Significance of Xenobiotic Metabolism for Bioaccumulation Kinetics of Organic Chemicals in Gammarus pulex

Bioaccumulation and biotransformation are key toxicokinetic processes that modify toxicity of chemicals and sensitivity of organisms. Bioaccumulation kinetics vary greatly among organisms and chemicals; thus, we investigated the influence of biotransformation kinetics on bioaccumulation in a model aquatic invertebrate using fifteen C-14-labeled organic xenobiotics from diverse chemical classes and physicochemical properties (1,2,3-trichlorobenzene, imidacloprid, 4,6-dinitro-o-cresol, ethylacrylate, malathion, chlorpyrifos, aldicarb, carbofuran, carbaryl, 2,4-dichlorophenol, 2,4,5-trichlorophenol, pentachlorophenol, 4-nitrobenzyl-chloride, 2,4-dichloroaniline, and sea-nine (4,5-dichloro-2-octyl-3-isothiazolone)). We detected and identified metabolites using HPLC with UV and radio-detection as well as high resolution mass spectrometry (LTQ-Orbitrap). Kinetics of uptake, biotransformation, and elimination of parent compounds and metabolites were modeled with a first-order one-compartment model. Bioaccumulation factors were calculated for parent compounds and metabolite enrichment factors for metabolites. Out of 19 detected metabolites, we identified seven by standards or accurate mass measurements and two via pathway analysis and analogies to other compounds. 1,2,3-Trichlorobenzene, imidacloprid, and 4,6-dinitro-o-cresol were not biotransformed. Dietary uptake contributed little to overall uptake. Differentiation between parent and metabolites increased accuracy of bioaccumulation parameters compared to total C-14 measurements. Biotransformation dominated toxicokinetics and strongly affected internal concentrations of parent compounds and metabolites. Many metabolites reached higher internal concentrations than their parents, characterized by large metabolite enrichment factors

Environmental Risk Assessment of Fluctuating Diazinon Concentrations in an Urban and Agricultural Catchment Using Toxicokinetic–Toxicodynamic Modeling

Temporally resolved environmental risk assessment of fluctuating concentrations of micropollutants is presented. We separated the prediction of toxicity over time from the extrapolation from one to many species and from acute to sublethal effects. A toxicokinetic–toxicodynamic (TKTD) model predicted toxicity caused by fluctuating concentrations of diazinon, measured by time-resolved sampling over 108 days from three locations in a stream network, representing urban, agricultural and mixed land use. We calculated extrapolation factors to quantify variation in toxicity among species and effect types based on available toxicity data, while correcting for different test durations with the TKTD model. Sampling from the distribution of extrapolation factors and prediction of time-resolved toxicity with the TKTD model facilitated subsequent calculation of the risk of undesired toxic events. Approximately one-fifth of aquatic organisms were at risk and fluctuating concentrations were more toxic than their averages. Contribution of urban and agricultural sources of diazinon to the overall risk varied. Thus using fixed concentrations as water quality criteria appears overly simplistic because it ignores the temporal dimension of toxicity. However, the improved prediction of toxicity for fluctuating concentrations may be small compared to uncertainty due to limited diversity of toxicity data to base the extrapolation factors on

Integrated presentation of ecological risk from multiple stressors

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic

Modelling survival : exposure pattern, species sensitivity and uncertainty

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans

Minimised Bioconcentration Tests: A Useful Tool for Assessing Chemical Uptake into Terrestrial and Aquatic Invertebrates?

