Sublethal toxicant effects with dynamic energy budget theory: application to mussel outplants

Oppia nitens C.L. Koch, 1836 (Acari: Oribatida): Current Status of Its Bionomics and Relevance as a Model Invertebrate in Soil Ecotoxicology

The oribatid soil mite Oppia nitens C.L. Koch, 1836, is a model microarthropod in soil ecotoxicity testing. This species has a significant role in supporting soil functions and as a suitable indicator of soil contamination. Despite its significance to the environment and to ecotoxicology, however, very little is known of its biology, ecology, and suborganismal responses to contaminants in the soil. In the present review, we present detailed and critical insights into the biology and ecology of O. nitens in relation to traits that are crucial to its adaptive responses to contaminants in soil. We used a species sensitivity distribution model to rank the species sensitivity to heavy metals (cadmium and zinc) and neonicotinoids (imidacloprid and thiacloprid) compared with other standardized soil invertebrates. Although the International Organization for Standardization and Environment and Climate Change Canada are currently standardizing a protocol for the use of O. nitens in soil toxicity testing, we believe that O. nitens is limited as a model soil invertebrate until the molecular pathways associated with its response to contaminants are better understood. These pathways can only be elucidated with information from the mites' genome or transcriptome, which is currently lacking. Despite this limitation, we propose a possible molecular pathway to metal tolerance and a putative adverse outcome pathway to heavy metal toxicity in O. nitens. Environ Toxicol Chem 2019;38:2593-2613. © 2019 SETAC.

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

Physiological modes of action across species and toxicants: the key to predictive ecotoxicology

As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.

Multigenerational effects of carbendazim in Daphnia magna

Carbendazim is a fungicide largely used in agriculture as a plant protection product. As a result of agricultural runoffs, drainage, and leaching, it reaches surface waters at concentrations possibly hazardous to aquatic communities. Because of potential and continuous release of carbendazim to aquatic systems, long-term exposure to aquatic organisms should be addressed. To fill the knowledge gap, the present study evaluated the responses of multiple generations of Daphnia magna (clone K6) to an environmentally relevant concentration of carbendazim (5 μg/L). Twelve successive generations were evaluated, and the effects in these offspring were compared with those from a control population. Neonates' fitness was assessed through immobilization, reproduction, and feeding activity tests, along with the comet assay for in vivo DNA damage evaluation. Recovery from long-term exposure was also assessed. In the F5 generation, the results revealed that when daphnids were re-exposed to carbendazim, DNA damage was higher in daphnids continuously exposed to carbendazim than those from clean medium. After daphnids were moved to a clean medium, a low recovery potential was observed for DNA damage. Daphnids exposed continuously for 6 generations (F6) to carbendazim displayed an increase in feeding rates when re-exposed to carbendazim compared with F6 daphnids reared in clean medium. Continuous exposure of daphnids to carbendazim induced a significant increase in DNA damage from the F0 to the F12 generation. Deleterious effects of the multigenerational exposure to carbendazim were more prominent at a subcellular level (DNA damage) compared with the individual level. Environ Toxicol Chem 2017;36:383-394. © 2016 SETAC.

The pros and cons of ecological risk assessment based on data from different levels of biological organization

Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.

Relating suborganismal processes to ecotoxicological and population level endpoints using a bioenergetic model

Ecological effects of environmental stressors are commonly evaluated using organismal or suborganismal data, such as standardized toxicity tests that characterize responses of individuals (e.g., mortality and reproduction) and a rapidly growing body of "omics" data. A key challenge for environmental risk assessment is relating such information to population dynamics. One approach uses dynamic energy budget (DEB) models that relate growth and reproduction of individuals to underlying flows of energy and elemental matter. We hypothesize that suborganismal information identifies DEB parameters that are most likely impacted by a particular stressor and that the DEB model can then project suborganismal effects on life history and population endpoints. We formulate and parameterize a model of growth and reproduction for the water flea Daphnia magna. Our model resembles previous generic bioenergetic models, but has explicit representation of discrete molts, an important feature of Daphnia life history. We test its ability to predict six endpoints commonly used in chronic toxicity studies in specified food environments. With just one adjustable parameter, the model successfully predicts growth and reproduction of individuals from a wide array of experiments performed in multiple laboratories using different clones of D. magna raised on different food sources. Fecundity is the most sensitive endpoint, and there is broad correlation between the sensitivities of fecundity and long-run growth rate, as is desirable for the default metric used in chronic toxicity tests. Under some assumptions, we can combine our DEB model with the Euler-Lotka equation to estimate longrun population growth rates at different food levels. A review of Daphnia gene-expression experiments on the effects of contaminant exposure reveals several connections to model parameters, in particular a general trend of increased transcript expression of genes involved in energy assimilation and utilization at concentrations affecting growth and reproduction. The sensitivity of fecundity to many model parameters was consistent with frequent generalized observations of decreased expression of genes involved in reproductive physiology, but interpretation of these observations requires further mechanistic modeling. We thus propose an approach based on generic DEB models incorporating few essential species-specific features for rapid extrapolation of ecotoxicogenomic assays for Daphnia-based population risk assessment.

