Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies.

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health.

CONTEXT: Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM: Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION: The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION: This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION: Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.

Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network.

In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.

Greener residential environment is associated with increased bacterial diversity in outdoor ambient air.

In urban areas, exposure to greenspace has been found to be beneficial to human health. The biodiversity hypothesis proposed that exposure to diverse ambient microbes in greener areas may be one pathway leading to health benefits such as improved immune system functioning, reduced systemic inflammation, and ultimately reduced morbidity and mortality. Previous studies observed differences in ambient outdoor bacterial diversity between areas of high and low vegetated land cover but didn't focus on residential environments which are important to human health. This research examined the relationship between vegetated land and tree cover near residence and outdoor ambient air bacterial diversity and composition. We used a filter and pump system to collect ambient bacteria samples outside residences in the Raleigh-Durham-Chapel Hill metropolitan area and identified bacteria by 16S rRNA amplicon sequencing. Geospatial quantification of total vegetated land or tree cover was conducted within 500 m of each residence. Shannon's diversity index and weighted UniFrac distances were calculated to measure α (within-sample) and ß (between-sample) diversity, respectively. Linear regression for α-diversity and permutational analysis of variance (PERMANOVA) for ß-diversity were used to model relationships between vegetated land and tree cover and bacterial diversity. Data analysis included 73 ambient air samples collected near 69 residences. Analysis of ß-diversity demonstrated differences in ambient air microbiome composition between areas of high and low vegetated land (p = 0.03) and tree cover (p = 0.07). These relationships remained consistent among quintiles of vegetated land (p = 0.03) and tree cover (p = 0.008) and continuous measures of vegetated land (p = 0.03) and tree cover (p = 0.03). Increased vegetated land and tree cover were also associated with increased ambient microbiome α-diversity (p = 0.06 and p = 0.03, respectively). To our knowledge, this is the first study to demonstrate associations between vegetated land and tree cover and the ambient air microbiome's diversity and composition in the residential ecosystem.

Occurrence and prevalence of antimicrobial resistance in urban karst groundwater systems based on targeted resistome analysis.

Antimicrobial resistance (AMR) is a global crisis threatening human, animal, and environmental health. The natural environment, specifically water resources, has been recognized as a reservoir and dissemination pathway for AMR; however, urban karst aquifer systems have been overlooked. This is a concern as these aquifer systems provide drinking water to about 10 % of the global population; yet, the urban influence on the resistome in these vulnerable aquifers is sparingly explored. This study used high-throughput qPCR to determine the occurrence and relative abundance of antimicrobial resistant genes (ARG) in a developing urban karst groundwater system in Bowling Green, KY. Ten sites throughout the city were sampled weekly and analyzed for 85 ARGs, as well as seven microbial source tracking (MST) genes for human and animal sources, providing a spatiotemporal understanding of the resistome in urban karst groundwater. To further understand ARGs in this environment, potential drivers (landuse, karst feature type, season, source of fecal pollution) were considered in relation to the resistome relative abundance. The MST markers highlighted a prominent human influence to the resistome in this karst setting. The concentration of targeted genes varied between the sample weeks, but all targeted ARGs were prevalent throughout the aquifer regardless of karst feature type or season, with high concentrations captured for sulfonamide (sul1), quaternary ammonium compound (qacE), and aminoglycoside (strB) antimicrobial classes. Higher prevalence and relative abundance were detected during the summer and fall seasons, as well as at the spring features. Linear discriminant analysis suggested that karst feature type had higher influence on ARGs in the aquifer compared to season and the source of fecal pollution had the least influence. These findings can contribute to the development of effective management and mitigation strategies for AMR.

Geospatial Patterns of Antimicrobial Resistance Genes in the US EPA National Rivers and Streams Assessment Survey.

Antimicrobial resistance (AR) is a serious global problem due to the overuse of antimicrobials in human, animal, and agriculture sectors. There is intense research to control the dissemination of AR, but little is known regarding the environmental drivers influencing its spread. Although AR genes (ARGs) are detected in many different environments, the risk associated with the spread of these genes to microbial pathogens is unknown. Recreational microbial exposure risks are likely to be greater in water bodies receiving discharge from human and animal waste in comparison to less disturbed aquatic environments. Given this scenario, research practitioners are encouraged to consider an ecological context to assess the effect of environmental ARGs on public health. Here, we use a stratified, probabilistic survey of nearly 2000 sites to determine national patterns of the anthropogenic indicator class I integron Integrase gene (intI1) and several ARGs in 1.2 million kilometers of United States (US) rivers and streams. Gene concentrations were greater in eastern than in western regions and in rivers and streams in poor condition. These first of their kind findings on the national distribution of intI1 and ARGs provide new information to aid risk assessment and implement mitigation strategies to protect public health.

