of chloride-impacted freshwaters

There are few biological indicators for freshwater systems subjected to high chloride levels. Freshwater systems receive many forms of chloride such as road salts (e.g., NaCl, CaCl₂, MgCl₂), fertilizers (e.g., KCl), and year-round water softener pollution. The goal our study was to investigate Halomonadaceae populations as prospective biological indicators of chloride-impacted freshwaters. The bacterial family Halomonadaceae are halophiles that generally require the presence of salt to survive, which make them an attractive candidate in determining chloride impaired areas. Field sediment surveys assessed how salt tolerant and halophilic bacteria abundance corresponded to chloride and conductivity measurements. Colony forming unit (CFU) counts on modified M9 6% NaCl plates (w/v) at urbanized sites compared to the rural sites had highest counts during winter and spring when chloride concentrations were also highest. Select isolates identified as Halomonadaceae through 16S rRNA sequencing were kept as active cultures to determine the NaCl concentration and temperature preference that resulted in the isolates optimal growth. Isolates tested under 5 °C (cold) grew optimally in 2 % NaCl (w/v), whereas under 18 °C (warm), isolates showed optimal growth at 6 % NaCl. The majority of isolates had maximum growth in the warmer temperature, however, select isolates grew better in the cold temperature. Culture-independent methods were used and identified Halomonadaceae were widespread and permeant members of the microbial community in a Lake Michigan drainage basin. Quantitative polymerase chain reaction (qPCR) targeting Halomonadaceae genera demonstrated that abundance varied by site, but overall were present throughout the year. However, community sequencing revealed there were a large relative proportion of specific Halomonadaceae populations present in winter versus summer. Methods targeting salt tolerant bacteria and specific members of Halomonadaceae appears to be a promising approach to assess chloride-impacted areas to better understand the long-term ecological impacts as we continue to salinize freshwater resources.

Guts of the Urban Ecosystem: Microbial Ecology of Sewer Infrastructure

Microbes have inhabited the oceans and soils for millions of years and are uniquely adapted to their habitat. In contrast, sewer infrastructure in modern cities dates back only ~150 years. Sewer pipes transport human waste and provide a view into public health, but the resident organisms that likely modulate these features are relatively unexplored. Here, we show that the bacterial assemblages sequenced from untreated wastewater in 71 U.S. cities were highly coherent at a fine sequence level, suggesting that urban infrastructure separated by great spatial distances can give rise to strikingly similar communities. Within the overall microbial community structure, temperature had a discernible impact on the distribution patterns of closely related amplicon sequence variants, resulting in warm and cold ecotypes. Two bacterial genera were dominant in most cities regardless of their size or geographic location; on average, Arcobacter accounted for 11% and Acinetobacter 10% of the entire community. Metagenomic analysis of six cities revealed these highly abundant resident organisms carry clinically important antibiotic resistant genes blaCTX-M, blaOXA, and blaTEM. In contrast, human fecal bacteria account for only ~13% of the community; therefore, antibiotic resistance gene inputs from human sources to the sewer system could be comparatively small, which will impact measurement capabilities when monitoring human populations using wastewater. With growing awareness of the metabolic potential of microbes within these vast networks of pipes and the ability to examine the health of human populations, it is timely to increase our understanding of the ecology of these systems. IMPORTANCE Sewer infrastructure is a relatively new habitat comprised of thousands of kilometers of pipes beneath cities. These wastewater conveyance systems contain large reservoirs of microbial biomass with a wide range of metabolic potential and are significant reservoirs of antibiotic resistant organisms; however, we lack an adequate understanding of the ecology or activity of these communities beyond wastewater treatment plants. The striking coherence of the sewer microbiome across the United States demonstrates that the sewer environment is highly selective for a particular microbial community composition. Therefore, results from more in-depth studies or proven engineering controls in one system could be extrapolated more broadly. Understanding the complex ecology of sewer infrastructure is critical for not only improving our ability to treat human waste and increasing the sustainability of our cities but also to create scalable and effective sewage microbial observatories, which are inevitable investments of the future to monitor health in human populations.

Rainfall leads to elevated levels of antibiotic resistance genes within seawater at an Australian beach

Anthropogenic waste streams can be major sources of antibiotic resistant microbes within the environment, creating a potential risk to public health. We examined patterns in the occurrence of a suite of antibiotic resistance genes (ARGs) and their links to enteric bacteria at a popular swimming beach in Australia that experiences intermittent contamination by sewage, with potential points of input including stormwater drains and a coastal lagoon. Samples were collected throughout a significant rainfall event (40.8 mm over 3 days) and analysed using both qPCR and 16S rRNA amplicon sequencing. Before the rainfall event, low levels of faecal indicator bacteria and a microbial source tracking human faeces (sewage) marker (Lachno3) were observed. These levels increased over 10x following rainfall. Within lagoon, drain and seawater samples, levels of the ARGs sulI, dfrA1 and qnrS increased by between 1 and 2 orders of magnitude after 20.4 mm of rain, while levels of tetA increased by an order of magnitude after a total of 40.8 mm. After 40.8 mm of rain sulI, tetA and qnrS could be detected 300 m offshore with levels remaining high five days after the rain event. Highest levels of sewage markers and ARGs were observed adjacent to the lagoon (when opened) and in-front of the stormwater drains, pinpointing these as the points of ARG input. Significant positive correlations were observed between all ARGs, and a suite of Amplicon Sequence Variants that were identified as stormwater drain indicator taxa using 16S rRNA amplicon sequencing data. Of note, some stormwater drain indicator taxa, which exhibited correlations to ARG abundance, included the human pathogens Arcobacter butzleri and Bacteroides fragilis. Given that previous research has linked high levels of ARGs in recreationally used environments to antimicrobial resistant pathogen infections, the observed patterns indicate a potentially elevated human health risk at a popular swimming beach following significant rainfall events.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Optical Properties of Water for Prediction of Wastewater Contamination, Human-Associated Bacteria, and Fecal Indicator Bacteria in Surface Water at Three Watershed Scales

