Gene expression of fathead minnows (Pimephales promelas) exposed to two types of treated municipal wastewater effluents

An investigation into the biological effects of indirect potable reuse water using zebrafish embryos

Advanced treatment technologies are being assessed as a proactive measure to assist with the transformation of treated wastewater into a source of water for potable water production. We investigated the biological effects along an advanced water treatment pilot plant, using zebrafish embryos throughout early development. The study compared phenotypic observations with global transcriptome responses, enabling us to keep an open mind about the chemicals that might influence the biological activity. There was no evidence of acute toxicity at any treatment stage, but skeletal, cardiovascular and pigmentation changes occurred in a small proportion of embryos along the treatment process, and in a tap water; not detected in the aquarium water control. Reverse osmosis (RO) reduced the concentration of measured chemical contaminants in the water the most, while eliminating the occurrence of abnormalities detected in fish embryos. Conversely, advanced oxidation reversed the benefits of RO treatment by increasing the frequency of teratogenic and sub-lethal abnormalities seen. Using the molecular responses of zebrafish embryos to different IPR water, we report the bioactivity within the water at different stages of advanced treatment and associate these to perturbed biological functions. Transcriptomic analysis revealed alterations to the retinoid system, which was consistent with the observed teratogenic effects. Changes to tryptophan metabolism (associated with the production of melatonin required for the control of normal circadian rhythms) and somatolactin-beta (associated with normal pigmentation in fish) were also found. We show that underexplored forms of biological activity occur in treated wastewater effluent, and/or may be created depending on the type of advanced treatment process used. By integrating the available analytical chemistry we highlight chemical groups associated to this response. Our study shows that more detailed and in-depth characterisation of chemicals and biological pathways associated with advanced treatment water systems are needed to mitigate possible risks to downstream organisms.

EcoToxModules: Custom Gene Sets to Organize and Analyze Toxicogenomics Data from Ecological Species

Traditional results from toxicogenomics studies are complex lists of significantly impacted genes or gene sets, which are challenging to synthesize down to actionable results with a clear interpretation. Here, we defined two sets of 21 custom gene sets, called the functional and statistical EcoToxModules, in fathead minnow (Pimephales promelas) to (1) re-cast predefined molecular pathways into a toxicological framework and (2) provide a data-driven, unsupervised grouping of genes impacted by exposure to environmental contaminants. The functional EcoToxModules were identified by re-organizing KEGG pathways into biological processes that are more relevant to ecotoxicology based on the input from expert scientists and regulators. The statistical EcoToxModules were identified using co-expression analysis of publicly available microarray data (n = 303 profiles) measured in livers of fathead minnows after exposure to 38 different conditions. Potential applications of the EcoToxModules were demonstrated with two case studies that represent exposure to a pure chemical and to environmental wastewater samples. In comparisons to differential expression and gene set analysis, we found that EcoToxModule responses were consistent with these traditional results. Additionally, they were easier to visualize and quantitatively compare across different conditions, which facilitated drawing conclusions about the relative toxicity of the exposures within each case study.

A Self-Organizing Map of the Fathead Minnow Liver Transcriptome to Identify Consistent Toxicogenomic Patterns across Chemical Fingerprints

Lack of consistent findings in different experimental settings remains a major challenge in toxicogenomics. The present study investigated whether consistency between findings of different microarray experiments can be improved when the analysis is based on a common reference frame ("toxicogenomic universe"), which can be generated using the machine learning algorithm of the self-organizing map (SOM). This algorithm arranges and clusters genes on a 2-dimensional grid according to their similarity in expression across all considered data. In the present study, 19 data sets, comprising of 54 different adult fathead minnow liver exposure experiments, were retrieved from Gene Expression Omnibus and used to train a SOM. The resulting toxicogenomic universe aggregates 58 872 probes to 2500 nodes and was used to project, visualize, and compare the fingerprints of these 54 different experiments. For example, we could identify a common pattern, with 14% of significantly regulated nodes in common, in the data sets of an interlaboratory study of ethinylestradiol exposures. Consistency could be improved compared with the 5% total overlap in regulated genes reported before. Furthermore, we could determine a specific and consistent estrogen-related pattern of differentially expressed nodes and clusters in the toxicogenomic universe by applying additional clustering steps and comparing all obtained fingerprints. Our study shows that the SOM-based approach is useful for generating comparable toxicogenomic fingerprints and improving consistency between results of different experiments. Environ Toxicol Chem 2020;39:526-537. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Surface water extracts impair gene profiles and differentiation in human mesenchymal stem cells