Development of a Risk Characterization Tool for Harmful Cyanobacteria Blooms on the Ohio River.

A data-driven approach to characterizing the risk of cyanobacteria-based harmful algal blooms (cyanoHABs) was undertaken for the Ohio River. Twenty-five years of river discharge data were used to develop Bayesian regression models that are currently applicable to 20 sites spread-out along the entire 1579 km of the river's length. Two site-level prediction models were developed based on the antecedent flow conditions of the two blooms that occurred on the river in 2015 and 2019: one predicts if the current year will have a bloom (the occurrence model), and another predicts bloom persistence (the persistence model). Predictors for both models were based on time-lagged average flow exceedances and a site's characteristic residence time under low flow conditions. Model results are presented in terms of probabilities of occurrence or persistence with uncertainty. Although the occurrence of the 2019 bloom was well predicted with the modeling approach, the limited number of events constrained formal model validation. However, as a measure of performance, leave-one-out cross validation returned low misclassification rates, suggesting that future years with flow time series like the previous bloom years will be correctly predicted and characterized for persistence potential. The prediction probabilities are served in real time as a component of a risk characterization tool/web application. In addition to presenting the model's results, the tool was designed with visualization options for studying water quality trends among eight river sites currently collecting data that could be associated with or indicative of bloom conditions. The tool is made accessible to river water quality professionals to support risk communication to stakeholders, as well as serving as a real-time water data monitoring utility.

Understanding Microbial Loads in Wastewater Treatment Works as Source Water for Water Reuse.

Facing challenges in water demands and population size, particularly in the water-scarce regions in the United States, the reuse of treated municipal wastewater has become a viable potential to relieve the ever-increasing demands of providing water for (non-)potable use. The objectives of this study were to assess microbial quality of reclaimed water and to investigate treatability of microorganisms during different treatment processes. Raw and final treated effluent samples from three participating utilities were collected monthly for 16 months and analyzed for various microbial pathogens and fecal indicator organisms. Results revealed that the detectable levels of microbial pathogens tested were observed in the treated effluent samples from all participating utilities. Log10 reduction values (LRVs) of Cryptosporidium oocysts and Giardia cysts were at least two orders of magnitude lower than those of human adenovirus and all fecal indicator organisms except for aerobic endospores, which showed the lowest LRVs. The relatively higher LRV of the indicator organisms such as bacteriophages suggested that these microorganisms are not good candidates of viral indicators of human adenovirus during wastewater treatment processes. Overall, this study will assist municipalities considering the use of wastewater effluent as another source of drinking water by providing important data on the prevalence, occurrence, and reduction of waterborne pathogens in wastewater. More importantly, the results from this study will aid in building a richer microbial occurrence database that can be used towards evaluating reuse guidelines and disinfection practices for water reuse practices.

Monoassociation with bacterial isolates reveals the role of colonization, community complexity and abundance on locomotor behavior in larval zebrafish.

BACKGROUND: Across taxa, animals with depleted intestinal microbiomes show disrupted behavioral phenotypes. Axenic (i.e., microbe-free) mice, zebrafish, and fruit flies exhibit increased locomotor behavior, or hyperactivity. The mechanism through which bacteria interact with host cells to trigger normal neurobehavioral development in larval zebrafish is not well understood. Here, we monoassociated zebrafish with either one of six different zebrafish-associated bacteria, mixtures of these host-associates, or with an environmental bacterial isolate. RESULTS: As predicted, the axenic cohort was hyperactive. Monoassociation with three different host-associated bacterial species, as well as with the mixtures, resulted in control-like locomotor behavior. Monoassociation with one host-associate and the environmental isolate resulted in the hyperactive phenotype characteristic of axenic larvae, while monoassociation with two other host-associated bacteria partially blocked this phenotype. Furthermore, we found an inverse relationship between the total concentration of bacteria per larvae and locomotor behavior. Lastly, in the axenic and associated cohorts, but not in the larvae with complex communities, we detected unexpected bacteria, some of which may be present as facultative predators. CONCLUSIONS: These data support a growing body of evidence that individual species of bacteria can have different effects on host behavior, potentially related to their success at intestinal colonization. Specific to the zebrafish model, our results suggest that differences in the composition of microbes in fish facilities could affect the results of behavioral assays within pharmacological and toxicological studies.