Relations between spectral absorbance and fluorescence properties of water and human-associated and fecal indicator bacteria were developed for facilitating field sensor applications to estimate wastewater contamination in waterways. Leaking wastewater conveyance infrastructure commonly contaminates receiving waters. Methods to quantify such contamination can be time consuming, expensive, and often nonspecific. Human-associated bacteria are wastewater specific but require discrete sampling and laboratory analyses, introducing latency. Human sewage has fluorescence and absorbance properties different than those of natural waters. To assist real-time field sensor development, this study investigated optical properties for use as surrogates for human-associated bacteria to estimate wastewater prevalence in environmental waters. Three spatial scales were studied: Eight watershed-scale sites, five subwatershed-scale sites, and 213 storm sewers and open channels within three small watersheds (small-scale sites) were sampled (996 total samples) for optical properties, human-associated bacteria, fecal indicator bacteria, and, for selected samples, human viruses. Regression analysis indicated that bacteria concentrations could be estimated by optical properties used in existing field sensors for watershed and subwatershed scales. Human virus occurrence increased with modeled human-associated bacteria concentration, providing confidence in these regressions as surrogates for wastewater contamination. Adequate regressions were not found for small-scale sites to reliably estimate bacteria concentrations likely due to inconsistent local sanitary sewer inputs.

SARS-CoV-2 Wastewater Surveillance for Public Health Action

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.

SARS-CoV-2 Wastewater Surveillance for Public Health Action

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.

A weight-of-evidence approach for identifying potential sources of untreated sewage inputs into a complex urbanized catchment

The Hawkesbury-Nepean River (HNR) is the largest catchment in the Sydney region and is undergoing unprecedented population growth. The HNR system receives a mix of anthropogenic inputs such as treated sewage, stormwater and agricultural runoff. Combined, these can diminish the ecological system health and pose potential concerns to human health. Of particular concern are inputs of untreated sewage, that can occur due to a range of different reasons including illegal point source discharges, failure of the sewerage network, and overloading of wastewater treatment plants during storm events. Here, we present findings of an intensive assessment across the HNR catchment where we used a weight-of-evidence (WOE) approach to identify untreated sewage contamination in surface waters against the background of treated effluent and diffuse inputs during post high flow conditions. Total nitrogen and phosphorus concentrations were used to assess treated effluent and diffuse inputs, and microbial analysis, including both culture-based traditional methods for E. coli and enterococci and qPCR analysis of Bacteroides and Lachnospiraceae, were used to assess raw sewage contamination. Despite a background of diffuse inputs from recent high flow events and the influence of treated wastewater, we found no gradient of faecal contamination along the HNR system or its tributaries. We observed two sites with evidence of untreated sewage contamination, where the human markers Bacteroides and Lachnospiraceae qPCR copy numbers were high. The biological and chemical approaches suggested these latter two hotspots originate from an industrial runoff source and possibly from a dry weather sewage leak. Our findings demonstrate the potential of a WOE approach in the assessment of human faecal signal in an urban river that can also pinpoint small sources of contamination as a strategy that can reshape the way monitoring is performed and the chemical end-points chosen to provide pertinent information on the potential risks to aquatic system health.

Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of metainformation to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what metainformation should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.

Microbial Communities Associated with Farmed Genypterus chilensis: Detection in Water Prior to Bacterial Outbreaks Using Culturing and High-Throughput Sequencing

The red conger eel (Genypterus chilensis, Guichenot) is a native species included in the Chilean Aquaculture Diversification Program due to high commercial demand. In the context of intensified farming, prior reports link two disease outbreaks with emerging pathogens in the Vibrio and Tenacibaculum genera. However, the roles remain unclear for the bacterial community and each specific bacterium is associated with the rearing environment for healthy specimens. The success of red conger eel farming therefore warrants research into the bacterial composition of aquaculture conditions and the antimicrobial susceptibilities thereof. This study used culturing methods and high-throughput sequencing to describe the bacterial community associated with water in which G. chilensis was farmed. With culturing methods, the predominant genera were Vibrio (21.6%), Pseudolteromonas (15.7%), Aliivibrio (13.7%), and Shewanella (7.8%). Only a few bacterial isolates showed amylase, gelatinase, or lipase activity, and almost all showed inhibition zones to commonly-used antibiotics in aquaculture. By contrast, high-throughput sequencing established Paraperlucidibaca, Colwellia, Polaribacter, Saprospiraceae, and Tenacibaculum as the predominant genera, with Vibrio ranking twenty-seventh in abundance. High-throughput sequencing also established a link between previous outbreaks with increased relative abundances of Vibrio and Tenacibaculum. Therefore, monitoring the presence and abundance of these potential pathogens could be useful in providing prophylactic measures to prevent future outbreaks.

The unexpected habitat in sewer pipes for the propagation of microbial communities and their imprint on urban waters

Modern urban sewer pipe infrastructure is a unique niche where microbes can thrive. Arcobacter, Acinetobacter, Aeromonas, and Trichococcus are among the organisms that dominate the microbial community of sewage influent, but are not major members of human fecal microbiome, drinking water, or groundwater. Pipe resident communities in untreated sewage are distinct from sewer biofilm communities. Because of their high biomass, these organisms likely have a role in biotransformation of waste during conveyance and could represent an important inoculum for treatment plants. Studies demonstrate stormwater systems act as direct conduits for sewage to surface waters, releasing organisms propagated in sewer pipes. Frequent occurrence of these pipe residents, in particular Arcobacter, demonstrates the extent that urban infrastructure impacts rivers, lakes, and urban coasts worldwide.

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.

Fecal source identification using random forest

BACKGROUND

Clostridiales and Bacteroidales are uniquely adapted to the gut environment and have co-evolved with their hosts resulting in convergent microbiome patterns within mammalian species. As a result, members of Clostridiales and Bacteroidales are particularly suitable for identifying sources of fecal contamination in environmental samples. However, a comprehensive evaluation of their predictive power and development of computational approaches is lacking. Given the global public health concern for waterborne disease, accurate identification of fecal pollution sources is essential for effective risk assessment and management. Here, we use random forest algorithm and 16S rRNA gene amplicon sequences assigned to Clostridiales and Bacteroidales to identify common fecal pollution sources. We benchmarked the accuracy, consistency, and sensitivity of our classification approach using fecal, environmental, and artificial in silico generated samples.

