A one health approach for monitoring antimicrobial resistance: developing a national freshwater pilot effort.

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

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.

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.

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.

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.

Characterization of roof runoff microbial quality in four U.S. cities with varying climate and land use characteristics.

Roof runoff has the potential to serve as an important local water source in regions with growing populations and limited water supply. Given the scarcity of guidance regulating the use of roof runoff, a need exists to characterize the microbial quality of roof runoff. The objective of this 2-year research effort was to examine roof runoff microbial quality in four U.S. cities: Fort Collins, CO; Tucson, AZ; Baltimore, MD; and Miami, FL. Seven participants, i.e., homeowners and schools, were recruited in each city to collect roof runoff samples across 13 precipitation events. Sample collection was done as part of a citizen science approach. The presence and concentrations of indicator organisms and potentially human-infectious pathogens in roof runoff were determined using culture methods and digital droplet polymerase chain reaction (ddPCR), respectively. The analyzed pathogens included Salmonella spp., Campylobacter spp., Giardia duodenalis, and Cryptosporidium parvum. Several factors were evaluated to study their influence on the presence of potentially human-infectious pathogens including the physicochemical characteristics (total suspended solids, volatile suspended solids, total dissolved solids, chemical oxygen demand, and turbidity) of roof runoff, concentrations of indicator organisms, presence/absence of trees, storm properties (rainfall depth and antecedent dry period), percent of impervious cover surrounding each sampling location, seasonality, and geographical location. E. coli and enterococci were detected in 73.4% and 96.2% of the analyzed samples, respectively. Concentrations of both E. coli and enterococci ranged from <0 log10 to >3.38 log10 MPN/100 mL. Salmonella spp. invA, Campylobacter spp. ceuE, and G. duodenalis ß - giardin gene targets were detected in 8.9%, 2.5%, and 5.1% of the analyzed samples, respectively. Campylobacter spp. mapA and C. parvum 18S rRNA gene targets were not detected in any of the analyzed samples. The detection of Salmonella spp. invA was influenced by the geographical location of the sampling site (Chi-square p-value < 0.001) as well as the number of antecedent dry days prior to a rain event (p-value = 0.002, negative correlation). The antecedent dry period was negatively correlated with the occurrence of Campylobacter spp. ceuE as well (p-value = 0.07). On the other hand, the presence of G. duodenalis ß-giardin in roof runoff was positively correlated with rainfall depth (p-value = 0.05). While physicochemical parameters and impervious area were not found to be correlated with the presence/absence of potentially human-infectious pathogens, significant correlations were found between meteorological parameters and the presence/absence of potentially human-infectious pathogens. Additionally, a weak, yet significant positive correlation, was found only between the concentrations of E. coli and those of Giardia duodenalis ß-giardin. This dataset represents the largest-scale study to date of enteric pathogens in U.S. roof runoff collections and will inform treatment targets for different non-potable end uses for roof runoff. However, the dataset is limited by the low percent detection of bacterial and protozoan pathogens, an issue that is likely to persist challenging the characterization of roof runoff microbial quality given sampling limitations related to the volume and number of samples.

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.

Bringing Community Ecology to Bear on the Issue of Antimicrobial Resistance.

Antimicrobial resistance (AMR) is a global concern, pertaining not only to human health but also to the health of industry and the environment. AMR research has traditionally focused on genetic exchange mechanisms and abiotic environmental constraints, leaving important aspects of microbial ecology unresolved. The genetic and ecological aspects of AMR, however, not only contribute separately to the problem but also are interrelated. For example, mutualistic associations among microbes such as biofilms can both serve as a barrier to antibiotic penetration and a breeding ground for horizontal exchange of antimicrobial resistance genes (ARGs). In this review, we elucidate how species interactions promote and impede the establishment, maintenance, and spread of ARGs and indicate how management initiatives might benefit from leveraging the principles and tools of community ecology to better understand and manipulate the processes underlying AMR.

Triclosan-Selected Host-Associated Microbiota Perform Xenobiotic Biotransformations in Larval Zebrafish.

Microbiota regulate important physiologic processes during early host development. They also biotransform xenobiotics and serve as key intermediaries for chemical exposure. Antimicrobial agents in the environment may disrupt these complex interactions and alter key metabolic functions provided by host-associated microbiota. To examine the role of microbiota in xenobiotic metabolism, we exposed zebrafish larvae to the antimicrobial agent triclosan. Conventionally colonized (CC), microbe-free axenic (AX), or axenic colonized on day 1 (AC1) zebrafish were exposed to 0.16-0.30 µM triclosan or vehicle on days 1, 6, 7, 8, and 9 days post fertilization (dpf). After 6 and 10 dpf, host-associated microbial community structure and putative function were assessed by 16S rRNA gene sequencing. At 10 dpf, triclosan exposure selected for bacterial taxa, including Rheinheimera. Triclosan-selected microbes were predicted to be enriched in pathways related to mechanisms of antibiotic resistance, sulfonation, oxidative stress, and drug metabolism. Furthermore, at 10 dpf, colonized zebrafish contained 2.5-3 times more triclosan relative to AX larvae. Nontargeted chemical analysis revealed that, relative to AX larvae, both cohorts of colonized larvae showed elevations in 23 chemical features, including parent triclosan and putative triclosan sulfate. Taken together, these data suggest that triclosan exposure selects for microbes that harbor the capacity to biotransform triclosan into chemical metabolites with unknown toxicity profiles. More broadly, these data support the concept that microbiota modify the toxicokinetics of xenobiotic exposure.

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.