Design and evaluation of degassed anaerobic membrane biofilm reactors for improved methane recovery.

Anaerobic treatment of domestic wastewater (DWW) produces dissolved methane that needs to be recovered for use as an energy product. Membrane-based recovery systems have been reported in the literature but are often limited by fouling. The objective of this study was to develop a methane producing biofilm on the shell side surface a membrane to allow for immediate recovery of methane as it was produced, negating mass transfer resistance caused by fouling. Between 89 and 96% of total methane produced was recovered via in-situ degassing without the need for fouling control or cleaning throughout 72 weeks of operation. High methane recovery efficiencies led to predictions of net positive energy yield in one reactor and a 32-61% reduction in energy demand in the others compared to the control. This research demonstrates the feasibility and usefulness of combining attached growth anaerobic wastewater treatment processes with hollow fiber membrane methane recovery systems for improved operation.

Droplet digital PCR quantification of norovirus and adenovirus in decentralized wastewater and graywater collections: Implications for onsite reuse.

Risk-based treatment of onsite wastewaters for decentralized reuse requires information on the occurrence and density of pathogens in source waters, which differ from municipal wastewater due to scaling and dilution effects in addition to variable source contributions. In this first quantitative report of viral enteric pathogens in onsite-collected graywater and wastewater, untreated graywater (n = 50 samples) and combined wastewater (i.e., including blackwater; n = 28) from three decentralized collection systems were analyzed for two norovirus genogroups (GI/GII) and human adenoviruses using droplet digital polymerase chain reaction (ddPCR). Compared to traditional quantitative PCR (qPCR), which had insufficient sensitivity to quantify viruses in graywater, ddPCR allowed quantification of norovirus GII and adenovirus in 4% and 14% of graywater samples, respectively (none quantifiable for norovirus GI). Norovirus GII was routinely quantifiable in combined wastewater by either PCR method (96% of samples), with well-correlated results between the analyses (R2 = 0.96) indicating a density range of 5.2-7.9 log10 genome copies/L. These concentrations are greater than typically reported in centralized municipal wastewater, yet agree well with an epidemiology-based model previously used to develop pathogen log-reduction targets (LRTs) for decentralized non-potable water systems. Results emphasize the unique quality of onsite wastewaters, supporting the previous LRTs and further quantitative microbial risk assessment (QMRA) of decentralized water reuse.

Genome Sequences of Escherichia Bacteriophages Isolated from Raw Wastewater.

Somatic coliphages are alternative indicators of fecal pollution and attractive surrogates for viral pathogens. Here, we report the draft genome sequences of three replicate plaques from a novel Myoviridae bacteriophage isolated from raw wastewater. These genomes were similar to felix01virus phage and are predicted to contain up to 148 protein-coding genes.

Microbiota alter metabolism and mediate neurodevelopmental toxicity of 17ß-estradiol.

Estrogenic chemicals are widespread environmental contaminants associated with diverse health and ecological effects. During early vertebrate development, estrogen receptor signaling is critical for many different physiologic responses, including nervous system function. Recently, host-associated microbiota have been shown to influence neurodevelopment. Here, we hypothesized that microbiota may biotransform exogenous 17-ßestradiol (E2) and modify E2 effects on swimming behavior. Colonized zebrafish were continuously exposed to non-teratogenic E2 concentrations from 1 to 10 days post-fertilization (dpf). Changes in microbial composition and predicted metagenomic function were evaluated. Locomotor activity was assessed in colonized and axenic (microbe-free) zebrafish exposed to E2 using a standard light/dark behavioral assay. Zebrafish tissue was collected for chemistry analyses. While E2 exposure did not alter microbial composition or putative function, colonized E2-exposed larvae showed reduced locomotor activity in the light, in contrast to axenic E2-exposed larvae, which exhibited normal behavior. Measured E2 concentrations were significantly higher in axenic relative to colonized zebrafish. Integrated peak area for putative sulfonated and glucuronidated E2 metabolites showed a similar trend. These data demonstrate that E2 locomotor effects in the light phase are dependent on the presence of microbiota and suggest that microbiota influence chemical E2 toxicokinetics. More broadly, this work supports the concept that microbial colonization status may influence chemical toxicity.

Host Developmental Toxicity of BPA and BPA Alternatives Is Inversely Related to Microbiota Disruption in Zebrafish.