RESULTS

Clostridiales and Bacteroidales classifiers were composed mainly of sequences that displayed differential distributions (host-preferred) among sewage, cow, deer, pig, cat, and dog sources. Each classifier correctly identified human and individual animal sources in approximately 90% of the fecal and environmental samples tested. Misclassifications resulted mostly from false-positive identification of cat and dog fecal signatures in host animals not used to build the classifiers, suggesting characterization of additional animals would improve accuracy. Random forest predictions were highly reproducible, reflecting the consistency of the bacterial signatures within each of the animal and sewage sources. Using in silico generated samples, we could detect fecal bacterial signatures when the source dataset accounted for as little as ~ 0.5% of the assemblage, with ~ 0.04% of the sequences matching the classifiers. Finally, we developed a proxy to estimate proportions among sources, which allowed us to determine which sources contribute the most to observed fecal pollution.

CONCLUSION

Random forest classification with 16S rRNA gene amplicons offers a rapid, sensitive, and accurate solution for identifying host microbial signatures to detect human and animal fecal contamination in environmental samples.

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.

Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes

Nitrogen fixation in the surface ocean impacts global marine nitrogen bioavailability and thus microbial primary productivity. Until now, cyanobacterial populations have been viewed as the main suppliers of bioavailable nitrogen in this habitat. Although PCR amplicon surveys targeting the nitrogenase reductase gene have revealed the existence of diverse non-cyanobacterial diazotrophic populations, subsequent quantitative PCR surveys suggest that they generally occur in low abundance. Here, we use state-of-the-art metagenomic assembly and binning strategies to recover nearly one thousand non-redundant microbial population genomes from the TARA Oceans metagenomes. Among these, we provide the first genomic evidence for non-cyanobacterial diazotrophs inhabiting surface waters of the open ocean, which correspond to lineages within the Proteobacteria and, most strikingly, the Planctomycetes. Members of the latter phylum are prevalent in aquatic systems, but have never been linked to nitrogen fixation previously. Moreover, using genome-wide quantitative read recruitment, we demonstrate that the discovered diazotrophs were not only widespread but also remarkably abundant (up to 0.3% of metagenomic reads for a single population) in both the Pacific Ocean and the Atlantic Ocean northwest. Our results extend decades of PCR-based gene surveys, and substantiate the importance of heterotrophic bacteria in the fixation of nitrogen in the surface ocean.

A Randomized Controlled Trial of an Intensive Nutrition Intervention Versus Standard Nutrition Care to Avoid Excess Weight Gain After Kidney Transplantation: The INTENT Trial

OBJECTIVE

Excessive weight gain is common after kidney transplantation and increases cardiovascular risk. The aim of this randomized controlled trial was to determine whether an intensive nutrition and exercise intervention delivered alongside routine post-transplant care would reduce post-transplant weight gain.

DESIGN

Single-blind, randomized controlled trial.

SUBJECTS AND SETTING

Adult kidney transplant recipients at a regional transplant center were recruited during routine outpatient clinic visits in the first month after transplant. Patients with a body mass index >40 kg/m² or <18.5 kg/m², severe malnutrition, or ongoing medical complications were excluded.

INTERVENTION

Participants were randomized to intensive nutrition intervention (individualized nutrition and exercise counselling; 12 dietitian visits; 3 exercise physiologist visits over 12 months) or to standard nutrition care (guideline based; 4 dietitian visits).

MAIN OUTCOME MEASURES

The primary outcome was weight at 6 months after transplant adjusted for baseline weight, obesity, and gender, analyzed using analysis of covariance. The secondary outcomes included body composition, biochemistry, quality of life, and physical function.

RESULTS

Thirty-seven participants were randomized to the intensive intervention (n = 19) or to standard care (n = 18); one intensive group participant withdrew before baseline. Weight increased between baseline, 6 and 12 months (78.0 ± 13.7 [standard deviation], 79.6 ± 13.0 kg, 81.6 ± 12.9 kg; mean change 4.6% P < .001) but at 6 months did not differ significantly between the groups: 77.0 ± 12.4 kg (intensive); 82.2 ± 13.4 kg (standard); difference in adjusted means 0.4 kg (95% confidence interval: -2.2 to 3.0 kg); analysis of covariance P = .7. No between-group differences in secondary outcomes were observed. Across the whole cohort, total body protein and physical function (gait speed, sit to stand, grip strength, physical activity, and quality of life [all but 2 domains]) improved. However, adverse changes were seen for total body fat, HbA1c, and fasting glucose across the cohort.

CONCLUSIONS

Kidney transplant recipients in the first year after transplant did not benefit from an intensive nutrition intervention compared with standard nutrition care, although weight gain was relatively modest in both groups.

Sewage loading and microbial risk in urban waters of the Great Lakes

Despite modern sewer system infrastructure, the release of sewage from deteriorating pipes and sewer overflows is a major water pollution problem in US cities, particularly in coastal watersheds that are highly developed with large human populations. We quantified fecal pollution sources and loads entering Lake Michigan from a large watershed of mixed land use using host-associated indicators. Wastewater treatment plant influent had stable concentrations of human Bacteroides and human Lachnospiraceae with geometric mean concentrations of 2.77 × 10⁷ and 5.94 × 10⁷ copy number (by quantitative PCR) per 100 ml, respectively. Human-associated indicator levels were four orders of magnitude higher than norovirus concentrations, suggesting that these human-associated bacteria could be sensitive indicators of pathogen risk. Norovirus concentrations in these same samples were used in calculations for quantitative microbial risk assessment. Assuming a typical recreational exposure to untreated sewage in water, concentrations of 7,800 copy number of human Bacteroides per 100 mL or 14,000 copy number of human Lachnospiraceae per 100 mL corresponded to an illness risk of 0.03. These levels were exceeded in estuarine waters during storm events with greater than 5 cm of rainfall. Following overflows from combined sewer systems (which must accommodate both sewage and stormwater), concentrations were 10-fold higher than under rainfall conditions. Automated high frequency sampling allowed for loads of human-associated markers to be determined, which could then be related back to equivalent volumes of untreated sewage that were released. Evidence of sewage contamination decreased as ruminant-associated indicators increased approximately one day post-storm, demonstrating the delayed impact of upstream agricultural sources on the estuary. These results demonstrate that urban areas are a diffuse source of sewage contamination to urban waters and that storm-driven release of sewage, particularly when sewage overflows occur, creates a serious though transient human health risk.