Current guidelines for determining bioconcentration factors (BCF) and uptake and depuration rate constants require labor intensive studies with large numbers of organisms. A minimized approach has recently been proposed for fish BCF studies but its applicability to other taxonomic groups is unknown. In this study, we therefore evaluate the use of the minimized approach for estimating BCF and uptake and depuration rate constants for chemicals in aquatic and terrestrial invertebrates. Data from a range of previous BCF studies were resampled to calculate BCFs and rate constants using the minimized method. The resulting values were then compared to values obtained using full study designs. Results demonstrated a good correlation for uptake rate constants, a poor correlation for depuration rate constants and a very good correlation between the BCFs obtained using the traditional and minimized approach for a variety of organic compounds. The minimized approach therefore has merit in deriving bioconcentration factors and uptake rate constants but may not be appropriate for deriving depuration rate constants for use in, for example, toxico-kinetic toxico-dynamic modeling. The approach uses up to 70% fewer organisms, requires less labor and has lower analytical costs. The minimized design therefore could be a valuable approach for running large multifactorial studies to assess bioconcentration of the plethora of chemicals that occur in the environment into the many taxonomic groups that occur in the environment. The approach should therefore help in accelerating the development of our understanding of factors and processes affecting uptake of chemicals into organisms in the environment

Optical absorption in the strong coupling limit of Eliashberg theory

We calculate the optical conductivity of superconductors in the strong-coupling limit. In this anomalous limit the typical energy scale is set by the coupling energy, and other energy scales such as the energy of the bosons mediating the attraction are negligibly small. We find a universal frequency dependence of the optical absorption which is dominated by bound states and differs significantly from the weak coupling results. A comparison with absorption spectra of superconductors with enhanced electron-phonon coupling shows that typical features of the strong-coupling limit are already present at intermediate coupling.Comment: 10 pages, revtex, 4 uuencoded figure

Variability in the Dynamics of Mortality and Immobility Responses of Freshwater Arthropods Exposed to Chlorpyrifos

The species sensitivity distribution (SSD) concept is an important probabilistic tool for environmental risk assessment (ERA) and accounts for differences in species sensitivity to different chemicals. The SSD model assumes that the sensitivity of the species included is randomly distributed. If this assumption is violated, indicator values, such as the 50% hazardous concentration, can potentially change dramatically. Fundamental research, however, has discovered and described specific mechanisms and factors influencing toxicity and sensitivity for several model species and chemical combinations. Further knowledge on how these mechanisms and factors relate to toxicologic standard end points would be beneficial for ERA. For instance, little is known about how the processes of toxicity relate to the dynamics of standard toxicity end points and how these may vary across species. In this article, we discuss the relevance of immobilization and mortality as end points for effects of the organophosphate insecticide chlorpyrifos on 14 freshwater arthropods in the context of ERA. For this, we compared the differences in response dynamics during 96 h of exposure with the two end points across species using dose response models and SSDs. The investigated freshwater arthropods vary less in their immobility than in their mortality response. However, differences in observed immobility and mortality were surprisingly large for some species even after 96 h of exposure. As expected immobility was consistently the more sensitive end point and less variable across the tested species and may therefore be considered as the relevant end point for population of SSDs and ERA, although an immobile animal may still potentially recover. This is even more relevant because an immobile animal is unlikely to survive for long periods under field conditions. This and other such considerations relevant to the decision-making process for a particular end point are discussed

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management

Predicting Concentrations of Organic Chemicals in Fish by Using Toxicokinetic Models

Quantification of chemical toxicity continues to be generally based on measured external concentrations. Yet, internal chemical concentrations have been suggested to be a more suitable parameter. To better understand the relationship between the external and internal concentrations of chemicals in fish, and to quantify internal concentrations we compared three. toxicokinetic (TK) models with each other and with literature data of measured concentrations of 39 chemicals. Two one, compartment models, together with the physiologically based toxicokinetic (PBTK) model, in which we improved the treatment of lipids, were used to predict concentrations of organic chemicals in two fish species: rainbow trout (Oncorhynchus mykiss) and fathead minnow (Pimephales promelas). All models predicted the measured internal concentrations in fish within I order of magnitude for at least 68% of the chemicals. Furthermore, the PBTK model outperformed the one-compartment models with respect to simulating chemical concentrations in the whole body (at least 88% of internal concentrations were predicted within 1 order of magnitude using the PBTK model). All the models can be used to predict concentrations in different fish species without additional experiments. However, further development of TK models is required for polar, ionizable, and easily biotransformed compounds