Host-associated microbiota can biotransform xenobiotics, mediate health effects of chemical exposure, and play important roles in early development. Bisphenol A (BPA) is a widespread environmental chemical that has been associated with adverse endocrine and neurodevelopmental effects, some of which may be mediated by microbiota. Growing public concern over the safety of BPA has resulted in its replacement with structurally similar alternatives. In this study, we evaluated whether BPA and BPA alternatives alter microbiota and modulate secondary adverse behavioral effects in zebrafish. Zebrafish were developmentally exposed to BPA, Bisphenol AF (BPAF), Bisphenol B (BPB), Bisphenol F (BPF), or Bisphenol S (BPS). At 10 days post fertilization (dpf), toxicity assessments were completed and 16S rRNA gene sequencing was performed to evaluate potential chemical-dependent shifts in microbial community structure and predicted function. A standard light/dark behavioral assay was used to assess locomotor activity. Based on developmental toxicity assessments at 10 dpf, a range of potencies was observed: BPAF > BPB > BPF ∼ BPA > BPS. Analysis of 16S rRNA gene sequencing data showed significant concentration-dependent disruption of microbial community structure and enrichment of putative microbial functions with exposure to BPS, BPA, or BPF, but not BPB or BPAF. Interestingly, microbial disruption was inversely related to host developmental toxicity and estrogenicity. Exposure to BP analogs did not cause behavioral effects at 10 dpf. Our findings indicate that some BP analogs disrupt host microbiota early in life and demonstrate novel chemical-microbiota interactions that may add important context to current hazard identification strategies.

Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States.

Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water. One group of possible contaminants are enteric viruses. Measurement of viral quantities in environmental water systems are often performed using polymerase chain reaction (PCR) or quantitative PCR (qPCR). However, true values may be underestimated due to challenges involved in a multi-step viral concentration process and due to PCR inhibition. In this study, water samples were concentrated from 25 drinking water treatment plants (DWTPs) across the US to study the occurrence of enteric viruses in source water and removal after treatment. The five different types of viruses studied were adenovirus, norovirus GI, norovirus GII, enterovirus, and polyomavirus. Quantitative PCR was performed on all samples to determine presence or absence of these viruses in each sample. Ten DWTPs showed presence of one or more viruses in source water, with four DWTPs having treated drinking water testing positive. Furthermore, PCR inhibition was assessed for each sample using an exogenous amplification control, which indicated that all of the DWTP samples, including source and treated water samples, had some level of inhibition, confirming that inhibition plays an important role in PCR-based assessments of environmental samples. PCR inhibition measurements, viral recovery, and other assessments were incorporated into a Bayesian model to more accurately determine viral load in both source and treated water. Results of the Bayesian model indicated that viruses are present in source water and treated water. By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters.

Reducing inherent biases introduced during DNA viral metagenome analyses of municipal wastewater.

Metagenomics is a powerful tool for characterizing viral composition within environmental samples, but sample and molecular processing steps can bias the estimation of viral community structure. The objective of this study is to understand the inherent variability introduced when conducting viral metagenomic analyses of wastewater and provide a bioinformatic strategy to accurately analyze sequences for viral community analyses. A standard approach using a combination of ultrafiltration, membrane filtration, and DNase treatment, and multiple displacement amplification (MDA) produced DNA preparations without any bacterial derived genes. Results showed recoveries in wastewater matrix ranged between 60-100%. A bias towards small single stranded DNA (ssDNA; polyomavirus) virus types vs larger double stranded DNA (dsDNA; adenovirus) viruses was also observed with a total estimated recovery of small circular viruses to be as much as 173-fold higher. Notably, ssDNA abundance decreased with sample dilution while large dsDNA genomes (e.g., Caudovirales) initially increased in abundance with dilution before gradually decreasing with further dilution in wastewater samples. The present study revealed the inherent biases associated with different components of viral metagenomic methods applied to wastewater. Overall, these results provide a well-characterized approach for effectively conducting viral metagenomics analysis of wastewater and reveal that dilution can effectively mitigate MDA bias.

Differential Sensitivity of Wetland-Derived Nitrogen Cycling Microorganisms to Copper Nanoparticles.