Freshwater Recirculating Aquaculture System Operations Drive Biofilter Bacterial Community Shifts around a Stable Nitrifying Consortium of Ammonia-Oxidizing Archaea and Comammox Nitrospira

Recirculating aquaculture systems (RAS) are unique engineered ecosystems that minimize environmental perturbation by reducing nutrient pollution discharge. RAS typically employ a biofilter to control ammonia levels produced as a byproduct of fish protein catabolism. Nitrosomonas (ammonia-oxidizing), Nitrospira, and Nitrobacter (nitrite-oxidizing) species are thought to be the primary nitrifiers present in RAS biofilters. We explored this assertion by characterizing the biofilter bacterial and archaeal community of a commercial scale freshwater RAS that has been in operation for >15 years. We found the biofilter community harbored a diverse array of bacterial taxa (>1000 genus-level taxon assignments) dominated by Chitinophagaceae (~12%) and Acidobacteria (~9%). The bacterial community exhibited significant composition shifts with changes in biofilter depth and in conjunction with operational changes across a fish rearing cycle. Archaea also were abundant, and were comprised solely of a low diversity assemblage of Thaumarchaeota (>95%), thought to be ammonia-oxidizing archaea (AOA) from the presence of AOA ammonia monooxygenase genes. Nitrosomonas were present at all depths and time points. However, their abundance was >3 orders of magnitude less than AOA and exhibited significant depth-time variability not observed for AOA. Phylogenetic analysis of the nitrite oxidoreductase beta subunit (nxrB) gene indicated two distinct Nitrospira populations were present, while Nitrobacter were not detected. Subsequent identification of Nitrospira ammonia monooxygenase alpha subunit genes in conjunction with the phylogenetic placement and quantification of the nxrB genotypes suggests complete ammonia-oxidizing (comammox) and nitrite-oxidizing Nitrospira populations co-exist with relatively equivalent and stable abundances in this system. It appears RAS biofilters harbor complex microbial communities whose composition can be affected directly by typical system operations while supporting multiple ammonia oxidation lifestyles within the nitrifying consortium.

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.

A unique assemblage of cosmopolitan freshwater bacteria and higher community diversity differentiate an urbanized estuary from oligotrophic Lake Michigan

Water quality is impacted significantly by urbanization. The delivery of increased nutrient loads to waterways is a primary characteristic of this land use change. Despite the recognized effects of nutrient loading on aquatic systems, the influence of urbanization on the bacterial community composition of these systems is not understood. We used massively-parallel sequencing of bacterial 16S rRNA genes to examine the bacterial assemblages in transect samples spanning the heavily urbanized estuary of Milwaukee, WI to the relatively un-impacted waters of Lake Michigan. With this approach, we found that genera and lineages common to freshwater lake epilimnia were common and abundant in both the high nutrient, urban-impacted waterways, and the low nutrient Lake Michigan. Although the two environments harbored many taxa in common, we identified a significant change in the community assemblage across the urban-influence gradient, and three distinct community features drove this change. First, we found the urban-influenced waterways harbored significantly greater bacterial richness and diversity than Lake Michigan (i.e., taxa augmentation). Second, we identified a shift in the relative abundance among common freshwater lineages, where acI, acTH1, Algoriphagus and LD12, had decreased representation and Limnohabitans, Polynucleobacter, and Rhodobacter had increased representation in the urban estuary. Third, by oligotyping 18 common freshwater genera/lineages, we found that oligotypes (highly resolved sequence clusters) within many of these genera/lineages had opposite preferences for the two environments. With these data, we suggest many of the defined cosmopolitan freshwater genera/lineages contain both oligotroph and more copiotroph species or populations, promoting the idea that within-genus lifestyle specialization, in addition to shifts in the dominance among core taxa and taxa augmentation, drive bacterial community change in urbanized waters.

The microbiome of urban waters

More than 50% of the world's population lives in urban centers. As collection basins for landscape activity, urban waters are an interface between human activity and the natural environment. The microbiome of urban waters could provide insight into the impacts of pollution, the presence of human health risks, or the potential for long-term consequences for these ecosystems and the people who depend upon them. An integral part of the urban water cycle is sewer infrastructure. Thousands of miles of pipes line cities as part of wastewater and stormwater systems. As stormwater and sewage are released into natural waterways, traces of human and animal microbiomes reflect the sources and magnitude of fecal pollution and indicate the presence of pollutants, such as nutrients, pathogens, and chemicals. Non-fecal organisms are also released as part of these systems. Runoff from impervious surfaces delivers microbes from soils, plants and the built environment to stormwater systems. Further, urban sewer infrastructure contains its own unique microbial community seemingly adapted to this relatively new artificial habitat. High microbial densities are conveyed via pipes to waterways, and these organisms can be found as an urban microbial signature imprinted on the natural community of rivers and urban coastal waters. The potential consequences of mass releases of non-indigenous microorganisms into natural waters include creation of reservoirs for emerging human pathogens, altered nutrient flows into aquatic food webs, and increased genetic exchange between two distinct gene pools. This review highlights the recent characterization of the microbiome of urban sewer and stormwater infrastructure and its connection to and potential impact upon freshwater systems.

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.

