The Effects of Single and Combined Stressors on Daphnids-Enzyme Markers of Physiology and Metabolomics Validate the Impact of Pollution

The continuous global increase in population and consumption of resources due to human activities has had a significant impact on the environment. Therefore, assessment of environmental exposure to toxic chemicals as well as their impact on biological systems is of significant importance. Freshwater systems are currently under threat and monitored; however, current methods for pollution assessment can neither provide mechanistic insight nor predict adverse effects from complex pollution. Using daphnids as a bioindicator, we assessed the impact in acute exposures of eight individual chemicals and specifically two metals, four pharmaceuticals, a pesticide and a stimulant, and their composite mixture combining phenotypic, biochemical and metabolic markers of physiology. Toxicity levels were in the same order of magnitude and significantly enhanced in the composite mixture. Results from individual chemicals showed distinct biochemical responses for key enzyme activities such as phosphatases, lipase, peptidase, β-galactosidase and glutathione-S-transferase. Following this, a more realistic mixture scenario was assessed with the aforementioned enzyme markers and a metabolomic approach. A clear dose-dependent effect for the composite mixture was validated with enzyme markers of physiology, and the metabolomic analysis verified the effects observed, thus providing a sensitive metrics in metabolite perturbations. Our study highlights that sensitive enzyme markers can be used in advance on the design of metabolic and holistic assays to guide the selection of chemicals and the trajectory of the study, while providing mechanistic insight. In the future this could prove to become a useful tool for understanding and predicting freshwater pollution.

Epigenetics in the Anthropocene: an interview with Oskar Karlsson

In this interview, Oskar Karlsson speaks with Storm Johnson, commissioning editor for Epigenomics, on his work to date in the field of toxicological origins of disease and gene-environment interactions. Oskar Karlsson, is an associate professor at the Science for Life Laboratory (SciLifeLab), Department of Environmental Science, Stockholm University, Sweden. Dr. Karlsson earned a PhD in toxicology at the Department of Pharmaceutical Bioscience, Uppsala University, and has also worked at Centre of Molecular Medicine, Karolinska Institute, as well as Harvard University School of Public Health. His research combines experimental model systems, computational and omics tools, and epidemiological studies to investigate the influence of environmental exposures on wildlife and human health, and underlying molecular mechanisms. In particular, his research focuses on developmental origins of health and disease with an emphasis on environmental exposures and epigenetic mechanisms. The projects concern the effects of exposures such as endocrine disrupting chemicals, flame retardants, pesticides, metals and particulate air pollution, as well as drugs, psycho-social stressors and ethnical disparities. Ongoing efforts include studies of paternal epigenetic inheritance in the ERC-funded project PATER.

Interactive Metal Mixture Toxicity to Daphnia magna Populations as an Emergent Property in a Dynamic Energy Budget Individual-Based Model

Environmental risk assessment of metal mixtures is challenging due to the large number of possible mixtures and interactions. Mixture toxicity data cannot realistically be generated for all relevant scenarios. Therefore, methods for prediction of mixture toxicity from single-metal toxicity data are needed. We tested how well toxicity of Cu-Ni-Zn mixtures to Daphnia magna populations can be predicted based on the Dynamic Energy Budget theory with an individual-based model (DEB-IBM), assuming non-interactivity of metals on the physiological level. We exposed D. magna populations to Cu, Ni, and Zn and their mixture at a fixed concentration ratio. We calibrated the DEB-IBM with single-metal data and generated blind predictions of mixture toxicity (population size over time), with account for uncertainty. We compared the predictive performance of the DEB-IBM with respect to mixture effects on population density and population growth rates with that of two reference models applied on the population level, independent action and concentration addition. Our inferred physiological modes of action (pMoA) differed from literature-reported pMoAs, raising the question of whether this is a result of different model selection approaches, intraspecific variability, or whether different pMoAs might actually drive toxicity in a population context. Observed mixture effects were concentration- and endpoint-dependent. The independent action was overall more accurate than the concentration addition but concentration addition-predicted effects on population growth rate were slightly better. The DEB-IBM most accurately predicted effects on 6-week density, including antagonistic effects at high concentrations, which emerged from non-interactivity at the physiological level. Mixture effects on initial population growth rate appear to be more difficult to predict. To explain why model accuracy is endpoint-dependent, relationships between individual-level and population-level endpoints should be illuminated. Environ Toxicol Chem 2021;40:3034-3048. © 2021 SETAC.

Assessment of mixture toxicity of (tri)azoles and their hepatotoxic effects in vitro by means of omics technologies

Consumers are constantly exposed to chemical mixtures such as multiple residues of different pesticides via the diet. This raises questions concerning potential combination effects, especially because these substances are tested for regulatory purposes on an individual basis. With approximately 500 active substances approved as pesticides, there are too many possible combinations to be tested in standard animal experiments generally requested for regulatory purposes. Therefore, the development of in vitro tools and alternative testing strategies for the assessment of mixture effects is extremely important. As a first step in the development of such in vitro tools, we used (tri)azoles as model substances in a set of different cell lines derived from the primary target organ of these substances, the liver (human: HepaRG, rat: H4IIE). Concentrations were reconciled with measured tissue concentrations obtained from in vivo experiments to ensure comparable effect levels. The effects of the substances were subsequently analyzed by transcriptomics and metabolomics techniques and compared to data from corresponding in vivo studies. The results show that similar toxicity pathways are affected by substances and combinations, thus indicating a similar mode of action and additive effects. Two biomarkers obtained by the approach, CAR and Cyp1A1, were used for mixture toxicity modeling and confirmed the concentration-additive effects, thus supporting the selected testing strategy and raising hope for the development of in vitro methods suitable to detect combination effects and prioritize mixtures of concern for further testing.