Low concentrations of pollutants in surface water challenge the assessment of chronic effects on human health. Human bone mesenchymal stem cells (hBMSCs) were employed as a sensitive and relevant in vitro model to evaluate the potential biological effects caused by mixtures of pollutants in surface water. Organic extracts of surface water collected from Hun River inhibited cell viability in a dose-dependent manner. Surface water extracts at noncytotoxic concentrations induced 533 to 1055 differentially expressed genes (DEGs) in hBMSCs after 48 h of exposure. Total of 370 genes were commonly affected by surface water from different sites and accounted for 35-69% of DEGs impaired by individual sample. Pathways related to human diseases, genetic information processing and organismal systems were enriched based on DEGs. Interleukins (IL1B, IL6 and IL8) were affected and involved in most human diseases related pathways. The significantly downregulation of COL1A1 and the variation of rheumatoid arthritis pathway suggested that surface water potentially inhibited osteogenic differentiation of hBMSCs. Clustering analysis and principle component analysis with DEGs distinguish the surface water from tributary and mainstream. The crossing-species comparison of transcriptomic changes identified 923 and 2715 differentially expressed orthologs in hBMSCs and zebrafish, respectively. After the exposure ceased, the followed osteogenic and adipogenic differentiation in hBMSCs for 14 days were inhibited by the treatment of surface water during undifferentiated period, whereas the non-polar fraction exhibited stronger potency in affecting differentiation than the mid to polar fractions. hBMSCs, combining unsupervised transcriptomic technique and specific endpoints test, are promising in screening the health effects of environmental mixtures in surface water.

Metabolic implications of exposure to wastewater effluent in bluegill sunfish

Effluent from wastewater treatment plants (WWTP) contains a complex mixture of contaminants and is a major worldwide source of aquatic pollution. We examined the effects of exposure to treated effluent from a municipal WWTP on the metabolic physiology of bluegill sunfish (Lepomis macrochirus). We studied fish that were wild-caught or experimentally caged (28 d) downstream of the WWTP, and compared them to fish that were caught or caged at clean reference sites. Survival was reduced in fish caged at the effluent-contaminated site compared to those caged at the reference site. Resting rates of O₂ consumption (MO₂) were higher in fish from the contaminated site, reflecting a metabolic cost of wastewater exposure. The increases in routine MO₂ did not reduce aerobic scope (difference or quotient of maximal MO₂ and resting MO₂), suggesting that physiological compensations accompanied the metabolic costs of wastewater exposure. Fish exposed to wastewater also had larger hearts and livers. The activity of mitochondrial enzymes (cytochrome c oxidase, citrate synthase) per liver mass was unaltered across treatments, so the increased mass of this organ increased its cumulative oxidative capacity in the fish. Wastewater exposure also reduced glycogen content per liver mass. The effects of caging itself, based on comparisons between fish that were wild-caught or caged at clean sites, were generally subtle and not statistically significant. We conclude that exposure to wastewater effluent invokes a metabolic cost that leads to compensatory physiological adjustments that partially offset the detrimental metabolic impacts of exposure.