Blautia and Prevotella sequences distinguish human and animal fecal pollution in Brazil surface waters

Untreated sewage discharges and limited agricultural manure management practices contribute to fecal pollution in rural Brazilian waterways. Most microbial source tracking studies have focused on Bacteroidales, and few have tested host-specific indicators in underdeveloped regions. Sequencing of sewage and human and animal feces with Illumina HiSeq revealed Prevotellaceae as the most abundant family in humans, with Lachnospiraceae and Ruminococcaceae also comprising a large proportion of the microbiome. These same families were also dominant in animals. Bacteroides, the genus containing the most commonly utilized human-specific marker in the United States was present in very low abundance. We used oligotyping to identify Prevotella and Blautia sequences that can distinguish human fecal contamination. Thirty-five of 61 Blautia oligotypes and 13 of 108 Prevotella oligotypes in humans were host-specific or highly abundant (i.e. host-preferred) compared to pig, dog, horse and cow sources. Certain human Prevotella and Blautia oligotypes increased more than an order of magnitude along a polluted river transect in rural Brazil, but traditional fecal indicator levels followed a steady or even decreasing trend. While both Prevotella and Blautia oligotypes distinguished human and animal fecal pollution in Brazil surface waters, Blautia appears to contain more discriminatory and globally applicable markers for tracking sources of fecal pollution.

Population dynamics and ecology of Arcobacter in sewage

Arcobacter species are highly abundant in sewage where they often comprise approximately 5-11% of the bacterial community. Oligotyping of sequences amplified from the V4V5 region of the 16S rRNA gene revealed Arcobacter populations from different cities were similar and dominated by 1-3 members, with extremely high microdiversity in the minor members. Overall, nine subgroups within the Arcobacter genus accounted for >80% of the total Arcobacter sequences in all samples analyzed. The distribution of oligotypes varied by both sample site and temperature, with samples from the same site generally being more similar to each other than other sites. Seven oligotypes matched with 100% identity to characterized Arcobacter species, but the remaining 19 abundant oligotypes appear to be unknown species. Sequences representing the two most abundant oligotypes matched exactly to the reference strains for A. cryaerophilus group 1B (CCUG 17802) and group 1A (CCUG 17801(T)), respectively. Oligotype 1 showed generally lower relative abundance in colder samples and higher relative abundance in warmer samples; the converse was true for Oligotype 2. Ten other oligotypes had significant positive or negative correlations between temperature and proportion in samples as well. The oligotype that corresponded to A. butzleri, the Arcobacter species most commonly isolated by culturing in sewage studies, was only the eleventh most abundant oligotype. This work suggests that Arcobacter populations within sewer infrastructure are modulated by temperature. Furthermore, current culturing methods used for identification of Arcobacter fail to identify some abundant members of the community and may underestimate the presence of species with affinities for growth at lower temperatures. Understanding the ecological factors that affect the survival and growth of Arcobacter spp. in sewer infrastructure may better inform the risks associated with these emerging pathogens.

Sources and distribution of surface water fecal contamination and prevalence of schistosomiasis in a Brazilian village

BACKGROUND

The relationship between poor sanitation and the parasitic infection schistosomiasis is well-known, but still rarely investigated directly and quantitatively. In a Brazilian village we correlated the spatial concentration of human fecal contamination of its main river and the prevalence of schistosomiasis.

METHODS

We validated three bacterial markers of contamination in this population by high throughput sequencing of the 16S rRNA gene and qPCR of feces from local residents. The qPCR of genetic markers from the 16S rRNA gene of Bacteroides-Prevotella group, Bacteroides HF8 cluster, and Lachnospiraceae Lachno2 cluster as well as sequencing was performed on georeferenced samples of river water. Ninety-six percent of residents were examined for schistosomiasis.

FINDINGS

Sequence of 16S rRNA DNA from stool samples validated the relative human specificity of the HF8 and Lachno 2 fecal indicators compared to animals. The concentration of fecal contamination increased markedly along the river as it passed an increasing proportion of the population on its way downstream as did the sequence reads from bacterial families associated with human feces. Lachnospiraceae provided the most robust signal of human fecal contamination. The prevalence of schistosomiasis likewise increased downstream. Using a linear regression model, a significant correlation was demonstrated between the prevalence of S. mansoni infection and local concentration of human fecal contamination based on the Lachnospiraceae Lachno2 cluster (r2 0.53) as compared to the correlation with the general fecal marker E. coli (r2 0.28).

INTERPRETATION

Fecal contamination in rivers has a downstream cumulative effect. The transmission of schistosomiasis correlates with very local factors probably resulting from the distribution of human fecal contamination, the limited movement of snails, and the frequency of water contact near the home. In endemic regions, the combined use of human associated bacterial markers and GIS analysis can quantitatively identify areas with risk for schistosomiasis as well as assess the efficacy of sanitation and environmental interventions for prevention.

The effect of intensive nutrition interventions on weight gain after kidney transplantation: protocol of a randomised controlled trial

BACKGROUND

Weight gain and obesity are common after kidney transplantation, particularly during the first year. Obesity is a risk factor for the development of new-onset diabetes after transplantation, and is associated with reduced graft survival. There is a lack of evidence for effective interventions to prevent weight gain after kidney transplantation.

METHODS/DESIGN

The effect of INTEnsive Nutrition interventions on weight gain after kidney Transplantation (INTENT) trial is a single-blind (outcomes assessor), randomised controlled trial to assess the effect of intensive nutrition interventions, including exercise advice, on weight gain and metabolic parameters in the first year after transplantation. Participants will be randomised during the first post-transplant month to either standard care (four visits with a renal dietitian over twelve months) or intensive nutrition intervention (eight visits with a renal dietitian over the first six months, four visits over the second six months, and three visits over the first six months with an exercise physiologist). In the intensive intervention group, nutrition counselling will be provided using motivational interviewing techniques to encourage quality engagement. Collaborative goal setting will be used to develop personalised nutrition care plans. Individualised advice regarding physical activity will be provided by an exercise physiologist. The primary outcome of the study is weight at six months after transplant, adjusted for baseline (one month post-transplant) weight, obesity and gender. Secondary outcomes will include changes in weight and other anthropometric measures over 12 months, body composition (in vivo neutron activation analysis, total body potassium, dual-energy X-ray absorptiometry, and bioelectrical impedance), biochemistry (fasting glucose, lipids, haemoglobin A1c and insulin), dietary intake and nutritional status, quality of life, and physical function.

