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.

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.

A cryptic plasmid is among the most numerous genetic elements in the human gut.

Plasmids are extrachromosomal genetic elements that often encode fitness-enhancing features. However, many bacteria carry "cryptic" plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes and is 14 times as numerous as crAssphage, currently established as the most abundant extrachromosomal genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales, and although it does not appear to impact bacterial host fitness in vivo, it can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an alternative approach to track human colonic inflammatory states.

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.

A highly conserved and globally prevalent cryptic plasmid is among the most numerous mobile genetic elements in the human gut.

Plasmids are extrachromosomal genetic elements that often encode fitness enhancing features. However, many bacteria carry 'cryptic' plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes, and is 14 times as numerous as crAssphage, currently established as the most abundant genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales and although it does not appear to impact bacterial host fitness in vivo, can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an inexpensive alternative for detecting human colonic inflammatory states.

Genetic Determinants of Escherichia coli Survival in Beach Sand.

Escherichia coli contain a high level of genetic diversity and are generally associated with the guts of warm-blooded animals but have also been isolated from secondary habitats outside hosts. We used E. coli isolates from previous in situ microcosm experiments conducted under actual beach conditions and performed population-level genomic analysis to identify accessory genes associated with survival within the beach sand environment. E. coli strains capable of surviving had been selected for by seeding isolates originating from sand, sewage, and gull waste (n = 528; 176 from each source) into sand, which was sealed in microcosm chambers and buried for 45 days in the backshore beach of Lake Michigan. In the current work, survival-associated genes were identified by comparing the pangenome of viable E. coli populations at the end of the microcosm experiment with the original isolate collection and identifying loci enriched in the out put samples. We found that environmental survival was associated with a wide variety of genetic factors, with the majority corresponding to metabolism enzymes and transport proteins. Of the 414 unique functions identified, most were present across E. coli phylogroups, except B2 which is often associated with human pathogens. Gene modules that were enriched in surviving populations included a betaine biosynthesis pathway, which produces an osmoprotectant, and the GABA (gamma-aminobutyrate) biosynthesis pathway, which aids in pH homeostasis and nutrient use versatility. Overall, these results demonstrate that the genetic flexibility within this species allows for survival in the environment for extended periods. IMPORTANCE Escherichia coli is commonly used as an indicator of recent fecal pollution in recreational water despite its known ability to survive in secondary environments, such as beach sand. These long-term survivors from sand reservoirs can be introduced into the water column through wave action or runoff during precipitation events, thereby impacting the perception of local water quality. Current beach monitoring methods cannot differentiate long-term environmental survivors from E. coli derived from recent fecal input, resulting in inaccurate monitoring results and unnecessary beach closures. This work identified the genetic factors that are associated with long-term survivors, providing insight into the mechanistic basis for E. coli accumulation in beach sand. A greater understanding of the intrinsic ability of E. coli to survive long-term and conditions that promote such survival will provide evidence of the limitations of beach water quality assessments using this indicator.

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.

Influence of Nutrients and the Native Community on E. coli Survival in the Beach Environment.

Previous research has identified E. coli populations that persist in freshwater beach sand distinct from fecal pollution events. This work identifies factors that influence the survival of E. coli in sand using laboratory microcosms to replicate beach conditions. Microcosms were deployed to examine the effect of genetic background, competition with native microbial community, and increased nutrient concentrations on E. coli survival. Survival was comparable between the phylotypes B1 and B2, however, deficiency of stress response greatly reduced survival. In the absence of the native community under nutrient conditions comparable to those observed in sand, E. coli cell densities remained within an order of magnitude of initial concentrations after 5 weeks of incubation. Increased nitrogen was associated with decreased decay rates in the first 2 weeks, and increased carbon appeared to provide an advantage at later time points. However, the highest survival was found with the addition of both carbon and nitrogen. Native sand seeded with fresh Cladophora maintained higher concentrations of E. coli, compared to sand containing decayed Cladophora or no Cladophora. Our findings demonstrate persistent E. coli populations in sand can be affected by the availability of carbon and nitrogen, the ability to regulate stress, and the presence of algal mats (i.e., Cladophora). Further, this work suggests that the native microbial communities may modulate survival by outcompeting E. coli for nutrients. IMPORTANCE Current monitoring for fecal pollution does not account for persistent E. coli populations in freshwater sand, which can result in higher concentrations in water when no threat to human health is present. This work examined the drivers for persistent E. coli populations in sand to aid beach management techniques. We examined the influence of nutrients, including localized sources such as stranded Cladophora, on E. coli populations. We found the major determinant of E. coli survival in freshwater beach sand was the addition of nutrients, specifically carbon and nitrogen concentrations 10-fold higher than baseline concentrations on beaches. This work provides the framework for identifying pollution sources that can promote E. coli survival in sand through the characterization of carbon and nitrogen content, which can be incorporated into beach management techniques. Through this improved knowledge, we can begin to understand E. coli fluctuations in water due to resuspension from sand into water.

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.

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.

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.

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.

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.

Selective survival of Escherichia coli phylotypes in freshwater beach sand.

Escherichia coli is used as an indicator of fecal pollution at beaches despite evidence of long-term survival in sand. This work investigated the basis for survival of E. coli through field microcosm experiments and phylotypic characterization of more than >1400 E. coli isolated from sand, sewage, and gulls, enabling identification of long-surviving populations and environmental drivers of their persistence. Microcosms containing populations of E. coli from each source (n=176) were buried in the backshore of Lake Michigan for 45 & 96 days under several different nutrient treatments, including unaltered native sand, sterile autoclaved sand and baked nutrient depleted sand. Availability of carbon and nitrogen and competition with the indigenous community were major factors that influenced E. coli survival. E. coli Clermont phylotypes B1 and A were the most dominant phylotypes surviving seasonally (>6 weeks), regardless of source and nutrient treatment, whereas cryptic clade and D/E phylotypes survived over winter (>300 days). Autoclaved sand, presumably supplying nutrients through increased availability, promoted growth and the presence of the indigenous microbial community reduced this effect. Screening of 849 sand E. coli from four freshwater beaches demonstrated that B1, but also D/E, were the most common phylotypes recovered. Analysis by qPCR for the Gull2, Lachno3 and HB human markers demonstrated only 25% of the samples had evidence of gull waste and none of the samples had evidence of human waste. These findings suggest prevalence of E. coli in the sand could be attributed more to long term surviving populations than to new fecal pollution.IMPORTANCE Fecal pollution monitoring still relies upon the enumeration of E. coli, despite the fact that this organism can survive for prolonged periods and has been shown to be easily transported from sand into surrounding waters through waves and runoff, thus no longer represents recent fecal pollution events. Here, we experimentally demonstrate that regardless of host source, certain genetically distinct subgroups, or phylotypes, survive longer than others under conditions typical of Great Lakes beach sites. We found nutrients were a major driver of survival and could actually promote growth, and the presence of native microorganisms modulated these effects. These insights into the dynamics and drivers of survival will improve the interpretation of E. coli measurements at beaches and inform strategies that could focus on reducing nutrient inputs to beaches or maintaining a robust natural microbiome in beach sand.

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.