Considerations for test design to accommodate energy-budget models in ecotoxicology: a case study for acetone in the pond snail Lymnaea stagnalis

Toxicokinetic-toxicodynamic (TKTD) modeling offers many advantages in the analysis of ecotoxicity test data. Calibration of TKTD models, however, places different demands on test design compared with classical concentration-response approaches. In the present study, useful complementary information is provided regarding test design for TKTD modeling. A case study is presented for the pond snail Lymnaea stagnalis exposed to the narcotic compound acetone, in which the data on all endpoints were analyzed together using a relatively simple TKTD model called DEBkiss. Furthermore, the influence of the data used for calibration on accuracy and precision of model parameters is discussed. The DEBkiss model described toxic effects on survival, growth, and reproduction over time well, within a single integrated analysis. Regarding the parameter estimates (e.g., no-effect concentration), precision rather than accuracy was affected depending on which data set was used for model calibration. In addition, the present study shows that the intrinsic sensitivity of snails to acetone stays the same across different life stages, including the embryonic stage. In fact, the data on egg development allowed for selection of a unique metabolic mode of action for the toxicant. Practical and theoretical considerations for test design to accommodate TKTD modeling are discussed in the hope that this information will aid other researchers to make the best possible use of their test animals.

Toxicity of magnesium pulses to tropical freshwater species and the development of a duration-based water quality guideline

Six freshwater species (Chlorella sp., Lemna aequinoctialis, Amerianna cumingi, Hydra viridissima, Moinodaphnia macleayi, and Mogurnda mogurnda) were exposed to 4-h, 8-h, and 24-h Mg pulses in natural creek water. Magnesium toxicity to all species increased with exposure duration; however, the extent of increase and the nature of the relationship differed greatly between species. Based on median inhibitory concentrations (IC50s), and compared with continuous exposure data from a previous study, the increase in toxicity with increasing exposure duration from 4 h to continuous (72-144 h) ranged from approximately 2-fold for Chlorella sp. and H. viridissima to greater than 40-fold for A. cumingi. Moreover, the form of the relationship between Mg toxicity and duration ranged from linear or near-linear to exponential for different species. The life-stage at which M. macleayi was exposed was important, with cladocerans pulsed at the onset of reproductive maturity being approximately 4 times more sensitive (based on IC50s) than younger than 6-h-old neonates. Species sensitivity distributions were constructed for the 4-h, 8-h, and 24-h pulse durations, from which 99% species protection guideline values (95% confidence limits [CLs]) of 94 (6.4-1360) mg/L, 14 (0.5-384) mg/L, and 8.0 (0.5-144) mg/L Mg, respectively, were derived. These values were plotted against exposure duration (h) and polynomial interpolation used to derive a guideline value for any pulse duration within the range assessed.

Implementation of a multidisciplinary approach to solve complex nano EHS problems by the UC Center for the Environmental Implications of Nanotechnology

UC CEIN was established with funding from the US National Science Foundation and the US Environmental Protection Agency in 2008 with the mission to study the impact of nanotechnology on the environment, including the identification of hazard and exposure scenarios that take into consideration the unique physicochemical properties of engineered nanomaterials (ENMs). Since its inception, the Center has made great progress in assembling a multidisciplinary team to develop the scientific underpinnings, research, knowledge acquisition, education and outreach that is required for assessing the safe implementation of nanotechnology in the environment. In this essay, the development of the infrastructure, protocols, and decision-making tools that are required to effectively integrate complementary scientific disciplines allowing knowledge gathering in a complex study area that goes beyond the traditional safety and risk assessment protocols of the 20th century is outlined. UC CEIN's streamlined approach, premised on predictive hazard and exposure assessment methods, high-throughput discovery platforms and environmental decision-making tools that consider a wide range of nano/bio interfaces in terrestrial and aquatic ecosystems, demonstrates the implementation of a 21st-century approach to the safe implementation of nanotechnology in the environment.

Impact of engineered zinc oxide nanoparticles on the individual performance of Mytilus galloprovincialis

The increased use of engineered nanoparticles (ENPs) in consumer products raises the concern of environmental release and subsequent impacts in natural communities. We tested for physiological and demographic impacts of ZnO, a prevalent metal oxide ENP, on the mussel Mytilus galloprovincialis. We exposed mussels of two size classes, <4.5 and ≥ 4.5 cm shell length, to 0.1-2 mg l(-1) ZnO ENPs in seawater for 12 wk, and measured the effect on mussel respiration, accumulation of Zn, growth, and survival. After 12 wk of exposure to ZnO ENPs, respiration rates of mussels increased with ZnO concentration. Mussels had up to three fold more Zn in tissues than control groups after 12 wk of exposure, but patterns of Zn accumulation varied with mussel size and Zn concentrations. Small mussels accumulated Zn 10 times faster than large mussels at 0.5 mg l(-1), while large mussels accumulated Zn four times faster than small mussels at 2 mg l(-1). Mussels exposed to 2 mg l(-1) ZnO grew 40% less than mussels in our control group for both size classes. Survival significantly decreased only in groups exposed to the highest ZnO concentration (2 mg l(-1)) and was lower for small mussels than large. Our results indicate that ZnO ENPs are toxic to mussels but at levels unlikely to be reached in natural marine waters.