DISCUSSION

There are currently few randomised clinical trials of nutrition interventions after kidney transplantation. The INTENT trial will thus provide important data on the effect of intensive nutrition interventions on weight gain after transplant and the associated metabolic consequences. Additionally, by assessing changes in glucose metabolism, the study will also provide data on the feasibility of undertaking larger multi-centre trials of nutrition interventions to reduce the incidence or severity of diabetes after transplantation.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry Number: ACTRN12614000155695.

Discovering new indicators of fecal pollution

Fecal pollution indicators are essential to identify and remediate contamination sources and protect public health. Historically, easily cultured facultative anaerobes such as fecal coliforms, Escherichia coli, or enterococci have been used but these indicators generally provide no information as to their source. More recently, molecular methods have targeted fecal anaerobes, which are much more abundant in humans and other mammals, and some strains appear to be associated with particular host sources. Next-generation sequencing and microbiome studies have created an unprecedented inventory of microbial communities associated with fecal sources, allowing reexamination of which taxonomic groups are best suited as informative indicators. The use of new computational methods, such as oligotyping coupled with well-established machine learning approaches, is providing new insights into patterns of host association. In this review we examine the basis for host-specificity and the rationale for using 16S rRNA gene targets for alternative indicators and highlight two taxonomic groups, Bacteroidales and Lachnospiraceae, which are rich in host-specific bacterial organisms. Finally, we discuss considerations for using alternative indicators for water quality assessments with a particular focus on detecting human sewage sources of contamination.

The polycyclic aromatic hydrocarbon degradation potential of Gulf of Mexico native coastal microbial communities after the Deepwater Horizon oil spill

The Deepwater Horizon (DWH) blowout resulted in oil transport, including polycyclic aromatic hydrocarbons (PAHs) to the Gulf of Mexico shoreline. The microbial communities of these shorelines are thought to be responsible for the intrinsic degradation of PAHs. To investigate the Gulf Coast beach microbial community response to hydrocarbon exposure, we examined the functional gene diversity, bacterial community composition, and PAH degradation capacity of a heavily oiled and non-oiled beach following the oil exposure. With a non-expression functional gene microarray targeting 539 gene families, we detected 28,748 coding sequences. Of these sequences, 10% were uniquely associated with the severely oil-contaminated beach and 6.0% with the non-oiled beach. There was little variation in the functional genes detected between the two beaches; however the relative abundance of functional genes involved in oil degradation pathways, including polycyclic aromatic hydrocarbons (PAHs), were greater in the oiled beach. The microbial PAH degradation potentials of both beaches, were tested in mesocosms. Mesocosms were constructed in glass columns using sands with native microbial communities, circulated with artificial sea water and challenged with a mixture of PAHs. The low-molecular weight PAHs, fluorene and naphthalene, showed rapid depletion in all mesocosms while the high-molecular weight benzo[α]pyrene was not degraded by either microbial community. Both the heavily oiled and the non-impacted coastal communities showed little variation in their biodegradation ability for low molecular weight PAHs. Massively-parallel sequencing of 16S rRNA genes from mesocosm DNA showed that known PAH degraders and genera frequently associated with oil hydrocarbon degradation represented a major portion of the bacterial community. The observed similar response by microbial communities from beaches with a different recent history of oil exposure suggests that Gulf Coast beach communities are primed for PAH degradation.

Comparison of bacterial communities in sands and water at beaches with bacterial water quality violations

Recreational water quality, as measured by culturable fecal indicator bacteria (FIB), may be influenced by persistent populations of these bacteria in local sands or wrack, in addition to varied fecal inputs from human and/or animal sources. In this study, pyrosequencing was used to generate short sequence tags of the 16S hypervariable region ribosomal DNA from shallow water samples and from sand samples collected at the high tide line and at the intertidal water line at sites with and without FIB exceedance events. These data were used to examine the sand and water bacterial communities to assess the similarity between samples, and to determine the impact of water quality exceedance events on the community composition. Sequences belonging to a group of bacteria previously identified as alternative fecal indicators were also analyzed in relationship to water quality violation events. We found that sand and water samples hosted distinctly different overall bacterial communities, and there was greater similarity in the community composition between coastal water samples from two distant sites. The dissimilarity between high tide and intertidal sand bacterial communities, although more similar to each other than to water, corresponded to greater tidal range between the samples. Within the group of alternative fecal indicators greater similarity was observed within sand and water from the same site, likely reflecting the anthropogenic contribution at each beach. This study supports the growing evidence that community-based molecular tools can be leveraged to identify the sources and potential impact of fecal pollution in the environment, and furthermore suggests that a more diverse bacterial community in beach sand and water may reflect a less contaminated site and better water quality.

Shifts in the microbial community composition of Gulf Coast beaches following beach oiling

Microorganisms associated with coastal sands serve as a natural biofilter, providing essential nutrient recycling in nearshore environments and acting to maintain coastal ecosystem health. Anthropogenic stressors often impact these ecosystems, but little is known about whether these disturbances can be identified through microbial community change. The blowout of the Macondo Prospect reservoir on April 20, 2010, which released oil hydrocarbons into the Gulf of Mexico, presented an opportunity to examine whether microbial community composition might provide a sensitive measure of ecosystem disturbance. Samples were collected on four occasions, beginning in mid-June, during initial beach oiling, until mid-November from surface sand and surf zone waters at seven beaches stretching from Bay St. Louis, MS to St. George Island, FL USA. Oil hydrocarbon measurements and NOAA shoreline assessments indicated little to no impact on the two most eastern beaches (controls). Sequence comparisons of bacterial ribosomal RNA gene hypervariable regions isolated from beach sands located to the east and west of Mobile Bay in Alabama demonstrated that regional drivers account for markedly different bacterial communities. Individual beaches had unique community signatures that persisted over time and exhibited spatial relationships, where community similarity decreased as horizontal distance between samples increased from one to hundreds of meters. In contrast, sequence analyses detected larger temporal and less spatial variation among the water samples. Superimposed upon these beach community distance and time relationships, was increased variability in bacterial community composition from oil hydrocarbon contaminated sands. The increased variability was observed among the core, resident, and transient community members, indicating the occurrence of community-wide impacts rather than solely an overprinting of oil hydrocarbon-degrading bacteria onto otherwise relatively stable sand population structures. Among sequences classified to genus, Alcanivorax, Alteromonas, Marinobacter, Winogradskyella, and Zeaxanthinibacter exhibited the largest relative abundance increases in oiled sands.