Genome-Wide Stress Responses to Copper and Arsenic in a Field Population of Daphnia

Over the past decade, significant advances have been made to unravel molecular mechanisms of stress response in different ecotoxicological model species. Within this study, we focus on population level transcriptomic responses of a natural population of Daphnia magna Straus, (1820), to heavy metals. We aim to characterize the population level transcriptomic responses, which include standing genetic variation, and improve our understanding on how populations respond to environmental stress at a molecular level. We studied population level responses to two heavy metals, copper and arsenic, and their binary mixture across time. Transcriptomic patterns identified significantly regulated gene families and genes at the population level including cuticle proteins and resilins. Furthermore, some of these differentially regulated gene families, such as cuticle proteins, were also significantly enriched for genetic variations including SNPs and MNPs. In general, genetic variation was observed in specific gene families, many of which are known to be involved in stress response. Overall, our results indicate that molecular stress responses can be identified within natural populations and that linking molecular mechanisms with genetic variation at the population level could contribute significantly to adverse outcome frameworks.

Transcriptomic Profiles in Zebrafish Liver Permit the Discrimination of Surface Water with Pollution Gradient and Different Discharges

The present study aims to evaluate the potential of transcriptomic profiles in evaluating the impacts of complex mixtures of pollutants at environmentally relevant concentrations on aquatic vertebrates. The changes in gene expression were determined using microarray in the liver of male zebrafish (Danio rerio) exposed to surface water collected from selected locations on the Hun River, China. The numbers of differentially expressed genes (DEGs) in each treatment ranged from 728 to 3292, which were positively correlated with chemical oxygen demand (COD). Predominant transcriptomic responses included peroxisome proliferator-activated receptors (PPAR) signaling and steroid biosynthesis. Key pathways in immune system were also affected. Notably, two human diseases related pathways, insulin resistance and Salmonella infection were enriched. Clustering analysis and principle component analysis with DEGs differentiated the upstream and downstream site of Shenyang City, and the mainstream and the tributary sites near the junction. Comparison the gene expression profiles of zebrafish exposed to river surface water with those to individual chemicals found higher similarity of the river water with estradiol than several other organic pollutants and metals. Results suggested that the transcriptomic profiles of zebrafish is promising in differentiating surface water with pollution gradient and different discharges and in providing valuable information to support discharge management.

How Does Reference Site Selection Influence Interpretation of Omics Data?: Evaluating Liver Transcriptome Responses in Male Rainbow Darter (Etheostoma caeruleum) across an Urban Environment

Studies quantifying the influence of reference site selection on transcriptomic profiles in aquatic organisms exposed to complex mixtures are lacking in the literature, despite the significant implications of such research for the interpretation of omics data sets. We measured hepatic transcriptomic responses in fish across an urban environment in the central Grand River watershed (Ontario, Canada). Adult male rainbow darter (RBD) (Etheostoma caeruleum) were collected from nine sites at varying distances from two major municipal wastewater treatment plants (MWWTPs) (Waterloo, Kitchener), including three upstream reference sites. The transcriptomic response in RBD was independently compared with that of fish from each of the three reference sites. Data collected in fish downstream of the Waterloo MWWTP (poorest effluent quality) suggested that ∼15.5% of the transcriptome response was influenced by reference site selection. In contrast, at sites where the impact of MWWTPs was less-pronounced and fish showed less of a transcriptome response, reference site selection had a greater influence (i.e., ∼56.9% of transcripts were different depending on the site used). This study highlights the importance of conducting transcriptomics studies that leverage more than one reference site, and it broadens our understanding of the molecular responses in fish in dynamic natural environments.

Critical assessment of the ubiquitous occurrence and fate of the insect repellent N,N-diethyl-m-toluamide in water

