Assessing the impact of wastewater treatment plant effluent on downstream drinking water-source quality using a zebrafish (Danio Rerio) liver cell-based metabolomics approach
Graphical abstract
Introduction
The past several decades have witnessed a rapidly increasing demand for water resources due to global economic development and an ever-increasing population. In many densely populated or arid regions, the lack of sufficient potable water has led to the use of treated wastewater (e.g., discharges from wastewater treatment plants (WWTPs)) for many non-potable applications, such as agricultural and landscape irrigations and groundwater recharge (USDA, 2013; USEPA, 2004). Unfortunately, the discharge of treated wastewater into natural systems, e.g., rivers and lakes, has also inadvertently resulted in introduction of a complex mixture of organic contaminants to local aquatic ecosystems and, importantly, surface-water derived drinking water supplies. This use of treated wastewater (after mixing with receiving waters) has been referred to as de facto (unplanned) potable reuse by a National Academy of Engineering study (NRC, 2012). It was estimated recently that 50% of 2056 surface water intakes that serve 1210 drinking water treatment plants (DWTPs) across the U.S. are potentially affected by upstream WWTP discharges (Rice and Westerhoff, 2015).
WWTP effluent is one of the main sources of contaminants of emerging concern (CECs) to surface waters (Kolpin et al., 2002). CECs comprise a wide variety of chemicals including pharmaceuticals and personal care products (PPCPs), endocrine disrupting compounds (EDCs), disinfection by-products (DBPs), antibiotics, and pesticides. Many CECs have been reported to cause adverse ecotoxicological effects at environmentally relevant concentrations, raising concerns over their presence in receiving waters (David et al., 2018; Kolpin et al., 2002). Adding to these concerns are the growing number of instances in which these same surface waters are used as drinking water sources (i.e., de facto water reuse). To date, there have been a limited number of studies demonstrating the influence of WWTP effluent on the quality of drinking water sources (Boleda et al., 2009; Guo and Krasner, 2009; Rodayan et al., 2016). For example, under extremely low streamflow conditions, some DWTP intakes could contain almost 100% WWTP discharge, that is, complete de facto reuse (Rice et al., 2013), and the concentrations of some PPCPs at DWTP intakes have been comparable to those from upstream WWTP effluents (Guo and Krasner, 2009). This is potentially concerning given that other studies have shown incomplete (<90%) removal of many CECs during the drinking water treatment process, including benzoylecgonine, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine, methadone, cocaine, methylenedioxyamphetamine, ephedrine, and several prescription opioids (Boleda et al., 2009; Rodayan et al., 2016).
The presence of these and many other CECs in streams receiving WWTP effluent, coupled with the potential for their incomplete removal during the drinking water treatment process, poses a signifcant and increasing challenge to chemical risk assessment. Indeed, the vast number of chemicals in wastewater has far exceeded our analytical capability based on individual targeted analysis (NRC, 2007). Moreover, there remains a dearth of information regarding the toxic modes-of-action (MOAs) of most targeted chemicals; this implies an even greater level of uncertainty when unidentified contaminants are considered (Judson et al., 2009). The limited understanding of how individual chemical toxicities are modified when chemicals occur in very complex mixtures at environmental conditions further complicates the risk assessment process (Schwarzenbach et al., 2006). To address these and other limitations of the conventional targeted chemical monitoring approach, a variety of biological effects-based tools have emerged and have increasingly been used in water quality assessment (Escher and Leusch, 2012). These tools include bioassays that target specific biological activities such as estrogenic or androgenic receptor binding (Escher and Leusch, 2012). More recently, “-omics” tools that analyze gene transcripts, proteins, and/or endogenous metabolites have gained popularity for MOA assessments of individual chemicals, as well as complex environmental mixtures (Davis et al., 2017; Skelton et al., 2014; Xia et al., 2017). These effects-based tools are particularly attractive as a complement to conventional chemical monitoring because they are both open-ended (i.e., untargeted), and they provide insights into the biological impacts of complex mixtures even when the individual contaminants cannot be uniquely identified or quantified.