Metallic nanoparticles (NPs), the most abundant nanomaterials in consumer and industrial products, are the most probable class to enter the environment. In this study, wetland-derived microcosms were incubated with copper nanoparticles (Cu-NP) and ionic CuCl2 to investigate acute (10 days) and chronic (100 days) exposure towards nitrogen cycling microorganisms. The microbial ecology of wetlands play a crucial role in balancing nitrogen in pristine environments as well as in areas impacted by high nutrient loads (e.g., at wastewater effluent discharges). Gene abundance and expression changes were monitored using the GeoChip 5.0 high throughput functional gene microarray and metatranscriptomic shotgun sequencing (RNA-seq), respectively. After 10 days, the Cu-NP impacted microbial communities experienced structural shifts within microorganisms associated with dissimilatory nitrogen reduction accompanied by lower nitrate removal as compared to the unexposed controls. By day 100, these differences were largely resolved and nitrate removal was similar to the unexposed control. Furthermore, the Cu-NP exposed microcosms tolerated copper and were more resilient and adaptive than the unexposed controls based on the abundance and expression of other functions, including electron transfer, metal homeostasis, and stress response. These findings suggest sudden influxes of Cu-NPs into wetland systems may impair nitrogen removal initially, but long-term microbial shifts and functional redundancy would promote the net flux of total nitrogen out of the wetlands.

Microbial colonization is required for normal neurobehavioral development in zebrafish.

Changes in resident microbiota may have wide-ranging effects on human health. We investigated whether early life microbial disruption alters neurodevelopment and behavior in larval zebrafish. Conventionally colonized, axenic, and axenic larvae colonized at 1 day post fertilization (dpf) were evaluated using a standard locomotor assay. At 10 dpf, axenic zebrafish exhibited hyperactivity compared to conventionalized and conventionally colonized controls. Impairment of host colonization using antibiotics also caused hyperactivity in conventionally colonized larvae. To determine whether there is a developmental requirement for microbial colonization, axenic embryos were serially colonized on 1, 3, 6, or 9 dpf and evaluated on 10 dpf. Normal activity levels were observed in axenic larvae colonized on 1-6 dpf, but not on 9 dpf. Colonization of axenic embryos at 1 dpf with individual bacterial species Aeromonas veronii or Vibrio cholerae was sufficient to block locomotor hyperactivity at 10 dpf. Exposure to heat-killed bacteria or microbe-associated molecular patterns pam3CSK4 or Poly(I:C) was not sufficient to block hyperactivity in axenic larvae. These data show that microbial colonization during early life is required for normal neurobehavioral development and support the concept that antibiotics and other environmental chemicals may exert neurobehavioral effects via disruption of host-associated microbial communities.

Retrospective Surveillance of Wastewater To Examine Seasonal Dynamics of Enterovirus Infections.

Enteroviruses are RNA viruses that are responsible for both mild gastroenteritis and mild respiratory illnesses as well as debilitating diseases such as meningitis and myocarditis. The disease burden of enteroviruses in the United States is difficult to assess because most infections are not recorded. Since infected individuals shed enterovirus in feces and urine, surveillance of municipal wastewater can reveal the diversity of enteroviruses circulating in human populations. Therefore, monthly municipal wastewater samples were collected for 1 year and enteroviruses were quantified by reverse transcriptase quantitative PCR and identified by next-generation, high-throughput sequencing. Enterovirus concentrations ranged from 3.8 to 5.9 log10 equivalent copies/liter in monthly samples. From the mean monthly concentration, it can be estimated that 2.8% of the contributing population was shedding enterovirus daily. Sequence analysis showed that Enterovirus A and Enterovirus B alternate in predominance, with Enterovirus B comprising over 80% of the reads during the summer and fall months and Enterovirus A accounting for >45% of the reads in spring. Enterovirus C was observed throughout the year, while Enterovirus D was present intermittently. Principal-component analysis further supported the date corresponding to enterovirus seasonal trends as CVA6 (Enterovirus A) was predominant in the spring months; CVB3, CVB5, and E9 (Enterovirus B) were predominant in the summer and fall months; and CVA1, CVA19, and CVA22 (Enterovirus C) and EV97 (Enterovirus B) were predominant in winter. Rhinoviruses were also observed. Wastewater monitoring of human enterovirus provided improved insight into the seasonal patterns of enteroviruses circulating in communities and can contribute to understanding of enterovirus disease burden. IMPORTANCE Enterovirus infections are often not tracked or reported to health officials. This makes it hard to know how many people in a community are infected with these viruses at any given time. Here, we explored enterovirus in municipal wastewater to look at this issue. We show that enteroviruses are present year-round in municipal wastewater at levels of up to 800,000 genomic copies per liter. We estimate that, on average, 2.8% of the people contributing to the wastewater shed enterovirus daily. Sequence analysis of the viral capsid protein 4 gene shows that 8 enterovirus types are key drivers of seasonal trends. Populations of Enterovirus A members peak in the spring, while Enterovirus B types are most prevalent during the summer and fall months and Enterovirus C members influence the winter months. Enterovirus D was observed sporadically and did not influence seasonal trends.