Perinatal exposure to mixtures of anti-androgenic chemicals causes proliferative lesions in rat prostate

BACKGROUND

Elevated levels of endogenous or exogenous estrogens during fetal life can induce permanent disturbances in prostate growth and predispose to precancerous lesions. Recent studies have indicated that also early anti-androgen exposure may affect prostate cancer risk.

METHODS

We examined the influence of perinatal exposure to mixtures of anti-androgenic and estrogenic chemicals on prostate development. Wistar rats were exposed from gestation day 7 to postnatal day 22 to a mixture of 8 anti-androgenic compounds (AAMix), a mixture of four estrogenic compounds (EMix), or paracetamol or a mixture of all 13 compounds (TotalMix) in mixture ratios reflecting human exposure levels.

RESULTS

Ventral prostate weights were reduced by the TotalMix and AAMix in pre-pubertal rats. Histological changes in prostate appeared with increasing age and indicated a shift from the normal age-dependent epithelial atrophy towards hyperplasia. These lesions showed similarities to pre-cancerous lesions in humans. Increased proliferation was observed already in pre-puberty and it was hypothesized that this could be associated with reduced ERβ signaling, but no clear conclusions could be made from gene expression studies on ERβ-related pathways. The influences of the estrogenic chemicals and paracetamol on prostate morphology were minor, but in young adulthood the estrogen mixture reduced ventral prostate mRNA levels of Igf1 and paracetamol reduced the mRNA level ofPbpc3.

CONCLUSIONS

Mixtures of endocrine disrupters relevant for human exposure was found to elicit persistent effects on the rat prostate following perinatal exposure, suggesting that human perinatal exposure to environmental chemicals may increase the risk of prostate cancer later in life.

Comparative pharmacology and toxicology of pharmaceuticals in the environment: diphenhydramine protection of diazinon toxicity in Danio rerio but not Daphnia magna

Pharmaceuticals and other contaminants of emerging concern present unique challenges to environmental risk assessment and management. Fortunately, mammalian pharmacology and toxicology safety data are more readily available for pharmaceuticals than other environmental contaminants. Identifying approaches to read-across such pharmaceutical safety information to non-target species represents a major research need to assess environmental hazards. Here, we tested a biological read-across hypothesis from emergency medicine with common aquatic invertebrate and vertebrate models. In mammals, the antihistamine diphenhydramine (DPH) confers protection from poisoning by acetylcholinesterase inhibition because DPH blocks the acetylcholine receptor. We employed standardized toxicity methods to examine individual and mixture toxicity of DPH and the acetylcholinesterase inhibitor diazinon (DZN) in Daphnia magna (an invertebrate) and Danio rerio (zebrafish, a vertebrate). Though the standardized Fish Embryo Toxicity method evaluates early life stage toxicity of zebrafish (0-3 days post fertilization, dpf), we further evaluated DPH, DZN, and their equipotent mixture during three development stages (0-3, 3-6, 7-10 dpf) in zebrafish embryos. Independent action and concentration addition mixture models and fish plasma modeling were used to assist interpretation of mixture toxicity experiments. Though our primary hypothesis was not confirmed in acute studies with Daphnia magna, DPH conferred a protective effect for acute DZN toxicity to zebrafish when DPH plasma levels were expected to be greater than mammalian therapeutic, but lower than acutely lethal, internal doses. We further observed that timing of developmental exposure influenced the magnitude of DZN and DPH toxicity to zebrafish, which suggests that future zebrafish toxicity studies with pharmaceuticals and pesticides should examine exposure during developmental stages.

Bridging environmental mixtures and toxic effects

Biological Response Indicator Devices Gauging Environmental Stressors (BRIDGES) is a bioanalytical tool that combines passive sampling with the embryonic zebrafish developmental toxicity bioassay to provide a quantitative measure of the toxicity of bioavailable complex mixtures. Passive sampling devices (PSDs), which sequester and concentrate bioavailable organic contaminants from the environment, were deployed in the Willamette and Columbia Rivers within and outside of the Portland Harbor Superfund site in Portland, OR, USA. Six sampling events were conducted in the summer and fall of 2009 and 2010. Passive sampling device extracts were analyzed for polycyclic aromatic hydrocarbon (PAH) compounds and screened for 1,201 chemicals of concern using deconvolution-reporting software. The developmental toxicity of the extracts was analyzed using the embryonic zebrafish bioassay. The BRIDGES tool provided site-specific, temporally resolved information about environmental contaminant mixtures and their toxicity. Multivariate modeling approaches were applied to paired chemical and toxic effects data sets to help unravel chemistry-toxicity associations. Modeling elucidated spatial and temporal trends in PAH concentrations and the toxicity of the samples and identified a subset of PAH analytes that were the most highly correlated with observed toxicity. Although the present study highlights the complexity of discerning specific bioactive compounds in complex mixtures, it demonstrates methods for associating toxic effects with chemical characteristics of environmental samples.