Ecological nanotoxicology: integrating nanomaterial hazard considerations across the subcellular, population, community, and ecosystems levels

Research into the health and environmental safety of nanotechnology has seriously lagged behind its emergence in industry. While humans have often adopted synthetic chemicals without considering ancillary consequences, the lessons learned from worldwide pollution should motivate making nanotechnology compatible with environmental concerns. Researchers and policymakers need to understand exposure and harm of engineered nanomaterials (ENMs), currently nanotechnology's main products, to influence the ENM industry toward sustainable growth. Yet, how should research proceed? Standard toxicity testing anchored in single-organism, dose-response characterizations does not adequately represent real-world exposure and receptor scenarios and their complexities. Our approach is different: it derives from ecology, the study of organisms' interactions with each other and their environments. Our approach involves the characterization of ENMs and the mechanistic assessment of their property-based effects. Using high throughput/content screening (HTS/HCS) with cells or environmentally-relevant organisms, we measure the effects of ENMs on a subcellular or population level. We then relate those effects to mechanisms within dynamic energy budget (DEB) models of growth and reproduction. We reconcile DEB model predictions with experimental data on organism and population responses. Finally, we use microcosm studies to measure the potential for community- or ecosystem-level effects by ENMs that are likely to be produced in large quantities and for which either HTS/HCS or DEB modeling suggest their potential to harm populations and ecosystems. Our approach accounts for ecological interactions across scales, from within organisms to whole ecosystems. Organismal ENM effects, if propagated through populations, can alter communities comprising multiple populations (e.g., plant, fish, bacteria) within food webs. Altered communities can change ecosystem services: processes that cycle carbon, nutrients, and energy, and regulate Earth's waters and atmosphere. We have shown ENM effects on populations, communities, and ecosystems, including transfer and concentration of ENMs through food chains, for a range of exposure scenarios; in many cases, we have identified subcellular ENM effects mechanisms. To keep pace with ENM development, rapid assessment of the mechanisms of ENM effects and modeling are needed. DEB models provide a method for mathematically representing effects such as the generation of reactive oxygen species and their associated damage. These models account for organism-level effects on metabolism and reproduction and can predict outcomes of ENM-organism combinations on populations; those predictions can then suggest ENM characteristics to be avoided. HTS/HCS provides a rapid assessment tool of the ENM chemical characteristics that affect biological systems; such results guide and expand DEB model expressions of hazard. Our approach addresses ecological processes in both natural and managed ecosystems (agriculture) and has the potential to deliver timely and meaningful understanding towards environmentally sustainable nanotechnology.

Dynamic energy budget approach to modeling mechanisms of CdSe quantum dot toxicity

A mechanistic model of bacterial growth based on dynamic energy budget (DEB) theory is utilized to investigate mechanisms of toxicity of CdSe quantum dots (QDs). The model of QD toxicity is developed by extending a previously published DEB model of cadmium ion toxicity to include a separate model of QD toxic action. The extension allows for testing whether toxicity from QD exposure can be explained fully by dissolved cadmium exposure only, or if the separate effects of QDs need to be taken into account as well. Two major classes of QD toxicity mechanisms are considered: acclimation expressed through initial retardation of growth, and three separate metabolic effects that can be a result of QDs either reversibly or irreversibly associating with the cell. The model is consistent with the data, and is able to distinguish toxic effects due to QD nano-particles from the effects due to cadmium ions. Results suggest that, in contrast to ionic exposure where required acclimation remains constant as exposure increases, increase of the energy required for acclimation with exposure is the primary toxic effect of QDs. Reactive oxygen species measurements help conclude that increase in energetic cost of maintenance processes such as cellular repair and maintenance of cross-membrane gradients is the most important of the three metabolic effects of QD toxicity.

Modeling physiological processes that relate toxicant exposure and bacterial population dynamics

Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB) theory, can link physiological processes to microbial growth.Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS). Extensions considered are: (i) additional terms in the equation for the "hazard rate" that quantifies mortality risk; (ii) a variable representing environmental degradation; (iii) a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels; (iv) a new representation of the "lag time" based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd)/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd)/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory.

An ecological perspective on nanomaterial impacts in the environment

Growing concerns over the potential for unintended, adverse consequences of engineered nanoparticles (ENPs) in the environment have generated new research initiatives focused on understanding the ecological effects of ENPs. Almost nothing is currently known about the fate and transport of ENPs in environmental waters, soils, and sediments or about the biological impacts of ENPs in natural environments, and the bulk of modern nanotoxicogical research is focused on highly controlled laboratory studies with single species in simple media. In this paper, we provide an ecological perspective on the current state of knowledge regarding the likely environmental impacts of nanomaterials and propose a strategy for making rapid progress in new research in ecological nanoscience.