The insect repellent diethyltoluamide (DEET) is among the most frequently detected organic chemical contaminants in water across a wide range of geographies from around the world. These observations are raising critical questions and increasing concerns regarding potential environmental relevance, particularly when the emergence of severe neurological conditions attributed to the Zika virus has increased the use of insect repellents. After dermal application, DEET is washed from the skin when bathing and enters the municipal sewer system before discharge into the environment. Mainly measured by gas chromatography or liquid chromatography coupled to mass spectrometry (GC-MS or LC-MS), more than 200 peer-reviewed publications have already reported concentrations of DEET ranging ng/L to mg/L in several water matrices from North America, Europe, Asia, Oceania, and more recently Africa and South America. While conventional wastewater treatment technology has limited capacity of removal, advanced technologies are capable of better attenuation and could lower the environmental discharge of organic contaminants, including DEET. For instance, adsorption on activated carbon, desalinating membrane processes (nanofiltration and reverse osmosis), ozonation, and advanced oxidation processes can achieve 50% to essentially 100% DEET attenuation. Despite the abundant literature on the topic, the ubiquity of DEET in the environment still raises questions due to the apparent lack of obvious spatio-temporal trends in concentrations measured in surface water, which does not fit the expected usage pattern of insect repellents. Moreover, two recent studies showed discrepancies between the concentrations obtained by GC-MS and LC-MS analyses. While the occurrence of DEET in the environment is well established, the concentrations reported should be interpreted cautiously, considering the disparities in methodologies applied and occurrence patterns observed. Therefore, this manuscript provides a critical overview of the origin of DEET in the environment, the relevant analytical methods, the occurrence reported in peer-reviewed literature, and the attenuation efficacy of water treatment processes.

Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles

Background

A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs.

Results

Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications.

Conclusions

The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2406-y) contains supplementary material, which is available to authorized users.

Defining the role of omics in assessing ecosystem health: Perspectives from the Canadian environmental monitoring program

Scientific reviews and studies continue to describe omics technologies as the next generation of tools for environmental monitoring, while cautioning that there are limitations and obstacles to overcome. However, omics has not yet transitioned into national environmental monitoring programs designed to assess ecosystem health. Using the example of the Canadian Environmental Effects Monitoring (EEM) program, the authors describe the steps that would be required for omics technologies to be included in such an established program. These steps include baseline collection of omics endpoints across different species and sites to generate a range of what is biologically normal within a particular ecosystem. Natural individual variability in the omes is not adequately characterized and is often not measured in the field, but is a key component to an environmental monitoring program, to determine the critical effect size or action threshold for management. Omics endpoints must develop a level of standardization, consistency, and rigor that will allow interpretation of the relevance of changes across broader scales. To date, population-level consequences of routinely measured endpoints such as reduced gonad size or intersex in fish is not entirely clear, and the significance of genome-wide molecular, proteome, or metabolic changes on organism or population health is further removed from the levels of ecological change traditionally managed. The present review is not intended to dismiss the idea that omics will play a future role in large-scale environmental monitoring studies, but rather outlines the necessary actions for its inclusion in regulatory monitoring programs focused on assessing ecosystem health.

Omics for aquatic ecotoxicology: control of extraneous variability to enhance the analysis of environmental effects

There are multiple sources of biological and technical variation in a typical ecotoxicology study that may not be revealed by traditional endpoints but that become apparent in an omics dataset. As researchers increasingly apply omics technologies to environmental studies, it will be necessary to understand and control the main source(s) of variability to facilitate meaningful interpretation of such data. For instance, can variability in omics studies be addressed by changing the approach to study design and data analysis? Are there statistical methods that can be employed to correctly interpret omics data and make use of unattributed, inherent variability? The present study presents a review of experimental design and statistical considerations applicable to the use of omics methods in systems toxicology studies. In addition to highlighting potential sources that contribute to experimental variability, this review suggests strategies with which to reduce and/or control such variability so as to improve reliability, reproducibility, and ultimately the application of omics data for systems toxicology.

Linking Landscape-Scale Disturbances to Stress and Condition of Fish: Implications for Restoration and Conservation