A microbial signature approach to identify fecal pollution in the waters off an urbanized coast of Lake Michigan

Urban coasts receive watershed drainage from ecosystems that include highly developed lands with sewer and stormwater infrastructure. In these complex ecosystems, coastal waters are often contaminated with fecal pollution, where multiple delivery mechanisms that often contain multiple fecal sources make it difficult to mitigate the pollution. Here, we exploit bacterial community sequencing of the V6 and V6V4 hypervariable regions of the bacterial 16S rRNA gene to identify bacterial distributions that signal the presence of sewer, fecal, and human fecal pollution. The sequences classified to three sewer infrastructure-associated bacterial genera, Acinetobacter, Arcobacter, and Trichococcus, and five fecal-associated bacterial families, Bacteroidaceae, Porphyromonadaceae, Clostridiaceae, Lachnospiraceae, and Ruminococcaceae, served as signatures of sewer and fecal contamination, respectively. The human fecal signature was determined with the Bayesian source estimation program SourceTracker, which we applied to a set of 40 sewage influent samples collected in Milwaukee, WI, USA to identify operational taxonomic units (≥ 97 % identity) that were most likely of human fecal origin. During periods of dry weather, the magnitudes of all three signatures were relatively low in Milwaukee's urban rivers and harbor and nearly zero in Lake Michigan. However, the relative contribution of the sewer and fecal signature frequently increased to > 2 % of the measured surface water communities following sewer overflows. Also during combined sewer overflows, the ratio of the human fecal pollution signature to the fecal pollution signature in surface waters was generally close to that of sewage, but this ratio decreased dramatically during dry weather and rain events, suggesting that nonhuman fecal pollution was the dominant source during these weather-driven scenarios. The qPCR detection of two human fecal indicators, human Bacteroides and Lachno2, confirmed the urban fecal footprint in this ecosystem extends to at least 8 km offshore.

Sewage reflects the distribution of human faecal Lachnospiraceae

Faecal pollution contains a rich and diverse community of bacteria derived from animals and humans, many of which might serve as alternatives to the traditional enterococci and Escherichia coli faecal indicators. We used massively parallel sequencing (MPS) of the 16S rRNA gene to characterize microbial communities from wastewater treatment plant (WWTP) influent sewage from 12 cities geographically distributed across the USA. We examined members of the Clostridiales, which included the families Clostridiaceae, Lachnospiraceae and Ruminococcaceae for their potential as sewage indicators. Lachnospiraceae was one of the most abundant groups of faecal bacteria in sewage, and several Lachnospiraceae high-abundance sewage pyrotags occurred in at least 46 of 48 human faecal samples. Clone libraries targeting Clostridium coccoides (C. coccoides) in sewage samples demonstrated that Lachnospiraceae-annotated V6 pyrotags encompassed the previously reported C. coccoides group. We used oligotyping to profile the genus Blautia within Lachnospiraceae and found oligotypes comprised of 24 entropy components that showed patterns of host specificity. These findings suggest that indicators based on Blautia might have the capacity to discriminate between different faecal pollution sources. Development of source-specific alternative indicators would enhance water quality assessments, which leads to improved ecosystem health and reduced human health risk due to waterborne disease.

Acinetobacter, Aeromonas and Trichococcus populations dominate the microbial community within urban sewer infrastructure

We evaluated the population structure and temporal dynamics of the dominant community members within sewage influent from two wastewater treatment plants (WWTPs) in Milwaukee, WI. We generated > 1.1 M bacterial pyrotag sequences from the V6 hypervariable region of 16S rRNA genes from 38 influent samples and two samples taken upstream in the sanitary sewer system. Only a small fraction of pyrotags from influent samples (∼ 15%) matched sequences from human faecal samples. The faecal components of the sewage samples included enriched pyrotag populations from Lactococcus and Enterobacteriaceae relative to their fractional representation in human faecal samples. In contrast to the large number of distinct pyrotags that represent faecal bacteria such as Lachnospiraceae and Bacteroides, only one or two unique V6 sequences represented Acinetobacter, Aeromonas and Trichococcus, which collectively account for nearly 35% of the total sewage community. Two dominant Acinetobacter V6 pyrotags (designated Acineto tag 1 and Acineto tag 2) fluctuated inversely with a seasonal pattern over a 3-year period, suggesting two distinct Acinetobacter populations respond differently to ecological forcings in the system. A single nucleotide change in the V6 pyrotags accounted for the difference in these populations and corresponded to two phylogenetically distinct clades based on full-length sequences. Analysis of wavelet functions, derived from a mathematical model of temporal fluctuations, demonstrated that other abundant sewer associated populations including Trichococcus and Aeromonas had temporal patterns similar to either Acineto tag 1 or Acineto tag 2. Populations with related temporal fluctuations were found to significantly correlate with the same WWTP variables (5-day BOD, flow, ammonia, total phosphorous and suspended solids). These findings illustrate that small differences in V6 sequences can represent phylogenetically and ecologically distinct taxa. This work provides insight into microbial community composition and dynamics within the defined environment of urban sewer infrastructure.

Lachnospiraceae and Bacteroidales alternative fecal indicators reveal chronic human sewage contamination in an urban harbor

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.