Due to advantages that have been discussed elsewhere (Bundy et al., 2009; Lankadurai et al., 2013), metabolomics has been shown to be a particularly useful “-omics” approach for evaluating comprehensive biological responses to various environmental stressors. For example, this approach has been extensively employed to investigate the MOAs of various xenobiotics, including nanoparticles (Ratnasekhar et al., 2015), PPCPs (Gomez-Canela et al., 2016), and EDCs (Davis et al., 2017), through laboratory-based animal (e.g., rodents, fish, and invertebrates) exposures. In addition, field-based metabolomics assessments using on-site exposure of fish have been used successfully to investigate the biological effect of complex contaminant mixtures discharging from both point (e.g., WWTP effluent) and non-point sources (Davis et al., 2013; Skelton et al., 2014). However, metabolomics studies that employ live animals are labor- and resource-intensive, and typically require lethal sampling to collect the relevant tissues and/or biofluids. In an effort to circumvent these drawbacks, we previously developed a cell culture-based metabolomics method and applied it to investigate the effect(s) of exposure to 17α-ethynylestradiol on zebrafish (Danio rerio) liver (ZFL) cells (Teng et al., 2013). Our findings showed that the cellular responses agreed with those metabolite changes observed in vivo (Teng et al., 2013). This suggested that cell-based metabolomics approaches have the potential of providing valuable ecotoxicological information in a particularly high-throughput and cost-effective manner.
In the current study, the ZFL cell-based metabolomics approach was extended to investigate the biological effect(s) of a WWTP effluent discharged into a stream and further downstream to a DWTP in a de facto potable reuse cycle. Previously, zebrafish has been identified as a model vertebrate for investigating chemical toxicity both in vivo and in vitro and proven highly relevant for both human and ecological health (Dai et al., 2014). The primary goal of this study was to evaluate the effectiveness of cell-based metabolomics for tracking the biological effects of contaminants as they travel from the WWTP to the corresponding downstream DWTP, as well as the final drinking water product. A second goal was to test the applicability and efficacy of cell-based metabolomics for ecological assessments of complex environmental mixtures, and to identify relationships between metabolomics endpoints and conventional contaminant detections.
Section snippets
Sampling locations
In April 2015, water samples were taken from a stretch of a river in the northeastern USA where a WWTP is located 14.5 km upstream of the intake of a DWTP. The relative locations of all six sampling sites are shown in Fig. 1. Grab samples were collected upstream (UPS) of the WWTP, at the effluent pipe (EFP) of the WWTP, a proximal location downstream of the WWTP outfall (EMZ) where the effluent is well mixed with the river (as demonstrated by conductivity), a distal location downstream of the
Comparison of metabolite profiles of ZFL cells following exposure to water from each site
PCA score plots displayed an overall alteration of metabolite profiles of ZFL cells following exposure to field water samples relative to controls (Fig. 2). Distinct separations across several of the sampling sites was achieved in the first component of PCA score plots for both hydrophilic (Fig. 2A) and lipophilic (Fig. 2B) sample extracts. ANOVA with post-hoc (Tukey's HSD) analysis was applied to evaluate the significance of metabolite profile differences between individual sites using the PCA
Conclusions
The main goal of the current study was to determine the effectiveness of cell-based metabolomics for tracking biological impacts of complex chemical mixtures as they move through aquatic systems from their initial release at a WWTP to a treated water intended for human consumption at a DWTP. The analyses of both the hydrophilic and lipophilic metabolomes revealed a gradient of response intensities, generally diminishing with the distance of the sampling sites downstream from the WWTP and after
Acknowledgments
H.Z. was supported by the Great Lakes National Program Office and a National Research Council Research Associateship award at the National Exposure Research Laboratory of U.S. Environmental Protection Agency (EPA). The research described in this article has been funded in part by the EPA through Interagency Agreement DW 92401501 to the U.S. Geological Survey (USGS), and through programmatic support of the USGS Toxic Substances Hydrology Program and the EPA's Office of Research and Development.
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