Humans have dramatically altered landscapes as a result of urban and agricultural development, which has led to decreases in the quality and quantity of habitats for animals. This is particularly the case for freshwater fish that reside in fluvial systems, given that changes to adjacent lands have direct impacts on the structure and function of watersheds. Because choices of habitat have physiological consequences for organisms, animals that occupy sub-optimal habitats may experience increased expenditure of energy or homeostatic overload that can cause negative outcomes for individuals and populations. With the imperiled and threatened status of many freshwater fish, there is a critical need to define relationships between land use, quality of the habitat, and physiological performance for resident fish as an aid to restoration and management. Here, we synthesize existing literature to relate variation in land use at the scale of watersheds to the physiological status of resident fish. This examination revealed that landscape-level disturbances can influence a host of physiological properties of resident fishes, ranging from cellular and genomic levels to the hormonal and whole-animal levels. More importantly, these physiological responses have been integrated into traditional field-based monitoring protocols to provide a mechanistic understanding of how organisms interact with their environment, and to enhance restoration. We also generated a conceptual model that provides a basis for relating landscape-level changes to physiological responses in fish. We conclude that physiological sampling of resident fish has the potential to assess the effects of landscape-scale disturbances on freshwater fish and to enhance restoration and conservation.

Using transcriptomic tools to evaluate biological effects across effluent gradients at a diverse set of study sites in Minnesota, USA

The aim of this study was to explore the utility of "omics" approaches in monitoring aquatic environments where complex, often unknown stressors make chemical-specific risk assessment untenable. We examined changes in the fathead minnow (Pimephales promelas) ovarian transcriptome following 4-day exposures conducted at three sites in Minnesota (MN, USA). Within each site, fish were exposed to water from three locations along a spatial gradient relative to a wastewater treatment plant (WWTP) discharge. After exposure, site-specific impacts on gene expression in ovaries were assessed. Using an intragradient point of comparison, biological responses specifically associated with the WWTP effluent were identified using functional enrichment analyses. Fish exposed to water from locations downstream of the effluent discharges exhibited many transcriptomic responses in common with those exposed to the effluent, indicating that effects of the discharge do not fully dissipate downstream. Functional analyses showed a range of biological pathways impacted through effluent exposure at all three sites. Several of those impacted pathways at each site could be linked to potential adverse reproductive outcomes associated with the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows, specifically signaling pathways associated with oocyte meiosis, TGF-beta signaling, gonadotropin-releasing hormone (GnRH) and epidermal growth factor receptor family (ErbB), and gene sets associated with cyclin B-1 and metalloproteinase. The utility of this approach comes from the ability to identify biological responses to pollutant exposure, particularly those that can be tied to adverse outcomes at the population level and those that identify molecular targets for future studies.

Assessing gene network stability and individual variability in the fathead minnow (Pimephales promelas) transcriptome

Transcriptomics is increasingly used to assess biological responses to environmental stimuli and stressors such as aquatic pollutants. However, fundamental studies characterizing individual variability in mRNA levels are lacking, which currently limits the use of transcriptomics in environmental monitoring assessments. To address individual variability in transcript abundance, we performed a meta-analysis on 231 microarrays that were conducted in the fathead minnow (FHM), a widely used toxicological model. The mean variability for gene probes was ranked from most to least variable based upon the coefficient of variation. Transcripts that were the most variable in individual tissues included NADH dehydrogenase flavoprotein 1, GTPase IMAP family member 7-like and v-set domain-containing T-cell activation inhibitor 1-like while genes encoding ribosomal proteins (rpl24 and rpl36), basic transcription factor 3, and nascent polypeptide-associated complex alpha subunit were the least variable in individuals across a range of microarray experiments. Gene networks that showed high variability (based upon the variation in expression of individual members within the network) included cell proliferation, metabolism (steroid, lipids, and glucose), cell adhesion, vascularization, and regeneration while those that showed low variability (more stability) included mRNA and rRNA processing, regulation of translational fidelity, RNA splicing, and ribosome biogenesis. Real-time PCR was conducted on a subset of genes for comparison of variability collected from the microarrays. There was a significant positive relationship between the two methods when measuring individual variability, suggesting that variability detected in microarray data can be used to guide decisions on sample sizes for measuring transcripts in real-time PCR experiments. A power analysis revealed that measuring estrogen receptor ba (esrba) requires fewer biological replicates than that of estrogen receptor bb (esrbb) in the gonad and samples sizes required to detect a 50% change for reproductive-related transcripts is between 12 and 20. Characterizing individual variability at the molecular level will prove necessary as efforts are made toward integrating molecular tools into environmental risk assessments.