Detection of the human specific Bacteroides genetic marker provides evidence of widespread sewage contamination of stormwater in the urban environment

Human sewage contamination of surface waters is a major human health concern. We found urban stormwater systems that collect and convey runoff from impervious surfaces act as a conduit for sewage originating from breeches in sanitary sewer infrastructure. A total of 828 samples at 45 stormwater outfalls were collected over a four-year period and assessed by culture based methods, PCR, and quantitative PCR (qPCR) to test for traditional and alternative indicators of fecal pollution. All outfalls had the HF183 (human) Bacteroides genetic marker detected in at least one sample, suggesting sewage contamination is nearly ubiquitous in the urban environment. However, most outfalls were intermittently positive, ranging from detection in 11%-100% of the samples. Positive results did not correlate with seasonality, rainfall amounts, or days since previous rainfall. Approximately two-thirds of the outfalls had high (>5000 copy number, i.e. CN, per 100 ml) or moderate levels (1000-5000 CN per 100 ml) of the human Bacteroides genetic marker. Escherichia coli (E. coli) and enterococci levels did not correlate to human Bacteroides. A total of 66% of all outfall samples had standard fecal indicator levels above 10,000 CFU per 100 ml. A tiered assessment using this benchmark to identify high priority sites would have failed to flag 35% of the samples that had evidence of sewage contamination. In addition, high fecal indicators would have flagged 33% of samples as priority that had low or no evidence of sewage. Enteric virus levels in one outfall with high levels of the human Bacteroides genetic marker were similar to untreated wastewater, which illustrates stormwater can serve as a pathway for pathogen contamination. The major source of fecal pollution at four of five river sites that receive stormwater discharge appeared to be from sewage sources rather than non-human sources based on the ratios of human Bacteroides to total Bacteroides spp. This study shows the feasibility and benefits of employing molecular methods to test for alternative indicators of fecal pollution to identify sewage sources and potential health risks and for prioritization of remediation efforts.

Association between rainfall and pediatric emergency department visits for acute gastrointestinal illness

BACKGROUND

Microbial water contamination after periods of heavy rainfall is well described, but its link to acute gastrointestinal illness (AGI) in children is not well known.

OBJECTIVES

We hypothesize an association between rainfall and pediatric emergency department (ED) visits for AGI that may represent an unrecognized, endemic burden of pediatric disease in a major U.S. metropolitan area served by municipal drinking water systems.

METHODS

We conducted a retrospective time series analysis of visits to the Children's Hospital of Wisconsin ED in Wauwatosa, Wisconsin. Daily visit totals of discharge International Classification of Diseases, 9th Revision codes of gastroenteritis or diarrhea were collected along with daily rainfall totals during the study period from 2002 to 2007. We used an autoregressive moving average model, adjusting for confounding variables such as sewage release events and season, to look for an association between daily visits and rainfall after a lag of 1-7 days.

RESULTS

A total of 17,357 AGI visits were identified (mean daily total, 7.9; range, 0-56). Any rainfall 4 days prior was significantly associated with an 11% increase in AGI visits. Expected seasonal effects were also seen, with increased AGI visits in winter months.

CONCLUSIONS

We observed a significant association between rainfall and pediatric ED visits for AGI, suggesting a waterborne component of disease transmission in this population. The observed increase in ED visits for AGI occurred in the absence of any disease outbreaks reported to public health officials in our region, suggesting that rainfall-associated illness may be underestimated. Further study is warranted to better address this association.

Reliability of mCP method for identification of Clostridium perfringens from faecal polluted aquatic environments

AIMS

The purpose of the work was to evaluate the mCP method to correctly identify and enumerate Clostridium perfringens that are present in surface waters impacted by a mixture of faecal pollution sources.

METHODS

Clostridium perfringens were enumerated and isolated from sewage influent, surface water and suspended sediments using the mCP method. Molecular characterization of isolates was performed using species-specific PCR, along with full-length sequencing of the 16S rRNA gene for a subset of isolates.

RESULTS

The environmental isolates were presumptively identified as C. perfringens based on utilization of sucrose, inability to ferment cellobiose and a positive action for acid phosphatase activity. All isolates (n = 126) were classified as C. perfringens based on positive results with species-specific PCR with a subset confirmed as C. perfringens based on the 16S rRNA gene identity.

CONCLUSIONS

The molecular results indicated all of the presumptive positive isolates were C. perfringens regardless of the source, e.g. sewage influent or environmental water samples. Sequencing revealed that C. perfringens obtained from sewage and the aquatic environment were nearly identical (c. 99.5% similarity).

SIGNIFICANCE AND IMPACT OF THE STUDY

From this study we conclude that the mCP method is a robust approach to enumerate and isolate C. perfringens from aquatic environments that receive diverse sources of faecal pollution.

Diversity and population structure of sewage-derived microorganisms in wastewater treatment plant influent

The release of untreated sewage introduces non-indigenous microbial populations of uncertain composition into surface waters. We used massively parallel 454 pyrosequencing of hypervariable regions in rRNA genes to profile microbial communities from eight untreated sewage influent samples of two wastewater treatment plants (WWTPs) in metropolitan Milwaukee. The sewage profiles included a discernible human faecal signature made up of several taxonomic groups including multiple Bifidobacteriaceae, Coriobacteriaceae, Bacteroidaceae, Lachnospiraceae and Ruminococcaceae genera. The faecal signature made up a small fraction of the taxa present in sewage but the relative abundance of these sequence tags mirrored the population structures of human faecal samples. These genera were much more prevalent in the sewage influent than standard indicators species. High-abundance sequences from taxonomic groups within the Beta- and Gammaproteobacteria dominated the sewage samples but occurred at very low levels in faecal and surface water samples, suggesting that these organisms proliferate within the sewer system. Samples from Jones Island (JI--servicing residential plus a combined sewer system) and South Shore (SS--servicing a residential area) WWTPs had very consistent community profiles, with greater similarity between WWTPs on a given collection day than the same plant collected on different days. Rainfall increased influent flows at SS and JI WWTPs, and this corresponded to greater diversity in the community at both plants. Overall, the sewer system appears to be a defined environment with both infiltration of rainwater and stormwater inputs modulating community composition. Microbial sewage communities represent a combination of inputs from human faecal microbes and enrichment of specific microbes from the environment to form a unique population structure.